Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks.

PubMed

Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime

2016-01-01

It has been shown that, in cultured neuronal networks on a multielectrode, pseudorandom-like sequences (codes) are detected, and they flow with some spatial decay constant. Each cultured neuronal network is characterized by a specific spectrum curve. That is, we may consider the spectrum curve as a "signature" of its associated neuronal network that is dependent on the characteristics of neurons and network configuration, including the weight distribution. In the present study, we used an integrate-and-fire model of neurons with intrinsic and instantaneous fluctuations of characteristics for performing a simulation of a code spectrum from multielectrodes on a 2D mesh neural network. We showed that it is possible to estimate the characteristics of neurons such as the distribution of number of neurons around each electrode and their refractory periods. Although this process is a reverse problem and theoretically the solutions are not sufficiently guaranteed, the parameters seem to be consistent with those of neurons. That is, the proposed neural network model may adequately reflect the behavior of a cultured neuronal network. Furthermore, such prospect is discussed that code analysis will provide a base of communication within a neural network that will also create a base of natural intelligence.

Leaky gate model: intensity-dependent coding of pain and itch in the spinal cord

PubMed Central

Sun, Shuohao; Xu, Qian; Guo, Changxiong; Guan, Yun; Liu, Qin; Dong, Xinzhong

2017-01-01

SUMMARY Coding of itch versus pain has been heatedly debated for decades. However, the current coding theories (labeled line, intensity and selectivity theory) cannot accommodate all experimental observations. Here we identified a subset of spinal interneurons, labeled by gastrin releasing peptide (Grp), that receive direct synaptic input from both pain and itch primary sensory neurons. When activated, these Grp+ neurons generated rarely-seen simultaneous robust pain and itch responses that were intensity-dependent. Accordingly, we propose a “leaky gate” model, in which Grp+ neurons transmit both itch and weak pain signals, however upon strong painful stimuli the recruitment of endogenous opioids works to close this gate, reducing overwhelming pain generated by parallel pathways. Consistent with our model, loss of these Grp+ neurons increased pain responses while itch was decreased. Our new model serves as an example of non-monotonic coding in the spinal cord and better explains observations in human psychophysical studies. PMID:28231466

Catenin-dependent cadherin function drives divisional segregation of spinal motor neurons.

PubMed

Bello, Sanusi M; Millo, Hadas; Rajebhosale, Manisha; Price, Stephen R

2012-01-11

Motor neurons that control limb movements are organized as a neuronal nucleus in the developing ventral horn of the spinal cord called the lateral motor column. Neuronal migration segregates motor neurons into distinct lateral and medial divisions within the lateral motor column that project axons to dorsal or ventral limb targets, respectively. This migratory phase is followed by an aggregation phase whereby motor neurons within a division that project to the same muscle cluster together. These later phases of motor neuron organization depend on limb-regulated differential cadherin expression within motor neurons. Initially, all motor neurons display the same cadherin expression profile, which coincides with the migratory phase of motor neuron segregation. Here, we show that this early, pan-motor neuron cadherin function drives the divisional segregation of spinal motor neurons in the chicken embryo by controlling motor neuron migration. We manipulated pan-motor neuron cadherin function through dissociation of cadherin binding to their intracellular partners. We found that of the major intracellular transducers of cadherin signaling, γ-catenin and α-catenin predominate in the lateral motor column. In vivo manipulations that uncouple cadherin-catenin binding disrupt divisional segregation via deficits in motor neuron migration. Additionally, reduction of the expression of cadherin-7, a cadherin predominantly expressed in motor neurons only during their migration, also perturbs divisional segregation. Our results show that γ-catenin-dependent cadherin function is required for spinal motor neuron migration and divisional segregation and suggest a prolonged role for cadherin expression in all phases of motor neuron organization.

Direction-selective circuits shape noise to ensure a precise population code

PubMed Central

Zylberberg, Joel; Cafaro, Jon; Turner, Maxwell H

2016-01-01

Summary Neural responses are noisy, and circuit structure can correlate this noise across neurons. Theoretical studies show that noise correlations can have diverse effects on population coding, but these studies rarely explore stimulus dependence of noise correlations. Here, we show that noise correlations in responses of ON-OFF direction-selective retinal ganglion cells are strongly stimulus dependent and we uncover the circuit mechanisms producing this stimulus dependence. A population model based on these mechanistic studies shows that stimulus-dependent noise correlations improve the encoding of motion direction two-fold compared to independent noise. This work demonstrates a mechanism by which a neural circuit effectively shapes its signal and noise in concert, minimizing corruption of signal by noise. Finally, we generalize our findings beyond direction coding in the retina and show that stimulus-dependent correlations will generally enhance information coding in populations of diversely tuned neurons. PMID:26796691

A phase code for memory could arise from circuit mechanisms in entorhinal cortex

PubMed Central

Hasselmo, Michael E.; Brandon, Mark P.; Yoshida, Motoharu; Giocomo, Lisa M.; Heys, James G.; Fransen, Erik; Newman, Ehren L.; Zilli, Eric A.

2009-01-01

Neurophysiological data reveals intrinsic cellular properties that suggest how entorhinal cortical neurons could code memory by the phase of their firing. Potential cellular mechanisms for this phase coding in models of entorhinal function are reviewed. This mechanism for phase coding provides a substrate for modeling the responses of entorhinal grid cells, as well as the replay of neural spiking activity during waking and sleep. Efforts to implement these abstract models in more detailed biophysical compartmental simulations raise specific issues that could be addressed in larger scale population models incorporating mechanisms of inhibition. PMID:19656654

Theta frequency background tunes transmission but not summation of spiking responses.

PubMed

Parameshwaran, Dhanya; Bhalla, Upinder S

2013-01-01

Hippocampal neurons are known to fire as a function of frequency and phase of spontaneous network rhythms, associated with the animal's behaviour. This dependence is believed to give rise to precise rate and temporal codes. However, it is not well understood how these periodic membrane potential fluctuations affect the integration of synaptic inputs. Here we used sinusoidal current injection to the soma of CA1 pyramidal neurons in the rat brain slice to simulate background oscillations in the physiologically relevant theta and gamma frequency range. We used a detailed compartmental model to show that somatic current injection gave comparable results to more physiological synaptically driven theta rhythms incorporating excitatory input in the dendrites, and inhibitory input near the soma. We systematically varied the phase of synaptic inputs with respect to this background, and recorded changes in response and summation properties of CA1 neurons using whole-cell patch recordings. The response of the cell was dependent on both the phase of synaptic inputs and frequency of the background input. The probability of the cell spiking for a given synaptic input was up to 40% greater during the depolarized phases between 30-135 degrees of theta frequency current injection. Summation gain on the other hand, was not affected either by the background frequency or the phasic afferent inputs. This flat summation gain, coupled with the enhanced spiking probability during depolarized phases of the theta cycle, resulted in enhanced transmission of summed inputs during the same phase window of 30-135 degrees. Overall, our study suggests that although oscillations provide windows of opportunity to selectively boost transmission and EPSP size, summation of synaptic inputs remains unaffected during membrane oscillations.

Correlated variability modifies working memory fidelity in primate prefrontal neuronal ensembles

PubMed Central

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

Voltage-dependent K+ channels improve the energy efficiency of signalling in blowfly photoreceptors

PubMed Central

2017-01-01

Voltage-dependent conductances in many spiking neurons are tuned to reduce action potential energy consumption, so improving the energy efficiency of spike coding. However, the contribution of voltage-dependent conductances to the energy efficiency of analogue coding, by graded potentials in dendrites and non-spiking neurons, remains unclear. We investigate the contribution of voltage-dependent conductances to the energy efficiency of analogue coding by modelling blowfly R1-6 photoreceptor membrane. Two voltage-dependent delayed rectifier K+ conductances (DRs) shape the membrane's voltage response and contribute to light adaptation. They make two types of energy saving. By reducing membrane resistance upon depolarization they convert the cheap, low bandwidth membrane needed in dim light to the expensive high bandwidth membrane needed in bright light. This investment of energy in bandwidth according to functional requirements can halve daily energy consumption. Second, DRs produce negative feedback that reduces membrane impedance and increases bandwidth. This negative feedback allows an active membrane with DRs to consume at least 30% less energy than a passive membrane with the same capacitance and bandwidth. Voltage-dependent conductances in other non-spiking neurons, and in dendrites, might be organized to make similar savings. PMID:28381642

Voltage-dependent K+ channels improve the energy efficiency of signalling in blowfly photoreceptors.

PubMed

Heras, Francisco J H; Anderson, John; Laughlin, Simon B; Niven, Jeremy E

2017-04-01

Voltage-dependent conductances in many spiking neurons are tuned to reduce action potential energy consumption, so improving the energy efficiency of spike coding. However, the contribution of voltage-dependent conductances to the energy efficiency of analogue coding, by graded potentials in dendrites and non-spiking neurons, remains unclear. We investigate the contribution of voltage-dependent conductances to the energy efficiency of analogue coding by modelling blowfly R1-6 photoreceptor membrane. Two voltage-dependent delayed rectifier K + conductances (DRs) shape the membrane's voltage response and contribute to light adaptation. They make two types of energy saving. By reducing membrane resistance upon depolarization they convert the cheap, low bandwidth membrane needed in dim light to the expensive high bandwidth membrane needed in bright light. This investment of energy in bandwidth according to functional requirements can halve daily energy consumption. Second, DRs produce negative feedback that reduces membrane impedance and increases bandwidth. This negative feedback allows an active membrane with DRs to consume at least 30% less energy than a passive membrane with the same capacitance and bandwidth. Voltage-dependent conductances in other non-spiking neurons, and in dendrites, might be organized to make similar savings. © 2017 The Author(s).

Phasic and tonic neuron ensemble codes for stimulus-environment conjunctions in the lateral entorhinal cortex.

PubMed

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.

Activity-Dependent Human Brain Coding/Noncoding Gene Regulatory Networks

PubMed Central

Lipovich, Leonard; Dachet, Fabien; Cai, Juan; Bagla, Shruti; Balan, Karina; Jia, Hui; Loeb, Jeffrey A.

2012-01-01

While most gene transcription yields RNA transcripts that code for proteins, a sizable proportion of the genome generates RNA transcripts that do not code for proteins, but may have important regulatory functions. The brain-derived neurotrophic factor (BDNF) gene, a key regulator of neuronal activity, is overlapped by a primate-specific, antisense long noncoding RNA (lncRNA) called BDNFOS. We demonstrate reciprocal patterns of BDNF and BDNFOS transcription in highly active regions of human neocortex removed as a treatment for intractable seizures. A genome-wide analysis of activity-dependent coding and noncoding human transcription using a custom lncRNA microarray identified 1288 differentially expressed lncRNAs, of which 26 had expression profiles that matched activity-dependent coding genes and an additional 8 were adjacent to or overlapping with differentially expressed protein-coding genes. The functions of most of these protein-coding partner genes, such as ARC, include long-term potentiation, synaptic activity, and memory. The nuclear lncRNAs NEAT1, MALAT1, and RPPH1, composing an RNAse P-dependent lncRNA-maturation pathway, were also upregulated. As a means to replicate human neuronal activity, repeated depolarization of SY5Y cells resulted in sustained CREB activation and produced an inverse pattern of BDNF-BDNFOS co-expression that was not achieved with a single depolarization. RNAi-mediated knockdown of BDNFOS in human SY5Y cells increased BDNF expression, suggesting that BDNFOS directly downregulates BDNF. Temporal expression patterns of other lncRNA-messenger RNA pairs validated the effect of chronic neuronal activity on the transcriptome and implied various lncRNA regulatory mechanisms. lncRNAs, some of which are unique to primates, thus appear to have potentially important regulatory roles in activity-dependent human brain plasticity. PMID:22960213

Fly Photoreceptors Encode Phase Congruency

PubMed Central

Friederich, Uwe; Billings, Stephen A.; Hardie, Roger C.; Juusola, Mikko; Coca, Daniel

2016-01-01

More than five decades ago it was postulated that sensory neurons detect and selectively enhance behaviourally relevant features of natural signals. Although we now know that sensory neurons are tuned to efficiently encode natural stimuli, until now it was not clear what statistical features of the stimuli they encode and how. Here we reverse-engineer the neural code of Drosophila photoreceptors and show for the first time that photoreceptors exploit nonlinear dynamics to selectively enhance and encode phase-related features of temporal stimuli, such as local phase congruency, which are invariant to changes in illumination and contrast. We demonstrate that to mitigate for the inherent sensitivity to noise of the local phase congruency measure, the nonlinear coding mechanisms of the fly photoreceptors are tuned to suppress random phase signals, which explains why photoreceptor responses to naturalistic stimuli are significantly different from their responses to white noise stimuli. PMID:27336733

Emphasis of spatial cues in the temporal fine structure during the rising segments of amplitude-modulated sounds II: single-neuron recordings

PubMed Central

Marquardt, Torsten; Stange, Annette; Pecka, Michael; Grothe, Benedikt; McAlpine, David

2014-01-01

Recently, with the use of an amplitude-modulated binaural beat (AMBB), in which sound amplitude and interaural-phase difference (IPD) were modulated with a fixed mutual relationship (Dietz et al. 2013b), we demonstrated that the human auditory system uses interaural timing differences in the temporal fine structure of modulated sounds only during the rising portion of each modulation cycle. However, the degree to which peripheral or central mechanisms contribute to the observed strong dominance of the rising slope remains to be determined. Here, by recording responses of single neurons in the medial superior olive (MSO) of anesthetized gerbils and in the inferior colliculus (IC) of anesthetized guinea pigs to AMBBs, we report a correlation between the position within the amplitude-modulation (AM) cycle generating the maximum response rate and the position at which the instantaneous IPD dominates the total neural response. The IPD during the rising segment dominates the total response in 78% of MSO neurons and 69% of IC neurons, with responses of the remaining neurons predominantly coding the IPD around the modulation maximum. The observed diversity of dominance regions within the AM cycle, especially in the IC, and its comparison with the human behavioral data suggest that only the subpopulation of neurons with rising slope dominance codes the sound-source location in complex listening conditions. A comparison of two models to account for the data suggests that emphasis on IPDs during the rising slope of the AM cycle depends on adaptation processes occurring before binaural interaction. PMID:24554782

Large‐scale analysis reveals populational contributions of cortical spike rate and synchrony to behavioural functions

PubMed Central

Saiki, Akiko; Fujiwara‐Tsukamoto, Yoko; Sakai, Yutaka; Isomura, Yoshikazu

2016-01-01

Key points There have been few systematic population‐wide analyses of relationships between spike synchrony within a period of several milliseconds and behavioural functions.In this study, we obtained a large amount of spike data from > 23,000 neuron pairs by multiple single‐unit recording from deep layer neurons in motor cortical areas in rats performing a forelimb movement task.The temporal changes of spike synchrony in the whole neuron pairs were statistically independent of behavioural changes during the task performance, although some neuron pairs exhibited correlated changes in spike synchrony.Mutual information analyses revealed that spike synchrony made a smaller contribution than spike rate to behavioural functions.The strength of spike synchrony between two neurons was statistically independent of the spike rate‐based preferences of the pair for behavioural functions. Abstract Spike synchrony within a period of several milliseconds in presynaptic neurons enables effective integration of functional information in the postsynaptic neuron. However, few studies have systematically analysed the population‐wide relationships between spike synchrony and behavioural functions. Here we obtained a sufficiently large amount of spike data among regular‐spiking (putatively excitatory) and fast‐spiking (putatively inhibitory) neuron subtypes (> 23,000 pairs) by multiple single‐unit recording from deep layers in motor cortical areas (caudal forelimb area, rostral forelimb area) in rats performing a forelimb movement task. After holding a lever, rats pulled the lever either in response to a cue tone (external‐trigger trials) or spontaneously without any cue (internal‐trigger trials). Many neurons exhibited functional spike activity in association with forelimb movements, and the preference of regular‐spiking neurons in the rostral forelimb area was more biased toward externally triggered movement than that in the caudal forelimb area. We found that a population of neuron pairs with spike synchrony does exist, and that some neuron pairs exhibit a dependence on movement phase during task performance. However, the population‐wide analysis revealed that spike synchrony was statistically independent of the movement phase and the spike rate‐based preferences of the pair for behavioural functions, whereas spike rates were clearly dependent on the movement phase. In fact, mutual information analyses revealed that the contribution of spike synchrony to the behavioural functions was small relative to the contribution of spike rate. Our large‐scale analysis revealed that cortical spike rate, rather than spike synchrony, contributes to population coding for movement. PMID:27488936

Large-scale analysis reveals populational contributions of cortical spike rate and synchrony to behavioural functions.

PubMed

Kimura, Rie; Saiki, Akiko; Fujiwara-Tsukamoto, Yoko; Sakai, Yutaka; Isomura, Yoshikazu

2017-01-01

There have been few systematic population-wide analyses of relationships between spike synchrony within a period of several milliseconds and behavioural functions. In this study, we obtained a large amount of spike data from > 23,000 neuron pairs by multiple single-unit recording from deep layer neurons in motor cortical areas in rats performing a forelimb movement task. The temporal changes of spike synchrony in the whole neuron pairs were statistically independent of behavioural changes during the task performance, although some neuron pairs exhibited correlated changes in spike synchrony. Mutual information analyses revealed that spike synchrony made a smaller contribution than spike rate to behavioural functions. The strength of spike synchrony between two neurons was statistically independent of the spike rate-based preferences of the pair for behavioural functions. Spike synchrony within a period of several milliseconds in presynaptic neurons enables effective integration of functional information in the postsynaptic neuron. However, few studies have systematically analysed the population-wide relationships between spike synchrony and behavioural functions. Here we obtained a sufficiently large amount of spike data among regular-spiking (putatively excitatory) and fast-spiking (putatively inhibitory) neuron subtypes (> 23,000 pairs) by multiple single-unit recording from deep layers in motor cortical areas (caudal forelimb area, rostral forelimb area) in rats performing a forelimb movement task. After holding a lever, rats pulled the lever either in response to a cue tone (external-trigger trials) or spontaneously without any cue (internal-trigger trials). Many neurons exhibited functional spike activity in association with forelimb movements, and the preference of regular-spiking neurons in the rostral forelimb area was more biased toward externally triggered movement than that in the caudal forelimb area. We found that a population of neuron pairs with spike synchrony does exist, and that some neuron pairs exhibit a dependence on movement phase during task performance. However, the population-wide analysis revealed that spike synchrony was statistically independent of the movement phase and the spike rate-based preferences of the pair for behavioural functions, whereas spike rates were clearly dependent on the movement phase. In fact, mutual information analyses revealed that the contribution of spike synchrony to the behavioural functions was small relative to the contribution of spike rate. Our large-scale analysis revealed that cortical spike rate, rather than spike synchrony, contributes to population coding for movement. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Stable and Dynamic Coding for Working Memory in Primate Prefrontal Cortex

PubMed Central

Watanabe, Kei; Funahashi, Shintaro; Stokes, Mark G.

2017-01-01

Working memory (WM) provides the stability necessary for high-level cognition. Influential theories typically assume that WM depends on the persistence of stable neural representations, yet increasing evidence suggests that neural states are highly dynamic. Here we apply multivariate pattern analysis to explore the population dynamics in primate lateral prefrontal cortex (PFC) during three variants of the classic memory-guided saccade task (recorded in four animals). We observed the hallmark of dynamic population coding across key phases of a working memory task: sensory processing, memory encoding, and response execution. Throughout both these dynamic epochs and the memory delay period, however, the neural representational geometry remained stable. We identified two characteristics that jointly explain these dynamics: (1) time-varying changes in the subpopulation of neurons coding for task variables (i.e., dynamic subpopulations); and (2) time-varying selectivity within neurons (i.e., dynamic selectivity). These results indicate that even in a very simple memory-guided saccade task, PFC neurons display complex dynamics to support stable representations for WM. SIGNIFICANCE STATEMENT Flexible, intelligent behavior requires the maintenance and manipulation of incoming information over various time spans. For short time spans, this faculty is labeled “working memory” (WM). Dominant models propose that WM is maintained by stable, persistent patterns of neural activity in prefrontal cortex (PFC). However, recent evidence suggests that neural activity in PFC is dynamic, even while the contents of WM remain stably represented. Here, we explored the neural dynamics in PFC during a memory-guided saccade task. We found evidence for dynamic population coding in various task epochs, despite striking stability in the neural representational geometry of WM. Furthermore, we identified two distinct cellular mechanisms that contribute to dynamic population coding. PMID:28559375

Predicting spike occurrence and neuronal responsiveness from LFPs in primary somatosensory cortex.

PubMed

Storchi, Riccardo; Zippo, Antonio G; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E M

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neuronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role.

Correlated neuronal discharges that increase coding efficiency during perceptual discrimination.

PubMed

Romo, Ranulfo; Hernández, Adrián; Zainos, Antonio; Salinas, Emilio

2003-05-22

During a sensory discrimination task, the responses of multiple sensory neurons must be combined to generate a choice. The optimal combination of responses is determined both by their dependence on the sensory stimulus and by their cofluctuations across trials-that is, the noise correlations. Positively correlated noise is considered deleterious, because it limits the coding accuracy of populations of similarly tuned neurons. However, positively correlated fluctuations between differently tuned neurons actually increase coding accuracy, because they allow the common noise to be subtracted without signal loss. This is demonstrated with data recorded from the secondary somatosensory cortex of monkeys performing a vibrotactile discrimination task. The results indicate that positive correlations are not always harmful and may be exploited by cortical networks to enhance the neural representation of features to be discriminated.

Neural dynamics and information representation in microcircuits of motor cortex.

PubMed

Tsubo, Yasuhiro; Isomura, Yoshikazu; Fukai, Tomoki

2013-01-01

The brain has to analyze and respond to external events that can change rapidly from time to time, suggesting that information processing by the brain may be essentially dynamic rather than static. The dynamical features of neural computation are of significant importance in motor cortex that governs the process of movement generation and learning. In this paper, we discuss these features based primarily on our recent findings on neural dynamics and information coding in the microcircuit of rat motor cortex. In fact, cortical neurons show a variety of dynamical behavior from rhythmic activity in various frequency bands to highly irregular spike firing. Of particular interest are the similarity and dissimilarity of the neuronal response properties in different layers of motor cortex. By conducting electrophysiological recordings in slice preparation, we report the phase response curves (PRCs) of neurons in different cortical layers to demonstrate their layer-dependent synchronization properties. We then study how motor cortex recruits task-related neurons in different layers for voluntary arm movements by simultaneous juxtacellular and multiunit recordings from behaving rats. The results suggest an interesting difference in the spectrum of functional activity between the superficial and deep layers. Furthermore, the task-related activities recorded from various layers exhibited power law distributions of inter-spike intervals (ISIs), in contrast to a general belief that ISIs obey Poisson or Gamma distributions in cortical neurons. We present a theoretical argument that this power law of in vivo neurons may represent the maximization of the entropy of firing rate with limited energy consumption of spike generation. Though further studies are required to fully clarify the functional implications of this coding principle, it may shed new light on information representations by neurons and circuits in motor cortex.

The Effect of Inhibitory Neuron on the Evolution Model of Higher-Order Coupling Neural Oscillator Population

PubMed Central

Qi, Yi; Wang, Rubin; Jiao, Xianfa; Du, Ying

2014-01-01

We proposed a higher-order coupling neural network model including the inhibitory neurons and examined the dynamical evolution of average number density and phase-neural coding under the spontaneous activity and external stimulating condition. The results indicated that increase of inhibitory coupling strength will cause decrease of average number density, whereas increase of excitatory coupling strength will cause increase of stable amplitude of average number density. Whether the neural oscillator population is able to enter the new synchronous oscillation or not is determined by excitatory and inhibitory coupling strength. In the presence of external stimulation, the evolution of the average number density is dependent upon the external stimulation and the coupling term in which the dominator will determine the final evolution. PMID:24516505

Stimulus features coded by single neurons of a macaque body category selective patch.

PubMed

Popivanov, Ivo D; Schyns, Philippe G; Vogels, Rufin

2016-04-26

Body category-selective regions of the primate temporal cortex respond to images of bodies, but it is unclear which fragments of such images drive single neurons' responses in these regions. Here we applied the Bubbles technique to the responses of single macaque middle superior temporal sulcus (midSTS) body patch neurons to reveal the image fragments the neurons respond to. We found that local image fragments such as extremities (limbs), curved boundaries, and parts of the torso drove the large majority of neurons. Bubbles revealed the whole body in only a few neurons. Neurons coded the features in a manner that was tolerant to translation and scale changes. Most image fragments were excitatory but for a few neurons both inhibitory and excitatory fragments (opponent coding) were present in the same image. The fragments we reveal here in the body patch with Bubbles differ from those suggested in previous studies of face-selective neurons in face patches. Together, our data indicate that the majority of body patch neurons respond to local image fragments that occur frequently, but not exclusively, in bodies, with a coding that is tolerant to translation and scale. Overall, the data suggest that the body category selectivity of the midSTS body patch depends more on the feature statistics of bodies (e.g., extensions occur more frequently in bodies) than on semantics (bodies as an abstract category).

The neuronal encoding of information in the brain.

PubMed

Rolls, Edmund T; Treves, Alessandro

2011-11-01

We describe the results of quantitative information theoretic analyses of neural encoding, particularly in the primate visual, olfactory, taste, hippocampal, and orbitofrontal cortex. Most of the information turns out to be encoded by the firing rates of the neurons, that is by the number of spikes in a short time window. This has been shown to be a robust code, for the firing rate representations of different neurons are close to independent for small populations of neurons. Moreover, the information can be read fast from such encoding, in as little as 20 ms. In quantitative information theoretic studies, only a little additional information is available in temporal encoding involving stimulus-dependent synchronization of different neurons, or the timing of spikes within the spike train of a single neuron. Feature binding appears to be solved by feature combination neurons rather than by temporal synchrony. The code is sparse distributed, with the spike firing rate distributions close to exponential or gamma. A feature of the code is that it can be read by neurons that take a synaptically weighted sum of their inputs. This dot product decoding is biologically plausible. Understanding the neural code is fundamental to understanding not only how the cortex represents, but also processes, information. Copyright © 2011 Elsevier Ltd. All rights reserved.

Phasic and tonic neuron ensemble codes for stimulus-environment conjunctions in the lateral entorhinal cortex

PubMed Central

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

Sensory and Working Memory Representations of Small and Large Numerosities in the Crow Endbrain.

PubMed

Ditz, Helen M; Nieder, Andreas

2016-11-23

Neurons in the avian nidopallium caudolaterale (NCL), an endbrain structure that originated independently from the mammalian neocortex, process visual numerosities. To clarify the code for number in this anatomically distinct endbrain area in birds, neuronal responses to a broad range of numerosities were analyzed. We recorded single-neuron activity from the NCL of crows performing a delayed match-to-sample task with visual numerosities as discriminanda. The responses of >20% of randomly selected neurons were modulated significantly by numerosities ranging from one to 30 items. Numerosity-selective neurons showed bell-shaped tuning curves with one of the presented numerosities as preferred numerosity regardless of the physical appearance of the items. The resulting labeled-line code exhibited logarithmic compression obeying the Weber-Fechner law for magnitudes. Comparable proportions of selective neurons were found, not only during stimulus presentation, but also in the delay phase, indicating a dominant role of the NCL in numerical working memory. Both during sensory encoding and memorization of numerosities in working memory, NCL activity predicted the crows' number discrimination performance. These neuronal data reveal striking similarities across vertebrate taxa in their code for number despite convergently evolved and anatomically distinct endbrain structures. Birds are known for their capabilities to process numerical quantity. However, birds lack a six-layered neocortex that enables primates with numerical competence. We aimed to decipher the neuronal code for numerical quantity in the independently and distinctly evolved endbrain of birds. We recorded the activity of neurons in an endbrain association area termed nidopallium caudolaterale (NCL) from crows that assessed and briefly memorized numerosities from one to 30 dots. We report a neuronal code for sensory representation and working memory of numerosities in the crow NCL exhibiting several characteristics that are surprisingly similar to the ones found in primates. Our data suggest a common code for number in two different vertebrate taxa that has evolved based on convergent evolution. Copyright © 2016 the authors 0270-6474/16/3612044-09$15.00/0.

Nonspatial Sequence Coding in CA1 Neurons

PubMed Central

Allen, Timothy A.; Salz, Daniel M.; McKenzie, Sam

2016-01-01

The hippocampus is critical to the memory for sequences of events, a defining feature of episodic memory. However, the fundamental neuronal mechanisms underlying this capacity remain elusive. While considerable research indicates hippocampal neurons can represent sequences of locations, direct evidence of coding for the memory of sequential relationships among nonspatial events remains lacking. To address this important issue, we recorded neural activity in CA1 as rats performed a hippocampus-dependent sequence-memory task. Briefly, the task involves the presentation of repeated sequences of odors at a single port and requires rats to identify each item as “in sequence” or “out of sequence”. We report that, while the animals' location and behavior remained constant, hippocampal activity differed depending on the temporal context of items—in this case, whether they were presented in or out of sequence. Some neurons showed this effect across items or sequence positions (general sequence cells), while others exhibited selectivity for specific conjunctions of item and sequence position information (conjunctive sequence cells) or for specific probe types (probe-specific sequence cells). We also found that the temporal context of individual trials could be accurately decoded from the activity of neuronal ensembles, that sequence coding at the single-cell and ensemble level was linked to sequence memory performance, and that slow-gamma oscillations (20–40 Hz) were more strongly modulated by temporal context and performance than theta oscillations (4–12 Hz). These findings provide compelling evidence that sequence coding extends beyond the domain of spatial trajectories and is thus a fundamental function of the hippocampus. SIGNIFICANCE STATEMENT The ability to remember the order of life events depends on the hippocampus, but the underlying neural mechanisms remain poorly understood. Here we addressed this issue by recording neural activity in hippocampal region CA1 while rats performed a nonspatial sequence memory task. We found that hippocampal neurons code for the temporal context of items (whether odors were presented in the correct or incorrect sequential position) and that this activity is linked with memory performance. The discovery of this novel form of temporal coding in hippocampal neurons advances our fundamental understanding of the neurobiology of episodic memory and will serve as a foundation for our cross-species, multitechnique approach aimed at elucidating the neural mechanisms underlying memory impairments in aging and dementia. PMID:26843637

The opponent channel population code of sound location is an efficient representation of natural binaural sounds.

PubMed

Młynarski, Wiktor

2015-05-01

In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a "panoramic" code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding.

Neural noise and movement-related codes in the macaque supplementary motor area.

PubMed

Averbeck, Bruno B; Lee, Daeyeol

2003-08-20

We analyzed the variability of spike counts and the coding capacity of simultaneously recorded pairs of neurons in the macaque supplementary motor area (SMA). We analyzed the mean-variance functions for single neurons, as well as signal and noise correlations between pairs of neurons. All three statistics showed a strong dependence on the bin width chosen for analysis. Changes in the correlation structure of single neuron spike trains over different bin sizes affected the mean-variance function, and signal and noise correlations between pairs of neurons were much smaller at small bin widths, increasing monotonically with the width of the bin. Analyses in the frequency domain showed that the noise between pairs of neurons, on average, was most strongly correlated at low frequencies, which explained the increase in noise correlation with increasing bin width. The coding performance was analyzed to determine whether the temporal precision of spike arrival times and the interactions within and between neurons could improve the prediction of the upcoming movement. We found that in approximately 62% of neuron pairs, the arrival times of spikes at a resolution between 66 and 40 msec carried more information than spike counts in a 200 msec bin. In addition, in 19% of neuron pairs, inclusion of within (11%)- or between-neuron (8%) correlations in spike trains improved decoding accuracy. These results suggest that in some SMA neurons elements of the spatiotemporal pattern of activity may be relevant for neural coding.

State Dependency of Chemosensory Coding in the Gustatory Thalamus (VPMpc) of Alert Rats

PubMed Central

Liu, Haixin

2015-01-01

The parvicellular portion of the ventroposteromedial nucleus (VPMpc) is the part of the thalamus that processes gustatory information. Anatomical evidence shows that the VPMpc receives ascending gustatory inputs from the parabrachial nucleus (PbN) in the brainstem and sends projections to the gustatory cortex (GC). Although taste processing in PbN and GC has been the subject of intense investigation in behaving rodents, much less is known on how VPMpc neurons encode gustatory information. Here we present results from single-unit recordings in the VPMpc of alert rats receiving multiple tastants. Thalamic neurons respond to taste with time-varying modulations of firing rates, consistent with those observed in GC and PbN. These responses encode taste quality as well as palatability. Comparing responses to tastants either passively delivered, or self-administered after a cue, unveiled the effects of general expectation on taste processing in VPMpc. General expectation led to an improvement of taste coding by modulating response dynamics, and single neuron ability to encode multiple tastants. Our results demonstrate that the time course of taste coding as well as single neurons' ability to encode for multiple qualities are not fixed but rather can be altered by the state of the animal. Together, the data presented here provide the first description that taste coding in VPMpc is dynamic and state-dependent. SIGNIFICANCE STATEMENT Over the past years, a great deal of attention has been devoted to understanding taste coding in the brainstem and cortex of alert rodents. Thanks to this research, we now know that taste coding is dynamic, distributed, and context-dependent. Alas, virtually nothing is known on how the gustatory thalamus (VPMpc) processes gustatory information in behaving rats. This manuscript investigates taste processing in the VPMpc of behaving rats. Our results show that thalamic neurons encode taste and palatability with time-varying patterns of activity and that thalamic coding of taste is modulated by general expectation. Our data will appeal not only to researchers interested in taste, but also to a broader audience of sensory and systems neuroscientists interested in the thalamocortical system. PMID:26609147

Incorporating spike-rate adaptation into a rate code in mathematical and biological neurons

PubMed Central

Ralston, Bridget N.; Flagg, Lucas Q.; Faggin, Eric

2016-01-01

For a slowly varying stimulus, the simplest relationship between a neuron's input and output is a rate code, in which the spike rate is a unique function of the stimulus at that instant. In the case of spike-rate adaptation, there is no unique relationship between input and output, because the spike rate at any time depends both on the instantaneous stimulus and on prior spiking (the “history”). To improve the decoding of spike trains produced by neurons that show spike-rate adaptation, we developed a simple scheme that incorporates “history” into a rate code. We utilized this rate-history code successfully to decode spike trains produced by 1) mathematical models of a neuron in which the mechanism for adaptation (IAHP) is specified, and 2) the gastropyloric receptor (GPR2), a stretch-sensitive neuron in the stomatogastric nervous system of the crab Cancer borealis, that exhibits long-lasting adaptation of unknown origin. Moreover, when we modified the spike rate either mathematically in a model system or by applying neuromodulatory agents to the experimental system, we found that changes in the rate-history code could be related to the biophysical mechanisms responsible for altering the spiking. PMID:26888106

Stimulus features coded by single neurons of a macaque body category selective patch

PubMed Central

Popivanov, Ivo D.; Schyns, Philippe G.; Vogels, Rufin

2016-01-01

Body category-selective regions of the primate temporal cortex respond to images of bodies, but it is unclear which fragments of such images drive single neurons’ responses in these regions. Here we applied the Bubbles technique to the responses of single macaque middle superior temporal sulcus (midSTS) body patch neurons to reveal the image fragments the neurons respond to. We found that local image fragments such as extremities (limbs), curved boundaries, and parts of the torso drove the large majority of neurons. Bubbles revealed the whole body in only a few neurons. Neurons coded the features in a manner that was tolerant to translation and scale changes. Most image fragments were excitatory but for a few neurons both inhibitory and excitatory fragments (opponent coding) were present in the same image. The fragments we reveal here in the body patch with Bubbles differ from those suggested in previous studies of face-selective neurons in face patches. Together, our data indicate that the majority of body patch neurons respond to local image fragments that occur frequently, but not exclusively, in bodies, with a coding that is tolerant to translation and scale. Overall, the data suggest that the body category selectivity of the midSTS body patch depends more on the feature statistics of bodies (e.g., extensions occur more frequently in bodies) than on semantics (bodies as an abstract category). PMID:27071095

Biophysical Insights into How Spike Threshold Depends on the Rate of Membrane Potential Depolarization in Type I and Type II Neurons

PubMed Central

Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin

2015-01-01

Dynamic spike threshold plays a critical role in neuronal input-output relations. In many neurons, the threshold potential depends on the rate of membrane potential depolarization (dV/dt) preceding a spike. There are two basic classes of neural excitability, i.e., Type I and Type II, according to input-output properties. Although the dynamical and biophysical basis of their spike initiation has been established, the spike threshold dynamic for each cell type has not been well described. Here, we use a biophysical model to investigate how spike threshold depends on dV/dt in two types of neuron. It is observed that Type II spike threshold is more depolarized and more sensitive to dV/dt than Type I. With phase plane analysis, we show that each threshold dynamic arises from the different separatrix and K+ current kinetics. By analyzing subthreshold properties of membrane currents, we find the activation of hyperpolarizing current prior to spike initiation is a major factor that regulates the threshold dynamics. The outward K+ current in Type I neuron does not activate at the perithresholds, which makes its spike threshold insensitive to dV/dt. The Type II K+ current activates prior to spike initiation and there is a large net hyperpolarizing current at the perithresholds, which results in a depolarized threshold as well as a pronounced threshold dynamic. These predictions are further attested in several other functionally equivalent cases of neural excitability. Our study provides a fundamental description about how intrinsic biophysical properties contribute to the threshold dynamics in Type I and Type II neurons, which could decipher their significant functions in neural coding. PMID:26083350

A Novel RNA Editing Sensor Tool and a Specific Agonist Determine Neuronal Protein Expression of RNA-Edited Glycine Receptors and Identify a Genomic APOBEC1 Dimorphism as a New Genetic Risk Factor of Epilepsy

PubMed Central

Kankowski, Svenja; Förstera, Benjamin; Winkelmann, Aline; Knauff, Pina; Wanker, Erich E.; You, Xintian A.; Semtner, Marcus; Hetsch, Florian; Meier, Jochen C.

2018-01-01

C-to-U RNA editing of glycine receptors (GlyR) can play an important role in disease progression of temporal lobe epilepsy (TLE) as it may contribute in a neuron type-specific way to neuropsychiatric symptoms of the disease. It is therefore necessary to develop tools that allow identification of neuron types that express RNA-edited GlyR protein. In this study, we identify NH4 as agonist of C-to-U RNA edited GlyRs. Furthermore, we generated a new molecular C-to-U RNA editing sensor tool that detects Apobec-1- dependent RNA editing in HEPG2 cells and rat primary hippocampal neurons. Using this sensor combined with NH4 application, we were able to identify C-to-U RNA editing-competent neurons and expression of C-to-U RNA-edited GlyR protein in neurons. Bioinformatic analysis of 1,000 Genome Project Phase 3 allele frequencies coding for human Apobec-1 80M and 80I variants showed differences between populations, and the results revealed a preference of the 80I variant to generate RNA-edited GlyR protein. Finally, we established a new PCR-based restriction fragment length polymorphism (RFLP) approach to profile mRNA expression with regard to the genetic APOBEC1 dimorphism of patients with intractable temporal lobe epilepsy (iTLE) and found that the patients fall into two groups. Patients with expression of the Apobec-1 80I variant mostly suffered from simple or complex partial seizures, whereas patients with 80M expression exhibited secondarily generalized seizure activity. Thus, our method allows the characterization of Apobec-1 80M and 80l variants in the brain and provides a new way to epidemiologically and semiologically classify iTLE according to the two different APOBEC1 alleles. Together, these results demonstrate Apobec-1-dependent expression of RNA-edited GlyR protein in neurons and identify the APOBEC1 80I/M-coding alleles as new genetic risk factors for iTLE patients. PMID:29375302

Tonic nanomolar dopamine enables an activity-dependent phase recovery mechanism that persistently alters the maximal conductance of the hyperpolarization-activated current in a rhythmically active neuron.

PubMed

Rodgers, Edmund W; Fu, Jing Jing; Krenz, Wulf-Dieter C; Baro, Deborah J

2011-11-09

The phases at which network neurons fire in rhythmic motor outputs are critically important for the proper generation of motor behaviors. The pyloric network in the crustacean stomatogastric ganglion generates a rhythmic motor output wherein neuronal phase relationships are remarkably invariant across individuals and throughout lifetimes. The mechanisms for maintaining these robust phase relationships over the long-term are not well described. Here we show that tonic nanomolar dopamine (DA) acts at type 1 DA receptors (D1Rs) to enable an activity-dependent mechanism that can contribute to phase maintenance in the lateral pyloric (LP) neuron. The LP displays continuous rhythmic bursting. The activity-dependent mechanism was triggered by a prolonged decrease in LP burst duration, and it generated a persistent increase in the maximal conductance (G(max)) of the LP hyperpolarization-activated current (I(h)), but only in the presence of steady-state DA. Interestingly, micromolar DA produces an LP phase advance accompanied by a decrease in LP burst duration that abolishes normal LP network function. During a 1 h application of micromolar DA, LP phase recovered over tens of minutes because, the activity-dependent mechanism enabled by steady-state DA was triggered by the micromolar DA-induced decrease in LP burst duration. Presumably, this mechanism restored normal LP network function. These data suggest steady-state DA may enable homeostatic mechanisms that maintain motor network output during protracted neuromodulation. This DA-enabled, activity-dependent mechanism to preserve phase may be broadly relevant, as diminished dopaminergic tone has recently been shown to reduce I(h) in rhythmically active neurons in the mammalian brain.

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

PubMed Central

Storchi, Riccardo; Zippo, Antonio G.; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E. M.

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

Synchronization properties of heterogeneous neuronal networks with mixed excitability type

NASA Astrophysics Data System (ADS)

Leone, Michael J.; Schurter, Brandon N.; Letson, Benjamin; Booth, Victoria; Zochowski, Michal; Fink, Christian G.

2015-03-01

We study the synchronization of neuronal networks with dynamical heterogeneity, showing that network structures with the same propensity for synchronization (as quantified by master stability function analysis) may develop dramatically different synchronization properties when heterogeneity is introduced with respect to neuronal excitability type. Specifically, we investigate networks composed of neurons with different types of phase response curves (PRCs), which characterize how oscillating neurons respond to excitatory perturbations. Neurons exhibiting type 1 PRC respond exclusively with phase advances, while neurons exhibiting type 2 PRC respond with either phase delays or phase advances, depending on when the perturbation occurs. We find that Watts-Strogatz small world networks transition to synchronization gradually as the proportion of type 2 neurons increases, whereas scale-free networks may transition gradually or rapidly, depending upon local correlations between node degree and excitability type. Random placement of type 2 neurons results in gradual transition to synchronization, whereas placement of type 2 neurons as hubs leads to a much more rapid transition, showing that type 2 hub cells easily "hijack" neuronal networks to synchronization. These results underscore the fact that the degree of synchronization observed in neuronal networks is determined by a complex interplay between network structure and the dynamical properties of individual neurons, indicating that efforts to recover structural connectivity from dynamical correlations must in general take both factors into account.

Temporal coding of reward-guided choice in the posterior parietal cortex

PubMed Central

Hawellek, David J.; Wong, Yan T.; Pesaran, Bijan

2016-01-01

Making a decision involves computations across distributed cortical and subcortical networks. How such distributed processing is performed remains unclear. We test how the encoding of choice in a key decision-making node, the posterior parietal cortex (PPC), depends on the temporal structure of the surrounding population activity. We recorded spiking and local field potential (LFP) activity in the PPC while two rhesus macaques performed a decision-making task. We quantified the mutual information that neurons carried about an upcoming choice and its dependence on LFP activity. The spiking of PPC neurons was correlated with LFP phases at three distinct time scales in the theta, beta, and gamma frequency bands. Importantly, activity at these time scales encoded upcoming decisions differently. Choice information contained in neural firing varied with the phase of beta and gamma activity. For gamma activity, maximum choice information occurred at the same phase as the maximum spike count. However, for beta activity, choice information and spike count were greatest at different phases. In contrast, theta activity did not modulate the encoding properties of PPC units directly but was correlated with beta and gamma activity through cross-frequency coupling. We propose that the relative timing of local spiking and choice information reveals temporal reference frames for computations in either local or large-scale decision networks. Differences between the timing of task information and activity patterns may be a general signature of distributed processing across large-scale networks. PMID:27821752

Spatial cue reliability drives frequency tuning in the barn Owl's midbrain

PubMed Central

Cazettes, Fanny; Fischer, Brian J; Pena, Jose L

2014-01-01

The robust representation of the environment from unreliable sensory cues is vital for the efficient function of the brain. However, how the neural processing captures the most reliable cues is unknown. The interaural time difference (ITD) is the primary cue to localize sound in horizontal space. ITD is encoded in the firing rate of neurons that detect interaural phase difference (IPD). Due to the filtering effect of the head, IPD for a given location varies depending on the environmental context. We found that, in barn owls, at each location there is a frequency range where the head filtering yields the most reliable IPDs across contexts. Remarkably, the frequency tuning of space-specific neurons in the owl's midbrain varies with their preferred sound location, matching the range that carries the most reliable IPD. Thus, frequency tuning in the owl's space-specific neurons reflects a higher-order feature of the code that captures cue reliability. DOI: http://dx.doi.org/10.7554/eLife.04854.001 PMID:25531067

Non-redundant odor coding by sister mitral cells revealed by light addressable glomeruli in the mouse

PubMed Central

Dhawale, Ashesh K.; Hagiwara, Akari; Bhalla, Upinder S.; Murthy, Venkatesh N.; Albeanu, Dinu F.

2011-01-01

Sensory inputs frequently converge on the brain in a spatially organized manner, often with overlapping inputs to multiple target neurons. Whether the responses of target neurons with common inputs become decorrelated depends on the contribution of local circuit interactions. We addressed this issue in the olfactory system using newly generated transgenic mice expressing channelrhodopsin-2 in all olfactory sensory neurons. By selectively stimulating individual glomeruli with light, we identified mitral/tufted (M/T) cells that receive common input (sister cells). Sister M/T cells had highly correlated responses to odors as measured by average spike rates, but their spike timing in relation to respiration was differentially altered. In contrast, non-sister M/T cells correlated poorly on both these measures. We suggest that sister M/T cells carry two different channels of information: average activity representing shared glomerular input, and phase-specific information that refines odor representations and is substantially independent for sister M/T cells. PMID:20953197

Constructing Neuronal Network Models in Massively Parallel Environments.

PubMed

Ippen, Tammo; Eppler, Jochen M; Plesser, Hans E; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers.

Constructing Neuronal Network Models in Massively Parallel Environments

PubMed Central

Ippen, Tammo; Eppler, Jochen M.; Plesser, Hans E.; Diesmann, Markus

2017-01-01

Recent advances in the development of data structures to represent spiking neuron network models enable us to exploit the complete memory of petascale computers for a single brain-scale network simulation. In this work, we investigate how well we can exploit the computing power of such supercomputers for the creation of neuronal networks. Using an established benchmark, we divide the runtime of simulation code into the phase of network construction and the phase during which the dynamical state is advanced in time. We find that on multi-core compute nodes network creation scales well with process-parallel code but exhibits a prohibitively large memory consumption. Thread-parallel network creation, in contrast, exhibits speedup only up to a small number of threads but has little overhead in terms of memory. We further observe that the algorithms creating instances of model neurons and their connections scale well for networks of ten thousand neurons, but do not show the same speedup for networks of millions of neurons. Our work uncovers that the lack of scaling of thread-parallel network creation is due to inadequate memory allocation strategies and demonstrates that thread-optimized memory allocators recover excellent scaling. An analysis of the loop order used for network construction reveals that more complex tests on the locality of operations significantly improve scaling and reduce runtime by allowing construction algorithms to step through large networks more efficiently than in existing code. The combination of these techniques increases performance by an order of magnitude and harnesses the increasingly parallel compute power of the compute nodes in high-performance clusters and supercomputers. PMID:28559808

Phase precession through acceleration of local theta rhythm: a biophysical model for the interaction between place cells and local inhibitory neurons.

PubMed

Castro, Luísa; Aguiar, Paulo

2012-08-01

Phase precession is one of the most well known examples within the temporal coding hypothesis. Here we present a biophysical spiking model for phase precession in hippocampal CA1 which focuses on the interaction between place cells and local inhibitory interneurons. The model's functional block is composed of a place cell (PC) connected with a local inhibitory cell (IC) which is modulated by the population theta rhythm. Both cells receive excitatory inputs from the entorhinal cortex (EC). These inputs are both theta modulated and space modulated. The dynamics of the two neuron types are described by integrate-and-fire models with conductance synapses, and the EC inputs are described using non-homogeneous Poisson processes. Phase precession in our model is caused by increased drive to specific PC/IC pairs when the animal is in their place field. The excitation increases the IC's firing rate, and this modulates the PC's firing rate such that both cells precess relative to theta. Our model implies that phase coding in place cells may not be independent from rate coding. The absence of restrictive connectivity constraints in this model predicts the generation of phase precession in any network with similar architecture and subject to a clocking rhythm, independently of the involvement in spatial tasks.

[Multi-channel in vivo recording techniques: analysis of phase coupling between spikes and rhythmic oscillations of local field potentials].

PubMed

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.

The Opponent Channel Population Code of Sound Location Is an Efficient Representation of Natural Binaural Sounds

PubMed Central

Młynarski, Wiktor

2015-01-01

In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a “panoramic” code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding. PMID:25996373

Phase-locking of bursting neuronal firing to dominant LFP frequency components.

PubMed

Constantinou, Maria; Elijah, Daniel H; Squirrell, Daniel; Gigg, John; Montemurro, Marcelo A

2015-10-01

Neuronal firing in the hippocampal formation relative to the phase of local field potentials (LFP) has a key role in memory processing and spatial navigation. Firing can be in either tonic or burst mode. Although bursting neurons are common in the hippocampal formation, the characteristics of their locking to LFP phase are not completely understood. We investigated phase-locking properties of bursting neurons using simulations generated by a dual compartmental model of a pyramidal neuron adapted to match the bursting activity in the subiculum of a rat. The model was driven with stochastic input signals containing a power spectral profile consistent with physiologically relevant frequencies observed in LFP. The single spikes and spike bursts fired by the model were locked to a preferred phase of the predominant frequency band where there was a peak in the power of the driving signal. Moreover, the preferred phase of locking shifted with increasing burst size, providing evidence that LFP phase can be encoded by burst size. We also provide initial support for the model results by analysing example data of spontaneous LFP and spiking activity recorded from the subiculum of a single urethane-anaesthetised rat. Subicular neurons fired single spikes, two-spike bursts and larger bursts that locked to a preferred phase of either dominant slow oscillations or theta rhythms within the LFP, according to the model prediction. Both power-modulated phase-locking and gradual shift in the preferred phase of locking as a function of burst size suggest that neurons can use bursts to encode timing information contained in LFP phase into a spike-count code. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.

PubMed

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.

The Chronotron: A Neuron That Learns to Fire Temporally Precise Spike Patterns

PubMed Central

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

Odour intensity learning in fruit flies

PubMed Central

Yarali, Ayse; Ehser, Sabrina; Hapil, Fatma Zehra; Huang, Ju; Gerber, Bertram

2009-01-01

Animals' behaviour towards odours depends on both odour quality and odour intensity. While neuronal coding of odour quality is fairly well studied, how odour intensity is treated by olfactory systems is less clear. Here we study odour intensity processing at the behavioural level, using the fruit fly Drosophila melanogaster. We trained flies by pairing a MEDIUM intensity of an odour with electric shock, and then, at a following test phase, measured flies' conditioned avoidance of either this previously trained MEDIUM intensity or a LOWer or a HIGHer intensity. With respect to 3-octanol, n-amylacetate and 4-methylcyclohexanol, we found that conditioned avoidance is strongest when training and test intensities match, speaking for intensity-specific memories. With respect to a fourth odour, benzaldehyde, on the other hand, we found no such intensity specificity. These results form the basis for further studies of odour intensity processing at the behavioural, neuronal and molecular level. PMID:19586944

First-spike latency in Hodgkin's three classes of neurons.

PubMed

Wang, Hengtong; Chen, Yueling; Chen, Yong

2013-07-07

We study the first-spike latency (FSL) in Hodgkin's three classes of neurons with the Morris-Lecar neuron model. It is found that all the three classes of neurons can encode an external stimulus into FSLs. With DC inputs, the FSLs of all of the neurons decrease with input intensity. With input current decreased to the threshold, class 1 neurons show an arbitrary long FSL whereas class 2 and 3 neurons exhibit the short-limit FSLs. When the input current is sinusoidal, the amplitude, frequency and initial phase can be encoded by all the three classes of neurons. The FSLs of all of the neurons decrease with the input amplitude and frequency. When the input frequency is too high, all of the neurons respond with infinite FSLs. When the initial phase increases, the FSL decreases and then jumps to a maximal value and finally decreases linearly. With changes in the input parameters, the FSLs of the class 1 and 2 neurons exhibit similar properties. However, the FSL of the class 3 neurons became slightly longer and only produces responses for a narrow range of initial phase if input frequencies are low. Moreover, our results also show that the FSL and firing rate responses are mutually independent processes and that neurons can encode an external stimulus into different FSLs and firing rates simultaneously. This finding is consistent with the current theory of dual or multiple complementary coding mechanisms. Copyright © 2013 Elsevier Ltd. All rights reserved.

S phase entry causes homocysteine-induced death while ataxia telangiectasia and Rad3 related protein functions anti-apoptotically to protect neurons.

PubMed

Ye, Weizhen; Blain, Stacy W

2010-08-01

A major phenotype seen in neurodegenerative disorders is the selective loss of neurons due to apoptotic death and evidence suggests that inappropriate re-activation of cell cycle proteins in post-mitotic neurons may be responsible. To investigate whether reactivation of the G1 cell cycle proteins and S phase entry was linked with apoptosis, we examined homocysteine-induced neuronal cell death in a rat cortical neuron tissue culture system. Hyperhomocysteinaemia is a physiological risk factor for a variety of neurodegenerative diseases, including Alzheimer's disease. We found that in response to homocysteine treatment, cyclin D1, and cyclin-dependent kinases 4 and 2 translocated to the nucleus, and p27 levels decreased. Both cyclin-dependent kinases 4 and 2 regained catalytic activity, the G1 gatekeeper retinoblastoma protein was phosphorylated and DNA synthesis was detected, suggesting transit into S phase. Double-labelling immunofluorescence showed a 95% co-localization of anti-bromodeoxyuridine labelling with apoptotic markers, demonstrating that those cells that entered S phase eventually died. Neurons could be protected from homocysteine-induced death by methods that inhibited G1 phase progression, including down-regulation of cyclin D1 expression, inhibition of cyclin-dependent kinases 4 or 2 activity by small molecule inhibitors, or use of the c-Abl kinase inhibitor, Gleevec, which blocked cyclin D and cyclin-dependent kinase 4 nuclear translocation. However, blocking cell cycle progression post G1, using DNA replication inhibitors, did not prevent apoptosis, suggesting that death was not preventable post the G1-S phase checkpoint. While homocysteine treatment caused DNA damage and activated the DNA damage response, its mechanism of action was distinct from that of more traditional DNA damaging agents, such as camptothecin, as it was p53-independent. Likewise, inhibition of the DNA damage sensors, ataxia-telangiectasia mutant and ataxia telangiectasia and Rad3 related proteins, did not rescue apoptosis and in fact exacerbated death, suggesting that the DNA damage response might normally function neuroprotectively to block S phase-dependent apoptosis induction. As cell cycle events appear to be maintained in vivo in affected neurons for weeks to years before apoptosis is observed, activation of the DNA damage response might be able to hold cell cycle-induced death in check.

Timing and Causality in the Generation of Learned Eyelid Responses

PubMed Central

Sánchez-Campusano, Raudel; Gruart, Agnès; Delgado-García, José M.

2011-01-01

The cerebellum-red nucleus-facial motoneuron (Mn) pathway has been reported as being involved in the proper timing of classically conditioned eyelid responses. This special type of associative learning serves as a model of event timing for studying the role of the cerebellum in dynamic motor control. Here, we have re-analyzed the firing activities of cerebellar posterior interpositus (IP) neurons and orbicularis oculi (OO) Mns in alert behaving cats during classical eyeblink conditioning, using a delay paradigm. The aim was to revisit the hypothesis that the IP neurons (IPns) can be considered a neuronal phase-modulating device supporting OO Mns firing with an emergent timing mechanism and an explicit correlation code during learned eyelid movements. Optimized experimental and computational tools allowed us to determine the different causal relationships (temporal order and correlation code) during and between trials. These intra- and inter-trial timing strategies expanding from sub-second range (millisecond timing) to longer-lasting ranges (interval timing) expanded the functional domain of cerebellar timing beyond motor control. Interestingly, the results supported the above-mentioned hypothesis. The causal inferences were influenced by the precise motor and pre-motor spike timing in the cause-effect interval, and, in addition, the timing of the learned responses depended on cerebellar–Mn network causality. Furthermore, the timing of CRs depended upon the probability of simulated causal conditions in the cause-effect interval and not the mere duration of the inter-stimulus interval. In this work, the close relation between timing and causality was verified. It could thus be concluded that the firing activities of IPns may be related more to the proper performance of ongoing CRs (i.e., the proper timing as a consequence of the pertinent causality) than to their generation and/or initiation. PMID:21941469

Neural coding of sound envelope in reverberant environments.

PubMed

Slama, Michaël C C; Delgutte, Bertrand

2015-03-11

Speech reception depends critically on temporal modulations in the amplitude envelope of the speech signal. Reverberation encountered in everyday environments can substantially attenuate these modulations. To assess the effect of reverberation on the neural coding of amplitude envelope, we recorded from single units in the inferior colliculus (IC) of unanesthetized rabbit using sinusoidally amplitude modulated (AM) broadband noise stimuli presented in simulated anechoic and reverberant environments. Although reverberation degraded both rate and temporal coding of AM in IC neurons, in most neurons, the degradation in temporal coding was smaller than the AM attenuation in the stimulus. This compensation could largely be accounted for by the compressive shape of the modulation input-output function (MIOF), which describes the nonlinear transformation of modulation depth from acoustic stimuli into neural responses. Additionally, in a subset of neurons, the temporal coding of AM was better for reverberant stimuli than for anechoic stimuli having the same modulation depth at the ear. Using hybrid anechoic stimuli that selectively possess certain properties of reverberant sounds, we show that this reverberant advantage is not caused by envelope distortion, static interaural decorrelation, or spectral coloration. Overall, our results suggest that the auditory system may possess dual mechanisms that make the coding of amplitude envelope relatively robust in reverberation: one general mechanism operating for all stimuli with small modulation depths, and another mechanism dependent on very specific properties of reverberant stimuli, possibly the periodic fluctuations in interaural correlation at the modulation frequency. Copyright © 2015 the authors 0270-6474/15/354452-17$15.00/0.

Dnmt1-dependent Chk1 pathway suppression is protective against neuron division.

PubMed

Oshikawa, Mio; Okada, Kei; Tabata, Hidenori; Nagata, Koh-Ichi; Ajioka, Itsuki

2017-09-15

Neuronal differentiation and cell-cycle exit are tightly coordinated, even in pathological situations. When pathological neurons re-enter the cell cycle and progress through the S phase, they undergo cell death instead of division. However, the mechanisms underlying mitotic resistance are mostly unknown. Here, we have found that acute inactivation of retinoblastoma (Rb) family proteins (Rb, p107 and p130) in mouse postmitotic neurons leads to cell death after S-phase progression. Checkpoint kinase 1 (Chk1) pathway activation during the S phase prevented the cell death, and allowed the division of cortical neurons that had undergone acute Rb family inactivation, oxygen-glucose deprivation (OGD) or in vivo hypoxia-ischemia. During neurogenesis, cortical neurons became protected from S-phase Chk1 pathway activation by the DNA methyltransferase Dnmt1, and underwent cell death after S-phase progression. Our results indicate that Chk1 pathway activation overrides mitotic safeguards and uncouples neuronal differentiation from mitotic resistance. © 2017. Published by The Company of Biologists Ltd.

Decoding thalamic afferent input using microcircuit spiking activity

PubMed Central

Sederberg, Audrey J.; Palmer, Stephanie E.

2015-01-01

A behavioral response appropriate to a sensory stimulus depends on the collective activity of thousands of interconnected neurons. The majority of cortical connections arise from neighboring neurons, and thus understanding the cortical code requires characterizing information representation at the scale of the cortical microcircuit. Using two-photon calcium imaging, we densely sampled the thalamically evoked response of hundreds of neurons spanning multiple layers and columns in thalamocortical slices of mouse somatosensory cortex. We then used a biologically plausible decoder to characterize the representation of two distinct thalamic inputs, at the level of the microcircuit, to reveal those aspects of the activity pattern that are likely relevant to downstream neurons. Our data suggest a sparse code, distributed across lamina, in which a small population of cells carries stimulus-relevant information. Furthermore, we find that, within this subset of neurons, decoder performance improves when noise correlations are taken into account. PMID:25695647

Decoding thalamic afferent input using microcircuit spiking activity.

PubMed

Sederberg, Audrey J; Palmer, Stephanie E; MacLean, Jason N

2015-04-01

A behavioral response appropriate to a sensory stimulus depends on the collective activity of thousands of interconnected neurons. The majority of cortical connections arise from neighboring neurons, and thus understanding the cortical code requires characterizing information representation at the scale of the cortical microcircuit. Using two-photon calcium imaging, we densely sampled the thalamically evoked response of hundreds of neurons spanning multiple layers and columns in thalamocortical slices of mouse somatosensory cortex. We then used a biologically plausible decoder to characterize the representation of two distinct thalamic inputs, at the level of the microcircuit, to reveal those aspects of the activity pattern that are likely relevant to downstream neurons. Our data suggest a sparse code, distributed across lamina, in which a small population of cells carries stimulus-relevant information. Furthermore, we find that, within this subset of neurons, decoder performance improves when noise correlations are taken into account. Copyright © 2015 the American Physiological Society.

Gap junctions between interneurons are required for normal spatial coding in the hippocampus and short-term spatial memory

PubMed Central

Allen, Kevin; Fuchs, Elke C.; Jaschonek, Hannah; Bannerman, David M.; Monyer, Hannah

2011-01-01

Gap junctions containing connexin-36 (Cx36) electrically couple interneurons in many brain regions and synchronize their activity. We used Cx36 knockout mice (Cx36−/−) to study the importance of electrical coupling between interneurons for spatial coding in the hippocampus and for different forms of hippocampus-dependent spatial memory. Recordings in behaving mice revealed that the spatial selectivity of hippocampal pyramidal neurons was reduced and less stable in Cx36−/− mice. Altered network activity was reflected in slower theta oscillations in the mutants. Temporal coding, assessed by determining the presence and characteristics of theta phase precession, had different dynamics in Cx36−/− mice compared to controls. At the behavioral level, Cx36−/− mice displayed impaired short-term spatial memory but normal spatial reference memory. These results highlight the functional role of electrically coupled interneurons for spatial coding and cognition. Moreover, they suggest that the precise spatial selectivity of place cells is not essential for normal performance on spatial tasks assessing associative long-term memory. PMID:21525295

Space coding for sensorimotor transformations can emerge through unsupervised learning.

PubMed

De Filippo De Grazia, Michele; Cutini, Simone; Lisi, Matteo; Zorzi, Marco

2012-08-01

The posterior parietal cortex (PPC) is fundamental for sensorimotor transformations because it combines multiple sensory inputs and posture signals into different spatial reference frames that drive motor programming. Here, we present a computational model mimicking the sensorimotor transformations occurring in the PPC. A recurrent neural network with one layer of hidden neurons (restricted Boltzmann machine) learned a stochastic generative model of the sensory data without supervision. After the unsupervised learning phase, the activity of the hidden neurons was used to compute a motor program (a population code on a bidimensional map) through a simple linear projection and delta rule learning. The average motor error, calculated as the difference between the expected and the computed output, was less than 3°. Importantly, analyses of the hidden neurons revealed gain-modulated visual receptive fields, thereby showing that space coding for sensorimotor transformations similar to that observed in the PPC can emerge through unsupervised learning. These results suggest that gain modulation is an efficient coding strategy to integrate visual and postural information toward the generation of motor commands.

Entracking as a Brain Stem Code for Pitch: The Butte Hypothesis.

PubMed

Joris, Philip X

2016-01-01

The basic nature of pitch is much debated. A robust code for pitch exists in the auditory nerve in the form of an across-fiber pooled interspike interval (ISI) distribution, which resembles the stimulus autocorrelation. An unsolved question is how this representation can be "read out" by the brain. A new view is proposed in which a known brain-stem property plays a key role in the coding of periodicity, which I refer to as "entracking", a contraction of "entrained phase-locking". It is proposed that a scalar rather than vector code of periodicity exists by virtue of coincidence detectors that code the dominant ISI directly into spike rate through entracking. Perfect entracking means that a neuron fires one spike per stimulus-waveform repetition period, so that firing rate equals the repetition frequency. Key properties are invariance with SPL and generalization across stimuli. The main limitation in this code is the upper limit of firing (~ 500 Hz). It is proposed that entracking provides a periodicity tag which is superimposed on a tonotopic analysis: at low SPLs and fundamental frequencies > 500 Hz, a spectral or place mechanism codes for pitch. With increasing SPL the place code degrades but entracking improves and first occurs in neurons with low thresholds for the spectral components present. The prediction is that populations of entracking neurons, extended across characteristic frequency, form plateaus ("buttes") of firing rate tied to periodicity.

Phase Locking of Multiple Single Neurons to the Local Field Potential in Cat V1.

PubMed

Martin, Kevan A C; Schröder, Sylvia

2016-02-24

The local field potential (LFP) is thought to reflect a temporal reference for neuronal spiking, which may facilitate information coding and orchestrate the communication between neural populations. To explore this proposed role, we recorded the LFP and simultaneously the spike activity of one to three nearby neurons in V1 of anesthetized cats during the presentation of drifting sinusoidal gratings, binary dense noise stimuli, and natural movies. In all stimulus conditions and during spontaneous activity, the average LFP power at frequencies >20 Hz was higher when neurons were spiking versus not spiking. The spikes were weakly but significantly phase locked to all frequencies of the LFP. The average spike phase of the LFP was stable across high and low levels of LFP power, but the strength of phase locking at low frequencies (≤10 Hz) increased with increasing LFP power. In a next step, we studied how strong stimulus responses of single neurons are reflected in the LFP and the LFP-spike relationship. We found that LFP power was slightly increased and phase locking was slightly stronger during strong compared with weak stimulus-locked responses. In summary, the coupling strength between high frequencies of the LFP and spikes was not strongly modulated by LFP power, which is thought to reflect spiking synchrony, nor was it strongly influenced by how strongly the neuron was driven by the stimulus. Furthermore, a comparison between neighboring neurons showed no clustering of preferred LFP phase. We argue that hypotheses on the relevance of phase locking in their current form are inconsistent with our findings. Copyright © 2016 the authors 0270-6474/16/362494-09$15.00/0.

Neural coding of syntactic structure in learned vocalizations in the songbird.

PubMed

Fujimoto, Hisataka; Hasegawa, Taku; Watanabe, Dai

2011-07-06

Although vocal signals including human languages are composed of a finite number of acoustic elements, complex and diverse vocal patterns can be created from combinations of these elements, linked together by syntactic rules. To enable such syntactic vocal behaviors, neural systems must extract the sequence patterns from auditory information and establish syntactic rules to generate motor commands for vocal organs. However, the neural basis of syntactic processing of learned vocal signals remains largely unknown. Here we report that the basal ganglia projecting premotor neurons (HVC(X) neurons) in Bengalese finches represent syntactic rules that generate variable song sequences. When vocalizing an alternative transition segment between song elements called syllables, sparse burst spikes of HVC(X) neurons code the identity of a specific syllable type or a specific transition direction among the alternative trajectories. When vocalizing a variable repetition sequence of the same syllable, HVC(X) neurons not only signal the initiation and termination of the repetition sequence but also indicate the progress and state-of-completeness of the repetition. These different types of syntactic information are frequently integrated within the activity of single HVC(X) neurons, suggesting that syntactic attributes of the individual neurons are not programmed as a basic cellular subtype in advance but acquired in the course of vocal learning and maturation. Furthermore, some auditory-vocal mirroring type HVC(X) neurons display transition selectivity in the auditory phase, much as they do in the vocal phase, suggesting that these songbirds may extract syntactic rules from auditory experience and apply them to form their own vocal behaviors.

Dual Coding of Frequency Modulation in the Ventral Cochlear Nucleus.

PubMed

Paraouty, Nihaad; Stasiak, Arkadiusz; Lorenzi, Christian; Varnet, Léo; Winter, Ian M

2018-04-25

Frequency modulation (FM) is a common acoustic feature of natural sounds and is known to play a role in robust sound source recognition. Auditory neurons show precise stimulus-synchronized discharge patterns that may be used for the representation of low-rate FM. However, it remains unclear whether this representation is based on synchronization to slow temporal envelope (ENV) cues resulting from cochlear filtering or phase locking to faster temporal fine structure (TFS) cues. To investigate the plausibility of those encoding schemes, single units of the ventral cochlear nucleus of guinea pigs of either sex were recorded in response to sine FM tones centered at the unit's best frequency (BF). The results show that, in contrast to high-BF units, for modulation depths within the receptive field, low-BF units (<4 kHz) demonstrate good phase locking to TFS. For modulation depths extending beyond the receptive field, the discharge patterns follow the ENV and fluctuate at the modulation rate. The receptive field proved to be a good predictor of the ENV responses for most primary-like and chopper units. The current in vivo data also reveal a high level of diversity in responses across unit types. TFS cues are mainly conveyed by low-frequency and primary-like units and ENV cues by chopper and onset units. The diversity of responses exhibited by cochlear nucleus neurons provides a neural basis for a dual-coding scheme of FM in the brainstem based on both ENV and TFS cues. SIGNIFICANCE STATEMENT Natural sounds, including speech, convey informative temporal modulations in frequency. Understanding how the auditory system represents those frequency modulations (FM) has important implications as robust sound source recognition depends crucially on the reception of low-rate FM cues. Here, we recorded 115 single-unit responses from the ventral cochlear nucleus in response to FM and provide the first physiological evidence of a dual-coding mechanism of FM via synchronization to temporal envelope cues and phase locking to temporal fine structure cues. We also demonstrate a diversity of neural responses with different coding specializations. These results support the dual-coding scheme proposed by psychophysicists to account for FM sensitivity in humans and provide new insights on how this might be implemented in the early stages of the auditory pathway. Copyright © 2018 the authors 0270-6474/18/384123-15$15.00/0.

Independent coding of absolute duration and distance magnitudes in the prefrontal cortex

PubMed Central

Marcos, Encarni; Tsujimoto, Satoshi

2016-01-01

The estimation of space and time can interfere with each other, and neuroimaging studies have shown overlapping activation in the parietal and prefrontal cortical areas. We used duration and distance discrimination tasks to determine whether space and time share resources in prefrontal cortex (PF) neurons. Monkeys were required to report which of two stimuli, a red circle or blue square, presented sequentially, were longer and farther, respectively, in the duration and distance tasks. In a previous study, we showed that relative duration and distance are coded by different populations of neurons and that the only common representation is related to goal coding. Here, we examined the coding of absolute duration and distance. Our results support a model of independent coding of absolute duration and distance metrics by demonstrating that not only relative magnitude but also absolute magnitude are independently coded in the PF. NEW & NOTEWORTHY Human behavioral studies have shown that spatial and duration judgments can interfere with each other. We investigated the neural representation of such magnitudes in the prefrontal cortex. We found that the two magnitudes are independently coded by prefrontal neurons. We suggest that the interference among magnitude judgments might depend on the goal rather than the perceptual resource sharing. PMID:27760814

Computation of the phase response curve: a direct numerical approach.

PubMed

Govaerts, W; Sautois, B

2006-04-01

Neurons are often modeled by dynamical systems--parameterized systems of differential equations. A typical behavioral pattern of neurons is periodic spiking; this corresponds to the presence of stable limit cycles in the dynamical systems model. The phase resetting and phase response curves (PRCs) describe the reaction of the spiking neuron to an input pulse at each point of the cycle. We develop a new method for computing these curves as a by-product of the solution of the boundary value problem for the stable limit cycle. The method is mathematically equivalent to the adjoint method, but our implementation is computationally much faster and more robust than any existing method. In fact, it can compute PRCs even where the limit cycle can hardly be found by time integration, for example, because it is close to another stable limit cycle. In addition, we obtain the discretized phase response curve in a form that is ideally suited for most applications. We present several examples and provide the implementation in a freely available Matlab code.

A coupled-oscillator model of olfactory bulb gamma oscillations

PubMed Central

2017-01-01

The olfactory bulb transforms not only the information content of the primary sensory representation, but also its underlying coding metric. High-variance, slow-timescale primary odor representations are transformed by bulbar circuitry into secondary representations based on principal neuron spike patterns that are tightly regulated in time. This emergent fast timescale for signaling is reflected in gamma-band local field potentials, presumably serving to efficiently integrate olfactory sensory information into the temporally regulated information networks of the central nervous system. To understand this transformation and its integration with interareal coordination mechanisms requires that we understand its fundamental dynamical principles. Using a biophysically explicit, multiscale model of olfactory bulb circuitry, we here demonstrate that an inhibition-coupled intrinsic oscillator framework, pyramidal resonance interneuron network gamma (PRING), best captures the diversity of physiological properties exhibited by the olfactory bulb. Most importantly, these properties include global zero-phase synchronization in the gamma band, the phase-restriction of informative spikes in principal neurons with respect to this common clock, and the robustness of this synchronous oscillatory regime to multiple challenging conditions observed in the biological system. These conditions include substantial heterogeneities in afferent activation levels and excitatory synaptic weights, high levels of uncorrelated background activity among principal neurons, and spike frequencies in both principal neurons and interneurons that are irregular in time and much lower than the gamma frequency. This coupled cellular oscillator architecture permits stable and replicable ensemble responses to diverse sensory stimuli under various external conditions as well as to changes in network parameters arising from learning-dependent synaptic plasticity. PMID:29140973

Ability of primary auditory cortical neurons to detect amplitude modulation with rate and temporal codes: neurometric analysis

PubMed Central

Johnson, Jeffrey S.; Yin, Pingbo; O'Connor, Kevin N.

2012-01-01

Amplitude modulation (AM) is a common feature of natural sounds, and its detection is biologically important. Even though most sounds are not fully modulated, the majority of physiological studies have focused on fully modulated (100% modulation depth) sounds. We presented AM noise at a range of modulation depths to awake macaque monkeys while recording from neurons in primary auditory cortex (A1). The ability of neurons to detect partial AM with rate and temporal codes was assessed with signal detection methods. On average, single-cell synchrony was as or more sensitive than spike count in modulation detection. Cells are less sensitive to modulation depth if tested away from their best modulation frequency, particularly for temporal measures. Mean neural modulation detection thresholds in A1 are not as sensitive as behavioral thresholds, but with phase locking the most sensitive neurons are more sensitive, suggesting that for temporal measures the lower-envelope principle cannot account for thresholds. Three methods of preanalysis pooling of spike trains (multiunit, similar to convergence from a cortical column; within cell, similar to convergence of cells with matched response properties; across cell, similar to indiscriminate convergence of cells) all result in an increase in neural sensitivity to modulation depth for both temporal and rate codes. For the across-cell method, pooling of a few dozen cells can result in detection thresholds that approximate those of the behaving animal. With synchrony measures, indiscriminate pooling results in sensitive detection of modulation frequencies between 20 and 60 Hz, suggesting that differences in AM response phase are minor in A1. PMID:22422997

A phase transition in the first passage of a Brownian process through a fluctuating boundary with implications for neural coding.

PubMed

Taillefumier, Thibaud; Magnasco, Marcelo O

2013-04-16

Finding the first time a fluctuating quantity reaches a given boundary is a deceptively simple-looking problem of vast practical importance in physics, biology, chemistry, neuroscience, economics, and industrial engineering. Problems in which the bound to be traversed is itself a fluctuating function of time include widely studied problems in neural coding, such as neuronal integrators with irregular inputs and internal noise. We show that the probability p(t) that a Gauss-Markov process will first exceed the boundary at time t suffers a phase transition as a function of the roughness of the boundary, as measured by its Hölder exponent H. The critical value occurs when the roughness of the boundary equals the roughness of the process, so for diffusive processes the critical value is Hc = 1/2. For smoother boundaries, H > 1/2, the probability density is a continuous function of time. For rougher boundaries, H < 1/2, the probability is concentrated on a Cantor-like set of zero measure: the probability density becomes divergent, almost everywhere either zero or infinity. The critical point Hc = 1/2 corresponds to a widely studied case in the theory of neural coding, in which the external input integrated by a model neuron is a white-noise process, as in the case of uncorrelated but precisely balanced excitatory and inhibitory inputs. We argue that this transition corresponds to a sharp boundary between rate codes, in which the neural firing probability varies smoothly, and temporal codes, in which the neuron fires at sharply defined times regardless of the intensity of internal noise.

Medial orbitofrontal cortex codes relative rather than absolute value of financial rewards in humans.

PubMed

Elliott, R; Agnew, Z; Deakin, J F W

2008-05-01

Functional imaging studies in recent years have confirmed the involvement of orbitofrontal cortex (OFC) in human reward processing and have suggested that OFC responses are context-dependent. A seminal electrophysiological experiment in primates taught animals to associate abstract visual stimuli with differently valuable food rewards. Subsequently, pairs of these learned abstract stimuli were presented and firing of OFC neurons to the medium-value stimulus was measured. OFC firing was shown to depend on the relative value context. In this study, we developed a human analogue of this paradigm and scanned subjects using functional magnetic resonance imaging. The analysis compared neuronal responses to two superficially identical events, which differed only in terms of the preceding context. Medial OFC response to the same perceptual stimulus was greater when the stimulus predicted the more valuable of two rewards than when it predicted the less valuable. Additional responses were observed in other components of reward circuitry, the amygdala and ventral striatum. The central finding is consistent with the primate results and suggests that OFC neurons code relative rather than absolute reward value. Amygdala and striatal involvement in coding reward value is also consistent with recent functional imaging data. By using a simpler and less confounded paradigm than many functional imaging studies, we are able to demonstrate that relative financial reward value per se is coded in distinct subregions of an extended reward and decision-making network.

Temporal processing and adaptation in the songbird auditory forebrain.

PubMed

Nagel, Katherine I; Doupe, Allison J

2006-09-21

Songbird auditory neurons must encode the dynamics of natural sounds at many volumes. We investigated how neural coding depends on the distribution of stimulus intensities. Using reverse-correlation, we modeled responses to amplitude-modulated sounds as the output of a linear filter and a nonlinear gain function, then asked how filters and nonlinearities depend on the stimulus mean and variance. Filter shape depended strongly on mean amplitude (volume): at low mean, most neurons integrated sound over many milliseconds, while at high mean, neurons responded more to local changes in amplitude. Increasing the variance (contrast) of amplitude modulations had less effect on filter shape but decreased the gain of firing in most cells. Both filter and gain changes occurred rapidly after a change in statistics, suggesting that they represent nonlinearities in processing. These changes may permit neurons to signal effectively over a wider dynamic range and are reminiscent of findings in other sensory systems.

Astrocyte and Neuronal Plasticity in the Somatosensory System

PubMed Central

Sims, Robert E.; Butcher, John B.; Parri, H. Rheinallt; Glazewski, Stanislaw

2015-01-01

Changing the whisker complement on a rodent's snout can lead to two forms of experience-dependent plasticity (EDP) in the neurons of the barrel cortex, where whiskers are somatotopically represented. One form, termed coding plasticity, concerns changes in synaptic transmission and connectivity between neurons. This is thought to underlie learning and memory processes and so adaptation to a changing environment. The second, called homeostatic plasticity, serves to maintain a restricted dynamic range of neuronal activity thus preventing its saturation or total downregulation. Current explanatory models of cortical EDP are almost exclusively neurocentric. However, in recent years, increasing evidence has emerged on the role of astrocytes in brain function, including plasticity. Indeed, astrocytes appear as necessary partners of neurons at the core of the mechanisms of coding and homeostatic plasticity recorded in neurons. In addition to neuronal plasticity, several different forms of astrocytic plasticity have recently been discovered. They extend from changes in receptor expression and dynamic changes in morphology to alteration in gliotransmitter release. It is however unclear how astrocytic plasticity contributes to the neuronal EDP. Here, we review the known and possible roles for astrocytes in the barrel cortex, including its plasticity. PMID:26345481

Coding and decoding with adapting neurons: a population approach to the peri-stimulus time histogram.

PubMed

Naud, Richard; Gerstner, Wulfram

2012-01-01

The response of a neuron to a time-dependent stimulus, as measured in a Peri-Stimulus-Time-Histogram (PSTH), exhibits an intricate temporal structure that reflects potential temporal coding principles. Here we analyze the encoding and decoding of PSTHs for spiking neurons with arbitrary refractoriness and adaptation. As a modeling framework, we use the spike response model, also known as the generalized linear neuron model. Because of refractoriness, the effect of the most recent spike on the spiking probability a few milliseconds later is very strong. The influence of the last spike needs therefore to be described with high precision, while the rest of the neuronal spiking history merely introduces an average self-inhibition or adaptation that depends on the expected number of past spikes but not on the exact spike timings. Based on these insights, we derive a 'quasi-renewal equation' which is shown to yield an excellent description of the firing rate of adapting neurons. We explore the domain of validity of the quasi-renewal equation and compare it with other rate equations for populations of spiking neurons. The problem of decoding the stimulus from the population response (or PSTH) is addressed analogously. We find that for small levels of activity and weak adaptation, a simple accumulator of the past activity is sufficient to decode the original input, but when refractory effects become large decoding becomes a non-linear function of the past activity. The results presented here can be applied to the mean-field analysis of coupled neuron networks, but also to arbitrary point processes with negative self-interaction.

Potential roles of cholinergic modulation in the neural coding of location and movement speed

PubMed Central

Dannenberg, Holger; Hinman, James R.; Hasselmo, Michael E.

2016-01-01

Behavioral data suggest that cholinergic modulation may play a role in certain aspects of spatial memory, and neurophysiological data demonstrate neurons that fire in response to spatial dimensions, including grid cells and place cells that respond on the basis of location and running speed. These neurons show firing responses that depend upon the visual configuration of the environment, due to coding in visually-responsive regions of the neocortex. This review focuses on the physiological effects of acetylcholine that may influence the sensory coding of spatial dimensions relevant to behavior. In particular, the local circuit effects of acetylcholine within the cortex regulate the influence of sensory input relative to internal memory representations, via presynaptic inhibition of excitatory and inhibitory synaptic transmission, and the modulation of intrinsic currents in cortical excitatory and inhibitory neurons. In addition, circuit effects of acetylcholine regulate the dynamics of cortical circuits including oscillations at theta and gamma frequencies. These effects of acetylcholine on local circuits and network dynamics could underlie the role of acetylcholine in coding of spatial information for the performance of spatial memory tasks. PMID:27677935

Automatic Fitting of Spiking Neuron Models to Electrophysiological Recordings

PubMed Central

Rossant, Cyrille; Goodman, Dan F. M.; Platkiewicz, Jonathan; Brette, Romain

2010-01-01

Spiking models can accurately predict the spike trains produced by cortical neurons in response to somatically injected currents. Since the specific characteristics of the model depend on the neuron, a computational method is required to fit models to electrophysiological recordings. The fitting procedure can be very time consuming both in terms of computer simulations and in terms of code writing. We present algorithms to fit spiking models to electrophysiological data (time-varying input and spike trains) that can run in parallel on graphics processing units (GPUs). The model fitting library is interfaced with Brian, a neural network simulator in Python. If a GPU is present it uses just-in-time compilation to translate model equations into optimized code. Arbitrary models can then be defined at script level and run on the graphics card. This tool can be used to obtain empirically validated spiking models of neurons in various systems. We demonstrate its use on public data from the INCF Quantitative Single-Neuron Modeling 2009 competition by comparing the performance of a number of neuron spiking models. PMID:20224819

A neuronal reward inequity signal in primate striatum

PubMed Central

van Coeverden, Charlotte R.; Schultz, Wolfram

2015-01-01

Primates are social animals, and their survival depends on social interactions with others. Especially important for social interactions and welfare is the observation of rewards obtained by other individuals and the comparison with own reward. The fundamental social decision variable for the comparison process is reward inequity, defined by an asymmetric reward distribution among individuals. An important brain structure for coding reward inequity may be the striatum, a component of the basal ganglia involved in goal-directed behavior. Two rhesus monkeys were seated opposite each other and contacted a touch-sensitive table placed between them to obtain specific magnitudes of reward that were equally or unequally distributed among them. Response times in one of the animals demonstrated differential behavioral sensitivity to reward inequity. A group of neurons in the striatum showed distinct signals reflecting disadvantageous and advantageous reward inequity. These neuronal signals occurred irrespective of, or in conjunction with, own reward coding. These data demonstrate that striatal neurons of macaque monkeys sense the differences between other's and own reward. The neuronal activities are likely to contribute crucial reward information to neuronal mechanisms involved in social interactions. PMID:26378202

Distinct 3-O-Sulfated Heparan Sulfate Modification Patterns Are Required for kal-1−Dependent Neurite Branching in a Context-Dependent Manner in Caenorhabditis elegans

PubMed Central

Tecle, Eillen; Diaz-Balzac, Carlos A.; Bülow, Hannes E.

2013-01-01

Heparan sulfate (HS) is an unbranched glycosaminoglycan exhibiting substantial molecular diversity due to multiple, nonuniformly introduced modifications, including sulfations, epimerization, and acetylation. HS modifications serve specific and instructive roles in neuronal development, leading to the hypothesis of a HS code that regulates nervous system patterning. Although the in vivo roles of many of the HS modifications have been investigated, very little is known about the function of HS 3-O-sulfation in vivo. By examining patterning of the Caenorhabditis elegans nervous system in loss of function mutants of the two 3-O-sulfotransferases, hst-3.1 and hst-3.2, we found HS 3-O-sulfation to be largely dispensable for overall neural development. However, generation of stereotypical neurite branches in hermaphroditic-specific neurons required hst-3.1, hst-3.2, as well as an extracellular cell adhesion molecule encoded by kal-1, the homolog of Kallmann Syndrome associated gene 1/anosmin-1. In contrast, kal-1−dependent neurite branching in AIY neurons required catalytic activity of hst-3.2 but not hst-3.1. The context-dependent requirement for hst-3.2 and hst-3.1 indicates that both enzymes generate distinct types of HS modification patterns in different cell types, which regulate kal-1 to promote neurite branching. We conclude that HS 3-O-sulfation does not play a general role in establishing the HS code in C. elegans but rather plays a specialized role in a context-dependent manner to establish defined aspects of neuronal circuits. PMID:23451335

Traveling Theta Waves in the Human Hippocampus

PubMed Central

Zhang, Honghui

2015-01-01

The hippocampal theta oscillation is strongly correlated with behaviors such as memory and spatial navigation, but we do not understand its specific functional role. One hint of theta's function came from the discovery in rodents that theta oscillations are traveling waves that allow parts of the hippocampus to simultaneously exhibit separate oscillatory phases. Because hippocampal theta oscillations in humans have different properties compared with rodents, we examined these signals directly using multielectrode recordings from neurosurgical patients. Our findings confirm that human hippocampal theta oscillations are traveling waves, but also show that these oscillations appear at a broader range of frequencies compared with rodents. Human traveling waves showed a distinctive pattern of spatial propagation such that there is a consistent phase spread across the hippocampus regardless of the oscillations' frequency. This suggests that traveling theta oscillations are important functionally in humans because they coordinate phase coding throughout the hippocampus in a consistent manner. SIGNIFICANCE STATEMENT We show for the first time in humans that hippocampal theta oscillations are traveling waves, moving along the length of the hippocampus in a posterior–anterior direction. The existence of these traveling theta waves is important for understanding hippocampal neural coding because they cause neurons at separate positions in the hippocampus to experience different theta phases simultaneously. The theta phase that a neuron measures is a key factor in how that cell represents behavioral information. Therefore, the existence of traveling theta waves indicates that, to fully understand how a hippocampal neuron represents information, it is vital to also account for that cell's location in addition to conventional measures of neural activity. PMID:26354915

Stimulus background influences phase invariant coding by correlated neural activity

PubMed Central

Metzen, Michael G; Chacron, Maurice J

2017-01-01

Previously we reported that correlations between the activities of peripheral afferents mediate a phase invariant representation of natural communication stimuli that is refined across successive processing stages thereby leading to perception and behavior in the weakly electric fish Apteronotus leptorhynchus (Metzen et al., 2016). Here, we explore how phase invariant coding and perception of natural communication stimuli are affected by changes in the sinusoidal background over which they occur. We found that increasing background frequency led to phase locking, which decreased both detectability and phase invariant coding. Correlated afferent activity was a much better predictor of behavior as assessed from both invariance and detectability than single neuron activity. Thus, our results provide not only further evidence that correlated activity likely determines perception of natural communication signals, but also a novel explanation as to why these preferentially occur on top of low frequency as well as low-intensity sinusoidal backgrounds. DOI: http://dx.doi.org/10.7554/eLife.24482.001 PMID:28315519

Task-Dependent Changes in Cross-Level Coupling between Single Neurons and Oscillatory Activity in Multiscale Networks

PubMed Central

Canolty, Ryan T.; Ganguly, Karunesh; Carmena, Jose M.

2012-01-01

Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP) activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC) or under direct neural control through a brain-machine interface (Brain Control, BC). In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10–45 Hz) during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to spike rate and timing may hold for models of computation and communication in distributed functional brain networks. PMID:23284276

Input-dependent frequency modulation of cortical gamma oscillations shapes spatial synchronization and enables phase coding.

PubMed

Lowet, Eric; Roberts, Mark; Hadjipapas, Avgis; Peter, Alina; van der Eerden, Jan; De Weerd, Peter

2015-02-01

Fine-scale temporal organization of cortical activity in the gamma range (∼25-80Hz) may play a significant role in information processing, for example by neural grouping ('binding') and phase coding. Recent experimental studies have shown that the precise frequency of gamma oscillations varies with input drive (e.g. visual contrast) and that it can differ among nearby cortical locations. This has challenged theories assuming widespread gamma synchronization at a fixed common frequency. In the present study, we investigated which principles govern gamma synchronization in the presence of input-dependent frequency modulations and whether they are detrimental for meaningful input-dependent gamma-mediated temporal organization. To this aim, we constructed a biophysically realistic excitatory-inhibitory network able to express different oscillation frequencies at nearby spatial locations. Similarly to cortical networks, the model was topographically organized with spatially local connectivity and spatially-varying input drive. We analyzed gamma synchronization with respect to phase-locking, phase-relations and frequency differences, and quantified the stimulus-related information represented by gamma phase and frequency. By stepwise simplification of our models, we found that the gamma-mediated temporal organization could be reduced to basic synchronization principles of weakly coupled oscillators, where input drive determines the intrinsic (natural) frequency of oscillators. The gamma phase-locking, the precise phase relation and the emergent (measurable) frequencies were determined by two principal factors: the detuning (intrinsic frequency difference, i.e. local input difference) and the coupling strength. In addition to frequency coding, gamma phase contained complementary stimulus information. Crucially, the phase code reflected input differences, but not the absolute input level. This property of relative input-to-phase conversion, contrasting with latency codes or slower oscillation phase codes, may resolve conflicting experimental observations on gamma phase coding. Our modeling results offer clear testable experimental predictions. We conclude that input-dependency of gamma frequencies could be essential rather than detrimental for meaningful gamma-mediated temporal organization of cortical activity.

Input-Dependent Frequency Modulation of Cortical Gamma Oscillations Shapes Spatial Synchronization and Enables Phase Coding

PubMed Central

Lowet, Eric; Roberts, Mark; Hadjipapas, Avgis; Peter, Alina; van der Eerden, Jan; De Weerd, Peter

2015-01-01

Fine-scale temporal organization of cortical activity in the gamma range (∼25–80Hz) may play a significant role in information processing, for example by neural grouping (‘binding’) and phase coding. Recent experimental studies have shown that the precise frequency of gamma oscillations varies with input drive (e.g. visual contrast) and that it can differ among nearby cortical locations. This has challenged theories assuming widespread gamma synchronization at a fixed common frequency. In the present study, we investigated which principles govern gamma synchronization in the presence of input-dependent frequency modulations and whether they are detrimental for meaningful input-dependent gamma-mediated temporal organization. To this aim, we constructed a biophysically realistic excitatory-inhibitory network able to express different oscillation frequencies at nearby spatial locations. Similarly to cortical networks, the model was topographically organized with spatially local connectivity and spatially-varying input drive. We analyzed gamma synchronization with respect to phase-locking, phase-relations and frequency differences, and quantified the stimulus-related information represented by gamma phase and frequency. By stepwise simplification of our models, we found that the gamma-mediated temporal organization could be reduced to basic synchronization principles of weakly coupled oscillators, where input drive determines the intrinsic (natural) frequency of oscillators. The gamma phase-locking, the precise phase relation and the emergent (measurable) frequencies were determined by two principal factors: the detuning (intrinsic frequency difference, i.e. local input difference) and the coupling strength. In addition to frequency coding, gamma phase contained complementary stimulus information. Crucially, the phase code reflected input differences, but not the absolute input level. This property of relative input-to-phase conversion, contrasting with latency codes or slower oscillation phase codes, may resolve conflicting experimental observations on gamma phase coding. Our modeling results offer clear testable experimental predictions. We conclude that input-dependency of gamma frequencies could be essential rather than detrimental for meaningful gamma-mediated temporal organization of cortical activity. PMID:25679780

Coding of odors by temporal binding within a model network of the locust antennal lobe.

PubMed

Patel, Mainak J; Rangan, Aaditya V; Cai, David

2013-01-01

The locust olfactory system interfaces with the external world through antennal receptor neurons (ORNs), which represent odors in a distributed, combinatorial manner. ORN axons bundle together to form the antennal nerve, which relays sensory information centrally to the antennal lobe (AL). Within the AL, an odor generates a dynamically evolving ensemble of active cells, leading to a stimulus-specific temporal progression of neuronal spiking. This experimental observation has led to the hypothesis that an odor is encoded within the AL by a dynamically evolving trajectory of projection neuron (PN) activity that can be decoded piecewise to ascertain odor identity. In order to study information coding within the locust AL, we developed a scaled-down model of the locust AL using Hodgkin-Huxley-type neurons and biologically realistic connectivity parameters and current components. Using our model, we examined correlations in the precise timing of spikes across multiple neurons, and our results suggest an alternative to the dynamic trajectory hypothesis. We propose that the dynamical interplay of fast and slow inhibition within the locust AL induces temporally stable correlations in the spiking activity of an odor-dependent neural subset, giving rise to a temporal binding code that allows rapid stimulus detection by downstream elements.

The Vestibular System Implements a Linear–Nonlinear Transformation In Order to Encode Self-Motion

PubMed Central

Massot, Corentin; Schneider, Adam D.; Chacron, Maurice J.; Cullen, Kathleen E.

2012-01-01

Although it is well established that the neural code representing the world changes at each stage of a sensory pathway, the transformations that mediate these changes are not well understood. Here we show that self-motion (i.e. vestibular) sensory information encoded by VIIIth nerve afferents is integrated nonlinearly by post-synaptic central vestibular neurons. This response nonlinearity was characterized by a strong (∼50%) attenuation in neuronal sensitivity to low frequency stimuli when presented concurrently with high frequency stimuli. Using computational methods, we further demonstrate that a static boosting nonlinearity in the input-output relationship of central vestibular neurons accounts for this unexpected result. Specifically, when low and high frequency stimuli are presented concurrently, this boosting nonlinearity causes an intensity-dependent bias in the output firing rate, thereby attenuating neuronal sensitivities. We suggest that nonlinear integration of afferent input extends the coding range of central vestibular neurons and enables them to better extract the high frequency features of self-motion when embedded with low frequency motion during natural movements. These findings challenge the traditional notion that the vestibular system uses a linear rate code to transmit information and have important consequences for understanding how the representation of sensory information changes across sensory pathways. PMID:22911113

Input-output relation and energy efficiency in the neuron with different spike threshold dynamics.

PubMed

Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin

2015-01-01

Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na(+) and K(+) currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism.

Input-output relation and energy efficiency in the neuron with different spike threshold dynamics

PubMed Central

Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin

2015-01-01

Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na+ and K+ currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism. PMID:26074810

A model for the characterization of the spatial properties in vestibular neurons

NASA Technical Reports Server (NTRS)

Angelaki, D. E.; Bush, G. A.; Perachio, A. A.

1992-01-01

Quantitative study of the static and dynamic response properties of some otolith-sensitive neurons has been difficult in the past partly because their responses to different linear acceleration vectors exhibited no "null" plane and a dependence of phase on stimulus orientation. The theoretical formulation of the response ellipse provides a quantitative way to estimate the spatio-temporal properties of such neurons. Its semi-major axis gives the direction of the polarization vector (i.e., direction of maximal sensitivity) and it estimates the neuronal response for stimulation along that direction. In addition, the semi-minor axis of the ellipse provides an estimate of the neuron's maximal sensitivity in the "null" plane. In this paper, extracellular recordings from otolith-sensitive vestibular nuclei neurons in decerebrate rats were used to demonstrate the practical application of the method. The experimentally observed gain and phase dependence on the orientation angle of the acceleration vector in a head-horizontal plane was described and satisfactorily fit by the response ellipse model. In addition, the model satisfactorily fits neuronal responses in three-dimensions and unequivocally demonstrates that the response ellipse formulation is the general approach to describe quantitatively the spatial properties of vestibular neurons.

Structures of Neural Correlation and How They Favor Coding

PubMed Central

Franke, Felix; Fiscella, Michele; Sevelev, Maksim; Roska, Botond; Hierlemann, Andreas; da Silveira, Rava Azeredo

2017-01-01

Summary The neural representation of information suffers from “noise”—the trial-to-trial variability in the response of neurons. The impact of correlated noise upon population coding has been debated, but a direct connection between theory and experiment remains tenuous. Here, we substantiate this connection and propose a refined theoretical picture. Using simultaneous recordings from a population of direction-selective retinal ganglion cells, we demonstrate that coding benefits from noise correlations. The effect is appreciable already in small populations, yet it is a collective phenomenon. Furthermore, the stimulus-dependent structure of correlation is key. We develop simple functional models that capture the stimulus-dependent statistics. We then use them to quantify the performance of population coding, which depends upon interplays of feature sensitivities and noise correlations in the population. Because favorable structures of correlation emerge robustly in circuits with noisy, nonlinear elements, they will arise and benefit coding beyond the confines of retina. PMID:26796692

Prefrontal Parvalbumin Neurons in Control of Attention

PubMed Central

Kim, Hoseok; Ährlund-Richter, Sofie; Wang, Xinming; Deisseroth, Karl; Carlén, Marie

2016-01-01

Summary While signatures of attention have been extensively studied in sensory systems, the neural sources and computations responsible for top-down control of attention are largely unknown. Using chronic recordings in mice, we found that fast-spiking parvalbumin (FS-PV) interneurons in medial prefrontal cortex (mPFC) uniformly show increased and sustained firing during goal-driven attentional processing, correlating to the level of attention. Elevated activity of FS-PV neurons on the timescale of seconds predicted successful execution of behavior. Successful allocation of attention was characterized by strong synchronization of FS-PV neurons, increased gamma oscillations, and phase locking of pyramidal firing. Phase-locked pyramidal neurons showed gamma-phase-dependent rate modulation during successful attentional processing. Optogenetic silencing of FS-PV neurons deteriorated attentional processing, while optogenetic synchronization of FS-PV neurons at gamma frequencies had pro-cognitive effects and improved goal-directed behavior. FS-PV neurons thus act as a functional unit coordinating the activity in the local mPFC circuit during goal-driven attentional processing. PMID:26771492

Coding rate and duration of vocalizations of the frog, Xenopus laevis.

PubMed

Zornik, Erik; Yamaguchi, Ayako

2012-08-29

Vocalizations involve complex rhythmic motor patterns, but the underlying temporal coding mechanisms in the nervous system are poorly understood. Using a recently developed whole-brain preparation from which "fictive" vocalizations are readily elicited in vitro, we investigated the cellular basis of temporal complexity of African clawed frogs (Xenopus laevis). Male advertisement calls contain two alternating components--fast trills (∼300 ms) and slow trills (∼700 ms) that contain clicks repeated at ∼60 and ∼30 Hz, respectively. We found that males can alter the duration of fast trills without changing click rates. This finding led us to hypothesize that call rate and duration are regulated by independent mechanisms. We tested this by obtaining whole-cell patch-clamp recordings in the "fictively" calling isolated brain. We discovered a single type of premotor neuron with activity patterns correlated with both the rate and duration of fast trills. These "fast-trill neurons" (FTNs) exhibited long-lasting depolarizations (LLDs) correlated with each fast trill and action potentials that were phase-locked with motor output-neural correlates of call duration and rate, respectively. When depolarized without central pattern generator activation, FTNs produced subthreshold oscillations and action potentials at fast-trill rates, indicating FTN resonance properties are tuned to, and may dictate, the fast-trill rhythm. NMDA receptor (NMDAR) blockade eliminated LLDs in FTNs, and NMDAR activation in synaptically isolated FTNs induced repetitive LLDs. These results suggest FTNs contain an NMDAR-dependent mechanism that may regulate fast-trill duration. We conclude that a single premotor neuron population employs distinct mechanisms to regulate call rate and duration.

Coding and Decoding with Adapting Neurons: A Population Approach to the Peri-Stimulus Time Histogram

PubMed Central

Naud, Richard; Gerstner, Wulfram

2012-01-01

The response of a neuron to a time-dependent stimulus, as measured in a Peri-Stimulus-Time-Histogram (PSTH), exhibits an intricate temporal structure that reflects potential temporal coding principles. Here we analyze the encoding and decoding of PSTHs for spiking neurons with arbitrary refractoriness and adaptation. As a modeling framework, we use the spike response model, also known as the generalized linear neuron model. Because of refractoriness, the effect of the most recent spike on the spiking probability a few milliseconds later is very strong. The influence of the last spike needs therefore to be described with high precision, while the rest of the neuronal spiking history merely introduces an average self-inhibition or adaptation that depends on the expected number of past spikes but not on the exact spike timings. Based on these insights, we derive a ‘quasi-renewal equation’ which is shown to yield an excellent description of the firing rate of adapting neurons. We explore the domain of validity of the quasi-renewal equation and compare it with other rate equations for populations of spiking neurons. The problem of decoding the stimulus from the population response (or PSTH) is addressed analogously. We find that for small levels of activity and weak adaptation, a simple accumulator of the past activity is sufficient to decode the original input, but when refractory effects become large decoding becomes a non-linear function of the past activity. The results presented here can be applied to the mean-field analysis of coupled neuron networks, but also to arbitrary point processes with negative self-interaction. PMID:23055914

A Linear Model of Phase-Dependent Power Correlations in Neuronal Oscillations

PubMed Central

Eriksson, David; Vicente, Raul; Schmidt, Kerstin

2011-01-01

Recently, it has been suggested that effective interactions between two neuronal populations are supported by the phase difference between the oscillations in these two populations, a hypothesis referred to as “communication through coherence” (CTC). Experimental work quantified effective interactions by means of the power correlations between the two populations, where power was calculated on the local field potential and/or multi-unit activity. Here, we present a linear model of interacting oscillators that accounts for the phase dependency of the power correlation between the two populations and that can be used as a reference for detecting non-linearities such as gain control. In the experimental analysis, trials were sorted according to the coupled phase difference of the oscillators while the putative interaction between oscillations was taking place. Taking advantage of the modeling, we further studied the dependency of the power correlation on the uncoupled phase difference, connection strength, and topology. Since the uncoupled phase difference, i.e., the phase relation before the effective interaction, is the causal variable in the CTC hypothesis we also describe how power correlations depend on that variable. For uni-directional connectivity we observe that the width of the uncoupled phase dependency is broader than for the coupled phase. Furthermore, the analytical results show that the characteristics of the phase dependency change when a bidirectional connection is assumed. The width of the phase dependency indicates which oscillation frequencies are optimal for a given connection delay distribution. We propose that a certain width enables a stimulus-contrast dependent extent of effective long-range lateral connections. PMID:21808618

Local and global synchronization transitions induced by time delays in small-world neuronal networks with chemical synapses.

PubMed

Yu, Haitao; Wang, Jiang; Du, Jiwei; Deng, Bin; Wei, Xile

2015-02-01

Effects of time delay on the local and global synchronization in small-world neuronal networks with chemical synapses are investigated in this paper. Numerical results show that, for both excitatory and inhibitory coupling types, the information transmission delay can always induce synchronization transitions of spiking neurons in small-world networks. In particular, regions of in-phase and out-of-phase synchronization of connected neurons emerge intermittently as the synaptic delay increases. For excitatory coupling, all transitions to spiking synchronization occur approximately at integer multiples of the firing period of individual neurons; while for inhibitory coupling, these transitions appear at the odd multiples of the half of the firing period of neurons. More importantly, the local synchronization transition is more profound than the global synchronization transition, depending on the type of coupling synapse. For excitatory synapses, the local in-phase synchronization observed for some values of the delay also occur at a global scale; while for inhibitory ones, this synchronization, observed at the local scale, disappears at a global scale. Furthermore, the small-world structure can also affect the phase synchronization of neuronal networks. It is demonstrated that increasing the rewiring probability can always improve the global synchronization of neuronal activity, but has little effect on the local synchronization of neighboring neurons.

The neuromechanics of hearing

NASA Astrophysics Data System (ADS)

Araya, Mussie K.; Brownell, William E.

2015-12-01

Hearing requires precise detection and coding of acoustic signals by the inner ear and equally precise communication of the information through the auditory brainstem. A membrane based motor in the outer hair cell lateral wall contributes to the transformation of sound into a precise neural code. Structural, molecular and energetic similarities between the outer hair cell and auditory brainstem neurons suggest that a similar membrane based motor may contribute to signal processing in the auditory CNS. Cooperative activation of voltage gated ion channels enhances neuronal temporal processing and increases the upper frequency limit for phase locking. We explore the possibility that membrane mechanics contribute to ion channel cooperativity as a consequence of the nearly instantaneous speed of electromechanical signaling and the fact that membrane composition and mechanics modulate ion channel function.

Cell cycle S phase markers are expressed in cerebral neuron nuclei of cats infected by the Feline Panleukopenia Virus.

PubMed

Poncelet, Luc; Garigliany, Mutien; Ando, Kunie; Franssen, Mathieu; Desmecht, Daniel; Brion, Jean-Pierre

2016-12-16

The cell cycle-associated neuronal death hypothesis, which has been proposed as a common mechanism for most neurodegenerative diseases, is notably supported by evidencing cell cycle effectors in neurons. However, in naturally occurring nervous system diseases, these markers are not expressed in neuron nuclei but in cytoplasmic compartments. In other respects, the Feline Panleukopenia Virus (FPV) is able to complete its cycle in mature brain neurons in the feline species. As a parvovirus, the FPV is strictly dependent on its host cell reaching the cell cycle S phase to start its multiplication. In this retrospective study on the whole brain of 12 cats with naturally-occurring, FPV-associated cerebellar atrophy, VP2 capsid protein expression was detected by immunostaining not only in some brain neuronal nuclei but also in neuronal cytoplasm in 2 cats, suggesting that viral mRNA translation was still occurring. In these cats, double immunostainings demonstrated the expression of cell cycle S phase markers cyclin A, cdk2 and PCNA in neuronal nuclei. Parvoviruses are able to maintain their host cells in S phase by triggering the DNA damage response. S139 phospho H2A1, a key player in the cell cycle arrest, was detected in some neuronal nuclei, supporting that infected neurons were also blocked into the S phase. PCR studies did not support a co-infection with an adeno or herpes virus. ERK1/2 nuclear accumulation was observed in some neurons suggesting that the ERK signaling pathway might be involved as a mechanism driving these neurons far into the cell cycle.

Which spike train distance is most suitable for distinguishing rate and temporal coding?

PubMed

Satuvuori, Eero; Kreuz, Thomas

2018-04-01

It is commonly assumed in neuronal coding that repeated presentations of a stimulus to a coding neuron elicit similar responses. One common way to assess similarity are spike train distances. These can be divided into spike-resolved, such as the Victor-Purpura and the van Rossum distance, and time-resolved, e.g. the ISI-, the SPIKE- and the RI-SPIKE-distance. We use independent steady-rate Poisson processes as surrogates for spike trains with fixed rate and no timing information to address two basic questions: How does the sensitivity of the different spike train distances to temporal coding depend on the rates of the two processes and how do the distances deal with very low rates? Spike-resolved distances always contain rate information even for parameters indicating time coding. This is an issue for reasonably high rates but beneficial for very low rates. In contrast, the operational range for detecting time coding of time-resolved distances is superior at normal rates, but these measures produce artefacts at very low rates. The RI-SPIKE-distance is the only measure that is sensitive to timing information only. While our results on rate-dependent expectation values for the spike-resolved distances agree with Chicharro et al. (2011), we here go one step further and specifically investigate applicability for very low rates. The most appropriate measure depends on the rates of the data being analysed. Accordingly, we summarize our results in one table that allows an easy selection of the preferred measure for any kind of data. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Phase-amplitude coupling supports phase coding in human ECoG

PubMed Central

Watrous, Andrew J; Deuker, Lorena; Fell, Juergen; Axmacher, Nikolai

2015-01-01

Prior studies have shown that high-frequency activity (HFA) is modulated by the phase of low-frequency activity. This phenomenon of phase-amplitude coupling (PAC) is often interpreted as reflecting phase coding of neural representations, although evidence for this link is still lacking in humans. Here, we show that PAC indeed supports phase-dependent stimulus representations for categories. Six patients with medication-resistant epilepsy viewed images of faces, tools, houses, and scenes during simultaneous acquisition of intracranial recordings. Analyzing 167 electrodes, we observed PAC at 43% of electrodes. Further inspection of PAC revealed that category specific HFA modulations occurred at different phases and frequencies of the underlying low-frequency rhythm, permitting decoding of categorical information using the phase at which HFA events occurred. These results provide evidence for categorical phase-coded neural representations and are the first to show that PAC coincides with phase-dependent coding in the human brain. DOI: http://dx.doi.org/10.7554/eLife.07886.001 PMID:26308582

Inter-synaptic learning of combination rules in a cortical network model

PubMed Central

Lavigne, Frédéric; Avnaïm, Francis; Dumercy, Laurent

2014-01-01

Selecting responses in working memory while processing combinations of stimuli depends strongly on their relations stored in long-term memory. However, the learning of XOR-like combinations of stimuli and responses according to complex rules raises the issue of the non-linear separability of the responses within the space of stimuli. One proposed solution is to add neurons that perform a stage of non-linear processing between the stimuli and responses, at the cost of increasing the network size. Based on the non-linear integration of synaptic inputs within dendritic compartments, we propose here an inter-synaptic (IS) learning algorithm that determines the probability of potentiating/depressing each synapse as a function of the co-activity of the other synapses within the same dendrite. The IS learning is effective with random connectivity and without either a priori wiring or additional neurons. Our results show that IS learning generates efficacy values that are sufficient for the processing of XOR-like combinations, on the basis of the sole correlational structure of the stimuli and responses. We analyze the types of dendrites involved in terms of the number of synapses from pre-synaptic neurons coding for the stimuli and responses. The synaptic efficacy values obtained show that different dendrites specialize in the detection of different combinations of stimuli. The resulting behavior of the cortical network model is analyzed as a function of inter-synaptic vs. Hebbian learning. Combinatorial priming effects show that the retrospective activity of neurons coding for the stimuli trigger XOR-like combination-selective prospective activity of neurons coding for the expected response. The synergistic effects of inter-synaptic learning and of mixed-coding neurons are simulated. The results show that, although each mechanism is sufficient by itself, their combined effects improve the performance of the network. PMID:25221529

Dynamics of human subthalamic neuron phase-locking to motor and sensory cortical oscillations during movement.

PubMed

Lipski, Witold J; Wozny, Thomas A; Alhourani, Ahmad; Kondylis, Efstathios D; Turner, Robert S; Crammond, Donald J; Richardson, Robert Mark

2017-09-01

Coupled oscillatory activity recorded between sensorimotor regions of the basal ganglia-thalamocortical loop is thought to reflect information transfer relevant to movement. A neuronal firing-rate model of basal ganglia-thalamocortical circuitry, however, has dominated thinking about basal ganglia function for the past three decades, without knowledge of the relationship between basal ganglia single neuron firing and cortical population activity during movement itself. We recorded activity from 34 subthalamic nucleus (STN) neurons, simultaneously with cortical local field potentials and motor output, in 11 subjects with Parkinson's disease (PD) undergoing awake deep brain stimulator lead placement. STN firing demonstrated phase synchronization to both low- and high-beta-frequency cortical oscillations, and to the amplitude envelope of gamma oscillations, in motor cortex. We found that during movement, the magnitude of this synchronization was dynamically modulated in a phase-frequency-specific manner. Importantly, we found that phase synchronization was not correlated with changes in neuronal firing rate. Furthermore, we found that these relationships were not exclusive to motor cortex, because STN firing also demonstrated phase synchronization to both premotor and sensory cortex. The data indicate that models of basal ganglia function ultimately will need to account for the activity of populations of STN neurons that are bound in distinct functional networks with both motor and sensory cortices and code for movement parameters independent of changes in firing rate. NEW & NOTEWORTHY Current models of basal ganglia-thalamocortical networks do not adequately explain simple motor functions, let alone dysfunction in movement disorders. Our findings provide data that inform models of human basal ganglia function by demonstrating how movement is encoded by networks of subthalamic nucleus (STN) neurons via dynamic phase synchronization with cortex. The data also demonstrate, for the first time in humans, a mechanism through which the premotor and sensory cortices are functionally connected to the STN. Copyright © 2017 the American Physiological Society.

A neuronal model of predictive coding accounting for the mismatch negativity.

PubMed

Wacongne, Catherine; Changeux, Jean-Pierre; Dehaene, Stanislas

2012-03-14

The mismatch negativity (MMN) is thought to index the activation of specialized neural networks for active prediction and deviance detection. However, a detailed neuronal model of the neurobiological mechanisms underlying the MMN is still lacking, and its computational foundations remain debated. We propose here a detailed neuronal model of auditory cortex, based on predictive coding, that accounts for the critical features of MMN. The model is entirely composed of spiking excitatory and inhibitory neurons interconnected in a layered cortical architecture with distinct input, predictive, and prediction error units. A spike-timing dependent learning rule, relying upon NMDA receptor synaptic transmission, allows the network to adjust its internal predictions and use a memory of the recent past inputs to anticipate on future stimuli based on transition statistics. We demonstrate that this simple architecture can account for the major empirical properties of the MMN. These include a frequency-dependent response to rare deviants, a response to unexpected repeats in alternating sequences (ABABAA…), a lack of consideration of the global sequence context, a response to sound omission, and a sensitivity of the MMN to NMDA receptor antagonists. Novel predictions are presented, and a new magnetoencephalography experiment in healthy human subjects is presented that validates our key hypothesis: the MMN results from active cortical prediction rather than passive synaptic habituation.

Role of protein kinase C in the induction and maintenance of serotonin-dependent enhancement of the glutamate response in isolated siphon motor neurons of Aplysia californica.

PubMed

Villareal, Greg; Li, Quan; Cai, Diancai; Fink, Ann E; Lim, Travis; Bougie, Joanna K; Sossin, Wayne S; Glanzman, David L

2009-04-22

Serotonin (5-HT) mediates learning-related facilitation of sensorimotor synapses in Aplysia californica. Under some circumstances 5-HT-dependent facilitation requires the activity of protein kinase C (PKC). One critical site of PKC's contribution to 5-HT-dependent synaptic facilitation is the presynaptic sensory neuron. Here, we provide evidence that postsynaptic PKC also contributes to synaptic facilitation. We investigated the contribution of PKC to enhancement of the glutamate-evoked potential (Glu-EP) in isolated siphon motor neurons in cell culture. A 10 min application of either 5-HT or phorbol ester, which activates PKC, produced persistent (> 50 min) enhancement of the Glu-EP. Chelerythrine and bisindolylmaleimide-1 (Bis), two inhibitors of PKC, both blocked the induction of 5-HT-dependent enhancement. An inhibitor of calpain, a calcium-dependent protease, also blocked 5-HT's effect. Interestingly, whereas chelerythrine blocked maintenance of the enhancement, Bis did not. Because Bis has greater selectivity for conventional and novel isoforms of PKC than for atypical isoforms, this result implicates an atypical isoform in the maintenance of 5-HT's effect. Although induction of enhancement of the Glu-EP requires protein synthesis (Villareal et al., 2007), we found that maintenance of the enhancement does not. Maintenance of 5-HT-dependent enhancement appears to be mediated by a PKM-type fragment generated by calpain-dependent proteolysis of atypical PKC. Together, our results suggest that 5-HT treatment triggers two phases of PKC activity within the motor neuron, an early phase that may involve conventional, novel or atypical isoforms of PKC, and a later phase that selectively involves an atypical isoform.

Hyperpolarizing and age-dependent depolarizing responses of cultured locus coeruleus neurons to noradrenaline.

PubMed

Finlayson, P G; Marshall, K C

1984-08-01

The electrical activity and responses to noradrenaline (NA) of locus coeruleus (LC) neurons have been studied in organotypic cultures using intracellular recording. Most LC neurons were predominantly quiescent, though occasional bursts of activity were observed; a few cells were tonically active at rates of 0.5-5/s. In most cells tested, iontophoretic application of NA evoked responses which were initially hyperpolarizing, sometimes followed by a depolarizing phase and frequently followed by a period of increased excitatory synaptic activity. The enhanced synaptic activity appeared to be an indirect effect since it was blocked by bath application of tetrodotoxin (TTX). In the presence of TTX, responses to NA of all but one cell were simple hyperpolarizations or biphasic (hyperpolarization/depolarization) responses. The presence of the depolarizing component appeared to be age-dependent, since it was frequently observed in cultures grown in vitro for less than 26 days, while neurons in older cultures exhibited only hyperpolarizing responses. If such age-dependent depolarizing responses are present in vivo, they would represent a unique example of a transmitter response which is present only during a transient developmental phase.

Neuronal Cell Fate Specification by the Convergence of Different Spatiotemporal Cues on a Common Terminal Selector Cascade

PubMed Central

Rubio-Ferrera, Irene; Millán-Crespo, Irene; Contero-García, Patricia; Bahrampour, Shahrzad

2016-01-01

Specification of the myriad of unique neuronal subtypes found in the nervous system depends upon spatiotemporal cues and terminal selector gene cascades, often acting in sequential combinatorial codes to determine final cell fate. However, a specific neuronal cell subtype can often be generated in different parts of the nervous system and at different stages, indicating that different spatiotemporal cues can converge on the same terminal selectors to thereby generate a similar cell fate. However, the regulatory mechanisms underlying such convergence are poorly understood. The Nplp1 neuropeptide neurons in the Drosophila ventral nerve cord can be subdivided into the thoracic-ventral Tv1 neurons and the dorsal-medial dAp neurons. The activation of Nplp1 in Tv1 and dAp neurons depends upon the same terminal selector cascade: col>ap/eya>dimm>Nplp1. However, Tv1 and dAp neurons are generated by different neural progenitors (neuroblasts) with different spatiotemporal appearance. Here, we find that the same terminal selector cascade is triggered by Kr/pdm>grn in dAp neurons, but by Antp/hth/exd/lbe/cas in Tv1 neurons. Hence, two different spatiotemporal combinations can funnel into a common downstream terminal selector cascade to determine a highly related cell fate. PMID:27148744

Impact of adaptation currents on synchronization of coupled exponential integrate-and-fire neurons.

PubMed

Ladenbauer, Josef; Augustin, Moritz; Shiau, LieJune; Obermayer, Klaus

2012-01-01

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in local excitatory networks, but indicate that inhibition rather than excitation generates coherent rhythms at higher frequencies.

Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons

PubMed Central

Ladenbauer, Josef; Augustin, Moritz; Shiau, LieJune; Obermayer, Klaus

2012-01-01

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in local excitatory networks, but indicate that inhibition rather than excitation generates coherent rhythms at higher frequencies. PMID:22511861

Sensory Afferents Use Different Coding Strategies for Heat and Cold.

PubMed

Wang, Feng; Bélanger, Erik; Côté, Sylvain L; Desrosiers, Patrick; Prescott, Steven A; Côté, Daniel C; De Koninck, Yves

2018-05-15

Primary afferents transduce environmental stimuli into electrical activity that is transmitted centrally to be decoded into corresponding sensations. However, it remains unknown how afferent populations encode different somatosensory inputs. To address this, we performed two-photon Ca 2+ imaging from thousands of dorsal root ganglion (DRG) neurons in anesthetized mice while applying mechanical and thermal stimuli to hind paws. We found that approximately half of all neurons are polymodal and that heat and cold are encoded very differently. As temperature increases, more heating-sensitive neurons are activated, and most individual neurons respond more strongly, consistent with graded coding at population and single-neuron levels, respectively. In contrast, most cooling-sensitive neurons respond in an ungraded fashion, inconsistent with graded coding and suggesting combinatorial coding, based on which neurons are co-activated. Although individual neurons may respond to multiple stimuli, our results show that different stimuli activate distinct combinations of diversely tuned neurons, enabling rich population-level coding. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

PubMed Central

Nessler, Bernhard; Pfeiffer, Michael; Buesing, Lars; Maass, Wolfgang

2013-01-01

The principles by which networks of neurons compute, and how spike-timing dependent plasticity (STDP) of synaptic weights generates and maintains their computational function, are unknown. Preceding work has shown that soft winner-take-all (WTA) circuits, where pyramidal neurons inhibit each other via interneurons, are a common motif of cortical microcircuits. We show through theoretical analysis and computer simulations that Bayesian computation is induced in these network motifs through STDP in combination with activity-dependent changes in the excitability of neurons. The fundamental components of this emergent Bayesian computation are priors that result from adaptation of neuronal excitability and implicit generative models for hidden causes that are created in the synaptic weights through STDP. In fact, a surprising result is that STDP is able to approximate a powerful principle for fitting such implicit generative models to high-dimensional spike inputs: Expectation Maximization. Our results suggest that the experimentally observed spontaneous activity and trial-to-trial variability of cortical neurons are essential features of their information processing capability, since their functional role is to represent probability distributions rather than static neural codes. Furthermore it suggests networks of Bayesian computation modules as a new model for distributed information processing in the cortex. PMID:23633941

A stimulus-dependent spike threshold is an optimal neural coder

PubMed Central

Jones, Douglas L.; Johnson, Erik C.; Ratnam, Rama

2015-01-01

A neural code based on sequences of spikes can consume a significant portion of the brain's energy budget. Thus, energy considerations would dictate that spiking activity be kept as low as possible. However, a high spike-rate improves the coding and representation of signals in spike trains, particularly in sensory systems. These are competing demands, and selective pressure has presumably worked to optimize coding by apportioning a minimum number of spikes so as to maximize coding fidelity. The mechanisms by which a neuron generates spikes while maintaining a fidelity criterion are not known. Here, we show that a signal-dependent neural threshold, similar to a dynamic or adapting threshold, optimizes the trade-off between spike generation (encoding) and fidelity (decoding). The threshold mimics a post-synaptic membrane (a low-pass filter) and serves as an internal decoder. Further, it sets the average firing rate (the energy constraint). The decoding process provides an internal copy of the coding error to the spike-generator which emits a spike when the error equals or exceeds a spike threshold. When optimized, the trade-off leads to a deterministic spike firing-rule that generates optimally timed spikes so as to maximize fidelity. The optimal coder is derived in closed-form in the limit of high spike-rates, when the signal can be approximated as a piece-wise constant signal. The predicted spike-times are close to those obtained experimentally in the primary electrosensory afferent neurons of weakly electric fish (Apteronotus leptorhynchus) and pyramidal neurons from the somatosensory cortex of the rat. We suggest that KCNQ/Kv7 channels (underlying the M-current) are good candidates for the decoder. They are widely coupled to metabolic processes and do not inactivate. We conclude that the neural threshold is optimized to generate an energy-efficient and high-fidelity neural code. PMID:26082710

Phase Shifting Capacity of the Circadian Pacemaker Determined by the SCN Neuronal Network Organization

PubMed Central

vanderLeest, Henk Tjebbe; Rohling, Jos H. T.; Michel, Stephan; Meijer, Johanna H.

2009-01-01

Background In mammals, a major circadian pacemaker that drives daily rhythms is located in the suprachiasmatic nuclei (SCN), at the base of the hypothalamus. The SCN receive direct light input via the retino-hypothalamic tract. Light during the early night induces phase delays of circadian rhythms while during the late night it leads to phase advances. The effects of light on the circadian system are strongly dependent on the photoperiod to which animals are exposed. An explanation for this phenomenon is currently lacking. Methodology and Principal Findings We recorded running wheel activity in C57 mice and observed large amplitude phase shifts in short photoperiods and small shifts in long photoperiods. We investigated whether these different light responses under short and long days are expressed within the SCN by electrophysiological recordings of electrical impulse frequency in SCN slices. Application of N-methyl-D-aspartate (NMDA) induced sustained increments in electrical activity that were not significantly different in the slices from long and short photoperiods. These responses led to large phase shifts in slices from short days and small phase shifts in slices from long days. An analysis of neuronal subpopulation activity revealed that in short days the amplitude of the rhythm was larger than in long days. Conclusions The data indicate that the photoperiodic dependent phase responses are intrinsic to the SCN. In contrast to earlier predictions from limit cycle theory, we observed large phase shifting responses in high amplitude rhythms in slices from short days, and small shifts in low amplitude rhythms in slices from long days. We conclude that the photoperiodic dependent phase responses are determined by the SCN and propose that synchronization among SCN neurons enhances the phase shifting capacity of the circadian system. PMID:19305510

Long-Term Temporal Imprecision of Information Coding in the Anterior Cingulate Cortex of Mice with Peripheral Inflammation or Nerve Injury

PubMed Central

Li, Xiang-Yao; Wang, Ning; Wang, Yong-Jie; Zuo, Zhen-Xing; Koga, Kohei; Luo, Fei

2014-01-01

Temporal properties of spike firing in the central nervous system (CNS) are critical for neuronal coding and the precision of information storage. Chronic pain has been reported to affect cognitive and emotional functions, in addition to trigger long-term plasticity in sensory synapses and behavioral sensitization. Less is known about the possible changes in temporal precision of cortical neurons in chronic pain conditions. In the present study, we investigated the temporal precision of action potential firing in the anterior cingulate cortex (ACC) by using both in vivo and in vitro electrophysiological approaches. We found that peripheral inflammation caused by complete Freund's adjuvant (CFA) increased the standard deviation (SD) of spikes latency (also called jitter) of ∼51% of recorded neurons in the ACC of adult rats in vivo. Similar increases in jitter were found in ACC neurons using in vitro brain slices from adult mice with peripheral inflammation or nerve injury. Bath application of glutamate receptor antagonists CNQX and AP5 abolished the enhancement of jitter induced by CFA injection or nerve injury, suggesting that the increased jitter depends on the glutamatergic synaptic transmission. Activation of adenylyl cyclases (ACs) by bath application of forskolin increased jitter, whereas genetic deletion of AC1 abolished the change of jitter caused by CFA inflammation. Our study provides strong evidence for long-term changes of temporal precision of information coding in cortical neurons after peripheral injuries and explains neuronal mechanism for chronic pain caused cognitive and emotional impairment. PMID:25100600

Place and contingency differential responses of monkey septal neurons during conditional place-object discrimination.

PubMed

Kita, T; Nishijo, H; Eifuku, S; Terasawa, K; Ono, T

1995-03-01

To elucidate spatial and cognitive function of the septal nuclei, neural activity was recorded from alert monkeys during performance of a place-dependent go/no-go (PGN) task. Response/reinforcement contingencies of given objects were conditional upon the location of a motorized, movable device (cab) containing a monkey in one of four places. The task was initiated by presentation of the outside view (place phase) followed by presentation of an object (object phase) selected from a total of four. A lever press was reinforced only if the correct object was seen in its corresponding place, and the same object was never reinforced in any of the other three places. Of 430 septal neurons recorded, the responses during the place phase in the four places were significantly different in 58 neurons. Responses of eight of these neurons were also place-differential during the object phase as well as the place phase. Furthermore, when the outside view was not presented before the object phase, differential responses in the object phase disappeared. Responses of 91 neurons in the object phase were differential in terms of go/no-go responses and reward availability. Of these 91 neurons, 72 were further tested on a place-independent asymmetrical go/no-go (AGN) task, which required no conditional discrimination. Forty-three neurons responded differentially only in the PGN task. It is thus concluded that this PGN-specific activity reflected conditional place-object relations. Of the remaining 29 neurons that responded differentially in both tasks, 21 were further tested by a place-independent symmetrical go/no-go task (no-go responses were also rewarded). Responses of 19 of these 21 neurons were related to the reward/nonreward contingency but not to the response contingency. The results suggest that septal nuclei are involved in integrating spatial information, conditional place-object relations, and reward/nonreward contingency.

Temporal coding in a silicon network of integrate-and-fire neurons.

PubMed

Liu, Shih-Chii; Douglas, Rodney

2004-09-01

Spatio-temporal processing of spike trains by neuronal networks depends on a variety of mechanisms distributed across synapses, dendrites, and somata. In natural systems, the spike trains and the processing mechanisms cohere though their common physical instantiation. This coherence is lost when the natural system is encoded for simulation on a general purpose computer. By contrast, analog VLSI circuits are, like neurons, inherently related by their real-time physics, and so, could provide a useful substrate for exploring neuronlike event-based processing. Here, we describe a hybrid analog-digital VLSI chip comprising a set of integrate-and-fire neurons and short-term dynamical synapses that can be configured into simple network architectures with some properties of neocortical neuronal circuits. We show that, despite considerable fabrication variance in the properties of individual neurons, the chip offers a viable substrate for exploring real-time spike-based processing in networks of neurons.

Unfolding the neutron spectrum of a NE213 scintillator using artificial neural networks.

PubMed

Sharghi Ido, A; Bonyadi, M R; Etaati, G R; Shahriari, M

2009-10-01

Artificial neural networks technology has been applied to unfold the neutron spectra from the pulse height distribution measured with NE213 liquid scintillator. Here, both the single and multi-layer perceptron neural network models have been implemented to unfold the neutron spectrum from an Am-Be neutron source. The activation function and the connectivity of the neurons have been investigated and the results have been analyzed in terms of the network's performance. The simulation results show that the neural network that utilizes the Satlins transfer function has the best performance. In addition, omitting the bias connection of the neurons improve the performance of the network. Also, the SCINFUL code is used for generating the response functions in the training phase of the process. Finally, the results of the neural network simulation have been compared with those of the FORIST unfolding code for both (241)Am-Be and (252)Cf neutron sources. The results of neural network are in good agreement with FORIST code.

Sensory Coding and Sensitivity to Local Estrogens Shift during Critical Period Milestones in the Auditory Cortex of Male Songbirds.

PubMed

Vahaba, Daniel M; Macedo-Lima, Matheus; Remage-Healey, Luke

2017-01-01

Vocal learning occurs during an experience-dependent, age-limited critical period early in development. In songbirds, vocal learning begins when presinging birds acquire an auditory memory of their tutor's song (sensory phase) followed by the onset of vocal production and refinement (sensorimotor phase). Hearing is necessary throughout the vocal learning critical period. One key brain area for songbird auditory processing is the caudomedial nidopallium (NCM), a telencephalic region analogous to mammalian auditory cortex. Despite NCM's established role in auditory processing, it is unclear how the response properties of NCM neurons may shift across development. Moreover, communication processing in NCM is rapidly enhanced by local 17β-estradiol (E2) administration in adult songbirds; however, the function of dynamically fluctuating E 2 in NCM during development is unknown. We collected bilateral extracellular recordings in NCM coupled with reverse microdialysis delivery in juvenile male zebra finches ( Taeniopygia guttata ) across the vocal learning critical period. We found that auditory-evoked activity and coding accuracy were substantially higher in the NCM of sensory-aged animals compared to sensorimotor-aged animals. Further, we observed both age-dependent and lateralized effects of local E 2 administration on sensory processing. In sensory-aged subjects, E 2 decreased auditory responsiveness across both hemispheres; however, a similar trend was observed in age-matched control subjects. In sensorimotor-aged subjects, E 2 dampened auditory responsiveness in left NCM but enhanced auditory responsiveness in right NCM. Our results reveal an age-dependent physiological shift in auditory processing and lateralized E 2 sensitivity that each precisely track a key neural "switch point" from purely sensory (pre-singing) to sensorimotor (singing) in developing songbirds.

Sensory Coding and Sensitivity to Local Estrogens Shift during Critical Period Milestones in the Auditory Cortex of Male Songbirds

PubMed Central

2017-01-01

Abstract Vocal learning occurs during an experience-dependent, age-limited critical period early in development. In songbirds, vocal learning begins when presinging birds acquire an auditory memory of their tutor’s song (sensory phase) followed by the onset of vocal production and refinement (sensorimotor phase). Hearing is necessary throughout the vocal learning critical period. One key brain area for songbird auditory processing is the caudomedial nidopallium (NCM), a telencephalic region analogous to mammalian auditory cortex. Despite NCM’s established role in auditory processing, it is unclear how the response properties of NCM neurons may shift across development. Moreover, communication processing in NCM is rapidly enhanced by local 17β-estradiol (E2) administration in adult songbirds; however, the function of dynamically fluctuating E2 in NCM during development is unknown. We collected bilateral extracellular recordings in NCM coupled with reverse microdialysis delivery in juvenile male zebra finches (Taeniopygia guttata) across the vocal learning critical period. We found that auditory-evoked activity and coding accuracy were substantially higher in the NCM of sensory-aged animals compared to sensorimotor-aged animals. Further, we observed both age-dependent and lateralized effects of local E2 administration on sensory processing. In sensory-aged subjects, E2 decreased auditory responsiveness across both hemispheres; however, a similar trend was observed in age-matched control subjects. In sensorimotor-aged subjects, E2 dampened auditory responsiveness in left NCM but enhanced auditory responsiveness in right NCM. Our results reveal an age-dependent physiological shift in auditory processing and lateralized E2 sensitivity that each precisely track a key neural “switch point” from purely sensory (pre-singing) to sensorimotor (singing) in developing songbirds. PMID:29255797

Population responses in primary auditory cortex simultaneously represent the temporal envelope and periodicity features in natural speech.

PubMed

Abrams, Daniel A; Nicol, Trent; White-Schwoch, Travis; Zecker, Steven; Kraus, Nina

2017-05-01

Speech perception relies on a listener's ability to simultaneously resolve multiple temporal features in the speech signal. Little is known regarding neural mechanisms that enable the simultaneous coding of concurrent temporal features in speech. Here we show that two categories of temporal features in speech, the low-frequency speech envelope and periodicity cues, are processed by distinct neural mechanisms within the same population of cortical neurons. We measured population activity in primary auditory cortex of anesthetized guinea pig in response to three variants of a naturally produced sentence. Results show that the envelope of population responses closely tracks the speech envelope, and this cortical activity more closely reflects wider bandwidths of the speech envelope compared to narrow bands. Additionally, neuronal populations represent the fundamental frequency of speech robustly with phase-locked responses. Importantly, these two temporal features of speech are simultaneously observed within neuronal ensembles in auditory cortex in response to clear, conversation, and compressed speech exemplars. Results show that auditory cortical neurons are adept at simultaneously resolving multiple temporal features in extended speech sentences using discrete coding mechanisms. Copyright © 2017 Elsevier B.V. All rights reserved.

Memory modulates journey-dependent coding in the rat hippocampus

PubMed Central

Ferbinteanu, J.; Shirvalkar, P.; Shapiro, M. L.

2011-01-01

Neurons in the rat hippocampus signal current location by firing in restricted areas called place fields. During goal-directed tasks in mazes, place fields can also encode past and future positions through journey-dependent activity, which could guide hippocampus-dependent behavior and underlie other temporally extended memories, such as autobiographical recollections. The relevance of journey-dependent activity for hippocampal-dependent memory, however, is not well understood. To further investigate the relationship between hippocampal journey-dependent activity and memory we compared neural firing in rats performing two mnemonically distinct but behaviorally identical tasks in the plus maze: a hippocampus-dependent spatial navigation task, and a hippocampus-independent cue response task. While place, prospective, and retrospective coding reflected temporally extended behavioral episodes in both tasks, memory strategy altered coding differently before and after the choice point. Before the choice point, when discriminative selection of memory strategy was critical, a switch between the tasks elicited a change in a field’s coding category, so that a field that signaled current location in one task coded pending journeys in the other task. After the choice point, however, when memory strategy became irrelevant, the fields preserved coding categories across tasks, so that the same field consistently signaled either current location or the recent journeys. Additionally, on the start arm firing rates were affected at comparable levels by task and journey, while on the goal arm firing rates predominantly encoded journey. The data demonstrate a direct link between journey-dependent coding and memory, and suggest that episodes are encoded by both population and firing rate coding. PMID:21697365

A Protein Encoded by the Latency-Related Gene of Bovine Herpesvirus 1 Is Expressed in Trigeminal Ganglionic Neurons of Latently Infected Cattle and Interacts with Cyclin-Dependent Kinase 2 during Productive Infection

PubMed Central

Jiang, Yunquan; Hossain, Ashfaque; Winkler, Maria Teresa; Holt, Todd; Doster, Alan; Jones, Clinton

1998-01-01

Despite productive viral gene expression in the peripheral nervous system during acute infection, the bovine herpesvirus 1 (BHV-1) infection cycle is blocked in sensory ganglionic neurons and consequently latency is established. The only abundant viral transcript expressed during latency is the latency-related (LR) RNA. LR gene products inhibit S-phase entry, and binding of the LR protein (LRP) to cyclin A was hypothesized to block cell cycle progression. This study demonstrates LRP is a nuclear protein which is expressed in neurons of latently infected cattle. Affinity chromatography indicated that LRP interacts with cyclin-dependent kinase 2 (cdk2)-cyclin complexes or cdc2-cyclin complexes in transfected human cells or infected bovine cells. After partial purification using three different columns (DEAE-Sepharose, Econo S, and heparin-agarose), LRP was primarily associated with cdk2-cyclin E complexes, an enzyme which is necessary for G1-to-S-phase cell cycle progression. During acute infection of trigeminal ganglia or following dexamethasone-induced reactivation, BHV-1 induces expression of cyclin A in neurons (L. M. Schang, A. Hossain, and C. Jones, J. Virol. 70:3807–3814, 1996). Expression of S-phase regulatory proteins (cyclin A, for example) leads to neuronal apoptosis. Consequently, we hypothesize that interactions between LRP and cell cycle regulatory proteins promote survival of postmitotic neurons during acute infection and/or reactivation. PMID:9733854

A protein encoded by the latency-related gene of bovine herpesvirus 1 is expressed in trigeminal ganglionic neurons of latently infected cattle and interacts with cyclin-dependent kinase 2 during productive infection.

PubMed

Jiang, Y; Hossain, A; Winkler, M T; Holt, T; Doster, A; Jones, C

1998-10-01

Despite productive viral gene expression in the peripheral nervous system during acute infection, the bovine herpesvirus 1 (BHV-1) infection cycle is blocked in sensory ganglionic neurons and consequently latency is established. The only abundant viral transcript expressed during latency is the latency-related (LR) RNA. LR gene products inhibit S-phase entry, and binding of the LR protein (LRP) to cyclin A was hypothesized to block cell cycle progression. This study demonstrates LRP is a nuclear protein which is expressed in neurons of latently infected cattle. Affinity chromatography indicated that LRP interacts with cyclin-dependent kinase 2 (cdk2)-cyclin complexes or cdc2-cyclin complexes in transfected human cells or infected bovine cells. After partial purification using three different columns (DEAE-Sepharose, Econo S, and heparin-agarose), LRP was primarily associated with cdk2-cyclin E complexes, an enzyme which is necessary for G1-to-S-phase cell cycle progression. During acute infection of trigeminal ganglia or following dexamethasone-induced reactivation, BHV-1 induces expression of cyclin A in neurons (L. M. Schang, A. Hossain, and C. Jones, J. Virol. 70:3807-3814, 1996). Expression of S-phase regulatory proteins (cyclin A, for example) leads to neuronal apoptosis. Consequently, we hypothesize that interactions between LRP and cell cycle regulatory proteins promote survival of postmitotic neurons during acute infection and/or reactivation.

Neuronal functions associated with endo- and exocytotic events-cum-molecular trafficking may be cell maturation-dependent: lessons learned from studies on botulism.

PubMed

Ray, Radharaman; Zhang, Peng; Ray, Prabhati

2011-08-01

The passion in the scientific endeavors of Marshall Warren Nirenberg had been his quest for knowledge regarding the storage, retrieval, and processing of information in the cell. After deciphering the genetic code for which he shared the Nobel Prize in Physiology and Medicine in 1968, Nirenberg devoted his attention to unraveling the mysteries in the most complex cellular organization in the body, i.e., the nervous system, especially those governing neuronal development, plasticity, and synaptogenesis. During the tenure of the primary author (RR) as a postdoctoral Staff Fellow in the Nirenberg laboratory in the late seventies to early eighties, he had the opportunity of working on projects related to what Nirenberg used to broadly define as the "synaptic code." The major aspects of these projects dealt with the functional macromolecules relevant to neuronal growth, organization, lineage, selectivity, stabilization, synaptogenesis, and functions such as neuroexocytosis. This author's emphasis was particularly on voltage-gated calcium channels that regulate stimulus-induced neurotransmitter release. One central as well as crucial theme in these studies was the fact that the neurons had to be mature and differentiated in order to study these entities (Science 222: 794-799, 1983; Cold Spring Harb Symp Quant Biol 48: 707-715, 1983). In this communication, we illustrate how did this basic knowledge, i.e., cell maturation-dependent properties being essential for neuronal functions, led to a successful experimental design and demonstration of the validity of the targeted neurologic therapeutic delivery approach based on recombinant botulinum toxin serotype A (BoNT/A) heavy chain (rHC) serving as a neuron-specific targeting molecule (BMC Pharmacol 9: 12, 2009).

Interactive Exploration for Continuously Expanding Neuron Databases.

PubMed

Li, Zhongyu; Metaxas, Dimitris N; Lu, Aidong; Zhang, Shaoting

2017-02-15

This paper proposes a novel framework to help biologists explore and analyze neurons based on retrieval of data from neuron morphological databases. In recent years, the continuously expanding neuron databases provide a rich source of information to associate neuronal morphologies with their functional properties. We design a coarse-to-fine framework for efficient and effective data retrieval from large-scale neuron databases. In the coarse-level, for efficiency in large-scale, we employ a binary coding method to compress morphological features into binary codes of tens of bits. Short binary codes allow for real-time similarity searching in Hamming space. Because the neuron databases are continuously expanding, it is inefficient to re-train the binary coding model from scratch when adding new neurons. To solve this problem, we extend binary coding with online updating schemes, which only considers the newly added neurons and update the model on-the-fly, without accessing the whole neuron databases. In the fine-grained level, we introduce domain experts/users in the framework, which can give relevance feedback for the binary coding based retrieval results. This interactive strategy can improve the retrieval performance through re-ranking the above coarse results, where we design a new similarity measure and take the feedback into account. Our framework is validated on more than 17,000 neuron cells, showing promising retrieval accuracy and efficiency. Moreover, we demonstrate its use case in assisting biologists to identify and explore unknown neurons. Copyright © 2017 Elsevier Inc. All rights reserved.

Clustering of neural code words revealed by a first-order phase transition

NASA Astrophysics Data System (ADS)

Huang, Haiping; Toyoizumi, Taro

2016-06-01

A network of neurons in the central nervous system collectively represents information by its spiking activity states. Typically observed states, i.e., code words, occupy only a limited portion of the state space due to constraints imposed by network interactions. Geometrical organization of code words in the state space, critical for neural information processing, is poorly understood due to its high dimensionality. Here, we explore the organization of neural code words using retinal data by computing the entropy of code words as a function of Hamming distance from a particular reference codeword. Specifically, we report that the retinal code words in the state space are divided into multiple distinct clusters separated by entropy-gaps, and that this structure is shared with well-known associative memory networks in a recallable phase. Our analysis also elucidates a special nature of the all-silent state. The all-silent state is surrounded by the densest cluster of code words and located within a reachable distance from most code words. This code-word space structure quantitatively predicts typical deviation of a state-trajectory from its initial state. Altogether, our findings reveal a non-trivial heterogeneous structure of the code-word space that shapes information representation in a biological network.

Spike Phase Locking in CA1 Pyramidal Neurons depends on Background Conductance and Firing Rate

PubMed Central

Broiche, Tilman; Malerba, Paola; Dorval, Alan D.; Borisyuk, Alla; Fernandez, Fernando R.; White, John A.

2012-01-01

Oscillatory activity in neuronal networks correlates with different behavioral states throughout the nervous system, and the frequency-response characteristics of individual neurons are believed to be critical for network oscillations. Recent in vivo studies suggest that neurons experience periods of high membrane conductance, and that action potentials are often driven by membrane-potential fluctuations in the living animal. To investigate the frequency-response characteristics of CA1 pyramidal neurons in the presence of high conductance and voltage fluctuations, we performed dynamic-clamp experiments in rat hippocampal brain slices. We drove neurons with noisy stimuli that included a sinusoidal component ranging, in different trials, from 0.1 to 500 Hz. In subsequent data analysis, we determined action potential phase-locking profiles with respect to background conductance, average firing rate, and frequency of the sinusoidal component. We found that background conductance and firing rate qualitatively change the phase-locking profiles of CA1 pyramidal neurons vs. frequency. In particular, higher average spiking rates promoted band-pass profiles, and the high-conductance state promoted phase-locking at frequencies well above what would be predicted from changes in the membrane time constant. Mechanistically, spike-rate adaptation and frequency resonance in the spike-generating mechanism are implicated in shaping the different phase-locking profiles. Our results demonstrate that CA1 pyramidal cells can actively change their synchronization properties in response to global changes in activity associated with different behavioral states. PMID:23055508

Origins of correlated activity in an olfactory circuit.

PubMed

Kazama, Hokto; Wilson, Rachel I

2009-09-01

Multineuronal recordings often reveal synchronized spikes in different neurons. The manner in which correlated spike timing affects neural codes depends on the statistics of correlations, which in turn reflects the connectivity that gives rise to correlations. However, determining the connectivity of neurons recorded in vivo can be difficult. We investigated the origins of correlated activity in genetically labeled neurons of the Drosophila antennal lobe. Dual recordings showed synchronized spontaneous spikes in projection neurons (PNs) postsynaptic to the same type of olfactory receptor neuron (ORN). Odors increased these correlations. The primary origin of correlations lies in the divergence of each ORN onto every PN in its glomerulus. Reciprocal PN-PN connections make a smaller contribution to correlations and PN spike trains in different glomeruli were only weakly correlated. PN axons from the same glomerulus reconverge in the lateral horn, where pooling redundant signals may allow lateral horn neurons to average out noise that arises independently in these PNs.

Temporal characteristics of gustatory responses in rat parabrachial neurons vary by stimulus and chemosensitive neuron type.

PubMed

Geran, Laura; Travers, Susan

2013-01-01

It has been demonstrated that temporal features of spike trains can increase the amount of information available for gustatory processing. However, the nature of these temporal characteristics and their relationship to different taste qualities and neuron types are not well-defined. The present study analyzed the time course of taste responses from parabrachial (PBN) neurons elicited by multiple applications of "sweet" (sucrose), "salty" (NaCl), "sour" (citric acid), and "bitter" (quinine and cycloheximide) stimuli in an acute preparation. Time course varied significantly by taste stimulus and best-stimulus classification. Across neurons, the ensemble code for the three electrolytes was similar initially but quinine diverged from NaCl and acid during the second 500 ms of stimulation and all four qualities became distinct just after 1s. This temporal evolution was reflected in significantly broader tuning during the initial response. Metric space analyses of quality discrimination by individual neurons showed that increases in information (H) afforded by temporal factors was usually explained by differences in rate envelope, which had a greater impact during the initial 2s (22.5% increase in H) compared to the later response (9.5%). Moreover, timing had a differential impact according to cell type, with between-quality discrimination in neurons activated maximally by NaCl or citric acid most affected. Timing was also found to dramatically improve within-quality discrimination (80% increase in H) in neurons that responded optimally to bitter stimuli (B-best). Spikes from B-best neurons were also more likely to occur in bursts. These findings suggest that among PBN taste neurons, time-dependent increases in mutual information can arise from stimulus- and neuron-specific differences in response envelope during the initial dynamic period. A stable rate code predominates in later epochs.

Temporal Characteristics of Gustatory Responses in Rat Parabrachial Neurons Vary by Stimulus and Chemosensitive Neuron Type

PubMed Central

Geran, Laura; Travers, Susan

2013-01-01

It has been demonstrated that temporal features of spike trains can increase the amount of information available for gustatory processing. However, the nature of these temporal characteristics and their relationship to different taste qualities and neuron types are not well-defined. The present study analyzed the time course of taste responses from parabrachial (PBN) neurons elicited by multiple applications of “sweet” (sucrose), “salty” (NaCl), “sour” (citric acid), and “bitter” (quinine and cycloheximide) stimuli in an acute preparation. Time course varied significantly by taste stimulus and best-stimulus classification. Across neurons, the ensemble code for the three electrolytes was similar initially but quinine diverged from NaCl and acid during the second 500ms of stimulation and all four qualities became distinct just after 1s. This temporal evolution was reflected in significantly broader tuning during the initial response. Metric space analyses of quality discrimination by individual neurons showed that increases in information (H) afforded by temporal factors was usually explained by differences in rate envelope, which had a greater impact during the initial 2s (22.5% increase in H) compared to the later response (9.5%). Moreover, timing had a differential impact according to cell type, with between-quality discrimination in neurons activated maximally by NaCl or citric acid most affected. Timing was also found to dramatically improve within-quality discrimination (80% increase in H) in neurons that responded optimally to bitter stimuli (B-best). Spikes from B-best neurons were also more likely to occur in bursts. These findings suggest that among PBN taste neurons, time-dependent increases in mutual information can arise from stimulus- and neuron-specific differences in response envelope during the initial dynamic period. A stable rate code predominates in later epochs. PMID:24124597

The Nrf2/SKN-1-dependent glutathione S-transferase π homologue GST-1 inhibits dopamine neuron degeneration in a Caenorhabditis elegans model of manganism.

PubMed

Settivari, Raja; VanDuyn, Natalia; LeVora, Jennifer; Nass, Richard

2013-09-01

Exposure to high levels of manganese (Mn) results in a neurological condition termed manganism, which is characterized by oxidative stress, abnormal dopamine (DA) signaling, and cell death. Epidemiological evidence suggests correlations with occupational exposure to Mn and the development of the movement disorder Parkinson's disease (PD), yet the molecular determinants common between the diseases are ill-defined. Glutathione S-transferases (GSTs) of the class pi (GSTπ) are phase II detoxification enzymes that conjugate both endogenous and exogenous compounds to glutathione to reduce cellular oxidative stress, and their decreased expression has recently been implicated in PD progression. In this study we demonstrate that a Caenorhabditis elegans GSTπ homologue, GST-1, inhibits Mn-induced DA neuron degeneration. We show that GST-1 is expressed in DA neurons, Mn induces GST-1 gene and protein expression, and GST-1-mediated neuroprotection is dependent on the PD-associated transcription factor Nrf2/SKN-1, as a reduction in SKN-1 gene expression results in a decrease in GST-1 protein expression and an increase in DA neuronal death. Furthermore, decreases in gene expression of the SKN-1 inhibitor WDR-23 or the GSTπ-binding cell death activator JNK/JNK-1 result in an increase in resistance to the metal. Finally, we show that the Mn-induced DA neuron degeneration is independent of the dopamine transporter DAT, but is largely dependent on the caspases CED-3 and the novel caspase CSP-1. This study identifies a C. elegans Nrf2/SKN-1-dependent GSTπ homologue, cell death effectors of GSTπ-associated xenobiotic-induced pathology, and provides the first in vivo evidence that a phase II detoxification enzyme may modulate DA neuron vulnerability in manganism. Copyright © 2013 Elsevier Inc. All rights reserved.

Microelectrode array recordings of cultured hippocampal networks reveal a simple model for transcription and protein synthesis-dependent plasticity

PubMed Central

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

Microelectrode array recordings of cultured hippocampal networks reveal a simple model for transcription and protein synthesis-dependent plasticity.

PubMed

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.

Self-Organized Near-Zero-Lag Synchronization Induced by Spike-Timing Dependent Plasticity in Cortical Populations

PubMed Central

Matias, Fernanda S.; Carelli, Pedro V.; Mirasso, Claudio R.; Copelli, Mauro

2015-01-01

Several cognitive tasks related to learning and memory exhibit synchronization of macroscopic cortical areas together with synaptic plasticity at neuronal level. Therefore, there is a growing effort among computational neuroscientists to understand the underlying mechanisms relating synchrony and plasticity in the brain. Here we numerically study the interplay between spike-timing dependent plasticity (STDP) and anticipated synchronization (AS). AS emerges when a dominant flux of information from one area to another is accompanied by a negative time lag (or phase). This means that the receiver region pulses before the sender does. In this paper we study the interplay between different synchronization regimes and STDP at the level of three-neuron microcircuits as well as cortical populations. We show that STDP can promote auto-organized zero-lag synchronization in unidirectionally coupled neuronal populations. We also find synchronization regimes with negative phase difference (AS) that are stable against plasticity. Finally, we show that the interplay between negative phase difference and STDP provides limited synaptic weight distribution without the need of imposing artificial boundaries. PMID:26474165

Spatiotemporal Computations of an Excitable and Plastic Brain: Neuronal Plasticity Leads to Noise-Robust and Noise-Constructive Computations

PubMed Central

Toutounji, Hazem; Pipa, Gordon

2014-01-01

It is a long-established fact that neuronal plasticity occupies the central role in generating neural function and computation. Nevertheless, no unifying account exists of how neurons in a recurrent cortical network learn to compute on temporally and spatially extended stimuli. However, these stimuli constitute the norm, rather than the exception, of the brain's input. Here, we introduce a geometric theory of learning spatiotemporal computations through neuronal plasticity. To that end, we rigorously formulate the problem of neural representations as a relation in space between stimulus-induced neural activity and the asymptotic dynamics of excitable cortical networks. Backed up by computer simulations and numerical analysis, we show that two canonical and widely spread forms of neuronal plasticity, that is, spike-timing-dependent synaptic plasticity and intrinsic plasticity, are both necessary for creating neural representations, such that these computations become realizable. Interestingly, the effects of these forms of plasticity on the emerging neural code relate to properties necessary for both combating and utilizing noise. The neural dynamics also exhibits features of the most likely stimulus in the network's spontaneous activity. These properties of the spatiotemporal neural code resulting from plasticity, having their grounding in nature, further consolidate the biological relevance of our findings. PMID:24651447

Cracking the barcode of fullerene-like cortical microcolumns.

PubMed

Tozzi, Arturo; Peters, James F; Ori, Ottorino

2017-03-22

Artificial neural systems and nervous graph theoretical analysis rely upon the stance that the neural code is embodied in logic circuits, e.g., spatio-temporal sequences of ON/OFF spiking neurons. Nevertheless, this assumption does not fully explain complex brain functions. Here we show how nervous activity, other than logic circuits, could instead depend on topological transformations and symmetry constraints occurring at the micro-level of the cortical microcolumn, i.e., the embryological, anatomical and functional basic unit of the brain. Tubular microcolumns can be flattened in fullerene-like two-dimensional lattices, equipped with about 80 nodes standing for pyramidal neurons where neural computations take place. We show how the countless possible combinations of activated neurons embedded in the lattice resemble a barcode. Despite the fact that further experimental verification is required in order to validate our claim, different assemblies of firing neurons might have the appearance of diverse codes, each one responsible for a single mental activity. A two-dimensional fullerene-like lattice, grounded on simple topological changes standing for pyramidal neurons' activation, not just displays analogies with the real microcolumn's microcircuitry and the neural connectome, but also the potential for the manufacture of plastic, robust and fast artificial networks in robotic forms of full-fledged neural systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Contour Curvature As an Invariant Code for Objects in Visual Area V4

PubMed Central

Pasupathy, Anitha

2016-01-01

Size-invariant object recognition—the ability to recognize objects across transformations of scale—is a fundamental feature of biological and artificial vision. To investigate its basis in the primate cerebral cortex, we measured single neuron responses to stimuli of varying size in visual area V4, a cornerstone of the object-processing pathway, in rhesus monkeys (Macaca mulatta). Leveraging two competing models for how neuronal selectivity for the bounding contours of objects may depend on stimulus size, we show that most V4 neurons (∼70%) encode objects in a size-invariant manner, consistent with selectivity for a size-independent parameter of boundary form: for these neurons, “normalized” curvature, rather than “absolute” curvature, provided a better account of responses. Our results demonstrate the suitability of contour curvature as a basis for size-invariant object representation in the visual cortex, and posit V4 as a foundation for behaviorally relevant object codes. SIGNIFICANCE STATEMENT Size-invariant object recognition is a bedrock for many perceptual and cognitive functions. Despite growing neurophysiological evidence for invariant object representations in the primate cortex, we still lack a basic understanding of the encoding rules that govern them. Classic work in the field of visual shape theory has long postulated that a representation of objects based on information about their bounding contours is well suited to mediate such an invariant code. In this study, we provide the first empirical support for this hypothesis, and its instantiation in single neurons of visual area V4. PMID:27194333

Dynamical responses to external stimuli for both cases of excitatory and inhibitory synchronization in a complex neuronal network.

PubMed

Kim, Sang-Yoon; Lim, Woochang

2017-10-01

For studying how dynamical responses to external stimuli depend on the synaptic-coupling type, we consider two types of excitatory and inhibitory synchronization (i.e., synchronization via synaptic excitation and inhibition) in complex small-world networks of excitatory regular spiking (RS) pyramidal neurons and inhibitory fast spiking (FS) interneurons. For both cases of excitatory and inhibitory synchronization, effects of synaptic couplings on dynamical responses to external time-periodic stimuli S ( t ) (applied to a fraction of neurons) are investigated by varying the driving amplitude A of S ( t ). Stimulated neurons are phase-locked to external stimuli for both cases of excitatory and inhibitory couplings. On the other hand, the stimulation effect on non-stimulated neurons depends on the type of synaptic coupling. The external stimulus S ( t ) makes a constructive effect on excitatory non-stimulated RS neurons (i.e., it causes external phase lockings in the non-stimulated sub-population), while S ( t ) makes a destructive effect on inhibitory non-stimulated FS interneurons (i.e., it breaks up original inhibitory synchronization in the non-stimulated sub-population). As results of these different effects of S ( t ), the type and degree of dynamical response (e.g., synchronization enhancement or suppression), characterized by the dynamical response factor [Formula: see text] (given by the ratio of synchronization degree in the presence and absence of stimulus), are found to vary in a distinctly different way, depending on the synaptic-coupling type. Furthermore, we also measure the matching degree between the dynamics of the two sub-populations of stimulated and non-stimulated neurons in terms of a "cross-correlation" measure [Formula: see text]. With increasing A , based on [Formula: see text], we discuss the cross-correlations between the two sub-populations, affecting the dynamical responses to S ( t ).

Cortical pyramidal cells as non-linear oscillators: experiment and spike-generation theory.

PubMed

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.

Effect of interacting second- and third-order stimulus-dependent correlations on population-coding asymmetries.

PubMed

Montangie, Lisandro; Montani, Fernando

2016-10-01

Spike correlations among neurons are widely encountered in the brain. Although models accounting for pairwise interactions have proved able to capture some of the most important features of population activity at the level of the retina, the evidence shows that pairwise neuronal correlation analysis does not resolve cooperative population dynamics by itself. By means of a series expansion for short time scales of the mutual information conveyed by a population of neurons, the information transmission can be broken down into firing rate and correlational components. In a proposed extension of this framework, we investigate the information components considering both second- and higher-order correlations. We show that the existence of a mixed stimulus-dependent correlation term defines a new scenario for the interplay between pairwise and higher-than-pairwise interactions in noise and signal correlations that would lead either to redundancy or synergy in the information-theoretic sense.

Single neurons in prefrontal cortex encode abstract rules.

PubMed

Wallis, J D; Anderson, K C; Miller, E K

2001-06-21

The ability to abstract principles or rules from direct experience allows behaviour to extend beyond specific circumstances to general situations. For example, we learn the 'rules' for restaurant dining from specific experiences and can then apply them in new restaurants. The use of such rules is thought to depend on the prefrontal cortex (PFC) because its damage often results in difficulty in following rules. Here we explore its neural basis by recording from single neurons in the PFC of monkeys trained to use two abstract rules. They were required to indicate whether two successively presented pictures were the same or different depending on which rule was currently in effect. The monkeys performed this task with new pictures, thus showing that they had learned two general principles that could be applied to stimuli that they had not yet experienced. The most prevalent neuronal activity observed in the PFC reflected the coding of these abstract rules.

Interplay between low threshold voltage-gated K+ channels and synaptic inhibition in neurons of the chicken nucleus laminaris along its frequency axis

PubMed Central

Hamlet, William R.; Liu, Yu-Wei; Tang, Zheng-Quan; Lu, Yong

2014-01-01

Central auditory neurons that localize sound in horizontal space have specialized intrinsic and synaptic cellular mechanisms to tightly control the threshold and timing for action potential generation. However, the critical interplay between intrinsic voltage-gated conductances and extrinsic synaptic conductances in determining neuronal output are not well understood. In chicken, neurons in the nucleus laminaris (NL) encode sound location using interaural time difference (ITD) as a cue. Along the tonotopic axis of NL, there exist robust differences among low, middle, and high frequency (LF, MF, and HF, respectively) neurons in a variety of neuronal properties such as low threshold voltage-gated K+ (LTK) channels and depolarizing inhibition. This establishes NL as an ideal model to examine the interactions between LTK currents and synaptic inhibition across the tonotopic axis. Using whole-cell patch clamp recordings prepared from chicken embryos (E17–E18), we found that LTK currents were larger in MF and HF neurons than in LF neurons. Kinetic analysis revealed that LTK currents in MF neurons activated at lower voltages than in LF and HF neurons, whereas the inactivation of the currents was similar across the tonotopic axis. Surprisingly, blockade of LTK currents using dendrotoxin-I (DTX) tended to broaden the duration and increase the amplitude of the depolarizing inhibitory postsynaptic potentials (IPSPs) in NL neurons without dependence on coding frequency regions. Analyses of the effects of DTX on inhibitory postsynaptic currents led us to interpret this unexpected observation as a result of primarily postsynaptic effects of LTK currents on MF and HF neurons, and combined presynaptic and postsynaptic effects in LF neurons. Furthermore, DTX transferred subthreshold IPSPs to spikes. Taken together, the results suggest a critical role for LTK currents in regulating inhibitory synaptic strength in ITD-coding neurons at various frequencies. PMID:24904297

Interplay between low threshold voltage-gated K(+) channels and synaptic inhibition in neurons of the chicken nucleus laminaris along its frequency axis.

PubMed

Hamlet, William R; Liu, Yu-Wei; Tang, Zheng-Quan; Lu, Yong

2014-01-01

Central auditory neurons that localize sound in horizontal space have specialized intrinsic and synaptic cellular mechanisms to tightly control the threshold and timing for action potential generation. However, the critical interplay between intrinsic voltage-gated conductances and extrinsic synaptic conductances in determining neuronal output are not well understood. In chicken, neurons in the nucleus laminaris (NL) encode sound location using interaural time difference (ITD) as a cue. Along the tonotopic axis of NL, there exist robust differences among low, middle, and high frequency (LF, MF, and HF, respectively) neurons in a variety of neuronal properties such as low threshold voltage-gated K(+) (LTK) channels and depolarizing inhibition. This establishes NL as an ideal model to examine the interactions between LTK currents and synaptic inhibition across the tonotopic axis. Using whole-cell patch clamp recordings prepared from chicken embryos (E17-E18), we found that LTK currents were larger in MF and HF neurons than in LF neurons. Kinetic analysis revealed that LTK currents in MF neurons activated at lower voltages than in LF and HF neurons, whereas the inactivation of the currents was similar across the tonotopic axis. Surprisingly, blockade of LTK currents using dendrotoxin-I (DTX) tended to broaden the duration and increase the amplitude of the depolarizing inhibitory postsynaptic potentials (IPSPs) in NL neurons without dependence on coding frequency regions. Analyses of the effects of DTX on inhibitory postsynaptic currents led us to interpret this unexpected observation as a result of primarily postsynaptic effects of LTK currents on MF and HF neurons, and combined presynaptic and postsynaptic effects in LF neurons. Furthermore, DTX transferred subthreshold IPSPs to spikes. Taken together, the results suggest a critical role for LTK currents in regulating inhibitory synaptic strength in ITD-coding neurons at various frequencies.

Neural Oscillations and Synchrony in Brain Dysfunction and Neuropsychiatric Disorders: It's About Time.

PubMed

Mathalon, Daniel H; Sohal, Vikaas S

2015-08-01

Neural oscillations are rhythmic fluctuations over time in the activity or excitability of single neurons, local neuronal populations or "assemblies," and/or multiple regionally distributed neuronal assemblies. Synchronized oscillations among large numbers of neurons are evident in electrocorticographic, electroencephalographic, magnetoencephalographic, and local field potential recordings and are generally understood to depend on inhibition that paces assemblies of excitatory neurons to produce alternating temporal windows of reduced and increased excitability. Synchronization of neural oscillations is supported by the extensive networks of local and long-range feedforward and feedback bidirectional connections between neurons. Here, we review some of the major methods and measures used to characterize neural oscillations, with a focus on gamma oscillations. Distinctions are drawn between stimulus-independent oscillations recorded during resting states or intervals between task events, stimulus-induced oscillations that are time locked but not phase locked to stimuli, and stimulus-evoked oscillations that are both time and phase locked to stimuli. Synchrony of oscillations between recording sites, and between the amplitudes and phases of oscillations of different frequencies (cross-frequency coupling), is described and illustrated. Molecular mechanisms underlying gamma oscillations are also reviewed. Ultimately, understanding the temporal organization of neuronal network activity, including interactions between neural oscillations, is critical for elucidating brain dysfunction in neuropsychiatric disorders.

Global dynamics of a stochastic neuronal oscillator

NASA Astrophysics Data System (ADS)

Yamanobe, Takanobu

2013-11-01

Nonlinear oscillators have been used to model neurons that fire periodically in the absence of input. These oscillators, which are called neuronal oscillators, share some common response structures with other biological oscillations such as cardiac cells. In this study, we analyze the dependence of the global dynamics of an impulse-driven stochastic neuronal oscillator on the relaxation rate to the limit cycle, the strength of the intrinsic noise, and the impulsive input parameters. To do this, we use a Markov operator that both reflects the density evolution of the oscillator and is an extension of the phase transition curve, which describes the phase shift due to a single isolated impulse. Previously, we derived the Markov operator for the finite relaxation rate that describes the dynamics of the entire phase plane. Here, we construct a Markov operator for the infinite relaxation rate that describes the stochastic dynamics restricted to the limit cycle. In both cases, the response of the stochastic neuronal oscillator to time-varying impulses is described by a product of Markov operators. Furthermore, we calculate the number of spikes between two consecutive impulses to relate the dynamics of the oscillator to the number of spikes per unit time and the interspike interval density. Specifically, we analyze the dynamics of the number of spikes per unit time based on the properties of the Markov operators. Each Markov operator can be decomposed into stationary and transient components based on the properties of the eigenvalues and eigenfunctions. This allows us to evaluate the difference in the number of spikes per unit time between the stationary and transient responses of the oscillator, which we show to be based on the dependence of the oscillator on past activity. Our analysis shows how the duration of the past neuronal activity depends on the relaxation rate, the noise strength, and the impulsive input parameters.

Global dynamics of a stochastic neuronal oscillator.

PubMed

Yamanobe, Takanobu

2013-11-01

Nonlinear oscillators have been used to model neurons that fire periodically in the absence of input. These oscillators, which are called neuronal oscillators, share some common response structures with other biological oscillations such as cardiac cells. In this study, we analyze the dependence of the global dynamics of an impulse-driven stochastic neuronal oscillator on the relaxation rate to the limit cycle, the strength of the intrinsic noise, and the impulsive input parameters. To do this, we use a Markov operator that both reflects the density evolution of the oscillator and is an extension of the phase transition curve, which describes the phase shift due to a single isolated impulse. Previously, we derived the Markov operator for the finite relaxation rate that describes the dynamics of the entire phase plane. Here, we construct a Markov operator for the infinite relaxation rate that describes the stochastic dynamics restricted to the limit cycle. In both cases, the response of the stochastic neuronal oscillator to time-varying impulses is described by a product of Markov operators. Furthermore, we calculate the number of spikes between two consecutive impulses to relate the dynamics of the oscillator to the number of spikes per unit time and the interspike interval density. Specifically, we analyze the dynamics of the number of spikes per unit time based on the properties of the Markov operators. Each Markov operator can be decomposed into stationary and transient components based on the properties of the eigenvalues and eigenfunctions. This allows us to evaluate the difference in the number of spikes per unit time between the stationary and transient responses of the oscillator, which we show to be based on the dependence of the oscillator on past activity. Our analysis shows how the duration of the past neuronal activity depends on the relaxation rate, the noise strength, and the impulsive input parameters.

Predictive Feedback Can Account for Biphasic Responses in the Lateral Geniculate Nucleus

PubMed Central

Jehee, Janneke F. M.; Ballard, Dana H.

2009-01-01

Biphasic neural response properties, where the optimal stimulus for driving a neural response changes from one stimulus pattern to the opposite stimulus pattern over short periods of time, have been described in several visual areas, including lateral geniculate nucleus (LGN), primary visual cortex (V1), and middle temporal area (MT). We describe a hierarchical model of predictive coding and simulations that capture these temporal variations in neuronal response properties. We focus on the LGN-V1 circuit and find that after training on natural images the model exhibits the brain's LGN-V1 connectivity structure, in which the structure of V1 receptive fields is linked to the spatial alignment and properties of center-surround cells in the LGN. In addition, the spatio-temporal response profile of LGN model neurons is biphasic in structure, resembling the biphasic response structure of neurons in cat LGN. Moreover, the model displays a specific pattern of influence of feedback, where LGN receptive fields that are aligned over a simple cell receptive field zone of the same polarity decrease their responses while neurons of opposite polarity increase their responses with feedback. This phase-reversed pattern of influence was recently observed in neurophysiology. These results corroborate the idea that predictive feedback is a general coding strategy in the brain. PMID:19412529

Paradox of pattern separation and adult neurogenesis: A dual role for new neurons balancing memory resolution and robustness.

PubMed

Johnston, Stephen T; Shtrahman, Matthew; Parylak, Sarah; Gonçalves, J Tiago; Gage, Fred H

2016-03-01

Hippocampal adult neurogenesis is thought to subserve pattern separation, the process by which similar patterns of neuronal inputs are transformed into distinct neuronal representations, permitting the discrimination of highly similar stimuli in hippocampus-dependent tasks. However, the mechanism by which immature adult-born dentate granule neurons cells (abDGCs) perform this function remains unknown. Two theories of abDGC function, one by which abDGCs modulate and sparsify activity in the dentate gyrus and one by which abDGCs act as autonomous coding units, are generally suggested to be mutually exclusive. This review suggests that these two mechanisms work in tandem to dynamically regulate memory resolution while avoiding memory interference and maintaining memory robustness. Copyright © 2015 Elsevier Inc. All rights reserved.

Coding stimulus amplitude by correlated neural activity

NASA Astrophysics Data System (ADS)

Metzen, Michael G.; Ávila-Åkerberg, Oscar; Chacron, Maurice J.

2015-04-01

While correlated activity is observed ubiquitously in the brain, its role in neural coding has remained controversial. Recent experimental results have demonstrated that correlated but not single-neuron activity can encode the detailed time course of the instantaneous amplitude (i.e., envelope) of a stimulus. These have furthermore demonstrated that such coding required and was optimal for a nonzero level of neural variability. However, a theoretical understanding of these results is still lacking. Here we provide a comprehensive theoretical framework explaining these experimental findings. Specifically, we use linear response theory to derive an expression relating the correlation coefficient to the instantaneous stimulus amplitude, which takes into account key single-neuron properties such as firing rate and variability as quantified by the coefficient of variation. The theoretical prediction was in excellent agreement with numerical simulations of various integrate-and-fire type neuron models for various parameter values. Further, we demonstrate a form of stochastic resonance as optimal coding of stimulus variance by correlated activity occurs for a nonzero value of noise intensity. Thus, our results provide a theoretical explanation of the phenomenon by which correlated but not single-neuron activity can code for stimulus amplitude and how key single-neuron properties such as firing rate and variability influence such coding. Correlation coding by correlated but not single-neuron activity is thus predicted to be a ubiquitous feature of sensory processing for neurons responding to weak input.

A neural mechanism of dynamic gating of task-relevant information by top-down influence in primary visual cortex.

PubMed

Kamiyama, Akikazu; Fujita, Kazuhisa; Kashimori, Yoshiki

2016-12-01

Visual recognition involves bidirectional information flow, which consists of bottom-up information coding from retina and top-down information coding from higher visual areas. Recent studies have demonstrated the involvement of early visual areas such as primary visual area (V1) in recognition and memory formation. V1 neurons are not passive transformers of sensory inputs but work as adaptive processor, changing their function according to behavioral context. Top-down signals affect tuning property of V1 neurons and contribute to the gating of sensory information relevant to behavior. However, little is known about the neuronal mechanism underlying the gating of task-relevant information in V1. To address this issue, we focus on task-dependent tuning modulations of V1 neurons in two tasks of perceptual learning. We develop a model of the V1, which receives feedforward input from lateral geniculate nucleus and top-down input from a higher visual area. We show here that the change in a balance between excitation and inhibition in V1 connectivity is necessary for gating task-relevant information in V1. The balance change well accounts for the modulations of tuning characteristic and temporal properties of V1 neuronal responses. We also show that the balance change of V1 connectivity is shaped by top-down signals with temporal correlations reflecting the perceptual strategies of the two tasks. We propose a learning mechanism by which synaptic balance is modulated. To conclude, top-down signal changes the synaptic balance between excitation and inhibition in V1 connectivity, enabling early visual area such as V1 to gate context-dependent information under multiple task performances. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Dynamic Divisive Normalization Predicts Time-Varying Value Coding in Decision-Related Circuits

PubMed Central

LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W.

2014-01-01

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. PMID:25429145

Polarized skylight navigation in insects: model and electrophysiology of e-vector coding by neurons in the central complex.

PubMed

Sakura, Midori; Lambrinos, Dimitrios; Labhart, Thomas

2008-02-01

Many insects exploit skylight polarization for visual compass orientation or course control. As found in crickets, the peripheral visual system (optic lobe) contains three types of polarization-sensitive neurons (POL neurons), which are tuned to different ( approximately 60 degrees diverging) e-vector orientations. Thus each e-vector orientation elicits a specific combination of activities among the POL neurons coding any e-vector orientation by just three neural signals. In this study, we hypothesize that in the presumed orientation center of the brain (central complex) e-vector orientation is population-coded by a set of "compass neurons." Using computer modeling, we present a neural network model transforming the signal triplet provided by the POL neurons to compass neuron activities coding e-vector orientation by a population code. Using intracellular electrophysiology and cell marking, we present evidence that neurons with the response profile of the presumed compass neurons do indeed exist in the insect brain: each of these compass neuron-like (CNL) cells is activated by a specific e-vector orientation only and otherwise remains silent. Morphologically, CNL cells are tangential neurons extending from the lateral accessory lobe to the lower division of the central body. Surpassing the modeled compass neurons in performance, CNL cells are insensitive to the degree of polarization of the stimulus between 99% and at least down to 18% polarization and thus largely disregard variations of skylight polarization due to changing solar elevations or atmospheric conditions. This suggests that the polarization vision system includes a gain control circuit keeping the output activity at a constant level.

Context-dependent modulation of Pol II CTD phosphatase SSUP-72 regulates alternative polyadenylation in neuronal development

PubMed Central

Chen, Fei; Zhou, Yu; Qi, Yingchuan B.; Khivansara, Vishal; Li, Hairi; Chun, Sang Young; Kim, John K.; Fu, Xiang-Dong; Jin, Yishi

2015-01-01

Alternative polyadenylation (APA) is widespread in neuronal development and activity-mediated neural plasticity. However, the underlying molecular mechanisms are largely unknown. We used systematic genetic studies and genome-wide surveys of the transcriptional landscape to identify a context-dependent regulatory pathway controlling APA in the Caenorhabditis elegans nervous system. Loss of function in ssup-72, a Ser5 phosphatase for the RNA polymerase II (Pol II) C-terminal domain (CTD), dampens transcription termination at a strong intronic polyadenylation site (PAS) in unc-44/ankyrin yet promotes termination at the weak intronic PAS of the MAP kinase dlk-1. A nuclear protein, SYDN-1, which regulates neuronal development, antagonizes the function of SSUP-72 and several nuclear polyadenylation factors. This regulatory pathway allows the production of a neuron-specific isoform of unc-44 and an inhibitory isoform of dlk-1. Dysregulation of the unc-44 and dlk-1 mRNA isoforms in sydn-1 mutants impairs neuronal development. Deleting the intronic PAS of unc-44 results in increased pre-mRNA processing of neuronal ankyrin and suppresses sydn-1 mutants. These results reveal a mechanism by which regulation of CTD phosphorylation controls coding region APA in the nervous system. PMID:26588990

Epigenetic Basis of Neuronal and Synaptic Plasticity.

PubMed

Karpova, Nina N; Sales, Amanda J; Joca, Samia R

2017-01-01

Neuronal network and plasticity change as a function of experience. Altered neural connectivity leads to distinct transcriptional programs of neuronal plasticity-related genes. The environmental challenges throughout life may promote long-lasting reprogramming of gene expression and the development of brain disorders. The modifications in neuronal epigenome mediate gene-environmental interactions and are required for activity-dependent regulation of neuronal differentiation, maturation and plasticity. Here, we highlight the latest advances in understanding the role of the main players of epigenetic machinery (DNA methylation and demethylation, histone modifications, chromatin-remodeling enzymes, transposons, and non-coding RNAs) in activity-dependent and long- term neural and synaptic plasticity. The review focuses on both the transcriptional and post-transcriptional regulation of gene expression levels, including the processes of promoter activation, alternative splicing, regulation of stability of gene transcripts by natural antisense RNAs, and alternative polyadenylation. Further, we discuss the epigenetic aspects of impaired neuronal plasticity and the pathogenesis of neurodevelopmental (Rett syndrome, Fragile X Syndrome, genomic imprinting disorders, schizophrenia, and others), stressrelated (mood disorders) and neurodegenerative Alzheimer's, Parkinson's and Huntington's disorders. The review also highlights the pharmacological compounds that modulate epigenetic programming of gene expression, the potential treatment strategies of discussed brain disorders, and the questions that should be addressed during the development of effective and safe approaches for the treatment of brain disorders.

Bitter Taste Stimuli Induce Differential Neural Codes in Mouse Brain

PubMed Central

Wilson, David M.; Boughter, John D.; Lemon, Christian H.

2012-01-01

A growing literature suggests taste stimuli commonly classified as “bitter” induce heterogeneous neural and perceptual responses. Here, the central processing of bitter stimuli was studied in mice with genetically controlled bitter taste profiles. Using these mice removed genetic heterogeneity as a factor influencing gustatory neural codes for bitter stimuli. Electrophysiological activity (spikes) was recorded from single neurons in the nucleus tractus solitarius during oral delivery of taste solutions (26 total), including concentration series of the bitter tastants quinine, denatonium benzoate, cycloheximide, and sucrose octaacetate (SOA), presented to the whole mouth for 5 s. Seventy-nine neurons were sampled; in many cases multiple cells (2 to 5) were recorded from a mouse. Results showed bitter stimuli induced variable gustatory activity. For example, although some neurons responded robustly to quinine and cycloheximide, others displayed concentration-dependent activity (p<0.05) to quinine but not cycloheximide. Differential activity to bitter stimuli was observed across multiple neurons recorded from one animal in several mice. Across all cells, quinine and denatonium induced correlated spatial responses that differed (p<0.05) from those to cycloheximide and SOA. Modeling spatiotemporal neural ensemble activity revealed responses to quinine/denatonium and cycloheximide/SOA diverged during only an early, at least 1 s wide period of the taste response. Our findings highlight how temporal features of sensory processing contribute differences among bitter taste codes and build on data suggesting heterogeneity among “bitter” stimuli, data that challenge a strict monoguesia model for the bitter quality. PMID:22844505

Coding of cognitive magnitude: compressed scaling of numerical information in the primate prefrontal cortex.

PubMed

Nieder, Andreas; Miller, Earl K

2003-01-09

Whether cognitive representations are better conceived as language-based, symbolic representations or perceptually related, analog representations is a subject of debate. If cognitive processes parallel perceptual processes, then fundamental psychophysical laws should hold for each. To test this, we analyzed both behavioral and neuronal representations of numerosity in the prefrontal cortex of rhesus monkeys. The data were best described by a nonlinearly compressed scaling of numerical information, as postulated by the Weber-Fechner law or Stevens' law for psychophysical/sensory magnitudes. This nonlinear compression was observed on the neural level during the acquisition phase of the task and maintained through the memory phase with no further compression. These results suggest that certain cognitive and perceptual/sensory representations share the same fundamental mechanisms and neural coding schemes.

Responses of flocculus and vestibular nuclei neurons in Weaver mutant mice (B6CBA wv/wv) to combined head and body rotation.

PubMed

Grüsser-Cornehls, U

1995-01-01

The responses of vestibular nuclei (Vn) neurons and floccular Purkinje (P) cells to natural stimulation of the horizontal canals were recorded in paralyzed Weaver mutant mice. The Weaver mice suffer from an almost complete postnatal degeneration of granule cells and a portion of the P cells (Sidman et al. 1965). Parallel fibers are never elaborated (Bradley and Berry 1978). Recording sites were localized by means of small, iontophoretically applied HRP markings. Phase and sensitivity were analyzed by a Fourier analysis and a "best sine fitting" program. As in the normal "control" mice (Grüsser-Cornehls et al. 1995), the "simple spike" discharges of Vn and P cells in Weaver mutant mice are modulated sinusoidally upon sinusoidal stimulation. The neuronal response amplitude at fundamental frequency (determined from peristimulus time histograms, PSTHs increased with frequency (0.05-0.5 Hz) for both Vn and floccular neurons. The stimulus frequency/response amplitude and sensitivity (re velocity) curves for floccular neurons are distinctly lower in magnitude than those of Vn neurons (P < 0.01). In our sample of neurons, the Vn neurons curves of the mutants display a remarkable be behavior: the mean value curve of type I neurons is shifted upward, indicating a loss of inhibition but that of type II, downward, demonstrating a downregulation in comparison with the control values. The difference between the two curves is statistically significant (P < 0.001). The mean value curve of all mutant Vn neurons depends on the different fractions of type I and type II neurons in the sample investigated. In our investigations, the mean value curves of both type I and type II neurons also exceed those of the normal controls. The phase shift relative to head angular velocity in the midfrequency range in Vn neurons was very similar to that in normal controls, but the phase advance in the range of 0.3-0.5 Hz was somewhat larger and the SD larger over the whole range tested. Concerning the phase relationship for floccular neurons, a major difference occurred in contrast to the normal controls: the phase lead and phase lag varied from neurons to neuron, in individual neurons from frequency to frequency, and in some neurons distinctly from trial to trail. It is hypothesized that an intact mossy fiber-granule cell-parallel fiber system plays an important role in an orderly information flow, transmitted through the P-cell axons, and that the morphological disruption has implications for target cell activity. There is a strong suggestion that the diverse behavior of type I and type II neurons in the Vn may have implications for the poor motor performance in Weaver mutant mice.

Population coding in sparsely connected networks of noisy neurons.

PubMed

Tripp, Bryan P; Orchard, Jeff

2012-01-01

This study examines the relationship between population coding and spatial connection statistics in networks of noisy neurons. Encoding of sensory information in the neocortex is thought to require coordinated neural populations, because individual cortical neurons respond to a wide range of stimuli, and exhibit highly variable spiking in response to repeated stimuli. Population coding is rooted in network structure, because cortical neurons receive information only from other neurons, and because the information they encode must be decoded by other neurons, if it is to affect behavior. However, population coding theory has often ignored network structure, or assumed discrete, fully connected populations (in contrast with the sparsely connected, continuous sheet of the cortex). In this study, we modeled a sheet of cortical neurons with sparse, primarily local connections, and found that a network with this structure could encode multiple internal state variables with high signal-to-noise ratio. However, we were unable to create high-fidelity networks by instantiating connections at random according to spatial connection probabilities. In our models, high-fidelity networks required additional structure, with higher cluster factors and correlations between the inputs to nearby neurons.

Population receptive field (pRF) measurements of chromatic responses in human visual cortex using fMRI.

PubMed

Welbourne, Lauren E; Morland, Antony B; Wade, Alex R

2018-02-15

The spatial sensitivity of the human visual system depends on stimulus color: achromatic gratings can be resolved at relatively high spatial frequencies while sensitivity to isoluminant color contrast tends to be more low-pass. Models of early spatial vision often assume that the receptive field size of pattern-sensitive neurons is correlated with their spatial frequency sensitivity - larger receptive fields are typically associated with lower optimal spatial frequency. A strong prediction of this model is that neurons coding isoluminant chromatic patterns should have, on average, a larger receptive field size than neurons sensitive to achromatic patterns. Here, we test this assumption using functional magnetic resonance imaging (fMRI). We show that while spatial frequency sensitivity depends on chromaticity in the manner predicted by behavioral measurements, population receptive field (pRF) size measurements show no such dependency. At any given eccentricity, the mean pRF size for neuronal populations driven by luminance, opponent red/green and S-cone isolating contrast, are identical. Changes in pRF size (for example, an increase with eccentricity and visual area hierarchy) are also identical across the three chromatic conditions. These results suggest that fMRI measurements of receptive field size and spatial resolution can be decoupled under some circumstances - potentially reflecting a fundamental dissociation between these parameters at the level of neuronal populations. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

An all-digital receiver for satellite audio broadcasting signals using trellis coded quasi-orthogonal code-division multiplexing

NASA Astrophysics Data System (ADS)

Braun, Walter; Eglin, Peter; Abello, Ricard

1993-02-01

Spread Spectrum Code Division Multiplex is an attractive scheme for the transmission of multiple signals over a satellite transponder. By using orthogonal or quasi-orthogonal spreading codes the interference between the users can be virtually eliminated. However, the acquisition and tracking of the spreading code phase can not take advantage of the code orthogonality since sequential acquisition and Delay-Locked loop tracking depend on correlation with code phases other than the optimal despreading phase. Hence, synchronization is a critical issue in such a system. A demonstration hardware for the verification of the orthogonal CDM synchronization and data transmission concept is being designed and implemented. The system concept, the synchronization scheme, and the implementation are described. The performance of the system is discussed based on computer simulations.

Nuclear Organization in the Spinal Cord Depends on Motor Neuron Lamination Orchestrated by Catenin and Afadin Function.

PubMed

Dewitz, Carola; Pimpinella, Sofia; Hackel, Patrick; Akalin, Altuna; Jessell, Thomas M; Zampieri, Niccolò

2018-02-13

Motor neurons in the spinal cord are found grouped in nuclear structures termed pools, whose position is precisely orchestrated during development. Despite the emerging role of pool organization in the assembly of spinal circuits, little is known about the morphogenetic programs underlying the patterning of motor neuron subtypes. We applied three-dimensional analysis of motor neuron position to reveal the roles and contributions of cell adhesive function by inactivating N-cadherin, catenin, and afadin signaling. Our findings reveal that nuclear organization of motor neurons is dependent on inside-out positioning, orchestrated by N-cadherin, catenin, and afadin activities, controlling cell body layering on the medio-lateral axis. In addition to this lamination-like program, motor neurons undergo a secondary, independent phase of organization. This process results in segregation of motor neurons along the dorso-ventral axis of the spinal cord, does not require N-cadherin or afadin activity, and can proceed even when medio-lateral positioning is perturbed. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Hydroxyurea-mediated neuroblast ablation establishes birthdates of secondary lineages and addresses neuronal interactions in the developing Drosophila brain

PubMed Central

Lovick, Jennifer K.; Hartenstein, Volker

2015-01-01

The Drosophila brain is comprised of neurons formed by approximately 100 lineages, each of which is derived from a stereotyped, asymmetrically dividing neuroblast. Lineages serve as structural and developmental units of Drosophila brain anatomy and reconstruction of lineage projection patterns represents a suitable map of Drosophila brain circuitry at the level of neuron populations (“macro-circuitry”). Two phases of neuroblast proliferation, the first in the embryo and the second during the larval phase (following a period of mitotic quiescence), produce primary and secondary lineages, respectively. Using temporally controlled pulses of hydroxyurea (HU) to ablate neuroblasts and their corresponding secondary lineages during the larval phase, we analyzed the effect on development of primary and secondary lineages in the late larval and adult brain. Our findings indicate that timing of neuroblast re-activation is highly stereotyped, allowing us to establish “birth dates” for all secondary lineages. Furthermore, our results demonstrate that, whereas the trajectory and projection pattern of primary and secondary lineages is established in a largely independent manner, the final branching pattern of secondary neurons is dependent upon the presence of appropriate neuronal targets. Taken together, our data provide new insights into the degree of neuronal plasticity during Drosophila brain development. PMID:25773365

Correlates of decisional dynamics in the dorsal anterior cingulate cortex

PubMed Central

Hayden, Benjamin Y.

2017-01-01

We hypothesized that during binary economic choice, decision makers use the first option they attend as a default to which they compare the second. To test this idea, we recorded activity of neurons in the dorsal anterior cingulate cortex (dACC) of macaques choosing between gambles presented asynchronously. We find that ensemble encoding of the value of the first offer includes both choice-dependent and choice-independent aspects, as if reflecting a partial decision. That is, its responses are neither entirely pre- nor post-decisional. In contrast, coding of the value of the second offer is entirely decision dependent (i.e., post-decisional). This result holds even when offer-value encodings are compared within the same time period. Additionally, we see no evidence for 2 pools of neurons linked to the 2 offers; instead, all comparison appears to occur within a single functionally homogenous pool of task-selective neurons. These observations suggest that economic choices reflect a context-dependent evaluation of attended options. Moreover, they raise the possibility that value representations reflect, to some extent, a tentative commitment to a choice. PMID:29141002

Coding of time-dependent stimuli in homogeneous and heterogeneous neural populations.

PubMed

Beiran, Manuel; Kruscha, Alexandra; Benda, Jan; Lindner, Benjamin

2018-04-01

We compare the information transmission of a time-dependent signal by two types of uncoupled neuron populations that differ in their sources of variability: i) a homogeneous population whose units receive independent noise and ii) a deterministic heterogeneous population, where each unit exhibits a different baseline firing rate ('disorder'). Our criterion for making both sources of variability quantitatively comparable is that the interspike-interval distributions are identical for both systems. Numerical simulations using leaky integrate-and-fire neurons unveil that a non-zero amount of both noise or disorder maximizes the encoding efficiency of the homogeneous and heterogeneous system, respectively, as a particular case of suprathreshold stochastic resonance. Our findings thus illustrate that heterogeneity can render similarly profitable effects for neuronal populations as dynamic noise. The optimal noise/disorder depends on the system size and the properties of the stimulus such as its intensity or cutoff frequency. We find that weak stimuli are better encoded by a noiseless heterogeneous population, whereas for strong stimuli a homogeneous population outperforms an equivalent heterogeneous system up to a moderate noise level. Furthermore, we derive analytical expressions of the coherence function for the cases of very strong noise and of vanishing intrinsic noise or heterogeneity, which predict the existence of an optimal noise intensity. Our results show that, depending on the type of signal, noise as well as heterogeneity can enhance the encoding performance of neuronal populations.

Observability and synchronization of neuron models.

PubMed

Aguirre, Luis A; Portes, Leonardo L; Letellier, Christophe

2017-10-01

Observability is the property that enables recovering the state of a dynamical system from a reduced number of measured variables. In high-dimensional systems, it is therefore important to make sure that the variable recorded to perform the analysis conveys good observability of the system dynamics. The observability of a network of neuron models depends nontrivially on the observability of the node dynamics and on the topology of the network. The aim of this paper is twofold. First, to perform a study of observability using four well-known neuron models by computing three different observability coefficients. This not only clarifies observability properties of the models but also shows the limitations of applicability of each type of coefficients in the context of such models. Second, to study the emergence of phase synchronization in networks composed of neuron models. This is done performing multivariate singular spectrum analysis which, to the best of the authors' knowledge, has not been used in the context of networks of neuron models. It is shown that it is possible to detect phase synchronization: (i) without having to measure all the state variables, but only one (that provides greatest observability) from each node and (ii) without having to estimate the phase.

What is the function of hippocampal theta rhythm?--Linking behavioral data to phasic properties of field potential and unit recording data.

PubMed

Hasselmo, Michael E

2005-01-01

The extensive physiological data on hippocampal theta rhythm provide an opportunity to evaluate hypotheses about the role of theta rhythm for hippocampal network function. Computational models based on these hypotheses help to link behavioral data with physiological measurements of different variables during theta rhythm. This paper reviews work on network models in which theta rhythm contributes to the following functions: (1) separating the dynamics of encoding and retrieval, (2) enhancing the context-dependent retrieval of sequences, (3) buffering of novel information in entorhinal cortex (EC) for episodic encoding, and (4) timing interactions between prefrontal cortex and hippocampus for memory-guided action selection. Modeling shows how these functional mechanisms are related to physiological data from the hippocampal formation, including (1) the phase relationships of synaptic currents during theta rhythm measured by current source density analysis of electroencephalographic data from region CA1 and dentate gyrus, (2) the timing of action potentials, including the theta phase precession of single place cells during running on a linear track, the context-dependent changes in theta phase precession across trials on each day, and the context-dependent firing properties of hippocampal neurons in spatial alternation (e.g., "splitter cells"), (3) the cholinergic regulation of sustained activity in entorhinal cortical neurons, and (4) the phasic timing of prefrontal cortical neurons relative to hippocampal theta rhythm. Copyright 2005 Wiley-Liss, Inc.

CLOCKΔ19 mutation modifies the manner of synchrony among oscillation neurons in the suprachiasmatic nucleus.

PubMed

Sujino, Mitsugu; Asakawa, Takeshi; Nagano, Mamoru; Koinuma, Satoshi; Masumoto, Koh-Hei; Shigeyoshi, Yasufumi

2018-01-16

In mammals, the principal circadian oscillator exists in the hypothalamic suprachiasmatic nucleus (SCN). In the SCN, CLOCK works as an essential component of molecular circadian oscillation, and ClockΔ19 mutant mice show unique characteristics of circadian rhythms such as extended free running periods, amplitude attenuation, and high-magnitude phase-resetting responses. Here we investigated what modifications occur in the spatiotemporal organization of clock gene expression in the SCN of ClockΔ19 mutants. The cultured SCN, sampled from neonatal homozygous ClockΔ19 mice on an ICR strain comprising PERIOD2::LUCIFERASE, demonstrated that the Clock gene mutation not only extends the circadian period, but also affects the spatial phase and period distribution of circadian oscillations in the SCN. In addition, disruption of the synchronization among neurons markedly attenuated the amplitude of the circadian rhythm of individual oscillating neurons in the mutant SCN. Further, with numerical simulations based on the present studies, the findings suggested that, in the SCN of the ClockΔ19 mutant mice, stable oscillation was preserved by the interaction among oscillating neurons, and that the orderly phase and period distribution that makes a phase wave are dependent on the functionality of CLOCK.

Control of neuronal polarity and plasticity--a renaissance for microtubules?

PubMed

Hoogenraad, Casper C; Bradke, Frank

2009-12-01

Microtubules have been regarded as essential structures for stable neuronal morphology but new studies are highlighting their role in dynamic neuronal processes. Recent work demonstrates that the microtubule cytoskeleton has an active role during different phases of neuronal polarization - microtubules and their stability determine axon formation, they maintain the identity of axons and they regulate the dynamics of dendritic spines, the major sites of excitatory synaptic input. Although microtubules fulfill distinct cellular functions at different developmental stages, the underlying molecular mechanisms are remarkably similar. Reccurring themes are that microtubules direct specific membrane traffic and affect actin dynamics to locally organize axon growth and spine dynamics. We review the novel role of microtubules during neuronal development and discuss models for microtubule-dependent signaling in neuronal plasticity.

A G protein-coupled receptor, groom-of-PDF, is required for PDF neuron action in circadian behavior.

PubMed

Lear, Bridget C; Merrill, C Elaine; Lin, Jui-Ming; Schroeder, Analyne; Zhang, Luoying; Allada, Ravi

2005-10-20

The neuropeptide Pigment-Dispersing Factor (PDF) plays a critical role in mediating circadian control of behavior in Drosophila. Here we identify mutants (groom-of-PDF; gop) that display phase-advanced evening activity and poor free-running rhythmicity, phenocopying pdf mutants. In gop mutants, a spontaneous retrotransposon disrupts a coding exon of a G protein-coupled receptor, CG13758. Disruption of the receptor is accompanied by phase-advanced oscillations of the core clock protein PERIOD. Moreover, effects on circadian timing induced by perturbation of PDF neurons require gop. Yet PDF oscillations themselves remain robust in gop mutants, suggesting that GOP acts downstream of PDF. gop is expressed most strongly in the dorsal brain in regions that lie in proximity to PDF-containing nerve terminals. Taken together, these studies implicate GOP as a PDF receptor in Drosophila.

Reduction in ins-7 gene expression in non-neuronal cells of high glucose exposed Caenorhabditis elegans protects from reactive metabolites, preserves neuronal structure and head motility, and prolongs lifespan.

PubMed

Mendler, Michael; Riedinger, Christin; Schlotterer, Andrea; Volk, Nadine; Fleming, Thomas; Herzig, Stephan; Nawroth, Peter P; Morcos, Michael

2017-02-01

Glucose derived metabolism generates reactive metabolites affecting the neuronal system and lifespan in C. elegans. Here, the role of the insulin homologue ins-7 and its downstream effectors in the generation of high glucose induced neuronal damage and shortening of lifespan was studied. In C. elegans high glucose conditions induced the expression of the insulin homologue ins-7. Abrogating ins-7 under high glucose conditions in non-neuronal cells decreased reactive oxygen species (ROS)-formation and accumulation of methylglyoxal derived advanced glycation endproducts (AGEs), prevented structural neuronal damage and normalised head motility and lifespan. The restoration of lifespan by decreased ins-7 expression was dependent on the concerted action of sod-3 and glod-4 coding for the homologues of iron-manganese superoxide dismutase and glyoxalase 1, respectively. Under high glucose conditions mitochondria-mediated oxidative stress and glycation are downstream targets of ins-7. This impairs the neuronal system and longevity via a non-neuronal/neuronal crosstalk by affecting sod-3 and glod-4, thus giving further insight into the pathophysiology of diabetic complications. Copyright © 2017 Elsevier Inc. All rights reserved.

Inducible Knockout of the Cyclin-Dependent Kinase 5 Activator p35 Alters Hippocampal Spatial Coding and Neuronal Excitability

PubMed Central

Kamiki, Eriko; Boehringer, Roman; Polygalov, Denis; Ohshima, Toshio; McHugh, Thomas J.

2018-01-01

p35 is an activating co-factor of Cyclin-dependent kinase 5 (Cdk5), a protein whose dysfunction has been implicated in a wide-range of neurological disorders including cognitive impairment and disease. Inducible deletion of the p35 gene in adult mice results in profound deficits in hippocampal-dependent spatial learning and synaptic physiology, however the impact of the loss of p35 function on hippocampal in vivo physiology and spatial coding remains unknown. Here, we recorded CA1 pyramidal cell activity in freely behaving p35 cKO and control mice and found that place cells in the mutant mice have elevated firing rates and impaired spatial coding, accompanied by changes in the temporal organization of spiking both during exploration and rest. These data shed light on the role of p35 in maintaining cellular and network excitability and provide a physiological correlate of the spatial learning deficits in these mice. PMID:29867369

Coding of Velocity Storage in the Vestibular Nuclei.

PubMed

Yakushin, Sergei B; Raphan, Theodore; Cohen, Bernard

2017-01-01

Semicircular canal afferents sense angular acceleration and output angular velocity with a short time constant of ≈4.5 s. This output is prolonged by a central integrative network, velocity storage that lengthens the time constants of eye velocity. This mechanism utilizes canal, otolith, and visual (optokinetic) information to align the axis of eye velocity toward the spatial vertical when head orientation is off-vertical axis. Previous studies indicated that vestibular-only (VO) and vestibular-pause-saccade (VPS) neurons located in the medial and superior vestibular nucleus could code all aspects of velocity storage. A recently developed technique enabled prolonged recording while animals were rotated and received optokinetic stimulation about a spatial vertical axis while upright, side-down, prone, and supine. Firing rates of 33 VO and 8 VPS neurons were studied in alert cynomolgus monkeys. Majority VO neurons were closely correlated with the horizontal component of velocity storage in head coordinates, regardless of head orientation in space. Approximately, half of all tested neurons (46%) code horizontal component of velocity in head coordinates, while the other half (54%) changed their firing rates as the head was oriented relative to the spatial vertical, coding the horizontal component of eye velocity in spatial coordinates. Some VO neurons only coded the cross-coupled pitch or roll components that move the axis of eye rotation toward the spatial vertical. Sixty-five percent of these VO and VPS neurons were more sensitive to rotation in one direction (predominantly contralateral), providing directional orientation for the subset of VO neurons on either side of the brainstem. This indicates that the three-dimensional velocity storage integrator is composed of directional subsets of neurons that are likely to be the bases for the spatial characteristics of velocity storage. Most VPS neurons ceased firing during drowsiness, but the firing rates of VO neurons were unaffected by states of alertness and declined with the time constant of velocity storage. Thus, the VO neurons are the prime components of the mechanism of coding for velocity storage, whereas the VPS neurons are likely to provide the path from the vestibular to the oculomotor system for the VO neurons.

Coding of Velocity Storage in the Vestibular Nuclei

PubMed Central

Yakushin, Sergei B.; Raphan, Theodore; Cohen, Bernard

2017-01-01

Semicircular canal afferents sense angular acceleration and output angular velocity with a short time constant of ≈4.5 s. This output is prolonged by a central integrative network, velocity storage that lengthens the time constants of eye velocity. This mechanism utilizes canal, otolith, and visual (optokinetic) information to align the axis of eye velocity toward the spatial vertical when head orientation is off-vertical axis. Previous studies indicated that vestibular-only (VO) and vestibular-pause-saccade (VPS) neurons located in the medial and superior vestibular nucleus could code all aspects of velocity storage. A recently developed technique enabled prolonged recording while animals were rotated and received optokinetic stimulation about a spatial vertical axis while upright, side-down, prone, and supine. Firing rates of 33 VO and 8 VPS neurons were studied in alert cynomolgus monkeys. Majority VO neurons were closely correlated with the horizontal component of velocity storage in head coordinates, regardless of head orientation in space. Approximately, half of all tested neurons (46%) code horizontal component of velocity in head coordinates, while the other half (54%) changed their firing rates as the head was oriented relative to the spatial vertical, coding the horizontal component of eye velocity in spatial coordinates. Some VO neurons only coded the cross-coupled pitch or roll components that move the axis of eye rotation toward the spatial vertical. Sixty-five percent of these VO and VPS neurons were more sensitive to rotation in one direction (predominantly contralateral), providing directional orientation for the subset of VO neurons on either side of the brainstem. This indicates that the three-dimensional velocity storage integrator is composed of directional subsets of neurons that are likely to be the bases for the spatial characteristics of velocity storage. Most VPS neurons ceased firing during drowsiness, but the firing rates of VO neurons were unaffected by states of alertness and declined with the time constant of velocity storage. Thus, the VO neurons are the prime components of the mechanism of coding for velocity storage, whereas the VPS neurons are likely to provide the path from the vestibular to the oculomotor system for the VO neurons. PMID:28861030

Collective dynamics in heterogeneous networks of neuronal cellular automata

NASA Astrophysics Data System (ADS)

Manchanda, Kaustubh; Bose, Amitabha; Ramaswamy, Ramakrishna

2017-12-01

We examine the collective dynamics of heterogeneous random networks of model neuronal cellular automata. Each automaton has b active states, a single silent state and r - b - 1 refractory states, and can show 'spiking' or 'bursting' behavior, depending on the values of b. We show that phase transitions that occur in the dynamical activity can be related to phase transitions in the structure of Erdõs-Rényi graphs as a function of edge probability. Different forms of heterogeneity allow distinct structural phase transitions to become relevant. We also show that the dynamics on the network can be described by a semi-annealed process and, as a result, can be related to the Boolean Lyapunov exponent.

Intrinsic Cellular Properties and Connectivity Density Determine Variable Clustering Patterns in Randomly Connected Inhibitory Neural Networks

PubMed Central

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

Orbitofrontal Cortex Signals Expected Outcomes with Predictive Codes When Stable Contingencies Promote the Integration of Reward History

PubMed Central

Shapiro, Matthew L.

2017-01-01

Memory can inform goal-directed behavior by linking current opportunities to past outcomes. The orbitofrontal cortex (OFC) may guide value-based responses by integrating the history of stimulus–reward associations into expected outcomes, representations of predicted hedonic value and quality. Alternatively, the OFC may rapidly compute flexible “online” reward predictions by associating stimuli with the latest outcome. OFC neurons develop predictive codes when rats learn to associate arbitrary stimuli with outcomes, but the extent to which predictive coding depends on most recent events and the integrated history of rewards is unclear. To investigate how reward history modulates OFC activity, we recorded OFC ensembles as rats performed spatial discriminations that differed only in the number of rewarded trials between goal reversals. The firing rate of single OFC neurons distinguished identical behaviors guided by different goals. When >20 rewarded trials separated goal switches, OFC ensembles developed stable and anticorrelated population vectors that predicted overall choice accuracy and the goal selected in single trials. When <10 rewarded trials separated goal switches, OFC population vectors decorrelated rapidly after each switch, but did not develop anticorrelated firing patterns or predict choice accuracy. The results show that, whereas OFC signals respond rapidly to contingency changes, they predict choices only when reward history is relatively stable, suggesting that consecutive rewarded episodes are needed for OFC computations that integrate reward history into expected outcomes. SIGNIFICANCE STATEMENT Adapting to changing contingencies and making decisions engages the orbitofrontal cortex (OFC). Previous work shows that OFC function can either improve or impair learning depending on reward stability, suggesting that OFC guides behavior optimally when contingencies apply consistently. The mechanisms that link reward history to OFC computations remain obscure. Here, we examined OFC unit activity as rodents performed tasks controlled by contingencies that varied reward history. When contingencies were stable, OFC neurons signaled past, present, and pending events; when contingencies were unstable, past and present coding persisted, but predictive coding diminished. The results suggest that OFC mechanisms require stable contingencies across consecutive episodes to integrate reward history, represent predicted outcomes, and inform goal-directed choices. PMID:28115481

Biological conservation law as an emerging functionality in dynamical neuronal networks.

PubMed

Podobnik, Boris; Jusup, Marko; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M; Stanley, H Eugene

2017-11-07

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law-the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective.

Biological conservation law as an emerging functionality in dynamical neuronal networks

PubMed Central

Podobnik, Boris; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M.

2017-01-01

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law—the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective. PMID:29078286

Frequency-dependent reliability of spike propagation is function of axonal voltage-gated sodium channels in cerebellar Purkinje cells.

PubMed

Yang, Zhilai; Wang, Jin-Hui

2013-12-01

The spike propagation on nerve axons, like synaptic transmission, is essential to ensure neuronal communication. The secure propagation of sequential spikes toward axonal terminals has been challenged in the neurons with a high firing rate, such as cerebellar Purkinje cells. The shortfall of spike propagation makes some digital spikes disappearing at axonal terminals, such that the elucidation of the mechanisms underlying spike propagation reliability is crucial to find the strategy of preventing loss of neuronal codes. As the spike propagation failure is influenced by the membrane potentials, this process is likely caused by altering the functional status of voltage-gated sodium channels (VGSC). We examined this hypothesis in Purkinje cells by using pair-recordings at their somata and axonal blebs in cerebellar slices. The reliability of spike propagation was deteriorated by elevating spike frequency. The frequency-dependent reliability of spike propagation was attenuated by inactivating VGSCs and improved by removing their inactivation. Thus, the functional status of axonal VGSCs influences the reliability of spike propagation.

Distributed coding of actual and hypothetical outcomes in the orbital and dorsolateral prefrontal cortex

PubMed Central

Abe, Hiroshi; Lee, Daeyeol

2011-01-01

SUMMARY Knowledge about hypothetical outcomes from unchosen actions is beneficial only when such outcomes can be correctly attributed to specific actions. Here, we show that during a simulated rock-paper-scissors game, rhesus monkeys can adjust their choice behaviors according to both actual and hypothetical outcomes from their chosen and unchosen actions, respectively. In addition, neurons in both dorsolateral prefrontal cortex and orbitofrontal cortex encoded the signals related to actual and hypothetical outcomes immediately after they were revealed to the animal. Moreover, compared to the neurons in the orbitofrontal cortex, those in the dorsolateral prefrontal cortex were more likely to change their activity according to the hypothetical outcomes from specific actions. Conjunctive and parallel coding of multiple actions and their outcomes in the prefrontal cortex might enhance the efficiency of reinforcement learning and also contribute to their context-dependent memory. PMID:21609828

Noise-enhanced coding in phasic neuron spike trains.

PubMed

Ly, Cheng; Doiron, Brent

2017-01-01

The stochastic nature of neuronal response has lead to conjectures about the impact of input fluctuations on the neural coding. For the most part, low pass membrane integration and spike threshold dynamics have been the primary features assumed in the transfer from synaptic input to output spiking. Phasic neurons are a common, but understudied, neuron class that are characterized by a subthreshold negative feedback that suppresses spike train responses to low frequency signals. Past work has shown that when a low frequency signal is accompanied by moderate intensity broadband noise, phasic neurons spike trains are well locked to the signal. We extend these results with a simple, reduced model of phasic activity that demonstrates that a non-Markovian spike train structure caused by the negative feedback produces a noise-enhanced coding. Further, this enhancement is sensitive to the timescales, as opposed to the intensity, of a driving signal. Reduced hazard function models show that noise-enhanced phasic codes are both novel and separate from classical stochastic resonance reported in non-phasic neurons. The general features of our theory suggest that noise-enhanced codes in excitable systems with subthreshold negative feedback are a particularly rich framework to study.

Spike Code Flow in Cultured Neuronal Networks.

PubMed

Tamura, Shinichi; Nishitani, Yoshi; Hosokawa, Chie; Miyoshi, Tomomitsu; Sawai, Hajime; Kamimura, Takuya; Yagi, Yasushi; Mizuno-Matsumoto, Yuko; Chen, Yen-Wei

2016-01-01

We observed spike trains produced by one-shot electrical stimulation with 8 × 8 multielectrodes in cultured neuronal networks. Each electrode accepted spikes from several neurons. We extracted the short codes from spike trains and obtained a code spectrum with a nominal time accuracy of 1%. We then constructed code flow maps as movies of the electrode array to observe the code flow of "1101" and "1011," which are typical pseudorandom sequence such as that we often encountered in a literature and our experiments. They seemed to flow from one electrode to the neighboring one and maintained their shape to some extent. To quantify the flow, we calculated the "maximum cross-correlations" among neighboring electrodes, to find the direction of maximum flow of the codes with lengths less than 8. Normalized maximum cross-correlations were almost constant irrespective of code. Furthermore, if the spike trains were shuffled in interval orders or in electrodes, they became significantly small. Thus, the analysis suggested that local codes of approximately constant shape propagated and conveyed information across the network. Hence, the codes can serve as visible and trackable marks of propagating spike waves as well as evaluating information flow in the neuronal network.

Phase-specific Surround suppression in Mouse Primary Visual Cortex Correlates with Figure Detection Behavior Based on Phase Discontinuity.

PubMed

Li, Fengling; Jiang, Weiqian; Wang, Tian-Yi; Xie, Taorong; Yao, Haishan

2018-05-21

In the primary visual cortex (V1), neuronal responses to stimuli within the receptive field (RF) are modulated by stimuli in the RF surround. A common effect of surround modulation is surround suppression, which is dependent on the feature difference between stimuli within and surround the RF and is suggested to be involved in the perceptual phenomenon of figure-ground segregation. In this study, we examined the relationship between feature-specific surround suppression of V1 neurons and figure detection behavior based on figure-ground feature difference. We trained freely moving mice to perform a figure detection task using figure and ground gratings that differed in spatial phase. The performance of figure detection increased with the figure-ground phase difference, and was modulated by stimulus contrast. Electrophysiological recordings from V1 in head-fixed mice showed that the increase in phase difference between stimuli within and surround the RF caused a reduction in surround suppression, which was associated with an increase in V1 neural discrimination between stimuli with and without RF-surround phase difference. Consistent with the behavioral performance, the sensitivity of V1 neurons to RF-surround phase difference could be influenced by stimulus contrast. Furthermore, inhibiting V1 by optogenetically activating either parvalbumin (PV)- or somatostatin (SOM)-expressing inhibitory neurons both decreased the behavioral performance of figure detection. Thus, the phase-specific surround suppression in V1 represents a neural correlate of figure detection behavior based on figure-ground phase discontinuity. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.

PubMed

Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W

2014-11-26

Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.

Interaction of cellular and network mechanisms for efficient pheromone coding in moths.

PubMed

Belmabrouk, Hana; Nowotny, Thomas; Rospars, Jean-Pierre; Martinez, Dominique

2011-12-06

Sensory systems, both in the living and in machines, have to be optimized with respect to their environmental conditions. The pheromone subsystem of the olfactory system of moths is a particularly well-defined example in which rapid variations of odor content in turbulent plumes require fast, concentration-invariant neural representations. It is not clear how cellular and network mechanisms in the moth antennal lobe contribute to coding efficiency. Using computational modeling, we show that intrinsic potassium currents (I(A) and I(SK)) in projection neurons may combine with extrinsic inhibition from local interneurons to implement a dual latency code for both pheromone identity and intensity. The mean latency reflects stimulus intensity, whereas latency differences carry concentration-invariant information about stimulus identity. In accordance with physiological results, the projection neurons exhibit a multiphasic response of inhibition-excitation-inhibition. Together with synaptic inhibition, intrinsic currents I(A) and I(SK) account for the first and second inhibitory phases and contribute to a rapid encoding of pheromone information. The first inhibition plays the role of a reset to limit variability in the time to first spike. The second inhibition prevents responses of excessive duration to allow tracking of intermittent stimuli.

Opponent Coding of Sound Location (Azimuth) in Planum Temporale is Robust to Sound-Level Variations

PubMed Central

Derey, Kiki; Valente, Giancarlo; de Gelder, Beatrice; Formisano, Elia

2016-01-01

Coding of sound location in auditory cortex (AC) is only partially understood. Recent electrophysiological research suggests that neurons in mammalian auditory cortex are characterized by broad spatial tuning and a preference for the contralateral hemifield, that is, a nonuniform sampling of sound azimuth. Additionally, spatial selectivity decreases with increasing sound intensity. To accommodate these findings, it has been proposed that sound location is encoded by the integrated activity of neuronal populations with opposite hemifield tuning (“opponent channel model”). In this study, we investigated the validity of such a model in human AC with functional magnetic resonance imaging (fMRI) and a phase-encoding paradigm employing binaural stimuli recorded individually for each participant. In all subjects, we observed preferential fMRI responses to contralateral azimuth positions. Additionally, in most AC locations, spatial tuning was broad and not level invariant. We derived an opponent channel model of the fMRI responses by subtracting the activity of contralaterally tuned regions in bilateral planum temporale. This resulted in accurate decoding of sound azimuth location, which was unaffected by changes in sound level. Our data thus support opponent channel coding as a neural mechanism for representing acoustic azimuth in human AC. PMID:26545618

Mixed-mode oscillations and population bursting in the pre-Bötzinger complex

PubMed Central

Bacak, Bartholomew J; Kim, Taegyo; Smith, Jeffrey C; Rubin, Jonathan E; Rybak, Ilya A

2016-01-01

This study focuses on computational and theoretical investigations of neuronal activity arising in the pre-Bötzinger complex (pre-BötC), a medullary region generating the inspiratory phase of breathing in mammals. A progressive increase of neuronal excitability in medullary slices containing the pre-BötC produces mixed-mode oscillations (MMOs) characterized by large amplitude population bursts alternating with a series of small amplitude bursts. Using two different computational models, we demonstrate that MMOs emerge within a heterogeneous excitatory neural network because of progressive neuronal recruitment and synchronization. The MMO pattern depends on the distributed neuronal excitability, the density and weights of network interconnections, and the cellular properties underlying endogenous bursting. Critically, the latter should provide a reduction of spiking frequency within neuronal bursts with increasing burst frequency and a dependence of the after-burst recovery period on burst amplitude. Our study highlights a novel mechanism by which heterogeneity naturally leads to complex dynamics in rhythmic neuronal populations. DOI: http://dx.doi.org/10.7554/eLife.13403.001 PMID:26974345

Electrophysiological models of neural processing.

PubMed

Nelson, Mark E

2011-01-01

The brain is an amazing information processing system that allows organisms to adaptively monitor and control complex dynamic interactions with their environment across multiple spatial and temporal scales. Mathematical modeling and computer simulation techniques have become essential tools in understanding diverse aspects of neural processing ranging from sub-millisecond temporal coding in the sound localization circuity of barn owls to long-term memory storage and retrieval in humans that can span decades. The processing capabilities of individual neurons lie at the core of these models, with the emphasis shifting upward and downward across different levels of biological organization depending on the nature of the questions being addressed. This review provides an introduction to the techniques for constructing biophysically based models of individual neurons and local networks. Topics include Hodgkin-Huxley-type models of macroscopic membrane currents, Markov models of individual ion-channel currents, compartmental models of neuronal morphology, and network models involving synaptic interactions among multiple neurons.

Rational modulation of neuronal processing with applied electric fields.

PubMed

Bikson, Marom; Radman, Thomas; Datta, Abhishek

2006-01-01

Traditional approaches to electrical stimulation, using trains of supra-threshold pulses to trigger action potentials, may be replaced or augmented by using 'rational' sub-threshold stimulation protocols that incorporate knowledge of single neuron geometry, inhomogeneous tissue properties, and nervous system information coding. Sub-threshold stimulation, at intensities (well) below those sufficient to trigger action potentials, may none-the-less exert a profound effect on brain function through modulation of concomitant neuronal activity. For example, small DC fields may coherently polarize a network of neurons and thus modulate the simultaneous processing of afferent synaptic input as well as resulting changes in synaptic plasticity. Through 'activity-dependent plasticity', sub-threshold fields may allow specific targeting of pathological networks and are thus particularly suitable to overcome the poor anatomical focus of noninvasive (transcranial) electrical stimulation. Additional approaches to improve targeting in transcranial stimulation using novel electrode configurations are also introduced.

A dynamic code for economic object valuation in prefrontal cortex neurons

PubMed Central

Tsutsui, Ken-Ichiro; Grabenhorst, Fabian; Kobayashi, Shunsuke; Schultz, Wolfram

2016-01-01

Neuronal reward valuations provide the physiological basis for economic behaviour. Yet, how such valuations are converted to economic decisions remains unclear. Here we show that the dorsolateral prefrontal cortex (DLPFC) implements a flexible value code based on object-specific valuations by single neurons. As monkeys perform a reward-based foraging task, individual DLPFC neurons signal the value of specific choice objects derived from recent experience. These neuronal object values satisfy principles of competitive choice mechanisms, track performance fluctuations and follow predictions of a classical behavioural model (Herrnstein’s matching law). Individual neurons dynamically encode both, the updating of object values from recently experienced rewards, and their subsequent conversion to object choices during decision-making. Decoding from unselected populations enables a read-out of motivational and decision variables not emphasized by individual neurons. These findings suggest a dynamic single-neuron and population value code in DLPFC that advances from reward experiences to economic object values and future choices. PMID:27618960

Encrypted optical storage with wavelength-key and random phase codes.

PubMed

Matoba, O; Javidi, B

1999-11-10

An encrypted optical memory system that uses a wavelength code as well as input and Fourier-plane random phase codes is proposed. Original data are illuminated by a coherent light source with a specified wavelength and are then encrypted with two random phase codes before being stored holographically in a photorefractive material. Successful decryption requires the use of a readout beam with the same wavelength as that used in the recording, in addition to the correct phase key in the Fourier plane. The wavelength selectivity of the proposed system is evaluated numerically. We show that the number of available wavelength keys depends on the correlation length of the phase key in the Fourier plane. Preliminary experiments of encryption and decryption of optical memory in a LiNbO(3):Fe photorefractive crystal are demonstrated.

Growth Cone Localization of the mRNA Encoding the Chromatin Regulator HMGN5 Modulates Neurite Outgrowth

PubMed Central

Moretti, Francesca; Rolando, Chiara; Winker, Moritz; Ivanek, Robert; Rodriguez, Javier; Von Kriegsheim, Alex; Taylor, Verdon; Bustin, Michael

2015-01-01

Neurons exploit local mRNA translation and retrograde transport of transcription factors to regulate gene expression in response to signaling events at distal neuronal ends. Whether epigenetic factors could also be involved in such regulation is not known. We report that the mRNA encoding the high-mobility group N5 (HMGN5) chromatin binding protein localizes to growth cones of both neuron-like cells and of hippocampal neurons, where it has the potential to be translated, and that HMGN5 can be retrogradely transported into the nucleus along neurites. Loss of HMGN5 function induces transcriptional changes and impairs neurite outgrowth, while HMGN5 overexpression induces neurite outgrowth and chromatin decompaction; these effects are dependent on growth cone localization of Hmgn5 mRNA. We suggest that the localization and local translation of transcripts coding for epigenetic factors couple the dynamic neuronal outgrowth process with chromatin regulation in the nucleus. PMID:25825524

Odor identity coding by distributed ensembles of neurons in the mouse olfactory cortex

PubMed Central

Roland, Benjamin; Deneux, Thomas; Franks, Kevin M; Bathellier, Brice; Fleischmann, Alexander

2017-01-01

Olfactory perception and behaviors critically depend on the ability to identify an odor across a wide range of concentrations. Here, we use calcium imaging to determine how odor identity is encoded in olfactory cortex. We find that, despite considerable trial-to-trial variability, odor identity can accurately be decoded from ensembles of co-active neurons that are distributed across piriform cortex without any apparent spatial organization. However, piriform response patterns change substantially over a 100-fold change in odor concentration, apparently degrading the population representation of odor identity. We show that this problem can be resolved by decoding odor identity from a subpopulation of concentration-invariant piriform neurons. These concentration-invariant neurons are overrepresented in piriform cortex but not in olfactory bulb mitral and tufted cells. We therefore propose that distinct perceptual features of odors are encoded in independent subnetworks of neurons in the olfactory cortex. DOI: http://dx.doi.org/10.7554/eLife.26337.001 PMID:28489003

Learning complex temporal patterns with resource-dependent spike timing-dependent plasticity.

PubMed

Hunzinger, Jason F; Chan, Victor H; Froemke, Robert C

2012-07-01

Studies of spike timing-dependent plasticity (STDP) have revealed that long-term changes in the strength of a synapse may be modulated substantially by temporal relationships between multiple presynaptic and postsynaptic spikes. Whereas long-term potentiation (LTP) and long-term depression (LTD) of synaptic strength have been modeled as distinct or separate functional mechanisms, here, we propose a new shared resource model. A functional consequence of our model is fast, stable, and diverse unsupervised learning of temporal multispike patterns with a biologically consistent spiking neural network. Due to interdependencies between LTP and LTD, dendritic delays, and proactive homeostatic aspects of the model, neurons are equipped to learn to decode temporally coded information within spike bursts. Moreover, neurons learn spike timing with few exposures in substantial noise and jitter. Surprisingly, despite having only one parameter, the model also accurately predicts in vitro observations of STDP in more complex multispike trains, as well as rate-dependent effects. We discuss candidate commonalities in natural long-term plasticity mechanisms.

Coding of auditory temporal and pitch information by hippocampal individual cells and cell assemblies in the rat.

PubMed

Sakurai, Y

2002-01-01

This study reports how hippocampal individual cells and cell assemblies cooperate for neural coding of pitch and temporal information in memory processes for auditory stimuli. Each rat performed two tasks, one requiring discrimination of auditory pitch (high or low) and the other requiring discrimination of their duration (long or short). Some CA1 and CA3 complex-spike neurons showed task-related differential activity between the high and low tones in only the pitch-discrimination task. However, without exception, neurons which showed task-related differential activity between the long and short tones in the duration-discrimination task were always task-related neurons in the pitch-discrimination task. These results suggest that temporal information (long or short), in contrast to pitch information (high or low), cannot be coded independently by specific neurons. The results also indicate that the two different behavioral tasks cannot be fully differentiated by the task-related single neurons alone and suggest a model of cell-assembly coding of the tasks. Cross-correlation analysis among activities of simultaneously recorded multiple neurons supported the suggested cell-assembly model.Considering those results, this study concludes that dual coding by hippocampal single neurons and cell assemblies is working in memory processing of pitch and temporal information of auditory stimuli. The single neurons encode both auditory pitches and their temporal lengths and the cell assemblies encode types of tasks (contexts or situations) in which the pitch and the temporal information are processed.

Prospective Coding by Spiking Neurons

PubMed Central

Brea, Johanni; Gaál, Alexisz Tamás; Senn, Walter

2016-01-01

Animals learn to make predictions, such as associating the sound of a bell with upcoming feeding or predicting a movement that a motor command is eliciting. How predictions are realized on the neuronal level and what plasticity rule underlies their learning is not well understood. Here we propose a biologically plausible synaptic plasticity rule to learn predictions on a single neuron level on a timescale of seconds. The learning rule allows a spiking two-compartment neuron to match its current firing rate to its own expected future discounted firing rate. For instance, if an originally neutral event is repeatedly followed by an event that elevates the firing rate of a neuron, the originally neutral event will eventually also elevate the neuron’s firing rate. The plasticity rule is a form of spike timing dependent plasticity in which a presynaptic spike followed by a postsynaptic spike leads to potentiation. Even if the plasticity window has a width of 20 milliseconds, associations on the time scale of seconds can be learned. We illustrate prospective coding with three examples: learning to predict a time varying input, learning to predict the next stimulus in a delayed paired-associate task and learning with a recurrent network to reproduce a temporally compressed version of a sequence. We discuss the potential role of the learning mechanism in classical trace conditioning. In the special case that the signal to be predicted encodes reward, the neuron learns to predict the discounted future reward and learning is closely related to the temporal difference learning algorithm TD(λ). PMID:27341100

Contribution of amygdalar and lateral hypothalamic neurons to visual information processing of food and nonfood in monkey.

PubMed

Ono, T; Tamura, R; Nishijo, H; Nakamura, K; Tabuchi, E

1989-02-01

Visual information processing was investigated in the inferotemporal cortical (ITCx)-amygdalar (AM)-lateral hypothalamic (LHA) axis which contributes to food-nonfood discrimination. Neuronal activity was recorded from monkey AM and LHA during discrimination of sensory stimuli including sight of food or nonfood. The task had four phases: control, visual, bar press, and ingestion. Of 710 AM neurons tested, 220 (31.0%) responded during visual phase: 48 to only visual stimulation, 13 (1.9%) to visual plus oral sensory stimulation, 142 (20.0%) to multimodal stimulation and 17 (2.4%) to one affectively significant item. Of 669 LHA neurons tested, 106 (15.8%) responded in the visual phase. Of 80 visual-related neurons tested systematically, 33 (41.2%) responded selectively to the sight of any object predicting the availability of reward, and 47 (58.8%) responded nondifferentially to both food and nonfood. Many of AM neuron responses were graded according to the degree of affective significance of sensory stimuli (sensory-affective association), but responses of LHA food responsive neurons did not depend on the kind of reward indicated by the sensory stimuli (stimulus-reinforcement association). Some AM and LHA food responses were modulated by extinction or reversal. Dynamic information processing in ITCx-AM-LHA axis was investigated by reversible deficits of bilateral ITCx or AM by cooling. ITCx cooling suppressed discrimination by vision responding AM neurons (8/17). AM cooling suppressed LHA responses to food (9/22). We suggest deep AM-LHA involvement in food-nonfood discrimination based on AM sensory-affective association and LHA stimulus-reinforcement association.

Modulation of spike coding by subthreshold extracellular electric fields and neuronal morphology

NASA Astrophysics Data System (ADS)

Wei, Xile; Li, Bingjie; Lu, Meili; Yi, Guosheng; Wang, Jiang

2015-07-01

We use a two-compartment model, which includes soma and dendrite, to explore how extracellular subthreshold sinusoidal electric fields (EFs) influence the spike coding of an active neuron. By changing the intensity and the frequency of subthreshold EFs, we find that subthreshold EFs indeed affect neuronal coding remarkably within several stimulus frequency windows where the field effects on spike timing are stronger than that on spiking rate. The field effects are maximized at several harmonics of the intrinsic spiking frequency of an active neuron. Our findings implicate the potential resonance mechanism underlying subthreshold field effects. We also discuss how neuronal morphologic properties constrain subthreshold EF effects on spike timing. The morphologic properties are represented by two parameters, gc and p, where gc is the internal conductance between soma and dendrite and geometric factor p characterizes the proportion of area occupied by soma. We find that the contribution to field effects from the variation of p is stronger than that from gc, which suggests that neuronal geometric features play a crucial role in subthreshold field effects. Theoretically, these insights into how subthreshold sinusoidal EFs modulate ongoing neuron behaviors could contribute to uncovering the relevant mechanism of subthreshold sinusoidal EFs effects on neuronal coding. Furthermore, they are useful in rationally designing noninvasive brain stimulation strategies and developing electromagnetic stimulus techniques.

Synergism and Combinatorial Coding for Binary Odor Mixture Perception in Drosophila

PubMed Central

Chakraborty, Tuhin Subhra; Siddiqi, Obaid

2016-01-01

Most odors in the natural environment are mixtures of several compounds. Olfactory receptors housed in the olfactory sensory neurons detect these odors and transmit the information to the brain, leading to decision-making. But whether the olfactory system detects the ingredients of a mixture separately or treats mixtures as different entities is not well understood. Using Drosophila melanogaster as a model system, we have demonstrated that fruit flies perceive binary odor mixtures in a manner that is heavily dependent on both the proportion and the degree of dilution of the components, suggesting a combinatorial coding at the peripheral level. This coding strategy appears to be receptor specific and is independent of interneuronal interactions. PMID:27588303

The theta/gamma discrete phase code occuring during the hippocampal phase precession may be a more general brain coding scheme.

PubMed

Lisman, John

2005-01-01

In the hippocampus, oscillations in the theta and gamma frequency range occur together and interact in several ways, indicating that they are part of a common functional system. It is argued that these oscillations form a coding scheme that is used in the hippocampus to organize the readout from long-term memory of the discrete sequence of upcoming places, as cued by current position. This readout of place cells has been analyzed in several ways. First, plots of the theta phase of spikes vs. position on a track show a systematic progression of phase as rats run through a place field. This is termed the phase precession. Second, two cells with nearby place fields have a systematic difference in phase, as indicated by a cross-correlation having a peak with a temporal offset that is a significant fraction of a theta cycle. Third, several different decoding algorithms demonstrate the information content of theta phase in predicting the animal's position. It appears that small phase differences corresponding to jitter within a gamma cycle do not carry information. This evidence, together with the finding that principle cells fire preferentially at a given gamma phase, supports the concept of theta/gamma coding: a given place is encoded by the spatial pattern of neurons that fire in a given gamma cycle (the exact timing within a gamma cycle being unimportant); sequential places are encoded in sequential gamma subcycles of the theta cycle (i.e., with different discrete theta phase). It appears that this general form of coding is not restricted to readout of information from long-term memory in the hippocampus because similar patterns of theta/gamma oscillations have been observed in multiple brain regions, including regions involved in working memory and sensory integration. It is suggested that dual oscillations serve a general function: the encoding of multiple units of information (items) in a way that preserves their serial order. The relationship of such coding to that proposed by Singer and von der Malsburg is discussed; in their scheme, theta is not considered. It is argued that what theta provides is the absolute phase reference needed for encoding order. Theta/gamma coding therefore bears some relationship to the concept of "word" in digital computers, with word length corresponding to the number of gamma cycles within a theta cycle, and discrete phase corresponding to the ordered "place" within a word. Copyright 2005 Wiley-Liss, Inc.

Emergent gamma synchrony in all-to-all interneuronal networks.

PubMed

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

PubMed Central

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

Neuronal periodicity detection as a basis for the perception of consonance: a mathematical model of tonal fusion.

PubMed

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.

Distal gap junctions and active dendrites can tune network dynamics.

PubMed

Saraga, Fernanda; Ng, Leo; Skinner, Frances K

2006-03-01

Gap junctions allow direct electrical communication between CNS neurons. From theoretical and modeling studies, it is well known that although gap junctions can act to synchronize network output, they can also give rise to many other dynamic patterns including antiphase and other phase-locked states. The particular network pattern that arises depends on cellular, intrinsic properties that affect firing frequencies as well as the strength and location of the gap junctions. Interneurons or GABAergic neurons in hippocampus are diverse in their cellular characteristics and have been shown to have active dendrites. Furthermore, parvalbumin-positive GABAergic neurons, also known as basket cells, can contact one another via gap junctions on their distal dendrites. Using two-cell network models, we explore how distal electrical connections affect network output. We build multi-compartment models of hippocampal basket cells using NEURON and endow them with varying amounts of active dendrites. Two-cell networks of these model cells as well as reduced versions are explored. The relationship between intrinsic frequency and the level of active dendrites allows us to define three regions based on what sort of network dynamics occur with distal gap junction coupling. Weak coupling theory is used to predict the delineation of these regions as well as examination of phase response curves and distal dendritic polarization levels. We find that a nonmonotonic dependence of network dynamic characteristics (phase lags) on gap junction conductance occurs. This suggests that distal electrical coupling and active dendrite levels can control how sensitive network dynamics are to gap junction modulation. With the extended geometry, gap junctions located at more distal locations must have larger conductances for pure synchrony to occur. Furthermore, based on simulations with heterogeneous networks, it may be that one requires active dendrites if phase-locking is to occur in networks formed with distal gap junctions.

Spike-train communities: finding groups of similar spike trains.

PubMed

Humphries, Mark D

2011-02-09

Identifying similar spike-train patterns is a key element in understanding neural coding and computation. For single neurons, similar spike patterns evoked by stimuli are evidence of common coding. Across multiple neurons, similar spike trains indicate potential cell assemblies. As recording technology advances, so does the urgent need for grouping methods to make sense of large-scale datasets of spike trains. Existing methods require specifying the number of groups in advance, limiting their use in exploratory analyses. I derive a new method from network theory that solves this key difficulty: it self-determines the maximum number of groups in any set of spike trains, and groups them to maximize intragroup similarity. This method brings us revealing new insights into the encoding of aversive stimuli by dopaminergic neurons, and the organization of spontaneous neural activity in cortex. I show that the characteristic pause response of a rat's dopaminergic neuron depends on the state of the superior colliculus: when it is inactive, aversive stimuli invoke a single pattern of dopaminergic neuron spiking; when active, multiple patterns occur, yet the spike timing in each is reliable. In spontaneous multineuron activity from the cortex of anesthetized cat, I show the existence of neural ensembles that evolve in membership and characteristic timescale of organization during global slow oscillations. I validate these findings by showing that the method both is remarkably reliable at detecting known groups and can detect large-scale organization of dynamics in a model of the striatum.

Stimulus-Response-Outcome Coding in the Pigeon Nidopallium Caudolaterale

PubMed Central

Starosta, Sarah; Güntürkün, Onur; Stüttgen, Maik C.

2013-01-01

A prerequisite for adaptive goal-directed behavior is that animals constantly evaluate action outcomes and relate them to both their antecedent behavior and to stimuli predictive of reward or non-reward. Here, we investigate whether single neurons in the avian nidopallium caudolaterale (NCL), a multimodal associative forebrain structure and a presumed analogue of mammalian prefrontal cortex, represent information useful for goal-directed behavior. We subjected pigeons to a go-nogo task, in which responding to one visual stimulus (S+) was partially reinforced, responding to another stimulus (S–) was punished, and responding to test stimuli from the same physical dimension (spatial frequency) was inconsequential. The birds responded most intensely to S+, and their response rates decreased monotonically as stimuli became progressively dissimilar to S+; thereby, response rates provided a behavioral index of reward expectancy. We found that many NCL neurons' responses were modulated in the stimulus discrimination phase, the outcome phase, or both. A substantial fraction of neurons increased firing for cues predicting non-reward or decreased firing for cues predicting reward. Interestingly, the same neurons also responded when reward was expected but not delivered, and could thus provide a negative reward prediction error or, alternatively, signal negative value. In addition, many cells showed motor-related response modulation. In summary, NCL neurons represent information about the reward value of specific stimuli, instrumental actions as well as action outcomes, and therefore provide signals useful for adaptive behavior in dynamically changing environments. PMID:23437383

Time dependent impact of perinatal hypoxia on growth hormone, insulin-like growth factor 1 and insulin-like growth factor binding protein-3.

PubMed

Kartal, Ömer; Aydınöz, Seçil; Kartal, Ayşe Tuğba; Kelestemur, Taha; Caglayan, Ahmet Burak; Beker, Mustafa Caglar; Karademir, Ferhan; Süleymanoğlu, Selami; Kul, Mustafa; Yulug, Burak; Kilic, Ertugrul

2016-08-01

Hypoxic-ischemia (HI) is a widely used animal model to mimic the preterm or perinatal sublethal hypoxia, including hypoxic-ischemic encephalopathy. It causes diffuse neurodegeneration in the brain and results in mental retardation, hyperactivity, cerebral palsy, epilepsy and neuroendocrine disturbances. Herein, we examined acute and subacute correlations between neuronal degeneration and serum growth factor changes, including growth hormone (GH), insulin-like growth factor 1 (IGF-1) and insulin-like growth factor binding protein-3 (IGFBP-3) after hypoxic-ischemia (HI) in neonatal rats. In the acute phase of hypoxia, brain volume was increased significantly as compared with control animals, which was associated with reduced GH and IGF-1 secretions. Reduced neuronal survival and increased DNA fragmentation were also noticed in these animals. However, in the subacute phase of hypoxia, neuronal survival and brain volume were significantly decreased, accompanied by increased apoptotic cell death in the hippocampus and cortex. Serum GH, IGF-1, and IGFBP-3 levels were significantly reduced in the subacute phase of HI. Significant retardation in the brain and body development were noted in the subacute phase of hypoxia. Here, we provide evidence that serum levels of growth-hormone and factors were decreased in the acute and subacute phase of hypoxia, which was associated with increased DNA fragmentation and decreased neuronal survival.

Adaptation and inhibition underlie responses to time-varying interaural phase cues in a model of inferior colliculus neurons.

PubMed

Borisyuk, Alla; Semple, Malcolm N; Rinzel, John

2002-10-01

A mathematical model was developed for exploring the sensitivity of low-frequency inferior colliculus (IC) neurons to interaural phase disparity (IPD). The formulation involves a firing-rate-type model that does not include spikes per se. The model IC neuron receives IPD-tuned excitatory and inhibitory inputs (viewed as the output of a collection of cells in the medial superior olive). The model cell possesses cellular properties of firing rate adaptation and postinhibitory rebound (PIR). The descriptions of these mechanisms are biophysically reasonable, but only semi-quantitative. We seek to explain within a minimal model the experimentally observed mismatch between responses to IPD stimuli delivered dynamically and those delivered statically (McAlpine et al. 2000; Spitzer and Semple 1993). The model reproduces many features of the responses to static IPD presentations, binaural beat, and partial range sweep stimuli. These features include differences in responses to a stimulus presented in static or dynamic context: sharper tuning and phase shifts in response to binaural beats, and hysteresis and "rise-from-nowhere" in response to partial range sweeps. Our results suggest that dynamic response features are due to the structure of inputs and the presence of firing rate adaptation and PIR mechanism in IC cells, but do not depend on a specific biophysical mechanism. We demonstrate how the model's various components contribute to shaping the observed phenomena. For example, adaptation, PIR, and transmission delay shape phase advances and delays in responses to binaural beats, adaptation and PIR shape hysteresis in different ranges of IPD, and tuned inhibition underlies asymmetry in dynamic tuning properties. We also suggest experiments to test our modeling predictions: in vitro simulation of the binaural beat (phase advance at low beat frequencies, its dependence on firing rate), in vivo partial range sweep experiments (dependence of the hysteresis curve on parameters), and inhibition blocking experiments (to study inhibitory tuning properties by observation of phase shifts).

Microglia as Biosensors and Effectors of Neurodysfunction

DTIC Science & Technology

2010-04-01

induce or exacerbate the onset and progression of autism spectrum disorders. Dendritic spines receive the majority of excitatory synapses in the brain... autism spectrum disorders, synaptogenesis 15. NUMBER OF PAGES 24 synaptogenesis 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT...4/1/09-4/30/10 INTRODUCTION: Autism occurs during the post-natal period that neurons form new experience-dependent synaptic connections

Artificial neural networks using complex numbers and phase encoded weights.

PubMed

Michel, Howard E; Awwal, Abdul Ahad S

2010-04-01

The model of a simple perceptron using phase-encoded inputs and complex-valued weights is proposed. The aggregation function, activation function, and learning rule for the proposed neuron are derived and applied to Boolean logic functions and simple computer vision tasks. The complex-valued neuron (CVN) is shown to be superior to traditional perceptrons. An improvement of 135% over the theoretical maximum of 104 linearly separable problems (of three variables) solvable by conventional perceptrons is achieved without additional logic, neuron stages, or higher order terms such as those required in polynomial logic gates. The application of CVN in distortion invariant character recognition and image segmentation is demonstrated. Implementation details are discussed, and the CVN is shown to be very attractive for optical implementation since optical computations are naturally complex. The cost of the CVN is less in all cases than the traditional neuron when implemented optically. Therefore, all the benefits of the CVN can be obtained without additional cost. However, on those implementations dependent on standard serial computers, CVN will be more cost effective only in those applications where its increased power can offset the requirement for additional neurons.

Phase dependencies of the human baroreceptor reflex

NASA Technical Reports Server (NTRS)

Seidel, H.; Herzel, H.; Eckberg, D. L.

1997-01-01

We studied the influence of respiratory and cardiac phase on responses of the cardiac pacemaker to brief (0.35-s) increases of carotid baroreceptor afferent traffic provoked by neck suction in seven healthy young adult subjects. Cardiac responses to neck suction were measured indirectly from electrocardiographic changes of heart period. Our results show that it is possible to separate the influences of respiratory and cardiac phases at the onset of a neck suction impulse by a product of two factors: one depending only on the respiratory phase and one depending only on the cardiac phase. This result is consistent with the hypothesis that efferent vagal activity is a function of afferent baroreceptor activity, whereas respiratory neurons modulate that medullary throughput independent of the cardiac phase. Furthermore, we have shown that stimulus broadening and stimulus cropping influence the outcome of neck suction experiments in a way that makes it virtually impossible to obtain information on the phase dependency of the cardiac pacemaker's sensitivity to vagal stimulation without accurate knowledge of the functional shape of stimulus broadening.

Oscillatory encoding of visual stimulus familiarity.

PubMed

Kissinger, Samuel T; Pak, Alexandr; Tang, Yu; Masmanidis, Sotiris C; Chubykin, Alexander A

2018-06-18

Familiarity of the environment changes the way we perceive and encode incoming information. However, the neural substrates underlying this phenomenon are poorly understood. Here we describe a new form of experience-dependent low frequency oscillations in the primary visual cortex (V1) of awake adult male mice. The oscillations emerged in visually evoked potentials (VEPs) and single-unit activity following repeated visual stimulation. The oscillations were sensitive to the spatial frequency content of a visual stimulus and required the muscarinic acetylcholine receptors (mAChRs) for their induction and expression. Finally, ongoing visually evoked theta (4-6 Hz) oscillations boost the VEP amplitude of incoming visual stimuli if the stimuli are presented at the high excitability phase of the oscillations. Our results demonstrate that an oscillatory code can be used to encode familiarity and serves as a gate for oncoming sensory inputs. Significance Statement. Previous experience can influence the processing of incoming sensory information by the brain and alter perception. However, the mechanistic understanding of how this process takes place is lacking. We have discovered that persistent low frequency oscillations in the primary visual cortex encode information about familiarity and the spatial frequency of the stimulus. These familiarity evoked oscillations influence neuronal responses to the oncoming stimuli in a way that depends on the oscillation phase. Our work demonstrates a new mechanism of visual stimulus feature detection and learning. Copyright © 2018 the authors.

Slow Temporal Integration Enables Robust Neural Coding and Perception of a Cue to Sound Source Location.

PubMed

Brown, Andrew D; Tollin, Daniel J

2016-09-21

In mammals, localization of sound sources in azimuth depends on sensitivity to interaural differences in sound timing (ITD) and level (ILD). Paradoxically, while typical ILD-sensitive neurons of the auditory brainstem require millisecond synchrony of excitatory and inhibitory inputs for the encoding of ILDs, human and animal behavioral ILD sensitivity is robust to temporal stimulus degradations (e.g., interaural decorrelation due to reverberation), or, in humans, bilateral clinical device processing. Here we demonstrate that behavioral ILD sensitivity is only modestly degraded with even complete decorrelation of left- and right-ear signals, suggesting the existence of a highly integrative ILD-coding mechanism. Correspondingly, we find that a majority of auditory midbrain neurons in the central nucleus of the inferior colliculus (of chinchilla) effectively encode ILDs despite complete decorrelation of left- and right-ear signals. We show that such responses can be accounted for by relatively long windows of bilateral excitatory-inhibitory interaction, which we explicitly measure using trains of narrowband clicks. Neural and behavioral data are compared with the outputs of a simple model of ILD processing with a single free parameter, the duration of excitatory-inhibitory interaction. Behavioral, neural, and modeling data collectively suggest that ILD sensitivity depends on binaural integration of excitation and inhibition within a ≳3 ms temporal window, significantly longer than observed in lower brainstem neurons. This relatively slow integration potentiates a unique role for the ILD system in spatial hearing that may be of particular importance when informative ITD cues are unavailable. In mammalian hearing, interaural differences in the timing (ITD) and level (ILD) of impinging sounds carry critical information about source location. However, natural sounds are often decorrelated between the ears by reverberation and background noise, degrading the fidelity of both ITD and ILD cues. Here we demonstrate that behavioral ILD sensitivity (in humans) and neural ILD sensitivity (in single neurons of the chinchilla auditory midbrain) remain robust under stimulus conditions that render ITD cues undetectable. This result can be explained by "slow" temporal integration arising from several-millisecond-long windows of excitatory-inhibitory interaction evident in midbrain, but not brainstem, neurons. Such integrative coding can account for the preservation of ILD sensitivity despite even extreme temporal degradations in ecological acoustic stimuli. Copyright © 2016 the authors 0270-6474/16/369908-14$15.00/0.

Transformation of binaural response properties in the ascending auditory pathway: influence of time-varying interaural phase disparity.

PubMed

Spitzer, M W; Semple, M N

1998-12-01

Transformation of binaural response properties in the ascending auditory pathway: influence of time-varying interaural phase disparity. J. Neurophysiol. 80: 3062-3076, 1998. Previous studies demonstrated that tuning of inferior colliculus (IC) neurons to interaural phase disparity (IPD) is often profoundly influenced by temporal variation of IPD, which simulates the binaural cue produced by a moving sound source. To determine whether sensitivity to simulated motion arises in IC or at an earlier stage of binaural processing we compared responses in IC with those of two major IPD-sensitive neuronal classes in the superior olivary complex (SOC), neurons whose discharges were phase locked (PL) to tonal stimuli and those that were nonphase locked (NPL). Time-varying IPD stimuli consisted of binaural beats, generated by presenting tones of slightly different frequencies to the two ears, and interaural phase modulation (IPM), generated by presenting a pure tone to one ear and a phase modulated tone to the other. IC neurons and NPL-SOC neurons were more sharply tuned to time-varying than to static IPD, whereas PL-SOC neurons were essentially uninfluenced by the mode of stimulus presentation. Preferred IPD was generally similar in responses to static and time-varying IPD for all unit populations. A few IC neurons were highly influenced by the direction and rate of simulated motion, but the major effect for most IC neurons and all SOC neurons was a linear shift of preferred IPD at high rates-attributable to response latency. Most IC and NPL-SOC neurons were strongly influenced by IPM stimuli simulating motion through restricted ranges of azimuth; simulated motion through partially overlapping azimuthal ranges elicited discharge profiles that were highly discontiguous, indicating that the response associated with a particular IPD is dependent on preceding portions of the stimulus. In contrast, PL-SOC responses tracked instantaneous IPD throughout the trajectory of simulated motion, resulting in highly contiguous discharge profiles for overlapping stimuli. This finding indicates that responses of PL-SOC units to time-varying IPD reflect only instantaneous IPD with no additional influence of dynamic stimulus attributes. Thus the neuronal representation of auditory spatial information undergoes a major transformation as interaural delay is initially processed in the SOC and subsequently reprocessed in IC. The finding that motion sensitivity in IC emerges from motion-insensitive input suggests that information about change of position is crucial to spatial processing at higher levels of the auditory system.

Temporally evolving gain mechanisms of attention in macaque area V4.

PubMed

Sani, Ilaria; Santandrea, Elisa; Morrone, Maria Concetta; Chelazzi, Leonardo

2017-08-01

Cognitive attention and perceptual saliency jointly govern our interaction with the environment. Yet, we still lack a universally accepted account of the interplay between attention and luminance contrast, a fundamental dimension of saliency. We measured the attentional modulation of V4 neurons' contrast response functions (CRFs) in awake, behaving macaque monkeys and applied a new approach that emphasizes the temporal dynamics of cell responses. We found that attention modulates CRFs via different gain mechanisms during subsequent epochs of visually driven activity: an early contrast-gain, strongly dependent on prestimulus activity changes (baseline shift); a time-limited stimulus-dependent multiplicative modulation, reaching its maximal expression around 150 ms after stimulus onset; and a late resurgence of contrast-gain modulation. Attention produced comparable time-dependent attentional gain changes on cells heterogeneously coding contrast, supporting the notion that the same circuits mediate attention mechanisms in V4 regardless of the form of contrast selectivity expressed by the given neuron. Surprisingly, attention was also sometimes capable of inducing radical transformations in the shape of CRFs. These findings offer important insights into the mechanisms that underlie contrast coding and attention in primate visual cortex and a new perspective on their interplay, one in which time becomes a fundamental factor. NEW & NOTEWORTHY We offer an innovative perspective on the interplay between attention and luminance contrast in macaque area V4, one in which time becomes a fundamental factor. We place emphasis on the temporal dynamics of attentional effects, pioneering the notion that attention modulates contrast response functions of V4 neurons via the sequential engagement of distinct gain mechanisms. These findings advance understanding of attentional influences on visual processing and help reconcile divergent results in the literature. Copyright © 2017 the American Physiological Society.

Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability.

PubMed

Tanaka, Takuma; Aoyagi, Toshio; Kaneko, Takeshi

2012-10-01

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

Encoding of head acceleration in vestibular neurons. I. Spatiotemporal response properties to linear acceleration

NASA Technical Reports Server (NTRS)

Bush, G. A.; Perachio, A. A.; Angelaki, D. E.

1993-01-01

1. Extracellular recordings were made in and around the medial vestibular nuclei in decerebrated rats. Neurons were functionally identified according to their semicircular canal input on the basis of their responses to angular head rotations around the yaw, pitch, and roll head axes. Those cells responding to angular acceleration were classified as either horizontal semicircular canal-related (HC) or vertical semicircular canal-related (VC) neurons. The HC neurons were further characterized as either type I or type II, depending on the direction of rotation producing excitation. Cells that lacked a response to angular head acceleration, but exhibited sensitivity to a change in head position, were classified as purely otolith organ-related (OTO) neurons. All vestibular neurons were then tested for their response to sinusoidal linear translation in the horizontal head plane. 2. Convergence of macular and canal inputs onto central vestibular nuclei neurons occurred in 73% of the type I HC, 79% of the type II HC, and 86% of the VC neurons. Out of the 223 neurons identified as receiving macular input, 94 neurons were further studied, and their spatiotemporal response properties to sinusoidal stimulation with pure linear acceleration were quantified. Data were obtained from 33 type I HC, 22 type II HC, 22 VC, and 17 OTO neurons. 3. For each neuron the angle of the translational stimulus vector was varied by 15, 30, or 45 degrees increments in the horizontal head plane. In all tested neurons, a direction of maximum sensitivity was identified. An interesting difference among neurons was their response to translation along the direction perpendicular to that that produced the maximum response ("null" direction). For the majority of neurons tested, it was possible to evoke a nonzero response during stimulation along the null direction always had response phases that varied as a function of stimulus direction. 4. These spatiotemporal response properties were quantified in two independent ways. First, the data were evaluated on the basis of the traditional one-dimensional principle governed by the "cosine gain rule" and constant response phase at different stimulus orientations. Second, the response gain and phase values that were empirically determined for each orientation of the applied linear stimulus vector were fitted on the basis of a newly developed formalism that treats neuronal responses as exhibiting two-dimensional spatial sensitivity. Thus two response vectors were determined for each neuron on the basis of its response gain and phase at different stimulus directions in the horizontal head plane.(ABSTRACT TRUNCATED AT 400 WORDS).

Interaural time sensitivity of high-frequency neurons in the inferior colliculus.

PubMed

Yin, T C; Kuwada, S; Sujaku, Y

1984-11-01

Recent psychoacoustic experiments have shown that interaural time differences provide adequate cues for lateralizing high-frequency sounds, provided the stimuli are complex and not pure tones. We present here physiological evidence in support of these findings. Neurons of high best frequency in the cat inferior colliculus respond to interaural phase differences of amplitude modulated waveforms, and this response depends upon preservation of phase information of the modulating signal. Interaural phase differences were introduced in two ways: by interaural delays of the entire waveform and by binaural beats in which there was an interaural frequency difference in the modulating waveform. Results obtained with these two methods are similar. Our results show that high-frequency cells can respond to interaural time differences of amplitude modulated signals and that they do so by a sensitivity to interaural phase differences of the modulating waveform.

Cell-assembly coding in several memory processes.

PubMed

Sakurai, Y

1998-01-01

The present paper discusses why the cell assembly, i.e., an ensemble population of neurons with flexible functional connections, is a tenable view of the basic code for information processes in the brain. The main properties indicating the reality of cell-assembly coding are neurons overlaps among different assemblies and connection dynamics within and among the assemblies. The former can be detected as multiple functions of individual neurons in processing different kinds of information. Individual neurons appear to be involved in multiple information processes. The latter can be detected as changes of functional synaptic connections in processing different kinds of information. Correlations of activity among some of the recorded neurons appear to change in multiple information processes. Recent experiments have compared several different memory processes (tasks) and detected these two main properties, indicating cell-assembly coding of memory in the working brain. The first experiment compared different types of processing of identical stimuli, i.e., working memory and reference memory of auditory stimuli. The second experiment compared identical processes of different types of stimuli, i.e., discriminations of simple auditory, simple visual, and configural auditory-visual stimuli. The third experiment compared identical processes of different types of stimuli with or without temporal processing of stimuli, i.e., discriminations of elemental auditory, configural auditory-visual, and sequential auditory-visual stimuli. Some possible features of the cell-assembly coding, especially "dual coding" by individual neurons and cell assemblies, are discussed for future experimental approaches. Copyright 1998 Academic Press.

Processing of Intraoral Olfactory and Gustatory Signals in the Gustatory Cortex of Awake Rats

PubMed Central

Fontanini, Alfredo

2017-01-01

The integration of gustatory and olfactory information is essential to the perception of flavor. Human neuroimaging experiments have pointed to the gustatory cortex (GC) as one of the areas involved in mediating flavor perception. Although GC's involvement in encoding the chemical identity and hedonic value of taste stimuli is well studied, it is unknown how single GC neurons process olfactory stimuli emanating from the mouth. In this study, we relied on multielectrode recordings to investigate how single GC neurons respond to intraorally delivered tastants and tasteless odorants dissolved in water and whether/how these two modalities converge in the same neurons. We found that GC neurons could either be unimodal, responding exclusively to taste (taste-only) or odor (odor-only), or bimodal, responding to both gustatory and olfactory stimuli. Odor responses were confirmed to result from retronasal olfaction: monitoring respiration revealed that exhalation preceded odor-evoked activity and reversible inactivation of olfactory receptors in the nasal epithelium significantly reduced responses to intraoral odorants but not to tastants. Analysis of bimodal neurons revealed that they encode palatability significantly better than the unimodal taste-only group. Bimodal neurons exhibited similar responses to palatable tastants and odorants dissolved in water. This result suggested that odorized water could be palatable. This interpretation was further supported with a brief access task, where rats avoided consuming aversive taste stimuli and consumed the palatable tastants and dissolved odorants. These results demonstrate the convergence of the chemosensory components of flavor onto single GC neurons and provide evidence for the integration of flavor with palatability coding. SIGNIFICANCE STATEMENT Food perception and choice depend upon the concurrent processing of olfactory and gustatory signals from the mouth. The primary gustatory cortex has been proposed to integrate chemosensory stimuli; however, no study has examined the single-unit responses to intraoral odorant presentation. Here we found that neurons in gustatory cortex can respond either exclusively to tastants, exclusively to odorants, or to both (bimodal). Several differences exist between these groups' responses; notably, bimodal neurons code palatability significantly better than unimodal neurons. This group of neurons might represent a substrate for how odorants gain the quality of tastants. PMID:28077705

Feedback Inhibition Shapes Emergent Computational Properties of Cortical Microcircuit Motifs.

PubMed

Jonke, Zeno; Legenstein, Robert; Habenschuss, Stefan; Maass, Wolfgang

2017-08-30

Cortical microcircuits are very complex networks, but they are composed of a relatively small number of stereotypical motifs. Hence, one strategy for throwing light on the computational function of cortical microcircuits is to analyze emergent computational properties of these stereotypical microcircuit motifs. We are addressing here the question how spike timing-dependent plasticity shapes the computational properties of one motif that has frequently been studied experimentally: interconnected populations of pyramidal cells and parvalbumin-positive inhibitory cells in layer 2/3. Experimental studies suggest that these inhibitory neurons exert some form of divisive inhibition on the pyramidal cells. We show that this data-based form of feedback inhibition, which is softer than that of winner-take-all models that are commonly considered in theoretical analyses, contributes to the emergence of an important computational function through spike timing-dependent plasticity: The capability to disentangle superimposed firing patterns in upstream networks, and to represent their information content through a sparse assembly code. SIGNIFICANCE STATEMENT We analyze emergent computational properties of a ubiquitous cortical microcircuit motif: populations of pyramidal cells that are densely interconnected with inhibitory neurons. Simulations of this model predict that sparse assembly codes emerge in this microcircuit motif under spike timing-dependent plasticity. Furthermore, we show that different assemblies will represent different hidden sources of upstream firing activity. Hence, we propose that spike timing-dependent plasticity enables this microcircuit motif to perform a fundamental computational operation on neural activity patterns. Copyright © 2017 the authors 0270-6474/17/378511-13$15.00/0.

Neural coding of image structure and contrast polarity of Cartesian, hyperbolic, and polar gratings in the primary and secondary visual cortex of the tree shrew.

PubMed

Poirot, Jordan; De Luna, Paolo; Rainer, Gregor

2016-04-01

We comprehensively characterize spiking and visual evoked potential (VEP) activity in tree shrew V1 and V2 using Cartesian, hyperbolic, and polar gratings. Neural selectivity to structure of Cartesian gratings was higher than other grating classes in both visual areas. From V1 to V2, structure selectivity of spiking activity increased, whereas corresponding VEP values tended to decrease, suggesting that single-neuron coding of Cartesian grating attributes improved while the cortical columnar organization of these neurons became less precise from V1 to V2. We observed that neurons in V2 generally exhibited similar selectivity for polar and Cartesian gratings, suggesting that structure of polar-like stimuli might be encoded as early as in V2. This hypothesis is supported by the preference shift from V1 to V2 toward polar gratings of higher spatial frequency, consistent with the notion that V2 neurons encode visual scene borders and contours. Neural sensitivity to modulations of polarity of hyperbolic gratings was highest among all grating classes and closely related to the visual receptive field (RF) organization of ON- and OFF-dominated subregions. We show that spatial RF reconstructions depend strongly on grating class, suggesting that intracortical contributions to RF structure are strongest for Cartesian and polar gratings. Hyperbolic gratings tend to recruit least cortical elaboration such that the RF maps are similar to those generated by sparse noise, which most closely approximate feedforward inputs. Our findings complement previous literature in primates, rodents, and carnivores and highlight novel aspects of shape representation and coding occurring in mammalian early visual cortex. Copyright © 2016 the American Physiological Society.

Spiking and bursting patterns of fractional-order Izhikevich model

NASA Astrophysics Data System (ADS)

Teka, Wondimu W.; Upadhyay, Ranjit Kumar; Mondal, Argha

2018-03-01

Bursting and spiking oscillations play major roles in processing and transmitting information in the brain through cortical neurons that respond differently to the same signal. These oscillations display complex dynamics that might be produced by using neuronal models and varying many model parameters. Recent studies have shown that models with fractional order can produce several types of history-dependent neuronal activities without the adjustment of several parameters. We studied the fractional-order Izhikevich model and analyzed different kinds of oscillations that emerge from the fractional dynamics. The model produces a wide range of neuronal spike responses, including regular spiking, fast spiking, intrinsic bursting, mixed mode oscillations, regular bursting and chattering, by adjusting only the fractional order. Both the active and silent phase of the burst increase when the fractional-order model further deviates from the classical model. For smaller fractional order, the model produces memory dependent spiking activity after the pulse signal turned off. This special spiking activity and other properties of the fractional-order model are caused by the memory trace that emerges from the fractional-order dynamics and integrates all the past activities of the neuron. On the network level, the response of the neuronal network shifts from random to scale-free spiking. Our results suggest that the complex dynamics of spiking and bursting can be the result of the long-term dependence and interaction of intracellular and extracellular ionic currents.

An input-representing interneuron regulates spike timing and thereby phase switching in a motor network.

PubMed

Sasaki, Kosei; Jing, Jian; Due, Michael R; Weiss, Klaudiusz R

2008-02-20

Despite the importance of spike-timing regulation in network functioning, little is known about this regulation at the cellular level. In the Aplysia feeding network, we show that interneuron B65 regulates the timing of the spike initiation of phase-switch neurons B64 and cerebral-buccal interneuron-5/6 (CBI-5/6), and thereby determines the identity of the neuron that acts as a protraction terminator. Previous work showed that B64 begins to fire before the end of protraction phase and terminates protraction in CBI-2-elicited ingestive, but not in CBI-2-elicited egestive programs, thus indicating that the spike timing and phase-switching function of B64 depend on the type of the central pattern generator (CPG)-elicited response rather than on the input used to activate the CPG. Here, we find that CBI-5/6 is a protraction terminator in egestive programs elicited by the esophageal nerve (EN), but not by CBI-2, thus indicating that, in contrast to B64, the spike timing and protraction-terminating function of CBI-5/6 depends on the input to the CPG rather than the response type. Interestingly, B65 activity also depends on the input in that B65 is highly active in EN-elicited programs, but not in CBI-2-elicited programs independent of whether the programs are ingestive or egestive. Notably, during EN-elicited egestive programs, hyperpolarization of B65 delays the onset of CBI-5/6 firing, whereas in CBI-2-elicited ingestive programs, B65 stimulation simultaneously advances CBI-5/6 firing and delays B64 firing, thereby substituting CBI-5/6 for B64 as the protraction terminator. Thus, we identified a neural mechanism that, in an input-dependent manner, regulates spike timing and thereby the functional role of specific neurons.

Model cerebellar granule cells can faithfully transmit modulated firing rate signals

PubMed Central

Rössert, Christian; Solinas, Sergio; D'Angelo, Egidio; Dean, Paul; Porrill, John

2014-01-01

A crucial assumption of many high-level system models of the cerebellum is that information in the granular layer is encoded in a linear manner. However, granule cells are known for their non-linear and resonant synaptic and intrinsic properties that could potentially impede linear signal transmission. In this modeling study we analyse how electrophysiological granule cell properties and spike sampling influence information coded by firing rate modulation, assuming no signal-related, i.e., uncorrelated inhibitory feedback (open-loop mode). A detailed one-compartment granule cell model was excited in simulation by either direct current or mossy-fiber synaptic inputs. Vestibular signals were represented as tonic inputs to the flocculus modulated at frequencies up to 20 Hz (approximate upper frequency limit of vestibular-ocular reflex, VOR). Model outputs were assessed using estimates of both the transfer function, and the fidelity of input-signal reconstruction measured as variance-accounted-for. The detailed granule cell model with realistic mossy-fiber synaptic inputs could transmit information faithfully and linearly in the frequency range of the vestibular-ocular reflex. This was achieved most simply if the model neurons had a firing rate at least twice the highest required frequency of modulation, but lower rates were also adequate provided a population of neurons was utilized, especially in combination with push-pull coding. The exact number of neurons required for faithful transmission depended on the precise values of firing rate and noise. The model neurons were also able to combine excitatory and inhibitory signals linearly, and could be replaced by a simpler (modified) integrate-and-fire neuron in the case of high tonic firing rates. These findings suggest that granule cells can in principle code modulated firing-rate inputs in a linear manner, and are thus consistent with the high-level adaptive-filter model of the cerebellar microcircuit. PMID:25352777

STDP-based spiking deep convolutional neural networks for object recognition.

PubMed

Kheradpisheh, Saeed Reza; Ganjtabesh, Mohammad; Thorpe, Simon J; Masquelier, Timothée

2018-03-01

Previous studies have shown that spike-timing-dependent plasticity (STDP) can be used in spiking neural networks (SNN) to extract visual features of low or intermediate complexity in an unsupervised manner. These studies, however, used relatively shallow architectures, and only one layer was trainable. Another line of research has demonstrated - using rate-based neural networks trained with back-propagation - that having many layers increases the recognition robustness, an approach known as deep learning. We thus designed a deep SNN, comprising several convolutional (trainable with STDP) and pooling layers. We used a temporal coding scheme where the most strongly activated neurons fire first, and less activated neurons fire later or not at all. The network was exposed to natural images. Thanks to STDP, neurons progressively learned features corresponding to prototypical patterns that were both salient and frequent. Only a few tens of examples per category were required and no label was needed. After learning, the complexity of the extracted features increased along the hierarchy, from edge detectors in the first layer to object prototypes in the last layer. Coding was very sparse, with only a few thousands spikes per image, and in some cases the object category could be reasonably well inferred from the activity of a single higher-order neuron. More generally, the activity of a few hundreds of such neurons contained robust category information, as demonstrated using a classifier on Caltech 101, ETH-80, and MNIST databases. We also demonstrate the superiority of STDP over other unsupervised techniques such as random crops (HMAX) or auto-encoders. Taken together, our results suggest that the combination of STDP with latency coding may be a key to understanding the way that the primate visual system learns, its remarkable processing speed and its low energy consumption. These mechanisms are also interesting for artificial vision systems, particularly for hardware solutions. Copyright © 2017 Elsevier Ltd. All rights reserved.

On the molecular basis of the receptor mosaic hypothesis of the engram.

PubMed

Agnati, Luigi F; Ferré, Sergi; Leo, Giuseppina; Lluis, Carme; Canela, Enric I; Franco, Rafael; Fuxe, Kjell

2004-08-01

1. This paper revisits the so-called "receptor mosaic hypothesis" for memory trace formation in the light of recent findings in "functional (or interaction) proteomics." The receptor mosaic hypothesis maintains that receptors may form molecular aggregates at the plasma membrane level representing part of the computational molecular networks. 2. Specific interactions between receptors occur as a consequence of the pattern of transmitter release from the source neurons, which release the chemical code impinging on the receptor mosaics of the target neuron. Thus, the decoding of the chemical message depends on the receptors forming the receptor mosaics and on the type of interactions among receptors and other proteins in the molecular network with novel long-term mosaics formed by their stabilization via adapter proteins formed in target neurons through the incoming neurotransmitter code. The internalized receptor heteromeric complexes or parts of them may act as transcription factors for the formation of such adapter proteins. 3. Receptor mosaics are formed both at the pre- and postsynaptic level of the plasma membranes and this phenomenon can play a role in the Hebbian behavior of some synaptic contacts. The appropriate "matching" of the pre- with the postsynaptic receptor mosaic can be thought of as the "clamping of the synapse to the external teaching signal." According to our hypothesis the behavior of the molecular networks at plasma membrane level to which the receptor mosaics belong can be set in a "frozen" conformation (i.e. in a frozen functional state) and this may represent a mechanism to maintain constant the input to a neuron. 4. Thus, we are suggesting that molecular networks at plasma membrane level may display multiple "attractors" each of which stores the memory of a specific neurotransmitter code due to a unique firing pattern. Hence, this mechanism may play a role in learning processes where the input to a neuron is likely to remain constant for a while.

When Long-Range Zero-Lag Synchronization is Feasible in Cortical Networks

PubMed Central

Viriyopase, Atthaphon; Bojak, Ingo; Zeitler, Magteld; Gielen, Stan

2012-01-01

Many studies have reported long-range synchronization of neuronal activity between brain areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 and 40–80 Hz, respectively. Several studies have reported synchrony with zero phase lag, which is remarkable considering the synaptic and conduction delays inherent in the connections between distant brain areas. This result has led to many speculations about the possible functional role of zero-lag synchrony, such as for neuronal communication, attention, memory, and feature binding. However, recent studies using recordings of single-unit activity and local field potentials report that neuronal synchronization may occur with non-zero phase lags. This raises the questions whether zero-lag synchrony can occur in the brain and, if so, under which conditions. We used analytical methods and computer simulations to investigate which connectivity between neuronal populations allows or prohibits zero-lag synchrony. We did so for a model where two oscillators interact via a relay oscillator. Analytical results and computer simulations were obtained for both type I Mirollo–Strogatz neurons and type II Hodgkin–Huxley neurons. We have investigated the dynamics of the model for various types of synaptic coupling and importantly considered the potential impact of Spike-Timing Dependent Plasticity (STDP) and its learning window. We confirm previous results that zero-lag synchrony can be achieved in this configuration. This is much easier to achieve with Hodgkin–Huxley neurons, which have a biphasic phase response curve, than for type I neurons. STDP facilitates zero-lag synchrony as it adjusts the synaptic strengths such that zero-lag synchrony is feasible for a much larger range of parameters than without STDP. PMID:22866034

Architecture and Chemical Coding of the Inner and Outer Submucous Plexus in the Colon of Piglets

PubMed Central

Petto, Carola; Gäbel, Gotthold; Pfannkuche, Helga

2015-01-01

In the porcine colon, the submucous plexus is divided into an inner submucous plexus (ISP) on the epithelial side and an outer submucous plexus (OSP) on the circular muscle side. Although both plexuses are probably involved in the regulation of epithelial functions, they might differ in function and neurochemical coding according to their localization. Therefore, we examined expression and co-localization of different neurotransmitters and neuronal markers in both plexuses as well as in neuronal fibres. Immunohistochemical staining was performed on wholemount preparations of ISP and OSP and on cryostat sections. Antibodies against choline acetyltransferase (ChAT), substance P (SP), somatostatin (SOM), neuropeptide Y (NPY), vasoactive intestinal peptide (VIP), neuronal nitric oxide synthase (nNOS) and the pan-neuronal markers Hu C/D and neuron specific enolase (NSE) were used. The ISP contained 1,380 ± 131 ganglia per cm2 and 122 ± 12 neurons per ganglion. In contrast, the OSP showed a wider meshwork (215 ± 33 ganglia per cm2) and smaller ganglia (57 ± 3 neurons per ganglion). In the ISP, 42% of all neurons expressed ChAT. About 66% of ChAT-positive neurons co-localized SP. A small number of ISP neurons expressed SOM. Chemical coding in the OSP was more complex. Besides the ChAT/±SP subpopulation (32% of all neurons), a nNOS-immunoreactive population (31%) was detected. Most nitrergic neurons were only immunoreactive for nNOS; 10% co-localized with VIP. A small subpopulation of OSP neurons was immunoreactive for ChAT/nNOS/±VIP. All types of neurotransmitters found in the ISP or OSP were also detected in neuronal fibres within the mucosa. We suppose that the cholinergic population in the ISP is involved in the control of epithelial functions. Regarding neurochemical coding, the OSP shares some similarities with the myenteric plexus. Because of its location and neurochemical characteristics, the OSP may be involved in controlling both the mucosa and circular muscle. PMID:26230272

Differences between primary auditory cortex and auditory belt related to encoding and choice for AM sounds

PubMed Central

Niwa, Mamiko; Johnson, Jeffrey S.; O’Connor, Kevin N.; Sutter, Mitchell L.

2013-01-01

We recorded from middle-lateral (ML) and primary (A1) auditory cortex while macaques discriminated amplitude modulated (AM) from unmodulated noise. Compared to A1, ML had a higher proportion of neurons that encode increasing AM depth by decreasing their firing-rates (‘decreasing’ neurons), particularly with responses that were not synchronized to the modulation. Choice probability (CP) analysis revealed that A1 and ML activity were different during the first half of the test stimulus. In A1, significant CP begins prior to the test stimulus, remains relatively constant (or increases slightly) during the stimulus and increases greatly within 200 ms of lever-release. Neurons in ML behave similarly, except that significant CP disappears during the first half of the stimulus and reappears during the second half and pre-release periods. CP differences between A1 and ML depend on neural response type. In ML (but not A1), when activity is lower during the first half of the stimulus in non-synchronized ‘decreasing’ neurons, the monkey is more likely to report AM. Neurons that both increase firing rate with increasing modulation depth (‘increasing’ neurons) and synchronize their responses to AM had similar choice-related activity dynamics in ML and A1. The results suggest that, when ascending the auditory system, there is a transformation in coding AM from primarily synchronized ‘increasing’ responses in A1 to non-synchronized and dual (‘increasing’/’decreasing’) coding in ML. This sensory transformation is accompanied by changes in the timing of activity related to choice, suggesting functional differences between A1 and ML related to attention and/or behavior. PMID:23658177

Does Spike-Timing-Dependent Synaptic Plasticity Couple or Decouple Neurons Firing in Synchrony?

PubMed Central

Knoblauch, Andreas; Hauser, Florian; Gewaltig, Marc-Oliver; Körner, Edgar; Palm, Günther

2012-01-01

Spike synchronization is thought to have a constructive role for feature integration, attention, associative learning, and the formation of bidirectionally connected Hebbian cell assemblies. By contrast, theoretical studies on spike-timing-dependent plasticity (STDP) report an inherently decoupling influence of spike synchronization on synaptic connections of coactivated neurons. For example, bidirectional synaptic connections as found in cortical areas could be reproduced only by assuming realistic models of STDP and rate coding. We resolve this conflict by theoretical analysis and simulation of various simple and realistic STDP models that provide a more complete characterization of conditions when STDP leads to either coupling or decoupling of neurons firing in synchrony. In particular, we show that STDP consistently couples synchronized neurons if key model parameters are matched to physiological data: First, synaptic potentiation must be significantly stronger than synaptic depression for small (positive or negative) time lags between presynaptic and postsynaptic spikes. Second, spike synchronization must be sufficiently imprecise, for example, within a time window of 5–10 ms instead of 1 ms. Third, axonal propagation delays should not be much larger than dendritic delays. Under these assumptions synchronized neurons will be strongly coupled leading to a dominance of bidirectional synaptic connections even for simple STDP models and low mean firing rates at the level of spontaneous activity. PMID:22936909

LSENS, a general chemical kinetics and sensitivity analysis code for gas-phase reactions: User's guide

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; Bittker, David A.

1993-01-01

A general chemical kinetics and sensitivity analysis code for complex, homogeneous, gas-phase reactions is described. The main features of the code, LSENS, are its flexibility, efficiency and convenience in treating many different chemical reaction models. The models include static system, steady, one-dimensional, inviscid flow, shock initiated reaction, and a perfectly stirred reactor. In addition, equilibrium computations can be performed for several assigned states. An implicit numerical integration method, which works efficiently for the extremes of very fast and very slow reaction, is used for solving the 'stiff' differential equation systems that arise in chemical kinetics. For static reactions, sensitivity coefficients of all dependent variables and their temporal derivatives with respect to the initial values of dependent variables and/or the rate coefficient parameters can be computed. This paper presents descriptions of the code and its usage, and includes several illustrative example problems.

Optimal size of stochastic Hodgkin-Huxley neuronal systems for maximal energy efficiency in coding pulse signals

NASA Astrophysics Data System (ADS)

Yu, Lianchun; Liu, Liwei

2014-03-01

The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.

Optimal size of stochastic Hodgkin-Huxley neuronal systems for maximal energy efficiency in coding pulse signals.

PubMed

Yu, Lianchun; Liu, Liwei

2014-03-01

The generation and conduction of action potentials (APs) represents a fundamental means of communication in the nervous system and is a metabolically expensive process. In this paper, we investigate the energy efficiency of neural systems in transferring pulse signals with APs. By analytically solving a bistable neuron model that mimics the AP generation with a particle crossing the barrier of a double well, we find the optimal number of ion channels that maximizes the energy efficiency of a neuron. We also investigate the energy efficiency of a neuron population in which the input pulse signals are represented with synchronized spikes and read out with a downstream coincidence detector neuron. We find an optimal number of neurons in neuron population, as well as the number of ion channels in each neuron that maximizes the energy efficiency. The energy efficiency also depends on the characters of the input signals, e.g., the pulse strength and the interpulse intervals. These results are confirmed by computer simulation of the stochastic Hodgkin-Huxley model with a detailed description of the ion channel random gating. We argue that the tradeoff between signal transmission reliability and energy cost may influence the size of the neural systems when energy use is constrained.

Decoding synchronized oscillations within the brain: phase-delayed inhibition provides a robust mechanism for creating a sharp synchrony filter.

PubMed

Patel, Mainak; Joshi, Badal

2013-10-07

The widespread presence of synchronized neuronal oscillations within the brain suggests that a mechanism must exist that is capable of decoding such activity. Two realistic designs for such a decoder include: (1) a read-out neuron with a high spike threshold, or (2) a phase-delayed inhibition network motif. Despite requiring a more elaborate network architecture, phase-delayed inhibition has been observed in multiple systems, suggesting that it may provide inherent advantages over simply imposing a high spike threshold. In this work, we use a computational and mathematical approach to investigate the efficacy of the phase-delayed inhibition motif in detecting synchronized oscillations. We show that phase-delayed inhibition is capable of creating a synchrony detector with sharp synchrony filtering properties that depend critically on the time course of inputs. Additionally, we show that phase-delayed inhibition creates a synchrony filter that is far more robust than that created by a high spike threshold. Copyright © 2013 Elsevier Ltd. All rights reserved.

Olfactory coding: giant inhibitory neuron governs sparse odor codes.

PubMed

Gupta, Nitin; Stopfer, Mark

2011-07-12

Electrophysiological investigations in locusts have revealed that the sparseness of odor representations, in the brain region expected to mediate olfactory learning, is shaped by a unique inhibitory neuron. Copyright © 2011 Elsevier Ltd. All rights reserved.

Hearing sounds, understanding actions: action representation in mirror neurons.

PubMed

Kohler, Evelyne; Keysers, Christian; Umiltà, M Alessandra; Fogassi, Leonardo; Gallese, Vittorio; Rizzolatti, Giacomo

2002-08-02

Many object-related actions can be recognized by their sound. We found neurons in monkey premotor cortex that discharge when the animal performs a specific action and when it hears the related sound. Most of the neurons also discharge when the monkey observes the same action. These audiovisual mirror neurons code actions independently of whether these actions are performed, heard, or seen. This discovery in the monkey homolog of Broca's area might shed light on the origin of language: audiovisual mirror neurons code abstract contents-the meaning of actions-and have the auditory access typical of human language to these contents.

Opponent Coding of Sound Location (Azimuth) in Planum Temporale is Robust to Sound-Level Variations.

PubMed

Derey, Kiki; Valente, Giancarlo; de Gelder, Beatrice; Formisano, Elia

2016-01-01

Coding of sound location in auditory cortex (AC) is only partially understood. Recent electrophysiological research suggests that neurons in mammalian auditory cortex are characterized by broad spatial tuning and a preference for the contralateral hemifield, that is, a nonuniform sampling of sound azimuth. Additionally, spatial selectivity decreases with increasing sound intensity. To accommodate these findings, it has been proposed that sound location is encoded by the integrated activity of neuronal populations with opposite hemifield tuning ("opponent channel model"). In this study, we investigated the validity of such a model in human AC with functional magnetic resonance imaging (fMRI) and a phase-encoding paradigm employing binaural stimuli recorded individually for each participant. In all subjects, we observed preferential fMRI responses to contralateral azimuth positions. Additionally, in most AC locations, spatial tuning was broad and not level invariant. We derived an opponent channel model of the fMRI responses by subtracting the activity of contralaterally tuned regions in bilateral planum temporale. This resulted in accurate decoding of sound azimuth location, which was unaffected by changes in sound level. Our data thus support opponent channel coding as a neural mechanism for representing acoustic azimuth in human AC. © The Author 2015. Published by Oxford University Press.

Inhibitory neurons promote robust critical firing dynamics in networks of integrate-and-fire neurons.

PubMed

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).

Covariation of axon initial segment location and dendritic tree normalizes the somatic action potential

PubMed Central

Hamada, Mustafa S.; Goethals, Sarah; de Vries, Sharon I.; Brette, Romain

2016-01-01

In mammalian neurons, the axon initial segment (AIS) electrically connects the somatodendritic compartment with the axon and converts the incoming synaptic voltage changes into a temporally precise action potential (AP) output code. Although axons often emanate directly from the soma, they may also originate more distally from a dendrite, the implications of which are not well-understood. Here, we show that one-third of the thick-tufted layer 5 pyramidal neurons have an axon originating from a dendrite and are characterized by a reduced dendritic complexity and thinner main apical dendrite. Unexpectedly, the rising phase of somatic APs is electrically indistinguishable between neurons with a somatic or a dendritic axon origin. Cable analysis of the neurons indicated that the axonal axial current is inversely proportional to the AIS distance, denoting the path length between the soma and the start of the AIS, and to produce invariant somatic APs, it must scale with the local somatodendritic capacitance. In agreement, AIS distance inversely correlates with the apical dendrite diameter, and model simulations confirmed that the covariation suffices to normalize the somatic AP waveform. Therefore, in pyramidal neurons, the AIS location is finely tuned with the somatodendritic capacitive load, serving as a homeostatic regulation of the somatic AP in the face of diverse neuronal morphologies. PMID:27930291

Fast Gamma Rhythms in the Hippocampus Promote Encoding of Novel Object–Place Pairings

PubMed Central

Bieri, Kevin Wood; Hwaun, Ernie

2016-01-01

Abstract Hippocampal gamma rhythms increase during mnemonic operations (Johnson and Redish, 2007; Montgomery and Buzsáki, 2007; Sederberg et al., 2007; Jutras et al., 2009; Trimper et al., 2014) and may affect memory encoding by coordinating activity of neurons that code related information (Jensen and Lisman, 2005). Here, a hippocampal-dependent, object–place association task (Clark et al., 2000; Broadbent et al., 2004; Eacott and Norman, 2004; Lee et al., 2005; Winters et al., 2008; Barker and Warburton, 2011) was used in rats to investigate how slow and fast gamma rhythms in the hippocampus relate to encoding of memories for novel object–place associations. In novel object tasks, the degree of hippocampal dependence has been reported to vary depending on the type of novelty (Eichenbaum et al., 2007; Winters et al., 2008). Therefore, gamma activity was examined during three novelty conditions: a novel object presented in a location where a familiar object had been (NO), a familiar object presented in a location where no object had been (NL), and a novel object presented in a location where no object had been (NO+NL). The strongest and most consistent effects were observed for fast gamma rhythms during the NO+NL condition. Fast gamma power, CA3–CA1 phase synchrony, and phase-locking of place cell spikes increased during exploration of novel, compared to familiar, object–place associations. Additionally, place cell spiking during exploration of novel object–place pairings was increased when fast gamma rhythms were present. These results suggest that fast gamma rhythms promote encoding of memories for novel object–place associations. PMID:27257621

Dual Coding Theory Explains Biphasic Collective Computation in Neural Decision-Making.

PubMed

Daniels, Bryan C; Flack, Jessica C; Krakauer, David C

2017-01-01

A central question in cognitive neuroscience is how unitary, coherent decisions at the whole organism level can arise from the distributed behavior of a large population of neurons with only partially overlapping information. We address this issue by studying neural spiking behavior recorded from a multielectrode array with 169 channels during a visual motion direction discrimination task. It is well known that in this task there are two distinct phases in neural spiking behavior. Here we show Phase I is a distributed or incompressible phase in which uncertainty about the decision is substantially reduced by pooling information from many cells. Phase II is a redundant or compressible phase in which numerous single cells contain all the information present at the population level in Phase I, such that the firing behavior of a single cell is enough to predict the subject's decision. Using an empirically grounded dynamical modeling framework, we show that in Phase I large cell populations with low redundancy produce a slow timescale of information aggregation through critical slowing down near a symmetry-breaking transition. Our model indicates that increasing collective amplification in Phase II leads naturally to a faster timescale of information pooling and consensus formation. Based on our results and others in the literature, we propose that a general feature of collective computation is a "coding duality" in which there are accumulation and consensus formation processes distinguished by different timescales.

Dual Coding Theory Explains Biphasic Collective Computation in Neural Decision-Making

PubMed Central

Daniels, Bryan C.; Flack, Jessica C.; Krakauer, David C.

2017-01-01

A central question in cognitive neuroscience is how unitary, coherent decisions at the whole organism level can arise from the distributed behavior of a large population of neurons with only partially overlapping information. We address this issue by studying neural spiking behavior recorded from a multielectrode array with 169 channels during a visual motion direction discrimination task. It is well known that in this task there are two distinct phases in neural spiking behavior. Here we show Phase I is a distributed or incompressible phase in which uncertainty about the decision is substantially reduced by pooling information from many cells. Phase II is a redundant or compressible phase in which numerous single cells contain all the information present at the population level in Phase I, such that the firing behavior of a single cell is enough to predict the subject's decision. Using an empirically grounded dynamical modeling framework, we show that in Phase I large cell populations with low redundancy produce a slow timescale of information aggregation through critical slowing down near a symmetry-breaking transition. Our model indicates that increasing collective amplification in Phase II leads naturally to a faster timescale of information pooling and consensus formation. Based on our results and others in the literature, we propose that a general feature of collective computation is a “coding duality” in which there are accumulation and consensus formation processes distinguished by different timescales. PMID:28634436

A neural circuit for gamma-band coherence across the retinotopic map in mouse visual cortex

PubMed Central

Hakim, Richard; Shamardani, Kiarash

2018-01-01

Cortical gamma oscillations have been implicated in a variety of cognitive, behavioral, and circuit-level phenomena. However, the circuit mechanisms of gamma-band generation and synchronization across cortical space remain uncertain. Using optogenetic patterned illumination in acute brain slices of mouse visual cortex, we define a circuit composed of layer 2/3 (L2/3) pyramidal cells and somatostatin (SOM) interneurons that phase-locks ensembles across the retinotopic map. The network oscillations generated here emerge from non-periodic stimuli, and are stimulus size-dependent, coherent across cortical space, narrow band (30 Hz), and depend on SOM neuron but not parvalbumin (PV) neuron activity; similar to visually induced gamma oscillations observed in vivo. Gamma oscillations generated in separate cortical locations exhibited high coherence as far apart as 850 μm, and lateral gamma entrainment depended on SOM neuron activity. These data identify a circuit that is sufficient to mediate long-range gamma-band coherence in the primary visual cortex. PMID:29480803

Geometric phase coded metasurface: from polarization dependent directive electromagnetic wave scattering to diffusion-like scattering.

PubMed

Chen, Ke; Feng, Yijun; Yang, Zhongjie; Cui, Li; Zhao, Junming; Zhu, Bo; Jiang, Tian

2016-10-24

Ultrathin metasurface compromising various sub-wavelength meta-particles offers promising advantages in controlling electromagnetic wave by spatially manipulating the wavefront characteristics across the interface. The recently proposed digital coding metasurface could even simplify the design and optimization procedures due to the digitalization of the meta-particle geometry. However, current attempts to implement the digital metasurface still utilize several structural meta-particles to obtain certain electromagnetic responses, and requiring time-consuming optimization especially in multi-bits coding designs. In this regard, we present herein utilizing geometric phase based single structured meta-particle with various orientations to achieve either 1-bit or multi-bits digital metasurface. Particular electromagnetic wave scattering patterns dependent on the incident polarizations can be tailored by the encoded metasurfaces with regular sequences. On the contrast, polarization insensitive diffusion-like scattering can also been successfully achieved by digital metasurface encoded with randomly distributed coding sequences leading to substantial suppression of backward scattering in a broadband microwave frequency. The proposed digital metasurfaces provide simple designs and reveal new opportunities for controlling electromagnetic wave scattering with or without polarization dependence.

Geometric phase coded metasurface: from polarization dependent directive electromagnetic wave scattering to diffusion-like scattering

PubMed Central

Chen, Ke; Feng, Yijun; Yang, Zhongjie; Cui, Li; Zhao, Junming; Zhu, Bo; Jiang, Tian

2016-01-01

Ultrathin metasurface compromising various sub-wavelength meta-particles offers promising advantages in controlling electromagnetic wave by spatially manipulating the wavefront characteristics across the interface. The recently proposed digital coding metasurface could even simplify the design and optimization procedures due to the digitalization of the meta-particle geometry. However, current attempts to implement the digital metasurface still utilize several structural meta-particles to obtain certain electromagnetic responses, and requiring time-consuming optimization especially in multi-bits coding designs. In this regard, we present herein utilizing geometric phase based single structured meta-particle with various orientations to achieve either 1-bit or multi-bits digital metasurface. Particular electromagnetic wave scattering patterns dependent on the incident polarizations can be tailored by the encoded metasurfaces with regular sequences. On the contrast, polarization insensitive diffusion-like scattering can also been successfully achieved by digital metasurface encoded with randomly distributed coding sequences leading to substantial suppression of backward scattering in a broadband microwave frequency. The proposed digital metasurfaces provide simple designs and reveal new opportunities for controlling electromagnetic wave scattering with or without polarization dependence. PMID:27775064

Spatial Correlations in Natural Scenes Modulate Response Reliability in Mouse Visual Cortex

PubMed Central

Rikhye, Rajeev V.

2015-01-01

Intrinsic neuronal variability significantly limits information encoding in the primary visual cortex (V1). Certain stimuli can suppress this intertrial variability to increase the reliability of neuronal responses. In particular, responses to natural scenes, which have broadband spatiotemporal statistics, are more reliable than responses to stimuli such as gratings. However, very little is known about which stimulus statistics modulate reliable coding and how this occurs at the neural ensemble level. Here, we sought to elucidate the role that spatial correlations in natural scenes play in reliable coding. We developed a novel noise-masking method to systematically alter spatial correlations in natural movies, without altering their edge structure. Using high-speed two-photon calcium imaging in vivo, we found that responses in mouse V1 were much less reliable at both the single neuron and population level when spatial correlations were removed from the image. This change in reliability was due to a reorganization of between-neuron correlations. Strongly correlated neurons formed ensembles that reliably and accurately encoded visual stimuli, whereas reducing spatial correlations reduced the activation of these ensembles, leading to an unreliable code. Together with an ensemble-specific normalization model, these results suggest that the coordinated activation of specific subsets of neurons underlies the reliable coding of natural scenes. SIGNIFICANCE STATEMENT The natural environment is rich with information. To process this information with high fidelity, V1 neurons have to be robust to noise and, consequentially, must generate responses that are reliable from trial to trial. While several studies have hinted that both stimulus attributes and population coding may reduce noise, the details remain unclear. Specifically, what features of natural scenes are important and how do they modulate reliability? This study is the first to investigate the role of spatial correlations, which are a fundamental attribute of natural scenes, in shaping stimulus coding by V1 neurons. Our results provide new insights into how stimulus spatial correlations reorganize the correlated activation of specific ensembles of neurons to ensure accurate information processing in V1. PMID:26511254

Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality.

PubMed

Li, Zhongyu; Butler, Erik; Li, Kang; Lu, Aidong; Ji, Shuiwang; Zhang, Shaoting

2018-02-12

Recently released large-scale neuron morphological data has greatly facilitated the research in neuroinformatics. However, the sheer volume and complexity of these data pose significant challenges for efficient and accurate neuron exploration. In this paper, we propose an effective retrieval framework to address these problems, based on frontier techniques of deep learning and binary coding. For the first time, we develop a deep learning based feature representation method for the neuron morphological data, where the 3D neurons are first projected into binary images and then learned features using an unsupervised deep neural network, i.e., stacked convolutional autoencoders (SCAEs). The deep features are subsequently fused with the hand-crafted features for more accurate representation. Considering the exhaustive search is usually very time-consuming in large-scale databases, we employ a novel binary coding method to compress feature vectors into short binary codes. Our framework is validated on a public data set including 58,000 neurons, showing promising retrieval precision and efficiency compared with state-of-the-art methods. In addition, we develop a novel neuron visualization program based on the techniques of augmented reality (AR), which can help users take a deep exploration of neuron morphologies in an interactive and immersive manner.

Behavior‐dependent activity patterns of GABAergic long‐range projecting neurons in the rat hippocampus

PubMed Central

Micklem, Ben; Borhegyi, Zsolt; Swiejkowski, Daniel A.; Valenti, Ornella; Viney, Tim J.; Kotzadimitriou, Dimitrios; Klausberger, Thomas

2017-01-01

ABSTRACT Long‐range glutamatergic and GABAergic projections participate in temporal coordination of neuronal activity in distributed cortical areas. In the hippocampus, GABAergic neurons project to the medial septum and retrohippocampal areas. Many GABAergic projection cells express somatostatin (SOM+) and, together with locally terminating SOM+ bistratified and O‐LM cells, contribute to dendritic inhibition of pyramidal cells. We tested the hypothesis that diversity in SOM+ cells reflects temporal specialization during behavior using extracellular single cell recording and juxtacellular neurobiotin‐labeling in freely moving rats. We have demonstrated that rare GABAergic projection neurons discharge rhythmically and are remarkably diverse. During sharp wave‐ripples, most projection cells, including a novel SOM+ GABAergic back‐projecting cell, increased their activity similar to bistratified cells, but unlike O‐LM cells. During movement, most projection cells discharged along the descending slope of theta cycles, but some fired at the trough jointly with bistratified and O‐LM cells. The specialization of hippocampal SOM+ projection neurons complements the action of local interneurons in differentially phasing inputs from the CA3 area to CA1 pyramidal cell dendrites during sleep and wakefulness. Our observations suggest that GABAergic projection cells mediate the behavior‐ and network state‐dependent binding of neuronal assemblies amongst functionally‐related brain regions by transmitting local rhythmic entrainment of neurons in CA1 to neuronal populations in other areas. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. PMID:27997999

LRP8-Reelin-regulated Neuronal (LRN) Enhancer Signature Underlying Learning and Memory Formation

PubMed Central

Telese, Francesca; Ma, Qi; Perez, Patricia Montilla; Notani, Dimple; Oh, Soohwan; Li, Wenbo; Comoletti, Davide; Ohgi, Kenneth A.; Taylor, Havilah; Rosenfeld, Michael G.

2015-01-01

Summary One of the exceptional properties of the brain is its ability to acquire new knowledge through learning and to store that information through memory. The epigenetic mechanisms linking changes in neuronal transcriptional programs to behavioral plasticity remain largely unknown. Here, we identify the epigenetic signature of the neuronal enhancers required for transcriptional regulation of synaptic plasticity genes during memory formation, linking this to Reelin signaling. The binding of Reelin to its receptor, LRP8, triggers activation of this cohort of LRP8-Reelin-regulated-Neuronal (LRN) enhancers that serve as the ultimate convergence point of a novel synapse-to-nucleus pathway. Reelin simultaneously regulates NMDA-receptor transmission, which reciprocally permits the required, γ-secretase-dependent cleavage of LRP8, revealing an unprecedented role for its intracellular domain in the regulation of synaptically generated signals. These results uncover an in vivo enhancer code serving as a critical molecular component of cognition and relevant to psychiatric disorders linked to defects in Reelin signaling. PMID:25892301

The search for a hippocampal engram.

PubMed

Mayford, Mark

2014-01-05

Understanding the molecular and cellular changes that underlie memory, the engram, requires the identification, isolation and manipulation of the neurons involved. This presents a major difficulty for complex forms of memory, for example hippocampus-dependent declarative memory, where the participating neurons are likely to be sparse, anatomically distributed and unique to each individual brain and learning event. In this paper, I discuss several new approaches to this problem. In vivo calcium imaging techniques provide a means of assessing the activity patterns of large numbers of neurons over long periods of time with precise anatomical identification. This provides important insight into how the brain represents complex information and how this is altered with learning. The development of techniques for the genetic modification of neural ensembles based on their natural, sensory-evoked, activity along with optogenetics allows direct tests of the coding function of these ensembles. These approaches provide a new methodological framework in which to examine the mechanisms of complex forms of learning at the level of the neurons involved in a specific memory.

The search for a hippocampal engram

PubMed Central

Mayford, Mark

2014-01-01

Understanding the molecular and cellular changes that underlie memory, the engram, requires the identification, isolation and manipulation of the neurons involved. This presents a major difficulty for complex forms of memory, for example hippocampus-dependent declarative memory, where the participating neurons are likely to be sparse, anatomically distributed and unique to each individual brain and learning event. In this paper, I discuss several new approaches to this problem. In vivo calcium imaging techniques provide a means of assessing the activity patterns of large numbers of neurons over long periods of time with precise anatomical identification. This provides important insight into how the brain represents complex information and how this is altered with learning. The development of techniques for the genetic modification of neural ensembles based on their natural, sensory-evoked, activity along with optogenetics allows direct tests of the coding function of these ensembles. These approaches provide a new methodological framework in which to examine the mechanisms of complex forms of learning at the level of the neurons involved in a specific memory. PMID:24298162

The spectrotemporal filter mechanism of auditory selective attention

PubMed Central

Lakatos, Peter; Musacchia, Gabriella; O’Connell, Monica N.; Falchier, Arnaud Y.; Javitt, Daniel C.; Schroeder, Charles E.

2013-01-01

SUMMARY While we have convincing evidence that attention to auditory stimuli modulates neuronal responses at or before the level of primary auditory cortex (A1), the underlying physiological mechanisms are unknown. We found that attending to rhythmic auditory streams resulted in the entrainment of ongoing oscillatory activity reflecting rhythmic excitability fluctuations in A1. Strikingly, while the rhythm of the entrained oscillations in A1 neuronal ensembles reflected the temporal structure of the attended stream, the phase depended on the attended frequency content. Counter-phase entrainment across differently tuned A1 regions resulted in both the amplification and sharpening of responses at attended time points, in essence acting as a spectrotemporal filter mechanism. Our data suggest that selective attention generates a dynamically evolving model of attended auditory stimulus streams in the form of modulatory subthreshold oscillations across tonotopically organized neuronal ensembles in A1 that enhances the representation of attended stimuli. PMID:23439126

Neurochemical coding of enteric neurons in the guinea pig stomach.

PubMed

Schemann, M; Schaaf, C; Mäder, M

1995-03-06

The aim of this study was to investigate the neurochemical coding of myenteric neurons in the guinea pig gastric corpus by using immunohistochemical methods. Antibodies and antisera against calbindin (CALB), calretinin (CALRET), choline acetyltransferase (ChAT), calcitonin gene-related peptide (CGRP), dopamine beta-hydroxylase (DBH), beta-endorphin (ENK), neuropeptide Y (NPY), neuron-specific enolase (NSE), nitric oxide synthase (NOS), protein gene product 9.5 (PGP), parvalbumin (PARV), serotonin (5-HT), somatostatin (SOM), substance P (SP), tyrosine hydroxylase (TH), and vasoactive intestinal peptide (VIP) were used. Double- and triple-labeling studies revealed colocalization of certain transmitters and enabled the identification of distinct subpopulations of gastric enteric neurons. NPY/VIP/NOS/ENK were present in 28% of all neurons, whereas 11% had NPY/VIP/DBH/ChAT; NOS-only neurons made up 2% of the population. The combination SP/ChAT/ENK occurred in 21% of the population, whereas SP/ChAT/ENK/CALRET and SP/CHAT/SOM/ +/- CALRET was identified in 5% and 6% of all cells, respectively. 5-HT-containing neurons comprised 2% of all cells and could be further classified by the presence of additional antigens as 5-HT/SP/(ChAT) or 5-HT/VIP/(ChAT). Approximately 21% of all neurons contained only ChAT with no additional antigen present and are referred to as ChAT/-. Gastric myenteric ganglion cells were not immunoreactive for CALB, PARV, CGRP, or TH. The results of this study indicate that gastric myenteric neurons can be characterized on the basis of different chemical coding. Neurochemical coding of corpus myenteric neurons revealed some similarities and significant differences in comparison with other regions of the gut. These differences might reflect adaptation of enteric nerves according to regional specialization and the distinct functions of the proximal stomach as a gastric reservoir.

Mind the gap: Neural coding of species identity in birdsong prosody.

PubMed

Araki, Makoto; Bandi, M M; Yazaki-Sugiyama, Yoko

2016-12-09

Juvenile songbirds learn vocal communication from adult tutors of the same species but not from adults of other species. How species-specific learning emerges from the basic features of song prosody remains unknown. In the zebra finch auditory cortex, we discovered a class of neurons that register the silent temporal gaps between song syllables and are distinct from neurons encoding syllable morphology. Behavioral learning and neuronal coding of temporal gap structure resisted song tutoring from other species: Zebra finches fostered by Bengalese finch parents learned Bengalese finch song morphology transposed onto zebra finch temporal gaps. During the vocal learning period, temporal gap neurons fired selectively to zebra finch song. The innate temporal coding of intersyllable silent gaps suggests a neuronal barcode for conspecific vocal learning and social communication in acoustically diverse environments. Copyright © 2016, American Association for the Advancement of Science.

Network synchronization in hippocampal neurons.

PubMed

Penn, Yaron; Segal, Menahem; Moses, Elisha

2016-03-22

Oscillatory activity is widespread in dynamic neuronal networks. The main paradigm for the origin of periodicity consists of specialized pacemaking elements that synchronize and drive the rest of the network; however, other models exist. Here, we studied the spontaneous emergence of synchronized periodic bursting in a network of cultured dissociated neurons from rat hippocampus and cortex. Surprisingly, about 60% of all active neurons were self-sustained oscillators when disconnected, each with its own natural frequency. The individual neuron's tendency to oscillate and the corresponding oscillation frequency are controlled by its excitability. The single neuron intrinsic oscillations were blocked by riluzole, and are thus dependent on persistent sodium leak currents. Upon a gradual retrieval of connectivity, the synchrony evolves: Loose synchrony appears already at weak connectivity, with the oscillators converging to one common oscillation frequency, yet shifted in phase across the population. Further strengthening of the connectivity causes a reduction in the mean phase shifts until zero-lag is achieved, manifested by synchronous periodic network bursts. Interestingly, the frequency of network bursting matches the average of the intrinsic frequencies. Overall, the network behaves like other universal systems, where order emerges spontaneously by entrainment of independent rhythmic units. Although simplified with respect to circuitry in the brain, our results attribute a basic functional role for intrinsic single neuron excitability mechanisms in driving the network's activity and dynamics, contributing to our understanding of developing neural circuits.

Development of a CFD code for casting simulation

NASA Technical Reports Server (NTRS)

Murph, Jesse E.

1993-01-01

Because of high rejection rates for large structural castings (e.g., the Space Shuttle Main Engine Alternate Turbopump Design Program), a reliable casting simulation computer code is very desirable. This code would reduce both the development time and life cycle costs by allowing accurate modeling of the entire casting process. While this code could be used for other types of castings, the most significant reductions of time and cost would probably be realized in complex investment castings, where any reduction in the number of development castings would be of significant benefit. The casting process is conveniently divided into three distinct phases: (1) mold filling, where the melt is poured or forced into the mold cavity; (2) solidification, where the melt undergoes a phase change to the solid state; and (3) cool down, where the solidified part continues to cool to ambient conditions. While these phases may appear to be separate and distinct, temporal overlaps do exist between phases (e.g., local solidification occurring during mold filling), and some phenomenological events are affected by others (e.g., residual stresses depend on solidification and cooling rates). Therefore, a reliable code must accurately model all three phases and the interactions between each. While many codes have been developed (to various stages of complexity) to model the solidification and cool down phases, only a few codes have been developed to model mold filling.

Extraction of Inter-Aural Time Differences Using a Spiking Neuron Network Model of the Medial Superior Olive.

PubMed

Encke, Jörg; Hemmert, Werner

2018-01-01

The mammalian auditory system is able to extract temporal and spectral features from sound signals at the two ears. One important cue for localization of low-frequency sound sources in the horizontal plane are inter-aural time differences (ITDs) which are first analyzed in the medial superior olive (MSO) in the brainstem. Neural recordings of ITD tuning curves at various stages along the auditory pathway suggest that ITDs in the mammalian brainstem are not represented in form of a Jeffress-type place code. An alternative is the hemispheric opponent-channel code, according to which ITDs are encoded as the difference in the responses of the MSO nuclei in the two hemispheres. In this study, we present a physiologically-plausible, spiking neuron network model of the mammalian MSO circuit and apply two different methods of extracting ITDs from arbitrary sound signals. The network model is driven by a functional model of the auditory periphery and physiological models of the cochlear nucleus and the MSO. Using a linear opponent-channel decoder, we show that the network is able to detect changes in ITD with a precision down to 10 μs and that the sensitivity of the decoder depends on the slope of the ITD-rate functions. A second approach uses an artificial neuronal network to predict ITDs directly from the spiking output of the MSO and ANF model. Using this predictor, we show that the MSO-network is able to reliably encode static and time-dependent ITDs over a large frequency range, also for complex signals like speech.

Effects of isoflurane anesthesia on ensemble patterns of Ca2+ activity in mouse v1: reduced direction selectivity independent of increased correlations in cellular activity.

PubMed

Goltstein, Pieter M; Montijn, Jorrit S; Pennartz, Cyriel M A

2015-01-01

Anesthesia affects brain activity at the molecular, neuronal and network level, but it is not well-understood how tuning properties of sensory neurons and network connectivity change under its influence. Using in vivo two-photon calcium imaging we matched neuron identity across episodes of wakefulness and anesthesia in the same mouse and recorded spontaneous and visually evoked activity patterns of neuronal ensembles in these two states. Correlations in spontaneous patterns of calcium activity between pairs of neurons were increased under anesthesia. While orientation selectivity remained unaffected by anesthesia, this treatment reduced direction selectivity, which was attributable to an increased response to the null-direction. As compared to anesthesia, populations of V1 neurons coded more mutual information on opposite stimulus directions during wakefulness, whereas information on stimulus orientation differences was lower. Increases in correlations of calcium activity during visual stimulation were correlated with poorer population coding, which raised the hypothesis that the anesthesia-induced increase in correlations may be causal to degrading directional coding. Visual stimulation under anesthesia, however, decorrelated ongoing activity patterns to a level comparable to wakefulness. Because visual stimulation thus appears to 'break' the strength of pairwise correlations normally found in spontaneous activity under anesthesia, the changes in correlational structure cannot explain the awake-anesthesia difference in direction coding. The population-wide decrease in coding for stimulus direction thus occurs independently of anesthesia-induced increments in correlations of spontaneous activity.

Effects of Isoflurane Anesthesia on Ensemble Patterns of Ca2+ Activity in Mouse V1: Reduced Direction Selectivity Independent of Increased Correlations in Cellular Activity

PubMed Central

Goltstein, Pieter M.; Montijn, Jorrit S.; Pennartz, Cyriel M. A.

2015-01-01

Anesthesia affects brain activity at the molecular, neuronal and network level, but it is not well-understood how tuning properties of sensory neurons and network connectivity change under its influence. Using in vivo two-photon calcium imaging we matched neuron identity across episodes of wakefulness and anesthesia in the same mouse and recorded spontaneous and visually evoked activity patterns of neuronal ensembles in these two states. Correlations in spontaneous patterns of calcium activity between pairs of neurons were increased under anesthesia. While orientation selectivity remained unaffected by anesthesia, this treatment reduced direction selectivity, which was attributable to an increased response to the null-direction. As compared to anesthesia, populations of V1 neurons coded more mutual information on opposite stimulus directions during wakefulness, whereas information on stimulus orientation differences was lower. Increases in correlations of calcium activity during visual stimulation were correlated with poorer population coding, which raised the hypothesis that the anesthesia-induced increase in correlations may be causal to degrading directional coding. Visual stimulation under anesthesia, however, decorrelated ongoing activity patterns to a level comparable to wakefulness. Because visual stimulation thus appears to ‘break’ the strength of pairwise correlations normally found in spontaneous activity under anesthesia, the changes in correlational structure cannot explain the awake-anesthesia difference in direction coding. The population-wide decrease in coding for stimulus direction thus occurs independently of anesthesia-induced increments in correlations of spontaneous activity. PMID:25706867

Intrinsic and integrative properties of substantia nigra pars reticulata neurons

PubMed Central

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

Computer simulations of stimulus dependent state switching in basic circuits of bursting neurons

NASA Astrophysics Data System (ADS)

Rabinovich, Mikhail; Huerta, Ramón; Bazhenov, Maxim; Kozlov, Alexander K.; Abarbanel, Henry D. I.

1998-11-01

We investigate the ability of oscillating neural circuits to switch between different states of oscillation in two basic neural circuits. We model two quite distinct small neural circuits. The first circuit is based on invertebrate central pattern generator (CPG) studies [A. I. Selverston and M. Moulins, The Crustacean Stomatogastric System (Springer-Verlag, Berlin, 1987)] and is composed of two neurons coupled via both gap junction and inhibitory synapses. The second consists of coupled pairs of interconnected thalamocortical relay and thalamic reticular neurons with both inhibitory and excitatory synaptic coupling. The latter is an elementary unit of the thalamic networks passing sensory information to the cerebral cortex [M. Steriade, D. A. McCormick, and T. J. Sejnowski, Science 262, 679 (1993)]. Both circuits have contradictory coupling between symmetric parts. The thalamocortical model has excitatory and inhibitory connections and the CPG has reciprocal inhibitory and electrical coupling. We describe the dynamics of the individual neurons in these circuits by conductance based ordinary differential equations of Hodgkin-Huxley type [J. Physiol. (London) 117, 500 (1952)]. Both model circuits exhibit bistability and hysteresis in a wide region of coupling strengths. The two main modes of behavior are in-phase and out-of-phase oscillations of the symmetric parts of the network. We investigate the response of these circuits, while they are operating in bistable regimes, to externally imposed excitatory spike trains with varying interspike timing and small amplitude pulses. These are meant to represent spike trains received by the basic circuits from sensory neurons. Circuits operating in a bistable region are sensitive to the frequency of these excitatory inputs. Frequency variations lead to changes from in-phase to out-of-phase coordination or vice versa. The signaling information contained in a spike train driving the network can place the circuit into one or another state depending on the interspike interval and this happens within a few spikes. These states are maintained by the basic circuit after the input signal is ended. When a new signal of the correct frequency enters the circuit, it can be switched to another state with the same ease.

Spontaneous action potentials and neural coding in unmyelinated axons.

PubMed

O'Donnell, Cian; van Rossum, Mark C W

2015-04-01

The voltage-gated Na and K channels in neurons are responsible for action potential generation. Because ion channels open and close in a stochastic fashion, spontaneous (ectopic) action potentials can result even in the absence of stimulation. While spontaneous action potentials have been studied in detail in single-compartment models, studies on spatially extended processes have been limited. The simulations and analysis presented here show that spontaneous rate in unmyelinated axon depends nonmonotonically on the length of the axon, that the spontaneous activity has sub-Poisson statistics, and that neural coding can be hampered by the spontaneous spikes by reducing the probability of transmitting the first spike in a train.

Temporal-pattern recognition by single neurons in a sensory pathway devoted to social communication behavior

PubMed Central

Carlson, Bruce A.

2010-01-01

Sensory systems often encode stimulus information into the temporal pattern of action potential activity. However, little is known about how the information contained within these patterns is extracted by postsynaptic neurons. Similar to temporal coding by sensory neurons, social information in mormyrid fish is encoded into the temporal patterning of an electric organ discharge (EOD). In the current study, sensitivity to temporal patterns of electrosensory stimuli was found to arise within the midbrain posterior exterolateral nucleus (ELp). Whole-cell patch recordings from ELp neurons in vivo revealed three patterns of interpulse interval (IPI) tuning: low-pass neurons tuned to long intervals, high-pass neurons tuned to short intervals and band-pass neurons tuned to intermediate intervals. Many neurons within each class also responded preferentially to either increasing or decreasing IPIs. Playback of electric signaling patterns recorded from freely behaving fish revealed that the IPI and direction tuning of ELp neurons resulted in selective responses to particular social communication displays characterized by distinct IPI patterns. The postsynaptic potential responses of many neurons indicated a combination of excitatory and inhibitory synaptic input, and the IPI tuning of ELp neurons was directly related to rate-dependent changes in the direction and amplitude of postsynaptic potentials. These results suggest that differences in the dynamics of short-term synaptic plasticity in excitatory and inhibitory pathways may tune central sensory neurons to particular temporal patterns of presynaptic activity. This may represent a general mechanism for the processing of behaviorally-relevant stimulus information encoded into temporal patterns of activity by sensory neurons. PMID:19641105

Temporal-pattern recognition by single neurons in a sensory pathway devoted to social communication behavior.

PubMed

Carlson, Bruce A

2009-07-29

Sensory systems often encode stimulus information into the temporal pattern of action potential activity. However, little is known about how the information contained within these patterns is extracted by postsynaptic neurons. Similar to temporal coding by sensory neurons, social information in mormyrid fish is encoded into the temporal patterning of an electric organ discharge. In the current study, sensitivity to temporal patterns of electrosensory stimuli was found to arise within the midbrain posterior exterolateral nucleus (ELp). Whole-cell patch recordings from ELp neurons in vivo revealed three patterns of interpulse interval (IPI) tuning: low-pass neurons tuned to long intervals, high-pass neurons tuned to short intervals, and bandpass neurons tuned to intermediate intervals. Many neurons within each class also responded preferentially to either increasing or decreasing IPIs. Playback of electric signaling patterns recorded from freely behaving fish revealed that the IPI and direction tuning of ELp neurons resulted in selective responses to particular social communication displays characterized by distinct IPI patterns. The postsynaptic potential responses of many neurons indicated a combination of excitatory and inhibitory synaptic input, and the IPI tuning of ELp neurons was directly related to rate-dependent changes in the direction and amplitude of postsynaptic potentials. These results suggest that differences in the dynamics of short-term synaptic plasticity in excitatory and inhibitory pathways may tune central sensory neurons to particular temporal patterns of presynaptic activity. This may represent a general mechanism for the processing of behaviorally relevant stimulus information encoded into temporal patterns of activity by sensory neurons.

FMRFamide produces biphasic modulation of the LFS motor neurons in the neural circuit of the siphon withdrawal reflex of Aplysia by activating Na+ and K+ currents.

PubMed

Belkin, K J; Abrams, T W

1993-12-01

The molluscan neuropeptide FMRFamide has an inhibitory effect on transmitter release from the presynaptic sensory neurons in the neural circuit for the siphon withdrawal reflex. We have explored whether FMRFamide also acts postsynaptically in motor neurons in this circuit, focusing on the LFS motor neurons. FMRFamide typically produces a biphasic response in LFS neurons: a fast excitatory response followed by a prolonged inhibitory response. We have analyzed these postsynaptic actions and compared them with the mechanism of FMRFamide's inhibition of the presynaptic sensory neurons. The transient excitatory effect of FMRFamide, which desensitizes rapidly, is due to activation of a TTX-insensitive, Na(+)-dependent inward current. The late hyperpolarizing phase of the FMRFamide response results from activation of at least two K+ currents. One component of the hyperpolarizing response is active at rest and at more hyperpolarized membrane potentials, and is blocked by 5 mM 4-aminopyridine, suggesting that it differs from the previously described FMRFamide-modulated K+ currents in the presynaptic sensory neurons. In addition, FMRFamide increases a 4-aminopyridine-insensitive K+ current. Presynaptically, FMRFamide increases K+ conductance, acting via release of arachidonic acid. In the LFS motor neurons, application of arachidonic acid mimicked the prolonged, hyperpolarizing phase of the FMRFamide response; 4-bromophenacyl bromide, an inhibitor of phospholipase A2, selectively blocked this component of the FMRFamide response. Thus, FMRFamide may act in parallel pre- and post-synaptically to inhibit the output of the siphon withdrawal reflex circuit, producing this inhibitory effect via the same second messenger in the sensory neurons and motor neurons, though a number of the K+ currents modulated in these two types of neurons are different.

Synchronization properties of coupled chaotic neurons: The role of random shared input

NASA Astrophysics Data System (ADS)

Kumar, Rupesh; Bilal, Shakir; Ramaswamy, Ram

2016-06-01

Spike-time correlations of neighbouring neurons depend on their intrinsic firing properties as well as on the inputs they share. Studies have shown that periodically firing neurons, when subjected to random shared input, exhibit asynchronicity. Here, we study the effect of random shared input on the synchronization of weakly coupled chaotic neurons. The cases of so-called electrical and chemical coupling are both considered, and we observe a wide range of synchronization behaviour. When subjected to identical shared random input, there is a decrease in the threshold coupling strength needed for chaotic neurons to synchronize in-phase. The system also supports lag-synchronous states, and for these, we find that shared input can cause desynchronization. We carry out a master stability function analysis for a network of such neurons and show agreement with the numerical simulations. The contrasting role of shared random input for complete and lag synchronized neurons is useful in understanding spike-time correlations observed in many areas of the brain.

Synchronization properties of coupled chaotic neurons: The role of random shared input

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Rupesh; Bilal, Shakir; Ramaswamy, Ram

Spike-time correlations of neighbouring neurons depend on their intrinsic firing properties as well as on the inputs they share. Studies have shown that periodically firing neurons, when subjected to random shared input, exhibit asynchronicity. Here, we study the effect of random shared input on the synchronization of weakly coupled chaotic neurons. The cases of so-called electrical and chemical coupling are both considered, and we observe a wide range of synchronization behaviour. When subjected to identical shared random input, there is a decrease in the threshold coupling strength needed for chaotic neurons to synchronize in-phase. The system also supports lag–synchronous states,more » and for these, we find that shared input can cause desynchronization. We carry out a master stability function analysis for a network of such neurons and show agreement with the numerical simulations. The contrasting role of shared random input for complete and lag synchronized neurons is useful in understanding spike-time correlations observed in many areas of the brain.« less

A hypothalamic circuit for the circadian control of aggression.

PubMed

Todd, William D; Fenselau, Henning; Wang, Joshua L; Zhang, Rong; Machado, Natalia L; Venner, Anne; Broadhurst, Rebecca Y; Kaur, Satvinder; Lynagh, Timothy; Olson, David P; Lowell, Bradford B; Fuller, Patrick M; Saper, Clifford B

2018-05-01

'Sundowning' in dementia and Alzheimer's disease is characterized by early-evening agitation and aggression. While such periodicity suggests a circadian origin, whether the circadian clock directly regulates aggressive behavior is unknown. We demonstrate that a daily rhythm in aggression propensity in male mice is gated by GABAergic subparaventricular zone (SPZ GABA ) neurons, the major postsynaptic targets of the central circadian clock, the suprachiasmatic nucleus. Optogenetic mapping revealed that SPZ GABA neurons receive input from vasoactive intestinal polypeptide suprachiasmatic nucleus neurons and innervate neurons in the ventrolateral part of the ventromedial hypothalamus (VMH), which is known to regulate aggression. Additionally, VMH-projecting dorsal SPZ neurons are more active during early day than early night, and acute chemogenetic inhibition of SPZ GABA transmission phase-dependently increases aggression. Finally, SPZ GABA -recipient central VMH neurons directly innervate ventrolateral VMH neurons, and activation of this intra-VMH circuit drove attack behavior. Altogether, we reveal a functional polysynaptic circuit by which the suprachiasmatic nucleus clock regulates aggression.

Noise-constrained switching times for heteroclinic computing

NASA Astrophysics Data System (ADS)

Neves, Fabio Schittler; Voit, Maximilian; Timme, Marc

2017-03-01

Heteroclinic computing offers a novel paradigm for universal computation by collective system dynamics. In such a paradigm, input signals are encoded as complex periodic orbits approaching specific sequences of saddle states. Without inputs, the relevant states together with the heteroclinic connections between them form a network of states—the heteroclinic network. Systems of pulse-coupled oscillators or spiking neurons naturally exhibit such heteroclinic networks of saddles, thereby providing a substrate for general analog computations. Several challenges need to be resolved before it becomes possible to effectively realize heteroclinic computing in hardware. The time scales on which computations are performed crucially depend on the switching times between saddles, which in turn are jointly controlled by the system's intrinsic dynamics and the level of external and measurement noise. The nonlinear dynamics of pulse-coupled systems often strongly deviate from that of time-continuously coupled (e.g., phase-coupled) systems. The factors impacting switching times in pulse-coupled systems are still not well understood. Here we systematically investigate switching times in dependence of the levels of noise and intrinsic dissipation in the system. We specifically reveal how local responses to pulses coact with external noise. Our findings confirm that, like in time-continuous phase-coupled systems, piecewise-continuous pulse-coupled systems exhibit switching times that transiently increase exponentially with the number of switches up to some order of magnitude set by the noise level. Complementarily, we show that switching times may constitute a good predictor for the computation reliability, indicating how often an input signal must be reiterated. By characterizing switching times between two saddles in conjunction with the reliability of a computation, our results provide a first step beyond the coding of input signal identities toward a complementary coding for the intensity of those signals. The results offer insights on how future heteroclinic computing systems may operate under natural, and thus noisy, conditions.

In vitro Neurons in Mammalian Cortical Layer 4 Exhibit Intrinsic Oscillatory Activity in the 10- to 50-Hz Frequency Range

NASA Astrophysics Data System (ADS)

Llinas, Rodolfo R.; Grace, Anthony A.; Yarom, Yosef

1991-02-01

We report here the presence of fast subthreshold oscillatory potentials recorded in vitro from neurons within layer 4 of the guinea pig frontal cortex. Two types of oscillatory neurons were recorded: (i) One type exhibited subthreshold oscillations whose frequency increased with membrane depolarization and encompassed a range of 10-45 Hz. Action potentials in this type of neuron demonstrated clear after-hyperpolarizations. (ii) The second type of neuron was characterized by narrow-frequency oscillations near 35-50 Hz. These oscillations often outlasted the initiating depolarizing stimulus. No calcium component could be identified in their action potential. In both types of cell the subthreshold oscillations were tetrodotoxin-sensitive, indicating that the depolarizing phase of the oscillation was generated by a voltage-dependent sodium conductance. The initial depolarizing phase was followed by a potassium conductance responsible for the falling phase of the oscillatory wave. In both types of cell, the subthreshold oscillation could trigger spikes at the oscillatory frequency, if the membrane was sufficiently depolarized. Combining intracellular recordings with Lucifer yellow staining showed that the narrow-frequency oscillatory activity was produced by a sparsely spinous interneuron located in layer 4 of the cortex. This neuron has extensive local axonal collaterals that ramify in layers 3 and 4 such that they may contribute to the columnar synchronization of activity in the 40- to 50-Hz range. Cortical activity in this frequency range has been proposed as the basis for the "conjunctive properties" of central nervous system networks.

Electrophysiology of the mammillary complex in vitro. I. Tuberomammillary and lateral mammillary neurons

NASA Technical Reports Server (NTRS)

Llinas, R. R.; Alonso, A.

1992-01-01

1. The electrophysiological properties of the tuberomammillary and lateral mammillary neurons in the guinea pig mammillary body were studied using an in vitro brain slice preparation. 2. Tuberomammillary (n = 79) neurons were recorded mainly ventral to the lateral mammillary body as well as ventromedially to the fornix within the rostral part of the medial mammillary nucleus. Intracellular staining with horseradish peroxidase (n = 9) and Lucifer yellow (n = 3) revealed that these cells have several thick, long, spiny dendrites emerging from large (20-35 microns) fusiform somata. 3. Most tuberomammillary neurons (66%) fired spontaneously at a relatively low frequency (0.5-10 Hz) at the resting membrane potential. The action potentials were broad (2.3 ms) with a prominent Ca(2+)-dependent shoulder on the falling phase. Deep (17.8 mV), long-lasting spike afterhyperpolarizations were largely Ca(2+)-independent. 4. All tuberomammillary neurons recorded displayed pronounced delayed firing when the cells were activated from a potential negative to the resting level. The cells also displayed a delayed return to the baseline at the break of hyperpolarizing pulses applied from a membrane potential level close to firing threshold. Analysis of the voltage- and time dependence of this delayed rectification suggested the presence of a transient outward current similar to the A current (IA). These were not completely blocked by high concentrations of 4-aminopyridine, whereas the delayed onset of firing was always abolished when voltage-dependent Ca2+ conductances were blocked by superfusion with Cd2+. 5. Tuberomammillary neurons also displayed inward rectification in the hyperpolarizing and, primarily, depolarizing range. Block of voltage-gated Na(+)-dependent conductances with tetrodotoxin (TTX) selectively abolished inward rectification in the depolarizing range, indicating the presence of a persistent low-threshold sodium-dependent conductance (gNap). In fact, persistent TTX-sensitive, plateau potentials were always elicited following Ca2+ block with Cd2+ when K+ currents were reduced by superfusion with tetraethylammonium. 6. The gNap in tuberomammillary neurons may subserve the pacemaker current underlying the spontaneous firing of these cells. The large-amplitude spike afterhyperpolarization of these neurons sets the availability of the transient outward rectifier, which, in conjunction with the pacemaker current, establishes the rate at which membrane potential approaches spike threshold. 7. Repetitive firing elicited by direct depolarization enhanced the spike shoulder of tuberomammillary neurons. Spike trains were followed by a Ca(2+)-dependent, apamine-sensitive, slow afterhyperpolarization. 8. Lateral mammillary neurons were morphologically and electrophysiologically different from tuberomammillary neurons. All lateral mammillary neurons neurons recorded (n = 44) were silent at rest (-60 mV).(ABSTRACT TRUNCATED AT 400 WORDS).

Mind bomb-1 is an essential modulator of long-term memory and synaptic plasticity via the Notch signaling pathway

PubMed Central

2012-01-01

Background Notch signaling is well recognized as a key regulator of the neuronal fate during embryonic development, but its function in the adult brain is still largely unknown. Mind bomb-1 (Mib1) is an essential positive regulator in the Notch pathway, acting non-autonomously in the signal-sending cells. Therefore, genetic ablation of Mib1 in mature neuron would give valuable insight to understand the cell-to-cell interaction between neurons via Notch signaling for their proper function. Results Here we show that the inactivation of Mib1 in mature neurons in forebrain results in impaired hippocampal dependent spatial memory and contextual fear memory. Consistently, hippocampal slices from Mib1-deficient mice show impaired late-phase, but not early-phase, long-term potentiation and long-term depression without change in basal synaptic transmission at SC-CA1 synapses. Conclusions These data suggest that Mib1-mediated Notch signaling is essential for long-lasting synaptic plasticity and memory formation in the rodent hippocampus. PMID:23111145

Structure of a randomly grown 2-d network.

PubMed

Ajazi, Fioralba; Napolitano, George M; Turova, Tatyana; Zaurbek, Izbassar

2015-10-01

We introduce a growing random network on a plane as a model of a growing neuronal network. The properties of the structure of the induced graph are derived. We compare our results with available data. In particular, it is shown that depending on the parameters of the model the system undergoes in time different phases of the structure. We conclude with a possible explanation of some empirical data on the connections between neurons. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Efficient transformation of an auditory population code in a small sensory system.

PubMed

Clemens, Jan; Kutzki, Olaf; Ronacher, Bernhard; Schreiber, Susanne; Wohlgemuth, Sandra

2011-08-16

Optimal coding principles are implemented in many large sensory systems. They include the systematic transformation of external stimuli into a sparse and decorrelated neuronal representation, enabling a flexible readout of stimulus properties. Are these principles also applicable to size-constrained systems, which have to rely on a limited number of neurons and may only have to fulfill specific and restricted tasks? We studied this question in an insect system--the early auditory pathway of grasshoppers. Grasshoppers use genetically fixed songs to recognize mates. The first steps of neural processing of songs take place in a small three-layer feed-forward network comprising only a few dozen neurons. We analyzed the transformation of the neural code within this network. Indeed, grasshoppers create a decorrelated and sparse representation, in accordance with optimal coding theory. Whereas the neuronal input layer is best read out as a summed population, a labeled-line population code for temporal features of the song is established after only two processing steps. At this stage, information about song identity is maximal for a population decoder that preserves neuronal identity. We conclude that optimal coding principles do apply to the early auditory system of the grasshopper, despite its size constraints. The inputs, however, are not encoded in a systematic, map-like fashion as in many larger sensory systems. Already at its periphery, part of the grasshopper auditory system seems to focus on behaviorally relevant features, and is in this property more reminiscent of higher sensory areas in vertebrates.

In-situ recording of ionic currents in projection neurons and Kenyon cells in the olfactory pathway of the honeybee

PubMed Central

Rössler, Wolfgang

2018-01-01

The honeybee olfactory pathway comprises an intriguing pattern of convergence and divergence: ~60.000 olfactory sensory neurons (OSN) convey olfactory information on ~900 projection neurons (PN) in the antennal lobe (AL). To transmit this information reliably, PNs employ relatively high spiking frequencies with complex patterns. PNs project via a dual olfactory pathway to the mushroom bodies (MB). This pathway comprises the medial (m-ALT) and the lateral antennal lobe tract (l-ALT). PNs from both tracts transmit information from a wide range of similar odors, but with distinct differences in coding properties. In the MBs, PNs form synapses with many Kenyon cells (KC) that encode odors in a spatially and temporally sparse way. The transformation from complex information coding to sparse coding is a well-known phenomenon in insect olfactory coding. Intrinsic neuronal properties as well as GABAergic inhibition are thought to contribute to this change in odor representation. In the present study, we identified intrinsic neuronal properties promoting coding differences between PNs and KCs using in-situ patch-clamp recordings in the intact brain. We found very prominent K+ currents in KCs clearly differing from the PN currents. This suggests that odor coding differences between PNs and KCs may be caused by differences in their specific ion channel properties. Comparison of ionic currents of m- and l-ALT PNs did not reveal any differences at a qualitative level. PMID:29351552

Causal relationships between neurons of the nucleus incertus and the hippocampal theta activity in the rat.

PubMed

Martínez-Bellver, Sergio; Cervera-Ferri, Ana; Luque-García, Aina; Martínez-Ricós, Joana; Valverde-Navarro, Alfonso; Bataller, Manuel; Guerrero, Juan; Teruel-Marti, Vicent

2017-03-01

The nucleus incertus is a key node of the brainstem circuitry involved in hippocampal theta rhythmicity. Synchronisation exists between the nucleus incertus and hippocampal activities during theta periods. By the Granger causality analysis, we demonstrated a directional information flow between theta rhythmical neurons in the nucleus incertus and the hippocampus in theta-on states. The electrical stimulation of the nucleus incertus is also able to evoke a phase reset of the hippocampal theta wave. Our data suggest that the nucleus incertus is a key node of theta generation and the modulation network. In recent years, a body of evidence has shown that the nucleus incertus (NI), in the dorsal tegmental pons, is a key node of the brainstem circuitry involved in hippocampal theta rhythmicity. Ascending reticular brainstem system activation evokes hippocampal theta rhythm with coupled neuronal activity in the NI. In a recent paper, we showed three populations of neurons in the NI with differential firing during hippocampal theta activation. The objective of this work was to better evaluate the causal relationship between the activity of NI neurons and the hippocampus during theta activation in order to further understand the role of the NI in the theta network. A Granger causality analysis was run to determine whether hippocampal theta activity with sensory-evoked theta depends on the neuronal activity of the NI, or vice versa. The analysis showed causal interdependence between the NI and the hippocampus during theta activity, whose directional flow depended on the different neuronal assemblies of the NI. Whereas type I and II NI neurons mainly acted as receptors of hippocampal information, type III neuronal activity was the predominant source of flow between the NI and the hippocampus in theta states. We further determined that the electrical activation of the NI was able to reset hippocampal waves with enhanced theta-band power, depending on the septal area. Collectively, these data suggest that hippocampal theta oscillations after sensory activation show dependence on NI neuron activity, which could play a key role in establishing optimal conditions for memory encoding. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Performance breakdown in optimal stimulus decoding

NASA Astrophysics Data System (ADS)

Kostal, Lubomir; Lansky, Petr; Pilarski, Stevan

2015-06-01

Objective. One of the primary goals of neuroscience is to understand how neurons encode and process information about their environment. The problem is often approached indirectly by examining the degree to which the neuronal response reflects the stimulus feature of interest. Approach. In this context, the methods of signal estimation and detection theory provide the theoretical limits on the decoding accuracy with which the stimulus can be identified. The Cramér-Rao lower bound on the decoding precision is widely used, since it can be evaluated easily once the mathematical model of the stimulus-response relationship is determined. However, little is known about the behavior of different decoding schemes with respect to the bound if the neuronal population size is limited. Main results. We show that under broad conditions the optimal decoding displays a threshold-like shift in performance in dependence on the population size. The onset of the threshold determines a critical range where a small increment in size, signal-to-noise ratio or observation time yields a dramatic gain in the decoding precision. Significance. We demonstrate the existence of such threshold regions in early auditory and olfactory information coding. We discuss the origin of the threshold effect and its impact on the design of effective coding approaches in terms of relevant population size.

Perforated Patch-clamp Recording of Mouse Olfactory Sensory Neurons in Intact Neuroepithelium: Functional Analysis of Neurons Expressing an Identified Odorant Receptor

PubMed Central

Jarriault, David; Grosmaitre, Xavier

2015-01-01

Analyzing the physiological responses of olfactory sensory neurons (OSN) when stimulated with specific ligands is critical to understand the basis of olfactory-driven behaviors and their modulation. These coding properties depend heavily on the initial interaction between odor molecules and the olfactory receptor (OR) expressed in the OSNs. The identity, specificity and ligand spectrum of the expressed OR are critical. The probability to find the ligand of the OR expressed in an OSN chosen randomly within the epithelium is very low. To address this challenge, this protocol uses genetically tagged mice expressing the fluorescent protein GFP under the control of the promoter of defined ORs. OSNs are located in a tight and organized epithelium lining the nasal cavity, with neighboring cells influencing their maturation and function. Here we describe a method to isolate an intact olfactory epithelium and record through patch-clamp recordings the properties of OSNs expressing defined odorant receptors. The protocol allows one to characterize OSN membrane properties while keeping the influence of the neighboring tissue. Analysis of patch-clamp results yields a precise quantification of ligand/OR interactions, transduction pathways and pharmacology, OSNs' coding properties and their modulation at the membrane level.  PMID:26275097

Performance breakdown in optimal stimulus decoding.

PubMed

Lubomir Kostal; Lansky, Petr; Pilarski, Stevan

2015-06-01

One of the primary goals of neuroscience is to understand how neurons encode and process information about their environment. The problem is often approached indirectly by examining the degree to which the neuronal response reflects the stimulus feature of interest. In this context, the methods of signal estimation and detection theory provide the theoretical limits on the decoding accuracy with which the stimulus can be identified. The Cramér-Rao lower bound on the decoding precision is widely used, since it can be evaluated easily once the mathematical model of the stimulus-response relationship is determined. However, little is known about the behavior of different decoding schemes with respect to the bound if the neuronal population size is limited. We show that under broad conditions the optimal decoding displays a threshold-like shift in performance in dependence on the population size. The onset of the threshold determines a critical range where a small increment in size, signal-to-noise ratio or observation time yields a dramatic gain in the decoding precision. We demonstrate the existence of such threshold regions in early auditory and olfactory information coding. We discuss the origin of the threshold effect and its impact on the design of effective coding approaches in terms of relevant population size.

Effect of helium-neon laser on fast excitatory postsynaptic potential of neurons in the isolated rat superior cervical ganglia

NASA Astrophysics Data System (ADS)

Mo, Hua; He, Ping; Mo, Ning

2004-08-01

The aim of this study is to further measure the effect of 632.8-nm helium-neon laser on fast excitatory postsynaptic potential (f-EPSP) of postganglionic neurons in isolated rat superior cervical ganglia by means of intracellular recording techniques. The neurons with f-EPSP were irradiated by different power densities (1-5 mW/cm2) laser. Irradiated by the 2-mW/cm2 laser, the amplitude of the f-EPSP could augment (P<0.05, paired t test) and even cause action potential at the end of the first 1-2 minutes, the f-EPSP could descend and last for 3-8 minutes. But the amplitude of the f-EPSP of neurons irradiated by the 5-mW/cm2 laser could depress for the irradiating periods. The results show that: 1) the variation of the amplitude of f-EPSP caused by laser is power density-dependent and time-dependent; 2) there exist the second-order phases in the interaction of the helium-neon laser with neurons. These findings may provide certain evidence in explanation of the mechanisms of clinical helium-neon laser therapy.

Decoding the ubiquitous role of microRNAs in neurogenesis.

PubMed

Nampoothiri, Sreekala S; Rajanikant, G K

2017-04-01

Neurogenesis generates fledgling neurons that mature to form an intricate neuronal circuitry. The delusion on adult neurogenesis was far resolved in the past decade and became one of the largely explored domains to identify multifaceted mechanisms bridging neurodevelopment and neuropathology. Neurogenesis encompasses multiple processes including neural stem cell proliferation, neuronal differentiation, and cell fate determination. Each neurogenic process is specifically governed by manifold signaling pathways, several growth factors, coding, and non-coding RNAs. A class of small non-coding RNAs, microRNAs (miRNAs), is ubiquitously expressed in the brain and has emerged to be potent regulators of neurogenesis. It functions by fine-tuning the expression of specific neurogenic gene targets at the post-transcriptional level and modulates the development of mature neurons from neural progenitor cells. Besides the commonly discussed intrinsic factors, the neuronal morphogenesis is also under the control of several extrinsic temporal cues, which in turn are regulated by miRNAs. This review enlightens on dicer controlled switch from neurogenesis to gliogenesis, miRNA regulation of neuronal maturation and the differential expression of miRNAs in response to various extrinsic cues affecting neurogenesis.

Energy-efficient neural information processing in individual neurons and neuronal networks.

PubMed

Yu, Lianchun; Yu, Yuguo

2017-11-01

Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Ca2+ and frequency dependence of exocytosis in isolated somata of magnocellular supraoptic neurones of the rat hypothalamus

PubMed Central

Soldo, Brandi L; Giovannucci, David R; Stuenkel, Edward L; Moises, Hylan C

2004-01-01

In addition to action potential-evoked exocytotic release at neurohypophysial nerve terminals, the neurohormones arginine vasopressin (aVP) and oxytocin (OT) undergo Ca2+-dependent somatodendritic release within the supraoptic and paraventricular hypothalamic nuclei. However, the cellular and molecular mechanisms that underlie this release have not been elucidated. In the present study, the whole-cell patch-clamp technique was utilized in combination with high-time-resolved measurements of membrane capacitance (Cm) and microfluorometric measurements of cytosolic free Ca2+ concentration ([Ca2+]i) to examine the Ca2+ and stimulus dependence of exocytosis in the somata of magnocellular neurosecretory cells (MNCs) isolated from rat supraoptic nucleus (SON). Single depolarizing steps (≥20 ms) that evoked high-voltage-activated (HVA) Ca2+ currents (ICa) and elevations in intracellular Ca2+ concentration were accompanied by an increase in Cm in a majority (40/47) of SON neurones. The Cm responses were composed of an initial Ca2+-independent, transient component and a subsequent, sustained phase of increased Cm (termed ΔCm) mediated by an influx of Ca2+, and increased with corresponding prolongation of depolarizing step durations (20–200 ms). From this relationship we estimated the rate of vesicular release to be 1533 vesicles s−1. Delivery of neurone-derived action potential waveforms (APWs) as stimulus templates elicited ICa and also induced a ΔCm, provided APWs were applied in trains of greater than 13 Hz. A train of APWs modelled after the bursting pattern recorded from an OT-containing neurone during the milk ejection reflex was effective in supporting an exocytotic ΔCm in isolated MNCs, indicating that the somata of SON neurones respond to physiological patterns of neuronal activity with Ca2+-dependent exocytotic activity. PMID:14645448

Processing of Intraoral Olfactory and Gustatory Signals in the Gustatory Cortex of Awake Rats.

PubMed

Samuelsen, Chad L; Fontanini, Alfredo

2017-01-11

The integration of gustatory and olfactory information is essential to the perception of flavor. Human neuroimaging experiments have pointed to the gustatory cortex (GC) as one of the areas involved in mediating flavor perception. Although GC's involvement in encoding the chemical identity and hedonic value of taste stimuli is well studied, it is unknown how single GC neurons process olfactory stimuli emanating from the mouth. In this study, we relied on multielectrode recordings to investigate how single GC neurons respond to intraorally delivered tastants and tasteless odorants dissolved in water and whether/how these two modalities converge in the same neurons. We found that GC neurons could either be unimodal, responding exclusively to taste (taste-only) or odor (odor-only), or bimodal, responding to both gustatory and olfactory stimuli. Odor responses were confirmed to result from retronasal olfaction: monitoring respiration revealed that exhalation preceded odor-evoked activity and reversible inactivation of olfactory receptors in the nasal epithelium significantly reduced responses to intraoral odorants but not to tastants. Analysis of bimodal neurons revealed that they encode palatability significantly better than the unimodal taste-only group. Bimodal neurons exhibited similar responses to palatable tastants and odorants dissolved in water. This result suggested that odorized water could be palatable. This interpretation was further supported with a brief access task, where rats avoided consuming aversive taste stimuli and consumed the palatable tastants and dissolved odorants. These results demonstrate the convergence of the chemosensory components of flavor onto single GC neurons and provide evidence for the integration of flavor with palatability coding. Food perception and choice depend upon the concurrent processing of olfactory and gustatory signals from the mouth. The primary gustatory cortex has been proposed to integrate chemosensory stimuli; however, no study has examined the single-unit responses to intraoral odorant presentation. Here we found that neurons in gustatory cortex can respond either exclusively to tastants, exclusively to odorants, or to both (bimodal). Several differences exist between these groups' responses; notably, bimodal neurons code palatability significantly better than unimodal neurons. This group of neurons might represent a substrate for how odorants gain the quality of tastants. Copyright © 2017 the authors 0270-6474/17/370244-14$15.00/0.

Behavior-dependent activity patterns of GABAergic long-range projecting neurons in the rat hippocampus.

PubMed

Katona, Linda; Micklem, Ben; Borhegyi, Zsolt; Swiejkowski, Daniel A; Valenti, Ornella; Viney, Tim J; Kotzadimitriou, Dimitrios; Klausberger, Thomas; Somogyi, Peter

2017-04-01

Long-range glutamatergic and GABAergic projections participate in temporal coordination of neuronal activity in distributed cortical areas. In the hippocampus, GABAergic neurons project to the medial septum and retrohippocampal areas. Many GABAergic projection cells express somatostatin (SOM+) and, together with locally terminating SOM+ bistratified and O-LM cells, contribute to dendritic inhibition of pyramidal cells. We tested the hypothesis that diversity in SOM+ cells reflects temporal specialization during behavior using extracellular single cell recording and juxtacellular neurobiotin-labeling in freely moving rats. We have demonstrated that rare GABAergic projection neurons discharge rhythmically and are remarkably diverse. During sharp wave-ripples, most projection cells, including a novel SOM+ GABAergic back-projecting cell, increased their activity similar to bistratified cells, but unlike O-LM cells. During movement, most projection cells discharged along the descending slope of theta cycles, but some fired at the trough jointly with bistratified and O-LM cells. The specialization of hippocampal SOM+ projection neurons complements the action of local interneurons in differentially phasing inputs from the CA3 area to CA1 pyramidal cell dendrites during sleep and wakefulness. Our observations suggest that GABAergic projection cells mediate the behavior- and network state-dependent binding of neuronal assemblies amongst functionally-related brain regions by transmitting local rhythmic entrainment of neurons in CA1 to neuronal populations in other areas. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.

Dopamine reward prediction error coding.

PubMed

Schultz, Wolfram

2016-03-01

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.

Dopamine reward prediction error coding

PubMed Central

Schultz, Wolfram

2016-01-01

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards—an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware. PMID:27069377

Novelty-Sensitive Dopaminergic Neurons in the Human Substantia Nigra Predict Success of Declarative Memory Formation.

PubMed

Kamiński, Jan; Mamelak, Adam N; Birch, Kurtis; Mosher, Clayton P; Tagliati, Michele; Rutishauser, Ueli

2018-05-07

The encoding of information into long-term declarative memory is facilitated by dopamine. This process depends on hippocampal novelty signals, but it remains unknown how midbrain dopaminergic neurons are modulated by declarative-memory-based information. We recorded individual substantia nigra (SN) neurons and cortical field potentials in human patients performing a recognition memory task. We found that 25% of SN neurons were modulated by stimulus novelty. Extracellular waveform shape and anatomical location indicated that these memory-selective neurons were putatively dopaminergic. The responses of memory-selective neurons appeared 527 ms after stimulus onset, changed after a single trial, and were indicative of recognition accuracy. SN neurons phase locked to frontal cortical theta-frequency oscillations, and the extent of this coordination predicted successful memory formation. These data reveal that dopaminergic neurons in the human SN are modulated by memory signals and demonstrate a progression of information flow in the hippocampal-basal ganglia-frontal cortex loop for memory encoding. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Firing patterns in the adaptive exponential integrate-and-fire model.

PubMed

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.

Biophysical synaptic dynamics in an analog VLSI network of Hodgkin-Huxley neurons.

PubMed

Yu, Theodore; Cauwenberghs, Gert

2009-01-01

We study synaptic dynamics in a biophysical network of four coupled spiking neurons implemented in an analog VLSI silicon microchip. The four neurons implement a generalized Hodgkin-Huxley model with individually configurable rate-based kinetics of opening and closing of Na+ and K+ ion channels. The twelve synapses implement a rate-based first-order kinetic model of neurotransmitter and receptor dynamics, accounting for NMDA and non-NMDA type chemical synapses. The implemented models on the chip are fully configurable by 384 parameters accounting for conductances, reversal potentials, and pre/post-synaptic voltage-dependence of the channel kinetics. We describe the models and present experimental results from the chip characterizing single neuron dynamics, single synapse dynamics, and multi-neuron network dynamics showing phase-locking behavior as a function of synaptic coupling strength. The 3mm x 3mm microchip consumes 1.29 mW power making it promising for applications including neuromorphic modeling and neural prostheses.

Ab initio reconstruction of transcriptomes of pluripotent and lineage committed cells reveals gene structures of thousands of lincRNAs

PubMed Central

Guttman, Mitchell; Garber, Manuel; Levin, Joshua Z.; Donaghey, Julie; Robinson, James; Adiconis, Xian; Fan, Lin; Koziol, Magdalena J.; Gnirke, Andreas; Nusbaum, Chad; Rinn, John L.; Lander, Eric S.; Regev, Aviv

2010-01-01

RNA-Seq provides an unbiased way to study a transcriptome, including both coding and non-coding genes. To date, most RNA-Seq studies have critically depended on existing annotations, and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We apply it to mouse embryonic stem cells, neuronal precursor cells, and lung fibroblasts to accurately reconstruct the full-length gene structures for the vast majority of known expressed genes. We identify substantial variation in protein-coding genes, including thousands of novel 5′-start sites, 3′-ends, and internal coding exons. We then determine the gene structures of over a thousand lincRNA and antisense loci. Our results open the way to direct experimental manipulation of thousands of non-coding RNAs, and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes. PMID:20436462

Molecular codes for neuronal individuality and cell assembly in the brain

PubMed Central

Yagi, Takeshi

2012-01-01

The brain contains an enormous, but finite, number of neurons. The ability of this limited number of neurons to produce nearly limitless neural information over a lifetime is typically explained by combinatorial explosion; that is, by the exponential amplification of each neuron's contribution through its incorporation into “cell assemblies” and neural networks. In development, each neuron expresses diverse cellular recognition molecules that permit the formation of the appropriate neural cell assemblies to elicit various brain functions. The mechanism for generating neuronal assemblies and networks must involve molecular codes that give neurons individuality and allow them to recognize one another and join appropriate networks. The extensive molecular diversity of cell-surface proteins on neurons is likely to contribute to their individual identities. The clustered protocadherins (Pcdh) is a large subfamily within the diverse cadherin superfamily. The clustered Pcdh genes are encoded in tandem by three gene clusters, and are present in all known vertebrate genomes. The set of clustered Pcdh genes is expressed in a random and combinatorial manner in each neuron. In addition, cis-tetramers composed of heteromultimeric clustered Pcdh isoforms represent selective binding units for cell-cell interactions. Here I present the mathematical probabilities for neuronal individuality based on the random and combinatorial expression of clustered Pcdh isoforms and their formation of cis-tetramers in each neuron. Notably, clustered Pcdh gene products are known to play crucial roles in correct axonal projections, synaptic formation, and neuronal survival. Their molecular and biological features induce a hypothesis that the diverse clustered Pcdh molecules provide the molecular code by which neuronal individuality and cell assembly permit the combinatorial explosion of networks that supports enormous processing capability and plasticity of the brain. PMID:22518100

Cosine Directional Tuning of Theta Cell Burst Frequencies: Evidence for Spatial Coding by Oscillatory Interference

PubMed Central

Welday, Adam C.; Shlifer, I. Gary; Bloom, Matthew L.; Zhang, Kechen

2011-01-01

The rodent septohippocampal system contains “theta cells,” which burst rhythmically at 4–12 Hz, but the functional significance of this rhythm remains poorly understood (Buzsáki, 2006). Theta rhythm commonly modulates the spike trains of spatially tuned neurons such as place (O'Keefe and Dostrovsky, 1971), head direction (Tsanov et al., 2011a), grid (Hafting et al., 2005), and border cells (Savelli et al., 2008; Solstad et al., 2008). An “oscillatory interference” theory has hypothesized that some of these spatially tuned neurons may derive their positional firing from phase interference among theta oscillations with frequencies that are modulated by the speed and direction of translational movements (Burgess et al., 2005, 2007). This theory is supported by studies reporting modulation of theta frequency by movement speed (Rivas et al., 1996; Geisler et al., 2007; Jeewajee et al., 2008a), but modulation of theta frequency by movement direction has never been observed. Here we recorded theta cells from hippocampus, medial septum, and anterior thalamus of freely behaving rats. Theta cell burst frequencies varied as the cosine of the rat's movement direction, and this directional tuning was influenced by landmark cues, in agreement with predictions of the oscillatory interference theory. Computer simulations and mathematical analysis demonstrated how a postsynaptic neuron can detect location-dependent synchrony among inputs from such theta cells, and thereby mimic the spatial tuning properties of place, grid, or border cells. These results suggest that theta cells may serve a high-level computational function by encoding a basis set of oscillatory signals that interfere with one another to synthesize spatial memory representations. PMID:22072668

All-memristive neuromorphic computing with level-tuned neurons

NASA Astrophysics Data System (ADS)

Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

2016-09-01

In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

All-memristive neuromorphic computing with level-tuned neurons.

PubMed

Pantazi, Angeliki; Woźniak, Stanisław; Tuma, Tomas; Eleftheriou, Evangelos

2016-09-02

In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from many sources. Brain-inspired neuromorphic computing systems increasingly attract research interest as an alternative to the classical von Neumann processor architecture, mainly because of the coexistence of memory and processing units. In these systems, the basic components are neurons interconnected by synapses. The neurons, based on their nonlinear dynamics, generate spikes that provide the main communication mechanism. The computational tasks are distributed across the neural network, where synapses implement both the memory and the computational units, by means of learning mechanisms such as spike-timing-dependent plasticity. In this work, we present an all-memristive neuromorphic architecture comprising neurons and synapses realized by using the physical properties and state dynamics of phase-change memristors. The architecture employs a novel concept of interconnecting the neurons in the same layer, resulting in level-tuned neuronal characteristics that preferentially process input information. We demonstrate the proposed architecture in the tasks of unsupervised learning and detection of multiple temporal correlations in parallel input streams. The efficiency of the neuromorphic architecture along with the homogenous neuro-synaptic dynamics implemented with nanoscale phase-change memristors represent a significant step towards the development of ultrahigh-density neuromorphic co-processors.

Determining which mechanisms lead to activation in the motor cortex: a modeling study of transcranial magnetic stimulation using realistic stimulus waveforms and sulcal geometry1

PubMed Central

Salvador, R.; Silva, S.; Basser, P. J.; Miranda, P. C.

2010-01-01

Objective To determine which mechanisms lead to activation of neurons in the motor cortex during transcranial magnetic stimulation (TMS) with different current directions and pulse waveforms. Methods The total electric field induced in a simplified model of a cortical sulcus by a figure-eight coil was calculated using the finite element method (FEM). This electric field was then used as the input to determine the response of compartmental models of several types of neurons. Results The modeled neurons were stimulated at different sites: fiber bends for pyramidal tract neurons, axonal terminations for cortical interneurons and axon collaterals, and a combination of both for pyramidal association fibers. All neurons were more easily stimulated by a PA directed electric field, except association fibers. Additionally, the second phase of a biphasic pulse was found to be more efficient than the first phase of either monophasic or biphasic pulses. Conclusion The stimulation threshold for different types of neurons depends on the pulse waveform and current direction. The reported results might account for the range of responses obtained in TMS of the motor cortex when using different stimulation parameters. Significance Modeling studies combining electric field calculations and neuronal models may lead to a deeper understanding of the effect of the TMS-induced electric field on cortical tissue, and may be used to evaluate improvements in TMS coil and waveform design. PMID:21035390

Developmental Experience Alters Information Coding in Auditory Midbrain and Forebrain Neurons

PubMed Central

Woolley, Sarah M. N.; Hauber, Mark E.; Theunissen, Frederic E.

2010-01-01

In songbirds, species identity and developmental experience shape vocal behavior and behavioral responses to vocalizations. The interaction of species identity and developmental experience may also shape the coding properties of sensory neurons. We tested whether responses of auditory midbrain and forebrain neurons to songs differed between species and between groups of conspecific birds with different developmental exposure to song. We also compared responses of individual neurons to conspecific and heterospecific songs. Zebra and Bengalese finches that were raised and tutored by conspecific birds, and zebra finches that were cross-tutored by Bengalese finches were studied. Single-unit responses to zebra and Bengalese finch songs were recorded and analyzed by calculating mutual information, response reliability, mean spike rate, fluctuations in time-varying spike rate, distributions of time-varying spike rates, and neural discrimination of individual songs. Mutual information quantifies a response’s capacity to encode information about a stimulus. In midbrain and forebrain neurons, mutual information was significantly higher in normal zebra finch neurons than in Bengalese finch and cross-tutored zebra finch neurons, but not between Bengalese finch and cross-tutored zebra finch neurons. Information rate differences were largely due to spike rate differences. Mutual information did not differ between responses to conspecific and heterospecific songs. Therefore, neurons from normal zebra finches encoded more information about songs than did neurons from other birds, but conspecific and heterospecific songs were encoded equally. Neural discrimination of songs and mutual information were highly correlated. Results demonstrate that developmental exposure to vocalizations shapes the information coding properties of songbird auditory neurons. PMID:20039264

Frequency-dependent, transient effects of subthalamic nucleus deep brain stimulation on methamphetamine-induced circling and neuronal activity in the hemiparkinsonian rat.

PubMed

So, Rosa Q; McConnell, George C; Grill, Warren M

2017-03-01

Methamphetamine-induced circling is used to quantify the behavioral effects of subthalamic nucleus (STN) deep brain stimulation (DBS) in hemiparkinsonian rats. We observed a frequency-dependent transient effect of DBS on circling, and quantified this effect to determine its neuronal basis. High frequency STN DBS (75-260Hz) resulted in transient circling contralateral to the lesion at the onset of stimulation, which was not sustained after the first several seconds of stimulation. Following the transient behavioral change, DBS resulted in a frequency-dependent steady-state reduction in pathological ipsilateral circling, but no change in overall movement. Recordings from single neurons in globus pallidus externa (GPe) and substantia nigra pars reticulata (SNr) revealed that high frequency, but not low frequency, STN DBS elicited transient changes in both firing rate and neuronal oscillatory power at the stimulation frequency in a subpopulation of GPe and SNr neurons. These transient changes were not sustained, and most neurons exhibited a different response during the steady-state phase of DBS. During the steady-state, DBS produced elevated neuronal oscillatory power at the stimulus frequency in a majority of GPe and SNr neurons, and the increase was more pronounced during high frequency DBS than during low frequency DBS. Changes in oscillatory power during both transient and steady-state DBS were highly correlated with changes in firing rates. These results suggest that distinct neural mechanisms were responsible for transient and sustained behavioral responses to STN DBS. The transient contralateral turning behavior following the onset of high frequency DBS was paralleled by transient changes in firing rate and oscillatory power in the GPe and SNr, while steady-state suppression of ipsilateral turning was paralleled by sustained increased synchronization of basal ganglia neurons to the stimulus pulses. Our analysis of distinct frequency-dependent transient and steady-state responses to DBS lays the foundation for future mechanistic studies of the immediate and persistent effects of DBS. Copyright © 2016 Elsevier B.V. All rights reserved.

Neuronal population coding of perceived and memorized visual features in the lateral prefrontal cortex

PubMed Central

Mendoza-Halliday, Diego; Martinez-Trujillo, Julio C.

2017-01-01

The primate lateral prefrontal cortex (LPFC) encodes visual stimulus features while they are perceived and while they are maintained in working memory. However, it remains unclear whether perceived and memorized features are encoded by the same or different neurons and population activity patterns. Here we record LPFC neuronal activity while monkeys perceive the motion direction of a stimulus that remains visually available, or memorize the direction if the stimulus disappears. We find neurons with a wide variety of combinations of coding strength for perceived and memorized directions: some neurons encode both to similar degrees while others preferentially or exclusively encode either one. Reading out the combined activity of all neurons, a machine-learning algorithm reliably decode the motion direction and determine whether it is perceived or memorized. Our results indicate that a functionally diverse population of LPFC neurons provides a substrate for discriminating between perceptual and mnemonic representations of visual features. PMID:28569756

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.

Emergence of Adaptive Computation by Single Neurons in the Developing Cortex

PubMed Central

Famulare, Michael; Gjorgjieva, Julijana; Moody, William J.

2013-01-01

Adaptation is a fundamental computational motif in neural processing. To maintain stable perception in the face of rapidly shifting input, neural systems must extract relevant information from background fluctuations under many different contexts. Many neural systems are able to adjust their input–output properties such that an input's ability to trigger a response depends on the size of that input relative to its local statistical context. This “gain-scaling” strategy has been shown to be an efficient coding strategy. We report here that this property emerges during early development as an intrinsic property of single neurons in mouse sensorimotor cortex, coinciding with the disappearance of spontaneous waves of network activity, and can be modulated by changing the balance of spike-generating currents. Simultaneously, developing neurons move toward a common intrinsic operating point and a stable ratio of spike-generating currents. This developmental trajectory occurs in the absence of sensory input or spontaneous network activity. Through a combination of electrophysiology and modeling, we demonstrate that developing cortical neurons develop the ability to perform nearly perfect gain scaling by virtue of the maturing spike-generating currents alone. We use reduced single neuron models to identify the conditions for this property to hold. PMID:23884925

Convergent input from brainstem coincidence detectors onto delay-sensitive neurons in the inferior colliculus.

PubMed

McAlpine, D; Jiang, D; Shackleton, T M; Palmer, A R

1998-08-01

Responses of low-frequency neurons in the inferior colliculus (IC) of anesthetized guinea pigs were studied with binaural beats to assess their mean best interaural phase (BP) to a range of stimulating frequencies. Phase plots (stimulating frequency vs BP) were produced, from which measures of characteristic delay (CD) and characteristic phase (CP) for each neuron were obtained. The CD provides an estimate of the difference in travel time from each ear to coincidence-detector neurons in the brainstem. The CP indicates the mechanism underpinning the coincidence detector responses. A linear phase plot indicates a single, constant delay between the coincidence-detector inputs from the two ears. In more than half (54 of 90) of the neurons, the phase plot was not linear. We hypothesized that neurons with nonlinear phase plots received convergent input from brainstem coincidence detectors with different CDs. Presentation of a second tone with a fixed, unfavorable delay suppressed the response of one input, linearizing the phase plot and revealing other inputs to be relatively simple coincidence detectors. For some neurons with highly complex phase plots, the suppressor tone altered BP values, but did not resolve the nature of the inputs. For neurons with linear phase plots, the suppressor tone either completely abolished their responses or reduced their discharge rate with no change in BP. By selectively suppressing inputs with a second tone, we are able to reveal the nature of underlying binaural inputs to IC neurons, confirming the hypothesis that the complex phase plots of many IC neurons are a result of convergence from simple brainstem coincidence detectors.

Synchrony and the binding problem in macaque visual cortex

PubMed Central

Dong, Yi; Mihalas, Stefan; Qiu, Fangtu; von der Heydt, Rüdiger; Niebur, Ernst

2009-01-01

We tested the binding-by-synchrony hypothesis which proposes that object representations are formed by synchronizing spike activity between neurons that code features of the same object. We studied responses of 32 pairs of neurons recorded with microelectrodes 3 mm apart in the visual cortex of macaques performing a fixation task. Upon mapping the receptive fields of the neurons, a quadrilateral was generated so that two of its sides were centered in the receptive fields at the optimal orientations. This one-figure condition was compared with a two-figure condition in which the neurons were stimulated by two separate figures, keeping the local edges in the receptive fields identical. For each neuron, we also determined its border ownership selectivity (H. Zhou, H. S. Friedman, & R. von der Heydt, 2000). We examined both synchronization and correlation at nonzero time lag. After correcting for effects of the firing rate, we found that synchrony did not depend on the binding condition. However, finding synchrony in a pair of neurons was correlated with finding border-ownership selectivity in both members of the pair. This suggests that the synchrony reflected the connectivity in the network that generates border ownership assignment. Thus, we have not found evidence to support the binding-by-synchrony hypothesis. PMID:19146262

Intrinsic Plasticity Induced by Group II Metabotropic Glutamate Receptors via Enhancement of High Threshold KV Currents in Sound Localizing Neurons

PubMed Central

Hamlet, William R.; Lu, Yong

2016-01-01

Intrinsic plasticity has emerged as an important mechanism regulating neuronal excitability and output under physiological and pathological conditions. Here, we report a novel form of intrinsic plasticity. Using perforated patch clamp recordings, we examined the modulatory effects of group II metabotropic glutamate receptors (mGluR II) on voltage-gated potassium (KV) currents and the firing properties of neurons in the chicken nucleus laminaris (NL), the first central auditory station where interaural time cues are analyzed for sound localization. We found that activation of mGluR II by synthetic agonists resulted in a selective increase of the high threshold KV currents. More importantly, synaptically released glutamate (with reuptake blocked) also enhanced the high threshold KV currents. The enhancement was frequency-coding region dependent, being more pronounced in low frequency neurons compared to middle and high frequency neurons. The intracellular mechanism involved the Gβγ signaling pathway associated with phospholipase C and protein kinase C. The modulation strengthened membrane outward rectification, sharpened action potentials, and improved the ability of NL neurons to follow high frequency inputs. These data suggest that mGluR II provides a feedforward modulatory mechanism that may regulate temporal processing under the condition of heightened synaptic inputs. PMID:26964678

Negative Correlations in Visual Cortical Networks

PubMed Central

Chelaru, Mircea I.; Dragoi, Valentin

2016-01-01

The amount of information encoded by cortical circuits depends critically on the capacity of nearby neurons to exhibit trial-to-trial (noise) correlations in their responses. Depending on their sign and relationship to signal correlations, noise correlations can either increase or decrease the population code accuracy relative to uncorrelated neuronal firing. Whereas positive noise correlations have been extensively studied using experimental and theoretical tools, the functional role of negative correlations in cortical circuits has remained elusive. We addressed this issue by performing multiple-electrode recording in the superficial layers of the primary visual cortex (V1) of alert monkey. Despite the fact that positive noise correlations decayed exponentially with the difference in the orientation preference between cells, negative correlations were uniformly distributed across the population. Using a statistical model for Fisher Information estimation, we found that a mild increase in negative correlations causes a sharp increase in network accuracy even when mean correlations were held constant. To examine the variables controlling the strength of negative correlations, we implemented a recurrent spiking network model of V1. We found that increasing local inhibition and reducing excitation causes a decrease in the firing rates of neurons while increasing the negative noise correlations, which in turn increase the population signal-to-noise ratio and network accuracy. Altogether, these results contribute to our understanding of the neuronal mechanism involved in the generation of negative correlations and their beneficial impact on cortical circuit function. PMID:25217468

Experience-dependent phase-reversal of hippocampal neuron firing during REM sleep.

PubMed

Poe, G R; Nitz, D A; McNaughton, B L; Barnes, C A

2000-02-07

The idea that sleep could serve a cognitive function has remained popular since Freud stated that dreams were "not nonsense" but a time to sort out experiences [S. Freud, Letter to Wilhelm Fliess, May 1897, in The Origins of Psychoanalysis - Personal Letters of Sigmund Freud, M. Bonaparte, A. Freud, E. Kris (Eds.), Translated by E. Mosbacher, J. Strachey, Basic Books and Imago Publishing, 1954]. Rapid eye movement (REM) sleep, which is associated with dream reports, is now known to be is important for acquisition of some tasks [A. Karni, D. Tanne, B.S. Rubenstein, J.J.M. Askenasy, D. Sagi, Dependence on REM sleep of overnight improvement of a perceptual skill, Science 265 (1994) 679-682; C. Smith, Sleep states and learning: a review of the animal literature, Biobehav. Rev. 9 (1985) 157-168]; although why this is so remains obscure. It has been proposed that memories may be consolidated during REM sleep or that forgetting of unnecessary material occurs in this state [F. Crick, G. Mitchison, The function of dream sleep, Nature 304 (1983) 111-114; D. Marr, Simple memory: a theory for archicortex, Philos. Trans. R. Soc. B. 262 (1971) 23-81]. We studied the firing of multiple single neurons in the hippocampus, a structure that is important for episodic memory, during familiar and novel experiences and in subsequent REM sleep. Cells active in familiar places during waking exhibited a reversal of firing phase relative to local theta oscillations in REM sleep. Because firing-phase can influence whether synapses are strengthened or weakened [C. Holscher, R. Anwyl, M.J. Rowan, Stimulation on the positive phase of hippocampal theta rhythm induces long-term potentiation that can be depotentiated by stimulation on the negative phase in area CA1 in vivo, J. Neurosci. 15 (1977) 6470-6477; P.T. Huerta, J.E. Lisman, Bidirectional synaptic plasticity induced by a single burst during cholinergic theta oscillation in CA1 in vitro, Neuron 15 (1995) 1053-1063; C. Pavlides, Y.J. Greenstein, M. Grudman, J. Winson, Long-term potentiation in the dentate gyrus is induced preferentially on the positive phase of theta-rhythm, Brain Res. 439 (1988) 383-387] this experience-dependent phase shift, which developed progressively over multiple sessions in the environment, is consistent with the hypothesis that circuits may be restructured during REM sleep by selectively strengthening recently acquired memories and weakening older ones.

Parallel representation of stimulus identity and intensity in a dual pathway model inspired by the olfactory system of the honeybee.

PubMed

Schmuker, Michael; Yamagata, Nobuhiro; Nawrot, Martin Paul; Menzel, Randolf

2011-01-01

The honeybee Apis mellifera has a remarkable ability to detect and locate food sources during foraging, and to associate odor cues with food rewards. In the honeybee's olfactory system, sensory input is first processed in the antennal lobe (AL) network. Uniglomerular projection neurons (PNs) convey the sensory code from the AL to higher brain regions via two parallel but anatomically distinct pathways, the lateral and the medial antenno-cerebral tract (l- and m-ACT). Neurons innervating either tract show characteristic differences in odor selectivity, concentration dependence, and representation of mixtures. It is still unknown how this differential stimulus representation is achieved within the AL network. In this contribution, we use a computational network model to demonstrate that the experimentally observed features of odor coding in PNs can be reproduced by varying lateral inhibition and gain control in an otherwise unchanged AL network. We show that odor coding in the l-ACT supports detection and accurate identification of weak odor traces at the expense of concentration sensitivity, while odor coding in the m-ACT provides the basis for the computation and following of concentration gradients but provides weaker discrimination power. Both coding strategies are mutually exclusive, which creates a tradeoff between detection accuracy and sensitivity. The development of two parallel systems may thus reflect an evolutionary solution to this problem that enables honeybees to achieve both tasks during bee foraging in their natural environment, and which could inspire the development of artificial chemosensory devices for odor-guided navigation in robots.

Effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks

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.

Effects of partial time delays on phase synchronization in Watts-Strogatz small-world neuronal networks.

PubMed

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.

Dynamic Monte Carlo simulations of radiatively accelerated GRB fireballs

NASA Astrophysics Data System (ADS)

Chhotray, Atul; Lazzati, Davide

2018-05-01

We present a novel Dynamic Monte Carlo code (DynaMo code) that self-consistently simulates the Compton-scattering-driven dynamic evolution of a plasma. We use the DynaMo code to investigate the time-dependent expansion and acceleration of dissipationless gamma-ray burst fireballs by varying their initial opacities and baryonic content. We study the opacity and energy density evolution of an initially optically thick, radiation-dominated fireball across its entire phase space - in particular during the Rph < Rsat regime. Our results reveal new phases of fireball evolution: a transition phase with a radial extent of several orders of magnitude - the fireball transitions from Γ ∝ R to Γ ∝ R0, a post-photospheric acceleration phase - where fireballs accelerate beyond the photosphere and a Thomson-dominated acceleration phase - characterized by slow acceleration of optically thick, matter-dominated fireballs due to Thomson scattering. We quantify the new phases by providing analytical expressions of Lorentz factor evolution, which will be useful for deriving jet parameters.

Multifocus microscopy with precise color multi-phase diffractive optics applied in functional neuronal imaging.

PubMed

Abrahamsson, Sara; Ilic, Rob; Wisniewski, Jan; Mehl, Brian; Yu, Liya; Chen, Lei; Davanco, Marcelo; Oudjedi, Laura; Fiche, Jean-Bernard; Hajj, Bassam; Jin, Xin; Pulupa, Joan; Cho, Christine; Mir, Mustafa; El Beheiry, Mohamed; Darzacq, Xavier; Nollmann, Marcelo; Dahan, Maxime; Wu, Carl; Lionnet, Timothée; Liddle, J Alexander; Bargmann, Cornelia I

2016-03-01

Multifocus microscopy (MFM) allows high-resolution instantaneous three-dimensional (3D) imaging and has been applied to study biological specimens ranging from single molecules inside cells nuclei to entire embryos. We here describe pattern designs and nanofabrication methods for diffractive optics that optimize the light-efficiency of the central optical component of MFM: the diffractive multifocus grating (MFG). We also implement a "precise color" MFM layout with MFGs tailored to individual fluorophores in separate optical arms. The reported advancements enable faster and brighter volumetric time-lapse imaging of biological samples. In live microscopy applications, photon budget is a critical parameter and light-efficiency must be optimized to obtain the fastest possible frame rate while minimizing photodamage. We provide comprehensive descriptions and code for designing diffractive optical devices, and a detailed methods description for nanofabrication of devices. Theoretical efficiencies of reported designs is ≈90% and we have obtained efficiencies of > 80% in MFGs of our own manufacture. We demonstrate the performance of a multi-phase MFG in 3D functional neuronal imaging in living C. elegans.

Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.

PubMed

Burbank, Kendra S

2015-12-01

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field's Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks.

Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons

PubMed Central

Burbank, Kendra S.

2015-01-01

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field’s Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks. PMID:26633645

Hierarchical differences in population coding within auditory cortex.

PubMed

Downer, Joshua D; Niwa, Mamiko; Sutter, Mitchell L

2017-08-01

Most models of auditory cortical (AC) population coding have focused on primary auditory cortex (A1). Thus our understanding of how neural coding for sounds progresses along the cortical hierarchy remains obscure. To illuminate this, we recorded from two AC fields: A1 and middle lateral belt (ML) of rhesus macaques. We presented amplitude-modulated (AM) noise during both passive listening and while the animals performed an AM detection task ("active" condition). In both fields, neurons exhibit monotonic AM-depth tuning, with A1 neurons mostly exhibiting increasing rate-depth functions and ML neurons approximately evenly distributed between increasing and decreasing functions. We measured noise correlation ( r noise ) between simultaneously recorded neurons and found that whereas engagement decreased average r noise in A1, engagement increased average r noise in ML. This finding surprised us, because attentive states are commonly reported to decrease average r noise We analyzed the effect of r noise on AM coding in both A1 and ML and found that whereas engagement-related shifts in r noise in A1 enhance AM coding, r noise shifts in ML have little effect. These results imply that the effect of r noise differs between sensory areas, based on the distribution of tuning properties among the neurons within each population. A possible explanation of this is that higher areas need to encode nonsensory variables (e.g., attention, choice, and motor preparation), which impart common noise, thus increasing r noise Therefore, the hierarchical emergence of r noise -robust population coding (e.g., as we observed in ML) enhances the ability of sensory cortex to integrate cognitive and sensory information without a loss of sensory fidelity. NEW & NOTEWORTHY Prevailing models of population coding of sensory information are based on a limited subset of neural structures. An important and under-explored question in neuroscience is how distinct areas of sensory cortex differ in their population coding strategies. In this study, we compared population coding between primary and secondary auditory cortex. Our findings demonstrate striking differences between the two areas and highlight the importance of considering the diversity of neural structures as we develop models of population coding. Copyright © 2017 the American Physiological Society.

Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance.

PubMed

Siebenhühner, Felix; Wang, Sheng H; Palva, J Matias; Palva, Satu

2016-09-26

Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha-gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions.

Exact event-driven implementation for recurrent networks of stochastic perfect integrate-and-fire neurons.

PubMed

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.

Neuronal cell fate specification by the molecular convergence of different spatio-temporal cues on a common initiator terminal selector gene

PubMed Central

Stratmann, Johannes

2017-01-01

The extensive genetic regulatory flows underlying specification of different neuronal subtypes are not well understood at the molecular level. The Nplp1 neuropeptide neurons in the developing Drosophila nerve cord belong to two sub-classes; Tv1 and dAp neurons, generated by two distinct progenitors. Nplp1 neurons are specified by spatial cues; the Hox homeotic network and GATA factor grn, and temporal cues; the hb -> Kr -> Pdm -> cas -> grh temporal cascade. These spatio-temporal cues combine into two distinct codes; one for Tv1 and one for dAp neurons that activate a common terminal selector feedforward cascade of col -> ap/eya -> dimm -> Nplp1. Here, we molecularly decode the specification of Nplp1 neurons, and find that the cis-regulatory organization of col functions as an integratory node for the different spatio-temporal combinatorial codes. These findings may provide a logical framework for addressing spatio-temporal control of neuronal sub-type specification in other systems. PMID:28414802

Sparse bursts optimize information transmission in a multiplexed neural code.

PubMed

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.

Assembly of the Auditory Circuitry by a Hox Genetic Network in the Mouse Brainstem

PubMed Central

Di Bonito, Maria; Narita, Yuichi; Avallone, Bice; Sequino, Luigi; Mancuso, Marta; Andolfi, Gennaro; Franzè, Anna Maria; Puelles, Luis; Rijli, Filippo M.; Studer, Michèle

2013-01-01

Rhombomeres (r) contribute to brainstem auditory nuclei during development. Hox genes are determinants of rhombomere-derived fate and neuronal connectivity. Little is known about the contribution of individual rhombomeres and their associated Hox codes to auditory sensorimotor circuitry. Here, we show that r4 contributes to functionally linked sensory and motor components, including the ventral nucleus of lateral lemniscus, posterior ventral cochlear nuclei (VCN), and motor olivocochlear neurons. Assembly of the r4-derived auditory components is involved in sound perception and depends on regulatory interactions between Hoxb1 and Hoxb2. Indeed, in Hoxb1 and Hoxb2 mutant mice the transmission of low-level auditory stimuli is lost, resulting in hearing impairments. On the other hand, Hoxa2 regulates the Rig1 axon guidance receptor and controls contralateral projections from the anterior VCN to the medial nucleus of the trapezoid body, a circuit involved in sound localization. Thus, individual rhombomeres and their associated Hox codes control the assembly of distinct functionally segregated sub-circuits in the developing auditory brainstem. PMID:23408898

Assembly of the auditory circuitry by a Hox genetic network in the mouse brainstem.

PubMed

Di Bonito, Maria; Narita, Yuichi; Avallone, Bice; Sequino, Luigi; Mancuso, Marta; Andolfi, Gennaro; Franzè, Anna Maria; Puelles, Luis; Rijli, Filippo M; Studer, Michèle

2013-01-01

Rhombomeres (r) contribute to brainstem auditory nuclei during development. Hox genes are determinants of rhombomere-derived fate and neuronal connectivity. Little is known about the contribution of individual rhombomeres and their associated Hox codes to auditory sensorimotor circuitry. Here, we show that r4 contributes to functionally linked sensory and motor components, including the ventral nucleus of lateral lemniscus, posterior ventral cochlear nuclei (VCN), and motor olivocochlear neurons. Assembly of the r4-derived auditory components is involved in sound perception and depends on regulatory interactions between Hoxb1 and Hoxb2. Indeed, in Hoxb1 and Hoxb2 mutant mice the transmission of low-level auditory stimuli is lost, resulting in hearing impairments. On the other hand, Hoxa2 regulates the Rig1 axon guidance receptor and controls contralateral projections from the anterior VCN to the medial nucleus of the trapezoid body, a circuit involved in sound localization. Thus, individual rhombomeres and their associated Hox codes control the assembly of distinct functionally segregated sub-circuits in the developing auditory brainstem.

Unsupervised Feature Learning With Winner-Takes-All Based STDP

PubMed Central

Ferré, Paul; Mamalet, Franck; Thorpe, Simon J.

2018-01-01

We present a novel strategy for unsupervised feature learning in image applications inspired by the Spike-Timing-Dependent-Plasticity (STDP) biological learning rule. We show equivalence between rank order coding Leaky-Integrate-and-Fire neurons and ReLU artificial neurons when applied to non-temporal data. We apply this to images using rank-order coding, which allows us to perform a full network simulation with a single feed-forward pass using GPU hardware. Next we introduce a binary STDP learning rule compatible with training on batches of images. Two mechanisms to stabilize the training are also presented : a Winner-Takes-All (WTA) framework which selects the most relevant patches to learn from along the spatial dimensions, and a simple feature-wise normalization as homeostatic process. This learning process allows us to train multi-layer architectures of convolutional sparse features. We apply our method to extract features from the MNIST, ETH80, CIFAR-10, and STL-10 datasets and show that these features are relevant for classification. We finally compare these results with several other state of the art unsupervised learning methods. PMID:29674961

High baseline activity in inferior temporal cortex improves neural and behavioral discriminability during visual categorization

PubMed Central

Emadi, Nazli; Rajimehr, Reza; Esteky, Hossein

2014-01-01

Spontaneous firing is a ubiquitous property of neural activity in the brain. Recent literature suggests that this baseline activity plays a key role in perception. However, it is not known how the baseline activity contributes to neural coding and behavior. Here, by recording from the single neurons in the inferior temporal cortex of monkeys performing a visual categorization task, we thoroughly explored the relationship between baseline activity, the evoked response, and behavior. Specifically we found that a low-frequency (<8 Hz) oscillation in the spike train, prior and phase-locked to the stimulus onset, was correlated with increased gamma power and neuronal baseline activity. This enhancement of the baseline activity was then followed by an increase in the neural selectivity and the response reliability and eventually a higher behavioral performance. PMID:25404900

The Influence of Neuronal Density and Maturation on Network Activity of Hippocampal Cell Cultures: A Methodological Study

PubMed Central

Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2013-01-01

It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm2 cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm2 cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm2 are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are intended to be a reference for the planning of in vitro neurophysiological and neuropharmacological experiments with MEAs. PMID:24386305

The influence of neuronal density and maturation on network activity of hippocampal cell cultures: a methodological study.

PubMed

Biffi, Emilia; Regalia, Giulia; Menegon, Andrea; Ferrigno, Giancarlo; Pedrocchi, Alessandra

2013-01-01

It is known that cell density influences the maturation process of in vitro neuronal networks. Neuronal cultures plated with different cell densities differ in number of synapses per neuron and thus in single neuron synaptic transmission, which results in a density-dependent neuronal network activity. Although many authors provided detailed information about the effects of cell density on neuronal culture activity, a dedicated report of density and age influence on neuronal hippocampal culture activity has not yet been reported. Therefore, this work aims at providing reference data to researchers that set up an experimental study on hippocampal neuronal cultures, helping in planning and decoding the experiments. In this work, we analysed the effects of both neuronal density and culture age on functional attributes of maturing hippocampal cultures. We characterized the electrophysiological activity of neuronal cultures seeded at three different cell densities, recording their spontaneous electrical activity over maturation by means of MicroElectrode Arrays (MEAs). We had gather data from 86 independent hippocampal cultures to achieve solid statistic results, considering the high culture-to-culture variability. Network activity was evaluated in terms of simple spiking, burst and network burst features. We observed that electrical descriptors were characterized by a functional peak during maturation, followed by a stable phase (for sparse and medium density cultures) or by a decrease phase (for high dense neuronal cultures). Moreover, 900 cells/mm(2) cultures showed characteristics suitable for long lasting experiments (e.g. chronic effect of drug treatments) while 1800 cells/mm(2) cultures should be preferred for experiments that require intense electrical activity (e.g. to evaluate the effect of inhibitory molecules). Finally, cell cultures at 3600 cells/mm(2) are more appropriate for experiments in which time saving is relevant (e.g. drug screenings). These results are intended to be a reference for the planning of in vitro neurophysiological and neuropharmacological experiments with MEAs.

Auditory cortical neurons are sensitive to static and continuously changing interaural phase cues.

PubMed

Reale, R A; Brugge, J F

1990-10-01

1. The interaural-phase-difference (IPD) sensitivity of single neurons in the primary auditory (AI) cortex of the anesthetized cat was studied at stimulus frequencies ranging from 120 to 2,500 Hz. Best frequencies of the 43 AI cells sensitive to IPD ranged from 190 to 2,400 Hz. 2. A static IPD was produced when a pair of low-frequency tone bursts, differing from one another only in starting phase, were presented dichotically. The resulting IPD-sensitivity curves, which plot the number of discharges evoked by the binaural signal as a function of IPD, were deeply modulated circular functions. IPD functions were analyzed for their mean vector length (r) and mean interaural phase (phi). Phase sensitivity was relatively independent of best frequency (BF) but highly dependent on stimulus frequency. Regardless of BF or stimulus frequency within the excitatory response area the majority of cells fired maximally when the ipsilateral tone lagged the contralateral signal and fired least when this interaural-phase relationship was reversed. 3. Sensitivity to continuously changing IPD was studied by delivering to the two ears 3-s tones that differed slightly in frequency, resulting in a binaural beat. Approximately 26% of the cells that showed a sensitivity to static changes in IPD also showed a sensitivity to dynamically changing IPD created by this binaural tonal combination. The discharges were highly periodic and tightly synchronized to a particular phase of the binaural beat cycle. High synchrony can be attributed to the fact that cortical neurons typically respond to an excitatory stimulus with but a single spike that is often precisely timed to stimulus onset. A period histogram, binned on the binaural beat frequency (fb), produced an equivalent IPD-sensitivity function for dynamically changing interaural phase. For neurons sensitive to both static and continuously changing interaural phase there was good correspondence between their static (phi s) and dynamic (phi d) mean interaural phases. 4. All cells responding to a dynamically changing stimulus exhibited a linear relationship between mean interaural phase and beat frequency. Most cells responded equally well to binaural beats regardless of the initial direction of phase change. For a fixed duration stimulus, and at relatively low fb, the number of spikes evoked increased with increasing fb, reflecting the increasing number of effective stimulus cycles. At higher fb, AI neurons were unable to follow the rate at which the most effective phase repeated itself during the 3 s of stimulation.(ABSTRACT TRUNCATED AT 400 WORDS)

Data-driven inference of network connectivity for modeling the dynamics of neural codes in the insect antennal lobe

PubMed Central

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

Cracking Taste Codes by Tapping into Sensory Neuron Impulse Traffic

PubMed Central

Frank, Marion E.; Lundy, Robert F.; Contreras, Robert J.

2008-01-01

Insights into the biological basis for mammalian taste quality coding began with electrophysiological recordings from “taste” nerves and this technique continues to produce essential information today. Chorda tympani (geniculate ganglion) neurons, which are particularly involved in taste quality discrimination, are specialists or generalists. Specialists respond to stimuli characterized by a single taste quality as defined by behavioral cross-generalization in conditioned taste tests. Generalists respond to electrolytes that elicit multiple aversive qualities. Na+-salt (N) specialists in rodents and sweet-stimulus (S) specialists in multiple orders of mammals are well-characterized. Specialists are associated with species’ nutritional needs and their activation is known to be malleable by internal physiological conditions and contaminated external caloric sources. S specialists, associated with the heterodimeric G-protein coupled receptor: T1R, and N specialists, associated with the epithelial sodium channel: ENaC, are consistent with labeled line coding from taste bud to afferent neuron. Yet, S-specialist neurons and behavior are less specific thanT1R2-3 in encompassing glutamate and E generalist neurons are much less specific than a candidate, PDK TRP channel, sour receptor in encompassing salts and bitter stimuli. Specialist labeled lines for nutrients and generalist patterns for aversive electrolytes may be transmitting taste information to the brain side by side. However, specific roles of generalists in taste quality coding may be resolved by selecting stimuli and stimulus levels found in natural situations. T2Rs, participating in reflexes via the glossopharynygeal nerve, became highly diversified in mammalian phylogenesis as they evolved to deal with dangerous substances within specific environmental niches. Establishing the information afferent neurons traffic to the brain about natural taste stimuli imbedded in dynamic complex mixtures will ultimately “crack taste codes.” PMID:18824076

Emergence of an abstract categorical code enabling the discrimination of temporally structured tactile stimuli

PubMed Central

Rossi-Pool, Román; Salinas, Emilio; Zainos, Antonio; Alvarez, Manuel; Vergara, José; Parga, Néstor; Romo, Ranulfo

2016-01-01

The problem of neural coding in perceptual decision making revolves around two fundamental questions: (i) How are the neural representations of sensory stimuli related to perception, and (ii) what attributes of these neural responses are relevant for downstream networks, and how do they influence decision making? We studied these two questions by recording neurons in primary somatosensory (S1) and dorsal premotor (DPC) cortex while trained monkeys reported whether the temporal pattern structure of two sequential vibrotactile stimuli (of equal mean frequency) was the same or different. We found that S1 neurons coded the temporal patterns in a literal way and only during the stimulation periods and did not reflect the monkeys’ decisions. In contrast, DPC neurons coded the stimulus patterns as broader categories and signaled them during the working memory, comparison, and decision periods. These results show that the initial sensory representation is transformed into an intermediate, more abstract categorical code that combines past and present information to ultimately generate a perceptually informed choice. PMID:27872293

Functional differentiation of macaque visual temporal cortical neurons using a parametric action space.

PubMed

Vangeneugden, Joris; Pollick, Frank; Vogels, Rufin

2009-03-01

Neurons in the rostral superior temporal sulcus (STS) are responsive to displays of body movements. We employed a parametric action space to determine how similarities among actions are represented by visual temporal neurons and how form and motion information contributes to their responses. The stimulus space consisted of a stick-plus-point-light figure performing arm actions and their blends. Multidimensional scaling showed that the responses of temporal neurons represented the ordinal similarity between these actions. Further tests distinguished neurons responding equally strongly to static presentations and to actions ("snapshot" neurons), from those responding much less strongly to static presentations, but responding well when motion was present ("motion" neurons). The "motion" neurons were predominantly found in the upper bank/fundus of the STS, and "snapshot" neurons in the lower bank of the STS and inferior temporal convexity. Most "motion" neurons showed strong response modulation during the course of an action, thus responding to action kinematics. "Motion" neurons displayed a greater average selectivity for these simple arm actions than did "snapshot" neurons. We suggest that the "motion" neurons code for visual kinematics, whereas the "snapshot" neurons code for form/posture, and that both can contribute to action recognition, in agreement with computation models of action recognition.

Cerebellar Nuclear Neurons Use Time and Rate Coding to Transmit Purkinje Neuron Pauses.

PubMed

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.

Proportional spike-timing precision and firing reliability underlie efficient temporal processing of periodicity and envelope shape cues

PubMed Central

Zheng, Y.

2013-01-01

Temporal sound cues are essential for sound recognition, pitch, rhythm, and timbre perception, yet how auditory neurons encode such cues is subject of ongoing debate. Rate coding theories propose that temporal sound features are represented by rate tuned modulation filters. However, overwhelming evidence also suggests that precise spike timing is an essential attribute of the neural code. Here we demonstrate that single neurons in the auditory midbrain employ a proportional code in which spike-timing precision and firing reliability covary with the sound envelope cues to provide an efficient representation of the stimulus. Spike-timing precision varied systematically with the timescale and shape of the sound envelope and yet was largely independent of the sound modulation frequency, a prominent cue for pitch. In contrast, spike-count reliability was strongly affected by the modulation frequency. Spike-timing precision extends from sub-millisecond for brief transient sounds up to tens of milliseconds for sounds with slow-varying envelope. Information theoretic analysis further confirms that spike-timing precision depends strongly on the sound envelope shape, while firing reliability was strongly affected by the sound modulation frequency. Both the information efficiency and total information were limited by the firing reliability and spike-timing precision in a manner that reflected the sound structure. This result supports a temporal coding strategy in the auditory midbrain where proportional changes in spike-timing precision and firing reliability can efficiently signal shape and periodicity temporal cues. PMID:23636724

The Simpsons program 6-D phase space tracking with acceleration

NASA Astrophysics Data System (ADS)

Machida, S.

1993-12-01

A particle tracking code, Simpsons, in 6-D phase space including energy ramping has been developed to model proton synchrotrons and storage rings. We take time as the independent variable to change machine parameters and diagnose beam quality in a quite similar way as real machines, unlike existing tracking codes for synchrotrons which advance a particle element by element. Arbitrary energy ramping and rf voltage curves as a function of time are read as an input file for defining a machine cycle. The code is used to study beam dynamics with time dependent parameters. Some of the examples from simulations of the Superconducting Super Collider (SSC) boosters are shown.

Expression of c-Fos in the rat retrosplenial cortex during instrumental re-learning of appetitive bar-pressing depends on the number of stages of previous training.

PubMed

Svarnik, Olga E; Bulava, Alexandra I; Alexandrov, Yuri I

2013-01-01

Learning is known to be accompanied by induction of c-Fos expression in cortical neurons. However, not all neurons are involved in this process. What the c-Fos expression pattern depends on is still unknown. In the present work we studied whether and to what degree previous animal experience about Task 1 (the first phase of an instrumental learning) influenced neuronal c-Fos expression in the retrosplenial cortex during acquisition of Task 2 (the second phase of an instrumental learning). Animals were progressively shaped across days to bar-press for food at the left side of the experimental chamber (Task 1). This appetitive bar-pressing behavior was shaped by nine stages ("9 stages" group), five stages ("5 stages" group) or one intermediate stage ("1 stage" group). After all animals acquired the first skill and practiced it for five days, the bar and feeder on the left, familiar side of the chamber were inactivated, and the animals were allowed to learn a similar instrumental task at the opposite side of the chamber using another pair of a bar and a feeder (Task 2). The highest number of c-Fos positive neurons was found in the retrosplenial cortex of "1 stage" animals as compared to the other groups. The number of c-Fos positive neurons in "5 stages" group animals was significantly lower than in "1 stage" animals and significantly higher than in "9 stages" animals. The number of c-Fos positive neurons in the cortex of "9 stages" animals was significantly higher than in home caged control animals. At the same time, there were no significant differences between groups in such behavioral variables as the number of entrees into the feeder or bar zones during Task 2 learning. Our results suggest that c-Fos expression in the retrosplenial cortex during Task 2 acquisition was influenced by the previous learning history.

Taste quality decoding parallels taste sensations.

PubMed

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.

Ankle joint movements are encoded by both cutaneous and muscle afferents in humans.

PubMed

Aimonetti, Jean-Marc; Roll, Jean-Pierre; Hospod, Valérie; Ribot-Ciscar, Edith

2012-08-01

We analyzed the cutaneous encoding of two-dimensional movements by investigating the coding of movement velocity for differently oriented straight-line movements and the coding of complex trajectories describing cursive letters. The cutaneous feedback was then compared with that of the underlying muscle afferents previously recorded during the same "writing-like" movements. The unitary activity of 43 type II cutaneous afferents was recorded in the common peroneal nerve in healthy subjects during imposed ankle movements. These movements consisted first of ramp-and-hold movements imposed at two different and close velocities in seven directions and secondly of "writing-like" movements. In both cases, the responses were analyzed using the neuronal population vector model. The results show that movement velocity encoding depended on the direction of the ongoing movement. Discriminating between two velocities therefore involved processing the activity of afferent populations located in the various skin areas surrounding the moving joint, as shown by the statistically significant difference observed in the amplitude of the sum vectors. Secondly, "writing-like" movements induced cutaneous neuronal patterns of activity, which were reproducible and specific to each trajectory. Lastly, the "cutaneous neuronal trajectories," built by adding the sum vectors tip-to-tail, nearly matched both the movement trajectories and the "muscle neuronal trajectories," built from previously recorded muscle afferents. It was concluded that type II cutaneous and the underlying muscle afferents show similar encoding properties of two-dimensional movement parameters. This similarity is discussed in relation to a central gating process that would for instance increase the gain of cutaneous inputs when muscle information is altered by the fusimotor drive.

Precision digital pulse phase generator

DOEpatents

McEwan, T.E.

1996-10-08

A timing generator comprises a crystal oscillator connected to provide an output reference pulse. A resistor-capacitor combination is connected to provide a variable-delay output pulse from an input connected to the crystal oscillator. A phase monitor is connected to provide duty-cycle representations of the reference and variable-delay output pulse phase. An operational amplifier drives a control voltage to the resistor-capacitor combination according to currents integrated from the phase monitor and injected into summing junctions. A digital-to-analog converter injects a control current into the summing junctions according to an input digital control code. A servo equilibrium results that provides a phase delay of the variable-delay output pulse to the output reference pulse that linearly depends on the input digital control code. 2 figs.

Precision digital pulse phase generator

DOEpatents

McEwan, Thomas E.

1996-01-01

A timing generator comprises a crystal oscillator connected to provide an output reference pulse. A resistor-capacitor combination is connected to provide a variable-delay output pulse from an input connected to the crystal oscillator. A phase monitor is connected to provide duty-cycle representations of the reference and variable-delay output pulse phase. An operational amplifier drives a control voltage to the resistor-capacitor combination according to currents integrated from the phase monitor and injected into summing junctions. A digital-to-analog converter injects a control current into the summing junctions according to an input digital control code. A servo equilibrium results that provides a phase delay of the variable-delay output pulse to the output reference pulse that linearly depends on the input digital control code.

Responses of mirror neurons in area F5 to hand and tool grasping observation

PubMed Central

Rochat, Magali J.; Caruana, Fausto; Jezzini, Ahmad; Escola, Ludovic; Intskirveli, Irakli; Grammont, Franck; Gallese, Vittorio; Rizzolatti, Giacomo

2010-01-01

Mirror neurons are a distinct class of neurons that discharge both during the execution of a motor act and during observation of the same or similar motor act performed by another individual. However, the extent to which mirror neurons coding a motor act with a specific goal (e.g., grasping) might also respond to the observation of a motor act having the same goal, but achieved with artificial effectors, is not yet established. In the present study, we addressed this issue by recording mirror neurons from the ventral premotor cortex (area F5) of two monkeys trained to grasp objects with pliers. Neuron activity was recorded during the observation and execution of grasping performed with the hand, with pliers and during observation of an experimenter spearing food with a stick. The results showed that virtually all neurons responding to the observation of hand grasping also responded to the observation of grasping with pliers and, many of them to the observation of spearing with a stick. However, the intensity and pattern of the response differed among conditions. Hand grasping observation determined the earliest and the strongest discharge, while pliers grasping and spearing observation triggered weaker responses at longer latencies. We conclude that F5 grasping mirror neurons respond to the observation of a family of stimuli leading to the same goal. However, the response pattern depends upon the similarity between the observed motor act and the one executed by the hand, the natural motor template. PMID:20577726

Place field assembly distribution encodes preferred locations

PubMed Central

Mamad, Omar; Stumpp, Lars; McNamara, Harold M.; Ramakrishnan, Charu; Deisseroth, Karl; Reilly, Richard B.

2017-01-01

The hippocampus is the main locus of episodic memory formation and the neurons there encode the spatial map of the environment. Hippocampal place cells represent location, but their role in the learning of preferential location remains unclear. The hippocampus may encode locations independently from the stimuli and events that are associated with these locations. We have discovered a unique population code for the experience-dependent value of the context. The degree of reward-driven navigation preference highly correlates with the spatial distribution of the place fields recorded in the CA1 region of the hippocampus. We show place field clustering towards rewarded locations. Optogenetic manipulation of the ventral tegmental area demonstrates that the experience-dependent place field assembly distribution is directed by tegmental dopaminergic activity. The ability of the place cells to remap parallels the acquisition of reward context. Our findings present key evidence that the hippocampal neurons are not merely mapping the static environment but also store the concurrent context reward value, enabling episodic memory for past experience to support future adaptive behavior. PMID:28898248

Complementary theta resonance filtering by two spatially segregated mechanisms in CA1 hippocampal pyramidal neurons.

PubMed

Hu, Hua; Vervaeke, Koen; Graham, Lyle J; Storm, Johan F

2009-11-18

Synaptic input to a neuron may undergo various filtering steps, both locally and during transmission to the soma. Using simultaneous whole-cell recordings from soma and apical dendrites from rat CA1 hippocampal pyramidal cells, and biophysically detailed modeling, we found two complementary resonance (bandpass) filters of subthreshold voltage signals. Both filters favor signals in the theta (3-12 Hz) frequency range, but have opposite location, direction, and voltage dependencies: (1) dendritic H-resonance, caused by h/HCN-channels, filters signals propagating from soma to dendrite when the membrane potential is close to rest; and (2) somatic M-resonance, caused by M/Kv7/KCNQ and persistent Na(+) (NaP) channels, filters signals propagating from dendrite to soma when the membrane potential approaches spike threshold. Hippocampal pyramidal cells participate in theta network oscillations during behavior, and we suggest that that these dual, polarized theta resonance mechanisms may convey voltage-dependent tuning of theta-mediated neural coding in the entorhinal/hippocampal system during locomotion, spatial navigation, memory, and sleep.

Stochastic Computations in Cortical Microcircuit Models

PubMed Central

Maass, Wolfgang

2013-01-01

Experimental data from neuroscience suggest that a substantial amount of knowledge is stored in the brain in the form of probability distributions over network states and trajectories of network states. We provide a theoretical foundation for this hypothesis by showing that even very detailed models for cortical microcircuits, with data-based diverse nonlinear neurons and synapses, have a stationary distribution of network states and trajectories of network states to which they converge exponentially fast from any initial state. We demonstrate that this convergence holds in spite of the non-reversibility of the stochastic dynamics of cortical microcircuits. We further show that, in the presence of background network oscillations, separate stationary distributions emerge for different phases of the oscillation, in accordance with experimentally reported phase-specific codes. We complement these theoretical results by computer simulations that investigate resulting computation times for typical probabilistic inference tasks on these internally stored distributions, such as marginalization or marginal maximum-a-posteriori estimation. Furthermore, we show that the inherent stochastic dynamics of generic cortical microcircuits enables them to quickly generate approximate solutions to difficult constraint satisfaction problems, where stored knowledge and current inputs jointly constrain possible solutions. This provides a powerful new computing paradigm for networks of spiking neurons, that also throws new light on how networks of neurons in the brain could carry out complex computational tasks such as prediction, imagination, memory recall and problem solving. PMID:24244126

Vocalization frequency and duration are coded in separate hindbrain nuclei.

PubMed

Chagnaud, Boris P; Baker, Robert; Bass, Andrew H

2011-06-14

Temporal patterning is an essential feature of neural networks producing precisely timed behaviours such as vocalizations that are widely used in vertebrate social communication. Here we show that intrinsic and network properties of separate hindbrain neuronal populations encode the natural call attributes of frequency and duration in vocal fish. Intracellular structure/function analyses indicate that call duration is encoded by a sustained membrane depolarization in vocal prepacemaker neurons that innervate downstream pacemaker neurons. Pacemaker neurons, in turn, encode call frequency by rhythmic, ultrafast oscillations in their membrane potential. Pharmacological manipulations show prepacemaker activity to be independent of pacemaker function, thus accounting for natural variation in duration which is the predominant feature distinguishing call types. Prepacemaker neurons also innervate key hindbrain auditory nuclei thereby effectively serving as a call-duration corollary discharge. We propose that premotor compartmentalization of neurons coding distinct acoustic attributes is a fundamental trait of hindbrain vocal pattern generators among vertebrates.

Vocalization frequency and duration are coded in separate hindbrain nuclei

PubMed Central

Chagnaud, Boris P.; Baker, Robert; Bass, Andrew H.

2011-01-01

Temporal patterning is an essential feature of neural networks producing precisely timed behaviours such as vocalizations that are widely used in vertebrate social communication. Here we show that intrinsic and network properties of separate hindbrain neuronal populations encode the natural call attributes of frequency and duration in vocal fish. Intracellular structure/function analyses indicate that call duration is encoded by a sustained membrane depolarization in vocal prepacemaker neurons that innervate downstream pacemaker neurons. Pacemaker neurons, in turn, encode call frequency by rhythmic, ultrafast oscillations in their membrane potential. Pharmacological manipulations show prepacemaker activity to be independent of pacemaker function, thus accounting for natural variation in duration which is the predominant feature distinguishing call types. Prepacemaker neurons also innervate key hindbrain auditory nuclei thereby effectively serving as a call-duration corollary discharge. We propose that premotor compartmentalization of neurons coding distinct acoustic attributes is a fundamental trait of hindbrain vocal pattern generators among vertebrates. PMID:21673667

Odor-evoked inhibition of olfactory sensory neurons drives olfactory perception in Drosophila.

PubMed

Cao, Li-Hui; Yang, Dong; Wu, Wei; Zeng, Xiankun; Jing, Bi-Yang; Li, Meng-Tong; Qin, Shanshan; Tang, Chao; Tu, Yuhai; Luo, Dong-Gen

2017-11-07

Inhibitory response occurs throughout the nervous system, including the peripheral olfactory system. While odor-evoked excitation in peripheral olfactory cells is known to encode odor information, the molecular mechanism and functional roles of odor-evoked inhibition remain largely unknown. Here, we examined Drosophila olfactory sensory neurons and found that inhibitory odors triggered outward receptor currents by reducing the constitutive activities of odorant receptors, inhibiting the basal spike firing in olfactory sensory neurons. Remarkably, this odor-evoked inhibition of olfactory sensory neurons elicited by itself a full range of olfactory behaviors from attraction to avoidance, as did odor-evoked olfactory sensory neuron excitation. These results indicated that peripheral inhibition is comparable to excitation in encoding sensory signals rather than merely regulating excitation. Furthermore, we demonstrated that a bidirectional code with both odor-evoked inhibition and excitation in single olfactory sensory neurons increases the odor-coding capacity, providing a means of efficient sensory encoding.

Anti-Müllerian hormone may regulate the number of calbindin-positive neurons in the sexually dimorphic nucleus of the preoptic area of male mice

PubMed Central

2013-01-01

Background The male brain is putatively organised early in development by testosterone, with the sexually dimorphic nucleus of the medial preoptic area (SDN) a main exemplifier of this. However, pubescent neurogenesis occurs in the rat SDN, and the immature testes secrete anti-Müllerian hormone (AMH) as well as testosterone. We have therefore re-examined the development of the murine SDN to determine whether it is influenced by AMH and/or whether the number of calbindin-positive (calbindin+ve) neurons in it changes after pre-pubescent development. Methods In mice, the SDN nucleus is defined by calbindin+ve neurons (CALB-SDN). The number and size of the neurons in the CALB-SDN of male and female AMH null mutant (Amh-/-) mice and their wild-type littermates (Amh+/+) were studied using stereological techniques. Groups of mice were examined immediately before the onset of puberty (20 days postnatal) and at adulthood (129–147 days old). Results The wild-type pre-pubertal male mice had 47% more calbindin+ve neurons in the CALB-SDN than their female wild-type littermates. This sex difference was entirely absent in Amh-/- mice. In adults, the extent of sexual dimorphism almost doubled due to a net reduction in the number and size of calbindin+ve neurons in females and a net increase in neuron number in males. These changes occurred to a similar extent in the Amh-/- and Amh+/+ mice. Consequently, the number of calbindin+ve neurons in Amh-/- adult male mice was intermediate between Amh+/+ males and Amh+/+ females. The sex difference in the size of the neurons was predominantly generated by a female-specific atrophy after 20 days, independent of AMH. Conclusions The establishment of dimorphic cell number in the CALB-SDN of mice is biphasic, with each phase being subject to different regulation. The second phase of dimorphism is not dependent on the first phase having occurred as it was present in the Amh-/- male mice that have female-like numbers of calbindin+ve neurons at 20 days. These observations extend emerging evidence that the organisation of highly dimorphic neuronal networks changes during puberty or afterwards. They also raise the possibility that cellular events attributed to the imprinting effects of testosterone are mediated by AMH. PMID:24119315

Anti-Müllerian hormone may regulate the number of calbindin-positive neurons in the sexually dimorphic nucleus of the preoptic area of male mice.

PubMed

Wittmann, Walter; McLennan, Ian S

2013-10-11

The male brain is putatively organised early in development by testosterone, with the sexually dimorphic nucleus of the medial preoptic area (SDN) a main exemplifier of this. However, pubescent neurogenesis occurs in the rat SDN, and the immature testes secrete anti-Müllerian hormone (AMH) as well as testosterone. We have therefore re-examined the development of the murine SDN to determine whether it is influenced by AMH and/or whether the number of calbindin-positive (calbindin+ve) neurons in it changes after pre-pubescent development. In mice, the SDN nucleus is defined by calbindin+ve neurons (CALB-SDN). The number and size of the neurons in the CALB-SDN of male and female AMH null mutant (Amh-/-) mice and their wild-type littermates (Amh+/+) were studied using stereological techniques. Groups of mice were examined immediately before the onset of puberty (20 days postnatal) and at adulthood (129-147 days old). The wild-type pre-pubertal male mice had 47% more calbindin+ve neurons in the CALB-SDN than their female wild-type littermates. This sex difference was entirely absent in Amh-/- mice. In adults, the extent of sexual dimorphism almost doubled due to a net reduction in the number and size of calbindin+ve neurons in females and a net increase in neuron number in males. These changes occurred to a similar extent in the Amh-/- and Amh+/+ mice. Consequently, the number of calbindin+ve neurons in Amh-/- adult male mice was intermediate between Amh+/+ males and Amh+/+ females. The sex difference in the size of the neurons was predominantly generated by a female-specific atrophy after 20 days, independent of AMH. The establishment of dimorphic cell number in the CALB-SDN of mice is biphasic, with each phase being subject to different regulation. The second phase of dimorphism is not dependent on the first phase having occurred as it was present in the Amh-/- male mice that have female-like numbers of calbindin+ve neurons at 20 days. These observations extend emerging evidence that the organisation of highly dimorphic neuronal networks changes during puberty or afterwards. They also raise the possibility that cellular events attributed to the imprinting effects of testosterone are mediated by AMH.

Neural learning circuits utilizing nano-crystalline silicon transistors and memristors.

PubMed

Cantley, Kurtis D; Subramaniam, Anand; Stiegler, Harvey J; Chapman, Richard A; Vogel, Eric M

2012-04-01

Properties of neural circuits are demonstrated via SPICE simulations and their applications are discussed. The neuron and synapse subcircuits include ambipolar nano-crystalline silicon transistor and memristor device models based on measured data. Neuron circuit characteristics and the Hebbian synaptic learning rule are shown to be similar to biology. Changes in the average firing rate learning rule depending on various circuit parameters are also presented. The subcircuits are then connected into larger neural networks that demonstrate fundamental properties including associative learning and pulse coincidence detection. Learned extraction of a fundamental frequency component from noisy inputs is demonstrated. It is then shown that if the fundamental sinusoid of one neuron input is out of phase with the rest, its synaptic connection changes differently than the others. Such behavior indicates that the system can learn to detect which signals are important in the general population, and that there is a spike-timing-dependent component of the learning mechanism. Finally, future circuit design and considerations are discussed, including requirements for the memristive device.

Dendritic sodium channels promote active decorrelation and reduce phase locking to parkinsonian input oscillations in model globus pallidus neurons

PubMed Central

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

Period gene expression in four neurons is sufficient for rhythmic activity of Drosophila melanogaster under dim light conditions.

PubMed

Rieger, Dirk; Wülbeck, Corinna; Rouyer, Francois; Helfrich-Förster, Charlotte

2009-08-01

The clock gene expressing lateral neurons (LN) is crucial for Drosophila 's rhythmic locomotor activity under constant conditions. Among the LN, the PDF expressing small ventral lateral neurons (s-LN(v)) are thought to control the morning activity of the fly (M oscillators) and to drive rhythmic activity under constant darkness. In contrast, a 5th PDF-negative s-LN( v) and the dorsal lateral neurons (LN(d)) appeared to control the fly's evening activity (E oscillators) and to drive rhythmic activity under constant light. Here, the authors restricted period gene expression to 4 LN-the 5th s-LN(v) and 3 LN(d)- that are all thought to belong to the E oscillators and tested them in low light conditions. Interestingly, such flies showed rather normal bimodal activity patterns under light moonlight and constant moonlight conditions, except that the phase of M and E peaks was different. This suggests that these 4 neurons behave as ''M'' and ''E'' cells in these conditions. Indeed, they found by PER and TIM immunohistochemistry that 2 LN(d) advanced their phase upon moonlight as predicted for M oscillators, whereas the 5th s-LN(v) and 1 LN(d) delayed their activity upon moonlight as predicted for E oscillators. Their results suggest that the M or E characteristic of clock neurons is rather flexible. M and E oscillator function may not be restricted to certain anatomically defined groups of clock neurons but instead depends on the environmental conditions.

Potential role of monkey inferior parietal neurons coding action semantic equivalences as precursors of parts of speech.

PubMed

Yamazaki, Yumiko; Yokochi, Hiroko; Tanaka, Michio; Okanoya, Kazuo; Iriki, Atsushi

2010-01-01

The anterior portion of the inferior parietal cortex possesses comprehensive representations of actions embedded in behavioural contexts. Mirror neurons, which respond to both self-executed and observed actions, exist in this brain region in addition to those originally found in the premotor cortex. We found that parietal mirror neurons responded differentially to identical actions embedded in different contexts. Another type of parietal mirror neuron represents an inverse and complementary property of responding equally to dissimilar actions made by itself and others for an identical purpose. Here, we propose a hypothesis that these sets of inferior parietal neurons constitute a neural basis for encoding the semantic equivalence of various actions across different agents and contexts. The neurons have mirror neuron properties, and they encoded generalization of agents, differentiation of outcomes, and categorization of actions that led to common functions. By integrating the activities of these mirror neurons with various codings, we further suggest that in the ancestral primates' brains, these various representations of meaningful action led to the gradual establishment of equivalence relations among the different types of actions, by sharing common action semantics. Such differential codings of the components of actions might represent precursors to the parts of protolanguage, such as gestural communication, which are shared among various members of a society. Finally, we suggest that the inferior parietal cortex serves as an interface between this action semantics system and other higher semantic systems, through common structures of action representation that mimic language syntax.

Potential role of monkey inferior parietal neurons coding action semantic equivalences as precursors of parts of speech

PubMed Central

Yamazaki, Yumiko; Yokochi, Hiroko; Tanaka, Michio; Okanoya, Kazuo; Iriki, Atsushi

2010-01-01

The anterior portion of the inferior parietal cortex possesses comprehensive representations of actions embedded in behavioural contexts. Mirror neurons, which respond to both self-executed and observed actions, exist in this brain region in addition to those originally found in the premotor cortex. We found that parietal mirror neurons responded differentially to identical actions embedded in different contexts. Another type of parietal mirror neuron represents an inverse and complementary property of responding equally to dissimilar actions made by itself and others for an identical purpose. Here, we propose a hypothesis that these sets of inferior parietal neurons constitute a neural basis for encoding the semantic equivalence of various actions across different agents and contexts. The neurons have mirror neuron properties, and they encoded generalization of agents, differentiation of outcomes, and categorization of actions that led to common functions. By integrating the activities of these mirror neurons with various codings, we further suggest that in the ancestral primates' brains, these various representations of meaningful action led to the gradual establishment of equivalence relations among the different types of actions, by sharing common action semantics. Such differential codings of the components of actions might represent precursors to the parts of protolanguage, such as gestural communication, which are shared among various members of a society. Finally, we suggest that the inferior parietal cortex serves as an interface between this action semantics system and other higher semantic systems, through common structures of action representation that mimic language syntax. PMID:20119879

The synchronous activity of lateral habenular neurons is essential for regulating hippocampal theta oscillation.

PubMed

Aizawa, Hidenori; Yanagihara, Shin; Kobayashi, Megumi; Niisato, Kazue; Takekawa, Takashi; Harukuni, Rie; McHugh, Thomas J; Fukai, Tomoki; Isomura, Yoshikazu; Okamoto, Hitoshi

2013-05-15

Lateral habenula (LHb) has attracted growing interest as a regulator of serotonergic and dopaminergic neurons in the CNS. However, it remains unclear how the LHb modulates brain states in animals. To identify the neural substrates that are under the influence of LHb regulation, we examined the effects of rat LHb lesions on the hippocampal oscillatory activity associated with the transition of brain states. Our results showed that the LHb lesion shortened the theta activity duration both in anesthetized and sleeping rats. Furthermore, this inhibitory effect of LHb lesion on theta maintenance depended upon an intact serotonergic median raphe, suggesting that LHb activity plays an essential role in maintaining hippocampal theta oscillation via the serotonergic raphe. Multiunit recording of sleeping rats further revealed that firing of LHb neurons showed significant phase-locking activity at each theta oscillation cycle in the hippocampus. LHb neurons showing activity that was coordinated with that of the hippocampal theta were localized in the medial LHb division, which receives afferents from the diagonal band of Broca (DBB), a pacemaker region for the hippocampal theta oscillation. Thus, our findings indicate that the DBB may pace not only the hippocampus, but also the LHb, during rapid eye movement sleep. Since serotonin is known to negatively regulate theta oscillation in the hippocampus, phase-locking activity of the LHb neurons may act, under the influence of the DBB, to maintain the hippocampal theta oscillation by modulating the activity of serotonergic neurons.

Conserved mechanisms of vocalization coding in mammalian and songbird auditory midbrain.

PubMed

Woolley, Sarah M N; Portfors, Christine V

2013-11-01

The ubiquity of social vocalizations among animals provides the opportunity to identify conserved mechanisms of auditory processing that subserve communication. Identifying auditory coding properties that are shared across vocal communicators will provide insight into how human auditory processing leads to speech perception. Here, we compare auditory response properties and neural coding of social vocalizations in auditory midbrain neurons of mammalian and avian vocal communicators. The auditory midbrain is a nexus of auditory processing because it receives and integrates information from multiple parallel pathways and provides the ascending auditory input to the thalamus. The auditory midbrain is also the first region in the ascending auditory system where neurons show complex tuning properties that are correlated with the acoustics of social vocalizations. Single unit studies in mice, bats and zebra finches reveal shared principles of auditory coding including tonotopy, excitatory and inhibitory interactions that shape responses to vocal signals, nonlinear response properties that are important for auditory coding of social vocalizations and modulation tuning. Additionally, single neuron responses in the mouse and songbird midbrain are reliable, selective for specific syllables, and rely on spike timing for neural discrimination of distinct vocalizations. We propose that future research on auditory coding of vocalizations in mouse and songbird midbrain neurons adopt similar experimental and analytical approaches so that conserved principles of vocalization coding may be distinguished from those that are specialized for each species. This article is part of a Special Issue entitled "Communication Sounds and the Brain: New Directions and Perspectives". Copyright © 2013 Elsevier B.V. All rights reserved.

The WINCOF-I code: Detailed description

NASA Technical Reports Server (NTRS)

Murthy, S. N. B.; Mullican, A.

1993-01-01

The performance of an axial-flow fan-compressor unit is basically unsteady when there is ingestion of water along with the gas phase. The gas phase is a mixture of air and water vapor in the case of a bypass fan engine that provides thrust power to an aircraft. The liquid water may be in the form of droplets and film at entry to the fan. The unsteadiness is then associated with the relative motion between the gas phase and water, at entry and within the machine, while the water undergoes impact on material surfaces, centrifuging, heat and mass transfer processes, and reingestion in blade wakes, following peal off from blade surfaces. The unsteadiness may be caused by changes in atmospheric conditions and at entry into and exit from rain storms while the aircraft is in flight. In a multi-stage machine, with an uneven distribution of blade tip clearance, the combined effect of various processes in the presence of steady or time-dependent ingestion is such as to make the performance of a fan and a compressor unit time-dependent from the start of ingestion up to a short time following termination of ingestion. The original WINCOF code was developed without accounting for the relative motion between gas and liquid phases in the ingested fluid. A modification of the WINCOF code was developed and named WINCOF-1. The WINCOF-1 code can provide the transient performance of a fan-compressor unit under a variety of input conditions.

A neuronal network model for context-dependence of pitch change perception.

PubMed

Huang, Chengcheng; Englitz, Bernhard; Shamma, Shihab; Rinzel, John

2015-01-01

Many natural stimuli have perceptual ambiguities that can be cognitively resolved by the surrounding context. In audition, preceding context can bias the perception of speech and non-speech stimuli. Here, we develop a neuronal network model that can account for how context affects the perception of pitch change between a pair of successive complex tones. We focus especially on an ambiguous comparison-listeners experience opposite percepts (either ascending or descending) for an ambiguous tone pair depending on the spectral location of preceding context tones. We developed a recurrent, firing-rate network model, which detects frequency-change-direction of successively played stimuli and successfully accounts for the context-dependent perception demonstrated in behavioral experiments. The model consists of two tonotopically organized, excitatory populations, E up and E down, that respond preferentially to ascending or descending stimuli in pitch, respectively. These preferences are generated by an inhibitory population that provides inhibition asymmetric in frequency to the two populations; context dependence arises from slow facilitation of inhibition. We show that contextual influence depends on the spectral distribution of preceding tones and the tuning width of inhibitory neurons. Further, we demonstrate, using phase-space analysis, how the facilitated inhibition from previous stimuli and the waning inhibition from the just-preceding tone shape the competition between the E up and E down populations. In sum, our model accounts for contextual influences on the pitch change perception of an ambiguous tone pair by introducing a novel decoding strategy based on direction-selective units. The model's network architecture and slow facilitating inhibition emerge as predictions of neuronal mechanisms for these perceptual dynamics. Since the model structure does not depend on the specific stimuli, we show that it generalizes to other contextual effects and stimulus types.

A self-resetting spiking phase-change neuron

NASA Astrophysics Data System (ADS)

Cobley, R. A.; Hayat, H.; Wright, C. D.

2018-05-01

Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.

A self-resetting spiking phase-change neuron.

PubMed

Cobley, R A; Hayat, H; Wright, C D

2018-05-11

Neuromorphic, or brain-inspired, computing applications of phase-change devices have to date concentrated primarily on the implementation of phase-change synapses. However, the so-called accumulation mode of operation inherent in phase-change materials and devices can also be used to mimic the integrative properties of a biological neuron. Here we demonstrate, using physical modelling of nanoscale devices and SPICE modelling of associated circuits, that a single phase-change memory cell integrated into a comparator type circuit can deliver a basic hardware mimic of an integrate-and-fire spiking neuron with self-resetting capabilities. Such phase-change neurons, in combination with phase-change synapses, can potentially open a new route for the realisation of all-phase-change neuromorphic computing.

Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons.

PubMed

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.

Genetic variation in glia-neuron signalling modulates ageing rate.

PubMed

Yin, Jiang-An; Gao, Ge; Liu, Xi-Juan; Hao, Zi-Qian; Li, Kai; Kang, Xin-Lei; Li, Hong; Shan, Yuan-Hong; Hu, Wen-Li; Li, Hai-Peng; Cai, Shi-Qing

2017-11-08

The rate of behavioural decline in the ageing population is remarkably variable among individuals. Despite the considerable interest in studying natural variation in ageing rate to identify factors that control healthy ageing, no such factor has yet been found. Here we report a genetic basis for variation in ageing rates in Caenorhabditis elegans. We find that C. elegans isolates show diverse lifespan and age-related declines in virility, pharyngeal pumping, and locomotion. DNA polymorphisms in a novel peptide-coding gene, named regulatory-gene-for-behavioural-ageing-1 (rgba-1), and the neuropeptide receptor gene npr-28 influence the rate of age-related decline of worm mating behaviour; these two genes might have been subjected to recent selective sweeps. Glia-derived RGBA-1 activates NPR-28 signalling, which acts in serotonergic and dopaminergic neurons to accelerate behavioural deterioration. This signalling involves the SIR-2.1-dependent activation of the mitochondrial unfolded protein response, a pathway that modulates ageing. Thus, natural variation in neuropeptide-mediated glia-neuron signalling modulates the rate of ageing in C. elegans.

Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites

PubMed Central

Schiess, Mathieu; Urbanczik, Robert; Senn, Walter

2016-01-01

In the last decade dendrites of cortical neurons have been shown to nonlinearly combine synaptic inputs by evoking local dendritic spikes. It has been suggested that these nonlinearities raise the computational power of a single neuron, making it comparable to a 2-layer network of point neurons. But how these nonlinearities can be incorporated into the synaptic plasticity to optimally support learning remains unclear. We present a theoretically derived synaptic plasticity rule for supervised and reinforcement learning that depends on the timing of the presynaptic, the dendritic and the postsynaptic spikes. For supervised learning, the rule can be seen as a biological version of the classical error-backpropagation algorithm applied to the dendritic case. When modulated by a delayed reward signal, the same plasticity is shown to maximize the expected reward in reinforcement learning for various coding scenarios. Our framework makes specific experimental predictions and highlights the unique advantage of active dendrites for implementing powerful synaptic plasticity rules that have access to downstream information via backpropagation of action potentials. PMID:26841235

The Representation of Prediction Error in Auditory Cortex

PubMed Central

Rubin, Jonathan; Ulanovsky, Nachum; Tishby, Naftali

2016-01-01

To survive, organisms must extract information from the past that is relevant for their future. How this process is expressed at the neural level remains unclear. We address this problem by developing a novel approach from first principles. We show here how to generate low-complexity representations of the past that produce optimal predictions of future events. We then illustrate this framework by studying the coding of ‘oddball’ sequences in auditory cortex. We find that for many neurons in primary auditory cortex, trial-by-trial fluctuations of neuronal responses correlate with the theoretical prediction error calculated from the short-term past of the stimulation sequence, under constraints on the complexity of the representation of this past sequence. In some neurons, the effect of prediction error accounted for more than 50% of response variability. Reliable predictions often depended on a representation of the sequence of the last ten or more stimuli, although the representation kept only few details of that sequence. PMID:27490251

Information transmission and detection thresholds in the vestibular nuclei: single neurons vs. population encoding

PubMed Central

Massot, Corentin; Chacron, Maurice J.

2011-01-01

Understanding how sensory neurons transmit information about relevant stimuli remains a major goal in neuroscience. Of particular relevance are the roles of neural variability and spike timing in neural coding. Peripheral vestibular afferents display differential variability that is correlated with the importance of spike timing; regular afferents display little variability and use a timing code to transmit information about sensory input. Irregular afferents, conversely, display greater variability and instead use a rate code. We studied how central neurons within the vestibular nuclei integrate information from both afferent classes by recording from a group of neurons termed vestibular only (VO) that are known to make contributions to vestibulospinal reflexes and project to higher-order centers. We found that, although individual central neurons had sensitivities that were greater than or equal to those of individual afferents, they transmitted less information. In addition, their velocity detection thresholds were significantly greater than those of individual afferents. This is because VO neurons display greater variability, which is detrimental to information transmission and signal detection. Combining activities from multiple VO neurons increased information transmission. However, the information rates were still much lower than those of equivalent afferent populations. Furthermore, combining responses from multiple VO neurons led to lower velocity detection threshold values approaching those measured from behavior (∼2.5 vs. 0.5–1°/s). Our results suggest that the detailed time course of vestibular stimuli encoded by afferents is not transmitted by VO neurons. Instead, they suggest that higher vestibular pathways must integrate information from central vestibular neuron populations to give rise to behaviorally observed detection thresholds. PMID:21307329

A computer code for multiphase all-speed transient flows in complex geometries. MAST version 1.0

NASA Technical Reports Server (NTRS)

Chen, C. P.; Jiang, Y.; Kim, Y. M.; Shang, H. M.

1991-01-01

The operation of the MAST code, which computes transient solutions to the multiphase flow equations applicable to all-speed flows, is described. Two-phase flows are formulated based on the Eulerian-Lagrange scheme in which the continuous phase is described by the Navier-Stokes equation (or Reynolds equations for turbulent flows). Dispersed phase is formulated by a Lagrangian tracking scheme. The numerical solution algorithms utilized for fluid flows is a newly developed pressure-implicit algorithm based on the operator-splitting technique in generalized nonorthogonal coordinates. This operator split allows separate operation on each of the variable fields to handle pressure-velocity coupling. The obtained pressure correction equation has the hyperbolic nature and is effective for Mach numbers ranging from the incompressible limit to supersonic flow regimes. The present code adopts a nonstaggered grid arrangement; thus, the velocity components and other dependent variables are collocated at the same grid. A sequence of benchmark-quality problems, including incompressible, subsonic, transonic, supersonic, gas-droplet two-phase flows, as well as spray-combustion problems, were performed to demonstrate the robustness and accuracy of the present code.

A New Approach for Determining Phase Response Curves Reveals that Purkinje Cells Can Act as Perfect Integrators

PubMed Central

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

Premotor neurons encode torsional eye velocity during smooth-pursuit eye movements

NASA Technical Reports Server (NTRS)

Angelaki, Dora E.; Dickman, J. David

2003-01-01

Responses to horizontal and vertical ocular pursuit and head and body rotation in multiple planes were recorded in eye movement-sensitive neurons in the rostral vestibular nuclei (VN) of two rhesus monkeys. When tested during pursuit through primary eye position, the majority of the cells preferred either horizontal or vertical target motion. During pursuit of targets that moved horizontally at different vertical eccentricities or vertically at different horizontal eccentricities, eye angular velocity has been shown to include a torsional component the amplitude of which is proportional to half the gaze angle ("half-angle rule" of Listing's law). Approximately half of the neurons, the majority of which were characterized as "vertical" during pursuit through primary position, exhibited significant changes in their response gain and/or phase as a function of gaze eccentricity during pursuit, as if they were also sensitive to torsional eye velocity. Multiple linear regression analysis revealed a significant contribution of torsional eye movement sensitivity to the responsiveness of the cells. These findings suggest that many VN neurons encode three-dimensional angular velocity, rather than the two-dimensional derivative of eye position, during smooth-pursuit eye movements. Although no clear clustering of pursuit preferred-direction vectors along the semicircular canal axes was observed, the sensitivity of VN neurons to torsional eye movements might reflect a preservation of similar premotor coding of visual and vestibular-driven slow eye movements for both lateral-eyed and foveate species.

The fate of Nissl-stained dark neurons following traumatic brain injury in rats: difference between neocortex and hippocampus regarding survival rate.

PubMed

Ooigawa, Hidetoshi; Nawashiro, Hiroshi; Fukui, Shinji; Otani, Naoki; Osumi, Atsushi; Toyooka, Terushige; Shima, Katsuji

2006-10-01

We studied the fate of Nissl-stained dark neurons (N-DNs) following traumatic brain injury (TBI). N-DNs were investigated in the cerebral neocortex and the hippocampus using a rat lateral fluid percussion injury model. Nissl stain, acid fuchsin stain and immunohistochemistry with phosphorylated extracellular signal-regulated protein kinase (pERK) antibody were used in order to assess posttraumatic neurons. In the neocortex, the number of dead neurons at 24 h postinjury was significantly less than that of the observed N-DNs in the earlier phase. Only a few N-DNs increased their pERK immunoreactivity. On the other hand, in the hippocampus the number of dead neurons was approximately the same number as that of the N-DNs, and most N-DNs showed an increased pERK immunoreactivity. These data suggest that not all N-DNs inevitably die especially in the neocortex after TBI. The fate of N-DNs is thus considered to differ depending on brain subfields.

Noise-enhanced coupling between two oscillators with long-term plasticity

NASA Astrophysics Data System (ADS)

Lücken, Leonhard; Popovych, Oleksandr V.; Tass, Peter A.; Yanchuk, Serhiy

2016-03-01

Spike timing-dependent plasticity is a fundamental adaptation mechanism of the nervous system. It induces structural changes of synaptic connectivity by regulation of coupling strengths between individual cells depending on their spiking behavior. As a biophysical process its functioning is constantly subjected to natural fluctuations. We study theoretically the influence of noise on a microscopic level by considering only two coupled neurons. Adopting a phase description for the neurons we derive a two-dimensional system which describes the averaged dynamics of the coupling strengths. We show that a multistability of several coupling configurations is possible, where some configurations are not found in systems without noise. Intriguingly, it is possible that a strong bidirectional coupling, which is not present in the noise-free situation, can be stabilized by the noise. This means that increased noise, which is normally expected to desynchronize the neurons, can be the reason for an antagonistic response of the system, which organizes itself into a state of stronger coupling and counteracts the impact of noise. This mechanism, as well as a high potential for multistability, is also demonstrated numerically for a coupled pair of Hodgkin-Huxley neurons.

Identification of AOSC-binding proteins in neurons

NASA Astrophysics Data System (ADS)

Liu, Ming; Nie, Qin; Xin, Xianliang; Geng, Meiyu

2008-11-01

Acidic oligosaccharide sugar chain (AOSC), a D-mannuronic acid oligosaccharide, derived from brown algae polysaccharide, has been completed Phase I clinical trial in China as an anti-Alzheimer’s Disease (AD) drug candidate. The identification of AOSC-binding protein(s) in neurons is very important for understanding its action mechanism. To determine the binding protein(s) of AOSC in neurons mediating its anti-AD activities, confocal microscopy, affinity chromatography, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis were used. Confocal microscopy analysis shows that AOSC binds to SH-SY5Y cells in concentration-, time-, and temperature-dependent fashions. The AOSC binding proteins were purified by affinity chromatography and identified by LC-MS/MS analysis. The results showed that there are 349 proteins binding AOSC, including clathrin, adaptor protein-2 (AP-2) and amyloid precursor protein (APP). These results suggest that the binding/entrance of AOSC to neurons is probably responsible for anti-AD activities.

Ca(2+) and frequency dependence of exocytosis in isolated somata of magnocellular supraoptic neurones of the rat hypothalamus.

PubMed

Soldo, Brandi L; Giovannucci, David R; Stuenkel, Edward L; Moises, Hylan C

2004-03-16

In addition to action potential-evoked exocytotic release at neurohypophysial nerve terminals, the neurohormones arginine vasopressin (aVP) and oxytocin (OT) undergo Ca(2+)-dependent somatodendritic release within the supraoptic and paraventricular hypothalamic nuclei. However, the cellular and molecular mechanisms that underlie this release have not been elucidated. In the present study, the whole-cell patch-clamp technique was utilized in combination with high-time-resolved measurements of membrane capacitance (C(m)) and microfluorometric measurements of cytosolic free Ca(2+) concentration ([Ca(2+)](i)) to examine the Ca(2+) and stimulus dependence of exocytosis in the somata of magnocellular neurosecretory cells (MNCs) isolated from rat supraoptic nucleus (SON). Single depolarizing steps (> or =20 ms) that evoked high-voltage-activated (HVA) Ca(2+) currents (I(Ca)) and elevations in intracellular Ca(2+) concentration were accompanied by an increase in C(m) in a majority (40/47) of SON neurones. The C(m) responses were composed of an initial Ca(2+)-independent, transient component and a subsequent, sustained phase of increased C(m) (termed DeltaC(m)) mediated by an influx of Ca(2+), and increased with corresponding prolongation of depolarizing step durations (20-200 ms). From this relationship we estimated the rate of vesicular release to be 1533 vesicles s(-1). Delivery of neurone-derived action potential waveforms (APWs) as stimulus templates elicited I(Ca) and also induced a DeltaC(m), provided APWs were applied in trains of greater than 13 Hz. A train of APWs modelled after the bursting pattern recorded from an OT-containing neurone during the milk ejection reflex was effective in supporting an exocytotic DeltaC(m) in isolated MNCs, indicating that the somata of SON neurones respond to physiological patterns of neuronal activity with Ca(2+)-dependent exocytotic activity.

Large-scale two-photon imaging revealed super-sparse population codes in the V1 superficial layer of awake monkeys.

PubMed

Tang, Shiming; Zhang, Yimeng; Li, Zhihao; Li, Ming; Liu, Fang; Jiang, Hongfei; Lee, Tai Sing

2018-04-26

One general principle of sensory information processing is that the brain must optimize efficiency by reducing the number of neurons that process the same information. The sparseness of the sensory representations in a population of neurons reflects the efficiency of the neural code. Here, we employ large-scale two-photon calcium imaging to examine the responses of a large population of neurons within the superficial layers of area V1 with single-cell resolution, while simultaneously presenting a large set of natural visual stimuli, to provide the first direct measure of the population sparseness in awake primates. The results show that only 0.5% of neurons respond strongly to any given natural image - indicating a ten-fold increase in the inferred sparseness over previous measurements. These population activities are nevertheless necessary and sufficient to discriminate visual stimuli with high accuracy, suggesting that the neural code in the primary visual cortex is both super-sparse and highly efficient. © 2018, Tang et al.

Sleep-Dependent Memory Consolidation and Incremental Sentence Comprehension: Computational Dependencies during Language Learning as Revealed by Neuronal Oscillations

PubMed Central

Cross, Zachariah R.; Kohler, Mark J.; Schlesewsky, Matthias; Gaskell, M. G.; Bornkessel-Schlesewsky, Ina

2018-01-01

We hypothesize a beneficial influence of sleep on the consolidation of the combinatorial mechanisms underlying incremental sentence comprehension. These predictions are grounded in recent work examining the effect of sleep on the consolidation of linguistic information, which demonstrate that sleep-dependent neurophysiological activity consolidates the meaning of novel words and simple grammatical rules. However, the sleep-dependent consolidation of sentence-level combinatorics has not been studied to date. Here, we propose that dissociable aspects of sleep neurophysiology consolidate two different types of combinatory mechanisms in human language: sequence-based (order-sensitive) and dependency-based (order-insensitive) combinatorics. The distinction between the two types of combinatorics is motivated both by cross-linguistic considerations and the neurobiological underpinnings of human language. Unifying this perspective with principles of sleep-dependent memory consolidation, we posit that a function of sleep is to optimize the consolidation of sequence-based knowledge (the when) and the establishment of semantic schemas of unordered items (the what) that underpin cross-linguistic variations in sentence comprehension. This hypothesis builds on the proposal that sleep is involved in the construction of predictive codes, a unified principle of brain function that supports incremental sentence comprehension. Finally, we discuss neurophysiological measures (EEG/MEG) that could be used to test these claims, such as the quantification of neuronal oscillations, which reflect basic mechanisms of information processing in the brain. PMID:29445333

The up and down states of cortical networks

NASA Astrophysics Data System (ADS)

Ghorbani, Maryam; Levine, Alex J.; Mehta, Mayank; Bruinsma, Robijn

2011-03-01

The cortical networks show a collective activity of alternating active and silent states known as up and down states during slow wave sleep or anesthesia. The mechanism of this spontaneous activity as well as the anesthesia or sleep are still not clear. Here, using a mean field approach, we present a simple model to study the spontaneous activity of a homogenous cortical network of excitatory and inhibitory neurons that are recurrently connected. A key new ingredient in this model is that the activity-dependant synaptic depression is considered only for the excitatory neurons. We find depending on the strength of the synaptic depression and synaptic efficacies, the phase space contains strange attractors or stable fixed points at active or quiescent regimes. At the strange attractor phase, we can have oscillations similar to up and down states with flat and noisy up states. Moreover, we show that by increasing the synaptic efficacy corresponding to the connections between the excitatory neurons, the characteristics of the up and down states change in agreement with the changes that we observe in the intracellular recordings of the membrane potential from the entorhinal cortex by varying the depth of anesthesia. Thus, we propose that by measuring the value of this synaptic efficacy, one can quantify the depth of anesthesia which is clinically very important. These findings provide a simple, analytical understanding of the spontaneous cortical dynamics.

Ergodic properties of spiking neuronal networks with delayed interactions

NASA Astrophysics Data System (ADS)

Palmigiano, Agostina; Wolf, Fred

The dynamical stability of neuronal networks, and the possibility of chaotic dynamics in the brain pose profound questions to the mechanisms underlying perception. Here we advance on the tractability of large neuronal networks of exactly solvable neuronal models with delayed pulse-coupled interactions. Pulse coupled delayed systems with an infinite dimensional phase space can be studied in equivalent systems of fixed and finite degrees of freedom by introducing a delayer variable for each neuron. A Jacobian of the equivalent system can be analytically obtained, and numerically evaluated. We find that depending on the action potential onset rapidness and the level of heterogeneities, the asynchronous irregular regime characteristic of balanced state networks loses stability with increasing delays to either a slow synchronous irregular or a fast synchronous irregular state. In networks of neurons with slow action potential onset, the transition to collective oscillations leads to an increase of the exponential rate of divergence of nearby trajectories and of the entropy production rate of the chaotic dynamics. The attractor dimension, instead of increasing linearly with increasing delay as reported in many other studies, decreases until eventually the network reaches full synchrony

Computational model of electrically coupled, intrinsically distinct pacemaker neurons.

PubMed

Soto-Treviño, Cristina; Rabbah, Pascale; Marder, Eve; Nadim, Farzan

2005-07-01

Electrical coupling between neurons with similar properties is often studied. Nonetheless, the role of electrical coupling between neurons with widely different intrinsic properties also occurs, but is less well understood. Inspired by the pacemaker group of the crustacean pyloric network, we developed a multicompartment, conductance-based model of a small network of intrinsically distinct, electrically coupled neurons. In the pyloric network, a small intrinsically bursting neuron, through gap junctions, drives 2 larger, tonically spiking neurons to reliably burst in-phase with it. Each model neuron has 2 compartments, one responsible for spike generation and the other for producing a slow, large-amplitude oscillation. We illustrate how these compartments interact and determine the dynamics of the model neurons. Our model captures the dynamic oscillation range measured from the isolated and coupled biological neurons. At the network level, we explore the range of coupling strengths for which synchronous bursting oscillations are possible. The spatial segregation of ionic currents significantly enhances the ability of the 2 neurons to burst synchronously, and the oscillation range of the model pacemaker network depends not only on the strength of the electrical synapse but also on the identity of the neuron receiving inputs. We also compare the activity of the electrically coupled, distinct neurons with that of a network of coupled identical bursting neurons. For small to moderate coupling strengths, the network of identical elements, when receiving asymmetrical inputs, can have a smaller dynamic range of oscillation than that of its constituent neurons in isolation.

Efficient coding of spectrotemporal binaural sounds leads to emergence of the auditory space representation

PubMed Central

Młynarski, Wiktor

2014-01-01

To date a number of studies have shown that receptive field shapes of early sensory neurons can be reproduced by optimizing coding efficiency of natural stimulus ensembles. A still unresolved question is whether the efficient coding hypothesis explains formation of neurons which explicitly represent environmental features of different functional importance. This paper proposes that the spatial selectivity of higher auditory neurons emerges as a direct consequence of learning efficient codes for natural binaural sounds. Firstly, it is demonstrated that a linear efficient coding transform—Independent Component Analysis (ICA) trained on spectrograms of naturalistic simulated binaural sounds extracts spatial information present in the signal. A simple hierarchical ICA extension allowing for decoding of sound position is proposed. Furthermore, it is shown that units revealing spatial selectivity can be learned from a binaural recording of a natural auditory scene. In both cases a relatively small subpopulation of learned spectrogram features suffices to perform accurate sound localization. Representation of the auditory space is therefore learned in a purely unsupervised way by maximizing the coding efficiency and without any task-specific constraints. This results imply that efficient coding is a useful strategy for learning structures which allow for making behaviorally vital inferences about the environment. PMID:24639644

Motor neurons with limb-innervating character in the cervical spinal cord are sculpted by apoptosis based on the Hox code in chick embryo.

PubMed

Mukaigasa, Katsuki; Sakuma, Chie; Okada, Tomoaki; Homma, Shunsaku; Shimada, Takako; Nishiyama, Keiji; Sato, Noboru; Yaginuma, Hiroyuki

2017-12-15

In the developing chick embryo, a certain population of motor neurons (MNs) in the non-limb-innervating cervical spinal cord undergoes apoptosis between embryonic days 4 and 5. However, the characteristics of these apoptotic MNs remain undefined. Here, by examining the spatiotemporal profiles of apoptosis and MN subtype marker expression in normal or apoptosis-inhibited chick embryos, we found that this apoptotic population is distinguishable by Foxp1 expression. When apoptosis was inhibited, the Foxp1 + MNs survived and showed characteristics of lateral motor column (LMC) neurons, which are of a limb-innervating subtype, suggesting that cervical Foxp1 + MNs are the rostral continuation of the LMC. Knockdown and misexpression of Foxp1 did not affect apoptosis progression, but revealed the role of Foxp1 in conferring LMC identity on the cervical MNs. Furthermore, ectopic expression of Hox genes that are normally expressed in the brachial region prevented apoptosis, and directed Foxp1 + MNs to LMC neurons at the cervical level. These results indicate that apoptosis in the cervical spinal cord plays a role in sculpting Foxp1 + MNs committed to LMC neurons, depending on the Hox expression pattern. © 2017. Published by The Company of Biologists Ltd.

Recording from two neurons: second-order stimulus reconstruction from spike trains and population coding.

PubMed

Fernandes, N M; Pinto, B D L; Almeida, L O B; Slaets, J F W; Köberle, R

2010-10-01

We study the reconstruction of visual stimuli from spike trains, representing the reconstructed stimulus by a Volterra series up to second order. We illustrate this procedure in a prominent example of spiking neurons, recording simultaneously from the two H1 neurons located in the lobula plate of the fly Chrysomya megacephala. The fly views two types of stimuli, corresponding to rotational and translational displacements. Second-order reconstructions require the manipulation of potentially very large matrices, which obstructs the use of this approach when there are many neurons. We avoid the computation and inversion of these matrices using a convenient set of basis functions to expand our variables in. This requires approximating the spike train four-point functions by combinations of two-point functions similar to relations, which would be true for gaussian stochastic processes. In our test case, this approximation does not reduce the quality of the reconstruction. The overall contribution to stimulus reconstruction of the second-order kernels, measured by the mean squared error, is only about 5% of the first-order contribution. Yet at specific stimulus-dependent instants, the addition of second-order kernels represents up to 100% improvement, but only for rotational stimuli. We present a perturbative scheme to facilitate the application of our method to weakly correlated neurons.

Spinal neurons require Islet1 for subtype-specific differentiation of electrical excitability

PubMed Central

2014-01-01

Background In the spinal cord, stereotypic patterns of transcription factor expression uniquely identify neuronal subtypes. These transcription factors function combinatorially to regulate gene expression. Consequently, a single transcription factor may regulate divergent development programs by participation in different combinatorial codes. One such factor, the LIM-homeodomain transcription factor Islet1, is expressed in the vertebrate spinal cord. In mouse, chick and zebrafish, motor and sensory neurons require Islet1 for specification of biochemical and morphological signatures. Little is known, however, about the role that Islet1 might play for development of electrical membrane properties in vertebrates. Here we test for a role of Islet1 in differentiation of excitable membrane properties of zebrafish spinal neurons. Results We focus our studies on the role of Islet1 in two populations of early born zebrafish spinal neurons: ventral caudal primary motor neurons (CaPs) and dorsal sensory Rohon-Beard cells (RBs). We take advantage of transgenic lines that express green fluorescent protein (GFP) to identify CaPs, RBs and several classes of interneurons for electrophysiological study. Upon knock-down of Islet1, cells occupying CaP-like and RB-like positions continue to express GFP. With respect to voltage-dependent currents, CaP-like and RB-like neurons have novel repertoires that distinguish them from control CaPs and RBs, and, in some respects, resemble those of neighboring interneurons. The action potentials fired by CaP-like and RB-like neurons also have significantly different properties compared to those elicited from control CaPs and RBs. Conclusions Overall, our findings suggest that, for both ventral motor and dorsal sensory neurons, Islet1 directs differentiation programs that ultimately specify electrical membrane as well as morphological properties that act together to sculpt neuron identity. PMID:25149090

Excitatory Effects of Parvalbumin-Expressing Interneurons Maintain Hippocampal Epileptiform Activity via Synchronous Afterdischarges

PubMed Central

Ellender, Tommas J.; Raimondo, Joseph V.; Irkle, Agnese; Lamsa, Karri P.

2014-01-01

Epileptic seizures are characterized by periods of hypersynchronous, hyperexcitability within brain networks. Most seizures involve two stages: an initial tonic phase, followed by a longer clonic phase that is characterized by rhythmic bouts of synchronized network activity called afterdischarges (ADs). Here we investigate the cellular and network mechanisms underlying hippocampal ADs in an effort to understand how they maintain seizure activity. Using in vitro hippocampal slice models from rats and mice, we performed electrophysiological recordings from CA3 pyramidal neurons to monitor network activity and changes in GABAergic signaling during epileptiform activity. First, we show that the highest synchrony occurs during clonic ADs, consistent with the idea that specific circuit dynamics underlie this phase of the epileptiform activity. We then show that ADs require intact GABAergic synaptic transmission, which becomes excitatory as a result of a transient collapse in the chloride (Cl−) reversal potential. The depolarizing effects of GABA are strongest at the soma of pyramidal neurons, which implicates somatic-targeting interneurons in AD activity. To test this, we used optogenetic techniques to selectively control the activity of somatic-targeting parvalbumin-expressing (PV+) interneurons. Channelrhodopsin-2-mediated activation of PV+ interneurons during the clonic phase generated excitatory GABAergic responses in pyramidal neurons, which were sufficient to elicit and entrain synchronous AD activity across the network. Finally, archaerhodopsin-mediated selective silencing of PV+ interneurons reduced the occurrence of ADs during the clonic phase. Therefore, we propose that activity-dependent Cl− accumulation subverts the actions of PV+ interneurons to perpetuate rather than terminate pathological network hyperexcitability during the clonic phase of seizures. PMID:25392490

PDF neuron firing phase-shifts key circadian activity neurons in Drosophila

PubMed Central

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.

PubMed

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.

Single neurons in the nucleus of the solitary tract respond selectively to bitter taste stimuli.

PubMed

Geran, Laura C; Travers, Susan P

2006-11-01

Molecular data suggest that receptors for all bitter ligands are coexpressed in the same taste receptor cells (TRCs), whereas physiological results indicate that individual TRCs respond to only a subset of bitter stimuli. It is also unclear to what extent bitter-responsive neurons are stimulated by nonbitter stimuli. To explore these issues, single neuron responses were recorded from the rat nucleus of the solitary tract (NST) during whole mouth stimulation with a variety of bitter compounds: 10 microM cycloheximide, 7 mM propylthiouracil, 10 mM denatonium benzoate, and 3 mM quinine hydrochloride at intensities matched for behavioral effectiveness. Stimuli representing the remaining putative taste qualities were also tested. Particular emphasis was given to activating taste receptors in the foliate papillae innervated by the quinine-sensitive glossopharyngeal nerve. This method revealed a novel population of bitter-best (B-best) cells with foliate receptive fields and significant selectivity for bitter tastants. Across all neurons, multidimensional scaling depicted bitter stimuli as loosely clustered yet clearly distinct from nonbitter tastants. When neurons with posterior receptive fields were analyzed alone, bitter stimuli formed a tighter cluster. Nevertheless, responses to bitter stimuli were variable across B-best neurons, with cycloheximide the most, and quinine the least frequent optimal stimulus. These results indicate heterogeneity for the processing of ionic and nonionic bitter tastants, which is dependent on receptive field. Further, they suggest that neurons selective for bitter substances could contribute to taste coding.

The scaffold protein Nde1 safeguards the brain genome during S phase of early neural progenitor differentiation

PubMed Central

Houlihan, Shauna L; Feng, Yuanyi

2014-01-01

Successfully completing the S phase of each cell cycle ensures genome integrity. Impediment of DNA replication can lead to DNA damage and genomic disorders. In this study, we show a novel function for NDE1, whose mutations cause brain developmental disorders, in safeguarding the genome through S phase during early steps of neural progenitor fate restrictive differentiation. Nde1 mutant neural progenitors showed catastrophic DNA double strand breaks concurrent with the DNA replication. This evoked DNA damage responses, led to the activation of p53-dependent apoptosis, and resulted in the reduction of neurons in cortical layer II/III. We discovered a nuclear pool of Nde1, identified the interaction of Nde1 with cohesin and its associated chromatin remodeler, and showed that stalled DNA replication in Nde1 mutants specifically occurred in mid-late S phase at heterochromatin domains. These findings suggest that NDE1-mediated heterochromatin replication is indispensible for neuronal differentiation, and that the loss of NDE1 function may lead to genomic neurological disorders. DOI: http://dx.doi.org/10.7554/eLife.03297.001 PMID:25245017

Sparse orthogonal population representation of spatial context in the retrosplenial cortex.

PubMed

Mao, Dun; Kandler, Steffen; McNaughton, Bruce L; Bonin, Vincent

2017-08-15

Sparse orthogonal coding is a key feature of hippocampal neural activity, which is believed to increase episodic memory capacity and to assist in navigation. Some retrosplenial cortex (RSC) neurons convey distributed spatial and navigational signals, but place-field representations such as observed in the hippocampus have not been reported. Combining cellular Ca 2+ imaging in RSC of mice with a head-fixed locomotion assay, we identified a population of RSC neurons, located predominantly in superficial layers, whose ensemble activity closely resembles that of hippocampal CA1 place cells during the same task. Like CA1 place cells, these RSC neurons fire in sequences during movement, and show narrowly tuned firing fields that form a sparse, orthogonal code correlated with location. RSC 'place' cell activity is robust to environmental manipulations, showing partial remapping similar to that observed in CA1. This population code for spatial context may assist the RSC in its role in memory and/or navigation.Neurons in the retrosplenial cortex (RSC) encode spatial and navigational signals. Here the authors use calcium imaging to show that, similar to the hippocampus, RSC neurons also encode place cell-like activity in a sparse orthogonal representation, partially anchored to the allocentric cues on the linear track.

Early-stage attenuation of phase-amplitude coupling in the hippocampus and medial prefrontal cortex in a transgenic rat model of Alzheimer's disease.

PubMed

Bazzigaluppi, Paolo; Beckett, Tina L; Koletar, Margaret M; Lai, Aaron Y; Joo, Illsung L; Brown, Mary E; Carlen, Peter L; McLaurin, JoAnne; Stefanovic, Bojana

2018-03-01

Alzheimer's disease (AD) is pathologically characterized by amyloid-β peptide (Aβ) accumulation, neurofibrillary tangle formation, and neurodegeneration. Preclinical studies on neuronal impairments associated with progressive amyloidosis have demonstrated some Aβ-dependent neuronal dysfunction including modulation of gamma-aminobutyric acid-ergic signaling. The present work focuses on the early stage of disease progression and uses TgF344-AD rats that recapitulate a broad repertoire of AD-like pathologies to investigate the neuronal network functioning using simultaneous intracranial recordings from the hippocampus (HPC) and the medial prefrontal cortex (mPFC), followed by pathological analyses of gamma-aminobutyric acid (GABA A ) receptor subunits α1 , α5, and δ, and glutamic acid decarboxylases (GAD65 and GAD67). Concomitant to amyloid deposition and tau hyperphosphorylation, low-gamma band power was strongly attenuated in the HPC and mPFC of TgF344-AD rats in comparison to those in non-transgenic littermates. In addition, the phase-amplitude coupling of the neuronal networks in both areas was impaired, evidenced by decreased modulation of theta band phase on gamma band amplitude in TgF344-AD animals. Finally, the gamma coherence between HPC and mPFC was attenuated as well. These results demonstrate significant neuronal network dysfunction at an early stage of AD-like pathology. This network dysfunction precedes the onset of cognitive deficits and is likely driven by Aβ and tau pathologies. This article is part of the Special Issue "Vascular Dementia". © 2017 Her Majesty the Queen in Right of Canada Journal of Neurochemistry © 2017 International Society for Neurochemistry.

Canonical microcircuits for predictive coding

PubMed Central

Bastos, Andre M.; Usrey, W. Martin; Adams, Rick A.; Mangun, George R.; Fries, Pascal; Friston, Karl J.

2013-01-01

Summary This review considers the influential notion of a canonical (cortical) microcircuit in light of recent theories about neuronal processing. Specifically, we conciliate quantitative studies of microcircuitry and the functional logic of neuronal computations. We revisit the established idea that message passing among hierarchical cortical areas implements a form of Bayesian inference – paying careful attention to the implications for intrinsic connections among neuronal populations. By deriving canonical forms for these computations, one can associate specific neuronal populations with specific computational roles. This analysis discloses a remarkable correspondence between the microcircuitry of the cortical column and the connectivity implied by predictive coding. Furthermore, it provides some intuitive insights into the functional asymmetries between feedforward and feedback connections and the characteristic frequencies over which they operate. PMID:23177956

Synaptic potentials in respiratory neurones during evoked phase switching after NMDA receptor blockade in the cat

PubMed Central

Pierrefiche, O; Haji, A; Foutz, A S; Takeda, R; Champagnat, J; Denavit-Saubié, M

1998-01-01

Blockade of NMDA receptors by dizocilpine impairs the inspiratory off-switch (IOS) of central origin but not the IOS evoked by stimulation of sensory afferents. To investigate whether this difference was due to the effects of different patterns of synaptic interactions on respiratory neurones, we stimulated electrically the superior laryngeal nerve (SLN) or vagus nerve in decerebrate cats before and after i.v. administration of dizocilpine, whilst recording intracellularly. Phrenic nerve responses to ipsilateral SLN or vagal stimulation were: at mid-inspiration, a transient inhibition often followed by a brief burst of activity; at late inspiration, an IOS; and at mid-expiration, a late burst of activity. In all neurones (n = 16), SLN stimulation at mid-inspiration evoked an early EPSP during phase 1 (latency to the arrest of phrenic nerve activity), followed by an IPSP in inspiratory (I) neurones (n = 8) and by a wave of EPSPs in post-inspiratory (PI) neurones (n = 8) during phase 2 (inhibition of phrenic activity). An EPSP in I neurones and an IPSP in PI neurones occurred during phase 3 (brief phrenic burst) following phase 2. Evoked IOS was associated with a fast (phase 1) activation of PI neurones, whereas during spontaneous IOS, a progressive (30-50 ms) depolarization of PI neurones preceded the arrest of phrenic activity. Phase 3 PSPs were similar to those occurring during the burst of activity seen at the start of spontaneous inspiration. Dizocilpine did not suppress the evoked phrenic inhibition and the late burst of activity. The shapes and timing of the evoked PSPs and the changes in membrane potential in I and PI neurones during the phase transition were not altered. We hypothesize that afferent sensory pathways not requiring NMDA receptors (1) terminate inspiration through a premature activation of PI neurones, and (2) evoke a late burst of phrenic activity which might be the first stage of the inspiratory on-switch. PMID:9508816

Pushing the threshold: How NMDAR antagonists induce homeostasis through protein synthesis to remedy depression.

PubMed

Raab-Graham, Kimberly F; Workman, Emily R; Namjoshi, Sanjeev; Niere, Farr

2016-09-15

Healthy neurons have an optimal operating range, coded globally by the frequency of action potentials or locally by calcium. The maintenance of this range is governed by homeostatic plasticity. Here, we discuss how new approaches to treat depression alter synaptic activity. These approaches induce the neuron to recruit homeostatic mechanisms to relieve depression. Homeostasis generally implies that the direction of activity necessary to restore the neuron's critical operating range is opposite in direction to its current activity pattern. Unconventional antidepressant therapies-deep brain stimulation and NMDAR antagonists-alter the neuron's "depressed" state by pushing the neuron's current activity in the same direction but to the extreme edge. These therapies rally the intrinsic drive of neurons in the opposite direction, thereby allowing the cell to return to baseline activity, form new synapses, and restore proper communication. In this review, we discuss seminal studies on protein synthesis dependent homeostatic plasticity and their contribution to our understanding of molecular mechanisms underlying the effectiveness of NMDAR antagonists as rapid antidepressants. Rapid antidepressant efficacy is likely to require a cascade of mRNA translational regulation. Emerging evidence suggests that changes in synaptic strength or intrinsic excitability converge on the same protein synthesis pathways, relieving depressive symptoms. Thus, we address the question: Are there multiple homeostatic mechanisms that induce the neuron and neuronal circuits to self-correct to regulate mood in vivo? Targeting alternative ways to induce homeostatic protein synthesis may provide, faster, safer, and longer lasting antidepressants. This article is part of a Special Issue entitled SI:RNA Metabolism in Disease. Published by Elsevier B.V.

Position-dependent and neuron-specific splicing regulation by the CELF family RNA-binding protein UNC-75 in Caenorhabditis elegans

PubMed Central

Kuroyanagi, Hidehito; Watanabe, Yohei; Suzuki, Yutaka; Hagiwara, Masatoshi

2013-01-01

A large fraction of protein-coding genes in metazoans undergo alternative pre-mRNA splicing in tissue- or cell-type-specific manners. Recent genome-wide approaches have identified many putative-binding sites for some of tissue-specific trans-acting splicing regulators. However, the mechanisms of splicing regulation in vivo remain largely unknown. To elucidate the modes of splicing regulation by the neuron-specific CELF family RNA-binding protein UNC-75 in Caenorhabditis elegans, we performed deep sequencing of poly(A)+ RNAs from the unc-75(+)- and unc-75-mutant worms and identified more than 20 cassette and mutually exclusive exons repressed or activated by UNC-75. Motif searches revealed that (G/U)UGUUGUG stretches are enriched in the upstream and downstream introns of the UNC-75-repressed and -activated exons, respectively. Recombinant UNC-75 protein specifically binds to RNA fragments carrying the (G/U)UGUUGUG stretches in vitro. Bi-chromatic fluorescence alternative splicing reporters revealed that the UNC-75-target exons are regulated in tissue-specific and (G/U)UGUUGUG element-dependent manners in vivo. The unc-75 mutation affected the splicing reporter expression specifically in the nervous system. These results indicate that UNC-75 regulates alternative splicing of its target exons in neuron-specific and position-dependent manners through the (G/U)UGUUGUG elements in C. elegans. This study thus reveals the repertoire of target events for the CELF family in the living organism. PMID:23416545

Non-linear Membrane Properties in Entorhinal Cortical Stellate Cells Reduce Modulation of Input-Output Responses by Voltage Fluctuations

PubMed Central

Fernandez, Fernando R.; Malerba, Paola; White, John A.

2015-01-01

The presence of voltage fluctuations arising from synaptic activity is a critical component in models of gain control, neuronal output gating, and spike rate coding. The degree to which individual neuronal input-output functions are modulated by voltage fluctuations, however, is not well established across different cortical areas. Additionally, the extent and mechanisms of input-output modulation through fluctuations have been explored largely in simplified models of spike generation, and with limited consideration for the role of non-linear and voltage-dependent membrane properties. To address these issues, we studied fluctuation-based modulation of input-output responses in medial entorhinal cortical (MEC) stellate cells of rats, which express strong sub-threshold non-linear membrane properties. Using in vitro recordings, dynamic clamp and modeling, we show that the modulation of input-output responses by random voltage fluctuations in stellate cells is significantly limited. In stellate cells, a voltage-dependent increase in membrane resistance at sub-threshold voltages mediated by Na+ conductance activation limits the ability of fluctuations to elicit spikes. Similarly, in exponential leaky integrate-and-fire models using a shallow voltage-dependence for the exponential term that matches stellate cell membrane properties, a low degree of fluctuation-based modulation of input-output responses can be attained. These results demonstrate that fluctuation-based modulation of input-output responses is not a universal feature of neurons and can be significantly limited by subthreshold voltage-gated conductances. PMID:25909971

Non-linear Membrane Properties in Entorhinal Cortical Stellate Cells Reduce Modulation of Input-Output Responses by Voltage Fluctuations.

PubMed

Fernandez, Fernando R; Malerba, Paola; White, John A

2015-04-01

The presence of voltage fluctuations arising from synaptic activity is a critical component in models of gain control, neuronal output gating, and spike rate coding. The degree to which individual neuronal input-output functions are modulated by voltage fluctuations, however, is not well established across different cortical areas. Additionally, the extent and mechanisms of input-output modulation through fluctuations have been explored largely in simplified models of spike generation, and with limited consideration for the role of non-linear and voltage-dependent membrane properties. To address these issues, we studied fluctuation-based modulation of input-output responses in medial entorhinal cortical (MEC) stellate cells of rats, which express strong sub-threshold non-linear membrane properties. Using in vitro recordings, dynamic clamp and modeling, we show that the modulation of input-output responses by random voltage fluctuations in stellate cells is significantly limited. In stellate cells, a voltage-dependent increase in membrane resistance at sub-threshold voltages mediated by Na+ conductance activation limits the ability of fluctuations to elicit spikes. Similarly, in exponential leaky integrate-and-fire models using a shallow voltage-dependence for the exponential term that matches stellate cell membrane properties, a low degree of fluctuation-based modulation of input-output responses can be attained. These results demonstrate that fluctuation-based modulation of input-output responses is not a universal feature of neurons and can be significantly limited by subthreshold voltage-gated conductances.

Cross-frequency synchronization connects networks of fast and slow oscillations during visual working memory maintenance

PubMed Central

Siebenhühner, Felix; Wang, Sheng H; Palva, J Matias; Palva, Satu

2016-01-01

Neuronal activity in sensory and fronto-parietal (FP) areas underlies the representation and attentional control, respectively, of sensory information maintained in visual working memory (VWM). Within these regions, beta/gamma phase-synchronization supports the integration of sensory functions, while synchronization in theta/alpha bands supports the regulation of attentional functions. A key challenge is to understand which mechanisms integrate neuronal processing across these distinct frequencies and thereby the sensory and attentional functions. We investigated whether such integration could be achieved by cross-frequency phase synchrony (CFS). Using concurrent magneto- and electroencephalography, we found that CFS was load-dependently enhanced between theta and alpha–gamma and between alpha and beta-gamma oscillations during VWM maintenance among visual, FP, and dorsal attention (DA) systems. CFS also connected the hubs of within-frequency-synchronized networks and its strength predicted individual VWM capacity. We propose that CFS integrates processing among synchronized neuronal networks from theta to gamma frequencies to link sensory and attentional functions. DOI: http://dx.doi.org/10.7554/eLife.13451.001 PMID:27669146

Group delay variations of GPS transmitting and receiving antennas

NASA Astrophysics Data System (ADS)

Wanninger, Lambert; Sumaya, Hael; Beer, Susanne

2017-09-01

GPS code pseudorange measurements exhibit group delay variations at the transmitting and the receiving antenna. We calibrated C1 and P2 delay variations with respect to dual-frequency carrier phase observations and obtained nadir-dependent corrections for 32 satellites of the GPS constellation in early 2015 as well as elevation-dependent corrections for 13 receiving antenna models. The combined delay variations reach up to 1.0 m (3.3 ns) in the ionosphere-free linear combination for specific pairs of satellite and receiving antennas. Applying these corrections to the code measurements improves code/carrier single-frequency precise point positioning, ambiguity fixing based on the Melbourne-Wübbena linear combination, and determination of ionospheric total electron content. It also affects fractional cycle biases and differential code biases.

Decoding a Decision Process in the Neuronal Population of Dorsal Premotor Cortex.

PubMed

Rossi-Pool, Román; Zainos, Antonio; Alvarez, Manuel; Zizumbo, Jerónimo; Vergara, José; Romo, Ranulfo

2017-12-20

When trained monkeys discriminate the temporal structure of two sequential vibrotactile stimuli, dorsal premotor cortex (DPC) showed high heterogeneity among its neuronal responses. Notably, DPC neurons coded stimulus patterns as broader categories and signaled them during working memory, comparison, and postponed decision periods. Here, we show that such population activity can be condensed into two major coding components: one that persistently represented in working memory both the first stimulus identity and the postponed informed choice and another that transiently coded the initial sensory information and the result of the comparison between the two stimuli. Additionally, we identified relevant signals that coded the timing of task events. These temporal and task-parameter readouts were shown to be strongly linked to the monkeys' behavior when contrasted to those obtained in a non-demanding cognitive control task and during error trials. These signals, hidden in the heterogeneity, were prominently represented by the DPC population response. Copyright © 2017 Elsevier Inc. All rights reserved.

Ground-state coding in partially connected neural networks

NASA Technical Reports Server (NTRS)

Baram, Yoram

1989-01-01

Patterns over (-1,0,1) define, by their outer products, partially connected neural networks, consisting of internally strongly connected, externally weakly connected subnetworks. The connectivity patterns may have highly organized structures, such as lattices and fractal trees or nests. Subpatterns over (-1,1) define the subcodes stored in the subnetwork, that agree in their common bits. It is first shown that the code words are locally stable stares of the network, provided that each of the subcodes consists of mutually orthogonal words or of, at most, two words. Then it is shown that if each of the subcodes consists of two orthogonal words, the code words are the unique ground states (absolute minima) of the Hamiltonian associated with the network. The regions of attraction associated with the code words are shown to grow with the number of subnetworks sharing each of the neurons. Depending on the particular network architecture, the code sizes of partially connected networks can be vastly greater than those of fully connected ones and their error correction capabilities can be significantly greater than those of the disconnected subnetworks. The codes associated with lattice-structured and hierarchical networks are discussed in some detail.

Multidimensional Characterization and Differentiation of Neurons in the Anteroventral Cochlear Nucleus

PubMed Central

Typlt, Marei; Englitz, Bernhard; Sonntag, Mandy; Dehmel, Susanne; Kopp-Scheinpflug, Cornelia; Ruebsamen, Rudolf

2012-01-01

Multiple parallel auditory pathways ascend from the cochlear nucleus. It is generally accepted that the origin of these pathways are distinct groups of neurons differing in their anatomical and physiological properties. In extracellular in vivo recordings these neurons are typically classified on the basis of their peri-stimulus time histogram. In the present study we reconsider the question of classification of neurons in the anteroventral cochlear nucleus (AVCN) by taking a wider range of response properties into account. The study aims at a better understanding of the AVCN's functional organization and its significance as the source of different ascending auditory pathways. The analyses were based on 223 neurons recorded in the AVCN of the Mongolian gerbil. The range of analysed parameters encompassed spontaneous activity, frequency coding, sound level coding, as well as temporal coding. In order to categorize the unit sample without any presumptions as to the relevance of certain response parameters, hierarchical cluster analysis and additional principal component analysis were employed which both allow a classification on the basis of a multitude of parameters simultaneously. Even with the presently considered wider range of parameters, high number of neurons and more advanced analytical methods, no clear boundaries emerged which would separate the neurons based on their physiology. At the current resolution of the analysis, we therefore conclude that the AVCN units more likely constitute a multi-dimensional continuum with different physiological characteristics manifested at different poles. However, more complex stimuli could be useful to uncover physiological differences in future studies. PMID:22253838

The vestibular-related frontal cortex and its role in smooth-pursuit eye movements and vestibular-pursuit interactions

PubMed Central

Fukushima, Junko; Akao, Teppei; Kurkin, Sergei; Kaneko, Chris R.S.; Fukushima, Kikuro

2006-01-01

In order to see clearly when a target is moving slowly, primates with high acuity foveae use smooth-pursuit and vergence eye movements. The former rotates both eyes in the same direction to track target motion in frontal planes, while the latter rotates left and right eyes in opposite directions to track target motion in depth. Together, these two systems pursue targets precisely and maintain their images on the foveae of both eyes. During head movements, both systems must interact with the vestibular system to minimize slip of the retinal images. The primate frontal cortex contains two pursuit-related areas; the caudal part of the frontal eye fields (FEF) and supplementary eye fields (SEF). Evoked potential studies have demonstrated vestibular projections to both areas and pursuit neurons in both areas respond to vestibular stimulation. The majority of FEF pursuit neurons code parameters of pursuit such as pursuit and vergence eye velocity, gaze velocity, and retinal image motion for target velocity in frontal and depth planes. Moreover, vestibular inputs contribute to the predictive pursuit responses of FEF neurons. In contrast, the majority of SEF pursuit neurons do not code pursuit metrics and many SEF neurons are reported to be active in more complex tasks. These results suggest that FEF- and SEF-pursuit neurons are involved in different aspects of vestibular-pursuit interactions and that eye velocity coding of SEF pursuit neurons is specialized for the task condition. PMID:16917164

Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons

PubMed Central

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

Contextual effects of noise on vocalization encoding in primary auditory cortex

PubMed Central

Ni, Ruiye; Bender, David A.; Shanechi, Amirali M.; Gamble, Jeffrey R.

2016-01-01

Robust auditory perception plays a pivotal function for processing behaviorally relevant sounds, particularly with distractions from the environment. The neuronal coding enabling this ability, however, is still not well understood. In this study, we recorded single-unit activity from the primary auditory cortex (A1) of awake marmoset monkeys (Callithrix jacchus) while delivering conspecific vocalizations degraded by two different background noises: broadband white noise and vocalization babble. Noise effects on neural representation of target vocalizations were quantified by measuring the responses' similarity to those elicited by natural vocalizations as a function of signal-to-noise ratio. A clustering approach was used to describe the range of response profiles by reducing the population responses to a summary of four response classes (robust, balanced, insensitive, and brittle) under both noise conditions. This clustering approach revealed that, on average, approximately two-thirds of the neurons change their response class when encountering different noises. Therefore, the distortion induced by one particular masking background in single-unit responses is not necessarily predictable from that induced by another, suggesting the low likelihood of a unique group of noise-invariant neurons across different background conditions in A1. Regarding noise influence on neural activities, the brittle response group showed addition of spiking activity both within and between phrases of vocalizations relative to clean vocalizations, whereas the other groups generally showed spiking activity suppression within phrases, and the alteration between phrases was noise dependent. Overall, the variable single-unit responses, yet consistent response types, imply that primate A1 performs scene analysis through the collective activity of multiple neurons. NEW & NOTEWORTHY The understanding of where and how auditory scene analysis is accomplished is of broad interest to neuroscientists. In this paper, we systematically investigated neuronal coding of multiple vocalizations degraded by two distinct noises at various signal-to-noise ratios in nonhuman primates. In the process, we uncovered heterogeneity of single-unit representations for different auditory scenes yet homogeneity of responses across the population. PMID:27881720

Parallel emergence of stable and dynamic memory engrams in the hippocampus.

PubMed

Hainmueller, Thomas; Bartos, Marlene

2018-06-06

During our daily life, we depend on memories of past experiences to plan future behaviour. These memories are represented by the activity of specific neuronal groups or 'engrams' 1,2 . Neuronal engrams are assembled during learning by synaptic modification, and engram reactivation represents the memorized experience 1 . Engrams of conscious memories are initially stored in the hippocampus for several days and then transferred to cortical areas 2 . In the dentate gyrus of the hippocampus, granule cells transform rich inputs from the entorhinal cortex into a sparse output, which is forwarded to the highly interconnected pyramidal cell network in hippocampal area CA3 3 . This process is thought to support pattern separation 4 (but see refs. 5,6 ). CA3 pyramidal neurons project to CA1, the hippocampal output region. Consistent with the idea of transient memory storage in the hippocampus, engrams in CA1 and CA2 do not stabilize over time 7-10 . Nevertheless, reactivation of engrams in the dentate gyrus can induce recall of artificial memories even after weeks 2 . Reconciliation of this apparent paradox will require recordings from dentate gyrus granule cells throughout learning, which has so far not been performed for more than a single day 6,11,12 . Here, we use chronic two-photon calcium imaging in head-fixed mice performing a multiple-day spatial memory task in a virtual environment to record neuronal activity in all major hippocampal subfields. Whereas pyramidal neurons in CA1-CA3 show precise and highly context-specific, but continuously changing, representations of the learned spatial sceneries in our behavioural paradigm, granule cells in the dentate gyrus have a spatial code that is stable over many days, with low place- or context-specificity. Our results suggest that synaptic weights along the hippocampal trisynaptic loop are constantly reassigned to support the formation of dynamic representations in downstream hippocampal areas based on a stable code provided by the dentate gyrus.

Contextual effects of noise on vocalization encoding in primary auditory cortex.

PubMed

Ni, Ruiye; Bender, David A; Shanechi, Amirali M; Gamble, Jeffrey R; Barbour, Dennis L

2017-02-01

Robust auditory perception plays a pivotal function for processing behaviorally relevant sounds, particularly with distractions from the environment. The neuronal coding enabling this ability, however, is still not well understood. In this study, we recorded single-unit activity from the primary auditory cortex (A1) of awake marmoset monkeys (Callithrix jacchus) while delivering conspecific vocalizations degraded by two different background noises: broadband white noise and vocalization babble. Noise effects on neural representation of target vocalizations were quantified by measuring the responses' similarity to those elicited by natural vocalizations as a function of signal-to-noise ratio. A clustering approach was used to describe the range of response profiles by reducing the population responses to a summary of four response classes (robust, balanced, insensitive, and brittle) under both noise conditions. This clustering approach revealed that, on average, approximately two-thirds of the neurons change their response class when encountering different noises. Therefore, the distortion induced by one particular masking background in single-unit responses is not necessarily predictable from that induced by another, suggesting the low likelihood of a unique group of noise-invariant neurons across different background conditions in A1. Regarding noise influence on neural activities, the brittle response group showed addition of spiking activity both within and between phrases of vocalizations relative to clean vocalizations, whereas the other groups generally showed spiking activity suppression within phrases, and the alteration between phrases was noise dependent. Overall, the variable single-unit responses, yet consistent response types, imply that primate A1 performs scene analysis through the collective activity of multiple neurons. The understanding of where and how auditory scene analysis is accomplished is of broad interest to neuroscientists. In this paper, we systematically investigated neuronal coding of multiple vocalizations degraded by two distinct noises at various signal-to-noise ratios in nonhuman primates. In the process, we uncovered heterogeneity of single-unit representations for different auditory scenes yet homogeneity of responses across the population. Copyright © 2017 the American Physiological Society.

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains.

PubMed

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

PubMed Central

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

Differential distribution of voltage-gated channels in myelinated and unmyelinated baroreceptor afferents.

PubMed

Schild, John H; Kunze, Diana L

2012-12-24

Voltage gated ion channels (VGC) make possible the frequency coding of arterial pressure and the neurotransmission of this information along myelinated and unmyelinated fiber pathways. Although many of the same VGC isoforms are expressed in both fiber types, it is the relative expression of each that defines the unique discharge properties of myelinated A-type and unmyelinated C-type baroreceptors. For example, the fast inward Na⁺ current is a major determinant of the action potential threshold and the regenerative transmembrane current needed to sustain repetitive discharge. In A-type baroreceptors the TTX-sensitive Na(v)1.7 VGC contributes to the whole cell Na⁺ current. Na(v)1.7 is expressed at a lower density in C-type neurons and in conjunction with TTX-insensitive Na(v)1.8 and Na(v)1.9 VGC. As a result, action potentials of A-type neurons have firing thresholds that are 15-20 mV more negative and upstroke velocities that are 5-10 times faster than unmyelinated C-type neurons. A more depolarized threshold in conjunction with a broader complement of non-inactivating K(V) VGC subtypes produces C-type action potentials that are 3-4 times longer in duration than A-type neurons and at markedly lower levels of cell excitability. Unmyelinated baroreceptors also express KCa1.1 which provides approximately 25% of the total outward K⁺ current. KCa1.1 plays a critically important role in shaping the action potential profile of C-type neurons and strongly impacts neuronal excitability. A-type neurons do not functionally express the KCa1.1 channel despite having a whole cell Ca(V) current quite similar to that of C-type neurons. As a result, A-type neurons do not have the frequency-dependent braking forces of KCa1.1. Lack of a KCa current and only a limited complement of non-inactivating K(V) VGC in addition to a hyperpolarization activated HCN1 current that is nearly 10 times larger than in C-type neurons leads to elevated levels of discharge in A-type neurons, a hallmark of myelinated baroreceptors. Interestingly, HCN2 and HCN4 expression levels are comparable in both fiber types. Collectively, such apportion of VGC constrains the neural coding of myelinated A-type baroreceptors to low threshold, high frequency, high fidelity discharge but with a limited capacity for neuromodulation of afferent bandwidth. Unmyelinated C-type baroreceptors require greater depolarizing forces for spike initiation and have a low frequency discharge profile that is often poorly correlated with the physiological stimulus. But the complement of VGC in C-type neurons provides far greater capacity for neuromodulation of cell excitability than can be obtained from A-type baroreceptors. Copyright © 2012 Elsevier B.V. All rights reserved.

Interactions between behaviorally relevant rhythms and synaptic plasticity alter coding in the piriform cortex

PubMed Central

Urban, Nathaniel N.

2012-01-01

Understanding how neural and behavioral timescales interact to influence cortical activity and stimulus coding is an important issue in sensory neuroscience. In air-breathing animals, voluntary changes in respiratory frequency alter the temporal patterning olfactory input. In the olfactory bulb, these behavioral timescales are reflected in the temporal properties of mitral/tufted (M/T) cell spike trains. As the odor information contained in these spike trains is relayed from the bulb to the cortex, interactions between presynaptic spike timing and short-term synaptic plasticity dictate how stimulus features are represented in cortical spike trains. Here we demonstrate how the timescales associated with respiratory frequency, spike timing and short-term synaptic plasticity interact to shape cortical responses. Specifically, we quantified the timescales of short-term synaptic facilitation and depression at excitatory synapses between bulbar M/T cells and cortical neurons in slices of mouse olfactory cortex. We then used these results to generate simulated M/T population synaptic currents that were injected into real cortical neurons. M/T population inputs were modulated at frequencies consistent with passive respiration or active sniffing. We show how the differential recruitment of short-term plasticity at breathing versus sniffing frequencies alters cortical spike responses. For inputs at sniffing frequencies, cortical neurons linearly encoded increases in presynaptic firing rates with increased phase locked, firing rates. In contrast, at passive breathing frequencies, cortical responses saturated with changes in presynaptic rate. Our results suggest that changes in respiratory behavior can gate the transfer of stimulus information between the olfactory bulb and cortex. PMID:22553016

Phase-locking and bistability in neuronal networks with synaptic depression

NASA Astrophysics Data System (ADS)

Akcay, Zeynep; Huang, Xinxian; Nadim, Farzan; Bose, Amitabha

2018-02-01

We consider a recurrent network of two oscillatory neurons that are coupled with inhibitory synapses. We use the phase response curves of the neurons and the properties of short-term synaptic depression to define Poincaré maps for the activity of the network. The fixed points of these maps correspond to phase-locked modes of the network. Using these maps, we analyze the conditions that allow short-term synaptic depression to lead to the existence of bistable phase-locked, periodic solutions. We show that bistability arises when either the phase response curve of the neuron or the short-term depression profile changes steeply enough. The results apply to any Type I oscillator and we illustrate our findings using the Quadratic Integrate-and-Fire and Morris-Lecar neuron models.

Scene segmentation by spike synchronization in reciprocally connected visual areas. I. Local effects of cortical feedback.

PubMed

Knoblauch, Andreas; Palm, Günther

2002-09-01

To investigate scene segmentation in the visual system we present a model of two reciprocally connected visual areas using spiking neurons. Area P corresponds to the orientation-selective subsystem of the primary visual cortex, while the central visual area C is modeled as associative memory representing stimulus objects according to Hebbian learning. Without feedback from area C, a single stimulus results in relatively slow and irregular activity, synchronized only for neighboring patches (slow state), while in the complete model activity is faster with an enlarged synchronization range (fast state). When presenting a superposition of several stimulus objects, scene segmentation happens on a time scale of hundreds of milliseconds by alternating epochs of the slow and fast states, where neurons representing the same object are simultaneously in the fast state. Correlation analysis reveals synchronization on different time scales as found in experiments (designated as tower, castle, and hill peaks). On the fast time scale (tower peaks, gamma frequency range), recordings from two sites coding either different or the same object lead to correlograms that are either flat or exhibit oscillatory modulations with a central peak. This is in agreement with experimental findings, whereas standard phase-coding models would predict shifted peaks in the case of different objects.

Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit

PubMed Central

Bharioke, Arjun; Chklovskii, Dmitri B.

2015-01-01

Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. PMID:26247884

Neuronal hyperexcitability in the ventral posterior thalamus of neuropathic rats: modality selective effects of pregabalin

PubMed Central

Dickenson, Anthony H.

2016-01-01

Neuropathic pain represents a substantial clinical challenge; understanding the underlying neural mechanisms and back-translation of therapeutics could aid targeting of treatments more effectively. The ventral posterior thalamus (VP) is the major termination site for the spinothalamic tract and relays nociceptive activity to the somatosensory cortex; however, under neuropathic conditions, it is unclear how hyperexcitability of spinal neurons converges onto thalamic relays. This study aimed to identify neural substrates of hypersensitivity and the influence of pregabalin on central processing. In vivo electrophysiology was performed to record from VP wide dynamic range (WDR) and nociceptive-specific (NS) neurons in anesthetized spinal nerve-ligated (SNL), sham-operated, and naive rats. In neuropathic rats, WDR neurons had elevated evoked responses to low- and high-intensity punctate mechanical stimuli, dynamic brushing, and innocuous and noxious cooling, but less so to heat stimulation, of the receptive field. NS neurons in SNL rats also displayed increased responses to noxious punctate mechanical stimulation, dynamic brushing, noxious cooling, and noxious heat. Additionally, WDR, but not NS, neurons in SNL rats exhibited substantially higher rates of spontaneous firing, which may correlate with ongoing pain. The ratio of WDR-to-NS neurons was comparable between SNL and naive/sham groups, suggesting relatively few NS neurons gain sensitivity to low-intensity stimuli leading to a “WDR phenotype.” After neuropathy was induced, the proportion of cold-sensitive WDR and NS neurons increased, supporting the suggestion that changes in frequency-dependent firing and population coding underlie cold hypersensitivity. In SNL rats, pregabalin inhibited mechanical and heat responses but not cold-evoked or elevated spontaneous activity. PMID:27098028

Neuronal hyperexcitability in the ventral posterior thalamus of neuropathic rats: modality selective effects of pregabalin.

PubMed

Patel, Ryan; Dickenson, Anthony H

2016-07-01

Neuropathic pain represents a substantial clinical challenge; understanding the underlying neural mechanisms and back-translation of therapeutics could aid targeting of treatments more effectively. The ventral posterior thalamus (VP) is the major termination site for the spinothalamic tract and relays nociceptive activity to the somatosensory cortex; however, under neuropathic conditions, it is unclear how hyperexcitability of spinal neurons converges onto thalamic relays. This study aimed to identify neural substrates of hypersensitivity and the influence of pregabalin on central processing. In vivo electrophysiology was performed to record from VP wide dynamic range (WDR) and nociceptive-specific (NS) neurons in anesthetized spinal nerve-ligated (SNL), sham-operated, and naive rats. In neuropathic rats, WDR neurons had elevated evoked responses to low- and high-intensity punctate mechanical stimuli, dynamic brushing, and innocuous and noxious cooling, but less so to heat stimulation, of the receptive field. NS neurons in SNL rats also displayed increased responses to noxious punctate mechanical stimulation, dynamic brushing, noxious cooling, and noxious heat. Additionally, WDR, but not NS, neurons in SNL rats exhibited substantially higher rates of spontaneous firing, which may correlate with ongoing pain. The ratio of WDR-to-NS neurons was comparable between SNL and naive/sham groups, suggesting relatively few NS neurons gain sensitivity to low-intensity stimuli leading to a "WDR phenotype." After neuropathy was induced, the proportion of cold-sensitive WDR and NS neurons increased, supporting the suggestion that changes in frequency-dependent firing and population coding underlie cold hypersensitivity. In SNL rats, pregabalin inhibited mechanical and heat responses but not cold-evoked or elevated spontaneous activity. Copyright © 2016 the American Physiological Society.

Glucose rapidly induces different forms of excitatory synaptic plasticity in hypothalamic POMC neurons.

PubMed

Hu, Jun; Jiang, Lin; Low, Malcolm J; Rui, Liangyou

2014-01-01

Hypothalamic POMC neurons are required for glucose and energy homeostasis. POMC neurons have a wide synaptic connection with neurons both within and outside the hypothalamus, and their activity is controlled by a balance between excitatory and inhibitory synaptic inputs. Brain glucose-sensing plays an essential role in the maintenance of normal body weight and metabolism; however, the effect of glucose on synaptic transmission in POMC neurons is largely unknown. Here we identified three types of POMC neurons (EPSC(+), EPSC(-), and EPSC(+/-)) based on their glucose-regulated spontaneous excitatory postsynaptic currents (sEPSCs), using whole-cell patch-clamp recordings. Lowering extracellular glucose decreased the frequency of sEPSCs in EPSC(+) neurons, but increased it in EPSC(-) neurons. Unlike EPSC(+) and EPSC(-) neurons, EPSC(+/-) neurons displayed a bi-phasic sEPSC response to glucoprivation. In the first phase of glucoprivation, both the frequency and the amplitude of sEPSCs decreased, whereas in the second phase, they increased progressively to the levels above the baseline values. Accordingly, lowering glucose exerted a bi-phasic effect on spontaneous action potentials in EPSC(+/-) neurons. Glucoprivation decreased firing rates in the first phase, but increased them in the second phase. These data indicate that glucose induces distinct excitatory synaptic plasticity in different subpopulations of POMC neurons. This synaptic remodeling is likely to regulate the sensitivity of the melanocortin system to neuronal and hormonal signals.

Rapid processing of chemosensor transients in a neuromorphic implementation of the insect macroglomerular complex

PubMed Central

Pearce, Timothy C.; Karout, Salah; Rácz, Zoltán; Capurro, Alberto; Gardner, Julian W.; Cole, Marina

2012-01-01

We present a biologically-constrained neuromorphic spiking model of the insect antennal lobe macroglomerular complex that encodes concentration ratios of chemical components existing within a blend, implemented using a set of programmable logic neuronal modeling cores. Depending upon the level of inhibition and symmetry in its inhibitory connections, the model exhibits two dynamical regimes: fixed point attractor (winner-takes-all type), and limit cycle attractor (winnerless competition type) dynamics. We show that, when driven by chemosensor input in real-time, the dynamical trajectories of the model's projection neuron population activity accurately encode the concentration ratios of binary odor mixtures in both dynamical regimes. By deploying spike timing-dependent plasticity in a subset of the synapses in the model, we demonstrate that a Hebbian-like associative learning rule is able to organize weights into a stable configuration after exposure to a randomized training set comprising a variety of input ratios. Examining the resulting local interneuron weights in the model shows that each inhibitory neuron competes to represent possible ratios across the population, forming a ratiometric representation via mutual inhibition. After training the resulting dynamical trajectories of the projection neuron population activity show amplification and better separation in their response to inputs of different ratios. Finally, we demonstrate that by using limit cycle attractor dynamics, it is possible to recover and classify blend ratio information from the early transient phases of chemosensor responses in real-time more rapidly and accurately compared to a nearest-neighbor classifier applied to the normalized chemosensor data. Our results demonstrate the potential of biologically-constrained neuromorphic spiking models in achieving rapid and efficient classification of early phase chemosensor array transients with execution times well beyond biological timescales. PMID:23874265

Effect of stimulus intensity on spike-LFP relationship in Secondary Somatosensory cortex

PubMed Central

Hsiao, Steven S.; Crone, Nathan E.; Franaszczuk, Piotr J.; Niebur, Ernst

2008-01-01

Neuronal oscillations in the gamma frequency range have been reported in many cortical areas, but the role they play in cortical processing remains unclear. We tested a recently proposed hypothesis that the intensity of sensory input is coded in the timing of action potentials relative to the phase of gamma oscillations, thus converting amplitude information to a temporal code. We recorded spikes and local field potential (LFP) from secondary somatosensory (SII) cortex in awake monkeys while presenting a vibratory stimulus at different amplitudes. We developed a novel technique based on matching pursuit to study the interaction between the highly transient gamma oscillations and spikes with high time-frequency resolution. We found that spikes were weakly coupled to LFP oscillations in the gamma frequency range (40−80 Hz), and strongly coupled to oscillations in higher gamma frequencies. However, the phase relationship of neither low-gamma nor high-gamma oscillations changed with stimulus intensity, even with a ten-fold increase. We conclude that, in SII, gamma oscillations are synchronized with spikes, but their phase does not vary with stimulus intensity. Furthermore, high-gamma oscillations (>60 Hz) appear to be closely linked to the occurrence of action potentials, suggesting that LFP high-gamma power could be a sensitive index of the population firing rate near the microelectrode. PMID:18632937

Neuronal Reward and Decision Signals: From Theories to Data

PubMed Central

Schultz, Wolfram

2015-01-01

Rewards are crucial objects that induce learning, approach behavior, choices, and emotions. Whereas emotions are difficult to investigate in animals, the learning function is mediated by neuronal reward prediction error signals which implement basic constructs of reinforcement learning theory. These signals are found in dopamine neurons, which emit a global reward signal to striatum and frontal cortex, and in specific neurons in striatum, amygdala, and frontal cortex projecting to select neuronal populations. The approach and choice functions involve subjective value, which is objectively assessed by behavioral choices eliciting internal, subjective reward preferences. Utility is the formal mathematical characterization of subjective value and a prime decision variable in economic choice theory. It is coded as utility prediction error by phasic dopamine responses. Utility can incorporate various influences, including risk, delay, effort, and social interaction. Appropriate for formal decision mechanisms, rewards are coded as object value, action value, difference value, and chosen value by specific neurons. Although all reward, reinforcement, and decision variables are theoretical constructs, their neuronal signals constitute measurable physical implementations and as such confirm the validity of these concepts. The neuronal reward signals provide guidance for behavior while constraining the free will to act. PMID:26109341

The Cerebellar Mossy Fiber Synapse as a Model for High-Frequency Transmission in the Mammalian CNS.

PubMed

Delvendahl, Igor; Hallermann, Stefan

2016-11-01

The speed of neuronal information processing depends on neuronal firing frequency. Here, we describe the evolutionary advantages and ubiquitous occurrence of high-frequency firing within the mammalian nervous system in general. The highest firing frequencies so far have been observed at the cerebellar mossy fiber to granule cell synapse. The mechanisms enabling high-frequency transmission at this synapse are reviewed and compared with other synapses. Finally, information coding of high-frequency signals at the mossy fiber synapse is discussed. The exceptionally high firing frequencies and amenability to high-resolution technical approaches both in vitro and in vivo establish the cerebellar mossy fiber synapse as an attractive model to investigate high-frequency signaling from the molecular up to the network level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamic state estimation based on Poisson spike trains—towards a theory of optimal encoding

NASA Astrophysics Data System (ADS)

Susemihl, Alex; Meir, Ron; Opper, Manfred

2013-03-01

Neurons in the nervous system convey information to higher brain regions by the generation of spike trains. An important question in the field of computational neuroscience is how these sensory neurons encode environmental information in a way which may be simply analyzed by subsequent systems. Many aspects of the form and function of the nervous system have been understood using the concepts of optimal population coding. Most studies, however, have neglected the aspect of temporal coding. Here we address this shortcoming through a filtering theory of inhomogeneous Poisson processes. We derive exact relations for the minimal mean squared error of the optimal Bayesian filter and, by optimizing the encoder, obtain optimal codes for populations of neurons. We also show that a class of non-Markovian, smooth stimuli are amenable to the same treatment, and provide results for the filtering and prediction error which hold for a general class of stochastic processes. This sets a sound mathematical framework for a population coding theory that takes temporal aspects into account. It also formalizes a number of studies which discussed temporal aspects of coding using time-window paradigms, by stating them in terms of correlation times and firing rates. We propose that this kind of analysis allows for a systematic study of temporal coding and will bring further insights into the nature of the neural code.

Simulation of Containment Atmosphere Mixing and Stratification Experiment in the ThAI Facility with a CFD Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Babic, Miroslav; Kljenak, Ivo; Mavko, Borut

2006-07-01

The CFD code CFX4.4 was used to simulate an experiment in the ThAI facility, which was designed for investigation of thermal-hydraulic processes during a severe accident inside a Light Water Reactor containment. In the considered experiment, air was initially present in the vessel, and helium and steam were injected during different phases of the experiment at various mass flow rates and at different locations. The main purpose of the proposed work was to assess the capabilities of the CFD code to reproduce the atmosphere structure with a three-dimensional model, coupled with condensation models proposed by the authors. A three-dimensional modelmore » of the ThAI vessel for the CFX4.4 code was developed. The flow in the simulation domain was modeled as single-phase. Steam condensation on vessel walls was modeled as a sink of mass and energy using a correlation that was originally developed for an integral approach. A simple model of bulk phase change was also included. Calculated time-dependent variables together with temperature and volume fraction distributions at the end of different experiment phases are compared to experimental results. (authors)« less

Growth dynamics explain the development of spatiotemporal burst activity of young cultured neuronal networks in detail.

PubMed

Gritsun, Taras A; le Feber, Joost; Rutten, Wim L C

2012-01-01

A typical property of isolated cultured neuronal networks of dissociated rat cortical cells is synchronized spiking, called bursting, starting about one week after plating, when the dissociated cells have sufficiently sent out their neurites and formed enough synaptic connections. This paper is the third in a series of three on simulation models of cultured networks. Our two previous studies [26], [27] have shown that random recurrent network activity models generate intra- and inter-bursting patterns similar to experimental data. The networks were noise or pacemaker-driven and had Izhikevich-neuronal elements with only short-term plastic (STP) synapses (so, no long-term potentiation, LTP, or depression, LTD, was included). However, elevated pre-phases (burst leaders) and after-phases of burst main shapes, that usually arise during the development of the network, were not yet simulated in sufficient detail. This lack of detail may be due to the fact that the random models completely missed network topology .and a growth model. Therefore, the present paper adds, for the first time, a growth model to the activity model, to give the network a time dependent topology and to explain burst shapes in more detail. Again, without LTP or LTD mechanisms. The integrated growth-activity model yielded realistic bursting patterns. The automatic adjustment of various mutually interdependent network parameters is one of the major advantages of our current approach. Spatio-temporal bursting activity was validated against experiment. Depending on network size, wave reverberation mechanisms were seen along the network boundaries, which may explain the generation of phases of elevated firing before and after the main phase of the burst shape.In summary, the results show that adding topology and growth explain burst shapes in great detail and suggest that young networks still lack/do not need LTP or LTD mechanisms.

Expression of c-Fos in the rat retrosplenial cortex during instrumental re-learning of appetitive bar-pressing depends on the number of stages of previous training

PubMed Central

Svarnik, Olga E.; Bulava, Alexandra I.; Alexandrov, Yuri I.

2013-01-01

Learning is known to be accompanied by induction of c-Fos expression in cortical neurons. However, not all neurons are involved in this process. What the c-Fos expression pattern depends on is still unknown. In the present work we studied whether and to what degree previous animal experience about Task 1 (the first phase of an instrumental learning) influenced neuronal c-Fos expression in the retrosplenial cortex during acquisition of Task 2 (the second phase of an instrumental learning). Animals were progressively shaped across days to bar-press for food at the left side of the experimental chamber (Task 1). This appetitive bar-pressing behavior was shaped by nine stages (“9 stages” group), five stages (“5 stages” group) or one intermediate stage (“1 stage” group). After all animals acquired the first skill and practiced it for five days, the bar and feeder on the left, familiar side of the chamber were inactivated, and the animals were allowed to learn a similar instrumental task at the opposite side of the chamber using another pair of a bar and a feeder (Task 2). The highest number of c-Fos positive neurons was found in the retrosplenial cortex of “1 stage” animals as compared to the other groups. The number of c-Fos positive neurons in “5 stages” group animals was significantly lower than in “1 stage” animals and significantly higher than in “9 stages” animals. The number of c-Fos positive neurons in the cortex of “9 stages” animals was significantly higher than in home caged control animals. At the same time, there were no significant differences between groups in such behavioral variables as the number of entrees into the feeder or bar zones during Task 2 learning. Our results suggest that c-Fos expression in the retrosplenial cortex during Task 2 acquisition was influenced by the previous learning history. PMID:23847484

[Function of glutamate in pattern-gene-rating network is modified by nitric oxide NO].

PubMed

D'iakonova, T L; D'iakonova, V E

2007-03-01

In previous study on the terrestrial snail Helix pomatia, it has been shown that responsiveness of certain neurons to glutamate is controlled by NO; specifically, the donors of NO produced transformation of inhibitory responses to excitatory ones. Here, we extend this study to buccal neurons related to feeding behavior of the pond snail L. stagnalis. Glutamate is known to operate in the standard three-phase feeding pattern as a phase transmitter which mediates the effects of the second phase interneuron N2v. In isolated CNS, we recorded motor neuron B4 that was inhibited during firing of glutamatergic N2v, but expressed excitatory glutamate receptors as well. In some preparations (n = 17), bath application of 0.1 mM glutamate resulted in profound hyperpolarization of, and cessation of synaptic inputs to, the B4. Following treatment for 10-15 min with the NO donor sodium nitroprusside (n = 9), glutamate effect on B4 became excitatory, and a peculiar, sustained two-phase rhythmic activity of the pattern-generating network appeared. In other non-treated preparations (n = 12), 0.1 mM glutamate produced depolarization and excitation of B4, supplemented, in 8 cases, with emergence of the above mentioned two-phase rhythmic activity. Pretreatment for 10-20 min with the NO scavenger 2-phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl-3-oxide (n = 7) abolished these effects of glutamate. Our results suggest that 1) glutamate role in buccal rhythm generation depends on NO level, and 2) this mechanism is involved in modification of the feeding behavior in Lymnaea.

Learning Midlevel Auditory Codes from Natural Sound Statistics.

PubMed

Młynarski, Wiktor; McDermott, Josh H

2018-03-01

Interaction with the world requires an organism to transform sensory signals into representations in which behaviorally meaningful properties of the environment are made explicit. These representations are derived through cascades of neuronal processing stages in which neurons at each stage recode the output of preceding stages. Explanations of sensory coding may thus involve understanding how low-level patterns are combined into more complex structures. To gain insight into such midlevel representations for sound, we designed a hierarchical generative model of natural sounds that learns combinations of spectrotemporal features from natural stimulus statistics. In the first layer, the model forms a sparse convolutional code of spectrograms using a dictionary of learned spectrotemporal kernels. To generalize from specific kernel activation patterns, the second layer encodes patterns of time-varying magnitude of multiple first-layer coefficients. When trained on corpora of speech and environmental sounds, some second-layer units learned to group similar spectrotemporal features. Others instantiate opponency between distinct sets of features. Such groupings might be instantiated by neurons in the auditory cortex, providing a hypothesis for midlevel neuronal computation.

Regulatory consequences of neuronal ELAV-like protein binding to coding and non-coding RNAs in human brain

PubMed Central

Scheckel, Claudia; Drapeau, Elodie; Frias, Maria A; Park, Christopher Y; Fak, John; Zucker-Scharff, Ilana; Kou, Yan; Haroutunian, Vahram; Ma'ayan, Avi

2016-01-01

Neuronal ELAV-like (nELAVL) RNA binding proteins have been linked to numerous neurological disorders. We performed crosslinking-immunoprecipitation and RNAseq on human brain, and identified nELAVL binding sites on 8681 transcripts. Using knockout mice and RNAi in human neuroblastoma cells, we showed that nELAVL intronic and 3' UTR binding regulates human RNA splicing and abundance. We validated hundreds of nELAVL targets among which were important neuronal and disease-associated transcripts, including Alzheimer's disease (AD) transcripts. We therefore investigated RNA regulation in AD brain, and observed differential splicing of 150 transcripts, which in some cases correlated with differential nELAVL binding. Unexpectedly, the most significant change of nELAVL binding was evident on non-coding Y RNAs. nELAVL/Y RNA complexes were specifically remodeled in AD and after acute UV stress in neuroblastoma cells. We propose that the increased nELAVL/Y RNA association during stress may lead to nELAVL sequestration, redistribution of nELAVL target binding, and altered neuronal RNA splicing. DOI: http://dx.doi.org/10.7554/eLife.10421.001 PMID:26894958

Amplification of a bi-phase shift-key modulated signal by a mm-wave FEL

DOE Office of Scientific and Technical Information (OSTI.GOV)

Prosnitz, D.; Scharlemann, E.T.; Sheaffer, M.K.

Bi-phase shift keying (BPSK) is a modulation scheme used in communications and radar in which the phase of a transmitted rf signal is switched in a coded pattern between discrete values differing by {pi} radians. The transmitted information rate (in communications) or resolution (in imaging radar) depends on the rate at which the transmitted signal can be modulated. Modulation rates of greater than 1 GHz are generally desired. Although the instantaneous gain bandwidth of a mm-wave FEL amplifier can be much greater than 10 GHz, slippage may limit the BPSK modulation rate that can be amplified. Qualitative slippage arguments wouldmore » limit the modulation rate to relatively low values; nevertheless, simulations with a time-dependent FEL code (GINGER) indicate that rates of 2 GHz or more are amplified without much loss in modulation integrity. In this paper we describe the effects of slippage in the simulations and discuss the limits of simple arguments.« less

Spatiotemporal Coding of Individual Chemicals by the Gustatory System

PubMed Central

Reiter, Sam; Campillo Rodriguez, Chelsey; Sun, Kui

2015-01-01

Four of the five major sensory systems (vision, olfaction, somatosensation, and audition) are thought to use different but partially overlapping sets of neurons to form unique representations of vast numbers of stimuli. The only exception is gustation, which is thought to represent only small numbers of basic taste categories. However, using new methods for delivering tastant chemicals and making electrophysiological recordings from the tractable gustatory system of the moth Manduca sexta, we found chemical-specific information is as follows: (1) initially encoded in the population of gustatory receptor neurons as broadly distributed spatiotemporal patterns of activity; (2) dramatically integrated and temporally transformed as it propagates to monosynaptically connected second-order neurons; and (3) observed in tastant-specific behavior. Our results are consistent with an emerging view of the gustatory system: rather than constructing basic taste categories, it uses a spatiotemporal population code to generate unique neural representations of individual tastant chemicals. SIGNIFICANCE STATEMENT Our results provide a new view of taste processing. Using a new, relatively simple model system and a new set of techniques to deliver taste stimuli and to examine gustatory receptor neurons and their immediate followers, we found no evidence for labeled line connectivity, or basic taste categories such as sweet, salty, bitter, and sour. Rather, individual tastant chemicals are represented as patterns of spiking activity distributed across populations of receptor neurons. These representations are transformed substantially as multiple types of receptor neurons converge upon follower neurons, leading to a combinatorial coding format that uniquely, rapidly, and efficiently represents individual taste chemicals. Finally, we found that the information content of these neurons can drive tastant-specific behavior. PMID:26338341

Spatiotemporal Coding of Individual Chemicals by the Gustatory System.

PubMed

Reiter, Sam; Campillo Rodriguez, Chelsey; Sun, Kui; Stopfer, Mark

2015-09-02

Four of the five major sensory systems (vision, olfaction, somatosensation, and audition) are thought to use different but partially overlapping sets of neurons to form unique representations of vast numbers of stimuli. The only exception is gustation, which is thought to represent only small numbers of basic taste categories. However, using new methods for delivering tastant chemicals and making electrophysiological recordings from the tractable gustatory system of the moth Manduca sexta, we found chemical-specific information is as follows: (1) initially encoded in the population of gustatory receptor neurons as broadly distributed spatiotemporal patterns of activity; (2) dramatically integrated and temporally transformed as it propagates to monosynaptically connected second-order neurons; and (3) observed in tastant-specific behavior. Our results are consistent with an emerging view of the gustatory system: rather than constructing basic taste categories, it uses a spatiotemporal population code to generate unique neural representations of individual tastant chemicals. Our results provide a new view of taste processing. Using a new, relatively simple model system and a new set of techniques to deliver taste stimuli and to examine gustatory receptor neurons and their immediate followers, we found no evidence for labeled line connectivity, or basic taste categories such as sweet, salty, bitter, and sour. Rather, individual tastant chemicals are represented as patterns of spiking activity distributed across populations of receptor neurons. These representations are transformed substantially as multiple types of receptor neurons converge upon follower neurons, leading to a combinatorial coding format that uniquely, rapidly, and efficiently represents individual taste chemicals. Finally, we found that the information content of these neurons can drive tastant-specific behavior. Copyright © 2015 the authors 0270-6474/15/3512309-13$15.00/0.

Delay selection by spike-timing-dependent plasticity in recurrent networks of spiking neurons receiving oscillatory inputs.

PubMed

Kerr, Robert R; Burkitt, Anthony N; Thomas, Doreen A; Gilson, Matthieu; Grayden, David B

2013-01-01

Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem.

Delay Selection by Spike-Timing-Dependent Plasticity in Recurrent Networks of Spiking Neurons Receiving Oscillatory Inputs

PubMed Central

Kerr, Robert R.; Burkitt, Anthony N.; Thomas, Doreen A.; Gilson, Matthieu; Grayden, David B.

2013-01-01

Learning rules, such as spike-timing-dependent plasticity (STDP), change the structure of networks of neurons based on the firing activity. A network level understanding of these mechanisms can help infer how the brain learns patterns and processes information. Previous studies have shown that STDP selectively potentiates feed-forward connections that have specific axonal delays, and that this underlies behavioral functions such as sound localization in the auditory brainstem of the barn owl. In this study, we investigate how STDP leads to the selective potentiation of recurrent connections with different axonal and dendritic delays during oscillatory activity. We develop analytical models of learning with additive STDP in recurrent networks driven by oscillatory inputs, and support the results using simulations with leaky integrate-and-fire neurons. Our results show selective potentiation of connections with specific axonal delays, which depended on the input frequency. In addition, we demonstrate how this can lead to a network becoming selective in the amplitude of its oscillatory response to this frequency. We extend this model of axonal delay selection within a single recurrent network in two ways. First, we show the selective potentiation of connections with a range of both axonal and dendritic delays. Second, we show axonal delay selection between multiple groups receiving out-of-phase, oscillatory inputs. We discuss the application of these models to the formation and activation of neuronal ensembles or cell assemblies in the cortex, and also to missing fundamental pitch perception in the auditory brainstem. PMID:23408878

Locking of correlated neural activity to ongoing oscillations

PubMed Central

Helias, Moritz

2017-01-01

Population-wide oscillations are ubiquitously observed in mesoscopic signals of cortical activity. In these network states a global oscillatory cycle modulates the propensity of neurons to fire. Synchronous activation of neurons has been hypothesized to be a separate channel of signal processing information in the brain. A salient question is therefore if and how oscillations interact with spike synchrony and in how far these channels can be considered separate. Experiments indeed showed that correlated spiking co-modulates with the static firing rate and is also tightly locked to the phase of beta-oscillations. While the dependence of correlations on the mean rate is well understood in feed-forward networks, it remains unclear why and by which mechanisms correlations tightly lock to an oscillatory cycle. We here demonstrate that such correlated activation of pairs of neurons is qualitatively explained by periodically-driven random networks. We identify the mechanisms by which covariances depend on a driving periodic stimulus. Mean-field theory combined with linear response theory yields closed-form expressions for the cyclostationary mean activities and pairwise zero-time-lag covariances of binary recurrent random networks. Two distinct mechanisms cause time-dependent covariances: the modulation of the susceptibility of single neurons (via the external input and network feedback) and the time-varying variances of single unit activities. For some parameters, the effectively inhibitory recurrent feedback leads to resonant covariances even if mean activities show non-resonant behavior. Our analytical results open the question of time-modulated synchronous activity to a quantitative analysis. PMID:28604771

The neuropeptide PDF acts directly on evening pacemaker neurons to regulate multiple features of circadian behavior.

PubMed

Lear, Bridget C; Zhang, Luoying; Allada, Ravi

2009-07-01

Discrete clusters of circadian clock neurons temporally organize daily behaviors such as sleep and wake. In Drosophila, a network of just 150 neurons drives two peaks of timed activity in the morning and evening. A subset of these neurons expresses the neuropeptide pigment dispersing factor (PDF), which is important for promoting morning behavior as well as maintaining robust free-running rhythmicity in constant conditions. Yet, how PDF acts on downstream circuits to mediate rhythmic behavior is unknown. Using circuit-directed rescue of PDF receptor mutants, we show that PDF targeting of just approximately 30 non-PDF evening circadian neurons is sufficient to drive morning behavior. This function is not accompanied by large changes in core molecular oscillators in light-dark, indicating that PDF RECEPTOR likely regulates the output of these cells under these conditions. We find that PDF also acts on this focused set of non-PDF neurons to regulate both evening activity phase and period length, consistent with modest resetting effects on core oscillators. PDF likely acts on more distributed pacemaker neuron targets, including the PDF neurons themselves, to regulate rhythmic strength. Here we reveal defining features of the circuit-diagram for PDF peptide function in circadian behavior, revealing the direct neuronal targets of PDF as well as its behavioral functions at those sites. These studies define a key direct output circuit sufficient for multiple PDF dependent behaviors.

A Network of HSPG Core Proteins and HS Modifying Enzymes Regulates Netrin-Dependent Guidance of D-Type Motor Neurons in Caenorhabditis elegans

PubMed Central

Gysi, Stephan; Rhiner, Christa; Flibotte, Stephane; Moerman, Donald G.; Hengartner, Michael O.

2013-01-01

Heparan sulfate proteoglycans (HSPGs) are proteins with long covalently attached sugar side chains of the heparan sulfate (HS) type. Depending on the cellular context HS chains carry multiple structural modifications such as sulfate residues or epimerized sugars allowing them to bind to a wide range of molecules. HSPGs have been found to play extremely diverse roles in animal development and were shown to interact with certain axon guidance molecules. In this study we describe the role of the Caenorhabditis elegans HSPG core proteins Syndecan (SDN-1) and Glypican (LON-2) and the HS modifying enzymes in the dorsal guidance of D-type motor axons, a process controlled mainly by the conserved axon guidance molecule UNC-6/Netrin. Our genetic analysis established the specific HS code relevant for this axon guidance event. Using two sensitized genetic backgrounds, we isolated novel components influencing D-type motor axon guidance with a link to HSPGs, as well as new alleles of several previously characterized axon guidance genes. Interestingly, the dorsal axon guidance defects induced by mutations in zfp-1 or lin-35 depended on the transgene oxIs12 used to visualize the D-type motor neurons. oxIs12 is a large multi-copy transgene that enlarges the X chromosome by approximately 20%. In a search for genes with a comparable phenotype we found that a mutation in the known dosage compensation gene dpy-21 showed similar axon guidance defects as zfp-1 or lin-35 mutants. Thus, derepression of genes on X, where many genes relevant for HS dependent axon guidance are located, might also influence axon guidance of D-type motor neurons. PMID:24066155

Glucose Rapidly Induces Different Forms of Excitatory Synaptic Plasticity in Hypothalamic POMC Neurons

PubMed Central

Hu, Jun; Jiang, Lin; Low, Malcolm J.; Rui, Liangyou

2014-01-01

Hypothalamic POMC neurons are required for glucose and energy homeostasis. POMC neurons have a wide synaptic connection with neurons both within and outside the hypothalamus, and their activity is controlled by a balance between excitatory and inhibitory synaptic inputs. Brain glucose-sensing plays an essential role in the maintenance of normal body weight and metabolism; however, the effect of glucose on synaptic transmission in POMC neurons is largely unknown. Here we identified three types of POMC neurons (EPSC(+), EPSC(−), and EPSC(+/−)) based on their glucose-regulated spontaneous excitatory postsynaptic currents (sEPSCs), using whole-cell patch-clamp recordings. Lowering extracellular glucose decreased the frequency of sEPSCs in EPSC(+) neurons, but increased it in EPSC(−) neurons. Unlike EPSC(+) and EPSC(−) neurons, EPSC(+/−) neurons displayed a bi-phasic sEPSC response to glucoprivation. In the first phase of glucoprivation, both the frequency and the amplitude of sEPSCs decreased, whereas in the second phase, they increased progressively to the levels above the baseline values. Accordingly, lowering glucose exerted a bi-phasic effect on spontaneous action potentials in EPSC(+/−) neurons. Glucoprivation decreased firing rates in the first phase, but increased them in the second phase. These data indicate that glucose induces distinct excitatory synaptic plasticity in different subpopulations of POMC neurons. This synaptic remodeling is likely to regulate the sensitivity of the melanocortin system to neuronal and hormonal signals. PMID:25127258

Reward-dependent learning in neuronal networks for planning and decision making.

PubMed

Dehaene, S; Changeux, J P

2000-01-01

Neuronal network models have been proposed for the organization of evaluation and decision processes in prefrontal circuitry and their putative neuronal and molecular bases. The models all include an implementation and simulation of an elementary reward mechanism. Their central hypothesis is that tentative rules of behavior, which are coded by clusters of active neurons in prefrontal cortex, are selected or rejected based on an evaluation by this reward signal, which may be conveyed, for instance, by the mesencephalic dopaminergic neurons with which the prefrontal cortex is densely interconnected. At the molecular level, the reward signal is postulated to be a neurotransmitter such as dopamine, which exerts a global modulatory action on prefrontal synaptic efficacies, either via volume transmission or via targeted synaptic triads. Negative reinforcement has the effect of destabilizing the currently active rule-coding clusters; subsequently, spontaneous activity varies again from one cluster to another, giving the organism the chance to discover and learn a new rule. Thus, reward signals function as effective selection signals that either maintain or suppress currently active prefrontal representations as a function of their current adequacy. Simulations of this variation-selection have successfully accounted for the main features of several major tasks that depend on prefrontal cortex integrity, such as the delayed-response test, the Wisconsin card sorting test, the Tower of London test and the Stroop test. For the more complex tasks, we have found it necessary to supplement the external reward input with a second mechanism that supplies an internal reward; it consists of an auto-evaluation loop which short-circuits the reward input from the exterior. This allows for an internal evaluation of covert motor intentions without actualizing them as behaviors, by simply testing them covertly by comparison with memorized former experiences. This element of architecture gives access to enhanced rates of learning via an elementary process of internal or covert mental simulation. We have recently applied these ideas to a new model, developed with M. Kerszberg, which hypothesizes that prefrontal cortex and its reward-related connections contribute crucially to conscious effortful tasks. This model distinguishes two main computational spaces within the human brain: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative and attentional processors. We postulate that workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice; they selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously co-activated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. This model makes predictions concerning the spatio-temporal activation patterns during brain imaging of cognitive tasks, particularly concerning the conditions of activation of dorsolateral prefrontal cortex and anterior cingulate, their relation to reward mechanisms, and their specific reaction during error processing.

Cochlear spike synchronization and neuron coincidence detection model

NASA Astrophysics Data System (ADS)

Bader, Rolf

2018-02-01

Coincidence detection of a spike pattern fed from the cochlea into a single neuron is investigated using a physical Finite-Difference model of the cochlea and a physiologically motivated neuron model. Previous studies have shown experimental evidence of increased spike synchronization in the nucleus cochlearis and the trapezoid body [Joris et al., J. Neurophysiol. 71(3), 1022-1036 and 1037-1051 (1994)] and models show tone partial phase synchronization at the transition from mechanical waves on the basilar membrane into spike patterns [Ch. F. Babbs, J. Biophys. 2011, 435135]. Still the traveling speed of waves on the basilar membrane cause a frequency-dependent time delay of simultaneously incoming sound wavefronts up to 10 ms. The present model shows nearly perfect synchronization of multiple spike inputs as neuron outputs with interspike intervals (ISI) at the periodicity of the incoming sound for frequencies from about 30 to 300 Hz for two different amounts of afferent nerve fiber neuron inputs. Coincidence detection serves here as a fusion of multiple inputs into one single event enhancing pitch periodicity detection for low frequencies, impulse detection, or increased sound or speech intelligibility due to dereverberation.

Opposite patterns of age-associated changes in neurons and glial cells of the thalamus of human brain.

PubMed

Guidolin, D; Zunarelli, E; Genedani, S; Trentini, G P; De Gaetani, C; Fuxe, K; Benegiamo, C; Agnati, L F

2008-06-01

In an autopsy series of 19 individuals, age-ranged 24-94, a relatively age-spared region, the anterior-ventral thalamus, was analyzed by immunohistochemical techniques to visualize neurons (neurofilament protein), astrocytes (glial fibrillary acidic protein), microglial cells (CD68) and amyloid precursor protein. The pattern of immunoreactivity was determined by surface fractal dimension and lacunarity, the size by the field area (FA) and the spatial uniformity by the uniformity index. From the normalized FA values of immunoreactivity for the four markers studied, a global parameter was defined to give an overall characterization of the age-dependent changes in the glio-neuronal networks. A significant exponential decline of the GP was observed with increasing age. This finding suggests that early in life (age<50 years) an adaptive response might be triggered, involving the glio-neuronal networks in plastic adaptive adjustments to cope with the environmental challenges and the continuous wearing off of the neuronal structures. The slow decay of the GP observed in a later phase (age>70 years) could be due to the non-trophic reserve still available.

Behavior-Dependent Activity and Synaptic Organization of Septo-hippocampal GABAergic Neurons Selectively Targeting the Hippocampal CA3 Area.

PubMed

Joshi, Abhilasha; Salib, Minas; Viney, Tim James; Dupret, David; Somogyi, Peter

2017-12-20

Rhythmic medial septal (MS) GABAergic input coordinates cortical theta oscillations. However, the rules of innervation of cortical cells and regions by diverse septal neurons are unknown. We report a specialized population of septal GABAergic neurons, the Teevra cells, selectively innervating the hippocampal CA3 area bypassing CA1, CA2, and the dentate gyrus. Parvalbumin-immunopositive Teevra cells show the highest rhythmicity among MS neurons and fire with short burst duration (median, 38 ms) preferentially at the trough of both CA1 theta and slow irregular oscillations, coincident with highest hippocampal excitability. Teevra cells synaptically target GABAergic axo-axonic and some CCK interneurons in restricted septo-temporal CA3 segments. The rhythmicity of their firing decreases from septal to temporal termination of individual axons. We hypothesize that Teevra neurons coordinate oscillatory activity across the septo-temporal axis, phasing the firing of specific CA3 interneurons, thereby contributing to the selection of pyramidal cell assemblies at the theta trough via disinhibition. VIDEO ABSTRACT. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Neural coding of basic reward terms of animal learning theory, game theory, microeconomics and behavioural ecology.

PubMed

Schultz, Wolfram

2004-04-01

Neurons in a small number of brain structures detect rewards and reward-predicting stimuli and are active during the expectation of predictable food and liquid rewards. These neurons code the reward information according to basic terms of various behavioural theories that seek to explain reward-directed learning, approach behaviour and decision-making. The involved brain structures include groups of dopamine neurons, the striatum including the nucleus accumbens, the orbitofrontal cortex and the amygdala. The reward information is fed to brain structures involved in decision-making and organisation of behaviour, such as the dorsolateral prefrontal cortex and possibly the parietal cortex. The neural coding of basic reward terms derived from formal theories puts the neurophysiological investigation of reward mechanisms on firm conceptual grounds and provides neural correlates for the function of rewards in learning, approach behaviour and decision-making.

Somatodendritic surface expression of epitope-tagged and KChIP binding-deficient Kv4.2 channels in hippocampal neurons.

PubMed

Prechtel, Helena; Hartmann, Sven; Minge, Daniel; Bähring, Robert

2018-01-01

Kv4.2 channels mediate a subthreshold-activating somatodendritic A-type current (ISA) in hippocampal neurons. We examined the role of accessory Kv channel interacting protein (KChIP) binding in somatodendritic surface expression and activity-dependent decrease in the availability of Kv4.2 channels. For this purpose we transfected cultured hippocampal neurons with cDNA coding for Kv4.2 wild-type (wt) or KChIP binding-deficient Kv4.2 mutants. All channels were equipped with an externally accessible hemagglutinin (HA)-tag and an EGFP-tag, which was attached to the C-terminal end. Combined analyses of EGFP self-fluorescence, surface HA immunostaining and patch-clamp recordings demonstrated similar dendritic trafficking and functional surface expression for Kv4.2[wt]HA,EGFP and the KChIP binding-deficient Kv4.2[A14K]HA,EGFP. Coexpression of exogenous KChIP2 augmented the surface expression of Kv4.2[wt]HA,EGFP but not Kv4.2[A14K]HA,EGFP. Notably, activity-dependent decrease in availability was more pronounced in Kv4.2[wt]HA,EGFP + KChIP2 coexpressing than in Kv4.2[A14K]HA,EGFP + KChIP2 coexpressing neurons. Our results do not support the notion that accessory KChIP binding is a prerequisite for dendritic trafficking and functional surface expression of Kv4.2 channels, however, accessory KChIP binding may play a potential role in Kv4.2 modulation during intrinsic plasticity processes.

Phase synchronization of bursting neurons in clustered small-world networks

NASA Astrophysics Data System (ADS)

Batista, C. A. S.; Lameu, E. L.; Batista, A. M.; Lopes, S. R.; Pereira, T.; Zamora-López, G.; Kurths, J.; Viana, R. L.

2012-07-01

We investigate the collective dynamics of bursting neurons on clustered networks. The clustered network model is composed of subnetworks, each of them presenting the so-called small-world property. This model can also be regarded as a network of networks. In each subnetwork a neuron is connected to other ones with regular as well as random connections, the latter with a given intracluster probability. Moreover, in a given subnetwork each neuron has an intercluster probability to be connected to the other subnetworks. The local neuron dynamics has two time scales (fast and slow) and is modeled by a two-dimensional map. In such small-world network the neuron parameters are chosen to be slightly different such that, if the coupling strength is large enough, there may be synchronization of the bursting (slow) activity. We give bounds for the critical coupling strength to obtain global burst synchronization in terms of the network structure, that is, the probabilities of intracluster and intercluster connections. We find that, as the heterogeneity in the network is reduced, the network global synchronizability is improved. We show that the transitions to global synchrony may be abrupt or smooth depending on the intercluster probability.

Resolving Phase Ambiguities In OQPSK

NASA Technical Reports Server (NTRS)

Nguyen, Tien M.

1991-01-01

Improved design for modulator and demodulator in offset-quaternary-phase-key-shifting (OQPSK) communication system enables receiver to resolve ambiguity in estimated phase of received signal. Features include unique-code-word modulation and detection and digital implementation of Costas loop in carrier-recovery subsystem. Enchances performance of carrier-recovery subsystem, reduces complexity of receiver by removing redundant circuits from previous design, and eliminates dependence of timing in receiver upon parallel-to-serial-conversion clock.

Spatiotemporal processing of linear acceleration: primary afferent and central vestibular neuron responses

NASA Technical Reports Server (NTRS)

Angelaki, D. E.; Dickman, J. D.

2000-01-01

Spatiotemporal convergence and two-dimensional (2-D) neural tuning have been proposed as a major neural mechanism in the signal processing of linear acceleration. To examine this hypothesis, we studied the firing properties of primary otolith afferents and central otolith neurons that respond exclusively to horizontal linear accelerations of the head (0.16-10 Hz) in alert rhesus monkeys. Unlike primary afferents, the majority of central otolith neurons exhibited 2-D spatial tuning to linear acceleration. As a result, central otolith dynamics vary as a function of movement direction. During movement along the maximum sensitivity direction, the dynamics of all central otolith neurons differed significantly from those observed for the primary afferent population. Specifically at low frequencies (

Capturing and Understanding Experiment Provenance using NiNaC

NASA Astrophysics Data System (ADS)

Rosati, C.

2017-12-01

A problem the model development team faces at the GFDL is determining climate model experiment provenance. Each experiment is configured with at least one configuration file which may reference other files. The experiment then passes through three phases before completion. Configuration files or other input files may be modified between phases. Finding the modifications later is tedious due to the expanse of the experiment input and duplication across phases. Determining provenance may be impossible if any file has been changed or deleted. To reduce these efforts and address these problems, we propose a new toolset, NiNaC, for archiving experiment provenance from the beginning of the experiment to the end and every phase in-between. Each of the three phases, check-out, build, and run, of the experiment depends on the previous phase. We use a graph to model the phase dependencies. Let each phase be represented by a node. Let each edge correspond to a dependency between phases where the node incident with the tail depends on the node incident with the head. It follows that the dependency graph is a tree. We reduce the problem to finding the lowest common ancestor and diffing the successor nodes. All files related to input for a phase are assigned a checksum. A new file is created to aggregate the checksums. Then each phase is assigned a checksum of aforementioned file as an identifier. Any change to part of a phase configuration will create unique checksums in all subsequent phases. Finding differences between experiments with this toolset is as simple as diffing two files containing checksums found by traversing the tree. One new benefit is that this toolset now allows differences in source code to be found after experiments are run, which was previously impossible for executables that cannot be linked to a known version controlled source code. Knowing that these changes exist allows us to give priority to help desk tickets concerning unmodified supported experiment releases, and minimize effort spent on unsupported experiments. It is also possible that a change is made, either by mistake or by system error. NiNaC would find the exact file in the precise phase with the change. In this way, NiNaC makes provenance tracking less tedious and solves problems where tracking provenance may previously have been impossible to do.

Adaptive Correlation Space Adjusted Open-Loop Tracking Approach for Vehicle Positioning with Global Navigation Satellite System in Urban Areas

PubMed Central

Ruan, Hang; Li, Jian; Zhang, Lei; Long, Teng

2015-01-01

For vehicle positioning with Global Navigation Satellite System (GNSS) in urban areas, open-loop tracking shows better performance because of its high sensitivity and superior robustness against multipath. However, no previous study has focused on the effects of the code search grid size on the code phase measurement accuracy of open-loop tracking. Traditional open-loop tracking methods are performed by the batch correlators with fixed correlation space. The code search grid size, which is the correlation space, is a constant empirical value and the code phase measuring accuracy will be largely degraded due to the improper grid size, especially when the signal carrier-to-noise density ratio (C/N0) varies. In this study, the Adaptive Correlation Space Adjusted Open-Loop Tracking Approach (ACSA-OLTA) is proposed to improve the code phase measurement dependent pseudo range accuracy. In ACSA-OLTA, the correlation space is adjusted according to the signal C/N0. The novel Equivalent Weighted Pseudo Range Error (EWPRE) is raised to obtain the optimal code search grid sizes for different C/N0. The code phase measuring errors of different measurement calculation methods are analyzed for the first time. The measurement calculation strategy of ACSA-OLTA is derived from the analysis to further improve the accuracy but reduce the correlator consumption. Performance simulation and real tests confirm that the pseudo range and positioning accuracy of ASCA-OLTA are better than the traditional open-loop tracking methods in the usual scenarios of urban area. PMID:26343683

SMN control of RNP assembly: from post-transcriptional gene regulation to motor neuron disease

PubMed Central

Li, Darrick K.; Tisdale, Sarah; Lotti, Francesco; Pellizzoni, Livio

2014-01-01

At the post-transcriptional level, expression of protein-coding genes is controlled by a series of RNA regulatory events including nuclear processing of primary transcripts, transport of mature mRNAs to specific cellular compartments, translation and ultimately, turnover. These processes are orchestrated through the dynamic association of mRNAs with RNA binding proteins and ribonucleoprotein (RNP) complexes. Accurate formation of RNPs in vivo is fundamentally important to cellular development and function, and its impairment often leads to human disease. The survival motor neuron (SMN) protein is key to this biological paradigm: SMN is essential for the biogenesis of various RNPs that function in mRNA processing, and genetic mutations leading to SMN deficiency cause the neurodegenerative disease spinal muscular atrophy. Here we review the expanding role of SMN in the regulation of gene expression through its multiple functions in RNP assembly. We discuss advances in our understanding of SMN activity as a chaperone of RNPs and how disruption of SMN-dependent RNA pathways can cause motor neuron disease. PMID:24769255

Phase-locked cluster oscillations in periodically forced integrate-and-fire-or-burst neuronal populations.

PubMed

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.

Analysis of variance study of the rat cortical layer 4 barrel and layer 5b neurones

PubMed Central

Ito, Muneyuki; Kato, Miyuki

2002-01-01

Unique formation of rodent cortical barrels by layer 4 neurones attracts study of the sensory function of cortical input stage neurones (layer 4) compared with that of output stage neurones (layer 5). We have recorded extracellular responses from rat somatosensory cortical neurones to deflections of contralateral vibrissae. Thirty-two layer 4 barrel neurones and 29 layer 5b neurones were studied. Whisker stimulations were ramp-and-hold deflections with one of six different ramp velocities (100–2.5 mm s−1) and one of four different plateau amplitudes (2000–200 μm). Twenty-four (6 × 4) different stimulus forms were applied to the tip of a whisker trimmed to 10 mm in a predetermined order in stimulus cycles of 20–50 repetitions. Spike counts for a period of 2560 ms in 10 ms bins were summed to construct a matrix of 24 peristimulus histograms for each neurone. Twenty-four amplitude and 24 velocity values were computed from counts during the plateau and ramp phases, respectively. To determine the amplitude- and velocity dependence of a neurone, an amplitude F value (the ratio of variations among-/within-amplitude of the amplitude value) and a velocity F value (ratio of variations among-/within-velocity of the velocity value) were derived by analysis of variance. The amplitude F value of the layer 4 barrel neurones was greater than that of the layer 5b neurones (P < 0.0001). The velocity F value of the barrel neurones was smaller than that of the layer 5b neurones (P = 0.0226). The results suggests that barrel neurones and layer 5b neurones tend to detect amplitude and velocity components of whisker deflection, respectively. PMID:11882683

Transformation of the neural code for tactile detection from thalamus to cortex.

PubMed

Vázquez, Yuriria; Salinas, Emilio; Romo, Ranulfo

2013-07-09

To understand how sensory-driven neural activity gives rise to perception, it is essential to characterize how various relay stations in the brain encode stimulus presence. Neurons in the ventral posterior lateral (VPL) nucleus of the somatosensory thalamus and in primary somatosensory cortex (S1) respond to vibrotactile stimulation with relatively slow modulations (∼100 ms) of their firing rate. In addition, faster modulations (∼10 ms) time-locked to the stimulus waveform are observed in both areas, but their contribution to stimulus detection is unknown. Furthermore, it is unclear whether VPL and S1 neurons encode stimulus presence with similar accuracy and via the same response features. To address these questions, we recorded single neurons while trained monkeys judged the presence or absence of a vibrotactile stimulus of variable amplitude, and their activity was analyzed with a unique decoding method that is sensitive to the time scale of the firing rate fluctuations. We found that the maximum detection accuracy of single neurons is similar in VPL and S1. However, VPL relies more heavily on fast rate modulations than S1, and as a consequence, the neural code in S1 is more tolerant: its performance degrades less when the readout method or the time scale of integration is suboptimal. Therefore, S1 neurons implement a more robust code, one less sensitive to the temporal integration window used to infer stimulus presence downstream. The differences between VPL and S1 responses signaling the appearance of a stimulus suggest a transformation of the neural code from thalamus to cortex.

The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code.

PubMed

Kunkel, Susanne; Schenck, Wolfram

2017-01-01

NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling.

The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code

PubMed Central

Kunkel, Susanne; Schenck, Wolfram

2017-01-01

NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling. PMID:28701946

Effects of spectral and temporal disruption on cortical encoding of gerbil vocalizations

PubMed Central

Ter-Mikaelian, Maria; Semple, Malcolm N.

2013-01-01

Animal communication sounds contain spectrotemporal fluctuations that provide powerful cues for detection and discrimination. Human perception of speech is influenced both by spectral and temporal acoustic features but is most critically dependent on envelope information. To investigate the neural coding principles underlying the perception of communication sounds, we explored the effect of disrupting the spectral or temporal content of five different gerbil call types on neural responses in the awake gerbil's primary auditory cortex (AI). The vocalizations were impoverished spectrally by reduction to 4 or 16 channels of band-passed noise. For this acoustic manipulation, an average firing rate of the neuron did not carry sufficient information to distinguish between call types. In contrast, the discharge patterns of individual AI neurons reliably categorized vocalizations composed of only four spectral bands with the appropriate natural token. The pooled responses of small populations of AI cells classified spectrally disrupted and natural calls with an accuracy that paralleled human performance on an analogous speech task. To assess whether discharge pattern was robust to temporal perturbations of an individual call, vocalizations were disrupted by time-reversing segments of variable duration. For this acoustic manipulation, cortical neurons were relatively insensitive to short reversal lengths. Consistent with human perception of speech, these results indicate that the stable representation of communication sounds in AI is more dependent on sensitivity to slow temporal envelopes than on spectral detail. PMID:23761696

Chimera States in Neural Oscillators

NASA Astrophysics Data System (ADS)

Bahar, Sonya; Glaze, Tera

2014-03-01

Chimera states have recently been explored both theoretically and experimentally, in various coupled nonlinear oscillators, ranging from phase-oscillator models to coupled chemical reactions. In a chimera state, both coherent and incoherent (or synchronized and desynchronized) states occur simultaneously in populations of identical oscillators. We investigate chimera behavior in a population of neural oscillators using the Huber-Braun model, a Hodgkin-Huxley-like model originally developed to characterize the temperature-dependent bursting behavior of mammalian cold receptors. One population of neurons is allowed to synchronize, with each neuron receiving input from all the others in its group (global within-group coupling). Subsequently, a second population of identical neurons is placed under an identical global within-group coupling, and the two populations are also coupled to each other (between-group coupling). For certain values of the coupling constants, the neurons in the two populations exhibit radically different synchronization behavior. We will discuss the range of chimera activity in the model, and discuss its implications for actual neural activity, such as unihemispheric sleep.

More Gamma More Predictions: Gamma-Synchronization as a Key Mechanism for Efficient Integration of Classical Receptive Field Inputs with Surround Predictions

PubMed Central

Vinck, Martin; Bosman, Conrado A.

2016-01-01

During visual stimulation, neurons in visual cortex often exhibit rhythmic and synchronous firing in the gamma-frequency (30–90 Hz) band. Whether this phenomenon plays a functional role during visual processing is not fully clear and remains heavily debated. In this article, we explore the function of gamma-synchronization in the context of predictive and efficient coding theories. These theories hold that sensory neurons utilize the statistical regularities in the natural world in order to improve the efficiency of the neural code, and to optimize the inference of the stimulus causes of the sensory data. In visual cortex, this relies on the integration of classical receptive field (CRF) data with predictions from the surround. Here we outline two main hypotheses about gamma-synchronization in visual cortex. First, we hypothesize that the precision of gamma-synchronization reflects the extent to which CRF data can be accurately predicted by the surround. Second, we hypothesize that different cortical columns synchronize to the extent that they accurately predict each other’s CRF visual input. We argue that these two hypotheses can account for a large number of empirical observations made on the stimulus dependencies of gamma-synchronization. Furthermore, we show that they are consistent with the known laminar dependencies of gamma-synchronization and the spatial profile of intercolumnar gamma-synchronization, as well as the dependence of gamma-synchronization on experience and development. Based on our two main hypotheses, we outline two additional hypotheses. First, we hypothesize that the precision of gamma-synchronization shows, in general, a negative dependence on RF size. In support, we review evidence showing that gamma-synchronization decreases in strength along the visual hierarchy, and tends to be more prominent in species with small V1 RFs. Second, we hypothesize that gamma-synchronized network dynamics facilitate the emergence of spiking output that is particularly information-rich and sparse. PMID:27199684

Emergent Oscillations in Networks of Stochastic Spiking Neurons

PubMed Central

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

Evolutionarily conserved coding properties of auditory neurons across grasshopper species

PubMed Central

Neuhofer, Daniela; Wohlgemuth, Sandra; Stumpner, Andreas; Ronacher, Bernhard

2008-01-01

We investigated encoding properties of identified auditory interneurons in two not closely related grasshopper species (Acrididae). The neurons can be homologized on the basis of their similar morphologies and physiologies. As test stimuli, we used the species-specific stridulation signals of Chorthippus biguttulus, which evidently are not relevant for the other species, Locusta migratoria. We recorded spike trains produced in response to these signals from several neuron types at the first levels of the auditory pathway in both species. Using a spike train metric to quantify differences between neuronal responses, we found a high similarity in the responses of homologous neurons: interspecific differences between the responses of homologous neurons in the two species were not significantly larger than intraspecific differences (between several specimens of a neuron in one species). These results suggest that the elements of the thoracic auditory pathway have been strongly conserved during the evolutionary divergence of these species. According to the ‘efficient coding’ hypothesis, an adaptation of the thoracic auditory pathway to the specific needs of acoustic communication could be expected. We conclude that there must have been stabilizing selective forces at work that conserved coding characteristics and prevented such an adaptation. PMID:18505715

Supranormal orientation selectivity of visual neurons in orientation-restricted animals.

PubMed

Sasaki, Kota S; Kimura, Rui; Ninomiya, Taihei; Tabuchi, Yuka; Tanaka, Hiroki; Fukui, Masayuki; Asada, Yusuke C; Arai, Toshiya; Inagaki, Mikio; Nakazono, Takayuki; Baba, Mika; Kato, Daisuke; Nishimoto, Shinji; Sanada, Takahisa M; Tani, Toshiki; Imamura, Kazuyuki; Tanaka, Shigeru; Ohzawa, Izumi

2015-11-16

Altered sensory experience in early life often leads to remarkable adaptations so that humans and animals can make the best use of the available information in a particular environment. By restricting visual input to a limited range of orientations in young animals, this investigation shows that stimulus selectivity, e.g., the sharpness of tuning of single neurons in the primary visual cortex, is modified to match a particular environment. Specifically, neurons tuned to an experienced orientation in orientation-restricted animals show sharper orientation tuning than neurons in normal animals, whereas the opposite was true for neurons tuned to non-experienced orientations. This sharpened tuning appears to be due to elongated receptive fields. Our results demonstrate that restricted sensory experiences can sculpt the supranormal functions of single neurons tailored for a particular environment. The above findings, in addition to the minimal population response to orientations close to the experienced one, agree with the predictions of a sparse coding hypothesis in which information is represented efficiently by a small number of activated neurons. This suggests that early brain areas adopt an efficient strategy for coding information even when animals are raised in a severely limited visual environment where sensory inputs have an unnatural statistical structure.

Supranormal orientation selectivity of visual neurons in orientation-restricted animals

PubMed Central

Sasaki, Kota S.; Kimura, Rui; Ninomiya, Taihei; Tabuchi, Yuka; Tanaka, Hiroki; Fukui, Masayuki; Asada, Yusuke C.; Arai, Toshiya; Inagaki, Mikio; Nakazono, Takayuki; Baba, Mika; Kato, Daisuke; Nishimoto, Shinji; Sanada, Takahisa M.; Tani, Toshiki; Imamura, Kazuyuki; Tanaka, Shigeru; Ohzawa, Izumi

2015-01-01

Altered sensory experience in early life often leads to remarkable adaptations so that humans and animals can make the best use of the available information in a particular environment. By restricting visual input to a limited range of orientations in young animals, this investigation shows that stimulus selectivity, e.g., the sharpness of tuning of single neurons in the primary visual cortex, is modified to match a particular environment. Specifically, neurons tuned to an experienced orientation in orientation-restricted animals show sharper orientation tuning than neurons in normal animals, whereas the opposite was true for neurons tuned to non-experienced orientations. This sharpened tuning appears to be due to elongated receptive fields. Our results demonstrate that restricted sensory experiences can sculpt the supranormal functions of single neurons tailored for a particular environment. The above findings, in addition to the minimal population response to orientations close to the experienced one, agree with the predictions of a sparse coding hypothesis in which information is represented efficiently by a small number of activated neurons. This suggests that early brain areas adopt an efficient strategy for coding information even when animals are raised in a severely limited visual environment where sensory inputs have an unnatural statistical structure. PMID:26567927

Two-phase flows and heat transfer within systems with ambient pressure above the thermodynamic critical pressure

NASA Technical Reports Server (NTRS)

Hendricks, R. C.; Braun, M. J.; Mullen, R. L.

1986-01-01

In systems where the design inlet and outlet pressures P sub amb are maintained above the thermodynamic critical pressure P sub c, it is often assumed that heat and mass transfer are governed by single-phase relations and that two-phase flows cannot occur. This simple rule of thumb is adequate in many low-power designs but is inadequate for high-performance turbomachines, boilers, and other systems where two-phase regions can exist even though P sub amb P sub c. Heat and mass transfer and rotordynamic-fluid-mechanic restoring forces depend on momentum differences, and those for a two-phase zone can differ significantly from those for a single-phase zone. By using a laminar, variable-property bearing code and a rotating boiler code, pressure and temperature surfaces were determined that illustrate nesting of a two-phase region within a supercritical pressure region. The method of corresponding states is applied to bearings with reasonable rapport.

Two-phase flows and heat transfer within systems with ambient pressure above the thermodynamic critical pressure

NASA Technical Reports Server (NTRS)

Hendricks, R. C.; Braun, M. J.; Mullen, R. L.

1986-01-01

In systems where the design inlet and outlet pressure P sub amb are maintained above the thermodynamic critical pressure P sub c, it is often assumed that heat and mass transfer are governed by single-phase relations and that two-phase flows cannot occur. This simple rule of thumb is adequate in many low-power designs but is inadequate for high-performance turbomachines, boilers, and other systems where two-phase regions can exist even though P sub amb P sub c. Heat and mass transfer and rotordynamic-fluid-mechanic restoring forces depend on momentum differences, and those for a two-phase zone can differ significantly from those for a single-phase zone. By using a laminar, variable-property bearing code and a rotating boiler code, pressure and temperature surfaces were determined that illustrate nesting of a two-phase region within a supercritical pressure region. The method of corresponding states is applied to bearings with reasonable rapport.

Optimal Design for Hetero-Associative Memory: Hippocampal CA1 Phase Response Curve and Spike-Timing-Dependent Plasticity

PubMed Central

Miyata, Ryota; Ota, Keisuke; Aonishi, Toru

2013-01-01

Recently reported experimental findings suggest that the hippocampal CA1 network stores spatio-temporal spike patterns and retrieves temporally reversed and spread-out patterns. In this paper, we explore the idea that the properties of the neural interactions and the synaptic plasticity rule in the CA1 network enable it to function as a hetero-associative memory recalling such reversed and spread-out spike patterns. In line with Lengyel’s speculation (Lengyel et al., 2005), we firstly derive optimally designed spike-timing-dependent plasticity (STDP) rules that are matched to neural interactions formalized in terms of phase response curves (PRCs) for performing the hetero-associative memory function. By maximizing object functions formulated in terms of mutual information for evaluating memory retrieval performance, we search for STDP window functions that are optimal for retrieval of normal and doubly spread-out patterns under the constraint that the PRCs are those of CA1 pyramidal neurons. The system, which can retrieve normal and doubly spread-out patterns, can also retrieve reversed patterns with the same quality. Finally, we demonstrate that purposely designed STDP window functions qualitatively conform to typical ones found in CA1 pyramidal neurons. PMID:24204822

Executive Control Over Cognition: Stronger and Earlier Rule-Based Modulation of Spatial Category Signals in Prefrontal Cortex Relative to Parietal Cortex

PubMed Central

Goodwin, Shikha J.; Blackman, Rachael K.; Sakellaridi, Sofia

2012-01-01

Human cognition is characterized by flexibility, the ability to select not only which action but which cognitive process to engage to best achieve the current behavioral objective. The ability to tailor information processing in the brain to rules, goals, or context is typically referred to as executive control, and although there is consensus that prefrontal cortex is importantly involved, at present we have an incomplete understanding of how computational flexibility is implemented at the level of prefrontal neurons and networks. To better understand the neural mechanisms of computational flexibility, we simultaneously recorded the electrical activity of groups of single neurons within prefrontal and posterior parietal cortex of monkeys performing a task that required executive control of spatial cognitive processing. In this task, monkeys applied different spatial categorization rules to reassign the same set of visual stimuli to alternative categories on a trial-by-trial basis. We found that single neurons were activated to represent spatially defined categories in a manner that was rule dependent, providing a physiological signature of a cognitive process that was implemented under executive control. We found also that neural signals coding rule-dependent categories were distributed between the parietal and prefrontal cortex—however, not equally. Rule-dependent category signals were stronger, more powerfully modulated by the rule, and earlier to emerge in prefrontal cortex relative to parietal cortex. This suggests that prefrontal cortex may initiate the switch in neural representation at a network level that is important for computational flexibility. PMID:22399773

Divergent Routing of Positive and Negative Information from the Amygdala during Memory Retrieval.

PubMed

Beyeler, Anna; Namburi, Praneeth; Glober, Gordon F; Simonnet, Clémence; Calhoon, Gwendolyn G; Conyers, Garrett F; Luck, Robert; Wildes, Craig P; Tye, Kay M

2016-04-20

Although the basolateral amygdala (BLA) is known to play a critical role in the formation of memories of both positive and negative valence, the coding and routing of valence-related information is poorly understood. Here, we recorded BLA neurons during the retrieval of associative memories and used optogenetic-mediated phototagging to identify populations of neurons that synapse in the nucleus accumbens (NAc), the central amygdala (CeA), or ventral hippocampus (vHPC). We found that despite heterogeneous neural responses within each population, the proportions of BLA-NAc neurons excited by reward predictive cues and of BLA-CeA neurons excited by aversion predictive cues were higher than within the entire BLA. Although the BLA-vHPC projection is known to drive behaviors of innate negative valence, these neurons did not preferentially code for learned negative valence. Together, these findings suggest that valence encoding in the BLA is at least partially mediated via divergent activity of anatomically defined neural populations. Copyright © 2016 Elsevier Inc. All rights reserved.

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition

PubMed Central

Khubieh, Ayah; Ratté, Stéphanie; Lankarany, Milad; Prescott, Steven A.

2016-01-01

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding. PMID:26209846

Increased spontaneous apoptosis of rat primary neurospheres in vitro after experimental autoimmune encephalomyelitis.

PubMed

Sajad, Mir; Zargan, Jamil; Sharma, Jyoti; Chawla, Raman; Arora, Rajesh; Umar, Sadiq; Khan, Haider A

2011-06-01

Survival of neuronal progenitors (NPCs) is a critical determinant of the regenerative capacity of brain following cellular loss. Herein, we report for the first time, the increased spontaneous apoptosis of the first acute phase of Experimental Autoimmune Encephalomyelitis (EAE) derived neurospheres in vitro. Neuronal as well as oligodendroglial loss occurs during experimental autoimmune encephalomyelitis (EAE). This loss is replenished spontaneously by the concomitant increase in the NPC proliferation evidenced by the presence of thin myelin sheaths in the remodeled lesions. However, remyelination depends upon the survival of NPCs and their lineage specific differentiation. We observed significant increase (P < 0.001) in number of BrdU (+) cells in ependymal subventricular zone (SVZ) in EAE rats. EAE derived NPCs showed remarkable increase in S-phase population which was indeed due to the decrease in G-phase progeny suggesting activation of neuronal progenitor cells (NPCs) from quiescence. However, EAE derived neurospheres showed limited survival in vitro which was mediated by the significantly (P < 0.01) depolarized mitochondria, elevated Caspase-3 (P < 0.001) and fragmentation of nuclear DNA evidenced by single cell gel electrophoresis. Our results suggest EAE induced spontaneous apoptosis of NPCs in vitro which may increase the possibility of early stage cell death in the negative regulation of the proliferative cell number and may explain the failure of regeneration in human multiple sclerosis.

Cholinergic Plasticity of Oscillating Neuronal Assemblies in Mouse Hippocampal Slices

PubMed Central

Zylla, Maura M.; Zhang, Xiaomin; Reichinnek, Susanne; Draguhn, Andreas; Both, Martin

2013-01-01

The mammalian hippocampus expresses several types of network oscillations which entrain neurons into transiently stable assemblies. These groups of co-active neurons are believed to support the formation, consolidation and recall of context-dependent memories. Formation of new assemblies occurs during theta- and gamma-oscillations under conditions of high cholinergic activity. Memory consolidation is linked to sharp wave-ripple oscillations (SPW-R) during decreased cholinergic tone. We hypothesized that increased cholinergic tone supports plastic changes of assemblies while low cholinergic tone favors their stability. Coherent spatiotemporal network patterns were measured during SPW-R activity in mouse hippocampal slices. We compared neuronal activity within the oscillating assemblies before and after a transient phase of carbachol-induced gamma oscillations. Single units maintained their coupling to SPW-R throughout the experiment and could be re-identified after the transient phase of gamma oscillations. However, the frequency of SPW-R-related unit firing was enhanced after muscarinic stimulation. At the network level, these changes resulted in altered patterns of extracellularly recorded SPW-R waveforms. In contrast, recording of ongoing SPW-R activity without intermittent cholinergic stimulation revealed remarkably stable repetitive activation of assemblies. These results show that activation of cholinergic receptors induces plasticity at the level of oscillating hippocampal assemblies, in line with the different role of gamma- and SPW-R network activity for memory formation and –consolidation, respectively. PMID:24260462

Visual experience and subsequent sleep induce sequential plastic changes in putative inhibitory and excitatory cortical neurons

PubMed Central

Aton, Sara J.; Broussard, Christopher; Dumoulin, Michelle; Seibt, Julie; Watson, Adam; Coleman, Tammi; Frank, Marcos G.

2013-01-01

Ocular dominance plasticity in the developing primary visual cortex is initiated by monocular deprivation (MD) and consolidated during subsequent sleep. To clarify how visual experience and sleep affect neuronal activity and plasticity, we continuously recorded extragranular visual cortex fast-spiking (FS) interneurons and putative principal (i.e., excitatory) neurons in freely behaving cats across periods of waking MD and post-MD sleep. Consistent with previous reports in mice, MD induces two related changes in FS interneurons: a response shift in favor of the closed eye and depression of firing. Spike-timing–dependent depression of open-eye–biased principal neuron inputs to FS interneurons may mediate these effects. During post-MD nonrapid eye movement sleep, principal neuron firing increases and becomes more phase-locked to slow wave and spindle oscillations. Ocular dominance (OD) shifts in favor of open-eye stimulation—evident only after post-MD sleep—are proportional to MD-induced changes in FS interneuron activity and to subsequent sleep-associated changes in principal neuron activity. OD shifts are greatest in principal neurons that fire 40–300 ms after neighboring FS interneurons during post-MD slow waves. Based on these data, we propose that MD-induced changes in FS interneurons play an instructive role in ocular dominance plasticity, causing disinhibition among open-eye–biased principal neurons, which drive plasticity throughout the visual cortex during subsequent sleep. PMID:23300282

On a phase diagram for random neural networks with embedded spike timing dependent plasticity.

PubMed

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.

Independent Neuronal Representation of Facial and Vocal Identity in the Monkey Hippocampus and Inferotemporal Cortex.

PubMed

Sliwa, Julia; Planté, Aurélie; Duhamel, Jean-René; Wirth, Sylvia

2016-03-01

Social interactions make up to a large extent the prime material of episodic memories. We therefore asked how social signals are coded by neurons in the hippocampus. Human hippocampus is home to neurons representing familiar individuals in an abstract and invariant manner ( Quian Quiroga et al. 2009). In contradistinction, activity of rat hippocampal cells is only weakly altered by the presence of other rats ( von Heimendahl et al. 2012; Zynyuk et al. 2012). We probed the activity of monkey hippocampal neurons to faces and voices of familiar and unfamiliar individuals (monkeys and humans). Thirty-one percent of neurons recorded without prescreening responded to faces or to voices. Yet responses to faces were more informative about individuals than responses to voices and neuronal responses to facial and vocal identities were not correlated, indicating that in our sample identity information was not conveyed in an invariant manner like in human neurons. Overall, responses displayed by monkey hippocampal neurons were similar to the ones of neurons recorded simultaneously in inferotemporal cortex, whose role in face perception is established. These results demonstrate that the monkey hippocampus participates in the read-out of social information contrary to the rat hippocampus, but possibly lack an explicit conceptual coding of as found in humans. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Monkey primary somatosensory cortical activity during the early reaction time period differs with cues that guide movements

PubMed Central

Liu, Yu; Denton, John M.; Nelson, Randall J.

2009-01-01

Vibration-related neurons in monkey primary somatosensory cortex (SI) discharge rhythmically when vibratory stimuli are presented. It remains unclear how functional information carried by vibratory inputs is coded in rhythmic neuronal activity. In the present study, we compared neuronal activity during wrist movements in response to two sets of cues. In the first, movements were guided by vibratory cue only (VIB trials). In the second, movements were guided by simultaneous presentation of both vibratory and visual cues (COM trials). SI neurons were recorded extracellularly during both wrist extensions and flexions. Neuronal activity during the instructed delay period (IDP) and the early reaction time period (RTP) were analyzed. A total of 96 cases from 48 neurons (each neuron contributed two cases, one each for extension and flexion) showed significant vibration entrainment during the early RTPs, as determined by circular statistics (Rayleigh test). Of these, 50 cases had cutaneous (CUTA) and 46 had deep (DEEP) receptive fields. The CUTA neurons showed lower firing rates during the IDPs and greater firing rate changes during the early RTPs when compared with the DEEP neurons. The CUTA neurons also demonstrated decreases in activity entrainment during VIB trials when compared with COM trials. For the DEEP neurons, the difference of entrainment between VIB and COM trials was not statistically significant. The results suggest that somatic vibratory input is coded by both the firing rate and the activity entrainment of the CUTA neurons in SI. The results also suggest that when vibratory inputs are required for successful task completion, the activity of the CUTA neurons increases but the entrainment degrades. The DEEP neurons may be tuned before movement initiation for processing information encoded by proprioceptive afferents. PMID:18288475

Monkey primary somatosensory cortical activity during the early reaction time period differs with cues that guide movements.

PubMed

Liu, Yu; Denton, John M; Nelson, Randall J

2008-05-01

Vibration-related neurons in monkey primary somatosensory cortex (SI) discharge rhythmically when vibratory stimuli are presented. It remains unclear how functional information carried by vibratory inputs is coded in rhythmic neuronal activity. In the present study, we compared neuronal activity during wrist movements in response to two sets of cues. In the first, movements were guided by vibratory cue only (VIB trials). In the second, movements were guided by simultaneous presentation of both vibratory and visual cues (COM trials). SI neurons were recorded extracellularly during both wrist extensions and flexions. Neuronal activity during the instructed delay period (IDP) and the early reaction time period (RTP) were analyzed. A total of 96 cases from 48 neurons (each neuron contributed two cases, one each for extension and flexion) showed significant vibration entrainment during the early RTPs, as determined by circular statistics (Rayleigh test). Of these, 50 cases had cutaneous (CUTA) and 46 had deep (DEEP) receptive fields. The CUTA neurons showed lower firing rates during the IDPs and greater firing rate changes during the early RTPs when compared with the DEEP neurons. The CUTA neurons also demonstrated decreases in activity entrainment during VIB trials when compared with COM trials. For the DEEP neurons, the difference of entrainment between VIB and COM trials was not statistically significant. The results suggest that somatic vibratory input is coded by both the firing rate and the activity entrainment of the CUTA neurons in SI. The results also suggest that when vibratory inputs are required for successful task completion, the activity of the CUTA neurons increases but the entrainment degrades. The DEEP neurons may be tuned before movement initiation for processing information encoded by proprioceptive afferents.

Mirror neurons and their clinical relevance.

PubMed

Rizzolatti, Giacomo; Fabbri-Destro, Maddalena; Cattaneo, Luigi

2009-01-01

One of the most exciting events in neurosciences over the past few years has been the discovery of a mechanism that unifies action perception and action execution. The essence of this 'mirror' mechanism is as follows: whenever individuals observe an action being done by someone else, a set of neurons that code for that action is activated in the observers' motor system. Since the observers are aware of the outcome of their motor acts, they also understand what the other individual is doing without the need for intermediate cognitive mediation. In this Review, after discussing the most pertinent data concerning the mirror mechanism, we examine the clinical relevance of this mechanism. We first discuss the relationship between mirror mechanism impairment and some core symptoms of autism. We then outline the theoretical principles of neurorehabilitation strategies based on the mirror mechanism. We conclude by examining the relationship between the mirror mechanism and some features of the environmental dependency syndromes.

Cortical Double-Opponent Cells in Color Perception: Perceptual Scaling and Chromatic Visual Evoked Potentials.

PubMed

Nunez, Valerie; Shapley, Robert M; Gordon, James

2018-01-01

In the early visual cortex V1, there are currently only two known neural substrates for color perception: single-opponent and double-opponent cells. Our aim was to explore the relative contributions of these neurons to color perception. We measured the perceptual scaling of color saturation for equiluminant color checkerboard patterns (designed to stimulate double-opponent neurons preferentially) and uniformly colored squares (designed to stimulate only single-opponent neurons) at several cone contrasts. The spatially integrative responses of single-opponent neurons would produce the same response magnitude for checkerboards as for uniform squares of the same space-averaged cone contrast. However, perceived saturation of color checkerboards was higher than for the corresponding squares. The perceptual results therefore imply that double-opponent cells are involved in color perception of patterns. We also measured the chromatic visual evoked potential (cVEP) produced by the same stimuli; checkerboard cVEPs were much larger than those for corresponding squares, implying that double-opponent cells also contribute to the cVEP response. The total Fourier power of the cVEP grew sublinearly with cone contrast. However, the 6-Hz Fourier component's power grew linearly with contrast-like saturation perception. This may also indicate that cortical coding of color depends on response dynamics.

Cortical Double-Opponent Cells in Color Perception: Perceptual Scaling and Chromatic Visual Evoked Potentials

PubMed Central

Shapley, Robert M.; Gordon, James

2018-01-01

In the early visual cortex V1, there are currently only two known neural substrates for color perception: single-opponent and double-opponent cells. Our aim was to explore the relative contributions of these neurons to color perception. We measured the perceptual scaling of color saturation for equiluminant color checkerboard patterns (designed to stimulate double-opponent neurons preferentially) and uniformly colored squares (designed to stimulate only single-opponent neurons) at several cone contrasts. The spatially integrative responses of single-opponent neurons would produce the same response magnitude for checkerboards as for uniform squares of the same space-averaged cone contrast. However, perceived saturation of color checkerboards was higher than for the corresponding squares. The perceptual results therefore imply that double-opponent cells are involved in color perception of patterns. We also measured the chromatic visual evoked potential (cVEP) produced by the same stimuli; checkerboard cVEPs were much larger than those for corresponding squares, implying that double-opponent cells also contribute to the cVEP response. The total Fourier power of the cVEP grew sublinearly with cone contrast. However, the 6-Hz Fourier component’s power grew linearly with contrast-like saturation perception. This may also indicate that cortical coding of color depends on response dynamics. PMID:29375753

Modeling of Non-Homogeneous Containment Atmosphere in the ThAI Experimental Facility Using a CFD Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Babic, Miroslav; Kljenak, Ivo; Mavko, Borut

2006-07-01

The CFD code CFX4.4 was used to simulate an experiment in the ThAI facility, which was designed for investigation of thermal-hydraulic processes during a severe accident inside a Light Water Reactor containment. In the considered experiment, air was initially present in the vessel, and helium and steam were injected during different phases of the experiment at various mass flow rates and at different locations. The main purpose of the simulation was to reproduce the non-homogeneous temperature and species concentration distributions in the ThAI experimental facility. A three-dimensional model of the ThAI vessel for the CFX4.4 code was developed. The flowmore » in the simulation domain was modeled as single-phase. Steam condensation on vessel walls was modeled as a sink of mass and energy using a correlation that was originally developed for an integral approach. A simple model of bulk phase change was also introduced. The calculated time-dependent variables together with temperature and concentration distributions at the end of experiment phases are compared to experimental results. (authors)« less

Spatial training promotes short-term survival and neuron-like differentiation of newborn cells in Aβ1-42-injected rats.

PubMed

Zeng, Juan; Jiang, Xia; Hu, Xian-Feng; Ma, Rong-Hong; Chai, Gao-Shang; Sun, Dong-Sheng; Xu, Zhi-Peng; Li, Li; Bao, Jian; Feng, Qiong; Hu, Yu; Chu, Jiang; Chai, Da-Min; Hong, Xiao-Yue; Wang, Jian-Zhi; Liu, Gong-Ping

2016-09-01

Neurogenesis plays a role in hippocampus-dependent learning and impaired neurogenesis may correlate with cognitive deficits in Alzheimer's disease. Spatial training influences the production and fate of newborn cells in hippocampus of normal animals, whereas the effects on neurogenesis in Alzheimer-like animal are not reported until now. Here, for the first time, we investigated the effect of Morris water maze training on proliferation, survival, apoptosis, migration, and differentiation of newborn cells in β-amyloid-treated Alzheimer-like rats. We found that spatial training could preserve a short-term survival of newborn cells generated before training, during the early phase, and the late phase of training. However, the training had no effect on the long-term survival of mature newborn cells generated at previously mentioned 3 different phases. We also demonstrated that spatial training promoted newborn cell differentiation preferentially to the neuron direction. These findings suggest a time-independent neurogenesis induced by spatial training, which may be indicative for the cognitive stimulation in Alzheimer's disease therapy. Copyright © 2016 Elsevier Inc. All rights reserved.

Generic reactive transport codes as flexible tools to integrate soil organic matter degradation models with water, transport and geochemistry in soils

NASA Astrophysics Data System (ADS)

Jacques, Diederik; Gérard, Fréderic; Mayer, Uli; Simunek, Jirka; Leterme, Bertrand

2016-04-01

A large number of organic matter degradation, CO2 transport and dissolved organic matter models have been developed during the last decades. However, organic matter degradation models are in many cases strictly hard-coded in terms of organic pools, degradation kinetics and dependency on environmental variables. The scientific input of the model user is typically limited to the adjustment of input parameters. In addition, the coupling with geochemical soil processes including aqueous speciation, pH-dependent sorption and colloid-facilitated transport are not incorporated in many of these models, strongly limiting the scope of their application. Furthermore, the most comprehensive organic matter degradation models are combined with simplified representations of flow and transport processes in the soil system. We illustrate the capability of generic reactive transport codes to overcome these shortcomings. The formulations of reactive transport codes include a physics-based continuum representation of flow and transport processes, while biogeochemical reactions can be described as equilibrium processes constrained by thermodynamic principles and/or kinetic reaction networks. The flexibility of these type of codes allows for straight-forward extension of reaction networks, permits the inclusion of new model components (e.g.: organic matter pools, rate equations, parameter dependency on environmental conditions) and in such a way facilitates an application-tailored implementation of organic matter degradation models and related processes. A numerical benchmark involving two reactive transport codes (HPx and MIN3P) demonstrates how the process-based simulation of transient variably saturated water flow (Richards equation), solute transport (advection-dispersion equation), heat transfer and diffusion in the gas phase can be combined with a flexible implementation of a soil organic matter degradation model. The benchmark includes the production of leachable organic matter and inorganic carbon in the aqueous and gaseous phases, as well as different decomposition functions with first-order, linear dependence or nonlinear dependence on a biomass pool. In addition, we show how processes such as local bioturbation (bio-diffusion) can be included implicitly through a Fickian formulation of transport of soil organic matter. Coupling soil organic matter models with generic and flexible reactive transport codes offers a valuable tool to enhance insights into coupled physico-chemical processes at different scales within the scope of C-biogeochemical cycles, possibly linked with other chemical elements such as plant nutrients and pollutants.

Evaluation of Savings in Energy-Efficient Public Housing in the Pacific Northwest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gordon, A.; Lubliner, M.; Howard, L.

2013-10-01

This report presents the results of an energy performance and cost-effectiveness analysis. The Salishan phase 7 and demonstration homes were compared to Salishan phase 6 homes built to 2006 Washington State Energy Code specifications 2. Predicted annual energy savings (over Salishan phase 6) was 19% for Salishan phase 7, and between 19-24% for the demonstration homes (depending on ventilation strategy). Approximately two-thirds of the savings are attributable to the DHP. Working with the electric utility provider, Tacoma Public Utilities, researchers conducted a billing analysis for Salishan phase 7.

LSENS: A General Chemical Kinetics and Sensitivity Analysis Code for homogeneous gas-phase reactions. Part 1: Theory and numerical solution procedures

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan

1994-01-01

LSENS, the Lewis General Chemical Kinetics and Sensitivity Analysis Code, has been developed for solving complex, homogeneous, gas-phase chemical kinetics problems and contains sensitivity analysis for a variety of problems, including nonisothermal situations. This report is part 1 of a series of three reference publications that describe LENS, provide a detailed guide to its usage, and present many example problems. Part 1 derives the governing equations and describes the numerical solution procedures for the types of problems that can be solved. The accuracy and efficiency of LSENS are examined by means of various test problems, and comparisons with other methods and codes are presented. LSENS is a flexible, convenient, accurate, and efficient solver for chemical reaction problems such as static system; steady, one-dimensional, inviscid flow; reaction behind incident shock wave, including boundary layer correction; and perfectly stirred (highly backmixed) reactor. In addition, the chemical equilibrium state can be computed for the following assigned states: temperature and pressure, enthalpy and pressure, temperature and volume, and internal energy and volume. For static problems the code computes the sensitivity coefficients of the dependent variables and their temporal derivatives with respect to the initial values of the dependent variables and/or the three rate coefficient parameters of the chemical reactions.

Overview of long non-coding RNA and mRNA expression in response to methamphetamine treatment in vitro.

PubMed

Xiong, Kun; Long, Lingling; Zhang, Xudong; Qu, Hongke; Deng, Haixiao; Ding, Yanjun; Cai, Jifeng; Wang, Shuchao; Wang, Mi; Liao, Lvshuang; Huang, Jufang; Yi, Chun-Xia; Yan, Jie

2017-10-01

Long non-coding RNAs (lncRNAs) display multiple functions including regulation of neuronal injury. However, their impact in methamphetamine (METH)-induced neurotoxicity has rarely been reported. Here, using microarray analysis, we investigated the expression profiling of lncRNAs and mRNAs in primary cultured prefrontal cortical neurons after METH treatment. We observed a difference in lncRNA and mRNA expression between the experimental and sham control groups. Using bioinformatics, we analyzed the highest enriched gene ontology (GO) terms of biological process, cellular component, and molecular function, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and pathway network analysis. Furthermore, an lncRNA-mRNA co-expression sub-network for aberrantly expressed terms revealed possible interactions of lncRNA NR_110713 and NR_027943 with their related genes. Afterwards, three lncRNAs (NR_110713, NR_027943, GAS5) and two mRNAs (Ddit3, Casp12) were targeted to validate the microarray data by qRT-PCR. This presented an overview of lncRNA and mRNA expression profiling and indicated that lncRNA might participate in METH-induced neuronal apoptosis by regulating the coding genes of neurons. Copyright © 2017 Elsevier Ltd. All rights reserved.

Probing phase- and frequency-dependent characteristics of cortical interneurons using combined transcranial alternating current stimulation and transcranial magnetic stimulation.

PubMed

Hussain, Sara J; Thirugnanasambandam, Nivethida

2017-06-01

Paired-pulse transcranial magnetic stimulation (TMS) and peripheral stimulation combined with TMS can be used to study cortical interneuronal circuitry. By combining these procedures with concurrent transcranial alternating current stimulation (tACS), Guerra and colleagues recently showed that different cortical interneuronal populations are differentially modulated by the phase and frequency of tACS-imposed oscillations (Guerra A, Pogosyan A, Nowak M, Tan H, Ferreri F, Di Lazzaro V, Brown P. Cerebral Cortex 26: 3977-2990, 2016). This work suggests that different cortical interneuronal populations can be characterized by their phase and frequency dependency. Here we discuss how combining TMS and tACS can reveal the frequency at which cortical interneuronal populations oscillate, the neuronal origins of behaviorally relevant cortical oscillations, and how entraining cortical oscillations could potentially treat brain disorders. Copyright © 2017 the American Physiological Society.

Mapping visual stimuli to perceptual decisions via sparse decoding of mesoscopic neural activity.

PubMed

Sajda, Paul

2010-01-01

In this talk I will describe our work investigating sparse decoding of neural activity, given a realistic mapping of the visual scene to neuronal spike trains generated by a model of primary visual cortex (V1). We use a linear decoder which imposes sparsity via an L1 norm. The decoder can be viewed as a decoding neuron (linear summation followed by a sigmoidal nonlinearity) in which there are relatively few non-zero synaptic weights. We find: (1) the best decoding performance is for a representation that is sparse in both space and time, (2) decoding of a temporal code results in better performance than a rate code and is also a better fit to the psychophysical data, (3) the number of neurons required for decoding increases monotonically as signal-to-noise in the stimulus decreases, with as little as 1% of the neurons required for decoding at the highest signal-to-noise levels, and (4) sparse decoding results in a more accurate decoding of the stimulus and is a better fit to psychophysical performance than a distributed decoding, for example one imposed by an L2 norm. We conclude that sparse coding is well-justified from a decoding perspective in that it results in a minimum number of neurons and maximum accuracy when sparse representations can be decoded from the neural dynamics.

Biphasic effects of substance P on respiratory activity and respiration-related neurones in ventrolateral medulla in the neonatal rat brainstem in vitro.

PubMed

Shvarev, Y N; Lagercrantz, H; Yamamoto, Y

2002-01-01

The effects of substance P (SP) on respiratory activity in the brainstem-spinal cord preparation from neonatal rats (0-4 days old) were investigated. The respiratory activity was recorded from C4 ventral roots and intracellularly from three types of respiration-related neurones, i.e. pre-inspiratory (or biphasic E), three subtypes of inspiratory; expiratory and tonic neurones in the ventrolateral medulla (VLM). After the onset of SP bath application (10 nM-1 microM) a dose-dependent decline of burst rate (by 48%) occurred, followed by a weaker dose-dependent increase (by 17.5%) in burst rate. The biphasic effect of SP on inspiratory burst rate was associated with sustained membrane depolarization (in a range of 0.5-13 mV) of respiration-related and tonic neurones. There were no significant changes in membrane resistance in any type of neurones when SP was applied alone or when synaptic transmission was blocked with tetrodotoxin (TTX). The initial depolarization was associated with an increase in inspiratory drive potential (by 25%) as well as in bursting time (by 65%) and membrane excitability in inspiratory and pre-inspiratory neurones, which corresponded to the decrease in burst rate (C4 activity). The spiking frequency of expiratory and tonic neurones was also increased (by 36 and 48%). This activation was followed by restoration of the synaptic drive potential and bursting time in inspiratory and to a less extent in pre-inspiratory neurones, which corresponded to the increase in burst rate. The discharge frequency of expiratory and tonic neurones also decreased to control values. This phase followed the peak membrane depolarization. At the peak depolarization, SP reduced the amplitude of the action potential by 4-8% in all types of neurones. Our results suggest that SP exerts a general excitatory effect on respiration-related neurones and synaptic coupling within the respiratory network in the VLM. The transient changes in neuronal activity in the VLM may underlie the biphasic effect of SP in the brainstem respiration activity recorded in C4 roots. However, the biphasic effect of SP on inspiratory burst rate seems to be also defined by the balance in activity of other SP-sensitive systems and neurones in the respiratory network in the brainstem and spinal cord, which can modify the activity of medullary respiratory rhythm generator.

Self-phase modulation and two-photon absorption imaging of cells and active neurons

NASA Astrophysics Data System (ADS)

Fischer, Martin C.; Liu, Henry; Piletic, Ivan R.; Ye, Tong; Yasuda, Ryohei; Warren, Warren S.

2007-02-01

Even though multi-photon fluorescence microscopy offers higher resolution and better penetration depth than traditional fluorescence microscopy, its use is restricted to the detection of molecules that fluoresce. Two-photon absorption (TPA) imaging can provide contrast in non-fluorescent molecules while retaining the high resolution and sectioning capabilities of nonlinear imaging modalities. In the long-wavelength water window, tissue TPA is dominated by the endogenous molecules melanin and hemoglobin with an almost complete absence of endogenous two-photon fluorescence. A complementary nonlinear contrast mechanism is self-phase modulation (SPM), which can provide intrinsic signatures that can depend on local tissue anisotropy, chemical environment, or other structural properties. We have developed a spectral hole refilling measurement technique for TPA and SPM measurements using shaped ultrafast laser pulses. Here we report on a microscopy setup to simultaneously acquire 3D, high-resolution TPA and SPM images. We have acquired data in mounted B16 melanoma cells with very modest laser power levels. We will also discuss the possible application of this measurement technique to neuronal imaging. Since SPM is sensitive to material structure we can expect SPM properties of neurons to change during neuronal firing. Using our hole-refilling technique we have now demonstrated strong novel intrinsic nonlinear signatures of neuronal activation in a hippocampal brain slice. The observed changes in nonlinear signal upon collective activation were up to factors of two, unlike other intrinsic optical signal changes on the percent level. These results show that TPA and SPM imaging can provide important novel functional contrast in tissue using very modest power levels suitable for in vivo applications.

A cephalic projection neuron involved in locomotion is dye coupled to the dopaminergic neural network in the medicinal leech.

PubMed

Crisp, Kevin M; Mesce, Karen A

2004-12-01

It is widely appreciated that the selection and modulation of locomotor circuits are dependent on the actions of higher-order projection neurons. In the leech, Hirudo medicinalis, locomotion is modulated by a number of cephalic projection neurons that descend from the subesophageal ganglion in the head. Specifically, descending brain interneuron Tr2 functions as a command-like neuron that can terminate or sometimes trigger fictive swimming. In this study, we demonstrate that Tr2 is dye coupled to the dopaminergic neural network distributed in the head brain. These findings represent the first anatomical evidence in support of dopamine (DA) playing a role in the modulation of locomotion in the leech. In addition, we have determined that bath application of DA to the brain and entire nerve cord reliably and rapidly terminates swimming in all preparations exhibiting fictive swimming. By contrast, DA application to nerve cords expressing ongoing fictive crawling does not inhibit this motor rhythm. Furthermore, we show that Tr2 receives rhythmic feedback from the crawl central pattern generator. For example, Tr2 receives inhibitory post-synaptic potentials during the elongation phase of each crawl cycle. When crawling is not expressed, spontaneous inhibitory post-synaptic potentials in Tr2 correlate in time with spontaneous excitatory post-synaptic potentials in the CV motor neuron, a circular muscle excitor that bursts during the elongation phase of crawling. Our data are consistent with the idea that DA biases the nervous system to produce locomotion in the form of crawling.

Minimum energy control for in vitro neurons.

PubMed

Nabi, Ali; Stigen, Tyler; Moehlis, Jeff; Netoff, Theoden

2013-06-01

To demonstrate the applicability of optimal control theory for designing minimum energy charge-balanced input waveforms for single periodically-firing in vitro neurons from brain slices of Long-Evans rats. The method of control uses the phase model of a neuron and does not require prior knowledge of the neuron's biological details. The phase model of a neuron is a one-dimensional model that is characterized by the neuron's phase response curve (PRC), a sensitivity measure of the neuron to a stimulus applied at different points in its firing cycle. The PRC for each neuron is experimentally obtained by measuring the shift in phase due to a short-duration pulse injected into the periodically-firing neuron at various phase values. Based on the measured PRC, continuous-time, charge-balanced, minimum energy control waveforms have been designed to regulate the next firing time of the neuron upon application at the onset of an action potential. The designed waveforms can achieve the inter-spike-interval regulation for in vitro neurons with energy levels that are lower than those of conventional monophasic pulsatile inputs of past studies by at least an order of magnitude. They also provide the advantage of being charge-balanced. The energy efficiency of these waveforms is also shown by performing several supporting simulations that compare the performance of the designed waveforms against that of phase shuffled surrogate inputs, variants of the minimum energy waveforms obtained from suboptimal PRCs, as well as pulsatile stimuli that are applied at the point of maximum PRC. It was found that the minimum energy waveforms perform better than all other stimuli both in terms of control and in the amount of energy used. Specifically, it was seen that these charge-balanced waveforms use at least an order of magnitude less energy than conventional monophasic pulsatile stimuli. The significance of this work is that it uses concepts from the theory of optimal control and introduces a novel approach in designing minimum energy charge-balanced input waveforms for neurons that are robust to noise and implementable in electrophysiological experiments.

Hydrocode and Molecular Dynamics modelling of uniaxial shock wave experiments on Silicon

NASA Astrophysics Data System (ADS)

Stubley, Paul; McGonegle, David; Patel, Shamim; Suggit, Matthew; Wark, Justin; Higginbotham, Andrew; Comley, Andrew; Foster, John; Rothman, Steve; Eggert, Jon; Kalantar, Dan; Smith, Ray

2015-06-01

Recent experiments have provided further evidence that the response of silicon to shock compression has anomalous properties, not described by the usual two-wave elastic-plastic response. A recent experimental campaign on the Orion laser in particular has indicated a complex multi-wave response. While Molecular Dynamics (MD) simulations can offer a detailed insight into the response of crystals to uniaxial compression, they are extremely computationally expensive. For this reason, we are adapting a simple quasi-2D hydrodynamics code to capture phase change under uniaxial compression, and the intervening mixed phase region, keeping track of the stresses and strains in each of the phases. This strain information is of such importance because a large number of shock experiments use diffraction as a key diagnostic, and these diffraction patterns depend solely on the elastic strains in the sample. We present here a comparison of the new hydrodynamics code with MD simulations, and show that the simulated diffraction taken from the code agrees qualitatively with measured diffraction from our recent Orion campaign.

Phasic Firing in Vasopressin Cells: Understanding Its Functional Significance through Computational Models

PubMed Central

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

Correlated activity supports efficient cortical processing

PubMed Central

Hung, Chou P.; Cui, Ding; Chen, Yueh-peng; Lin, Chia-pei; Levine, Matthew R.

2015-01-01

Visual recognition is a computational challenge that is thought to occur via efficient coding. An important concept is sparseness, a measure of coding efficiency. The prevailing view is that sparseness supports efficiency by minimizing redundancy and correlations in spiking populations. Yet, we recently reported that “choristers”, neurons that behave more similarly (have correlated stimulus preferences and spontaneous coincident spiking), carry more generalizable object information than uncorrelated neurons (“soloists”) in macaque inferior temporal (IT) cortex. The rarity of choristers (as low as 6% of IT neurons) indicates that they were likely missed in previous studies. Here, we report that correlation strength is distinct from sparseness (choristers are not simply broadly tuned neurons), that choristers are located in non-granular output layers, and that correlated activity predicts human visual search efficiency. These counterintuitive results suggest that a redundant correlational structure supports efficient processing and behavior. PMID:25610392

Differences in the emergent coding properties of cortical and striatal ensembles

PubMed Central

Ma, L.; Hyman, J.M.; Lindsay, A.J.; Phillips, A.G.; Seamans, J.K.

2016-01-01

The function of a given brain region is often defined by the coding properties of its individual neurons, yet how this information is combined at the ensemble level is an equally important consideration. In the present study, multiple neurons from the anterior cingulate cortex (ACC) and the dorsal striatum (DS) were recorded simultaneously as rats performed different sequences of the same three actions. Sequence and lever decoding was remarkably similar on a per-neuron basis in the two regions. At the ensemble level, sequence-specific representations in the DS appeared synchronously but transiently along with the representation of lever location, while these two streams of information appeared independently and asynchronously in the ACC. As a result the ACC achieved superior ensemble decoding accuracy overall. Thus, the manner in which information was combined across neurons in an ensemble determined the functional separation of the ACC and DS on this task. PMID:24974796