Bursting as a source of non-linear determinism in the firing patterns of nigral dopamine neurons
Jeong, Jaeseung; Shi, Wei-Xing; Hoffman, Ralph; Oh, Jihoon; Gore, John C.; Bunney, Benjamin S.; Peterson, Bradley S.
2012-01-01
Nigral dopamine (DA) neurons in vivo exhibit complex firing patterns consisting of tonic single-spikes and phasic bursts that encode information for certain types of reward-related learning and behavior. Non-linear dynamical analysis has previously demonstrated the presence of a non-linear deterministic structure in complex firing patterns of DA neurons, yet the origin of this non-linear determinism remains unknown. In this study, we hypothesized that bursting activity is the primary source of non-linear determinism in the firing patterns of DA neurons. To test this hypothesis, we investigated the dimension complexity of inter-spike interval data recorded in vivo from bursting and non-bursting DA neurons in the chloral hydrate-anesthetized rat substantia nigra. We found that bursting DA neurons exhibited non-linear determinism in their firing patterns, whereas non-bursting DA neurons showed truly stochastic firing patterns. Determinism was also detected in the isolated burst and inter-burst interval data extracted from firing patterns of bursting neurons. Moreover, less bursting DA neurons in halothane-anesthetized rats exhibited higher dimensional spiking dynamics than do more bursting DA neurons in chloral hydrate-anesthetized rats. These results strongly indicate that bursting activity is the main source of low-dimensional, non-linear determinism in the firing patterns of DA neurons. This finding furthermore suggests that bursts are the likely carriers of meaningful information in the firing activities of DA neurons. PMID:22831464
GABAB-receptor activation alters the firing pattern of dopamine neurons in the rat substantia nigra.
Engberg, G; Kling-Petersen, T; Nissbrandt, H
1993-11-01
Previous electrophysiological experiments have emphasized the importance of the firing pattern for the functioning of midbrain dopamine (DA) neurons. In this regard, excitatory amino acid receptors appear to constitute an important modulatory control mechanism. In the present study, extracellular recording techniques were used to investigate the significance of GABAB-receptor activation for the firing properties of DA neurons in the substantia nigra (SN) in the rat. Intravenous administration of the GABAB-receptor agonist baclofen (1-16 mg/kg) was associated with a dose-dependent regularization of the firing pattern, concomitant with a reduction in burst firing. At higher doses (16-32 mg/kg), the firing rate of the DA neurons was dose-dependently decreased. Also, microiontophoretic application of baclofen regularized the firing pattern of nigral DA neurons, including a reduction of burst firing. Both the regularization of the firing pattern and inhibition of firing rate produced by systemic baclofen administration was antagonized by the GABAB-receptor antagonist CGP 35348 (200 mg/kg, i.v.). The GABAA-receptor agonist muscimol produced effects on the firing properties of DA neurons that were opposite to those observed following baclofen, i.e., an increase in firing rate accompanied by a decreased regularity. The NMDA receptor antagonist MK 801 (0.4-3.2 mg/kg, i.v.) produced a moderate, dose-dependent increase in the firing rate of the nigral DA neurons as well as a slightly regularized firing pattern. Pretreatment with MK 801 (3.2 mg/kg, i.v., 3-10 min) did neither promote nor prevent the regularization of the firing pattern or inhibition of firing rate on the nigral DA neurons produced by baclofen. The present results clearly show that GABAB-receptors can alter the firing pattern of nigral DA neurons, hereby counterbalancing the previously described ability of glutamate to induce burst firing activity on these neurons.
Bursting as a source of non-linear determinism in the firing patterns of nigral dopamine neurons.
Jeong, Jaeseung; Shi, Wei-Xing; Hoffman, Ralph; Oh, Jihoon; Gore, John C; Bunney, Benjamin S; Peterson, Bradley S
2012-11-01
Nigral dopamine (DA) neurons in vivo exhibit complex firing patterns consisting of tonic single-spikes and phasic bursts that encode information for certain types of reward-related learning and behavior. Non-linear dynamical analysis has previously demonstrated the presence of a non-linear deterministic structure in complex firing patterns of DA neurons, yet the origin of this non-linear determinism remains unknown. In this study, we hypothesized that bursting activity is the primary source of non-linear determinism in the firing patterns of DA neurons. To test this hypothesis, we investigated the dimension complexity of inter-spike interval data recorded in vivo from bursting and non-bursting DA neurons in the chloral hydrate-anesthetized rat substantia nigra. We found that bursting DA neurons exhibited non-linear determinism in their firing patterns, whereas non-bursting DA neurons showed truly stochastic firing patterns. Determinism was also detected in the isolated burst and inter-burst interval data extracted from firing patterns of bursting neurons. Moreover, less bursting DA neurons in halothane-anesthetized rats exhibited higher dimensional spiking dynamics than do more bursting DA neurons in chloral hydrate-anesthetized rats. These results strongly indicate that bursting activity is the main source of low-dimensional, non-linear determinism in the firing patterns of DA neurons. This finding furthermore suggests that bursts are the likely carriers of meaningful information in the firing activities of DA neurons. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.
Li, Chunyan; Tripathi, Pradeep K; Armstrong, William E
2007-01-01
The firing pattern of magnocellular neurosecretory neurons is intimately related to hormone release, but the relative contribution of synaptic versus intrinsic factors to the temporal dispersion of spikes is unknown. In the present study, we examined the firing patterns of vasopressin (VP) and oxytocin (OT) supraoptic neurons in coronal slices from virgin female rats, with and without blockade of inhibitory and excitatory synaptic currents. Inhibitory postsynaptic currents (IPSCs) were twice as prevalent as their excitatory counterparts (EPSCs), and both were more prevalent in OT compared with VP neurons. Oxytocin neurons fired more slowly and irregularly than VP neurons near threshold. Blockade of Cl− currents (including tonic and synaptic currents) with picrotoxin reduced interspike interval (ISI) variability of continuously firing OT and VP neurons without altering input resistance or firing rate. Blockade of EPSCs did not affect firing pattern. Phasic bursting neurons (putative VP neurons) were inconsistently affected by broad synaptic blockade, suggesting that intrinsic factors may dominate the ISI distribution during this mode in the slice. Specific blockade of synaptic IPSCs with gabazine also reduced ISI variability, but only in OT neurons. In all cases, the effect of inhibitory blockade on firing pattern was independent of any consistent change in input resistance or firing rate. Since the great majority of IPSCs are randomly distributed, miniature events (mIPSCs) in the coronal slice, these findings imply that even mIPSCs can impart irregularity to the firing pattern of OT neurons in particular, and could be important in regulating spike patterning in vivo. For example, the increased firing variability that precedes bursting in OT neurons during lactation could be related to significant changes in synaptic activity. PMID:17332000
Furong, Liu; Shengtian, L I
2016-05-25
To investigate patterns of action potential firing in cortical heurons of neonatal mice and their electrophysiological properties. The passive and active membrane properties of cortical neurons from 3-d neonatal mice were observed by whole-cell patch clamp with different voltage and current mode. Three patterns of action potential firing were identified in response to depolarized current injection. The effects of action potential firing patterns on voltage-dependent inward and outward current were found. Neurons with three different firing patterns had different thresholds of depolarized current. In the morphology analysis of action potential, the three type neurons were different in rise time, duration, amplitude and threshold of the first action potential evoked by 80 pA current injection. The passive properties were similar in three patterns of action potential firing. These results indicate that newborn cortical neurons exhibit different patterns of action potential firing with different action potential parameters such as shape and threshold.
Rhythmic activities of hypothalamic magnocellular neurons: autocontrol mechanisms.
Richard, P; Moos, F; Dayanithi, G; Gouzènes, L; Sabatier, N
1997-12-01
Electrophysiological recordings in lactating rats show that oxytocin (OT) and vasopressin (AVP) neurons exhibit specific patterns of activities in relation to peripheral stimuli: periodic bursting firing for OT neurons during suckling, phasic firing for AVP neurons during hyperosmolarity (systemic injection of hypertonic saline). These activities are autocontrolled by OT and AVP released somato-dentritically within the hypothalamic magnocellular nuclei. In vivo, OT enhances the amplitude and frequency of bursts, an effect accompanied with an increase in basal firing rate. However, the characteristics of firing change as facilitation proceeds: the spike patterns become very irregular with clusters of spikes spaced by long silences; the firing rate is highly variable and clearly oscillates before facilitated bursts. This unstable behaviour dramatically decreases during intense tonic activation which temporarily interrupts bursting, and could therefore be a prerequisite for bursting. In vivo, the effects of AVP depend on the initial firing pattern of AVP neurons: AVP excites weakly active neurons (increasing duration of active periods and decreasing silences), inhibits highly active neurons, and does not affect neurons with intermediate phasic activity. AVP brings the entire population of AVP neurons to discharge with a medium phasic activity characterised by periods of firing and silence lasting 20-40 s, a pattern shown to optimise the release of AVP from the neurohypophysis. Each of the peptides (OT or AVP) induces an increase in intracellular Ca2+ concentration, specifically in the neurons containing either OT or AVP respectively. OT evokes the release of Ca2+ from IP3-sensitive intracellular stores. AVP induces an influx of Ca2+ through voltage-dependent Ca2+ channels of T-, L- and N-types. We postulate that the facilitatory autocontrol of OT and AVP neurons could be mediated by Ca2+ known to play a key role in the control of the patterns of phasic neurons.
Rothkegel, Alexander; Lehnertz, Klaus
2009-03-01
We investigate numerically the collective dynamical behavior of pulse-coupled nonleaky integrate-and-fire neurons that are arranged on a two-dimensional small-world network. To ensure ongoing activity, we impose a probability for spontaneous firing for each neuron. We study network dynamics evolving from different sets of initial conditions in dependence on coupling strength and rewiring probability. Besides a homogeneous equilibrium state for low coupling strength, we observe different local patterns including cyclic waves, spiral waves, and turbulentlike patterns, which-depending on network parameters-interfere with the global collective firing of the neurons. We attribute the various network dynamics to distinct regimes in the parameter space. For the same network parameters different network dynamics can be observed depending on the set of initial conditions only. Such a multistable behavior and the interplay between local pattern formation and global collective firing may be attributable to the spatiotemporal dynamics of biological networks.
Effect of inhibitory firing pattern on coherence resonance in random neural networks
NASA Astrophysics Data System (ADS)
Yu, Haitao; Zhang, Lianghao; Guo, Xinmeng; Wang, Jiang; Cao, Yibin; Liu, Jing
2018-01-01
The effect of inhibitory firing patterns on coherence resonance (CR) in random neuronal network is systematically studied. Spiking and bursting are two main types of firing pattern considered in this work. Numerical results show that, irrespective of the inhibitory firing patterns, the regularity of network is maximized by an optimal intensity of external noise, indicating the occurrence of coherence resonance. Moreover, the firing pattern of inhibitory neuron indeed has a significant influence on coherence resonance, but the efficacy is determined by network property. In the network with strong coupling strength but weak inhibition, bursting neurons largely increase the amplitude of resonance, while they can decrease the noise intensity that induced coherence resonance within the neural system of strong inhibition. Different temporal windows of inhibition induced by different inhibitory neurons may account for the above observations. The network structure also plays a constructive role in the coherence resonance. There exists an optimal network topology to maximize the regularity of the neural systems.
Gouzènes, L; Desarménien, M G; Hussy, N; Richard, P; Moos, F C
1998-03-01
Vasopressin (AVP) magnocellular neurons of hypothalamic nuclei express specific phasic firing (successive periods of activity and silence), which conditions the mode of neurohypophyseal vasopression release. In situations favoring plasmatic secretion of AVP, the hormone is also released at the somatodendritic level, at which it is believed to modulate the activity of AVP neurons. We investigated the nature of this autocontrol by testing the effects of juxtamembrane applications of AVP on the extracellular activity of presumed AVP neurons in paraventricular and supraoptic nuclei of anesthetized rats. AVP had three effects depending on the initial firing pattern: (1) excitation of faintly active neurons (periods of activity of <10 sec), which acquired or reinforced their phasic pattern; (2) inhibition of quasi-continuously active neurons (periods of silences of <10 sec), which became clearly phasic; and (3) no effect on neurons already showing an intermediate phasic pattern (active and silent periods of 10-30 sec). Consequently, AVP application resulted in a narrower range of activity patterns of the population of AVP neurons, with a Gaussian distribution centered around a mode of 57% of time in activity, indicating a homogenization of the firing pattern. The resulting phasic pattern had characteristics close to those established previously for optimal release of AVP from neurohypophyseal endings. These results suggest a new role for AVP as an optimizing factor that would foster the population of AVP neurons to discharge with a phasic pattern known to be most efficient for hormone release.
Interplay between population firing stability and single neuron dynamics in hippocampal networks
Slomowitz, Edden; Styr, Boaz; Vertkin, Irena; Milshtein-Parush, Hila; Nelken, Israel; Slutsky, Michael; Slutsky, Inna
2015-01-01
Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules. DOI: http://dx.doi.org/10.7554/eLife.04378.001 PMID:25556699
Spencer, Nick J; Hibberd, Timothy J; Travis, Lee; Wiklendt, Lukasz; Costa, Marcello; Hu, Hongzhen; Brookes, Simon J; Wattchow, David A; Dinning, Phil G; Keating, Damien J; Sorensen, Julian
2018-05-28
The enteric nervous system (ENS) contains millions of neurons essential for organization of motor behaviour of the intestine. It is well established the large intestine requires ENS activity to drive propulsive motor behaviours. However, the firing pattern of the ENS underlying propagating neurogenic contractions of the large intestine remains unknown. To identify this, we used high resolution neuronal imaging with electrophysiology from neighbouring smooth muscle. Myoelectric activity underlying propagating neurogenic contractions along murine large intestine (referred to as colonic migrating motor complexes, CMMCs) consisted of prolonged bursts of rhythmic depolarizations at a frequency of ∼2 Hz. Temporal coordination of this activity in the smooth muscle over large spatial fields (∼7mm, longitudinally) was dependent on the ENS. During quiescent periods between neurogenic contractions, recordings from large populations of enteric neurons, in mice of either sex, revealed ongoing activity. The onset of neurogenic contractions was characterized by the emergence of temporally synchronized activity across large populations of excitatory and inhibitory neurons. This neuronal firing pattern was rhythmic and temporally synchronized across large numbers of ganglia at ∼2 Hz. ENS activation preceded smooth muscle depolarization, indicating rhythmic depolarizations in smooth muscle were controlled by firing of enteric neurons. The cyclical emergence of temporally coordinated firing of large populations of enteric neurons represents a unique neural motor pattern outside the central nervous system. This is the first direct observation of rhythmic firing in the ENS underlying rhythmic electrical depolarizations in smooth muscle. The pattern of neuronal activity we identified underlies the generation of CMMCs. SIGNIFICANCE STATEMENT How the enteric nervous system (ENS) generates neurogenic contractions of smooth muscle in the gastrointestinal (GI) tract has been a long-standing mystery in vertebrates. It is well known that myogenic pacemaker cells exist in the GI-tract (called Interstitial cells of Cajal, ICC) that generate rhythmic myogenic contractions. However, the mechanisms underlying the generation of rhythmic neurogenic contractions of smooth muscle in the GI-tract remains unknown. We developed a high resolution neuronal imaging method with electrophysiology to address this issue. This technique revealed a novel pattern of rhythmic coordinated neuronal firing in the ENS that has never been identified. Rhythmic neuronal firing in the ENS was found to generate rhythmic neurogenic depolarizations in smooth muscle that underlie contraction of the GI-tract. Copyright © 2018 the authors.
Firing patterns in the adaptive exponential integrate-and-fire model.
Naud, Richard; Marcille, Nicolas; Clopath, Claudia; Gerstner, Wulfram
2008-11-01
For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.
Iida, Shoko; Shimba, Kenta; Sakai, Koji; Kotani, Kiyoshi; Jimbo, Yasuhiko
2018-06-18
The balance between glutamate-mediated excitation and GABA-mediated inhibition is critical to cortical functioning. However, the contribution of network structure consisting of the both neurons to cortical functioning has not been elucidated. We aimed to evaluate the relationship between the network structure and functional activity patterns in vitro. We used mouse induced pluripotent stem cells (iPSCs) to construct three types of neuronal populations; excitatory-rich (Exc), inhibitory-rich (Inh), and control (Cont). Then, we analyzed the activity patterns of these neuronal populations using microelectrode arrays (MEAs). Inhibitory synaptic densities differed between the three types of iPSC-derived neuronal populations, and the neurons showed spontaneously synchronized bursting activity with functional maturation for one month. Moreover, different firing patterns were observed between the three populations; Exc demonstrated the highest firing rates, including frequent, long, and dominant bursts. In contrast, Inh demonstrated the lowest firing rates and the least dominant bursts. Synchronized bursts were enhanced by disinhibition via GABA A receptor blockade. The present study, using iPSC-derived neurons and MEAs, for the first time show that synchronized bursting of cortical networks in vitro depends on the network structure consisting of excitatory and inhibitory neurons. Copyright © 2018 Elsevier Inc. All rights reserved.
Horikawa, Yo
2016-04-01
Metastable dynamical transient patterns in arrays of bidirectionally coupled neurons with self-coupling and asymmetric output were studied. First, an array of asymmetric sigmoidal neurons with symmetric inhibitory bidirectional coupling and self-coupling was considered and the bifurcations of its steady solutions were shown. Metastable dynamical transient spatially nonuniform states existed in the presence of a pair of spatially symmetric stable solutions as well as unstable spatially nonuniform solutions in a restricted range of the output gain of a neuron. The duration of the transients increased exponentially with the number of neurons up to the maximum number at which the spatially nonuniform steady solutions were stabilized. The range of the output gain for which they existed reduced as asymmetry in a sigmoidal output function of a neuron increased, while the existence range expanded as the strength of inhibitory self-coupling increased. Next, arrays of spiking neuron models with slow synaptic inhibitory bidirectional coupling and self-coupling were considered with computer simulation. In an array of Class 1 Hindmarsh-Rose type models, in which each neuron showed a graded firing rate, metastable dynamical transient firing patterns were observed in the presence of inhibitory self-coupling. This agreed with the condition for the existence of metastable dynamical transients in an array of sigmoidal neurons. In an array of Class 2 Bonhoeffer-van der Pol models, in which each neuron had a clear threshold between firing and resting, long-lasting transient firing patterns with bursting and irregular motion were observed. Copyright © 2016 Elsevier Ltd. All rights reserved.
Task-phase-specific dynamics of basal forebrain neuronal ensembles
Tingley, David; Alexander, Andrew S.; Kolbu, Sean; de Sa, Virginia R.; Chiba, Andrea A.; Nitz, Douglas A.
2014-01-01
Cortically projecting basal forebrain neurons play a critical role in learning and attention, and their degeneration accompanies age-related impairments in cognition. Despite the impressive anatomical and cell-type complexity of this system, currently available data suggest that basal forebrain neurons lack complexity in their response fields, with activity primarily reflecting only macro-level brain states such as sleep and wake, onset of relevant stimuli and/or reward obtainment. The current study examined the spiking activity of basal forebrain neuron populations across multiple phases of a selective attention task, addressing, in particular, the issue of complexity in ensemble firing patterns across time. Clustering techniques applied to the full population revealed a large number of distinct categories of task-phase-specific activity patterns. Unique population firing-rate vectors defined each task phase and most categories of task-phase-specific firing had counterparts with opposing firing patterns. An analogous set of task-phase-specific firing patterns was also observed in a population of posterior parietal cortex neurons. Thus, consistent with the known anatomical complexity, basal forebrain population dynamics are capable of differentially modulating their cortical targets according to the unique sets of environmental stimuli, motor requirements, and cognitive processes associated with different task phases. PMID:25309352
Cerebellar Nuclear Neurons Use Time and Rate Coding to Transmit Purkinje Neuron Pauses.
Sudhakar, Shyam Kumar; Torben-Nielsen, Benjamin; De Schutter, Erik
2015-12-01
Neurons of the cerebellar nuclei convey the final output of the cerebellum to their targets in various parts of the brain. Within the cerebellum their direct upstream connections originate from inhibitory Purkinje neurons. Purkinje neurons have a complex firing pattern of regular spikes interrupted by intermittent pauses of variable length. How can the cerebellar nucleus process this complex input pattern? In this modeling study, we investigate different forms of Purkinje neuron simple spike pause synchrony and its influence on candidate coding strategies in the cerebellar nuclei. That is, we investigate how different alignments of synchronous pauses in synthetic Purkinje neuron spike trains affect either time-locking or rate-changes in the downstream nuclei. We find that Purkinje neuron synchrony is mainly represented by changes in the firing rate of cerebellar nuclei neurons. Pause beginning synchronization produced a unique effect on nuclei neuron firing, while the effect of pause ending and pause overlapping synchronization could not be distinguished from each other. Pause beginning synchronization produced better time-locking of nuclear neurons for short length pauses. We also characterize the effect of pause length and spike jitter on the nuclear neuron firing. Additionally, we find that the rate of rebound responses in nuclear neurons after a synchronous pause is controlled by the firing rate of Purkinje neurons preceding it.
New aspects of firing pattern autocontrol in oxytocin and vasopressin neurones.
Moos, F; Gouzènes, L; Brown, D; Dayanithi, G; Sabatier, N; Boissin, L; Rabié, A; Richard, P
1998-01-01
In the rat, oxytocin (OT) and vasopressin (AVP) neurones exhibit specific electrical activities which are controlled by OT and AVP released from soma and dendrites within the magnocellular hypothalamic nuclei. OT enhances amplitude and frequency of suckling-induced bursts, and changes basal firing characteristics: spike patterning becomes very irregular (spike clusters separated by long silences), firing rate is highly variable, oscillating before facilitated bursts. This unstable behaviour which markedly decreases during hyperosmotic stimulation (interrupting bursting) could be a prerequisite for bursting. The effects of AVP depend on the initial phasic pattern of AVP neurones: AVP excites weakly active neurones (increasing burst duration, decreasing silences) and inhibits highly active neurones; neurones with intermediate phasic activity are unaffected. Thus, AVP ensures all AVP neurones discharge with moderate phasic activity (bursts and silences lasting 20-40 s), known to optimise systemic AVP release. V1a-type receptors are involved in AVP actions. In conclusion, OT and AVP control their respective neurones in a complex manner to favour the patterns of activity which are the best suited for an efficient systemic hormone release.
How noise affects the synchronization properties of recurrent networks of inhibitory neurons.
Brunel, Nicolas; Hansel, David
2006-05-01
GABAergic interneurons play a major role in the emergence of various types of synchronous oscillatory patterns of activity in the central nervous system. Motivated by these experimental facts, modeling studies have investigated mechanisms for the emergence of coherent activity in networks of inhibitory neurons. However, most of these studies have focused either when the noise in the network is absent or weak or in the opposite situation when it is strong. Hence, a full picture of how noise affects the dynamics of such systems is still lacking. The aim of this letter is to provide a more comprehensive understanding of the mechanisms by which the asynchronous states in large, fully connected networks of inhibitory neurons are destabilized as a function of the noise level. Three types of single neuron models are considered: the leaky integrate-and-fire (LIF) model, the exponential integrate-and-fire (EIF), model and conductance-based models involving sodium and potassium Hodgkin-Huxley (HH) currents. We show that in all models, the instabilities of the asynchronous state can be classified in two classes. The first one consists of clustering instabilities, which exist in a restricted range of noise. These instabilities lead to synchronous patterns in which the population of neurons is broken into clusters of synchronously firing neurons. The irregularity of the firing patterns of the neurons is weak. The second class of instabilities, termed oscillatory firing rate instabilities, exists at any value of noise. They lead to cluster state at low noise. As the noise is increased, the instability occurs at larger coupling, and the pattern of firing that emerges becomes more irregular. In the regime of high noise and strong coupling, these instabilities lead to stochastic oscillations in which neurons fire in an approximately Poisson way with a common instantaneous probability of firing that oscillates in time.
Sahasranamam, Ajith; Vlachos, Ioannis; Aertsen, Ad; Kumar, Arvind
2016-01-01
Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relationship. Using this model, we show that the effect of single neuron spiking on the network dynamics is contingent on the network activity state. While spike bursting can both generate and disrupt oscillations, these patterns are ineffective in large regions of the network state space in changing the network activity qualitatively. Finally, we show that when single-neuron properties are made dependent on the population activity, a hysteresis like dynamics emerges. This novel phenomenon has important implications for determining the network response to time-varying inputs and for the network sensitivity at different operating points. PMID:27212008
Sahasranamam, Ajith; Vlachos, Ioannis; Aertsen, Ad; Kumar, Arvind
2016-05-23
Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relationship. Using this model, we show that the effect of single neuron spiking on the network dynamics is contingent on the network activity state. While spike bursting can both generate and disrupt oscillations, these patterns are ineffective in large regions of the network state space in changing the network activity qualitatively. Finally, we show that when single-neuron properties are made dependent on the population activity, a hysteresis like dynamics emerges. This novel phenomenon has important implications for determining the network response to time-varying inputs and for the network sensitivity at different operating points.
Effects of Morphology Constraint on Electrophysiological Properties of Cortical Neurons
NASA Astrophysics Data System (ADS)
Zhu, Geng; Du, Liping; Jin, Lei; Offenhäusser, Andreas
2016-04-01
There is growing interest in engineering nerve cells in vitro to control architecture and connectivity of cultured neuronal networks or to build neuronal networks with predictable computational function. Pattern technologies, such as micro-contact printing, have been developed to design ordered neuronal networks. However, electrophysiological characteristics of the single patterned neuron haven’t been reported. Here, micro-contact printing, using polyolefine polymer (POP) stamps with high resolution, was employed to grow cortical neurons in a designed structure. The results demonstrated that the morphology of patterned neurons was well constrained, and the number of dendrites was decreased to be about 2. Our electrophysiological results showed that alterations of dendritic morphology affected firing patterns of neurons and neural excitability. When stimulated by current, though both patterned and un-patterned neurons presented regular spiking, the dynamics and strength of the response were different. The un-patterned neurons exhibited a monotonically increasing firing frequency in response to injected current, while the patterned neurons first exhibited frequency increase and then a slow decrease. Our findings indicate that the decrease in dendritic complexity of cortical neurons will influence their electrophysiological characteristics and alter their information processing activity, which could be considered when designing neuronal circuitries.
McConnell, George C; So, Rosa Q; Grill, Warren M
2016-06-01
Subthalamic nucleus (STN) deep brain stimulation (DBS) is an established treatment for the motor symptoms of Parkinson's disease (PD). However, the mechanisms of action of DBS are unknown. Random temporal patterns of DBS are less effective than regular DBS, but the neuronal basis for this dependence on temporal pattern of stimulation is unclear. Using a rat model of PD, we quantified the changes in behavior and single-unit activity in globus pallidus externa and substantia nigra pars reticulata during high-frequency STN DBS with different degrees of irregularity. Although all stimulus trains had the same average rate, 130-Hz regular DBS more effectively reversed motor symptoms, including circling and akinesia, than 130-Hz irregular DBS. A mixture of excitatory and inhibitory neuronal responses was present during all stimulation patterns, and mean firing rate did not change during DBS. Low-frequency (7-10 Hz) oscillations of single-unit firing times present in hemiparkinsonian rats were suppressed by regular DBS, and neuronal firing patterns were entrained to 130 Hz. Irregular patterns of DBS less effectively suppressed 7- to 10-Hz oscillations and did not regularize firing patterns. Random DBS resulted in a larger proportion of neuron pairs with increased coherence at 7-10 Hz compared with regular 130-Hz DBS, which suggested that long pauses (interpulse interval >50 ms) during random DBS facilitated abnormal low-frequency oscillations in the basal ganglia. These results suggest that the efficacy of high-frequency DBS stems from its ability to regularize patterns of neuronal firing and thereby suppress abnormal oscillatory neural activity within the basal ganglia. Copyright © 2016 the American Physiological Society.
Lu, Ting; Wade, Kirstie; Sanchez, Jason Tait
2017-01-01
ABSTRACT We have previously shown that late-developing avian nucleus magnocellularis (NM) neurons (embryonic [E] days 19–21) fire action potentials (APs) that resembles a band-pass filter in response to sinusoidal current injections of varying frequencies. NM neurons located in the mid- to high-frequency regions of the nucleus fire preferentially at 75 Hz, but only fire a single onset AP to frequency inputs greater than 200 Hz. Surprisingly, NM neurons do not fire APs to sinusoidal inputs less than 20 Hz regardless of the strength of the current injection. In the present study we evaluated intrinsic mechanisms that prevent AP generation to low frequency inputs. We constructed a computational model to simulate the frequency-firing patterns of NM neurons based on experimental data at both room and near physiologic temperatures. The results from our model confirm that the interaction among low- and high-voltage activated potassium channels (KLVA and KHVA, respectively) and voltage dependent sodium channels (NaV) give rise to the frequency-firing patterns observed in vitro. In particular, we evaluated the regulatory role of KLVA during low frequency sinusoidal stimulation. The model shows that, in response to low frequency stimuli, activation of large KLVA current counterbalances the slow-depolarizing current injection, likely permitting NaV closed-state inactivation and preventing the generation of APs. When the KLVA current density was reduced, the model neuron fired multiple APs per sinusoidal cycle, indicating that KLVA channels regulate low frequency AP firing of NM neurons. This intrinsic property of NM neurons may assist in optimizing response to different rates of synaptic inputs. PMID:28481659
Sasaki, Takuya; Piatti, Verónica C; Hwaun, Ernie; Ahmadi, Siavash; Lisman, John E; Leutgeb, Stefan; Leutgeb, Jill K
2018-02-01
Complex spatial working memory tasks have been shown to require both hippocampal sharp-wave ripple (SWR) activity and dentate gyrus (DG) neuronal activity. We therefore asked whether DG inputs to CA3 contribute to spatial working memory by promoting SWR generation. Recordings from DG and CA3 while rats performed a dentate-dependent working memory task on an eight-arm radial maze revealed that the activity of dentate neurons and the incidence rate of SWRs both increased during reward consumption. We then found reduced reward-related CA3 SWR generation without direct input from dentate granule neurons. Furthermore, CA3 cells with place fields in not-yet-visited arms preferentially fired during SWRs at reward locations, and these prospective CA3 firing patterns were more pronounced for correct trials and were dentate-dependent. These results indicate that coordination of CA3 neuronal activity patterns by DG is necessary for the generation of neuronal firing patterns that support goal-directed behavior and memory.
Galarraga, E; Vilchis, C; Tkatch, T; Salgado, H; Tecuapetla, F; Perez-Rosello, T; Perez-Garci, E; Hernandez-Echeagaray, E; Surmeier, D J; Bargas, J
2007-05-11
Somatostatin is synthesized and released by aspiny GABAergic interneurons of the neostriatum, some of them identified as low threshold spike generating neurons (LTS-interneurons). These neurons make synaptic contacts with spiny neostriatal projection neurons. However, very few somatostatin actions on projection neurons have been described. The present work reports that somatostatin modulates the Ca(2+) activated K(+) currents (K(Ca) currents) expressed by projection cells. These actions contribute in designing the firing pattern of the spiny projection neuron; which is the output of the neostriatum. Small conductance (SK) and large conductance (BK) K(Ca) currents represent between 30% and 50% of the sustained outward current in spiny cells. Somatostatin reduces SK-type K(+) currents and at the same time enhances BK-type K(+) currents. This dual effect enhances the fast component of the after hyperpolarizing potential while reducing the slow component. Somatostatin then modifies the firing pattern of spiny neurons which changed from a tonic regular pattern to an interrupted "stuttering"-like pattern. Semi-quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) tissue expression analysis of dorsal striatal somatostatinergic receptors (SSTR) mRNA revealed that all five SSTR mRNAs are present. However, single cell RT-PCR profiling suggests that the most probable receptor in charge of this modulation is the SSTR2 receptor. Interestingly, aspiny interneurons may exhibit a "stuttering"-like firing pattern. Therefore, somatostatin actions appear to be the entrainment of projection neurons to the rhythms generated by some interneurons. Somatostatin is then capable of modifying the processing and output of the neostriatum.
Vanacker, Charlotte; Moya, Manuel Ricu; DeFazio, R Anthony; Johnson, Michael L; Moenter, Suzanne M
2017-10-01
Pulsatile release of gonadotropin-releasing hormone (GnRH) is key to fertility. Pulse frequency is modulated by gonadal steroids and likely arises subsequent to coordination of GnRH neuron firing activity. The source of rhythm generation and the site of steroid feedback remain critical unanswered questions. Arcuate neurons that synthesize kisspeptin, neurokinin B, and dynorphin (KNDy) may be involved in both of these processes. We tested the hypotheses that action potential firing in KNDy neurons is episodic and that gonadal steroids regulate this pattern. Targeted extracellular recordings were made of green fluorescent protein-identified KNDy neurons in brain slices from adult male mice that were intact, castrated, or castrated and treated with estradiol or dihydrotestosterone (DHT). KNDy neurons exhibited marked peaks and nadirs in action potential firing activity during recordings lasting 1 to 3.5 hours. Peaks, identified by Cluster analysis, occurred more frequently in castrated than intact mice, and either estradiol or DHT in vivo or blocking neurokinin type 3 receptor in vitro restored peak frequency to intact levels. The frequency of peaks in firing rate and estradiol regulation of this frequency is similar to that observed for GnRH neurons, whereas DHT suppressed firing in KNDy but not GnRH neurons. We further examined the patterning of action potentials to identify bursts that may be associated with increased neuromodulator release. Burst frequency and duration are increased in castrated compared with intact and steroid-treated mice. The observation that KNDy neurons fire in an episodic manner that is regulated by steroid feedback is consistent with a role for these neurons in GnRH pulse generation and regulation. Copyright © 2017 Endocrine Society.
Neurons in the Amygdala with Response-Selectivity for Anxiety in Two Ethologically Based Tests
Wang, Dong V.; Wang, Fang; Liu, Jun; Zhang, Lu; Wang, Zhiru; Lin, Longnian
2011-01-01
The amygdala is a key area in the brain for detecting potential threats or dangers, and further mediating anxiety. However, the neuronal mechanisms of anxiety in the amygdala have not been well characterized. Here we report that in freely-behaving mice, a group of neurons in the basolateral amygdala (BLA) fires tonically under anxiety conditions in both open-field and elevated plus-maze tests. The firing patterns of these neurons displayed a characteristic slow onset and progressively increased firing rates. Specifically, these firing patterns were correlated to a gradual development of anxiety-like behaviors in the open-field test. Moreover, these neurons could be activated by any impoverished environment similar to an open-field; and introduction of both comfortable and uncomfortable stimuli temporarily suppressed the activity of these BLA neurons. Importantly, the excitability of these BLA neurons correlated well with levels of anxiety. These results demonstrate that this type of BLA neuron is likely to represent anxiety and/or emotional values of anxiety elicited by anxiogenic environmental stressors. PMID:21494567
Deep brain stimulation changes basal ganglia output nuclei firing pattern in the dystonic hamster.
Leblois, Arthur; Reese, René; Labarre, David; Hamann, Melanie; Richter, Angelika; Boraud, Thomas; Meissner, Wassilios G
2010-05-01
Dystonia is a heterogeneous syndrome of movement disorders characterized by involuntary muscle contractions leading to abnormal movements and postures. While medical treatment is often ineffective, deep brain stimulation (DBS) of the internal pallidum improves dystonia. Here, we studied the impact of DBS in the entopeduncular nucleus (EP), the rodent equivalent of the human globus pallidus internus, on basal ganglia output in the dt(sz)-hamster, a well-characterized model of dystonia by extracellular recordings. Previous work has shown that EP-DBS improves dystonic symptoms in dt(sz)-hamsters. We report that EP-DBS changes firing pattern in the EP, most neurons switching to a less regular firing pattern during DBS. In contrast, EP-DBS did not change the average firing rate of EP neurons. EP neurons display multiphasic responses to each stimulation impulse, likely underlying the disruption of their firing rhythm. Finally, neurons in the substantia nigra pars reticulata display similar responses to EP-DBS, supporting the idea that EP-DBS affects basal ganglia output activity through the activation of common afferent fibers. Copyright 2010 Elsevier Inc. All rights reserved.
Park, Eunkyoung; Song, Inho; Jang, Dong Pyo; Kim, In Young
2014-08-08
The pedunculopontine nucleus (PPN) has recently been introduced as an alternative target to the subthalamic nucleus (STN) or globus pallidus internus (GPi) for the treatment of advanced Parkinson's disease with severe and medically intractable axial symptoms such as gait and postural impairment. However, it is little known about how electrical stimulation of the PPN affects control of neuronal activities between the PPN and basal ganglia. We examined how low frequency stimulation of the pedunculopontine tegmental nucleus (PPTg) affects control of neuronal activities between the PPN and basal ganglia in 6-OHDA lesioned rats. In order to identify the effect of low frequency stimulation on the PPTg, neuronal activity in both the STN and substantia nigra par reticulata (SNr) were recorded and subjected to quantitative analysis, including analysis of firing rates and firing patterns. In this study, we found that the firing rates of the STN and SNr were suppressed during low frequency stimulation of the PPTg. However, the firing pattern, in contrast to the firing rate, did not exhibit significant changes in either the STN or SNr of 6-OHDA lesioned rats during low frequency stimulation of the PPTg. In addition, we also found that the firing rate of STN and SNr neurons displaying burst and random pattern were decreased by low frequency stimulation of PPTg, while the neurons displaying regular pattern were not affected. These results indicate that low frequency stimulation of the PPTg affects neuronal activity in both the STN and SNr, and may represent electrophysiological efficacy of low frequency PPN stimulation. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Correlation transfer from basal ganglia to thalamus in Parkinson's disease
Pamela, Reitsma; Brent, Doiron; Jonathan, Rubin
2011-01-01
Spike trains from neurons in the basal ganglia of parkinsonian primates show increased pairwise correlations, oscillatory activity, and burst rate compared to those from neurons recorded during normal brain activity. However, it is not known how these changes affect the behavior of downstream thalamic neurons. To understand how patterns of basal ganglia population activity may affect thalamic spike statistics, we study pairs of model thalamocortical (TC) relay neurons receiving correlated inhibitory input from the internal segment of the globus pallidus (GPi), a primary output nucleus of the basal ganglia. We observe that the strength of correlations of TC neuron spike trains increases with the GPi correlation level, and bursty firing patterns such as those seen in the parkinsonian GPi allow for stronger transfer of correlations than do firing patterns found under normal conditions. We also show that the T-current in the TC neurons does not significantly affect correlation transfer, despite its pronounced effects on spiking. Oscillatory firing patterns in GPi are shown to affect the timescale at which correlations are best transferred through the system. To explain this last result, we analytically compute the spike count correlation coefficient for oscillatory cases in a reduced point process model. Our analysis indicates that the dependence of the timescale of correlation transfer is robust to different levels of input spike and rate correlations and arises due to differences in instantaneous spike correlations, even when the long timescale rhythmic modulations of neurons are identical. Overall, these results show that parkinsonian firing patterns in GPi do affect the transfer of correlations to the thalamus. PMID:22355287
The Chronotron: A Neuron That Learns to Fire Temporally Precise Spike Patterns
Florian, Răzvan V.
2012-01-01
In many cases, neurons process information carried by the precise timings of spikes. Here we show how neurons can learn to generate specific temporally precise output spikes in response to input patterns of spikes having precise timings, thus processing and memorizing information that is entirely temporally coded, both as input and as output. We introduce two new supervised learning rules for spiking neurons with temporal coding of information (chronotrons), one that provides high memory capacity (E-learning), and one that has a higher biological plausibility (I-learning). With I-learning, the neuron learns to fire the target spike trains through synaptic changes that are proportional to the synaptic currents at the timings of real and target output spikes. We study these learning rules in computer simulations where we train integrate-and-fire neurons. Both learning rules allow neurons to fire at the desired timings, with sub-millisecond precision. We show how chronotrons can learn to classify their inputs, by firing identical, temporally precise spike trains for different inputs belonging to the same class. When the input is noisy, the classification also leads to noise reduction. We compute lower bounds for the memory capacity of chronotrons and explore the influence of various parameters on chronotrons' performance. The chronotrons can model neurons that encode information in the time of the first spike relative to the onset of salient stimuli or neurons in oscillatory networks that encode information in the phases of spikes relative to the background oscillation. Our results show that firing one spike per cycle optimizes memory capacity in neurons encoding information in the phase of firing relative to a background rhythm. PMID:22879876
Endogenous Sequential Cortical Activity Evoked by Visual Stimuli
Miller, Jae-eun Kang; Hamm, Jordan P.; Jackson, Jesse; Yuste, Rafael
2015-01-01
Although the functional properties of individual neurons in primary visual cortex have been studied intensely, little is known about how neuronal groups could encode changing visual stimuli using temporal activity patterns. To explore this, we used in vivo two-photon calcium imaging to record the activity of neuronal populations in primary visual cortex of awake mice in the presence and absence of visual stimulation. Multidimensional analysis of the network activity allowed us to identify neuronal ensembles defined as groups of cells firing in synchrony. These synchronous groups of neurons were themselves activated in sequential temporal patterns, which repeated at much higher proportions than chance and were triggered by specific visual stimuli such as natural visual scenes. Interestingly, sequential patterns were also present in recordings of spontaneous activity without any sensory stimulation and were accompanied by precise firing sequences at the single-cell level. Moreover, intrinsic dynamics could be used to predict the occurrence of future neuronal ensembles. Our data demonstrate that visual stimuli recruit similar sequential patterns to the ones observed spontaneously, consistent with the hypothesis that already existing Hebbian cell assemblies firing in predefined temporal sequences could be the microcircuit substrate that encodes visual percepts changing in time. PMID:26063915
Mechanisms of Firing Patterns in Fast-Spiking Cortical Interneurons
Golomb, David; Donner, Karnit; Shacham, Liron; Shlosberg, Dan; Amitai, Yael; Hansel, David
2007-01-01
Cortical fast-spiking (FS) interneurons display highly variable electrophysiological properties. Their spike responses to step currents occur almost immediately following the step onset or after a substantial delay, during which subthreshold oscillations are frequently observed. Their firing patterns include high-frequency tonic firing and rhythmic or irregular bursting (stuttering). What is the origin of this variability? In the present paper, we hypothesize that it emerges naturally if one assumes a continuous distribution of properties in a small set of active channels. To test this hypothesis, we construct a minimal, single-compartment conductance-based model of FS cells that includes transient Na+, delayed-rectifier K+, and slowly inactivating d-type K+ conductances. The model is analyzed using nonlinear dynamical system theory. For small Na+ window current, the neuron exhibits high-frequency tonic firing. At current threshold, the spike response is almost instantaneous for small d-current conductance, g d, and it is delayed for larger g d. As g d further increases, the neuron stutters. Noise substantially reduces the delay duration and induces subthreshold oscillations. In contrast, when the Na+ window current is large, the neuron always fires tonically. Near threshold, the firing rates are low, and the delay to firing is only weakly sensitive to noise; subthreshold oscillations are not observed. We propose that the variability in the response of cortical FS neurons is a consequence of heterogeneities in their g d and in the strength of their Na+ window current. We predict the existence of two types of firing patterns in FS neurons, differing in the sensitivity of the delay duration to noise, in the minimal firing rate of the tonic discharge, and in the existence of subthreshold oscillations. We report experimental results from intracellular recordings supporting this prediction. PMID:17696606
Mechanisms of firing patterns in fast-spiking cortical interneurons.
Golomb, David; Donner, Karnit; Shacham, Liron; Shlosberg, Dan; Amitai, Yael; Hansel, David
2007-08-01
Cortical fast-spiking (FS) interneurons display highly variable electrophysiological properties. Their spike responses to step currents occur almost immediately following the step onset or after a substantial delay, during which subthreshold oscillations are frequently observed. Their firing patterns include high-frequency tonic firing and rhythmic or irregular bursting (stuttering). What is the origin of this variability? In the present paper, we hypothesize that it emerges naturally if one assumes a continuous distribution of properties in a small set of active channels. To test this hypothesis, we construct a minimal, single-compartment conductance-based model of FS cells that includes transient Na(+), delayed-rectifier K(+), and slowly inactivating d-type K(+) conductances. The model is analyzed using nonlinear dynamical system theory. For small Na(+) window current, the neuron exhibits high-frequency tonic firing. At current threshold, the spike response is almost instantaneous for small d-current conductance, gd, and it is delayed for larger gd. As gd further increases, the neuron stutters. Noise substantially reduces the delay duration and induces subthreshold oscillations. In contrast, when the Na(+) window current is large, the neuron always fires tonically. Near threshold, the firing rates are low, and the delay to firing is only weakly sensitive to noise; subthreshold oscillations are not observed. We propose that the variability in the response of cortical FS neurons is a consequence of heterogeneities in their gd and in the strength of their Na(+) window current. We predict the existence of two types of firing patterns in FS neurons, differing in the sensitivity of the delay duration to noise, in the minimal firing rate of the tonic discharge, and in the existence of subthreshold oscillations. We report experimental results from intracellular recordings supporting this prediction.
A Topological Paradigm for Hippocampal Spatial Map Formation Using Persistent Homology
Dabaghian, Y.; Mémoli, F.; Frank, L.; Carlsson, G.
2012-01-01
An animal's ability to navigate through space rests on its ability to create a mental map of its environment. The hippocampus is the brain region centrally responsible for such maps, and it has been assumed to encode geometric information (distances, angles). Given, however, that hippocampal output consists of patterns of spiking across many neurons, and downstream regions must be able to translate those patterns into accurate information about an animal's spatial environment, we hypothesized that 1) the temporal pattern of neuronal firing, particularly co-firing, is key to decoding spatial information, and 2) since co-firing implies spatial overlap of place fields, a map encoded by co-firing will be based on connectivity and adjacency, i.e., it will be a topological map. Here we test this topological hypothesis with a simple model of hippocampal activity, varying three parameters (firing rate, place field size, and number of neurons) in computer simulations of rat trajectories in three topologically and geometrically distinct test environments. Using a computational algorithm based on recently developed tools from Persistent Homology theory in the field of algebraic topology, we find that the patterns of neuronal co-firing can, in fact, convey topological information about the environment in a biologically realistic length of time. Furthermore, our simulations reveal a “learning region” that highlights the interplay between the parameters in combining to produce hippocampal states that are more or less adept at map formation. For example, within the learning region a lower number of neurons firing can be compensated by adjustments in firing rate or place field size, but beyond a certain point map formation begins to fail. We propose that this learning region provides a coherent theoretical lens through which to view conditions that impair spatial learning by altering place cell firing rates or spatial specificity. PMID:22912564
McConnell, George C; So, Rosa Q; Hilliard, Justin D; Lopomo, Paola; Grill, Warren M
2012-11-07
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for the motor symptoms of Parkinson's disease (PD). The effects of DBS depend strongly on stimulation frequency: high frequencies (>90 Hz) improve motor symptoms, while low frequencies (<50 Hz) are either ineffective or exacerbate symptoms. The neuronal basis for these frequency-dependent effects of DBS is unclear. The effects of different frequencies of STN-DBS on behavior and single-unit neuronal activity in the basal ganglia were studied in the unilateral 6-hydroxydopamine lesioned rat model of PD. Only high-frequency DBS reversed motor symptoms, and the effectiveness of DBS depended strongly on stimulation frequency in a manner reminiscent of its clinical effects in persons with PD. Quantification of single-unit activity in the globus pallidus externa (GPe) and substantia nigra reticulata (SNr) revealed that high-frequency DBS, but not low-frequency DBS, reduced pathological low-frequency oscillations (∼9 Hz) and entrained neurons to fire at the stimulation frequency. Similarly, the coherence between simultaneously recorded pairs of neurons within and across GPe and SNr shifted from the pathological low-frequency band to the stimulation frequency during high-frequency DBS, but not during low-frequency DBS. The changes in firing patterns in basal ganglia neurons were not correlated with changes in firing rate. These results indicate that high-frequency DBS is more effective than low-frequency DBS, not as a result of changes in firing rate, but rather due to its ability to replace pathological low-frequency network oscillations with a regularized pattern of neuronal firing.
McConnell, George C.; So, Rosa Q.; Hilliard, Justin D; Lopomo, Paola; Grill, Warren M.
2012-01-01
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for the motor symptoms of Parkinson’s disease (PD). The effects of DBS depend strongly on stimulation frequency: high frequencies (>90Hz) improve motor symptoms, while low frequencies (<50Hz) are either ineffective or exacerbate symptoms. The neuronal basis for these frequency-dependent effects of DBS is unclear. The effects of different frequencies of STN-DBS on behavior and single-unit neuronal activity in the basal ganglia were studied in the unilateral 6-hydroxydopamine lesioned rat model of PD. Only high frequency DBS reversed motor symptoms and the effectiveness of DBS depended strongly on stimulation frequency in a manner reminiscent of its clinical effects in persons with PD. Quantification of single-unit activity in the globus pallidus externa (GPe) and substantia nigra reticulata (SNr) revealed that high frequency DBS, but not low frequency DBS, reduced pathological low frequency oscillations (~9Hz) and entrained neurons to fire at the stimulation frequency. Similarly, the coherence between simultaneously recorded pairs of neurons within and across GPe and SNr shifted from the pathological low frequency band to the stimulation frequency during high frequency DBS, but not during low frequency DBS. The changes in firing patterns in basal ganglia neurons were not correlated with changes in firing rate. These results indicate that high frequency DBS is more effective than low frequency DBS, not as a result of changes in firing rate, but rather due to its ability to replace pathological low frequency network oscillations with a regularized pattern of neuronal firing. PMID:23136407
Michmizos, Kostis P; Nikita, Konstantina S
2011-01-01
The crucial engagement of the subthalamic nucleus (STN) with the neurosurgical procedure of deep brain stimulation (DBS) that alleviates medically intractable Parkinsonian tremor augments the need to refine our current understanding of STN. To enhance the efficacy of DBS as a result of precise targeting, STN boundaries are accurately mapped using extracellular microelectrode recordings (MERs). We utilized the intranuclear MER to acquire the local field potential (LFP) and drive an Izhikevich model of an STN neuron. Using the model as the test bed for clinically acquired data, we demonstrated that stimulation of the STN neuron produces excitatory responses that tonically increase its average firing rate and alter the pattern of its neuronal activity. We also found that the spiking rhythm increases linearly with the increase of amplitude, frequency, and duration of the DBS pulse, inside the clinical range. Our results are in agreement with the current hypothesis that DBS increases the firing rate of STN and masks its pathological bursting firing pattern.
Zimnik, Andrew J.; Nora, Gerald J.; Desmurget, Michel
2015-01-01
Deep brain stimulation (DBS) of the subthalamic nucleus (STN-DBS) has largely replaced ablative therapies for Parkinson's disease. Because of the similar efficacies of the two treatments, it has been proposed that DBS acts by creating an “informational lesion,” whereby pathologic neuronal firing patterns are replaced by low-entropy, stimulus-entrained firing patterns. The informational lesion hypothesis, in its current form, states that DBS blocks the transmission of all information from the basal ganglia, including both pathologic firing patterns and normal, task-related modulations in activity. We tested this prediction in two healthy rhesus macaques by recording single-unit spiking activity from the globus pallidus (232 neurons) while the animals completed choice reaction time reaching movements with and without STN-DBS. Despite strong effects of DBS on the activity of most pallidal cells, reach-related modulations in firing rate were equally prevalent in the DBS-on and DBS-off states. This remained true even when the analysis was restricted to cells affected significantly by DBS. In addition, the overall form and timing of perimovement modulations in firing rate were preserved between DBS-on and DBS-off states in the majority of neurons (66%). Active movement and DBS had largely additive effects on the firing rate of most neurons, indicating an orthogonal relationship in which both inputs contribute independently to the overall firing rate of pallidal neurons. These findings suggest that STN-DBS does not act as an indiscriminate informational lesion but rather as a filter that permits task-related modulations in activity while, presumably, eliminating the pathological firing associated with parkinsonism. PMID:25740526
Forrest, Michael D.
2014-01-01
Without synaptic input, Purkinje neurons can spontaneously fire in a repeating trimodal pattern that consists of tonic spiking, bursting and quiescence. Climbing fiber input (CF) switches Purkinje neurons out of the trimodal firing pattern and toggles them between a tonic firing and a quiescent state, while setting the gain of their response to Parallel Fiber (PF) input. The basis to this transition is unclear. We investigate it using a biophysical Purkinje cell model under conditions of CF and PF input. The model can replicate these toggle and gain functions, dependent upon a novel account of intracellular calcium dynamics that we hypothesize to be applicable in real Purkinje cells. PMID:25191262
Model of the songbird nucleus HVC as a network of central pattern generators
Abarbanel, Henry D. I.
2016-01-01
We propose a functional architecture of the adult songbird nucleus HVC in which the core element is a “functional syllable unit” (FSU). In this model, HVC is organized into FSUs, each of which provides the basis for the production of one syllable in vocalization. Within each FSU, the inhibitory neuron population takes one of two operational states: 1) simultaneous firing wherein all inhibitory neurons fire simultaneously, and 2) competitive firing of the inhibitory neurons. Switching between these basic modes of activity is accomplished via changes in the synaptic strengths among the inhibitory neurons. The inhibitory neurons connect to excitatory projection neurons such that during state 1 the activity of projection neurons is suppressed, while during state 2 patterns of sequential firing of projection neurons can occur. The latter state is stabilized by feedback from the projection to the inhibitory neurons. Song composition for specific species is distinguished by the manner in which different FSUs are functionally connected to each other. Ours is a computational model built with biophysically based neurons. We illustrate that many observations of HVC activity are explained by the dynamics of the proposed population of FSUs, and we identify aspects of the model that are currently testable experimentally. In addition, and standing apart from the core features of an FSU, we propose that the transition between modes may be governed by the biophysical mechanism of neuromodulation. PMID:27535375
The medial prefrontal and orbitofrontal cortices differentially regulate dopamine system function.
Lodge, Daniel J
2011-05-01
The prefrontal cortex (PFC) is essential for top-down control over higher-order executive function. In this study we demonstrate that the medial prefrontal cortex (mPFC) and orbitofrontal cortex (OFC) differentially regulate VTA dopamine neuron activity, and furthermore, the pattern of activity in the PFC drastically alters the dopamine neuron response. Thus, although single-pulse activation of the mPFC either excites or inhibits equivalent numbers of dopamine neurons, activation of the OFC induces a primarily inhibitory response. Moreover, activation of the PFC with a pattern that mimics spontaneous burst firing of pyramidal neurons produces a strikingly different response. Specifically, burst-like activation of the mPFC induces a massive increase in dopamine neuron firing, whereas a similar pattern of OFC activation largely inhibits dopamine activity. Taken together, these data demonstrate that the mPFC and OFC differentially regulate dopamine neuron activity, and that the pattern of cortical activation is critical for determining dopamine system output.
Irregular behavior in an excitatory-inhibitory neuronal network
NASA Astrophysics Data System (ADS)
Park, Choongseok; Terman, David
2010-06-01
Excitatory-inhibitory networks arise in many regions throughout the central nervous system and display complex spatiotemporal firing patterns. These neuronal activity patterns (of individual neurons and/or the whole network) are closely related to the functional status of the system and differ between normal and pathological states. For example, neurons within the basal ganglia, a group of subcortical nuclei that are responsible for the generation of movement, display a variety of dynamic behaviors such as correlated oscillatory activity and irregular, uncorrelated spiking. Neither the origins of these firing patterns nor the mechanisms that underlie the patterns are well understood. We consider a biophysical model of an excitatory-inhibitory network in the basal ganglia and explore how specific biophysical properties of the network contribute to the generation of irregular spiking. We use geometric dynamical systems and singular perturbation methods to systematically reduce the model to a simpler set of equations, which is suitable for analysis. The results specify the dependence on the strengths of synaptic connections and the intrinsic firing properties of the cells in the irregular regime when applied to the subthalamopallidal network of the basal ganglia.
Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.
Onken, Arno; Liu, Jian K; Karunasekara, P P Chamanthi R; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano
2016-11-01
Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding.
Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains
Onken, Arno; Liu, Jian K.; Karunasekara, P. P. Chamanthi R.; Delis, Ioannis; Gollisch, Tim; Panzeri, Stefano
2016-01-01
Advances in neuronal recording techniques are leading to ever larger numbers of simultaneously monitored neurons. This poses the important analytical challenge of how to capture compactly all sensory information that neural population codes carry in their spatial dimension (differences in stimulus tuning across neurons at different locations), in their temporal dimension (temporal neural response variations), or in their combination (temporally coordinated neural population firing). Here we investigate the utility of tensor factorizations of population spike trains along space and time. These factorizations decompose a dataset of single-trial population spike trains into spatial firing patterns (combinations of neurons firing together), temporal firing patterns (temporal activation of these groups of neurons) and trial-dependent activation coefficients (strength of recruitment of such neural patterns on each trial). We validated various factorization methods on simulated data and on populations of ganglion cells simultaneously recorded in the salamander retina. We found that single-trial tensor space-by-time decompositions provided low-dimensional data-robust representations of spike trains that capture efficiently both their spatial and temporal information about sensory stimuli. Tensor decompositions with orthogonality constraints were the most efficient in extracting sensory information, whereas non-negative tensor decompositions worked well even on non-independent and overlapping spike patterns, and retrieved informative firing patterns expressed by the same population in response to novel stimuli. Our method showed that populations of retinal ganglion cells carried information in their spike timing on the ten-milliseconds-scale about spatial details of natural images. This information could not be recovered from the spike counts of these cells. First-spike latencies carried the majority of information provided by the whole spike train about fine-scale image features, and supplied almost as much information about coarse natural image features as firing rates. Together, these results highlight the importance of spike timing, and particularly of first-spike latencies, in retinal coding. PMID:27814363
Faghihi, Faramarz; Moustafa, Ahmed A.
2015-01-01
Information processing in the hippocampus begins by transferring spiking activity of the entorhinal cortex (EC) into the dentate gyrus (DG). Activity pattern in the EC is separated by the DG such that it plays an important role in hippocampal functions including memory. The structural and physiological parameters of these neural networks enable the hippocampus to be efficient in encoding a large number of inputs that animals receive and process in their life time. The neural encoding capacity of the DG depends on its single neurons encoding and pattern separation efficiency. In this study, encoding by the DG is modeled such that single neurons and pattern separation efficiency are measured using simulations of different parameter values. For this purpose, a probabilistic model of single neurons efficiency is presented to study the role of structural and physiological parameters. Known neurons number of the EC and the DG is used to construct a neural network by electrophysiological features of granule cells of the DG. Separated inputs as activated neurons in the EC with different firing probabilities are presented into the DG. For different connectivity rates between the EC and DG, pattern separation efficiency of the DG is measured. The results show that in the absence of feedback inhibition on the DG neurons, the DG demonstrates low separation efficiency and high firing frequency. Feedback inhibition can increase separation efficiency while resulting in very low single neuron’s encoding efficiency in the DG and very low firing frequency of neurons in the DG (sparse spiking). This work presents a mechanistic explanation for experimental observations in the hippocampus, in combination with theoretical measures. Moreover, the model predicts a critical role for impaired inhibitory neurons in schizophrenia where deficiency in pattern separation of the DG has been observed. PMID:25859189
Borges, F S; Protachevicz, P R; Lameu, E L; Bonetti, R C; Iarosz, K C; Caldas, I L; Baptista, M S; Batista, A M
2017-06-01
We have studied neuronal synchronisation in a random network of adaptive exponential integrate-and-fire neurons. We study how spiking or bursting synchronous behaviour appears as a function of the coupling strength and the probability of connections, by constructing parameter spaces that identify these synchronous behaviours from measurements of the inter-spike interval and the calculation of the order parameter. Moreover, we verify the robustness of synchronisation by applying an external perturbation to each neuron. The simulations show that bursting synchronisation is more robust than spike synchronisation. Copyright © 2017 Elsevier Ltd. All rights reserved.
Kim, Steve M; Ganguli, Surya; Frank, Loren M
2012-08-22
Hippocampal place cells convey spatial information through a combination of spatially selective firing and theta phase precession. The way in which this information influences regions like the subiculum that receive input from the hippocampus remains unclear. The subiculum receives direct inputs from area CA1 of the hippocampus and sends divergent output projections to many other parts of the brain, so we examined the firing patterns of rat subicular neurons. We found a substantial transformation in the subicular code for space from sparse to dense firing rate representations along a proximal-distal anatomical gradient: neurons in the proximal subiculum are more similar to canonical, sparsely firing hippocampal place cells, whereas neurons in the distal subiculum have higher firing rates and more distributed spatial firing patterns. Using information theory, we found that the more distributed spatial representation in the subiculum carries, on average, more information about spatial location and context than the sparse spatial representation in CA1. Remarkably, despite the disparate firing rate properties of subicular neurons, we found that neurons at all proximal-distal locations exhibit robust theta phase precession, with similar spiking oscillation frequencies as neurons in area CA1. Our findings suggest that the subiculum is specialized to compress sparse hippocampal spatial codes into highly informative distributed codes suitable for efficient communication to other brain regions. Moreover, despite this substantial compression, the subiculum maintains finer scale temporal properties that may allow it to participate in oscillatory phase coding and spike timing-dependent plasticity in coordination with other regions of the hippocampal circuit.
A hidden Markov model approach to neuron firing patterns.
Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G
1996-11-01
Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing.
Lin, Chia-Wei; Sim, Shuyin; Ainsworth, Alice; Okada, Masayoshi; Kelsch, Wolfgang; Lois, Carlos
2009-01-01
New neurons are added to the adult brain throughout life, but only half ultimately integrate into existing circuits. Sensory experience is an important regulator of the selection of new neurons but it remains unknown whether experience provides specific patterns of synaptic input, or simply a minimum level of overall membrane depolarization critical for integration. To investigate this issue, we genetically modified intrinsic electrical properties of adult-generated neurons in the mammalian olfactory bulb. First, we observed that suppressing levels of cell-intrinsic neuronal activity via expression of ESKir2.1 potassium channels decreases, whereas enhancing activity via expression of NaChBac sodium channels increases survival of new neurons. Neither of these modulations affects synaptic formation. Furthermore, even when neurons are induced to fire dramatically altered patterns of action potentials, increased levels of cell-intrinsic activity completely blocks cell death triggered by NMDA receptor deletion. These findings demonstrate that overall levels of cell-intrinsic activity govern survival of new neurons and precise firing patterns are not essential for neuronal integration into existing brain circuits. PMID:20152111
Chen, Ting Y; Zhang, Die; Dragomir, Andrei; Akay, Yasemin; Akay, Metin
2011-05-01
We investigated the influence of nicotine exposure and prefrontal cortex (PFC) transections on ventral tegmental areas (VTA) dopamine (DA) neurons' firing activities using a time-frequency method based on the continuous wavelet transform (CWT). Extracellular single-unit neural activity was recorded from DA neurons in the VTA area of rats. One group had their PFC inputs to the VTA intact, while the other group had the inputs to VTA bilaterally transected immediate caudal to the PFC. We hypothesized that the systemic nicotine exposure will significantly change the energy distribution in the recorded neural activity. Additionally, we investigated whether the loss of inputs to the VTA caused by the PFC transection resulted in the cancellation of the nicotine' effect on the neurons' firing patterns. The time-frequency representations of VTA DA neurons firing activity were estimated from the reconstructed firing rate histogram. The energy contents were estimated from three frequency bands, which are known to encompass the significant modes of operation of DA neurons. Our results show that systemic nicotine exposure disrupts the energy distribution in PFC-intact rats. Particularly, there is a significant increase in energy contents of the 1-1.5 Hz frequency band. This corresponds to an observed increase in the firing rate of VTA DA neurons following nicotine exposure. Additionally, our results from PFC-transected rats show that there is no change in the energy distribution of the recordings after systemic nicotine exposure. These results indicate that the PFC plays an important role in affecting the activities of VTA DA neurons and that the CWT is a useful method for monitoring the changes in neural activity patterns in both time and frequency domains.
A Calcium-Dependent Chloride Current Increases Repetitive Firing in Mouse Sympathetic Neurons
Martinez-Pinna, Juan; Soriano, Sergi; Tudurí, Eva; Nadal, Angel; de Castro, Fernando
2018-01-01
Ca2+-activated ion channels shape membrane excitability in response to elevations in intracellular Ca2+. The most extensively studied Ca2+-sensitive ion channels are Ca2+-activated K+ channels, whereas the physiological importance of Ca2+-activated Cl- channels has been poorly studied. Here we show that a Ca2+-activated Cl- currents (CaCCs) modulate repetitive firing in mouse sympathetic ganglion cells. Electrophysiological recording of mouse sympathetic neurons in an in vitro preparation of the superior cervical ganglion (SCG) identifies neurons with two different firing patterns in response to long depolarizing current pulses (1 s). Neurons classified as phasic (Ph) made up 67% of the cell population whilst the remainders were tonic (T). When a high frequency train of spikes was induced by intracellular current injection, SCG sympathetic neurons reached an afterpotential mainly dependent on the ratio of activation of two Ca2+-dependent currents: the K+ [IK(Ca)] and CaCC. When the IK(Ca) was larger, an afterhyperpolarization was the predominant afterpotential but when the CaCC was larger, an afterdepolarization (ADP) was predominant. These afterpotentials can be observed after a single action potential (AP). Ph and T neurons had similar ADPs and hence, the CaCC does not seem to determine the firing pattern (Ph or T) of these neurons. However, inhibition of Ca2+-activated Cl- channels with anthracene-9′-carboxylic acid (9AC) selectively inhibits the ADP, reducing the firing frequency and the instantaneous frequency without affecting the characteristics of single- or first-spike firing of both Ph and T neurons. Furthermore, we found that the CaCC underlying the ADP was significantly larger in SCG neurons from males than from females. Furthermore, the CaCC ANO1/TMEM16A was more strongly expressed in male than in female SCGs. Blocking ADPs with 9AC did not modify synaptic transmission in either Ph or T neurons. We conclude that the CaCC responsible for ADPs increases repetitive firing in both Ph and T neurons, and it is more relevant in male mouse sympathetic ganglion neurons. PMID:29867553
A Calcium-Dependent Chloride Current Increases Repetitive Firing in Mouse Sympathetic Neurons.
Martinez-Pinna, Juan; Soriano, Sergi; Tudurí, Eva; Nadal, Angel; de Castro, Fernando
2018-01-01
Ca 2+ -activated ion channels shape membrane excitability in response to elevations in intracellular Ca 2+ . The most extensively studied Ca 2+ -sensitive ion channels are Ca 2+ -activated K + channels, whereas the physiological importance of Ca 2+ -activated Cl - channels has been poorly studied. Here we show that a Ca 2+ -activated Cl - currents (CaCCs) modulate repetitive firing in mouse sympathetic ganglion cells. Electrophysiological recording of mouse sympathetic neurons in an in vitro preparation of the superior cervical ganglion (SCG) identifies neurons with two different firing patterns in response to long depolarizing current pulses (1 s). Neurons classified as phasic (Ph) made up 67% of the cell population whilst the remainders were tonic (T). When a high frequency train of spikes was induced by intracellular current injection, SCG sympathetic neurons reached an afterpotential mainly dependent on the ratio of activation of two Ca 2+ -dependent currents: the K + [I K(Ca) ] and CaCC. When the I K(Ca) was larger, an afterhyperpolarization was the predominant afterpotential but when the CaCC was larger, an afterdepolarization (ADP) was predominant. These afterpotentials can be observed after a single action potential (AP). Ph and T neurons had similar ADPs and hence, the CaCC does not seem to determine the firing pattern (Ph or T) of these neurons. However, inhibition of Ca 2+ -activated Cl - channels with anthracene-9'-carboxylic acid (9AC) selectively inhibits the ADP, reducing the firing frequency and the instantaneous frequency without affecting the characteristics of single- or first-spike firing of both Ph and T neurons. Furthermore, we found that the CaCC underlying the ADP was significantly larger in SCG neurons from males than from females. Furthermore, the CaCC ANO1/TMEM16A was more strongly expressed in male than in female SCGs. Blocking ADPs with 9AC did not modify synaptic transmission in either Ph or T neurons. We conclude that the CaCC responsible for ADPs increases repetitive firing in both Ph and T neurons, and it is more relevant in male mouse sympathetic ganglion neurons.
Goldberg, Jesse H.; Adler, Avital; Bergman, Hagai; Fee, Michale S.
2010-01-01
The songbird area X is a basal ganglia homologue that contains two pallidal cell types—local neurons that project within the basal ganglia and output neurons that project to the thalamus. Based on these projections, it has been proposed that these classes are structurally homologous to the primate external (GPe) and internal (GPi) pallidal segments. To test the hypothesis that the two area X pallidal types are functionally homologous to GPe and GPi neurons, we recorded from neurons in area X of singing juvenile male zebra finches, and directly compare their firing patterns to neurons recorded in the primate pallidus. In area X, we find two cell classes that exhibited high firing (HF) rates (>60Hz) characteristic of pallidal neurons. HF-1 neurons, like most GPe neurons we examined, exhibited large firing rate modulations, including bursts and long pauses. In contrast, HF-2 neurons, like GPi neurons, discharged continuously without bursts or long pauses. To test if HF-2 neurons were the output neurons that project to the thalamus, we next recorded directly from pallidal axon terminals in thalamic nucleus DLM, and found that all terminals exhibited singing-related firing patterns indistinguishable from HF-2 neurons. Our data show that singing-related neural activity distinguishes two putative pallidal cell types in area X: thalamus-projecting neurons that exhibit activity similar to the primate GPi, and non-thalamus-projecting neurons that exhibit activity similar to the primate GPe. These results suggest that song learning in birds and motor learning in mammals employ conserved basal ganglia signaling strategies. PMID:20484651
Kim, J H; Ohara, S; Lenz, F A
2009-04-01
Primate thalamic action potential bursts associated with low-threshold spikes (LTS) occur during waking sensory and motor activity. We now test the hypothesis that different firing and LTS burst characteristics occur during quiet wakefulness (spontaneous condition) versus mental arithmetic (counting condition). This hypothesis was tested by thalamic recordings during the surgical treatment of tremor. Across all neurons and epochs, preburst interspike intervals (ISIs) were bimodal at median values, consistent with the duration of type A and type B gamma-aminobutyric acid inhibitory postsynaptic potentials. Neuronal spike trains (117 neurons) were categorized by joint ISI distributions into those firing as LTS bursts (G, grouped), firing as single spikes (NG, nongrouped), or firing as single spikes with sporadic LTS bursting (I, intermediate). During the spontaneous condition (46 neurons) only I spike trains changed category. Overall, burst rates (BRs) were lower and firing rates (FRs) were higher during the counting versus the spontaneous condition. Spike trains in the G category sometimes changed to I and NG categories at the transition from the spontaneous to the counting condition, whereas those in the I category often changed to NG. Among spike trains that did not change category by condition, G spike trains had lower BRs during counting, whereas NG spike trains had higher FRs. BRs were significantly greater than zero for G and I categories during wakefulness (both conditions). The changes between the spontaneous and counting conditions are most pronounced for the I category, which may be a transitional firing pattern between the bursting (G) and relay modes of thalamic firing (NG).
Effects of topologies on signal propagation in feedforward networks
NASA Astrophysics Data System (ADS)
Zhao, Jia; Qin, Ying-Mei; Che, Yan-Qiu
2018-01-01
We systematically investigate the effects of topologies on signal propagation in feedforward networks (FFNs) based on the FitzHugh-Nagumo neuron model. FFNs with different topological structures are constructed with same number of both in-degrees and out-degrees in each layer and given the same input signal. The propagation of firing patterns and firing rates are found to be affected by the distribution of neuron connections in the FFNs. Synchronous firing patterns emerge in the later layers of FFNs with identical, uniform, and exponential degree distributions, but the number of synchronous spike trains in the output layers of the three topologies obviously differs from one another. The firing rates in the output layers of the three FFNs can be ordered from high to low according to their topological structures as exponential, uniform, and identical distributions, respectively. Interestingly, the sequence of spiking regularity in the output layers of the three FFNs is consistent with the firing rates, but their firing synchronization is in the opposite order. In summary, the node degree is an important factor that can dramatically influence the neuronal network activity.
Effects of topologies on signal propagation in feedforward networks.
Zhao, Jia; Qin, Ying-Mei; Che, Yan-Qiu
2018-01-01
We systematically investigate the effects of topologies on signal propagation in feedforward networks (FFNs) based on the FitzHugh-Nagumo neuron model. FFNs with different topological structures are constructed with same number of both in-degrees and out-degrees in each layer and given the same input signal. The propagation of firing patterns and firing rates are found to be affected by the distribution of neuron connections in the FFNs. Synchronous firing patterns emerge in the later layers of FFNs with identical, uniform, and exponential degree distributions, but the number of synchronous spike trains in the output layers of the three topologies obviously differs from one another. The firing rates in the output layers of the three FFNs can be ordered from high to low according to their topological structures as exponential, uniform, and identical distributions, respectively. Interestingly, the sequence of spiking regularity in the output layers of the three FFNs is consistent with the firing rates, but their firing synchronization is in the opposite order. In summary, the node degree is an important factor that can dramatically influence the neuronal network activity.
Intrinsic modulation of pulse-coupled integrate-and-fire neurons
NASA Astrophysics Data System (ADS)
Coombes, S.; Lord, G. J.
1997-11-01
Intrinsic neuromodulation is observed in sensory and neuromuscular circuits and in biological central pattern generators. We model a simple neuronal circuit with a system of two pulse-coupled integrate-and-fire neurons and explore the parameter regimes for periodic firing behavior. The inclusion of biologically realistic features shows that the speed and onset of neuronal response plays a crucial role in determining the firing phase for periodic rhythms. We explore the neurophysiological function of distributed delays arising from both the synaptic transmission process and dendritic structure as well as discrete delays associated with axonal communication delays. Bifurcation and stability diagrams are constructed with a mixture of simple analysis, numerical continuation and the Kuramoto phase-reduction technique. Moreover, we show that, for asynchronous behavior, the strength of electrical synapses can control the firing rate of the system.
Toward heterogeneity in feedforward network with synaptic delays based on FitzHugh-Nagumo model
NASA Astrophysics Data System (ADS)
Qin, Ying-Mei; Men, Cong; Zhao, Jia; Han, Chun-Xiao; Che, Yan-Qiu
2018-01-01
We focus on the role of heterogeneity on the propagation of firing patterns in feedforward network (FFN). Effects of heterogeneities both in parameters of neuronal excitability and synaptic delays are investigated systematically. Neuronal heterogeneity is found to modulate firing rates and spiking regularity by changing the excitability of the network. Synaptic delays are strongly related with desynchronized and synchronized firing patterns of the FFN, which indicate that synaptic delays may play a significant role in bridging rate coding and temporal coding. Furthermore, quasi-coherence resonance (quasi-CR) phenomenon is observed in the parameter domain of connection probability and delay-heterogeneity. All these phenomena above enable a detailed characterization of neuronal heterogeneity in FFN, which may play an indispensable role in reproducing the important properties of in vivo experiments.
A hidden Markov model approach to neuron firing patterns.
Camproux, A C; Saunier, F; Chouvet, G; Thalabard, J C; Thomas, G
1996-01-01
Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing. Images FIGURE 3 PMID:8913581
Agarwal, Rahul; Thakor, Nitish V; Sarma, Sridevi V; Massaquoi, Steve G
2015-06-24
The premotor cortex (PM) is known to be a site of visuo-somatosensory integration for the production of movement. We sought to better understand the ventral PM (PMv) by modeling its signal encoding in greater detail. Neuronal firing data was obtained from 110 PMv neurons in two male rhesus macaques executing four reach-grasp-manipulate tasks. We found that in the large majority of neurons (∼90%) the firing patterns across the four tasks could be explained by assuming that a high-dimensional position/configuration trajectory-like signal evolving ∼250 ms before movement was encoded within a multidimensional Gaussian field (MGF). Our findings are consistent with the possibility that PMv neurons process a visually specified reference command for the intended arm/hand position trajectory with respect to a proprioceptively or visually sensed initial configuration. The estimated MGF were (hyper) disc-like, such that each neuron's firing modulated strongly only with commands that evolved along a single direction within position/configuration space. Thus, many neurons appeared to be tuned to slices of this input signal space that as a collection appeared to well cover the space. The MGF encoding models appear to be consistent with the arm-referent, bell-shaped, visual target tuning curves and target selectivity patterns observed in PMV visual-motor neurons. These findings suggest that PMv may implement a lookup table-like mechanism that helps translate intended movement trajectory into time-varying patterns of activation in motor cortex and spinal cord. MGFs provide an improved nonlinear framework for potentially decoding visually specified, intended multijoint arm/hand trajectories well in advance of movement. Copyright © 2015 the authors 0270-6474/15/359508-18$15.00/0.
Contribution of synchronized GABAergic neurons to dopaminergic neuron firing and bursting.
Morozova, Ekaterina O; Myroshnychenko, Maxym; Zakharov, Denis; di Volo, Matteo; Gutkin, Boris; Lapish, Christopher C; Kuznetsov, Alexey
2016-10-01
In the ventral tegmental area (VTA), interactions between dopamine (DA) and γ-aminobutyric acid (GABA) neurons are critical for regulating DA neuron activity and thus DA efflux. To provide a mechanistic explanation of how GABA neurons influence DA neuron firing, we developed a circuit model of the VTA. The model is based on feed-forward inhibition and recreates canonical features of the VTA neurons. Simulations revealed that γ-aminobutyric acid (GABA) receptor (GABAR) stimulation can differentially influence the firing pattern of the DA neuron, depending on the level of synchronization among GABA neurons. Asynchronous activity of GABA neurons provides a constant level of inhibition to the DA neuron and, when removed, produces a classical disinhibition burst. In contrast, when GABA neurons are synchronized by common synaptic input, their influence evokes additional spikes in the DA neuron, resulting in increased measures of firing and bursting. Distinct from previous mechanisms, the increases were not based on lowered firing rate of the GABA neurons or weaker hyperpolarization by the GABAR synaptic current. This phenomenon was induced by GABA-mediated hyperpolarization of the DA neuron that leads to decreases in intracellular calcium (Ca 2+ ) concentration, thus reducing the Ca 2+ -dependent potassium (K + ) current. In this way, the GABA-mediated hyperpolarization replaces Ca 2+ -dependent K + current; however, this inhibition is pulsatile, which allows the DA neuron to fire during the rhythmic pauses in inhibition. Our results emphasize the importance of inhibition in the VTA, which has been discussed in many studies, and suggest a novel mechanism whereby computations can occur locally. Copyright © 2016 the American Physiological Society.
Contribution of synchronized GABAergic neurons to dopaminergic neuron firing and bursting
Myroshnychenko, Maxym; Zakharov, Denis; di Volo, Matteo; Gutkin, Boris; Lapish, Christopher C.; Kuznetsov, Alexey
2016-01-01
In the ventral tegmental area (VTA), interactions between dopamine (DA) and γ-aminobutyric acid (GABA) neurons are critical for regulating DA neuron activity and thus DA efflux. To provide a mechanistic explanation of how GABA neurons influence DA neuron firing, we developed a circuit model of the VTA. The model is based on feed-forward inhibition and recreates canonical features of the VTA neurons. Simulations revealed that γ-aminobutyric acid (GABA) receptor (GABAR) stimulation can differentially influence the firing pattern of the DA neuron, depending on the level of synchronization among GABA neurons. Asynchronous activity of GABA neurons provides a constant level of inhibition to the DA neuron and, when removed, produces a classical disinhibition burst. In contrast, when GABA neurons are synchronized by common synaptic input, their influence evokes additional spikes in the DA neuron, resulting in increased measures of firing and bursting. Distinct from previous mechanisms, the increases were not based on lowered firing rate of the GABA neurons or weaker hyperpolarization by the GABAR synaptic current. This phenomenon was induced by GABA-mediated hyperpolarization of the DA neuron that leads to decreases in intracellular calcium (Ca2+) concentration, thus reducing the Ca2+-dependent potassium (K+) current. In this way, the GABA-mediated hyperpolarization replaces Ca2+-dependent K+ current; however, this inhibition is pulsatile, which allows the DA neuron to fire during the rhythmic pauses in inhibition. Our results emphasize the importance of inhibition in the VTA, which has been discussed in many studies, and suggest a novel mechanism whereby computations can occur locally. PMID:27440240
Saito, Yasuhiko; Zhang, Yue; Yanagawa, Yuchio
2015-04-01
Although it has been proposed that neurons that contain both acetylcholine (ACh) and γ-aminobutyric acid (GABA) are present in the prepositus hypoglossi nucleus (PHN), these neurons have not been characterized because of the difficulty in identifying them. In the present study, PHN neurons that express both choline acetyltransferase and the vesicular GABA transporter (VGAT) were identified using double-transgenic rats, in which the cholinergic and inhibitory neurons express the fluorescent proteins tdTomato and Venus, respectively. To characterize the neurons that express both tdTomato and Venus (D+ neurons), the afterhyperpolarization (AHP) profiles and firing patterns of these neurons were investigated via whole-cell recordings of brainstem slice preparations. Regarding the three AHP profiles and four firing patterns that the D+ neurons exhibited, an AHP with an afterdepolarization and a firing pattern that exhibited a delay in the generation of the first spike were the preferential properties of these neurons. In the three morphological types classified, the multipolar type that exhibited radiating dendrites was predominant among the D+ neurons. Immunocytochemical analysis revealed that the VGAT-immunopositive axonal boutons that expressed tdTomato were primarily located in the dorsal cap of inferior olive (IO) and the PHN. Although the PHN receives cholinergic inputs from the pedunculopontine tegmental nucleus and laterodorsal tegmental nucleus, D+ neurons were absent from these brain areas. Together, these results suggest that PHN neurons that co-express ACh and GABA exhibit specific electrophysiological and morphological properties, and innervate the dorsal cap of the IO and the PHN. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Pulse-coupled neural network sensor fusion
NASA Astrophysics Data System (ADS)
Johnson, John L.; Schamschula, Marius P.; Inguva, Ramarao; Caulfield, H. John
1998-03-01
Perception is assisted by sensed impressions of the outside world but not determined by them. The primary organ of perception is the brain and, in particular, the cortex. With that in mind, we have sought to see how a computer-modeled cortex--the PCNN or Pulse Coupled Neural Network--performs as a sensor fusing element. In essence, the PCNN is comprised of an array of integrate-and-fire neurons with one neuron for each input pixel. In such a system, the neurons corresponding to bright pixels reach firing threshold faster than the neurons corresponding to duller pixels. Thus, firing rate is proportional to brightness. In PCNNs, when a neuron fires it sends some of the resulting signal to its neighbors. This linking can cause a near-threshold neuron to fire earlier than it would have otherwise. This leads to synchronization of the pulses across large regions of the image. We can simplify the 3D PCNN output by integrating out the time dimension. Over a long enough time interval, the resulting 2D (x,y) pattern IS the input image. The PCNN has taken it apart and put it back together again. The shorter- term time integrals are interesting in themselves and will be commented upon in the paper. The main thrust of this paper is the use of multiple PCNNs mutually coupled in various ways to assemble a single 2D pattern or fused image. Results of experiments on PCNN image fusion and an evaluation of its advantages are our primary objectives.
Hasselmo, Michael E.
2008-01-01
This article presents a model of grid cell firing based on the intrinsic persistent firing shown experimentally in neurons of entorhinal cortex. In this model, the mechanism of persistent firing allows individual neurons to hold a stable baseline firing frequency. Depolarizing input from speed modulated head direction cells transiently shifts the frequency of firing from baseline, resulting in a shift in spiking phase in proportion to the integral of velocity. The convergence of input from different persistent firing neurons causes spiking in a grid cell only when the persistent firing neurons are within similar phase ranges. This model effectively simulates the two-dimensional firing of grid cells in open field environments, as well as the properties of theta phase precession. This model provides an alternate implementation of oscillatory interference models. The persistent firing could also interact on a circuit level with rhythmic inhibition and neurons showing membrane potential oscillations to code position with spiking phase. These mechanisms could operate in parallel with computation of position from visual angle and distance of stimuli. In addition to simulating two-dimensional grid patterns, models of phase interference can account for context-dependent firing in other tasks. In network simulations of entorhinal cortex, hippocampus and postsubiculum, the reset of phase effectively replicates context-dependent firing by entorhinal and hippocampal neurons during performance of a continuous spatial alternation task, a delayed spatial alternation task with running in a wheel during the delay period, and a hairpin maze task. PMID:19021258
Neuron-Type-Specific Utility in a Brain-Machine Interface: a Pilot Study.
Garcia-Garcia, Martha G; Bergquist, Austin J; Vargas-Perez, Hector; Nagai, Mary K; Zariffa, Jose; Marquez-Chin, Cesar; Popovic, Milos R
2017-11-01
Firing rates of single cortical neurons can be volitionally modulated through biofeedback (i.e. operant conditioning), and this information can be transformed to control external devices (i.e. brain-machine interfaces; BMIs). However, not all neurons respond to operant conditioning in BMI implementation. Establishing criteria that predict neuron utility will assist translation of BMI research to clinical applications. Single cortical neurons (n=7) were recorded extracellularly from primary motor cortex of a Long-Evans rat. Recordings were incorporated into a BMI involving up-regulation of firing rate to control the brightness of a light-emitting-diode and subsequent reward. Neurons were classified as 'fast-spiking', 'bursting' or 'regular-spiking' according to waveform-width and intrinsic firing patterns. Fast-spiking and bursting neurons were found to up-regulate firing rate by a factor of 2.43±1.16, demonstrating high utility, while regular-spiking neurons decreased firing rates on average by a factor of 0.73±0.23, demonstrating low utility. The ability to select neurons with high utility will be important to minimize training times and maximize information yield in future clinical BMI applications. The highly contrasting utility observed between fast-spiking and bursting neurons versus regular-spiking neurons allows for the hypothesis to be advanced that intrinsic electrophysiological properties may be useful criteria that predict neuron utility in BMI implementation.
Stress and Sucrose Intake Modulate Neuronal Activity in the Anterior Hypothalamic Area in Rats
Mitra, Arojit; Guèvremont, Geneviève; Timofeeva, Elena
2016-01-01
The anterior hypothalamic area (AHA) is an important integrative relay structure for a variety of autonomic, endocrine, and behavioral responses including feeding behavior and response to stress. However, changes in the activity of the AHA neurons during stress and feeding in freely moving rats are not clear. The present study investigated the firing rate and burst activity of neurons in the central nucleus of the AHA (cAHA) during sucrose intake in non-stressful conditions and after acute stress in freely behaving rats. Rats were implanted with micro-electrodes into the cAHA, and extracellular multi-unit activity was recorded during 1-h access to 10% sucrose in non-stressful conditions or after acute foot shock stress. Acute stress significantly reduced sucrose intake, total sucrose lick number, and lick frequency in licking clusters, and increased inter-lick intervals. At the cluster start (CS) of sucrose licking, the cAHA neurons increased (CS-excited, 20% of the recorded neurons), decreased (CS-inhibited, 42% of the neurons) or did not change (CS-nonresponsive, 38% of the neurons) their firing rate. Stress resulted in a significant increase in the firing rate of the CS-inhibited neurons by decreasing inter-spike intervals within the burst firing of these neurons. This increase in the stress-induced firing rate of the CS-inhibited neurons was accompanied by a disruption of the correlation between the firing rate of CS-inhibited and CS-nonresponsive neurons that was observed in non-stressful conditions. Stress did not affect the firing rate of the CS-excited and CS-nonresponsive neurons. However, stress changed the pattern of burst firing of the CS-excited and CS-nonresponsive neurons by decreasing and increasing the burst number in the CS-excited and CS-nonresponsive neurons, respectively. These results suggest that the cAHA neurons integrate the signals related to stress and intake of palatable food and play a role in the stress- and eating-related circuitry. PMID:27243579
Stress and Sucrose Intake Modulate Neuronal Activity in the Anterior Hypothalamic Area in Rats.
Mitra, Arojit; Guèvremont, Geneviève; Timofeeva, Elena
2016-01-01
The anterior hypothalamic area (AHA) is an important integrative relay structure for a variety of autonomic, endocrine, and behavioral responses including feeding behavior and response to stress. However, changes in the activity of the AHA neurons during stress and feeding in freely moving rats are not clear. The present study investigated the firing rate and burst activity of neurons in the central nucleus of the AHA (cAHA) during sucrose intake in non-stressful conditions and after acute stress in freely behaving rats. Rats were implanted with micro-electrodes into the cAHA, and extracellular multi-unit activity was recorded during 1-h access to 10% sucrose in non-stressful conditions or after acute foot shock stress. Acute stress significantly reduced sucrose intake, total sucrose lick number, and lick frequency in licking clusters, and increased inter-lick intervals. At the cluster start (CS) of sucrose licking, the cAHA neurons increased (CS-excited, 20% of the recorded neurons), decreased (CS-inhibited, 42% of the neurons) or did not change (CS-nonresponsive, 38% of the neurons) their firing rate. Stress resulted in a significant increase in the firing rate of the CS-inhibited neurons by decreasing inter-spike intervals within the burst firing of these neurons. This increase in the stress-induced firing rate of the CS-inhibited neurons was accompanied by a disruption of the correlation between the firing rate of CS-inhibited and CS-nonresponsive neurons that was observed in non-stressful conditions. Stress did not affect the firing rate of the CS-excited and CS-nonresponsive neurons. However, stress changed the pattern of burst firing of the CS-excited and CS-nonresponsive neurons by decreasing and increasing the burst number in the CS-excited and CS-nonresponsive neurons, respectively. These results suggest that the cAHA neurons integrate the signals related to stress and intake of palatable food and play a role in the stress- and eating-related circuitry.
Cortical firing and sleep homeostasis.
Vyazovskiy, Vladyslav V; Olcese, Umberto; Lazimy, Yaniv M; Faraguna, Ugo; Esser, Steve K; Williams, Justin C; Cirelli, Chiara; Tononi, Giulio
2009-09-24
The need to sleep grows with the duration of wakefulness and dissipates with time spent asleep, a process called sleep homeostasis. What are the consequences of staying awake on brain cells, and why is sleep needed? Surprisingly, we do not know whether the firing of cortical neurons is affected by how long an animal has been awake or asleep. Here, we found that after sustained wakefulness cortical neurons fire at higher frequencies in all behavioral states. During early NREM sleep after sustained wakefulness, periods of population activity (ON) are short, frequent, and associated with synchronous firing, while periods of neuronal silence are long and frequent. After sustained sleep, firing rates and synchrony decrease, while the duration of ON periods increases. Changes in firing patterns in NREM sleep correlate with changes in slow-wave activity, a marker of sleep homeostasis. Thus, the systematic increase of firing during wakefulness is counterbalanced by staying asleep.
Insel, Nathan; Barnes, Carol A.
2015-01-01
The medial prefrontal cortex is thought to be important for guiding behavior according to an animal's expectations. Efforts to decode the region have focused not only on the question of what information it computes, but also how distinct circuit components become engaged during behavior. We find that the activity of regular-firing, putative projection neurons contains rich information about behavioral context and firing fields cluster around reward sites, while activity among putative inhibitory and fast-spiking neurons is most associated with movement and accompanying sensory stimulation. These dissociations were observed even between adjacent neurons with apparently reciprocal, inhibitory–excitatory connections. A smaller population of projection neurons with burst-firing patterns did not show clustered firing fields around rewards; these neurons, although heterogeneous, were generally less selective for behavioral context than regular-firing cells. The data suggest a network that tracks an animal's behavioral situation while, at the same time, regulating excitation levels to emphasize high valued positions. In this scenario, the function of fast-spiking inhibitory neurons is to constrain network output relative to incoming sensory flow. This scheme could serve as a bridge between abstract sensorimotor information and single-dimensional codes for value, providing a neural framework to generate expectations from behavioral state. PMID:24700585
Cortical pyramidal cells as non-linear oscillators: experiment and spike-generation theory.
Brumberg, Joshua C; Gutkin, Boris S
2007-09-26
Cortical neurons are capable of generating trains of action potentials in response to current injections. These discharges can take different forms, e.g., repetitive firing that adapts during the period of current injection or bursting behaviors. We have used a combined experimental and computational approach to characterize the dynamics leading to action potential responses in single neurons. Specifically we investigated the origin of complex firing patterns in response to sinusoidal current injections. Using a reduced model, the theta-neuron, alongside recordings from cortical pyramidal cells we show that both real and simulated neurons show phase-locking to sine wave stimuli up to a critical frequency, above which period skipping and 1-to-x phase-locking occurs. The locking behavior follows a complex "devil's staircase" phenomena, where locked modes are interleaved with irregular firing. We further show that the critical frequency depends on the time scale of spike generation and on the level of spike frequency adaptation. These results suggest that phase-locking of neuronal responses to complex input patterns can be explained by basic properties of the spike-generating machinery.
Anti-correlated cortical networks arise from spontaneous neuronal dynamics at slow timescales.
Kodama, Nathan X; Feng, Tianyi; Ullett, James J; Chiel, Hillel J; Sivakumar, Siddharth S; Galán, Roberto F
2018-01-12
In the highly interconnected architectures of the cerebral cortex, recurrent intracortical loops disproportionately outnumber thalamo-cortical inputs. These networks are also capable of generating neuronal activity without feedforward sensory drive. It is unknown, however, what spatiotemporal patterns may be solely attributed to intrinsic connections of the local cortical network. Using high-density microelectrode arrays, here we show that in the isolated, primary somatosensory cortex of mice, neuronal firing fluctuates on timescales from milliseconds to tens of seconds. Slower firing fluctuations reveal two spatially distinct neuronal ensembles, which correspond to superficial and deeper layers. These ensembles are anti-correlated: when one fires more, the other fires less and vice versa. This interplay is clearest at timescales of several seconds and is therefore consistent with shifts between active sensing and anticipatory behavioral states in mice.
Effects of ZD7288 on firing pattern of thermosensitive neurons isolated from hypothalamus.
Cai, Chunqing; Meng, Xiaojing; He, Junchu; Wu, Hangyu; Zou, Fei
2012-01-11
The role of the hyperpolarization-activated current (Ih) mediated by HCN channels in temperature sensing by the hypothalamus was addressed. In warm-sensitive neurons (WSNs), exposure to ZD7288, an inhibitor of Ih mediated by hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, decreased their action potential amplitudes and frequencies significantly. By contrast, ZD7288 had little or no effect on temperature-insensitive neurons (TINs). Exposure of WSNs to ZD7288 led to a significant increase in the duration of the inter-spike interval and a reduction of Ih irreversibly. These results suggest that ZD7288 have the contrasting effects on the firing patterns of WSNs versus TINs, which implies HCN channels play a central role in temperature sensing by hypothalamic neurons. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Neuronal activity in the globus pallidus internus in patients with tics.
Zhuang, P; Hallett, M; Zhang, X; Li, J; Zhang, Y; Li, Y
2009-10-01
To explore the role of neuronal activity in the globus pallidus internus (GPi) in the generation of tic movements. 8 patients with Tourette's syndrome with medically intractable tics who underwent a unilateral pallidotomy for severe tics were studied. They ranged in age from 17 to 24 years; disease duration was 7-19 years. Microelectrode recording was performed in the GPi. The electromyogram (EMG) was simultaneously recorded in muscle groups appropriate for the patient's tics. The relationship between neuronal firing pattern and the EMG was studied. 232 neurons were recorded during tics from eight trajectories. Of these neurons, in addition to decreased neuronal firing rate and irregular firing pattern, 105 (45%) were tic related showing either a burst of activity or a pause in ongoing tonic activity. They could be synchronous (n = 75), earlier than EMG onset (n = 27) or following EMG onset (n = 3). The GPi neuronal bursts preceded EMG onset with decreased (n = 6) or increased activity (n = 21). The initial change in neural activity occurred about 50 ms to 2 s before the EMG onset. Although the data are descriptive and preliminary, the tic related neuronal activity observed in GPi appears to indicate that the basal ganglia motor circuit is involved in tic movements. The early neuronal activity seen in GPi may reflect premonitory sensations that precede a tic.
Jang, Jin Young; Jang, Miae; Kim, Shin Hye; Um, Ki Bum; Kang, Yun Kyung; Kim, Hyun Jin; Chung, Sungkwon; Park, Myoung Kyu
2011-03-01
Dopamine (DA) receptors generate many cellular signals and play various roles in locomotion, motivation, hormone production, and drug abuse. According to the location and expression types of the receptors in the brain, DA signals act in either stimulatory or inhibitory manners. Although DA autoreceptors in the substantia nigra pars compacta are known to regulate firing activity, the exact expression patterns and roles of DA autoreceptor types on the firing activity are highly debated. Therefore, we performed individual correlation studies between firing activity and receptor expression patterns using acutely isolated rat substantia nigra pars compacta DA neurons. When we performed single-cell RT-PCR experiments, D(1), D(2)S, D(2)L, D(3), and D(5) receptor mRNA were heterogeneously expressed in the order of D(2)L > D(2)S > D(3) > D(5) > D(1). Stimulation of D(2) receptors with quinpirole suppressed spontaneous firing similarly among all neurons expressing mRNA solely for D(2)S, D(2)L, or D(3) receptors. However, quinpirole most strongly suppressed spontaneous firing in the neurons expressing mRNA for both D(2) and D(3) receptors. These data suggest that D(2) S, D(2)L, and D(3) receptors are able to equally suppress firing activity, but that D(2) and D(3) receptors synergistically suppress firing. This diversity in DA autoreceptors could explain the various actions of DA in the brain. © 2011 The Authors. Journal of Neurochemistry © 2011 International Society for Neurochemistry.
Population rate dynamics and multineuron firing patterns in sensory cortex
Okun, Michael; Yger, Pierre; Marguet, Stephan; Gerard-Mercier, Florian; Benucci, Andrea; Katzner, Steffen; Busse, Laura; Carandini, Matteo; Harris, Kenneth D.
2012-01-01
Cortical circuits encode sensory stimuli through the firing of neuronal ensembles, and also produce spontaneous population patterns in the absence of sensory drive. This population activity is often characterized experimentally by the distribution of multineuron “words” (binary firing vectors), and a match between spontaneous and evoked word distributions has been suggested to reflect learning of a probabilistic model of the sensory world. We analyzed multineuron word distributions in sensory cortex of anesthetized rats and cats, and found that they are dominated by fluctuations in population firing rate rather than precise interactions between individual units. Furthermore, cortical word distributions change when brain state shifts, and similar behavior is seen in simulated networks with fixed, random connectivity. Our results suggest that similarity or dissimilarity in multineuron word distributions could primarily reflect similarity or dissimilarity in population firing rate dynamics, and not necessarily the precise interactions between neurons that would indicate learning of sensory features. PMID:23197704
Phasic spike patterning in rat supraoptic neurones in vivo and in vitro
Sabatier, Nancy; Brown, Colin H; Ludwig, Mike; Leng, Gareth
2004-01-01
In vivo, most vasopressin cells of the hypothalamic supraoptic nucleus fire action potentials in a ‘phasic’ pattern when the systemic osmotic pressure is elevated, while most oxytocin cells fire continuously. The phasic firing pattern is believed to arise as a consequence of intrinsic activity-dependent changes in membrane potential, and these have been extensively studied in vitro. Here we analysed the discharge patterning of supraoptic nucleus neurones in vivo, to infer the characteristics of the post-spike sequence of hyperpolarization and depolarization from the observed spike patterning. We then compared patterning in phasic cells in vivo and in vitro, and we found systematic differences in the interspike interval distributions, and in other statistical parameters that characterized activity patterns within bursts. Analysis of hazard functions (probability of spike initiation as a function of time since the preceding spike) revealed that phasic firing in vitro appears consistent with a regenerative process arising from a relatively slow, late depolarizing afterpotential that approaches or exceeds spike threshold. By contrast, in vivo activity appears to be dominated by stochastic rather than deterministic mechanisms, and appears consistent with a relatively early and fast depolarizing afterpotential that modulates the probability that random synaptic input exceeds spike threshold. Despite superficial similarities in the phasic firing patterns observed in vivo and in vitro, there are thus fundamental differences in the underlying mechanisms. PMID:15146047
Sousa, Mafalda; Szucs, Peter; Lima, Deolinda; Aguiar, Paulo
2014-04-01
Despite the importance and significant clinical impact of understanding information processing in the nociceptive system, the functional properties of neurons in many parts of this system are still unknown. In this work we performed whole cell patch-clamp recording in rat brain stem blocks to characterize the electrophysiological properties of neurons in the dorsal reticular nucleus (DRt), a region known to be involved in pronociceptive modulation. We also compared properties of DRt neurons with those in the adjacent parvicellular reticular nucleus and in neighboring regions outside the reticular formation. We found that neurons in the DRt and parvicellular reticular nucleus had similar electrophysiological properties and exhibited mostly toniclike firing patterns, whereas neurons outside the reticular formation showed a larger diversity of firing patterns. Interestingly, more than one-half of the neurons also showed spontaneous activity. While the general view of the reticular formation, being a loosely associated mesh of groups of neurons with diverse function, and earlier reports suggests more electrophysiological heterogeneity, we showed that this is indeed not the case. Our results indicate that functional difference of neurons in the reticular formation may mostly be determined by their connectivity profiles and not by their intrinsic electrophysiological properties. The dominance of tonic neurons in the DRt supports previous conclusions that these neurons encode stimulus intensity through their firing frequency, while the high prevalence of spontaneous activity most likely shapes nociceptive modulation by this brain stem region.
Differential roles of ventral pallidum subregions during cocaine self-administration behaviors
Root, David H.; Ma, Sisi; Barker, David J.; Megehee, Laura; Striano, Brendan M.; Ralston, Carla M.; Fabbricatore, Anthony T.; West, Mark O.
2012-01-01
The ventral pallidum (VP) is necessary for drug-seeking behavior. VP contains ventromedial (VPvm) and dorsolateral (VPdl) subregions which receive projections from the nucleus accumbens shell and core, respectively. To date, no study has investigated the behavioral functions of the VPdl and VPvm subregions. To address this issue, we investigated whether changes in firing rate (FR) differed between VP subregions during four events: approaching toward, responding on, or retreating away from a cocaine-reinforced operandum, and a cocaine-associated cue. Baseline FR and waveform characteristics did not differ between subregions. VPdl neurons exhibited a greater change in FR compared to VPvm neurons during approaches toward, as well as responses on, the cocaine-reinforced operandum. VPdl neurons were more likely to exhibit a similar change in FR (direction and magnitude) during approach and response than VPvm neurons. In contrast, VPvm firing patterns were heterogeneous, changing FRs during approach or response alone, or both. VP neurons did not discriminate cued behaviors from uncued behaviors. No differences were found between subregions during the retreat and no VP neurons exhibited patterned changes in FR in response to the cocaine-associated cue. The stronger, sustained FR changes of VPdl neurons during approach and response may implicate VPdl in the processing of drug-seeking and drug-taking behavior via projections to subthalamic nucleus and substantia nigra pars reticulata. In contrast, heterogeneous firing patterns of VPvm neurons may implicate VPvm in facilitating mesocortical structures with information related to the sequence of behaviors predicting cocaine self-infusions via projections to mediodorsal thalamus and ventral tegmental area. PMID:22806483
Dorsal–Ventral Gradient for Neuronal Plasticity in the Embryonic Spinal Cord
Pineda, Ricardo H.; Ribera, Angeles B.
2008-01-01
Within the developing Xenopus spinal cord, voltage-gated potassium (Kv) channel genes display different expression patterns, many of which occur in opposing dorsal–ventral gradients. Regional differences in Kv gene expression would predict different patterns of potassium current (IKv) regulation. However, during the first 24 h of postmitotic differentiation, all primary spinal neurons undergo a temporally coordinated upregulation of IKv density that shortens the duration of the action potential. Here, we tested whether spinal neurons demonstrate regional differences in IKv regulation subsequent to action potential maturation. We show that two types of neurons, I and II, can be identified in culture on the basis of biophysical and pharmacological properties of IKv and different firing patterns. Chronic increases in extracellular potassium, a signature of high neuronal activity, do not alter excitability properties of either neuron type. However, elevating extracellular potassium acutely after the period of action potential maturation leads to different changes in membrane properties of the two types of neurons. IKv of type I neurons gains sensitivity to the blocker XE991, whereas type II neurons increase IKv density and fire fewer action potentials. Moreover, by recording from neurons in vivo, we found that primary spinal neurons can be identified as either type I or type II. Type I neurons predominate in dorsal regions, whereas type II neurons localize to ventral regions. The findings reveal a dorsal–ventral gradient for IKv regulation and a novel form of neuronal plasticity in spinal cord neurons. PMID:18385340
Ascarrunz, F G; Kisley, M A; Flach, K A; Hamilton, R W; MacGregor, R J
1995-07-01
This paper applies a general mathematical system for characterizing and scaling functional connectivity and information flow across the diffuse (EC) and discrete (DG) input junctions to the CA3 hippocampus. Both gross connectivity and coordinated multiunit informational firing patterns are quantitatively characterized in terms of 32 defining parameters interrelated by 17 equations, and then scaled down according to rules for uniformly proportional scaling and for partial representation. The diffuse EC-CA3 junction is shown to be uniformly scalable with realistic representation of both essential spatiotemporal cooperativity and coordinated firing patterns down to populations of a few hundred neurons. Scaling of the discrete DG-CA3 junction can be effected with a two-step process, which necessarily deviates from uniform proportionality but nonetheless produces a valuable and readily interpretable reduced model, also utilizing a few hundred neurons in the receiving population. Partial representation produces a reduced model of only a portion of the full network where each model neuron corresponds directly to a biological neuron. The mathematical analysis illustrated here shows that although omissions and distortions are inescapable in such an application, satisfactorily complete and accurate models the size of pattern modules are possible. Finally, the mathematical characterization of these junctions generates a theory which sees the DG as a definer of the fine structure of embedded traces in the hippocampus and entire coordinated patterns of sequences of 14-cell links in CA3 as triggered by the firing of sequences of individual neurons in DG.
Caspari, Franziska; Baumann, Veronika J.; Garcia-Pino, Elisabet; Koch, Ursula
2015-01-01
The ventral nucleus of the lateral lemniscus (VNLL) provides a major inhibitory projection to the inferior colliculus (IC). Neurons in the VNLL respond with various firing patterns and different temporal precision to acoustic stimulation. The present study investigates the underlying intrinsic and synaptic properties of various cell types in different regions of the VNLL, using in vitro electrophysiological recordings from acute brain slices of mice and immunohistochemistry. We show that the biophysical membrane properties and excitatory input characteristics differed between dorsal and ventral VNLL neurons. Neurons in the ventral VNLL displayed an onset-type firing pattern and little hyperpolarization-activated current (Ih). Stimulation of lemniscal inputs evoked a large all-or-none excitatory response similar to Calyx of Held synapses in neurons in the lateral part of the ventral VNLL. Neurons that were located within the fiber tract of the lateral lemniscus, received several and weak excitatory input fibers. In the dorsal VNLL onset-type and sustained firing neurons were intermingled. These neurons showed large Ih and were strongly immunopositive for the hyperpolarization-activated cyclic nucleotide-gated channel 1 (HCN1) subunit. Both neuron types received several excitatory inputs that were weaker and slower compared to ventrolateral VNLL neurons. Using a mouse model that expresses channelrhodopsin under the promotor of the vesicular GABA transporter (VGAT) suggests that dorsal and ventral neurons were inhibitory since they were all depolarized by light stimulation. The diverse membrane and input properties in dorsal and ventral VNLL neurons suggest differential roles of these neurons for sound processing. PMID:26635535
Dehydration-induced modulation of κ-opioid inhibition of vasopressin neurone activity
Scott, Victoria; Bishop, Valerie R; Leng, Gareth; Brown, Colin H
2009-01-01
Dehydration increases vasopressin (antidiuretic hormone) secretion from the posterior pituitary gland to reduce water loss in the urine. Vasopressin secretion is determined by action potential firing in vasopressin neurones, which can exhibit continuous, phasic (alternating periods of activity and silence), or irregular activity. Autocrine κ-opioid inhibition contributes to the generation of activity patterning of vasopressin neurones under basal conditions and so we used in vivo extracellular single unit recording to test the hypothesis that changes in autocrine κ-opioid inhibition drive changes in activity patterning of vasopressin neurones during dehydration. Dehydration increased the firing rate of rat vasopressin neurones displaying continuous activity (from 7.1 ± 0.5 to 9.0 ± 0.6 spikes s−1) and phasic activity (from 4.2 ± 0.7 to 7.8 ± 0.9 spikes s−1), but not those displaying irregular activity. The dehydration-induced increase in phasic activity was via an increase in intraburst firing rate. The selective κ-opioid receptor antagonist nor-binaltorphimine increased the firing rate of phasic neurones in non-dehydrated rats (from 3.4 ± 0.8 to 5.3 ± 0.6 spikes s−1) and dehydrated rats (from 6.4 ± 0.5 to 9.1 ± 1.2 spikes s−1), indicating that κ-opioid feedback inhibition of phasic bursts is maintained during dehydration. In a separate series of experiments, prodynorphin mRNA expression was increased in vasopressin neurones of hyperosmotic rats, compared to hypo-osmotic rats. Hence, it appears that dynorphin expression in vasopressin neurones undergoes dynamic changes in proportion to the required secretion of vasopressin so that, even under stimulated conditions, autocrine feedback inhibition of vasopressin neurones prevents over-excitation. PMID:19822541
A simplified memory network model based on pattern formations
NASA Astrophysics Data System (ADS)
Xu, Kesheng; Zhang, Xiyun; Wang, Chaoqing; Liu, Zonghua
2014-12-01
Many experiments have evidenced the transition with different time scales from short-term memory (STM) to long-term memory (LTM) in mammalian brains, while its theoretical understanding is still under debate. To understand its underlying mechanism, it has recently been shown that it is possible to have a long-period rhythmic synchronous firing in a scale-free network, provided the existence of both the high-degree hubs and the loops formed by low-degree nodes. We here present a simplified memory network model to show that the self-sustained synchronous firing can be observed even without these two necessary conditions. This simplified network consists of two loops of coupled excitable neurons with different synaptic conductance and with one node being the sensory neuron to receive an external stimulus signal. This model can be further used to show how the diversity of firing patterns can be selectively formed by varying the signal frequency, duration of the stimulus and network topology, which corresponds to the patterns of STM and LTM with different time scales. A theoretical analysis is presented to explain the underlying mechanism of firing patterns.
Athanassiadis, T; Westberg, K-G; Olsson, K A; Kolta, A
2005-12-01
A population of neurons in the trigeminal principal sensory nucleus (NVsnpr) fire rhythmically during fictive mastication induced in the in vivo rabbit. To elucidate whether these neurons form part of the central pattern generator (CPG) for mastication, we performed intracellular recordings in brainstem slices taken from young rats. Two cell types were defined, nonbursting (63%) and bursting (37%). In response to membrane depolarization, bursting cells, which dominated in the dorsal part of the NVsnpr, fired an initial burst followed by single spikes or recurring bursts. Non-bursting neurons, scattered throughout the nucleus, fired single action potentials. Microstimulation applied to the trigeminal motor nucleus (NVmt), the reticular border zone surrounding the NVmt, the parvocellular reticular formation or the nucleus reticularis pontis caudalis (NPontc) elicited a postsynaptic potential in 81% of the neurons tested for synaptic inputs. Responses obtained were predominately excitatory and sensitive to glutamatergic antagonists DNQX and/or APV. Some inhibitory and biphasic responses were also evoked. Bicuculline methiodide or strychnine blocked the IPSPs indicating that they were mediated by GABA(A) or glycinergic receptors. About one-third of the stimulations activated both types of neurons antidromically, mostly from the masseteric motoneuron pool of NVmt and dorsal part of NPontc. In conclusion, our new findings show that some neurons in the dorsal NVsnpr display both firing properties and axonal connections which support the hypothesis that they may participate in masticatory pattern generation. Thus, the present data provide an extended basis for further studies on the organization of the masticatory CPG network.
Tuckwell, Henry C
2006-01-01
The circuitry of cortical networks involves interacting populations of excitatory (E) and inhibitory (I) neurons whose relationships are now known to a large extent. Inputs to E- and I-cells may have their origins in remote or local cortical areas. We consider a rudimentary model involving E- and I-cells. One of our goals is to test an analytic approach to finding firing rates in neural networks without using a diffusion approximation and to this end we consider in detail networks of excitatory neurons with leaky integrate-and-fire (LIF) dynamics. A simple measure of synchronization, denoted by S(q), where q is between 0 and 100 is introduced. Fully connected E-networks have a large tendency to become dominated by synchronously firing groups of cells, except when inputs are relatively weak. We observed random or asynchronous firing in such networks with diverse sets of parameter values. When such firing patterns were found, the analytical approach was often able to accurately predict average neuronal firing rates. We also considered several properties of E-E networks, distinguishing several kinds of firing pattern. Included were those with silences before or after periods of intense activity or with periodic synchronization. We investigated the occurrence of synchronized firing with respect to changes in the internal excitatory postsynaptic potential (EPSP) magnitude in a network of 100 neurons with fixed values of the remaining parameters. When the internal EPSP size was less than a certain value, synchronization was absent. The amount of synchronization then increased slowly as the EPSP amplitude increased until at a particular EPSP size the amount of synchronization abruptly increased, with S(5) attaining the maximum value of 100%. We also found network frequency transfer characteristics for various network sizes and found a linear dependence of firing frequency over wide ranges of the external afferent frequency, with non-linear effects at lower input frequencies. The theory may also be applied to sparsely connected networks, whose firing behaviour was found to change abruptly as the probability of a connection passed through a critical value. The analytical method was also found to be useful for a feed-forward excitatory network and a network of excitatory and inhibitory neurons.
Criticality in Neuronal Networks
NASA Astrophysics Data System (ADS)
Friedman, Nir; Ito, Shinya; Brinkman, Braden A. W.; Shimono, Masanori; Deville, R. E. Lee; Beggs, John M.; Dahmen, Karin A.; Butler, Tom C.
2012-02-01
In recent years, experiments detecting the electrical firing patterns in slices of in vitro brain tissue have been analyzed to suggest the presence of scale invariance and possibly criticality in the brain. Much of the work done however has been limited in two ways: 1) the data collected is from local field potentials that do not represent the firing of individual neurons; 2) the analysis has been primarily limited to histograms. In our work we examine data based on the firing of individual neurons (spike data), and greatly extend the analysis by considering shape collapse and exponents. Our results strongly suggest that the brain operates near a tuned critical point of a highly distinctive universality class.
Symmetry breaking in two interacting populations of quadratic integrate-and-fire neurons.
Ratas, Irmantas; Pyragas, Kestutis
2017-10-01
We analyze the dynamics of two coupled identical populations of quadratic integrate-and-fire neurons, which represent the canonical model for class I neurons near the spiking threshold. The populations are heterogeneous; they include both inherently spiking and excitable neurons. The coupling within and between the populations is global via synapses that take into account the finite width of synaptic pulses. Using a recently developed reduction method based on the Lorentzian ansatz, we derive a closed system of equations for the neuron's firing rates and the mean membrane potentials in both populations. The reduced equations are exact in the infinite-size limit. The bifurcation analysis of the equations reveals a rich variety of nonsymmetric patterns, including a splay state, antiphase periodic oscillations, chimera-like states, and chaotic oscillations as well as bistabilities between various states. The validity of the reduced equations is confirmed by direct numerical simulations of the finite-size networks.
Symmetry breaking in two interacting populations of quadratic integrate-and-fire neurons
NASA Astrophysics Data System (ADS)
Ratas, Irmantas; Pyragas, Kestutis
2017-10-01
We analyze the dynamics of two coupled identical populations of quadratic integrate-and-fire neurons, which represent the canonical model for class I neurons near the spiking threshold. The populations are heterogeneous; they include both inherently spiking and excitable neurons. The coupling within and between the populations is global via synapses that take into account the finite width of synaptic pulses. Using a recently developed reduction method based on the Lorentzian ansatz, we derive a closed system of equations for the neuron's firing rates and the mean membrane potentials in both populations. The reduced equations are exact in the infinite-size limit. The bifurcation analysis of the equations reveals a rich variety of nonsymmetric patterns, including a splay state, antiphase periodic oscillations, chimera-like states, and chaotic oscillations as well as bistabilities between various states. The validity of the reduced equations is confirmed by direct numerical simulations of the finite-size networks.
Masoli, Stefano; Rizza, Martina F; Sgritta, Martina; Van Geit, Werner; Schürmann, Felix; D'Angelo, Egidio
2017-01-01
In realistic neuronal modeling, once the ionic channel complement has been defined, the maximum ionic conductance (G i-max ) values need to be tuned in order to match the firing pattern revealed by electrophysiological recordings. Recently, selection/mutation genetic algorithms have been proposed to efficiently and automatically tune these parameters. Nonetheless, since similar firing patterns can be achieved through different combinations of G i-max values, it is not clear how well these algorithms approximate the corresponding properties of real cells. Here we have evaluated the issue by exploiting a unique opportunity offered by the cerebellar granule cell (GrC), which is electrotonically compact and has therefore allowed the direct experimental measurement of ionic currents. Previous models were constructed using empirical tuning of G i-max values to match the original data set. Here, by using repetitive discharge patterns as a template, the optimization procedure yielded models that closely approximated the experimental G i-max values. These models, in addition to repetitive firing, captured additional features, including inward rectification, near-threshold oscillations, and resonance, which were not used as features. Thus, parameter optimization using genetic algorithms provided an efficient modeling strategy for reconstructing the biophysical properties of neurons and for the subsequent reconstruction of large-scale neuronal network models.
Tonic and Phasic Receptor Neurons in the Vertebrate Olfactory Epithelium
Madrid, Rodolfo; Sanhueza, Magdalena; Alvarez, Osvaldo; Bacigalupo, Juan
2003-01-01
Olfactory receptor neurons (ORNs) respond to odorants with characteristic patterns of action potentials that are relevant for odor coding. Prolonged odorant exposures revealed three populations of dissociated toad ORNs, which were mimicked by depolarizing currents: tonic (TN, displaying sustained firing, 49% of 102 cells), phasic (PN, exhibiting brief action potential trains, 36%) and intermediate neurons (IN, generating trains longer than PN, 15%). We studied the biophysical properties underlying the differences between TNs and PNs, the most extreme cases among ORNs. TNs and PNs possessed similar membrane capacitances (∼4 pF), but they differed in resting potential (−82 versus −64 mV), input resistance (4.2 versus 2.9 GΩ) and unspecific current, Iu (TNs: 0 < Iu ≤ 1 pA/pF; and PNs: Iu > 1 pA/pF). Firing behavior did not correlate with differences in voltage-gated conductances. We developed a mathematical model that accurately simulates tonic and phasic patterns. Whole cell recordings from rat ORNs in fragments (∼4 mm2) of olfactory epithelium showed that such a tissue normally contains tonic and phasic receptor neurons, suggesting that this feature is common across a wide range of vertebrates. Our findings show that the individual passive electrical properties can govern the firing patterns of ORNs. PMID:12770919
Raman, Baranidharan; Joseph, Joby; Tang, Jeff; Stopfer, Mark
2010-01-01
Odorants are represented as spatiotemporal patterns of spikes in neurons of the antennal lobe (AL, insects) and olfactory bulb (OB, vertebrates). These response patterns have been thought to arise primarily from interactions within the AL/OB, an idea supported, in part, by the assumption that olfactory receptor neurons (ORNs) respond to odorants with simple firing patterns. However, activating the AL directly with simple pulses of current evoked responses in AL neurons that were much less diverse, complex, and enduring than responses elicited by odorants. Similarly, models of the AL driven by simplistic inputs generated relatively simple output. How then are dynamic neural codes for odors generated? Consistent with recent results from several other species, our recordings from locust ORNs showed a great diversity of temporal structure. Further, we found that, viewed as a population, many response features of ORNs were remarkably similar to those observed within the AL. Using a set of computational models constrained by our electrophysiological recordings, we found that the temporal heterogeneity of responses of ORNs critically underlies the generation of spatiotemporal odor codes in the AL. A test then performed in vivo confirmed that, given temporally homogeneous input, the AL cannot create diverse spatiotemporal patterns on its own; however, given temporally heterogeneous input, the AL generated realistic firing patterns. Finally, given the temporally structured input provided by ORNs, we clarified several separate, additional contributions of the AL to olfactory information processing. Thus, our results demonstrate the origin and subsequent reformatting of spatiotemporal neural codes for odors. PMID:20147528
Feedback Enhances Feedforward Figure-Ground Segmentation by Changing Firing Mode
Supèr, Hans; Romeo, August
2011-01-01
In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforwardspiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses withthe responses to a homogenous texture. We propose that feedback controlsfigure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons. PMID:21738747
Feedback enhances feedforward figure-ground segmentation by changing firing mode.
Supèr, Hans; Romeo, August
2011-01-01
In the visual cortex, feedback projections are conjectured to be crucial in figure-ground segregation. However, the precise function of feedback herein is unclear. Here we tested a hypothetical model of reentrant feedback. We used a previous developed 2-layered feedforward spiking network that is able to segregate figure from ground and included feedback connections. Our computer model data show that without feedback, neurons respond with regular low-frequency (∼9 Hz) bursting to a figure-ground stimulus. After including feedback the firing pattern changed into a regular (tonic) spiking pattern. In this state, we found an extra enhancement of figure responses and a further suppression of background responses resulting in a stronger figure-ground signal. Such push-pull effect was confirmed by comparing the figure-ground responses with the responses to a homogenous texture. We propose that feedback controls figure-ground segregation by influencing the neural firing patterns of feedforward projecting neurons.
Complexity of VTA DA neural activities in response to PFC transection in nicotine treated rats.
Chen, Ting Y; Zhang, Die; Dragomir, Andrei; Akay, Yasemin M; Akay, Metin
2011-02-27
The dopaminergic (DA) neurons in the ventral tegmental area (VTA) are widely implicated in the addiction and natural reward circuitry of the brain. These neurons project to several areas of the brain, including prefrontal cortex (PFC), nucleus accubens (NAc) and amygdala. The functional coupling between PFC and VTA has been demonstrated, but little is known about how PFC mediates nicotinic modulation in VTA DA neurons. The objectives of this study were to investigate the effect of acute nicotine exposure on the VTA DA neuronal firing and to understand how the disruption of communication from PFC affects the firing patterns of VTA DA neurons. Extracellular single-unit recordings were performed on Sprague-Dawley rats and nicotine was administered after stable recording was established as baseline. In order to test how input from PFC affects the VTA DA neuronal firing, bilateral transections were made immediate caudal to PFC to mechanically delete the interaction between VTA and PFC. The complexity of the recorded neural firing was subsequently assessed using a method based on the Lempel-Ziv estimator. The results were compared with those obtained when computing the entropy of neural firing. Exposure to nicotine triggered a significant increase in VTA DA neurons firing complexity when communication between PFC and VTA was present, while transection obliterated the effect of nicotine. Similar results were obtained when entropy values were estimated. Our findings suggest that PFC plays a vital role in mediating VTA activity. We speculate that increased firing complexity with acute nicotine administration in PFC intact subjects is due to the close functional coupling between PFC and VTA. This hypothesis is supported by the fact that deletion of PFC results in minor alterations of VTA DA neural firing when nicotine is acutely administered.
MacGregor, Duncan J.; Leng, Gareth
2012-01-01
Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing. PMID:23093929
Wallisch, Pascal; Ostojic, Srdjan
2016-01-01
Synaptic plasticity is sensitive to the rate and the timing of presynaptic and postsynaptic action potentials. In experimental protocols inducing plasticity, the imposed spike trains are typically regular and the relative timing between every presynaptic and postsynaptic spike is fixed. This is at odds with firing patterns observed in the cortex of intact animals, where cells fire irregularly and the timing between presynaptic and postsynaptic spikes varies. To investigate synaptic changes elicited by in vivo-like firing, we used numerical simulations and mathematical analysis of synaptic plasticity models. We found that the influence of spike timing on plasticity is weaker than expected from regular stimulation protocols. Moreover, when neurons fire irregularly, synaptic changes induced by precise spike timing can be equivalently induced by a modest firing rate variation. Our findings bridge the gap between existing results on synaptic plasticity and plasticity occurring in vivo, and challenge the dominant role of spike timing in plasticity. SIGNIFICANCE STATEMENT Synaptic plasticity, the change in efficacy of connections between neurons, is thought to underlie learning and memory. The dominant paradigm posits that the precise timing of neural action potentials (APs) is central for plasticity induction. This concept is based on experiments using highly regular and stereotyped patterns of APs, in stark contrast with natural neuronal activity. Using synaptic plasticity models, we investigated how irregular, in vivo-like activity shapes synaptic plasticity. We found that synaptic changes induced by precise timing of APs are much weaker than suggested by regular stimulation protocols, and can be equivalently induced by modest variations of the AP rate alone. Our results call into question the dominant role of precise AP timing for plasticity in natural conditions. PMID:27807166
Short pauses in thalamic deep brain stimulation promote tremor and neuronal bursting.
Swan, Brandon D; Brocker, David T; Hilliard, Justin D; Tatter, Stephen B; Gross, Robert E; Turner, Dennis A; Grill, Warren M
2016-02-01
We conducted intraoperative measurements of tremor during DBS containing short pauses (⩽50 ms) to determine if there is a minimum pause duration that preserves tremor suppression. Nine subjects with ET and thalamic DBS participated during IPG replacement surgery. Patterns of DBS included regular 130 Hz stimulation interrupted by 0, 15, 25 or 50 ms pauses. The same patterns were applied to a model of the thalamic network to quantify effects of pauses on activity of model neurons. All patterns of DBS decreased tremor relative to 'off'. Patterns with pauses generated less tremor reduction than regular high frequency DBS. The model revealed that rhythmic burst-driver inputs to thalamus were masked during DBS, but pauses in stimulation allowed propagation of bursting activity. The mean firing rate of bursting-type model neurons as well as the firing pattern entropy of model neurons were both strongly correlated with tremor power across stimulation conditions. The temporal pattern of stimulation influences the efficacy of thalamic DBS. Pauses in stimulation resulted in decreased tremor suppression indicating that masking of pathological bursting is a mechanism of thalamic DBS for tremor. Pauses in stimulation decreased the efficacy of open-loop DBS for suppression of tremor. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.
2015-01-01
To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT (“face patches”) did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. SIGNIFICANCE STATEMENT We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887
Directed functional connectivity matures with motor learning in a cortical pattern generator.
Day, Nancy F; Terleski, Kyle L; Nykamp, Duane Q; Nick, Teresa A
2013-02-01
Sequential motor skills may be encoded by feedforward networks that consist of groups of neurons that fire in sequence (Abeles 1991; Long et al. 2010). However, there has been no evidence of an anatomic map of activation sequence in motor control circuits, which would be potentially detectable as directed functional connectivity of coactive neuron groups. The proposed pattern generator for birdsong, the HVC (Long and Fee 2008; Vu et al. 1994), contains axons that are preferentially oriented in the rostrocaudal axis (Nottebohm et al. 1982; Stauffer et al. 2012). We used four-tetrode recordings to assess the activity of ensembles of single neurons along the rostrocaudal HVC axis in anesthetized zebra finches. We found an axial, polarized neural network in which sequential activity is directionally organized along the rostrocaudal axis in adult males, who produce a stereotyped song. Principal neurons fired in rostrocaudal order and with interneurons that were rostral to them, suggesting that groups of excitatory neurons fire at the leading edge of travelling waves of inhibition. Consistent with the synchronization of neurons by caudally travelling waves of inhibition, the activity of interneurons was more coherent in the orthogonal mediolateral axis than in the rostrocaudal axis. If directed functional connectivity within the HVC is important for stereotyped, learned song, then it may be lacking in juveniles, which sing a highly variable song. Indeed, we found little evidence for network directionality in juveniles. These data indicate that a functionally directed network within the HVC matures during sensorimotor learning and may underlie vocal patterning.
Directed functional connectivity matures with motor learning in a cortical pattern generator
Day, Nancy F.; Terleski, Kyle L.; Nykamp, Duane Q.
2013-01-01
Sequential motor skills may be encoded by feedforward networks that consist of groups of neurons that fire in sequence (Abeles 1991; Long et al. 2010). However, there has been no evidence of an anatomic map of activation sequence in motor control circuits, which would be potentially detectable as directed functional connectivity of coactive neuron groups. The proposed pattern generator for birdsong, the HVC (Long and Fee 2008; Vu et al. 1994), contains axons that are preferentially oriented in the rostrocaudal axis (Nottebohm et al. 1982; Stauffer et al. 2012). We used four-tetrode recordings to assess the activity of ensembles of single neurons along the rostrocaudal HVC axis in anesthetized zebra finches. We found an axial, polarized neural network in which sequential activity is directionally organized along the rostrocaudal axis in adult males, who produce a stereotyped song. Principal neurons fired in rostrocaudal order and with interneurons that were rostral to them, suggesting that groups of excitatory neurons fire at the leading edge of travelling waves of inhibition. Consistent with the synchronization of neurons by caudally travelling waves of inhibition, the activity of interneurons was more coherent in the orthogonal mediolateral axis than in the rostrocaudal axis. If directed functional connectivity within the HVC is important for stereotyped, learned song, then it may be lacking in juveniles, which sing a highly variable song. Indeed, we found little evidence for network directionality in juveniles. These data indicate that a functionally directed network within the HVC matures during sensorimotor learning and may underlie vocal patterning. PMID:23175804
Sasaki, Kosei; Cropper, Elizabeth C; Weiss, Klaudiusz R; Jing, Jian
2013-01-01
Although electrical coupling is present in many microcircuits, the extent to which it will determine neuronal firing patterns and network activity remains poorly understood. This is particularly true when the coupling is present in a population of heterogeneous, or intrinsically distinct circuit elements. We examine this question in the Aplysia californica feeding motor network in five electrically-coupled identified cells, B64, B4/5, B70, B51 and a newly-identified interneuron B71. These neurons exhibit distinct activity patterns during the radula retraction phase of motor programs. In a subset of motor programs, retraction can be flexibly extended by adding a phase of network activity (hyper-retraction). This is manifested most prominently as an additional burst in the radula closure motoneuron B8. Two neurons that excite B8 (B51 and B71) and one that inhibits it (B70) are active during hyper-retraction. Consistent with their near synchronous firing, B51 and B71 showed one of the strongest coupling ratios in this group of neurons. Nonetheless, by manipulating their activity, we found that B51 preferentially acted as a driver of B64/B71 activity, whereas B71 played a larger role in driving B8 activity. In contrast, B70 was weakly coupled to other neurons and its inhibition of B8 counter-acted the excitatory drive to B8. Finally, the distinct firing patterns of the electrically-coupled neurons were fine-tuned by their intrinsic properties and the largely chemical cross-inhibition between some of them. Thus, the small microcircuit of Aplysia feeding network is advantageous in understanding how a population of electrically-coupled heterogeneous neurons may fulfill specific network functions. PMID:23283325
Continuous attractor network models of grid cell firing based on excitatory–inhibitory interactions
Shipston‐Sharman, Oliver; Solanka, Lukas
2016-01-01
Abstract Neurons in the medial entorhinal cortex encode location through spatial firing fields that have a grid‐like organisation. The challenge of identifying mechanisms for grid firing has been addressed through experimental and theoretical investigations of medial entorhinal circuits. Here, we discuss evidence for continuous attractor network models that account for grid firing by synaptic interactions between excitatory and inhibitory cells. These models assume that grid‐like firing patterns are the result of computation of location from velocity inputs, with additional spatial input required to oppose drift in the attractor state. We focus on properties of continuous attractor networks that are revealed by explicitly considering excitatory and inhibitory neurons, their connectivity and their membrane potential dynamics. Models at this level of detail can account for theta‐nested gamma oscillations as well as grid firing, predict spatial firing of interneurons as well as excitatory cells, show how gamma oscillations can be modulated independently from spatial computations, reveal critical roles for neuronal noise, and demonstrate that only a subset of excitatory cells in a network need have grid‐like firing fields. Evaluating experimental data against predictions from detailed network models will be important for establishing the mechanisms mediating grid firing. PMID:27870120
NASA Astrophysics Data System (ADS)
Yuan, Chunhua; Wang, Jiang; Yi, Guosheng
2017-03-01
Estimation of ion channel parameters is crucial to spike initiation of neurons. The biophysical neuron models have numerous ion channel parameters, but only a few of them play key roles in the firing patterns of the models. So we choose three parameters featuring the adaptation in the Ermentrout neuron model to be estimated. However, the traditional particle swarm optimization (PSO) algorithm is still easy to fall into local optimum and has the premature convergence phenomenon in the study of some problems. In this paper, we propose an improved method that uses a concave function and dynamic logistic chaotic mapping mixed to adjust the inertia weights of the fitness value, effectively improve the global convergence ability of the algorithm. The perfect predicting firing trajectories of the rebuilt model using the estimated parameters prove that only estimating a few important ion channel parameters can establish the model well and the proposed algorithm is effective. Estimations using two classic PSO algorithms are also compared to the improved PSO to verify that the algorithm proposed in this paper can avoid local optimum and quickly converge to the optimal value. The results provide important theoretical foundations for building biologically realistic neuron models.
Mouse Visual Neocortex Supports Multiple Stereotyped Patterns of Microcircuit Activity
Sadovsky, Alexander J.
2014-01-01
Spiking correlations between neocortical neurons provide insight into the underlying synaptic connectivity that defines cortical microcircuitry. Here, using two-photon calcium fluorescence imaging, we observed the simultaneous dynamics of hundreds of neurons in slices of mouse primary visual cortex (V1). Consistent with a balance of excitation and inhibition, V1 dynamics were characterized by a linear scaling between firing rate and circuit size. Using lagged firing correlations between neurons, we generated functional wiring diagrams to evaluate the topological features of V1 microcircuitry. We found that circuit connectivity exhibited both cyclic graph motifs, indicating recurrent wiring, and acyclic graph motifs, indicating feedforward wiring. After overlaying the functional wiring diagrams onto the imaged field of view, we found properties consistent with Rentian scaling: wiring diagrams were topologically efficient because they minimized wiring with a modular architecture. Within single imaged fields of view, V1 contained multiple discrete circuits that were overlapping and highly interdigitated but were still distinct from one another. The majority of neurons that were shared between circuits displayed peri-event spiking activity whose timing was specific to the active circuit, whereas spike times for a smaller percentage of neurons were invariant to circuit identity. These data provide evidence that V1 microcircuitry exhibits balanced dynamics, is efficiently arranged in anatomical space, and is capable of supporting a diversity of multineuron spike firing patterns from overlapping sets of neurons. PMID:24899701
Yger, Pierre; El Boustani, Sami; Destexhe, Alain; Frégnac, Yves
2011-10-01
The relationship between the dynamics of neural networks and their patterns of connectivity is far from clear, despite its importance for understanding functional properties. Here, we have studied sparsely-connected networks of conductance-based integrate-and-fire (IF) neurons with balanced excitatory and inhibitory connections and with finite axonal propagation speed. We focused on the genesis of states with highly irregular spiking activity and synchronous firing patterns at low rates, called slow Synchronous Irregular (SI) states. In such balanced networks, we examined the "macroscopic" properties of the spiking activity, such as ensemble correlations and mean firing rates, for different intracortical connectivity profiles ranging from randomly connected networks to networks with Gaussian-distributed local connectivity. We systematically computed the distance-dependent correlations at the extracellular (spiking) and intracellular (membrane potential) levels between randomly assigned pairs of neurons. The main finding is that such properties, when they are averaged at a macroscopic scale, are invariant with respect to the different connectivity patterns, provided the excitatory-inhibitory balance is the same. In particular, the same correlation structure holds for different connectivity profiles. In addition, we examined the response of such networks to external input, and found that the correlation landscape can be modulated by the mean level of synchrony imposed by the external drive. This modulation was found again to be independent of the external connectivity profile. We conclude that first and second-order "mean-field" statistics of such networks do not depend on the details of the connectivity at a microscopic scale. This study is an encouraging step toward a mean-field description of topological neuronal networks.
Sparse bursts optimize information transmission in a multiplexed neural code.
Naud, Richard; Sprekeler, Henning
2018-06-22
Many cortical neurons combine the information ascending and descending the cortical hierarchy. In the classical view, this information is combined nonlinearly to give rise to a single firing-rate output, which collapses all input streams into one. We analyze the extent to which neurons can simultaneously represent multiple input streams by using a code that distinguishes spike timing patterns at the level of a neural ensemble. Using computational simulations constrained by experimental data, we show that cortical neurons are well suited to generate such multiplexing. Interestingly, this neural code maximizes information for short and sparse bursts, a regime consistent with in vivo recordings. Neurons can also demultiplex this information, using specific connectivity patterns. The anatomy of the adult mammalian cortex suggests that these connectivity patterns are used by the nervous system to maintain sparse bursting and optimal multiplexing. Contrary to firing-rate coding, our findings indicate that the physiology and anatomy of the cortex may be interpreted as optimizing the transmission of multiple independent signals to different targets. Copyright © 2018 the Author(s). Published by PNAS.
Williams, Mark S.; Altwegg‐Boussac, Tristan; Chavez, Mario; Lecas, Sarah; Mahon, Séverine
2016-01-01
Key points Absence seizures are accompanied by spike‐and‐wave discharges in cortical electroencephalograms. These complex paroxysmal activities, affecting the thalamocortical networks, profoundly alter cognitive performances and preclude conscious perception.Here, using a well‐recognized genetic model of absence epilepsy, we investigated in vivo how information processing was impaired in the ictogenic neurons, i.e. the population of cortical neurons responsible for seizure initiation.In between seizures, ictogenic neurons were more prone to generate bursting activity and their firing response to weak depolarizing events was considerably facilitated compared to control neurons.In the course of seizures, information processing became unstable in ictogenic cells, alternating between an increased and a decreased responsiveness to excitatory inputs, depending on the spike and wave patterns.The state‐dependent modulation in the excitability of ictogenic neurons affects their inter‐seizure transfer function and their time‐to‐time responsiveness to incoming inputs during absences. Abstract Epileptic seizures result from aberrant cellular and/or synaptic properties that can alter the capacity of neurons to integrate and relay information. During absence seizures, spike‐and‐wave discharges (SWDs) interfere with incoming sensory inputs and preclude conscious experience. The Genetic Absence Epilepsy Rats from Strasbourg (GAERS), a well‐established animal model of absence epilepsy, allows exploration of the cellular basis of this impaired information processing. Here, by combining in vivo electrocorticographic and intracellular recordings from GAERS and control animals, we investigated how the pro‐ictogenic properties of seizure‐initiating cortical neurons modify their integrative properties and input–output operation during inter‐ictal periods and during the spike (S‐) and wave (W‐) cortical patterns alternating during seizures. In addition to a sustained depolarization and an excessive firing rate in between seizures, ictogenic neurons exhibited a pronounced hyperpolarization‐activated depolarization compared to homotypic control neurons. Firing frequency versus injected current relations indicated an increased sensitivity of GAERS cells to weak excitatory inputs, without modifications in the trial‐to‐trial variability of current‐induced firing. During SWDs, the W‐component resulted in paradoxical effects in ictogenic neurons, associating an increased membrane input resistance with a reduction in the current‐evoked firing responses. Conversely, the collapse of cell membrane resistance during the S‐component was accompanied by an elevated current‐evoked firing relative to W‐sequences, which remained, however, lower compared to inter‐ictal periods. These findings show a dynamic modulation of ictogenic neurons’ intrinsic properties that may alter inter‐seizure cortical function and participate in compromising information processing in cortical networks during absences. PMID:27311433
Crone, Nathan E.; Niebur, Ernst; Franaszczuk, Piotr J.; Hsiao, Steven S.
2009-01-01
Recent studies using electrocorticographic (ECoG) recordings in humans have shown that functional activation of cortex is associated with an increase in power in the high-gamma frequency range (∼60–200 Hz). Here we investigate the neural correlates of this high-gamma activity in local field potential (LFP). Single units and LFP were recorded with microelectrodes from the hand region of macaque SII cortex while vibrotactile stimuli of varying intensities were presented to the hand. We found that high-gamma power in the LFP was strongly correlated with the average firing rate recorded by the microelectrodes, both temporally and on a trial-by-trial basis. In comparison, the correlation between firing rate and low-gamma power (40–80 Hz) was much smaller. In order to explore the potential effects of neuronal firing on ECoG, we developed a model to estimate ECoG power generated by different firing patterns of the underlying cortical population and studied how ECoG power varies with changes in firing rate versus the degree of synchronous firing between neurons in the population. Both an increase in firing rate and neuronal synchrony increased high-gamma power in the simulated ECoG data. However, ECoG high-gamma activity was much more sensitive to increases in neuronal synchrony than firing rate. PMID:18987189
Eugenin, J; Nicholls, J G; Cohen, L B; Muller, K J
2006-01-01
Unfailing respiration depends on neural mechanisms already present in mammals before birth. Experiments were made to determine how inspiratory and expiratory neurons are grouped in the brainstem of fetal mice. A further aim was to assess whether rhythmicity arises from a single pacemaker or is generated by multiple sites in the brainstem. To measure neuronal firing, a fluorescent calcium indicator dye was applied to embryonic central nervous systems isolated from mice. While respiratory commands were monitored electrically from third to fifth cervical ventral roots, activity was measured optically over areas containing groups of respiratory neurones, or single neurones, along the medulla from the facial nucleus to the pre-Bötzinger complex. Large optical signals allowed recordings to be made during individual respiratory cycles. Inspiratory and expiratory neurones were intermingled. A novel finding was that bursts of activity arose in a discrete area intermittently, occurring during some breaths, but failing in others. Raised CO2 partial pressure or lowered pH increased the frequency of respiration; neurons then fired reliably with every cycle. Movies of activity revealed patterns of activation of inspiratory and expiratory neurones during successive respiratory cycles; there was no evidence for waves spreading systematically from region to region. Our results suggest that firing of neurons in immature respiratory circuits is a stochastic process, and that the rhythm does not depend on a single pacemaker. Respiratory circuits in fetal mouse brainstem appear to possess a high safety factor for generating rhythmicity, which may or may not persist as development proceeds.
Hurwitz, I; Neustadter, D; Morton, D W; Chiel, H J; Susswein, A J
1996-04-01
1. B31 and B32 are pattern-initiator neurons in the buccal ganglia of Aplysia. Along with the B61/B62 neurons, B31/B32 are also motor neurons that innervate the 12 buccal muscle via the I2 nerve. This research was aimed at determining the physiological functions of the B31/B32 and B61/B62 neurons, and of the I2 muscle. 2. Stimulating the I2 muscle in the radula rest position produces radula protraction. In addition, in behaving animals lesioning either the muscle or the I2 nerve greatly reduces radula protraction. 3. During buccal motor programs in reduced preparations, B31/B32 and B61/62 fire preceding activity in neuron B4, whose firing indicates the onset of radula retraction. In addition, during both ingestion-like and rejection-like patterns the activity in the I2 nerve is correlated with protraction. 4. B31/B32 fire at frequencies of 15-25 Hz. Neither B31/B32 nor B61/B62 elicit facilitating end-junction potentials (EJPs) and electromyograms (EMGs) in the I2 muscle. EMGs from B31/B32 are smaller than those from B61/B62. B31/B32 and B61/B62 innervate all areas of the muscle approximately uniformly. 5. In behaving animals, EMGs consistent with B31/B32 activity are seen in the I2 muscle during the protraction phase of biting, swallowing, and rejection movements. In addition, the I2 muscle receives inputs that cannot be attributed to either the B31/B32 or B61/B62 neurons, either because the potentials are too large, firing frequencies are too low, or a prominent facilitation is seen. Such potentials are associated with lip movements, and also with radula retraction. 6. EMGs were recorded from the I2 muscle during feeding behavior after a lesion of the I2 nerve. Animals that had severe deficits in protraction showed no activity consistent with B31/B32 or B61/B62, but did show activity during retraction. 7. Our data indicate that the I2 muscle and the B31/B32 motor neurons are essential constituents contributing to protraction movements. Activity in these neurons is associated with radula protraction, which occurs as a component of a number of different feeding movements. The I2 muscle may also contribute to retraction, via activation by other motor neurons.
Amatrudo, Joseph M.; Weaver, Christina M.; Crimins, Johanna L.; Hof, Patrick R.; Rosene, Douglas L.; Luebke, Jennifer I.
2012-01-01
Whole-cell patch-clamp recordings and high-resolution 3D morphometric analyses of layer 3 pyramidal neurons in in vitro slices of monkey primary visual cortex (V1) and dorsolateral granular prefrontal cortex (dlPFC) revealed that neurons in these two brain areas possess highly distinctive structural and functional properties. Area V1 pyramidal neurons are much smaller than dlPFC neurons, with significantly less extensive dendritic arbors and far fewer dendritic spines. Relative to dlPFC neurons, V1 neurons have a significantly higher input resistance, depolarized resting membrane potential and higher action potential (AP) firing rates. Most V1 neurons exhibit both phasic and regular-spiking tonic AP firing patterns, while dlPFC neurons exhibit only tonic firing. Spontaneous postsynaptic currents are lower in amplitude and have faster kinetics in V1 than in dlPFC neurons, but are no different in frequency. Three-dimensional reconstructions of V1 and dlPFC neurons were incorporated into computational models containing Hodgkin-Huxley and AMPA- and GABAA-receptor gated channels. Morphology alone largely accounted for observed passive physiological properties, but led to AP firing rates that differed more than observed empirically, and to synaptic responses that opposed empirical results. Accordingly, modeling predicts that active channel conductances differ between V1 and dlPFC neurons. The unique features of V1 and dlPFC neurons are likely fundamental determinants of area-specific network behavior. The compact electrotonic arbor and increased excitability of V1 neurons support the rapid signal integration required for early processing of visual information. The greater connectivity and dendritic complexity of dlPFC neurons likely support higher level cognitive functions including working memory and planning. PMID:23035077
Irregular synchronous activity in stochastically-coupled networks of integrate-and-fire neurons.
Lin, J K; Pawelzik, K; Ernst, U; Sejnowski, T J
1998-08-01
We investigate the spatial and temporal aspects of firing patterns in a network of integrate-and-fire neurons arranged in a one-dimensional ring topology. The coupling is stochastic and shaped like a Mexican hat with local excitation and lateral inhibition. With perfect precision in the couplings, the attractors of activity in the network occur at every position in the ring. Inhomogeneities in the coupling break the translational invariance of localized attractors and lead to synchronization within highly active as well as weakly active clusters. The interspike interval variability is high, consistent with recent observations of spike time distributions in visual cortex. The robustness of our results is demonstrated with more realistic simulations on a network of McGregor neurons which model conductance changes and after-hyperpolarization potassium currents.
Modulation of the subthalamic nucleus activity by serotonergic agents and fluoxetine administration.
Aristieta, A; Morera-Herreras, T; Ruiz-Ortega, J A; Miguelez, C; Vidaurrazaga, I; Arrue, A; Zumarraga, M; Ugedo, L
2014-05-01
Within the basal ganglia, the subthalamic nucleus (STN) is the only glutamatergic structure and occupies a central position in the indirect pathway. In rat, the STN receives serotonergic input from the dorsal raphe nucleus and expresses serotonergic receptors. This study examined the consequences of serotonergic neurotransmission modulation on STN neuron activity. In vivo single-unit extracellular recordings, HPLC determination, and rotarod and bar test were performed in control, 4-chloro-DL-phenylalanine methyl ester hydrochloride- (pCPA, a serotonin synthesis inhibitor) and chronically fluoxetine-treated rats. The pCPA treatment and the administration of serotonin (5-HT) receptor antagonists increased number of bursting neurons in the STN. The systemic administration of the 5-HT(1A) agonist, 8-OH-DPAT, decreased the firing rate and increased the coefficient of variation of STN neurons in pCPA-treated rats but not in control animals. Additionally, microinjection of 8-OH-DPAT into the STN reduced the firing rate of STN neurons, while microinjection of the 5-HT(2C) agonist, Ro 60-0175, increased the firing rate in both control and fluoxetine-treated animals. Finally, the fluoxetine challenge increased the firing rate of STN neurons in fluoxetine-treated rats and induced catalepsy. Our results indicate that the depletion and the blockage of 5-HT modify STN neuron firing pattern. STN neuron activity is under the control of 5-HT(1A) and 5-HT(2C) receptors located both inside and outside the STN. Finally, fluoxetine increases STN neuron activity in chronically fluoxetine-treated rats, which may explain the role of this nucleus in fluoxetine-induced extrapyramidal side effects.
Synchrony and neural coding in cerebellar circuits
Person, Abigail L.; Raman, Indira M.
2012-01-01
The cerebellum regulates complex movements and is also implicated in cognitive tasks, and cerebellar dysfunction is consequently associated not only with movement disorders, but also with conditions like autism and dyslexia. How information is encoded by specific cerebellar firing patterns remains debated, however. A central question is how the cerebellar cortex transmits its integrated output to the cerebellar nuclei via GABAergic synapses from Purkinje neurons. Possible answers come from accumulating evidence that subsets of Purkinje cells synchronize their firing during behaviors that require the cerebellum. Consistent with models predicting that coherent activity of inhibitory networks has the capacity to dictate firing patterns of target neurons, recent experimental work supports the idea that inhibitory synchrony may regulate the response of cerebellar nuclear cells to Purkinje inputs, owing to the interplay between unusually fast inhibitory synaptic responses and high rates of intrinsic activity. Data from multiple laboratories lead to a working hypothesis that synchronous inhibitory input from Purkinje cells can set the timing and rate of action potentials produced by cerebellar nuclear cells, thereby relaying information out of the cerebellum. If so, then changing spatiotemporal patterns of Purkinje activity would allow different subsets of inhibitory neurons to control cerebellar output at different times. Here we explore the evidence for and against the idea that a synchrony code defines, at least in part, the input–output function between the cerebellar cortex and nuclei. We consider the literature on the existence of simple spike synchrony, convergence of Purkinje neurons onto nuclear neurons, and intrinsic properties of nuclear neurons that contribute to responses to inhibition. Finally, we discuss factors that may disrupt or modulate a synchrony code and describe the potential contributions of inhibitory synchrony to other motor circuits. PMID:23248585
Hippocampal “Time Cells”: Time versus Path Integration
Kraus, Benjamin J.; Robinson, Robert J.; White, John A.; Eichenbaum, Howard; Hasselmo, Michael E.
2014-01-01
SUMMARY Recent studies have reported the existence of hippocampal “time cells,” neurons that fire at particular moments during periods when behavior and location are relatively constant. However, an alternative explanation of apparent time coding is that hippocampal neurons “path integrate” to encode the distance an animal has traveled. Here, we examined hippocampal neuronal firing patterns as rats ran in place on a treadmill, thus “clamping” behavior and location, while we varied the treadmill speed to distinguish time elapsed from distance traveled. Hippocampal neurons were strongly influenced by time and distance, and less so by minor variations in location. Furthermore, the activity of different neurons reflected integration over time and distance to varying extents, with most neurons strongly influenced by both factors and some significantly influenced by only time or distance. Thus, hippocampal neuronal networks captured both the organization of time and distance in a situation where these dimensions dominated an ongoing experience. PMID:23707613
Feng, Li; Motelow, Joshua E; Ma, Chanthia; Biche, William; McCafferty, Cian; Smith, Nicholas; Liu, Mengran; Zhan, Qiong; Jia, Ruonan; Xiao, Bo; Duque, Alvaro; Blumenfeld, Hal
2017-11-22
The thalamus plays diverse roles in cortical-subcortical brain activity patterns. Recent work suggests that focal temporal lobe seizures depress subcortical arousal systems and convert cortical activity into a pattern resembling slow-wave sleep. The potential simultaneous and paradoxical role of the thalamus in both limbic seizure propagation, and in sleep-like cortical rhythms has not been investigated. We recorded neuronal activity from the central lateral (CL), anterior (ANT), and ventral posteromedial (VPM) nuclei of the thalamus in an established female rat model of focal limbic seizures. We found that population firing of neurons in CL decreased during seizures while the cortex exhibited slow waves. In contrast, ANT showed a trend toward increased neuronal firing compatible with polyspike seizure discharges seen in the hippocampus. Meanwhile, VPM exhibited a remarkable increase in sleep spindles during focal seizures. Single-unit juxtacellular recordings from CL demonstrated reduced overall firing rates, but a switch in firing pattern from single spikes to burst firing during seizures. These findings suggest that different thalamic nuclei play very different roles in focal limbic seizures. While limbic nuclei, such as ANT, appear to participate directly in seizure propagation, arousal nuclei, such as CL, may contribute to depressed cortical function, whereas sleep spindles in relay nuclei, such as VPM, may interrupt thalamocortical information flow. These combined effects could be critical for controlling both seizure severity and impairment of consciousness. Further understanding of differential effects of seizures on different thalamocortical networks may lead to improved treatments directly targeting these modes of impaired function. SIGNIFICANCE STATEMENT Temporal lobe epilepsy has a major negative impact on quality of life. Previous work suggests that the thalamus plays a critical role in thalamocortical network modulation and subcortical arousal maintenance, but its precise seizure-associated functions are not known. We recorded neuronal activity in three different thalamic regions and found divergent activity patterns, which may respectively participate in seizure propagation, impaired level of conscious arousal, and altered relay of information to the cortex during focal limbic seizures. These very different activity patterns within the thalamus may help explain why focal temporal lobe seizures often disrupt widespread network function, and can help guide future treatments aimed at restoring normal thalamocortical network activity and cognition. Copyright © 2017 the authors 0270-6474/17/3711441-14$15.00/0.
Feng, Li; Motelow, Joshua E.; Ma, Chanthia; Liu, Mengran; Zhan, Qiong; Jia, Ruonan; Xiao, Bo; Duque, Alvaro
2017-01-01
The thalamus plays diverse roles in cortical-subcortical brain activity patterns. Recent work suggests that focal temporal lobe seizures depress subcortical arousal systems and convert cortical activity into a pattern resembling slow-wave sleep. The potential simultaneous and paradoxical role of the thalamus in both limbic seizure propagation, and in sleep-like cortical rhythms has not been investigated. We recorded neuronal activity from the central lateral (CL), anterior (ANT), and ventral posteromedial (VPM) nuclei of the thalamus in an established female rat model of focal limbic seizures. We found that population firing of neurons in CL decreased during seizures while the cortex exhibited slow waves. In contrast, ANT showed a trend toward increased neuronal firing compatible with polyspike seizure discharges seen in the hippocampus. Meanwhile, VPM exhibited a remarkable increase in sleep spindles during focal seizures. Single-unit juxtacellular recordings from CL demonstrated reduced overall firing rates, but a switch in firing pattern from single spikes to burst firing during seizures. These findings suggest that different thalamic nuclei play very different roles in focal limbic seizures. While limbic nuclei, such as ANT, appear to participate directly in seizure propagation, arousal nuclei, such as CL, may contribute to depressed cortical function, whereas sleep spindles in relay nuclei, such as VPM, may interrupt thalamocortical information flow. These combined effects could be critical for controlling both seizure severity and impairment of consciousness. Further understanding of differential effects of seizures on different thalamocortical networks may lead to improved treatments directly targeting these modes of impaired function. SIGNIFICANCE STATEMENT Temporal lobe epilepsy has a major negative impact on quality of life. Previous work suggests that the thalamus plays a critical role in thalamocortical network modulation and subcortical arousal maintenance, but its precise seizure-associated functions are not known. We recorded neuronal activity in three different thalamic regions and found divergent activity patterns, which may respectively participate in seizure propagation, impaired level of conscious arousal, and altered relay of information to the cortex during focal limbic seizures. These very different activity patterns within the thalamus may help explain why focal temporal lobe seizures often disrupt widespread network function, and can help guide future treatments aimed at restoring normal thalamocortical network activity and cognition. PMID:29066556
Xu, Kesheng; Maidana, Jean P.; Caviedes, Mauricio; Quero, Daniel; Aguirre, Pablo; Orio, Patricio
2017-01-01
In this article, we describe and analyze the chaotic behavior of a conductance-based neuronal bursting model. This is a model with a reduced number of variables, yet it retains biophysical plausibility. Inspired by the activity of cold thermoreceptors, the model contains a persistent Sodium current, a Calcium-activated Potassium current and a hyperpolarization-activated current (Ih) that drive a slow subthreshold oscillation. Driven by this oscillation, a fast subsystem (fast Sodium and Potassium currents) fires action potentials in a periodic fashion. Depending on the parameters, this model can generate a variety of firing patterns that includes bursting, regular tonic and polymodal firing. Here we show that the transitions between different firing patterns are often accompanied by a range of chaotic firing, as suggested by an irregular, non-periodic firing pattern. To confirm this, we measure the maximum Lyapunov exponent of the voltage trajectories, and the Lyapunov exponent and Lempel-Ziv's complexity of the ISI time series. The four-variable slow system (without spiking) also generates chaotic behavior, and bifurcation analysis shows that this is often originated by period doubling cascades. Either with or without spikes, chaos is no longer generated when the Ih is removed from the system. As the model is biologically plausible with biophysically meaningful parameters, we propose it as a useful tool to understand chaotic dynamics in neurons. PMID:28344550
Okada, Ken-ichi; Nakamura, Kae; Kobayashi, Yasushi
2011-01-01
Dopamine, acetylcholine, and serotonin, the main modulators of the central nervous system, have been proposed to play important roles in the execution of movement, control of several forms of attentional behavior, and reinforcement learning. While the response pattern of midbrain dopaminergic neurons and its specific role in reinforcement learning have been revealed, the role of the other neuromodulators remains rather elusive. Here, we review our recent studies using extracellular recording from neurons in the pedunculopontine tegmental nucleus, where many cholinergic neurons exist, and the dorsal raphe nucleus, where many serotonergic neurons exist, while monkeys performed eye movement tasks to obtain different reward values. The firing patterns of these neurons are often tonic throughout the task period, while dopaminergic neurons exhibited a phasic activity pattern to the task event. The different modulation patterns, together with the activity of dopaminergic neurons, reveal dynamic information processing between these different neuromodulator systems. PMID:22013541
Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J
2015-09-30
To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. Copyright © 2015 the authors 0270-6474/15/3513402-17$15.00/0.
Schalow, G
2010-01-01
Coordination Dynamics Therapy (CDT) has been shown to be able to partly repair CNS injury. The repair is based on a movement-based re-learning theory which requires at least three levels of description: the movement or pattern (and anamnesis) level, the collective variable level, and the neuron level. Upon CDT not only the actually performed movement pattern itself is repaired, but the entire dynamics of CNS organization is improved, which is the theoretical basis for (re-) learning transfer. The transfer of learning for repair from jumping on springboard and exercising on a special CDT and recording device to urinary bladder functions is investigated at the neuron level. At the movement or pattern level, the improvement of central nervous system (CNS) functioning in human patients can be seen (or partly measured) by the improvement of the performance of the pattern. At the collective variable level, coordination tendencies can be measured by the so-called 'coordination dynamics' before, during and after treatment. At the neuron level, re-learning can additionally be assessed by surface electromyography (sEMG) as alterations of single motor unit firings and motor programs. But to express the ongoing interaction between the numerous neural, muscular, and metabolic elements involved in perception and action, it is relevant to inquire how the individual afferent and efferent neurons adjust their phase and frequency coordination to other neurons to satisfy learning task requirements. With the single-nerve fibre action potential recording method it was possible to measure that distributed single neurons communicate by phase and frequency coordination. It is shown that this timed firing of neurons is getting impaired upon injury and has to be improved by learning The stability of phase and frequency coordination among afferent and efferent neuron firings can be related to pattern stability. The stability of phase and frequency coordination at the neuron level can therefore be assessed integratively at the (non-invasive) collective variable level by the arrhythmicity of turning (coordination dynamics) when a patient is exercising on a special CDT device. Upon jumping on springboard and exercising on the special CDT device, the intertwined neuronal networks, subserving movements (somatic) and urinary bladder functions (autonomic and somatic) in the sacral spinal cord, are synchronously activated and entrained to give rise to learning transfer from movements to bladder functions. Jumping on springboard and other movements primarily repair the pattern dynamics, whereas the exactly coordinated performed movements, performed on the special CDT device for turning, primarily improve the preciseness of the timed firing of neurons. The synchronous learning of perceptuomotor and perceptuobladder functioning from a dynamical perspective (giving rise to learning transfer) can be understood at the neuron level. Especially the activated phase and frequency coordination upon natural stimulation under physiologic and pathophysiologic conditions among a and gamma-motoneurons, muscle spindle afferents, touch and pain afferents, and urinary bladder stretch and tension receptor afferents in the human sacral spinal cord make understandable that somatic and parasympathetic functions are integrated in their functioning and give rise to learning transfer from movements to bladder functions. The power of this human treatment research project lies in the unit of theory, diagnostic/measurement, and praxis, namely that CNS injury can partly be repaired, including urinary bladder functions, and the repair can partly be understood even at the neuron level of description in human.
Adrenergic receptor-mediated modulation of striatal firing patterns.
Ohta, Hiroyuki; Kohno, Yu; Arake, Masashi; Tamura, Risa; Yukawa, Suguru; Sato, Yoshiaki; Morimoto, Yuji; Nishida, Yasuhiro; Yawo, Hiromu
2016-11-01
Although noradrenaline and adrenaline are some of the most important neurotransmitters in the central nervous system, the effects of noradrenergic/adrenergic modulation on the striatum have not been determined. In order to explore the effects of adrenergic receptor (AR) agonists on the striatal firing patterns, we used optogenetic methods which can induce continuous firings. We employed transgenic rats expressing channelrhodopsin-2 (ChR2) in neurons. The medium spiny neuron showed a slow rising depolarization during the 1-s long optogenetic striatal photostimulation and a residual potential with 8.6-s half-life decay after the photostimulation. As a result of the residual potential, five repetitive 1-sec long photostimulations with 20-s onset intervals cumulatively increased the number of spikes. This 'firing increment', possibly relating to the timing control function of the striatum, was used to evaluate the AR modulation. The β-AR agonist isoproterenol decreased the firing increment between the 1st and 5th stimulation cycles, while the α 1 -AR agonist phenylephrine enhanced the firing increment. Isoproterenol and adrenaline increased the early phase (0-0.5s of the photostimulation) firing response. This adrenergic modulation was inhibited by the β-antagonist propranolol. Conversely, phenylephrine and noradrenaline reduced the early phase response. β-ARs and α 1 -ARs work in opposition controlling the striatal firing initiation and the firing increment. Copyright © 2016 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.
Albéri, Lavinia; Lintas, Alessandra; Kretz, Robert; Schwaller, Beat; Villa, Alessandro E P
2013-06-01
The reticular thalamic nucleus (RTN) of the mouse is characterized by an overwhelming majority of GABAergic neurons receiving afferences from both the thalamus and the cerebral cortex and sending projections mainly on thalamocortical neurons. The RTN neurons express high levels of the "slow Ca(2+) buffer" parvalbumin (PV) and are characterized by low-threshold Ca(2+) currents, I(T). We performed extracellular recordings in ketamine/xylazine anesthetized mice in the rostromedial portion of the RTN. In the RTN of wild-type and PV knockout (PVKO) mice we distinguished four types of neurons characterized on the basis of their firing pattern: irregular firing (type I), medium bursting (type II), long bursting (type III), and tonically firing (type IV). Compared with wild-type mice, we observed in the PVKOs the medium bursting (type II) more frequently than the long bursting type and longer interspike intervals within the burst without affecting the number of spikes. This suggests that PV may affect the firing properties of RTN neurons via a mechanism associated with the kinetics of burst discharges. Ca(v)3.2 channels, which mediate the I(T) currents, were more localized to the somatic plasma membrane of RTN neurons in PVKO mice, whereas Ca(v)3.3 expression was similar in both genotypes. The immunoelectron microscopy analysis showed that Ca(v)3.2 channels were localized at active axosomatic synapses, thus suggesting that the differential localization of Ca(v)3.2 in the PVKOs may affect bursting dynamics. Cross-correlation analysis of simultaneously recorded neurons from the same electrode tip showed that about one-third of the cell pairs tended to fire synchronously in both genotypes, independent of PV expression. In summary, PV deficiency does not affect the functional connectivity between RTN neurons but affects the distribution of Ca(v)3.2 channels and the dynamics of burst discharges of RTN cells, which in turn regulate the activity in the thalamocortical circuit.
Grewe, Benjamin F.; Bonnan, Audrey; Frick, Andreas
2009-01-01
Pyramidal neurons of layer 5A are a major neocortical output type and clearly distinguished from layer 5B pyramidal neurons with respect to morphology, in vivo firing patterns, and connectivity; yet knowledge of their dendritic properties is scant. We used a combination of whole-cell recordings and Ca2+ imaging techniques in vitro to explore the specific dendritic signaling role of physiological action potential patterns recorded in vivo in layer 5A pyramidal neurons of the whisker-related ‘barrel cortex’. Our data provide evidence that the temporal structure of physiological action potential patterns is crucial for an effective invasion of the main apical dendrites up to the major branch point. Both the critical frequency enabling action potential trains to invade efficiently and the dendritic calcium profile changed during postnatal development. In contrast to the main apical dendrite, the more passive properties of the short basal and apical tuft dendrites prevented an efficient back-propagation. Various Ca2+ channel types contributed to the enhanced calcium signals during high-frequency firing activity, whereas A-type K+ and BKCa channels strongly suppressed it. Our data support models in which the interaction of synaptic input with action potential output is a function of the timing, rate and pattern of action potentials, and dendritic location. PMID:20508744
Maass, Wolfgang
2008-01-01
Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how behaviorally relevant adaptive changes in complex networks of spiking neurons could be achieved in a self-organizing manner through local synaptic plasticity. However, the capabilities and limitations of this learning rule could so far only be tested through computer simulations. This article provides tools for an analytic treatment of reward-modulated STDP, which allows us to predict under which conditions reward-modulated STDP will achieve a desired learning effect. These analytical results imply that neurons can learn through reward-modulated STDP to classify not only spatial but also temporal firing patterns of presynaptic neurons. They also can learn to respond to specific presynaptic firing patterns with particular spike patterns. Finally, the resulting learning theory predicts that even difficult credit-assignment problems, where it is very hard to tell which synaptic weights should be modified in order to increase the global reward for the system, can be solved in a self-organizing manner through reward-modulated STDP. This yields an explanation for a fundamental experimental result on biofeedback in monkeys by Fetz and Baker. In this experiment monkeys were rewarded for increasing the firing rate of a particular neuron in the cortex and were able to solve this extremely difficult credit assignment problem. Our model for this experiment relies on a combination of reward-modulated STDP with variable spontaneous firing activity. Hence it also provides a possible functional explanation for trial-to-trial variability, which is characteristic for cortical networks of neurons but has no analogue in currently existing artificial computing systems. In addition our model demonstrates that reward-modulated STDP can be applied to all synapses in a large recurrent neural network without endangering the stability of the network dynamics. PMID:18846203
Bi, Zedong; Zhou, Changsong
2016-01-01
Synapses may undergo variable changes during plasticity because of the variability of spike patterns such as temporal stochasticity and spatial randomness. Here, we call the variability of synaptic weight changes during plasticity to be efficacy variability. In this paper, we investigate how four aspects of spike pattern statistics (i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations) influence the efficacy variability under pair-wise additive spike-timing dependent plasticity (STDP) and synaptic homeostasis (the mean strength of plastic synapses into a neuron is bounded), by implementing spike shuffling methods onto spike patterns self-organized by a network of excitatory and inhibitory leaky integrate-and-fire (LIF) neurons. With the increase of the decay time scale of the inhibitory synaptic currents, the LIF network undergoes a transition from asynchronous state to weak synchronous state and then to synchronous bursting state. We first shuffle these spike patterns using a variety of methods, each designed to evidently change a specific pattern statistics; and then investigate the change of efficacy variability of the synapses under STDP and synaptic homeostasis, when the neurons in the network fire according to the spike patterns before and after being treated by a shuffling method. In this way, we can understand how the change of pattern statistics may cause the change of efficacy variability. Our results are consistent with those of our previous study which implements spike-generating models on converging motifs. We also find that burstiness/regularity is important to determine the efficacy variability under asynchronous states, while heterogeneity of cross-correlations is the main factor to cause efficacy variability when the network moves into synchronous bursting states (the states observed in epilepsy). PMID:27555816
Krieger, Patrik; de Kock, Christiaan P. J.; Frick, Andreas
2017-01-01
Layer 5 (L5) is a major neocortical output layer containing L5A slender-tufted (L5A-st) and L5B thick-tufted (L5B-tt) pyramidal neurons. These neuron types differ in their in vivo firing patterns, connectivity and dendritic morphology amongst other features, reflecting their specific functional role within the neocortical circuits. Here, we asked whether the active properties of the basal dendrites that receive the great majority of synaptic inputs within L5 differ between these two pyramidal neuron classes. To quantify their active properties, we measured the efficacy with which action potential (AP) firing patterns backpropagate along the basal dendrites by measuring the accompanying calcium transients using two-photon laser scanning microscopy in rat somatosensory cortex slices. For these measurements we used both “artificial” three-AP patterns and more complex physiological AP patterns that were previously recorded in anesthetized rats in L5A-st and L5B-tt neurons in response to whisker stimulation. We show that AP patterns with relatively few APs (3APs) evoke a calcium response in L5B-tt, but not L5A-st, that is dependent on the temporal pattern of the three APs. With more complex in vivo recorded AP patterns, the average calcium response was similar in the proximal dendrites but with a decay along dendrites (measured up to 100 μm) of L5B-tt but not L5A-st neurons. Interestingly however, the whisker evoked AP patterns—although very different for the two cell types—evoke similar calcium responses. In conclusion, although the effectiveness with which different AP patterns evoke calcium transients vary between L5A-st and L5B-tt cell, the calcium influx appears to be tuned such that whisker-evoked calcium transients are within the same dynamic range for both cell types. PMID:28744201
Neuronal excitability level transition induced by electrical stimulation
NASA Astrophysics Data System (ADS)
Florence, G.; Kurths, J.; Machado, B. S.; Fonoff, E. T.; Cerdeira, H. A.; Teixeira, M. J.; Sameshima, K.
2014-12-01
In experimental studies, electrical stimulation (ES) has been applied to induce neuronal activity or to disrupt pathological patterns. Nevertheless, the underlying mechanisms of these activity pattern transitions are not clear. To study these phenomena, we simulated a model of the hippocampal region CA1. The computational simulations using different amplitude levels and duration of ES revealed three states of neuronal excitability: burst-firing mode, depolarization block and spreading depression wave. We used the bifurcation theory to analyse the interference of ES in the cellular excitability and the neuronal dynamics. Understanding this process would help to improve the ES techniques to control some neurological disorders.
Regular theta-firing neurons in the nucleus incertus during sustained hippocampal activation.
Martínez-Bellver, Sergio; Cervera-Ferri, Ana; Martínez-Ricós, Joana; Ruiz-Torner, Amparo; Luque-Garcia, Aina; Luque-Martinez, Aina; Blasco-Serra, Arantxa; Guerrero-Martínez, Juan; Bataller-Mompeán, Manuel; Teruel-Martí, Vicent
2015-04-01
This paper describes the existence of theta-coupled neuronal activity in the nucleus incertus (NI). Theta rhythm is relevant for cognitive processes such as spatial navigation and memory processing, and can be recorded in a number of structures related to the hippocampal activation including the NI. Strong evidence supports the role of this tegmental nucleus in neural circuits integrating behavioural activation with the hippocampal theta rhythm. Theta oscillations have been recorded in the local field potential of the NI, highly coupled to the hippocampal waves, although no rhythmical activity has been reported in neurons of this nucleus. The present work analyses the neuronal activity in the NI in conditions leading to sustained hippocampal theta in the urethane-anaesthetised rat, in order to test whether such activation elicits a differential firing pattern. Wavelet analysis has been used to better define the neuronal activity already described in the nucleus, i.e., non-rhythmical neurons firing at theta frequency (type I neurons) and fast-firing rhythmical neurons (type II). However, the most remarkable finding was that sustained stimulation activated regular-theta neurons (type III), which were almost silent in baseline conditions and have not previously been reported. Thus, we describe the electrophysiological properties of type III neurons, focusing on their coupling to the hippocampal theta. Their spike rate, regularity and phase locking to the oscillations increased at the beginning of the stimulation, suggesting a role in the activation or reset of the oscillation. Further research is needed to address the specific contribution of these neurons to the entire circuit. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Gilson, Matthieu; Burkitt, Anthony N; Grayden, David B; Thomas, Doreen A; van Hemmen, J Leo
2009-12-01
In neuronal networks, the changes of synaptic strength (or weight) performed by spike-timing-dependent plasticity (STDP) are hypothesized to give rise to functional network structure. This article investigates how this phenomenon occurs for the excitatory recurrent connections of a network with fixed input weights that is stimulated by external spike trains. We develop a theoretical framework based on the Poisson neuron model to analyze the interplay between the neuronal activity (firing rates and the spike-time correlations) and the learning dynamics, when the network is stimulated by correlated pools of homogeneous Poisson spike trains. STDP can lead to both a stabilization of all the neuron firing rates (homeostatic equilibrium) and a robust weight specialization. The pattern of specialization for the recurrent weights is determined by a relationship between the input firing-rate and correlation structures, the network topology, the STDP parameters and the synaptic response properties. We find conditions for feed-forward pathways or areas with strengthened self-feedback to emerge in an initially homogeneous recurrent network.
Recurrent Coupling Improves Discrimination of Temporal Spike Patterns
Yuan, Chun-Wei; Leibold, Christian
2012-01-01
Despite the ubiquitous presence of recurrent synaptic connections in sensory neuronal systems, their general functional purpose is not well understood. A recent conceptual advance has been achieved by theories of reservoir computing in which recurrent networks have been proposed to generate short-term memory as well as to improve neuronal representation of the sensory input for subsequent computations. Here, we present a numerical study on the distinct effects of inhibitory and excitatory recurrence in a canonical linear classification task. It is found that both types of coupling improve the ability to discriminate temporal spike patterns as compared to a purely feed-forward system, although in different ways. For a large class of inhibitory networks, the network’s performance is optimal as long as a fraction of roughly 50% of neurons per stimulus is active in the resulting population code. Thereby the contribution of inactive neurons to the neural code is found to be even more informative than that of the active neurons, generating an inherent robustness of classification performance against temporal jitter of the input spikes. Excitatory couplings are found to not only produce a short-term memory buffer but also to improve linear separability of the population patterns by evoking more irregular firing as compared to the purely inhibitory case. As the excitatory connectivity becomes more sparse, firing becomes more variable, and pattern separability improves. We argue that the proposed paradigm is particularly well-suited as a conceptual framework for processing of sensory information in the auditory pathway. PMID:22586392
Nikaido, Y; Nakashima, T
2011-03-17
The medial prefrontal cortex (mPFC) is involved in stimulus perception, attentional control, emotional behavior, and the stress response. These functions are thought to be mediated by the infralimbic (IL) and prelimbic (PL) subregions of mPFC; however, few studies have examined the roles of IL and PL cortices in olfactory cognition. In the present study, we investigated the acute effects of two odors, 2,5-dihydro-2,4,5-trimethylthiazoline (TMT) and a mixture of cis-3-hexenol and trans-2-hexenal (green odor: GO), on behavioral responses and IL and PL neuronal activities using extracellular single-unit recordings in a freely moving rat. We found that the total number of spike firings in IL and PL neurons did not change with 10s presentation of odors. TMT presentation induced significant changes in burst firing activity in IL and PL neurons, while GO presentation induced changes in burst firing only in IL neurons. In the temporal profile of the firing activity of IL neurons, TMT exposure induced transient activation and GO exposure induced sustained activation. Those of PL neurons showed sustained activation during TMT exposure and transient activations during GO exposure. GO exposure induced a stretch-attend posture, whereas TMT exposure induced immobility. Furthermore, multiple regression analysis indicated that the property of the odor and neuronal activities of IL and PL regions were correlated with behavioral responses. These findings reveal that olfaction-related neurons exist in IL and PL regions, and that the neurons in these regions might temporarily encode odor information in order to modulate motor outputs by tuning firing properties in the early stage of cognition according to the odor property. Copyright © 2010 Elsevier B.V. All rights reserved.
Wenger Combremont, Anne-Laure; Bayer, Laurence; Dupré, Anouk; Mühlethaler, Michel; Serafin, Mauro
2016-01-01
Neurons firing spontaneously in bursts in the absence of synaptic transmission have been previously recorded in different layers of cortical brain slices. It has been suggested that such neurons could contribute to the generation of alternating UP and DOWN states, a pattern of activity seen during slow-wave sleep. Here, we show that in layer 6b (L6b), known from our previous studies to contain neurons highly responsive to the wake-promoting transmitter hypocretin/orexin (hcrt/orx), there is a set of neurons, endowed with distinct intrinsic properties, which displayed a strong propensity to fire spontaneously in rhythmic bursts. In response to small depolarizing steps, they responded with a delayed firing of action potentials which, upon higher depolarizing steps, invariably inactivated and were followed by a depolarized plateau potential and a depolarizing afterpotential. These cells also displayed a strong hyperpolarization-activated rectification compatible with the presence of an Ih current. Most L6b neurons with such properties were able to fire spontaneously in bursts. Their bursting activity was of intrinsic origin as it persisted not only in presence of blockers of ionotropic glutamatergic and GABAergic receptors but also in a condition of complete synaptic blockade. However, a small number of these neurons displayed a mix of intrinsic bursting and synaptically driven recurrent UP and DOWN states. Most of the bursting L6b neurons were depolarized and excited by hcrt/orx through a direct postsynaptic mechanism that led to tonic firing and eventually inactivation. Similarly, they were directly excited by noradrenaline, histamine, dopamine, and neurotensin. Finally, the intracellular injection of these cells with dye and their subsequent Neurolucida reconstruction indicated that they were spiny non-pyramidal neurons. These results lead us to suggest that the propensity for slow rhythmic bursting of this set of L6b neurons could be directly impeded by hcrt/orx and other wake-promoting transmitters. PMID:27379007
Detection of Bursts and Pauses in Spike Trains
Ko, D.; Wilson, C. J.; Lobb, C. J.; Paladini, C. A.
2012-01-01
Midbrain dopaminergic neurons in vivo exhibit a wide range of firing patterns. They normally fire constantly at a low rate, and speed up, firing a phasic burst when reward exceeds prediction, or pause when an expected reward does not occur. Therefore, the detection of bursts and pauses from spike train data is a critical problem when studying the role of phasic dopamine (DA) in reward related learning, and other DA dependent behaviors. However, few statistical methods have been developed that can identify bursts and pauses simultaneously. We propose a new statistical method, the Robust Gaussian Surprise (RGS) method, which performs an exhaustive search of bursts and pauses in spike trains simultaneously. We found that the RGS method is adaptable to various patterns of spike trains recorded in vivo, and is not influenced by baseline firing rate, making it applicable to all in vivo spike trains where baseline firing rates vary over time. We compare the performance of the RGS method to other methods of detecting bursts, such as the Poisson Surprise (PS), Rank Surprise (RS), and Template methods. Analysis of data using the RGS method reveals potential mechanisms underlying how bursts and pauses are controlled in DA neurons. PMID:22939922
Defined types of cortical interneurone structure space and spike timing in the hippocampus
Somogyi, Peter; Klausberger, Thomas
2005-01-01
The cerebral cortex encodes, stores and combines information about the internal and external environment in rhythmic activity of multiple frequency ranges. Neurones of the cortex can be defined, recognized and compared on the comprehensive application of the following measures: (i) brain area- and cell domain-specific distribution of input and output synapses, (ii) expression of molecules involved in cell signalling, (iii) membrane and synaptic properties reflecting the expression of membrane proteins, (iv) temporal structure of firing in vivo, resulting from (i)–(iii). Spatial and temporal measures of neurones in the network reflect an indivisible unity of evolutionary design, i.e. neurones do not have separate structure or function. The blueprint of this design is most easily accessible in the CA1 area of the hippocampus, where a relatively uniform population of pyramidal cells and their inputs follow an instantly recognizable laminated pattern and act within stereotyped network activity patterns. Reviewing the cell types and their spatio-temporal interactions, we suggest that CA1 pyramidal cells are supported by at least 16 distinct types of GABAergic neurone. During a given behaviour-contingent network oscillation, interneurones of a given type exhibit similar firing patterns. During different network oscillations representing two distinct brain states, interneurones of the same class show different firing patterns modulating their postsynaptic target-domain in a brain-state-dependent manner. These results suggest roles for specific interneurone types in structuring the activity of pyramidal cells via their respective target domains, and accurately timing and synchronizing pyramidal cell discharge, rather than providing generalized inhibition. Finally, interneurones belonging to different classes may fire preferentially at distinct time points during a given oscillation. As different interneurones innervate distinct domains of the pyramidal cells, the different compartments will receive GABAergic input differentiated in time. Such a dynamic, spatio-temporal, GABAergic control, which evolves distinct patterns during different brain states, is ideally suited to regulating the input integration of individual pyramidal cells contributing to the formation of cell assemblies and representations in the hippocampus and, probably, throughout the cerebral cortex. PMID:15539390
Forero-Vivas, María E; Hernández-Cruz, Arturo
2014-01-01
The hormone leptin, by binding to hypothalamic receptors, suppresses food intake and decreases body adiposity. Leptin receptors are also widely expressed in extra-hypothalamic areas such as hippocampus, amygdala and cerebellum, where leptin modulates synaptic transmission. Here we show that a defective leptin receptor affects the electrophysiological properties of cerebellar Purkinje neurons (PNs). PNs from (db/db) mice recorded in cerebellar slices display a higher firing rate of spontaneous action potentials than PNs from wild type (WT) mice. Blockade of GABAergic tonic inhibition with bicuculline in WT mice changes the firing pattern from continuous, uninterrupted spiking into bursting firing, but bicuculline does not produce these alterations in db/db neurons, suggesting that they receive a weaker GABAergic inhibitory input. Our results also show that the intrinsic firing properties (auto-rhythmicity) of WT and db/db PNs are different. Tonic firing of PNs, the only efferent output from the cerebellar cortex, is a persistent signal to downstream cerebellar targets. The significance of leptin modulation of PNs spontaneous firing is not known. Also, it is not clear if the increased excitability of cerebellar PNs in db/db mice results from hyperglycemia or from the lack of leptin signaling, since both conditions coexist in the db/db strain.
Sugimura, Taketoshi; Yanagawa, Yuchio
2017-01-01
Gaze holding is primarily controlled by neural structures including the prepositus hypoglossi nucleus (PHN) for horizontal gaze and the interstitial nucleus of Cajal (INC) for vertical and torsional gaze. In contrast to the accumulating findings of the PHN, there is no report regarding the membrane properties of INC neurons or the local networks in the INC. In this study, to verify whether the neural structure of the INC is similar to that of the PHN, we investigated the neuronal and network properties of the INC using whole-cell recordings in rat brainstem slices. Three types of afterhyperpolarization (AHP) profiles and five firing patterns observed in PHN neurons were also observed in INC neurons. However, the overall distributions based on the AHP profile and the firing patterns of INC neurons were different from those of PHN neurons. The application of burst stimulation to a nearby site of a recorded INC neuron induced an increase in the frequency of spontaneous EPSCs. The duration of the increased EPSC frequency of INC neurons was not significantly different from that of PHN neurons. The percent of duration reduction induced by a Ca2+-permeable AMPA (CP-AMPA) receptor antagonist was significantly smaller in the INC than in the PHN. These findings suggest that local excitatory networks that activate sustained EPSC responses also exist in the INC, but their activation mechanisms including the contribution of CP-AMPA receptors differ between the INC and the PHN. PMID:28966973
Associative memory of phase-coded spatiotemporal patterns in leaky Integrate and Fire networks.
Scarpetta, Silvia; Giacco, Ferdinando
2013-04-01
We study the collective dynamics of a Leaky Integrate and Fire network in which precise relative phase relationship of spikes among neurons are stored, as attractors of the dynamics, and selectively replayed at different time scales. Using an STDP-based learning process, we store in the connectivity several phase-coded spike patterns, and we find that, depending on the excitability of the network, different working regimes are possible, with transient or persistent replay activity induced by a brief signal. We introduce an order parameter to evaluate the similarity between stored and recalled phase-coded pattern, and measure the storage capacity. Modulation of spiking thresholds during replay changes the frequency of the collective oscillation or the number of spikes per cycle, keeping preserved the phases relationship. This allows a coding scheme in which phase, rate and frequency are dissociable. Robustness with respect to noise and heterogeneity of neurons parameters is studied, showing that, since dynamics is a retrieval process, neurons preserve stable precise phase relationship among units, keeping a unique frequency of oscillation, even in noisy conditions and with heterogeneity of internal parameters of the units.
Repeating firing fields of CA1 neurons shift forward in response to increasing angular velocity.
Cowen, Stephen L; Nitz, Douglas A
2014-01-01
Self-motion information influences spatially-specific firing patterns exhibited by hippocampal neurons. Moreover, these firing patterns can repeat across similar subsegments of an environment, provided that there is similarity of path shape and head orientations across subsegments. The influence of self-motion variables on repeating fields remains to be determined. To investigate the role of path shape and angular rotation on hippocampal activity, we recorded the activity of CA1 neurons from rats trained to run on spiral-shaped tracks. During inbound traversals of circular-spiral tracks, angular velocity increases continuously. Under this condition, most neurons (74%) exhibited repeating fields across at least three adjacent loops. Of these neurons, 86% exhibited forward shifts in the angles of field centers relative to centers on preceding loops. Shifts were absent on squared-spiral tracks, minimal and less reliable on concentric-circle tracks, and absent on outward-bound runs on circular-spiral tracks. However, outward-bound runs on the circular-spiral track in the dark were associated with backward shifts. Together, the most parsimonious interpretation of the results is that continuous increases or decreases in angular velocity are particularly effective at shifting the center of mass of repeating fields, although it is also possible that a nonlinear integration of step counts contributes to the shift. Furthermore, the unexpected absence of field shifts during outward journeys in light (but not darkness) suggests visual cues around the goal location anchored the map of space to an allocentric reference frame.
Oprisan, Sorinel A.; Buhusi, Catalin V.
2011-01-01
In most species, the capability of perceiving and using the passage of time in the seconds-to-minutes range (interval timing) is not only accurate but also scalar: errors in time estimation are linearly related to the estimated duration. The ubiquity of scalar timing extends over behavioral, lesion, and pharmacological manipulations. For example, in mammals, dopaminergic drugs induce an immediate, scalar change in the perceived time (clock pattern), whereas cholinergic drugs induce a gradual, scalar change in perceived time (memory pattern). How do these properties emerge from unreliable, noisy neurons firing in the milliseconds range? Neurobiological information relative to the brain circuits involved in interval timing provide support for an striatal beat frequency (SBF) model, in which time is coded by the coincidental activation of striatal spiny neurons by cortical neural oscillators. While biologically plausible, the impracticality of perfect oscillators, or their lack thereof, questions this mechanism in a brain with noisy neurons. We explored the computational mechanisms required for the clock and memory patterns in an SBF model with biophysically realistic and noisy Morris–Lecar neurons (SBF–ML). Under the assumption that dopaminergic drugs modulate the firing frequency of cortical oscillators, and that cholinergic drugs modulate the memory representation of the criterion time, we show that our SBF–ML model can reproduce the pharmacological clock and memory patterns observed in the literature. Numerical results also indicate that parameter variability (noise) – which is ubiquitous in the form of small fluctuations in the intrinsic frequencies of neural oscillators within and between trials, and in the errors in recording/retrieving stored information related to criterion time – seems to be critical for the time-scale invariance of the clock and memory patterns. PMID:21977014
Moran, Anan; Stein, Edward; Tischler, Hadass; Belelovsky, Katya; Bar-Gad, Izhar
2011-01-01
Deep brain stimulation (DBS) in the subthalamic nucleus (STN) is a well-established therapy for patients with severe Parkinson's disease (PD); however, its mechanism of action is still unclear. In this study we explored static and dynamic activation patterns in the basal ganglia (BG) during high-frequency macro-stimulation of the STN. Extracellular multi-electrode recordings were performed in primates rendered parkinsonian using 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. Recordings were preformed simultaneously in the STN and the globus pallidus externus and internus. Single units were recorded preceding and during the stimulation. During the stimulation, STN mean firing rate dropped significantly, while pallidal mean firing rates did not change significantly. The vast majority of neurons across all three nuclei displayed stimulation driven modulations, which were stereotypic within each nucleus but differed across nuclei. The predominant response pattern of STN neurons was somatic inhibition. However, most pallidal neurons demonstrated synaptic activation patterns. A minority of neurons across all nuclei displayed axonal activation. Temporal dynamics were observed in the response to stimulation over the first 10 seconds in the STN and over the first 30 seconds in the pallidum. In both pallidal segments, the synaptic activation response patterns underwent delay and decay of the magnitude of the peak response due to short term synaptic depression. We suggest that during STN macro-stimulation the STN goes through a functional ablation as its upper bound on information transmission drops significantly. This notion is further supported by the evident dissociation between the stimulation driven pre-synaptic STN somatic inhibition and the post-synaptic axonal activation of its downstream targets. Thus, BG output maintains its firing rate while losing the deleterious effect of the STN. This may be a part of the mechanism leading to the beneficial effect of DBS in PD.
Kasap, Bahadir; van Opstal, A John
2017-08-01
Single-unit recordings suggest that the midbrain superior colliculus (SC) acts as an optimal controller for saccadic gaze shifts. The SC is proposed to be the site within the visuomotor system where the nonlinear spatial-to-temporal transformation is carried out: the population encodes the intended saccade vector by its location in the motor map (spatial), and its trajectory and velocity by the distribution of firing rates (temporal). The neurons' burst profiles vary systematically with their anatomical positions and intended saccade vectors, to account for the nonlinear main-sequence kinematics of saccades. Yet, the underlying collicular mechanisms that could result in these firing patterns are inaccessible to current neurobiological techniques. Here, we propose a simple spiking neural network model that reproduces the spike trains of saccade-related cells in the intermediate and deep SC layers during saccades. The model assumes that SC neurons have distinct biophysical properties for spike generation that depend on their anatomical position in combination with a center-surround lateral connectivity. Both factors are needed to account for the observed firing patterns. Our model offers a basis for neuronal algorithms for spatiotemporal transformations and bio-inspired optimal controllers.
Rich, Scott; Booth, Victoria; Zochowski, Michal
2016-01-01
The plethora of inhibitory interneurons in the hippocampus and cortex play a pivotal role in generating rhythmic activity by clustering and synchronizing cell firing. Results of our simulations demonstrate that both the intrinsic cellular properties of neurons and the degree of network connectivity affect the characteristics of clustered dynamics exhibited in randomly connected, heterogeneous inhibitory networks. We quantify intrinsic cellular properties by the neuron's current-frequency relation (IF curve) and Phase Response Curve (PRC), a measure of how perturbations given at various phases of a neurons firing cycle affect subsequent spike timing. We analyze network bursting properties of networks of neurons with Type I or Type II properties in both excitability and PRC profile; Type I PRCs strictly show phase advances and IF curves that exhibit frequencies arbitrarily close to zero at firing threshold while Type II PRCs display both phase advances and delays and IF curves that have a non-zero frequency at threshold. Type II neurons whose properties arise with or without an M-type adaptation current are considered. We analyze network dynamics under different levels of cellular heterogeneity and as intrinsic cellular firing frequency and the time scale of decay of synaptic inhibition are varied. Many of the dynamics exhibited by these networks diverge from the predictions of the interneuron network gamma (ING) mechanism, as well as from results in all-to-all connected networks. Our results show that randomly connected networks of Type I neurons synchronize into a single cluster of active neurons while networks of Type II neurons organize into two mutually exclusive clusters segregated by the cells' intrinsic firing frequencies. Networks of Type II neurons containing the adaptation current behave similarly to networks of either Type I or Type II neurons depending on network parameters; however, the adaptation current creates differences in the cluster dynamics compared to those in networks of Type I or Type II neurons. To understand these results, we compute neuronal PRCs calculated with a perturbation matching the profile of the synaptic current in our networks. Differences in profiles of these PRCs across the different neuron types reveal mechanisms underlying the divergent network dynamics. PMID:27812323
ERIC Educational Resources Information Center
Tort, Adriano B. L.; Komorowski, Robert; Kopell, Nancy; Eichenbaum, Howard
2011-01-01
The association of specific events with the context in which they occur is a fundamental feature of episodic memory. However, the underlying network mechanisms generating what-where associations are poorly understood. Recently we reported that some hippocampal principal neurons develop representations of specific events occurring in particular…
Transformation of a Spatial Map across the Hippocampal-Lateral Septal Circuit.
Tingley, David; Buzsáki, György
2018-05-15
The hippocampus constructs a map of the environment. How this "cognitive map" is utilized by other brain regions to guide behavior remains unexplored. To examine how neuronal firing patterns in the hippocampus are transmitted and transformed, we recorded neurons in its principal subcortical target, the lateral septum (LS). We observed that LS neurons carry reliable spatial information in the phase of action potentials, relative to hippocampal theta oscillations, while the firing rates of LS neurons remained uninformative. Furthermore, this spatial phase code had an anatomical microstructure within the LS and was bound to the hippocampal spatial code by synchronous gamma frequency cell assemblies. Using a data-driven model, we show that rate-independent spatial tuning arises through the dynamic weighting of CA1 and CA3 cell assemblies. Our findings demonstrate that transformation of the hippocampal spatial map depends on higher-order theta-dependent neuronal sequences. Copyright © 2018 Elsevier Inc. All rights reserved.
Pilkiw, Maryna; Insel, Nathan; Cui, Younghua; Finney, Caitlin; Morrissey, Mark D; Takehara-Nishiuchi, Kaori
2017-07-06
The lateral entorhinal cortex (LEC) is thought to bind sensory events with the environment where they took place. To compare the relative influence of transient events and temporally stable environmental stimuli on the firing of LEC cells, we recorded neuron spiking patterns in the region during blocks of a trace eyeblink conditioning paradigm performed in two environments and with different conditioning stimuli. Firing rates of some neurons were phasically selective for conditioned stimuli in a way that depended on which room the rat was in; nearly all neurons were tonically selective for environments in a way that depended on which stimuli had been presented in those environments. As rats moved from one environment to another, tonic neuron ensemble activity exhibited prospective information about the conditioned stimulus associated with the environment. Thus, the LEC formed phasic and tonic codes for event-environment associations, thereby accurately differentiating multiple experiences with overlapping features.
Spatio-temporal specialization of GABAergic septo-hippocampal neurons for rhythmic network activity.
Unal, Gunes; Crump, Michael G; Viney, Tim J; Éltes, Tímea; Katona, Linda; Klausberger, Thomas; Somogyi, Peter
2018-03-03
Medial septal GABAergic neurons of the basal forebrain innervate the hippocampus and related cortical areas, contributing to the coordination of network activity, such as theta oscillations and sharp wave-ripple events, via a preferential innervation of GABAergic interneurons. Individual medial septal neurons display diverse activity patterns, which may be related to their termination in different cortical areas and/or to the different types of innervated interneurons. To test these hypotheses, we extracellularly recorded and juxtacellularly labeled single medial septal neurons in anesthetized rats in vivo during hippocampal theta and ripple oscillations, traced their axons to distant cortical target areas, and analyzed their postsynaptic interneurons. Medial septal GABAergic neurons exhibiting different hippocampal theta phase preferences and/or sharp wave-ripple related activity terminated in restricted hippocampal regions, and selectively targeted a limited number of interneuron types, as established on the basis of molecular markers. We demonstrate the preferential innervation of bistratified cells in CA1 and of basket cells in CA3 by individual axons. One group of septal neurons was suppressed during sharp wave-ripples, maintained their firing rate across theta and non-theta network states and mainly fired along the descending phase of CA1 theta oscillations. In contrast, neurons that were active during sharp wave-ripples increased their firing significantly during "theta" compared to "non-theta" states, with most firing during the ascending phase of theta oscillations. These results demonstrate that specialized septal GABAergic neurons contribute to the coordination of network activity through parallel, target area- and cell type-selective projections to the hippocampus.
Liu, Pin W.
2014-01-01
Kv2 family “delayed-rectifier” potassium channels are widely expressed in mammalian neurons. Kv2 channels activate relatively slowly and their contribution to action potential repolarization under physiological conditions has been unclear. We explored the function of Kv2 channels using a Kv2-selective blocker, Guangxitoxin-1E (GxTX-1E). Using acutely isolated neurons, mixed voltage-clamp and current-clamp experiments were done at 37°C to study the physiological kinetics of channel gating and action potentials. In both rat superior cervical ganglion (SCG) neurons and mouse hippocampal CA1 pyramidal neurons, 100 nm GxTX-1E produced near-saturating block of a component of current typically constituting ∼60–80% of the total delayed-rectifier current. GxTX-1E also reduced A-type potassium current (IA), but much more weakly. In SCG neurons, 100 nm GxTX-1E broadened spikes and voltage clamp experiments using action potential waveforms showed that Kv2 channels carry ∼55% of the total outward current during action potential repolarization despite activating relatively late in the spike. In CA1 neurons, 100 nm GxTX-1E broadened spikes evoked from −70 mV, but not −80 mV, likely reflecting a greater role of Kv2 when other potassium channels were partially inactivated at −70 mV. In both CA1 and SCG neurons, inhibition of Kv2 channels produced dramatic depolarization of interspike voltages during repetitive firing. In CA1 neurons and some SCG neurons, this was associated with increased initial firing frequency. In all neurons, inhibition of Kv2 channels depressed maintained firing because neurons entered depolarization block more readily. Therefore, Kv2 channels can either decrease or increase neuronal excitability depending on the time scale of excitation. PMID:24695716
Law, Andrew J.; Rivlis, Gil
2014-01-01
Pioneering studies demonstrated that novel degrees of freedom could be controlled individually by directly encoding the firing rate of single motor cortex neurons, without regard to each neuron's role in controlling movement of the native limb. In contrast, recent brain-computer interface work has emphasized decoding outputs from large ensembles that include substantially more neurons than the number of degrees of freedom being controlled. To bridge the gap between direct encoding by single neurons and decoding output from large ensembles, we studied monkeys controlling one degree of freedom by comodulating up to four arbitrarily selected motor cortex neurons. Performance typically exceeded random quite early in single sessions and then continued to improve to different degrees in different sessions. We therefore examined factors that might affect performance. Performance improved with larger ensembles. In contrast, other factors that might have reflected preexisting synaptic architecture—such as the similarity of preferred directions—had little if any effect on performance. Patterns of comodulation among ensemble neurons became more consistent across trials as performance improved over single sessions. Compared with the ensemble neurons, other simultaneously recorded neurons showed less modulation. Patterns of voluntarily comodulated firing among small numbers of arbitrarily selected primary motor cortex (M1) neurons thus can be found and improved rapidly, with little constraint based on the normal relationships of the individual neurons to native limb movement. This rapid flexibility in relationships among M1 neurons may in part underlie our ability to learn new movements and improve motor skill. PMID:24920030
Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T
2013-01-01
Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in "intermediate" regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of inhomogeneous activity patterns.
Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T.
2014-01-01
Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in “intermediate” regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of inhomogeneous activity patterns. PMID:24501591
Khosrovani, S.; Van Der Giessen, R. S.; De Zeeuw, C. I.; De Jeu, M. T. G.
2007-01-01
In vitro whole-cell recordings of the inferior olive have demonstrated that its neurons are electrotonically coupled and have a tendency to oscillate. However, it remains to be shown to what extent subthreshold oscillations do indeed occur in the inferior olive in vivo and whether its spatiotemporal firing pattern may be dynamically generated by including or excluding different types of oscillatory neurons. Here, we did whole-cell recordings of olivary neurons in vivo to investigate the relation between their subthreshold activities and their spiking behavior in an intact brain. The vast majority of neurons (85%) showed subthreshold oscillatory activities. The frequencies of these subthreshold oscillations were used to distinguish four main olivary subtypes by statistical means. Type I showed both sinusoidal subthreshold oscillations (SSTOs) and low-threshold Ca2+ oscillations (LTOs) (16%); type II showed only sinusoidal subthreshold oscillations (13%); type III showed only low-threshold Ca2+ oscillations (56%); and type IV did not reveal any subthreshold oscillations (15%). These subthreshold oscillation frequencies were strongly correlated with the frequencies of preferred spiking. The frequency characteristics of the subthreshold oscillations and spiking behavior of virtually all olivary neurons were stable throughout the recordings. However, the occurrence of spontaneous or evoked action potentials modified the subthreshold oscillation by resetting the phase of its peak toward 90°. Together, these findings indicate that the inferior olive in intact mammals offers a rich repertoire of different neurons with relatively stable frequency settings, which can be used to generate and reset temporal firing patterns in a dynamically coupled ensemble. PMID:17895389
Lee, Inah; Kim, Jangjin
2010-08-01
Hippocampal-dependent tasks often involve specific associations among stimuli (including egocentric information), and such tasks are therefore prone to interference from irrelevant task strategies before a correct strategy is found. Using an object-place paired-associate task, we investigated changes in neural firing patterns in the hippocampus in association with a shift in strategy during learning. We used an object-place paired-associate task in which a pair of objects was presented in two different arms of a radial maze. Each object was associated with reward only in one of the arms, thus requiring the rats to consider both object identity and its location in the maze. Hippocampal neurons recorded in CA1 displayed a dynamic transition in their firing patterns during the acquisition of the task across days, and this corresponded to a shift in strategy manifested in behavioral data. Specifically, before the rats learned the task, they chose an object that maintained a particular egocentric relationship with their body (response strategy) irrespective of the object identity. However, as the animal acquired the task, it chose an object according to both its identity and the associated location in the maze (object-in-place strategy). We report that CA1 neurons in the hippocampus changed their prospective firing correlates according to the dominant strategy (i.e., response versus object-in-place strategy) employed at a given stage of learning. The results suggest that neural firing pattern in the hippocampus is heavily influenced by the task demand hypothesized by the animal and the firing pattern changes flexibly as the perceived task demand changes.
Burst firing and modulation of functional connectivity in cat striate cortex.
Snider, R K; Kabara, J F; Roig, B R; Bonds, A B
1998-08-01
We studied the influences of the temporal firing patterns of presynaptic cat visual cortical cells on spike generation by postsynaptic cells. Multiunit recordings were dissected into the activity of individual neurons within the recorded group. Cross-correlation analysis was then used to identify directly coupled neuron pairs. The 22 multiunit groups recorded typically showed activity from two to six neurons, each containing between 1 and 15 neuron pairs. From a total of 241 neuron pairs, 91 (38%) had a shifted cross-correlation peak, which indicated a possible direct connection. Only two multiunit groups contained no shifted peaks. Burst activity, defined by groups of two or more spikes with intervals of =8 ms from any single neuron, was analyzed in terms of its effectiveness in eliciting a spike from a second, driven neuron. We defined effectiveness as the percentage of spikes from the driving neuron that are time related to spikes of the driven neuron. The effectiveness of bursts (of any length) in eliciting a time-related response spike averaged 18.53% across all measurements as compared with the effectiveness of single spikes, which averaged 9.53%. Longer bursts were more effective than shorter ones. Effectiveness was reduced with spatially nonoptimal, as opposed to optimal, stimuli. The effectiveness of both bursts and single spikes decreased by the same amount across measurements with nonoptimal orientations, spatial frequencies and contrasts. At similar firing rates and burst lengths, the decrease was more pronounced for nonoptimal orientations than for lower contrasts, suggesting the existence of a mechanism that reduces effectiveness at nonoptimal orientations. These results support the hypothesis that neural information can be emphasized via instantaneous rate coding that is not preserved over long intervals or over trials. This is consistent with the integrate and fire model, where bursts participate in temporal integration.
Hertäg, Loreen; Durstewitz, Daniel; Brunel, Nicolas
2014-01-01
Computational models offer a unique tool for understanding the network-dynamical mechanisms which mediate between physiological and biophysical properties, and behavioral function. A traditional challenge in computational neuroscience is, however, that simple neuronal models which can be studied analytically fail to reproduce the diversity of electrophysiological behaviors seen in real neurons, while detailed neuronal models which do reproduce such diversity are intractable analytically and computationally expensive. A number of intermediate models have been proposed whose aim is to capture the diversity of firing behaviors and spike times of real neurons while entailing the simplest possible mathematical description. One such model is the exponential integrate-and-fire neuron with spike rate adaptation (aEIF) which consists of two differential equations for the membrane potential (V) and an adaptation current (w). Despite its simplicity, it can reproduce a wide variety of physiologically observed spiking patterns, can be fit to physiological recordings quantitatively, and, once done so, is able to predict spike times on traces not used for model fitting. Here we compute the steady-state firing rate of aEIF in the presence of Gaussian synaptic noise, using two approaches. The first approach is based on the 2-dimensional Fokker-Planck equation that describes the (V,w)-probability distribution, which is solved using an expansion in the ratio between the time constants of the two variables. The second is based on the firing rate of the EIF model, which is averaged over the distribution of the w variable. These analytically derived closed-form expressions were tested on simulations from a large variety of model cells quantitatively fitted to in vitro electrophysiological recordings from pyramidal cells and interneurons. Theoretical predictions closely agreed with the firing rate of the simulated cells fed with in-vivo-like synaptic noise.
Lee, Inah; Park, Seong-Beom
2013-01-01
Objects and their locations can associatively define an event and a conjoint representation of object-place can form an event memory. Remembering how to respond to a certain object in a spatial context is dependent on both hippocampus and perirhinal cortex (PER). However, the relative functional contributions of the two regions are largely unknown in object-place associative memory. We investigated the PER influence on hippocampal firing in a goal-directed object-place memory task by comparing the firing patterns of CA1 and CA3 of the dorsal hippocampus between conditions of PER muscimol inactivation and vehicle control infusions. Rats were required to choose one of the two objects in a specific spatial context (regardless of the object positions in the context), which was shown to be dependent on both hippocampus and PER. Inactivation of PER with muscimol (MUS) severely disrupted performance of well-trained rats, resulting in response bias (i.e., choosing any object on a particular side). MUS did not significantly alter the baseline firing rates of hippocampal neurons. We measured the similarity in firing patterns between two trial conditions in which the same target objects were chosen on opposite sides within the same arm [object-in-place (O-P) strategy] and compared the results with the similarity in firing between two trial conditions in which the rat chose any object encountered on a particular side [response-in-place (R-P) strategy]. We found that the similarity in firing patterns for O-P trials was significantly reduced with MUS compared to control conditions (CTs). Importantly, this was largely because MUS injections affected the O-P firing patterns in CA1 neurons, but not in CA3. The results suggest that PER is critical for goal-directed organization of object-place associative memory in the hippocampus presumably by influencing how object information is associated with spatial information in CA1 according to task demand.
Time-scale invariance as an emergent property in a perceptron with realistic, noisy neurons
Buhusi, Catalin V.; Oprisan, Sorinel A.
2013-01-01
In most species, interval timing is time-scale invariant: errors in time estimation scale up linearly with the estimated duration. In mammals, time-scale invariance is ubiquitous over behavioral, lesion, and pharmacological manipulations. For example, dopaminergic drugs induce an immediate, whereas cholinergic drugs induce a gradual, scalar change in timing. Behavioral theories posit that time-scale invariance derives from particular computations, rules, or coding schemes. In contrast, we discuss a simple neural circuit, the perceptron, whose output neurons fire in a clockwise fashion (interval timing) based on the pattern of coincidental activation of its input neurons. We show numerically that time-scale invariance emerges spontaneously in a perceptron with realistic neurons, in the presence of noise. Under the assumption that dopaminergic drugs modulate the firing of input neurons, and that cholinergic drugs modulate the memory representation of the criterion time, we show that a perceptron with realistic neurons reproduces the pharmacological clock and memory patterns, and their time-scale invariance, in the presence of noise. These results suggest that rather than being a signature of higher-order cognitive processes or specific computations related to timing, time-scale invariance may spontaneously emerge in a massively-connected brain from the intrinsic noise of neurons and circuits, thus providing the simplest explanation for the ubiquity of scale invariance of interval timing. PMID:23518297
Zhang, Hua; Liu, Jie; Sun, Suya; Pchitskaya, Ekaterina; Popugaeva, Elena; Bezprozvanny, Ilya
2015-01-01
Alzheimer's disease (AD) and aging result in impaired ability to store memories, but the cellular mechanisms responsible for these defects are poorly understood. Presenilin 1 (PS1) mutations are responsible for many early-onset familial AD (FAD) cases. The phenomenon of hippocampal long-term potentiation (LTP) is widely used in studies of memory formation and storage. Recent data revealed long-term LTP maintenance (L-LTP) is impaired in PS1-M146V knock-in (KI) FAD mice. To understand the basis for this phenomenon, in the present study we analyzed structural synaptic plasticity in hippocampal cultures from wild type (WT) and KI mice. We discovered that exposure to picrotoxin induces formation of mushroom spines in both WT and KI cultures, but the maintenance of mushroom spines is impaired in KI neurons. This maintenance defect can be explained by an abnormal firing pattern during the consolidation phase of structural plasticity in KI neurons. Reduced frequency of neuronal firing in KI neurons is caused by enhanced calcium-induced calcium release (CICR), enhanced activity of calcium-activated potassium channels, and increased afterhyperpolarization. As a result, "consolidation" pattern of neuronal activity converted to "depotentiation" pattern of neuronal activity in KI neurons. Consistent with this model, we demonstrated that pharmacological inhibitors of CICR (dantrolene), of calcium-activated potassium channels (apamin), and of calcium-dependent phosphatase calcineurin (FK506) are able to rescue structural plasticity defects in KI neurons. Furthermore, we demonstrate that incubation with dantrolene or apamin also rescued L-LTP defects in KI hippocampal slices, suggesting a role for a similar mechanism. This proposed mechanism may be responsible for memory defects in AD but also for age-related memory decline.
Das, Mainak; Bhargava, Neelima; Bhalkikar, Abhijeet; Kang, Jung Fong; Hickman, James J
2008-01-01
The ability to culture functional adult mammalian spinal-cord neurons represents an important step in the understanding and treatment of a spectrum of neurological disorders including spinal cord injury. Previously, the limited functional recovery of these cells, as characterized by a diminished ability to initiate action potentials and to exhibit repetitive firing patterns, has arisen as a major impediment to their physiological relevance. In this report we demonstrate that single temporal doses of the neurotransmitters serotonin, glutamate (N-acetyl-DL-glutamic acid) and acetylcholine-chloride leads to the full electrophysiological functional recovery of adult mammalian spinal-cord neurons, when they are cultured under defined serum-free conditions. Approximately 60% of the neurons treated regained their electrophysiological signature, often firing single, double and, most importantly, multiple action potentials. PMID:18005959
Developmental metaplasticity in neural circuit codes of firing and structure.
Baram, Yoram
2017-01-01
Firing-rate dynamics have been hypothesized to mediate inter-neural information transfer in the brain. While the Hebbian paradigm, relating learning and memory to firing activity, has put synaptic efficacy variation at the center of cortical plasticity, we suggest that the external expression of plasticity by changes in the firing-rate dynamics represents a more general notion of plasticity. Hypothesizing that time constants of plasticity and firing dynamics increase with age, and employing the filtering property of the neuron, we obtain the elementary code of global attractors associated with the firing-rate dynamics in each developmental stage. We define a neural circuit connectivity code as an indivisible set of circuit structures generated by membrane and synapse activation and silencing. Synchronous firing patterns under parameter uniformity, and asynchronous circuit firing are shown to be driven, respectively, by membrane and synapse silencing and reactivation, and maintained by the neuronal filtering property. Analytic, graphical and simulation representation of the discrete iteration maps and of the global attractor codes of neural firing rate are found to be consistent with previous empirical neurobiological findings, which have lacked, however, a specific correspondence between firing modes, time constants, circuit connectivity and cortical developmental stages. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hernandez, Oscar; Hernandez, Lilibeth; Vera, David; Santander, Alcides; Zurek, Eduardo
2015-01-01
The neurons of the Thalamic Reticular Nucleus (TRNn) respond to inputs in two activity modes called burst and tonic firing and both can be observed in different physiological states. The functional states of the thalamus depend in part on the properties of synaptic transmission between the TRNn and the thalamocortical and corticothalamic neurons. A dendrite can receive inhibitory and excitatory postsynaptic potentials. The novelties presented in this paper can be summarized as follows: First, it shows, through a computational simulation, that the burst and tonic firings observed in the TRNn soma could be explained as a product of random synaptic inputs on the distal dendrites, the tonic firings are generated by random excitatory stimuli, and the burst firings are generated by two different types of stimuli: inhibitory random stimuli, and a combination of inhibitory (from TRNn) and excitatory (from corticothalamic and thalamocortical neurons) random stimuli; second, according to in vivo recordings, we have found that the burst observed in the TRNn soma has graduate properties that are proportional to the stimuli frequency; and third, a novel method for showing in a quantitative manner the accelerando-decelerando pattern is proposed.
Motoneuron firing in amyotrophic lateral sclerosis (ALS)
de Carvalho, Mamede; Eisen, Andrew; Krieger, Charles; Swash, Michael
2014-01-01
Amyotrophic lateral sclerosis is an inexorably progressive neurodegenerative disorder involving the classical motor system and the frontal effector brain, causing muscular weakness and atrophy, with variable upper motor neuron signs and often an associated fronto-temporal dementia. The physiological disturbance consequent on the motor system degeneration is beginning to be well understood. In this review we describe aspects of the motor cortical, neuronal, and lower motor neuron dysfunction. We show how studies of the changes in the pattern of motor unit firing help delineate the underlying pathophysiological disturbance as the disease progresses. Such studies are beginning to illuminate the underlying disordered pathophysiological processes in the disease, and are important in designing new approaches to therapy and especially for clinical trials. PMID:25294995
ERIC Educational Resources Information Center
Lee, Eunjeong; Oliveira-Ferreira, Ana I.; de Water, Ed; Gerritsen, Hans; Bakker, Mattijs C.; Kalwij, Jan A. W.; van Goudoever, Tjerk; Buster, Wietze H.; Pennartz, Cyriel M. A.
2009-01-01
To meet an increasing need to examine the neurophysiological underpinnings of behavior in rats, we developed a behavioral system for studying sensory processing, attention and discrimination learning in rats while recording firing patterns of neurons in one or more brain areas of interest. Because neuronal activity is sensitive to variations in…
Taillefumier, Thibaud; Touboul, Jonathan; Magnasco, Marcelo
2012-12-01
In vivo cortical recording reveals that indirectly driven neural assemblies can produce reliable and temporally precise spiking patterns in response to stereotyped stimulation. This suggests that despite being fundamentally noisy, the collective activity of neurons conveys information through temporal coding. Stochastic integrate-and-fire models delineate a natural theoretical framework to study the interplay of intrinsic neural noise and spike timing precision. However, there are inherent difficulties in simulating their networks' dynamics in silico with standard numerical discretization schemes. Indeed, the well-posedness of the evolution of such networks requires temporally ordering every neuronal interaction, whereas the order of interactions is highly sensitive to the random variability of spiking times. Here, we answer these issues for perfect stochastic integrate-and-fire neurons by designing an exact event-driven algorithm for the simulation of recurrent networks, with delayed Dirac-like interactions. In addition to being exact from the mathematical standpoint, our proposed method is highly efficient numerically. We envision that our algorithm is especially indicated for studying the emergence of polychronized motifs in networks evolving under spike-timing-dependent plasticity with intrinsic noise.
Shiau, LieJune; Schwalger, Tilo; Lindner, Benjamin
2015-06-01
We study the spike statistics of an adaptive exponential integrate-and-fire neuron stimulated by white Gaussian current noise. We derive analytical approximations for the coefficient of variation and the serial correlation coefficient of the interspike interval assuming that the neuron operates in the mean-driven tonic firing regime and that the stochastic input is weak. Our result for the serial correlation coefficient has the form of a geometric sequence and is confirmed by the comparison to numerical simulations. The theory predicts various patterns of interval correlations (positive or negative at lag one, monotonically decreasing or oscillating) depending on the strength of the spike-triggered and subthreshold components of the adaptation current. In particular, for pure subthreshold adaptation we find strong positive ISI correlations that are usually ascribed to positive correlations in the input current. Our results i) provide an alternative explanation for interspike-interval correlations observed in vivo, ii) may be useful in fitting point neuron models to experimental data, and iii) may be instrumental in exploring the role of adaptation currents for signal detection and signal transmission in single neurons.
Neuronal pattern separation of motion-relevant input in LIP activity
Berberian, Nareg; MacPherson, Amanda; Giraud, Eloïse; Richardson, Lydia
2016-01-01
In various regions of the brain, neurons discriminate sensory stimuli by decreasing the similarity between ambiguous input patterns. Here, we examine whether this process of pattern separation may drive the rapid discrimination of visual motion stimuli in the lateral intraparietal area (LIP). Starting with a simple mean-rate population model that captures neuronal activity in LIP, we show that overlapping input patterns can be reformatted dynamically to give rise to separated patterns of neuronal activity. The population model predicts that a key ingredient of pattern separation is the presence of heterogeneity in the response of individual units. Furthermore, the model proposes that pattern separation relies on heterogeneity in the temporal dynamics of neural activity and not merely in the mean firing rates of individual neurons over time. We confirm these predictions in recordings of macaque LIP neurons and show that the accuracy of pattern separation is a strong predictor of behavioral performance. Overall, results propose that LIP relies on neuronal pattern separation to facilitate decision-relevant discrimination of sensory stimuli. NEW & NOTEWORTHY A new hypothesis is proposed on the role of the lateral intraparietal (LIP) region of cortex during rapid decision making. This hypothesis suggests that LIP alters the representation of ambiguous inputs to reduce their overlap, thus improving sensory discrimination. A combination of computational modeling, theoretical analysis, and electrophysiological data shows that the pattern separation hypothesis links neural activity to behavior and offers novel predictions on the role of LIP during sensory discrimination. PMID:27881719
Zillmer, Rüdiger; Brunel, Nicolas; Hansel, David
2009-03-01
We present results of an extensive numerical study of the dynamics of networks of integrate-and-fire neurons connected randomly through inhibitory interactions. We first consider delayed interactions with infinitely fast rise and decay. Depending on the parameters, the network displays transients which are short or exponentially long in the network size. At the end of these transients, the dynamics settle on a periodic attractor. If the number of connections per neuron is large ( approximately 1000) , this attractor is a cluster state with a short period. In contrast, if the number of connections per neuron is small ( approximately 100) , the attractor has complex dynamics and very long period. During the long transients the neurons fire in a highly irregular manner. They can be viewed as quasistationary states in which, depending on the coupling strength, the pattern of activity is asynchronous or displays population oscillations. In the first case, the average firing rates and the variability of the single-neuron activity are well described by a mean-field theory valid in the thermodynamic limit. Bifurcations of the long transient dynamics from asynchronous to synchronous activity are also well predicted by this theory. The transient dynamics display features reminiscent of stable chaos. In particular, despite being linearly stable, the trajectories of the transient dynamics are destabilized by finite perturbations as small as O(1/N) . We further show that stable chaos is also observed for postsynaptic currents with finite decay time. However, we report in this type of network that chaotic dynamics characterized by positive Lyapunov exponents can also be observed. We show in fact that chaos occurs when the decay time of the synaptic currents is long compared to the synaptic delay, provided that the network is sufficiently large.
Cerebellar output controls generalized spike‐and‐wave discharge occurrence
Kros, Lieke; Eelkman Rooda, Oscar H. J.; Spanke, Jochen K.; Alva, Parimala; van Dongen, Marijn N.; Karapatis, Athanasios; Tolner, Else A.; Strydis, Christos; Davey, Neil; Winkelman, Beerend H. J.; Negrello, Mario; Serdijn, Wouter A.; Steuber, Volker; van den Maagdenberg, Arn M. J. M.; De Zeeuw, Chris I.
2015-01-01
Objective Disrupting thalamocortical activity patterns has proven to be a promising approach to stop generalized spike‐and‐wave discharges (GSWDs) characteristic of absence seizures. Here, we investigated to what extent modulation of neuronal firing in cerebellar nuclei (CN), which are anatomically in an advantageous position to disrupt cortical oscillations through their innervation of a wide variety of thalamic nuclei, is effective in controlling absence seizures. Methods Two unrelated mouse models of generalized absence seizures were used: the natural mutant tottering, which is characterized by a missense mutation in Cacna1a, and inbred C3H/HeOuJ. While simultaneously recording single CN neuron activity and electrocorticogram in awake animals, we investigated to what extent pharmacologically increased or decreased CN neuron activity could modulate GSWD occurrence as well as short‐lasting, on‐demand CN stimulation could disrupt epileptic seizures. Results We found that a subset of CN neurons show phase‐locked oscillatory firing during GSWDs and that manipulating this activity modulates GSWD occurrence. Inhibiting CN neuron action potential firing by local application of the γ‐aminobutyric acid type A (GABA‐A) agonist muscimol increased GSWD occurrence up to 37‐fold, whereas increasing the frequency and regularity of CN neuron firing with the use of GABA‐A antagonist gabazine decimated its occurrence. A single short‐lasting (30–300 milliseconds) optogenetic stimulation of CN neuron activity abruptly stopped GSWDs, even when applied unilaterally. Using a closed‐loop system, GSWDs were detected and stopped within 500 milliseconds. Interpretation CN neurons are potent modulators of pathological oscillations in thalamocortical network activity during absence seizures, and their potential therapeutic benefit for controlling other types of generalized epilepsies should be evaluated. Ann Neurol 2015;77:1027–1049 PMID:25762286
Franzen, Delwen L; Gleiss, Sarah A; Berger, Christina; Kümpfbeck, Franziska S; Ammer, Julian J; Felmy, Felix
2015-01-15
Passive and active membrane properties determine the voltage responses of neurons. Within the auditory brain stem, refinements in these intrinsic properties during late postnatal development usually generate short integration times and precise action-potential generation. This developmentally acquired temporal precision is crucial for auditory signal processing. How the interactions of these intrinsic properties develop in concert to enable auditory neurons to transfer information with high temporal precision has not yet been elucidated in detail. Here, we show how the developmental interaction of intrinsic membrane parameters generates high firing precision. We performed in vitro recordings from neurons of postnatal days 9-28 in the ventral nucleus of the lateral lemniscus of Mongolian gerbils, an auditory brain stem structure that converts excitatory to inhibitory information with high temporal precision. During this developmental period, the input resistance and capacitance decrease, and action potentials acquire faster kinetics and enhanced precision. Depending on the stimulation time course, the input resistance and capacitance contribute differentially to action-potential thresholds. The decrease in input resistance, however, is sufficient to explain the enhanced action-potential precision. Alterations in passive membrane properties also interact with a developmental change in potassium currents to generate the emergence of the mature firing pattern, characteristic of coincidence-detector neurons. Cholinergic receptor-mediated depolarizations further modulate this intrinsic excitability profile by eliciting changes in the threshold and firing pattern, irrespective of the developmental stage. Thus our findings reveal how intrinsic membrane properties interact developmentally to promote temporally precise information processing. Copyright © 2015 the American Physiological Society.
Juárez-Hernández, León J.; Bisson, Giacomo; Torre, Vincent
2013-01-01
The present manuscript aims at identifying patterns of electrical activity recorded from neurons of the leech nervous system, characterizing specific behaviors. When leeches are at rest, the electrical activity of neurons and motoneurons is poorly correlated. When leeches move their head and/or tail, in contrast, action potential (AP) firing becomes highly correlated. When the head or tail suckers detach, specific patterns of electrical activity are detected. During elongation and contraction the electrical activity of motoneurons in the Medial Anterior and Dorsal Posterior nerves increase, respectively, and several motoneurons are activated both during elongation and contraction. During crawling, swimming, and pseudo-swimming patterns of electrical activity are better described by the dendrograms of cross-correlations of motoneurons pairs. Dendrograms obtained from different animals exhibiting the same behavior are similar and by averaging these dendrograms we obtained a template underlying a given behavior. By using this template, the corresponding behavior is reliably identified from the recorded electrical activity. The analysis of dendrograms during different leech behavior reveals the fine orchestration of motoneurons firing specific to each stereotyped behavior. Therefore, dendrograms capture the subtle changes in the correlation pattern of neuronal networks when they become involved in different tasks or functions. PMID:24098274
Horn, Kyle G; Memelli, Heraldo; Solomon, Irene C
2012-01-01
Most models of central pattern generators (CPGs) involve two distinct nuclei mutually inhibiting one another via synapses. Here, we present a single-nucleus model of biologically realistic Hodgkin-Huxley neurons with random gap junction coupling. Despite no explicit division of neurons into two groups, we observe a spontaneous division of neurons into two distinct firing groups. In addition, we also demonstrate this phenomenon in a simplified version of the model, highlighting the importance of afterhyperpolarization currents (I(AHP)) to CPGs utilizing gap junction coupling. The properties of these CPGs also appear sensitive to gap junction conductance, probability of gap junction coupling between cells, topology of gap junction coupling, and, to a lesser extent, input current into our simulated nucleus.
Spatial cell firing during virtual navigation of open arenas by head-restrained mice.
Chen, Guifen; King, John Andrew; Lu, Yi; Cacucci, Francesca; Burgess, Neil
2018-06-18
We present a mouse virtual reality (VR) system which restrains head-movements to horizontal rotations, compatible with multi-photon imaging. This system allows expression of the spatial navigation and neuronal firing patterns characteristic of real open arenas (R). Comparing VR to R: place and grid, but not head-direction, cell firing had broader spatial tuning; place, but not grid, cell firing was more directional; theta frequency increased less with running speed; whereas increases in firing rates with running speed and place and grid cells' theta phase precession were similar. These results suggest that the omni-directional place cell firing in R may require local-cues unavailable in VR, and that the scale of grid and place cell firing patterns, and theta frequency, reflect translational motion inferred from both virtual (visual and proprioceptive) and real (vestibular translation and extra-maze) cues. By contrast, firing rates and theta phase precession appear to reflect visual and proprioceptive cues alone. © 2018, Chen et al.
Firing-rate resonances in the peripheral auditory system of the cricket, Gryllus bimaculatus.
Rau, Florian; Clemens, Jan; Naumov, Victor; Hennig, R Matthias; Schreiber, Susanne
2015-11-01
In many communication systems, information is encoded in the temporal pattern of signals. For rhythmic signals that carry information in specific frequency bands, a neuronal system may profit from tuning its inherent filtering properties towards a peak sensitivity in the respective frequency range. The cricket Gryllus bimaculatus evaluates acoustic communication signals of both conspecifics and predators. The song signals of conspecifics exhibit a characteristic pulse pattern that contains only a narrow range of modulation frequencies. We examined individual neurons (AN1, AN2, ON1) in the peripheral auditory system of the cricket for tuning towards specific modulation frequencies by assessing their firing-rate resonance. Acoustic stimuli with a swept-frequency envelope allowed an efficient characterization of the cells' modulation transfer functions. Some of the examined cells exhibited tuned band-pass properties. Using simple computational models, we demonstrate how different, cell-intrinsic or network-based mechanisms such as subthreshold resonances, spike-triggered adaptation, as well as an interplay of excitation and inhibition can account for the experimentally observed firing-rate resonances. Therefore, basic neuronal mechanisms that share negative feedback as a common theme may contribute to selectivity in the peripheral auditory pathway of crickets that is designed towards mate recognition and predator avoidance.
Noise focusing and the emergence of coherent activity in neuronal cultures
NASA Astrophysics Data System (ADS)
Orlandi, Javier G.; Soriano, Jordi; Alvarez-Lacalle, Enrique; Teller, Sara; Casademunt, Jaume
2013-09-01
At early stages of development, neuronal cultures in vitro spontaneously reach a coherent state of collective firing in a pattern of nearly periodic global bursts. Although understanding the spontaneous activity of neuronal networks is of chief importance in neuroscience, the origin and nature of that pulsation has remained elusive. By combining high-resolution calcium imaging with modelling in silico, we show that this behaviour is controlled by the propagation of waves that nucleate randomly in a set of points that is specific to each culture and is selected by a non-trivial interplay between dynamics and topology. The phenomenon is explained by the noise focusing effect--a strong spatio-temporal localization of the noise dynamics that originates in the complex structure of avalanches of spontaneous activity. Results are relevant to neuronal tissues and to complex networks with integrate-and-fire dynamics and metric correlations, for instance, in rumour spreading on social networks.
Propagating waves can explain irregular neural dynamics.
Keane, Adam; Gong, Pulin
2015-01-28
Cortical neurons in vivo fire quite irregularly. Previous studies about the origin of such irregular neural dynamics have given rise to two major models: a balanced excitation and inhibition model, and a model of highly synchronized synaptic inputs. To elucidate the network mechanisms underlying synchronized synaptic inputs and account for irregular neural dynamics, we investigate a spatially extended, conductance-based spiking neural network model. We show that propagating wave patterns with complex dynamics emerge from the network model. These waves sweep past neurons, to which they provide highly synchronized synaptic inputs. On the other hand, these patterns only emerge from the network with balanced excitation and inhibition; our model therefore reconciles the two major models of irregular neural dynamics. We further demonstrate that the collective dynamics of propagating wave patterns provides a mechanistic explanation for a range of irregular neural dynamics, including the variability of spike timing, slow firing rate fluctuations, and correlated membrane potential fluctuations. In addition, in our model, the distributions of synaptic conductance and membrane potential are non-Gaussian, consistent with recent experimental data obtained using whole-cell recordings. Our work therefore relates the propagating waves that have been widely observed in the brain to irregular neural dynamics. These results demonstrate that neural firing activity, although appearing highly disordered at the single-neuron level, can form dynamical coherent structures, such as propagating waves at the population level. Copyright © 2015 the authors 0270-6474/15/351591-15$15.00/0.
Regular Patterns in Cerebellar Purkinje Cell Simple Spike Trains
Shin, Soon-Lim; Hoebeek, Freek E.; Schonewille, Martijn; De Zeeuw, Chris I.; Aertsen, Ad; De Schutter, Erik
2007-01-01
Background Cerebellar Purkinje cells (PC) in vivo are commonly reported to generate irregular spike trains, documented by high coefficients of variation of interspike-intervals (ISI). In strong contrast, they fire very regularly in the in vitro slice preparation. We studied the nature of this difference in firing properties by focusing on short-term variability and its dependence on behavioral state. Methodology/Principal Findings Using an analysis based on CV2 values, we could isolate precise regular spiking patterns, lasting up to hundreds of milliseconds, in PC simple spike trains recorded in both anesthetized and awake rodents. Regular spike patterns, defined by low variability of successive ISIs, comprised over half of the spikes, showed a wide range of mean ISIs, and were affected by behavioral state and tactile stimulation. Interestingly, regular patterns often coincided in nearby Purkinje cells without precise synchronization of individual spikes. Regular patterns exclusively appeared during the up state of the PC membrane potential, while single ISIs occurred both during up and down states. Possible functional consequences of regular spike patterns were investigated by modeling the synaptic conductance in neurons of the deep cerebellar nuclei (DCN). Simulations showed that these regular patterns caused epochs of relatively constant synaptic conductance in DCN neurons. Conclusions/Significance Our findings indicate that the apparent irregularity in cerebellar PC simple spike trains in vivo is most likely caused by mixing of different regular spike patterns, separated by single long intervals, over time. We propose that PCs may signal information, at least in part, in regular spike patterns to downstream DCN neurons. PMID:17534435
Guehl, D; Pessiglione, M; François, C; Yelnik, J; Hirsch, E C; Féger, J; Tremblay, L
2003-06-01
The pathophysiology of parkinsonian tremor remains a matter of debate with two opposing hypotheses proposing a peripheral and a central origin, respectively. A central origin of tremor could arise either from a rhythmic activity of the internal segment of the globus pallidus (GPi) or from a structure such as the thalamus, outside the basal ganglia. In this study, single-unit recordings were performed in three 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-treated monkeys within the GPi and within three territories of the motor thalamus (delimited by their afferent inputs from the GPi, the substantia nigra and the cerebellum, respectively). For each recorded neuron, we compared the variations in firing rate and pattern in tremor and no tremor periods. Tremor either occurred spontaneously or was induced by external stimulation. When the animals entered into a tremor period we observed: (i) an increase in the mean firing rate in about half of the recorded neurons of the motor thalamus; and (ii), a change from an irregular to a rhythmic discharge within the range of tremor frequency (5-7 Hz) in about 10% of the recorded neurons of the motor thalamus (pallidal and cerebellar territories) and the GPi. Most of the thalamic neurons that exhibited a rhythmic discharge during tremor were found to be sensitive to external stimulation. Because the changes in firing rate occurred predominantly in the motor thalamus and not in the GPi, and because a fast rhythmic discharge of 10-15 Hz was frequently observed in the GPi and not in the motor thalamus, we conclude that thalamic activity is not a simple reproduction of basal ganglia output. Moreover, we suggest that thalamic processing of basal ganglia outputs could participate in the genesis of tremor, and that this thalamic processing could be influenced by sensory inputs and/or changes in attentional level elicited by external stimulation.
Pilkiw, Maryna; Insel, Nathan; Cui, Younghua; Finney, Caitlin; Morrissey, Mark D; Takehara-Nishiuchi, Kaori
2017-01-01
The lateral entorhinal cortex (LEC) is thought to bind sensory events with the environment where they took place. To compare the relative influence of transient events and temporally stable environmental stimuli on the firing of LEC cells, we recorded neuron spiking patterns in the region during blocks of a trace eyeblink conditioning paradigm performed in two environments and with different conditioning stimuli. Firing rates of some neurons were phasically selective for conditioned stimuli in a way that depended on which room the rat was in; nearly all neurons were tonically selective for environments in a way that depended on which stimuli had been presented in those environments. As rats moved from one environment to another, tonic neuron ensemble activity exhibited prospective information about the conditioned stimulus associated with the environment. Thus, the LEC formed phasic and tonic codes for event-environment associations, thereby accurately differentiating multiple experiences with overlapping features. DOI: http://dx.doi.org/10.7554/eLife.28611.001 PMID:28682237
Dong, Yi; Mihalas, Stefan; Russell, Alexander; Etienne-Cummings, Ralph; Niebur, Ernst
2012-01-01
When a neuronal spike train is observed, what can we say about the properties of the neuron that generated it? A natural way to answer this question is to make an assumption about the type of neuron, select an appropriate model for this type, and then to choose the model parameters as those that are most likely to generate the observed spike train. This is the maximum likelihood method. If the neuron obeys simple integrate and fire dynamics, Paninski, Pillow, and Simoncelli (2004) showed that its negative log-likelihood function is convex and that its unique global minimum can thus be found by gradient descent techniques. The global minimum property requires independence of spike time intervals. Lack of history dependence is, however, an important constraint that is not fulfilled in many biological neurons which are known to generate a rich repertoire of spiking behaviors that are incompatible with history independence. Therefore, we expanded the integrate and fire model by including one additional variable, a variable threshold (Mihalas & Niebur, 2009) allowing for history-dependent firing patterns. This neuronal model produces a large number of spiking behaviors while still being linear. Linearity is important as it maintains the distribution of the random variables and still allows for maximum likelihood methods to be used. In this study we show that, although convexity of the negative log-likelihood is not guaranteed for this model, the minimum of the negative log-likelihood function yields a good estimate for the model parameters, in particular if the noise level is treated as a free parameter. Furthermore, we show that a nonlinear function minimization method (r-algorithm with space dilation) frequently reaches the global minimum. PMID:21851282
Narusuye, Kenji; Nagahama, Tatsumi
2002-11-01
The Japanese species Aplysia kurodai feeds well on Ulva but rejects Gelidium with distinctive rhythmic patterned movements of the jaws and radula. We have previously shown that the patterned jaw movements during the rejection of Gelidium might be caused by long-lasting suppression of the monosynaptic transmission from the multiaction MA neurons to the jaw-closing (JC) motor neurons in the buccal ganglia and that the modulation might be directly produced by some cerebral neurons. In the present paper, we have identified a pair of catecholaminergic neurons (CBM1) in bilateral cerebral M clusters. The CBM1, probably equivalent to CBI-1 in A. californica, simultaneously produced monosynaptic excitatory postsynaptic potentials (EPSPs) in the MA and JC neurons. Firing of the CBM1 reduced the size of the inhibitory postsynaptic currents (IPSCs) in the JC neuron, evoked by the MA spikes, for >100 s. Moreover, the application of dopamine mimicked the CBM1 modulatory effects and pretreatment with a D1 antagonist, SCH23390, blocked the modulatory effects induced by dopamine. It could also largely block the modulatory effects induced by the CBM1 firing. These results suggest that the CBM1 may directly modulate the synaptic transmission by releasing dopamine. Moreover, we explored the CBM1 spike activity induced by taste stimulation of the animal lips with seaweed extracts by the use of calcium imaging. The calcium-sensitive dye, Calcium Green-1, was iontophoretically loaded into a cell body of the CBM1 using a microelectrode. Application of either Ulva or Gelidium extract to the lips increased the fluorescence intensity, but the Gelidium extract always induced a larger change in fluorescence compared with the Ulva extract, although the solution used induced the maximum spike responses of the CBM1 for each of the seaweed extracts. When the firing frequency of the CBM1 activity after taste stimulation was estimated, the Gelidium extract induced a spike activity of ~30 spikes/s while the Ulva extract induced an activity of ~20 spikes/s, consistent with the effective firing frequency (>25 spikes/s) for the synaptic modulation. These results suggest that the CBM1 may be one of the cerebral neurons contributing to the modulation of the basic feeding circuits for rejection induced by the taste of seaweeds such as Gelidium.
Control of Phasic Firing by a Background Leak Current in Avian Forebrain Auditory Neurons
Dagostin, André A.; Lovell, Peter V.; Hilscher, Markus M.; Mello, Claudio V.; Leão, Ricardo M.
2015-01-01
Central neurons express a variety of neuronal types and ion channels that promote firing heterogeneity among their distinct neuronal populations. Action potential (AP) phasic firing, produced by low-threshold voltage-activated potassium currents (VAKCs), is commonly observed in mammalian brainstem neurons involved in the processing of temporal properties of the acoustic information. The avian caudomedial nidopallium (NCM) is an auditory area analogous to portions of the mammalian auditory cortex that is involved in the perceptual discrimination and memorization of birdsong and shows complex responses to auditory stimuli We performed in vitro whole-cell patch-clamp recordings in brain slices from adult zebra finches (Taeniopygia guttata) and observed that half of NCM neurons fire APs phasically in response to membrane depolarizations, while the rest fire transiently or tonically. Phasic neurons fired APs faster and with more temporal precision than tonic and transient neurons. These neurons had similar membrane resting potentials, but phasic neurons had lower membrane input resistance and time constant. Surprisingly phasic neurons did not express low-threshold VAKCs, which curtailed firing in phasic mammalian brainstem neurons, having similar VAKCs to other NCM neurons. The phasic firing was determined not by VAKCs, but by the potassium background leak conductances, which was more prominently expressed in phasic neurons, a result corroborated by pharmacological, dynamic-clamp, and modeling experiments. These results reveal a new role for leak currents in generating firing diversity in central neurons. PMID:26696830
Distinct Mechanisms for Synchronization and Temporal Patterning of Odor-Encoding Neural Assemblies
NASA Astrophysics Data System (ADS)
MacLeod, Katrina; Laurent, Gilles
1996-11-01
Stimulus-evoked oscillatory synchronization of neural assemblies and temporal patterns of neuronal activity have been observed in many sensory systems, such as the visual and auditory cortices of mammals or the olfactory system of insects. In the locust olfactory system, single odor puffs cause the immediate formation of odor-specific neural assemblies, defined both by their transient synchronized firing and their progressive transformation over the course of a response. The application of an antagonist of ionotropic γ-aminobutyric acid (GABA) receptors to the first olfactory relay neuropil selectively blocked the fast inhibitory synapse between local and projection neurons. This manipulation abolished the synchronization of the odor-coding neural ensembles but did not affect each neuron's temporal response patterns to odors, even when these patterns contained periods of inhibition. Fast GABA-mediated inhibition, therefore, appears to underlie neuronal synchronization but not response tuning in this olfactory system. The selective desynchronization of stimulus-evoked oscillating neural assemblies in vivo is now possible, enabling direct functional tests of their significance for sensation and perception.
Spike Train Auto-Structure Impacts Post-Synaptic Firing and Timing-Based Plasticity
Scheller, Bertram; Castellano, Marta; Vicente, Raul; Pipa, Gordon
2011-01-01
Cortical neurons are typically driven by several thousand synapses. The precise spatiotemporal pattern formed by these inputs can modulate the response of a post-synaptic cell. In this work, we explore how the temporal structure of pre-synaptic inhibitory and excitatory inputs impact the post-synaptic firing of a conductance-based integrate and fire neuron. Both the excitatory and inhibitory input was modeled by renewal gamma processes with varying shape factors for modeling regular and temporally random Poisson activity. We demonstrate that the temporal structure of mutually independent inputs affects the post-synaptic firing, while the strength of the effect depends on the firing rates of both the excitatory and inhibitory inputs. In a second step, we explore the effect of temporal structure of mutually independent inputs on a simple version of Hebbian learning, i.e., hard bound spike-timing-dependent plasticity. We explore both the equilibrium weight distribution and the speed of the transient weight dynamics for different mutually independent gamma processes. We find that both the equilibrium distribution of the synaptic weights and the speed of synaptic changes are modulated by the temporal structure of the input. Finally, we highlight that the sensitivity of both the post-synaptic firing as well as the spike-timing-dependent plasticity on the auto-structure of the input of a neuron could be used to modulate the learning rate of synaptic modification. PMID:22203800
Hadzipasic, Muhamed; Ni, Weiming; Nagy, Maria; Steenrod, Natalie; McGinley, Matthew J.; Kaushal, Adi; Thomas, Eleanor; McCormick, David A.
2016-01-01
Amyotrophic lateral sclerosis (ALS) is a lethal neurodegenerative disease prominently featuring motor neuron (MN) loss and paralysis. A recent study using whole-cell patch clamp recording of MNs in acute spinal cord slices from symptomatic adult ALS mice showed that the fastest firing MNs are preferentially lost. To measure the in vivo effects of such loss, awake symptomatic-stage ALS mice performing self-initiated walking on a wheel were studied. Both single-unit extracellular recordings within spinal cord MN pools for lower leg flexor and extensor muscles and the electromyograms (EMGs) of the corresponding muscles were recorded. In the ALS mice, we observed absent or truncated high-frequency firing of MNs at the appropriate time in the step cycle and step-to-step variability of the EMG, as well as flexor-extensor coactivation. In turn, kinematic analysis of walking showed step-to-step variability of gait. At the MN level, the higher frequencies absent from recordings from mutant mice corresponded with the upper range of frequencies observed for fast-firing MNs in earlier slice measurements. These results suggest that, in SOD1-linked ALS mice, symptoms are a product of abnormal MN firing due at least in part to loss of neurons that fire at high frequency, associated with altered EMG patterns and hindlimb kinematics during gait. PMID:27821773
Dulka, Eden A; Moenter, Suzanne M
2017-11-01
Gonadotropin-releasing hormone (GnRH) neurons regulate reproduction though pulsatile hormone release. Disruption of GnRH release as measured via luteinizing hormone (LH) pulses occurs in polycystic ovary syndrome (PCOS), and in young hyperandrogenemic girls. In adult prenatally androgenized (PNA) mice, which exhibit many aspects of PCOS, increased LH is associated with increased GnRH neuron action potential firing. How GnRH neuron activity develops over the prepubertal period and whether this is altered by sex or prenatal androgen treatment are unknown. We hypothesized GnRH neurons are active before puberty and that this activity is sexually differentiated and altered by PNA. Dams were injected with dihydrotestosterone (DHT) on days 16 to 18 post copulation to generate PNA mice. Action potential firing of GFP-identified GnRH neurons in brain slices from 1-, 2-, 3-, and 4-week-old and adult mice was monitored. GnRH neurons were active at all ages tested. In control females, activity increased with age through 3 weeks, then decreased to adult levels. In contrast, activity did not change in PNA females and was reduced at 3 weeks. Activity was higher in control females than males from 2 to 3 weeks. PNA did not affect GnRH neuron firing rate in males at any age. Short-term action potential patterns were also affected by age and PNA treatment. GnRH neurons are thus typically more active during the prepubertal period than adulthood, and PNA reduces prepubertal activity in females. Prepubertal activity may play a role in establishing sexually differentiated neuronal networks upstream of GnRH neurons; androgen-induced changes during this time may contribute to the adult PNA, and possibly PCOS, phenotype. Copyright © 2017 Endocrine Society.
Synchronous behaviour in network model based on human cortico-cortical connections.
Protachevicz, Paulo Ricardo; Borges, Rafael Ribaski; Reis, Adriane da Silva; Borges, Fernando da Silva; Iarosz, Kelly Cristina; Caldas, Ibere Luiz; Lameu, Ewandson Luiz; Macau, Elbert Einstein Nehrer; Viana, Ricardo Luiz; Sokolov, Igor M; Ferrari, Fabiano A S; Kurths, Jürgen; Batista, Antonio Marcos
2018-06-22
We consider a network topology according to the cortico-cortical connec- tion network of the human brain, where each cortical area is composed of a random network of adaptive exponential integrate-and-fire neurons. Depending on the parameters, this neuron model can exhibit spike or burst patterns. As a diagnostic tool to identify spike and burst patterns we utilise the coefficient of variation of the neuronal inter-spike interval. In our neuronal network, we verify the existence of spike and burst synchronisation in different cortical areas. Our simulations show that the network arrangement, i.e., its rich-club organisation, plays an important role in the transition of the areas from desynchronous to synchronous behaviours. © 2018 Institute of Physics and Engineering in Medicine.
Falgairolle, Melanie; Puhl, Joshua G; Pujala, Avinash; Liu, Wenfang; O’Donovan, Michael J
2017-01-01
Motoneurons are traditionally viewed as the output of the spinal cord that do not influence locomotor rhythmogenesis. We assessed the role of motoneuron firing during ongoing locomotor-like activity in neonatal mice expressing archaerhopsin-3 (Arch), halorhodopsin (eNpHR), or channelrhodopsin-2 (ChR2) in Choline acetyltransferase neurons (ChAT+) or Arch in LIM-homeodomain transcription factor Isl1+ neurons. Illumination of the lumbar cord in mice expressing eNpHR or Arch in ChAT+ or Isl1+ neurons, depressed motoneuron discharge, transiently decreased the frequency, and perturbed the phasing of the locomotor-like rhythm. When the light was turned off motoneuron firing and locomotor frequency both transiently increased. These effects were not due to cholinergic neurotransmission, persisted during partial blockade of gap junctions and were mediated, in part, by AMPAergic transmission. In spinal cords expressing ChR2, illumination increased motoneuron discharge and transiently accelerated the rhythm. We conclude that motoneurons provide feedback to the central pattern generator (CPG) during drug-induced locomotor-like activity. DOI: http://dx.doi.org/10.7554/eLife.26622.001 PMID:28671548
Lu, Zhixin; Squires, Shane; Ott, Edward; Girvan, Michelle
2016-12-01
We study the firing dynamics of a discrete-state and discrete-time version of an integrate-and-fire neuronal network model with both excitatory and inhibitory neurons. When the integer-valued state of a neuron exceeds a threshold value, the neuron fires, sends out state-changing signals to its connected neurons, and returns to the resting state. In this model, a continuous phase transition from non-ceaseless firing to ceaseless firing is observed. At criticality, power-law distributions of avalanche size and duration with the previously derived exponents, -3/2 and -2, respectively, are observed. Using a mean-field approach, we show analytically how the critical point depends on model parameters. Our main result is that the combined presence of both inhibitory neurons and integrate-and-fire dynamics greatly enhances the robustness of critical power-law behavior (i.e., there is an increased range of parameters, including both sub- and supercritical values, for which several decades of power-law behavior occurs).
Neural correlates for angular head velocity in the rat dorsal tegmental nucleus
NASA Technical Reports Server (NTRS)
Bassett, J. P.; Taube, J. S.; Oman, C. M. (Principal Investigator)
2001-01-01
Many neurons in the rat lateral mammillary nuclei (LMN) fire selectively in relation to the animal's head direction (HD) in the horizontal plane independent of the rat's location or behavior. One hypothesis of how this representation is generated and updated is via subcortical projections from the dorsal tegmental nucleus (DTN). Here we report the type of activity in DTN neurons. The majority of cells (75%) fired as a function of the rat's angular head velocity (AHV). Cells exhibited one of two types of firing patterns: (1) symmetric, in which the firing rate was positively correlated with AHV during head turns in both directions, and (2) asymmetric, in which the firing rate was positively correlated with head turns in one direction and correlated either negatively or not at all in the opposite direction. In addition to modulation by AHV, some of the AHV cells (40.1%) were weakly modulated by the rat's linear velocity, and a smaller number were modulated by HD (11%) or head pitch (15.9%). Autocorrelation analyses indicated that with the head stationary, AHV cells displayed irregular discharge patterns. Because afferents from the DTN are the major source of information projecting to the LMN, these results suggest that AHV information from the DTN plays a significant role in generating the HD signal in LMN. A model is proposed showing how DTN AHV cells can generate and update the LMN HD cell signal.
On a phase diagram for random neural networks with embedded spike timing dependent plasticity.
Turova, Tatyana S; Villa, Alessandro E P
2007-01-01
This paper presents an original mathematical framework based on graph theory which is a first attempt to investigate the dynamics of a model of neural networks with embedded spike timing dependent plasticity. The neurons correspond to integrate-and-fire units located at the vertices of a finite subset of 2D lattice. There are two types of vertices, corresponding to the inhibitory and the excitatory neurons. The edges are directed and labelled by the discrete values of the synaptic strength. We assume that there is an initial firing pattern corresponding to a subset of units that generate a spike. The number of activated externally vertices is a small fraction of the entire network. The model presented here describes how such pattern propagates throughout the network as a random walk on graph. Several results are compared with computational simulations and new data are presented for identifying critical parameters of the model.
Reducing Neuronal Networks to Discrete Dynamics
Terman, David; Ahn, Sungwoo; Wang, Xueying; Just, Winfried
2008-01-01
We consider a general class of purely inhibitory and excitatory-inhibitory neuronal networks, with a general class of network architectures, and characterize the complex firing patterns that emerge. Our strategy for studying these networks is to first reduce them to a discrete model. In the discrete model, each neuron is represented as a finite number of states and there are rules for how a neuron transitions from one state to another. In this paper, we rigorously demonstrate that the continuous neuronal model can be reduced to the discrete model if the intrinsic and synaptic properties of the cells are chosen appropriately. In a companion paper [1], we analyze the discrete model. PMID:18443649
Rat globus pallidus neurons: functional classification and effects of dopamine depletion.
Karain, Brad; Xu, Dan; Bellone, John A; Hartman, Richard E; Shi, Wei-Xing
2015-01-01
The rat globus pallidus (GP) is homologous to the primate GP externus. Studies with injectable anesthetics suggest that GP neurons can be classified into Type-I and Type-II cells based on extracellularly recorded spike shape, or positively coupled (PC), negatively coupled (NC), and uncoupled (UC) cells based on functional connectivity with the cortex. In this study, we examined the electrophysiology of rat GP neurons using the inhalational anesthetic isoflurane which offers more constant and easily regulated levels of anesthesia than injectable anesthetics. In 130 GP neurons recorded using small-tip glass electrodes (<1 μm), all but one fired Type-II spikes (positive/negative waveform). Type-I cells were unlikely to be inhibited by isoflurane since all GP neurons also fired Type-II spikes under ketamine-induced anesthesia. When recorded with large-tip electrodes (∼2 μm), however, over 70% of GP neurons exhibited Type-I spikes (negative/positive waveform). These results suggest that the spike shape, recorded extracellularly, varies depending on the electrode used and is not reliable in distinguishing Type-I and Type-II neurons. Using dual-site recording, 40% of GP neurons were identified as PC cells, 17.5% NC cells, and 42.5% UC cells. The three subtypes also differed significantly in firing rate and pattern. Lesions of dopamine neurons increased the number of NC cells, decreased that of UC cells, and significantly shifted the phase relationship between PC cells and the cortex. These results support the presence of GP neuron subtypes and suggest that each subtype plays a different role in the pathophysiology of Parkinson's disease. Synapse 69:41-51, 2015. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.
Synchronization transition in neuronal networks composed of chaotic or non-chaotic oscillators.
Xu, Kesheng; Maidana, Jean Paul; Castro, Samy; Orio, Patricio
2018-05-30
Chaotic dynamics has been shown in the dynamics of neurons and neural networks, in experimental data and numerical simulations. Theoretical studies have proposed an underlying role of chaos in neural systems. Nevertheless, whether chaotic neural oscillators make a significant contribution to network behaviour and whether the dynamical richness of neural networks is sensitive to the dynamics of isolated neurons, still remain open questions. We investigated synchronization transitions in heterogeneous neural networks of neurons connected by electrical coupling in a small world topology. The nodes in our model are oscillatory neurons that - when isolated - can exhibit either chaotic or non-chaotic behaviour, depending on conductance parameters. We found that the heterogeneity of firing rates and firing patterns make a greater contribution than chaos to the steepness of the synchronization transition curve. We also show that chaotic dynamics of the isolated neurons do not always make a visible difference in the transition to full synchrony. Moreover, macroscopic chaos is observed regardless of the dynamics nature of the neurons. However, performing a Functional Connectivity Dynamics analysis, we show that chaotic nodes can promote what is known as multi-stable behaviour, where the network dynamically switches between a number of different semi-synchronized, metastable states.
Low- and high-threshold primary afferent inputs to spinal lamina III antenna-type neurons.
Fernandes, Elisabete C; Santos, Ines C; Kokai, Eva; Luz, Liliana L; Szucs, Peter; Safronov, Boris V
2018-06-21
and non-nociceptive sensory information. Antenna-type neurons with cell bodies located in lamina III and large dendritic trees extending from the superficial lamina I to deep lamina IV are best shaped for the integration of a wide variety of inputs arising from primary afferent fibers and intrinsic spinal circuitries. While the somatodendritic morphology, the hallmark of antenna neurons, has been well studied, little is still known about the axon structure and basic physiological properties of these cells. Here we did whole-cell recordings in a rat (P9-P12) spinal cord preparation with attached dorsal roots to examine the axon course, intrinsic firing properties and primary afferent inputs of antenna cells. Nine antenna cells were identified from a large sample of biocytin-filled lamina III neurons (n = 46). Axon of antenna cells showed intensive branching in laminae III-IV and, in half of the cases, issued dorsally directed collaterals reaching lamina I. Antenna cells exhibited tonic and rhythmic firing patterns; single spikes were followed by hyper- or depolarization. The neurons received monosynaptic inputs from the low-threshold Aβ afferents, Aδ afferents as well as from the high-threshold Aδ and C afferents. When selectively activated, C-fiber-driven mono- and polysynaptic EPSPs were sufficiently strong to evoke firing in the neurons. Thus, lamina III antenna neurons integrate low-threshold and nociceptive high-threshold primary afferent inputs, and can function as wide-dynamic-range neurons able to directly connect deep dorsal horn with the major nociceptive projection area lamina I.
Zerlaut, Yann; Chemla, Sandrine; Chavane, Frederic; Destexhe, Alain
2018-02-01
Voltage-sensitive dye imaging (VSDi) has revealed fundamental properties of neocortical processing at macroscopic scales. Since for each pixel VSDi signals report the average membrane potential over hundreds of neurons, it seems natural to use a mean-field formalism to model such signals. Here, we present a mean-field model of networks of Adaptive Exponential (AdEx) integrate-and-fire neurons, with conductance-based synaptic interactions. We study a network of regular-spiking (RS) excitatory neurons and fast-spiking (FS) inhibitory neurons. We use a Master Equation formalism, together with a semi-analytic approach to the transfer function of AdEx neurons to describe the average dynamics of the coupled populations. We compare the predictions of this mean-field model to simulated networks of RS-FS cells, first at the level of the spontaneous activity of the network, which is well predicted by the analytical description. Second, we investigate the response of the network to time-varying external input, and show that the mean-field model predicts the response time course of the population. Finally, to model VSDi signals, we consider a one-dimensional ring model made of interconnected RS-FS mean-field units. We found that this model can reproduce the spatio-temporal patterns seen in VSDi of awake monkey visual cortex as a response to local and transient visual stimuli. Conversely, we show that the model allows one to infer physiological parameters from the experimentally-recorded spatio-temporal patterns.
Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.
Teka, Wondimu W; Upadhyay, Ranjit Kumar; Mondal, Argha
2017-09-01
Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.
Neural correlates of object-in-place learning in hippocampus and prefrontal cortex.
Kim, Jangjin; Delcasso, Sébastien; Lee, Inah
2011-11-23
Hippocampus and prefrontal cortex (PFC) process spatiotemporally discrete events while maintaining goal-directed task demands. Although some studies have reported that neural activities in the two regions are coordinated, such observations have rarely been reported in an object-place paired-associate (OPPA) task in which animals must learn an object-in-place rule. In this study, we recorded single units and local field potentials simultaneously from the CA1 subfield of the hippocampus and PFC as rats learned that Object A, but not Object B, was rewarded in Place 1, but not in Place 2 (vice versa for Object B). Both hippocampus and PFC are required for normal performance in this task. PFC neurons fired in association with the regularity of the occurrence of a certain type of event independent of space, whereas neuronal firing in CA1 was spatially localized for representing a discrete place. Importantly, the differential firing patterns were observed in tandem with common learning-related changes in both regions. Specifically, once OPPA learning occurred and rats used an object-in-place strategy, (1) both CA1 and PFC neurons exhibited spatially more similar and temporally more synchronized firing patterns, (2) spiking activities in both regions were more phase locked to theta rhythms, and (3) CA1-medial PFC coherence in theta oscillation was maximal before entering a critical place for decision making. The results demonstrate differential as well as common neural dynamics between hippocampus and PFC in acquiring the OPPA task and strongly suggest that both regions form a unified functional network for processing an episodic event.
Neural correlates of object-in-place learning in hippocampus and prefrontal cortex
Kim, Jangjin; Delcasso, Sébastien; Lee, Inah
2011-01-01
Hippocampus and prefrontal cortex (PFC) process spatiotemporally discrete events while maintaining goal-directed task demands. Although some studies have reported that neural activities in the two regions are coordinated, such observations have rarely been reported in an object-place paired-associate (OPPA) task in which animals must learn an object-in-place rule. In this study, we recorded single units and local field potentials simultaneously from the CA1 subfield of the hippocampus and PFC as rats learned that object A, but not object B, was rewarded in place 1, but not in place 2 (vice versa for object B). Both hippocampus and PFC are required for normal performance in this task. PFC neurons fired in association with the regularity of the occurrence of a certain type of event independent of space, whereas neuronal firing in CA1 was spatially localized for representing a discrete place. Importantly, the differential firing patterns were observed in tandem with common learning-related changes in both regions. Specifically, once OPPA learning occurred and rats used an object-in-place strategy, (i) both CA1 and PFC neurons exhibited spatially more similar and temporally more synchronized firing patterns, (ii) spiking activities in both regions were more phase-locked to theta rhythms, (iii) CA1-mPFC coherence in theta oscillation was maximal before entering a critical place for decision making. The results demonstrate differential as well as common neural dynamics between hippocampus and PFC in acquiring the OPPA task and strongly suggest that both regions form a unified functional network for processing an episodic event. PMID:22114269
Position-dependent patterning of spontaneous action potentials in immature cochlear inner hair cells
Johnson, Stuart L.; Eckrich, Tobias; Kuhn, Stephanie; Zampini, Valeria; Franz, Christoph; Ranatunga, Kishani M.; Roberts, Terri P.; Masetto, Sergio; Knipper, Marlies; Kros, Corné J.; Marcotti, Walter
2011-01-01
Spontaneous action potential activity is crucial for mammalian sensory system development. In the auditory system, patterned firing activity has been observed in immature spiral ganglion cells and brain-stem neurons and is likely to depend on cochlear inner hair cell (IHC) action potentials. It remains uncertain whether spiking activity is intrinsic to developing IHCs and whether it shows patterning. We found that action potentials are intrinsically generated by immature IHCs of altricial rodents and that apical IHCs exhibit bursting activity as opposed to more sustained firing in basal cells. We show that the efferent neurotransmitter ACh, by fine-tuning the IHC’s resting membrane potential (Vm), is crucial for the bursting pattern in apical cells. Endogenous extracellular ATP also contributes to the Vm of apical and basal IHCs by activating SK2 channels. We hypothesize that the difference in firing pattern along the cochlea instructs the tonotopic differentiation of IHCs and auditory pathway. PMID:21572434
Johnson, Stuart L; Eckrich, Tobias; Kuhn, Stephanie; Zampini, Valeria; Franz, Christoph; Ranatunga, Kishani M; Roberts, Terri P; Masetto, Sergio; Knipper, Marlies; Kros, Corné J; Marcotti, Walter
2011-06-01
Spontaneous action potential activity is crucial for mammalian sensory system development. In the auditory system, patterned firing activity has been observed in immature spiral ganglion and brain-stem neurons and is likely to depend on cochlear inner hair cell (IHC) action potentials. It remains uncertain whether spiking activity is intrinsic to developing IHCs and whether it shows patterning. We found that action potentials were intrinsically generated by immature IHCs of altricial rodents and that apical IHCs showed bursting activity as opposed to more sustained firing in basal cells. We show that the efferent neurotransmitter acetylcholine fine-tunes the IHC's resting membrane potential (V(m)), and as such is crucial for the bursting pattern in apical cells. Endogenous extracellular ATP also contributes to the V(m) of apical and basal IHCs by triggering small-conductance Ca(2+)-activated K(+) (SK2) channels. We propose that the difference in firing pattern along the cochlea instructs the tonotopic differentiation of IHCs and auditory pathway.
Chen, Jessie; Reitzen, Shari D; Kohlenstein, Jane B; Gardner, Esther P
2009-12-01
Studies of hand manipulation neurons in posterior parietal cortex of monkeys suggest that their spike trains represent objects by the hand postures needed for grasping or by the underlying patterns of muscle activation. To analyze the role of hand kinematics and object properties in a trained prehension task, we correlated the firing rates of neurons in anterior area 5 with hand behaviors as monkeys grasped and lifted knobs of different shapes and locations in the workspace. Trials were divided into four classes depending on the approach trajectory: forward, lateral, and local approaches, and regrasps. The task factors controlled by the animal-how and when he used the hand-appeared to play the principal roles in modulating firing rates of area 5 neurons. In all, 77% of neurons studied (58/75) showed significant effects of approach style on firing rates; 80% of the population responded at higher rates and for longer durations on forward or lateral approaches that included reaching, wrist rotation, and hand preshaping prior to contact, but only 13% distinguished the direction of reach. The higher firing rates in reach trials reflected not only the arm movements needed to direct the hand to the target before contact, but persisted through the contact, grasp, and lift stages. Moreover, the approach style exerted a stronger effect on firing rates than object features, such as shape and location, which were distinguished by half of the population. Forty-three percent of the neurons signaled both the object properties and the hand actions used to acquire them. However, the spread in firing rates evoked by each knob on reach and no-reach trials was greater than distinctions between different objects grasped with the same approach style. Our data provide clear evidence for synergies between reaching and grasping that may facilitate smooth, coordinated actions of the arm and hand.
Hull, Michael J.; Soffe, Stephen R.; Willshaw, David J.; Roberts, Alan
2015-01-01
Gap junctions between fine unmyelinated axons can electrically couple groups of brain neurons to synchronise firing and contribute to rhythmic activity. To explore the distribution and significance of electrical coupling, we modelled a well analysed, small population of brainstem neurons which drive swimming in young frog tadpoles. A passive network of 30 multicompartmental neurons with unmyelinated axons was used to infer that: axon-axon gap junctions close to the soma gave the best match to experimentally measured coupling coefficients; axon diameter had a strong influence on coupling; most neurons were coupled indirectly via the axons of other neurons. When active channels were added, gap junctions could make action potential propagation along the thin axons unreliable. Increased sodium and decreased potassium channel densities in the initial axon segment improved action potential propagation. Modelling suggested that the single spike firing to step current injection observed in whole-cell recordings is not a cellular property but a dynamic consequence of shunting resulting from electrical coupling. Without electrical coupling, firing of the population during depolarising current was unsynchronised; with coupling, the population showed synchronous recruitment and rhythmic firing. When activated instead by increasing levels of modelled sensory pathway input, the population without electrical coupling was recruited incrementally to unpatterned activity. However, when coupled, the population was recruited all-or-none at threshold into a rhythmic swimming pattern: the tadpole “decided” to swim. Modelling emphasises uncertainties about fine unmyelinated axon physiology but, when informed by biological data, makes general predictions about gap junctions: locations close to the soma; relatively small numbers; many indirect connections between neurons; cause of action potential propagation failure in fine axons; misleading alteration of intrinsic firing properties. Modelling also indicates that electrical coupling within a population can synchronize recruitment of neurons and their pacemaker firing during rhythmic activity. PMID:25954930
Cymerblit-Sabba, Adi; Schiller, Yitzhak
2012-03-01
The prevailing view of epileptic seizures is that they are caused by increased hypersynchronous activity in the cortical network. However, this view is based mostly on electroencephalography (EEG) recordings that do not directly monitor neuronal synchronization of action potential firing. In this study, we used multielectrode single-unit recordings from the hippocampus to investigate firing of individual CA1 neurons and directly monitor synchronization of action potential firing between neurons during the different ictal phases of chemoconvulsant-induced epileptic seizures in vivo. During the early phase of seizures manifesting as low-amplitude rhythmic β-electrocorticography (ECoG) activity, the firing frequency of most neurons markedly increased. To our surprise, the average overall neuronal synchronization as measured by the cross-correlation function was reduced compared with control conditions with ~60% of neuronal pairs showing no significant correlated firing. However, correlated firing was not uniform and a minority of neuronal pairs showed a high degree of correlated firing. Moreover, during the early phase of seizures, correlated firing between 9.8 ± 5.1% of all stably recorded pairs increased compared with control conditions. As seizures progressed and high-frequency ECoG polyspikes developed, the firing frequency of neurons further increased and enhanced correlated firing was observed between virtually all neuronal pairs. These findings indicated that epileptic seizures represented a hyperactive state with widespread increase in action potential firing. Hypersynchrony also characterized seizures. However, it initially developed in a small subset of neurons and gradually spread to involve the entire cortical network only in the later more intense ictal phases.
Nuding, Sarah C.; Segers, Lauren S.; Iceman, Kimberly E.; O'Connor, Russell; Dean, Jay B.; Bolser, Donald C.; Baekey, David M.; Dick, Thomas E.; Shannon, Roger; Morris, Kendall F.
2015-01-01
Hyperventilation is a common feature of disordered breathing. Apnea ensues if CO2 drive is sufficiently reduced. We tested the hypothesis that medullary raphé, ventral respiratory column (VRC), and pontine neurons have functional connectivity and persistent or evoked activities appropriate for roles in the suppression of drive and rhythm during hyperventilation and apnea. Phrenic nerve activity, arterial blood pressure, end-tidal CO2, and other parameters were monitored in 10 decerebrate, vagotomized, neuromuscularly-blocked, and artificially ventilated cats. Multielectrode arrays recorded spiking activity of 649 neurons. Loss and return of rhythmic activity during passive hyperventilation to apnea were identified with the S-transform. Diverse fluctuating activity patterns were recorded in the raphé-pontomedullary respiratory network during the transition to hypocapnic apnea. The firing rates of 160 neurons increased during apnea; the rates of 241 others decreased or stopped. VRC inspiratory neurons were usually the last to cease firing or lose rhythmic activity during the transition to apnea. Mayer wave-related oscillations (0.04–0.1 Hz) in firing rate were also disrupted during apnea. Four-hundred neurons (62%) were elements of pairs with at least one hyperventilation-responsive neuron and a correlational signature of interaction identified by cross-correlation or gravitational clustering. Our results support a model with distinct groups of chemoresponsive raphé neurons contributing to hypocapnic apnea through parallel processes that incorporate disfacilitation and active inhibition of inspiratory motor drive by expiratory neurons. During apnea, carotid chemoreceptors can evoke rhythm reemergence and an inspiratory shift in the balance of reciprocal inhibition via suppression of ongoing tonic expiratory neuron activity. PMID:26203111
Three-dimensional chimera patterns in networks of spiking neuron oscillators
NASA Astrophysics Data System (ADS)
Kasimatis, T.; Hizanidis, J.; Provata, A.
2018-05-01
We study the stable spatiotemporal patterns that arise in a three-dimensional (3D) network of neuron oscillators, whose dynamics is described by the leaky integrate-and-fire (LIF) model. More specifically, we investigate the form of the chimera states induced by a 3D coupling matrix with nonlocal topology. The observed patterns are in many cases direct generalizations of the corresponding two-dimensional (2D) patterns, e.g., spheres, layers, and cylinder grids. We also find cylindrical and "cross-layered" chimeras that do not have an equivalent in 2D systems. Quantitative measures are calculated, such as the ratio of synchronized and unsynchronized neurons as a function of the coupling range, the mean phase velocities, and the distribution of neurons in mean phase velocities. Based on these measures, the chimeras are categorized in two families. The first family of patterns is observed for weaker coupling and exhibits higher mean phase velocities for the unsynchronized areas of the network. The opposite holds for the second family, where the unsynchronized areas have lower mean phase velocities. The various measures demonstrate discontinuities, indicating criticality as the parameters cross from the first family of patterns to the second.
Andrada, Jason; Livingston, Preetha; Lee, Bong Jae; Antognini, Joseph
2012-03-01
The sites where anesthetics produce unconsciousness are not well understood. Likely sites include the cerebral cortex, thalamus, and reticular formation. We examined the effects of propofol and etomidate on neuronal function in the cortex, thalamus, and reticular formation in intact animals. Five cats had a recording well and electroencephalogram screws placed under anesthesia. After a 5-day recovery period, the cats were repeatedly studied 3 to 4 times per week. Neuronal (single-unit) activity in the cerebral cortex (areas 7, 18 and 19), thalamus (ventral posterolateral and ventral posteromedial nuclei and medial geniculate body), and reticular formation (mesencephalic reticular nucleus and central tegmental field) was recorded before, during, and after infusion of either propofol or etomidate. Cortical neuronal action potentials were analyzed separately as either regular spiking neurons or fast spiking neurons. Propofol and etomidate decreased the spontaneous firing rate of cortical neurons by 37% to 41%; fast spiking neurons and regular spiking neurons were similarly affected by the anesthetics. The neuronal firing rate in the thalamus and reticular formation decreased 30% to 49% by propofol and etomidate. The electroencephalogram shifted from a low-amplitude, high-frequency pattern to a high-amplitude, low-frequency pattern during drug infusion suggesting an anesthetic effect; peak power occurred at 12 to 13 Hz during propofol infusion. There were 2 major peaks during etomidate anesthesia: one at 12 to 14 Hz and another at 7 to 8 Hz. The cats were heavily sedated, with depressed corneal and whisker reflexes; withdrawal to noxious stimulation remained intact. These data show that neurons in the cortex, thalamus, and reticular formation are similarly depressed by propofol and etomidate. Although anesthetic depression of neuronal activity likely contributes to anesthetic-induced unconsciousness, further work is needed to determine how anesthetic effects at these sites interact to produce unconsciousness.
Representation of 3-Dimenstional Objects by the Rat Perirhinal Cortex
Burke, S.N.; Maurer, A.P.; Hartzell, A.L.; Nematollahi, S.; Uprety, A.; Wallace, J.L.; Barnes, C.A.
2012-01-01
The perirhinal cortex (PRC) is known to play an important role in object recognition. Little is known, however, regarding the activity of PRC neurons during the presentation of stimuli that are commonly used for recognition memory tasks in rodents, that is, 3-dimensional objects. Rats in the present study were exposed to 3-dimensional objects while they traversed a circular track for food reward. Under some behavioral conditions the track contained novel objects, familiar objects, or no objects. Approximately 38% of PRC neurons demonstrated ‘object fields’ (a selective increase in firing at the location of one or more objects). Although the rats spent more time exploring the objects when they were novel compared to familiar, indicating successful recognition memory, the proportion of object fields and the firing rates of PRC neurons were not affected by the rats’ previous experience with the objects. Together these data indicate that the activity of PRC cells is powerfully affected by the presence of objects while animals navigate through an environment, but under these conditions, the firing patterns are not altered by the relative novelty of objects during successful object recognition. PMID:22987680
Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli
NASA Technical Reports Server (NTRS)
Paulin, M. G.; Hoffman, L. F.
1999-01-01
We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.
A systematic approach to selecting task relevant neurons.
Kahn, Kevin; Saxena, Shreya; Eskandar, Emad; Thakor, Nitish; Schieber, Marc; Gale, John T; Averbeck, Bruno; Eden, Uri; Sarma, Sridevi V
2015-04-30
Since task related neurons cannot be specifically targeted during surgery, a critical decision to make is to select which neurons are task-related when performing data analysis. Including neurons unrelated to the task degrade decoding accuracy and confound neurophysiological results. Traditionally, task-related neurons are selected as those with significant changes in firing rate when a stimulus is applied. However, this assumes that neurons' encoding of stimuli are dominated by their firing rate with little regard to temporal dynamics. This paper proposes a systematic approach for neuron selection, which uses a likelihood ratio test to capture the contribution of stimulus to spiking activity while taking into account task-irrelevant intrinsic dynamics that affect firing rates. This approach is denoted as the model deterioration excluding stimulus (MDES) test. MDES is compared to firing rate selection in four case studies: a simulation, a decoding example, and two neurophysiology examples. The MDES rankings in the simulation match closely with ideal rankings, while firing rate rankings are skewed by task-irrelevant parameters. For decoding, 95% accuracy is achieved using the top 8 MDES-ranked neurons, while the top 12 firing-rate ranked neurons are needed. In the neurophysiological examples, MDES matches published results when firing rates do encode salient stimulus information, and uncovers oscillatory modulations in task-related neurons that are not captured when neurons are selected using firing rates. These case studies illustrate the importance of accounting for intrinsic dynamics when selecting task-related neurons and following the MDES approach accomplishes that. MDES selects neurons that encode task-related information irrespective of these intrinsic dynamics which can bias firing rate based selection. Copyright © 2015 Elsevier B.V. All rights reserved.
Heterogeneous neuronal firing patterns during interictal epileptiform discharges in the human cortex
Keller, Corey J.; Truccolo, Wilson; Gale, John T.; Eskandar, Emad; Thesen, Thomas; Carlson, Chad; Devinsky, Orrin; Kuzniecky, Ruben; Doyle, Werner K.; Madsen, Joseph R.; Schomer, Donald L.; Mehta, Ashesh D.; Brown, Emery N.; Hochberg, Leigh R.; Ulbert, István; Halgren, Eric
2010-01-01
Epileptic cortex is characterized by paroxysmal electrical discharges. Analysis of these interictal discharges typically manifests as spike–wave complexes on electroencephalography, and plays a critical role in diagnosing and treating epilepsy. Despite their fundamental importance, little is known about the neurophysiological mechanisms generating these events in human focal epilepsy. Using three different systems of microelectrodes, we recorded local field potentials and single-unit action potentials during interictal discharges in patients with medically intractable focal epilepsy undergoing diagnostic workup for localization of seizure foci. We studied 336 single units in 20 patients. Ten different cortical areas and the hippocampus, including regions both inside and outside the seizure focus, were sampled. In three of these patients, high density microelectrode arrays simultaneously recorded between 43 and 166 single units from a small (4 mm × 4 mm) patch of cortex. We examined how the firing rates of individual neurons changed during interictal discharges by determining whether the firing rate during the event was the same, above or below a median baseline firing rate estimated from interictal discharge-free periods (Kruskal–Wallis one-way analysis, P<0.05). Only 48% of the recorded units showed such a modulation in firing rate within 500 ms of the discharge. Units modulated during the discharge exhibited significantly higher baseline firing and bursting rates than unmodulated units. As expected, many units (27% of the modulated population) showed an increase in firing rate during the fast segment of the discharge (±35 ms from the peak of the discharge), while 50% showed a decrease during the slow wave. Notably, in direct contrast to predictions based on models of a pure paroxysmal depolarizing shift, 7.7% of modulated units recorded in or near the seizure focus showed a decrease in activity well ahead (0–300 ms) of the discharge onset, while 12.2% of units increased in activity in this period. No such pre-discharge changes were seen in regions well outside the seizure focus. In many recordings there was also a decrease in broadband field potential activity during this same pre-discharge period. The different patterns of interictal discharge-modulated firing were classified into more than 15 different categories. This heterogeneity in single unit activity was present within small cortical regions as well as inside and outside the seizure onset zone, suggesting that interictal epileptiform activity in patients with epilepsy is not a simple paroxysm of hypersynchronous excitatory activity, but rather represents an interplay of multiple distinct neuronal types within complex neuronal networks. PMID:20511283
Starr, Philip A; Kang, Gail A; Heath, Susan; Shimamoto, Shoichi; Turner, Robert S
2008-05-01
Chorea is the predominant motor manifestation in the early symptomatic phase of adult onset Huntington's disease (HD). Pathologically, this stage is marked by differential loss of striatal neurons contributing to the indirect pathway. This pattern of neuronal loss predicts decreased neuronal firing rates in GPi and increased firing rates in GPe, the opposite of the changes in firing rate known to occur in Parkinson's disease (PD). We present single-unit discharge characteristics (33 neurons) observed in an awake patient with HD (41 CAG repeats) undergoing microelectrode guided surgery for pallidal deep brain stimulation. Pallidal single-unit activity at "rest" and during voluntary movement was discriminated off line by principal component analysis and evaluated with respect to discharge rate, bursting, and oscillatory activity in the 0-200 Hz range. 24 GPi and 9 GPe units were studied, and compared with 132 GPi and 50 GPe units from 14 patients with PD. The mean (+/-SEM) spontaneous discharge rate for HD was 58+/-4 for GPi and 73+/-5 for GPe. This contrasted with discharge rates in PD of 95+/-2 for GPi and 57+/-3 for GPe. HD GPi units showed more bursting than PD GPi units but much less oscillatory activity in the 2-35 Hz frequency range at rest. These findings are consistent with selective early loss of striatal cells originating the indirect pathway.
The hypothalamic slice approach to neuroendocrinology.
Hatton, G I
1983-07-01
The magnocellular peptidergic cells of the supraoptic and paraventricular nuclei comprise much of what is known as the hypothalamo-neurohypophysial system and is involved in several functions, including body fluid balance, parturition and lactation. While we have learned much from experiments in vivo, they have not produced a clear understanding of some of the crucial features associated with the functioning of this system. In particular, questions relating to the osmosensitivity of magnocellular neurones and the mechanism(s) by which their characteristic firing patterns are generated have not been answered using the older approaches. Electrophysiological studies with brain slices present direct evidence for osmosensitivity, and perhaps even osmoreceptivity, of magnocellular neurones. Other evidence indicates that the phasic bursting patterns of activity associated with vasopressin-releasing neurones (a) occur in the absence of patterned chemical synaptic input, (b) may be modulated by electrotonic conduction across gap junctions connecting magnocellular neurones and (c) are likely to be generated by endogenous membrane currents. These results make untenable the formerly held idea that phasic bursting activity is dependent upon recurrent synaptic inhibition.
Daneshzand, Mohammad; Faezipour, Miad; Barkana, Buket D.
2017-01-01
Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS devices. PMID:28848417
Daneshzand, Mohammad; Faezipour, Miad; Barkana, Buket D
2017-01-01
Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS devices.
Edgerton, Jeremy R.; Jaeger, Dieter
2011-01-01
Correlated firing among populations of neurons is present throughout the brain and is often rhythmic in nature, observable as an oscillatory fluctuation in the local field potential. Although rhythmic population activity is believed to be critical for normal function in many brain areas, synchronized neural oscillations are associated with disease states in other cases. In the globus pallidus (GP in rodents, homolog of the primate GPe), pairs of neurons generally have uncorrelated firing in normal animals despite an anatomical organization suggesting that they should receive substantial common input. By contrast, correlated and rhythmic GP firing is observed in animal models of Parkinson's disease (PD). Based in part on these findings it has been proposed that an important part of basal ganglia function is active decorrelation, whereby redundant information is compressed. Mechanisms that implement active decorrelation, and changes that cause it to fail in PD, are subjects of great interest. Rat GP neurons express fast, transient voltage-dependent sodium channels (NaF channels) in their dendrites, with the expression level being highest near asymmetric synapses. We recently showed that the dendritic NaF density strongly influences the responsiveness of model GP neurons to synchronous excitatory inputs. In the present study we use rat GP neuron models to show that dendritic NaF channel expression is a potential cellular mechanism of active decorrelation. We further show that model neurons with lower dendritic NaF channel expression have a greater tendency to phase lock with oscillatory synaptic input patterns like those observed in PD. PMID:21795543
Neuronal plasticity and thalamocortical sleep and waking oscillations
Timofeev, Igor
2011-01-01
Throughout life, thalamocortical (TC) network alternates between activated states (wake or rapid eye movement sleep) and slow oscillatory state dominating slow-wave sleep. The patterns of neuronal firing are different during these distinct states. I propose that due to relatively regular firing, the activated states preset some steady state synaptic plasticity and that the silent periods of slow-wave sleep contribute to a release from this steady state synaptic plasticity. In this respect, I discuss how states of vigilance affect short-, mid-, and long-term synaptic plasticity, intrinsic neuronal plasticity, as well as homeostatic plasticity. Finally, I suggest that slow oscillation is intrinsic property of cortical network and brain homeostatic mechanisms are tuned to use all forms of plasticity to bring cortical network to the state of slow oscillation. However, prolonged and profound shift from this homeostatic balance could lead to development of paroxysmal hyperexcitability and seizures as in the case of brain trauma. PMID:21854960
Lin, Shih-Chieh; Nicolelis, Miguel A. L.
2011-01-01
The medial septum-vertical limb of the diagonal band of Broca (MSvDB) is important for normal hippocampal functions and theta oscillations. Although many previous studies have focused on understanding how MSVDB neurons fire rhythmic bursts to pace hippocampal theta oscillations, a significant portion of MSVDB neurons are slow-firing and thus do not pace theta oscillations. The function of these MSVDB neurons, especially their role in modulating hippocampal activity, remains unknown. We recorded MSVDB neuronal ensembles in behaving rats, and identified a distinct physiologically homogeneous subpopulation of slow-firing neurons (overall firing <4 Hz) that shared three features: 1) much higher firing rate during rapid eye movement sleep than during slow-wave (SW) sleep; 2) temporary activation associated with transient arousals during SW sleep; 3) brief responses (latency 15∼30 ms) to auditory stimuli. Analysis of the fine temporal relationship of their spiking and theta oscillations showed that unlike the theta-pacing neurons, the firing of these “pro-arousal” neurons follows theta oscillations. However, their activity precedes short-term increases in hippocampal oscillation power in the theta and gamma range lasting for a few seconds. Together, these results suggest that these pro-arousal slow-firing MSvDB neurons may function collectively to promote hippocampal activation. PMID:21865435
Impact of Partial Time Delay on Temporal Dynamics of Watts-Strogatz Small-World Neuronal Networks
NASA Astrophysics Data System (ADS)
Yan, Hao; Sun, Xiaojuan
2017-06-01
In this paper, we mainly discuss effects of partial time delay on temporal dynamics of Watts-Strogatz (WS) small-world neuronal networks by controlling two parameters. One is the time delay τ and the other is the probability of partial time delay pdelay. Temporal dynamics of WS small-world neuronal networks are discussed with the aid of temporal coherence and mean firing rate. With the obtained simulation results, it is revealed that for small time delay τ, the probability pdelay could weaken temporal coherence and increase mean firing rate of neuronal networks, which indicates that it could improve neuronal firings of the neuronal networks while destroying firing regularity. For large time delay τ, temporal coherence and mean firing rate do not have great changes with respect to pdelay. Time delay τ always has great influence on both temporal coherence and mean firing rate no matter what is the value of pdelay. Moreover, with the analysis of spike trains and histograms of interspike intervals of neurons inside neuronal networks, it is found that the effects of partial time delays on temporal coherence and mean firing rate could be the result of locking between the period of neuronal firing activities and the value of time delay τ. In brief, partial time delay could have great influence on temporal dynamics of the neuronal networks.
Morris, Kendall F; Nuding, Sarah C; Segers, Lauren S; Iceman, Kimberly E; O'Connor, Russell; Dean, Jay B; Ott, Mackenzie M; Alencar, Pierina A; Shuman, Dale; Horton, Kofi-Kermit; Taylor-Clark, Thomas E; Bolser, Donald C; Lindsey, Bruce G
2018-02-01
We tested the hypothesis that carotid chemoreceptors tune breathing through parallel circuit paths that target distinct elements of an inspiratory neuron chain in the ventral respiratory column (VRC). Microelectrode arrays were used to monitor neuronal spike trains simultaneously in the VRC, peri-nucleus tractus solitarius (p-NTS)-medial medulla, the dorsal parafacial region of the lateral tegmental field (FTL-pF), and medullary raphe nuclei together with phrenic nerve activity during selective stimulation of carotid chemoreceptors or transient hypoxia in 19 decerebrate, neuromuscularly blocked, and artificially ventilated cats. Of 994 neurons tested, 56% had a significant change in firing rate. A total of 33,422 cell pairs were evaluated for signs of functional interaction; 63% of chemoresponsive neurons were elements of at least one pair with correlational signatures indicative of paucisynaptic relationships. We detected evidence for postinspiratory neuron inhibition of rostral VRC I-Driver (pre-Bötzinger) neurons, an interaction predicted to modulate breathing frequency, and for reciprocal excitation between chemoresponsive p-NTS neurons and more downstream VRC inspiratory neurons for control of breathing depth. Chemoresponsive pericolumnar tonic expiratory neurons, proposed to amplify inspiratory drive by disinhibition, were correlationally linked to afferent and efferent "chains" of chemoresponsive neurons extending to all monitored regions. The chains included coordinated clusters of chemoresponsive FTL-pF neurons with functional links to widespread medullary sites involved in the control of breathing. The results support long-standing concepts on brain stem network architecture and a circuit model for peripheral chemoreceptor modulation of breathing with multiple circuit loops and chains tuned by tegmental field neurons with quasi-periodic discharge patterns. NEW & NOTEWORTHY We tested the long-standing hypothesis that carotid chemoreceptors tune the frequency and depth of breathing through parallel circuit operations targeting the ventral respiratory column. Responses to stimulation of the chemoreceptors and identified functional connectivity support differential tuning of inspiratory neuron burst duration and firing rate and a model of brain stem network architecture incorporating tonic expiratory "hub" neurons regulated by convergent neuronal chains and loops through rostral lateral tegmental field neurons with quasi-periodic discharge patterns.
Transition to Chaos in Random Neuronal Networks
NASA Astrophysics Data System (ADS)
Kadmon, Jonathan; Sompolinsky, Haim
2015-10-01
Firing patterns in the central nervous system often exhibit strong temporal irregularity and considerable heterogeneity in time-averaged response properties. Previous studies suggested that these properties are the outcome of the intrinsic chaotic dynamics of the neural circuits. Indeed, simplified rate-based neuronal networks with synaptic connections drawn from Gaussian distribution and sigmoidal nonlinearity are known to exhibit chaotic dynamics when the synaptic gain (i.e., connection variance) is sufficiently large. In the limit of an infinitely large network, there is a sharp transition from a fixed point to chaos, as the synaptic gain reaches a critical value. Near the onset, chaotic fluctuations are slow, analogous to the ubiquitous, slow irregular fluctuations observed in the firing rates of many cortical circuits. However, the existence of a transition from a fixed point to chaos in neuronal circuit models with more realistic architectures and firing dynamics has not been established. In this work, we investigate rate-based dynamics of neuronal circuits composed of several subpopulations with randomly diluted connections. Nonzero connections are either positive for excitatory neurons or negative for inhibitory ones, while single neuron output is strictly positive with output rates rising as a power law above threshold, in line with known constraints in many biological systems. Using dynamic mean field theory, we find the phase diagram depicting the regimes of stable fixed-point, unstable-dynamic, and chaotic-rate fluctuations. We focus on the latter and characterize the properties of systems near this transition. We show that dilute excitatory-inhibitory architectures exhibit the same onset to chaos as the single population with Gaussian connectivity. In these architectures, the large mean excitatory and inhibitory inputs dynamically balance each other, amplifying the effect of the residual fluctuations. Importantly, the existence of a transition to chaos and its critical properties depend on the shape of the single-neuron nonlinear input-output transfer function, near firing threshold. In particular, for nonlinear transfer functions with a sharp rise near threshold, the transition to chaos disappears in the limit of a large network; instead, the system exhibits chaotic fluctuations even for small synaptic gain. Finally, we investigate transition to chaos in network models with spiking dynamics. We show that when synaptic time constants are slow relative to the mean inverse firing rates, the network undergoes a transition from fast spiking fluctuations with constant rates to a state where the firing rates exhibit chaotic fluctuations, similar to the transition predicted by rate-based dynamics. Systems with finite synaptic time constants and firing rates exhibit a smooth transition from a regime dominated by stationary firing rates to a regime of slow rate fluctuations. This smooth crossover obeys scaling properties, similar to crossover phenomena in statistical mechanics. The theoretical results are supported by computer simulations of several neuronal architectures and dynamics. Consequences for cortical circuit dynamics are discussed. These results advance our understanding of the properties of intrinsic dynamics in realistic neuronal networks and their functional consequences.
Emergence of Alpha and Gamma Like Rhythms in a Large Scale Simulation of Interacting Neurons
NASA Astrophysics Data System (ADS)
Gaebler, Philipp; Miller, Bruce
2007-10-01
In the normal brain, at first glance the electrical activity appears very random. However, certain frequencies emerge during specific stages of sleep or between quiet wake states. This raises the question of whether current mathematical and computational models of interacting neurons can display similar behavior. A recent model developed by Eugene Izhikevich appears to succeed. However, early dynamical simulations used to detect these patterns were possibly compromised by an over-simplified initial condition and evolution algorithm. Utilizing the same model, but a more robust algorithm, here we present our initial results, showing that these patterns persist under a wide range of initial conditions. We employ spectral analysis of the firing patterns of a system of interacting excitatory and inhibitory neurons to demonstrate a bimodal spectrum centered on two frequencies in the range characteristic of alpha and gamma rhythms in the human brain.
Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior.
Portugues, Ruben; Feierstein, Claudia E; Engert, Florian; Orger, Michael B
2014-03-19
Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate but ordered pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments systematically reveal the functional architecture of neural circuits underlying a sensorimotor behavior in a vertebrate brain. Copyright © 2014 Elsevier Inc. All rights reserved.
Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior
Portugues, Ruben; Feierstein, Claudia E.; Engert, Florian; Orger, Michael B.
2014-01-01
Summary Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate, but ordered, pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments reveal, for the first time in a vertebrate, the comprehensive functional architecture of the neural circuits underlying a sensorimotor behavior. PMID:24656252
McKinstry, Jeffrey L; Edelman, Gerald M
2013-01-01
Animal behavior often involves a temporally ordered sequence of actions learned from experience. Here we describe simulations of interconnected networks of spiking neurons that learn to generate patterns of activity in correct temporal order. The simulation consists of large-scale networks of thousands of excitatory and inhibitory neurons that exhibit short-term synaptic plasticity and spike-timing dependent synaptic plasticity. The neural architecture within each area is arranged to evoke winner-take-all (WTA) patterns of neural activity that persist for tens of milliseconds. In order to generate and switch between consecutive firing patterns in correct temporal order, a reentrant exchange of signals between these areas was necessary. To demonstrate the capacity of this arrangement, we used the simulation to train a brain-based device responding to visual input by autonomously generating temporal sequences of motor actions.
de Arruda, Henrique Ferraz; Comin, Cesar Henrique; Miazaki, Mauro; Viana, Matheus Palhares; Costa, Luciano da Fontoura
2015-04-30
A key point in developmental biology is to understand how gene expression influences the morphological and dynamical patterns that are observed in living beings. In this work we propose a methodology capable of addressing this problem that is based on estimating the mutual information and Pearson correlation between the intensity of gene expression and measurements of several morphological properties of the cells. A similar approach is applied in order to identify effects of gene expression over the system dynamics. Neuronal networks were artificially grown over a lattice by considering a reference model used to generate artificial neurons. The input parameters of the artificial neurons were determined according to two distinct patterns of gene expression and the dynamical response was assessed by considering the integrate-and-fire model. As far as single gene dependence is concerned, we found that the interaction between the gene expression and the network topology, as well as between the former and the dynamics response, is strongly affected by the gene expression pattern. In addition, we observed a high correlation between the gene expression and some topological measurements of the neuronal network for particular patterns of gene expression. To our best understanding, there are no similar analyses to compare with. A proper understanding of gene expression influence requires jointly studying the morphology, topology, and dynamics of neurons. The proposed framework represents a first step towards predicting gene expression patterns from morphology and connectivity. Copyright © 2015. Published by Elsevier B.V.
A single-cell spiking model for the origin of grid-cell patterns
Kempter, Richard
2017-01-01
Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity. PMID:28968386
Hu, Liang; Wang, Qin; Qin, Zhen; Su, Kaiqi; Huang, Liquan; Hu, Ning; Wang, Ping
2015-04-15
5-hydroxytryptamine (5-HT) is an important neurotransmitter in regulating emotions and related behaviors in mammals. To detect and monitor the 5-HT, effective and convenient methods are demanded in investigation of neuronal network. In this study, hippocampal neuronal networks (HNNs) endogenously expressing 5-HT receptors were employed as sensing elements to build an in vitro neuronal network-based biosensor. The electrophysiological characteristics were analyzed in both neuron and network levels. The firing rates and amplitudes were derived from signal to determine the biosensor response characteristics. The experimental results demonstrate a dose-dependent inhibitory effect of 5-HT on hippocampal neuron activities, indicating the effectiveness of this hybrid biosensor in detecting 5-HT with a response range from 0.01μmol/L to 10μmol/L. In addition, the cross-correlation analysis of HNNs activities suggests 5-HT could weaken HNN connectivity reversibly, providing more specificity of this biosensor in detecting 5-HT. Moreover, 5-HT induced spatiotemporal firing pattern alterations could be monitored in neuron and network levels simultaneously by this hybrid biosensor in a convenient and direct way. With those merits, this neuronal network-based biosensor will be promising to be a valuable and utility platform for the study of neurotransmitter in vitro. Copyright © 2014 Elsevier B.V. All rights reserved.
Noise adaptation in integrate-and fire neurons.
Rudd, M E; Brown, L G
1997-07-01
The statistical spiking response of an ensemble of identically prepared stochastic integrate-and-fire neurons to a rectangular input current plus gaussian white noise is analyzed. It is shown that, on average, integrate-and-fire neurons adapt to the root-mean-square noise level of their input. This phenomenon is referred to as noise adaptation. Noise adaptation is characterized by a decrease in the average neural firing rate and an accompanying decrease in the average value of the generator potential, both of which can be attributed to noise-induced resets of the generator potential mediated by the integrate-and-fire mechanism. A quantitative theory of noise adaptation in stochastic integrate-and-fire neurons is developed. It is shown that integrate-and-fire neurons, on average, produce transient spiking activity whenever there is an increase in the level of their input noise. This transient noise response is either reduced or eliminated over time, depending on the parameters of the model neuron. Analytical methods are used to prove that nonleaky integrate-and-fire neurons totally adapt to any constant input noise level, in the sense that their asymptotic spiking rates are independent of the magnitude of their input noise. For leaky integrate-and-fire neurons, the long-run noise adaptation is not total, but the response to noise is partially eliminated. Expressions for the probability density function of the generator potential and the first two moments of the potential distribution are derived for the particular case of a nonleaky neuron driven by gaussian white noise of mean zero and constant variance. The functional significance of noise adaptation for the performance of networks comprising integrate-and-fire neurons is discussed.
A cortical neural prosthesis for restoring and enhancing memory
NASA Astrophysics Data System (ADS)
Berger, Theodore W.; Hampson, Robert E.; Song, Dong; Goonawardena, Anushka; Marmarelis, Vasilis Z.; Deadwyler, Sam A.
2011-08-01
A primary objective in developing a neural prosthesis is to replace neural circuitry in the brain that no longer functions appropriately. Such a goal requires artificial reconstruction of neuron-to-neuron connections in a way that can be recognized by the remaining normal circuitry, and that promotes appropriate interaction. In this study, the application of a specially designed neural prosthesis using a multi-input/multi-output (MIMO) nonlinear model is demonstrated by using trains of electrical stimulation pulses to substitute for MIMO model derived ensemble firing patterns. Ensembles of CA3 and CA1 hippocampal neurons, recorded from rats performing a delayed-nonmatch-to-sample (DNMS) memory task, exhibited successful encoding of trial-specific sample lever information in the form of different spatiotemporal firing patterns. MIMO patterns, identified online and in real-time, were employed within a closed-loop behavioral paradigm. Results showed that the model was able to predict successful performance on the same trial. Also, MIMO model-derived patterns, delivered as electrical stimulation to the same electrodes, improved performance under normal testing conditions and, more importantly, were capable of recovering performance when delivered to animals with ensemble hippocampal activity compromised by pharmacologic blockade of synaptic transmission. These integrated experimental-modeling studies show for the first time that, with sufficient information about the neural coding of memories, a neural prosthesis capable of real-time diagnosis and manipulation of the encoding process can restore and even enhance cognitive, mnemonic processes.
Input dependent cell assembly dynamics in a model of the striatal medium spiny neuron network.
Ponzi, Adam; Wickens, Jeff
2012-01-01
The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior.
Input Dependent Cell Assembly Dynamics in a Model of the Striatal Medium Spiny Neuron Network
Ponzi, Adam; Wickens, Jeff
2012-01-01
The striatal medium spiny neuron (MSN) network is sparsely connected with fairly weak GABAergic collaterals receiving an excitatory glutamatergic cortical projection. Peri-stimulus time histograms (PSTH) of MSN population response investigated in various experimental studies display strong firing rate modulations distributed throughout behavioral task epochs. In previous work we have shown by numerical simulation that sparse random networks of inhibitory spiking neurons with characteristics appropriate for UP state MSNs form cell assemblies which fire together coherently in sequences on long behaviorally relevant timescales when the network receives a fixed pattern of constant input excitation. Here we first extend that model to the case where cortical excitation is composed of many independent noisy Poisson processes and demonstrate that cell assembly dynamics is still observed when the input is sufficiently weak. However if cortical excitation strength is increased more regularly firing and completely quiescent cells are found, which depend on the cortical stimulation. Subsequently we further extend previous work to consider what happens when the excitatory input varies as it would when the animal is engaged in behavior. We investigate how sudden switches in excitation interact with network generated patterned activity. We show that sequences of cell assembly activations can be locked to the excitatory input sequence and outline the range of parameters where this behavior is shown. Model cell population PSTH display both stimulus and temporal specificity, with large population firing rate modulations locked to elapsed time from task events. Thus the random network can generate a large diversity of temporally evolving stimulus dependent responses even though the input is fixed between switches. We suggest the MSN network is well suited to the generation of such slow coherent task dependent response which could be utilized by the animal in behavior. PMID:22438838
Hight, Ariel E; Kalluri, Radha
2016-08-01
The vestibular nerve is characterized by two broad groups of neurons that differ in the timing of their interspike intervals; some fire at highly regular intervals, whereas others fire at highly irregular intervals. Heterogeneity in ion channel properties has been proposed as shaping these firing patterns (Highstein SM, Politoff AL. Brain Res 150: 182-187, 1978; Smith CE, Goldberg JM. Biol Cybern 54: 41-51, 1986). Kalluri et al. (J Neurophysiol 104: 2034-2051, 2010) proposed that regularity is controlled by the density of low-voltage-activated potassium currents (IKL). To examine the impact of IKL on spike timing regularity, we implemented a single-compartment model with three conductances known to be present in the vestibular ganglion: transient sodium (gNa), low-voltage-activated potassium (gKL), and high-voltage-activated potassium (gKH). Consistent with in vitro observations, removing gKL depolarized resting potential, increased input resistance and membrane time constant, and converted current step-evoked firing patterns from transient (1 spike at current onset) to sustained (many spikes). Modeled neurons were driven with a time-varying synaptic conductance that captured the random arrival times and amplitudes of glutamate-driven synaptic events. In the presence of gKL, spiking occurred only in response to large events with fast onsets. Models without gKL exhibited greater integration by responding to the superposition of rapidly arriving events. Three synaptic conductance were modeled, each with different kinetics to represent a variety of different synaptic processes. In response to all three types of synaptic conductance, models containing gKL produced spike trains with irregular interspike intervals. Only models lacking gKL when driven by rapidly arriving small excitatory postsynaptic currents were capable of generating regular spiking. Copyright © 2016 the American Physiological Society.
Emergent Oscillations in Networks of Stochastic Spiking Neurons
van Drongelen, Wim; Cowan, Jack D.
2011-01-01
Networks of neurons produce diverse patterns of oscillations, arising from the network's global properties, the propensity of individual neurons to oscillate, or a mixture of the two. Here we describe noisy limit cycles and quasi-cycles, two related mechanisms underlying emergent oscillations in neuronal networks whose individual components, stochastic spiking neurons, do not themselves oscillate. Both mechanisms are shown to produce gamma band oscillations at the population level while individual neurons fire at a rate much lower than the population frequency. Spike trains in a network undergoing noisy limit cycles display a preferred period which is not found in the case of quasi-cycles, due to the even faster decay of phase information in quasi-cycles. These oscillations persist in sparsely connected networks, and variation of the network's connectivity results in variation of the oscillation frequency. A network of such neurons behaves as a stochastic perturbation of the deterministic Wilson-Cowan equations, and the network undergoes noisy limit cycles or quasi-cycles depending on whether these have limit cycles or a weakly stable focus. These mechanisms provide a new perspective on the emergence of rhythmic firing in neural networks, showing the coexistence of population-level oscillations with very irregular individual spike trains in a simple and general framework. PMID:21573105
Computational properties of networks of synchronous groups of spiking neurons.
Dayhoff, Judith E
2007-09-01
We demonstrate a model in which synchronously firing ensembles of neurons are networked to produce computational results. Each ensemble is a group of biological integrate-and-fire spiking neurons, with probabilistic interconnections between groups. An analogy is drawn in which each individual processing unit of an artificial neural network corresponds to a neuronal group in a biological model. The activation value of a unit in the artificial neural network corresponds to the fraction of active neurons, synchronously firing, in a biological neuronal group. Weights of the artificial neural network correspond to the product of the interconnection density between groups, the group size of the presynaptic group, and the postsynaptic potential heights in the synchronous group model. All three of these parameters can modulate connection strengths between neuronal groups in the synchronous group models. We give an example of nonlinear classification (XOR) and a function approximation example in which the capability of the artificial neural network can be captured by a neural network model with biological integrate-and-fire neurons configured as a network of synchronously firing ensembles of such neurons. We point out that the general function approximation capability proven for feedforward artificial neural networks appears to be approximated by networks of neuronal groups that fire in synchrony, where the groups comprise integrate-and-fire neurons. We discuss the advantages of this type of model for biological systems, its possible learning mechanisms, and the associated timing relationships.
Spatiotemporal activity patterns detected from single cell measurements from behaving animals
NASA Astrophysics Data System (ADS)
Villa, Alessandro E. P.; Tetko, Igor V.
1999-03-01
Precise temporal patterning of activity within and between neurons has been predicted on theoretical grounds, and found in the spike trains of neurons recorded from anesthetized and conscious animals, in association with sensor stimuli and particular phases of task performance. However, the functional significance of such patterning in the generation of behavior has not been confirmed. We recorded from multiple single neurons in regions of rat auditory cortex during the waiting period of a Go/NoGo task. During this time the animal waited for an auditory signal with high cognitive load. Of note is the fact that neural activity during the period analyzed was essentially stationary, with no event related variability in firing. Detected patterns therefore provide a measure of brain state that could not be addressed by standard methods relying on analysis of changes in mean discharge rate. The possibility is discussed that some patterns might reflect a preset bias to a particular response, formed in the waiting period. Others patterns might reflect a state of prior preparation of appropriate neural assemblies for analyzing a signal that is expected but of unknown behavioral valence.
Sabbar, M; Delaville, C; De Deurwaerdère, P; Benazzouz, A; Lakhdar-Ghazal, N
2012-05-17
Lead intoxication has been suggested as a high risk factor for the development of Parkinson disease. However, its impact on motor and nonmotor functions and the mechanism by which it can be involved in the disease are still unclear. In the present study, we studied the effects of lead intoxication on the following: (1) locomotor activity using an open field actimeter and motor coordination using the rotarod test, (2) anxiety behavior using the elevated plus maze, (3) "depression-like" behavior using sucrose preference test, and (4) subthalamic nucleus (STN) neuronal activity using extracellular single unit recordings. Male Sprague-Dawley rats were treated once a day with lead acetate or sodium acetate (20 mg/kg/d i.p.) during 3 weeks. The tissue content of monoamines was used to determine alteration of these systems at the end of experiments. Results show that lead significantly reduced exploratory activity, locomotor activity and the time spent on the rotarod bar. Furthermore, lead induced anxiety but not "depressive-like" behavior. The electrophysiological results show that lead altered the discharge pattern of STN neurons with an increase in the number of bursting and irregular cells without affecting the firing rate. Moreover, lead intoxication resulted in a decrease of tissue noradrenaline content without any change in the levels of dopamine and serotonin. Together, these results show for the first time that lead intoxication resulted in motor and nonmotor behavioral changes paralleled by noradrenaline depletion and changes in the firing activity of STN neurons, providing evidence consistent with the induction of atypical parkinsonian-like deficits. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.
Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits.
Ujfalussy, Balázs B; Makara, Judit K; Branco, Tiago; Lengyel, Máté
2015-12-24
Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here, we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalizes how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems--level properties of cortical circuits.
Nothing can be coincidence: synaptic inhibition and plasticity in the cerebellar nuclei
Pugh, Jason R.; Raman, Indira M.
2009-01-01
Many cerebellar neurons fire spontaneously, generating 10–100 action potentials per second even without synaptic input. This high basal activity correlates with information-coding mechanisms that differ from those of cells that are quiescent until excited synaptically. For example, in the deep cerebellar nuclei, Hebbian patterns of coincident synaptic excitation and postsynaptic firing fail to induce long-term increases in the strength of excitatory inputs. Instead, excitatory synaptic currents are potentiated by combinations of inhibition and excitation that resemble the activity of Purkinje and mossy fiber afferents that is predicted to occur during cerebellar associative learning tasks. Such results indicate that circuits with intrinsically active neurons have rules for information transfer and storage that distinguish them from other brain regions. PMID:19178955
NASA Astrophysics Data System (ADS)
Bressloff, P. C.; Bressloff, N. W.
2000-02-01
Orientation tuning in a ring of pulse-coupled integrate-and-fire (IF) neurons is analyzed in terms of spontaneous pattern formation. It is shown how the ring bifurcates from a synchronous state to a non-phase-locked state whose spike trains are characterized by quasiperiodic variations of the inter-spike intervals (ISIs) on closed invariant circles. The separation of these invariant circles in phase space results in a localized peak of activity as measured by the time-averaged firing rate of the neurons. This generates a sharp orientation tuning curve that can lock to a slowly rotating, weakly tuned external stimulus. For fast synapses, breakup of the quasiperiodic orbits occurs leading to high spike time variability suggestive of chaos.
NASA Astrophysics Data System (ADS)
Jia, Bing
2014-03-01
A comb-shaped chaotic region has been simulated in multiple two-dimensional parameter spaces using the Hindmarsh—Rose (HR) neuron model in many recent studies, which can interpret almost all of the previously simulated bifurcation processes with chaos in neural firing patterns. In the present paper, a comb-shaped chaotic region in a two-dimensional parameter space was reproduced, which presented different processes of period-adding bifurcations with chaos with changing one parameter and fixed the other parameter at different levels. In the biological experiments, different period-adding bifurcation scenarios with chaos by decreasing the extra-cellular calcium concentration were observed from some neural pacemakers at different levels of extra-cellular 4-aminopyridine concentration and from other pacemakers at different levels of extra-cellular caesium concentration. By using the nonlinear time series analysis method, the deterministic dynamics of the experimental chaotic firings were investigated. The period-adding bifurcations with chaos observed in the experiments resembled those simulated in the comb-shaped chaotic region using the HR model. The experimental results show that period-adding bifurcations with chaos are preserved in different two-dimensional parameter spaces, which provides evidence of the existence of the comb-shaped chaotic region and a demonstration of the simulation results in different two-dimensional parameter spaces in the HR neuron model. The results also present relationships between different firing patterns in two-dimensional parameter spaces.
NASA Technical Reports Server (NTRS)
Marshburn, T. H.; Kaufman, G. D.; Purcell, I. M.; Perachio, A. A.
1997-01-01
Immunolabeling patterns of the immediate early gene-related protein Fos in the gerbil brainstem were studied following stimulation of the sacculus by both hypergravity and galvanic stimulation. Head-restrained, alert animals were exposed to a prolonged (1 h) inertial vector of 2 G (19.6 m/s2) head acceleration directed in a dorso-ventral head axis to maximally stimulate the sacculus. Fos-defined immunoreactivity was quantified, and the results compared to a control group. The hypergravity stimulus produced Fos immunolabeling in the dorsomedial cell column (dmcc) of the inferior olive independently of other subnuclei. Similar dmcc labeling was induced by a 30 min galvanic stimulus of up to -100 microA applied through a stimulating electrode placed unilaterally on the bony labyrinth overlying the posterior canal (PC). The pattern of vestibular afferent firing activity induced by this galvanic stimulus was quantified in anesthetized gerbils by simultaneously recording from Scarpa's ganglion. Only saccular and PC afferent neurons exhibited increases in average firing rates of 200-300%, suggesting a pattern of current spread involving only PC and saccular afferent neurons at this level of stimulation. These results suggest that alteration in saccular afferent firing rates are sufficient to induce Fos-defined genomic activation of the dmcc, and lend further evidence to the existence of a functional vestibulo-olivary-cerebellar pathway of adaptation to novel gravito-inertial environments.
Hampson, Robert E.; Gerhardt, Greg A.; Marmarelis, Vasilis; Song, Dong; Opris, Ioan; Santos, Lucas; Berger, Theodore W.; Deadwyler, Sam A.
2012-01-01
Problem addressed Maintenance of cognitive control is a major concern for many human disease condition, therefore a major goal of human neuroprosthetics is to facilitate and/or recover cognitive function when such circumstances impair appropriate decision making. Methodology Nonhuman primates trained to perform a delayed match to sample (DMS) were employed to record mini-columnar activity in the prefrontal cortex (PFC) via custom designed conformal multielectrode arrays that provided inter-laminar recordings from neurons in PFC layer 2/3 and layer 5. Such recordings were analyzed via a previously demonstrated nonlinear multi-input multi-output (MIMO) neuroprosthesis in rodents, which extracted and characterized multi-columnar firing patterns during DMS performance. Results The MIMO model verified that the conformal recorded individual PFC minicolumns responded to entrained target selections in patterns critical for successful DMS performance. This allowed substitution of task-related layer 5 neuron firing patterns with electrical stimulation in the same recording regions during columnar transmission from layer 2/3 at the time of target selection. Such stimulation facilitated normal task performance, but more importantly, recovered performance when applied as a neuroprosthesis following pharmacological disruption of decision making in the same task. Significance and potential impact These findings provide the first successful application of a neuroprosthesis in primate brain designed specifically to restore or repair disrupted cognitive function. PMID:22976769
Merrison-Hort, Robert; Zhang, Hong-Yan; Borisyuk, Roman
2014-01-01
Many neural circuits are capable of generating multiple stereotyped outputs after different sensory inputs or neuromodulation. We have previously identified the central pattern generator (CPG) for Xenopus tadpole swimming that involves antiphase oscillations of activity between the left and right sides. Here we analyze the cellular basis for spontaneous left–right motor synchrony characterized by simultaneous bursting on both sides at twice the swimming frequency. Spontaneous synchrony bouts are rare in most tadpoles, and they instantly emerge from and switch back to swimming, most frequently within the first second after skin stimulation. Analyses show that only neurons that are active during swimming fire action potentials in synchrony, suggesting both output patterns derive from the same neural circuit. The firing of excitatory descending interneurons (dINs) leads that of other types of neurons in synchrony as it does in swimming. During synchrony, the time window between phasic excitation and inhibition is 7.9 ± 1 ms, shorter than that in swimming (41 ± 2.3 ms). The occasional, extra midcycle firing of dINs during swimming may initiate synchrony, and mismatches of timing in the left and right activity can switch synchrony back to swimming. Computer modeling supports these findings by showing that the same neural network, in which reciprocal inhibition mediates rebound firing, can generate both swimming and synchrony without circuit reconfiguration. Modeling also shows that lengthening the time window between phasic excitation and inhibition by increasing dIN synaptic/conduction delay can improve the stability of synchrony. PMID:24760866
Transfer of Timing Information from RGC to LGN Spike Trains
NASA Astrophysics Data System (ADS)
Teich, Malvin C.; Lowen, Steven B.; Saleh, Bahaa E. A.; Kaplan, Ehud
1998-03-01
We have studied the firing patterns of retinal ganglion cells (RGCs) and their target lateral geniculate nucleus (LGN) cells. We find that clusters of spikes in the RGC neural firing pattern appear at the LGN output essentially unchanged, while isolated RGC firing events are more likely to be eliminated; thus the LGN action-potential sequence is therefore not merely a randomly deleted version of the RGC spike train. Employing information-theoretic techniques we developed for point processes,(B. E. A. Saleh and M. C. Teich, Phys. Rev. Lett.) 58, 2656--2659 (1987). we are able to estimate the information efficiency of the LGN neuronal output --- the proportion of the variation in the LGN firing pattern that carries information about its associated RGC input. A suitably modified integrate-and-fire neural model reproduces both the enhanced clustering in the LGN data (which accounts for the increased coefficient of variation) and the measured value of information efficiency, as well as mimicking the results of other observed statistical measures. Reliable information transmission therefore coexists with fractal fluctuations, which appear in RGC and LGN firing patterns.(M. C. Teich, C. Heneghan, S. B. Lowen, T. Ozaki, and E. Kaplan, J. Opt. Soc. Am. A) 14, 529--546 (1997).
Roth, Arnd; Häusser, Michael
2010-01-01
Cerebellar Purkinje cells display complex intrinsic dynamics. They fire spontaneously, exhibit bistability, and via mutual network interactions are involved in the generation of high frequency oscillations and travelling waves of activity. To probe the dynamical properties of Purkinje cells we measured their phase response curves (PRCs). PRCs quantify the change in spike phase caused by a stimulus as a function of its temporal position within the interspike interval, and are widely used to predict neuronal responses to more complex stimulus patterns. Significant variability in the interspike interval during spontaneous firing can lead to PRCs with a low signal-to-noise ratio, requiring averaging over thousands of trials. We show using electrophysiological experiments and simulations that the PRC calculated in the traditional way by sampling the interspike interval with brief current pulses is biased. We introduce a corrected approach for calculating PRCs which eliminates this bias. Using our new approach, we show that Purkinje cell PRCs change qualitatively depending on the firing frequency of the cell. At high firing rates, Purkinje cells exhibit single-peaked, or monophasic PRCs. Surprisingly, at low firing rates, Purkinje cell PRCs are largely independent of phase, resembling PRCs of ideal non-leaky integrate-and-fire neurons. These results indicate that Purkinje cells can act as perfect integrators at low firing rates, and that the integration mode of Purkinje cells depends on their firing rate. PMID:20442875
Yang, C; Brown, R E
2014-01-31
Dorsal raphe nucleus (DRN) serotonin (5-HT) neurons play an important role in feeding, mood control and stress responses. One important feature of their activity across the sleep-wake cycle is their reduced firing during rapid-eye-movement (REM) sleep which stands in stark contrast to the wake/REM-on discharge pattern of brainstem cholinergic neurons. A prominent model of REM sleep control posits a reciprocal interaction between these cell groups. 5-HT inhibits cholinergic neurons, and activation of nicotinic receptors can excite DRN 5-HT neurons but the cholinergic effect on inhibitory inputs is incompletely understood. Here, in vitro, in DRN brain slices prepared from GAD67-GFP knock-in mice, a brief (3 min) bath application of carbachol (50 μM) increased the frequency of spontaneous inhibitory postsynaptic currents (sIPSCs) in GFP-negative, putative 5-HT neurons but did not affect miniature (tetrodotoxin-insensitive) IPSCs. Carbachol had no direct postsynaptic effect. Thus, carbachol likely increases the activity of local GABAergic neurons which synapse on 5-HT neurons. Removal of dorsal regions of the slice including the ventrolateral periaqueductal gray (vlPAG) region where GABAergic neurons projecting to the DRN have been identified, abolished the effect of carbachol on sIPSCs whereas the removal of ventral regions containing the oral region of the pontine reticular nucleus (PnO) did not. In addition, carbachol directly excited GFP-positive, GABAergic vlPAG neurons. Antagonism of both muscarinic and nicotinic receptors completely abolished the effects of carbachol. We suggest cholinergic neurons inhibit DRN 5-HT neurons when acetylcholine levels are lower i.e. during quiet wakefulness and the beginning of REM sleep periods, in part via excitation of muscarinic and nicotinic receptors located on local vlPAG and DRN GABAergic neurons. Higher firing rates or burst firing of cholinergic neurons associated with attentive wakefulness or phasic REM sleep periods leads to excitation of 5-HT neurons via the activation of nicotinic receptors located postsynaptically and presynaptically on excitatory afferents. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.
Yang, Chun; Brown, Ritchie E.
2013-01-01
Dorsal raphe nucleus (DRN) serotonin (5-HT) neurons play an important role in feeding, mood control and stress responses. One important feature of their activity across the sleep-wake cycle is their reduced firing during rapid-eye-movement (REM) sleep which stands in stark contrast to the wake/REM-on discharge pattern of brainstem cholinergic neurons. A prominent model of REM sleep control posits a reciprocal interaction between these cell groups. 5-HT inhibits cholinergic neurons, and activation of nicotinic receptors can excite DRN 5-HT neurons but the cholinergic effect on inhibitory inputs is incompletely understood. Here, in vitro, in DRN brain slices prepared from GAD67-GFP knock-in mice, a brief (3 min) bath application of carbachol (50 μM) increased the frequency of spontaneous inhibitory postsynaptic currents (sIPSCs) in GFP-negative, putative serotonin neurons but did not affect miniature (tetrodotoxin-insensitive) IPSCs. Carbachol had no direct postsynaptic effect. Thus, carbachol likely increases the activity of local GABAergic neurons which synapse on 5-HT neurons. Removal of dorsal regions of the slice including the ventrolateral periaqueductal gray (vlPAG) region where GABAergic neurons projecting to the DRN have been identified, abolished the effect of carbachol on sIPSCs whereas removal of ventral regions containing the oral region of the pontine reticular nucleus (PnO) did not. In addition, carbachol directly excited GFP-positive, GABAergic vlPAG neurons. Antagonism of both muscarinic and nicotinic receptors completely abolished the effects of carbachol. We suggest cholinergic neurons inhibit DRN 5-HT neurons when acetylcholine levels are lower i.e. during quiet wakefulness and the beginning of REM sleep periods, in part via excitation of muscarinic and nicotinic receptors located on local vlPAG and DRN GABAergic neurons. Higher firing rates or burst firing of cholinergic neurons associated with attentive wakefulness or phasic REM sleep periods leads to excitation of 5-HT neurons via activation of nicotinic receptors located postsynaptically and presynaptically on excitatory afferents. PMID:24231737
Cuevas Rivera, Dario; Bitzer, Sebastian; Kiebel, Stefan J.
2015-01-01
The olfactory information that is received by the insect brain is encoded in the form of spatiotemporal patterns in the projection neurons of the antennal lobe. These dense and overlapping patterns are transformed into a sparse code in Kenyon cells in the mushroom body. Although it is clear that this sparse code is the basis for rapid categorization of odors, it is yet unclear how the sparse code in Kenyon cells is computed and what information it represents. Here we show that this computation can be modeled by sequential firing rate patterns using Lotka-Volterra equations and Bayesian online inference. This new model can be understood as an ‘intelligent coincidence detector’, which robustly and dynamically encodes the presence of specific odor features. We found that the model is able to qualitatively reproduce experimentally observed activity in both the projection neurons and the Kenyon cells. In particular, the model explains mechanistically how sparse activity in the Kenyon cells arises from the dense code in the projection neurons. The odor classification performance of the model proved to be robust against noise and time jitter in the observed input sequences. As in recent experimental results, we found that recognition of an odor happened very early during stimulus presentation in the model. Critically, by using the model, we found surprising but simple computational explanations for several experimental phenomena. PMID:26451888
Complex distribution patterns of voltage-gated calcium channel α-subunits in the spiral ganglion
Chen, Wei Chun; Xue, Hui Zhong; Hsu, Yun (Lucy); Liu, Qing; Patel, Shail; Davis, Robin L.
2011-01-01
As with other elements of the peripheral auditory system, spiral ganglion neurons display specializations that vary as a function of location along the tonotopic axis. Previous work has shown that voltage-gated K+ channels and synaptic proteins show graded changes in their density that confers rapid responsiveness to neurons in the high frequency, basal region of the cochlea and slower, more maintained responsiveness to neurons in the low frequency, apical region of the cochlea. In order to understand how voltage-gated calcium channels (VGCCs) may contribute to these diverse phenotypes, we identified the VGCC α-subunits expressed in the ganglion, investigated aspects of Ca2+-dependent neuronal firing patterns, and mapped the intracellular and intercellular distributions of seven VGCC α-subunits in the spiral ganglion in vitro. Initial experiments with qRT-PCR showed that eight of the ten known VGCC α-subunits were expressed in the ganglion and electrophysiological analysis revealed firing patterns that were consistent with the presence of both LVA and HVA Ca2+ channels. Moreover, we were able to study seven of the α-subunits with immunocytochemistry, and we found that all were present in spiral ganglion neurons, and that three of them were neuron-specific (CaV1.3, CaV2.2, and CaV3.3). Further characterization of neuron-specific α-subunits showed that CaV1.3 and CaV3.3 were tonotopically-distributed, whereas CaV2.2 was uniformly distributed in apical and basal neurons. Multiple VGCC α-subunits were also immunolocalized to Schwann cells, having distinct intracellular localizations, and, significantly, appearing to distinguish putative compact0 (CaV2.3, CaV3.1) from loose (CaV1.2) myelin. Electrophysiological evaluation of spiral ganglion neurons in the presence of TEA revealed Ca2+ plateau potentials with slopes that varied proportionately with the cochlear region from which neurons were isolated. Because afterhyperpolarizations were minimal or absent under these conditions, we hypothesize that differential density and/or kinetics of one or more of the VGCC α-subunits could account for observed tonotopic differences. These experiments have set the stage for defining the clear multiplicity of functional control in neurons and Schwann cells of the spiral ganglion. PMID:21281707
Darbin, Olivier; Jin, Xingxing; von Wrangel, Christof; Schwabe, Kerstin; Nambu, Atsushi; Naritoku, Dean K; Krauss, Joachim K.; Alam, Mesbah
2016-01-01
The function of the nigro-striatal pathway on neuronal entropy in the basal ganglia (BG) output nucleus (entopeduncular nucleus, EPN) was investigated in the unilaterally 6-hyroxydopamine (6-OHDA)-lesioned rat model of Parkinson’s disease (PD). In both control subjects and subjects with 6-OHDA lesion of the nigro-striatal pathway, a histological hallmark for parkinsonism, neuronal entropy in EPN was maximal in neurons with firing rates ranging between 15Hz and 25 Hz. In 6-OHDA lesioned rats, neuronal entropy in the EPN was specifically higher in neurons with firing rates above 25Hz. Our data establishes that nigro-striatal pathway controls neuronal entropy in motor circuitry and that the parkinsonian condition is associated with abnormal relationship between firing rate and neuronal entropy in BG output nuclei. The neuronal firing rates and entropy relationship provide putative relevant electrophysiological information to investigate the sensory-motor processing in normal condition and conditions with movement disorders. PMID:26711712
Reliability, synchrony and noise
Ermentrout, G. Bard; Galán, Roberto F.; Urban, Nathaniel N.
2008-01-01
The brain is noisy. Neurons receive tens of thousands of highly fluctuating inputs and generate spike trains that appear highly irregular. Much of this activity is spontaneous—uncoupled to overt stimuli or motor outputs—leading to questions about the functional impact of this noise. Although noise is most often thought of as disrupting patterned activity and interfering with the encoding of stimuli, recent theoretical and experimental work has shown that noise can play a constructive role—leading to increased reliability or regularity of neuronal firing in single neurons and across populations. These results raise fundamental questions about how noise can influence neural function and computation. PMID:18603311
Ponzi, Adam; Wickens, Jeff
2010-04-28
The striatum is composed of GABAergic medium spiny neurons with inhibitory collaterals forming a sparse random asymmetric network and receiving an excitatory glutamatergic cortical projection. Because the inhibitory collaterals are sparse and weak, their role in striatal network dynamics is puzzling. However, here we show by simulation of a striatal inhibitory network model composed of spiking neurons that cells form assemblies that fire in sequential coherent episodes and display complex identity-temporal spiking patterns even when cortical excitation is simply constant or fluctuating noisily. Strongly correlated large-scale firing rate fluctuations on slow behaviorally relevant timescales of hundreds of milliseconds are shown by members of the same assembly whereas members of different assemblies show strong negative correlation, and we show how randomly connected spiking networks can generate this activity. Cells display highly irregular spiking with high coefficients of variation, broadly distributed low firing rates, and interspike interval distributions that are consistent with exponentially tailed power laws. Although firing rates vary coherently on slow timescales, precise spiking synchronization is absent in general. Our model only requires the minimal but striatally realistic assumptions of sparse to intermediate random connectivity, weak inhibitory synapses, and sufficient cortical excitation so that some cells are depolarized above the firing threshold during up states. Our results are in good qualitative agreement with experimental studies, consistent with recently determined striatal anatomy and physiology, and support a new view of endogenously generated metastable state switching dynamics of the striatal network underlying its information processing operations.
Cain, Stuart M; Tyson, John R; Jones, Karen L; Snutch, Terrance P
2015-06-01
Burst-firing in distinct subsets of thalamic relay (TR) neurons is thought to be a key requirement for the propagation of absence seizures. However, in the well-regarded Genetic Absence Epilepsy Rats from Strasbourg (GAERS) model as yet there has been no link described between burst-firing in TR neurons and spike-and-wave discharges (SWDs). GAERS ventrobasal (VB) neurons are a specific subset of TR neurons that do not normally display burst-firing during absence seizures in the GAERS model, and here, we assessed the underlying relationship of VB burst-firing with Ih and T-type calcium currents between GAERS and non-epileptic control (NEC) animals. In response to 200-ms hyperpolarizing current injections, adult epileptic but not pre-epileptic GAERS VB neurons displayed suppressed burst-firing compared to NEC. In response to longer duration 1,000-ms hyperpolarizing current injections, both pre-epileptic and epileptic GAERS VB neurons required significantly more hyperpolarizing current injection to burst-fire than those of NEC animals. The current density of the Hyperpolarization and Cyclic Nucleotide-activated (HCN) current (Ih) was found to be increased in GAERS VB neurons, and the blockade of Ih relieved the suppressed burst-firing in both pre-epileptic P15-P20 and adult animals. In support, levels of HCN-1 and HCN-3 isoform channel proteins were increased in GAERS VB thalamic tissue. T-type calcium channel whole-cell currents were found to be decreased in P7-P9 GAERS VB neurons, and also noted was a decrease in CaV3.1 mRNA and protein levels in adults. Z944, a potent T-type calcium channel blocker with anti-epileptic properties, completely abolished hyperpolarization-induced VB burst-firing in both NEC and GAERS VB neurons.
Specific responses of human hippocampal neurons are associated with better memory.
Suthana, Nanthia A; Parikshak, Neelroop N; Ekstrom, Arne D; Ison, Matias J; Knowlton, Barbara J; Bookheimer, Susan Y; Fried, Itzhak
2015-08-18
A population of human hippocampal neurons has shown responses to individual concepts (e.g., Jennifer Aniston) that generalize to different instances of the concept. However, recordings from the rodent hippocampus suggest an important function of these neurons is their ability to discriminate overlapping representations, or pattern separate, a process that may facilitate discrimination of similar events for successful memory. In the current study, we explored whether human hippocampal neurons can also demonstrate the ability to discriminate between overlapping representations and whether this selectivity could be directly related to memory performance. We show that among medial temporal lobe (MTL) neurons, certain populations of neurons are selective for a previously studied (target) image in that they show a significant decrease in firing rate to very similar (lure) images. We found that a greater proportion of these neurons can be found in the hippocampus compared with other MTL regions, and that memory for individual items is correlated to the degree of selectivity of hippocampal neurons responsive to those items. Moreover, a greater proportion of hippocampal neurons showed selective firing for target images in good compared with poor performers, with overall memory performance correlated with hippocampal selectivity. In contrast, selectivity in other MTL regions was not associated with memory performance. These findings show that a substantial proportion of human hippocampal neurons encode specific memories that support the discrimination of overlapping representations. These results also provide previously unidentified evidence consistent with a unique role of the human hippocampus in orthogonalization of representations in declarative memory.
Kim, Sei Eun; Lee, Seul Yi; Blanco, Cynthia L; Kim, Jun Hee
2014-08-20
The human fetus starts to hear and undergoes major developmental changes in the auditory system during the third trimester of pregnancy. Although there are significant data regarding development of the auditory system in rodents, changes in intrinsic properties and synaptic function of auditory neurons in developing primate brain at hearing onset are poorly understood. We performed whole-cell patch-clamp recordings of principal neurons in the medial nucleus of trapezoid body (MNTB) in preterm and term baboon brainstem slices to study the structural and functional maturation of auditory synapses. Each MNTB principal neuron received an excitatory input from a single calyx of Held terminal, and this one-to-one pattern of innervation was already formed in preterm baboons delivered at 67% of normal gestation. There was no difference in frequency or amplitude of spontaneous excitatory postsynaptic synaptic currents between preterm and term MNTB neurons. In contrast, the frequency of spontaneous GABA(A)/glycine receptor-mediated inhibitory postsynaptic synaptic currents, which were prevalent in preterm MNTB neurons, was significantly reduced in term MNTB neurons. Preterm MNTB neurons had a higher input resistance than term neurons and fired in bursts, whereas term MNTB neurons fired a single action potential in response to suprathreshold current injection. The maturation of intrinsic properties and dominance of excitatory inputs in the primate MNTB allow it to take on its mature role as a fast and reliable relay synapse. Copyright © 2014 the authors 0270-6474/14/3411399-06$15.00/0.
Optimal firing rate estimation
NASA Technical Reports Server (NTRS)
Paulin, M. G.; Hoffman, L. F.
2001-01-01
We define a measure for evaluating the quality of a predictive model of the behavior of a spiking neuron. This measure, information gain per spike (Is), indicates how much more information is provided by the model than if the prediction were made by specifying the neuron's average firing rate over the same time period. We apply a maximum Is criterion to optimize the performance of Gaussian smoothing filters for estimating neural firing rates. With data from bullfrog vestibular semicircular canal neurons and data from simulated integrate-and-fire neurons, the optimal bandwidth for firing rate estimation is typically similar to the average firing rate. Precise timing and average rate models are limiting cases that perform poorly. We estimate that bullfrog semicircular canal sensory neurons transmit in the order of 1 bit of stimulus-related information per spike.
Physiological modulators of Kv3.1 channels adjust firing patterns of auditory brain stem neurons.
Brown, Maile R; El-Hassar, Lynda; Zhang, Yalan; Alvaro, Giuseppe; Large, Charles H; Kaczmarek, Leonard K
2016-07-01
Many rapidly firing neurons, including those in the medial nucleus of the trapezoid body (MNTB) in the auditory brain stem, express "high threshold" voltage-gated Kv3.1 potassium channels that activate only at positive potentials and are required for stimuli to generate rapid trains of actions potentials. We now describe the actions of two imidazolidinedione derivatives, AUT1 and AUT2, which modulate Kv3.1 channels. Using Chinese hamster ovary cells stably expressing rat Kv3.1 channels, we found that lower concentrations of these compounds shift the voltage of activation of Kv3.1 currents toward negative potentials, increasing currents evoked by depolarization from typical neuronal resting potentials. Single-channel recordings also showed that AUT1 shifted the open probability of Kv3.1 to more negative potentials. Higher concentrations of AUT2 also shifted inactivation to negative potentials. The effects of lower and higher concentrations could be mimicked in numerical simulations by increasing rates of activation and inactivation respectively, with no change in intrinsic voltage dependence. In brain slice recordings of mouse MNTB neurons, both AUT1 and AUT2 modulated firing rate at high rates of stimulation, a result predicted by numerical simulations. Our results suggest that pharmaceutical modulation of Kv3.1 currents represents a novel avenue for manipulation of neuronal excitability and has the potential for therapeutic benefit in the treatment of hearing disorders. Copyright © 2016 the American Physiological Society.
Physiological modulators of Kv3.1 channels adjust firing patterns of auditory brain stem neurons
Brown, Maile R.; El-Hassar, Lynda; Zhang, Yalan; Alvaro, Giuseppe; Large, Charles H.
2016-01-01
Many rapidly firing neurons, including those in the medial nucleus of the trapezoid body (MNTB) in the auditory brain stem, express “high threshold” voltage-gated Kv3.1 potassium channels that activate only at positive potentials and are required for stimuli to generate rapid trains of actions potentials. We now describe the actions of two imidazolidinedione derivatives, AUT1 and AUT2, which modulate Kv3.1 channels. Using Chinese hamster ovary cells stably expressing rat Kv3.1 channels, we found that lower concentrations of these compounds shift the voltage of activation of Kv3.1 currents toward negative potentials, increasing currents evoked by depolarization from typical neuronal resting potentials. Single-channel recordings also showed that AUT1 shifted the open probability of Kv3.1 to more negative potentials. Higher concentrations of AUT2 also shifted inactivation to negative potentials. The effects of lower and higher concentrations could be mimicked in numerical simulations by increasing rates of activation and inactivation respectively, with no change in intrinsic voltage dependence. In brain slice recordings of mouse MNTB neurons, both AUT1 and AUT2 modulated firing rate at high rates of stimulation, a result predicted by numerical simulations. Our results suggest that pharmaceutical modulation of Kv3.1 currents represents a novel avenue for manipulation of neuronal excitability and has the potential for therapeutic benefit in the treatment of hearing disorders. PMID:27052580
Logarithmic Compression of Sensory Signals within the Dendritic Tree of a Collision-Sensitive Neuron
2012-01-01
Neurons in a variety of species, both vertebrate and invertebrate, encode the kinematics of objects approaching on a collision course through a time-varying firing rate profile that initially increases, then peaks, and eventually decays as collision becomes imminent. In this temporal profile, the peak firing rate signals when the approaching object's subtended size reaches an angular threshold, an event which has been related to the timing of escape behaviors. In a locust neuron called the lobula giant motion detector (LGMD), the biophysical basis of this angular threshold computation relies on a multiplicative combination of the object's angular size and speed, achieved through a logarithmic-exponential transform. To understand how this transform is implemented, we modeled the encoding of angular velocity along the pathway leading to the LGMD based on the experimentally determined activation pattern of its presynaptic neurons. These simulations show that the logarithmic transform of angular speed occurs between the synaptic conductances activated by the approaching object onto the LGMD's dendritic tree and its membrane potential at the spike initiation zone. Thus, we demonstrate an example of how a single neuron's dendritic tree implements a mathematical step in a neural computation important for natural behavior. PMID:22492048
Event-driven simulations of nonlinear integrate-and-fire neurons.
Tonnelier, Arnaud; Belmabrouk, Hana; Martinez, Dominique
2007-12-01
Event-driven strategies have been used to simulate spiking neural networks exactly. Previous work is limited to linear integrate-and-fire neurons. In this note, we extend event-driven schemes to a class of nonlinear integrate-and-fire models. Results are presented for the quadratic integrate-and-fire model with instantaneous or exponential synaptic currents. Extensions to conductance-based currents and exponential integrate-and-fire neurons are discussed.
Smith, G Troy
2006-01-01
The neural circuit that controls the electric organ discharge (EOD) of the brown ghost knifefish (Apteronotus leptorhynchus) contains two spontaneous oscillators. Both pacemaker neurons in the medulla and electromotor neurons (EMNs) in the spinal cord fire spontaneously at frequencies of 500-1,000 Hz to control the EOD. These neurons continue to fire in vitro at frequencies that are highly correlated with in vivo EOD frequency. Previous studies used channel blocking drugs to pharmacologically characterize ionic currents that control high-frequency firing in pacemaker neurons. The goal of the present study was to use similar techniques to investigate ionic currents in EMNs, the other type of spontaneously active neuron in the electromotor circuit. As in pacemaker neurons, high-frequency firing of EMNs was regulated primarily by tetrodotoxin-sensitive sodium currents and by potassium currents that were sensitive to 4-aminopyridine and kappaA-conotoxin SIVA, but resistant to tetraethylammonium. EMNs, however, differed from pacemaker neurons in their sensitivity to some channel blocking drugs. Alpha-dendrotoxin, which blocks a subset of Kv1 potassium channels, increased firing rates in EMNs, but not pacemaker neurons; and the sodium channel blocker muO-conotoxin MrVIA, which reduced firing rates of pacemaker neurons, had no effect on EMNs. These results suggest that similar, but not identical, ionic currents regulate high-frequency firing in EMNs and pacemaker neurons. The differences in the ionic currents expressed in pacemaker neurons and EMNs might be related to differences in the morphology, connectivity, or function of these two cell types.
Oscillations contribute to memory consolidation by changing criticality and stability in the brain
NASA Astrophysics Data System (ADS)
Wu, Jiaxing; Skilling, Quinton; Ognjanovski, Nicolette; Aton, Sara; Zochowski, Michal
Oscillations are a universal feature of every level of brain dynamics and have been shown to contribute to many brain functions. To investigate the fundamental mechanism underpinning oscillatory activity, the properties of heterogeneous networks are compared in situations with and without oscillations. Our results show that both network criticality and stability are changed in the presence of oscillations. Criticality describes the network state of neuronal avalanche, a cascade of bursts of action potential firing in neural network. Stability measures how stable the spike timing relationship between neuron pairs is over time. Using a detailed spiking model, we found that the branching parameter σ changes relative to oscillation and structural network properties, corresponding to transmission among different critical states. Also, analysis of functional network structures shows that the oscillation helps to stabilize neuronal representation of memory. Further, quantitatively similar results are observed in biological data recorded in vivo. In summary, we have observed that, by regulating the neuronal firing pattern, oscillations affect both criticality and stability properties of the network, and thus contribute to memory formation.
Phumsatitpong, Chayarndorn; Moenter, Suzanne M
2018-01-01
Gonadotropin-releasing hormone (GnRH) neurons are the final central regulators of reproduction, integrating various inputs that modulate fertility. Stress typically inhibits reproduction but can be stimulatory; stress effects can also be modulated by steroid milieu. Corticotropin-releasing hormone (CRH) released during the stress response may suppress reproduction independent of downstream glucocorticoids. We hypothesized CRH suppresses fertility by decreasing GnRH neuron firing activity. To test this, mice were ovariectomized (OVX) and either implanted with an estradiol capsule (OVX+E) or not treated further to examine the influence of estradiol on GnRH neuron response to CRH. Targeted extracellular recordings were used to record firing activity from green fluorescent protein-identified GnRH neurons in brain slices before and during CRH treatment; recordings were done in the afternoon when estradiol has a positive feedback effect to increase GnRH neuron firing. In OVX mice, CRH did not affect the firing rate of GnRH neurons. In contrast, CRH exhibited dose-dependent stimulatory (30 nM) or inhibitory (100 nM) effects on GnRH neuron firing activity in OVX+E mice; both effects were reversible. The dose-dependent effects of CRH appear to result from activation of different receptor populations; a CRH receptor type-1 agonist increased firing activity in GnRH neurons, whereas a CRH receptor type-2 agonist decreased firing activity. CRH and specific agonists also differentially regulated short-term burst frequency and burst properties, including burst duration, spikes/burst, and/or intraburst interval. These results indicate that CRH alters GnRH neuron activity and that estradiol is required for CRH to exert both stimulatory and inhibitory effects on GnRH neurons. Copyright © 2018 Endocrine Society.
Synaptic and intrinsic activation of GABAergic neurons in the cardiorespiratory brainstem network.
Frank, Julie G; Mendelowitz, David
2012-01-01
GABAergic pathways in the brainstem play an essential role in respiratory rhythmogenesis and interactions between the respiratory and cardiovascular neuronal control networks. However, little is known about the identity and function of these GABAergic inhibitory neurons and what determines their activity. In this study we have identified a population of GABAergic neurons in the ventrolateral medulla that receive increased excitatory post-synaptic potentials during inspiration, but also have spontaneous firing in the absence of synaptic input. Using transgenic mice that express GFP under the control of the Gad1 (GAD67) gene promoter, we determined that this population of GABAergic neurons is in close apposition to cardioinhibitory parasympathetic cardiac neurons in the nucleus ambiguus (NA). These neurons fire in synchronization with inspiratory activity. Although they receive excitatory glutamatergic synaptic inputs during inspiration, this excitatory neurotransmission was not altered by blocking nicotinic receptors, and many of these GABAergic neurons continue to fire after synaptic blockade. The spontaneous firing in these GABAergic neurons was not altered by the voltage-gated calcium channel blocker cadmium chloride that blocks both neurotransmission to these neurons and voltage-gated Ca(2+) currents, but spontaneous firing was diminished by riluzole, demonstrating a role of persistent sodium channels in the spontaneous firing in these cardiorespiratory GABAergic neurons that possess a pacemaker phenotype. The spontaneously firing GABAergic neurons identified in this study that increase their activity during inspiration would support respiratory rhythm generation if they acted primarily to inhibit post-inspiratory neurons and thereby release inspiration neurons to increase their activity. This population of inspiratory-modulated GABAergic neurons could also play a role in inhibiting neurons that are most active during expiration and provide a framework for respiratory sinus arrhythmia as there is an increase in heart rate during inspiration that occurs via inhibition of premotor parasympathetic cardioinhibitory neurons in the NA during inspiration.
Elliott, Terry; Kramer, Jörg
2002-10-01
We couple a previously studied, biologically inspired neurotrophic model of activity-dependent competitive synaptic plasticity and neuronal development to a neuromorphic retina chip. Using this system, we examine the development and refinement of a topographic mapping between an array of afferent neurons (the retinal ganglion cells) and an array of target neurons. We find that the plasticity model can indeed drive topographic refinement in the presence of afferent activity patterns generated by a real-world device. We examine the resilience of the developing system to the presence of high levels of noise by adjusting the spontaneous firing rate of the silicon neurons.
Schilström, Björn; Konradsson-Geuken, Asa; Ivanov, Vladimir; Gertow, Jens; Feltmann, Kristin; Marcus, Monica M; Jardemark, Kent; Svensson, Torgny H
2011-05-01
Escitalopram, the S-enantiomer of citalopram, possesses superior efficacy compared to other selective serotonin reuptake inhibitors (SSRIs) in the treatment of major depression. Escitalopram binds to an allosteric site on the serotonin transporter, which further enhances the blockade of serotonin reuptake, whereas R-citalopram antagonizes this positive allosteric modulation. Escitalopram's effects on neurotransmitters other than serotonin, for example, dopamine and glutamate, are not well studied. Therefore, we here studied the effects of escitalopram, citalopram, and R-citalopram on dopamine cell firing in the ventral tegmental area, using single-cell recording in vivo and on NMDA receptor-mediated currents in pyramidal neurons in the medial prefrontal cortex using in vitro electrophysiology in rats. The cognitive effects of escitalopram and citalopram were also compared using the novel object recognition test. Escitalopram (40-640 μg/kg i.v.) increased both firing rate and burst firing of dopaminergic neurons, whereas citalopram (80-1280 μg/kg) had no effect on firing rate and only increased burst firing at high dosage. R-citalopram (40-640 μg/kg) had no significant effects. R-citalopram (320 μg/kg) antagonized the effects of escitalopram (320 μg/kg). A very low concentration of escitalopram (5 nM), but not citalopram (10 nM) or R-citalopram (5 nM), potentiated NMDA-induced currents in pyramidal neurons. Escitalopram's effect was antagonized by R-citalopram and blocked by the dopamine D(1) receptor antagonist SCH23390. Escitalopram, but not citalopram, improved recognition memory. Our data suggest that the excitatory effect of escitalopram on dopaminergic and NMDA receptor-mediated neurotransmission may have bearing on its cognitive-enhancing effect and superior efficacy compared to other SSRIs in major depression. Copyright © 2010 Wiley-Liss, Inc.
A plausible neural circuit for decision making and its formation based on reinforcement learning.
Wei, Hui; Dai, Dawei; Bu, Yijie
2017-06-01
A human's, or lower insects', behavior is dominated by its nervous system. Each stable behavior has its own inner steps and control rules, and is regulated by a neural circuit. Understanding how the brain influences perception, thought, and behavior is a central mandate of neuroscience. The phototactic flight of insects is a widely observed deterministic behavior. Since its movement is not stochastic, the behavior should be dominated by a neural circuit. Based on the basic firing characteristics of biological neurons and the neural circuit's constitution, we designed a plausible neural circuit for this phototactic behavior from logic perspective. The circuit's output layer, which generates a stable spike firing rate to encode flight commands, controls the insect's angular velocity when flying. The firing pattern and connection type of excitatory and inhibitory neurons are considered in this computational model. We simulated the circuit's information processing using a distributed PC array, and used the real-time average firing rate of output neuron clusters to drive a flying behavior simulation. In this paper, we also explored how a correct neural decision circuit is generated from network flow view through a bee's behavior experiment based on the reward and punishment feedback mechanism. The significance of this study: firstly, we designed a neural circuit to achieve the behavioral logic rules by strictly following the electrophysiological characteristics of biological neurons and anatomical facts. Secondly, our circuit's generality permits the design and implementation of behavioral logic rules based on the most general information processing and activity mode of biological neurons. Thirdly, through computer simulation, we achieved new understanding about the cooperative condition upon which multi-neurons achieve some behavioral control. Fourthly, this study aims in understanding the information encoding mechanism and how neural circuits achieve behavior control. Finally, this study also helps establish a transitional bridge between the microscopic activity of the nervous system and macroscopic animal behavior.
Genealogy of the "grandmother cell".
Gross, Charles G
2002-10-01
A "grandmother cell" is a hypothetical neuron that responds only to a highly complex, specific, and meaningful stimulus, such as the image of one's grandmother. The term originated in a parable Jerry Lettvin told in 1967. A similar concept had been systematically developed a few years earlier by Jerzy Konorski who called such cells "gnostic" units. This essay discusses the origin, influence, and current status of these terms and of the alternative view that complex stimuli are represented by the pattern of firing across ensembles of neurons.
Ronzitti, Emiliano; Conti, Rossella; Zampini, Valeria; Tanese, Dimitrii; Klapoetke, Nathan; Boyden, Edward S.; Papagiakoumou, Eirini
2017-01-01
Optogenetic neuronal network manipulation promises to unravel a long-standing mystery in neuroscience: how does microcircuit activity relate causally to behavioral and pathological states? The challenge to evoke spikes with high spatial and temporal complexity necessitates further joint development of light-delivery approaches and custom opsins. Two-photon (2P) light-targeting strategies demonstrated in-depth generation of action potentials in photosensitive neurons both in vitro and in vivo, but thus far lack the temporal precision necessary to induce precisely timed spiking events. Here, we show that efficient current integration enabled by 2P holographic amplified laser illumination of Chronos, a highly light-sensitive and fast opsin, can evoke spikes with submillisecond precision and repeated firing up to 100 Hz in brain slices from Swiss male mice. These results pave the way for optogenetic manipulation with the spatial and temporal sophistication necessary to mimic natural microcircuit activity. SIGNIFICANCE STATEMENT To reveal causal links between neuronal activity and behavior, it is necessary to develop experimental strategies to induce spatially and temporally sophisticated perturbation of network microcircuits. Two-photon computer generated holography (2P-CGH) recently demonstrated 3D optogenetic control of selected pools of neurons with single-cell accuracy in depth in the brain. Here, we show that exciting the fast opsin Chronos with amplified laser 2P-CGH enables cellular-resolution targeting with unprecedented temporal control, driving spiking up to 100 Hz with submillisecond onset precision using low laser power densities. This system achieves a unique combination of spatial flexibility and temporal precision needed to pattern optogenetically inputs that mimic natural neuronal network activity patterns. PMID:28972125
Effects of dendritic load on the firing frequency of oscillating neurons.
Schwemmer, Michael A; Lewis, Timothy J
2011-03-01
We study the effects of passive dendritic properties on the dynamics of neuronal oscillators. We find that the addition of a passive dendrite can sometimes have counterintuitive effects on firing frequency. Specifically, the addition of a hyperpolarized passive dendritic load can either increase, decrease, or have negligible effects on firing frequency. We use the theory of weak coupling to derive phase equations for "ball-and-stick" model neurons and two-compartment model neurons. We then develop a framework for understanding how the addition of passive dendrites modulates the frequency of neuronal oscillators. We show that the average value of the neuronal oscillator's phase response curves measures the sensitivity of the neuron's firing rate to the dendritic load, including whether the addition of the dendrite causes an increase or decrease in firing frequency. We interpret this finding in terms of to the slope of the neuronal oscillator's frequency-applied current curve. We also show that equivalent results exist for constant and noisy point-source input to the dendrite. We note that the results are not specific to neurons but are applicable to any oscillator subject to a passive load.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moreno-Bote, Ruben; Parga, Nestor; Center for Theoretical Neuroscience, Center for Neurobiology and Behavior, Columbia University, New York 10032-2695
2006-01-20
An analytical description of the response properties of simple but realistic neuron models in the presence of noise is still lacking. We determine completely up to the second order the firing statistics of a single and a pair of leaky integrate-and-fire neurons receiving some common slowly filtered white noise. In particular, the auto- and cross-correlation functions of the output spike trains of pairs of cells are obtained from an improvement of the adiabatic approximation introduced previously by Moreno-Bote and Parga [Phys. Rev. Lett. 92, 028102 (2004)]. These two functions define the firing variability and firing synchronization between neurons, and aremore » of much importance for understanding neuron communication.« less
Sakurai, Yoshio; Song, Kichan; Tachibana, Shota; Takahashi, Susumu
2014-01-01
In this review, we focus on neuronal operant conditioning in which increments in neuronal activities are directly rewarded without behaviors. We discuss the potential of this approach to elucidate neuronal plasticity for enhancing specific brain functions and its interaction with the progress in neurorehabilitation and brain-machine interfaces. The key to-be-conditioned activities that this paper emphasizes are synchronous and oscillatory firings of multiple neurons that reflect activities of cell assemblies. First, we introduce certain well-known studies on neuronal operant conditioning in which conditioned enhancements of neuronal firing were reported in animals and humans. These studies demonstrated the feasibility of volitional control over neuronal activity. Second, we refer to the recent studies on operant conditioning of synchrony and oscillation of neuronal activities. In particular, we introduce a recent study showing volitional enhancement of oscillatory activity in monkey motor cortex and our study showing selective enhancement of firing synchrony of neighboring neurons in rat hippocampus. Third, we discuss the reasons for emphasizing firing synchrony and oscillation in neuronal operant conditioning, the main reason being that they reflect the activities of cell assemblies, which have been suggested to be basic neuronal codes representing information in the brain. Finally, we discuss the interaction of neuronal operant conditioning with neurorehabilitation and brain-machine interface (BMI). We argue that synchrony and oscillation of neuronal firing are the key activities required for developing both reliable neurorehabilitation and high-performance BMI. Further, we conclude that research of neuronal operant conditioning, neurorehabilitation, BMI, and system neuroscience will produce findings applicable to these interrelated fields, and neuronal synchrony and oscillation can be a common important bridge among all of them. PMID:24567704
Sakurai, Yoshio; Song, Kichan; Tachibana, Shota; Takahashi, Susumu
2014-01-01
In this review, we focus on neuronal operant conditioning in which increments in neuronal activities are directly rewarded without behaviors. We discuss the potential of this approach to elucidate neuronal plasticity for enhancing specific brain functions and its interaction with the progress in neurorehabilitation and brain-machine interfaces. The key to-be-conditioned activities that this paper emphasizes are synchronous and oscillatory firings of multiple neurons that reflect activities of cell assemblies. First, we introduce certain well-known studies on neuronal operant conditioning in which conditioned enhancements of neuronal firing were reported in animals and humans. These studies demonstrated the feasibility of volitional control over neuronal activity. Second, we refer to the recent studies on operant conditioning of synchrony and oscillation of neuronal activities. In particular, we introduce a recent study showing volitional enhancement of oscillatory activity in monkey motor cortex and our study showing selective enhancement of firing synchrony of neighboring neurons in rat hippocampus. Third, we discuss the reasons for emphasizing firing synchrony and oscillation in neuronal operant conditioning, the main reason being that they reflect the activities of cell assemblies, which have been suggested to be basic neuronal codes representing information in the brain. Finally, we discuss the interaction of neuronal operant conditioning with neurorehabilitation and brain-machine interface (BMI). We argue that synchrony and oscillation of neuronal firing are the key activities required for developing both reliable neurorehabilitation and high-performance BMI. Further, we conclude that research of neuronal operant conditioning, neurorehabilitation, BMI, and system neuroscience will produce findings applicable to these interrelated fields, and neuronal synchrony and oscillation can be a common important bridge among all of them.
Ranels, Heather J; Griffin, John D
2003-02-21
In response to an immune system challenge with lipopolysaccharide (LPS), recent work has shown that Fos immunoreactivity is displayed by neurons in the ventromedial preoptic area of the hypothalamus (VMPO). In addition, neurons in this region show distinct axonal projections to the anterior perifornical area (APFx) and the paraventricular nucleus (PVN). It has been hypothesized that neurons within the VMPO integrate their local responses to temperature with changes in firing activity that result from LPS induced production of prostaglandin E(2) (PGE(2)). This may be an important mechanism by which the set-point regulation of thermoeffector neurons in the APFx and PVN is altered, resulting in hyperthermia. To characterize the firing rate activity of VMPO neurons, single-unit recordings were made of neuronal extracellular activity in rat hypothalamic tissue slices. Based on the slope of firing rate as a function of tissue temperature, neurons were classified as either warm sensitive or temperature insensitive. Neurons were then treated with PGE(2) (200 nM) while tissue temperature was held at a constant level ( approximately 36 degrees C). The majority of temperature insensitive neurons responded to PGE(2) with an increase in firing rate activity, while warm sensitive neurons showed a reduction in firing rate. This suggests that both warm sensitive and temperature insensitive neurons in the VMPO may play critical and contrasting roles in the production of a fever during an acute phase response to infection.
Venugopal, S; Boulant, J A; Chen, Z; Travers, J B
2010-06-16
Neurons in the lower brainstem that control consummatory behavior are widely distributed in the reticular formation (RF) of the pons and medulla. The intrinsic membrane properties of neurons within this distributed system shape complex excitatory and inhibitory inputs from both orosensory and central structures implicated in homeostatic control to produce coordinated oromotor patterns. The current study explored the intrinsic membrane properties of neurons in the intermediate subdivision of the medullary reticular formation (IRt). Neurons in the IRt receive input from the overlying (gustatory) nucleus of the solitary tract and project to the oromotor nuclei. Recent behavioral pharmacology studies as well as computational modeling suggest that inhibition in the IRt plays an important role in the transition from a taste-initiated oromotor pattern of ingestion to one of rejection. The present study explored the impact of hyperpolarization on membrane properties. In response to depolarization, neurons responded with either a tonic discharge, an irregular/burst pattern or were spike-adaptive. A hyperpolarizing pre-pulse modulated the excitability of most (82%) IRt neurons to subsequent depolarization. Instances of both increased (30%) and decreased (52%) excitability were observed. Currents induced by the hyperpolarization included an outward 4-aminopyridine (4-AP) sensitive K+ current that suppressed excitability and an inward cation current that increased excitability. These currents are also present in other subpopulations of RF neurons that influence the oromotor nuclei and we discuss how these currents could alter firing characteristics to impact pattern generation. 2010 IBRO. Published by Elsevier Ltd. All rights reserved.
Ishikawa, Masago; Otaka, Mami; Huang, Yanhua H.; Schlüter, Oliver M.
2015-01-01
Background: The lateral habenula is a brain region that has been critically implicated in modulating negative emotional states and responses to aversive stimuli. Exposure to addictive drugs such as cocaine negatively impacts affective states, an effect persisting longer than acute drug effects. However, the mechanisms of this effect are poorly understood. We hypothesized that drugs of abuse, such as cocaine, may contribute to drug-induced negative affective states by altering the firing properties of lateral habenula neurons, thus changing the signaling patterns from the lateral habenula to downstream circuits. Methods: Using whole-cell current-clamp recording of acutely prepared brain slices of rats after various periods of withdrawal from cocaine self-administration, we characterized an important heterogeneous subregion of the lateral habenula based on membrane properties. Results: We found two major relevant neuronal subtypes: burst firing neurons and regular spiking neurons. We also found that lateral habenula regular spiking neurons had higher membrane excitability for at least 7 days following cocaine self-administration, likely due to a greater membrane resistance. Both the increase in lateral habenula excitability and membrane resistance returned to baseline when tested after a more prolonged period of 45 days of withdrawal. Conclusion: This is the first study to look at intrinsic lateral habenula neuron properties following cocaine exposure beyond acute drug effects. These results may help to explain how cocaine and other drugs negatively impact affect states. PMID:25548105
Dynamic interneuron-principal cell interplay leads to a specific pattern of in vitro ictogenesis.
Lévesque, Maxime; Chen, Li-Yuan; Hamidi, Shabnam; Avoli, Massimo
2018-07-01
Ictal discharges induced by 4-aminopyridine in the in vitro rodent entorhinal cortex present with either low-voltage fast or sudden onset patterns. The role of interneurons in initiating low-voltage fast onset ictal discharges is well established but the processes leading to sudden onset ictal discharges remain unclear. We analysed here the participation of interneurons (n = 75) and principal cells (n = 13) in the sudden onset pattern by employing in vitro tetrode wire recordings in the entorhinal cortex of brain slices from Sprague-Dawley rats. Ictal discharges emerged from a background of frequently occurring interictal spikes that were associated to a specific interneuron/principal cell interplay. High rates of interneuron firing occurred 12 ms before interictal spike onset while principal cells fired later during low interneuron firing. In contrast, the onset of sudden ictal discharges was characterized by increased firing from principal cells 627 ms before ictal onset whereas interneurons increased their firing rates 161 ms before ictal onset. Our data show that sudden onset ictogenesis is associated with frequently occurring interictal spikes resting on the interplay between interneurons and principal cells while ictal discharges stem from enhanced principal cell firing leading to increased interneuron activity. These findings indicate that specific patterns of interactions between interneurons and principal cells shape interictal and ictal discharges with sudden onset in the rodent entorhinal cortex. We propose that specific neuronal interactions lead to the generation of distinct onset patterns in focal epileptic disorders. Copyright © 2018 Elsevier Inc. All rights reserved.
Bi, Zedong; Zhou, Changsong
2016-01-01
In neural systems, synaptic plasticity is usually driven by spike trains. Due to the inherent noises of neurons and synapses as well as the randomness of connection details, spike trains typically exhibit variability such as spatial randomness and temporal stochasticity, resulting in variability of synaptic changes under plasticity, which we call efficacy variability. How the variability of spike trains influences the efficacy variability of synapses remains unclear. In this paper, we try to understand this influence under pair-wise additive spike-timing dependent plasticity (STDP) when the mean strength of plastic synapses into a neuron is bounded (synaptic homeostasis). Specifically, we systematically study, analytically and numerically, how four aspects of statistical features, i.e., synchronous firing, burstiness/regularity, heterogeneity of rates and heterogeneity of cross-correlations, as well as their interactions influence the efficacy variability in converging motifs (simple networks in which one neuron receives from many other neurons). Neurons (including the post-synaptic neuron) in a converging motif generate spikes according to statistical models with tunable parameters. In this way, we can explicitly control the statistics of the spike patterns, and investigate their influence onto the efficacy variability, without worrying about the feedback from synaptic changes onto the dynamics of the post-synaptic neuron. We separate efficacy variability into two parts: the drift part (DriftV) induced by the heterogeneity of change rates of different synapses, and the diffusion part (DiffV) induced by weight diffusion caused by stochasticity of spike trains. Our main findings are: (1) synchronous firing and burstiness tend to increase DiffV, (2) heterogeneity of rates induces DriftV when potentiation and depression in STDP are not balanced, and (3) heterogeneity of cross-correlations induces DriftV together with heterogeneity of rates. We anticipate our work important for understanding functional processes of neuronal networks (such as memory) and neural development. PMID:26941634
Burst Firing in Bee Gustatory Neurons Prevents Adaptation.
Miriyala, Ashwin; Kessler, Sébastien; Rind, F Claire; Wright, Geraldine A
2018-05-01
Animals detect changes in the environment using modality-specific, peripheral sensory neurons. The insect gustatory system encodes tastant identity and concentration through the independent firing of gustatory receptor neurons (GRNs) that spike rapidly at stimulus onset and quickly adapt. Here, we show the first evidence that concentrated sugar evokes a temporally structured burst pattern of spiking involving two GRNs within the gustatory sensilla of bumblebees. Bursts of spikes resulted when a sucrose-activated GRN was inhibited by another GRN at a frequency of ∼22 Hz during the first 1 s of stimulation. Pharmacological blockade of gap junctions abolished bursting, indicating that bee GRNs have electrical synapses that produce a temporal pattern of spikes when one GRN is activated by a sugar ligand. Bursting permitted bee GRNs to maintain a high rate of spiking and to exhibit the slowest rate of adaptation of any insect species. Feeding bout duration correlated with coherent bursting; only sugar concentrations that produced bursting evoked the bumblebee's feeding reflex. Volume of solution imbibed was a direct function of time in contact with food. We propose that gap junctions among GRNs enable a sustained rate of GRN spiking that is necessary to drive continuous feeding by the bee proboscis. Copyright © 2018 Elsevier Ltd. All rights reserved.
Lutas, Andrew; Birnbaumer, Lutz
2014-01-01
Neurons use glucose to fuel glycolysis and provide substrates for mitochondrial respiration, but neurons can also use alternative fuels that bypass glycolysis and feed directly into mitochondria. To determine whether neuronal pacemaking depends on active glucose metabolism, we switched the metabolic fuel from glucose to alternative fuels, lactate or β-hydroxybutyrate, while monitoring the spontaneous firing of GABAergic neurons in mouse substantia nigra pars reticulata (SNr) brain slices. We found that alternative fuels, in the absence of glucose, sustained SNr spontaneous firing at basal rates, but glycolysis may still be supported by glycogen in the absence of glucose. To prevent any glycogen-fueled glycolysis, we directly inhibited glycolysis using either 2-deoxyglucose or iodoacetic acid. Inhibiting glycolysis in the presence of alternative fuels lowered SNr firing to a slower sustained firing rate. Surprisingly, we found that the decrease in SNr firing was not mediated by ATP-sensitive potassium (KATP) channel activity, but if we lowered the perfusion flow rate or omitted the alternative fuel, KATP channels were activated and could silence SNr firing. The KATP-independent slowing of SNr firing that occurred with glycolytic inhibition in the presence of alternative fuels was consistent with a decrease in a nonselective cationic conductance. Although mitochondrial metabolism alone can prevent severe energy deprivation and KATP channel activation in SNr neurons, active glucose metabolism appears important for keeping open a class of ion channels that is crucial for the high spontaneous firing rate of SNr neurons. PMID:25471572
The rat suprachiasmatic nucleus: the master clock ticks at 30 Hz
Tsuji, Takahiro; Tsuji, Chiharu; Ludwig, Mike
2016-01-01
Key points Light‐responsive neurones in the rat suprachiasmatic nucleus discharge with a harmonic distribution of interspike intervals, whereas unresponsive neurones seldom do.This harmonic patterning has a fundamental frequency of close to 30 Hz, and is the same in light‐on cells as in light‐off cells, and is unaffected by exposure to light.Light‐on cells are more active than light‐off cells in both subjective day and subjective night, and both light‐on cells and light‐off cells respond more strongly to changes in light intensity during the subjective night than during the subjective day.Paired recordings indicate that the discharge of adjacent light‐responsive cells is very tightly synchronized.The gap junction inhibitor carbenoxolone increases the spontaneous activity of suprachiasmatic nucleus neurones but does not block the harmonic discharge patterning. Abstract The suprachiasmatic nucleus (SCN) of the hypothalamus has an essential role in orchestrating circadian rhythms of behaviour and physiology. In the present study, we recorded from single SCN neurons in urethane‐anaesthetized rats, categorized them by the statistical features of their electrical activity and by their responses to light, and examined how activity in the light phase differs from activity in the dark phase. We classified cells as light‐on cells or light‐off cells according to how their firing rate changed in acute response to light, or as non‐responsive cells. In both sets of light‐responsive neurons, responses to light were stronger at subjective night than in subjective day. Neuronal firing patterns were analysed by constructing hazard functions from interspike interval data. For most light‐responsive cells, the hazard functions showed a multimodal distribution, with a harmonic sequence of modes, indicating that spike activity was driven by an oscillatory input with a fundamental frequency of close to 30 Hz; this harmonic pattern was rarely seen in non‐responsive SCN cells. The frequency of the rhythm was the same in light‐on cells as in light‐off cells, was the same in subjective day as at subjective night, and was unaffected by exposure to light. Paired recordings indicated that the discharge of adjacent light‐responsive neurons was very tightly synchronized, consistent with electrical coupling. PMID:27061101
Effects of channel noise on firing coherence of small-world Hodgkin-Huxley neuronal networks
NASA Astrophysics Data System (ADS)
Sun, X. J.; Lei, J. Z.; Perc, M.; Lu, Q. S.; Lv, S. J.
2011-01-01
We investigate the effects of channel noise on firing coherence of Watts-Strogatz small-world networks consisting of biophysically realistic HH neurons having a fraction of blocked voltage-gated sodium and potassium ion channels embedded in their neuronal membranes. The intensity of channel noise is determined by the number of non-blocked ion channels, which depends on the fraction of working ion channels and the membrane patch size with the assumption of homogeneous ion channel density. We find that firing coherence of the neuronal network can be either enhanced or reduced depending on the source of channel noise. As shown in this paper, sodium channel noise reduces firing coherence of neuronal networks; in contrast, potassium channel noise enhances it. Furthermore, compared with potassium channel noise, sodium channel noise plays a dominant role in affecting firing coherence of the neuronal network. Moreover, we declare that the observed phenomena are independent of the rewiring probability.
Wang, Shan-shan; Wei, Chun-ling; Liu, Zhi-qiang; Ren, Wei
2011-02-25
Burst firing of dopaminergic neurons in ventral tegmental area (VTA) induces a large transient increase in synaptic dopamine (DA) release and thus is considered the reward-related signal. But the mechanisms of burst generation of dopaminergic neuron still remain unclear. This experiment investigated the burst firing of VTA dopaminergic neurons in rat midbrain slices perfused with carbachol and L-glutamate individually or simultaneously to understand the neurotransmitter mechanism underlying burst generation. The results showed that bath application of carbachol (10 μmol/L) and pulse application of L-glutamate (3 mmol/L) both induced burst firing in dopaminergic neuron. Co-application of carbachol and L-glutamate induced burst firing in VTA dopaminergic cells which couldn't be induced to burst by the two chemicals separately. The result indicates that carbachol and L-glutamate co-regulate burst firing of dopaminergic neuron.
Tandon, Shashank; Keefe, Kristen A; Taha, Sharif A
2017-02-15
The lateral habenula (LHb) has been implicated in regulation of drug-seeking behaviours through aversion-mediated learning. In this study, we recorded neuronal activity in the LHb of rats during an operant task before and after ethanol-induced conditioned taste aversion (CTA) to saccharin. Ethanol-induced CTA caused significantly higher baseline firing rates in LHb neurons, as well as elevated firing rates in response to cue presentation, lever press and saccharin taste. In a separate cohort of rats, we found that bilateral LHb lesions blocked ethanol-induced CTA. Our results strongly suggest that excitation of LHb neurons is required for ethanol-induced CTA, and point towards a mechanism through which LHb firing may regulate voluntary ethanol consumption. Ethanol, like other drugs of abuse, has both rewarding and aversive properties. Previous work suggests that sensitivity to ethanol's aversive effects negatively modulates voluntary alcohol intake and thus may be important in vulnerability to developing alcohol use disorders. We previously found that rats with lesions of the lateral habenula (LHb), which is implicated in aversion-mediated learning, show accelerated escalation of voluntary ethanol consumption. To understand neural encoding in the LHb contributing to ethanol-induced aversion, we recorded neural firing in the LHb of freely behaving, water-deprived rats before and after an ethanol-induced (1.5 g kg -1 20% ethanol, i.p.) conditioned taste aversion (CTA) to saccharin taste. Ethanol-induced CTA strongly decreased motivation for saccharin in an operant task to obtain the tastant. Comparison of LHb neural firing before and after CTA induction revealed four main differences in firing properties. First, baseline firing after CTA induction was significantly higher. Second, firing evoked by cues signalling saccharin availability shifted from a pattern of primarily inhibition before CTA to primarily excitation after CTA induction. Third, CTA induction reduced the magnitude of lever press-evoked inhibition. Finally, firing rates were significantly higher during consumption of the devalued saccharin solution after CTA induction. Next, we studied sham- and LHb-lesioned rats in our operant CTA paradigm and found that LHb lesion significantly attenuated CTA effects in the operant task. Our data demonstrate the importance of LHb excitation in regulating expression of ethanol-induced aversion and suggest a mechanism for its role in modulating escalation of voluntary ethanol intake. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.
Keefe, Kristen A.; Taha, Sharif A.
2016-01-01
Key points The lateral habenula (LHb) has been implicated in regulation of drug‐seeking behaviours through aversion‐mediated learning.In this study, we recorded neuronal activity in the LHb of rats during an operant task before and after ethanol‐induced conditioned taste aversion (CTA) to saccharin.Ethanol‐induced CTA caused significantly higher baseline firing rates in LHb neurons, as well as elevated firing rates in response to cue presentation, lever press and saccharin taste.In a separate cohort of rats, we found that bilateral LHb lesions blocked ethanol‐induced CTA.Our results strongly suggest that excitation of LHb neurons is required for ethanol‐induced CTA, and point towards a mechanism through which LHb firing may regulate voluntary ethanol consumption. Abstract Ethanol, like other drugs of abuse, has both rewarding and aversive properties. Previous work suggests that sensitivity to ethanol's aversive effects negatively modulates voluntary alcohol intake and thus may be important in vulnerability to developing alcohol use disorders. We previously found that rats with lesions of the lateral habenula (LHb), which is implicated in aversion‐mediated learning, show accelerated escalation of voluntary ethanol consumption. To understand neural encoding in the LHb contributing to ethanol‐induced aversion, we recorded neural firing in the LHb of freely behaving, water‐deprived rats before and after an ethanol‐induced (1.5 g kg−1 20% ethanol, i.p.) conditioned taste aversion (CTA) to saccharin taste. Ethanol‐induced CTA strongly decreased motivation for saccharin in an operant task to obtain the tastant. Comparison of LHb neural firing before and after CTA induction revealed four main differences in firing properties. First, baseline firing after CTA induction was significantly higher. Second, firing evoked by cues signalling saccharin availability shifted from a pattern of primarily inhibition before CTA to primarily excitation after CTA induction. Third, CTA induction reduced the magnitude of lever press‐evoked inhibition. Finally, firing rates were significantly higher during consumption of the devalued saccharin solution after CTA induction. Next, we studied sham‐ and LHb‐lesioned rats in our operant CTA paradigm and found that LHb lesion significantly attenuated CTA effects in the operant task. Our data demonstrate the importance of LHb excitation in regulating expression of ethanol‐induced aversion and suggest a mechanism for its role in modulating escalation of voluntary ethanol intake. PMID:27682823
Nakamura, Kouichi C.; Sharott, Andrew; Magill, Peter J.
2014-01-01
Neurons of the motor thalamus mediate basal ganglia and cerebellar influences on cortical activity. To elucidate the net result of γ-aminobutyric acid-releasing or glutamatergic bombardment of the motor thalamus by basal ganglia or cerebellar afferents, respectively, we recorded the spontaneous activities of thalamocortical neurons in distinct identified “input zones” in anesthetized rats during defined cortical activity states. Unexpectedly, the mean rates and brain state dependencies of the firing of neurons in basal ganglia-recipient zone (BZ) and cerebellar-recipient zone (CZ) were matched during slow-wave activity (SWA) and cortical activation. However, neurons were distinguished during SWA by their firing regularities, low-threshold spike bursts and, more strikingly, by the temporal coupling of their activities to ongoing cortical oscillations. The firing of neurons across the BZ was stronger and more precisely phase-locked to cortical slow (∼1 Hz) oscillations, although both neuron groups preferentially fired at the same phase. In contrast, neurons in BZ and CZ fired at different phases of cortical spindles (7–12 Hz), but with similar strengths of coupled firing. Thus, firing rates do not reflect the predicted inhibitory–excitatory imbalance across the motor thalamus, and input zone-specific temporal coding through oscillatory synchronization with the cortex could partly mediate the different roles of basal ganglia and cerebellum in behavior. PMID:23042738
Dynamical analysis of Parkinsonian state emulated by hybrid Izhikevich neuron models
NASA Astrophysics Data System (ADS)
Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Li, Huiyan; Loparo, Kenneth A.; Fietkiewicz, Chris
2015-11-01
Computational models play a significant role in exploring novel theories to complement the findings of physiological experiments. Various computational models have been developed to reveal the mechanisms underlying brain functions. Particularly, in the development of therapies to modulate behavioral and pathological abnormalities, computational models provide the basic foundations to exhibit transitions between physiological and pathological conditions. Considering the significant roles of the intrinsic properties of the globus pallidus and the coupling connections between neurons in determining the firing patterns and the dynamical activities of the basal ganglia neuronal network, we propose a hypothesis that pathological behaviors under the Parkinsonian state may originate from combined effects of intrinsic properties of globus pallidus neurons and synaptic conductances in the whole neuronal network. In order to establish a computational efficient network model, hybrid Izhikevich neuron model is used due to its capacity of capturing the dynamical characteristics of the biological neuronal activities. Detailed analysis of the individual Izhikevich neuron model can assist in understanding the roles of model parameters, which then facilitates the establishment of the basal ganglia-thalamic network model, and contributes to a further exploration of the underlying mechanisms of the Parkinsonian state. Simulation results show that the hybrid Izhikevich neuron model is capable of capturing many of the dynamical properties of the basal ganglia-thalamic neuronal network, such as variations of the firing rates and emergence of synchronous oscillations under the Parkinsonian condition, despite the simplicity of the two-dimensional neuronal model. It may suggest that the computational efficient hybrid Izhikevich neuron model can be used to explore basal ganglia normal and abnormal functions. Especially it provides an efficient way of emulating the large-scale neuron network and potentially contributes to development of improved therapy for neurological disorders such as Parkinson's disease.
Chicca, E; Badoni, D; Dante, V; D'Andreagiovanni, M; Salina, G; Carota, L; Fusi, S; Del Giudice, P
2003-01-01
Electronic neuromorphic devices with on-chip, on-line learning should be able to modify quickly the synaptic couplings to acquire information about new patterns to be stored (synaptic plasticity) and, at the same time, preserve this information on very long time scales (synaptic stability). Here, we illustrate the electronic implementation of a simple solution to this stability-plasticity problem, recently proposed and studied in various contexts. It is based on the observation that reducing the analog depth of the synapses to the extreme (bistable synapses) does not necessarily disrupt the performance of the device as an associative memory, provided that 1) the number of neurons is large enough; 2) the transitions between stable synaptic states are stochastic; and 3) learning is slow. The drastic reduction of the analog depth of the synaptic variable also makes this solution appealing from the point of view of electronic implementation and offers a simple methodological alternative to the technological solution based on floating gates. We describe the full custom analog very large-scale integration (VLSI) realization of a small network of integrate-and-fire neurons connected by bistable deterministic plastic synapses which can implement the idea of stochastic learning. In the absence of stimuli, the memory is preserved indefinitely. During the stimulation the synapse undergoes quick temporary changes through the activities of the pre- and postsynaptic neurons; those changes stochastically result in a long-term modification of the synaptic efficacy. The intentionally disordered pattern of connectivity allows the system to generate a randomness suited to drive the stochastic selection mechanism. We check by a suitable stimulation protocol that the stochastic synaptic plasticity produces the expected pattern of potentiation and depression in the electronic network.
Hinckley, Christopher A; Alaynick, William A; Gallarda, Benjamin W; Hayashi, Marito; Hilde, Kathryn L; Driscoll, Shawn P; Dekker, Joseph D; Tucker, Haley O; Sharpee, Tatyana O; Pfaff, Samuel L
2015-09-02
The coordination of multi-muscle movements originates in the circuitry that regulates the firing patterns of spinal motorneurons. Sensory neurons rely on the musculotopic organization of motorneurons to establish orderly connections, prompting us to examine whether the intraspinal circuitry that coordinates motor activity likewise uses cell position as an internal wiring reference. We generated a motorneuron-specific GCaMP6f mouse line and employed two-photon imaging to monitor the activity of lumbar motorneurons. We show that the central pattern generator neural network coordinately drives rhythmic columnar-specific motorneuron bursts at distinct phases of the locomotor cycle. Using multiple genetic strategies to perturb the subtype identity and orderly position of motorneurons, we found that neurons retained their rhythmic activity-but cell position was decoupled from the normal phasing pattern underlying flexion and extension. These findings suggest a hierarchical basis of motor circuit formation that relies on increasingly stringent matching of neuronal identity and position. Copyright © 2015 Elsevier Inc. All rights reserved.
A silicon central pattern generator controls locomotion in vivo.
Vogelstein, R J; Tenore, F; Guevremont, L; Etienne-Cummings, R; Mushahwar, V K
2008-09-01
We present a neuromorphic silicon chip that emulates the activity of the biological spinal central pattern generator (CPG) and creates locomotor patterns to support walking. The chip implements ten integrate-and-fire silicon neurons and 190 programmable digital-to-analog converters that act as synapses. This architecture allows for each neuron to make synaptic connections to any of the other neurons as well as to any of eight external input signals and one tonic bias input. The chip's functionality is confirmed by a series of experiments in which it controls the motor output of a paralyzed animal in real-time and enables it to walk along a three-meter platform. The walking is controlled under closed-loop conditions with the aide of sensory feedback that is recorded from the animal's legs and fed into the silicon CPG. Although we and others have previously described biomimetic silicon locomotor control systems for robots, this is the first demonstration of a neuromorphic device that can replace some functions of the central nervous system in vivo.
Analysis of noise-induced temporal correlations in neuronal spike sequences
NASA Astrophysics Data System (ADS)
Reinoso, José A.; Torrent, M. C.; Masoller, Cristina
2016-11-01
We investigate temporal correlations in sequences of noise-induced neuronal spikes, using a symbolic method of time-series analysis. We focus on the sequence of time-intervals between consecutive spikes (inter-spike-intervals, ISIs). The analysis method, known as ordinal analysis, transforms the ISI sequence into a sequence of ordinal patterns (OPs), which are defined in terms of the relative ordering of consecutive ISIs. The ISI sequences are obtained from extensive simulations of two neuron models (FitzHugh-Nagumo, FHN, and integrate-and-fire, IF), with correlated noise. We find that, as the noise strength increases, temporal order gradually emerges, revealed by the existence of more frequent ordinal patterns in the ISI sequence. While in the FHN model the most frequent OP depends on the noise strength, in the IF model it is independent of the noise strength. In both models, the correlation time of the noise affects the OP probabilities but does not modify the most probable pattern.
Fuentealba, Pablo; Klausberger, Thomas; Karayannis, Theofanis; Suen, Wai Yee; Huck, Jojanneke; Tomioka, Ryohei; Rockland, Kathleen; Capogna, Marco; Studer, Michèle; Morales, Marisela; Somogyi, Peter
2015-01-01
The COUP-TFII nuclear receptor, also known as NR2F2, is expressed in the developing ventral telencephalon and modulates the tangential migration of a set of subpallial neuronal progenitors during forebrain development. Little information is available about its expression patterns in the adult brain. We have identified the cell populations expressing COUP-TFII and the contribution of some of them to network activity in vivo. Expression of COUP-TFII by hippocampal pyramidal and dentate granule cells, as well as neurons in the neocortex, formed a gradient increasing from undetectable in the dorsal to very strong in the ventral sectors. In the dorsal hippocampal CA1 area, COUP-TFII was restricted to GABAergic interneurons and expressed in several, largely nonoverlapping neuronal populations. Immunoreactivity was present in calretinin-, neuronal nitric oxide synthase-, and reelin-expressing cells, as well as in subsets of cholecystokinin- or calbindin-expressing or radiatum-retrohippocampally projecting GABAergic cells, but not in parvalbumin-and/or somatostatin-expressing interneurons. In vivo recording and juxtacellular labeling of COUP-TFII-expressing cells revealed neurogliaform cells, basket cells in stratum radiatum and tachykinin-expressing radiatum dentate innervating interneurons, identified by their axodendritic distributions. They showed cell type-selective phase-locked firing to the theta rhythm but no activation during sharp wave/ripple oscillations. These basket cells in stratum radiatum and neurogliaform cells fired at the peak of theta oscillations detected extracellularly in stratum pyramidale, unlike previously reported ivy cells, which fired at the trough. The characterization of COUP-TFII-expressing neurons suggests that this developmentally important transcription factor plays cell type-specific role(s)in the adult hippocampus. PMID:20130170
Beyond Critical Exponents in Neuronal Avalanches
NASA Astrophysics Data System (ADS)
Friedman, Nir; Butler, Tom; Deville, Robert; Beggs, John; Dahmen, Karin
2011-03-01
Neurons form a complex network in the brain, where they interact with one another by firing electrical signals. Neurons firing can trigger other neurons to fire, potentially causing avalanches of activity in the network. In many cases these avalanches have been found to be scale independent, similar to critical phenomena in diverse systems such as magnets and earthquakes. We discuss models for neuronal activity that allow for the extraction of testable, statistical predictions. We compare these models to experimental results, and go beyond critical exponents.
Kendrick, Keith M; Zhan, Yang; Fischer, Hanno; Nicol, Alister U; Zhang, Xuejuan; Feng, Jianfeng
2011-06-09
How oscillatory brain rhythms alone, or in combination, influence cortical information processing to support learning has yet to be fully established. Local field potential and multi-unit neuronal activity recordings were made from 64-electrode arrays in the inferotemporal cortex of conscious sheep during and after visual discrimination learning of face or object pairs. A neural network model has been developed to simulate and aid functional interpretation of learning-evoked changes. Following learning the amplitude of theta (4-8 Hz), but not gamma (30-70 Hz) oscillations was increased, as was the ratio of theta to gamma. Over 75% of electrodes showed significant coupling between theta phase and gamma amplitude (theta-nested gamma). The strength of this coupling was also increased following learning and this was not simply a consequence of increased theta amplitude. Actual discrimination performance was significantly correlated with theta and theta-gamma coupling changes. Neuronal activity was phase-locked with theta but learning had no effect on firing rates or the magnitude or latencies of visual evoked potentials during stimuli. The neural network model developed showed that a combination of fast and slow inhibitory interneurons could generate theta-nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity in the model similar changes were produced as in inferotemporal cortex after learning. The model showed that these changes could potentiate the firing of downstream neurons by a temporal desynchronization of excitatory neuron output without increasing the firing frequencies of the latter. This desynchronization effect was confirmed in IT neuronal activity following learning and its magnitude was correlated with discrimination performance. Face discrimination learning produces significant increases in both theta amplitude and the strength of theta-gamma coupling in the inferotemporal cortex which are correlated with behavioral performance. A network model which can reproduce these changes suggests that a key function of such learning-evoked alterations in theta and theta-nested gamma activity may be increased temporal desynchronization in neuronal firing leading to optimal timing of inputs to downstream neural networks potentiating their responses. In this way learning can produce potentiation in neural networks simply through altering the temporal pattern of their inputs.
2011-01-01
Background How oscillatory brain rhythms alone, or in combination, influence cortical information processing to support learning has yet to be fully established. Local field potential and multi-unit neuronal activity recordings were made from 64-electrode arrays in the inferotemporal cortex of conscious sheep during and after visual discrimination learning of face or object pairs. A neural network model has been developed to simulate and aid functional interpretation of learning-evoked changes. Results Following learning the amplitude of theta (4-8 Hz), but not gamma (30-70 Hz) oscillations was increased, as was the ratio of theta to gamma. Over 75% of electrodes showed significant coupling between theta phase and gamma amplitude (theta-nested gamma). The strength of this coupling was also increased following learning and this was not simply a consequence of increased theta amplitude. Actual discrimination performance was significantly correlated with theta and theta-gamma coupling changes. Neuronal activity was phase-locked with theta but learning had no effect on firing rates or the magnitude or latencies of visual evoked potentials during stimuli. The neural network model developed showed that a combination of fast and slow inhibitory interneurons could generate theta-nested gamma. By increasing N-methyl-D-aspartate receptor sensitivity in the model similar changes were produced as in inferotemporal cortex after learning. The model showed that these changes could potentiate the firing of downstream neurons by a temporal desynchronization of excitatory neuron output without increasing the firing frequencies of the latter. This desynchronization effect was confirmed in IT neuronal activity following learning and its magnitude was correlated with discrimination performance. Conclusions Face discrimination learning produces significant increases in both theta amplitude and the strength of theta-gamma coupling in the inferotemporal cortex which are correlated with behavioral performance. A network model which can reproduce these changes suggests that a key function of such learning-evoked alterations in theta and theta-nested gamma activity may be increased temporal desynchronization in neuronal firing leading to optimal timing of inputs to downstream neural networks potentiating their responses. In this way learning can produce potentiation in neural networks simply through altering the temporal pattern of their inputs. PMID:21658251
Metabolic sensing neurons and the control of energy homeostasis.
Levin, Barry E
2006-11-30
The brain and periphery carry on a constant conversation; the periphery informs the brain about its metabolic needs and the brain provides for these needs through its control of somatomotor, autonomic and neurohumoral pathways involved in energy intake, expenditure and storage. Metabolic sensing neurons are the integrators of a variety of metabolic, humoral and neural inputs from the periphery. Such neurons, originally called "glucosensing", also respond to fatty acids, hormones and metabolites from the periphery. They are integrated within neural pathways involved in the regulation of energy homeostasis. Unlike most neurons, they utilize glucose and other metabolites as signaling molecules to regulate their membrane potential and firing rate. For glucosensing neurons, glucokinase acts as the rate-limiting step in glucosensing while the pathways that mediate responses to metabolites like lactate, ketone bodies and fatty acids are less well characterized. Many metabolic sensing neurons also respond to insulin and leptin and other peripheral hormones and receive neural inputs from peripheral organs. Each set of afferent signals arrives with different temporal profiles and by different routes and these inputs are summated at the level of the membrane potential to produce a given neural firing pattern. In some obese individuals, the relative sensitivity of metabolic sensing neurons to various peripheral inputs is genetically reduced. This may provide one mechanism underlying their propensity to become obese when exposed to diets high in fat and caloric density. Thus, metabolic sensing neurons may provide a potential therapeutic target for the treatment of obesity.
Reduced motor neuron excitability is an important contributor to weakness in a rat model of sepsis.
Nardelli, Paul; Vincent, Jacob A; Powers, Randall; Cope, Tim C; Rich, Mark M
2016-08-01
The mechanisms by which sepsis triggers intensive care unit acquired weakness (ICUAW) remain unclear. We previously identified difficulty with motor unit recruitment in patients as a novel contributor to ICUAW. To study the mechanism underlying poor recruitment of motor units we used the rat cecal ligation and puncture model of sepsis. We identified striking dysfunction of alpha motor neurons during repetitive firing. Firing was more erratic, and often intermittent. Our data raised the possibility that reduced excitability of motor neurons was a significant contributor to weakness induced by sepsis. In this study we quantified the contribution of reduced motor neuron excitability and compared its magnitude to the contributions of myopathy, neuropathy and failure of neuromuscular transmission. We injected constant depolarizing current pulses (5s) into the soma of alpha motor neurons in the lumbosacral spinal cord of anesthetized rats to trigger repetitive firing. In response to constant depolarization, motor neurons in untreated control rats fired at steady and continuous firing rates and generated smooth and sustained tetanic motor unit force as expected. In contrast, following induction of sepsis, motor neurons were often unable to sustain firing throughout the 5s current injection such that force production was reduced. Even when firing, motor neurons from septic rats fired erratically and discontinuously, leading to irregular production of motor unit force. Both fast and slow type motor neurons had similar disruption of excitability. We followed rats after recovery from sepsis to determine the time course of resolution of the defect in motor neuron excitability. By one week, rats appeared to have recovered from sepsis as they had no piloerection and appeared to be in no distress. The defects in motor neuron repetitive firing were still striking at 2weeks and, although improved, were present at one month. We infer that rats suffered from weakness due to reduced motor neuron excitability for weeks after resolution of sepsis. To assess whether additional contributions from myopathy, neuropathy and defects in neuromuscular transmission contributed to the reduction in force generation, we measured whole-muscle force production in response to electrical stimulation of the muscle nerve. We found no abnormality in force generation that would suggest the presence of myopathy, neuropathy or defective neuromuscular transmission. These data suggest disruption of repetitive firing of motor neurons is an important contributor to weakness induced by sepsis in rats and raise the possibility that reduced motor neuron excitability contributes to disability that persists after resolution of sepsis. Copyright © 2016 Elsevier Inc. All rights reserved.
Sequence memory based on coherent spin-interaction neural networks.
Xia, Min; Wong, W K; Wang, Zhijie
2014-12-01
Sequence information processing, for instance, the sequence memory, plays an important role on many functions of brain. In the workings of the human brain, the steady-state period is alterable. However, in the existing sequence memory models using heteroassociations, the steady-state period cannot be changed in the sequence recall. In this work, a novel neural network model for sequence memory with controllable steady-state period based on coherent spininteraction is proposed. In the proposed model, neurons fire collectively in a phase-coherent manner, which lets a neuron group respond differently to different patterns and also lets different neuron groups respond differently to one pattern. The simulation results demonstrating the performance of the sequence memory are presented. By introducing a new coherent spin-interaction sequence memory model, the steady-state period can be controlled by dimension parameters and the overlap between the input pattern and the stored patterns. The sequence storage capacity is enlarged by coherent spin interaction compared with the existing sequence memory models. Furthermore, the sequence storage capacity has an exponential relationship to the dimension of the neural network.
Dendritic nonlinearities are tuned for efficient spike-based computations in cortical circuits
Ujfalussy, Balázs B; Makara, Judit K; Branco, Tiago; Lengyel, Máté
2015-01-01
Cortical neurons integrate thousands of synaptic inputs in their dendrites in highly nonlinear ways. It is unknown how these dendritic nonlinearities in individual cells contribute to computations at the level of neural circuits. Here, we show that dendritic nonlinearities are critical for the efficient integration of synaptic inputs in circuits performing analog computations with spiking neurons. We developed a theory that formalizes how a neuron's dendritic nonlinearity that is optimal for integrating synaptic inputs depends on the statistics of its presynaptic activity patterns. Based on their in vivo preynaptic population statistics (firing rates, membrane potential fluctuations, and correlations due to ensemble dynamics), our theory accurately predicted the responses of two different types of cortical pyramidal cells to patterned stimulation by two-photon glutamate uncaging. These results reveal a new computational principle underlying dendritic integration in cortical neurons by suggesting a functional link between cellular and systems--level properties of cortical circuits. DOI: http://dx.doi.org/10.7554/eLife.10056.001 PMID:26705334
Correlated variability modifies working memory fidelity in primate prefrontal neuronal ensembles
Leavitt, Matthew L.; Pieper, Florian; Sachs, Adam J.; Martinez-Trujillo, Julio C.
2017-01-01
Neurons in the primate lateral prefrontal cortex (LPFC) encode working memory (WM) representations via sustained firing, a phenomenon hypothesized to arise from recurrent dynamics within ensembles of interconnected neurons. Here, we tested this hypothesis by using microelectrode arrays to examine spike count correlations (rsc) in LPFC neuronal ensembles during a spatial WM task. We found a pattern of pairwise rsc during WM maintenance indicative of stronger coupling between similarly tuned neurons and increased inhibition between dissimilarly tuned neurons. We then used a linear decoder to quantify the effects of the high-dimensional rsc structure on information coding in the neuronal ensembles. We found that the rsc structure could facilitate or impair coding, depending on the size of the ensemble and tuning properties of its constituent neurons. A simple optimization procedure demonstrated that near-maximum decoding performance could be achieved using a relatively small number of neurons. These WM-optimized subensembles were more signal correlation (rsignal)-diverse and anatomically dispersed than predicted by the statistics of the full recorded population of neurons, and they often contained neurons that were poorly WM-selective, yet enhanced coding fidelity by shaping the ensemble’s rsc structure. We observed a pattern of rsc between LPFC neurons indicative of recurrent dynamics as a mechanism for WM-related activity and that the rsc structure can increase the fidelity of WM representations. Thus, WM coding in LPFC neuronal ensembles arises from a complex synergy between single neuron coding properties and multidimensional, ensemble-level phenomena. PMID:28275096
Dopamine neurons in the ventral tegmental area fire faster in adolescent rats than in adults.
McCutcheon, James E; Conrad, Kelly L; Carr, Steven B; Ford, Kerstin A; McGehee, Daniel S; Marinelli, Michela
2012-09-01
Adolescence may be a period of vulnerability to drug addiction. In rats, elevated firing activity of ventral tegmental area (VTA) dopamine neurons predicts enhanced addiction liability. Our aim was to determine if dopamine neurons are more active in adolescents than in adults and to examine mechanisms underlying any age-related difference. VTA dopamine neurons fired faster in adolescents than in adults as measured with in vivo extracellular recordings. Dopamine neuron firing can be divided into nonbursting (single spikes) and bursting activity (clusters of high-frequency spikes). Nonbursting activity was higher in adolescents compared with adults. Frequency of burst events did not differ between ages, but bursts were longer in adolescents than in adults. Elevated dopamine neuron firing in adolescent rats was also observed in cell-attached recordings in ex vivo brain slices. Using whole cell recordings, we found that passive and active membrane properties were similar across ages. Hyperpolarization-activated cation currents and small-conductance calcium-activated potassium channel currents were also comparable across ages. We found no difference in dopamine D2-class autoreceptor function across ages, although the high baseline firing in adolescents resulted in autoreceptor activation being less effective at silencing neurons. Finally, AMPA receptor-mediated spontaneous excitatory postsynaptic currents occurred at lower frequency in adolescents; GABA(A) receptor-mediated spontaneous inhibitory postsynaptic currents occurred at both lower frequency and smaller amplitude in adolescents. In conclusion, VTA dopamine neurons fire faster in adolescence, potentially because GABA tone increases as rats reach adulthood. This elevation of firing rate during adolescence is consistent with it representing a vulnerable period for developing drug addiction.
Simplicity and efficiency of integrate-and-fire neuron models.
Plesser, Hans E; Diesmann, Markus
2009-02-01
Lovelace and Cios (2008) recently proposed a very simple spiking neuron (VSSN) model for simulations of large neuronal networks as an efficient replacement for the integrate-and-fire neuron model. We argue that the VSSN model falls behind key advances in neuronal network modeling over the past 20 years, in particular, techniques that permit simulators to compute the state of the neuron without repeated summation over the history of input spikes and to integrate the subthreshold dynamics exactly. State-of-the-art solvers for networks of integrate-and-fire model neurons are substantially more efficient than the VSSN simulator and allow routine simulations of networks of some 10(5) neurons and 10(9) connections on moderate computer clusters.
Neuronal Entropy-Rate Feature of Entopeduncular Nucleus in Rat Model of Parkinson's Disease.
Darbin, Olivier; Jin, Xingxing; Von Wrangel, Christof; Schwabe, Kerstin; Nambu, Atsushi; Naritoku, Dean K; Krauss, Joachim K; Alam, Mesbah
2016-03-01
The function of the nigro-striatal pathway on neuronal entropy in the basal ganglia (BG) output nucleus, i.e. the entopeduncular nucleus (EPN) was investigated in the unilaterally 6-hyroxydopamine (6-OHDA)-lesioned rat model of Parkinson's disease (PD). In both control subjects and subjects with 6-OHDA lesion of dopamine (DA) the nigro-striatal pathway, a histological hallmark for parkinsonism, neuronal entropy in EPN was maximal in neurons with firing rates ranging between 15 and 25 Hz. In 6-OHDA lesioned rats, neuronal entropy in the EPN was specifically higher in neurons with firing rates above 25 Hz. Our data establishes that the nigro-striatal pathway controls neuronal entropy in motor circuitry and that the parkinsonian condition is associated with abnormal relationship between firing rate and neuronal entropy in BG output nuclei. The neuronal firing rates and entropy relationship provide putative relevant electrophysiological information to investigate the sensory-motor processing in normal condition and conditions such as movement disorders.
Dreyer, Jakob K.; Jennings, Katie A.; Syed, Emilie C. J.; Wade-Martins, Richard; Cragg, Stephanie J.; Bolam, J. Paul; Magill, Peter J.
2016-01-01
Midbrain dopaminergic neurons are essential for appropriate voluntary movement, as epitomized by the cardinal motor impairments arising in Parkinson’s disease. Understanding the basis of such motor control requires understanding how the firing of different types of dopaminergic neuron relates to movement and how this activity is deciphered in target structures such as the striatum. By recording and labeling individual neurons in behaving mice, we show that the representation of brief spontaneous movements in the firing of identified midbrain dopaminergic neurons is cell-type selective. Most dopaminergic neurons in the substantia nigra pars compacta (SNc), but not in ventral tegmental area or substantia nigra pars lateralis, consistently represented the onset of spontaneous movements with a pause in their firing. Computational modeling revealed that the movement-related firing of these dopaminergic neurons can manifest as rapid and robust fluctuations in striatal dopamine concentration and receptor activity. The exact nature of the movement-related signaling in the striatum depended on the type of dopaminergic neuron providing inputs, the striatal region innervated, and the type of dopamine receptor expressed by striatal neurons. Importantly, in aged mice harboring a genetic burden relevant for human Parkinson’s disease, the precise movement-related firing of SNc dopaminergic neurons and the resultant striatal dopamine signaling were lost. These data show that distinct dopaminergic cell types differentially encode spontaneous movement and elucidate how dysregulation of their firing in early Parkinsonism can impair their effector circuits. PMID:27001837
Lutas, Andrew; Birnbaumer, Lutz; Yellen, Gary
2014-12-03
Neurons use glucose to fuel glycolysis and provide substrates for mitochondrial respiration, but neurons can also use alternative fuels that bypass glycolysis and feed directly into mitochondria. To determine whether neuronal pacemaking depends on active glucose metabolism, we switched the metabolic fuel from glucose to alternative fuels, lactate or β-hydroxybutyrate, while monitoring the spontaneous firing of GABAergic neurons in mouse substantia nigra pars reticulata (SNr) brain slices. We found that alternative fuels, in the absence of glucose, sustained SNr spontaneous firing at basal rates, but glycolysis may still be supported by glycogen in the absence of glucose. To prevent any glycogen-fueled glycolysis, we directly inhibited glycolysis using either 2-deoxyglucose or iodoacetic acid. Inhibiting glycolysis in the presence of alternative fuels lowered SNr firing to a slower sustained firing rate. Surprisingly, we found that the decrease in SNr firing was not mediated by ATP-sensitive potassium (KATP) channel activity, but if we lowered the perfusion flow rate or omitted the alternative fuel, KATP channels were activated and could silence SNr firing. The KATP-independent slowing of SNr firing that occurred with glycolytic inhibition in the presence of alternative fuels was consistent with a decrease in a nonselective cationic conductance. Although mitochondrial metabolism alone can prevent severe energy deprivation and KATP channel activation in SNr neurons, active glucose metabolism appears important for keeping open a class of ion channels that is crucial for the high spontaneous firing rate of SNr neurons. Copyright © 2014 the authors 0270-6474/14/3416336-12$15.00/0.
The Sodium-Activated Potassium Channel Slack Is Required for Optimal Cognitive Flexibility in Mice
ERIC Educational Resources Information Center
Bausch, Anne E.; Dieter, Rebekka; Nann, Yvette; Hausmann, Mario; Meyerdierks, Nora; Kaczmarek, Leonard K.; Ruth, Peter; Lukowski, Robert
2015-01-01
"Kcnt1" encoded sodium-activated potassium channels (Slack channels) are highly expressed throughout the brain where they modulate the firing patterns and general excitability of many types of neurons. Increasing evidence suggests that Slack channels may be important for higher brain functions such as cognition and normal intellectual…
Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.
Bush, Daniel; Philippides, Andrew; Husbands, Phil; O'Shea, Michael
2010-07-01
The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal's spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain.
Chimera patterns in two-dimensional networks of coupled neurons.
Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp
2017-03-01
We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.
Chimera patterns in two-dimensional networks of coupled neurons
NASA Astrophysics Data System (ADS)
Schmidt, Alexander; Kasimatis, Theodoros; Hizanidis, Johanne; Provata, Astero; Hövel, Philipp
2017-03-01
We discuss synchronization patterns in networks of FitzHugh-Nagumo and leaky integrate-and-fire oscillators coupled in a two-dimensional toroidal geometry. A common feature between the two models is the presence of fast and slow dynamics, a typical characteristic of neurons. Earlier studies have demonstrated that both models when coupled nonlocally in one-dimensional ring networks produce chimera states for a large range of parameter values. In this study, we give evidence of a plethora of two-dimensional chimera patterns of various shapes, including spots, rings, stripes, and grids, observed in both models, as well as additional patterns found mainly in the FitzHugh-Nagumo system. Both systems exhibit multistability: For the same parameter values, different initial conditions give rise to different dynamical states. Transitions occur between various patterns when the parameters (coupling range, coupling strength, refractory period, and coupling phase) are varied. Many patterns observed in the two models follow similar rules. For example, the diameter of the rings grows linearly with the coupling radius.
Xie, Rou-Gang; Chu, Wen-Guang; Hu, San-Jue; Luo, Ceng
2018-01-01
Sensory neuron types have been distinguished by distinct morphological and transcriptional characteristics. Excitability is the most fundamental functional feature of neurons. Mathematical models described by Hodgkin have revealed three types of neuronal excitability based on the relationship between firing frequency and applied current intensity. However, whether natural sensory neurons display different functional characteristics in terms of excitability and whether this excitability type undergoes plastic changes under pathological pain states have remained elusive. Here, by utilizing whole-cell patch clamp recordings, behavioral and pharmacological assays, we demonstrated that large dorsal root ganglion (DRG) neurons can be classified into three classes and four subclasses based on their excitability patterns, which is similar to mathematical models raised by Hodgkin. Analysis of hyperpolarization-activated cation current (Ih) revealed different magnitude of Ih in different excitability types of large DRG neurons, with higher Ih in Class 2-1 than that in Class 1, 2-2 and 3. This indicates a crucial role of Ih in the determination of excitability type of large DRG neurons. More importantly, this pattern of excitability displays plastic changes and transition under pathological pain states caused by peripheral nerve injury. This study sheds new light on the functional characteristics of large DRG neurons and extends functional classification of large DRG neurons by integration of transcriptomic and morphological characteristics. PMID:29303989
Predicting neural network firing pattern from phase resetting curve
NASA Astrophysics Data System (ADS)
Oprisan, Sorinel; Oprisan, Ana
2007-04-01
Autonomous neural networks called central pattern generators (CPG) are composed of endogenously bursting neurons and produce rhythmic activities, such as flying, swimming, walking, chewing, etc. Simplified CPGs for quadrupedal locomotion and swimming are modeled by a ring of neural oscillators such that the output of one oscillator constitutes the input for the subsequent neural oscillator. The phase response curve (PRC) theory discards the detailed conductance-based description of the component neurons of a network and reduces them to ``black boxes'' characterized by a transfer function, which tabulates the transient change in the intrinsic period of a neural oscillator subject to external stimuli. Based on open-loop PRC, we were able to successfully predict the phase-locked period and relative phase between neurons in a half-center network. We derived existence and stability criteria for heterogeneous ring neural networks that are in good agreement with experimental data.
Connectivity of Pacemaker Neurons in the Neonatal Rat Superficial Dorsal Horn
Ford, Neil C.; Arbabi, Shahriar; Baccei, Mark L.
2014-01-01
Pacemaker neurons with an intrinsic ability to generate rhythmic burst-firing have been characterized in lamina I of the neonatal spinal cord, where they are innervated by high-threshold sensory afferents. However, little is known about the output of these pacemakers, as the neuronal populations which are targeted by pacemaker axons have yet to be identified. The present study combines patch clamp recordings in the intact neonatal rat spinal cord with tract-tracing to demonstrate that lamina I pacemaker neurons contact multiple spinal motor pathways during early life. Retrograde labeling of premotor interneurons with the trans-synaptic virus PRV-152 revealed the presence of burst-firing in PRV-infected lamina I neurons, thereby confirming that pacemakers are synaptically coupled to motor networks in the spinal ventral horn. Notably, two classes of pacemakers could be distinguished in lamina I based on cell size and the pattern of their axonal projections. While small pacemaker neurons possessed ramified axons which contacted ipsilateral motor circuits, large pacemaker neurons had unbranched axons which crossed the midline and ascended rostrally in the contralateral white matter. Recordings from identified spino-parabrachial and spino-PAG neurons indicated the presence of pacemaker activity within neonatal lamina I projection neurons. Overall, these results show that lamina I pacemakers are positioned to regulate both the level of activity in developing motor circuits as well as the ascending flow of nociceptive information to the brain, thus highlighting a potential role for pacemaker activity in the maturation of pain and sensorimotor networks in the CNS. PMID:25380417
Shlizerman, Eli; Riffell, Jeffrey A.; Kutz, J. Nathan
2014-01-01
The antennal lobe (AL), olfactory processing center in insects, is able to process stimuli into distinct neural activity patterns, called olfactory neural codes. To model their dynamics we perform multichannel recordings from the projection neurons in the AL driven by different odorants. We then derive a dynamic neuronal network from the electrophysiological data. The network consists of lateral-inhibitory neurons and excitatory neurons (modeled as firing-rate units), and is capable of producing unique olfactory neural codes for the tested odorants. To construct the network, we (1) design a projection, an odor space, for the neural recording from the AL, which discriminates between distinct odorants trajectories (2) characterize scent recognition, i.e., decision-making based on olfactory signals and (3) infer the wiring of the neural circuit, the connectome of the AL. We show that the constructed model is consistent with biological observations, such as contrast enhancement and robustness to noise. The study suggests a data-driven approach to answer a key biological question in identifying how lateral inhibitory neurons can be wired to excitatory neurons to permit robust activity patterns. PMID:25165442
Prototypic and Arkypallidal Neurons in the Dopamine-Intact External Globus Pallidus
Abdi, Azzedine; Mallet, Nicolas; Mohamed, Foad Y.; Sharott, Andrew; Dodson, Paul D.; Nakamura, Kouichi C.; Suri, Sana; Avery, Sophie V.; Larvin, Joseph T.; Garas, Farid N.; Garas, Shady N.; Vinciati, Federica; Morin, Stéphanie; Bezard, Erwan
2015-01-01
Studies in dopamine-depleted rats indicate that the external globus pallidus (GPe) contains two main types of GABAergic projection cell; so-called “prototypic” and “arkypallidal” neurons. Here, we used correlative anatomical and electrophysiological approaches in rats to determine whether and how this dichotomous organization applies to the dopamine-intact GPe. Prototypic neurons coexpressed the transcription factors Nkx2-1 and Lhx6, comprised approximately two-thirds of all GPe neurons, and were the major GPe cell type innervating the subthalamic nucleus (STN). In contrast, arkypallidal neurons expressed the transcription factor FoxP2, constituted just over one-fourth of GPe neurons, and innervated the striatum but not STN. In anesthetized dopamine-intact rats, molecularly identified prototypic neurons fired at relatively high rates and with high regularity, regardless of brain state (slow-wave activity or spontaneous activation). On average, arkypallidal neurons fired at lower rates and regularities than prototypic neurons, and the two cell types could be further distinguished by the temporal coupling of their firing to ongoing cortical oscillations. Complementing the activity differences observed in vivo, the autonomous firing of identified arkypallidal neurons in vitro was slower and more variable than that of prototypic neurons, which tallied with arkypallidal neurons displaying lower amplitudes of a “persistent” sodium current important for such pacemaking. Arkypallidal neurons also exhibited weaker driven and rebound firing compared with prototypic neurons. In conclusion, our data support the concept that a dichotomous functional organization, as actioned by arkypallidal and prototypic neurons with specialized molecular, structural, and physiological properties, is fundamental to the operations of the dopamine-intact GPe. PMID:25926446
Transgenic mouse models enabling photolabeling of individual neurons in vivo.
Peter, Manuel; Bathellier, Brice; Fontinha, Bruno; Pliota, Pinelopi; Haubensak, Wulf; Rumpel, Simon
2013-01-01
One of the biggest tasks in neuroscience is to explain activity patterns of individual neurons during behavior by their cellular characteristics and their connectivity within the neuronal network. To greatly facilitate linking in vivo experiments with a more detailed molecular or physiological analysis in vitro, we have generated and characterized genetically modified mice expressing photoactivatable GFP (PA-GFP) that allow conditional photolabeling of individual neurons. Repeated photolabeling at the soma reveals basic morphological features due to diffusion of activated PA-GFP into the dendrites. Neurons photolabeled in vivo can be re-identified in acute brain slices and targeted for electrophysiological recordings. We demonstrate the advantages of PA-GFP expressing mice by the correlation of in vivo firing rates of individual neurons with their expression levels of the immediate early gene c-fos. Generally, the mouse models described in this study enable the combination of various analytical approaches to characterize living cells, also beyond the neurosciences.
Linear Look-Ahead in Conjunctive Cells: An Entorhinal Mechanism for Vector-Based Navigation
Kubie, John L.; Fenton, André A.
2012-01-01
The crisp organization of the “firing bumps” of entorhinal grid cells and conjunctive cells leads to the notion that the entorhinal cortex may compute linear navigation routes. Specifically, we propose a process, termed “linear look-ahead,” by which a stationary animal could compute a series of locations in the direction it is facing. We speculate that this computation could be achieved through learned patterns of connection strengths among entorhinal neurons. This paper has three sections. First, we describe the minimal grid cell properties that will be built into our network. Specifically, the network relies on “rigid modules” of neurons, where all members have identical grid scale and orientation, but differ in spatial phase. Additionally, these neurons must be densely interconnected with synapses that are modifiable early in the animal’s life. Second, we investigate whether plasticity during short bouts of locomotion could induce patterns of connections amongst grid cells or conjunctive cells. Finally, we run a simulation to test whether the learned connection patterns can exhibit linear look-ahead. Our results are straightforward. A simulated 30-min walk produces weak strengthening of synapses between grid cells that do not support linear look-ahead. Similar training in a conjunctive cell module produces a small subset of very strong connections between cells. These strong pairs have three properties: the pre- and post-synaptic cells have similar heading direction. The cell pairs have neighboring grid bumps. Finally, the spatial offset of firing bumps of the cell pair is in the direction of the common heading preference. Such a module can produce strong and accurate linear look-ahead starting in any location and extending in any direction. We speculate that this process may: (1) compute linear paths to goals; (2) update grid cell firing during navigation; and (3) stabilize the rigid modules of grid cells and conjunctive cells. PMID:22557948
Reorganization of the human central nervous system.
Schalow, G; Zäch, G A
2000-10-01
The key strategies on which the discovery of the functional organization of the central nervous system (CNS) under physiologic and pathophysiologic conditions have been based included (1) our measurements of phase and frequency coordination between the firings of alpha- and gamma-motoneurons and secondary muscle spindle afferents in the human spinal cord, (2) knowledge on CNS reorganization derived upon the improvement of the functions of the lesioned CNS in our patients in the short-term memory and the long-term memory (reorganization), and (3) the dynamic pattern approach for re-learning rhythmic coordinated behavior. The theory of self-organization and pattern formation in nonequilibrium systems is explicitly related to our measurements of the natural firing patterns of sets of identified single neurons in the human spinal premotor network and re-learned coordinated movements following spinal cord and brain lesions. Therapy induced cell proliferation, and maybe, neurogenesis seem to contribute to the host of structural changes during the process of re-learning of the lesioned CNS. So far, coordinated functions like movements could substantially be improved in every of the more than 100 patients with a CNS lesion by applying coordination dynamic therapy. As suggested by the data of our patients on re-learning, the human CNS seems to have a second integrative strategy for learning, re-learning, storing and recalling, which makes an essential contribution of the functional plasticity following a CNS lesion. A method has been developed by us for the simultaneous recording with wire electrodes of extracellular action potentials from single human afferent and efferent nerve fibres of undamaged sacral nerve roots. A classification scheme of the nerve fibres in the human peripheral nervous system (PNS) could be set up in which the individual classes of nerve fibres are characterized by group conduction velocities and group nerve fibre diameters. Natural impulse patterns of several identified single afferent and efferent nerve fibres (motoneuron axons) were extracted from multi-unit impulse patterns, and human CNS functions could be analyzed under physiologic and pathophysiologic conditions. With our discovery of premotor spinal oscillators it became possible to judge upon CNS neuronal network organization based on the firing patterns of these spinal oscillators and their driving afferents. Since motoneurons fire occasionally for low activation and oscillatory for high activation, the coherent organization of subnetworks to generate macroscopic function is very complex and for the time being, may be best described by the theory of coordination dynamics. Since oscillatory firing has also been observed by us in single motor unit firing patterns measured electromyographically, it seems possible to follow up therapeutic intervention in patients with spinal cord and brain lesions not only based on the activity levels and phases of motor programs during locomotion but also based on the physiologic and pathophysiologic firing patterns and recruitment of spinal oscillators. The improvement of the coordination dynamics of the CNS can be partly measured directly by rhythmicity upon the patient performing rhythmic movements coordinated up to milliseconds. Since rhythmic dynamic, coordinated, stereotyped movements are mainly located in the spinal cord and only little supraspinal drive is necessary to initiate, maintain, and terminate them, rhythmic, dynamic, coordinated movements were used in therapy to enforce reorganization of the lesioned CNS by improving the self-organization and relative coordination of spinal oscillators (and their interactions with occasionally firing motoneurons) which became pathologic in their firing following CNS lesion. Paraparetic, tetraparetic spinal cord and brain-lesioned patients re-learned running and other movements by an oscillator formation and coordination dynamic therapy. Our development in neurorehabilitation is in accordance with those of theoretical and computational neurosciences which deal with the self-organization of neuronal networks. In particular, jumping on a springboard 'in-phase' and in 'anti-phase' to re-learn phase relations of oscillator coupling can be understood in the framework of the Haken-Kelso-Bunz coordination dynamic model. By introducing broken symmetry, intention, learning and spasticity in the landscape of the potential function of the integrated CNS activity, the change in self-organization becomes understandable. Movement patterns re-learned by oscillator formation and coordination dynamic therapy evolve from reorganization and regeneration of the lesioned CNS by cooperative and competitive interplay between intrinsic coordination dynamics, extrinsic therapy related inputs with physiologic re-afferent input, including intention, motivation, supervised learning, interpersonal coordination, and genetic constraints including neurogenesis. (ABSTRACT TRUNCATED)
Firing rate of noisy integrate-and-fire neurons with synaptic current dynamics
DOE Office of Scientific and Technical Information (OSTI.GOV)
Andrieux, David; Monnai, Takaaki; Department of Applied Physics, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555
2009-08-15
We derive analytical formulas for the firing rate of integrate-and-fire neurons endowed with realistic synaptic dynamics. In particular, we include the possibility of multiple synaptic inputs as well as the effect of an absolute refractory period into the description. The latter affects the firing rate through its interaction with the synaptic dynamics.
Ethanol-Sensitive Pacemaker Neurons in the Mouse External Globus Pallidus
Abrahao, Karina P; Chancey, Jessica H; Chan, C Savio; Lovinger, David M
2017-01-01
Although ethanol is one of the most widely used drugs, we still lack a full understanding of which neuronal subtypes are affected by this drug. Pacemaker neurons exert powerful control over brain circuit function, but little is known about ethanol effects on these types of neurons. Neurons in the external globus pallidus (GPe) generate pacemaker activity that controls basal ganglia, circuitry associated with habitual and compulsive drug use. We performed patch-clamp recordings from GPe neurons and found that bath application of ethanol dose-dependently decreased the firing rate of low-frequency GPe neurons, but did not alter the firing of high-frequency neurons. GABA or glutamate receptor antagonists did not block the ethanol effect. The GPe is comprised of a heterogeneous population of neurons. We used Lhx6-EGFP and Npas1-tdTm mice strains to identify low-frequency neurons. Lhx6 and Npas1 neurons exhibited decreased firing with ethanol, but only Npas1 neurons were sensitive to 10 mM ethanol. Large-conductance voltage and Ca2+-activated K+ (BK) channel have a key role in the ethanol effect on GPe neurons, as the application of BK channel inhibitors blocked the ethanol-induced firing decrease. Ethanol also increased BK channel open probability measured in single-channel recordings from Npas1-tdTm neurons. In addition, in vivo electrophysiological recordings from GPe showed that ethanol decreased the firing of a large subset of low-frequency neurons. These findings indicate how selectivity of ethanol effects on pacemaker neurons can occur, and enhance our understanding of the mechanisms contributing to acute ethanol effects on the basal ganglia. PMID:27827370
Gonzalo-Gomez, Alicia; Turiegano, Enrique; León, Yolanda; Molina, Isabel; Torroja, Laura; Canal, Inmaculada
2012-01-01
HCN channels are becoming pharmacological targets mainly in cardiac diseases. But apart from their well-known role in heart pacemaking, these channels are widely expressed in the nervous system where they contribute to the neuron firing pattern. Consequently, abolishing Ih current might have detrimental consequences in a big repertoire of behavioral traits. Several studies in mammals have identified the Ih current as an important determinant of the firing activity of dopaminergic neurons, and recent evidences link alterations in this current to various dopamine-related disorders. We used the model organism Drosophila melanogaster to investigate how lack of Ih current affects dopamine levels and the behavioral consequences in the sleep:activity pattern. Unlike mammals, in Drosophila there is only one gene encoding HCN channels. We generated a deficiency of the DmIh core gene region and measured, by HPLC, levels of dopamine. Our data demonstrate daily variations of dopamine in wild-type fly heads. Lack of Ih current dramatically alters dopamine pattern, but different mechanisms seem to operate during light and dark conditions. Behaviorally, DmIh mutant flies display alterations in the rest:activity pattern, and altered circadian rhythms. Our data strongly suggest that Ih current is necessary to prevent dopamine overproduction at dark, while light input allows cycling of dopamine in an Ih current dependent manner. Moreover, lack of Ih current results in behavioral defects that are consistent with altered dopamine levels.
Arunachalam, Viswanathan; Akhavan-Tabatabaei, Raha; Lopez, Cristina
2013-01-01
The classical models of single neuron like Hodgkin-Huxley point neuron or leaky integrate and fire neuron assume the influence of postsynaptic potentials to last till the neuron fires. Vidybida (2008) in a refreshing departure has proposed models for binding neurons in which the trace of an input is remembered only for a finite fixed period of time after which it is forgotten. The binding neurons conform to the behaviour of real neurons and are applicable in constructing fast recurrent networks for computer modeling. This paper develops explicitly several useful results for a binding neuron like the firing time distribution and other statistical characteristics. We also discuss the applicability of the developed results in constructing a modified hourglass network model in which there are interconnected neurons with excitatory as well as inhibitory inputs. Limited simulation results of the hourglass network are presented.
Granados-Fuentes, Daniel; Norris, Aaron J; Carrasquillo, Yarimar; Nerbonne, Jeanne M; Herzog, Erik D
2012-07-18
Neurons in the suprachiasmatic nucleus (SCN) display coordinated circadian changes in electrical activity that are critical for daily rhythms in physiology, metabolism, and behavior. SCN neurons depolarize spontaneously and fire repetitively during the day and hyperpolarize, drastically reducing firing rates, at night. To explore the hypothesis that rapidly activating and inactivating A-type (I(A)) voltage-gated K(+) (Kv) channels, which are also active at subthreshold membrane potentials, are critical regulators of the excitability of SCN neurons, we examined locomotor activity and SCN firing in mice lacking Kv1.4 (Kv1.4(-/-)), Kv4.2 (Kv4.2(-/-)), or Kv4.3 (Kv4.3(-/-)), the pore-forming (α) subunits of I(A) channels. Mice lacking either Kv1.4 or Kv4.2 α subunits have markedly shorter (0.5 h) periods of locomotor activity than wild-type (WT) mice. In vitro extracellular multi-electrode recordings revealed that Kv1.4(-/-) and Kv4.2(-/-) SCN neurons display circadian rhythms in repetitive firing, but with shorter periods (0.5 h) than WT cells. In contrast, the periods of wheel-running activity in Kv4.3(-/-) mice and firing in Kv4.3(-/-) SCN neurons were indistinguishable from WT animals and neurons. Quantitative real-time PCR revealed that the transcripts encoding all three Kv channel α subunits, Kv1.4, Kv4.2, and Kv4.3, are expressed constitutively throughout the day and night in the SCN. Together, these results demonstrate that Kv1.4- and Kv4.2-encoded I(A) channels regulate the intrinsic excitability of SCN neurons during the day and night and determine the period and amplitude of circadian rhythms in SCN neuron firing and locomotor behavior.
Towards an Analogue Neuromorphic VLSI Instrument for the Sensing of Complex Odours
NASA Astrophysics Data System (ADS)
Ab Aziz, Muhammad Fazli; Harun, Fauzan Khairi Che; Covington, James A.; Gardner, Julian W.
2011-09-01
Almost all electronic nose instruments reported today employ pattern recognition algorithms written in software and run on digital processors, e.g. micro-processors, microcontrollers or FPGAs. Conversely, in this paper we describe the analogue VLSI implementation of an electronic nose through the design of a neuromorphic olfactory chip. The modelling, design and fabrication of the chip have already been reported. Here a smart interface has been designed and characterised for thisneuromorphic chip. Thus we can demonstrate the functionality of the a VLSI neuromorphic chip, producing differing principal neuron firing patterns to real sensor response data. Further work is directed towards integrating 9 separate neuromorphic chips to create a large neuronal network to solve more complex olfactory problems.
Hamaguchi, Kosuke; Riehle, Alexa; Brunel, Nicolas
2011-01-01
High firing irregularity is a hallmark of cortical neurons in vivo, and modeling studies suggest a balance of excitation and inhibition is necessary to explain this high irregularity. Such a balance must be generated, at least partly, from local interconnected networks of excitatory and inhibitory neurons, but the details of the local network structure are largely unknown. The dynamics of the neural activity depends on the local network structure; this in turn suggests the possibility of estimating network structure from the dynamics of the firing statistics. Here we report a new method to estimate properties of the local cortical network from the instantaneous firing rate and irregularity (CV(2)) under the assumption that recorded neurons are a part of a randomly connected sparse network. The firing irregularity, measured in monkey motor cortex, exhibits two features; many neurons show relatively stable firing irregularity in time and across different task conditions; the time-averaged CV(2) is widely distributed from quasi-regular to irregular (CV(2) = 0.3-1.0). For each recorded neuron, we estimate the three parameters of a local network [balance of local excitation-inhibition, number of recurrent connections per neuron, and excitatory postsynaptic potential (EPSP) size] that best describe the dynamics of the measured firing rates and irregularities. Our analysis shows that optimal parameter sets form a two-dimensional manifold in the three-dimensional parameter space that is confined for most of the neurons to the inhibition-dominated region. High irregularity neurons tend to be more strongly connected to the local network, either in terms of larger EPSP and inhibitory PSP size or larger number of recurrent connections, compared with the low irregularity neurons, for a given excitatory/inhibitory balance. Incorporating either synaptic short-term depression or conductance-based synapses leads many low CV(2) neurons to move to the excitation-dominated region as well as to an increase of EPSP size.
Starr, M. A.; Page, M. E.
2012-01-01
3,4-Methylenedioxymethamphetamine (MDMA) is known to enhance tactile sensory perception, an effect that contributes to its popularity as a recreational drug. The neurophysiological basis for the effects of MDMA on somatosensation are unknown. However, MDMA interactions with the serotonin transporter (SERT) and subsequent enhancement of serotonin neurotransmission are well known. The rat trigeminal somatosensory system receives serotonergic afferents from the dorsal raphe nucleus. Because these fibers express SERT, they should be vulnerable to MDMA-induced effects. We found that administration of a challenge injection of MDMA (3 mg/kg i.p.) after repeated MDMA treatment (3 mg/kg per day for 4 days) elicits both serotonin and norepinephrine efflux in the ventral posterior medial (VPM) thalamus of Long-Evans hooded rats, the main relay along the lemniscal portion of the rodent trigeminal somatosensory pathway. We evaluated the potential for repeated MDMA administration to modulate whisker-evoked discharge of individual neurons in this region. After surgically implanting stainless steel eight-wire multichannel electrode bundles, we recorded spike train activity of single cells while activating the whisker pathway using a piezoelectric mechanical stimulator. We found that repeated MDMA administration increased the spontaneous firing rate but reduced both the magnitude and duration of whisker-evoked discharge in individual VPM thalamic neurons. The time course of drug action on neuronal firing patterns was generally consistent with fluctuations in neurotransmitter efflux as shown from our microdialysis studies. On the basis of these results, we propose that single use and repeated administration of MDMA may “distort,” rather than enhance, tactile experiences in humans, in part, by disrupting normal spike firing patterns through somatosensory thalamic relay circuits. PMID:21984836
Synchronization in neural nets
NASA Technical Reports Server (NTRS)
Vidal, Jacques J.; Haggerty, John
1988-01-01
The paper presents an artificial neural network concept (the Synchronizable Oscillator Networks) where the instants of individual firings in the form of point processes constitute the only form of information transmitted between joining neurons. In the model, neurons fire spontaneously and regularly in the absence of perturbation. When interaction is present, the scheduled firings are advanced or delayed by the firing of neighboring neurons. Networks of such neurons become global oscillators which exhibit multiple synchronizing attractors. From arbitrary initial states, energy minimization learning procedures can make the network converge to oscillatory modes that satisfy multi-dimensional constraints. Such networks can directly represent routing and scheduling problems that consist of ordering sequences of events.
Implications of cellular models of dopamine neurons for disease
Evans, Rebekah C.; Oster, Andrew M.; Pissadaki, Eleftheria K.; Drion, Guillaume; Kuznetsov, Alexey S.; Gutkin, Boris S.
2016-01-01
This review addresses the present state of single-cell models of the firing pattern of midbrain dopamine neurons and the insights that can be gained from these models into the underlying mechanisms for diseases such as Parkinson's, addiction, and schizophrenia. We will explain the analytical technique of separation of time scales and show how it can produce insights into mechanisms using simplified single-compartment models. We also use morphologically realistic multicompartmental models to address spatially heterogeneous aspects of neural signaling and neural metabolism. Separation of time scale analyses are applied to pacemaking, bursting, and depolarization block in dopamine neurons. Differences in subpopulations with respect to metabolic load are addressed using multicompartmental models. PMID:27582295
Vydyanathan, Amaresh; Wu, Zi-Zhen; Chen, Shao-Rui; Pan, Hui-Lin
2005-06-01
Voltage-gated K+ channels (Kv) in primary sensory neurons are important for regulation of neuronal excitability. The dorsal root ganglion (DRG) neurons are heterogeneous, and the types of native Kv currents in different groups of nociceptive DRG neurons are not fully known. In this study, we determined the difference in the A-type Kv current and its influence on the firing properties between isolectin B4 (IB4)-positive and -negative DRG neurons. Whole cell voltage- and current-clamp recordings were performed on acutely dissociated small DRG neurons of rats. The total Kv current density was significantly higher in IB+-positive than that in IB(4)-negative neurons. Also, 4-aminopyridine (4-AP) produced a significantly greater reduction in Kv currents in IB4-positive than in IB4-negative neurons. In contrast, IB4-negative neurons exhibited a larger proportion of tetraethylammonium-sensitive Kv currents. Furthermore, IB4-positive neurons showed a longer latency of firing and required a significantly larger amount of current injection to evoke action potentials. 4-AP significantly decreased the latency of firing and increased the firing frequency in IB4-positive but not in IB4-negative neurons. Additionally, IB4-positive neurons are immunoreactive to Kv1.4 but not to Kv1.1 and Kv1.2 subunits. Collectively, this study provides new information that 4-AP-sensitive A-type Kv currents are mainly present in IB4-positive DRG neurons and preferentially dampen the initiation of action potentials of this subpopulation of nociceptors. The difference in the density of A-type Kv currents contributes to the distinct electrophysiological properties of IB4-positive and -negative DRG neurons.
Rodriguez, Alexander V.; Funk, Chadd M.; Vyazovskiy, Vladyslav V.; Nir, Yuval; Tononi, Giulio
2016-01-01
During non-rapid eye movement (NREM) sleep, cortical neurons alternate between ON periods of firing and OFF periods of silence. This bi-stability, which is largely synchronous across neurons, is reflected in the EEG as slow waves. Slow-wave activity (SWA) increases with wake duration and declines homeostatically during sleep, but the underlying mechanisms remain unclear. One possibility is neuronal “fatigue”: high, sustained firing in wake would force neurons to recover with more frequent and longer OFF periods during sleep. Another possibility is net synaptic potentiation during wake: stronger coupling among neurons would lead to greater synchrony and therefore higher SWA. Here, we obtained a comparable increase in sustained firing (6 h) in cortex by: (1) keeping mice awake by exposure to novel objects to promote plasticity and (2) optogenetically activating a local population of cortical neurons at wake-like levels during sleep. Sleep after extended wake led to increased SWA, higher synchrony, and more time spent OFF, with a positive correlation between SWA, synchrony, and OFF periods. Moreover, time spent OFF was correlated with cortical firing during prior wake. After local optogenetic stimulation, SWA and cortical synchrony decreased locally, time spent OFF did not change, and local SWA was not correlated with either measure. Moreover, laser-induced cortical firing was not correlated with time spent OFF afterward. Overall, these results suggest that high sustained firing per se may not be the primary determinant of SWA increases observed after extended wake. SIGNIFICANCE STATEMENT A long-standing hypothesis is that neurons fire less during slow-wave sleep to recover from the “fatigue” accrued during wake, when overall synaptic activity is higher than in sleep. This idea, however, has rarely been tested and other factors, namely increased cortical synchrony, could explain why sleep slow-wave activity (SWA) is higher after extended wake. We forced neurons in the mouse cortex to fire at high levels for 6 h in 2 different conditions: during active wake with exploration and during sleep. We find that neurons need more time OFF only after sustained firing in wake, suggesting that fatigue due to sustained firing alone is unlikely to account for the increase in SWA that follows sleep deprivation. PMID:27927960
Rodriguez, Alexander V; Funk, Chadd M; Vyazovskiy, Vladyslav V; Nir, Yuval; Tononi, Giulio; Cirelli, Chiara
2016-12-07
During non-rapid eye movement (NREM) sleep, cortical neurons alternate between ON periods of firing and OFF periods of silence. This bi-stability, which is largely synchronous across neurons, is reflected in the EEG as slow waves. Slow-wave activity (SWA) increases with wake duration and declines homeostatically during sleep, but the underlying mechanisms remain unclear. One possibility is neuronal "fatigue": high, sustained firing in wake would force neurons to recover with more frequent and longer OFF periods during sleep. Another possibility is net synaptic potentiation during wake: stronger coupling among neurons would lead to greater synchrony and therefore higher SWA. Here, we obtained a comparable increase in sustained firing (6 h) in cortex by: (1) keeping mice awake by exposure to novel objects to promote plasticity and (2) optogenetically activating a local population of cortical neurons at wake-like levels during sleep. Sleep after extended wake led to increased SWA, higher synchrony, and more time spent OFF, with a positive correlation between SWA, synchrony, and OFF periods. Moreover, time spent OFF was correlated with cortical firing during prior wake. After local optogenetic stimulation, SWA and cortical synchrony decreased locally, time spent OFF did not change, and local SWA was not correlated with either measure. Moreover, laser-induced cortical firing was not correlated with time spent OFF afterward. Overall, these results suggest that high sustained firing per se may not be the primary determinant of SWA increases observed after extended wake. A long-standing hypothesis is that neurons fire less during slow-wave sleep to recover from the "fatigue" accrued during wake, when overall synaptic activity is higher than in sleep. This idea, however, has rarely been tested and other factors, namely increased cortical synchrony, could explain why sleep slow-wave activity (SWA) is higher after extended wake. We forced neurons in the mouse cortex to fire at high levels for 6 h in 2 different conditions: during active wake with exploration and during sleep. We find that neurons need more time OFF only after sustained firing in wake, suggesting that fatigue due to sustained firing alone is unlikely to account for the increase in SWA that follows sleep deprivation. Copyright © 2016 the authors 0270-6474/16/3612436-12$15.00/0.
Changes in the neural control of a complex motor sequence during learning
Otchy, Timothy M.; Goldberg, Jesse H.; Aronov, Dmitriy; Fee, Michale S.
2011-01-01
The acquisition of complex motor sequences often proceeds through trial-and-error learning, requiring the deliberate exploration of motor actions and the concomitant evaluation of the resulting performance. Songbirds learn their song in this manner, producing highly variable vocalizations as juveniles. As the song improves, vocal variability is gradually reduced until it is all but eliminated in adult birds. In the present study we examine how the motor program underlying such a complex motor behavior evolves during learning by recording from the robust nucleus of the arcopallium (RA), a motor cortex analog brain region. In young birds, neurons in RA exhibited highly variable firing patterns that throughout development became more precise, sparse, and bursty. We further explored how the developing motor program in RA is shaped by its two main inputs: LMAN, the output nucleus of a basal ganglia-forebrain circuit, and HVC, a premotor nucleus. Pharmacological inactivation of LMAN during singing made the song-aligned firing patterns of RA neurons adultlike in their stereotypy without dramatically affecting the spike statistics or the overall firing patterns. Removing the input from HVC, on the other hand, resulted in a complete loss of stereotypy of both the song and the underlying motor program. Thus our results show that a basal ganglia-forebrain circuit drives motor exploration required for trial-and-error learning by adding variability to the developing motor program. As learning proceeds and the motor circuits mature, the relative contribution of LMAN is reduced, allowing the premotor input from HVC to drive an increasingly stereotyped song. PMID:21543758
Viskontas, Indre V
2008-12-01
To gain a complete understanding of how the brain functions, both in illness and good health, data from multiple levels of analysis must be integrated. Technical advances have made direct recordings of neuronal activity deep inside the human brain tractable, providing a rare glimpse into cellular processes during long-term memory formation. Recent findings using intracranial recordings in the medial temporal lobe inform current neural network models of memory, and may lead to a more comprehensive understanding of the neural basis of memory-related processes. These recordings have shown that cells in the hippocampus appear to support declarative learning by distinguishing novel and familiar stimuli via changes in firing patterns. Some cells with highly selective and invariant responses have also been described, and these responses seem to represent abstract concepts such as identity, rather than superficial perceptual features of items. Importantly, however, both selective and globally responsive cells are capable of changing their preferred stimulus depending on the conscious demands of the task. Firing patterns of human medial temporal lobe neurons indicate that cells can be both plastic and stable in terms of the information that they code; although some cells show highly selective and reproducible excitatory responses when presented with a familiar object, other cells change their receptive fields in line with changes in experience and the cognitive environment.
Post-eclosion odor experience modifies olfactory receptor neuron coding in Drosophila
Iyengar, Atulya; Chakraborty, Tuhin Subhra; Goswami, Sarit Pati; Wu, Chun-Fang; Siddiqi, Obaid
2010-01-01
Olfactory responses of Drosophila undergo pronounced changes after eclosion. The flies develop attraction to odors to which they are exposed and aversion to other odors. Behavioral adaptation is correlated with changes in the firing pattern of olfactory receptor neurons (ORNs). In this article, we present an information-theoretic analysis of the firing pattern of ORNs. Flies reared in a synthetic odorless medium were transferred after eclosion to three different media: (i) a synthetic medium relatively devoid of odor cues, (ii) synthetic medium infused with a single odorant, and (iii) complex cornmeal medium rich in odors. Recordings were made from an identified sensillum (type II), and the Jensen–Shannon divergence (DJS) was used to assess quantitatively the differences between ensemble spike responses to different odors. Analysis shows that prolonged exposure to ethyl acetate and several related esters increases sensitivity to these esters but does not improve the ability of the fly to distinguish between them. Flies exposed to cornmeal display varied sensitivity to these odorants and at the same time develop greater capacity to distinguish between odors. Deprivation of odor experience on an odorless synthetic medium leads to a loss of both sensitivity and acuity. Rich olfactory experience thus helps to shape the ORNs response and enhances its discriminative power. The experiments presented here demonstrate an experience-dependent adaptation at the level of the receptor neuron. PMID:20448199
Post-eclosion odor experience modifies olfactory receptor neuron coding in Drosophila.
Iyengar, Atulya; Chakraborty, Tuhin Subhra; Goswami, Sarit Pati; Wu, Chun-Fang; Siddiqi, Obaid
2010-05-25
Olfactory responses of Drosophila undergo pronounced changes after eclosion. The flies develop attraction to odors to which they are exposed and aversion to other odors. Behavioral adaptation is correlated with changes in the firing pattern of olfactory receptor neurons (ORNs). In this article, we present an information-theoretic analysis of the firing pattern of ORNs. Flies reared in a synthetic odorless medium were transferred after eclosion to three different media: (i) a synthetic medium relatively devoid of odor cues, (ii) synthetic medium infused with a single odorant, and (iii) complex cornmeal medium rich in odors. Recordings were made from an identified sensillum (type II), and the Jensen-Shannon divergence (D(JS)) was used to assess quantitatively the differences between ensemble spike responses to different odors. Analysis shows that prolonged exposure to ethyl acetate and several related esters increases sensitivity to these esters but does not improve the ability of the fly to distinguish between them. Flies exposed to cornmeal display varied sensitivity to these odorants and at the same time develop greater capacity to distinguish between odors. Deprivation of odor experience on an odorless synthetic medium leads to a loss of both sensitivity and acuity. Rich olfactory experience thus helps to shape the ORNs response and enhances its discriminative power. The experiments presented here demonstrate an experience-dependent adaptation at the level of the receptor neuron.
Yu, Haitao; Dhingra, Rishi R; Dick, Thomas E; Galán, Roberto F
2017-01-01
Neural activity generally displays irregular firing patterns even in circuits with apparently regular outputs, such as motor pattern generators, in which the output frequency fluctuates randomly around a mean value. This "circuit noise" is inherited from the random firing of single neurons, which emerges from stochastic ion channel gating (channel noise), spontaneous neurotransmitter release, and its diffusion and binding to synaptic receptors. Here we demonstrate how to expand conductance-based network models that are originally deterministic to include realistic, physiological noise, focusing on stochastic ion channel gating. We illustrate this procedure with a well-established conductance-based model of the respiratory pattern generator, which allows us to investigate how channel noise affects neural dynamics at the circuit level and, in particular, to understand the relationship between the respiratory pattern and its breath-to-breath variability. We show that as the channel number increases, the duration of inspiration and expiration varies, and so does the coefficient of variation of the breath-to-breath interval, which attains a minimum when the mean duration of expiration slightly exceeds that of inspiration. For small channel numbers, the variability of the expiratory phase dominates over that of the inspiratory phase, and vice versa for large channel numbers. Among the four different cell types in the respiratory pattern generator, pacemaker cells exhibit the highest sensitivity to channel noise. The model shows that suppressing input from the pons leads to longer inspiratory phases, a reduction in breathing frequency, and larger breath-to-breath variability, whereas enhanced input from the raphe nucleus increases breathing frequency without changing its pattern. A major source of noise in neuronal circuits is the "flickering" of ion currents passing through the neurons' membranes (channel noise), which cannot be suppressed experimentally. Computational simulations are therefore the best way to investigate the effects of this physiological noise by manipulating its level at will. We investigate the role of noise in the respiratory pattern generator and show that endogenous, breath-to-breath variability is tightly linked to the respiratory pattern. Copyright © 2017 the American Physiological Society.
Cortical ensemble activity increasingly predicts behaviour outcomes during learning of a motor task
NASA Astrophysics Data System (ADS)
Laubach, Mark; Wessberg, Johan; Nicolelis, Miguel A. L.
2000-06-01
When an animal learns to make movements in response to different stimuli, changes in activity in the motor cortex seem to accompany and underlie this learning. The precise nature of modifications in cortical motor areas during the initial stages of motor learning, however, is largely unknown. Here we address this issue by chronically recording from neuronal ensembles located in the rat motor cortex, throughout the period required for rats to learn a reaction-time task. Motor learning was demonstrated by a decrease in the variance of the rats' reaction times and an increase in the time the animals were able to wait for a trigger stimulus. These behavioural changes were correlated with a significant increase in our ability to predict the correct or incorrect outcome of single trials based on three measures of neuronal ensemble activity: average firing rate, temporal patterns of firing, and correlated firing. This increase in prediction indicates that an association between sensory cues and movement emerged in the motor cortex as the task was learned. Such modifications in cortical ensemble activity may be critical for the initial learning of motor tasks.
Bressloff, P C; Bressloff, N W; Cowan, J D
2000-11-01
Orientation tuning in a ring of pulse-coupled integrate-and-fire (IF) neurons is analyzed in terms of spontaneous pattern formation. It is shown how the ring bifurcates from a synchronous state to a non-phase-locked state whose spike trains are characterized by clustered but irregular fluctuations of the interspike intervals (ISIs). The separation of these clusters in phase space results in a localized peak of activity as measured by the time-averaged firing rate of the neurons. This generates a sharp orientation tuning curve that can lock to a slowly rotating, weakly tuned external stimulus. Under certain conditions, the peak can slowly rotate even to a fixed external stimulus. The ring also exhibits hysteresis due to the subcritical nature of the bifurcation to sharp orientation tuning. Such behavior is shown to be consistent with a corresponding analog version of the IF model in the limit of slow synaptic interactions. For fast synapses, the deterministic fluctuations of the ISIs associated with the tuning curve can support a coefficient of variation of order unity.
Liu, Pin W.; Blair, Nathaniel T.
2017-01-01
Action potential (AP) shape is a key determinant of cellular electrophysiological behavior. We found that in small-diameter, capsaicin-sensitive dorsal root ganglia neurons corresponding to nociceptors (from rats of either sex), stimulation at frequencies as low as 1 Hz produced progressive broadening of the APs. Stimulation at 10 Hz for 3 s resulted in an increase in AP width by an average of 76 ± 7% at 22°C and by 38 ± 3% at 35°C. AP clamp experiments showed that spike broadening results from frequency-dependent reduction of potassium current during spike repolarization. The major current responsible for frequency-dependent reduction of overall spike-repolarizing potassium current was identified as Kv3 current by its sensitivity to low concentrations of 4-aminopyridine (IC50 <100 μm) and block by the peptide inhibitor blood depressing substance I (BDS-I). There was a small component of Kv1-mediated current during AP repolarization, but this current did not show frequency-dependent reduction. In a small fraction of cells, there was a component of calcium-dependent potassium current that showed frequency-dependent reduction, but the contribution to overall potassium current reduction was almost always much smaller than that of Kv3-mediated current. These results show that Kv3 channels make a major contribution to spike repolarization in small-diameter DRG neurons and undergo frequency-dependent reduction, leading to spike broadening at moderate firing frequencies. Spike broadening from frequency-dependent reduction in Kv3 current could mitigate the frequency-dependent decreases in conduction velocity typical of C-fiber axons. SIGNIFICANCE STATEMENT Small-diameter dorsal root ganglia (DRG) neurons mediating nociception and other sensory modalities express many types of potassium channels, but how they combine to control firing patterns and conduction is not well understood. We found that action potentials of small-diameter rat DRG neurons showed spike broadening at frequencies as low as 1 Hz and that spike broadening resulted predominantly from frequency-dependent inactivation of Kv3 channels. Spike width helps to control transmitter release, conduction velocity, and firing patterns and understanding the role of particular potassium channels can help to guide new pharmacological strategies for targeting pain-sensing neurons selectively. PMID:28877968
Liu, Pin W; Blair, Nathaniel T; Bean, Bruce P
2017-10-04
Action potential (AP) shape is a key determinant of cellular electrophysiological behavior. We found that in small-diameter, capsaicin-sensitive dorsal root ganglia neurons corresponding to nociceptors (from rats of either sex), stimulation at frequencies as low as 1 Hz produced progressive broadening of the APs. Stimulation at 10 Hz for 3 s resulted in an increase in AP width by an average of 76 ± 7% at 22°C and by 38 ± 3% at 35°C. AP clamp experiments showed that spike broadening results from frequency-dependent reduction of potassium current during spike repolarization. The major current responsible for frequency-dependent reduction of overall spike-repolarizing potassium current was identified as Kv3 current by its sensitivity to low concentrations of 4-aminopyridine (IC 50 <100 μm) and block by the peptide inhibitor blood depressing substance I (BDS-I). There was a small component of Kv1-mediated current during AP repolarization, but this current did not show frequency-dependent reduction. In a small fraction of cells, there was a component of calcium-dependent potassium current that showed frequency-dependent reduction, but the contribution to overall potassium current reduction was almost always much smaller than that of Kv3-mediated current. These results show that Kv3 channels make a major contribution to spike repolarization in small-diameter DRG neurons and undergo frequency-dependent reduction, leading to spike broadening at moderate firing frequencies. Spike broadening from frequency-dependent reduction in Kv3 current could mitigate the frequency-dependent decreases in conduction velocity typical of C-fiber axons. SIGNIFICANCE STATEMENT Small-diameter dorsal root ganglia (DRG) neurons mediating nociception and other sensory modalities express many types of potassium channels, but how they combine to control firing patterns and conduction is not well understood. We found that action potentials of small-diameter rat DRG neurons showed spike broadening at frequencies as low as 1 Hz and that spike broadening resulted predominantly from frequency-dependent inactivation of Kv3 channels. Spike width helps to control transmitter release, conduction velocity, and firing patterns and understanding the role of particular potassium channels can help to guide new pharmacological strategies for targeting pain-sensing neurons selectively. Copyright © 2017 the authors 0270-6474/17/379705-10$15.00/0.
Mandelblat-Cerf, Yael; Ramesh, Rohan N; Burgess, Christian R; Patella, Paola; Yang, Zongfang; Lowell, Bradford B; Andermann, Mark L
2015-01-01
Agouti-related-peptide (AgRP) neurons—interoceptive neurons in the arcuate nucleus of the hypothalamus (ARC)—are both necessary and sufficient for driving feeding behavior. To better understand the functional roles of AgRP neurons, we performed optetrode electrophysiological recordings from AgRP neurons in awake, behaving AgRP-IRES-Cre mice. In free-feeding mice, we observed a fivefold increase in AgRP neuron firing with mounting caloric deficit in afternoon vs morning recordings. In food-restricted mice, as food became available, AgRP neuron firing dropped, yet remained elevated as compared to firing in sated mice. The rapid drop in spiking activity of AgRP neurons at meal onset may reflect a termination of the drive to find food, while residual, persistent spiking may reflect a sustained drive to consume food. Moreover, nearby neurons inhibited by AgRP neuron photostimulation, likely including satiety-promoting pro-opiomelanocortin (POMC) neurons, demonstrated opposite changes in spiking. Finally, firing of ARC neurons was also rapidly modulated within seconds of individual licks for liquid food. These findings suggest novel roles for antagonistic AgRP and POMC neurons in the regulation of feeding behaviors across multiple timescales. DOI: http://dx.doi.org/10.7554/eLife.07122.001 PMID:26159614
Farkas, Imre; Vastagh, Csaba; Sárvári, Miklós; Liposits, Zsolt
2013-01-01
The orexigenic peptide, ghrelin is known to influence function of GnRH neurons, however, the direct effects of the hormone upon these neurons have not been explored, yet. The present study was undertaken to reveal expression of growth hormone secretagogue receptor (GHS-R) in GnRH neurons and elucidate the mechanisms of ghrelin actions upon them. Ca(2+)-imaging revealed a ghrelin-triggered increase of the Ca(2+)-content in GT1-7 neurons kept in a steroid-free medium, which was abolished by GHS-R-antagonist JMV2959 (10 µM) suggesting direct action of ghrelin. Estradiol (1nM) eliminated the ghrelin-evoked rise of Ca(2+)-content, indicating the estradiol dependency of the process. Expression of GHS-R mRNA was then confirmed in GnRH-GFP neurons of transgenic mice by single cell RT-PCR. Firing rate and burst frequency of GnRH-GFP neurons were lower in metestrous than proestrous mice. Ghrelin (40 nM-4 μM) administration resulted in a decreased firing rate and burst frequency of GnRH neurons in metestrous, but not in proestrous mice. Ghrelin also decreased the firing rate of GnRH neurons in males. The ghrelin-evoked alterations of the firing parameters were prevented by JMV2959, supporting the receptor-specific actions of ghrelin on GnRH neurons. In metestrous mice, ghrelin decreased the frequency of GABAergic mPSCs in GnRH neurons. Effects of ghrelin were abolished by the cannabinoid receptor type-1 (CB1) antagonist AM251 (1µM) and the intracellularly applied DAG-lipase inhibitor THL (10 µM), indicating the involvement of retrograde endocannabinoid signaling. These findings demonstrate that ghrelin exerts direct regulatory effects on GnRH neurons via GHS-R, and modulates the firing of GnRH neurons in an ovarian-cycle and endocannabinoid dependent manner.
Mode-locking behavior of Izhikevich neurons under periodic external forcing
NASA Astrophysics Data System (ADS)
Farokhniaee, AmirAli; Large, Edward W.
2017-06-01
Many neurons in the auditory system of the brain must encode periodic signals. These neurons under periodic stimulation display rich dynamical states including mode locking and chaotic responses. Periodic stimuli such as sinusoidal waves and amplitude modulated sounds can lead to various forms of n :m mode-locked states, in which a neuron fires n action potentials per m cycles of the stimulus. Here, we study mode-locking in the Izhikevich neurons, a reduced model of the Hodgkin-Huxley neurons. The Izhikevich model is much simpler in terms of the dimension of the coupled nonlinear differential equations compared with other existing models, but excellent for generating the complex spiking patterns observed in real neurons. We obtained the regions of existence of the various mode-locked states on the frequency-amplitude plane, called Arnold tongues, for the Izhikevich neurons. Arnold tongue analysis provides useful insight into the organization of mode-locking behavior of neurons under periodic forcing. We find these tongues for both class-1 and class-2 excitable neurons in both deterministic and noisy regimes.
Luo, Sarah X; Timbang, Leah; Kim, Jae-Ick; Shang, Yulei; Sandoval, Kadellyn; Tang, Amy A; Whistler, Jennifer L; Ding, Jun B; Huang, Eric J
2016-12-20
Neural circuits involving midbrain dopaminergic (DA) neurons regulate reward and goal-directed behaviors. Although local GABAergic input is known to modulate DA circuits, the mechanism that controls excitatory/inhibitory synaptic balance in DA neurons remains unclear. Here, we show that DA neurons use autocrine transforming growth factor β (TGF-β) signaling to promote the growth of axons and dendrites. Surprisingly, removing TGF-β type II receptor in DA neurons also disrupts the balance in TGF-β1 expression in DA neurons and neighboring GABAergic neurons, which increases inhibitory input, reduces excitatory synaptic input, and alters phasic firing patterns in DA neurons. Mice lacking TGF-β signaling in DA neurons are hyperactive and exhibit inflexibility in relinquishing learned behaviors and re-establishing new stimulus-reward associations. These results support a role for TGF-β in regulating the delicate balance of excitatory/inhibitory synaptic input in local microcircuits involving DA and GABAergic neurons and its potential contributions to neuropsychiatric disorders. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.
Song, Ying; Zhang, Yong-Mei; Xu, Jie; Wu, Jing-Ru; Qin, Xia; Hua, Rong
2013-10-25
The aim of the paper is to study the effect of spontaneous firing of injured dorsal root ganglion (DRG) neuron in chronic compression of DRG (CCD) model on excitability of wide dynamic range (WDR) neuron in rat spinal dorsal horn. In vivo intracellular recording was done in DRG neurons and in vivo extracellular recording was done in spinal WDR neurons. After CCD, incidence of spontaneous discharge and firing frequency enhanced to 59.46% and (4.30 ± 0.69) Hz respectively from 22.81% and (0.60 ± 0.08) Hz in normal control group (P < 0.05). Local administration of 50 nmol/L tetrodotoxin (TTX) on DRG neuron in CCD rats decreased the spontaneous activities of WDR neurons from (191.97 ± 45.20)/min to (92.50 ± 30.32)/min (P < 0.05). On the other side, local administration of 100 mmol/L KCl on DRG neuron evoked spontaneous firing in a reversible way (n = 5) in silent WDR neurons of normal rats. There was 36.36% (12/33) WDR neuron showing after-discharge in response to innocuous mechanical stimuli on cutaneous receptive field in CCD rats, while after-discharge was not seen in control rats. Local administration of TTX on DRG with a concentration of 50 nmol/L attenuated innocuous electric stimuli-evoked after-discharge of WDR neurons in CCD rats in a reversible manner, and the frequency was decreased from (263 ± 56.5) Hz to (117 ± 30) Hz (P < 0.05). The study suggests that the excitability of WDR neurons is influenced by spontaneous firings of DRG neurons after CCD.
PDF neuron firing phase-shifts key circadian activity neurons in Drosophila
Guo, Fang; Cerullo, Isadora; Chen, Xiao; Rosbash, Michael
2014-01-01
Our experiments address two long-standing models for the function of the Drosophila brain circadian network: a dual oscillator model, which emphasizes the primacy of PDF-containing neurons, and a cell-autonomous model for circadian phase adjustment. We identify five different circadian (E) neurons that are a major source of rhythmicity and locomotor activity. Brief firing of PDF cells at different times of day generates a phase response curve (PRC), which mimics a light-mediated PRC and requires PDF receptor expression in the five E neurons. Firing also resembles light by causing TIM degradation in downstream neurons. Unlike light however, firing-mediated phase-shifting is CRY-independent and exploits the E3 ligase component CUL-3 in the early night to degrade TIM. Our results suggest that PDF neurons integrate light information and then modulate the phase of E cell oscillations and behavioral rhythms. The results also explain how fly brain rhythms persist in constant darkness and without CRY. DOI: http://dx.doi.org/10.7554/eLife.02780.001 PMID:24939987
PDF neuron firing phase-shifts key circadian activity neurons in Drosophila.
Guo, Fang; Cerullo, Isadora; Chen, Xiao; Rosbash, Michael
2014-06-17
Our experiments address two long-standing models for the function of the Drosophila brain circadian network: a dual oscillator model, which emphasizes the primacy of PDF-containing neurons, and a cell-autonomous model for circadian phase adjustment. We identify five different circadian (E) neurons that are a major source of rhythmicity and locomotor activity. Brief firing of PDF cells at different times of day generates a phase response curve (PRC), which mimics a light-mediated PRC and requires PDF receptor expression in the five E neurons. Firing also resembles light by causing TIM degradation in downstream neurons. Unlike light however, firing-mediated phase-shifting is CRY-independent and exploits the E3 ligase component CUL-3 in the early night to degrade TIM. Our results suggest that PDF neurons integrate light information and then modulate the phase of E cell oscillations and behavioral rhythms. The results also explain how fly brain rhythms persist in constant darkness and without CRY.
NASA Astrophysics Data System (ADS)
Jia, Bing
2014-05-01
The coexistence of a resting condition and period-1 firing near a subcritical Hopf bifurcation point, lying between the monostable resting condition and period-1 firing, is often observed in neurons of the central nervous systems. Near such a bifurcation point in the Morris—Lecar (ML) model, the attraction domain of the resting condition decreases while that of the coexisting period-1 firing increases as the bifurcation parameter value increases. With the increase of the coupling strength, and parameter and initial value dependent synchronization transition processes from non-synchronization to compete synchronization are simulated in two coupled ML neurons with coexisting behaviors: one neuron chosen as the resting condition and the other the coexisting period-1 firing. The complete synchronization is either a resting condition or period-1 firing dependent on the initial values of period-1 firing when the bifurcation parameter value is small or middle and is period-1 firing when the parameter value is large. As the bifurcation parameter value increases, the probability of the initial values of a period-1 firing neuron that lead to complete synchronization of period-1 firing increases, while that leading to complete synchronization of the resting condition decreases. It shows that the attraction domain of a coexisting behavior is larger, the probability of initial values leading to complete synchronization of this behavior is higher. The bifurcations of the coupled system are investigated and discussed. The results reveal the complex dynamics of synchronization behaviors of the coupled system composed of neurons with the coexisting resting condition and period-1 firing, and are helpful to further identify the dynamics of the spatiotemporal behaviors of the central nervous system.
Rolls, Edmund T
2015-01-01
The recall of information stored in the hippocampus involves a series of corticocortical backprojections via the entorhinal cortex, parahippocampal gyrus, and one or more neocortical stages. Each stage is considered to be a pattern association network, with the retrieval cue at each stage the firing of neurons in the previous stage. The leading factor that determines the capacity of this multistage pattern association backprojection pathway is the number of connections onto any one neuron, which provides a quantitative basis for why there are as many backprojections between adjacent stages in the hierarchy as forward projections. The issue arises of why this multistage backprojection system uses diluted connectivity. One reason is that a multistage backprojection system with expansion of neuron numbers at each stage enables the hippocampus to address during recall the very large numbers of neocortical neurons, which would otherwise require hippocampal neurons to make very large numbers of synapses if they were directly onto neocortical neurons. The second reason is that as shown here, diluted connectivity in the backprojection pathways reduces the probability of more than one connection onto a receiving neuron in the backprojecting pathways, which otherwise reduces the capacity of the system, that is the number of memories that can be recalled from the hippocampus to the neocortex. For similar reasons, diluted connectivity is advantageous in pattern association networks in other brain systems such as the orbitofrontal cortex and amygdala; for related reasons, in autoassociation networks in, for example, the hippocampal CA3 and the neocortex; and for the different reason that diluted connectivity facilitates the operation of competitive networks in forward-connected cortical systems. © 2015 Elsevier B.V. All rights reserved.
How Does the Sparse Memory “Engram” Neurons Encode the Memory of a Spatial–Temporal Event?
Guan, Ji-Song; Jiang, Jun; Xie, Hong; Liu, Kai-Yuan
2016-01-01
Episodic memory in human brain is not a fixed 2-D picture but a highly dynamic movie serial, integrating information at both the temporal and the spatial domains. Recent studies in neuroscience reveal that memory storage and recall are closely related to the activities in discrete memory engram (trace) neurons within the dentate gyrus region of hippocampus and the layer 2/3 of neocortex. More strikingly, optogenetic reactivation of those memory trace neurons is able to trigger the recall of naturally encoded memory. It is still unknown how the discrete memory traces encode and reactivate the memory. Considering a particular memory normally represents a natural event, which consists of information at both the temporal and spatial domains, it is unknown how the discrete trace neurons could reconstitute such enriched information in the brain. Furthermore, as the optogenetic-stimuli induced recall of memory did not depend on firing pattern of the memory traces, it is most likely that the spatial activation pattern, but not the temporal activation pattern of the discrete memory trace neurons encodes the memory in the brain. How does the neural circuit convert the activities in the spatial domain into the temporal domain to reconstitute memory of a natural event? By reviewing the literature, here we present how the memory engram (trace) neurons are selected and consolidated in the brain. Then, we will discuss the main challenges in the memory trace theory. In the end, we will provide a plausible model of memory trace cell network, underlying the conversion of neural activities between the spatial domain and the temporal domain. We will also discuss on how the activation of sparse memory trace neurons might trigger the replay of neural activities in specific temporal patterns. PMID:27601979
How Does the Sparse Memory "Engram" Neurons Encode the Memory of a Spatial-Temporal Event?
Guan, Ji-Song; Jiang, Jun; Xie, Hong; Liu, Kai-Yuan
2016-01-01
Episodic memory in human brain is not a fixed 2-D picture but a highly dynamic movie serial, integrating information at both the temporal and the spatial domains. Recent studies in neuroscience reveal that memory storage and recall are closely related to the activities in discrete memory engram (trace) neurons within the dentate gyrus region of hippocampus and the layer 2/3 of neocortex. More strikingly, optogenetic reactivation of those memory trace neurons is able to trigger the recall of naturally encoded memory. It is still unknown how the discrete memory traces encode and reactivate the memory. Considering a particular memory normally represents a natural event, which consists of information at both the temporal and spatial domains, it is unknown how the discrete trace neurons could reconstitute such enriched information in the brain. Furthermore, as the optogenetic-stimuli induced recall of memory did not depend on firing pattern of the memory traces, it is most likely that the spatial activation pattern, but not the temporal activation pattern of the discrete memory trace neurons encodes the memory in the brain. How does the neural circuit convert the activities in the spatial domain into the temporal domain to reconstitute memory of a natural event? By reviewing the literature, here we present how the memory engram (trace) neurons are selected and consolidated in the brain. Then, we will discuss the main challenges in the memory trace theory. In the end, we will provide a plausible model of memory trace cell network, underlying the conversion of neural activities between the spatial domain and the temporal domain. We will also discuss on how the activation of sparse memory trace neurons might trigger the replay of neural activities in specific temporal patterns.
Mechanisms and consequences of action potential burst firing in rat neocortical pyramidal neurons
Williams, Stephen R; Stuart, Greg J
1999-01-01
Electrophysiological recordings and pharmacological manipulations were used to investigate the mechanisms underlying the generation of action potential burst firing and its postsynaptic consequences in visually identified rat layer 5 pyramidal neurons in vitro.Based upon repetitive firing properties and subthreshold membrane characteristics, layer 5 pyramidal neurons were separated into three classes: regular firing and weak and strong intrinsically burst firing.High frequency (330 ± 10 Hz) action potential burst firing was abolished or greatly weakened by the removal of Ca2+ (n = 5) from, or by the addition of the Ca2+ channel antagonist Ni2+ (250–500 μm; n = 8) to, the perfusion medium.The blockade of apical dendritic sodium channels by the local dendritic application of TTX (100 nm; n = 5) abolished or greatly weakened action potential burst firing, as did the local apical dendritic application of Ni2+ (1 mm; n = 5).Apical dendritic depolarisation resulted in low frequency (157 ± 26 Hz; n = 6) action potential burst firing in regular firing neurons, as classified by somatic current injection. The intensity of action potential burst discharges in intrinsically burst firing neurons was facilitated by dendritic depolarisation (n = 11).Action potential amplitude decreased throughout a burst when recorded somatically, suggesting that later action potentials may fail to propagate axonally. Axonal recordings demonstrated that each action potential in a burst is axonally initiated and that no decrement in action potential amplitude is apparent in the axon > 30 μm from the soma.Paired recordings (n = 16) from synaptically coupled neurons indicated that each action potential in a burst could cause transmitter release. EPSPs or EPSCs evoked by a presynaptic burst of action potentials showed use-dependent synaptic depression.A postsynaptic, TTX-sensitive voltage-dependent amplification process ensured that later EPSPs in a burst were amplified when generated from membrane potentials positive to -60 mV, providing a postsynaptic mechanism that counteracts use-dependent depression at synapses between layer 5 pyramidal neurons. PMID:10581316
Bifurcations of large networks of two-dimensional integrate and fire neurons.
Nicola, Wilten; Campbell, Sue Ann
2013-08-01
Recently, a class of two-dimensional integrate and fire models has been used to faithfully model spiking neurons. This class includes the Izhikevich model, the adaptive exponential integrate and fire model, and the quartic integrate and fire model. The bifurcation types for the individual neurons have been thoroughly analyzed by Touboul (SIAM J Appl Math 68(4):1045-1079, 2008). However, when the models are coupled together to form networks, the networks can display bifurcations that an uncoupled oscillator cannot. For example, the networks can transition from firing with a constant rate to burst firing. This paper introduces a technique to reduce a full network of this class of neurons to a mean field model, in the form of a system of switching ordinary differential equations. The reduction uses population density methods and a quasi-steady state approximation to arrive at the mean field system. Reduced models are derived for networks with different topologies and different model neurons with biologically derived parameters. The mean field equations are able to qualitatively and quantitatively describe the bifurcations that the full networks display. Extensions and higher order approximations are discussed.
Zhang, Jiwei; Newhall, Katherine; Zhou, Douglas; Rangan, Aaditya
2014-04-01
Randomly connected populations of spiking neurons display a rich variety of dynamics. However, much of the current modeling and theoretical work has focused on two dynamical extremes: on one hand homogeneous dynamics characterized by weak correlations between neurons, and on the other hand total synchrony characterized by large populations firing in unison. In this paper we address the conceptual issue of how to mathematically characterize the partially synchronous "multiple firing events" (MFEs) which manifest in between these two dynamical extremes. We further develop a geometric method for obtaining the distribution of magnitudes of these MFEs by recasting the cascading firing event process as a first-passage time problem, and deriving an analytical approximation of the first passage time density valid for large neuron populations. Thus, we establish a direct link between the voltage distributions of excitatory and inhibitory neurons and the number of neurons firing in an MFE that can be easily integrated into population-based computational methods, thereby bridging the gap between homogeneous firing regimes and total synchrony.
Neural encoding of competitive effort in the anterior cingulate cortex.
Hillman, Kristin L; Bilkey, David K
2012-09-01
In social environments, animals often compete to obtain limited resources. Strategically electing to work against another animal represents a cost-benefit decision. Is the resource worth an investment of competitive effort? The anterior cingulate cortex (ACC) has been implicated in cost-benefit decision-making, but its role in competitive effort has not been examined. We recorded ACC neurons in freely moving rats as they performed a competitive foraging choice task. When at least one of the two choice options demanded competitive effort, the majority of ACC neurons exhibited heightened and differential firing between the goal trajectories. Inter- and intrasession manipulations revealed that differential firing was not attributable to effort or reward in isolation; instead ACC encoding patterns appeared to indicate net utility assessments of available choice options. Our findings suggest that the ACC is important for encoding competitive effort, a cost-benefit domain that has received little neural-level investigation despite its predominance in nature.
Leader neurons in leaky integrate and fire neural network simulations.
Zbinden, Cyrille
2011-10-01
In this paper, we highlight the topological properties of leader neurons whose existence is an experimental fact. Several experimental studies show the existence of leader neurons in population bursts of activity in 2D living neural networks (Eytan and Marom, J Neurosci 26(33):8465-8476, 2006; Eckmann et al., New J Phys 10(015011), 2008). A leader neuron is defined as a neuron which fires at the beginning of a burst (respectively network spike) more often than we expect by chance considering its mean firing rate. This means that leader neurons have some burst triggering power beyond a chance-level statistical effect. In this study, we characterize these leader neuron properties. This naturally leads us to simulate neural 2D networks. To build our simulations, we choose the leaky integrate and fire (lIF) neuron model (Gerstner and Kistler 2002; Cessac, J Math Biol 56(3):311-345, 2008), which allows fast simulations (Izhikevich, IEEE Trans Neural Netw 15(5):1063-1070, 2004; Gerstner and Naud, Science 326:379-380, 2009). The dynamics of our lIF model has got stable leader neurons in the burst population that we simulate. These leader neurons are excitatory neurons and have a low membrane potential firing threshold. Except for these two first properties, the conditions required for a neuron to be a leader neuron are difficult to identify and seem to depend on several parameters involved in the simulations themselves. However, a detailed linear analysis shows a trend of the properties required for a neuron to be a leader neuron. Our main finding is: A leader neuron sends signals to many excitatory neurons as well as to few inhibitory neurons and a leader neuron receives only signals from few other excitatory neurons. Our linear analysis exhibits five essential properties of leader neurons each with different relative importance. This means that considering a given neural network with a fixed mean number of connections per neuron, our analysis gives us a way of predicting which neuron is a good leader neuron and which is not. Our prediction formula correctly assesses leadership for at least ninety percent of neurons.
Integrate-and-fire neurons driven by asymmetric dichotomous noise.
Droste, Felix; Lindner, Benjamin
2014-12-01
We consider a general integrate-and-fire (IF) neuron driven by asymmetric dichotomous noise. In contrast to the Gaussian white noise usually used in the so-called diffusion approximation, this noise is colored, i.e., it exhibits temporal correlations. We give an analytical expression for the stationary voltage distribution of a neuron receiving such noise and derive recursive relations for the moments of the first passage time density, which allow us to calculate the firing rate and the coefficient of variation of interspike intervals. We study how correlations in the input affect the rate and regularity of firing under variation of the model's parameters for leaky and quadratic IF neurons. Further, we consider the limit of small correlation times and find lowest order corrections to the first passage time moments to be proportional to the square root of the correlation time. We show analytically that to this lowest order, correlations always lead to a decrease in firing rate for a leaky IF neuron. All theoretical expressions are compared to simulations of leaky and quadratic IF neurons.
Rybak, I A; O'Connor, R; Ross, A; Shevtsova, N A; Nuding, S C; Segers, L S; Shannon, R; Dick, T E; Dunin-Barkowski, W L; Orem, J M; Solomon, I C; Morris, K F; Lindsey, B G
2008-10-01
A large body of data suggests that the pontine respiratory group (PRG) is involved in respiratory phase-switching and the reconfiguration of the brain stem respiratory network. However, connectivity between the PRG and ventral respiratory column (VRC) in computational models has been largely ad hoc. We developed a network model with PRG-VRC connectivity inferred from coordinated in vivo experiments. Neurons were modeled in the "integrate-and-fire" style; some neurons had pacemaker properties derived from the model of Breen et al. We recapitulated earlier modeling results, including reproduction of activity profiles of different respiratory neurons and motor outputs, and their changes under different conditions (vagotomy, pontine lesions, etc.). The model also reproduced characteristic changes in neuronal and motor patterns observed in vivo during fictive cough and during hypoxia in non-rapid eye movement sleep. Our simulations suggested possible mechanisms for respiratory pattern reorganization during these behaviors. The model predicted that network- and pacemaker-generated rhythms could be co-expressed during the transition from gasping to eupnea, producing a combined "burst-ramp" pattern of phrenic discharges. To test this prediction, phrenic activity and multiple single neuron spike trains were monitored in vagotomized, decerebrate, immobilized, thoracotomized, and artificially ventilated cats during hypoxia and recovery. In most experiments, phrenic discharge patterns during recovery from hypoxia were similar to those predicted by the model. We conclude that under certain conditions, e.g., during recovery from severe brain hypoxia, components of a distributed network activity present during eupnea can be co-expressed with gasp patterns generated by a distinct, functionally "simplified" mechanism.
Han, Fang; Wang, Zhijie; Fan, Hong
2017-01-01
This paper proposed a new method to determine the neuronal tuning curves for maximum information efficiency by computing the optimum firing rate distribution. Firstly, we proposed a general definition for the information efficiency, which is relevant to mutual information and neuronal energy consumption. The energy consumption is composed of two parts: neuronal basic energy consumption and neuronal spike emission energy consumption. A parameter to model the relative importance of energy consumption is introduced in the definition of the information efficiency. Then, we designed a combination of exponential functions to describe the optimum firing rate distribution based on the analysis of the dependency of the mutual information and the energy consumption on the shape of the functions of the firing rate distributions. Furthermore, we developed a rapid algorithm to search the parameter values of the optimum firing rate distribution function. Finally, we found with the rapid algorithm that a combination of two different exponential functions with two free parameters can describe the optimum firing rate distribution accurately. We also found that if the energy consumption is relatively unimportant (important) compared to the mutual information or the neuronal basic energy consumption is relatively large (small), the curve of the optimum firing rate distribution will be relatively flat (steep), and the corresponding optimum tuning curve exhibits a form of sigmoid if the stimuli distribution is normal. PMID:28270760
COMMUNICATION: Electrophysiological response dynamics during focal cortical infarction
NASA Astrophysics Data System (ADS)
Chiganos, Terry C., Jr.; Jensen, Winnie; Rousche, Patrick J.
2006-12-01
While the intracellular processes of hypoxia-induced necrosis and the intercellular mechanisms of post-ischemic neurotoxicity associated with stroke are well documented, the dynamic electrophysiological (EP) response of neurons within the core or periinfarct zone remains unclear. The present study validates a method for continuous measurement of the local EP responses during focal cortical infarction induced via photothrombosis. Single microwire electrodes were acutely implanted into the primary auditory cortex of eight rats. Multi-unit neural activity, evoked via a continuous 2 Hz click stimulus, was recorded before, during and after infarction to assess neuronal function in response to local, permanent ischemia. During sham infarction, the average stimulus-evoked peak firing rate over 20 min remained stable at 495.5 ± 14.5 spikes s-1, indicating temporal stability of neural function under normal conditions. Stimulus-evoked peak firing was reliably reduced to background levels (firing frequency in the absence of stimulus) following initiation of photothrombosis over a period of 439 ± 92 s. The post-infarction firing patterns exhibited unique temporal degradation of the peak firing rate, suggesting a variable response to ischemic challenge. Despite the inherent complexity of cerebral ischemia secondary to microvascular occlusion, complete loss of EP function consistently occurred 300-600 s after photothrombosis. The results suggest that microwire recording during photothrombosis provides a simple and highly efficacious strategy for assessing the electrophysiological dynamics of cortical infarction.
Revill, Ann L; Fuglevand, Andrew J
2017-01-01
Motor neurons are the output neurons of the central nervous system and are responsible for controlling muscle contraction. When initially activated during voluntary contraction, firing rates of motor neurons increase steeply but then level out at modest rates. Activation of an intrinsic source of excitatory current at recruitment onset may underlie the initial steep increase in firing rate in motor neurons. We attempted to disable this intrinsic excitatory current by artificially activating an inhibitory reflex. When motor neuron activity was recorded while the inhibitory reflex was engaged, firing rates no longer increased steeply, suggesting that the intrinsic excitatory current was probably responsible for the initial sharp rise in motor neuron firing rate. During graded isometric contractions, motor unit (MU) firing rates increase steeply upon recruitment but then level off at modest rates even though muscle force continues to increase. The mechanisms underlying such firing behaviour are not known although activation of persistent inward currents (PICs) might be involved. PICs are intrinsic, voltage-dependent currents that activate strongly when motor neurons (MNs) are first recruited. Such activation might cause a sharp escalation in depolarizing current and underlie the steep initial rise in MU firing rate. Because PICs can be disabled with synaptic inhibition, we hypothesized that artificial activation of an inhibitory pathway might curb this initial steep rise in firing rate. To test this, human subjects performed slow triangular ramp contractions of the ankle dorsiflexors in the absence and presence of tonic synaptic inhibition delivered to tibialis anterior (TA) MNs by sural nerve stimulation. Firing rate profiles (expressed as a function of contraction force) of TA MUs recorded during these tasks were compared for control and stimulation conditions. Under control conditions, during the ascending phase of the triangular contractions, 93% of the firing rate profiles were best fitted by rising exponential functions. With stimulation, however, firing rate profiles were best fitted with linear functions or with less steeply rising exponentials. Firing rate profiles for the descending phases of the contractions were best fitted with linear functions for both control and stimulation conditions. These results seem consistent with the idea that PICs contribute to non-linear firing rate profiles during ascending but not descending phases of contractions. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.
Shaping Neuronal Network Activity by Presynaptic Mechanisms
Ashery, Uri
2015-01-01
Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level. PMID:26372048
A GABAergic nigrotectal pathway for coordination of drinking behavior
Rossi, Mark A.; Li, Haofang E.; Lu, Dongye; Kim, Il Hwan; Bartholomew, Ryan A.; Gaidis, Erin; Barter, Joseph W.; Kim, Namsoo; Cai, Min Tong; Soderling, Scott H.; Yin, Henry H.
2016-01-01
The contribution of basal ganglia outputs to consummatory behavior remains poorly understood. We recorded from the substantia nigra pars reticulata (SNR), the major basal ganglia output nucleus, during self-initiated drinking. The firing rates of many lateral SNR neurons were time-locked to individual licks. These neurons send GABAergic projections to the deep layers of the orofacial region of the lateral tectum (superior colliculus, SC). Many tectal neurons are also time-locked to licking, but their activity is usually antiphase to that of SNR neurons, suggesting inhibitory nigrotectal projections. We used optogenetics to selectively activate the GABAergic nigrotectal afferents in the deep layers of the SC. Photo-stimulation of the nigrotectal projections transiently inhibited the activity of the lick-related tectal neurons, disrupted their licking-related oscillatory pattern, and suppressed self-initiated drinking. These results demonstrate that GABAergic nigrotectal projections play a crucial role in coordinating drinking behavior. PMID:27043290
Slack channels expressed in sensory neurons control neuropathic pain in mice.
Lu, Ruirui; Bausch, Anne E; Kallenborn-Gerhardt, Wiebke; Stoetzer, Carsten; Debruin, Natasja; Ruth, Peter; Geisslinger, Gerd; Leffler, Andreas; Lukowski, Robert; Schmidtko, Achim
2015-01-21
Slack (Slo2.2) is a sodium-activated potassium channel that regulates neuronal firing activities and patterns. Previous studies identified Slack in sensory neurons, but its contribution to acute and chronic pain in vivo remains elusive. Here we generated global and sensory neuron-specific Slack mutant mice and analyzed their behavior in various animal models of pain. Global ablation of Slack led to increased hypersensitivity in models of neuropathic pain, whereas the behavior in models of inflammatory and acute nociceptive pain was normal. Neuropathic pain behaviors were also exaggerated after ablation of Slack selectively in sensory neurons. Notably, the Slack opener loxapine ameliorated persisting neuropathic pain behaviors. In conclusion, Slack selectively controls the sensory input in neuropathic pain states, suggesting that modulating its activity might represent a novel strategy for management of neuropathic pain. Copyright © 2015 the authors 0270-6474/15/351125-11$15.00/0.
Duménieu, Maël; Oulé, Marie; Kreutz, Michael R.; Lopez-Rojas, Jeffrey
2017-01-01
Neurons are highly polarized cells with apparent functional and morphological differences between dendrites and axon. A critical determinant for the molecular and functional identity of axonal and dendritic segments is the restricted expression of voltage-gated ion channels (VGCs). Several studies show an uneven distribution of ion channels and their differential regulation within dendrites and axons, which is a prerequisite for an appropriate integration of synaptic inputs and the generation of adequate action potential (AP) firing patterns. This review article will focus on the signaling pathways leading to segmented expression of voltage-gated potassium and sodium ion channels at the neuronal plasma membrane and the regulatory mechanisms ensuring segregated functions. We will also discuss the relevance of proper ion channel targeting for neuronal physiology and how alterations in polarized distribution contribute to neuronal pathology. PMID:28484374
Kohashi, Tsunehiko; Carlson, Bruce A
2014-01-01
Temporal patterns of spiking often convey behaviorally relevant information. Various synaptic mechanisms and intrinsic membrane properties can influence neuronal selectivity to temporal patterns of input. However, little is known about how synaptic mechanisms and intrinsic properties together determine the temporal selectivity of neuronal output. We tackled this question by recording from midbrain electrosensory neurons in mormyrid fish, in which the processing of temporal intervals between communication signals can be studied in a reduced in vitro preparation. Mormyrids communicate by varying interpulse intervals (IPIs) between electric pulses. Within the midbrain posterior exterolateral nucleus (ELp), the temporal patterns of afferent spike trains are filtered to establish single-neuron IPI tuning. We performed whole-cell recording from ELp neurons in a whole-brain preparation and examined the relationship between intrinsic excitability and IPI tuning. We found that spike frequency adaptation of ELp neurons was highly variable. Postsynaptic potentials (PSPs) of strongly adapting (phasic) neurons were more sharply tuned to IPIs than weakly adapting (tonic) neurons. Further, the synaptic filtering of IPIs by tonic neurons was more faithfully converted into variation in spiking output, particularly at short IPIs. Pharmacological manipulation under current- and voltage-clamp revealed that tonic firing is mediated by a fast, large-conductance Ca(2+)-activated K(+) (KCa) current (BK) that speeds up action potential repolarization. These results suggest that BK currents can shape the temporal filtering of sensory inputs by modifying both synaptic responses and PSP-to-spike conversion. Slow SK-type KCa currents have previously been implicated in temporal processing. Thus, both fast and slow KCa currents can fine-tune temporal selectivity.
Light-evoked hyperpolarization and silencing of neurons by conjugated polymers.
Feyen, Paul; Colombo, Elisabetta; Endeman, Duco; Nova, Mattia; Laudato, Lucia; Martino, Nicola; Antognazza, Maria Rosa; Lanzani, Guglielmo; Benfenati, Fabio; Ghezzi, Diego
2016-03-04
The ability to control and modulate the action potential firing in neurons represents a powerful tool for neuroscience research and clinical applications. While neuronal excitation has been achieved with many tools, including electrical and optical stimulation, hyperpolarization and neuronal inhibition are typically obtained through patch-clamp or optogenetic manipulations. Here we report the use of conjugated polymer films interfaced with neurons for inducing a light-mediated inhibition of their electrical activity. We show that prolonged illumination of the interface triggers a sustained hyperpolarization of the neuronal membrane that significantly reduces both spontaneous and evoked action potential firing. We demonstrate that the polymeric interface can be activated by either visible or infrared light and is capable of modulating neuronal activity in brain slices and explanted retinas. These findings prove the ability of conjugated polymers to tune neuronal firing and suggest their potential application for the in-vivo modulation of neuronal activity.
Light-evoked hyperpolarization and silencing of neurons by conjugated polymers
Feyen, Paul; Colombo, Elisabetta; Endeman, Duco; Nova, Mattia; Laudato, Lucia; Martino, Nicola; Antognazza, Maria Rosa; Lanzani, Guglielmo; Benfenati, Fabio; Ghezzi, Diego
2016-01-01
The ability to control and modulate the action potential firing in neurons represents a powerful tool for neuroscience research and clinical applications. While neuronal excitation has been achieved with many tools, including electrical and optical stimulation, hyperpolarization and neuronal inhibition are typically obtained through patch-clamp or optogenetic manipulations. Here we report the use of conjugated polymer films interfaced with neurons for inducing a light-mediated inhibition of their electrical activity. We show that prolonged illumination of the interface triggers a sustained hyperpolarization of the neuronal membrane that significantly reduces both spontaneous and evoked action potential firing. We demonstrate that the polymeric interface can be activated by either visible or infrared light and is capable of modulating neuronal activity in brain slices and explanted retinas. These findings prove the ability of conjugated polymers to tune neuronal firing and suggest their potential application for the in-vivo modulation of neuronal activity. PMID:26940513
Tuned normalization explains the size of attention modulations.
Ni, Amy M; Ray, Supratim; Maunsell, John H R
2012-02-23
The effect of attention on firing rates varies considerably within a single cortical area. The firing rate of some neurons is greatly modulated by attention while others are hardly affected. The reason for this variability across neurons is unknown. We found that the variability in attention modulation across neurons in area MT of macaques can be well explained by variability in the strength of tuned normalization across neurons. The presence of tuned normalization also explains a striking asymmetry in attention effects within neurons: when two stimuli are in a neuron's receptive field, directing attention to the preferred stimulus modulates firing rates more than directing attention to the nonpreferred stimulus. These findings show that much of the neuron-to-neuron variability in modulation of responses by attention depends on variability in the way the neurons process multiple stimuli, rather than differences in the influence of top-down signals related to attention. Copyright © 2012 Elsevier Inc. All rights reserved.
Ding, Shengyuan; Wei, Wei
2011-01-01
GABA projection neurons (GABA neurons) in the substantia nigra pars reticulata (SNr) and dopamine projection neurons (DA neurons) in substantia nigra pars compacta (SNc) have strikingly different firing properties. SNc DA neurons fire low-frequency, long-duration spikes, whereas SNr GABA neurons fire high-frequency, short-duration spikes. Since voltage-activated sodium (NaV) channels are critical to spike generation, the different firing properties raise the possibility that, compared with DA neurons, NaV channels in SNr GABA neurons have higher density, faster kinetics, and less cumulative inactivation. Our quantitative RT-PCR analysis on immunohistochemically identified nigral neurons indicated that mRNAs for pore-forming NaV1.1 and NaV1.6 subunits and regulatory NaVβ1 and Navβ4 subunits are more abundant in SNr GABA neurons than SNc DA neurons. These α-subunits and β-subunits are key subunits for forming NaV channels conducting the transient NaV current (INaT), persistent Na current (INaP), and resurgent Na current (INaR). Nucleated patch-clamp recordings showed that INaT had a higher density, a steeper voltage-dependent activation, and a faster deactivation in SNr GABA neurons than in SNc DA neurons. INaT also recovered more quickly from inactivation and had less cumulative inactivation in SNr GABA neurons than in SNc DA neurons. Furthermore, compared with nigral DA neurons, SNr GABA neurons had a larger INaR and INaP. Blockade of INaP induced a larger hyperpolarization in SNr GABA neurons than in SNc DA neurons. Taken together, these results indicate that NaV channels expressed in fast-spiking SNr GABA neurons and slow-spiking SNc DA neurons are tailored to support their different spiking capabilities. PMID:21880943
Optogenetic feedback control of neural activity
Newman, Jonathan P; Fong, Ming-fai; Millard, Daniel C; Whitmire, Clarissa J; Stanley, Garrett B; Potter, Steve M
2015-01-01
Optogenetic techniques enable precise excitation and inhibition of firing in specified neuronal populations and artifact-free recording of firing activity. Several studies have suggested that optical stimulation provides the precision and dynamic range requisite for closed-loop neuronal control, but no approach yet permits feedback control of neuronal firing. Here we present the ‘optoclamp’, a feedback control technology that provides continuous, real-time adjustments of bidirectional optical stimulation in order to lock spiking activity at specified targets over timescales ranging from seconds to days. We demonstrate how this system can be used to decouple neuronal firing levels from ongoing changes in network excitability due to multi-hour periods of glutamatergic or GABAergic neurotransmission blockade in vitro as well as impinging vibrissal sensory drive in vivo. This technology enables continuous, precise optical control of firing in neuronal populations in order to disentangle causally related variables of circuit activation in a physiologically and ethologically relevant manner. DOI: http://dx.doi.org/10.7554/eLife.07192.001 PMID:26140329
Antunes, Gabriela; Faria da Silva, Samuel F; Simoes de Souza, Fabio M
2018-06-01
Mirror neurons fire action potentials both when the agent performs a certain behavior and watches someone performing a similar action. Here, we present an original mirror neuron model based on the spike-timing-dependent plasticity (STDP) between two morpho-electrical models of neocortical pyramidal neurons. Both neurons fired spontaneously with basal firing rate that follows a Poisson distribution, and the STDP between them was modeled by the triplet algorithm. Our simulation results demonstrated that STDP is sufficient for the rise of mirror neuron function between the pairs of neocortical neurons. This is a proof of concept that pairs of neocortical neurons associating sensory inputs to motor outputs could operate like mirror neurons. In addition, we used the mirror neuron model to investigate whether channelopathies associated with autism spectrum disorder could impair the modeled mirror function. Our simulation results showed that impaired hyperpolarization-activated cationic currents (Ih) affected the mirror function between the pairs of neocortical neurons coupled by STDP.
Statistical mechanics of neocortical interactions. Derivation of short-term-memory capacity
NASA Astrophysics Data System (ADS)
Ingber, Lester
1984-06-01
A theory developed by the author to describe macroscopic neocortical interactions demonstrates that empirical values of chemical and electrical parameters of synaptic interactions establish several minima of the path-integral Lagrangian as a function of excitatory and inhibitory columnar firings. The number of possible minima, their time scales of hysteresis and probable reverberations, and their nearest-neighbor columnar interactions are all consistent with well-established empirical rules of human short-term memory. Thus, aspects of conscious experience are derived from neuronal firing patterns, using modern methods of nonlinear nonequilibrium statistical mechanics to develop realistic explicit synaptic interactions.
Asynchronous Rate Chaos in Spiking Neuronal Circuits
Harish, Omri; Hansel, David
2015-01-01
The brain exhibits temporally complex patterns of activity with features similar to those of chaotic systems. Theoretical studies over the last twenty years have described various computational advantages for such regimes in neuronal systems. Nevertheless, it still remains unclear whether chaos requires specific cellular properties or network architectures, or whether it is a generic property of neuronal circuits. We investigate the dynamics of networks of excitatory-inhibitory (EI) spiking neurons with random sparse connectivity operating in the regime of balance of excitation and inhibition. Combining Dynamical Mean-Field Theory with numerical simulations, we show that chaotic, asynchronous firing rate fluctuations emerge generically for sufficiently strong synapses. Two different mechanisms can lead to these chaotic fluctuations. One mechanism relies on slow I-I inhibition which gives rise to slow subthreshold voltage and rate fluctuations. The decorrelation time of these fluctuations is proportional to the time constant of the inhibition. The second mechanism relies on the recurrent E-I-E feedback loop. It requires slow excitation but the inhibition can be fast. In the corresponding dynamical regime all neurons exhibit rate fluctuations on the time scale of the excitation. Another feature of this regime is that the population-averaged firing rate is substantially smaller in the excitatory population than in the inhibitory population. This is not necessarily the case in the I-I mechanism. Finally, we discuss the neurophysiological and computational significance of our results. PMID:26230679
Mejias-Aponte, Carlos A.; Ye, Changquan; Bonci, Antonello; Kiyatkin, Eugene A.
2015-01-01
Systemic administration of cocaine is thought to decrease the firing rates of ventral tegmental area (VTA) dopamine (DA) neurons. However, this view is based on categorizations of recorded neurons as DA neurons using preselected electrophysiological characteristics lacking neurochemical confirmation. Without applying cellular preselection, we recorded the impulse activity of VTA neurons in response to cocaine administration in anesthetized adult rats. The phenotype of recorded neurons was determined by their juxtacellular labeling and immunohistochemical detection of tyrosine hydroxylase (TH), a DA marker. We found that intravenous cocaine altered firing rates in the majority of recorded VTA neurons. Within the cocaine-responsive neurons, half of the population was excited and the other half was inhibited. Both populations had similar discharge rates and firing regularities, and most neurons did not exhibit changes in burst firing. Inhibited neurons were more abundant in the posterior VTA, whereas excited neurons were distributed evenly throughout the VTA. Cocaine-excited neurons were more likely to be excited by footshock. Within the subpopulation of TH-positive neurons, 36% were excited by cocaine and 64% were inhibited. Within the subpopulation of TH-negative neurons, 44% were excited and 28% were inhibited. Contrary to the prevailing view that all DA neurons are inhibited by cocaine, we found a subset of confirmed VTA DA neurons that is excited by systemic administration of cocaine. We provide evidence indicating that DA neurons are heterogeneous in their response to cocaine and that VTA non-DA neurons play an active role in processing systemic cocaine. PMID:25653355
Jang, Min Jee; Nam, Yoonkey
2015-01-01
Abstract. Optical recording facilitates monitoring the activity of a large neural network at the cellular scale, but the analysis and interpretation of the collected data remain challenging. Here, we present a MATLAB-based toolbox, named NeuroCa, for the automated processing and quantitative analysis of large-scale calcium imaging data. Our tool includes several computational algorithms to extract the calcium spike trains of individual neurons from the calcium imaging data in an automatic fashion. Two algorithms were developed to decompose the imaging data into the activity of individual cells and subsequently detect calcium spikes from each neuronal signal. Applying our method to dense networks in dissociated cultures, we were able to obtain the calcium spike trains of ∼1000 neurons in a few minutes. Further analyses using these data permitted the quantification of neuronal responses to chemical stimuli as well as functional mapping of spatiotemporal patterns in neuronal firing within the spontaneous, synchronous activity of a large network. These results demonstrate that our method not only automates time-consuming, labor-intensive tasks in the analysis of neural data obtained using optical recording techniques but also provides a systematic way to visualize and quantify the collective dynamics of a network in terms of its cellular elements. PMID:26229973
Intrinsic and integrative properties of substantia nigra pars reticulata neurons
Zhou, Fu-Ming; Lee, Christian R.
2011-01-01
The GABA projection neurons of the substantia nigra pars reticulata (SNr) are output neurons for the basal ganglia and thus critical for movement control. Their most striking neurophysiological feature is sustained, spontaneous high frequency spike firing. A fundamental question is: what are the key ion channels supporting the remarkable firing capability in these neurons? Recent studies indicate that these neurons express tonically active TRPC3 channels that conduct a Na-dependent inward current even at hyperpolarized membrane potentials. When the membrane potential reaches −60 mV, a voltage-gated persistent sodium current (INaP) starts to activate, further depolarizing the membrane potential. At or slightly below −50 mV, the large transient voltage-activated sodium current (INaT) starts to activate and eventually triggers the rapid rising phase of action potentials. SNr GABA neurons have a higher density of (INaT), contributing to the faster rise and larger amplitude of action potentials, compared with the slow-spiking dopamine neurons. INaT also recovers from inactivation more quickly in SNr GABA neurons than in nigral dopamine neurons. In SNr GABA neurons, the rising phase of the action potential triggers the activation of high-threshold, inactivation-resistant Kv3-like channels that can rapidly repolarize the membrane. These intrinsic ion channels provide SNr GABA neurons with the ability to fire spontaneous and sustained high frequency spikes. Additionally, robust GABA inputs from direct pathway medium spiny neurons in the striatum and GABA neurons in the globus pallidus may inhibit and silence SNr GABA neurons, whereas glutamate synaptic input from the subthalamic nucleus may induce burst firing in SNr GABA neurons. Thus, afferent GABA and glutamate synaptic inputs sculpt the tonic high frequency firing of SNr GABA neurons and the consequent inhibition of their targets into an integrated motor control signal that is further fine-tuned by neuromodulators including dopamine, serotonin, endocannabinoids, and H2O2. PMID:21839148
Nagoya, Kouta; Nakamura, Shiro; Ikeda, Keiko; Onimaru, Hiroshi; Yoshida, Atsushi; Nakayama, Kiyomi; Mochizuki, Ayako; Kiyomoto, Masaaki; Sato, Fumihiko; Kawakami, Kiyoshi; Takahashi, Koji; Inoue, Tomio
2017-09-01
Phox2b encodes a paired-like homeodomain-containing transcription factor essential for development of the autonomic nervous system. Phox2b-expressing (Phox2b + ) neurons are present in the reticular formation dorsal to the trigeminal motor nucleus (RdV) as well as the nucleus of the solitary tract and parafacial respiratory group. However, the nature of Phox2b + RdV neurons is still unclear. We investigated the physiological and morphological properties of Phox2b + RdV neurons using postnatal day 2-7 transgenic rats expressing yellow fluorescent protein under the control of Phox2b. Almost all of Phox2b + RdV neurons were glutamatergic, whereas Phox2b-negative (Phox2b - ) RdV neurons consisted of a few glutamatergic, many GABAergic, and many glycinergic neurons. The majority (48/56) of Phox2b + neurons showed low-frequency firing (LF), while most of Phox2b - neurons (35/42) exhibited high-frequency firing (HF) in response to intracellularly injected currents. All, but one, Phox2b + neurons (55/56) did not fire spontaneously, whereas three-fourths of the Phox2b - neurons (31/42) were spontaneously active. K + channel and persistent Na + current blockers affected the firing of LF and HF neurons. The majority of Phox2b + (35/46) and half of the Phox2b - neurons (19/40) did not respond to stimulations of the mesencephalic trigeminal nucleus, the trigeminal tract, and the principal sensory trigeminal nucleus. Biocytin labeling revealed that about half of the Phox2b + (5/12) and Phox2b - RdV neurons (5/10) send their axons to the trigeminal motor nucleus. These results suggest that Phox2b + RdV neurons have distinct neurotransmitter phenotypes and firing properties from Phox2b - RdV neurons and might play important roles in feeding-related functions including suckling and possibly mastication. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.
Neuronal Spike Timing Adaptation Described with a Fractional Leaky Integrate-and-Fire Model
Teka, Wondimu; Marinov, Toma M.; Santamaria, Fidel
2014-01-01
The voltage trace of neuronal activities can follow multiple timescale dynamics that arise from correlated membrane conductances. Such processes can result in power-law behavior in which the membrane voltage cannot be characterized with a single time constant. The emergent effect of these membrane correlations is a non-Markovian process that can be modeled with a fractional derivative. A fractional derivative is a non-local process in which the value of the variable is determined by integrating a temporal weighted voltage trace, also called the memory trace. Here we developed and analyzed a fractional leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to 1, with 1 representing the normal derivative. As the exponent of the fractional derivative decreases, the weights of the voltage trace increase. Thus, the value of the voltage is increasingly correlated with the trajectory of the voltage in the past. By varying only the fractional exponent, our model can reproduce upward and downward spike adaptations found experimentally in neocortical pyramidal cells and tectal neurons in vitro. The model also produces spikes with longer first-spike latency and high inter-spike variability with power-law distribution. We further analyze spike adaptation and the responses to noisy and oscillatory input. The fractional model generates reliable spike patterns in response to noisy input. Overall, the spiking activity of the fractional leaky integrate-and-fire model deviates from the spiking activity of the Markovian model and reflects the temporal accumulated intrinsic membrane dynamics that affect the response of the neuron to external stimulation. PMID:24675903
Arnold, Fiona JL; Hofmann, Frank; Bengtson, C. Peter; Wittmann, Malte; Vanhoutte, Peter; Bading, Hilmar
2005-01-01
A simplified cell culture system was developed to study neuronal plasticity. As changes in synaptic strength may alter network activity patterns, we grew hippocampal neurones on a microelectrode array (MEA) and monitored their collective behaviour with 60 electrodes simultaneously. We found that exposure of the network for 15 min to the GABAA receptor antagonist bicuculline induced an increase in synaptic efficacy at excitatory synapses that was associated with an increase in the frequency of miniature AMPA receptor-mediated EPSCs and a change in network activity from uncoordinated firing of neurones (lacking any recognizable pattern) to a highly organized, periodic and synchronous burst pattern. Induction of recurrent synchronous bursting was dependent on NMDA receptor activation and required extracellular signal-regulated kinase (ERK)1/2 signalling and translation of pre-existing mRNAs. Once induced, the burst pattern persisted for several days; its maintenance phase (> 4 h) was dependent on gene transcription taking place in a critical period of 120 min following induction. Thus, cultured hippocampal neurones display a simple, transcription and protein synthesis-dependent form of plasticity. The non-invasive nature of MEA recordings provides a significant advantage over traditional assays for synaptic connectivity (i.e. long-term potentiation in brain slices) and facilitates the search for activity-regulated genes critical for late-phase plasticity. PMID:15618268
Arnold, Fiona J L; Hofmann, Frank; Bengtson, C Peter; Wittmann, Malte; Vanhoutte, Peter; Bading, Hilmar
2005-04-01
A simplified cell culture system was developed to study neuronal plasticity. As changes in synaptic strength may alter network activity patterns, we grew hippocampal neurones on a microelectrode array (MEA) and monitored their collective behaviour with 60 electrodes simultaneously. We found that exposure of the network for 15 min to the GABA(A) receptor antagonist bicuculline induced an increase in synaptic efficacy at excitatory synapses that was associated with an increase in the frequency of miniature AMPA receptor-mediated EPSCs and a change in network activity from uncoordinated firing of neurones (lacking any recognizable pattern) to a highly organized, periodic and synchronous burst pattern. Induction of recurrent synchronous bursting was dependent on NMDA receptor activation and required extracellular signal-regulated kinase (ERK)1/2 signalling and translation of pre-existing mRNAs. Once induced, the burst pattern persisted for several days; its maintenance phase (> 4 h) was dependent on gene transcription taking place in a critical period of 120 min following induction. Thus, cultured hippocampal neurones display a simple, transcription and protein synthesis-dependent form of plasticity. The non-invasive nature of MEA recordings provides a significant advantage over traditional assays for synaptic connectivity (i.e. long-term potentiation in brain slices) and facilitates the search for activity-regulated genes critical for late-phase plasticity.
Claussen, Catherine M; Dafny, Nachum
2016-01-01
The misuse and abuse of the psychostimulant, methylphenidate (MPD) the drug of choice in the treatment of attention deficit hyperactivity disorder (ADHD) has seen a sharp uprising in recent years among both youth and adults for its cognitive enhancing effects and for recreational purposes. This uprise in illicit use has lead to many questions concerning the long term consequences of MPD exposure. The objective of this study was to record animal behavior concomitantly with the caudate nucleus (CN) neuronal activity following acute and repetitive (chronic) dose response exposure to methylphenidate (MPD). A saline control and three MPD dose (0.6, 2.5, and 10.0 mg/kg) groups were used. Behaviorally, the same MPD dose in some animals following chronic MPD exposure elicited behavioral sensitization and other animals elicited behavioral tolerance. Based on this finding, the CN neuronal population recorded from animals expressing behavioral sensitization were also evaluated separately from CN neurons recorded from animals expressing behavioral tolerance to chronic MPD exposure, respectively. Significant differences in CN neuronal population responses between the behaviorally sensitized and the behaviorally tolerant animals was observed for the 2.5 and 10.0 mg/kg MPD exposed groups. For 2.5 mg/kg MPD, behaviorally sensitized animals responded by decreasing their firing rates while behaviorally tolerant animals showed mainly an increase in their firing rates. The CN neuronal responses recorded from the behaviorally sensitized animals following 10.0 mg/kg MPD responded by increasing their firing rates whereas the CN neuronal recordings from the behaviorally tolerant animals showed that approximately half decreased their firing rates in response to 10.0 mg/kg MPD exposure. The comparison of percentage change in neuronal firing rates showed that the behaviorally tolerant animals trended to exhibit increases in their neuronal firing rates at ED1 following initial MPD exposure and oppositely at ED10 MPD rechallenge. While the behaviorally sensitized animals in general increased in their percentage change of firing rats were observed following acute 10.0 mg/kg MPD and the behaviorally sensitized 10.0 mg/kg MPD animals and a robust increase in neuronal firing rates at ED1 and ED10 rechallenge. These results suggest the need to first individually analyze animal behavioral activity, and than to evaluate the neuronal responses to the drug based on the animals behavioral response to chronic MPD exposure. PMID:26101057
Midcervical neuronal discharge patterns during and following hypoxia
Sandhu, M. S.; Baekey, D. M.; Maling, N. G.; Sanchez, J. C.; Reier, P. J.
2014-01-01
Anatomical evidence indicates that midcervical interneurons can be synaptically coupled with phrenic motoneurons. Accordingly, we hypothesized that interneurons in the C3–C4 spinal cord can display discharge patterns temporally linked with inspiratory phrenic motor output. Anesthetized adult rats were studied before, during, and after a 4-min bout of moderate hypoxia. Neuronal discharge in C3–C4 lamina I–IX was monitored using a multielectrode array while phrenic nerve activity was extracellularly recorded. For the majority of cells, spike-triggered averaging (STA) of ipsilateral inspiratory phrenic nerve activity based on neuronal discharge provided no evidence of discharge synchrony. However, a distinct STA phrenic peak with a 6.83 ± 1.1 ms lag was present for 5% of neurons, a result that indicates a monosynaptic connection with phrenic motoneurons. The majority (93%) of neurons changed discharge rate during hypoxia, and the diverse responses included both increased and decreased firing. Hypoxia did not change the incidence of STA peaks in the phrenic nerve signal. Following hypoxia, 40% of neurons continued to discharge at rates above prehypoxia values (i.e., short-term potentiation, STP), and cells with initially low discharge rates were more likely to show STP (P < 0.001). We conclude that a population of nonphrenic C3–C4 neurons in the rat spinal cord is synaptically coupled to the phrenic motoneuron pool, and these cells can modulate inspiratory phrenic output. In addition, the C3–C4 propriospinal network shows a robust and complex pattern of activation both during and following an acute bout of hypoxia. PMID:25552641
Neural reactivations during sleep determine network credit assignment
Gulati, Tanuj; Guo, Ling; Ramanathan, Dhakshin S.; Bodepudi, Anitha; Ganguly, Karunesh
2018-01-01
A fundamental goal of motor learning is to establish neural patterns that produce a desired behavioral outcome. It remains unclear how and when the nervous system solves this “credit–assignment” problem. Using neuroprosthetic learning where we could control the causal relationship between neurons and behavior, here we show that sleep–dependent processing is required for credit-assignment and the establishment of task-related functional connectivity reflecting the casual neuron-behavior relationship. Importantly, we found a strong link between the microstructure of sleep reactivations and credit assignment, with downscaling of non–causal activity. Strikingly, decoupling of spiking to slow–oscillations using optogenetic methods eliminated rescaling. Thus, our results suggest that coordinated firing during sleep plays an essential role in establishing sparse activation patterns that reflect the causal neuron–behavior relationship. PMID:28692062
Tuned Normalization Explains the Size of Attention Modulations
Ni, Amy M.; Ray, Supratim; Maunsell, John H. R.
2012-01-01
SUMMARY The effect of attention on firing rates varies considerably within a single cortical area. The firing rate of some neurons is greatly modulated by attention while others are hardly affected. The reason for this variability across neurons is unknown. We found that the variability in attention modulation across neurons in area MT of macaques can be well explained by variability in the strength of tuned normalization across neurons. The presence of tuned normalization also explains a striking asymmetry in attention effects within neurons: when two stimuli are in a neuron’s receptive field, directing attention to the preferred stimulus modulates firing rates more than directing attention to the non-preferred stimulus. These findings show that much of the neuron-to-neuron variability in modulation of responses by attention depends on variability in the way the neurons process multiple stimuli, rather than differences in the influence of top-down signals related to attention. PMID:22365552
NASA Astrophysics Data System (ADS)
Sun, Xiaojuan; Perc, Matjaž; Kurths, Jürgen
2017-05-01
In this paper, we study effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks. Our focus is on the impact of two parameters, namely the time delay τ and the probability of partial time delay pdelay, whereby the latter determines the probability with which a connection between two neurons is delayed. Our research reveals that partial time delays significantly affect phase synchronization in this system. In particular, partial time delays can either enhance or decrease phase synchronization and induce synchronization transitions with changes in the mean firing rate of neurons, as well as induce switching between synchronized neurons with period-1 firing to synchronized neurons with period-2 firing. Moreover, in comparison to a neuronal network where all connections are delayed, we show that small partial time delay probabilities have especially different influences on phase synchronization of neuronal networks.
Sun, Xiaojuan; Perc, Matjaž; Kurths, Jürgen
2017-05-01
In this paper, we study effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks. Our focus is on the impact of two parameters, namely the time delay τ and the probability of partial time delay p delay , whereby the latter determines the probability with which a connection between two neurons is delayed. Our research reveals that partial time delays significantly affect phase synchronization in this system. In particular, partial time delays can either enhance or decrease phase synchronization and induce synchronization transitions with changes in the mean firing rate of neurons, as well as induce switching between synchronized neurons with period-1 firing to synchronized neurons with period-2 firing. Moreover, in comparison to a neuronal network where all connections are delayed, we show that small partial time delay probabilities have especially different influences on phase synchronization of neuronal networks.
Dodson, Paul D.; Larvin, Joseph T.; Duffell, James M.; Garas, Farid N.; Doig, Natalie M.; Kessaris, Nicoletta; Duguid, Ian C.; Bogacz, Rafal; Butt, Simon J.B.; Magill, Peter J.
2015-01-01
Summary Transcriptional codes initiated during brain development are ultimately realized in adulthood as distinct cell types performing specialized roles in behavior. Focusing on the mouse external globus pallidus (GPe), we demonstrate that the potential contributions of two GABAergic GPe cell types to voluntary action are fated from early life to be distinct. Prototypic GPe neurons derive from the medial ganglionic eminence of the embryonic subpallium and express the transcription factor Nkx2-1. These neurons fire at high rates during alert rest, and encode movements through heterogeneous firing rate changes, with many neurons decreasing their activity. In contrast, arkypallidal GPe neurons originate from lateral/caudal ganglionic eminences, express the transcription factor FoxP2, fire at low rates during rest, and encode movements with robust increases in firing. We conclude that developmental diversity positions prototypic and arkypallidal neurons to fulfil distinct roles in behavior via their disparate regulation of GABA release onto different basal ganglia targets. PMID:25843402
Kaabi, Mohamed Ghaith; Tonnelier, Arnaud; Martinez, Dominique
2011-05-01
In traditional event-driven strategies, spike timings are analytically given or calculated with arbitrary precision (up to machine precision). Exact computation is possible only for simplified neuron models, mainly the leaky integrate-and-fire model. In a recent paper, Zheng, Tonnelier, and Martinez (2009) introduced an approximate event-driven strategy, named voltage stepping, that allows the generic simulation of nonlinear spiking neurons. Promising results were achieved in the simulation of single quadratic integrate-and-fire neurons. Here, we assess the performance of voltage stepping in network simulations by considering more complex neurons (quadratic integrate-and-fire neurons with adaptation) coupled with multiple synapses. To handle the discrete nature of synaptic interactions, we recast voltage stepping in a general framework, the discrete event system specification. The efficiency of the method is assessed through simulations and comparisons with a modified time-stepping scheme of the Runge-Kutta type. We demonstrated numerically that the original order of voltage stepping is preserved when simulating connected spiking neurons, independent of the network activity and connectivity.
Zhong, Guisheng; Shevtsova, Natalia A; Rybak, Ilya A; Harris-Warrick, Ronald M
2012-01-01
We explored the organization of the spinal central pattern generator (CPG) for locomotion by analysing the activity of spinal interneurons and motoneurons during spontaneous deletions occurring during fictive locomotion in the isolated neonatal mouse spinal cord, following earlier work on locomotor deletions in the cat. In the isolated mouse spinal cord, most spontaneous deletions were non-resetting, with rhythmic activity resuming after an integer number of cycles. Flexor and extensor deletions showed marked asymmetry: flexor deletions were accompanied by sustained ipsilateral extensor activity, whereas rhythmic flexor bursting was not perturbed during extensor deletions. Rhythmic activity on one side of the cord was not perturbed during non-resetting spontaneous deletions on the other side, and these deletions could occur with no input from the other side of the cord. These results suggest that the locomotor CPG has a two-level organization with rhythm-generating (RG) and pattern-forming (PF) networks, in which only the flexor RG network is intrinsically rhythmic. To further explore the neuronal organization of the CPG, we monitored activity of motoneurons and selected identified interneurons during spontaneous non-resetting deletions. Motoneurons lost rhythmic synaptic drive during ipsilateral deletions. Flexor-related commissural interneurons continued to fire rhythmically during non-resetting ipsilateral flexor deletions. Deletion analysis revealed two classes of rhythmic V2a interneurons. Type I V2a interneurons retained rhythmic synaptic drive and firing during ipsilateral motor deletions, while type II V2a interneurons lost rhythmic synaptic input and fell silent during deletions. This suggests that the type I neurons are components of the RG, whereas the type II neurons are components of the PF network. We propose a computational model of the spinal locomotor CPG that reproduces our experimental results. The results may provide novel insights into the organization of spinal locomotor networks. PMID:22869012
Ramanathan, Kiruthika; Ning, Ning; Dhanasekar, Dhiviya; Li, Guoqi; Shi, Luping; Vadakkepat, Prahlad
2012-08-01
Our paper explores the interaction of persistent firing axonal and presynaptic processes in the generation of short term memory for habituation. We first propose a model of a sensory neuron whose axon is able to switch between passive conduction and persistent firing states, thereby triggering short term retention to the stimulus. Then we propose a model of a habituating synapse and explore all nine of the behavioral characteristics of short term habituation in a two neuron circuit. We couple the persistent firing neuron to the habituation synapse and investigate the behavior of short term retention of habituating response. Simulations show that, depending on the amount of synaptic resources, persistent firing either results in continued habituation or maintains the response, both leading to longer recovery times. The effectiveness of the model as an element in a bio-inspired memory system is discussed.
Neurons in Primary Motor Cortex Encode Hand Orientation in a Reach-to-Grasp Task.
Ma, Chaolin; Ma, Xuan; Fan, Jing; He, Jiping
2017-08-01
It is disputed whether those neurons in the primary motor cortex (M1) that encode hand orientation constitute an independent channel for orientation control in reach-to-grasp behaviors. Here, we trained two monkeys to reach forward and grasp objects positioned in the frontal plane at different orientation angles, and simultaneously recorded the activity of M1 neurons. Among the 2235 neurons recorded in M1, we found that 18.7% had a high correlation exclusively with hand orientation, 15.9% with movement direction, and 29.5% with both movement direction and hand orientation. The distributions of neurons encoding hand orientation and those encoding movement direction were not uniform but coexisted in the same region. The trajectory of hand rotation was reproduced by the firing patterns of the orientation-related neurons independent of the hand reaching direction. These results suggest that hand orientation is an independent component for the control of reaching and grasping activity.
Evidence for Consolidation of Neuronal Assemblies after Seizures in Humans
Stead, Matt; Bower, Regina S.; Kucewicz, Michal T.; Sulc, Vlastimil; Cimbalnik, Jan; Brinkmann, Benjamin H.; Vasoli, Vincent M.; St. Louis, Erik K.; Meyer, Fredric B.; Marsh, W. Richard; Worrell, Gregory A.
2015-01-01
The establishment of memories involves reactivation of waking neuronal activity patterns and strengthening of associated neural circuits during slow-wave sleep (SWS), a process known as “cellular consolidation” (Dudai and Morris, 2013). Reactivation of neural activity patterns during waking behaviors that occurs on a timescale of seconds to minutes is thought to constitute memory recall (O'Keefe and Nadel, 1978), whereas consolidation of memory traces may be revealed and served by correlated firing (reactivation) that appears during sleep under conditions suitable for synaptic modification (Buhry et al., 2011). Although reactivation has been observed in human neuronal recordings (Gelbard-Sagiv et al., 2008; Miller et al., 2013), reactivation during sleep has not, likely because data are difficult to obtain and the effect is subtle. Seizures, however, provide intense and synchronous, yet sparse activation (Bower et al., 2012) that could produce a stronger consolidation effect if seizures activate learning-related mechanisms similar to those activated by learned tasks. Continuous wide-bandwidth recordings from patients undergoing intracranial monitoring for drug-resistant epilepsy revealed reactivation of seizure-related neuronal activity during subsequent SWS, but not wakefulness. Those neuronal assemblies that were most strongly activated during seizures showed the largest correlation changes, suggesting that consolidation selectively strengthened neuronal circuits activated by seizures. These results suggest that seizures “hijack” physiological learning mechanisms and also suggest a novel epilepsy therapy targeting neuronal dynamics during post-seizure sleep. PMID:25609617
Constantinople, Christine M.; Disney, Anita A; Maffie, Jonathan; Rudy, Bernardo; Hawken, Michael J
2010-01-01
Voltage-gated potassium channels that are composed of Kv3 subunits exhibit distinct electrophysiological properties: activation at more depolarized potentials than other voltage-gated K+ channels and fast kinetics. These channels have been shown to contribute to the high-frequency firing of fast-spiking (FS) GABAergic interneurons in the rat and mouse brain. In the rodent neocortex, there are distinct patterns of expression for the Kv3.1b and Kv3.2 channel subunits and of co-expression of these subunits with neurochemical markers, such as the calcium-binding proteins parvalbumin (PV) and calbindin D-28K (CB). The distribution of Kv3 channels and interrelationship with calcium-binding protein expression has not been investigated in primate cortex. We used immunoperoxidase and immunofluorescent labeling and stereological counting techniques to characterize the laminar and cell-type distributions of Kv3-ir neurons in macaque V1. We found that across the cortical layers ~25% of both Kv3.1b- and Kv3.2-ir neurons are non-GABAergic. In contrast all Kv3-ir neurons in rodent cortex are GABAergic (Chow et al., 1999). The putatively excitatory Kv3-ir neurons were mostly located in layers 2, 3 and 4b. Further, the proportion of Kv3-ir neurons that express PV or CB also differs between macaque V1 and rodent cortex. These data indicate that, within the population of cortical neurons, a broader population of neurons, encompassing cells of a wider range of morphological classes may be capable of sustaining high-frequency firing in macaque V1. PMID:19634181
Gonzalo-Gomez, Alicia; Turiegano, Enrique; León, Yolanda; Molina, Isabel; Torroja, Laura; Canal, Inmaculada
2012-01-01
HCN channels are becoming pharmacological targets mainly in cardiac diseases. But apart from their well-known role in heart pacemaking, these channels are widely expressed in the nervous system where they contribute to the neuron firing pattern. Consequently, abolishing Ih current might have detrimental consequences in a big repertoire of behavioral traits. Several studies in mammals have identified the Ih current as an important determinant of the firing activity of dopaminergic neurons, and recent evidences link alterations in this current to various dopamine-related disorders. We used the model organism Drosophila melanogaster to investigate how lack of Ih current affects dopamine levels and the behavioral consequences in the sleep∶activity pattern. Unlike mammals, in Drosophila there is only one gene encoding HCN channels. We generated a deficiency of the DmIh core gene region and measured, by HPLC, levels of dopamine. Our data demonstrate daily variations of dopamine in wild-type fly heads. Lack of Ih current dramatically alters dopamine pattern, but different mechanisms seem to operate during light and dark conditions. Behaviorally, DmIh mutant flies display alterations in the rest∶activity pattern, and altered circadian rhythms. Our data strongly suggest that Ih current is necessary to prevent dopamine overproduction at dark, while light input allows cycling of dopamine in an Ih current dependent manner. Moreover, lack of Ih current results in behavioral defects that are consistent with altered dopamine levels. PMID:22574167
Zheng, W; Hall, J C
2000-01-01
The role of gamma-aminobutyric acid (GABA)ergic inhibition in shaping the excitatory frequency tuning of 74 neurons in the superior olivary nucleus of the leopard frog, Rana pipiens, was studied using iontophoretic application of the GABA(A) receptor antagonist, bicuculline methiodide. For 37 neurons, bicuculline application broadened and/or changed the configuration of the excitatory frequency-tuning curve. Results indicate that GABA-mediated inhibition not only sharpens the tuning curves of neurons but also plays a critical role in creating new frequency tuning properties in the superior olivary nucleus. Bicuculline application affected other neuronal response properties as well. Spontaneous firing rate increased 11-338% for 18 of 59 neurons. For 32 of 58 neurons there was an increase in stimulus-evoked discharge rate and a change in rate-level function. There was no qualitative effect on the discharge pattern of 60 neurons, though 2 tonically responding neurons did show an increase (> 30%) in response duration. Additional roles for GABAergic inhibition in monaural signal analysis are discussed.
Grid cells on steeply sloping terrain: evidence for planar rather than volumetric encoding
Hayman, Robin M. A.; Casali, Giulio; Wilson, Jonathan J.; Jeffery, Kate J.
2015-01-01
Neural encoding of navigable space involves a network of structures centered on the hippocampus, whose neurons –place cells – encode current location. Input to the place cells includes afferents from the entorhinal cortex, which contains grid cells. These are neurons expressing spatially localized activity patches, or firing fields, that are evenly spaced across the floor in a hexagonal close-packed array called a grid. It is thought that grids function to enable the calculation of distances. The question arises as to whether this odometry process operates in three dimensions, and so we queried whether grids permeate three-dimensional (3D) space – that is, form a lattice – or whether they simply follow the environment surface. If grids form a 3D lattice then this lattice would ordinarily be aligned horizontally (to explain the usual hexagonal pattern observed). A tilted floor would transect several layers of this putative lattice, resulting in interruption of the hexagonal pattern. We model this prediction with simulated grid lattices, and show that the firing of a grid cell on a 40°-tilted surface should cover proportionally less of the surface, with smaller field size, fewer fields, and reduced hexagonal symmetry. However, recording of real grid cells as animals foraged on a 40°-tilted surface found that firing of grid cells was almost indistinguishable, in pattern or rate, from that on the horizontal surface, with if anything increased coverage and field number, and preserved field size. It thus appears unlikely that the sloping surface transected a lattice. However, grid cells on the slope displayed slightly degraded firing patterns, with reduced coherence and slightly reduced symmetry. These findings collectively suggest that the grid cell component of the metric representation of space is not fixed in absolute 3D space but is influenced both by the surface the animal is on and by the relationship of this surface to the horizontal, supporting the hypothesis that the neural map of space is “multi-planar” rather than fully volumetric. PMID:26236245
Taste quality decoding parallels taste sensations.
Crouzet, Sébastien M; Busch, Niko A; Ohla, Kathrin
2015-03-30
In most species, the sense of taste is key in the distinction of potentially nutritious and harmful food constituents and thereby in the acceptance (or rejection) of food. Taste quality is encoded by specialized receptors on the tongue, which detect chemicals corresponding to each of the basic tastes (sweet, salty, sour, bitter, and savory [1]), before taste quality information is transmitted via segregated neuronal fibers [2], distributed coding across neuronal fibers [3], or dynamic firing patterns [4] to the gustatory cortex in the insula. In rodents, both hardwired coding by labeled lines [2] and flexible, learning-dependent representations [5] and broadly tuned neurons [6] seem to coexist. It is currently unknown how, when, and where taste quality representations are established in the cortex and whether these representations are used for perceptual decisions. Here, we show that neuronal response patterns allow to decode which of four tastants (salty, sweet, sour, and bitter) participants tasted in a given trial by using time-resolved multivariate pattern analyses of large-scale electrophysiological brain responses. The onset of this prediction coincided with the earliest taste-evoked responses originating from the insula and opercular cortices, indicating that quality is among the first attributes of a taste represented in the central gustatory system. These response patterns correlated with perceptual decisions of taste quality: tastes that participants discriminated less accurately also evoked less discriminated brain response patterns. The results therefore provide the first evidence for a link between taste-related decision-making and the predictive value of these brain response patterns. Copyright © 2015 Elsevier Ltd. All rights reserved.
Crisp, Kevin M; Mesce, Karen A
2006-05-01
The biological mechanisms of behavioral selection, as it relates to locomotion, are far from understood, even in relatively simple invertebrate animals. In the medicinal leech, Hirudo medicinalis, the decision to swim is distributed across populations of swim-activating and swim-inactivating neurons descending from the subesophageal ganglion of the compound cephalic ganglion, i.e. the brain. In the present study, we demonstrate that the serotonergic LL and Retzius cells in the brain are excited by swim-initiating stimuli and during spontaneous swim episodes. This activity likely influences or resets the neuromodulatory state of neural circuits involved in the activation or subsequent termination of locomotion. When serotonin (5-HT) was perfused over the brain, multi-unit recordings from descending brain neurons revealed rapid and substantial alterations. Subsequent intracellular recordings from identified command-like brain interneurons demonstrated that 5-HT, especially in combination with octopamine, inhibited swim-triggering neuron Tr1, as well as swim-inactivating neurons Tr2 and SIN1. Although 5-HT inhibited elements of the swim-inactivation pathway, rather than promoting them, the indirect and net effect of the amine was a reliable and sustained reduction in the firing of the segmental swim-gating neuron 204. This modulation caused cell 204 to relinquish its excitatory drive to the swim central pattern generator. The activation pattern of serotonergic brain neurons that we observed during swimming and the 5-HT-immunoreactive staining pattern obtained, suggest that within the head brain 5-HT secretion is massive. Over time, 5-HT secretion may provide a homeostatic feedback mechanism to limit swimming activity at the level of the head brain.
Iriki, Atsushi; Isoda, Masaki
2015-01-01
Abnormalities in cortico-basal ganglia (CBG) networks can cause a variety of movement disorders ranging from hypokinetic disorders, such as Parkinson's disease (PD), to hyperkinetic conditions, such as Tourette syndrome (TS). Each condition is characterized by distinct patterns of abnormal neural discharge (dysrhythmia) at both the local single-neuron level and the global network level. Despite divergent etiologies, behavioral phenotypes, and neurophysiological profiles, high-frequency deep brain stimulation (HF-DBS) in the basal ganglia has been shown to be effective for both hypo- and hyperkinetic disorders. The aim of this review is to compare and contrast the electrophysiological hallmarks of PD and TS phenotypes in nonhuman primates and discuss why the same treatment (HF-DBS targeted to the globus pallidus internus, GPi-DBS) is capable of ameliorating both symptom profiles. Recent studies have shown that therapeutic GPi-DBS entrains the spiking of neurons located in the vicinity of the stimulating electrode, resulting in strong stimulus-locked modulations in firing probability with minimal changes in the population-scale firing rate. This stimulus effect normalizes/suppresses the pathological firing patterns and dysrhythmia that underlie specific phenotypes in both the PD and TS models. We propose that the elimination of pathological states via stimulus-driven entrainment and suppression, while maintaining thalamocortical network excitability within a normal physiological range, provides a common therapeutic mechanism through which HF-DBS permits information transfer for purposive motor behavior through the CBG while ameliorating conditions with widely different symptom profiles. PMID:26180116
Correlated physiological and perceptual effects of noise in a tactile stimulus.
Lak, Armin; Arabzadeh, Ehsan; Harris, Justin A; Diamond, Mathew E
2010-04-27
We investigated connections between the physiology of rat barrel cortex neurons and the sensation of vibration in humans. One set of experiments measured neuronal responses in anesthetized rats to trains of whisker deflections, each train characterized either by constant amplitude across all deflections or by variable amplitude ("amplitude noise"). Firing rate and firing synchrony were, on average, boosted by the presence of noise. However, neurons were not uniform in their responses to noise. Barrel cortex neurons have been categorized as regular-spiking units (putative excitatory neurons) and fast-spiking units (putative inhibitory neurons). Among regular-spiking units, amplitude noise caused a higher firing rate and increased cross-neuron synchrony. Among fast-spiking units, noise had the opposite effect: It led to a lower firing rate and decreased cross-neuron synchrony. This finding suggests that amplitude noise affects the interaction between inhibitory and excitatory neurons. From these physiological effects, we expected that noise would lead to an increase in the perceived intensity of a vibration. We tested this notion using psychophysical measurements in humans. As predicted, subjects overestimated the intensity of noisy vibrations. Thus the physiological mechanisms present in barrel cortex also appear to be at work in the human tactile system, where they affect vibration perception.
Chevaleyre, Vivien; Murray, Karl D.; Piskorowski, Rebecca A.
2017-01-01
Abstract The CA1 region of the hippocampus plays a critical role in spatial and contextual memory, and has well-established circuitry, function and plasticity. In contrast, the properties of the flanking CA2 pyramidal neurons (PNs), important for social memory, and lacking CA1-like plasticity, remain relatively understudied. In particular, little is known regarding the expression of voltage-gated K+ (Kv) channels and the contribution of these channels to the distinct properties of intrinsic excitability, action potential (AP) waveform, firing patterns and neurotransmission between CA1 and CA2 PNs. In the present study, we used multiplex fluorescence immunolabeling of mouse brain sections, and whole-cell recordings in acute mouse brain slices, to define the role of heterogeneous expression of Kv2 family Kv channels in CA1 versus CA2 pyramidal cell excitability. Our results show that the somatodendritic delayed rectifier Kv channel subunits Kv2.1, Kv2.2, and their auxiliary subunit AMIGO-1 have region-specific differences in expression in PNs, with the highest expression levels in CA1, a sharp decrease at the CA1-CA2 boundary, and significantly reduced levels in CA2 neurons. PNs in CA1 exhibit a robust contribution of Guangxitoxin-1E-sensitive Kv2-based delayed rectifier current to AP shape and after-hyperpolarization potential (AHP) relative to that seen in CA2 PNs. Our results indicate that robust Kv2 channel expression confers a distinct pattern of intrinsic excitability to CA1 PNs, potentially contributing to their different roles in hippocampal network function. PMID:28856240
Chen, Shao-Rui; Chen, Hong; Zhou, Jing-Jing; Pradhan, Geetali; Sun, Yuxiang; Pan, Hui-Lin; Li, De-Pei
2017-08-01
Ghrelin increases food intake and body weight by stimulating orexigenic agouti-related protein (AgRP)/neuropeptide Y (NPY) neurons and inhibiting anorexic pro-opiomelanocortin (POMC) neurons in the hypothalamus. Growth hormone secretagogue receptor (Ghsr) mediates the effect of ghrelin on feeding behavior and energy homeostasis. However, the role of Ghsr in the ghrelin effect on these two populations of neurons is unclear. We hypothesized that Ghsr mediates the effect of ghrelin on AgRP and POMC neurons. In this study, we determined whether Ghsr similarly mediates the effects of ghrelin on AgRP/NPY and POMC neurons using cell type-specific Ghsr-knockout mice. Perforated whole-cell recordings were performed on green fluorescent protein-tagged AgRP/NPY and POMC neurons in the arcuate nucleus in hypothalamic slices. In Ghsr +/+ mice, ghrelin (100 nM) significantly increased the firing activity of AgRP/NPY neurons but inhibited the firing activity of POMC neurons. In Ghsr -/- mice, the excitatory effect of ghrelin on AgRP/NPY neurons was abolished. Ablation of Ghsr also eliminated ghrelin-induced increases in the frequency of GABAergic inhibitory postsynaptic currents of POMC neurons. Strikingly, ablation of Ghsr converted the ghrelin effect on POMC neurons from inhibition to excitation. Des-acylated ghrelin had no such effect on POMC neurons in Ghsr -/- mice. In both Ghsr +/+ and Ghsr -/- mice, blocking GABA A receptors with gabazine increased the basal firing activity of POMC neurons, and ghrelin further increased the firing activity of POMC neurons in the presence of gabazine. Our findings provide unequivocal evidence that Ghsr is essential for ghrelin-induced excitation of AgRP/NPY neurons. However, ghrelin excites POMC neurons through an unidentified mechanism that is distinct from conventional Ghsr. © 2017 International Society for Neurochemistry.
NASA Astrophysics Data System (ADS)
Steyn-Ross, Moira L.; Steyn-Ross, D. A.; Wilson, M. T.; Sleigh, J. W.
2007-07-01
One of the grand puzzles in neuroscience is establishing the link between cognition and the disparate patterns of spontaneous and task-induced brain activity that can be measured clinically using a wide range of detection modalities such as scalp electrodes and imaging tomography. High-level brain function is not a single-neuron property, yet emerges as a cooperative phenomenon of multiply-interacting populations of neurons. Therefore a fruitful modeling approach is to picture the cerebral cortex as a continuum characterized by parameters that have been averaged over a small volume of cortical tissue. Such mean-field cortical models have been used to investigate gross patterns of brain behavior such as anesthesia, the cycles of natural sleep, memory and erasure in slow-wave sleep, and epilepsy. There is persuasive and accumulating evidence that direct gap-junction connections between inhibitory neurons promote synchronous oscillatory behavior both locally and across distances of some centimeters, but, to date, continuum models have ignored gap-junction connectivity. In this paper we employ simple mean-field arguments to derive an expression for D2 , the diffusive coupling strength arising from gap-junction connections between inhibitory neurons. Using recent neurophysiological measurements reported by Fukuda [J. Neurosci. 26, 3434 (2006)], we estimate an upper limit of D2≈0.6cm2 . We apply a linear stability analysis to a standard mean-field cortical model, augmented with gap-junction diffusion, and find this value for the diffusive coupling strength to be close to the critical value required to destabilize the homogeneous steady state. Computer simulations demonstrate that larger values of D2 cause the noise-driven model cortex to spontaneously crystalize into random mazelike Turing structures: centimeter-scale spatial patterns in which regions of high-firing activity are intermixed with regions of low-firing activity. These structures are consistent with the spatial variations in brain activity patterns detected with the BOLD (blood oxygen-level-dependent) signal detected with magnetic resonance imaging, and may provide a natural substrate for synchronous gamma-band rhythms observed across separated EEG (electroencephalogram) electrodes.
Turcott, R G; Lowen, S B; Li, E; Johnson, D H; Tsuchitani, C; Teich, M C
1994-01-01
The behavior of lateral-superior-olive (LSO) auditory neurons over large time scales was investigated. Of particular interest was the determination as to whether LSO neurons exhibit the same type of fractal behavior as that observed in primary VIII-nerve auditory neurons. It has been suggested that this fractal behavior, apparent on long time scales, may play a role in optimally coding natural sounds. We found that a nonfractal model, the nonstationary dead-time-modified Poisson point process (DTMP), describes the LSO firing patterns well for time scales greater than a few tens of milliseconds, a region where the specific details of refractoriness are unimportant. The rate is given by the sum of two decaying exponential functions. The process is completely specified by the initial values and time constants of the two exponentials and by the dead-time relation. Specific measures of the firing patterns investigated were the interspike-interval (ISI) histogram, the Fano-factor time curve (FFC), and the serial count correlation coefficient (SCC) with the number of action potentials in successive counting times serving as the random variable. For all the data sets we examined, the latter portion of the recording was well approximated by a single exponential rate function since the initial exponential portion rapidly decreases to a negligible value. Analytical expressions available for the statistics of a DTMP with a single exponential rate function can therefore be used for this portion of the data. Good agreement was obtained among the analytical results, the computer simulation, and the experimental data on time scales where the details of refractoriness are insignificant.(ABSTRACT TRUNCATED AT 250 WORDS)
Functional role of A-type potassium currents in rat presympathetic PVN neurones
Sonner, Patrick M; Stern, Javier E
2007-01-01
Despite the fact that paraventricular nucleus (PVN) neurones innervating the rostral ventrolateral medulla (RVLM) play important roles in the control of sympathetic function both in physiological and pathological conditions, the precise mechanisms controlling their activity are still incompletely understood. In the present study, we evaluated whether the transient outward potassium current IA is expressed in PVN-RVLM neurones, characterized its biophysical and pharmacological properties, and determined its role in shaping action potentials and firing discharge in these neurones. Patch-clamp recordings obtained from retrogradely labelled, PVN-RVLM neurones indicate that a 4-AP sensitive, TEA insensitive current, with biophysical properties consistent with IA, is present in these neurones. Pharmacological blockade of IA depolarized resting Vm and prolonged Na+ action potential duration, by increasing its width and by slowing down its decay time course. Interestingly, blockade of IA either increased or decreased the firing activity of PVN-RVLM neurones, supporting the presence of subsets of PVN-RVLM neurones differentially modulated by IA. In all cases, the effects of IA on firing activity were prevented by a broad spectrum Ca2+ channel blocker. Immunohistochemical studies suggest that IA in PVN-RVLM neurons is mediated by Kv1.4 and/or Kv4.3 channel subunits. Overall, our results demonstrate the presence of IA in PVN-RVLM neurones, which actively modulates their action potential waveform and firing activity. These studies support IA as an important intrinsic mechanism controlling neuronal excitability in this central presympathetic neuronal population. PMID:17525115
Pseudorabies Virus Infection Alters Neuronal Activity and Connectivity In Vitro
McCarthy, Kelly M.; Tank, David W.; Enquist, Lynn W.
2009-01-01
Alpha-herpesviruses, including human herpes simplex virus 1 & 2, varicella zoster virus and the swine pseudorabies virus (PRV), infect the peripheral nervous system of their hosts. Symptoms of infection often include itching, numbness, or pain indicative of altered neurological function. To determine if there is an in vitro electrophysiological correlate to these characteristic in vivo symptoms, we infected cultured rat sympathetic neurons with well-characterized strains of PRV known to produce virulent or attenuated symptoms in animals. Whole-cell patch clamp recordings were made at various times after infection. By 8 hours of infection with virulent PRV, action potential (AP) firing rates increased substantially and were accompanied by hyperpolarized resting membrane potentials and spikelet-like events. Coincident with the increase in AP firing rate, adjacent neurons exhibited coupled firing events, first with AP-spikelets and later with near identical resting membrane potentials and AP firing. Small fusion pores between adjacent cell bodies formed early after infection as demonstrated by transfer of the low molecular weight dye, Lucifer Yellow. Later, larger pores formed as demonstrated by transfer of high molecular weight Texas red-dextran conjugates between infected cells. Further evidence for viral-induced fusion pores was obtained by infecting neurons with a viral mutant defective for glycoprotein B, a component of the viral membrane fusion complex. These infected neurons were essentially identical to mock infected neurons: no increased AP firing, no spikelet-like events, and no electrical or dye transfer. Infection with PRV Bartha, an attenuated circuit-tracing strain delayed, but did not eliminate the increased neuronal activity and coupling events. We suggest that formation of fusion pores between infected neurons results in electrical coupling and elevated firing rates, and that these processes may contribute to the altered neural function seen in PRV-infected animals. PMID:19876391
Kros, Lieke; Lindeman, Sander; Eelkman Rooda, Oscar H. J.; Murugesan, Pavithra; Bina, Lorenzo; Bosman, Laurens W. J.; De Zeeuw, Chris I.; Hoebeek, Freek E.
2017-01-01
Absence epilepsy is characterized by the occurrence of generalized spike and wave discharges (GSWDs) in electrocorticographical (ECoG) recordings representing oscillatory activity in thalamocortical networks. The oscillatory nature of GSWDs has been shown to be reflected in the simple spike activity of cerebellar Purkinje cells and in the activity of their target neurons in the cerebellar nuclei, but it is unclear to what extent complex spike activity is implicated in generalized epilepsy. Purkinje cell complex spike firing is elicited by climbing fiber activation and reflects action potential firing in the inferior olive. Here, we investigated to what extent modulation of complex spike firing is reflected in the temporal patterns of seizures. Extracellular single-unit recordings in awake, head-restrained homozygous tottering mice, which suffer from a mutation in the voltage-gated CaV2.1 calcium channel, revealed that a substantial proportion of Purkinje cells (26%) showed increased complex spike activity and rhythmicity during GSWDs. Moreover, Purkinje cells, recorded either electrophysiologically or by using Ca2+-imaging, showed a significant increase in complex spike synchronicity for both adjacent and remote Purkinje cells during ictal events. These seizure-related changes in firing frequency, rhythmicity and synchronicity were most prominent in the lateral cerebellum, a region known to receive cerebral input via the inferior olive. These data indicate profound and widespread changes in olivary firing that are most likely induced by seizure-related activity changes in the thalamocortical network, thereby highlighting the possibility that olivary neurons can compensate for pathological brain-state changes by dampening oscillations. PMID:29163057
The control of locomotor frequency by excitation and inhibition
Li, Wen-Chang; Moult, Peter R
2012-01-01
Every type of neural rhythm has its own operational range of frequency. Neuronal mechanisms underlying rhythms at different frequencies, however, are poorly understood. We use a simple aquatic vertebrate, the two day old Xenopus tadpole, to investigate how the brainstem and spinal circuits generate swimming rhythms of different speeds. We first determined that the basic motor output pattern was not altered with varying swimming frequencies. The firing reliability of different types of rhythmic neuron involved in swimming was then analysed. The results showed that there was a drop in the firing reliability in some inhibitory interneurons when fictive swimming slowed. We have recently established that premotor excitatory interneurons (descending interneurons; dINs) are critical in rhythmically driving activity in the swimming circuit. Voltage-clamp recordings from dINs showed higher frequency swimming correlated with stronger background excitation and phasic inhibition, but did not correlate with phasic excitation. Two parallel mechanisms have been proposed for tadpole swimming maintenance: post-inhibition rebound firing and NMDA receptor (NMDAR) dependent pace-maker firing in dINs. Rebound tests in dINs in this study showed that greater background depolarization and phasic inhibition led to faster rebound firing. Higher depolarization was previously shown to accelerate dIN pace-maker firing in the presence of NMDA. Here we show that enhancing dIN background excitation during swimming speeds up fictive swimming frequency whilst weakening phasic inhibition without changing background excitation slows down swimming rhythms. We conclude that both strong background excitation and phasic inhibition can promote faster tadpole swimming. PMID:22553028
Hampson, Robert E.; Song, Dong; Chan, Rosa H.M.; Sweatt, Andrew J.; Riley, Mitchell R.; Goonawardena, Anushka V.; Marmarelis, Vasilis Z.; Gerhardt, Greg A.; Berger, Theodore W.; Deadwyler, Sam A.
2012-01-01
A major factor involved in providing closed loop feedback for control of neural function is to understand how neural ensembles encode online information critical to the final behavioral endpoint. This issue was directly assessed in rats performing a short-term delay memory task in which successful encoding of task information is dependent upon specific spatiotemporal firing patterns recorded from ensembles of CA3 and CA1 hippocampal neurons. Such patterns, extracted by a specially designed nonlinear multi-input multi-output (MIMO) nonlinear mathematical model, were used to predict successful performance online via a closed loop paradigm which regulated trial difficulty (time of retention) as a function of the “strength” of stimulus encoding. The significance of the MIMO model as a neural prosthesis has been demonstrated by substituting trains of electrical stimulation pulses to mimic these same ensemble firing patterns. This feature was used repeatedly to vary “normal” encoding as a means of understanding how neural ensembles can be “tuned” to mimic the inherent process of selecting codes of different strength and functional specificity. The capacity to enhance and tune hippocampal encoding via MIMO model detection and insertion of critical ensemble firing patterns shown here provides the basis for possible extension to other disrupted brain circuitry. PMID:22498704
Moreno-Bote, Rubén; Parga, Néstor
2010-06-01
Delivery of neurotransmitter produces on a synapse a current that flows through the membrane and gets transmitted into the soma of the neuron, where it is integrated. The decay time of the current depends on the synaptic receptor's type and ranges from a few (e.g., AMPA receptors) to a few hundred milliseconds (e.g., NMDA receptors). The role of the variety of synaptic timescales, several of them coexisting in the same neuron, is at present not understood. A prime question to answer is which is the effect of temporal filtering at different timescales of the incoming spike trains on the neuron's response. Here, based on our previous work on linear synaptic filtering, we build a general theory for the stationary firing response of integrate-and-fire (IF) neurons receiving stochastic inputs filtered by one, two, or multiple synaptic channels, each characterized by an arbitrary timescale. The formalism applies to arbitrary IF model neurons and arbitrary forms of input noise (i.e., not required to be gaussian or to have small amplitude), as well as to any form of synaptic filtering (linear or nonlinear). The theory determines with exact analytical expressions the firing rate of an IF neuron for long synaptic time constants using the adiabatic approach. The correlated spiking (cross-correlations function) of two neurons receiving common as well as independent sources of noise is also described. The theory is illustrated using leaky, quadratic, and noise-thresholded IF neurons. Although the adiabatic approach is exact when at least one of the synaptic timescales is long, it provides a good prediction of the firing rate even when the timescales of the synapses are comparable to that of the leak of the neuron; it is not required that the synaptic time constants are longer than the mean interspike intervals or that the noise has small variance. The distribution of the potential for general IF neurons is also characterized. Our results provide powerful analytical tools that can allow a quantitative description of the dynamics of neuronal networks with realistic synaptic dynamics.
Ortiz-Rosario, Alexis; Adeli, Hojjat; Buford, John A
2017-01-15
Researchers often rely on simple methods to identify involvement of neurons in a particular motor task. The historical approach has been to inspect large groups of neurons and subjectively separate neurons into groups based on the expertise of the investigator. In cases where neuron populations are small it is reasonable to inspect these neuronal recordings and their firing rates carefully to avoid data omissions. In this paper, a new methodology is presented for automatic objective classification of neurons recorded in association with behavioral tasks into groups. By identifying characteristics of neurons in a particular group, the investigator can then identify functional classes of neurons based on their relationship to the task. The methodology is based on integration of a multiple signal classification (MUSIC) algorithm to extract relevant features from the firing rate and an expectation-maximization Gaussian mixture algorithm (EM-GMM) to cluster the extracted features. The methodology is capable of identifying and clustering similar firing rate profiles automatically based on specific signal features. An empirical wavelet transform (EWT) was used to validate the features found in the MUSIC pseudospectrum and the resulting signal features captured by the methodology. Additionally, this methodology was used to inspect behavioral elements of neurons to physiologically validate the model. This methodology was tested using a set of data collected from awake behaving non-human primates. Copyright © 2016 Elsevier B.V. All rights reserved.
Santin, Joseph M; Hartzler, Lynn K
2015-06-15
Locus coeruleus neurons of anuran amphibians contribute to breathing control and have spontaneous firing frequencies that, paradoxically, increase with cooling. We previously showed that cooling inhibits a depolarizing membrane current, the hyperpolarization-activated current (I h) in locus coeruleus neurons from bullfrogs, Lithobates catesbeianus (Santin JM, Watters KC, Putnam RW, Hartzler LK. Am J Physiol Regul Integr Comp Physiol 305: R1451-R1464, 2013). This suggests an unlikely role for I h in generating cold activation, but led us to hypothesize that inhibition of I h by cooling functions as a physiological brake to limit the cold-activated response. Using whole cell electrophysiology in brain slices, we employed 2 mM Cs(+) (an I h antagonist) to isolate the role of I h in spontaneous firing and cold activation in neurons recorded with either control or I h agonist (cyclic AMP)-containing artificial intracellular fluid. I h did not contribute to the membrane potential (V m) and spontaneous firing at 20°C. Although voltage-clamp analysis confirmed that cooling inhibits I h, its lack of involvement in setting baseline firing and V m precluded its ability to regulate cold activation as hypothesized. In contrast, neurons dialyzed with cAMP exhibited greater baseline firing frequencies at 20°C due to I h activation. Our hypothesis was supported when the starting level of I h was enhanced by elevating cAMP because cold activation was converted to more ordinary cold inhibition. These findings indicate that situations leading to enhancement of I h facilitate firing at 20°C, yet the hyperpolarization associated with inhibiting a depolarizing cation current by cooling blunts the net V m response to cooling to oppose normal cold-depolarizing factors. This suggests that the influence of I h activation state on neuronal firing varies in the poikilothermic neuronal environment. Copyright © 2015 the American Physiological Society.
Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian
2016-02-01
The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter--describing somatic integration--and the spike-history filter--accounting for spike-frequency adaptation--dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations.
Wang, Ce-Qun; Chen, Qiang; Zhang, Lu; Xu, Jia-Min; Lin, Long-Nian
2014-12-25
The purpose of this article is to introduce the measurements of phase coupling between spikes and rhythmic oscillations of local field potentials (LFPs). Multi-channel in vivo recording techniques allow us to record ensemble neuronal activity and LFPs simultaneously from the same sites in the brain. Neuronal activity is generally characterized by temporal spike sequences, while LFPs contain oscillatory rhythms in different frequency ranges. Phase coupling analysis can reveal the temporal relationships between neuronal firing and LFP rhythms. As the first step, the instantaneous phase of LFP rhythms can be calculated using Hilbert transform, and then for each time-stamped spike occurred during an oscillatory epoch, we marked instantaneous phase of the LFP at that time stamp. Finally, the phase relationships between the neuronal firing and LFP rhythms were determined by examining the distribution of the firing phase. Phase-locked spikes are revealed by the non-random distribution of spike phase. Theta phase precession is a unique phase relationship between neuronal firing and LFPs, which is one of the basic features of hippocampal place cells. Place cells show rhythmic burst firing following theta oscillation within a place field. And phase precession refers to that rhythmic burst firing shifted in a systematic way during traversal of the field, moving progressively forward on each theta cycle. This relation between phase and position can be described by a linear model, and phase precession is commonly quantified with a circular-linear coefficient. Phase coupling analysis helps us to better understand the temporal information coding between neuronal firing and LFPs.
Bifurcation and Firing Patterns of the Pancreatic β-Cell
NASA Astrophysics Data System (ADS)
Wang, Jing; Liu, Shenquan; Liu, Xuanliang; Zeng, Yanjun
Using a model of individual isolated pancreatic β-cells, we investigated bifurcation diagrams of interspike intervals (ISIs) and largest Lyapunov exponents (LLE), which clearly demonstrated a wide range of transitions between different firing patterns. The numerical simulation results revealed the effect of different time constants and ion channels on the neuronal discharge rhythm. Furthermore, an individual cell exhibited tonic spiking, square-wave bursting, and tapered bursting. Additionally, several bifurcation phenomena can be observed in this paper, such as period-doubling, period-adding, inverse period-doubling and inverse period-adding scenarios. In addition, we researched the mechanisms underlying two kinds of bursting (tapered and square-wave bursting) by use of fast-slow dynamics analysis. Finally, we analyzed the codimension-two bifurcation of the fast subsystem and studied cusp bifurcation, generalized Hopf (or Bautin) bifurcation and Bogdanov-Takens bifurcation.
Comparing Realistic Subthalamic Nucleus Neuron Models
NASA Astrophysics Data System (ADS)
Njap, Felix; Claussen, Jens C.; Moser, Andreas; Hofmann, Ulrich G.
2011-06-01
The mechanism of action of clinically effective electrical high frequency stimulation is still under debate. However, recent evidence points at the specific activation of GABA-ergic ion channels. Using a computational approach, we analyze temporal properties of the spike trains emitted by biologically realistic neurons of the subthalamic nucleus (STN) as a function of GABA-ergic synaptic input conductances. Our contribution is based on a model proposed by Rubin and Terman and exhibits a wide variety of different firing patterns, silent, low spiking, moderate spiking and intense spiking activity. We observed that most of the cells in our network turn to silent mode when we increase the GABAA input conductance above the threshold of 3.75 mS/cm2. On the other hand, insignificant changes in firing activity are observed when the input conductance is low or close to zero. We thus reproduce Rubin's model with vanishing synaptic conductances. To quantitatively compare spike trains from the original model with the modified model at different conductance levels, we apply four different (dis)similarity measures between them. We observe that Mahalanobis distance, Victor-Purpura metric, and Interspike Interval distribution are sensitive to different firing regimes, whereas Mutual Information seems undiscriminative for these functional changes.
Roland, Alison V; Moenter, Suzanne M
2011-02-01
Prenatal androgenization (PNA) of female mice with dihydrotestosterone programs reproductive dysfunction in adulthood, characterized by elevated luteinizing hormone levels, irregular estrous cycles, and central abnormalities. Here, we evaluated activity of GnRH neurons from PNA mice and the effects of in vivo treatment with metformin, an activator of AMP-activated protein kinase (AMPK) that is commonly used to treat the fertility disorder polycystic ovary syndrome. Estrous cycles were monitored in PNA and control mice before and after metformin administration. Before metformin, cycles were longer in PNA mice and percent time in estrus lower; metformin normalized cycles in PNA mice. Extracellular recordings were used to monitor GnRH neuron firing activity in brain slices from diestrous mice. Firing rate was higher and quiescence lower in GnRH neurons from PNA mice, demonstrating increased GnRH neuron activity. Metformin treatment of PNA mice restored firing activity and LH to control levels. To assess whether AMPK activation contributed to the metformin-induced reduction in GnRH neuron activity, the AMPK antagonist compound C was acutely applied to cells. Compound C stimulated cells from metformin-treated, but not untreated, mice, suggesting that AMPK was activated in GnRH neurons, or afferent neurons, in the former group. GnRH neurons from metformin-treated mice also showed a reduced inhibitory response to low glucose. These studies indicate that PNA causes enhanced firing activity of GnRH neurons and elevated LH that are reversible by metformin, raising the possibility that central AMPK activation by metformin may play a role in its restoration of reproductive cycles in polycystic ovary syndrome.
Death and rebirth of neural activity in sparse inhibitory networks
NASA Astrophysics Data System (ADS)
Angulo-Garcia, David; Luccioli, Stefano; Olmi, Simona; Torcini, Alessandro
2017-05-01
Inhibition is a key aspect of neural dynamics playing a fundamental role for the emergence of neural rhythms and the implementation of various information coding strategies. Inhibitory populations are present in several brain structures, and the comprehension of their dynamics is strategical for the understanding of neural processing. In this paper, we clarify the mechanisms underlying a general phenomenon present in pulse-coupled heterogeneous inhibitory networks: inhibition can induce not only suppression of neural activity, as expected, but can also promote neural re-activation. In particular, for globally coupled systems, the number of firing neurons monotonically reduces upon increasing the strength of inhibition (neuronal death). However, the random pruning of connections is able to reverse the action of inhibition, i.e. in a random sparse network a sufficiently strong synaptic strength can surprisingly promote, rather than depress, the activity of neurons (neuronal rebirth). Thus, the number of firing neurons reaches a minimum value at some intermediate synaptic strength. We show that this minimum signals a transition from a regime dominated by neurons with a higher firing activity to a phase where all neurons are effectively sub-threshold and their irregular firing is driven by current fluctuations. We explain the origin of the transition by deriving a mean field formulation of the problem able to provide the fraction of active neurons as well as the first two moments of their firing statistics. The introduction of a synaptic time scale does not modify the main aspects of the reported phenomenon. However, for sufficiently slow synapses the transition becomes dramatic, and the system passes from a perfectly regular evolution to irregular bursting dynamics. In this latter regime the model provides predictions consistent with experimental findings for a specific class of neurons, namely the medium spiny neurons in the striatum.
Fujita, Satoshi; Toyoda, Izumi; Thamattoor, Ajoy K.
2014-01-01
Previous studies suggest that spontaneous seizures in patients with temporal lobe epilepsy might be preceded by increased action potential firing of hippocampal neurons. Preictal activity is potentially important because it might provide new opportunities for predicting when a seizure is about to occur and insight into how spontaneous seizures are generated. We evaluated local field potentials and unit activity of single, putative excitatory neurons in the subiculum, CA1, CA3, and dentate gyrus of the dorsal hippocampus in epileptic pilocarpine-treated rats as they experienced spontaneous seizures. Average action potential firing rates of neurons in the subiculum, CA1, and dentate gyrus, but not CA3, increased significantly and progressively beginning 2–4 min before locally recorded spontaneous seizures. In the subiculum, CA1, and dentate gyrus, but not CA3, 41–57% of neurons displayed increased preictal activity with significant consistency across multiple seizures. Much of the increased preictal firing of neurons in the subiculum and CA1 correlated with preictal theta activity, whereas preictal firing of neurons in the dentate gyrus was independent of theta. In addition, some CA1 and dentate gyrus neurons displayed reduced firing rates preictally. These results reveal that different hippocampal subregions exhibit differences in the extent and potential underlying mechanisms of preictal activity. The finding of robust and significantly consistent preictal activity of subicular, CA1, and dentate neurons in the dorsal hippocampus, despite the likelihood that many seizures initiated in other brain regions, suggests the existence of a broader neuronal network whose activity changes minutes before spontaneous seizures initiate. PMID:25505320
A neuromorphic circuit mimicking biological short-term memory.
Barzegarjalali, Saeid; Parker, Alice C
2016-08-01
Research shows that the way we remember things for a few seconds is a different mechanism from the way we remember things for a longer time. Short-term memory is based on persistently firing neurons, whereas storing information for a longer time is based on strengthening the synapses or even forming new neural connections. Information about location and appearance of an object is segregated and processed by separate neurons. Furthermore neurons can continue firing using different mechanisms. Here, we have designed a biomimetic neuromorphic circuit that mimics short-term memory by firing neurons, using biological mechanisms to remember location and shape of an object. Our neuromorphic circuit has a hybrid architecture. Neurons are designed with CMOS 45nm technology and synapses are designed with carbon nanotubes (CNT).
Collective behavior of networks with linear (VLSI) integrate-and-fire neurons.
Fusi, S; Mattia, M
1999-04-01
We analyze in detail the statistical properties of the spike emission process of a canonical integrate-and-fire neuron, with a linear integrator and a lower bound for the depolarization, as often used in VLSI implementations (Mead, 1989). The spike statistics of such neurons appear to be qualitatively similar to conventional (exponential) integrate-and-fire neurons, which exhibit a wide variety of characteristics observed in cortical recordings. We also show that, contrary to current opinion, the dynamics of a network composed of such neurons has two stable fixed points, even in the purely excitatory network, corresponding to two different states of reverberating activity. The analytical results are compared with numerical simulations and are found to be in good agreement.
Hu, Jing; Zheng, Yi; Gao, Jianbo
2013-01-01
Understanding the causal relation between neural inputs and movements is very important for the success of brain-machine interfaces (BMIs). In this study, we analyze 104 neurons’ firings using statistical, information theoretic, and fractal analysis. The latter include Fano factor analysis, multifractal adaptive fractal analysis (MF-AFA), and wavelet multifractal analysis. We find neuronal firings are highly non-stationary, and Fano factor analysis always indicates long-range correlations in neuronal firings, irrespective of whether those firings are correlated with movement trajectory or not, and thus does not reveal any actual correlations between neural inputs and movements. On the other hand, MF-AFA and wavelet multifractal analysis clearly indicate that when neuronal firings are not well correlated with movement trajectory, they do not have or only have weak temporal correlations. When neuronal firings are well correlated with movements, they are characterized by very strong temporal correlations, up to a time scale comparable to the average time between two successive reaching tasks. This suggests that neurons well correlated with hand trajectory experienced a “re-setting” effect at the start of each reaching task, in the sense that within the movement correlated neurons the spike trains’ long-range dependences persisted about the length of time the monkey used to switch between task executions. A new task execution re-sets their activity, making them only weakly correlated with their prior activities on longer time scales. We further discuss the significance of the coalition of those important neurons in executing cortical control of prostheses. PMID:24130549
Lennon, William; Hecht-Nielsen, Robert; Yamazaki, Tadashi
2014-01-01
While the anatomy of the cerebellar microcircuit is well-studied, how it implements cerebellar function is not understood. A number of models have been proposed to describe this mechanism but few emphasize the role of the vast network Purkinje cells (PKJs) form with the molecular layer interneurons (MLIs)—the stellate and basket cells. We propose a model of the MLI-PKJ network composed of simple spiking neurons incorporating the major anatomical and physiological features. In computer simulations, the model reproduces the irregular firing patterns observed in PKJs and MLIs in vitro and a shift toward faster, more regular firing patterns when inhibitory synaptic currents are blocked. In the model, the time between PKJ spikes is shown to be proportional to the amount of feedforward inhibition from an MLI on average. The two key elements of the model are: (1) spontaneously active PKJs and MLIs due to an endogenous depolarizing current, and (2) adherence to known anatomical connectivity along a parasagittal strip of cerebellar cortex. We propose this model to extend previous spiking network models of the cerebellum and for further computational investigation into the role of irregular firing and MLIs in cerebellar learning and function. PMID:25520646
Signal propagation and logic gating in networks of integrate-and-fire neurons.
Vogels, Tim P; Abbott, L F
2005-11-16
Transmission of signals within the brain is essential for cognitive function, but it is not clear how neural circuits support reliable and accurate signal propagation over a sufficiently large dynamic range. Two modes of propagation have been studied: synfire chains, in which synchronous activity travels through feedforward layers of a neuronal network, and the propagation of fluctuations in firing rate across these layers. In both cases, a sufficient amount of noise, which was added to previous models from an external source, had to be included to support stable propagation. Sparse, randomly connected networks of spiking model neurons can generate chaotic patterns of activity. We investigate whether this activity, which is a more realistic noise source, is sufficient to allow for signal transmission. We find that, for rate-coded signals but not for synfire chains, such networks support robust and accurate signal reproduction through up to six layers if appropriate adjustments are made in synaptic strengths. We investigate the factors affecting transmission and show that multiple signals can propagate simultaneously along different pathways. Using this feature, we show how different types of logic gates can arise within the architecture of the random network through the strengthening of specific synapses.
Real-time estimation and biofeedback of single-neuron firing rates using local field potentials
Hall, Thomas M.; Nazarpour, Kianoush; Jackson, Andrew
2014-01-01
The long-term stability and low-frequency composition of local field potentials (LFPs) offer important advantages for robust and efficient neuroprostheses. However, cortical LFPs recorded by multi-electrode arrays are often assumed to contain only redundant information arising from the activity of large neuronal populations. Here we show that multichannel LFPs in monkey motor cortex each contain a slightly different mixture of distinctive slow potentials that accompany neuronal firing. As a result, the firing rates of individual neurons can be estimated with surprising accuracy. We implemented this method in a real-time biofeedback brain–machine interface, and found that monkeys could learn to modulate the activity of arbitrary neurons using feedback derived solely from LFPs. These findings provide a principled method for monitoring individual neurons without long-term recording of action potentials. PMID:25394574
Burkitt, A N
2006-08-01
The integrate-and-fire neuron model describes the state of a neuron in terms of its membrane potential, which is determined by the synaptic inputs and the injected current that the neuron receives. When the membrane potential reaches a threshold, an action potential (spike) is generated. This review considers the model in which the synaptic input varies periodically and is described by an inhomogeneous Poisson process, with both current and conductance synapses. The focus is on the mathematical methods that allow the output spike distribution to be analyzed, including first passage time methods and the Fokker-Planck equation. Recent interest in the response of neurons to periodic input has in part arisen from the study of stochastic resonance, which is the noise-induced enhancement of the signal-to-noise ratio. Networks of integrate-and-fire neurons behave in a wide variety of ways and have been used to model a variety of neural, physiological, and psychological phenomena. The properties of the integrate-and-fire neuron model with synaptic input described as a temporally homogeneous Poisson process are reviewed in an accompanying paper (Burkitt in Biol Cybern, 2006).
Langdon, Angela J; Breakspear, Michael; Coombes, Stephen
2012-12-01
The minimal integrate-and-fire-or-burst neuron model succinctly describes both tonic firing and postinhibitory rebound bursting of thalamocortical cells in the sensory relay. Networks of integrate-and-fire-or-burst (IFB) neurons with slow inhibitory synaptic interactions have been shown to support stable rhythmic states, including globally synchronous and cluster oscillations, in which network-mediated inhibition cyclically generates bursting in coherent subgroups of neurons. In this paper, we introduce a reduced IFB neuronal population model to study synchronization of inhibition-mediated oscillatory bursting states to periodic excitatory input. Using numeric methods, we demonstrate the existence and stability of 1:1 phase-locked bursting oscillations in the sinusoidally forced IFB neuronal population model. Phase locking is shown to arise when periodic excitation is sufficient to pace the onset of bursting in an IFB cluster without counteracting the inhibitory interactions necessary for burst generation. Phase-locked bursting states are thus found to destabilize when periodic excitation increases in strength or frequency. Further study of the IFB neuronal population model with pulse-like periodic excitatory input illustrates that this synchronization mechanism generalizes to a broad range of n:m phase-locked bursting states across both globally synchronous and clustered oscillatory regimes.
Optimal sparse approximation with integrate and fire neurons.
Shapero, Samuel; Zhu, Mengchen; Hasler, Jennifer; Rozell, Christopher
2014-08-01
Sparse approximation is a hypothesized coding strategy where a population of sensory neurons (e.g. V1) encodes a stimulus using as few active neurons as possible. We present the Spiking LCA (locally competitive algorithm), a rate encoded Spiking Neural Network (SNN) of integrate and fire neurons that calculate sparse approximations. The Spiking LCA is designed to be equivalent to the nonspiking LCA, an analog dynamical system that converges on a ℓ(1)-norm sparse approximations exponentially. We show that the firing rate of the Spiking LCA converges on the same solution as the analog LCA, with an error inversely proportional to the sampling time. We simulate in NEURON a network of 128 neuron pairs that encode 8 × 8 pixel image patches, demonstrating that the network converges to nearly optimal encodings within 20 ms of biological time. We also show that when using more biophysically realistic parameters in the neurons, the gain function encourages additional ℓ(0)-norm sparsity in the encoding, relative both to ideal neurons and digital solvers.
Zavala, Baltazar; Damera, Srikanth; Dong, Jian Wilson; Lungu, Codrin; Brown, Peter; Zaghloul, Kareem A.
2017-01-01
Recent evidence has suggested that prefrontal cortical structures may inhibit impulsive actions during conflict through activation of the subthalamic nucleus (STN). Consistent with this hypothesis, deep brain stimulation to the STN has been associated with altered prefrontal cortical activity and impaired response inhibition. The interactions between oscillatory activity in the STN and its presumably antikinetic neuronal spiking, however, remain poorly understood. Here, we simultaneously recorded intraoperative local field potential and spiking activity from the human STN as participants performed a sensorimotor action selection task involving conflict. We identified several STN neuronal response types that exhibited different temporal dynamics during the task. Some neurons showed early, cue-related firing rate increases that remained elevated longer during high conflict trials, whereas other neurons showed late, movement-related firing rate increases. Notably, the high conflict trials were associated with an entrainment of individual neurons by theta- and beta-band oscillations, both of which have been observed in cortical structures involved in response inhibition. Our data suggest that frequency-specific activity in the beta and theta bands influence STN firing to inhibit impulsivity during conflict. PMID:26494798
Organic electronics for high-resolution electrocorticography of the human brain.
Khodagholy, Dion; Gelinas, Jennifer N; Zhao, Zifang; Yeh, Malcolm; Long, Michael; Greenlee, Jeremy D; Doyle, Werner; Devinsky, Orrin; Buzsáki, György
2016-11-01
Localizing neuronal patterns that generate pathological brain signals may assist with tissue resection and intervention strategies in patients with neurological diseases. Precise localization requires high spatiotemporal recording from populations of neurons while minimizing invasiveness and adverse events. We describe a large-scale, high-density, organic material-based, conformable neural interface device ("NeuroGrid") capable of simultaneously recording local field potentials (LFPs) and action potentials from the cortical surface. We demonstrate the feasibility and safety of intraoperative recording with NeuroGrids in anesthetized and awake subjects. Highly localized and propagating physiological and pathological LFP patterns were recorded, and correlated neural firing provided evidence about their local generation. Application of NeuroGrids to brain disorders, such as epilepsy, may improve diagnostic precision and therapeutic outcomes while reducing complications associated with invasive electrodes conventionally used to acquire high-resolution and spiking data.
Delayed reverberation through time windows as a key to cerebellar function.
Kistler, W M; Leo van Hemmen, J
1999-11-01
We present a functional model of the cerebellum comprising cerebellar cortex, inferior olive, deep cerebellar nuclei, and brain stem nuclei. The discerning feature of the model being time coding, we consistently describe the system in terms of postsynaptic potentials, synchronous action potentials, and propagation delays. We show by means of detailed single-neuron modeling that (i) Golgi cells can fulfill a gating task in that they form short and well-defined time windows within which granule cells can reach firing threshold, thus organizing neuronal activity in discrete 'time slices', and that (ii) rebound firing in cerebellar nuclei cells is a robust mechanism leading to a delayed reverberation of Purkinje cell activity through cerebellar-reticular projections back to the cerebellar cortex. Computer simulations of the whole cerebellar network consisting of several thousand neurons reveal that reverberation in conjunction with long-term plasticity at the parallel fiber-Purkinje cell synapses enables the system to learn, store, and recall spatio-temporal patterns of neuronal activity. Climbing fiber spikes act both as a synchronization and as a teacher signal, not as an error signal. They are due to intrinsic oscillatory properties of inferior olivary neurons and to delayed reverberation within the network. In addition to clear experimental predictions the present theory sheds new light on a number of experimental observation such as the synchronicity of climbing fiber spikes and provides a novel explanation of how the cerebellum solves timing tasks on a time scale of several hundreds of milliseconds.
Locally Contractive Dynamics in Generalized Integrate-and-Fire Neurons*
Jimenez, Nicolas D.; Mihalas, Stefan; Brown, Richard; Niebur, Ernst; Rubin, Jonathan
2013-01-01
Integrate-and-fire models of biological neurons combine differential equations with discrete spike events. In the simplest case, the reset of the neuronal voltage to its resting value is the only spike event. The response of such a model to constant input injection is limited to tonic spiking. We here study a generalized model in which two simple spike-induced currents are added. We show that this neuron exhibits not only tonic spiking at various frequencies but also the commonly observed neuronal bursting. Using analytical and numerical approaches, we show that this model can be reduced to a one-dimensional map of the adaptation variable and that this map is locally contractive over a broad set of parameter values. We derive a sufficient analytical condition on the parameters for the map to be globally contractive, in which case all orbits tend to a tonic spiking state determined by the fixed point of the return map. We then show that bursting is caused by a discontinuity in the return map, in which case the map is piecewise contractive. We perform a detailed analysis of a class of piecewise contractive maps that we call bursting maps and show that they robustly generate stable bursting behavior. To the best of our knowledge, this work is the first to point out the intimate connection between bursting dynamics and piecewise contractive maps. Finally, we discuss bifurcations in this return map, which cause transitions between spiking patterns. PMID:24489486
Sleep Impairment and Reduced Interneuron Excitability in a Mouse Model of Dravet Syndrome
Kalume, Franck; Oakley, John C.; Westenbroek, Ruth E.; Gile, Jennifer; de la Iglesia, Horacio O.; Scheuer, Todd; Catterall, William A.
2015-01-01
Dravet Syndrome (DS) is caused by heterozygous loss-of-function mutations in voltage-gated sodium channel NaV1.1. Our genetic mouse model of DS recapitulates its severe seizures and premature death. Sleep disturbance is common in DS, but its mechanism is unknown. Electroencephalographic studies revealed abnormal sleep in DS mice, including reduced delta wave power, reduced sleep spindles, increased brief wakes, and numerous interictal spikes in Non-Rapid-Eye-Movement sleep. Theta power was reduced in Rapid-Eye-Movement sleep. Mice with NaV1.1 deleted specifically in forebrain interneurons exhibited similar sleep pathology to DS mice, but without changes in circadian rhythm. Sleep architecture depends on oscillatory activity in the thalamocortical network generated by excitatory neurons in the ventrobasal nucleus (VBN) of the thalamus and inhibitory GABAergic neurons in the reticular nucleus of the thalamus (RNT). Whole-cell NaV current was reduced in GABAergic RNT neurons but not in VBN neurons. Rebound firing of action potentials following hyperpolarization, the signature firing pattern of RNT neurons during sleep, was also reduced. These results demonstrate imbalance of excitatory vs. inhibitory neurons in this circuit. As predicted from this functional impairment, we found substantial deficit in homeostatic rebound of slow wave activity following sleep deprivation. Although sleep disorders in epilepsies have been attributed to anti-epileptic drugs, our results show that sleep disorder in DS mice arises from loss of NaV1.1 channels in forebrain GABAergic interneurons without drug treatment. Impairment of NaV currents and excitability of GABAergic RNT neurons are correlated with impaired sleep quality and homeostasis in these mice. PMID:25766678
Kammermeier, Stefan; Pittard, Damien; Hamada, Ikuma
2016-01-01
Deep brain stimulation of the internal globus pallidus (GPi) is a major treatment for advanced Parkinson's disease. The effects of this intervention on electrical activity patterns in targets of GPi output, specifically in the thalamus, are poorly understood. The experiments described here examined these effects using electrophysiological recordings in two Rhesus monkeys rendered moderately parkinsonian through treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), after sampling control data in the same animals. Analysis of spontaneous spiking activity of neurons in the basal ganglia-receiving areas of the ventral thalamus showed that MPTP-induced parkinsonism is associated with a reduction of firing rates of segments of the data that contained neither bursts nor decelerations, and with increased burst firing. Spectral analyses revealed an increase of power in the 3- to 13-Hz band and a reduction in the γ-range in the spiking activity of these neurons. Electrical stimulation of the ventrolateral motor territory of GPi with macroelectrodes, mimicking deep brain stimulation in parkinsonian patients (bipolar electrodes, 0.5 mm intercontact distance, biphasic stimuli, 120 Hz, 100 μs/phase, 200 μA), had antiparkinsonian effects. The stimulation markedly reduced oscillations in thalamic firing in the 13- to 30-Hz range and uncoupled the spiking activity of recorded neurons from simultaneously recorded local field potential (LFP) activity. These results confirm that oscillatory and nonoscillatory characteristics of spontaneous activity in the basal ganglia receiving ventral thalamus are altered in MPTP-induced parkinsonism. Electrical stimulation of GPi did not entrain thalamic activity but changed oscillatory activity in the ventral thalamus and altered the relationship between spikes and simultaneously recorded LFPs. PMID:27683881
Mean-field equations for neuronal networks with arbitrary degree distributions.
Nykamp, Duane Q; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex
2017-04-01
The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.
Mean-field equations for neuronal networks with arbitrary degree distributions
NASA Astrophysics Data System (ADS)
Nykamp, Duane Q.; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex
2017-04-01
The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.
Dell'Orco, James M.; Wasserman, Aaron H.; Chopra, Ravi; Ingram, Melissa A. C.; Hu, Yuan-Shih; Singh, Vikrant; Wulff, Heike; Opal, Puneet; Orr, Harry T.
2015-01-01
Neuronal atrophy in neurodegenerative diseases is commonly viewed as an early event in a continuum that ultimately results in neuronal loss. In a mouse model of the polyglutamine disorder spinocerebellar ataxia type 1 (SCA1), we tested the hypothesis that cerebellar Purkinje neuron atrophy serves an adaptive role rather than being simply a nonspecific response to injury. In acute cerebellar slices from SCA1 mice, we find that Purkinje neuron pacemaker firing is initially normal but, with the onset of motor dysfunction, becomes disrupted, accompanied by abnormal depolarization. Remarkably, subsequent Purkinje cell atrophy is associated with a restoration of pacemaker firing. The early inability of Purkinje neurons to support repetitive spiking is due to unopposed calcium currents resulting from a reduction in large-conductance calcium-activated potassium (BK) and subthreshold-activated potassium channels. The subsequent restoration of SCA1 Purkinje neuron firing correlates with the recovery of the density of these potassium channels that accompanies cell atrophy. Supporting a critical role for BK channels, viral-mediated increases in BK channel expression in SCA1 Purkinje neurons improves motor dysfunction and partially restores Purkinje neuron morphology. Cerebellar perfusion of flufenamic acid, an agent that restores the depolarized membrane potential of SCA1 Purkinje neurons by activating potassium channels, prevents Purkinje neuron dendritic atrophy. These results suggest that Purkinje neuron dendritic remodeling in ataxia is an adaptive response to increases in intrinsic membrane excitability. Similar adaptive remodeling could apply to other vulnerable neuronal populations in neurodegenerative disease. SIGNIFICANCE STATEMENT In neurodegenerative disease, neuronal atrophy has long been assumed to be an early nonspecific event preceding neuronal loss. However, in a mouse model of spinocerebellar ataxia type 1 (SCA1), we identify a previously unappreciated compensatory role for neuronal shrinkage. Purkinje neuron firing in these mice is initially normal, but is followed by abnormal membrane depolarization resulting from a reduction in potassium channels. Subsequently, these electrophysiological effects are counteracted by cell atrophy, which by restoring normal potassium channel membrane density, re-establishes pacemaker firing. Reversing the initial membrane depolarization improved motor function and Purkinje neuron morphology in the SCA1 mice. These results suggest that Purkinje neuron remodeling in ataxia is an active compensatory response that serves to normalize intrinsic membrane excitability. PMID:26269637
Ostojic, Srdjan; Brunel, Nicolas; Hakim, Vincent
2009-06-01
We investigate how synchrony can be generated or induced in networks of electrically coupled integrate-and-fire neurons subject to noisy and heterogeneous inputs. Using analytical tools, we find that in a network under constant external inputs, synchrony can appear via a Hopf bifurcation from the asynchronous state to an oscillatory state. In a homogeneous net work, in the oscillatory state all neurons fire in synchrony, while in a heterogeneous network synchrony is looser, many neurons skipping cycles of the oscillation. If the transmission of action potentials via the electrical synapses is effectively excitatory, the Hopf bifurcation is supercritical, while effectively inhibitory transmission due to pronounced hyperpolarization leads to a subcritical bifurcation. In the latter case, the network exhibits bistability between an asynchronous state and an oscillatory state where all the neurons fire in synchrony. Finally we show that for time-varying external inputs, electrical coupling enhances the synchronization in an asynchronous network via a resonance at the firing-rate frequency.
Regulation of ventral surface chemoreceptors by the central respiratory pattern generator.
Guyenet, Patrice G; Mulkey, Daniel K; Stornetta, Ruth L; Bayliss, Douglas A
2005-09-28
The rat retrotrapezoid nucleus (RTN) contains neurons described as central chemoreceptors in the adult and respiratory rhythm-generating pacemakers in neonates [parafacial respiratory group (pfRG)]. Here we test the hypothesis that both RTN and pfRG neurons are intrinsically chemosensitive and tonically firing neurons whose respiratory rhythmicity is caused by a synaptic feedback from the central respiratory pattern generator (CPG). In halothane-anesthetized adults, RTN neurons were silent below 4.5% end-expiratory (e-exp) CO2. Their activity increased linearly (3.2 Hz/1% CO2) up to 6.5% (CPG threshold) and then more slowly to peak approximately 10 Hz at 10% CO2. Respiratory modulation of RTN neurons was absent below CPG threshold, gradually stronger beyond, and, like pfRG neurons, typically (42%) characterized by twin periods of reduced activity near phrenic inspiration. After CPG inactivation with kynurenate (KYN), RTN neurons discharged linearly as a function of e-exp CO2 (slope, +1.7 Hz/1% CO2) and arterial pH (threshold, 7.48; slope, 39 Hz/pH unit). In coronal brain slices (postnatal days 7-12), RTN chemosensitive neurons were silent at pH 7.55. Their activity increased linearly with acidification up to pH 7.2 (17 Hz/pH unit at 35 degrees C) and was always tonic. In conclusion, consistent with their postulated central chemoreceptor role, RTN/pfRG neurons encode pH linearly and discharge tonically when disconnected from the rest of the respiratory centers in vivo (KYN treatment) and in vitro. In vivo, RTN neurons receive respiratory synchronous inhibitory inputs that may serve as feedback and impart these neurons with their characteristic respiratory modulation.
Reliable sex and strain discrimination in the mouse vomeronasal organ and accessory olfactory bulb.
Tolokh, Illya I; Fu, Xiaoyan; Holy, Timothy E
2013-08-21
Animals modulate their courtship and territorial behaviors in response to olfactory cues produced by other animals. In rodents, detecting these cues is the primary role of the accessory olfactory system (AOS). We sought to systematically investigate the natural stimulus coding logic and robustness in neurons of the first two stages of accessory olfactory processing, the vomeronasal organ (VNO) and accessory olfactory bulb (AOB). We show that firing rate responses of just a few well-chosen mouse VNO or AOB neurons can be used to reliably encode both sex and strain of other mice from cues contained in urine. Additionally, we show that this population code can generalize to new concentrations of stimuli and appears to represent stimulus identity in terms of diverging paths in coding space. Together, the results indicate that firing rate code on the temporal order of seconds is sufficient for accurate classification of pheromonal patterns at different concentrations and may be used by AOS neural circuitry to discriminate among naturally occurring urine stimuli.
TIDAL WAVES: Network mechanisms in the neuroendocrine control of prolactin release.
Lyons, David J; Broberger, Christian
2014-10-01
Neuroendocrine tuberoinfundibular dopamine (TIDA) neurons tonically inhibit pituitary release of the hormone, prolactin. Through the powerful actions of prolactin in promoting lactation and maternal behaviour while suppressing sexual drive and fertility, TIDA neurons play a key role in reproduction. We summarize insights from recent in vitro studies into the membrane properties and network behaviour of TIDA neurons including the observations that TIDA neurons exhibit a robust oscillation that is synchronized between cells and depends on intact gap junction communication. Comparisons are made with phasic firing patterns in other neuronal populations. Modulators involved in the control of lactation - including serotonin, thyrotropin-releasing hormone and prolactin itself - have been shown to change the electrical behaviour of TIDA cells. We propose that TIDA discharge mode may play a central role in tuning the amount of dopamine delivered to the pituitary and hence circulating prolactin concentrations in different reproductive states and pathological conditions. Copyright © 2014 Elsevier Inc. All rights reserved.
Does the entorhinal cortex use the Fourier transform?
Orchard, Jeff; Yang, Hao; Ji, Xiang
2013-01-01
Some neurons in the entorhinal cortex (EC) fire bursts when the animal occupies locations organized in a hexagonal grid pattern in their spatial environment. Place cells have also been observed, firing bursts only when the animal occupies a particular region of the environment. Both of these types of cells exhibit theta-cycle modulation, firing bursts in the 4–12 Hz range. Grid cells fire bursts of action potentials that precess with respect to the theta cycle, a phenomenon dubbed “theta precession.” Various models have been proposed to explain these phenomena, and how they relate to navigation. Among the most promising are the oscillator interference models. The bank-of-oscillators model proposed by Welday et al. (2011) exhibits all these features. However, their simulations are based on theoretical oscillators, and not implemented entirely with spiking neurons. We extend their work in a number of ways. First, we place the oscillators in a frequency domain and reformulate the model in terms of Fourier theory. Second, this perspective suggests a division of labor for implementing spatial maps: position vs. map layout. The animal's position is encoded in the phases of the oscillators, while the spatial map shape is encoded implicitly in the weights of the connections between the oscillators and the read-out nodes. Third, it reveals that the oscillator phases all need to conform to a linear relationship across the frequency domain. Fourth, we implement a partial model of the EC using spiking leaky integrate-and-fire (LIF) neurons. Fifth, we devise new coupling mechanisms, enlightened by the global phase constraint, and show they are capable of keeping spiking neural oscillators in consistent formation. Our model demonstrates place cells, grid cells, and phase precession. The Fourier model also gives direction for future investigations, such as integrating sensory feedback to combat drift, or explaining why grid cells exist at all. PMID:24376415
Multiplexing using synchrony in the zebrafish olfactory bulb.
Friedrich, Rainer W; Habermann, Christopher J; Laurent, Gilles
2004-08-01
In the olfactory bulb (OB) of zebrafish and other species, odors evoke fast oscillatory population activity and specific firing rate patterns across mitral cells (MCs). This activity evolves over a few hundred milliseconds from the onset of the odor stimulus. Action potentials of odor-specific MC subsets phase-lock to the oscillation, defining small and distributed ensembles within the MC population output. We found that oscillatory field potentials in the zebrafish OB propagate across the OB in waves. Phase-locked MC action potentials, however, were synchronized without a time lag. Firing rate patterns across MCs analyzed with low temporal resolution were informative about odor identity. When the sensitivity for phase-locked spiking was increased, activity patterns became progressively more informative about odor category. Hence, information about complementary stimulus features is conveyed simultaneously by the same population of neurons and can be retrieved selectively by biologically plausible mechanisms, indicating that seemingly alternative coding strategies operating on different time scales may coexist.
Network-induced chaos in integrate-and-fire neuronal ensembles.
Zhou, Douglas; Rangan, Aaditya V; Sun, Yi; Cai, David
2009-09-01
It has been shown that a single standard linear integrate-and-fire (IF) neuron under a general time-dependent stimulus cannot possess chaotic dynamics despite the firing-reset discontinuity. Here we address the issue of whether conductance-based, pulsed-coupled network interactions can induce chaos in an IF neuronal ensemble. Using numerical methods, we demonstrate that all-to-all, homogeneously pulse-coupled IF neuronal networks can indeed give rise to chaotic dynamics under an external periodic current drive. We also provide a precise characterization of the largest Lyapunov exponent for these high dimensional nonsmooth dynamical systems. In addition, we present a stable and accurate numerical algorithm for evaluating the largest Lyapunov exponent, which can overcome difficulties encountered by traditional methods for these nonsmooth dynamical systems with degeneracy induced by, e.g., refractoriness of neurons.
Dong, Jun; Xie, Xin-Hua; Lu, Da-Xiang; Fu, Yong-Mei
2007-01-09
Although there is considerable evidence supporting that fever evolved as a host defense response, it is important that the rise in body temperature would not be too high. Many endogenous cryogens or antipyretics that limit the rise in body temperature have been identified. Endogenous antipyretics attenuate fever by influencing the thermoregulatory neurons in the preoptic anterior hypothalamus (POAH) and in adjacent septal areas including ventral septal area (VSA). Our previous study showed that intracerebroventricular (I.C.V.) injection of interleukin-1beta (IL-1beta) affected electrophysiological activities of thermosensitive neurons in VSA regions, and electrical stimulation of POAH reversed the effect of IL-1beta. To further investigate the functional electrophysiological connection between POAH and VSA and its mechanisms in thermoregulation, the firing rates of thermosensitive neurons in POAH of forty-seven unit discharge were recorded by using extracellular microelectrode technique in New Zealand white rabbits. Our results show that the firing rates of the warm-sensitive neurons decreased significantly and those of the cold-sensitive neurons increased in POAH when the pyrogen (IL-1beta) was injected I.C.V. The effects of IL-1beta on firing rates in thermosensitive neurons of POAH were reversed by electrical stimulation of VSA. An arginine vasopressin (AVP) V1 antagonist abolished the regulatory effects of VSA on the firing rates in thermosensitive neurons of POAH evoked by IL-1beta. However, an AVP V2 antagonist had no effects. These data indicated that VSA regulates the activities of the thermosensitive neurons of POAH through AVP V1 but not AVP V2 receptor.
Motor Neurons Tune Premotor Activity in a Vertebrate Central Pattern Generator
2017-01-01
Central patterns generators (CPGs) are neural circuits that drive rhythmic motor output without sensory feedback. Vertebrate CPGs are generally believed to operate in a top-down manner in which premotor interneurons activate motor neurons that in turn drive muscles. In contrast, the frog (Xenopus laevis) vocal CPG contains a functionally unexplored neuronal projection from the motor nucleus to the premotor nucleus, indicating a recurrent pathway that may contribute to rhythm generation. In this study, we characterized the function of this bottom-up connection. The X. laevis vocal CPG produces a 50–60 Hz “fast trill” song used by males during courtship. We recorded “fictive vocalizations” in the in vitro CPG from the laryngeal nerve while simultaneously recording premotor activity at the population and single-cell level. We show that transecting the motor-to-premotor projection eliminated the characteristic firing rate of premotor neurons. Silencing motor neurons with the intracellular sodium channel blocker QX-314 also disrupted premotor rhythms, as did blockade of nicotinic synapses in the motor nucleus (the putative location of motor neuron-to-interneuron connections). Electrically stimulating the laryngeal nerve elicited primarily IPSPs in premotor neurons that could be blocked by a nicotinic receptor antagonist. Our results indicate that an inhibitory signal, activated by motor neurons, is required for proper CPG function. To our knowledge, these findings represent the first example of a CPG in which precise premotor rhythms are tuned by motor neuron activity. SIGNIFICANCE STATEMENT Central pattern generators (CPGs) are neural circuits that produce rhythmic behaviors. In vertebrates, motor neurons are not commonly known to contribute to CPG function, with the exception of a few spinal circuits where the functional significance of motor neuron feedback is still poorly understood. The frog hindbrain vocal circuit contains a previously unexplored connection from the motor to premotor region. Our results indicate that motor neurons activate this bottom-up connection, and blocking this signal eliminates normal premotor activity. These findings may promote increased awareness of potential involvement of motor neurons in a wider range of CPGs, perhaps clarifying our understanding of network principles underlying motor behaviors in numerous organisms, including humans. PMID:28219984
Computing with Neural Synchrony
Brette, Romain
2012-01-01
Neurons communicate primarily with spikes, but most theories of neural computation are based on firing rates. Yet, many experimental observations suggest that the temporal coordination of spikes plays a role in sensory processing. Among potential spike-based codes, synchrony appears as a good candidate because neural firing and plasticity are sensitive to fine input correlations. However, it is unclear what role synchrony may play in neural computation, and what functional advantage it may provide. With a theoretical approach, I show that the computational interest of neural synchrony appears when neurons have heterogeneous properties. In this context, the relationship between stimuli and neural synchrony is captured by the concept of synchrony receptive field, the set of stimuli which induce synchronous responses in a group of neurons. In a heterogeneous neural population, it appears that synchrony patterns represent structure or sensory invariants in stimuli, which can then be detected by postsynaptic neurons. The required neural circuitry can spontaneously emerge with spike-timing-dependent plasticity. Using examples in different sensory modalities, I show that this allows simple neural circuits to extract relevant information from realistic sensory stimuli, for example to identify a fluctuating odor in the presence of distractors. This theory of synchrony-based computation shows that relative spike timing may indeed have computational relevance, and suggests new types of neural network models for sensory processing with appealing computational properties. PMID:22719243
Wang, Min; Yang, Yang; Wang, Ching-Jung; Gamo, Nao J.; Jin, Lu E.; Mazer, James A.; Morrison, John H.; Wang, Xiao-Jing; Arnsten, Amy F.T.
2013-01-01
Summary Neurons in the primate dorsolateral prefrontal cortex (dlPFC) generate persistent firing in the absence of sensory stimulation, the foundation of mental representation. Persistent firing arises from recurrent excitation within a network of pyramidal Delay cells. Here, we examined glutamate receptor influences underlying persistent firing in primate dlPFC during a spatial working memory task. Computational models predicted dependence on NMDA receptor (NMDAR) NR2B stimulation, and Delay cell persistent firing was abolished by local NR2B NMDAR blockade or by systemic ketamine administration. AMPA receptors (AMPAR) contributed background depolarization to sustain network firing. In contrast, many Response cells -which likely predominate in rodent PFC- were sensitive to AMPAR blockade and increased firing following systemic ketamine, indicating that models of ketamine actions should be refined to reflect neuronal heterogeneity. The reliance of Delay cells on NMDAR may explain why insults to NMDARs in schizophrenia or Alzheimer’s Disease profoundly impair cognition. PMID:23439125
Karbasi, Amin; Salavati, Amir Hesam; Vetterli, Martin
2018-04-01
The connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network's topology has received a lot of attentions in neuroscience and has been the center of many research initiatives such as Human Connectome Project. Nevertheless, direct and invasive approaches that slice and observe the neural tissue have proven to be time consuming, complex and costly. As a result, the inverse methods that utilize firing activity of neurons in order to identify the (functional) connections have gained momentum recently, especially in light of rapid advances in recording technologies; It will soon be possible to simultaneously monitor the activities of tens of thousands of neurons in real time. While there are a number of excellent approaches that aim to identify the functional connections from firing activities, the scalability of the proposed techniques plays a major challenge in applying them on large-scale datasets of recorded firing activities. In exceptional cases where scalability has not been an issue, the theoretical performance guarantees are usually limited to a specific family of neurons or the type of firing activities. In this paper, we formulate the neural network reconstruction as an instance of a graph learning problem, where we observe the behavior of nodes/neurons (i.e., firing activities) and aim to find the links/connections. We develop a scalable learning mechanism and derive the conditions under which the estimated graph for a network of Leaky Integrate and Fire (LIf) neurons matches the true underlying synaptic connections. We then validate the performance of the algorithm using artificially generated data (for benchmarking) and real data recorded from multiple hippocampal areas in rats.
Diversity of layer 5 projection neurons in the mouse motor cortex
Oswald, Manfred J.; Tantirigama, Malinda L. S.; Sonntag, Ivo; Hughes, Stephanie M.; Empson, Ruth M.
2013-01-01
In the primary motor cortex (M1), layer 5 projection neurons signal directly to distant motor structures to drive movement. Despite their pivotal position and acknowledged diversity these neurons are traditionally separated into broad commissural and corticofugal types, and until now no attempt has been made at resolving the basis for their diversity. We therefore probed the electrophysiological and morphological properties of retrogradely labeled M1 corticospinal (CSp), corticothalamic (CTh), and commissural projecting corticostriatal (CStr) and corticocortical (CC) neurons. An unsupervised cluster analysis established at least four phenotypes with additional differences between lumbar and cervical projecting CSp neurons. Distinguishing parameters included the action potential (AP) waveform, firing behavior, the hyperpolarisation-activated sag potential, sublayer position, and soma and dendrite size. CTh neurons differed from CSp neurons in showing spike frequency acceleration and a greater sag potential. CStr neurons had the lowest AP amplitude and maximum rise rate of all neurons. Temperature influenced spike train behavior in corticofugal neurons. At 26°C CTh neurons fired bursts of APs more often than CSp neurons, but at 36°C both groups fired regular APs. Our findings provide reliable phenotypic fingerprints to identify distinct M1 projection neuron classes as a tool to understand their unique contributions to motor function. PMID:24137110
Sakurai, Akira; Katz, Paul S
2016-10-01
The nudibranch mollusc, Dendronotus iris, swims by rhythmically flexing its body from left to right. We identified a bilaterally represented interneuron, Si3, that provides strong excitatory drive to the previously identified Si2, forming a half-center oscillator, which functions as the central pattern generator (CPG) underlying swimming. As with Si2, Si3 inhibited its contralateral counterpart and exhibited rhythmic bursts in left-right alternation during the swim motor pattern. Si3 burst almost synchronously with the contralateral Si2 and was coactive with the efferent impulse activity in the contralateral body wall nerve. Perturbation of bursting in either Si3 or Si2 by current injection halted or phase-shifted the swim motor pattern, suggesting that they are both critical CPG members. Neither Si2 nor Si3 exhibited endogenous bursting properties when activated alone; activation of all four neurons was necessary to initiate and maintain the swim motor pattern. Si3 made a strong excitatory synapse onto the contralateral Si2 to which it is also electrically coupled. When Si3 was firing tonically but not exhibiting bursting, artificial enhancement of the Si3-to-Si2 synapse using dynamic clamp caused all four neurons to burst. In contrast, negation of the Si3-to-Si2 synapse by dynamic clamp blocked ongoing swim motor patterns. Together, these results suggest that the Dendronotus swim CPG is organized as a "twisted" half-center oscillator in which each "half" is composed of two excitatory-coupled neurons from both sides of the brain, each of which inhibits its contralateral counterpart. Consisting of only four neurons, this is perhaps the simplest known network oscillator for locomotion. Copyright © 2016 the American Physiological Society.
Characterisation of rebound depolarisation in mice deep dorsal horn neurons in vitro.
Rivera-Arconada, Ivan; Lopez-Garcia, Jose A
2015-09-01
Spinal dorsal horn neurons constitute the first relay for pain processing and participate in the processing of other sensory, motor and autonomic information. At the cellular level, intrinsic excitability is a factor contributing to network function. In turn, excitability is set by the array of ionic conductance expressed by neurons. Here, we set out to characterise rebound depolarisation following hyperpolarisation, a feature frequently described in dorsal horn neurons but never addressed in depth. To this end, an in vitro preparation of the spinal cord from mice pups was used combined with whole-cell recordings in current and voltage clamp modes. Results show the expression of H- and/or T-type currents in a significant proportion of dorsal horn neurons. The expression of these currents determines the presence of rebound behaviour at the end of hyperpolarising pulses. T-type calcium currents were associated to high-amplitude rebounds usually involving high-frequency action potential firing. H-currents were associated to low-amplitude rebounds less prone to elicit firing or firing at lower frequencies. For a large proportion of neurons expressing both currents, the H-current constitutes a mechanism to ensure a faster response after hyperpolarisations, adjusting the latency of the rebound firing. We conclude that rebound depolarisation and firing are intrinsic factors to many dorsal horn neurons that may constitute a mechanism to integrate somatosensory information in the spinal cord, allowing for a rapid switch from inhibited-to-excited states.
Mensi, Skander; Hagens, Olivier; Gerstner, Wulfram; Pozzorini, Christian
2016-01-01
The way in which single neurons transform input into output spike trains has fundamental consequences for network coding. Theories and modeling studies based on standard Integrate-and-Fire models implicitly assume that, in response to increasingly strong inputs, neurons modify their coding strategy by progressively reducing their selective sensitivity to rapid input fluctuations. Combining mathematical modeling with in vitro experiments, we demonstrate that, in L5 pyramidal neurons, the firing threshold dynamics adaptively adjust the effective timescale of somatic integration in order to preserve sensitivity to rapid signals over a broad range of input statistics. For that, a new Generalized Integrate-and-Fire model featuring nonlinear firing threshold dynamics and conductance-based adaptation is introduced that outperforms state-of-the-art neuron models in predicting the spiking activity of neurons responding to a variety of in vivo-like fluctuating currents. Our model allows for efficient parameter extraction and can be analytically mapped to a Generalized Linear Model in which both the input filter—describing somatic integration—and the spike-history filter—accounting for spike-frequency adaptation—dynamically adapt to the input statistics, as experimentally observed. Overall, our results provide new insights on the computational role of different biophysical processes known to underlie adaptive coding in single neurons and support previous theoretical findings indicating that the nonlinear dynamics of the firing threshold due to Na+-channel inactivation regulate the sensitivity to rapid input fluctuations. PMID:26907675
Bursting Transition Dynamics Within the Pre-Bötzinger Complex
NASA Astrophysics Data System (ADS)
Duan, Lixia; Chen, Xi; Tang, Xuhui; Su, Jianzhong
The pre-Bötzinger complex of the mammalian brain stem plays a crucial role in the respiratory rhythms generation. Neurons within the pre-Bötzinger complex have been found experimentally to yield different firing activities. In this paper, we study the spiking and bursting activities related to the respiratory rhythms in the pre-Bötzinger complex based on a mathematical model proposed by Butera. Using the one-dimensional first recurrence map induced by dynamics, we investigate the different bursting patterns and their transition of the pre-Bötzinger complex neurons based on the Butera model, after we derived a one-dimensional map from the dynamical characters of the differential equations, and we obtained conditions for the transition of different bursting patterns. These analytical results were verified through numerical simulations. We conclude that the one-dimensional map contains similar rhythmic patterns as the Butera model and can be used as a simpler modeling tool to study fast-slow models like pre-Bötzinger complex neural circuit.
Heteroassociative storage of hippocampal pattern sequences in the CA3 subregion
Recio, Renan S.; Reyes, Marcelo B.
2018-01-01
Background Recent research suggests that the CA3 subregion of the hippocampus has properties of both autoassociative network, due to its ability to complete partial cues, tolerate noise, and store associations between memories, and heteroassociative one, due to its ability to store and retrieve sequences of patterns. Although there are several computational models of the CA3 as an autoassociative network, more detailed evaluations of its heteroassociative properties are missing. Methods We developed a model of the CA3 subregion containing 10,000 integrate-and-fire neurons with both recurrent excitatory and inhibitory connections, and which exhibits coupled oscillations in the gamma and theta ranges. We stored thousands of pattern sequences using a heteroassociative learning rule with competitive synaptic scaling. Results We showed that a purely heteroassociative network model can (i) retrieve pattern sequences from partial cues with external noise and incomplete connectivity, (ii) achieve homeostasis regarding the number of connections per neuron when many patterns are stored when using synaptic scaling, (iii) continuously update the set of retrievable patterns, guaranteeing that the last stored patterns can be retrieved and older ones can be forgotten. Discussion Heteroassociative networks with synaptic scaling rules seem sufficient to achieve many desirable features regarding connectivity homeostasis, pattern sequence retrieval, noise tolerance and updating of the set of retrievable patterns. PMID:29312826
Correlations and Functional Connections in a Population of Grid Cells
Roudi, Yasser
2015-01-01
We study the statistics of spike trains of simultaneously recorded grid cells in freely behaving rats. We evaluate pairwise correlations between these cells and, using a maximum entropy kinetic pairwise model (kinetic Ising model), study their functional connectivity. Even when we account for the covariations in firing rates due to overlapping fields, both the pairwise correlations and functional connections decay as a function of the shortest distance between the vertices of the spatial firing pattern of pairs of grid cells, i.e. their phase difference. They take positive values between cells with nearby phases and approach zero or negative values for larger phase differences. We find similar results also when, in addition to correlations due to overlapping fields, we account for correlations due to theta oscillations and head directional inputs. The inferred connections between neurons in the same module and those from different modules can be both negative and positive, with a mean close to zero, but with the strongest inferred connections found between cells of the same module. Taken together, our results suggest that grid cells in the same module do indeed form a local network of interconnected neurons with a functional connectivity that supports a role for attractor dynamics in the generation of grid pattern. PMID:25714908
Gaucher, Quentin; Huetz, Chloé; Gourévitch, Boris
2013-01-01
In all sensory modalities, intracortical inhibition shapes the functional properties of cortical neurons but also influences the responses to natural stimuli. Studies performed in various species have revealed that auditory cortex neurons respond to conspecific vocalizations by temporal spike patterns displaying a high trial-to-trial reliability, which might result from precise timing between excitation and inhibition. Studying the guinea pig auditory cortex, we show that partial blockage of GABAA receptors by gabazine (GBZ) application (10 μm, a concentration that promotes expansion of cortical receptive fields) increased the evoked firing rate and the spike-timing reliability during presentation of communication sounds (conspecific and heterospecific vocalizations), whereas GABAB receptor antagonists [10 μm saclofen; 10–50 μm CGP55845 (p-3-aminopropyl-p-diethoxymethyl phosphoric acid)] had nonsignificant effects. Computing mutual information (MI) from the responses to vocalizations using either the evoked firing rate or the temporal spike patterns revealed that GBZ application increased the MI derived from the activity of single cortical site but did not change the MI derived from population activity. In addition, quantification of information redundancy showed that GBZ significantly increased redundancy at the population level. This result suggests that a potential role of intracortical inhibition is to reduce information redundancy during the processing of natural stimuli. PMID:23804094
Bellay, Timothy; Klaus, Andreas; Seshadri, Saurav; Plenz, Dietmar
2015-01-01
Spontaneous fluctuations in neuronal activity emerge at many spatial and temporal scales in cortex. Population measures found these fluctuations to organize as scale-invariant neuronal avalanches, suggesting cortical dynamics to be critical. Macroscopic dynamics, though, depend on physiological states and are ambiguous as to their cellular composition, spatiotemporal origin, and contributions from synaptic input or action potential (AP) output. Here, we study spontaneous firing in pyramidal neurons (PNs) from rat superficial cortical layers in vivo and in vitro using 2-photon imaging. As the animal transitions from the anesthetized to awake state, spontaneous single neuron firing increases in irregularity and assembles into scale-invariant avalanches at the group level. In vitro spike avalanches emerged naturally yet required balanced excitation and inhibition. This demonstrates that neuronal avalanches are linked to the global physiological state of wakefulness and that cortical resting activity organizes as avalanches from firing of local PN groups to global population activity. DOI: http://dx.doi.org/10.7554/eLife.07224.001 PMID:26151674
Zhu, Z T; Zhang, X X; Liu, J; Jin, G Z
1996-01-01
To study the spontaneous firing of CA1 neurons in rat hippocampus after transient cerebral ischemia and the effect of desipramine (Des) on the post-ischemic electric activity of CA1 neurons. Single-unit extracellular recordings were performed in rats on d 3 after 10 min of cerebral ischemia by occlusion of 4 arteries. Des and saline were injected into a tail vein. The histological changes of CA1 neurons was assessed by the neuronal density of the CA1 sector. The spontaneous firing rate of CA1 neurons on d 3 after ischemia was enhanced in comparison with the control value. Des (0.2 and 0.4 mg.kg-1, i.v., n = 5 & 6, respectively) reduced dose-dependently the increase of firing rate with maximal inhibition by 6 min (58% & 85%) to 9 min (69% & 94%) (vs vehicle group, P < 0.01). About 50% cells in CA1 region showed necrotic changes. Des antagonized the hyperexcitability of CA1 neurons after cerebral ischemia.
Single neuron firing properties impact correlation-based population coding
Hong, Sungho; Ratté, Stéphanie; Prescott, Steven A.; De Schutter, Erik
2012-01-01
Correlated spiking has been widely observed but its impact on neural coding remains controversial. Correlation arising from co-modulation of rates across neurons has been shown to vary with the firing rates of individual neurons. This translates into rate and correlation being equivalently tuned to the stimulus; under those conditions, correlated spiking does not provide information beyond that already available from individual neuron firing rates. Such correlations are irrelevant and can reduce coding efficiency by introducing redundancy. Using simulations and experiments in rat hippocampal neurons, we show here that pairs of neurons receiving correlated input also exhibit correlations arising from precise spike-time synchronization. Contrary to rate co-modulation, spike-time synchronization is unaffected by firing rate, thus enabling synchrony- and rate-based coding to operate independently. The type of output correlation depends on whether intrinsic neuron properties promote integration or coincidence detection: “ideal” integrators (with spike generation sensitive to stimulus mean) exhibit rate co-modulation whereas “ideal” coincidence detectors (with spike generation sensitive to stimulus variance) exhibit precise spike-time synchronization. Pyramidal neurons are sensitive to both stimulus mean and variance, and thus exhibit both types of output correlation proportioned according to which operating mode is dominant. Our results explain how different types of correlations arise based on how individual neurons generate spikes, and why spike-time synchronization and rate co-modulation can encode different stimulus properties. Our results also highlight the importance of neuronal properties for population-level coding insofar as neural networks can employ different coding schemes depending on the dominant operating mode of their constituent neurons. PMID:22279226
Hull, Michael J.; Soffe, Stephen R.; Willshaw, David J.; Roberts, Alan
2016-01-01
What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation; activity persists but rhythm breaks down without electrical coupling; NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition. PMID:26824331
Ketogenic diet metabolites reduce firing in central neurons by opening K(ATP) channels.
Ma, Weiyuan; Berg, Jim; Yellen, Gary
2007-04-04
A low-carbohydrate ketogenic diet remains one of the most effective (but mysterious) treatments for severe pharmacoresistant epilepsy. We have tested for an acute effect of physiological ketone bodies on neuronal firing rates and excitability, to discover possible therapeutic mechanisms of the ketogenic diet. Physiological concentrations of ketone bodies (beta-hydroxybutyrate or acetoacetate) reduced the spontaneous firing rate of neurons in slices from rat or mouse substantia nigra pars reticulata. This region is thought to act as a "seizure gate," controlling seizure generalization. Consistent with an anticonvulsant role, the ketone body effect is larger for cells that fire more rapidly. The effect of ketone bodies was abolished by eliminating the metabolically sensitive K(ATP) channels pharmacologically or by gene knock-out. We propose that ketone bodies or glycolytic restriction treat epilepsy by augmenting a natural activity-limiting function served by K(ATP) channels in neurons.
Using affordable LED arrays for photo-stimulation of neurons.
Valley, Matthew; Wagner, Sebastian; Gallarda, Benjamin W; Lledo, Pierre-Marie
2011-11-15
Standard slice electrophysiology has allowed researchers to probe individual components of neural circuitry by recording electrical responses of single cells in response to electrical or pharmacological manipulations(1,2). With the invention of methods to optically control genetically targeted neurons (optogenetics), researchers now have an unprecedented level of control over specific groups of neurons in the standard slice preparation. In particular, photosensitive channel rhodopsin-2 (ChR2) allows researchers to activate neurons with light(3,4). By combining careful calibration of LED-based photostimulation of ChR2 with standard slice electrophysiology, we are able to probe with greater detail the role of adult-born interneurons in the olfactory bulb, the first central relay of the olfactory system. Using viral expression of ChR2-YFP specifically in adult-born neurons, we can selectively control young adult-born neurons in a milieu of older and mature neurons. Our optical control uses a simple and inexpensive LED system, and we show how this system can be calibrated to understand how much light is needed to evoke spiking activity in single neurons. Hence, brief flashes of blue light can remotely control the firing pattern of ChR2-transduced newborn cells.
Kriener, Birgit; Enger, Håkon; Tetzlaff, Tom; Plesser, Hans E.; Gewaltig, Marc-Oliver; Einevoll, Gaute T.
2014-01-01
Random networks of integrate-and-fire neurons with strong current-based synapses can, unlike previously believed, assume stable states of sustained asynchronous and irregular firing, even without external random background or pacemaker neurons. We analyze the mechanisms underlying the emergence, lifetime and irregularity of such self-sustained activity states. We first demonstrate how the competition between the mean and the variance of the synaptic input leads to a non-monotonic firing-rate transfer in the network. Thus, by increasing the synaptic coupling strength, the system can become bistable: In addition to the quiescent state, a second stable fixed-point at moderate firing rates can emerge by a saddle-node bifurcation. Inherently generated fluctuations of the population firing rate around this non-trivial fixed-point can trigger transitions into the quiescent state. Hence, the trade-off between the magnitude of the population-rate fluctuations and the size of the basin of attraction of the non-trivial rate fixed-point determines the onset and the lifetime of self-sustained activity states. During self-sustained activity, individual neuronal activity is moreover highly irregular, switching between long periods of low firing rate to short burst-like states. We show that this is an effect of the strong synaptic weights and the finite time constant of synaptic and neuronal integration, and can actually serve to stabilize the self-sustained state. PMID:25400575
Kriener, Birgit; Enger, Håkon; Tetzlaff, Tom; Plesser, Hans E; Gewaltig, Marc-Oliver; Einevoll, Gaute T
2014-01-01
Random networks of integrate-and-fire neurons with strong current-based synapses can, unlike previously believed, assume stable states of sustained asynchronous and irregular firing, even without external random background or pacemaker neurons. We analyze the mechanisms underlying the emergence, lifetime and irregularity of such self-sustained activity states. We first demonstrate how the competition between the mean and the variance of the synaptic input leads to a non-monotonic firing-rate transfer in the network. Thus, by increasing the synaptic coupling strength, the system can become bistable: In addition to the quiescent state, a second stable fixed-point at moderate firing rates can emerge by a saddle-node bifurcation. Inherently generated fluctuations of the population firing rate around this non-trivial fixed-point can trigger transitions into the quiescent state. Hence, the trade-off between the magnitude of the population-rate fluctuations and the size of the basin of attraction of the non-trivial rate fixed-point determines the onset and the lifetime of self-sustained activity states. During self-sustained activity, individual neuronal activity is moreover highly irregular, switching between long periods of low firing rate to short burst-like states. We show that this is an effect of the strong synaptic weights and the finite time constant of synaptic and neuronal integration, and can actually serve to stabilize the self-sustained state.
Lewis, Jada; Dickson, Dennis W
2016-01-01
Tau is a microtubule-associated protein and a key regulator of microtubule stabilization as well as the main component of neurofibrillary tangles-a principle neuropathological hallmark of Alzheimer's disease (AD)-as well as pleomorphic neuronal and glial inclusions in neurodegenerative tauopathies. Cross-sectional studies of neurofibrillary pathology in AD reveal a stereotypic spatiotemporal pattern of neuronal vulnerability that correlates with disease severity; however, the relationship of this pattern to disease progression is less certain and exceptions to the typical pattern have been described in a subset of AD patients. The basis for the selective vulnerability of specific populations of neurons to tau pathology and cell death is largely unknown, although there have been a number of hypotheses based upon shared properties of vulnerable neurons (e.g., degree of axonal myelination or synaptic plasticity). A recent hypothesis for selective vulnerability takes into account the emerging science of functional connectivity based upon resting state functional magnetic resonance imaging, where subsets of neurons that fire synchronously define patterns of degeneration similar to specific neurodegenerative disorders, including various tauopathies. In the past 6 years, the concept of tau propagation has emerged from numerous studies in cell and animal models suggesting that tau moves from cell-to-cell and that this may trigger aggregation and region-to-region spread of tau pathology within the brain. How the spread of tau pathology relates to functional connectivity is an area of active investigation. Observations of templated folding and propagation of tau have prompted comparisons of tau to prions, the pathogenic proteins in transmissible spongiform encephalopathies. In this review, we discuss the most compelling studies in the field, discuss their shortcomings and consider their implications with respect to human tauopathies as well as the controversy that tauopathies may be prion-like disorders.
Noise in Attractor Networks in the Brain Produced by Graded Firing Rate Representations
Webb, Tristan J.; Rolls, Edmund T.; Deco, Gustavo; Feng, Jianfeng
2011-01-01
Representations in the cortex are often distributed with graded firing rates in the neuronal populations. The firing rate probability distribution of each neuron to a set of stimuli is often exponential or gamma. In processes in the brain, such as decision-making, that are influenced by the noise produced by the close to random spike timings of each neuron for a given mean rate, the noise with this graded type of representation may be larger than with the binary firing rate distribution that is usually investigated. In integrate-and-fire simulations of an attractor decision-making network, we show that the noise is indeed greater for a given sparseness of the representation for graded, exponential, than for binary firing rate distributions. The greater noise was measured by faster escaping times from the spontaneous firing rate state when the decision cues are applied, and this corresponds to faster decision or reaction times. The greater noise was also evident as less stability of the spontaneous firing state before the decision cues are applied. The implication is that spiking-related noise will continue to be a factor that influences processes such as decision-making, signal detection, short-term memory, and memory recall even with the quite large networks found in the cerebral cortex. In these networks there are several thousand recurrent collateral synapses onto each neuron. The greater noise with graded firing rate distributions has the advantage that it can increase the speed of operation of cortical circuitry. PMID:21931607
Yoshida, Motoharu; Jochems, Arthur; Hasselmo, Michael E
2013-01-01
Mechanisms underlying grid cell firing in the medial entorhinal cortex (MEC) still remain unknown. Computational modeling studies have suggested that cellular properties such as spike frequency adaptation and persistent firing might underlie the grid cell firing. Recent in vivo studies also suggest that cholinergic activation influences grid cell firing. Here we investigated the anatomical distribution of firing frequency adaptation, the medium spike after hyperpolarization potential (mAHP), subthreshold membrane potential oscillations, sag potential, input resistance and persistent firing, in MEC layer II principal cells using in vitro whole-cell patch clamp recordings in rats. Anatomical distributions of these properties were compared along both the dorso-ventral and medio-lateral axes, both with and without the cholinergic receptor agonist carbachol. We found that spike frequency adaptation is significantly stronger in ventral than in dorsal neurons both with and without carbachol. Spike frequency adaptation was significantly correlated with the duration of the mAHP, which also showed a gradient along the dorso-ventral axis. In carbachol, we found that about 50% of MEC layer II neurons show persistent firing which lasted more than 30 seconds. Persistent firing of MEC layer II neurons might contribute to grid cell firing by providing the excitatory drive. Dorso-ventral differences in spike frequency adaptation we report here are opposite from previous predictions by a computational model. We discuss an alternative mechanism as to how dorso-ventral differences in spike frequency adaptation could contribute to different scales of grid spacing.
Motor control by precisely timed spike patterns
Srivastava, Kyle H.; Holmes, Caroline M.; Vellema, Michiel; Pack, Andrea R.; Elemans, Coen P. H.; Nemenman, Ilya; Sober, Samuel J.
2017-01-01
A fundamental problem in neuroscience is understanding how sequences of action potentials (“spikes”) encode information about sensory signals and motor outputs. Although traditional theories assume that this information is conveyed by the total number of spikes fired within a specified time interval (spike rate), recent studies have shown that additional information is carried by the millisecond-scale timing patterns of action potentials (spike timing). However, it is unknown whether or how subtle differences in spike timing drive differences in perception or behavior, leaving it unclear whether the information in spike timing actually plays a role in brain function. By examining the activity of individual motor units (the muscle fibers innervated by a single motor neuron) and manipulating patterns of activation of these neurons, we provide both correlative and causal evidence that the nervous system uses millisecond-scale variations in the timing of spikes within multispike patterns to control a vertebrate behavior—namely, respiration in the Bengalese finch, a songbird. These findings suggest that a fundamental assumption of current theories of motor coding requires revision. PMID:28100491
Ebeling, Martin
2008-10-01
A mathematical model is presented here to explain the sensation of consonance and dissonance on the basis of neuronal coding and the properties of a neuronal periodicity detection mechanism. This mathematical model makes use of physiological data from a neuronal model of periodicity analysis in the midbrain, whose operation can be described mathematically by autocorrelation functions with regard to time windows. Musical intervals produce regular firing patterns in the auditory nerve that depend on the vibration ratio of the two tones. The mathematical model makes it possible to define a measure for the degree of these regularities for each vibration ratio. It turns out that this measure value is in line with the degree of tonal fusion as described by Stumpf [Tonpsychologie (Psychology of Tones) (Knuf, Hilversum), reprinted 1965]. This finding makes it probable that tonal fusion is a consequence of certain properties of the neuronal periodicity detection mechanism. Together with strong roughness resulting from interval tones with fundamentals close together or close to the octave, this neuronal mechanism may be regarded as the basis of consonance and dissonance.
Neural mechanisms of sequence generation in songbirds
NASA Astrophysics Data System (ADS)
Langford, Bruce
Animal models in research are useful for studying more complex behavior. For example, motor sequence generation of actions requiring good muscle coordination such as writing with a pen, playing an instrument, or speaking, may involve the interaction of many areas in the brain, each a complex system in itself; thus it can be difficult to determine causal relationships between neural behavior and the behavior being studied. Birdsong, however, provides an excellent model behavior for motor sequence learning, memory, and generation. The song consists of learned sequences of notes that are spectrographically stereotyped over multiple renditions of the song, similar to syllables in human speech. The main areas of the songbird brain involve in singing are known, however, the mechanisms by which these systems store and produce song are not well understood. We used a custom built, head-mounted, miniature motorized microdrive to chronically record the neural firing patterns of identified neurons in HVC, a pre-motor cortical nucleus which has been shown to be important in song timing. These were done in Bengalese finch which generate a song made up of stereotyped notes but variable note sequences. We observed song related bursting in neurons projecting to Area X, a homologue to basal ganglia, and tonic firing in HVC interneurons. Interneuron had firing rate patterns that were consistent over multiple renditions of the same note sequence. We also designed and built a light-weight, low-powered wireless programmable neural stimulator using Bluetooth Low Energy Protocol. It was able to generate perturbations in the song when current pulses were administered to RA, which projects to the brainstem nucleus responsible for syringeal muscle control.
Santin, Joseph M; Watters, Kayla C; Putnam, Robert W; Hartzler, Lynn K
2013-12-15
The locus coeruleus (LC) is a chemoreceptive brain stem region in anuran amphibians and contains neurons sensitive to physiological changes in CO2/pH. The ventilatory and central sensitivity to CO2/pH is proportional to the temperature in amphibians, i.e., sensitivity increases with increasing temperature. We hypothesized that LC neurons from bullfrogs, Lithobates catesbeianus, would increase CO2/pH sensitivity with increasing temperature and decrease CO2/pH sensitivity with decreasing temperature. Further, we hypothesized that cooling would decrease, while warming would increase, normocapnic firing rates of LC neurons. To test these hypotheses, we used whole cell patch-clamp electrophysiology to measure firing rate, membrane potential (V(m)), and input resistance (R(in)) in LC neurons in brain stem slices from adult bullfrogs over a physiological range of temperatures during normocapnia and hypercapnia. We found that cooling reduced chemosensitive responses of LC neurons as temperature decreased until elimination of CO2/pH sensitivity at 10°C. Chemosensitive responses increased at elevated temperatures. Surprisingly, chemosensitive LC neurons increased normocapnic firing rate and underwent membrane depolarization when cooled and decreased normocapnic firing rate and underwent membrane hyperpolarization when warmed. These responses to temperature were not observed in nonchemosensitive LC neurons or neurons in a brain stem slice 500 μm rostral to the LC. Our results indicate that modulation of cellular chemosensitivity within the LC during temperature changes may influence temperature-dependent respiratory drive during acid-base disturbances in amphibians. Additionally, cold-activated/warm-inhibited LC neurons introduce paradoxical temperature sensitivity in respiratory control neurons of amphibians.
How many neurons can we see with current spike sorting algorithms?
Pedreira, Carlos; Martinez, Juan; Ison, Matias J.; Quian Quiroga, Rodrigo
2012-01-01
Recent studies highlighted the disagreement between the typical number of neurons observed with extracellular recordings and the ones to be expected based on anatomical and physiological considerations. This disagreement has been mainly attributed to the presence of sparsely firing neurons. However, it is also possible that this is due to limitations of the spike sorting algorithms used to process the data. To address this issue, we used realistic simulations of extracellular recordings and found a relatively poor spike sorting performance for simulations containing a large number of neurons. In fact, the number of correctly identified neurons for single-channel recordings showed an asymptotic behavior saturating at about 8–10 units, when up to 20 units were present in the data. This performance was significantly poorer for neurons with low firing rates, as these units were twice more likely to be missed than the ones with high firing rates in simulations containing many neurons. These results uncover one of the main reasons for the relatively low number of neurons found in extracellular recording and also stress the importance of further developments of spike sorting algorithms. PMID:22841630
2009-01-01
A breakthrough for studying the neuronal basis of learning emerged when invertebrates with simple nervous systems, such as the sea slug Hermissenda crassicornis, were shown to exhibit classical conditioning. Hermissenda learns to associate light with turbulence: prior to learning, naive animals move toward light (phototaxis) and contract their foot in response to turbulence; after learning, conditioned animals delay phototaxis in response to light. The photoreceptors of the eye, which receive monosynaptic inputs from statocyst hair cells, are both sensory neurons and the first site of sensory convergence. The memory of light associated with turbulence is stored as changes in intrinsic and synaptic currents in these photoreceptors. The subcellular mechanisms producing these changes include activation of protein kinase C and MAP kinase, which act as coincidence detectors because they are activated by convergent signaling pathways. Pathways of interneurons and motorneurons, where additional changes in excitability and synaptic connections are found, contribute to delayed phototaxis. Bursting activity recorded at several points suggest the existence of small networks that produce complex spatio-temporal firing patterns. Thus, the change in behavior may be produced by a non-linear transformation of spatio-temporal firing patterns caused by plasticity of synaptic and intrinsic channels. The change in currents and the activation of PKC and MAPK produced by associative learning are similar to that observed in hippocampal and cerebellar neurons after rabbit classical conditioning, suggesting that these represent general mechanisms of memory storage. Thus, the knowledge gained from further study of Hermissenda will continue to illuminate mechanisms of mammalian learning. PMID:16437555
Mifflin, Steve W.
2017-01-01
μ-Opioid receptors are distributed widely in the brain stem respiratory network, and opioids with selectivity for μ-type receptors slow in vivo respiratory rhythm in lowest effective doses. Several studies have reported μ-opioid receptor effects on the three-phase rhythm of respiratory neurons, but there are until now no reports of opioid effects on oscillatory activity within respiratory discharges. In this study, effects of the μ-opioid receptor agonist fentanyl on spike train discharge properties of several different types of rhythm-modulating medullary respiratory neuron discharges were analyzed. Doses of fentanyl that were just sufficient for prolongation of discharges and slowing of the three-phase respiratory rhythm also produced pronounced enhancement of spike train properties. Oscillation and burst patterns detected by autocorrelation measurements were greatly enhanced, and interspike intervals were prolonged. Spike train properties under control conditions and after fentanyl were uniform within each experiment, but varied considerably between experiments, which might be related to variability in acid-base balance in the brain stem extracellular fluid. Discharge threshold was shifted to more negative levels of membrane potential. The effects on threshold are postulated to result from opioid-mediated disinhibition and postsynaptic enhancement of N-methyl-d- aspartate receptor current. Lowering of firing threshold, enhancement of spike train oscillations and bursts and prolongation of discharges by lowest effective doses of fentanyl could represent compensatory adjustments in the brain stem respiratory network to override opioid blunting of CO2/pH chemosensitivity. PMID:28202437
Lalley, Peter M; Mifflin, Steve W
2017-05-01
μ-Opioid receptors are distributed widely in the brain stem respiratory network, and opioids with selectivity for μ-type receptors slow in vivo respiratory rhythm in lowest effective doses. Several studies have reported μ-opioid receptor effects on the three-phase rhythm of respiratory neurons, but there are until now no reports of opioid effects on oscillatory activity within respiratory discharges. In this study, effects of the μ-opioid receptor agonist fentanyl on spike train discharge properties of several different types of rhythm-modulating medullary respiratory neuron discharges were analyzed. Doses of fentanyl that were just sufficient for prolongation of discharges and slowing of the three-phase respiratory rhythm also produced pronounced enhancement of spike train properties. Oscillation and burst patterns detected by autocorrelation measurements were greatly enhanced, and interspike intervals were prolonged. Spike train properties under control conditions and after fentanyl were uniform within each experiment, but varied considerably between experiments, which might be related to variability in acid-base balance in the brain stem extracellular fluid. Discharge threshold was shifted to more negative levels of membrane potential. The effects on threshold are postulated to result from opioid-mediated disinhibition and postsynaptic enhancement of N -methyl-d- aspartate receptor current. Lowering of firing threshold, enhancement of spike train oscillations and bursts and prolongation of discharges by lowest effective doses of fentanyl could represent compensatory adjustments in the brain stem respiratory network to override opioid blunting of CO 2 /pH chemosensitivity. Copyright © 2017 the American Physiological Society.
West, Charles Hutchison Keesor; Weiss, Jay Michael
2010-01-01
Increasing attention is now focused on reduced dopaminergic neurotransmission in the forebrain as participating in depression. The present paper assessed whether effective antidepressant (AD) treatments might counteract, or compensate for, such a change by altering the neuronal activity of dopaminergic neurons in the ventral tegmental area (VTA-DA neurons), the cell bodies of the mesocorticolimbic dopaminergic system. Eight AD drugs or vehicle were administered to rats for 14 days via subcutaneously-implanted minipumps, at which time single-unit electrophysiological activity of VTA-DA neurons was recorded under anesthesia. Also, animals received a series of five electroconvulsive shocks (ECS) or control procedures, after which VTA-DA activity was measured either three or five days after the last ECS. Results showed that the chronic administration of all AD drugs tested except for the monoamine oxidase inhibitor increased the spontaneous firing rate of VTA-DA neurons, while effects on “burst” firing activity were found to be considerably less notable or consistent. ECS increased both spontaneous firing rate and burst firing of VTA-DA neurons. It is suggested that the effects observed are consistent with reports of increased dopamine release in regions to which VTA neurons project after effective AD treatment. However, it is further suggested that changes in VTA-DA neuronal activity in response to AD treatment should be most appropriately assessed under conditions associated with depression, such as stressful conditions. PMID:20482941
McDaid, John; McElvain, Maureen A.; Brodie, Mark S.
2008-01-01
The dopaminergic neurons of the ventral tegmental area (DA VTA neurons) are important for the rewarding and reinforcing properties of drugs of abuse, including ethanol. Ethanol increases the firing frequency of DA VTA neurons from rats and mice. Because of a recent report on block of ethanol excitation in mouse DA VTA neurons with ZD7288, a selective blocker of the hyperpolarization-activated cationic current Ih, we examined the effect of ZD7288 on ethanol excitation in DA VTA neurons from C57Bl/6J and DBA/2J mice and Fisher 344 rats. Ethanol (80 mM) caused only increases in firing rate in mouse DA VTA neurons in the absence of ZD7288, but in the presence of ZD7288 (30 μM), ethanol produced a more transient excitation followed by a decrease of firing. This same biphasic phenomenon was observed in DA VTA neurons from rats in the presence of ZD7288 only at very high ethanol concentrations (160–240 mM) but not at lower pharmacologically relevant concentrations. The longer latency ethanol-induced inhibition was not observed in DA VTA neurons from mice or rats in the presence of barium (100 μM), which blocks G protein–linked potassium channels (GIRKs) and other inwardly rectifying potassium channels. Ethanol may have a direct effect to increase an inhibitory potassium conductance, but this effect of ethanol can only decrease the firing rate if Ih is blocked. PMID:18614756
From Spiking Neuron Models to Linear-Nonlinear Models
Ostojic, Srdjan; Brunel, Nicolas
2011-01-01
Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates. PMID:21283777
From spiking neuron models to linear-nonlinear models.
Ostojic, Srdjan; Brunel, Nicolas
2011-01-20
Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.
Functional Characterization of Lamina X Neurons in ex-Vivo Spinal Cord Preparation.
Krotov, Volodymyr; Tokhtamysh, Anastasia; Kopach, Olga; Dromaretsky, Andrew; Sheremet, Yevhenii; Belan, Pavel; Voitenko, Nana
2017-01-01
Functional properties of lamina X neurons in the spinal cord remain unknown despite the established role of this area for somatosensory integration, visceral nociception, autonomic regulation and motoneuron output modulation. Investigations of neuronal functioning in the lamina X have been hampered by technical challenges. Here we introduce an ex-vivo spinal cord preparation with both dorsal and ventral roots still attached for functional studies of the lamina X neurons and their connectivity using an oblique LED illumination for resolved visualization of lamina X neurons in a thick tissue. With the elaborated approach, we demonstrate electrophysiological characteristics of lamina X neurons by their membrane properties, firing pattern discharge and fiber innervation (either afferent or efferent). The tissue preparation has been also probed using Ca 2+ imaging with fluorescent Ca 2+ dyes (membrane-impermeable or -permeable) to demonstrate the depolarization-induced changes in intracellular calcium concentration in lamina X neurons. Finally, we performed visualization of subpopulations of lamina X neurons stained by retrograde labeling with aminostilbamidine dye to identify sympathetic preganglionic and projection neurons in the lamina X. Thus, the elaborated approach provides a reliable tool for investigation of functional properties and connectivity in specific neuronal subpopulations, boosting research of lamina X of the spinal cord.
Katz, P S; Frost, W N
1997-10-15
For the mollusc Tritonia diomedea to generate its escape swim motor pattern, interneuron C2, a crucial member of the central pattern generator (CPG) for this rhythmic behavior, must fire repetitive bursts of action potentials. Yet, before swimming, repeated depolarizing current pulses injected into C2 at periods similar those in the swim motor program are incapable of mimicking the firing rate attained by C2 on each cycle of a swim motor program. This resting level of C2 inexcitability is attributable to its own inherent spike frequency adaptation (SFA). Clearly, this property must be altered for the swim behavior to occur. The pathway for initiation of the swimming behavior involves activation of the serotonergic dorsal swim interneurons (DSIs), which are also intrinsic members of the swim CPG. Physiologically appropriate DSI stimulation transiently decreases C2 SFA, allowing C2 to fire at higher rates even when repeatedly depolarized at short intervals. The increased C2 excitability caused by DSI stimulation is mimicked and occluded by serotonin application. Furthermore, the change in excitability is not caused by the depolarization associated with DSI stimulation or serotonin application but is correlated with a decrease in C2 spike afterhyperpolarization. This suggests that the DSIs use serotonin to evoke a neuromodulatory action on a conductance in C2 that regulates its firing rate. This modulatory action of one CPG neuron on another is likely to play a role in configuring the swim circuit into its rhythmic pattern-generating mode and maintaining it in that state.
To Break or to Brake Neuronal Network Accelerated by Ammonium Ions?
Dynnik, Vladimir V.; Kononov, Alexey V.; Sergeev, Alexander I.; Teplov, Iliya Y.; Tankanag, Arina V.; Zinchenko, Valery P.
2015-01-01
Purpose The aim of present study was to investigate the effects of ammonium ions on in vitro neuronal network activity and to search alternative methods of acute ammonia neurotoxicity prevention. Methods Rat hippocampal neuronal and astrocytes co-cultures in vitro, fluorescent microscopy and perforated patch clamp were used to monitor the changes in intracellular Ca2+- and membrane potential produced by ammonium ions and various modulators in the cells implicated in neural networks. Results Low concentrations of NH4Cl (0.1–4 mM) produce short temporal effects on network activity. Application of 5–8 mM NH4Cl: invariably transforms diverse network firing regimen to identical burst patterns, characterized by substantial neuronal membrane depolarization at plateau phase of potential and high-amplitude Ca2+-oscillations; raises frequency and average for period of oscillations Ca2+-level in all cells implicated in network; results in the appearance of group of «run out» cells with high intracellular Ca2+ and steadily diminished amplitudes of oscillations; increases astrocyte Ca2+-signalling, characterized by the appearance of groups of cells with increased intracellular Ca2+-level and/or chaotic Ca2+-oscillations. Accelerated network activity may be suppressed by the blockade of NMDA or AMPA/kainate-receptors or by overactivation of AMPA/kainite-receptors. Ammonia still activate neuronal firing in the presence of GABA(A) receptors antagonist bicuculline, indicating that «disinhibition phenomenon» is not implicated in the mechanisms of networks acceleration. Network activity may also be slowed down by glycine, agonists of metabotropic inhibitory receptors, betaine, L-carnitine, L-arginine, etc. Conclusions Obtained results demonstrate that ammonium ions accelerate neuronal networks firing, implicating ionotropic glutamate receptors, having preserved the activities of group of inhibitory ionotropic and metabotropic receptors. This may mean, that ammonia neurotoxicity might be prevented by the activation of various inhibitory receptors (i.e. by the reinforcement of negative feedback control), instead of application of various enzyme inhibitors and receptor antagonists (breaking of neural, metabolic and signaling systems). PMID:26217943
Sadeh, Sadra; Rotter, Stefan
2014-01-01
Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity. PMID:25469704
Meza, Rodrigo C; López-Jury, Luciana; Canavier, Carmen C; Henny, Pablo
2018-01-17
The spontaneous tonic discharge activity of nigral dopamine neurons plays a fundamental role in dopaminergic signaling. To investigate the role of neuronal morphology and architecture with respect to spontaneous activity in this population, we visualized the 3D structure of the axon initial segment (AIS) along with the entire somatodendritic domain of adult male mouse dopaminergic neurons, previously recorded in vivo We observed a positive correlation of the firing rate with both proximity and size of the AIS. Computational modeling showed that the size of the AIS, but not its position within the somatodendritic domain, is the major causal determinant of the tonic firing rate in the intact model, by virtue of the higher intrinsic frequency of the isolated AIS. Further mechanistic analysis of the relationship between neuronal morphology and firing rate showed that dopaminergic neurons function as a coupled oscillator whose frequency of discharge results from a compromise between AIS and somatodendritic oscillators. Thus, morphology plays a critical role in setting the basal tonic firing rate, which in turn could control striatal dopaminergic signaling that mediates motivation and movement. SIGNIFICANCE STATEMENT The frequency at which nigral dopamine neurons discharge action potentials sets baseline dopamine levels in the brain, which enables activity in motor, cognitive, and motivational systems. Here, we demonstrate that the size of the axon initial segment, a subcellular compartment responsible for initiating action potentials, is a key determinant of the firing rate in these neurons. The axon initial segment and all the molecular components that underlie its critical function may provide a novel target for the regulation of dopamine levels in the brain. Copyright © 2018 the authors 0270-6474/18/380733-12$15.00/0.
Chong, Samuel L; Claussen, Catherine M; Dafny, Nachum
2012-01-01
Methylphenidate (MPD) is a psychostimulant that enhances dopaminergic neurotransmission in the central nervous system by using mechanisms similar to cocaine and amphetamine. The mode of action of brain circuitry responsible for an animal’s neuronal response to MPD is not fully understood. The nucleus accumbens (NAc) has been implicated in regulating the rewarding effects of psychostimulants. The present study used permanently implanted microelectrodes to investigate the acute and chronic effects of MPD on the firing rates of NAc neuronal units in freely behaving rats. On experimental day 1 (ED1), following a saline injection (control), a 30 minute baseline neuronal recording was obtained immediately followed by a 2.5 mg/kg i.p. MPD injection and subsequent 60 min neuronal recording. Daily 2.5 mg/kg MPD injections were given on ED2 through ED6 followed by 3 washout days (ED7 to 9). On ED10, neuronal recordings were resumed from the same animal after a saline and MPD (rechallenge) injection exactly as obtained on ED1. Sixty-seven NAc neuronal units exhibited similar wave shape, form and amplitude on ED1 and ED10 and their firing rates were used for analysis. MPD administration on ED1 elicited firing rate increases and decreases in 54% of NAc units when compared to their baselines. Six consecutive MPD administrations altered the neuronal baseline firing rates of 85% of NAc units. MPD rechallenge on ED10 elicited significant changes in 63% of NAc units. These alterations in firing rates are hypothesized to be through mechanisms that include D1 and D2-like DA receptor induced cellular adaptation and homeostatic adaptations/deregulation caused by acute and chronic MPD administration. PMID:22248440
Nichols, Nicole L.; Powell, Frank L.; Dean, Jay B.; Putnam, Robert W.
2014-01-01
NK1 receptors, which bind substance P, are present in the majority of brainstem regions that contain CO2/H+-sensitive neurons that play a role in central chemosensitivity. However, the effect of substance P on the chemosensitive response of neurons from these regions has not been studied. Hypoxia increases substance P release from peripheral afferents that terminate in the caudal nucleus tractus solitarius (NTS). Here we studied the effect of substance P on the chemosensitive responses of solitary complex (SC: NTS and dorsal motor nucleus) neurons from control and chronic hypoxia-adapted (CHx) adult rats. We simultaneously measured intracellular pH and electrical responses to hypercapnic acidosis in SC neurons from control and CHx adult rats using the blind whole cell patch clamp technique and fluorescence imaging microscopy. Substance P significantly increased the basal firing rate in SC neurons from control and CHx rats, although the increase was smaller in CHx rats. However, substance P did not affect the chemosensitive response of SC neurons from either group of rats. In conclusion, we found that substance P plays a role in modulating the basal firing rate of SC neurons but the magnitude of the effect is smaller for SC neurons from CHx adult rats, implying that NK1 receptors may be down regulated in CHx adult rats. Substance P does not appear to play a role in modulating the firing rate response to hypercapnic acidosis of SC neurons from either control or CHx adult rats. PMID:24516602
State-space decoding of primary afferent neuron firing rates
NASA Astrophysics Data System (ADS)
Wagenaar, J. B.; Ventura, V.; Weber, D. J.
2011-02-01
Kinematic state feedback is important for neuroprostheses to generate stable and adaptive movements of an extremity. State information, represented in the firing rates of populations of primary afferent (PA) neurons, can be recorded at the level of the dorsal root ganglia (DRG). Previous work in cats showed the feasibility of using DRG recordings to predict the kinematic state of the hind limb using reverse regression. Although accurate decoding results were attained, reverse regression does not make efficient use of the information embedded in the firing rates of the neural population. In this paper, we present decoding results based on state-space modeling, and show that it is a more principled and more efficient method for decoding the firing rates in an ensemble of PA neurons. In particular, we show that we can extract confounded information from neurons that respond to multiple kinematic parameters, and that including velocity components in the firing rate models significantly increases the accuracy of the decoded trajectory. We show that, on average, state-space decoding is twice as efficient as reverse regression for decoding joint and endpoint kinematics.
Moraes, Davi J A; Bonagamba, Leni G H; Costa, Kauê M; Costa-Silva, João H; Zoccal, Daniel B; Machado, Benedito H
2014-01-01
Individuals experiencing sustained hypoxia (SH) exhibit adjustments in the respiratory and autonomic functions by neural mechanisms not yet elucidated. In the present study we evaluated the central mechanisms underpinning the SH-induced changes in the respiratory pattern and their impact on the sympathetic outflow. Using a decerebrated arterially perfused in situ preparation, we verified that juvenile rats exposed to SH (10% O2) for 24 h presented an active expiratory pattern, with increased abdominal, hypoglossal and vagal activities during late-expiration (late-E). SH also enhanced the activity of augmenting-expiratory neurones and depressed the activity of post-inspiratory neurones of the Bötzinger complex (BötC) by mechanisms not related to changes in their intrinsic electrophysiological properties. SH rats exhibited high thoracic sympathetic activity and arterial pressure levels associated with an augmented firing frequency of pre-sympathetic neurones of the rostral ventrolateral medulla (RVLM) during the late-E phase. The antagonism of ionotropic glutamatergic receptors in the BötC/RVLM abolished the late-E bursts in expiratory and sympathetic outputs of SH rats, indicating that glutamatergic inputs to the BötC/RVLM are essential for the changes in the expiratory and sympathetic coupling observed in SH rats. We also observed that the usually silent late-E neurones of the retrotrapezoid nucleus/parafacial respiratory group became active in SH rats, suggesting that this neuronal population may provide the excitatory drive essential to the emergence of active expiration and sympathetic overactivity. We conclude that short-term SH induces the activation of medullary expiratory neurones, which affects the pattern of expiratory motor activity and its coupling with sympathetic activity. PMID:24614747
Oyama, Kei; Tateyama, Yukina; Hernádi, István; Tobler, Philippe N; Iijima, Toshio; Tsutsui, Ken-Ichiro
2015-11-01
To investigate how the striatum integrates sensory information with reward information for behavioral guidance, we recorded single-unit activity in the dorsal striatum of head-fixed rats participating in a probabilistic Pavlovian conditioning task with auditory conditioned stimuli (CSs) in which reward probability was fixed for each CS but parametrically varied across CSs. We found that the activity of many neurons was linearly correlated with the reward probability indicated by the CSs. The recorded neurons could be classified according to their firing patterns into functional subtypes coding reward probability in different forms such as stimulus value, reward expectation, and reward prediction error. These results suggest that several functional subgroups of dorsal striatal neurons represent different kinds of information formed through extensive prior exposure to CS-reward contingencies. Copyright © 2015 the American Physiological Society.
Oyama, Kei; Tateyama, Yukina; Hernádi, István; Tobler, Philippe N.; Iijima, Toshio
2015-01-01
To investigate how the striatum integrates sensory information with reward information for behavioral guidance, we recorded single-unit activity in the dorsal striatum of head-fixed rats participating in a probabilistic Pavlovian conditioning task with auditory conditioned stimuli (CSs) in which reward probability was fixed for each CS but parametrically varied across CSs. We found that the activity of many neurons was linearly correlated with the reward probability indicated by the CSs. The recorded neurons could be classified according to their firing patterns into functional subtypes coding reward probability in different forms such as stimulus value, reward expectation, and reward prediction error. These results suggest that several functional subgroups of dorsal striatal neurons represent different kinds of information formed through extensive prior exposure to CS-reward contingencies. PMID:26378201
Response Properties of Cochlear Nucleus Neurons in Monkeys
Roth, G. Linn; Recio, A.
2009-01-01
Much of what is known about how the cochlear nuclei participate in mammalian hearing comes from studies of non-primate mammalian species. To determine to what extent the cochlear nuclei of primates resemble those of other mammalian orders, we have recorded responses to sound in three primate species: marmosets, Cynomolgus macaques, and squirrel monkeys. These recordings show that the same types of temporal firing patterns are found in primates that have been described in other mammals. Responses to tones of neurons in the ventral cochlear nucleus have similar tuning, latencies, post-stimulus time and interspike interval histograms as those recorded in non-primate cochlear nucleus neurons. In the dorsal cochlear nucleus, too, responses were similar. From these results it is evident that insights gained from non-primate studies can be applied to the peripheral auditory system of primates. PMID:19531377
Spectrum of Lyapunov exponents of non-smooth dynamical systems of integrate-and-fire type.
Zhou, Douglas; Sun, Yi; Rangan, Aaditya V; Cai, David
2010-04-01
We discuss how to characterize long-time dynamics of non-smooth dynamical systems, such as integrate-and-fire (I&F) like neuronal network, using Lyapunov exponents and present a stable numerical method for the accurate evaluation of the spectrum of Lyapunov exponents for this large class of dynamics. These dynamics contain (i) jump conditions as in the firing-reset dynamics and (ii) degeneracy such as in the refractory period in which voltage-like variables of the network collapse to a single constant value. Using the networks of linear I&F neurons, exponential I&F neurons, and I&F neurons with adaptive threshold, we illustrate our method and discuss the rich dynamics of these networks.
Mirror neuron system: basic findings and clinical applications.
Iacoboni, Marco; Mazziotta, John C
2007-09-01
In primates, ventral premotor and rostral inferior parietal neurons fire during the execution of hand and mouth actions. Some cells (called mirror neurons) also fire when hand and mouth actions are just observed. Mirror neurons provide a simple neural mechanism for understanding the actions of others. In humans, posterior inferior frontal and rostral inferior parietal areas have mirror properties. These human areas are relevant to imitative learning and social behavior. Indeed, the socially isolating condition of autism is associated with a deficit in mirror neuron areas. Strategies inspired by mirror neuron research recently have been used in the treatment of autism and in motor rehabilitation after stroke.
Santin, J M; Hartzler, L K
2013-02-01
The locus coeruleus (LC) in the brainstem senses alterations in CO(2)/pH and influences ventilatory adjustments that restore blood gas values to starting levels in bullfrogs (Lithobates catesbeianus). We hypothesized that neurons of the bullfrog LC are sensitive to changes in CO(2)/pH and that chemosensitive responses are intrinsic to individual neurons. In addition, we hypothesized putative respiratory control neurons of the bullfrog LC would be stimulated by hypercapnic acidosis within physiological ranges of P(CO(2))/pH. 84% of LC neurons depolarized and increased firing rates during exposure to hypercapnic acidosis (HA). A pH dose response curve shows LC neurons from bullfrogs increase firing rates during physiologically relevant CO(2)/pH changes. With chemical synapses blocked, half of chemosensitive neurons lost sensitivity to HA; however, gap junction blockade did not alter chemosensitive responses. Intrinsically chemosensitive neurons increased input resistance during HA. These data demonstrate that majority of neurons within the bullfrog LC elicit robust firing responses during physiological ΔCO(2)/pH, likely enabling adjustment of acid-base balance through breathing. Copyright © 2012 Elsevier B.V. All rights reserved.
TETRAMETHRIN AND DDT INHIBIT SPONTANEOUS FIRING IN CORTICAL NEURONAL NETWORKS
The insecticidal and neurotoxic effects of pyrethroids result from prolonged sodium channel inactivation, which causes alterations in neuronal firing and communication. Previously, we determined the relative potencies of 11 type I and type II pyrethroid insecticides using microel...
Emergent gamma synchrony in all-to-all interneuronal networks.
Ratnadurai-Giridharan, Shivakeshavan; Khargonekar, Pramod P; Talathi, Sachin S
2015-01-01
We investigate the emergence of in-phase synchronization in a heterogeneous network of coupled inhibitory interneurons in the presence of spike timing dependent plasticity (STDP). Using a simple network of two mutually coupled interneurons (2-MCI), we first study the effects of STDP on in-phase synchronization. We demonstrate that, with STDP, the 2-MCI network can evolve to either a state of stable 1:1 in-phase synchronization or exhibit multiple regimes of higher order synchronization states. We show that the emergence of synchronization induces a structural asymmetry in the 2-MCI network such that the synapses onto the high frequency firing neurons are potentiated, while those onto the low frequency firing neurons are de-potentiated, resulting in the directed flow of information from low frequency firing neurons to high frequency firing neurons. Finally, we demonstrate that the principal findings from our analysis of the 2-MCI network contribute to the emergence of robust synchronization in the Wang-Buzsaki network (Wang and Buzsáki, 1996) of all-to-all coupled inhibitory interneurons (100-MCI) for a significantly larger range of heterogeneity in the intrinsic firing rate of the neurons in the network. We conclude that STDP of inhibitory synapses provide a viable mechanism for robust neural synchronization.
Emergent gamma synchrony in all-to-all interneuronal networks
Ratnadurai-Giridharan, Shivakeshavan; Khargonekar, Pramod P.; Talathi, Sachin S.
2015-01-01
We investigate the emergence of in-phase synchronization in a heterogeneous network of coupled inhibitory interneurons in the presence of spike timing dependent plasticity (STDP). Using a simple network of two mutually coupled interneurons (2-MCI), we first study the effects of STDP on in-phase synchronization. We demonstrate that, with STDP, the 2-MCI network can evolve to either a state of stable 1:1 in-phase synchronization or exhibit multiple regimes of higher order synchronization states. We show that the emergence of synchronization induces a structural asymmetry in the 2-MCI network such that the synapses onto the high frequency firing neurons are potentiated, while those onto the low frequency firing neurons are de-potentiated, resulting in the directed flow of information from low frequency firing neurons to high frequency firing neurons. Finally, we demonstrate that the principal findings from our analysis of the 2-MCI network contribute to the emergence of robust synchronization in the Wang-Buzsaki network (Wang and Buzsáki, 1996) of all-to-all coupled inhibitory interneurons (100-MCI) for a significantly larger range of heterogeneity in the intrinsic firing rate of the neurons in the network. We conclude that STDP of inhibitory synapses provide a viable mechanism for robust neural synchronization. PMID:26528174