Distributed Representation of Visual Objects by Single Neurons in the Human Brain
Valdez, André B.; Papesh, Megan H.; Treiman, David M.; Smith, Kris A.; Goldinger, Stephen D.
2015-01-01
It remains unclear how single neurons in the human brain represent whole-object visual stimuli. While recordings in both human and nonhuman primates have shown distributed representations of objects (many neurons encoding multiple objects), recordings of single neurons in the human medial temporal lobe, taken as subjects' discriminated objects during multiple presentations, have shown gnostic representations (single neurons encoding one object). Because some studies suggest that repeated viewing may enhance neural selectivity for objects, we had human subjects discriminate objects in a single, more naturalistic viewing session. We found that, across 432 well isolated neurons recorded in the hippocampus and amygdala, the average fraction of objects encoded was 26%. We also found that more neurons encoded several objects versus only one object in the hippocampus (28 vs 18%, p < 0.001) and in the amygdala (30 vs 19%, p < 0.001). Thus, during realistic viewing experiences, typical neurons in the human medial temporal lobe code for a considerable range of objects, across multiple semantic categories. PMID:25834044
Distributed representation of visual objects by single neurons in the human brain.
Valdez, André B; Papesh, Megan H; Treiman, David M; Smith, Kris A; Goldinger, Stephen D; Steinmetz, Peter N
2015-04-01
It remains unclear how single neurons in the human brain represent whole-object visual stimuli. While recordings in both human and nonhuman primates have shown distributed representations of objects (many neurons encoding multiple objects), recordings of single neurons in the human medial temporal lobe, taken as subjects' discriminated objects during multiple presentations, have shown gnostic representations (single neurons encoding one object). Because some studies suggest that repeated viewing may enhance neural selectivity for objects, we had human subjects discriminate objects in a single, more naturalistic viewing session. We found that, across 432 well isolated neurons recorded in the hippocampus and amygdala, the average fraction of objects encoded was 26%. We also found that more neurons encoded several objects versus only one object in the hippocampus (28 vs 18%, p < 0.001) and in the amygdala (30 vs 19%, p < 0.001). Thus, during realistic viewing experiences, typical neurons in the human medial temporal lobe code for a considerable range of objects, across multiple semantic categories. Copyright © 2015 the authors 0270-6474/15/355180-07$15.00/0.
Kashiwayanagi, M; Shimano, K; Kurihara, K
1996-11-04
The responses of single bullfrog olfactory neurons to various odorants were measured with the whole-cell patch clamp which offers direct information on cellular events and with the ciliary recording technique to obtain stable quantitative data from many neurons. A large portion of single olfactory neurons (about 64% and 79% in the whole-cell recording and in the ciliary recording, respectively) responded to many odorants with quite diverse molecular structures, including both odorants previously indicated to be cAMP-dependent (increasing) and independent odorants. One odorant elicited a response in many cells; e.g. hedione and citralva elicited the response in 100% and 92% of total neurons examined with the ciliary recording technique. To confirm that a single neuron carries different receptors or transduction pathways, the cross-adaptation technique was applied to single neurons. Application of hedione to a single neuron after desensitization of the current in response to lyral or citralva induced an inward current with a similar magnitude to that applied alone. It was suggested that most single olfactory neurons carry multiple receptors and at least dual transduction pathways.
Kuramoto, Eriko; Pan, Shixiu; Furuta, Takahiro; Tanaka, Yasuhiro R; Iwai, Haruki; Yamanaka, Atsushi; Ohno, Sachi; Kaneko, Takeshi; Goto, Tetsuya; Hioki, Hiroyuki
2017-01-01
The prefrontal cortex has an important role in a variety of cognitive and executive processes, and is generally defined by its reciprocal connections with the mediodorsal thalamic nucleus (MD). The rat MD is mainly subdivided into three segments, the medial (MDm), central (MDc), and lateral (MDl) divisions, on the basis of the cytoarchitecture and chemoarchitecture. The MD segments are known to topographically project to multiple prefrontal areas at the population level: the MDm mainly to the prelimbic, infralimbic, and agranular insular areas; the MDc to the orbital and agranular insular areas; and the MDl to the prelimbic and anterior cingulate areas. However, it is unknown whether individual MD neurons project to single or multiple prefrontal cortical areas. In the present study, we visualized individual MD neurons with Sindbis virus vectors, and reconstructed whole structures of MD neurons. While the main cortical projection targets of MDm, MDc, and MDl neurons were generally consistent with those of previous results, it was found that individual MD neurons sent their axon fibers to multiple prefrontal areas, and displayed various projection patterns in the target areas. Furthermore, the axons of single MD neurons were not homogeneously spread, but were rather distributed to form patchy axon arbors approximately 1 mm in diameter. The multiple-area projections and patchy axon arbors of single MD neurons might be able to coactivate cortical neuron groups in distant prefrontal areas simultaneously. Furthermore, considerable heterogeneity of the projection patterns is likely, to recruit the different sets of cortical neurons, and thus contributes to a variety of prefrontal functions. J. Comp. Neurol. 525:166-185, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Recording large-scale neuronal ensembles with silicon probes in the anesthetized rat.
Schjetnan, Andrea Gomez Palacio; Luczak, Artur
2011-10-19
Large scale electrophysiological recordings from neuronal ensembles offer the opportunity to investigate how the brain orchestrates the wide variety of behaviors from the spiking activity of its neurons. One of the most effective methods to monitor spiking activity from a large number of neurons in multiple local neuronal circuits simultaneously is by using silicon electrode arrays. Action potentials produce large transmembrane voltage changes in the vicinity of cell somata. These output signals can be measured by placing a conductor in close proximity of a neuron. If there are many active (spiking) neurons in the vicinity of the tip, the electrode records combined signal from all of them, where contribution of a single neuron is weighted by its 'electrical distance'. Silicon probes are ideal recording electrodes to monitor multiple neurons because of a large number of recording sites (+64) and a small volume. Furthermore, multiple sites can be arranged over a distance of millimeters, thus allowing for the simultaneous recordings of neuronal activity in the various cortical layers or in multiple cortical columns (Fig. 1). Importantly, the geometrically precise distribution of the recording sites also allows for the determination of the spatial relationship of the isolated single neurons. Here, we describe an acute, large-scale neuronal recording from the left and right forelimb somatosensory cortex simultaneously in an anesthetized rat with silicon probes (Fig. 2).
Recording Large-scale Neuronal Ensembles with Silicon Probes in the Anesthetized Rat
Schjetnan, Andrea Gomez Palacio; Luczak, Artur
2011-01-01
Large scale electrophysiological recordings from neuronal ensembles offer the opportunity to investigate how the brain orchestrates the wide variety of behaviors from the spiking activity of its neurons. One of the most effective methods to monitor spiking activity from a large number of neurons in multiple local neuronal circuits simultaneously is by using silicon electrode arrays1-3. Action potentials produce large transmembrane voltage changes in the vicinity of cell somata. These output signals can be measured by placing a conductor in close proximity of a neuron. If there are many active (spiking) neurons in the vicinity of the tip, the electrode records combined signal from all of them, where contribution of a single neuron is weighted by its 'electrical distance'. Silicon probes are ideal recording electrodes to monitor multiple neurons because of a large number of recording sites (+64) and a small volume. Furthermore, multiple sites can be arranged over a distance of millimeters, thus allowing for the simultaneous recordings of neuronal activity in the various cortical layers or in multiple cortical columns (Fig. 1). Importantly, the geometrically precise distribution of the recording sites also allows for the determination of the spatial relationship of the isolated single neurons4. Here, we describe an acute, large-scale neuronal recording from the left and right forelimb somatosensory cortex simultaneously in an anesthetized rat with silicon probes (Fig. 2). PMID:22042361
Action Potential Waveform Variability Limits Multi-Unit Separation in Freely Behaving Rats
Stratton, Peter; Cheung, Allen; Wiles, Janet; Kiyatkin, Eugene; Sah, Pankaj; Windels, François
2012-01-01
Extracellular multi-unit recording is a widely used technique to study spontaneous and evoked neuronal activity in awake behaving animals. These recordings are done using either single-wire or mulitwire electrodes such as tetrodes. In this study we have tested the ability of single-wire electrodes to discriminate activity from multiple neurons under conditions of varying noise and neuronal cell density. Using extracellular single-unit recording, coupled with iontophoresis to drive cell activity across a wide dynamic range, we studied spike waveform variability, and explored systematic differences in single-unit spike waveform within and between brain regions as well as the influence of signal-to-noise ratio (SNR) on the similarity of spike waveforms. We also modelled spike misclassification for a range of cell densities based on neuronal recordings obtained at different SNRs. Modelling predictions were confirmed by classifying spike waveforms from multiple cells with various SNRs using a leading commercial spike-sorting system. Our results show that for single-wire recordings, multiple units can only be reliably distinguished under conditions of high recording SNR (≥4) and low neuronal density (≈20,000/ mm3). Physiological and behavioural changes, as well as technical limitations typical of awake animal preparations, reduce the accuracy of single-channel spike classification, resulting in serious classification errors. For SNR <4, the probability of misclassifying spikes approaches 100% in many cases. Our results suggest that in studies where the SNR is low or neuronal density is high, separation of distinct units needs to be evaluated with great caution. PMID:22719894
hamlet, a binary genetic switch between single- and multiple- dendrite neuron morphology.
Moore, Adrian W; Jan, Lily Yeh; Jan, Yuh Nung
2002-08-23
The dendritic morphology of neurons determines the number and type of inputs they receive. In the Drosophila peripheral nervous system (PNS), the external sensory (ES) neurons have a single nonbranched dendrite, whereas the lineally related multidendritic (MD) neurons have extensively branched dendritic arbors. We report that hamlet is a binary genetic switch between these contrasting morphological types. In hamlet mutants, ES neurons are converted to an MD fate, whereas ectopic hamlet expression in MD precursors results in transformation of MD neurons into ES neurons. Moreover, hamlet expression induced in MD neurons undergoing dendrite outgrowth drastically reduces arbor branching.
Multiplicative mixing of object identity and image attributes in single inferior temporal neurons.
Ratan Murty, N Apurva; Arun, S P
2018-04-03
Object recognition is challenging because the same object can produce vastly different images, mixing signals related to its identity with signals due to its image attributes, such as size, position, rotation, etc. Previous studies have shown that both signals are present in high-level visual areas, but precisely how they are combined has remained unclear. One possibility is that neurons might encode identity and attribute signals multiplicatively so that each can be efficiently decoded without interference from the other. Here, we show that, in high-level visual cortex, responses of single neurons can be explained better as a product rather than a sum of tuning for object identity and tuning for image attributes. This subtle effect in single neurons produced substantially better population decoding of object identity and image attributes in the neural population as a whole. This property was absent both in low-level vision models and in deep neural networks. It was also unique to invariances: when tested with two-part objects, neural responses were explained better as a sum than as a product of part tuning. Taken together, our results indicate that signals requiring separate decoding, such as object identity and image attributes, are combined multiplicatively in IT neurons, whereas signals that require integration (such as parts in an object) are combined additively. Copyright © 2018 the Author(s). Published by PNAS.
Li, Ruijie; Wang, Meng; Yao, Jiwei; Liang, Shanshan; Liao, Xiang; Yang, Mengke; Zhang, Jianxiong; Yan, Junan; Jia, Hongbo; Chen, Xiaowei; Li, Xingyi
2018-01-01
In vivo two-photon Ca 2+ imaging is a powerful tool for recording neuronal activities during perceptual tasks and has been increasingly applied to behaving animals for acute or chronic experiments. However, the auditory cortex is not easily accessible to imaging because of the abundant temporal muscles, arteries around the ears and their lateral locations. Here, we report a protocol for two-photon Ca 2+ imaging in the auditory cortex of head-fixed behaving mice. By using a custom-made head fixation apparatus and a head-rotated fixation procedure, we achieved two-photon imaging and in combination with targeted cell-attached recordings of auditory cortical neurons in behaving mice. Using synthetic Ca 2+ indicators, we recorded the Ca 2+ transients at multiple scales, including neuronal populations, single neurons, dendrites and single spines, in auditory cortex during behavior. Furthermore, using genetically encoded Ca 2+ indicators (GECIs), we monitored the neuronal dynamics over days throughout the process of associative learning. Therefore, we achieved two-photon functional imaging at multiple scales in auditory cortex of behaving mice, which extends the tool box for investigating the neural basis of audition-related behaviors.
Li, Ruijie; Wang, Meng; Yao, Jiwei; Liang, Shanshan; Liao, Xiang; Yang, Mengke; Zhang, Jianxiong; Yan, Junan; Jia, Hongbo; Chen, Xiaowei; Li, Xingyi
2018-01-01
In vivo two-photon Ca2+ imaging is a powerful tool for recording neuronal activities during perceptual tasks and has been increasingly applied to behaving animals for acute or chronic experiments. However, the auditory cortex is not easily accessible to imaging because of the abundant temporal muscles, arteries around the ears and their lateral locations. Here, we report a protocol for two-photon Ca2+ imaging in the auditory cortex of head-fixed behaving mice. By using a custom-made head fixation apparatus and a head-rotated fixation procedure, we achieved two-photon imaging and in combination with targeted cell-attached recordings of auditory cortical neurons in behaving mice. Using synthetic Ca2+ indicators, we recorded the Ca2+ transients at multiple scales, including neuronal populations, single neurons, dendrites and single spines, in auditory cortex during behavior. Furthermore, using genetically encoded Ca2+ indicators (GECIs), we monitored the neuronal dynamics over days throughout the process of associative learning. Therefore, we achieved two-photon functional imaging at multiple scales in auditory cortex of behaving mice, which extends the tool box for investigating the neural basis of audition-related behaviors. PMID:29740289
Cytokines and cytokine networks target neurons to modulate long-term potentiation.
Prieto, G Aleph; Cotman, Carl W
2017-04-01
Cytokines play crucial roles in the communication between brain cells including neurons and glia, as well as in the brain-periphery interactions. In the brain, cytokines modulate long-term potentiation (LTP), a cellular correlate of memory. Whether cytokines regulate LTP by direct effects on neurons or by indirect mechanisms mediated by non-neuronal cells is poorly understood. Elucidating neuron-specific effects of cytokines has been challenging because most brain cells express cytokine receptors. Moreover, cytokines commonly increase the expression of multiple cytokines in their target cells, thus increasing the complexity of brain cytokine networks even after single-cytokine challenges. Here, we review evidence on both direct and indirect-mediated modulation of LTP by cytokines. We also describe novel approaches based on neuron- and synaptosome-enriched systems to identify cytokines able to directly modulate LTP, by targeting neurons and synapses. These approaches can test multiple samples in parallel, thus allowing the study of multiple cytokines simultaneously. Hence, a cytokine networks perspective coupled with neuron-specific analysis may contribute to delineation of maps of the modulation of LTP by cytokines. Copyright © 2017 Elsevier Ltd. All rights reserved.
Cytokines and cytokine networks target neurons to modulate long-term potentiation
Prieto, G. Aleph; Cotman, Carl W.
2017-01-01
Cytokines play crucial roles in the communication between brain cells including neurons and glia, as well as in the brain-periphery interactions. In the brain, cytokines modulate long-term potentiation (LTP), a cellular correlate of memory. Whether cytokines regulate LTP by direct effects on neurons or by indirect mechanisms mediated by non-neuronal cells is poorly understood. Elucidating neuron-specific effects of cytokines has been challenging because most brain cells express cytokine receptors. Moreover, cytokines commonly increase the expression of multiple cytokines in their target cells, thus increasing the complexity of brain cytokine networks even after single-cytokine challenges. Here, we review evidence on both direct and indirect-mediated modulation of LTP by cytokines. We also describe novel approaches based on neuron- and synaptosome-enriched systems to identify cytokines able to directly modulate LTP, by targeting neurons and synapses. These approaches can test multiple samples in parallel, thus allowing the study of multiple cytokines simultaneously. Hence, a cytokine networks perspective coupled with neuron-specific analysis may contribute to delineation of maps of the modulation of LTP by cytokines. PMID:28377062
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.
Developmental emergence of different forms of neuromodulation in Aplysia sensory neurons.
Marcus, E A; Carew, T J
1998-04-14
The capacity for neuromodulation and biophysical plasticity is a defining feature of most mature neuronal cell types. In several cases, modulation at the level of the individual neuron has been causally linked to changes in the functional output of a neuronal circuit and subsequent adaptive changes in the organism's behavioral responses. Understanding how such capacity for neuromodulation develops therefore may provide insights into the mechanisms both of neuronal development and learning and memory. We have examined the development of multiple forms of neuromodulation triggered by a common neurotransmitter, serotonin, in the pleural sensory neurons of Aplysia californica. We have found that multiple signaling cascades within a single neuron develop sequentially, with some being expressed only very late in development. In addition, our data suggest a model in which, within a single neuromodulatory pathway, the elements of the signaling cascade are developmentally expressed in a "retrograde" manner with the ionic channel that is modulated appearing early in development, functional elements in the second messenger cascade appearing later, and finally, coupling of the second messenger cascade to the serotonin receptor appearing quite late. These studies provide the characterization of the development of neuromodulation at the level of an identified cell type and offer insights into the potential roles of neuromodulatory processes in development and adult plasticity.
Periodic activation function and a modified learning algorithm for the multivalued neuron.
Aizenberg, Igor
2010-12-01
In this paper, we consider a new periodic activation function for the multivalued neuron (MVN). The MVN is a neuron with complex-valued weights and inputs/output, which are located on the unit circle. Although the MVN outperforms many other neurons and MVN-based neural networks have shown their high potential, the MVN still has a limited capability of learning highly nonlinear functions. A periodic activation function, which is introduced in this paper, makes it possible to learn nonlinearly separable problems and non-threshold multiple-valued functions using a single multivalued neuron. We call this neuron a multivalued neuron with a periodic activation function (MVN-P). The MVN-Ps functionality is much higher than that of the regular MVN. The MVN-P is more efficient in solving various classification problems. A learning algorithm based on the error-correction rule for the MVN-P is also presented. It is shown that a single MVN-P can easily learn and solve those benchmark classification problems that were considered unsolvable using a single neuron. It is also shown that a universal binary neuron, which can learn nonlinearly separable Boolean functions, and a regular MVN are particular cases of the MVN-P.
Ito, Shinya; Hansen, Michael E.; Heiland, Randy; Lumsdaine, Andrew; Litke, Alan M.; Beggs, John M.
2011-01-01
Transfer entropy (TE) is an information-theoretic measure which has received recent attention in neuroscience for its potential to identify effective connectivity between neurons. Calculating TE for large ensembles of spiking neurons is computationally intensive, and has caused most investigators to probe neural interactions at only a single time delay and at a message length of only a single time bin. This is problematic, as synaptic delays between cortical neurons, for example, range from one to tens of milliseconds. In addition, neurons produce bursts of spikes spanning multiple time bins. To address these issues, here we introduce a free software package that allows TE to be measured at multiple delays and message lengths. To assess performance, we applied these extensions of TE to a spiking cortical network model (Izhikevich, 2006) with known connectivity and a range of synaptic delays. For comparison, we also investigated single-delay TE, at a message length of one bin (D1TE), and cross-correlation (CC) methods. We found that D1TE could identify 36% of true connections when evaluated at a false positive rate of 1%. For extended versions of TE, this dramatically improved to 73% of true connections. In addition, the connections correctly identified by extended versions of TE accounted for 85% of the total synaptic weight in the network. Cross correlation methods generally performed more poorly than extended TE, but were useful when data length was short. A computational performance analysis demonstrated that the algorithm for extended TE, when used on currently available desktop computers, could extract effective connectivity from 1 hr recordings containing 200 neurons in ∼5 min. We conclude that extending TE to multiple delays and message lengths improves its ability to assess effective connectivity between spiking neurons. These extensions to TE soon could become practical tools for experimentalists who record hundreds of spiking neurons. PMID:22102894
Holographic 3D multi-spot two-photon excitation for fast optical stimulation in brain
NASA Astrophysics Data System (ADS)
Takiguchi, Yu; Toyoda, Haruyoshi
2017-04-01
We report here a holographic high speed accessing microscope of sensory-driven synaptic activity across all inputs to single living neurons in the context of the intact cerebral cortex. This system is based on holographic multiple beam generation with spatial light modulator, we have demonstrated performance of the holographic excitation efficiency in several in vitro prototype system. 3D weighted iterative Fourier Transform method using the Ewald sphere in consideration of calculation speed has been adopted; multiple locations can be patterned in 3D with single hologram. Standard deviation of intensities of spots are still large due to the aberration of the system and/or hologram calculation, we successfully excited multiple locations of neurons in living mouse brain to monitor the calcium signals.
Antkowiak, Maciej; Torres-Mapa, Maria Leilani; Witts, Emily C.; Miles, Gareth B.; Dholakia, Kishan; Gunn-Moore, Frank J.
2013-01-01
A prevailing problem in neuroscience is the fast and targeted delivery of DNA into selected neurons. The development of an appropriate methodology would enable the transfection of multiple genes into the same cell or different genes into different neighboring cells as well as rapid cell selective functionalization of neurons. Here, we show that optimized femtosecond optical transfection fulfills these requirements. We also demonstrate successful optical transfection of channelrhodopsin-2 in single selected neurons. We extend the functionality of this technique for wider uptake by neuroscientists by using fast three-dimensional laser beam steering enabling an image-guided “point-and-transfect” user-friendly transfection of selected cells. A sub-second transfection timescale per cell makes this method more rapid by at least two orders of magnitude when compared to alternative single-cell transfection techniques. This novel technology provides the ability to carry out large-scale cell selective genetic studies on neuronal ensembles and perform rapid genetic programming of neural circuits. PMID:24257461
Antkowiak, Maciej; Torres-Mapa, Maria Leilani; Witts, Emily C; Miles, Gareth B; Dholakia, Kishan; Gunn-Moore, Frank J
2013-11-21
A prevailing problem in neuroscience is the fast and targeted delivery of DNA into selected neurons. The development of an appropriate methodology would enable the transfection of multiple genes into the same cell or different genes into different neighboring cells as well as rapid cell selective functionalization of neurons. Here, we show that optimized femtosecond optical transfection fulfills these requirements. We also demonstrate successful optical transfection of channelrhodopsin-2 in single selected neurons. We extend the functionality of this technique for wider uptake by neuroscientists by using fast three-dimensional laser beam steering enabling an image-guided "point-and-transfect" user-friendly transfection of selected cells. A sub-second transfection timescale per cell makes this method more rapid by at least two orders of magnitude when compared to alternative single-cell transfection techniques. This novel technology provides the ability to carry out large-scale cell selective genetic studies on neuronal ensembles and perform rapid genetic programming of neural circuits.
Nonlinear multiplicative dendritic integration in neuron and network models
Zhang, Danke; Li, Yuanqing; Rasch, Malte J.; Wu, Si
2013-01-01
Neurons receive inputs from thousands of synapses distributed across dendritic trees of complex morphology. It is known that dendritic integration of excitatory and inhibitory synapses can be highly non-linear in reality and can heavily depend on the exact location and spatial arrangement of inhibitory and excitatory synapses on the dendrite. Despite this known fact, most neuron models used in artificial neural networks today still only describe the voltage potential of a single somatic compartment and assume a simple linear summation of all individual synaptic inputs. We here suggest a new biophysical motivated derivation of a single compartment model that integrates the non-linear effects of shunting inhibition, where an inhibitory input on the route of an excitatory input to the soma cancels or “shunts” the excitatory potential. In particular, our integration of non-linear dendritic processing into the neuron model follows a simple multiplicative rule, suggested recently by experiments, and allows for strict mathematical treatment of network effects. Using our new formulation, we further devised a spiking network model where inhibitory neurons act as global shunting gates, and show that the network exhibits persistent activity in a low firing regime. PMID:23658543
Richter, Craig G; Thompson, William H; Bosman, Conrado A; Fries, Pascal
2015-07-01
The quantification of covariance between neuronal activities (functional connectivity) requires the observation of correlated changes and therefore multiple observations. The strength of such neuronal correlations may itself undergo moment-by-moment fluctuations, which might e.g. lead to fluctuations in single-trial metrics such as reaction time (RT), or may co-fluctuate with the correlation between activity in other brain areas. Yet, quantifying the relation between moment-by-moment co-fluctuations in neuronal correlations is precluded by the fact that neuronal correlations are not defined per single observation. The proposed solution quantifies this relation by first calculating neuronal correlations for all leave-one-out subsamples (i.e. the jackknife replications of all observations) and then correlating these values. Because the correlation is calculated between jackknife replications, we address this approach as jackknife correlation (JC). First, we demonstrate the equivalence of JC to conventional correlation for simulated paired data that are defined per observation and therefore allow the calculation of conventional correlation. While the JC recovers the conventional correlation precisely, alternative approaches, like sorting-and-binning, result in detrimental effects of the analysis parameters. We then explore the case of relating two spectral correlation metrics, like coherence, that require multiple observation epochs, where the only viable alternative analysis approaches are based on some form of epoch subdivision, which results in reduced spectral resolution and poor spectral estimators. We show that JC outperforms these approaches, particularly for short epoch lengths, without sacrificing any spectral resolution. Finally, we note that the JC can be applied to relate fluctuations in any smooth metric that is not defined on single observations. Copyright © 2015. Published by Elsevier Inc.
Action potential propagation recorded from single axonal arbors using multi-electrode arrays.
Tovar, Kenneth R; Bridges, Daniel C; Wu, Bian; Randall, Connor; Audouard, Morgane; Jang, Jiwon; Hansma, Paul K; Kosik, Kenneth S
2018-04-11
We report the presence of co-occurring extracellular action potentials (eAPs) from cultured mouse hippocampal neurons among groups of planar electrodes on multi-electrode arrays (MEAs). The invariant sequences of eAPs among co-active electrode groups, repeated co-occurrences and short inter-electrode latencies are consistent with action potential propagation in unmyelinated axons. Repeated eAP co-detection by multiple electrodes was widespread in all our data records. Co-detection of eAPs confirms they result from the same neuron and allows these eAPs to be isolated from all other spikes independently of spike sorting algorithms. We averaged co-occurring events and revealed additional electrodes with eAPs that would otherwise be below detection threshold. We used these eAP cohorts to explore the temperature sensitivity of action potential propagation and the relationship between voltage-gated sodium channel density and propagation velocity. The sequence of eAPs among co-active electrodes 'fingerprints' neurons giving rise to these events and identifies them within neuronal ensembles. We used this property and the non-invasive nature of extracellular recording to monitor changes in excitability at multiple points in single axonal arbors simultaneously over several hours, demonstrating independence of axonal segments. Over several weeks, we recorded changes in inter-electrode propagation latencies and ongoing changes in excitability in different regions of single axonal arbors. Our work illustrates how repeated eAP co-occurrences can be used to extract physiological data from single axons with low electrode density MEAs. However, repeated eAP co-occurrences leads to over-sampling spikes from single neurons and thus can confound traditional spike-train analysis.
Tools for probing local circuits: high-density silicon probes combined with optogenetics
Buzsáki, György; Stark, Eran; Berényi, Antal; Khodagholy, Dion; Kipke, Daryl R.; Yoon, Euisik; Wise, Kensall
2015-01-01
To understand how function arises from the interactions between neurons, it is necessary to use methods that allow the monitoring of brain activity at the single-neuron, single-spike level and the targeted manipulation of the diverse neuron types selectively in a closed-loop manner. Large-scale recordings of neuronal spiking combined with optogenetic perturbation of identified individual neurons has emerged as a suitable method for such tasks in behaving animals. To fully exploit the potential power of these methods, multiple steps of technical innovation are needed. We highlight the current state-of-the-art in electrophysiological recording methods, combined with optogenetics, and discuss directions for progress. In addition, we point to areas where rapid development is in progress and discuss topics where near-term improvements are possible and needed. PMID:25856489
Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level.
Bono, Jacopo; Clopath, Claudia
2017-09-26
Synaptic plasticity is thought to be the principal neuronal mechanism underlying learning. Models of plastic networks typically combine point neurons with spike-timing-dependent plasticity (STDP) as the learning rule. However, a point neuron does not capture the local non-linear processing of synaptic inputs allowed for by dendrites. Furthermore, experimental evidence suggests that STDP is not the only learning rule available to neurons. By implementing biophysically realistic neuron models, we study how dendrites enable multiple synaptic plasticity mechanisms to coexist in a single cell. In these models, we compare the conditions for STDP and for synaptic strengthening by local dendritic spikes. We also explore how the connectivity between two cells is affected by these plasticity rules and by different synaptic distributions. Finally, we show that how memory retention during associative learning can be prolonged in networks of neurons by including dendrites.Synaptic plasticity is the neuronal mechanism underlying learning. Here the authors construct biophysical models of pyramidal neurons that reproduce observed plasticity gradients along the dendrite and show that dendritic spike dependent LTP which is predominant in distal sections can prolong memory retention.
A high-throughput method for generating uniform microislands for autaptic neuronal cultures
Sgro, Allyson E.; Nowak, Amy L.; Austin, Naola S.; Custer, Kenneth L.; Allen, Peter B.; Chiu, Daniel T.; Bajjalieh, Sandra M.
2013-01-01
Generating microislands of culture substrate on coverslips by spray application of poly-D lysine is a commonly used method for culturing isolated neurons that form self (autaptic) synapses. This preparation has multiple advantages for studying synaptic transmission in isolation; however, generating microislands by spraying produces islands of non-uniform size and thus cultures vary widely in the number of islands containing single neurons. To address these problems, we developed a high-throughput method for reliably generating uniformly-shaped microislands of culture substrate. Stamp molds formed of poly(dimethylsiloxane) (PDMS) were fabricated with arrays of circles and used to generate stamps made of 9.2% agarose. The agarose stamps were capable of loading sufficient poly D-lysine and collagen dissolved in acetic acid to rapidly generate coverslips containing at least 64 microislands per coverslip. When hippocampal neurons were cultured on these coverslips, there were significantly more single-neuron islands per coverslip. We noted that single neurons tended to form one of three distinct neurite-arbor morphologies, which varied with island size and the location of the cell body on the island. To our surprise, the number of synapses per autaptic neuron did not correlate with arbor shape or island size, suggesting that other factors regulate the number of synapses formed by isolated neurons. The stamping method we report can be used to increase the number of single-neuron islands per culture and aid in the rapid visualization of microislands. PMID:21515305
Kennerley, Steven W.; Wallis, Jonathan D.
2009-01-01
Damage to the frontal lobe can cause severe decision-making impairments. A mechanism that may underlie this is that neurons in the frontal cortex encode many variables that contribute to the valuation of a choice, such as its costs, benefits and probability of success. However, optimal decision-making requires that one considers these variables, not only when faced with the choice, but also when evaluating the outcome of the choice, in order to adapt future behaviour appropriately. To examine the role of the frontal cortex in encoding the value of different choice outcomes, we simultaneously recorded the activity of multiple single neurons in the anterior cingulate cortex (ACC), orbitofrontal cortex (OFC) and lateral prefrontal cortex (LPFC) while subjects evaluated the outcome of choices involving manipulations of probability, payoff and cost. Frontal neurons encoded many of the parameters that enabled the calculation of the value of these variables, including the onset and offset of reward and the amount of work performed, and often encoded the value of outcomes across multiple decision variables. In addition, many neurons encoded both the predicted outcome during the choice phase of the task as well as the experienced outcome in the outcome phase of the task. These patterns of selectivity were more prevalent in ACC relative to OFC and LPFC. These results support a role for the frontal cortex, principally ACC, in selecting between choice alternatives and evaluating the outcome of that selection thereby ensuring that choices are optimal and adaptive. PMID:19453638
Szabó, István; Hormay, Edina; Csetényi, Bettina; Nagy, Bernadett; Lénárd, László; Karádi, Zoltán
2018-02-01
Multiple functional attributes of glucose-monitoring neurons in the medial orbitofrontal (ventrolateral prefrontal) cortex. NEUROSCI BIOBEHAV REV 73(1) XXX-XXX, 2017.- Special chemosensory cells, the glucose-monitoring (GM) neurons, reportedly involved in the central feeding control, exist in the medial orbitofrontal (ventrolateral prefrontal) cortex (mVLPFC). Electrophysiological, metabolic and behavioral studies reveal complex functional attributes of these cells and raise their homeostatic significance. Single neuron recordings, by means of the multibarreled microelectrophoretic technique, elucidate differential sensitivities of limbic forebrain neurons in the rat and the rhesus monkey to glucose and other chemicals, whereas gustatory stimulations demonstrate their distinct taste responsiveness. Metabolic examinations provide evidence for alteration of blood glucose level in glucose tolerance test and elevation of plasma triglyceride concentration after destruction of the local GM cells by streptozotocin (STZ). In behavioral studies, STZ microinjection into the mVLPFC fails to interfere with the acquisition of saccharin conditioned taste avoidance, does cause, however, taste perception deficit in taste reactivity tests. Multiple functional attributes of GM neurons in the mVLPFC, within the frame of the hierarchically organized central GM neuronal network, appear to play important role in the maintenance of the homeostatic balance. Copyright © 2017 Elsevier Ltd. All rights reserved.
Neuron specific metabolic adaptations following multi-day exposures to oxygen glucose deprivation.
Zeiger, Stephanie L H; McKenzie, Jennifer R; Stankowski, Jeannette N; Martin, Jacob A; Cliffel, David E; McLaughlin, BethAnn
2010-11-01
Prior exposure to sub toxic insults can induce a powerful endogenous neuroprotective program known as ischemic preconditioning. Current models typically rely on a single stress episode to induce neuroprotection whereas the clinical reality is that patients may experience multiple transient ischemic attacks (TIAs) prior to suffering a stroke. We sought to develop a neuron-enriched preconditioning model using multiple oxygen glucose deprivation (OGD) episodes to assess the endogenous protective mechanisms neurons implement at the metabolic and cellular level. We found that neurons exposed to a five minute period of glucose deprivation recovered oxygen utilization and lactate production using novel microphysiometry techniques. Using the non-toxic and energetically favorable five minute exposure, we developed a preconditioning paradigm where neurons are exposed to this brief OGD for three consecutive days. These cells experienced a 45% greater survival following an otherwise lethal event and exhibited a longer lasting window of protection in comparison to our previous in vitro preconditioning model using a single stress. As in other models, preconditioned cells exhibited mild caspase activation, an increase in oxidized proteins and a requirement for reactive oxygen species for neuroprotection. Heat shock protein 70 was upregulated during preconditioning, yet the majority of this protein was released extracellularly. We believe coupling this neuron-enriched multi-day model with microphysiometry will allow us to assess neuronal specific real-time metabolic adaptations necessary for preconditioning. Copyright © 2010 Elsevier B.V. All rights reserved.
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
A real-time hybrid neuron network for highly parallel cognitive systems.
Christiaanse, Gerrit Jan; Zjajo, Amir; Galuzzi, Carlo; van Leuken, Rene
2016-08-01
For comprehensive understanding of how neurons communicate with each other, new tools need to be developed that can accurately mimic the behaviour of such neurons and neuron networks under `real-time' constraints. In this paper, we propose an easily customisable, highly pipelined, neuron network design, which executes optimally scheduled floating-point operations for maximal amount of biophysically plausible neurons per FPGA family type. To reduce the required amount of resources without adverse effect on the calculation latency, a single exponent instance is used for multiple neuron calculation operations. Experimental results indicate that the proposed network design allows the simulation of up to 1188 neurons on Virtex7 (XC7VX550T) device in brain real-time yielding a speed-up of x12.4 compared to the state-of-the art.
Das, Mainak; Bhargava, Neelima; Bhalkikar, Abhijeet; Kang, Jung Fong; Hickman, James J
2008-01-01
The ability to culture functional adult mammalian spinal-cord neurons represents an important step in the understanding and treatment of a spectrum of neurological disorders including spinal cord injury. Previously, the limited functional recovery of these cells, as characterized by a diminished ability to initiate action potentials and to exhibit repetitive firing patterns, has arisen as a major impediment to their physiological relevance. In this report we demonstrate that single temporal doses of the neurotransmitters serotonin, glutamate (N-acetyl-DL-glutamic acid) and acetylcholine-chloride leads to the full electrophysiological functional recovery of adult mammalian spinal-cord neurons, when they are cultured under defined serum-free conditions. Approximately 60% of the neurons treated regained their electrophysiological signature, often firing single, double and, most importantly, multiple action potentials. PMID:18005959
Optimization Methods for Spiking Neurons and Networks
Russell, Alexander; Orchard, Garrick; Dong, Yi; Mihalaş, Ştefan; Niebur, Ernst; Tapson, Jonathan; Etienne-Cummings, Ralph
2011-01-01
Spiking neurons and spiking neural circuits are finding uses in a multitude of tasks such as robotic locomotion control, neuroprosthetics, visual sensory processing, and audition. The desired neural output is achieved through the use of complex neuron models, or by combining multiple simple neurons into a network. In either case, a means for configuring the neuron or neural circuit is required. Manual manipulation of parameters is both time consuming and non-intuitive due to the nonlinear relationship between parameters and the neuron’s output. The complexity rises even further as the neurons are networked and the systems often become mathematically intractable. In large circuits, the desired behavior and timing of action potential trains may be known but the timing of the individual action potentials is unknown and unimportant, whereas in single neuron systems the timing of individual action potentials is critical. In this paper, we automate the process of finding parameters. To configure a single neuron we derive a maximum likelihood method for configuring a neuron model, specifically the Mihalas–Niebur Neuron. Similarly, to configure neural circuits, we show how we use genetic algorithms (GAs) to configure parameters for a network of simple integrate and fire with adaptation neurons. The GA approach is demonstrated both in software simulation and hardware implementation on a reconfigurable custom very large scale integration chip. PMID:20959265
Modeling of synchronization behavior of bursting neurons at nonlinearly coupled dynamical networks.
Çakir, Yüksel
2016-01-01
Synchronization behaviors of bursting neurons coupled through electrical and dynamic chemical synapses are investigated. The Izhikevich model is used with random and small world network of bursting neurons. Various currents which consist of diffusive electrical and time-delayed dynamic chemical synapses are used in the simulations to investigate the influences of synaptic currents and couplings on synchronization behavior of bursting neurons. The effects of parameters, such as time delay, inhibitory synaptic strengths, and decay time on synchronization behavior are investigated. It is observed that in random networks with no delay, bursting synchrony is established with the electrical synapse alone, single spiking synchrony is observed with hybrid coupling. In small world network with no delay, periodic bursting behavior with multiple spikes is observed when only chemical and only electrical synapse exist. Single-spike and multiple-spike bursting are established with hybrid couplings. A decrease in the synchronization measure is observed with zero time delay, as the decay time is increased in random network. For synaptic delays which are above active phase period, synchronization measure increases with an increase in synaptic strength and time delay in small world network. However, in random network, it increases with only an increase in synaptic strength.
Kirschen, Gregory W.; Shen, Jia; Wang, Jia; Man, Guoming; Wu, Song
2017-01-01
The continuous addition of new dentate granule cells (DGCs), which is regulated exquisitely by brain activity, renders the hippocampus plastic. However, how neural circuits encode experiences to affect the addition of adult-born neurons remains unknown. Here, we used endoscopic Ca2+ imaging to track the real-time activity of individual DGCs in freely behaving mice. For the first time, we found that active DGCs responded to a novel experience by increasing their Ca2+ event frequency preferentially. This elevated activity, which we found to be associated with object exploration, returned to baseline by 1 h in the same environment, but could be dishabituated via introduction to a novel environment. To transition seamlessly between environments, we next established a freely controllable virtual reality system for unrestrained mice. We again observed increased firing of active neurons in a virtual enriched environment. Interestingly, multiple novel virtual experiences increased the number of newborn neurons accumulatively compared with a single experience. Finally, optogenetic silencing of existing DGCs during novel environmental exploration perturbed experience-induced neuronal addition. Our study shows that the adult brain conveys novel, enriched experiences to increase the addition of adult-born hippocampal neurons by increasing the firing of active DGCs. SIGNIFICANCE STATEMENT Adult brains are constantly reshaping themselves from synapses to circuits as we encounter novel experiences from moment to moment. Importantly, this reshaping includes the addition of newborn hippocampal neurons. However, it remains largely unknown how our circuits encode experience-induced brain activity to govern the addition of new hippocampal neurons. By coupling in vivo Ca2+ imaging of dentate granule neurons with a novel, unrestrained virtual reality system for rodents, we discovered that a new experience increased firing of active dentate granule neurons rapidly and robustly. Exploration in multiple novel virtual environments, compared with a single environment, promoted dentate activation and enhanced the addition of new hippocampal neurons accumulatively. Finally, silencing this activation optogenetically during novel experiences perturbed experience-induced neuronal addition. PMID:28373391
Ravits, John; Appel, Stanley; Baloh, Robert H; Barohn, Richard; Brooks, Benjamin Rix; Elman, Lauren; Floeter, Mary Kay; Henderson, Christopher; Lomen-Hoerth, Catherine; Macklis, Jeffrey D; McCluskey, Leo; Mitsumoto, Hiroshi; Przedborski, Serge; Rothstein, Jeffrey; Trojanowski, John Q; van den Berg, Leonard H; Ringel, Steven
2013-05-01
Amyotrophic lateral sclerosis (ALS) is characterized phenotypically by progressive weakness and neuropathologically by loss of motor neurons. Phenotypically, there is marked heterogeneity. Typical ALS has mixed upper motor neuron (UMN) and lower motor neuron (LMN) involvement. Primary lateral sclerosis has predominant UMN involvement. Progressive muscular atrophy has predominant LMN involvement. Bulbar and limb ALS have predominant regional involvement. Frontotemporal dementia has significant cognitive and behavioral involvement. These phenotypes can be so distinctive that they would seem to have differing biology. However, they cannot be distinguished, at least neuropathologically or genetically. In sporadic ALS (SALS), they are mostly characterized by ubiquitinated cytoplasmic inclusions of TDP-43. In familial ALS (FALS), where phenotypes are indistinguishable from SALS and similarly heterogeneous, each mutated gene has its own genetic and molecular signature. Overall, since the same phenotypes can have multiple causes including different gene mutations, there must be multiple molecular mechanisms causing ALS - and ALS is a syndrome. Since, however, multiple phenotypes can be caused by one single gene mutation, a single molecular mechanism can cause heterogeneity. What the mechanisms are remain unknown, but active propagation of the pathology neuroanatomically seems to be a principal component. Leading candidate mechanisms include RNA processing, cell-cell interactions between neurons and non-neuronal neighbors, focal seeding from a misfolded protein that has prion-like propagation, and fatal errors introduced during neurodevelopment of the motor system. If fundamental mechanisms could be identified and understood, ALS therapy could rationally target progression and stop the disease - a goal that seems increasingly achievable.
Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels
Afshar, Saeed; George, Libin; Tapson, Jonathan; van Schaik, André; Hamilton, Tara J.
2014-01-01
This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotemporal spike patterns. SKAN is the first proposed neuron model to investigate the effects of dynamic synapto-dendritic kernels and demonstrate their computational power even at the single neuron scale. The rule-set defining the neuron is simple: there are no complex mathematical operations such as normalization, exponentiation or even multiplication. The functionalities of SKAN emerge from the real-time interaction of simple additive and binary processes. Like a biological neuron, SKAN is robust to signal and parameter noise, and can utilize both in its operations. At the network scale neurons are locked in a race with each other with the fastest neuron to spike effectively “hiding” its learnt pattern from its neighbors. The robustness to noise, high speed, and simple building blocks not only make SKAN an interesting neuron model in computational neuroscience, but also make it ideal for implementation in digital and analog neuromorphic systems which is demonstrated through an implementation in a Field Programmable Gate Array (FPGA). Matlab, Python, and Verilog implementations of SKAN are available at: http://www.uws.edu.au/bioelectronics_neuroscience/bens/reproducible_research. PMID:25505378
Afshar, Saeed; George, Libin; Tapson, Jonathan; van Schaik, André; Hamilton, Tara J
2014-01-01
This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotemporal spike patterns. SKAN is the first proposed neuron model to investigate the effects of dynamic synapto-dendritic kernels and demonstrate their computational power even at the single neuron scale. The rule-set defining the neuron is simple: there are no complex mathematical operations such as normalization, exponentiation or even multiplication. The functionalities of SKAN emerge from the real-time interaction of simple additive and binary processes. Like a biological neuron, SKAN is robust to signal and parameter noise, and can utilize both in its operations. At the network scale neurons are locked in a race with each other with the fastest neuron to spike effectively "hiding" its learnt pattern from its neighbors. The robustness to noise, high speed, and simple building blocks not only make SKAN an interesting neuron model in computational neuroscience, but also make it ideal for implementation in digital and analog neuromorphic systems which is demonstrated through an implementation in a Field Programmable Gate Array (FPGA). Matlab, Python, and Verilog implementations of SKAN are available at: http://www.uws.edu.au/bioelectronics_neuroscience/bens/reproducible_research.
Functional interdependence of neurons in a single canine intrinsic cardiac ganglionated plexus
Thompson, G W; Collier, K; Ardell, J L; Kember, G; Armour, J A
2000-01-01
To determine the activity characteristics displayed by different subpopulations of neurons in a single intrinsic cardiac ganglionated plexus, the behaviour and co-ordination of activity generated by neurons in two loci of the right atrial ganglionated plexus (RAGP) were evaluated in 16 anaesthetized dogs during basal states as well as in response to increasing inputs from ventricular sensory neurites. These sub-populations of right atrial neurons received afferent inputs from sensory neurites in both ventricles that were responsive to local mechanical stimuli and the nitric oxide donor nitroprusside. Neurons in at least one RAGP locus were activated by epicardial application of veratridine, bradykinin, the β1-adrenoceptor agonist prenaterol or glutamate. Epicardial application of angiotensin II, the selective β2-adrenoceptor agonist terbutaline and selective α-adrenoceptor agonists elicited inconsistent neuronal responses. The activity generated by both populations of atrial neurons studied over 5 min periods during basal states displayed periodic coupled behaviour (cross-correlation coefficients of activities that reached, on average, 0·88 ± 0·03; range 0·71–1) for 15–30 s periods of time. These periods of coupled activity occurred every 30–50 s during basal states, as well as when neuronal activity was enhanced by chemical activation of their ventricular sensory inputs. These results indicate that neurons throughout one intrinsic cardiac ganglionated plexus receive inputs from mechano- and chemosensory neurites located in both ventricles. That such neurons respond to multiple chemical stimuli, including those liberated from adjacent adrenergic efferent nerve terminals, indicates the complexity of the integrative processing of information that occurs within the intrinsic cardiac nervous system. It is proposed that the interdependent activity displayed by populations of neurons in different regions of one intrinsic cardiac ganglionated plexus, responding as they do to multiple cardiac sensory inputs, forms the basis for integrated regional cardiac control. PMID:11060132
Neuronal Assemblies Evidence Distributed Interactions within a Tactile Discrimination Task in Rats
Deolindo, Camila S.; Kunicki, Ana C. B.; da Silva, Maria I.; Lima Brasil, Fabrício; Moioli, Renan C.
2018-01-01
Accumulating evidence suggests that neural interactions are distributed and relate to animal behavior, but many open questions remain. The neural assembly hypothesis, formulated by Hebb, states that synchronously active single neurons may transiently organize into functional neural circuits—neuronal assemblies (NAs)—and that would constitute the fundamental unit of information processing in the brain. However, the formation, vanishing, and temporal evolution of NAs are not fully understood. In particular, characterizing NAs in multiple brain regions over the course of behavioral tasks is relevant to assess the highly distributed nature of brain processing. In the context of NA characterization, active tactile discrimination tasks with rats are elucidative because they engage several cortical areas in the processing of information that are otherwise masked in passive or anesthetized scenarios. In this work, we investigate the dynamic formation of NAs within and among four different cortical regions in long-range fronto-parieto-occipital networks (primary somatosensory, primary visual, prefrontal, and posterior parietal cortices), simultaneously recorded from seven rats engaged in an active tactile discrimination task. Our results first confirm that task-related neuronal firing rate dynamics in all four regions is significantly modulated. Notably, a support vector machine decoder reveals that neural populations contain more information about the tactile stimulus than the majority of single neurons alone. Then, over the course of the task, we identify the emergence and vanishing of NAs whose participating neurons are shown to contain more information about animal behavior than randomly chosen neurons. Taken together, our results further support the role of multiple and distributed neurons as the functional unit of information processing in the brain (NA hypothesis) and their link to active animal behavior. PMID:29375324
Blitz, Dawn M; Pritchard, Amy E; Latimer, John K; Wakefield, Andrew T
2017-04-01
Adaptive changes in the output of neural circuits underlying rhythmic behaviors are relayed to muscles via motor neuron activity. Presynaptic and postsynaptic properties of neuromuscular junctions can impact the transformation from motor neuron activity to muscle response. Further, synaptic plasticity occurring on the time scale of inter-spike intervals can differ between multiple muscles innervated by the same motor neuron. In rhythmic behaviors, motor neuron bursts can elicit additional synaptic plasticity. However, it is unknown whether plasticity regulated by the longer time scale of inter-burst intervals also differs between synapses from the same neuron, and whether any such distinctions occur across a physiological activity range. To address these issues, we measured electrical responses in muscles innervated by a chewing circuit neuron, the lateral gastric (LG) motor neuron, in a well-characterized small motor system, the stomatogastric nervous system (STNS) of the Jonah crab, Cancer borealis In vitro and in vivo , sensory, hormonal and modulatory inputs elicit LG bursting consisting of inter-spike intervals of 50-250 ms and inter-burst intervals of 2-24 s. Muscles expressed similar facilitation measured with paired stimuli except at the shortest inter-spike interval. However, distinct decay time constants resulted in differences in temporal summation. In response to bursting activity, augmentation occurred to different extents and saturated at different inter-burst intervals. Further, augmentation interacted with facilitation, resulting in distinct intra-burst facilitation between muscles. Thus, responses of multiple target muscles diverge across a physiological activity range as a result of distinct synaptic properties sensitive to multiple time scales. © 2017. Published by The Company of Biologists Ltd.
Tuned normalization explains the size of attention modulations.
Ni, Amy M; Ray, Supratim; Maunsell, John H R
2012-02-23
The effect of attention on firing rates varies considerably within a single cortical area. The firing rate of some neurons is greatly modulated by attention while others are hardly affected. The reason for this variability across neurons is unknown. We found that the variability in attention modulation across neurons in area MT of macaques can be well explained by variability in the strength of tuned normalization across neurons. The presence of tuned normalization also explains a striking asymmetry in attention effects within neurons: when two stimuli are in a neuron's receptive field, directing attention to the preferred stimulus modulates firing rates more than directing attention to the nonpreferred stimulus. These findings show that much of the neuron-to-neuron variability in modulation of responses by attention depends on variability in the way the neurons process multiple stimuli, rather than differences in the influence of top-down signals related to attention. Copyright © 2012 Elsevier Inc. All rights reserved.
Beetz, M Jerome; Hechavarría, Julio C; Kössl, Manfred
2016-10-27
Bats orientate in darkness by listening to echoes from their biosonar calls, a behaviour known as echolocation. Recent studies showed that cortical neurons respond in a highly selective manner when stimulated with natural echolocation sequences that contain echoes from single targets. However, it remains unknown how cortical neurons process echolocation sequences containing echo information from multiple objects. In the present study, we used echolocation sequences containing echoes from three, two or one object separated in the space depth as stimuli to study neuronal activity in the bat auditory cortex. Neuronal activity was recorded with multi-electrode arrays placed in the dorsal auditory cortex, where neurons tuned to target-distance are found. Our results show that target-distance encoding neurons are mostly selective to echoes coming from the closest object, and that the representation of echo information from distant objects is selectively suppressed. This suppression extends over a large part of the dorsal auditory cortex and may override possible parallel processing of multiple objects. The presented data suggest that global cortical suppression might establish a cortical "default mode" that allows selectively focusing on close obstacle even without active attention from the animals.
Beetz, M. Jerome; Hechavarría, Julio C.; Kössl, Manfred
2016-01-01
Bats orientate in darkness by listening to echoes from their biosonar calls, a behaviour known as echolocation. Recent studies showed that cortical neurons respond in a highly selective manner when stimulated with natural echolocation sequences that contain echoes from single targets. However, it remains unknown how cortical neurons process echolocation sequences containing echo information from multiple objects. In the present study, we used echolocation sequences containing echoes from three, two or one object separated in the space depth as stimuli to study neuronal activity in the bat auditory cortex. Neuronal activity was recorded with multi-electrode arrays placed in the dorsal auditory cortex, where neurons tuned to target-distance are found. Our results show that target-distance encoding neurons are mostly selective to echoes coming from the closest object, and that the representation of echo information from distant objects is selectively suppressed. This suppression extends over a large part of the dorsal auditory cortex and may override possible parallel processing of multiple objects. The presented data suggest that global cortical suppression might establish a cortical “default mode” that allows selectively focusing on close obstacle even without active attention from the animals. PMID:27786252
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.
Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology
Fu, Tian-Ming; Hong, Guosong; Viveros, Robert D.; Zhou, Tao
2017-01-01
Implantable electrical probes have led to advances in neuroscience, brain−machine interfaces, and treatment of neurological diseases, yet they remain limited in several key aspects. Ideally, an electrical probe should be capable of recording from large numbers of neurons across multiple local circuits and, importantly, allow stable tracking of the evolution of these neurons over the entire course of study. Silicon probes based on microfabrication can yield large-scale, high-density recording but face challenges of chronic gliosis and instability due to mechanical and structural mismatch with the brain. Ultraflexible mesh electronics, on the other hand, have demonstrated negligible chronic immune response and stable long-term brain monitoring at single-neuron level, although, to date, it has been limited to 16 channels. Here, we present a scalable scheme for highly multiplexed mesh electronics probes to bridge the gap between scalability and flexibility, where 32 to 128 channels per probe were implemented while the crucial brain-like structure and mechanics were maintained. Combining this mesh design with multisite injection, we demonstrate stable 128-channel local field potential and single-unit recordings from multiple brain regions in awake restrained mice over 4 mo. In addition, the newly integrated mesh is used to validate stable chronic recordings in freely behaving mice. This scalable scheme for mesh electronics together with demonstrated long-term stability represent important progress toward the realization of ideal implantable electrical probes allowing for mapping and tracking single-neuron level circuit changes associated with learning, aging, and neurodegenerative diseases. PMID:29109247
Using Single Sensillum Recording to Detect Olfactory Neuron Responses of Bed Bugs to Semiochemicals.
Liu, Feng; Liu, Nannan
2016-01-18
The insect olfactory system plays an important role in detecting semiochemicals in the environment. In particular, the antennal sensilla which house single or multiple neurons inside, are considered to make the major contribution in responding to the chemical stimuli. By directly recording action potential in the olfactory sensillum after exposure to stimuli, single sensillum recording (SSR) technique provides a powerful approach for investigating the neural responses of insects to chemical stimuli. For the bed bug, which is a notorious human parasite, multiple types of olfactory sensillum have been characterized. In this study, we demonstrated neural responses of bed bug olfactory sensilla to two chemical stimuli and the dose-dependent responses to one of them using the SSR method. This approach enables researchers to conduct early screening for individual chemical stimuli on the bed bug olfactory sensilla, which would provide valuable information for the development of new bed bug attractants or repellents and benefits the bed bug control efforts.
Using Single Sensillum Recording to Detect Olfactory Neuron Responses of Bed Bugs to Semiochemicals
Liu, Feng; Liu, Nannan
2016-01-01
The insect olfactory system plays an important role in detecting semiochemicals in the environment. In particular, the antennal sensilla which house single or multiple neurons inside, are considered to make the major contribution in responding to the chemical stimuli. By directly recording action potential in the olfactory sensillum after exposure to stimuli, single sensillum recording (SSR) technique provides a powerful approach for investigating the neural responses of insects to chemical stimuli. For the bed bug, which is a notorious human parasite, multiple types of olfactory sensillum have been characterized. In this study, we demonstrated neural responses of bed bug olfactory sensilla to two chemical stimuli and the dose-dependent responses to one of them using the SSR method. This approach enables researchers to conduct early screening for individual chemical stimuli on the bed bug olfactory sensilla, which would provide valuable information for the development of new bed bug attractants or repellents and benefits the bed bug control efforts. PMID:26862929
Gong, Hui; Xu, Dongli; Yuan, Jing; Li, Xiangning; Guo, Congdi; Peng, Jie; Li, Yuxin; Schwarz, Lindsay A.; Li, Anan; Hu, Bihe; Xiong, Benyi; Sun, Qingtao; Zhang, Yalun; Liu, Jiepeng; Zhong, Qiuyuan; Xu, Tonghui; Zeng, Shaoqun; Luo, Qingming
2016-01-01
The precise annotation and accurate identification of neural structures are prerequisites for studying mammalian brain function. The orientation of neurons and neural circuits is usually determined by mapping brain images to coarse axial-sampling planar reference atlases. However, individual differences at the cellular level likely lead to position errors and an inability to orient neural projections at single-cell resolution. Here, we present a high-throughput precision imaging method that can acquire a co-localized brain-wide data set of both fluorescent-labelled neurons and counterstained cell bodies at a voxel size of 0.32 × 0.32 × 2.0 μm in 3 days for a single mouse brain. We acquire mouse whole-brain imaging data sets of multiple types of neurons and projections with anatomical annotation at single-neuron resolution. The results show that the simultaneous acquisition of labelled neural structures and cytoarchitecture reference in the same brain greatly facilitates precise tracing of long-range projections and accurate locating of nuclei. PMID:27374071
Diversity amongst trigeminal neurons revealed by high throughput single cell sequencing
Nguyen, Minh Q.; Wu, Youmei; Bonilla, Lauren S.; von Buchholtz, Lars J.
2017-01-01
The trigeminal ganglion contains somatosensory neurons that detect a range of thermal, mechanical and chemical cues and innervate unique sensory compartments in the head and neck including the eyes, nose, mouth, meninges and vibrissae. We used single-cell sequencing and in situ hybridization to examine the cellular diversity of the trigeminal ganglion in mice, defining thirteen clusters of neurons. We show that clusters are well conserved in dorsal root ganglia suggesting they represent distinct functional classes of somatosensory neurons and not specialization associated with their sensory targets. Notably, functionally important genes (e.g. the mechanosensory channel Piezo2 and the capsaicin gated ion channel Trpv1) segregate into multiple clusters and often are expressed in subsets of cells within a cluster. Therefore, the 13 genetically-defined classes are likely to be physiologically heterogeneous rather than highly parallel (i.e., redundant) lines of sensory input. Our analysis harnesses the power of single-cell sequencing to provide a unique platform for in silico expression profiling that complements other approaches linking gene-expression with function and exposes unexpected diversity in the somatosensory system. PMID:28957441
Bayguinov, Peter O; Ma, Yihe; Gao, Yu; Zhao, Xinyu; Jackson, Meyer B
2017-09-20
Genetically encoded voltage indicators create an opportunity to monitor electrical activity in defined sets of neurons as they participate in the complex patterns of coordinated electrical activity that underlie nervous system function. Taking full advantage of genetically encoded voltage indicators requires a generalized strategy for targeting the probe to genetically defined populations of cells. To this end, we have generated a mouse line with an optimized hybrid voltage sensor (hVOS) probe within a locus designed for efficient Cre recombinase-dependent expression. Crossing this mouse with Cre drivers generated double transgenics expressing hVOS probe in GABAergic, parvalbumin, and calretinin interneurons, as well as hilar mossy cells, new adult-born neurons, and recently active neurons. In each case, imaging in brain slices from male or female animals revealed electrically evoked optical signals from multiple individual neurons in single trials. These imaging experiments revealed action potentials, dynamic aspects of dendritic integration, and trial-to-trial fluctuations in response latency. The rapid time response of hVOS imaging revealed action potentials with high temporal fidelity, and enabled accurate measurements of spike half-widths characteristic of each cell type. Simultaneous recording of rapid voltage changes in multiple neurons with a common genetic signature offers a powerful approach to the study of neural circuit function and the investigation of how neural networks encode, process, and store information. SIGNIFICANCE STATEMENT Genetically encoded voltage indicators hold great promise in the study of neural circuitry, but realizing their full potential depends on targeting the sensor to distinct cell types. Here we present a new mouse line that expresses a hybrid optical voltage sensor under the control of Cre recombinase. Crossing this line with Cre drivers generated double-transgenic mice, which express this sensor in targeted cell types. In brain slices from these animals, single-trial hybrid optical voltage sensor recordings revealed voltage changes with submillisecond resolution in multiple neurons simultaneously. This imaging tool will allow for the study of the emergent properties of neural circuits and permit experimental tests of the roles of specific types of neurons in complex circuit activity. Copyright © 2017 the authors 0270-6474/17/379305-15$15.00/0.
Giugliano, Michele; La Camera, Giancarlo; Fusi, Stefano; Senn, Walter
2008-11-01
The response of a population of neurons to time-varying synaptic inputs can show a rich phenomenology, hardly predictable from the dynamical properties of the membrane's inherent time constants. For example, a network of neurons in a state of spontaneous activity can respond significantly more rapidly than each single neuron taken individually. Under the assumption that the statistics of the synaptic input is the same for a population of similarly behaving neurons (mean field approximation), it is possible to greatly simplify the study of neural circuits, both in the case in which the statistics of the input are stationary (reviewed in La Camera et al. in Biol Cybern, 2008) and in the case in which they are time varying and unevenly distributed over the dendritic tree. Here, we review theoretical and experimental results on the single-neuron properties that are relevant for the dynamical collective behavior of a population of neurons. We focus on the response of integrate-and-fire neurons and real cortical neurons to long-lasting, noisy, in vivo-like stationary inputs and show how the theory can predict the observed rhythmic activity of cultures of neurons. We then show how cortical neurons adapt on multiple time scales in response to input with stationary statistics in vitro. Next, we review how it is possible to study the general response properties of a neural circuit to time-varying inputs by estimating the response of single neurons to noisy sinusoidal currents. Finally, we address the dendrite-soma interactions in cortical neurons leading to gain modulation and spike bursts, and show how these effects can be captured by a two-compartment integrate-and-fire neuron. Most of the experimental results reviewed in this article have been successfully reproduced by simple integrate-and-fire model neurons.
Holographic Photolysis for Multiple Cell Stimulation in Mouse Hippocampal Slices
Papagiakoumou, Eirini; Ventalon, Cathie; Angulo, María Cecilia; Emiliani, Valentina
2010-01-01
Background Advanced light microscopy offers sensitive and non-invasive means to image neural activity and to control signaling with photolysable molecules and, recently, light-gated channels. These approaches require precise and yet flexible light excitation patterns. For synchronous stimulation of subsets of cells, they also require large excitation areas with millisecond and micrometric resolution. We have recently developed a new method for such optical control using a phase holographic modulation of optical wave-fronts, which minimizes power loss, enables rapid switching between excitation patterns, and allows a true 3D sculpting of the excitation volumes. In previous studies we have used holographic photololysis to control glutamate uncaging on single neuronal cells. Here, we extend the use of holographic photolysis for the excitation of multiple neurons and of glial cells. Methods/Principal Findings The system combines a liquid crystal device for holographic patterned photostimulation, high-resolution optical imaging, the HiLo microscopy, to define the stimulated regions and a conventional Ca2+ imaging system to detect neural activity. By means of electrophysiological recordings and calcium imaging in acute hippocampal slices, we show that the use of excitation patterns precisely tailored to the shape of multiple neuronal somata represents a very efficient way for the simultaneous excitation of a group of neurons. In addition, we demonstrate that fast shaped illumination patterns also induce reliable responses in single glial cells. Conclusions/Significance We show that the main advantage of holographic illumination is that it allows for an efficient excitation of multiple cells with a spatiotemporal resolution unachievable with other existing approaches. Although this paper focuses on the photoactivation of caged molecules, our approach will surely prove very efficient for other probes, such as light-gated channels, genetically encoded photoactivatable proteins, photoactivatable fluorescent proteins, and voltage-sensitive dyes. PMID:20195547
Tuned Normalization Explains the Size of Attention Modulations
Ni, Amy M.; Ray, Supratim; Maunsell, John H. R.
2012-01-01
SUMMARY The effect of attention on firing rates varies considerably within a single cortical area. The firing rate of some neurons is greatly modulated by attention while others are hardly affected. The reason for this variability across neurons is unknown. We found that the variability in attention modulation across neurons in area MT of macaques can be well explained by variability in the strength of tuned normalization across neurons. The presence of tuned normalization also explains a striking asymmetry in attention effects within neurons: when two stimuli are in a neuron’s receptive field, directing attention to the preferred stimulus modulates firing rates more than directing attention to the non-preferred stimulus. These findings show that much of the neuron-to-neuron variability in modulation of responses by attention depends on variability in the way the neurons process multiple stimuli, rather than differences in the influence of top-down signals related to attention. PMID:22365552
Fully Integrated Silicon Probes for High-Density Recording of Neural Activity
Jun, James J.; Steinmetz, Nicholas A.; Siegle, Joshua H.; Denman, Daniel J.; Bauza, Marius; Barbarits, Brian; Lee, Albert K.; Anastassiou, Costas A.; Andrei, Alexandru; Aydın, Çağatay; Barbic, Mladen; Blanche, Timothy J.; Bonin, Vincent; Couto, João; Dutta, Barundeb; Gratiy, Sergey L.; Gutnisky, Diego A.; Häusser, Michael; Karsh, Bill; Ledochowitsch, Peter; Lopez, Carolina Mora; Mitelut, Catalin; Musa, Silke; Okun, Michael; Pachitariu, Marius; Putzeys, Jan; Rich, P. Dylan; Rossant, Cyrille; Sun, Wei-lung; Svoboda, Karel; Carandini, Matteo; Harris, Kenneth D.; Koch, Christof; O'Keefe, John; Harris, Timothy D.
2018-01-01
Summary Paragraph Sensory, motor, and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures1,2. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution but from only a few dozen neurons per shank. Optical Ca2+ imaging3–5 offers more coverage but lacks the temporal resolution to reliably distinguish individual spikes and does not measure local field potentials. To date, no technology compatible with unrestrained animals has combined high spatiotemporal resolution with large volume coverage. To satisfy this need, we designed, fabricated, and tested a new silicon probe called Neuropixels. Each probe has 384 recording channels that can programmably address 960 CMOS processing-compatible low-impedance TiN6 sites that tile a single 10 mm long, 70x20 µm cross section shank. The 6x9 mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed, and digitized on the base, allowing noise-free digital data transmission directly from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were simultaneously recorded from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed recording large populations of neurons from multiple brain structures in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens the path to record brain-wide neural activity during behavior. PMID:29120427
Contextual effects of noise on vocalization encoding in primary auditory cortex
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
Contextual effects of noise on vocalization encoding in primary auditory cortex.
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.
2017-01-01
Abstract Topography in the avian cochlear nucleus magnocellularis (NM) is represented as gradually increasing characteristic frequency (CF) along the caudolateral-to-rostromedial axis. In this study, we characterized the organization and cell biophysics of the caudolateral NM (NMc) in chickens (Gallus gallus). Examination of cellular and dendritic architecture first revealed that NMc contains small neurons and extensive dendritic processes, in contrast to adendritic, large neurons located more rostromedially. Individual dye-filling study further demonstrated that NMc is divided into two subregions, with NMc2 neurons having larger and more complex dendritic fields than NMc1. Axonal tract tracing studies confirmed that NMc1 and NMc2 neurons receive afferent inputs from the auditory nerve and the superior olivary nucleus, similar to the adendritic NM. However, the auditory axons synapse with NMc neurons via small bouton-like terminals, unlike the large end bulb synapses on adendritic NM neurons. Immunocytochemistry demonstrated that most NMc2 neurons express cholecystokinin but not calretinin, distinct from NMc1 and adendritic NM neurons that are cholecystokinin negative and mostly calretinin positive. Finally, whole-cell current clamp recordings revealed that NMc neurons require significantly lower threshold current for action potential generation than adendritic NM neurons. Moreover, in contrast to adendritic NM neurons that generate a single-onset action potential, NMc neurons generate multiple action potentials to suprathreshold sustained depolarization. Taken together, our data indicate that NMc contains multiple neuron types that are structurally, connectively, molecularly, and physiologically different from traditionally defined NM neurons, emphasizing specialized neural properties for processing low-frequency sounds. PMID:28413822
Precise Spatiotemporal Control of Optogenetic Activation Using an Acousto-Optic Device
Guo, Yanmeng; Song, Peipei; Zhang, Xiaohui; Zeng, Shaoqun; Wang, Zuoren
2011-01-01
Light activation and inactivation of neurons by optogenetic techniques has emerged as an important tool for studying neural circuit function. To achieve a high resolution, new methods are being developed to selectively manipulate the activity of individual neurons. Here, we report that the combination of an acousto-optic device (AOD) and single-photon laser was used to achieve rapid and precise spatiotemporal control of light stimulation at multiple points in a neural circuit with millisecond time resolution. The performance of this system in activating ChIEF expressed on HEK 293 cells as well as cultured neurons was first evaluated, and the laser stimulation patterns were optimized. Next, the spatiotemporally selective manipulation of multiple neurons was achieved in a precise manner. Finally, we demonstrated the versatility of this high-resolution method in dissecting neural circuits both in the mouse cortical slice and the Drosophila brain in vivo. Taken together, our results show that the combination of AOD-assisted laser stimulation and optogenetic tools provides a flexible solution for manipulating neuronal activity at high efficiency and with high temporal precision. PMID:22174813
Spike-train communities: finding groups of similar spike trains.
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.
Gold nanoparticle-mediated laser stimulation causes a complex stress signal in neuronal cells
NASA Astrophysics Data System (ADS)
Johannsmeier, Sonja; Heeger, Patrick; Terakawa, Mitsuhiro; Kalies, Stefan; Heisterkamp, Alexander; Ripken, Tammo; Heinemann, Dag
2017-07-01
Gold nanoparticle mediated laser stimulation of neuronal cells allows for cell activation on a single-cell level. It could therefore be considered an alternative to classical electric neurostimulation. The physiological impact of this new approach has not been intensively studied so far. Here, we investigate the targeted cell's reaction to a laser stimulus based on its calcium response. A complex cellular reaction involving multiple sources has been revealed.
Nakamura, Hisashi; Hioki, Hiroyuki; Furuta, Takahiro; Kaneko, Takeshi
2015-05-01
The lateral posterior thalamic nucleus (LP) is one of the components of the extrageniculate pathway in the rat visual system, and is cytoarchitecturally divided into three subdivisions--lateral (LPl), rostromedial (LPrm), and caudomedial (LPcm) portions. To clarify the differences in the dendritic fields and axonal arborisations among the three subdivisions, we applied a single-neuron labeling technique with viral vectors to LP neurons. The proximal dendrites of LPl neurons were more numerous than those of LPrm and LPcm neurons, and LPrm neurons tended to have wider dendritic fields than LPl neurons. We then analysed the axonal arborisations of LP neurons by reconstructing the axon fibers in the cortex. The LPl, LPrm and LPcm were different from one another in terms of the projection targets--the main target cortical regions of LPl and LPrm neurons were the secondary and primary visual areas, whereas those of LPcm neurons were the postrhinal and temporal association areas. Furthermore, the principal target cortical layers of LPl neurons in the visual areas were middle layers, but that of LPrm neurons was layer 1. This indicates that LPl and LPrm neurons can be categorised into the core and matrix types of thalamic neurons, respectively, in the visual areas. In addition, LPl neurons formed multiple axonal clusters within the visual areas, whereas the fibers of LPrm neurons were widely and diffusely distributed. It is therefore presumed that these two types of neurons play different roles in visual information processing by dual thalamocortical innervation of the visual areas. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Eugenin, J; Nicholls, J G; Cohen, L B; Muller, K J
2006-01-01
Unfailing respiration depends on neural mechanisms already present in mammals before birth. Experiments were made to determine how inspiratory and expiratory neurons are grouped in the brainstem of fetal mice. A further aim was to assess whether rhythmicity arises from a single pacemaker or is generated by multiple sites in the brainstem. To measure neuronal firing, a fluorescent calcium indicator dye was applied to embryonic central nervous systems isolated from mice. While respiratory commands were monitored electrically from third to fifth cervical ventral roots, activity was measured optically over areas containing groups of respiratory neurones, or single neurones, along the medulla from the facial nucleus to the pre-Bötzinger complex. Large optical signals allowed recordings to be made during individual respiratory cycles. Inspiratory and expiratory neurones were intermingled. A novel finding was that bursts of activity arose in a discrete area intermittently, occurring during some breaths, but failing in others. Raised CO2 partial pressure or lowered pH increased the frequency of respiration; neurons then fired reliably with every cycle. Movies of activity revealed patterns of activation of inspiratory and expiratory neurones during successive respiratory cycles; there was no evidence for waves spreading systematically from region to region. Our results suggest that firing of neurons in immature respiratory circuits is a stochastic process, and that the rhythm does not depend on a single pacemaker. Respiratory circuits in fetal mouse brainstem appear to possess a high safety factor for generating rhythmicity, which may or may not persist as development proceeds.
Chiang, Ann-Shyn; Lin, Chih-Yung; Chuang, Chao-Chun; Chang, Hsiu-Ming; Hsieh, Chang-Huain; Yeh, Chang-Wei; Shih, Chi-Tin; Wu, Jian-Jheng; Wang, Guo-Tzau; Chen, Yung-Chang; Wu, Cheng-Chi; Chen, Guan-Yu; Ching, Yu-Tai; Lee, Ping-Chang; Lin, Chih-Yang; Lin, Hui-Hao; Wu, Chia-Chou; Hsu, Hao-Wei; Huang, Yun-Ann; Chen, Jing-Yi; Chiang, Hsin-Jung; Lu, Chun-Fang; Ni, Ru-Fen; Yeh, Chao-Yuan; Hwang, Jenn-Kang
2011-01-11
Animal behavior is governed by the activity of interconnected brain circuits. Comprehensive brain wiring maps are thus needed in order to formulate hypotheses about information flow and also to guide genetic manipulations aimed at understanding how genes and circuits orchestrate complex behaviors. To assemble this map, we deconstructed the adult Drosophila brain into approximately 16,000 single neurons and reconstructed them into a common standardized framework to produce a virtual fly brain. We have constructed a mesoscopic map and found that it consists of 41 local processing units (LPUs), six hubs, and 58 tracts covering the whole Drosophila brain. Despite individual local variation, the architecture of the Drosophila brain shows invariance for both the aggregation of local neurons (LNs) within specific LPUs and for the connectivity of projection neurons (PNs) between the same set of LPUs. An open-access image database, named FlyCircuit, has been constructed for online data archiving, mining, analysis, and three-dimensional visualization of all single neurons, brain-wide LPUs, their wiring diagrams, and neural tracts. We found that the Drosophila brain is assembled from families of multiple LPUs and their interconnections. This provides an essential first step in the analysis of information processing within and between neurons in a complete brain. Copyright © 2011 Elsevier Ltd. All rights reserved.
Beyond the frontiers of neuronal types
Battaglia, Demian; Karagiannis, Anastassios; Gallopin, Thierry; Gutch, Harold W.; Cauli, Bruno
2012-01-01
Cortical neurons and, particularly, inhibitory interneurons display a large diversity of morphological, synaptic, electrophysiological, and molecular properties, as well as diverse embryonic origins. Various authors have proposed alternative classification schemes that rely on the concomitant observation of several multimodal features. However, a broad variability is generally observed even among cells that are grouped into a same class. Furthermore, the attribution of specific neurons to a single defined class is often difficult, because individual properties vary in a highly graded fashion, suggestive of continua of features between types. Going beyond the description of representative traits of distinct classes, we focus here on the analysis of atypical cells. We introduce a novel paradigm for neuronal type classification, assuming explicitly the existence of a structured continuum of diversity. Our approach, grounded on the theory of fuzzy sets, identifies a small optimal number of model archetypes. At the same time, it quantifies the degree of similarity between these archetypes and each considered neuron. This allows highlighting archetypal cells, which bear a clear similarity to a single model archetype, and edge cells, which manifest a convergence of traits from multiple archetypes. PMID:23403725
Mitochondrial DNA Depletion in Respiratory Chain-Deficient Parkinson Disease Neurons.
Grünewald, Anne; Rygiel, Karolina A; Hepplewhite, Philippa D; Morris, Christopher M; Picard, Martin; Turnbull, Doug M
2016-03-01
To determine the extent of respiratory chain abnormalities and investigate the contribution of mtDNA to the loss of respiratory chain complexes (CI-IV) in the substantia nigra (SN) of idiopathic Parkinson disease (IPD) patients at the single-neuron level. Multiple-label immunofluorescence was applied to postmortem sections of 10 IPD patients and 10 controls to quantify the abundance of CI-IV subunits (NDUFB8 or NDUFA13, SDHA, UQCRC2, and COXI) and mitochondrial transcription factors (TFAM and TFB2M) relative to mitochondrial mass (porin and GRP75) in dopaminergic neurons. To assess the involvement of mtDNA in respiratory chain deficiency in IPD, SN neurons, isolated with laser-capture microdissection, were assayed for mtDNA deletions, copy number, and presence of transcription/replication-associated 7S DNA employing a triplex real-time polymerase chain reaction (PCR) assay. Whereas mitochondrial mass was unchanged in single SN neurons from IPD patients, we observed a significant reduction in the abundances of CI and II subunits. At the single-cell level, CI and II deficiencies were correlated in patients. The CI deficiency concomitantly occurred with low abundances of the mtDNA transcription factors TFAM and TFB2M, which also initiate transcription-primed mtDNA replication. Consistent with this, real-time PCR analysis revealed fewer transcription/replication-associated mtDNA molecules and an overall reduction in mtDNA copy number in patients. This effect was more pronounced in single IPD neurons with severe CI deficiency. Respiratory chain dysfunction in IPD neurons not only involves CI, but also extends to CII. These deficiencies are possibly a consequence of the interplay between nDNA and mtDNA-encoded factors mechanistically connected via TFAM. © 2016 The Authors. Annals of Neurology published by Wiley Periodicals, Inc. on behalf of American Neurological Association.
Hu, L.; Zhang, Z.G.; Mouraux, A.; Iannetti, G.D.
2015-01-01
Transient sensory, motor or cognitive event elicit not only phase-locked event-related potentials (ERPs) in the ongoing electroencephalogram (EEG), but also induce non-phase-locked modulations of ongoing EEG oscillations. These modulations can be detected when single-trial waveforms are analysed in the time-frequency domain, and consist in stimulus-induced decreases (event-related desynchronization, ERD) or increases (event-related synchronization, ERS) of synchrony in the activity of the underlying neuronal populations. ERD and ERS reflect changes in the parameters that control oscillations in neuronal networks and, depending on the frequency at which they occur, represent neuronal mechanisms involved in cortical activation, inhibition and binding. ERD and ERS are commonly estimated by averaging the time-frequency decomposition of single trials. However, their trial-to-trial variability that can reflect physiologically-important information is lost by across-trial averaging. Here, we aim to (1) develop novel approaches to explore single-trial parameters (including latency, frequency and magnitude) of ERP/ERD/ERS; (2) disclose the relationship between estimated single-trial parameters and other experimental factors (e.g., perceived intensity). We found that (1) stimulus-elicited ERP/ERD/ERS can be correctly separated using principal component analysis (PCA) decomposition with Varimax rotation on the single-trial time-frequency distributions; (2) time-frequency multiple linear regression with dispersion term (TF-MLRd) enhances the signal-to-noise ratio of ERP/ERD/ERS in single trials, and provides an unbiased estimation of their latency, frequency, and magnitude at single-trial level; (3) these estimates can be meaningfully correlated with each other and with other experimental factors at single-trial level (e.g., perceived stimulus intensity and ERP magnitude). The methods described in this article allow exploring fully non-phase-locked stimulus-induced cortical oscillations, obtaining single-trial estimate of response latency, frequency, and magnitude. This permits within-subject statistical comparisons, correlation with pre-stimulus features, and integration of simultaneously-recorded EEG and fMRI. PMID:25665966
Sensory Afferents Use Different Coding Strategies for Heat and Cold.
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.
Exploring the brain on multiple scales with correlative two-photon and light sheet microscopy
NASA Astrophysics Data System (ADS)
Silvestri, Ludovico; Allegra Mascaro, Anna Letizia; Costantini, Irene; Sacconi, Leonardo; Pavone, Francesco S.
2014-02-01
One of the unique features of the brain is that its activity cannot be framed in a single spatio-temporal scale, but rather spans many orders of magnitude both in space and time. A single imaging technique can reveal only a small part of this complex machinery. To obtain a more comprehensive view of brain functionality, complementary approaches should be combined into a correlative framework. Here, we describe a method to integrate data from in vivo two-photon fluorescence imaging and ex vivo light sheet microscopy, taking advantage of blood vessels as reference chart. We show how the apical dendritic arbor of a single cortical pyramidal neuron imaged in living thy1-GFP-M mice can be found in the large-scale brain reconstruction obtained with light sheet microscopy. Starting from the apical portion, the whole pyramidal neuron can then be segmented. The correlative approach presented here allows contextualizing within a three-dimensional anatomic framework the neurons whose dynamics have been observed with high detail in vivo.
Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology.
Fu, Tian-Ming; Hong, Guosong; Viveros, Robert D; Zhou, Tao; Lieber, Charles M
2017-11-21
Implantable electrical probes have led to advances in neuroscience, brain-machine interfaces, and treatment of neurological diseases, yet they remain limited in several key aspects. Ideally, an electrical probe should be capable of recording from large numbers of neurons across multiple local circuits and, importantly, allow stable tracking of the evolution of these neurons over the entire course of study. Silicon probes based on microfabrication can yield large-scale, high-density recording but face challenges of chronic gliosis and instability due to mechanical and structural mismatch with the brain. Ultraflexible mesh electronics, on the other hand, have demonstrated negligible chronic immune response and stable long-term brain monitoring at single-neuron level, although, to date, it has been limited to 16 channels. Here, we present a scalable scheme for highly multiplexed mesh electronics probes to bridge the gap between scalability and flexibility, where 32 to 128 channels per probe were implemented while the crucial brain-like structure and mechanics were maintained. Combining this mesh design with multisite injection, we demonstrate stable 128-channel local field potential and single-unit recordings from multiple brain regions in awake restrained mice over 4 mo. In addition, the newly integrated mesh is used to validate stable chronic recordings in freely behaving mice. This scalable scheme for mesh electronics together with demonstrated long-term stability represent important progress toward the realization of ideal implantable electrical probes allowing for mapping and tracking single-neuron level circuit changes associated with learning, aging, and neurodegenerative diseases. Copyright © 2017 the Author(s). Published by PNAS.
Neurons in cat V1 show significant clustering by degree of tuning
Ziskind, Avi J.; Emondi, Al A.; Kurgansky, Andrei V.; Rebrik, Sergei P.
2015-01-01
Neighboring neurons in cat primary visual cortex (V1) have similar preferred orientation, direction, and spatial frequency. How diverse is their degree of tuning for these properties? To address this, we used single-tetrode recordings to simultaneously isolate multiple cells at single recording sites and record their responses to flashed and drifting gratings of multiple orientations, spatial frequencies, and, for drifting gratings, directions. Orientation tuning width, spatial frequency tuning width, and direction selectivity index (DSI) all showed significant clustering: pairs of neurons recorded at a single site were significantly more similar in each of these properties than pairs of neurons from different recording sites. The strength of the clustering was generally modest. The percent decrease in the median difference between pairs from the same site, relative to pairs from different sites, was as follows: for different measures of orientation tuning width, 29–35% (drifting gratings) or 15–25% (flashed gratings); for DSI, 24%; and for spatial frequency tuning width measured in octaves, 8% (drifting gratings). The clusterings of all of these measures were much weaker than for preferred orientation (68% decrease) but comparable to that seen for preferred spatial frequency in response to drifting gratings (26%). For the above properties, little difference in clustering was seen between simple and complex cells. In studies of spatial frequency tuning to flashed gratings, strong clustering was seen among simple-cell pairs for tuning width (70% decrease) and preferred frequency (71% decrease), whereas no clustering was seen for simple-complex or complex-complex cell pairs. PMID:25652921
State Dependency of Chemosensory Coding in the Gustatory Thalamus (VPMpc) of Alert Rats
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
Starosta, Sarah; Stüttgen, Maik C; Güntürkün, Onur
2014-06-02
While the subject of learning has attracted immense interest from both behavioral and neural scientists, only relatively few investigators have observed single-neuron activity while animals are acquiring an operantly conditioned response, or when that response is extinguished. But even in these cases, observation periods usually encompass only a single stage of learning, i.e. acquisition or extinction, but not both (exceptions include protocols employing reversal learning; see Bingman et al.(1) for an example). However, acquisition and extinction entail different learning mechanisms and are therefore expected to be accompanied by different types and/or loci of neural plasticity. Accordingly, we developed a behavioral paradigm which institutes three stages of learning in a single behavioral session and which is well suited for the simultaneous recording of single neurons' action potentials. Animals are trained on a single-interval forced choice task which requires mapping each of two possible choice responses to the presentation of different novel visual stimuli (acquisition). After having reached a predefined performance criterion, one of the two choice responses is no longer reinforced (extinction). Following a certain decrement in performance level, correct responses are reinforced again (reacquisition). By using a new set of stimuli in every session, animals can undergo the acquisition-extinction-reacquisition process repeatedly. Because all three stages of learning occur in a single behavioral session, the paradigm is ideal for the simultaneous observation of the spiking output of multiple single neurons. We use pigeons as model systems, but the task can easily be adapted to any other species capable of conditioned discrimination learning.
Preserving information in neural transmission.
Sincich, Lawrence C; Horton, Jonathan C; Sharpee, Tatyana O
2009-05-13
Along most neural pathways, the spike trains transmitted from one neuron to the next are altered. In the process, neurons can either achieve a more efficient stimulus representation, or extract some biologically important stimulus parameter, or succeed at both. We recorded the inputs from single retinal ganglion cells and the outputs from connected lateral geniculate neurons in the macaque to examine how visual signals are relayed from retina to cortex. We found that geniculate neurons re-encoded multiple temporal stimulus features to yield output spikes that carried more information about stimuli than was available in each input spike. The coding transformation of some relay neurons occurred with no decrement in information rate, despite output spike rates that averaged half the input spike rates. This preservation of transmitted information was achieved by the short-term summation of inputs that geniculate neurons require to spike. A reduced model of the retinal and geniculate visual responses, based on two stimulus features and their associated nonlinearities, could account for >85% of the total information available in the spike trains and the preserved information transmission. These results apply to neurons operating on a single time-varying input, suggesting that synaptic temporal integration can alter the temporal receptive field properties to create a more efficient representation of visual signals in the thalamus than the retina.
Simultaneous profiling of activity patterns in multiple neuronal subclasses.
Parrish, R Ryley; Grady, John; Codadu, Neela K; Trevelyan, Andrew J; Racca, Claudia
2018-06-01
Neuronal networks typically comprise heterogeneous populations of neurons. A core objective when seeking to understand such networks, therefore, is to identify what roles these different neuronal classes play. Acquiring single cell electrophysiology data for multiple cell classes can prove to be a large and daunting task. Alternatively, Ca 2+ network imaging provides activity profiles of large numbers of neurons simultaneously, but without distinguishing between cell classes. We therefore developed a strategy for combining cellular electrophysiology, Ca 2+ network imaging, and immunohistochemistry to provide activity profiles for multiple cell classes at once. This involves cross-referencing easily identifiable landmarks between imaging of the live and fixed tissue, and then using custom MATLAB functions to realign the two imaging data sets, to correct for distortions of the tissue introduced by the fixation or immunohistochemical processing. We illustrate the methodology for analyses of activity profiles during epileptiform events recorded in mouse brain slices. We further demonstrate the activity profile of a population of parvalbumin-positive interneurons prior, during, and following a seizure-like event. Current approaches to Ca 2+ network imaging analyses are severely limited in their ability to subclassify neurons, and often rely on transgenic approaches to identify cell classes. In contrast, our methodology is a generic, affordable, and flexible technique to characterize neuronal behaviour with respect to classification based on morphological and neurochemical identity. We present a new approach for analysing Ca 2+ network imaging datasets, and use this to explore the parvalbumin-positive interneuron activity during epileptiform events. Copyright © 2018 Elsevier B.V. All rights reserved.
Nonlinear Modeling of Causal Interrelationships in Neuronal Ensembles
Zanos, Theodoros P.; Courellis, Spiros H.; Berger, Theodore W.; Hampson, Robert E.; Deadwyler, Sam A.; Marmarelis, Vasilis Z.
2009-01-01
The increasing availability of multiunit recordings gives new urgency to the need for effective analysis of “multidimensional” time-series data that are derived from the recorded activity of neuronal ensembles in the form of multiple sequences of action potentials—treated mathematically as point-processes and computationally as spike-trains. Whether in conditions of spontaneous activity or under conditions of external stimulation, the objective is the identification and quantification of possible causal links among the neurons generating the observed binary signals. A multiple-input/multiple-output (MIMO) modeling methodology is presented that can be used to quantify the neuronal dynamics of causal interrelationships in neuronal ensembles using spike-train data recorded from individual neurons. These causal interrelationships are modeled as transformations of spike-trains recorded from a set of neurons designated as the “inputs” into spike-trains recorded from another set of neurons designated as the “outputs.” The MIMO model is composed of a set of multiinput/single-output (MISO) modules, one for each output. Each module is the cascade of a MISO Volterra model and a threshold operator generating the output spikes. The Laguerre expansion approach is used to estimate the Volterra kernels of each MISO module from the respective input–output data using the least-squares method. The predictive performance of the model is evaluated with the use of the receiver operating characteristic (ROC) curve, from which the optimum threshold is also selected. The Mann–Whitney statistic is used to select the significant inputs for each output by examining the statistical significance of improvements in the predictive accuracy of the model when the respective inputs is included. Illustrative examples are presented for a simulated system and for an actual application using multiunit data recordings from the hippocampus of a behaving rat. PMID:18701382
Breadth of tuning in taste afferent neurons varies with stimulus strength
Wu, An; Dvoryanchikov, Gennady; Pereira, Elizabeth; Chaudhari, Nirupa; Roper, Stephen D.
2015-01-01
Gustatory stimuli are detected by taste buds and transmitted to the hindbrain via sensory afferent neurons. Whether each taste quality (sweet, bitter and so on) is encoded by separate neurons (‘labelled lines') remains controversial. We used mice expressing GCaMP3 in geniculate ganglion sensory neurons to investigate taste-evoked activity. Using confocal calcium imaging, we recorded responses to oral stimulation with prototypic taste stimuli. Up to 69% of neurons respond to multiple tastants. Moreover, neurons tuned to a single taste quality at low concentration become more broadly tuned when stimuli are presented at higher concentration. Responses to sucrose and monosodium glutamate are most related. Although mice prefer dilute NaCl solutions and avoid concentrated NaCl, we found no evidence for two separate populations of sensory neurons that encode this distinction. Altogether, our data suggest that taste is encoded by activity in patterns of peripheral sensory neurons and challenge the notion of strict labelled line coding. PMID:26373451
Multi-Scale Molecular Deconstruction of the Serotonin Neuron System.
Okaty, Benjamin W; Freret, Morgan E; Rood, Benjamin D; Brust, Rachael D; Hennessy, Morgan L; deBairos, Danielle; Kim, Jun Chul; Cook, Melloni N; Dymecki, Susan M
2015-11-18
Serotonergic (5HT) neurons modulate diverse behaviors and physiology and are implicated in distinct clinical disorders. Corresponding diversity in 5HT neuronal phenotypes is becoming apparent and is likely rooted in molecular differences, yet a comprehensive approach characterizing molecular variation across the 5HT system is lacking, as is concomitant linkage to cellular phenotypes. Here we combine intersectional fate mapping, neuron sorting, and genome-wide RNA-seq to deconstruct the mouse 5HT system at multiple levels of granularity-from anatomy, to genetic sublineages, to single neurons. Our unbiased analyses reveal principles underlying system organization, 5HT neuron subtypes, constellations of differentially expressed genes distinguishing subtypes, and predictions of subtype-specific functions. Using electrophysiology, subtype-specific neuron silencing, and conditional gene knockout, we show that these molecularly defined 5HT neuron subtypes are functionally distinct. Collectively, this resource classifies molecular diversity across the 5HT system and discovers sertonergic subtypes, markers, organizing principles, and subtype-specific functions with potential disease relevance. Copyright © 2015 Elsevier Inc. All rights reserved.
Multi-Scale Molecular Deconstruction of the Serotonin Neuron System
Okaty, Benjamin W.; Freret, Morgan E.; Rood, Benjamin D.; Brust, Rachael D.; Hennessy, Morgan L.; deBairos, Danielle; Kim, Jun Chul; Cook, Melloni N.; Dymecki, Susan M.
2016-01-01
Summary Serotonergic (5HT) neurons modulate diverse behaviors and physiology and are implicated in distinct clinical disorders. Corresponding diversity in 5HT neuronal phenotypes is becoming apparent and is likely rooted in molecular differences, yet a comprehensive approach characterizing molecular variation across the 5HT system is lacking, as is concomitant linkage to cellular phenotypes. Here we combine intersectional fate mapping, neuron sorting, and genome-wide RNA-Seq to deconstruct the mouse 5HT system at multiple levels of granularity—from anatomy, to genetic sublineages, to single neurons. Our unbiased analyses reveal: principles underlying system organization, novel 5HT neuron subtypes, constellations of differentially expressed genes distinguishing subtypes, and predictions of subtype-specific functions. Using electrophysiology, subtype-specific neuron silencing, and conditional gene knockout, we show that these molecularly defined 5HT neuron subtypes are functionally distinct. Collectively, this resource classifies molecular diversity across the 5HT system and discovers new subtypes, markers, organizing principles, and subtype-specific functions with potential disease relevance. PMID:26549332
On two diffusion neuronal models with multiplicative noise: The mean first-passage time properties
NASA Astrophysics Data System (ADS)
D'Onofrio, G.; Lansky, P.; Pirozzi, E.
2018-04-01
Two diffusion processes with multiplicative noise, able to model the changes in the neuronal membrane depolarization between two consecutive spikes of a single neuron, are considered and compared. The processes have the same deterministic part but different stochastic components. The differences in the state-dependent variabilities, their asymptotic distributions, and the properties of the first-passage time across a constant threshold are investigated. Closed form expressions for the mean of the first-passage time of both processes are derived and applied to determine the role played by the parameters involved in the model. It is shown that for some values of the input parameters, the higher variability, given by the second moment, does not imply shorter mean first-passage time. The reason for that can be found in the complete shape of the stationary distribution of the two processes. Applications outside neuroscience are also mentioned.
Central auditory neurons have composite receptive fields.
Kozlov, Andrei S; Gentner, Timothy Q
2016-02-02
High-level neurons processing complex, behaviorally relevant signals are sensitive to conjunctions of features. Characterizing the receptive fields of such neurons is difficult with standard statistical tools, however, and the principles governing their organization remain poorly understood. Here, we demonstrate multiple distinct receptive-field features in individual high-level auditory neurons in a songbird, European starling, in response to natural vocal signals (songs). We then show that receptive fields with similar characteristics can be reproduced by an unsupervised neural network trained to represent starling songs with a single learning rule that enforces sparseness and divisive normalization. We conclude that central auditory neurons have composite receptive fields that can arise through a combination of sparseness and normalization in neural circuits. Our results, along with descriptions of random, discontinuous receptive fields in the central olfactory neurons in mammals and insects, suggest general principles of neural computation across sensory systems and animal classes.
Estimating Single-Trial Responses in EEG
NASA Technical Reports Server (NTRS)
Shah, A. S.; Knuth, K. H.; Truccolo, W. A.; Mehta, A. D.; Fu, K. G.; Johnston, T. A.; Ding, M.; Bressler, S. L.; Schroeder, C. E.; Clancy, Daniel (Technical Monitor)
2002-01-01
Accurate characterization of single-trial field potential responses is critical from a number of perspectives. For example, it allows differentiation of an evoked response from ongoing EEG. We previously developed the multiple component Event Related Potential (mcERP) algorithm to improve resolution of the single-trial evoked response. The mcERP model states that multiple components, each specified by a stereotypic waveform varying in latency and amplitude from trial to trial, comprise the evoked response. Application of the mcERP algorithm to simulated data with three independent, synthetic components has shown that the model is capable of separating these components and estimating their variability. Application of the model to single trial, visual evoked potentials recorded simultaneously from all V1 laminae in an awake, fixating macaque yielded local and far-field components. Certain local components estimated by the model were distributed in both granular and supragranular laminae. This suggests a linear coupling between the responses of thalamo-recipient neuronal ensembles and subsequent responses of supragranular neuronal ensembles, as predicted by the feedforward anatomy of V1. Our results indicate that the mcERP algorithm provides a valid estimation of single-trial responses. This will enable analyses that depend on trial-to-trial variations and those that require separation of the evoked response from background EEG rhythms
Sasaki, S
1999-10-01
Functional connections of single reticulospinal neurons (RSNs) in the nucleus reticularis gigantocellularis (NRG) with ipsilateral dorsal neck motoneurons were examined with the spike-triggered averaging technique. Extracellular spikes of single NRG-RSNs activated antidromically from the C6, but not from the L1 segment (C-RSNs) were used as the trigger. These neurons were monosynaptically activated from the superior colliculus and the cerebral peduncle. Single-RSN PSPs were recorded in 43 dorsal neck motoneurons [biventer cervicis and complexus (BCC) and splenius (SPL)] for 21 NRG-RSNs and 135 motoneurons tested. All synaptic potentials were EPSPs, and most of their latencies, measured from the triggering spikes, were 0.8-1.5 ms, which is in a monosynaptic range. The amplitudes of single-RSN EPSPs were 10-360 microV. Spike-triggered averaging revealed single-RSN EPSPs in multiple motoneurons of the same species (SPL or BCC), their locations extending up to nearly 1 mm rostrocaudally. Synaptic connections of single RSNs with both SPL and BCC motoneurons were also found with some predominance for one of them. The results provide direct evidence that NRG-RSNs make monosynaptic excitatory connections with SPL and BCC motoneurons. It appears that some NRG-RSNs connect predominantly with SPL motoneurons and others with BCC motoneurons.
Chen, I-Wen; Papagiakoumou, Eirini; Emiliani, Valentina
2018-06-01
Optogenetics neuronal targeting combined with single-photon wide-field illumination has already proved its enormous potential in neuroscience, enabling the optical control of entire neuronal networks and disentangling their role in the control of specific behaviors. However, establishing how a single or a sub-set of neurons controls a specific behavior, or how functionally identical neurons are connected in a particular task, or yet how behaviors can be modified in real-time by the complex wiring diagram of neuronal connections requires more sophisticated approaches enabling to drive neuronal circuits activity with single-cell precision and millisecond temporal resolution. This has motivated on one side the development of flexible optical methods for two-photon (2P) optogenetic activation using either, or a hybrid of two approaches: scanning and parallel illumination. On the other side, it has stimulated the engineering of new opsins with modified spectral characteristics, channel kinetics and spatial distribution of expression, offering the necessary flexibility of choosing the appropriate opsin for each application. The need for optical manipulation of multiple targets with millisecond temporal resolution has imposed three-dimension (3D) parallel holographic illumination as the technique of choice for optical control of neuronal circuits organized in 3D. Today 3D parallel illumination exists in several complementary variants, each with a different degree of simplicity, light uniformity, temporal precision and axial resolution. In parallel, the possibility to reach hundreds of targets in 3D volumes has prompted the development of low-repetition rate amplified laser sources enabling high peak power, while keeping low average power for stimulating each cell. All together those progresses open the way for a precise optical manipulation of neuronal circuits with unprecedented precision and flexibility. Copyright © 2018 Elsevier Ltd. All rights reserved.
Deep brain stimulation macroelectrodes compared to multiple microelectrodes in rat hippocampus
Arcot Desai, Sharanya; Gutekunst, Claire-Anne; Potter, Steve M.; Gross, Robert E.
2014-01-01
Microelectrode arrays (wire diameter <50 μm) were compared to traditional macroelectrodes for deep brain stimulation (DBS). Understanding the neuronal activation volume may help solve some of the mysteries associated with DBS, e.g., its mechanisms of action. We used c-fos immunohistochemistry to investigate neuronal activation in the rat hippocampus caused by multi-micro- and macroelectrode stimulation. At ± 1V stimulation at 25 Hz, microelectrodes (33 μm diameter) had a radius of activation of 100 μm, which is 50% of that seen with 150 μm diameter macroelectrode stimulation. Macroelectrodes activated about 5.8 times more neurons than a single microelectrode, but displaced ~20 times more neural tissue. The sphere of influence of stimulating electrodes can be significantly increased by reducing their impedance. By ultrasonic electroplating (sonicoplating) the microelectrodes with platinum to increase their surface area and reduce their impedance by an order of magnitude, the radius of activation increased by 50 μm and more than twice the number of neurons were activated within this increased radius compared to unplated microelectrodes. We suggest that a new approach to DBS, one that uses multiple high-surface area microelectrodes, may be more therapeutically effective due to increased neuronal activation. PMID:24971060
Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task
2017-01-01
Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of spiking neurons with multiple plastic layers. The network utilized both reward modulated and non-reward modulated STDP and implemented multiple mechanisms for homeostatic regulation of synaptic efficacy, including heterosynaptic plasticity, gain control, output balancing, activity normalization of rewarded STDP and hard limits on synaptic strength. We found that addition of a hidden layer of neurons employing non-rewarded STDP created neurons that responded to the specific combinations of inputs and thus performed basic classification of the input patterns. When combined with a following layer of neurons implementing rewarded STDP, the network was able to learn, despite the absence of labeled training data, discrimination between rewarding patterns and the patterns designated as punishing. Synaptic noise allowed for trial-and-error learning that helped to identify the goal-oriented strategies which were effective in task solving. The study predicts a critical set of properties of the spiking neuronal network with STDP that was sufficient to solve a complex foraging task involving pattern classification and decision making. PMID:28961245
A Simple Method to Simultaneously Detect and Identify Spikes from Raw Extracellular Recordings.
Petrantonakis, Panagiotis C; Poirazi, Panayiota
2015-01-01
The ability to track when and which neurons fire in the vicinity of an electrode, in an efficient and reliable manner can revolutionize the neuroscience field. The current bottleneck lies in spike sorting algorithms; existing methods for detecting and discriminating the activity of multiple neurons rely on inefficient, multi-step processing of extracellular recordings. In this work, we show that a single-step processing of raw (unfiltered) extracellular signals is sufficient for both the detection and identification of active neurons, thus greatly simplifying and optimizing the spike sorting approach. The efficiency and reliability of our method is demonstrated in both real and simulated data.
Demertzi, Athena; Gómez, Francisco; Crone, Julia Sophia; Vanhaudenhuyse, Audrey; Tshibanda, Luaba; Noirhomme, Quentin; Thonnard, Marie; Charland-Verville, Vanessa; Kirsch, Murielle; Laureys, Steven; Soddu, Andrea
2014-03-01
In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects. 300 fMRI volumes were obtained in 27 healthy controls and 53 patients in minimally conscious state (MCS), vegetative state/unresponsive wakefulness syndrome (VS/UWS) and coma. Independent component analysis (ICA) reduced data dimensionality. The ten networks were identified by means of a multiple template-matching procedure and were tested on neuronality properties (neuronal vs non-neuronal) in a data-driven way. Univariate analyses detected between-group differences in networks' neuronal properties and estimated voxel-wise functional connectivity in the networks, which were significantly less identifiable in patients. A nearest-neighbor "clinical" classifier was used to determine the networks with high between-group discriminative accuracy. Healthy controls were characterized by more neuronal components compared to patients in VS/UWS and in coma. Compared to healthy controls, fewer patients in MCS and VS/UWS showed components of neuronal origin for the left executive control network, default mode network (DMN), auditory, and right executive control network. The "clinical" classifier indicated the DMN and auditory network with the highest accuracy (85.3%) in discriminating patients from healthy subjects. FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics based on fMRI resting state acquisitions. Copyright © 2013 Elsevier Ltd. All rights reserved.
Do, Thanh D.; Comi, Troy J.; Dunham, Sage J. B.; Rubakhin, Stanislav S.; Sweedler, Jonathan V.
2017-01-01
A high-throughput single cell profiling method has been developed for matrix-enhanced secondary ion mass spectrometry (ME-SIMS) to investigate the lipid profiles of neuronal cells. Populations of cells are dispersed onto the substrate, their locations determined using optical microscopy, and the cell locations used to guide the acquisition of SIMS spectra from the cells. Up to 2,000 cells can be assayed in one experiment at a rate of 6 s per cell. Multiple saturated and unsaturated phosphatidylcholines (PCs) and their fragments are detected and verified with tandem mass spectrometry from individual cells when ionic liquids are employed as a matrix. Optically guided single cell profiling with ME-SIMS is suitable for a range of cell sizes, from Aplysia californica neurons larger than 75 μm to 7-μm rat cerebellar neurons. ME-SIMS analysis followed by t-distributed stochastic neighbor embedding of peaks in the lipid molecular mass range (m/z 700–850) distinguishes several cell types from the rat central nervous system, largely based on the relative proportions of the four dominant lipids, PC(32:0), PC(34:1), PC(36:1), and PC(38:5). Furthermore, subpopulations within each cell type are tentatively classified consistent with their endogenous lipid ratios. The results illustrate the efficacy of a new approach to classify single cell populations and subpopulations using SIMS profiling of lipid and metabolite contents. These methods are broadly applicable for high throughput single cell chemical analyses. PMID:28194949
Attention-related changes in correlated neuronal activity arise from normalization mechanisms
Verhoef, Bram-Ernst; Maunsell, John H.R.
2017-01-01
Attention is believed to enhance perception by altering the correlations between pairs of neurons. How attention changes neuronal correlations is unknown. Using multi-electrodes in primate visual cortex, we measured spike-count correlations when single or multiple stimuli were presented, and stimuli were attended or unattended. When stimuli were unattended, adding a suppressive, non-preferred, stimulus beside a preferred stimulus increased spike-count correlations between pairs of similarly-tuned neurons, but decreased spike-count correlations between pairs of oppositely-tuned neurons. These changes are explained by a stochastic normalization model containing populations of oppositely-tuned, mutually-suppressive neurons. Importantly, this model also explains why attention decreased (attend preferred stimulus) or increased (attend non-preferred stimulus) correlations: as an indirect consequence of attention-related changes in the inputs to normalization mechanisms. Our findings link normalization mechanisms to correlated neuronal activity and attention, showing that normalization mechanisms shape response correlations and that these correlations change when attention biases normalization mechanisms. PMID:28553943
Transcriptional Architecture of Synaptic Communication Delineates GABAergic Neuron Identity.
Paul, Anirban; Crow, Megan; Raudales, Ricardo; He, Miao; Gillis, Jesse; Huang, Z Josh
2017-10-19
Understanding the organizational logic of neural circuits requires deciphering the biological basis of neuronal diversity and identity, but there is no consensus on how neuron types should be defined. We analyzed single-cell transcriptomes of a set of anatomically and physiologically characterized cortical GABAergic neurons and conducted a computational genomic screen for transcriptional profiles that distinguish them from one another. We discovered that cardinal GABAergic neuron types are delineated by a transcriptional architecture that encodes their synaptic communication patterns. This architecture comprises 6 categories of ∼40 gene families, including cell-adhesion molecules, transmitter-modulator receptors, ion channels, signaling proteins, neuropeptides and vesicular release components, and transcription factors. Combinatorial expression of select members across families shapes a multi-layered molecular scaffold along the cell membrane that may customize synaptic connectivity patterns and input-output signaling properties. This molecular genetic framework of neuronal identity integrates cell phenotypes along multiple axes and provides a foundation for discovering and classifying neuron types. Copyright © 2017 Elsevier Inc. All rights reserved.
Baker, Christa A.; Ma, Lisa; Casareale, Chelsea R.
2016-01-01
In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8–12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. SIGNIFICANCE STATEMENT The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals. PMID:27559179
Baker, Christa A; Ma, Lisa; Casareale, Chelsea R; Carlson, Bruce A
2016-08-24
In many sensory pathways, central neurons serve as temporal filters for timing patterns in communication signals. However, how a population of neurons with diverse temporal filtering properties codes for natural variation in communication signals is unknown. Here we addressed this question in the weakly electric fish Brienomyrus brachyistius, which varies the time intervals between successive electric organ discharges to communicate. These fish produce an individually stereotyped signal called a scallop, which consists of a distinctive temporal pattern of ∼8-12 electric pulses. We manipulated the temporal structure of natural scallops during behavioral playback and in vivo electrophysiology experiments to probe the temporal sensitivity of scallop encoding and recognition. We found that presenting time-reversed, randomized, or jittered scallops increased behavioral response thresholds, demonstrating that fish's electric signaling behavior was sensitive to the precise temporal structure of scallops. Next, using in vivo intracellular recordings and discriminant function analysis, we found that the responses of interval-selective midbrain neurons were also sensitive to the precise temporal structure of scallops. Subthreshold changes in membrane potential recorded from single neurons discriminated natural scallops from time-reversed, randomized, and jittered sequences. Pooling the responses of multiple neurons improved the discriminability of natural sequences from temporally manipulated sequences. Finally, we found that single-neuron responses were sensitive to interindividual variation in scallop sequences, raising the question of whether fish may analyze scallop structure to gain information about the sender. Collectively, these results demonstrate that a population of interval-selective neurons can encode behaviorally relevant temporal patterns with millisecond precision. The timing patterns of action potentials, or spikes, play important roles in representing information in the nervous system. However, how these temporal patterns are recognized by downstream neurons is not well understood. Here we use the electrosensory system of mormyrid weakly electric fish to investigate how a population of neurons with diverse temporal filtering properties encodes behaviorally relevant input timing patterns, and how this relates to behavioral sensitivity. We show that fish are behaviorally sensitive to millisecond variations in natural, temporally patterned communication signals, and that the responses of individual midbrain neurons are also sensitive to variation in these patterns. In fact, the output of single neurons contains enough information to discriminate stereotyped communication signals produced by different individuals. Copyright © 2016 the authors 0270-6474/16/368985-16$15.00/0.
Sparse bursts optimize information transmission in a multiplexed neural code.
Naud, Richard; Sprekeler, Henning
2018-06-22
Many cortical neurons combine the information ascending and descending the cortical hierarchy. In the classical view, this information is combined nonlinearly to give rise to a single firing-rate output, which collapses all input streams into one. We analyze the extent to which neurons can simultaneously represent multiple input streams by using a code that distinguishes spike timing patterns at the level of a neural ensemble. Using computational simulations constrained by experimental data, we show that cortical neurons are well suited to generate such multiplexing. Interestingly, this neural code maximizes information for short and sparse bursts, a regime consistent with in vivo recordings. Neurons can also demultiplex this information, using specific connectivity patterns. The anatomy of the adult mammalian cortex suggests that these connectivity patterns are used by the nervous system to maintain sparse bursting and optimal multiplexing. Contrary to firing-rate coding, our findings indicate that the physiology and anatomy of the cortex may be interpreted as optimizing the transmission of multiple independent signals to different targets. Copyright © 2018 the Author(s). Published by PNAS.
Neurons in the Frontal Lobe Encode the Value of Multiple Decision Variables
Kennerley, Steven W.; Dahmubed, Aspandiar F.; Lara, Antonio H.; Wallis, Jonathan D.
2009-01-01
A central question in behavioral science is how we select among choice alternatives to obtain consistently the most beneficial outcomes. Three variables are particularly important when making a decision: the potential payoff, the probability of success, and the cost in terms of time and effort. A key brain region in decision making is the frontal cortex as damage here impairs the ability to make optimal choices across a range of decision types. We simultaneously recorded the activity of multiple single neurons in the frontal cortex while subjects made choices involving the three aforementioned decision variables. This enabled us to contrast the relative contribution of the anterior cingulate cortex (ACC), the orbito-frontal cortex, and the lateral prefrontal cortex to the decision-making process. Neurons in all three areas encoded value relating to choices involving probability, payoff, or cost manipulations. However, the most significant signals were in the ACC, where neurons encoded multiplexed representations of the three different decision variables. This supports the notion that the ACC is an important component of the neural circuitry underlying optimal decision making. PMID:18752411
Greve, Andrea; Donaldson, David I; van Rossum, Mark C W
2010-02-01
Dual-process theories of episodic memory state that retrieval is contingent on two independent processes: familiarity (providing a sense of oldness) and recollection (recovering events and their context). A variety of studies have reported distinct neural signatures for familiarity and recollection, supporting dual-process theory. One outstanding question is whether these signatures reflect the activation of distinct memory traces or the operation of different retrieval mechanisms on a single memory trace. We present a computational model that uses a single neuronal network to store memory traces, but two distinct and independent retrieval processes access the memory. The model is capable of performing familiarity and recollection-based discrimination between old and new patterns, demonstrating that dual-process models need not to rely on multiple independent memory traces, but can use a single trace. Importantly, our putative familiarity and recollection processes exhibit distinct characteristics analogous to those found in empirical data; they diverge in capacity and sensitivity to sparse and correlated patterns, exhibit distinct ROC curves, and account for performance on both item and associative recognition tests. The demonstration that a single-trace, dual-process model can account for a range of empirical findings highlights the importance of distinguishing between neuronal processes and the neuronal representations on which they operate.
Converging levels of analysis in the cognitive neuroscience of visual attention.
Duncan, J
1998-01-01
Experiments using behavioural, lesion, functional imaging and single neuron methods are considered in the context of a neuropsychological model of visual attention. According to this model, inputs compete for representation in multiple visually responsive brain systems, sensory and motor, cortical and subcortical. Competition is biased by advance priming of neurons responsive to current behavioural targets. Across systems competition is integrated such that the same, selected object tends to become dominant throughout. The behavioural studies reviewed concern divided attention within and between modalities. They implicate within-modality competition as one main restriction on concurrent stimulus identification. In contrast to the conventional association of lateral attentional focus with parietal lobe function, the lesion studies show attentional bias to be a widespread consequence of unilateral cortical damage. Although the clinical syndrome of unilateral neglect may indeed be associated with parietal lesions, this probably reflects an assortment of further deficits accompanying a simple attentional imbalance. The functional imaging studies show joint involvement of lateral prefrontal and occipital cortex in lateral attentional focus and competition. The single unit studies suggest how competition in several regions of extrastriate cortex is biased by advance priming of neurons responsive to current behavioural targets. Together, the concepts of competition, priming and integration allow a unified theoretical approach to findings from behavioural to single neuron levels. PMID:9770224
Schumacher, Joseph W.; Schneider, David M.
2011-01-01
The majority of sensory physiology experiments have used anesthesia to facilitate the recording of neural activity. Current techniques allow researchers to study sensory function in the context of varying behavioral states. To reconcile results across multiple behavioral and anesthetic states, it is important to consider how and to what extent anesthesia plays a role in shaping neural response properties. The role of anesthesia has been the subject of much debate, but the extent to which sensory coding properties are altered by anesthesia has yet to be fully defined. In this study we asked how urethane, an anesthetic commonly used for avian and mammalian sensory physiology, affects the coding of complex communication vocalizations (songs) and simple artificial stimuli in the songbird auditory midbrain. We measured spontaneous and song-driven spike rates, spectrotemporal receptive fields, and neural discriminability from responses to songs in single auditory midbrain neurons. In the same neurons, we recorded responses to pure tone stimuli ranging in frequency and intensity. Finally, we assessed the effect of urethane on population-level representations of birdsong. Results showed that intrinsic neural excitability is significantly depressed by urethane but that spectral tuning, single neuron discriminability, and population representations of song do not differ significantly between unanesthetized and anesthetized animals. PMID:21543752
Mameli, Ombretta; Caria, Marcello A; Biagi, Francesca; Zedda, Marco; Farina, Vittorio
2017-05-01
It has been recently shown in rats that spontaneous movements of whisker pad macrovibrissae elicited evoked responses in the trigeminal mesencephalic nucleus (Me5). In the present study, electrophysiological and neuroanatomical experiments were performed in anesthetized rats to evaluate whether, besides the whisker displacement per se, the Me5 neurons are also involved in encoding the kinematic properties of macrovibrissae movements, and also whether, as reported for the trigeminal ganglion, even within the Me5 nucleus exists a neuroanatomical representation of the whisker pad macrovibrissae. Extracellular electrical activity of single Me5 neurons was recorded before, during, and after mechanical deflection of the ipsilateral whisker pad macrovibrissae in different directions, and with different velocities and amplitudes. In several groups of animals, single or multiple injections of the tracer Dil were performed into the whisker pad of one side, in close proximity to the vibrissae follicles, in order to label the peripheral terminals of the Me5 neurons innervating the macrovibrissae (whisking-neurons), and therefore, the respective perikaria within the nucleus. Results showed that: (1) the whisker pad macrovibrissae were represented in the medial-caudal part of the Me5 nucleus by a single cluster of cells whose number seemed to match that of the macrovibrissae; (2) macrovibrissae mechanical deflection elicited significant responses in the Me5 whisking-neurons, which were related to the direction, amplitude, and frequency of the applied deflection. The specific functional role of Me5 neurons involved in encoding proprioceptive information arising from the macrovibrissae movements is discussed within the framework of the whole trigeminal nuclei activities. © 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.
Firing patterns in the adaptive exponential integrate-and-fire model.
Naud, Richard; Marcille, Nicolas; Clopath, Claudia; Gerstner, Wulfram
2008-11-01
For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.
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
Mouse Visual Neocortex Supports Multiple Stereotyped Patterns of Microcircuit Activity
Sadovsky, Alexander J.
2014-01-01
Spiking correlations between neocortical neurons provide insight into the underlying synaptic connectivity that defines cortical microcircuitry. Here, using two-photon calcium fluorescence imaging, we observed the simultaneous dynamics of hundreds of neurons in slices of mouse primary visual cortex (V1). Consistent with a balance of excitation and inhibition, V1 dynamics were characterized by a linear scaling between firing rate and circuit size. Using lagged firing correlations between neurons, we generated functional wiring diagrams to evaluate the topological features of V1 microcircuitry. We found that circuit connectivity exhibited both cyclic graph motifs, indicating recurrent wiring, and acyclic graph motifs, indicating feedforward wiring. After overlaying the functional wiring diagrams onto the imaged field of view, we found properties consistent with Rentian scaling: wiring diagrams were topologically efficient because they minimized wiring with a modular architecture. Within single imaged fields of view, V1 contained multiple discrete circuits that were overlapping and highly interdigitated but were still distinct from one another. The majority of neurons that were shared between circuits displayed peri-event spiking activity whose timing was specific to the active circuit, whereas spike times for a smaller percentage of neurons were invariant to circuit identity. These data provide evidence that V1 microcircuitry exhibits balanced dynamics, is efficiently arranged in anatomical space, and is capable of supporting a diversity of multineuron spike firing patterns from overlapping sets of neurons. PMID:24899701
Dal Maschio, Marco; Donovan, Joseph C; Helmbrecht, Thomas O; Baier, Herwig
2017-05-17
We introduce a flexible method for high-resolution interrogation of circuit function, which combines simultaneous 3D two-photon stimulation of multiple targeted neurons, volumetric functional imaging, and quantitative behavioral tracking. This integrated approach was applied to dissect how an ensemble of premotor neurons in the larval zebrafish brain drives a basic motor program, the bending of the tail. We developed an iterative photostimulation strategy to identify minimal subsets of channelrhodopsin (ChR2)-expressing neurons that are sufficient to initiate tail movements. At the same time, the induced network activity was recorded by multiplane GCaMP6 imaging across the brain. From this dataset, we computationally identified activity patterns associated with distinct components of the elicited behavior and characterized the contributions of individual neurons. Using photoactivatable GFP (paGFP), we extended our protocol to visualize single functionally identified neurons and reconstruct their morphologies. Together, this toolkit enables linking behavior to circuit activity with unprecedented resolution. Copyright © 2017 Elsevier Inc. All rights reserved.
Ozbay, Baris N; Futia, Gregory L; Ma, Ming; Bright, Victor M; Gopinath, Juliet T; Hughes, Ethan G; Restrepo, Diego; Gibson, Emily A
2018-05-25
We present a miniature head mounted two-photon fiber-coupled microscope (2P-FCM) for neuronal imaging with active axial focusing enabled using a miniature electrowetting lens. We show three-dimensional two-photon imaging of neuronal structure and record neuronal activity from GCaMP6s fluorescence from multiple focal planes in a freely-moving mouse. Two-color simultaneous imaging of GFP and tdTomato fluorescence is also demonstrated. Additionally, dynamic control of the axial scanning of the electrowetting lens allows tilting of the focal plane enabling neurons in multiple depths to be imaged in a single plane. Two-photon imaging allows increased penetration depth in tissue yielding a working distance of 450 μm with an additional 180 μm of active axial focusing. The objective NA is 0.45 with a lateral resolution of 1.8 μm, an axial resolution of 10 μm, and a field-of-view of 240 μm diameter. The 2P-FCM has a weight of only ~2.5 g and is capable of repeatable and stable head-attachment. The 2P-FCM with dynamic axial scanning provides a new capability to record from functionally distinct neuronal layers, opening new opportunities in neuroscience research.
Real-time Seizure Detection System Using Multiple Single-Neuron Recordings
2001-10-25
electrodes were implanted bilaterally into the temporal lobe of each rat. The rats were anesthetized with nebutal (50mg/kg). Small craniotomies were...1997. [9] Fanselow, E.E., Reid, A.P., Nicolelis, M.A.L., Reduction of pentylenetetrazole-induced seizure activity in awake rats by seizure-triggered
Multiplexed Neurochemical Signaling by Neurons of the Ventral Tegmental Area
Barker, David J.; Root, David H.; Zhang, Shiliang; Morales, Marisela
2016-01-01
The ventral tegmental area (VTA) is an evolutionarily conserved structure that has roles in reward-seeking, safety-seeking, learning, motivation, and neuropsychiatric disorders such as addiction and depression. The involvement of the VTA in these various behaviors and disorders is paralleled by its diverse signaling mechanisms. Here we review recent advances in our understanding of neuronal diversity in the VTA with a focus on cell phenotypes that participate in ‘multiplexed’ neurotransmission involving distinct signaling mechanisms. First, we describe the cellular diversity within the VTA, including neurons capable of transmitting dopamine, glutamate or GABA as well as neurons capable of multiplexing combinations of these neurotransmitters. Next, we describe the complex synaptic architecture used by VTA neurons in order to accommodate the transmission of multiple transmitters. We specifically cover recent findings showing that VTA multiplexed neurotransmission may be mediated by either the segregation of dopamine and glutamate into distinct microdomains within a single axon or by the integration of glutamate and GABA into a single axon terminal. In addition, we discuss our current understanding of the functional role that these multiplexed signaling pathways have in the lateral habenula and the nucleus accumbens. Finally, we consider the putative roles of VTA multiplexed neurotransmission in synaptic plasticity and discuss how changes in VTA multiplexed neurons may relate to various psychopathologies including drug addiction and depression. PMID:26763116
A stochastic-field description of finite-size spiking neural networks
Longtin, André
2017-01-01
Neural network dynamics are governed by the interaction of spiking neurons. Stochastic aspects of single-neuron dynamics propagate up to the network level and shape the dynamical and informational properties of the population. Mean-field models of population activity disregard the finite-size stochastic fluctuations of network dynamics and thus offer a deterministic description of the system. Here, we derive a stochastic partial differential equation (SPDE) describing the temporal evolution of the finite-size refractory density, which represents the proportion of neurons in a given refractory state at any given time. The population activity—the density of active neurons per unit time—is easily extracted from this refractory density. The SPDE includes finite-size effects through a two-dimensional Gaussian white noise that acts both in time and along the refractory dimension. For an infinite number of neurons the standard mean-field theory is recovered. A discretization of the SPDE along its characteristic curves allows direct simulations of the activity of large but finite spiking networks; this constitutes the main advantage of our approach. Linearizing the SPDE with respect to the deterministic asynchronous state allows the theoretical investigation of finite-size activity fluctuations. In particular, analytical expressions for the power spectrum and autocorrelation of activity fluctuations are obtained. Moreover, our approach can be adapted to incorporate multiple interacting populations and quasi-renewal single-neuron dynamics. PMID:28787447
Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing.
Renthal, William
2018-01-01
Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.
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.
Visualizing the spinal neuronal dynamics of locomotion
NASA Astrophysics Data System (ADS)
Subramanian, Kalpathi R.; Bashor, D. P.; Miller, M. T.; Foster, J. A.
2004-06-01
Modern imaging and simulation techniques have enhanced system-level understanding of neural function. In this article, we present an application of interactive visualization to understanding neuronal dynamics causing locomotion of a single hip joint, based on pattern generator output of the spinal cord. Our earlier work visualized cell-level responses of multiple neuronal populations. However, the spatial relationships were abstract, making communication with colleagues difficult. We propose two approaches to overcome this: (1) building a 3D anatomical model of the spinal cord with neurons distributed inside, animated by the simulation and (2) adding limb movements predicted by neuronal activity. The new system was tested using a cat walking central pattern generator driving a pair of opposed spinal motoneuron pools. Output of opposing motoneuron pools was combined into a single metric, called "Net Neural Drive", which generated angular limb movement in proportion to its magnitude. Net neural drive constitutes a new description of limb movement control. The combination of spatial and temporal information in the visualizations elegantly conveys the neural activity of the output elements (motoneurons), as well as the resulting movement. The new system encompasses five biological levels of organization from ion channels to observed behavior. The system is easily scalable, and provides an efficient interactive platform for rapid hypothesis testing.
NASA Astrophysics Data System (ADS)
Tan, Xiaodong; Xia, Nan; Young, Hunter; Richter, Claus-Peter
2015-02-01
Auditory prostheses may benefit from Infrared Neural Stimulation (INS) because optical stimulation allows for spatially selective activation of neuron populations. Selective activation of neurons in the cochlear spiral ganglion can be determined in the central nucleus of the inferior colliculus (ICC) because the tonotopic organization of frequencies in the cochlea is maintained throughout the auditory pathway. The activation profile of INS is well represented in the ICC by multichannel electrodes (MCEs). To characterize single unit properties in response to INS, however, single tungsten electrodes (STEs) should be used because of its better signal-to-noise ratio. In this study, we compared the temporal properties of ICC single units recorded with MCEs and STEs in order to characterize the response properties of single auditory neurons in response to INS in guinea pigs. The length along the cochlea stimulated with infrared radiation corresponded to a frequency range of about 0.6 octaves, similar to that recorded with STEs. The temporal properties of single units recorded with MCEs showed higher maximum rates, shorter latencies, and higher firing efficiencies compared to those recorded with STEs. When the preset amplitude threshold for triggering MCE recordings was raised to twice over the noise level, the temporal properties of the single units became similar to those obtained with STEs. Undistinguishable neural activities from multiple sources in MCE recordings could be responsible for the response property difference between MCEs and STEs. Thus, caution should be taken in single unit recordings with MCEs.
Baker, Christa A.
2014-01-01
A variety of synaptic mechanisms can contribute to single-neuron selectivity for temporal intervals in sensory stimuli. However, it remains unknown how these mechanisms interact to establish single-neuron sensitivity to temporal patterns of sensory stimulation in vivo. Here we address this question in a circuit that allows us to control the precise temporal patterns of synaptic input to interval-tuned neurons in behaviorally relevant ways. We obtained in vivo intracellular recordings under multiple levels of current clamp from midbrain neurons in the mormyrid weakly electric fish Brienomyrus brachyistius during stimulation with electrosensory pulse trains. To reveal the excitatory and inhibitory inputs onto interval-tuned neurons, we then estimated the synaptic conductances underlying responses. We found short-term depression in excitatory and inhibitory pathways onto all interval-tuned neurons. Short-interval selectivity was associated with excitation that depressed less than inhibition at short intervals, as well as temporally summating excitation. Long-interval selectivity was associated with long-lasting onset inhibition. We investigated tuning after separately nullifying the contributions of temporal summation and depression, and found the greatest diversity of interval selectivity among neurons when both mechanisms were at play. Furthermore, eliminating the effects of depression decreased sensitivity to directional changes in interval. These findings demonstrate that variation in depression and summation of excitation and inhibition helps to establish tuning to behaviorally relevant intervals in communication signals, and that depression contributes to neural coding of interval sequences. This work reveals for the first time how the interplay between short-term plasticity and temporal summation mediates the decoding of temporal sequences in awake, behaving animals. PMID:25339741
Kaabi, Mohamed Ghaith; Tonnelier, Arnaud; Martinez, Dominique
2011-05-01
In traditional event-driven strategies, spike timings are analytically given or calculated with arbitrary precision (up to machine precision). Exact computation is possible only for simplified neuron models, mainly the leaky integrate-and-fire model. In a recent paper, Zheng, Tonnelier, and Martinez (2009) introduced an approximate event-driven strategy, named voltage stepping, that allows the generic simulation of nonlinear spiking neurons. Promising results were achieved in the simulation of single quadratic integrate-and-fire neurons. Here, we assess the performance of voltage stepping in network simulations by considering more complex neurons (quadratic integrate-and-fire neurons with adaptation) coupled with multiple synapses. To handle the discrete nature of synaptic interactions, we recast voltage stepping in a general framework, the discrete event system specification. The efficiency of the method is assessed through simulations and comparisons with a modified time-stepping scheme of the Runge-Kutta type. We demonstrated numerically that the original order of voltage stepping is preserved when simulating connected spiking neurons, independent of the network activity and connectivity.
Structured networks support sparse traveling waves in rodent somatosensory cortex.
Moldakarimov, Samat; Bazhenov, Maxim; Feldman, Daniel E; Sejnowski, Terrence J
2018-05-15
Neurons responding to different whiskers are spatially intermixed in the superficial layer 2/3 (L2/3) of the rodent barrel cortex, where a single whisker deflection activates a sparse, distributed neuronal population that spans multiple cortical columns. How the superficial layer of the rodent barrel cortex is organized to support such distributed sensory representations is not clear. In a computer model, we tested the hypothesis that sensory representations in L2/3 of the rodent barrel cortex are formed by activity propagation horizontally within L2/3 from a site of initial activation. The model explained the observed properties of L2/3 neurons, including the low average response probability in the majority of responding L2/3 neurons, and the existence of a small subset of reliably responding L2/3 neurons. Sparsely propagating traveling waves similar to those observed in L2/3 of the rodent barrel cortex occurred in the model only when a subnetwork of strongly connected neurons was immersed in a much larger network of weakly connected neurons.
Passive dendrites enable single neurons to compute linearly non-separable functions.
Cazé, Romain Daniel; Humphries, Mark; Gutkin, Boris
2013-01-01
Local supra-linear summation of excitatory inputs occurring in pyramidal cell dendrites, the so-called dendritic spikes, results in independent spiking dendritic sub-units, which turn pyramidal neurons into two-layer neural networks capable of computing linearly non-separable functions, such as the exclusive OR. Other neuron classes, such as interneurons, may possess only a few independent dendritic sub-units, or only passive dendrites where input summation is purely sub-linear, and where dendritic sub-units are only saturating. To determine if such neurons can also compute linearly non-separable functions, we enumerate, for a given parameter range, the Boolean functions implementable by a binary neuron model with a linear sub-unit and either a single spiking or a saturating dendritic sub-unit. We then analytically generalize these numerical results to an arbitrary number of non-linear sub-units. First, we show that a single non-linear dendritic sub-unit, in addition to the somatic non-linearity, is sufficient to compute linearly non-separable functions. Second, we analytically prove that, with a sufficient number of saturating dendritic sub-units, a neuron can compute all functions computable with purely excitatory inputs. Third, we show that these linearly non-separable functions can be implemented with at least two strategies: one where a dendritic sub-unit is sufficient to trigger a somatic spike; another where somatic spiking requires the cooperation of multiple dendritic sub-units. We formally prove that implementing the latter architecture is possible with both types of dendritic sub-units whereas the former is only possible with spiking dendrites. Finally, we show how linearly non-separable functions can be computed by a generic two-compartment biophysical model and a realistic neuron model of the cerebellar stellate cell interneuron. Taken together our results demonstrate that passive dendrites are sufficient to enable neurons to compute linearly non-separable functions.
Passive Dendrites Enable Single Neurons to Compute Linearly Non-separable Functions
Cazé, Romain Daniel; Humphries, Mark; Gutkin, Boris
2013-01-01
Local supra-linear summation of excitatory inputs occurring in pyramidal cell dendrites, the so-called dendritic spikes, results in independent spiking dendritic sub-units, which turn pyramidal neurons into two-layer neural networks capable of computing linearly non-separable functions, such as the exclusive OR. Other neuron classes, such as interneurons, may possess only a few independent dendritic sub-units, or only passive dendrites where input summation is purely sub-linear, and where dendritic sub-units are only saturating. To determine if such neurons can also compute linearly non-separable functions, we enumerate, for a given parameter range, the Boolean functions implementable by a binary neuron model with a linear sub-unit and either a single spiking or a saturating dendritic sub-unit. We then analytically generalize these numerical results to an arbitrary number of non-linear sub-units. First, we show that a single non-linear dendritic sub-unit, in addition to the somatic non-linearity, is sufficient to compute linearly non-separable functions. Second, we analytically prove that, with a sufficient number of saturating dendritic sub-units, a neuron can compute all functions computable with purely excitatory inputs. Third, we show that these linearly non-separable functions can be implemented with at least two strategies: one where a dendritic sub-unit is sufficient to trigger a somatic spike; another where somatic spiking requires the cooperation of multiple dendritic sub-units. We formally prove that implementing the latter architecture is possible with both types of dendritic sub-units whereas the former is only possible with spiking dendrites. Finally, we show how linearly non-separable functions can be computed by a generic two-compartment biophysical model and a realistic neuron model of the cerebellar stellate cell interneuron. Taken together our results demonstrate that passive dendrites are sufficient to enable neurons to compute linearly non-separable functions. PMID:23468600
Single-cell axotomy of cultured hippocampal neurons integrated in neuronal circuits.
Gomis-Rüth, Susana; Stiess, Michael; Wierenga, Corette J; Meyn, Liane; Bradke, Frank
2014-05-01
An understanding of the molecular mechanisms of axon regeneration after injury is key for the development of potential therapies. Single-cell axotomy of dissociated neurons enables the study of the intrinsic regenerative capacities of injured axons. This protocol describes how to perform single-cell axotomy on dissociated hippocampal neurons containing synapses. Furthermore, to axotomize hippocampal neurons integrated in neuronal circuits, we describe how to set up coculture with a few fluorescently labeled neurons. This approach allows axotomy of single cells in a complex neuronal network and the observation of morphological and molecular changes during axon regeneration. Thus, single-cell axotomy of mature neurons is a valuable tool for gaining insights into cell intrinsic axon regeneration and the plasticity of neuronal polarity of mature neurons. Dissociation of the hippocampus and plating of hippocampal neurons takes ∼2 h. Neurons are then left to grow for 2 weeks, during which time they integrate into neuronal circuits. Subsequent axotomy takes 10 min per neuron and further imaging takes 10 min per neuron.
Dynamics of feature categorization.
Martí, Daniel; Rinzel, John
2013-01-01
In visual and auditory scenes, we are able to identify shared features among sensory objects and group them according to their similarity. This grouping is preattentive and fast and is thought of as an elementary form of categorization by which objects sharing similar features are clustered in some abstract perceptual space. It is unclear what neuronal mechanisms underlie this fast categorization. Here we propose a neuromechanistic model of fast feature categorization based on the framework of continuous attractor networks. The mechanism for category formation does not rely on learning and is based on biologically plausible assumptions, for example, the existence of populations of neurons tuned to feature values, feature-specific interactions, and subthreshold-evoked responses upon the presentation of single objects. When the network is presented with a sequence of stimuli characterized by some feature, the network sums the evoked responses and provides a running estimate of the distribution of features in the input stream. If the distribution of features is structured into different components or peaks (i.e., is multimodal), recurrent excitation amplifies the response of activated neurons, and categories are singled out as emerging localized patterns of elevated neuronal activity (bumps), centered at the centroid of each cluster. The emergence of bump states through sequential, subthreshold activation and the dependence on input statistics is a novel application of attractor networks. We show that the extraction and representation of multiple categories are facilitated by the rich attractor structure of the network, which can sustain multiple stable activity patterns for a robust range of connectivity parameters compatible with cortical physiology.
Two-population model for medial temporal lobe neurons: The vast majority are almost silent
NASA Astrophysics Data System (ADS)
Magyar, Andrew; Collins, John
2015-07-01
Recordings in the human medial temporal lobe have found many neurons that respond to pictures (and related stimuli) of just one particular person of those presented. It has been proposed that these are concept cells, responding to just a single concept. However, a direct experimental test of the concept cell idea appears impossible, because it would need the measurement of the response of each cell to enormous numbers of other stimuli. Here we propose a new statistical method for analysis of the data that gives a more powerful way to analyze how close data are to the concept-cell idea. Central to the model is the neuronal sparsity, defined as the total fraction of stimuli that elicit an above-threshold response in the neuron. The model exploits the large number of sampled neurons to give sensitivity to situations where the average response sparsity is much less than one response for the number of presented stimuli. We show that a conventional model where a single sparsity is postulated for all neurons gives an extremely poor fit to the data. In contrast, a model with two dramatically different populations gives an excellent fit to data from the hippocampus and entorhinal cortex. In the hippocampus, one population has 7% of the cells with a 2.6% sparsity. But a much larger fraction (93%) respond to only 0.1% of the stimuli. This can result in an extreme bias in the responsiveness of reported neurons compared with a typical neuron. Finally, we show how to allow for the fact that some identified units correspond to multiple neurons and find that our conclusions at the neural level are quantitatively changed but strengthened, with an even stronger difference between the two populations.
Method of analysis of local neuronal circuits in the vertebrate central nervous system.
Reinis, S; Weiss, D S; McGaraughty, S; Tsoukatos, J
1992-06-01
Although a considerable amount of knowledge has been accumulated about the activity of individual nerve cells in the brain, little is known about their mutual interactions at the local level. The method presented in this paper allows the reconstruction of functional relations within a group of neurons as recorded by a single microelectrode. Data are sampled at 10 or 13 kHz. Prominent spikes produced by one or more single cells are selected and sorted by K-means cluster analysis. The activities of single cells are then related to the background firing of neurons in their vicinity. Auto-correlograms of the leading cells, auto-correlograms of the background cells (mass correlograms) and cross-correlograms between these two levels of firing are computed and evaluated. The statistical probability of mutual interactions is determined, and the statistically significant, most common interspike intervals are stored and attributed to real pairs of spikes in the original record. Selected pairs of spikes, characterized by statistically significant intervals between them, are then assembled into a working model of the system. This method has revealed substantial differences between the information processing in the visual cortex, the inferior colliculus, the rostral ventromedial medulla and the ventrobasal complex of the thalamus. Even short 1-s records of the multiple neuronal activity may provide meaningful and statistically significant results.
Estrogen receptors in neuropeptide Y neurons: at the crossroads of feeding and reproduction.
Acosta-Martinez, Maricedes; Horton, Teresa; Levine, Jon E
2007-03-01
Hypothalamic neuropeptide Y (NPY) neurons function as physiological integrators in at least two different neuroendocrine systems - one governing feeding and the other controlling reproduction. Estrogen might modulate both systems by regulating NPY gene expression; it might reduce food intake by suppressing NPY expression, and evoke reproductive hormone surges by stimulating it. How can estrogen exert opposing effects in an ostensibly homogeneous NPY neuronal population? Recent work with immortalized NPY-producing cells suggests that the ratio of estrogen receptor alpha:estrogen receptor beta can determine the direction and temporal pattern of transcriptional responses to estrogen. Because this ratio might itself be physiologically regulated, these findings provide one explanation for multiple neuropeptidergic responses to a single steroid hormone.
Plavicki, Jessica; Mader, Sara; Pueschel, Eric; Peebles, Patrick; Boekhoff-Falk, Grace
2012-01-01
Vertebrate Dlx genes have been implicated in the differentiation of multiple neuronal subtypes, including cortical GABAergic interneurons, and mutations in Dlx genes have been linked to clinical conditions such as epilepsy and autism. Here we show that the single Drosophila Dlx homolog, distal-less, is required both to specify chemosensory neurons and to regulate the morphologies of their axons and dendrites. We establish that distal-less is necessary for development of the mushroom body, a brain region that processes olfactory information. These are important examples of distal-less function in an invertebrate nervous system and demonstrate that the Drosophila larval olfactory system is a powerful model in which to understand distal-less functions during neurogenesis. PMID:22307614
Estimation of the phase response curve from Parkinsonian tremor.
Saifee, Tabish A; Edwards, Mark J; Kassavetis, Panagiotis; Gilbertson, Tom
2016-01-01
Phase response curves (PRCs), characterizing the response of an oscillator to weak external perturbation, have been estimated from a broad range of biological oscillators, including single neurons in vivo. PRC estimates, in turn, provide an intuitive insight into how oscillatory systems become entrained and how they can be desynchronized. Here, we explore the application of PRC theory to the case of Parkinsonian tremor. Initial attempts to establish a causal effect of subthreshold transcranial magnetic stimulation applied to primary motor cortex on the filtered tremor phase were unsuccessful. We explored the possible explanations of this and demonstrate that assumptions made when estimating the PRC in a traditional setting, such as a single neuron, are not arbitrary when applied to the case of tremor PRC estimation. We go on to extract the PRC of Parkinsonian tremor using an iterative method that requires varying the definition of the tremor cycle and estimating the PRC at multiple peristimulus time samples. Justification for this method is supported by estimates of PRC from simulated single neuron data. We provide an approach to estimating confidence limits for tremor PRC and discuss the interpretational caveats introduced by tremor harmonics and the intrinsic variability of the tremor's period. Copyright © 2016 the American Physiological Society.
Estimation of the phase response curve from Parkinsonian tremor
Saifee, Tabish A.; Edwards, Mark J.; Kassavetis, Panagiotis
2015-01-01
Phase response curves (PRCs), characterizing the response of an oscillator to weak external perturbation, have been estimated from a broad range of biological oscillators, including single neurons in vivo. PRC estimates, in turn, provide an intuitive insight into how oscillatory systems become entrained and how they can be desynchronized. Here, we explore the application of PRC theory to the case of Parkinsonian tremor. Initial attempts to establish a causal effect of subthreshold transcranial magnetic stimulation applied to primary motor cortex on the filtered tremor phase were unsuccessful. We explored the possible explanations of this and demonstrate that assumptions made when estimating the PRC in a traditional setting, such as a single neuron, are not arbitrary when applied to the case of tremor PRC estimation. We go on to extract the PRC of Parkinsonian tremor using an iterative method that requires varying the definition of the tremor cycle and estimating the PRC at multiple peristimulus time samples. Justification for this method is supported by estimates of PRC from simulated single neuron data. We provide an approach to estimating confidence limits for tremor PRC and discuss the interpretational caveats introduced by tremor harmonics and the intrinsic variability of the tremor's period. PMID:26561596
Intrinsic Neuronal Properties Switch the Mode of Information Transmission in Networks
Gjorgjieva, Julijana; Mease, Rebecca A.; Moody, William J.; Fairhall, Adrienne L.
2014-01-01
Diverse ion channels and their dynamics endow single neurons with complex biophysical properties. These properties determine the heterogeneity of cell types that make up the brain, as constituents of neural circuits tuned to perform highly specific computations. How do biophysical properties of single neurons impact network function? We study a set of biophysical properties that emerge in cortical neurons during the first week of development, eventually allowing these neurons to adaptively scale the gain of their response to the amplitude of the fluctuations they encounter. During the same time period, these same neurons participate in large-scale waves of spontaneously generated electrical activity. We investigate the potential role of experimentally observed changes in intrinsic neuronal properties in determining the ability of cortical networks to propagate waves of activity. We show that such changes can strongly affect the ability of multi-layered feedforward networks to represent and transmit information on multiple timescales. With properties modeled on those observed at early stages of development, neurons are relatively insensitive to rapid fluctuations and tend to fire synchronously in response to wave-like events of large amplitude. Following developmental changes in voltage-dependent conductances, these same neurons become efficient encoders of fast input fluctuations over few layers, but lose the ability to transmit slower, population-wide input variations across many layers. Depending on the neurons' intrinsic properties, noise plays different roles in modulating neuronal input-output curves, which can dramatically impact network transmission. The developmental change in intrinsic properties supports a transformation of a networks function from the propagation of network-wide information to one in which computations are scaled to local activity. This work underscores the significance of simple changes in conductance parameters in governing how neurons represent and propagate information, and suggests a role for background synaptic noise in switching the mode of information transmission. PMID:25474701
Cell-intrinsic mechanisms of temperature compensation in a grasshopper sensory receptor neuron
Roemschied, Frederic A; Eberhard, Monika JB; Schleimer, Jan-Hendrik; Ronacher, Bernhard; Schreiber, Susanne
2014-01-01
Changes in temperature affect biochemical reaction rates and, consequently, neural processing. The nervous systems of poikilothermic animals must have evolved mechanisms enabling them to retain their functionality under varying temperatures. Auditory receptor neurons of grasshoppers respond to sound in a surprisingly temperature-compensated manner: firing rates depend moderately on temperature, with average Q10 values around 1.5. Analysis of conductance-based neuron models reveals that temperature compensation of spike generation can be achieved solely relying on cell-intrinsic processes and despite a strong dependence of ion conductances on temperature. Remarkably, this type of temperature compensation need not come at an additional metabolic cost of spike generation. Firing rate-based information transfer is likely to increase with temperature and we derive predictions for an optimal temperature dependence of the tympanal transduction process fostering temperature compensation. The example of auditory receptor neurons demonstrates how neurons may exploit single-cell mechanisms to cope with multiple constraints in parallel. DOI: http://dx.doi.org/10.7554/eLife.02078.001 PMID:24843016
NASA Astrophysics Data System (ADS)
Xiang, Shuiying; Wen, Aijun; Zhang, Hao; Li, Jiafu; Guo, Xingxing; Shang, Lei; Lin, Lin
2016-11-01
The polarization-resolved nonlinear dynamics of vertical-cavity surface-emitting lasers (VCSELs) subject to orthogonally polarized optical pulse injection are investigated numerically based on the spin flip model. By extensive numerical bifurcation analysis, the responses dynamics of photonic neuron based on VCSELs under the arrival of external stimuli of orthogonally polarized optical pulse injection are mainly discussed. It is found that, several neuron-like dynamics, such as phasic spiking of a single abrupt large amplitude pulse followed with or without subthreshold oscillation, and tonic spiking with multiple periodic pulses, are successfully reproduced in the numerical model of VCSELs. Besides, the effects of stimuli strength, pump current, frequency detuning, as well as the linewidth enhancement factor on the neuron-like response dynamics are examined carefully. The operating parameters ranges corresponding to different neuron-like dynamics are further identified. Thus, the numerical model and simulation results are very useful and interesting for the ultrafast brain-inspired neuromorphic photonics systems based on VCSELs.
Charoenkwan, Phasit; Hwang, Eric; Cutler, Robert W; Lee, Hua-Chin; Ko, Li-Wei; Huang, Hui-Ling; Ho, Shinn-Ying
2013-01-01
High-content screening (HCS) has become a powerful tool for drug discovery. However, the discovery of drugs targeting neurons is still hampered by the inability to accurately identify and quantify the phenotypic changes of multiple neurons in a single image (named multi-neuron image) of a high-content screen. Therefore, it is desirable to develop an automated image analysis method for analyzing multi-neuron images. We propose an automated analysis method with novel descriptors of neuromorphology features for analyzing HCS-based multi-neuron images, called HCS-neurons. To observe multiple phenotypic changes of neurons, we propose two kinds of descriptors which are neuron feature descriptor (NFD) of 13 neuromorphology features, e.g., neurite length, and generic feature descriptors (GFDs), e.g., Haralick texture. HCS-neurons can 1) automatically extract all quantitative phenotype features in both NFD and GFDs, 2) identify statistically significant phenotypic changes upon drug treatments using ANOVA and regression analysis, and 3) generate an accurate classifier to group neurons treated by different drug concentrations using support vector machine and an intelligent feature selection method. To evaluate HCS-neurons, we treated P19 neurons with nocodazole (a microtubule depolymerizing drug which has been shown to impair neurite development) at six concentrations ranging from 0 to 1000 ng/mL. The experimental results show that all the 13 features of NFD have statistically significant difference with respect to changes in various levels of nocodazole drug concentrations (NDC) and the phenotypic changes of neurites were consistent to the known effect of nocodazole in promoting neurite retraction. Three identified features, total neurite length, average neurite length, and average neurite area were able to achieve an independent test accuracy of 90.28% for the six-dosage classification problem. This NFD module and neuron image datasets are provided as a freely downloadable MatLab project at http://iclab.life.nctu.edu.tw/HCS-Neurons. Few automatic methods focus on analyzing multi-neuron images collected from HCS used in drug discovery. We provided an automatic HCS-based method for generating accurate classifiers to classify neurons based on their phenotypic changes upon drug treatments. The proposed HCS-neurons method is helpful in identifying and classifying chemical or biological molecules that alter the morphology of a group of neurons in HCS.
Nanosecond laser pulse stimulation of spiral ganglion neurons and model cells.
Rettenmaier, Alexander; Lenarz, Thomas; Reuter, Günter
2014-04-01
Optical stimulation of the inner ear has recently attracted attention, suggesting a higher frequency resolution compared to electrical cochlear implants due to its high spatial stimulation selectivity. Although the feasibility of the effect is shown in multiple in vivo experiments, the stimulation mechanism remains open to discussion. Here we investigate in single-cell measurements the reaction of spiral ganglion neurons and model cells to irradiation with a nanosecond-pulsed laser beam over a broad wavelength range from 420 nm up to 1950 nm using the patch clamp technique. Cell reactions were wavelength- and pulse-energy-dependent but too small to elicit action potentials in the investigated spiral ganglion neurons. As the applied radiant exposure was much higher than the reported threshold for in vivo experiments in the same laser regime, we conclude that in a stimulation paradigm with nanosecond-pulses, direct neuronal stimulation is not the main cause of optical cochlea stimulation.
Bottom-up and Top-down Input Augment the Variability of Cortical Neurons
Nassi, Jonathan J.; Kreiman, Gabriel; Born, Richard T.
2016-01-01
SUMMARY Neurons in the cerebral cortex respond inconsistently to a repeated sensory stimulus, yet they underlie our stable sensory experiences. Although the nature of this variability is unknown, its ubiquity has encouraged the general view that each cell produces random spike patterns that noisily represent its response rate. In contrast, here we show that reversibly inactivating distant sources of either bottom-up or top-down input to cortical visual areas in the alert primate reduces both the spike train irregularity and the trial-to-trial variability of single neurons. A simple model in which a fraction of the pre-synaptic input is silenced can reproduce this reduction in variability, provided that there exist temporal correlations primarily within, but not between, excitatory and inhibitory input pools. A large component of the variability of cortical neurons may therefore arise from synchronous input produced by signals arriving from multiple sources. PMID:27427459
Automated navigation of a glass micropipette on a high-density microelectrode array.
Jing Lin; Obien, Marie Engelene J; Hierlemann, Andreas; Frey, Urs
2015-08-01
High-density microelectrode arrays (HDMEAs) provide the capability to monitor the extracellular electric potential of multiple neurons at subcellular resolution over extended periods of time. In contrast, patch clamp allows for intracellular, sub-threshold recordings from a single patched neuron for very limited time on the order of an hour. Therefore, it will be beneficial to combine HDMEA and patch clamp for simultaneous intra- and extracellular recording of neuronal activity. Previously, it has been shown that the HDMEA can be used to localize and steer a glass micropipette towards a target location without using an optical microscope [1]. Here, we present an automated system, implemented in LabVIEW, which automatically locates and moves the glass micropipette towards a user-defined target. The presented system constitutes a first step towards developing an automated system to navigate a pipette to patch a neuron in vitro.
Hirabayashi, Toshiyuki; Tamura, Keita; Takeuchi, Daigo; Takeda, Masaki; Koyano, Kenji W; Miyashita, Yasushi
2014-07-09
In macaque monkeys, the anterior inferotemporal cortex, a region crucial for object memory processing, is composed of two adjacent, hierarchically distinct areas, TE and 36, for which different functional roles and neuronal responses in object memory tasks have been characterized. However, it remains unknown how the neuronal interactions differ between these areas during memory retrieval. Here, we conducted simultaneous recordings from multiple single-units in each of these areas while monkeys performed an object association memory task and examined the inter-area differences in neuronal interactions during the delay period. Although memory neurons showing sustained activity for the presented cue stimulus, cue-holding (CH) neurons, interacted with each other in both areas, only those neurons in area 36 interacted with another type of memory neurons coding for the to-be-recalled paired associate (pair-recall neurons) during memory retrieval. Furthermore, pairs of CH neurons in area TE showed functional coupling in response to each individual object during memory retention, whereas the same class of neuron pairs in area 36 exhibited a comparable strength of coupling in response to both associated objects. These results suggest predominant neuronal interactions in area 36 during the mnemonic processing, which may underlie the pivotal role of this brain area in both storage and retrieval of object association memory. Copyright © 2014 the authors 0270-6474/14/349377-12$15.00/0.
Viswanathan, Pooja; Nieder, Andreas
2017-12-01
The concept of receptive field (RF) describes the responsiveness of neurons to sensory space. Neurons in the primate association cortices have long been known to be spatially selective but a detailed characterisation and direct comparison of RFs between frontal and parietal association cortices are missing. We sampled the RFs of a large number of neurons from two interconnected areas of the frontal and parietal lobes, the dorsolateral prefrontal cortex (dlPFC) and ventral intraparietal area (VIP), of rhesus monkeys by systematically presenting a moving bar during passive fixation. We found that more than half of neurons in both areas showed spatial selectivity. Single neurons in both areas could be assigned to five classes according to the spatial response patterns: few non-uniform RFs with multiple discrete response maxima could be dissociated from the vast majority of uniform RFs showing a single maximum; the latter were further classified into full-field and confined foveal, contralateral and ipsilateral RFs. Neurons in dlPFC showed a preference for the contralateral visual space and collectively encoded the contralateral visual hemi-field. In contrast, VIP neurons preferred central locations, predominantly covering the foveal visual space. Putative pyramidal cells with broad-spiking waveforms in PFC had smaller RFs than putative interneurons showing narrow-spiking waveforms, but distributed similarly across the visual field. In VIP, however, both putative pyramidal cells and interneurons had similar RFs at similar eccentricities. We provide a first, thorough characterisation of visual RFs in two reciprocally connected areas of a fronto-parietal cortical network. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Responses of primate frontal cortex neurons during natural vocal communication.
Miller, Cory T; Thomas, A Wren; Nummela, Samuel U; de la Mothe, Lisa A
2015-08-01
The role of primate frontal cortex in vocal communication and its significance in language evolution have a controversial history. While evidence indicates that vocalization processing occurs in ventrolateral prefrontal cortex neurons, vocal-motor activity has been conjectured to be primarily subcortical and suggestive of a distinctly different neural architecture from humans. Direct evidence of neural activity during natural vocal communication is limited, as previous studies were performed in chair-restrained animals. Here we recorded the activity of single neurons across multiple regions of prefrontal and premotor cortex while freely moving marmosets engaged in a natural vocal behavior known as antiphonal calling. Our aim was to test whether neurons in marmoset frontal cortex exhibited responses during vocal-signal processing and/or vocal-motor production in the context of active, natural communication. We observed motor-related changes in single neuron activity during vocal production, but relatively weak sensory responses for vocalization processing during this natural behavior. Vocal-motor responses occurred both prior to and during call production and were typically coupled to the timing of each vocalization pulse. Despite the relatively weak sensory responses a population classifier was able to distinguish between neural activity that occurred during presentations of vocalization stimuli that elicited an antiphonal response and those that did not. These findings are suggestive of the role that nonhuman primate frontal cortex neurons play in natural communication and provide an important foundation for more explicit tests of the functional contributions of these neocortical areas during vocal behaviors. Copyright © 2015 the American Physiological Society.
Responses of primate frontal cortex neurons during natural vocal communication
Thomas, A. Wren; Nummela, Samuel U.; de la Mothe, Lisa A.
2015-01-01
The role of primate frontal cortex in vocal communication and its significance in language evolution have a controversial history. While evidence indicates that vocalization processing occurs in ventrolateral prefrontal cortex neurons, vocal-motor activity has been conjectured to be primarily subcortical and suggestive of a distinctly different neural architecture from humans. Direct evidence of neural activity during natural vocal communication is limited, as previous studies were performed in chair-restrained animals. Here we recorded the activity of single neurons across multiple regions of prefrontal and premotor cortex while freely moving marmosets engaged in a natural vocal behavior known as antiphonal calling. Our aim was to test whether neurons in marmoset frontal cortex exhibited responses during vocal-signal processing and/or vocal-motor production in the context of active, natural communication. We observed motor-related changes in single neuron activity during vocal production, but relatively weak sensory responses for vocalization processing during this natural behavior. Vocal-motor responses occurred both prior to and during call production and were typically coupled to the timing of each vocalization pulse. Despite the relatively weak sensory responses a population classifier was able to distinguish between neural activity that occurred during presentations of vocalization stimuli that elicited an antiphonal response and those that did not. These findings are suggestive of the role that nonhuman primate frontal cortex neurons play in natural communication and provide an important foundation for more explicit tests of the functional contributions of these neocortical areas during vocal behaviors. PMID:26084912
Selective neuronal lapses precede human cognitive lapses following sleep deprivation.
Nir, Yuval; Andrillon, Thomas; Marmelshtein, Amit; Suthana, Nanthia; Cirelli, Chiara; Tononi, Giulio; Fried, Itzhak
2017-12-01
Sleep deprivation is a major source of morbidity with widespread health effects, including increased risk of hypertension, diabetes, obesity, heart attack, and stroke. Moreover, sleep deprivation brings about vehicle accidents and medical errors and is therefore an urgent topic of investigation. During sleep deprivation, homeostatic and circadian processes interact to build up sleep pressure, which results in slow behavioral performance (cognitive lapses) typically attributed to attentional thalamic and frontoparietal circuits, but the underlying mechanisms remain unclear. Recently, through study of electroencephalograms (EEGs) in humans and local field potentials (LFPs) in nonhuman primates and rodents it was found that, during sleep deprivation, regional 'sleep-like' slow and theta (slow/theta) waves co-occur with impaired behavioral performance during wakefulness. Here we used intracranial electrodes to record single-neuron activities and LFPs in human neurosurgical patients performing a face/nonface categorization psychomotor vigilance task (PVT) over multiple experimental sessions, including a session after full-night sleep deprivation. We find that, just before cognitive lapses, the selective spiking responses of individual neurons in the medial temporal lobe (MTL) are attenuated, delayed, and lengthened. These 'neuronal lapses' are evident on a trial-by-trial basis when comparing the slowest behavioral PVT reaction times to the fastest. Furthermore, during cognitive lapses, LFPs exhibit a relative local increase in slow/theta activity that is correlated with degraded single-neuron responses and with baseline theta activity. Our results show that cognitive lapses involve local state-dependent changes in neuronal activity already present in the MTL.
Wang, Guangfu; Wyskiel, Daniel R; Yang, Weiguo; Wang, Yiqing; Milbern, Lana C; Lalanne, Txomin; Jiang, Xiaolong; Shen, Ying; Sun, Qian-Quan; Zhu, J Julius
2015-01-01
Deciphering neuronal circuitry is central to understanding brain function and dysfunction, yet it remains a daunting task. To facilitate the dissection of neuronal circuits, a process requiring functional analysis of synaptic connections and morphological identification of interconnected neurons, we present here a method for stable simultaneous octuple patch-clamp recordings. This method allows physiological analysis of synaptic interconnections among 4–8 simultaneously recorded neurons and/or 10–30 sequentially recorded neurons, and it allows anatomical identification of >85% of recorded interneurons and >99% of recorded principal neurons. We describe how to apply the method to rodent tissue slices; however, it can be used on other model organisms. We also describe the latest refinements and optimizations of mechanics, electronics, optics and software programs that are central to the realization of a combined single- and two-photon microscopy–based, optogenetics- and imaging-assisted, stable, simultaneous quadruple–viguple patch-clamp recording system. Setting up the system, from the beginning of instrument assembly and software installation to full operation, can be completed in 3–4 d. PMID:25654757
Ebina, Teppei; Masamizu, Yoshito; Tanaka, Yasuhiro R; Watakabe, Akiya; Hirakawa, Reiko; Hirayama, Yuka; Hira, Riichiro; Terada, Shin-Ichiro; Koketsu, Daisuke; Hikosaka, Kazuo; Mizukami, Hiroaki; Nambu, Atsushi; Sasaki, Erika; Yamamori, Tetsuo; Matsuzaki, Masanori
2018-05-14
Two-photon imaging in behaving animals has revealed neuronal activities related to behavioral and cognitive function at single-cell resolution. However, marmosets have posed a challenge due to limited success in training on motor tasks. Here we report the development of protocols to train head-fixed common marmosets to perform upper-limb movement tasks and simultaneously perform two-photon imaging. After 2-5 months of training sessions, head-fixed marmosets can control a manipulandum to move a cursor to a target on a screen. We conduct two-photon calcium imaging of layer 2/3 neurons in the motor cortex during this motor task performance, and detect task-relevant activity from multiple neurons at cellular and subcellular resolutions. In a two-target reaching task, some neurons show direction-selective activity over the training days. In a short-term force-field adaptation task, some neurons change their activity when the force field is on. Two-photon calcium imaging in behaving marmosets may become a fundamental technique for determining the spatial organization of the cortical dynamics underlying action and cognition.
Amount of fear extinction changes its underlying mechanisms.
An, Bobae; Kim, Jihye; Park, Kyungjoon; Lee, Sukwon; Song, Sukwoon; Choi, Sukwoo
2017-07-03
There has been a longstanding debate on whether original fear memory is inhibited or erased after extinction. One possibility that reconciles this uncertainty is that the inhibition and erasure mechanisms are engaged in different phases (early or late) of extinction. In this study, using single-session extinction training and its repetition (multiple-session extinction training), we investigated the inhibition and erasure mechanisms in the prefrontal cortex and amygdala of rats, where neural circuits underlying extinction reside. The inhibition mechanism was prevalent with single-session extinction training but faded when single-session extinction training was repeated. In contrast, the erasure mechanism became prevalent when single-session extinction training was repeated. Moreover, ablating the intercalated neurons of amygdala, which are responsible for maintaining extinction-induced inhibition, was no longer effective in multiple-session extinction training. We propose that the inhibition mechanism operates primarily in the early phase of extinction training, and the erasure mechanism takes over after that.
Quantitative neuroanatomy for connectomics in Drosophila
Schneider-Mizell, Casey M; Gerhard, Stephan; Longair, Mark; Kazimiers, Tom; Li, Feng; Zwart, Maarten F; Champion, Andrew; Midgley, Frank M; Fetter, Richard D; Saalfeld, Stephan; Cardona, Albert
2016-01-01
Neuronal circuit mapping using electron microscopy demands laborious proofreading or reconciliation of multiple independent reconstructions. Here, we describe new methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams. We measured the morphological underpinnings of connectivity in new and existing reconstructions of Drosophila sensorimotor (larva) and visual (adult) systems. Synaptic inputs were preferentially located on numerous small, microtubule-free 'twigs' which branch off a single microtubule-containing 'backbone'. Omission of individual twigs accounted for 96% of errors. However, the synapses of highly connected neurons were distributed across multiple twigs. Thus, the robustness of a strong connection to detailed twig anatomy was associated with robustness to reconstruction error. By comparing iterative reconstruction to the consensus of multiple reconstructions, we show that our method overcomes the need for redundant effort through the discovery and application of relationships between cellular neuroanatomy and synaptic connectivity. DOI: http://dx.doi.org/10.7554/eLife.12059.001 PMID:26990779
Puissant, Madeleine M.; Mouradian, Gary C.; Liu, Pengyuan; Hodges, Matthew R.
2017-01-01
Ventilation is continuously adjusted by a neural network to maintain blood gases and pH. Acute CO2 and/or pH regulation requires neural feedback from brainstem cells that encode CO2/pH to modulate ventilation, including but not limited to brainstem serotonin (5-HT) neurons. Brainstem 5-HT neurons modulate ventilation and are stimulated by hypercapnic acidosis, the sensitivity of which increases with increasing postnatal age. The proper function of brainstem 5-HT neurons, particularly during post-natal development is critical given that multiple abnormalities in the 5-HT system have been identified in victims of Sudden Infant Death Syndrome. Here, we tested the hypothesis that there are age-dependent increases in expression of pH-sensitive ion channels in brainstem 5-HT neurons, which may underlie their cellular CO2/pH sensitivity. Midline raphe neurons were acutely dissociated from neonatal and mature transgenic SSePet-eGFP rats [which have enhanced green fluorescent protein (eGFP) expression in all 5-HT neurons] and sorted with fluorescence-activated cell sorting (FACS) into 5-HT-enriched and non-5-HT cell pools for subsequent RNA extraction, cDNA library preparation and RNA sequencing. Overlapping differential expression analyses pointed to age-dependent shifts in multiple ion channels, including but not limited to the pH-sensitive potassium ion (K+) channel genes kcnj10 (Kir4.1), kcnj16 (Kir5.1), kcnk1 (TWIK-1), kcnk3 (TASK-1) and kcnk9 (TASK-3). Intracellular contents isolated from single adult eGFP+ 5-HT neurons confirmed gene expression of Kir4.1, Kir5.1 and other K+ channels, but also showed heterogeneity in the expression of multiple genes. 5-HT neuron-enriched cell pools from selected post-natal ages showed increases in Kir4.1, Kir5.1, and TWIK-1, fitting with age-dependent increases in Kir4.1 and Kir5.1 protein expression in raphe tissue samples. Immunofluorescence imaging confirmed Kir5.1 protein was co-localized to brainstem neurons and glia including 5-HT neurons as expected. However, Kir4.1 protein expression was restricted to glia, suggesting that it may not contribute to 5-HT neuron pH sensitivity. Although there are caveats to this approach, the data suggest that pH-sensitive Kir5.1 channels may underlie cellular CO2/pH chemosensitivity in brainstem 5-HT neurons. PMID:28270749
Quantitative 3D investigation of Neuronal network in mouse spinal cord model
NASA Astrophysics Data System (ADS)
Bukreeva, I.; Campi, G.; Fratini, M.; Spanò, R.; Bucci, D.; Battaglia, G.; Giove, F.; Bravin, A.; Uccelli, A.; Venturi, C.; Mastrogiacomo, M.; Cedola, A.
2017-01-01
The investigation of the neuronal network in mouse spinal cord models represents the basis for the research on neurodegenerative diseases. In this framework, the quantitative analysis of the single elements in different districts is a crucial task. However, conventional 3D imaging techniques do not have enough spatial resolution and contrast to allow for a quantitative investigation of the neuronal network. Exploiting the high coherence and the high flux of synchrotron sources, X-ray Phase-Contrast multiscale-Tomography allows for the 3D investigation of the neuronal microanatomy without any aggressive sample preparation or sectioning. We investigated healthy-mouse neuronal architecture by imaging the 3D distribution of the neuronal-network with a spatial resolution of 640 nm. The high quality of the obtained images enables a quantitative study of the neuronal structure on a subject-by-subject basis. We developed and applied a spatial statistical analysis on the motor neurons to obtain quantitative information on their 3D arrangement in the healthy-mice spinal cord. Then, we compared the obtained results with a mouse model of multiple sclerosis. Our approach paves the way to the creation of a “database” for the characterization of the neuronal network main features for a comparative investigation of neurodegenerative diseases and therapies.
Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics.
Harris, Kenneth D; Hochgerner, Hannah; Skene, Nathan G; Magno, Lorenza; Katona, Linda; Bengtsson Gonzales, Carolina; Somogyi, Peter; Kessaris, Nicoletta; Linnarsson, Sten; Hjerling-Leffler, Jens
2018-06-18
Understanding any brain circuit will require a categorization of its constituent neurons. In hippocampal area CA1, at least 23 classes of GABAergic neuron have been proposed to date. However, this list may be incomplete; additionally, it is unclear whether discrete classes are sufficient to describe the diversity of cortical inhibitory neurons or whether continuous modes of variability are also required. We studied the transcriptomes of 3,663 CA1 inhibitory cells, revealing 10 major GABAergic groups that divided into 49 fine-scale clusters. All previously described and several novel cell classes were identified, with three previously described classes unexpectedly found to be identical. A division into discrete classes, however, was not sufficient to describe the diversity of these cells, as continuous variation also occurred between and within classes. Latent factor analysis revealed that a single continuous variable could predict the expression levels of several genes, which correlated similarly with it across multiple cell types. Analysis of the genes correlating with this variable suggested it reflects a range from metabolically highly active faster-spiking cells that proximally target pyramidal cells to slower-spiking cells targeting distal dendrites or interneurons. These results elucidate the complexity of inhibitory neurons in one of the simplest cortical structures and show that characterizing these cells requires continuous modes of variation as well as discrete cell classes.
Fasting launches CRTC to facilitate long-term memory formation in Drosophila.
Hirano, Yukinori; Masuda, Tomoko; Naganos, Shintaro; Matsuno, Motomi; Ueno, Kohei; Miyashita, Tomoyuki; Horiuchi, Junjiro; Saitoe, Minoru
2013-01-25
Canonical aversive long-term memory (LTM) formation in Drosophila requires multiple spaced trainings, whereas appetitive LTM can be formed after a single training. Appetitive LTM requires fasting prior to training, which increases motivation for food intake. However, we found that fasting facilitated LTM formation in general; aversive LTM formation also occurred after single-cycle training when mild fasting was applied before training. Both fasting-dependent LTM (fLTM) and spaced training-dependent LTM (spLTM) required protein synthesis and cyclic adenosine monophosphate response element-binding protein (CREB) activity. However, spLTM required CREB activity in two neural populations--mushroom body and DAL neurons--whereas fLTM required CREB activity only in mushroom body neurons. fLTM uses the CREB coactivator CRTC, whereas spLTM uses the coactivator CBP. Thus, flies use distinct LTM machinery depending on their hunger state.
The Emergence of Single Neurons in Clinical Neurology
Cash, Sydney S.; Hochberg, Leigh R.
2015-01-01
Summary Single neuron actions and interactions are the sine qua non of brain function, and nearly all diseases and injuries of the central nervous system trace their clinical sequelae to neuronal dysfunction or failure. Remarkably, discussion of neuronal activity is largely absent in clinical neuroscience. Advances in neurotechnology and computational capabilities, accompanied by shifts in theoretical frameworks, have led to renewed interest in the information represented by single neurons. Using direct interfaces with the nervous system, millisecond-scale information will soon be extracted from single neurons in clinical environments, supporting personalized treatment of neurologic and psychiatric disease. In this review we focus on single neuronal activity in restoring communication and motor control in patients suffering from devastating neurological injuries. We also explore the single neuron's role in epilepsy and movement disorders, surgical anesthesia, and in cognitive processes disrupted in neurodegenerative and neuropsychiatric disease. Finally, we speculate on how technological advances will revolutionize neurotherapeutics. PMID:25856488
The emergence of single neurons in clinical neurology.
Cash, Sydney S; Hochberg, Leigh R
2015-04-08
Single neuron actions and interactions are the sine qua non of brain function, and nearly all diseases and injuries of the CNS trace their clinical sequelae to neuronal dysfunction or failure. Remarkably, discussion of neuronal activity is largely absent in clinical neuroscience. Advances in neurotechnology and computational capabilities, accompanied by shifts in theoretical frameworks, have led to renewed interest in the information represented by single neurons. Using direct interfaces with the nervous system, millisecond-scale information will soon be extracted from single neurons in clinical environments, supporting personalized treatment of neurologic and psychiatric disease. In this Perspective, we focus on single-neuronal activity in restoring communication and motor control in patients suffering from devastating neurological injuries. We also explore the single neuron's role in epilepsy and movement disorders, surgical anesthesia, and in cognitive processes disrupted in neurodegenerative and neuropsychiatric disease. Finally, we speculate on how technological advances will revolutionize neurotherapeutics. Copyright © 2015 Elsevier Inc. All rights reserved.
Measuring multiple spike train synchrony.
Kreuz, Thomas; Chicharro, Daniel; Andrzejak, Ralph G; Haas, Julie S; Abarbanel, Henry D I
2009-10-15
Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals (ISIs). In this study we propose two extensions of the ISI-distance, the straightforward averaged bivariate ISI-distance and the multivariate ISI-diversity based on the coefficient of variation. Like the original measure these extensions combine many properties desirable in applications to real data. In particular, they are parameter-free, time scale independent, and easy to visualize in a time-resolved manner, as we illustrate with in vitro recordings from a cortical neuron. Using a simulated network of Hindemarsh-Rose neurons as a controlled configuration we compare the performance of our methods in distinguishing different levels of multi-neuron spike train synchrony to the performance of six other previously published measures. We show and explain why the averaged bivariate measures perform better than the multivariate ones and why the multivariate ISI-diversity is the best performer among the multivariate methods. Finally, in a comparison against standard methods that rely on moving window estimates, we use single-unit monkey data to demonstrate the advantages of the instantaneous nature of our methods.
A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development.
Yao, Zizhen; Mich, John K; Ku, Sherman; Menon, Vilas; Krostag, Anne-Rachel; Martinez, Refugio A; Furchtgott, Leon; Mulholland, Heather; Bort, Susan; Fuqua, Margaret A; Gregor, Ben W; Hodge, Rebecca D; Jayabalu, Anu; May, Ryan C; Melton, Samuel; Nelson, Angelique M; Ngo, N Kiet; Shapovalova, Nadiya V; Shehata, Soraya I; Smith, Michael W; Tait, Leah J; Thompson, Carol L; Thomsen, Elliot R; Ye, Chaoyang; Glass, Ian A; Kaykas, Ajamete; Yao, Shuyuan; Phillips, John W; Grimley, Joshua S; Levi, Boaz P; Wang, Yanling; Ramanathan, Sharad
2017-01-05
During human brain development, multiple signaling pathways generate diverse cell types with varied regional identities. Here, we integrate single-cell RNA sequencing and clonal analyses to reveal lineage trees and molecular signals underlying early forebrain and mid/hindbrain cell differentiation from human embryonic stem cells (hESCs). Clustering single-cell transcriptomic data identified 41 distinct populations of progenitor, neuronal, and non-neural cells across our differentiation time course. Comparisons with primary mouse and human gene expression data demonstrated rostral and caudal progenitor and neuronal identities from early brain development. Bayesian analyses inferred a unified cell-type lineage tree that bifurcates between cortical and mid/hindbrain cell types. Two methods of clonal analyses confirmed these findings and further revealed the importance of Wnt/β-catenin signaling in controlling this lineage decision. Together, these findings provide a rich transcriptome-based lineage map for studying human brain development and modeling developmental disorders. Copyright © 2017 Elsevier Inc. All rights reserved.
Spatiotemporal activity patterns detected from single cell measurements from behaving animals
NASA Astrophysics Data System (ADS)
Villa, Alessandro E. P.; Tetko, Igor V.
1999-03-01
Precise temporal patterning of activity within and between neurons has been predicted on theoretical grounds, and found in the spike trains of neurons recorded from anesthetized and conscious animals, in association with sensor stimuli and particular phases of task performance. However, the functional significance of such patterning in the generation of behavior has not been confirmed. We recorded from multiple single neurons in regions of rat auditory cortex during the waiting period of a Go/NoGo task. During this time the animal waited for an auditory signal with high cognitive load. Of note is the fact that neural activity during the period analyzed was essentially stationary, with no event related variability in firing. Detected patterns therefore provide a measure of brain state that could not be addressed by standard methods relying on analysis of changes in mean discharge rate. The possibility is discussed that some patterns might reflect a preset bias to a particular response, formed in the waiting period. Others patterns might reflect a state of prior preparation of appropriate neural assemblies for analyzing a signal that is expected but of unknown behavioral valence.
Krashes, Michael J.; Waddell, Scott
2008-01-01
In Drosophila, formation of aversive olfactory long-term memory (LTM) requires multiple training sessions pairing odor and electric shock punishment with rest intervals. In contrast, here we show that a single 2 min training session pairing odor with a more ethologically relevant sugar reinforcement forms long-term appetitive memory that lasts for days. Appetitive LTM has some mechanistic similarity to aversive LTM in that it can be disrupted by cycloheximide, the dCreb2-b transcriptional repressor, and the crammer and tequila LTM-specific mutations. However, appetitive LTM is completely disrupted by the radish mutation that apparently represents a distinct mechanistic phase of consolidated aversive memory. Furthermore, appetitive LTM requires activity in the dorsal paired medial neuron and mushroom body α′ β′ neuron circuit during the first hour after training and mushroom body αβ neuron output during retrieval, suggesting that appetitive middle-term memory and LTM are mechanistically linked. Last, experiments feeding and/or starving flies after training reveals a critical motivational drive that enables appetitive LTM retrieval. PMID:18354013
Qin, Chao; Chen, Jiande D Z; Zhang, Jing; Foreman, Robert D
2007-12-01
Clinically, the overlap of gastroduodenal symptoms, such as visceral pain or hypersensitivity, is often observed in functional gastrointestinal disorders. The underlying mechanism may be related to intraspinal neuronal processing of noxious convergent inputs from the stomach and the intestine. The purpose of this study was to examine whether single low thoracic (T9-T10) spinal neurons responded to both gastric and duodenal mechanical stimulation. Extracellular potentials of single T9-T10 spinal neurons were recorded in pentobarbital anesthetized, paralyzed, and ventilated male rats. Graded gastric distensions (GD, 20, 40, 60 mm Hg, 20 s) were induced by air inflation of a latex balloon surgically placed in the stomach. Graded duodenal distensions (DD, 0.2, 0.4, 0.6 ml, 20 s) were produced by water inflation of a latex balloon placed into the duodenum. Of 70 deeper (depth from dorsal surface of spinal cord: 0.3-1.2 mm) spinal neurons responsive to noxious GD (> or =40 mm Hg), 44(63%) also responded to noxious DD (> or =0.4 ml). Similarly, 13/17 (76%) superficial neurons (depth <0.3 mm) responded to both GD and DD. Of 57 gastroduodenal convergent neurons, 41 (72%) had excitatory and 6 had inhibitory responses to both GD and DD; the remaining neurons exhibited multiple patterns of excitation and inhibition. 43/57 (75%) gastroduodenal convergent neurons had low-threshold (< or =20 mm Hg) responses to GD, whereas 42/57 (74%) of these neurons had high-threshold (> or =0.4 ml) responses to DD. In addition, 34/40 (85%) gastroduodenal convergent neurons had somatic receptive fields on the back, flank, and medial/lateral abdominal areas. These results suggested that superficial and deeper T9-T10 spinal neurons received innocuous and/or noxious convergent inputs from mechanical stimulation of the stomach and duodenum. Gastroduodenal convergent spinal neurons might contribute to intraspinal sensory transmission for cross-organ afferent-afferent communication between the stomach and duodenum and play a role in visceral nociception and reflexes.
Cannon, Jonathan
2017-01-01
Mutual information is a commonly used measure of communication between neurons, but little theory exists describing the relationship between mutual information and the parameters of the underlying neuronal interaction. Such a theory could help us understand how specific physiological changes affect the capacity of neurons to synaptically communicate, and, in particular, they could help us characterize the mechanisms by which neuronal dynamics gate the flow of information in the brain. Here we study a pair of linear-nonlinear-Poisson neurons coupled by a weak synapse. We derive an analytical expression describing the mutual information between their spike trains in terms of synapse strength, neuronal activation function, the time course of postsynaptic currents, and the time course of the background input received by the two neurons. This expression allows mutual information calculations that would otherwise be computationally intractable. We use this expression to analytically explore the interaction of excitation, information transmission, and the convexity of the activation function. Then, using this expression to quantify mutual information in simulations, we illustrate the information-gating effects of neural oscillations and oscillatory coherence, which may either increase or decrease the mutual information across the synapse depending on parameters. Finally, we show analytically that our results can quantitatively describe the selection of one information pathway over another when multiple sending neurons project weakly to a single receiving neuron.
Arandia-Romero, Iñigo; Tanabe, Seiji; Drugowitsch, Jan; Kohn, Adam; Moreno-Bote, Rubén
2016-01-01
Numerous studies have shown that neuronal responses are modulated by stimulus properties, and also by the state of the local network. However, little is known about how activity fluctuations of neuronal populations modulate the sensory tuning of cells and affect their encoded information. We found that fluctuations in ongoing and stimulus-evoked population activity in primate visual cortex modulate the tuning of neurons in a multiplicative and additive manner. While distributed on a continuum, neurons with stronger multiplicative effects tended to have less additive modulation, and vice versa. The information encoded by multiplicatively-modulated neurons increased with greater population activity, while that of additively-modulated neurons decreased. These effects offset each other, so that population activity had little effect on total information. Our results thus suggest that intrinsic activity fluctuations may act as a `traffic light' that determines which subset of neurons are most informative. PMID:26924437
Simultaneous neuron- and astrocyte-specific fluorescent marking
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schulze, Wiebke; Hayata-Takano, Atsuko; Kamo, Toshihiko
2015-03-27
Systematic and simultaneous analysis of multiple cell types in the brain is becoming important, but such tools have not yet been adequately developed. Here, we aimed to generate a method for the specific fluorescent labeling of neurons and astrocytes, two major cell types in the brain, and we have developed lentiviral vectors to express the red fluorescent protein tdTomato in neurons and the enhanced green fluorescent protein (EGFP) in astrocytes. Importantly, both fluorescent proteins are fused to histone 2B protein (H2B) to confer nuclear localization to distinguish between single cells. We also constructed several expression constructs, including a tandem alignmentmore » of the neuron- and astrocyte-expression cassettes for simultaneous labeling. Introducing these vectors and constructs in vitro and in vivo resulted in cell type-specific and nuclear-localized fluorescence signals enabling easy detection and distinguishability of neurons and astrocytes. This tool is expected to be utilized for the simultaneous analysis of changes in neurons and astrocytes in healthy and diseased brains. - Highlights: • We develop a method for the specific fluorescent labeling of neurons and astrocytes. • Neuron-specific labeling is achieved using Scg10 and synapsin promoters. • Astrocyte-specific labeling is generated using the minimal GFAP promoter. • Nuclear localization of fluorescent proteins is achieved with histone 2B protein.« less
Suppression and Contrast Normalization in Motion Processing
2017-01-01
Sensory neurons are activated by a range of stimuli to which they are said to be tuned. Usually, they are also suppressed by another set of stimuli that have little effect when presented in isolation. The interactions between preferred and suppressive stimuli are often quite complex and vary across neurons, even within a single area, making it difficult to infer their collective effect on behavioral responses mediated by activity across populations of neurons. Here, we investigated this issue by measuring, in human subjects (three males), the suppressive effect of static masks on the ocular following responses induced by moving stimuli. We found a wide range of effects, which depend in a nonlinear and nonseparable manner on the spatial frequency, contrast, and spatial location of both stimulus and mask. Under some conditions, the presence of the mask can be seen as scaling the contrast of the driving stimulus. Under other conditions, the effect is more complex, involving also a direct scaling of the behavioral response. All of this complexity at the behavioral level can be captured by a simple model in which stimulus and mask interact nonlinearly at two stages, one monocular and one binocular. The nature of the interactions is compatible with those observed at the level of single neurons in primates, usually broadly described as divisive normalization, without having to invoke any scaling mechanism. SIGNIFICANCE STATEMENT The response of sensory neurons to their preferred stimulus is often modulated by stimuli that are not effective when presented alone. Individual neurons can exhibit multiple modulatory effects, with considerable variability across neurons even in a single area. Such diversity has made it difficult to infer the impact of these modulatory mechanisms on behavioral responses. Here, we report the effects of a stationary mask on the reflexive eye movements induced by a moving stimulus. A model with two stages, each incorporating a divisive modulatory mechanism, reproduces our experimental results and suggests that qualitative variability of masking effects in cortical neurons might arise from differences in the extent to which such effects are inherited from earlier stages. PMID:29018158
An integrated multi-electrode-optrode array for in vitro optogenetics
Welkenhuysen, Marleen; Hoffman, Luis; Luo, Zhengxiang; De Proft, Anabel; Van den Haute, Chris; Baekelandt, Veerle; Debyser, Zeger; Gielen, Georges; Puers, Robert; Braeken, Dries
2016-01-01
Modulation of a group of cells or tissue needs to be very precise in order to exercise effective control over the cell population under investigation. Optogenetic tools have already demonstrated to be of great value in the study of neuronal circuits and in neuromodulation. Ideally, they should permit very accurate resolution, preferably down to the single cell level. Further, to address a spatially distributed sample, independently addressable multiple optical outputs should be present. In current techniques, at least one of these requirements is not fulfilled. In addition to this, it is interesting to directly monitor feedback of the modulation by electrical registration of the activity of the stimulated cells. Here, we present the fabrication and characterization of a fully integrated silicon-based multi-electrode-optrode array (MEOA) for in vitro optogenetics. We demonstrate that this device allows for artifact-free electrical recording. Moreover, the MEOA was used to reliably elicit spiking activity from ChR2-transduced neurons. Thanks to the single cell resolution stimulation capability, we could determine spatial and temporal activation patterns and spike latencies of the neuronal network. This integrated approach to multi-site combined optical stimulation and electrical recording significantly advances today’s tool set for neuroscientists in their search to unravel neuronal network dynamics. PMID:26832455
Synaptic heterogeneity and stimulus-induced modulation of depression in central synapses.
Hunter, J D; Milton, J G
2001-08-01
Short-term plasticity is a pervasive feature of synapses. Synapses exhibit many forms of plasticity operating over a range of time scales. We develop an optimization method that allows rapid characterization of synapses with multiple time scales of facilitation and depression. Investigation of paired neurons that are postsynaptic to the same identified interneuron in the buccal ganglion of Aplysia reveals that the responses of the two neurons differ in the magnitude of synaptic depression. Also, for single neurons, prolonged stimulation of the presynaptic neuron causes stimulus-induced increases in the early phase of synaptic depression. These observations can be described by a model that incorporates two availability factors, e.g., depletable vesicle pools or desensitizing receptor populations, with different time courses of recovery, and a single facilitation component. This model accurately predicts the responses to novel stimuli. The source of synaptic heterogeneity is identified with variations in the relative sizes of the two availability factors, and the stimulus-induced decrement in the early synaptic response is explained by a slowing of the recovery rate of one of the availability factors. The synaptic heterogeneity and stimulus-induced modifications in synaptic depression observed here emphasize that synaptic efficacy depends on both the individual properties of synapses and their past history.
Single-unit analysis of somatosensory processing in the core auditory cortex of hearing ferrets.
Meredith, M Alex; Allman, Brian L
2015-03-01
The recent findings in several species that the primary auditory cortex processes non-auditory information have largely overlooked the possibility of somatosensory effects. Therefore, the present investigation examined the core auditory cortices (anterior auditory field and primary auditory cortex) for tactile responsivity. Multiple single-unit recordings from anesthetised ferret cortex yielded histologically verified neurons (n = 311) tested with electronically controlled auditory, visual and tactile stimuli, and their combinations. Of the auditory neurons tested, a small proportion (17%) was influenced by visual cues, but a somewhat larger number (23%) was affected by tactile stimulation. Tactile effects rarely occurred alone and spiking responses were observed in bimodal auditory-tactile neurons. However, the broadest tactile effect that was observed, which occurred in all neuron types, was that of suppression of the response to a concurrent auditory cue. The presence of tactile effects in the core auditory cortices was supported by a substantial anatomical projection from the rostral suprasylvian sulcal somatosensory area. Collectively, these results demonstrate that crossmodal effects in the auditory cortex are not exclusively visual and that somatosensation plays a significant role in modulation of acoustic processing, and indicate that crossmodal plasticity following deafness may unmask these existing non-auditory functions. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Fully integrated silicon probes for high-density recording of neural activity.
Jun, James J; Steinmetz, Nicholas A; Siegle, Joshua H; Denman, Daniel J; Bauza, Marius; Barbarits, Brian; Lee, Albert K; Anastassiou, Costas A; Andrei, Alexandru; Aydın, Çağatay; Barbic, Mladen; Blanche, Timothy J; Bonin, Vincent; Couto, João; Dutta, Barundeb; Gratiy, Sergey L; Gutnisky, Diego A; Häusser, Michael; Karsh, Bill; Ledochowitsch, Peter; Lopez, Carolina Mora; Mitelut, Catalin; Musa, Silke; Okun, Michael; Pachitariu, Marius; Putzeys, Jan; Rich, P Dylan; Rossant, Cyrille; Sun, Wei-Lung; Svoboda, Karel; Carandini, Matteo; Harris, Kenneth D; Koch, Christof; O'Keefe, John; Harris, Timothy D
2017-11-08
Sensory, motor and cognitive operations involve the coordinated action of large neuronal populations across multiple brain regions in both superficial and deep structures. Existing extracellular probes record neural activity with excellent spatial and temporal (sub-millisecond) resolution, but from only a few dozen neurons per shank. Optical Ca 2+ imaging offers more coverage but lacks the temporal resolution needed to distinguish individual spikes reliably and does not measure local field potentials. Until now, no technology compatible with use in unrestrained animals has combined high spatiotemporal resolution with large volume coverage. Here we design, fabricate and test a new silicon probe known as Neuropixels to meet this need. Each probe has 384 recording channels that can programmably address 960 complementary metal-oxide-semiconductor (CMOS) processing-compatible low-impedance TiN sites that tile a single 10-mm long, 70 × 20-μm cross-section shank. The 6 × 9-mm probe base is fabricated with the shank on a single chip. Voltage signals are filtered, amplified, multiplexed and digitized on the base, allowing the direct transmission of noise-free digital data from the probe. The combination of dense recording sites and high channel count yielded well-isolated spiking activity from hundreds of neurons per probe implanted in mice and rats. Using two probes, more than 700 well-isolated single neurons were recorded simultaneously from five brain structures in an awake mouse. The fully integrated functionality and small size of Neuropixels probes allowed large populations of neurons from several brain structures to be recorded in freely moving animals. This combination of high-performance electrode technology and scalable chip fabrication methods opens a path towards recording of brain-wide neural activity during behaviour.
Interactions across Multiple Stimulus Dimensions in Primary Auditory Cortex.
Sloas, David C; Zhuo, Ran; Xue, Hongbo; Chambers, Anna R; Kolaczyk, Eric; Polley, Daniel B; Sen, Kamal
2016-01-01
Although sensory cortex is thought to be important for the perception of complex objects, its specific role in representing complex stimuli remains unknown. Complex objects are rich in information along multiple stimulus dimensions. The position of cortex in the sensory hierarchy suggests that cortical neurons may integrate across these dimensions to form a more gestalt representation of auditory objects. Yet, studies of cortical neurons typically explore single or few dimensions due to the difficulty of determining optimal stimuli in a high dimensional stimulus space. Evolutionary algorithms (EAs) provide a potentially powerful approach for exploring multidimensional stimulus spaces based on real-time spike feedback, but two important issues arise in their application. First, it is unclear whether it is necessary to characterize cortical responses to multidimensional stimuli or whether it suffices to characterize cortical responses to a single dimension at a time. Second, quantitative methods for analyzing complex multidimensional data from an EA are lacking. Here, we apply a statistical method for nonlinear regression, the generalized additive model (GAM), to address these issues. The GAM quantitatively describes the dependence between neural response and all stimulus dimensions. We find that auditory cortical neurons in mice are sensitive to interactions across dimensions. These interactions are diverse across the population, indicating significant integration across stimulus dimensions in auditory cortex. This result strongly motivates using multidimensional stimuli in auditory cortex. Together, the EA and the GAM provide a novel quantitative paradigm for investigating neural coding of complex multidimensional stimuli in auditory and other sensory cortices.
Integrated nanoscale tools for interrogating living cells
NASA Astrophysics Data System (ADS)
Jorgolli, Marsela
The development of next-generation, nanoscale technologies that interface biological systems will pave the way towards new understanding of such complex systems. Nanowires -- one-dimensional nanoscale structures -- have shown unique potential as an ideal physical interface to biological systems. Herein, we focus on the development of nanowire-based devices that can enable a wide variety of biological studies. First, we built upon standard nanofabrication techniques to optimize nanowire devices, resulting in perfectly ordered arrays of both opaque (Silicon) and transparent (Silicon dioxide) nanowires with user defined structural profile, densities, and overall patterns, as well as high sample consistency and large scale production. The high-precision and well-controlled fabrication method in conjunction with additional technologies laid the foundation for the generation of highly specialized platforms for imaging, electrochemical interrogation, and molecular biology. Next, we utilized nanowires as the fundamental structure in the development of integrated nanoelectronic platforms to directly interrogate the electrical activity of biological systems. Initially, we generated a scalable intracellular electrode platform based on vertical nanowires that allows for parallel electrical interfacing to multiple mammalian neurons. Our prototype device consisted of 16 individually addressable stimulation/recording sites, each containing an array of 9 electrically active silicon nanowires. We showed that these vertical nanowire electrode arrays could intracellularly record and stimulate neuronal activity in dissociated cultures of rat cortical neurons similar to patch clamp electrodes. In addition, we used our intracellular electrode platform to measure multiple individual synaptic connections, which enables the reconstruction of the functional connectivity maps of neuronal circuits. In order to expand and improve the capability of this functional prototype device we designed and fabricated a new hybrid chip that combines a front-side nanowire-based interface for neuronal recording with backside complementary metal oxide semiconductor (CMOS) circuits for on-chip multiplexing, voltage control for stimulation, signal amplification, and signal processing. Individual chips contain 1024 stimulation/recording sites enabling large-scale interfacing of neuronal networks with single cell resolution. Through electrical and electrochemical characterization of the devices, we demonstrated their enhanced functionality at a massively parallel scale. In our initial cell experiments, we achieved intracellular stimulations and recordings of changes in the membrane potential in a variety of cells including: HEK293T, cardiomyocytes, and rat cortical neurons. This demonstrated the device capability for single-cell-resolution recording/stimulation which when extended to a large number of neurons in a massively parallel fashion will enable the functional mapping of a complex neuronal network.
Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons.
Moon, Sung Joon; Cook, Katherine A; Rajendran, Karthikeyan; Kevrekidis, Ioannis G; Cisternas, Jaime; Laing, Carlo R
2015-12-01
The formation of oscillating phase clusters in a network of identical Hodgkin-Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition-through [Formula: see text] (possibly perturbed) period-doubling and subsequent bifurcations-to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar "fine" states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron's "identity" (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established "identity-state" correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.
Phase Locking of Multiple Single Neurons to the Local Field Potential in Cat V1.
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.
Schneider, David M; Woolley, Sarah M N
2010-06-01
Many social animals including songbirds use communication vocalizations for individual recognition. The perception of vocalizations depends on the encoding of complex sounds by neurons in the ascending auditory system, each of which is tuned to a particular subset of acoustic features. Here, we examined how well the responses of single auditory neurons could be used to discriminate among bird songs and we compared discriminability to spectrotemporal tuning. We then used biologically realistic models of pooled neural responses to test whether the responses of groups of neurons discriminated among songs better than the responses of single neurons and whether discrimination by groups of neurons was related to spectrotemporal tuning and trial-to-trial response variability. The responses of single auditory midbrain neurons could be used to discriminate among vocalizations with a wide range of abilities, ranging from chance to 100%. The ability to discriminate among songs using single neuron responses was not correlated with spectrotemporal tuning. Pooling the responses of pairs of neurons generally led to better discrimination than the average of the two inputs and the most discriminating input. Pooling the responses of three to five single neurons continued to improve neural discrimination. The increase in discriminability was largest for groups of neurons with similar spectrotemporal tuning. Further, we found that groups of neurons with correlated spike trains achieved the largest gains in discriminability. We simulated neurons with varying levels of temporal precision and measured the discriminability of responses from single simulated neurons and groups of simulated neurons. Simulated neurons with biologically observed levels of temporal precision benefited more from pooling correlated inputs than did neurons with highly precise or imprecise spike trains. These findings suggest that pooling correlated neural responses with the levels of precision observed in the auditory midbrain increases neural discrimination of complex vocalizations.
Temporal Interactions between Cortical Rhythms
Roopun, Anita K.; Kramer, Mark A.; Carracedo, Lucy M.; Kaiser, Marcus; Davies, Ceri H.; Traub, Roger D.; Kopell, Nancy J.; Whittington, Miles A.
2008-01-01
Multiple local neuronal circuits support different, discrete frequencies of network rhythm in neocortex. Relationships between different frequencies correspond to mechanisms designed to minimise interference, couple activity via stable phase interactions, and control the amplitude of one frequency relative to the phase of another. These mechanisms are proposed to form a framework for spectral information processing. Individual local circuits can also transform their frequency through changes in intrinsic neuronal properties and interactions with other oscillating microcircuits. Here we discuss a frequency transformation in which activity in two co-active local circuits may combine sequentially to generate a third frequency whose period is the concatenation sum of the original two. With such an interaction, the intrinsic periodicity in each component local circuit is preserved – alternate, single periods of each original rhythm form one period of a new frequency – suggesting a robust mechanism for combining information processed on multiple concurrent spatiotemporal scales. PMID:19225587
NASA Astrophysics Data System (ADS)
Takiguchi, Yu; Toyoda, Haruyoshi
2017-11-01
We report here an algorithm for calculating a hologram to be employed in a high-access speed microscope for observing sensory-driven synaptic activity across all inputs to single living neurons in an intact cerebral cortex. The system is based on holographic multi-beam generation using a two-dimensional phase-only spatial light modulator to excite multiple locations in three dimensions with a single hologram. The hologram was calculated with a three-dimensional weighted iterative Fourier transform method using the Ewald sphere restriction to increase the calculation speed. Our algorithm achieved good uniformity of three dimensionally generated excitation spots; the standard deviation of the spot intensities was reduced by a factor of two compared with a conventional algorithm.
NASA Astrophysics Data System (ADS)
Takiguchi, Yu; Toyoda, Haruyoshi
2018-06-01
We report here an algorithm for calculating a hologram to be employed in a high-access speed microscope for observing sensory-driven synaptic activity across all inputs to single living neurons in an intact cerebral cortex. The system is based on holographic multi-beam generation using a two-dimensional phase-only spatial light modulator to excite multiple locations in three dimensions with a single hologram. The hologram was calculated with a three-dimensional weighted iterative Fourier transform method using the Ewald sphere restriction to increase the calculation speed. Our algorithm achieved good uniformity of three dimensionally generated excitation spots; the standard deviation of the spot intensities was reduced by a factor of two compared with a conventional algorithm.
Spiking irregularity and frequency modulate the behavioral report of single-neuron stimulation.
Doron, Guy; von Heimendahl, Moritz; Schlattmann, Peter; Houweling, Arthur R; Brecht, Michael
2014-02-05
The action potential activity of single cortical neurons can evoke measurable sensory effects, but it is not known how spiking parameters and neuronal subtypes affect the evoked sensations. Here, we examined the effects of spike train irregularity, spike frequency, and spike number on the detectability of single-neuron stimulation in rat somatosensory cortex. For regular-spiking, putative excitatory neurons, detectability increased with spike train irregularity and decreasing spike frequencies but was not affected by spike number. Stimulation of single, fast-spiking, putative inhibitory neurons led to a larger sensory effect compared to regular-spiking neurons, and the effect size depended only on spike irregularity. An ideal-observer analysis suggests that, under our experimental conditions, rats were using integration windows of a few hundred milliseconds or more. Our data imply that the behaving animal is sensitive to single neurons' spikes and even to their temporal patterning. Copyright © 2014 Elsevier Inc. All rights reserved.
Balanced excitation and inhibition are required for high-capacity, noise-robust neuronal selectivity
Abbott, L. F.; Sompolinsky, Haim
2017-01-01
Neurons and networks in the cerebral cortex must operate reliably despite multiple sources of noise. To evaluate the impact of both input and output noise, we determine the robustness of single-neuron stimulus selective responses, as well as the robustness of attractor states of networks of neurons performing memory tasks. We find that robustness to output noise requires synaptic connections to be in a balanced regime in which excitation and inhibition are strong and largely cancel each other. We evaluate the conditions required for this regime to exist and determine the properties of networks operating within it. A plausible synaptic plasticity rule for learning that balances weight configurations is presented. Our theory predicts an optimal ratio of the number of excitatory and inhibitory synapses for maximizing the encoding capacity of balanced networks for given statistics of afferent activations. Previous work has shown that balanced networks amplify spatiotemporal variability and account for observed asynchronous irregular states. Here we present a distinct type of balanced network that amplifies small changes in the impinging signals and emerges automatically from learning to perform neuronal and network functions robustly. PMID:29042519
In vivo neuronal calcium imaging in C. elegans.
Chung, Samuel H; Sun, Lin; Gabel, Christopher V
2013-04-10
The nematode worm C. elegans is an ideal model organism for relatively simple, low cost neuronal imaging in vivo. Its small transparent body and simple, well-characterized nervous system allows identification and fluorescence imaging of any neuron within the intact animal. Simple immobilization techniques with minimal impact on the animal's physiology allow extended time-lapse imaging. The development of genetically-encoded calcium sensitive fluorophores such as cameleon and GCaMP allow in vivo imaging of neuronal calcium relating both cell physiology and neuronal activity. Numerous transgenic strains expressing these fluorophores in specific neurons are readily available or can be constructed using well-established techniques. Here, we describe detailed procedures for measuring calcium dynamics within a single neuron in vivo using both GCaMP and cameleon. We discuss advantages and disadvantages of both as well as various methods of sample preparation (animal immobilization) and image analysis. Finally, we present results from two experiments: 1) Using GCaMP to measure the sensory response of a specific neuron to an external electrical field and 2) Using cameleon to measure the physiological calcium response of a neuron to traumatic laser damage. Calcium imaging techniques such as these are used extensively in C. elegans and have been extended to measurements in freely moving animals, multiple neurons simultaneously and comparison across genetic backgrounds. C. elegans presents a robust and flexible system for in vivo neuronal imaging with advantages over other model systems in technical simplicity and cost.
Isl1 Is required for multiple aspects of motor neuron development
Liang, Xingqun; Song, Mi-Ryoung; Xu, ZengGuang; Lanuza, Guillermo M.; Liu, Yali; Zhuang, Tao; Chen, Yihan; Pfaff, Samuel L.; Evans, Sylvia M.; Sun, Yunfu
2011-01-01
The LIM homeodomain transcription factor Islet1 (Isl1) is expressed in multiple organs and plays essential roles during embryogenesis. Isl1 is required for the survival and specification of spinal cord motor neurons. Due to early embryonic lethality and loss of motor neurons, the role of Isl1 in other aspects of motor neuron development remains unclear. In this study, we generated Isl1 mutant mouse lines expressing graded doses of Isl1. Our study has revealed essential roles of Isl1 in multiple aspects of motor neuron development, including motor neuron cell body localization, motor column formation and axon growth. In addition, Isl1 is required for survival of cranial ganglia neurons. PMID:21569850
Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience.
Paninski, L; Cunningham, J P
2018-06-01
Modern large-scale multineuronal recording methodologies, including multielectrode arrays, calcium imaging, and optogenetic techniques, produce single-neuron resolution data of a magnitude and precision that were the realm of science fiction twenty years ago. The major bottlenecks in systems and circuit neuroscience no longer lie in simply collecting data from large neural populations, but also in understanding this data: developing novel scientific questions, with corresponding analysis techniques and experimental designs to fully harness these new capabilities and meaningfully interrogate these questions. Advances in methods for signal processing, network analysis, dimensionality reduction, and optimal control-developed in lockstep with advances in experimental neurotechnology-promise major breakthroughs in multiple fundamental neuroscience problems. These trends are clear in a broad array of subfields of modern neuroscience; this review focuses on recent advances in methods for analyzing neural time-series data with single-neuronal precision. Copyright © 2018 Elsevier Ltd. All rights reserved.
Rapid learning in visual cortical networks.
Wang, Ye; Dragoi, Valentin
2015-08-26
Although changes in brain activity during learning have been extensively examined at the single neuron level, the coding strategies employed by cell populations remain mysterious. We examined cell populations in macaque area V4 during a rapid form of perceptual learning that emerges within tens of minutes. Multiple single units and LFP responses were recorded as monkeys improved their performance in an image discrimination task. We show that the increase in behavioral performance during learning is predicted by a tight coordination of spike timing with local population activity. More spike-LFP theta synchronization is correlated with higher learning performance, while high-frequency synchronization is unrelated with changes in performance, but these changes were absent once learning had stabilized and stimuli became familiar, or in the absence of learning. These findings reveal a novel mechanism of plasticity in visual cortex by which elevated low-frequency synchronization between individual neurons and local population activity accompanies the improvement in performance during learning.
Holographic imaging and photostimulation of neural activity.
Yang, Weijian; Yuste, Rafael
2018-06-01
Optical imaging methods are powerful tools in neuroscience as they can systematically monitor the activity of neuronal populations with high spatiotemporal resolution using calcium or voltage indicators. Moreover, caged compounds and optogenetic actuators enable to optically manipulate neural activity. Among optical methods, computer-generated holography offers an enormous flexibility to sculpt the excitation light in three-dimensions (3D), particularly when combined with two-photon light sources. By projecting holographic light patterns on the sample, the activity of multiple neurons across a 3D brain volume can be simultaneously imaged or optically manipulated with single-cell precision. This flexibility makes two-photon holographic microscopy an ideal all-optical platform to simultaneously read and write activity in neuronal populations in vivo in 3D, a critical ability to dissect the function of neural circuits. Copyright © 2018 Elsevier Ltd. All rights reserved.
Spike timing precision of neuronal circuits.
Kilinc, Deniz; Demir, Alper
2018-06-01
Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.
A Complete Developmental Sequence of a Drosophila Neuronal Lineage as Revealed by Twin-Spot MARCM
He, Yisheng; Ding, Peng; Kao, Jui-Chun; Lee, Tzumin
2010-01-01
Drosophila brains contain numerous neurons that form complex circuits. These neurons are derived in stereotyped patterns from a fixed number of progenitors, called neuroblasts, and identifying individual neurons made by a neuroblast facilitates the reconstruction of neural circuits. An improved MARCM (mosaic analysis with a repressible cell marker) technique, called twin-spot MARCM, allows one to label the sister clones derived from a common progenitor simultaneously in different colors. It enables identification of every single neuron in an extended neuronal lineage based on the order of neuron birth. Here we report the first example, to our knowledge, of complete lineage analysis among neurons derived from a common neuroblast that relay olfactory information from the antennal lobe (AL) to higher brain centers. By identifying the sequentially derived neurons, we found that the neuroblast serially makes 40 types of AL projection neurons (PNs). During embryogenesis, one PN with multi-glomerular innervation and 18 uniglomerular PNs targeting 17 glomeruli of the adult AL are born. Many more PNs of 22 additional types, including four types of polyglomerular PNs, derive after the neuroblast resumes dividing in early larvae. Although different offspring are generated in a rather arbitrary sequence, the birth order strictly dictates the fate of each post-mitotic neuron, including the fate of programmed cell death. Notably, the embryonic progenitor has an altered temporal identity following each self-renewing asymmetric cell division. After larval hatching, the same progenitor produces multiple neurons for each cell type, but the number of neurons for each type is tightly regulated. These observations substantiate the origin-dependent specification of neuron types. Sequencing neuronal lineages will not only unravel how a complex brain develops but also permit systematic identification of neuron types for detailed structure and function analysis of the brain. PMID:20808769
Neuronal network imaging in acute slices using Ca2+ sensitive bioluminescent reporter.
Tricoire, Ludovic; Lambolez, Bertrand
2014-01-01
Genetically encoded indicators are valuable tools to study intracellular signaling cascades in real time using fluorescent or bioluminescent imaging techniques. Imaging of Ca(2+) indicators is widely used to record transient intracellular Ca(2+) increases associated with bioelectrical activity. The natural bioluminescent Ca(2+) sensor aequorin has been historically the first Ca(2+) indicator used to address biological questions. Aequorin imaging offers several advantages over fluorescent reporters: it is virtually devoid of background signal; it does not require light excitation and interferes little with intracellular processes. Genetically encoded sensors such as aequorin are commonly used in dissociated cultured cells; however it becomes more challenging to express them in differentiated intact specimen such as brain tissue. Here we describe a method to express a GFP-aequorin (GA) fusion protein in pyramidal cells of neocortical acute slices using recombinant Sindbis virus. This technique allows expressing GA in several hundreds of neurons on the same slice and to perform the bioluminescence recording of Ca(2+) transients in single neurons or multiple neurons simultaneously.
A plural role for lipids in motor neuron diseases: energy, signaling and structure
Schmitt, Florent; Hussain, Ghulam; Dupuis, Luc; Loeffler, Jean-Philippe; Henriques, Alexandre
2013-01-01
Motor neuron diseases (MNDs) are characterized by selective death of motor neurons and include mainly adult-onset amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA). Neurodegeneration is not the single pathogenic event occurring during disease progression. There are multiple lines of evidence for the existence of defects in lipid metabolism at peripheral level. For instance, hypermetabolism is well characterized in ALS, and dyslipidemia correlates with better prognosis in patients. Lipid metabolism plays also a role in other MNDs. In SMA, misuse of lipids as energetic nutrients is described in patients and in related animal models. The composition of structural lipids in the central nervous system is modified, with repercussion on membrane fluidity and on cell signaling mediated by bioactive lipids. Here, we review the main epidemiologic and mechanistic findings that link alterations of lipid metabolism and motor neuron degeneration, and we discuss the rationale of targeting these modifications for therapeutic management of MNDs. PMID:24600344
Ultrastructure of antennal sensilla of the peach aphid Myzus persicae Sulzer, 1776.
Ban, Li-Ping; Sun, Yin-Peng; Wang, Ying; Tu, Xiong-Bing; Zhang, Shan-Gan; Zhang, Yun-Ting; Wu, Yun-Sheng; Zhang, Ze-Hua
2015-02-01
The antennal sensilla of alate Myzus persicae were mapped using transmission electron microscopy and the ultrastructure of sensilla trichoidea, coeloconica, and placoidea are described. Trichoid sensilla, located on the tip of the antennae, are innervated by 2-4 neurons, with some outer dendrites reaching the distal end of the hair. Coeloconic sensilla in primary rhinaria are of two morphological types, both equipped with two dendrites. Dendrites of Type II coeloconic sensilla are enveloped in the dendrite sheath, containing the sensillum lymph. In sensilla coeloconica of Type I, instead, dendrites are enclosed by an electron opaque solid cuticle, with no space left for the sensillum lymph. The ultrastructure of big placoid sensillum reveals the presence of three groups of neurons, with 2-3 dendrites in each neuron group, while both small placoid sensilla are equipped with a single group of neurons, consisting of three dendrites. Both large and small placoid sensilla bear multiple pores on the outer cuticle. The function of these sensilla is also discussed. © 2014 Wiley Periodicals, Inc.
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.
Vallano, M L; Beaman-Hall, C M; Mathur, A; Chen, Q
2000-04-01
Multiple isoforms of type II Ca(2+)-calmodulin-dependent kinase (CaM KII) are composed of two major neuron-specific subunits, designated alpha and beta, and two less well-characterized subunits that are also expressed in non-neuronal tissues, designated delta and gamma. Regulated expression of these 4 gene products, and several variants produced by alternative splicing, shows temporal and regional specificity and influences intracellular targeting. We used immunoblotting and RT-PCR to analyze subunit and variant expression and distribution in cultured cerebellar astrocytes and neurons, and whole cerebellar cortex from rodent brain. The data indicate that: (i) astrocytes express a single splice variant of delta, namely delta(2); (ii) like neurons, astrocytes express two forms of CaM KII gamma; gamma(B) and gamma(A); (iii) these CaM KII variants are enriched in the supernate fraction in astrocytes, and the particulate fraction in neurons; (iv) unlike neurons, astrocytes do not express detectable levels of alpha or beta subunits or their respective splice variants. The results indicate that neurons and astrocytes express distinct CaM KII subunits and variants that localize to distinct subcellular compartments and, by inference, exert distinct cellular functions. Copyright 2000 Wiley-Liss, Inc.
Stimulus encoding and feature extraction by multiple sensory neurons.
Krahe, Rüdiger; Kreiman, Gabriel; Gabbiani, Fabrizio; Koch, Christof; Metzner, Walter
2002-03-15
Neighboring cells in topographical sensory maps may transmit similar information to the next higher level of processing. How information transmission by groups of nearby neurons compares with the performance of single cells is a very important question for understanding the functioning of the nervous system. To tackle this problem, we quantified stimulus-encoding and feature extraction performance by pairs of simultaneously recorded electrosensory pyramidal cells in the hindbrain of weakly electric fish. These cells constitute the output neurons of the first central nervous stage of electrosensory processing. Using random amplitude modulations (RAMs) of a mimic of the fish's own electric field within behaviorally relevant frequency bands, we found that pyramidal cells with overlapping receptive fields exhibit strong stimulus-induced correlations. To quantify the encoding of the RAM time course, we estimated the stimuli from simultaneously recorded spike trains and found significant improvements over single spike trains. The quality of stimulus reconstruction, however, was still inferior to the one measured for single primary sensory afferents. In an analysis of feature extraction, we found that spikes of pyramidal cell pairs coinciding within a time window of a few milliseconds performed significantly better at detecting upstrokes and downstrokes of the stimulus compared with isolated spikes and even spike bursts of single cells. Coincident spikes can thus be considered "distributed bursts." Our results suggest that stimulus encoding by primary sensory afferents is transformed into feature extraction at the next processing stage. There, stimulus-induced coincident activity can improve the extraction of behaviorally relevant features from the stimulus.
Isl1 is required for multiple aspects of motor neuron development.
Liang, Xingqun; Song, Mi-Ryoung; Xu, ZengGuang; Lanuza, Guillermo M; Liu, Yali; Zhuang, Tao; Chen, Yihan; Pfaff, Samuel L; Evans, Sylvia M; Sun, Yunfu
2011-07-01
The LIM homeodomain transcription factor Islet1 (Isl1) is expressed in multiple organs and plays essential roles during embryogenesis. Isl1 is required for the survival and specification of spinal cord motor neurons. Due to early embryonic lethality and loss of motor neurons, the role of Isl1 in other aspects of motor neuron development remains unclear. In this study, we generated Isl1 mutant mouse lines expressing graded doses of Isl1. Our study has revealed essential roles of Isl1 in multiple aspects of motor neuron development, including motor neuron cell body localization, motor column formation and axon growth. In addition, Isl1 is required for survival of cranial ganglia neurons. Copyright © 2011 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Wang, Qingyun; Zhang, Honghui; Chen, Guanrong
2012-12-01
We study the effect of heterogeneous neuron and information transmission delay on stochastic resonance of scale-free neuronal networks. For this purpose, we introduce the heterogeneity to the specified neuron with the highest degree. It is shown that in the absence of delay, an intermediate noise level can optimally assist spike firings of collective neurons so as to achieve stochastic resonance on scale-free neuronal networks for small and intermediate αh, which plays a heterogeneous role. Maxima of stochastic resonance measure are enhanced as αh increases, which implies that the heterogeneity can improve stochastic resonance. However, as αh is beyond a certain large value, no obvious stochastic resonance can be observed. If the information transmission delay is introduced to neuronal networks, stochastic resonance is dramatically affected. In particular, the tuned information transmission delay can induce multiple stochastic resonance, which can be manifested as well-expressed maximum in the measure for stochastic resonance, appearing every multiple of one half of the subthreshold stimulus period. Furthermore, we can observe that stochastic resonance at odd multiple of one half of the subthreshold stimulus period is subharmonic, as opposed to the case of even multiple of one half of the subthreshold stimulus period. More interestingly, multiple stochastic resonance can also be improved by the suitable heterogeneous neuron. Presented results can provide good insights into the understanding of the heterogeneous neuron and information transmission delay on realistic neuronal networks.
Building an organic computing device with multiple interconnected brains
Pais-Vieira, Miguel; Chiuffa, Gabriela; Lebedev, Mikhail; Yadav, Amol; Nicolelis, Miguel A. L.
2015-01-01
Recently, we proposed that Brainets, i.e. networks formed by multiple animal brains, cooperating and exchanging information in real time through direct brain-to-brain interfaces, could provide the core of a new type of computing device: an organic computer. Here, we describe the first experimental demonstration of such a Brainet, built by interconnecting four adult rat brains. Brainets worked by concurrently recording the extracellular electrical activity generated by populations of cortical neurons distributed across multiple rats chronically implanted with multi-electrode arrays. Cortical neuronal activity was recorded and analyzed in real time, and then delivered to the somatosensory cortices of other animals that participated in the Brainet using intracortical microstimulation (ICMS). Using this approach, different Brainet architectures solved a number of useful computational problems, such as discrete classification, image processing, storage and retrieval of tactile information, and even weather forecasting. Brainets consistently performed at the same or higher levels than single rats in these tasks. Based on these findings, we propose that Brainets could be used to investigate animal social behaviors as well as a test bed for exploring the properties and potential applications of organic computers. PMID:26158615
Single-neuron labeling with inducible cre-mediated knockout in transgenic mice
Young, Paul; Qiu, Li; Wang, Dongqing; Zhao, Shengli; Gross, James; Feng, Guoping
2011-01-01
To facilitate functional analysis of neuronal connectivity in a mammalian nervous system tightly packed with billions of cells, we developed a new technique that allows inducible genetic manipulations within fluorescently labeled single neurons in mice. We term this technique SLICK for Single-neuron Labeling with Inducible Cre-mediated Knockout. SLICK is achieved by co-expressing a drug-inducible form of cre recombinase and a fluorescent protein within the same small subsets of neurons. Thus, SLICK combines the powerful cre recombinase system for conditional genetic manipulation and the fluorescent labeling of single neurons for imaging. We demonstrate efficient inducible genetic manipulation in several types of neurons using SLICK. Furthermore, we apply SLICK to eliminate synaptic transmission in a small subset of neuromuscular junctions. Our results provide evidence for the long-term stability of inactive neuromuscular synapses in adult animals. More broadly, these studies demonstrate a cre-LoxP compatible system for dissecting gene functions in single identifiable neurons. PMID:18454144
Amount of fear extinction changes its underlying mechanisms
An, Bobae; Kim, Jihye; Park, Kyungjoon; Lee, Sukwon; Song, Sukwoon; Choi, Sukwoo
2017-01-01
There has been a longstanding debate on whether original fear memory is inhibited or erased after extinction. One possibility that reconciles this uncertainty is that the inhibition and erasure mechanisms are engaged in different phases (early or late) of extinction. In this study, using single-session extinction training and its repetition (multiple-session extinction training), we investigated the inhibition and erasure mechanisms in the prefrontal cortex and amygdala of rats, where neural circuits underlying extinction reside. The inhibition mechanism was prevalent with single-session extinction training but faded when single-session extinction training was repeated. In contrast, the erasure mechanism became prevalent when single-session extinction training was repeated. Moreover, ablating the intercalated neurons of amygdala, which are responsible for maintaining extinction-induced inhibition, was no longer effective in multiple-session extinction training. We propose that the inhibition mechanism operates primarily in the early phase of extinction training, and the erasure mechanism takes over after that. DOI: http://dx.doi.org/10.7554/eLife.25224.001 PMID:28671550
Neural correlates of olfactory learning paradigms in an identified neuron in the honeybee brain.
Mauelshagen, J
1993-02-01
1. Sensitization and classical odor conditioning of the proboscis extension reflex were functionally analyzed by repeated intracellular recordings from a single identified neuron (PE1-neuron) in the central bee brain. This neuron belongs to the class of "extrinsic cells" arising from the pedunculus of the mushroom bodies and has extensive arborizations in the median and lateral protocerebrum. The recordings were performed on isolated bee heads. 2. Two different series of physiological experiments were carried out with the use of a similar temporal succession of stimuli as in previous behavioral experiments. In the first series, one group of animals was used for a single conditioning trial [conditioned stimulus (CS), carnation; unconditioned stimulus (US), sucrose solution to the antennae and proboscis), a second group was used for sensitization (sensitizing stimulus, sucrose solution to the antennae and/or proboscis), and the third group served as control (no sucrose stimulation). In the second series, a differential conditioning paradigm (paired odor CS+, carnation; unpaired odor CS-, orange blossom) was applied to test the associative nature of the conditioning effect. 3. The PE1-neuron showed a characteristic burstlike odor response before the training procedures. The treatments resulted in different spike-frequency modulations of this response, which were specific for the nonassociative and associative stimulus paradigms applied. During differential conditioning, there are dynamic up and down modulations of spike frequencies and of the DC potentials underlying the responses to the CS+. Overall, only transient changes in the minute range were observed. 4. The results of the sensitization procedures suggest two qualitatively different US pathways. The comparison between sensitization and one-trial conditioning shows differential effects of nonassociative and associative stimulus paradigms on the response behavior of the PE1-neuron. The results of the differential conditioning procedure reveal that the effect observed for the one-trial conditioning paradigm is of an associative nature and that there might be modulations, which are specific for single and multiple trial conditioning procedures. It is hypothesized that the PE1-neuron is a possible element involved in the short-term acquisition, rather than in the long-term storage, of an associative olfactory memory in the honeybee.
Cracking Taste Codes by Tapping into Sensory Neuron Impulse Traffic
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
C. elegans STRADalpha and SAD cooperatively regulate neuronal polarity and synaptic organization.
Kim, Joanne S M; Hung, Wesley; Narbonne, Patrick; Roy, Richard; Zhen, Mei
2010-01-01
Neurons are polarized cells with morphologically and functionally distinct axons and dendrites. The SAD kinases are crucial for establishing the axon-dendrite identity across species. Previous studies suggest that a tumour suppressor kinase, LKB1, in the presence of a pseudokinase, STRADalpha, initiates axonal differentiation and growth through activating the SAD kinases in vertebrate neurons. STRADalpha was implicated in the localization, stabilization and activation of LKB1 in various cell culture studies. Its in vivo functions, however, have not been examined. In our present study, we analyzed the neuronal phenotypes of the first loss-of-function mutants for STRADalpha and examined their genetic interactions with LKB1 and SAD in C. elegans. Unexpectedly, only the C. elegans STRADalpha, STRD-1, functions exclusively through the SAD kinase, SAD-1, to regulate neuronal polarity and synaptic organization. Moreover, STRD-1 tightly associates with SAD-1 to coordinate its synaptic localizations. By contrast, the C. elegans LKB1, PAR-4, also functions in an additional genetic pathway independently of SAD-1 and STRD-1 to regulate neuronal polarity. We propose that STRD-1 establishes neuronal polarity and organizes synaptic proteins in a complex with the SAD-1 kinase. Our findings suggest that instead of a single, linear genetic pathway, STRADalpha and LKB1 regulate neuronal development through multiple effectors that are shared in some cellular contexts but distinct in others.
Lee, S K; Lee, S; Shin, S Y; Ryu, P D; Lee, S Y
2012-03-15
The hypothalamic paraventricular nucleus (PVN), a site for the integration of both the neuroendocrine and autonomic systems, has heterogeneous cell composition. These neurons are classified into type I and type II neurons based on their electrophysiological properties. In the present study, we investigated the molecular identification of voltage-gated K+ (Kv) channels, which determines a distinctive characteristic of type I PVN neurons, by means of single-cell reverse transcription-polymerase chain reaction (RT-PCR) along with slice patch clamp recordings. In order to determine the mRNA expression profiles, firstly, the PVN neurons of male rats were classified into type I and type II neurons, and then, single-cell RT-PCR and single-cell real-time RT-PCR analysis were performed using the identical cell. The single-cell RT-PCR analysis revealed that Kv1.2, Kv1.3, Kv1.4, Kv4.1, Kv4.2, and Kv4.3 were expressed both in type I and in type II neurons, and several Kv channels were co-expressed in a single PVN neuron. However, we found that the expression densities of Kv4.2 and Kv4.3 were significantly higher in type I neurons than in type II neurons. Taken together, several Kv channels encoding A-type K+ currents are present both in type I and in type II neurons, and among those, Kv4.2 and Kv4.3 are the major Kv subunits responsible for determining the distinct electrophysiological properties. Thus these 2 Kv subunits may play important roles in determining PVN cell types and regulating PVN neuronal excitability. This study further provides key molecular mechanisms for differentiating type I and type II PVN neurons. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.
A microprobe for parallel optical and electrical recordings from single neurons in vivo.
LeChasseur, Yoan; Dufour, Suzie; Lavertu, Guillaume; Bories, Cyril; Deschênes, Martin; Vallée, Réal; De Koninck, Yves
2011-04-01
Recording electrical activity from identified neurons in intact tissue is key to understanding their role in information processing. Recent fluorescence labeling techniques have opened new possibilities to combine electrophysiological recording with optical detection of individual neurons deep in brain tissue. For this purpose we developed dual-core fiberoptics-based microprobes, with an optical core to locally excite and collect fluorescence, and an electrolyte-filled hollow core for extracellular single unit electrophysiology. This design provides microprobes with tips < 10 μm, enabling analyses with single-cell optical resolution. We demonstrate combined electrical and optical detection of single fluorescent neurons in rats and mice. We combined electrical recordings and optical Ca²(+) measurements from single thalamic relay neurons in rats, and achieved detection and activation of single channelrhodopsin-expressing neurons in Thy1::ChR2-YFP transgenic mice. The microprobe expands possibilities for in vivo electrophysiological recording, providing parallel access to single-cell optical monitoring and control.
The Complex Structure of Receptive Fields in the Middle Temporal Area
Richert, Micah; Albright, Thomas D.; Krekelberg, Bart
2012-01-01
Neurons in the middle temporal area (MT) are often viewed as motion detectors that prefer a single direction of motion in a single region of space. This assumption plays an important role in our understanding of visual processing, and models of motion processing in particular. We used extracellular recordings in area MT of awake, behaving monkeys (M. mulatta) to test this assumption with a novel reverse correlation approach. Nearly half of the MT neurons in our sample deviated significantly from the classical view. First, in many cells, direction preference changed with the location of the stimulus within the receptive field. Second, the spatial response profile often had multiple peaks with apparent gaps in between. This shows that visual motion analysis in MT has access to motion detectors that are more complex than commonly thought. This complexity could be a mere byproduct of imperfect development, but can also be understood as the natural consequence of the non-linear, recurrent interactions among laterally connected MT neurons. An important direction for future research is to investigate whether these in homogeneities are advantageous, how they can be incorporated into models of motion detection, and whether they can provide quantitative insight into the underlying effective connectivity. PMID:23508640
O-GlcNAc cycling in the developing, adult and geriatric brain.
Lagerlöf, Olof
2018-06-01
Hundreds of proteins in the nervous system are modified by the monosaccharide O-GlcNAc. A single protein is often O-GlcNAcylated on several amino acids and the modification of a single site can play a crucial role for the function of the protein. Despite its complexity, only two enzymes add and remove O-GlcNAc from proteins, O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA). Global and local regulation of these enzymes make it possible for O-GlcNAc to coordinate multiple cellular functions at the same time as regulating specific pathways independently from each other. If O-GlcNAcylation is disrupted, metabolic disorder or intellectual disability may ensue, depending on what neurons are affected. O-GlcNAc's promise as a clinical target for developing drugs against neurodegenerative diseases has been recognized for many years. Recent literature puts O-GlcNAc in the forefront among mechanisms that can help us better understand how neuronal circuits integrate diverse incoming stimuli such as fluctuations in nutrient supply, metabolic hormones, neuronal activity and cellular stress. Here the functions of O-GlcNAc in the nervous system are reviewed.
A Novel and Simple Spike Sorting Implementation.
Petrantonakis, Panagiotis C; Poirazi, Panayiota
2017-04-01
Monitoring the activity of multiple, individual neurons that fire spikes in the vicinity of an electrode, namely perform a Spike Sorting (SS) procedure, comprises one of the most important tools for contemporary neuroscience in order to reverse-engineer the brain. As recording electrodes' technology rabidly evolves by integrating thousands of electrodes in a confined spatial setting, the algorithms that are used to monitor individual neurons from recorded signals have to become even more reliable and computationally efficient. In this work, we propose a novel framework of the SS approach in which a single-step processing of the raw (unfiltered) extracellular signal is sufficient for both the detection and sorting of the activity of individual neurons. Despite its simplicity, the proposed approach exhibits comparable performance with state-of-the-art approaches, especially for spike detection in noisy signals, and paves the way for a new family of SS algorithms with the potential for multi-recording, fast, on-chip implementations.
Multivesicular Bodies in Neurons: Distribution, Protein Content, and Trafficking Functions
VON BARTHELD, CHRISTOPHER S.; ALTICK, AMY L.
2011-01-01
Summary Multivesicular bodies (MVBs) are intracellular endosomal organelles characterized by multiple internal vesicles that are enclosed within a single outer membrane. MVBs were initially regarded as purely prelysosomal structures along the degradative endosomal pathway of internalized proteins. MVBs are now known to be involved in numerous endocytic and trafficking functions, including protein sorting, recycling, transport, storage, and release. This review of neuronal MVBs summarizes their research history, morphology, distribution, accumulation of cargo and constitutive proteins, transport, and theories of functions of MVBs in neurons and glia. Due to their complex morphologies, neurons have expanded trafficking and signaling needs, beyond those of “geometrically simpler” cells, but it is not known whether neuronal MVBs perform additional transport and signaling functions. This review examines the concept of compartment-specific MVB functions in endosomal protein trafficking and signaling within synapses, axons, dendrites and cell bodies. We critically evaluate reports of the accumulation of neuronal MVBs based on evidence of stress-induced MVB formation. Furthermore, we discuss potential functions of neuronal and glial MVBs in development, in dystrophic neuritic syndromes, injury, disease, and aging. MVBs may play a role in Alzheimer’s, Huntington’s, and Niemann-Pick diseases, some types of frontotemporal dementia, prion and virus trafficking, as well as in adaptive responses of neurons to trauma and toxin or drug exposure. Functions of MVBs in neurons have been much neglected, and major gaps in knowledge currently exist. Developing truly MVB-specific markers would help to elucidate the roles of neuronal MVBs in intra- and intercellular signaling of normal and diseased neurons. PMID:21216273
Responses of prefrontal multisensory neurons to mismatching faces and vocalizations.
Diehl, Maria M; Romanski, Lizabeth M
2014-08-20
Social communication relies on the integration of auditory and visual information, which are present in faces and vocalizations. Evidence suggests that the integration of information from multiple sources enhances perception compared with the processing of a unimodal stimulus. Our previous studies demonstrated that single neurons in the ventrolateral prefrontal cortex (VLPFC) of the rhesus monkey (Macaca mulatta) respond to and integrate conspecific vocalizations and their accompanying facial gestures. We were therefore interested in how VLPFC neurons respond differentially to matching (congruent) and mismatching (incongruent) faces and vocalizations. We recorded VLPFC neurons during the presentation of movies with congruent or incongruent species-specific facial gestures and vocalizations as well as their unimodal components. Recordings showed that while many VLPFC units are multisensory and respond to faces, vocalizations, or their combination, a subset of neurons showed a significant change in neuronal activity in response to incongruent versus congruent vocalization movies. Among these neurons, we typically observed incongruent suppression during the early stimulus period and incongruent enhancement during the late stimulus period. Incongruent-responsive VLPFC neurons were both bimodal and nonlinear multisensory, fostering their ability to respond to changes in either modality of a face-vocalization stimulus. These results demonstrate that ventral prefrontal neurons respond to changes in either modality of an audiovisual stimulus, which is important in identity processing and for the integration of multisensory communication information. Copyright © 2014 the authors 0270-6474/14/3411233-11$15.00/0.
Appel, Elena; Weissmann, Sarit; Salzberg, Yehuda; Orlovsky, Kira; Negreanu, Varda; Tsoory, Michael; Raanan, Calanit; Feldmesser, Ester; Bernstein, Yael; Wolstein, Orit; Levanon, Ditsa; Groner, Yoram
2016-12-01
The Runx3 transcription factor is essential for development and diversification of the dorsal root ganglia (DRGs) TrkC sensory neurons. In Runx3-deficient mice, developing TrkC neurons fail to extend central and peripheral afferents, leading to cell death and disruption of the stretch reflex circuit, resulting in severe limb ataxia. Despite its central role, the mechanisms underlying the spatiotemporal expression specificities of Runx3 in TrkC neurons were largely unknown. Here we first defined the genomic transcription unit encompassing regulatory elements (REs) that mediate the tissue-specific expression of Runx3. Using transgenic mice expressing BAC reporters spanning the Runx3 locus, we discovered three REs-dubbed R1, R2, and R3-that cross-talk with promoter-2 (P2) to drive TrkC neuron-specific Runx3 transcription. Deletion of single or multiple elements either in the BAC transgenics or by CRISPR/Cas9-mediated endogenous ablation established the REs' ability to promote and/or repress Runx3 expression in developing sensory neurons. Our analysis reveals that an intricate combinatorial interplay among the three REs governs Runx3 expression in distinct subtypes of TrkC neurons while concomitantly extinguishing its expression in non-TrkC neurons. These findings provide insights into the mechanism regulating cell type-specific expression and subtype diversification of TrkC neurons in developing DRGs. © 2016 Appel et al.; Published by Cold Spring Harbor Laboratory Press.
Unidirectional signal propagation in primary neurons micropatterned at a single-cell resolution
NASA Astrophysics Data System (ADS)
Yamamoto, H.; Matsumura, R.; Takaoki, H.; Katsurabayashi, S.; Hirano-Iwata, A.; Niwano, M.
2016-07-01
The structure and connectivity of cultured neuronal networks can be controlled by using micropatterned surfaces. Here, we demonstrate that the direction of signal propagation can be precisely controlled at a single-cell resolution by growing primary neurons on micropatterns. To achieve this, we first examined the process by which axons develop and how synapses form in micropatterned primary neurons using immunocytochemistry. By aligning asymmetric micropatterns with a marginal gap, it was possible to pattern primary neurons with a directed polarization axis at the single-cell level. We then examined how synapses develop on micropatterned hippocampal neurons. Three types of micropatterns with different numbers of short paths for dendrite growth were compared. A normal development in synapse density was observed when micropatterns with three or more short paths were used. Finally, we performed double patch clamp recordings on micropatterned neurons to confirm that these synapses are indeed functional, and that the neuronal signal is transmitted unidirectionally in the intended orientation. This work provides a practical guideline for patterning single neurons to design functional neuronal networks in vitro with the direction of signal propagation being controlled.
Yang, Yunze; Liu, Xian-Wei; Wang, Hui; Yu, Hui; Guan, Yan; Wang, Shaopeng; Tao, Nongjian
2018-03-28
Action potentials in neurons have been studied traditionally by intracellular electrophysiological recordings and more recently by the fluorescence detection methods. Here we describe a label-free optical imaging method that can measure mechanical motion in single cells with a sub-nanometer detection limit. Using the method, we have observed sub-nanometer mechanical motion accompanying the action potential in single mammalian neurons by averaging the repeated action potential spikes. The shape and width of the transient displacement are similar to those of the electrically recorded action potential, but the amplitude varies from neuron to neuron, and from one region of a neuron to another, ranging from 0.2-0.4 nm. The work indicates that action potentials may be studied noninvasively in single mammalian neurons by label-free imaging of the accompanying sub-nanometer mechanical motion.
Handel, Adam E.; Chintawar, Satyan; Lalic, Tatjana; Whiteley, Emma; Vowles, Jane; Giustacchini, Alice; Argoud, Karene; Sopp, Paul; Nakanishi, Mahito; Bowden, Rory; Cowley, Sally; Newey, Sarah; Akerman, Colin; Ponting, Chris P.; Cader, M. Zameel
2016-01-01
Induced pluripotent stem cell (iPSC)-derived cortical neurons potentially present a powerful new model to understand corticogenesis and neurological disease. Previous work has established that differentiation protocols can produce cortical neurons, but little has been done to characterize these at cellular resolution. In particular, it is unclear to what extent in vitro two-dimensional, relatively disordered culture conditions recapitulate the development of in vivo cortical layer identity. Single-cell multiplex reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was used to interrogate the expression of genes previously implicated in cortical layer or phenotypic identity in individual cells. Totally, 93.6% of single cells derived from iPSCs expressed genes indicative of neuronal identity. High proportions of single neurons derived from iPSCs expressed glutamatergic receptors and synaptic genes. And, 68.4% of iPSC-derived neurons expressing at least one layer marker could be assigned to a laminar identity using canonical cortical layer marker genes. We compared single-cell RNA-seq of our iPSC-derived neurons to available single-cell RNA-seq data from human fetal and adult brain and found that iPSC-derived cortical neurons closely resembled primary fetal brain cells. Unexpectedly, a subpopulation of iPSC-derived neurons co-expressed canonical fetal deep and upper cortical layer markers. However, this appeared to be concordant with data from primary cells. Our results therefore provide reassurance that iPSC-derived cortical neurons are highly similar to primary cortical neurons at the level of single cells but suggest that current layer markers, although effective, may not be able to disambiguate cortical layer identity in all cells. PMID:26740550
Shevchouk, Olesya T; Ball, Gregory F; Cornil, Charlotte A; Balthazart, Jacques
2017-01-01
In songbirds, neurogenesis in the song control nucleus HVC is sensitive to the hormonal and social environment but the dynamics of this process is difficult to assess with a single exogenous marker of new neurons. We simultaneously used three independent markers to investigate HVC neurogenesis in male and female canaries. Males were castrated, implanted with testosterone and housed either alone (M), with a female (M-F) or with another male (M-M) while females were implanted with 17β-estradiol and housed with a male (F-M). All subjects received injections of the two thymidine analogues, BrdU and of EdU, respectively 21 and 10 days before brain collection. Cells containing BrdU or EdU or expressing doublecortin (DCX), which labels newborn neurons, were quantified. Social context and sex differentially affected total BrdU+, EdU+, BrdU+EdU- and DCX+ populations. M-M males had a higher density of BrdU+ cells in the ventricular zone adjacent to HVC and of EdU+ in HVC than M-F males. M birds had a higher ratio of BrdU+EdU- to EdU+ cells than M-F subjects suggesting higher survival of newer neurons in the former group. Total number of HVC DCX+ cells was lower in M-F than in M-M males. Sex differences were also dependent of the type of marker used. Several technical limitations associated with the use of these multiple markers were also identified. These results indicate that proliferation, recruitment and survival of new neurons can be independently affected by environmental conditions and effects can only be fully discerned through the use of multiple neurogenesis markers.
Shevchouk, Olesya T.; Ball, Gregory F.; Cornil, Charlotte A.
2017-01-01
In songbirds, neurogenesis in the song control nucleus HVC is sensitive to the hormonal and social environment but the dynamics of this process is difficult to assess with a single exogenous marker of new neurons. We simultaneously used three independent markers to investigate HVC neurogenesis in male and female canaries. Males were castrated, implanted with testosterone and housed either alone (M), with a female (M-F) or with another male (M-M) while females were implanted with 17β-estradiol and housed with a male (F-M). All subjects received injections of the two thymidine analogues, BrdU and of EdU, respectively 21 and 10 days before brain collection. Cells containing BrdU or EdU or expressing doublecortin (DCX), which labels newborn neurons, were quantified. Social context and sex differentially affected total BrdU+, EdU+, BrdU+EdU- and DCX+ populations. M-M males had a higher density of BrdU+ cells in the ventricular zone adjacent to HVC and of EdU+ in HVC than M-F males. M birds had a higher ratio of BrdU+EdU- to EdU+ cells than M-F subjects suggesting higher survival of newer neurons in the former group. Total number of HVC DCX+ cells was lower in M-F than in M-M males. Sex differences were also dependent of the type of marker used. Several technical limitations associated with the use of these multiple markers were also identified. These results indicate that proliferation, recruitment and survival of new neurons can be independently affected by environmental conditions and effects can only be fully discerned through the use of multiple neurogenesis markers. PMID:28141859
Kim, J H; Ohara, S; Lenz, F A
2009-04-01
Primate thalamic action potential bursts associated with low-threshold spikes (LTS) occur during waking sensory and motor activity. We now test the hypothesis that different firing and LTS burst characteristics occur during quiet wakefulness (spontaneous condition) versus mental arithmetic (counting condition). This hypothesis was tested by thalamic recordings during the surgical treatment of tremor. Across all neurons and epochs, preburst interspike intervals (ISIs) were bimodal at median values, consistent with the duration of type A and type B gamma-aminobutyric acid inhibitory postsynaptic potentials. Neuronal spike trains (117 neurons) were categorized by joint ISI distributions into those firing as LTS bursts (G, grouped), firing as single spikes (NG, nongrouped), or firing as single spikes with sporadic LTS bursting (I, intermediate). During the spontaneous condition (46 neurons) only I spike trains changed category. Overall, burst rates (BRs) were lower and firing rates (FRs) were higher during the counting versus the spontaneous condition. Spike trains in the G category sometimes changed to I and NG categories at the transition from the spontaneous to the counting condition, whereas those in the I category often changed to NG. Among spike trains that did not change category by condition, G spike trains had lower BRs during counting, whereas NG spike trains had higher FRs. BRs were significantly greater than zero for G and I categories during wakefulness (both conditions). The changes between the spontaneous and counting conditions are most pronounced for the I category, which may be a transitional firing pattern between the bursting (G) and relay modes of thalamic firing (NG).
He, C; Chen, Q-H; Ye, J-N; Li, C; Yang, L; Zhang, J; Xia, J-X; Hu, Z-A
2015-06-25
The hypocretin signaling is thought to play a critical role in maintaining wakefulness via stimulating the subcortical arousal pathways. Although the cortical areas, including the medial prefrontal cortex (mPFC), receive dense hypocretinergic fibers and express its receptors, it remains unclear whether the hypocretins can directly regulate the neural activity of the mPFC in vivo. In the present study, using multiple-channel single-unit recording study, we found that infusion of the SB-334867, a blocker for the Hcrtr1, beside the recording sites within the mPFC substantially exerted an inhibitory effect on the putative pyramidal neuron (PPN) activity in naturally behaving rats. In addition, functional blockade of the Hcrtr1 also selectively reduced the power of the gamma oscillations. The PPN activity and the power of the neural oscillations were not affected after microinjection of the TCS-OX2-29, a blocker for the Hcrtr2, within the mPFC. Together, these data indicate that endogenous hypocretins acting on the Hcrtr1 are required for the normal neural activity in the mPFC in vivo, and thus might directly contribute cortical arousal and mPFC-dependent cognitive processes. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.
Reward inference by primate prefrontal and striatal neurons.
Pan, Xiaochuan; Fan, Hongwei; Sawa, Kosuke; Tsuda, Ichiro; Tsukada, Minoru; Sakagami, Masamichi
2014-01-22
The brain contains multiple yet distinct systems involved in reward prediction. To understand the nature of these processes, we recorded single-unit activity from the lateral prefrontal cortex (LPFC) and the striatum in monkeys performing a reward inference task using an asymmetric reward schedule. We found that neurons both in the LPFC and in the striatum predicted reward values for stimuli that had been previously well experienced with set reward quantities in the asymmetric reward task. Importantly, these LPFC neurons could predict the reward value of a stimulus using transitive inference even when the monkeys had not yet learned the stimulus-reward association directly; whereas these striatal neurons did not show such an ability. Nevertheless, because there were two set amounts of reward (large and small), the selected striatal neurons were able to exclusively infer the reward value (e.g., large) of one novel stimulus from a pair after directly experiencing the alternative stimulus with the other reward value (e.g., small). Our results suggest that although neurons that predict reward value for old stimuli in the LPFC could also do so for new stimuli via transitive inference, those in the striatum could only predict reward for new stimuli via exclusive inference. Moreover, the striatum showed more complex functions than was surmised previously for model-free learning.
Reward Inference by Primate Prefrontal and Striatal Neurons
Pan, Xiaochuan; Fan, Hongwei; Sawa, Kosuke; Tsuda, Ichiro; Tsukada, Minoru
2014-01-01
The brain contains multiple yet distinct systems involved in reward prediction. To understand the nature of these processes, we recorded single-unit activity from the lateral prefrontal cortex (LPFC) and the striatum in monkeys performing a reward inference task using an asymmetric reward schedule. We found that neurons both in the LPFC and in the striatum predicted reward values for stimuli that had been previously well experienced with set reward quantities in the asymmetric reward task. Importantly, these LPFC neurons could predict the reward value of a stimulus using transitive inference even when the monkeys had not yet learned the stimulus–reward association directly; whereas these striatal neurons did not show such an ability. Nevertheless, because there were two set amounts of reward (large and small), the selected striatal neurons were able to exclusively infer the reward value (e.g., large) of one novel stimulus from a pair after directly experiencing the alternative stimulus with the other reward value (e.g., small). Our results suggest that although neurons that predict reward value for old stimuli in the LPFC could also do so for new stimuli via transitive inference, those in the striatum could only predict reward for new stimuli via exclusive inference. Moreover, the striatum showed more complex functions than was surmised previously for model-free learning. PMID:24453328
Logarithmic Compression of Sensory Signals within the Dendritic Tree of a Collision-Sensitive Neuron
2012-01-01
Neurons in a variety of species, both vertebrate and invertebrate, encode the kinematics of objects approaching on a collision course through a time-varying firing rate profile that initially increases, then peaks, and eventually decays as collision becomes imminent. In this temporal profile, the peak firing rate signals when the approaching object's subtended size reaches an angular threshold, an event which has been related to the timing of escape behaviors. In a locust neuron called the lobula giant motion detector (LGMD), the biophysical basis of this angular threshold computation relies on a multiplicative combination of the object's angular size and speed, achieved through a logarithmic-exponential transform. To understand how this transform is implemented, we modeled the encoding of angular velocity along the pathway leading to the LGMD based on the experimentally determined activation pattern of its presynaptic neurons. These simulations show that the logarithmic transform of angular speed occurs between the synaptic conductances activated by the approaching object onto the LGMD's dendritic tree and its membrane potential at the spike initiation zone. Thus, we demonstrate an example of how a single neuron's dendritic tree implements a mathematical step in a neural computation important for natural behavior. PMID:22492048
Fornaro, Michele; Sharthiya, Harsh; Tiwari, Vaibhav
2018-03-09
This protocol describes an ex vivo model of mouse-derived dorsal root ganglia (DRG) explant and in vitro DRG-derived co-culture of dissociated sensory neurons and glial satellite cells. These are useful and versatile models to investigate a variety of biological responses associated with physiological and pathological conditions of the peripheral nervous system (PNS) ranging from neuron-glial interaction, neuroplasticity, neuroinflammation, and viral infection. The usage of DRG explant is scientifically advantageous compared to simplistic single cells models for multiple reasons. For instance, as an organotypic culture, the DRG explant allows ex vivo transfer of an entire neuronal network including the extracellular microenvironment that play a significant role in all the neuronal and glial functions. Further, DRG explants can also be maintained ex vivo for several days and the culture conditions can be perturbed as desired. In addition, the harvested DRG can be further dissociated into an in vitro co-culture of primary sensory neurons and satellite glial cells to investigate neuronal-glial interaction, neuritogenesis, axonal cone interaction with the extracellular microenvironment, and more general, any aspect associated with the neuronal metabolism. Therefore, the DRG-explant system offers a great deal of flexibility to study a wide array of events related to biological, physiological, and pathological conditions in a cost-effective manner.
Mapping cortical mesoscopic networks of single spiking cortical or sub-cortical neurons
Xiao, Dongsheng; Vanni, Matthieu P; Mitelut, Catalin C; Chan, Allen W; LeDue, Jeffrey M; Xie, Yicheng; Chen, Andrew CN; Swindale, Nicholas V; Murphy, Timothy H
2017-01-01
Understanding the basis of brain function requires knowledge of cortical operations over wide-spatial scales, but also within the context of single neurons. In vivo, wide-field GCaMP imaging and sub-cortical/cortical cellular electrophysiology were used in mice to investigate relationships between spontaneous single neuron spiking and mesoscopic cortical activity. We make use of a rich set of cortical activity motifs that are present in spontaneous activity in anesthetized and awake animals. A mesoscale spike-triggered averaging procedure allowed the identification of motifs that are preferentially linked to individual spiking neurons by employing genetically targeted indicators of neuronal activity. Thalamic neurons predicted and reported specific cycles of wide-scale cortical inhibition/excitation. In contrast, spike-triggered maps derived from single cortical neurons yielded spatio-temporal maps expected for regional cortical consensus function. This approach can define network relationships between any point source of neuronal spiking and mesoscale cortical maps. DOI: http://dx.doi.org/10.7554/eLife.19976.001 PMID:28160463
Synaptic dynamics contribute to long-term single neuron response fluctuations.
Reinartz, Sebastian; Biro, Istvan; Gal, Asaf; Giugliano, Michele; Marom, Shimon
2014-01-01
Firing rate variability at the single neuron level is characterized by long-memory processes and complex statistics over a wide range of time scales (from milliseconds up to several hours). Here, we focus on the contribution of non-stationary efficacy of the ensemble of synapses-activated in response to a given stimulus-on single neuron response variability. We present and validate a method tailored for controlled and specific long-term activation of a single cortical neuron in vitro via synaptic or antidromic stimulation, enabling a clear separation between two determinants of neuronal response variability: membrane excitability dynamics vs. synaptic dynamics. Applying this method we show that, within the range of physiological activation frequencies, the synaptic ensemble of a given neuron is a key contributor to the neuronal response variability, long-memory processes and complex statistics observed over extended time scales. Synaptic transmission dynamics impact on response variability in stimulation rates that are substantially lower compared to stimulation rates that drive excitability resources to fluctuate. Implications to network embedded neurons are discussed.
High-Dimensional Brain: A Tool for Encoding and Rapid Learning of Memories by Single Neurons.
Tyukin, Ivan; Gorban, Alexander N; Calvo, Carlos; Makarova, Julia; Makarov, Valeri A
2018-03-19
Codifying memories is one of the fundamental problems of modern Neuroscience. The functional mechanisms behind this phenomenon remain largely unknown. Experimental evidence suggests that some of the memory functions are performed by stratified brain structures such as the hippocampus. In this particular case, single neurons in the CA1 region receive a highly multidimensional input from the CA3 area, which is a hub for information processing. We thus assess the implication of the abundance of neuronal signalling routes converging onto single cells on the information processing. We show that single neurons can selectively detect and learn arbitrary information items, given that they operate in high dimensions. The argument is based on stochastic separation theorems and the concentration of measure phenomena. We demonstrate that a simple enough functional neuronal model is capable of explaining: (i) the extreme selectivity of single neurons to the information content, (ii) simultaneous separation of several uncorrelated stimuli or informational items from a large set, and (iii) dynamic learning of new items by associating them with already "known" ones. These results constitute a basis for organization of complex memories in ensembles of single neurons. Moreover, they show that no a priori assumptions on the structural organization of neuronal ensembles are necessary for explaining basic concepts of static and dynamic memories.
Auditory-nerve single-neuron thresholds to electrical stimulation from scala tympani electrodes.
Parkins, C W; Colombo, J
1987-12-31
Single auditory-nerve neuron thresholds were studied in sensory-deafened squirrel monkeys to determine the effects of electrical stimulus shape and frequency on single-neuron thresholds. Frequency was separated into its components, pulse width and pulse rate, which were analyzed separately. Square and sinusoidal pulse shapes were compared. There were no or questionably significant threshold differences in charge per phase between sinusoidal and square pulses of the same pulse width. There was a small (less than 0.5 dB) but significant threshold advantage for 200 microseconds/phase pulses delivered at low pulse rates (156 pps) compared to higher pulse rates (625 pps and 2500 pps). Pulse width was demonstrated to be the prime determinant of single-neuron threshold, resulting in strength-duration curves similar to other mammalian myelinated neurons, but with longer chronaxies. The most efficient electrical stimulus pulse width to use for cochlear implant stimulation was determined to be 100 microseconds/phase. This pulse width delivers the lowest charge/phase at threshold. The single-neuron strength-duration curves were compared to strength-duration curves of a computer model based on the specific anatomy of auditory-nerve neurons. The membrane capacitance and resulting chronaxie of the model can be varied by altering the length of the unmyelinated termination of the neuron, representing the unmyelinated portion of the neuron between the habenula perforata and the hair cell. This unmyelinated segment of the auditory-nerve neuron may be subject to aminoglycoside damage. Simulating a 10 micron unmyelinated termination for this model neuron produces a strength-duration curve that closely fits the single-neuron data obtained from aminoglycoside deafened animals. Both the model and the single-neuron strength-duration curves differ significantly from behavioral threshold data obtained from monkeys and humans with cochlear implants. This discrepancy can best be explained by the involvement of higher level neurologic processes in the behavioral responses. These findings suggest that the basic principles of neural membrane function must be considered in developing or analyzing electrical stimulation strategies for cochlear prostheses if the appropriate stimulation of frequency specific populations of auditory-nerve neurons is the objective.
Ojemann, George A; Ojemann, Jeffrey; Ramsey, Nick F
2013-01-01
The relation between changes in the blood oxygen dependent metabolic changes imaged by functional magnetic resonance imaging (fMRI) and neural events directly recorded from human cortex from single neurons, local field potentials (LFPs) and electrocorticogram (ECoG) is critically reviewed, based on the published literature including findings from the authors' laboratories. All these data are from special populations, usually patients with medically refractory epilepsy, as this provides the major opportunity for direct cortical neuronal recording in humans. For LFP and ECoG changes are often sought in different frequency bands, for single neurons in frequency of action potentials. Most fMRI studies address issues of functional localization. The relation of those findings to localized changes in neuronal recordings in humans has been established in several ways. Only a few studies have directly compared changes in activity from the same sites in the same individual, using the same behavioral measure. More often the comparison has been between fMRI and electrophysiologic changes in populations recorded from the same functional anatomic system as defined by lesion effects; in a few studies those systems have been defined by fMRI changes such as the "default" network. The fMRI-electrophysiologic relationships have been evaluated empirically by colocalization of significant changes, and by quantitative analyses, often multiple linear regression. There is some evidence that the fMRI-electrophysiology relationships differ in different cortical areas, particularly primary motor and sensory cortices compared to association cortex, but also within areas of association cortex. Although crucial for interpretation of fMRI changes as reflecting neural activity in human cortex, controversy remains as to these relationships. Supported by: Dutch Technology Foundation and University of Utrecht Grant UGT7685, ERC-Advanced grant 320708 (NR) and NIH grant NS065186 (JO).
Headley, Drew B; DeLucca, Michael V; Haufler, Darrell; Paré, Denis
2015-04-01
Recent advances in recording and computing hardware have enabled laboratories to record the electrical activity of multiple brain regions simultaneously. Lagging behind these technical advances, however, are the methods needed to rapidly produce microdrives and head-caps that can flexibly accommodate different recording configurations. Indeed, most available designs target single or adjacent brain regions, and, if multiple sites are targeted, specially constructed head-caps are used. Here, we present a novel design style, for both microdrives and head-caps, which takes advantage of three-dimensional printing technology. This design facilitates targeting of multiple brain regions in various configurations. Moreover, the parts are easily fabricated in large quantities, with only minor hand-tooling and finishing required. Copyright © 2015 the American Physiological Society.
DeLucca, Michael V.; Haufler, Darrell; Paré, Denis
2015-01-01
Recent advances in recording and computing hardware have enabled laboratories to record the electrical activity of multiple brain regions simultaneously. Lagging behind these technical advances, however, are the methods needed to rapidly produce microdrives and head-caps that can flexibly accommodate different recording configurations. Indeed, most available designs target single or adjacent brain regions, and, if multiple sites are targeted, specially constructed head-caps are used. Here, we present a novel design style, for both microdrives and head-caps, which takes advantage of three-dimensional printing technology. This design facilitates targeting of multiple brain regions in various configurations. Moreover, the parts are easily fabricated in large quantities, with only minor hand-tooling and finishing required. PMID:25652930
Richendrfer, Holly A; Swann, Jennifer M
2010-09-10
The magnocellular division of the medial Preoptic nucleus (MPN mag) plays a critical role in the regulation of male sexual behavior in the hamster. Results from previous studies indicated that the number of neurons in the MPN mag is greater in males than females but failed to find significant differences in the volume of the nucleus suggesting that other elements in the nucleus may be greater in the female. The results of the present study, using NeuN to identify neurons, are in line with this hypothesis. The data show that (1) neurons in the MPN mag display two distinct phenotypes, those with a single nucleolus and those with multiple nucleoli; (2) the percentage of each phenotype is sex specific, differing over the course of development and (3) there is no sex difference in the number of glial cells at any age. Sex differences in the numbers of each type are correlated with developmental milestones and suggest that morphological changes are influenced by changes in circulating gonadal steroids during development. 2010 Elsevier B.V. All rights reserved.
Nir, Yuval; Mukamel, Roy; Dinstein, Ilan; Privman, Eran; Harel, Michal; Fisch, Lior; Gelbard-Sagiv, Hagar; Kipervasser, Svetlana; Andelman, Fani; Neufeld, Miri Y; Kramer, Uri; Arieli, Amos; Fried, Itzhak; Malach, Rafael
2009-01-01
Animal studies have shown robust electrophysiological activity in the sensory cortex in the absence of stimuli or tasks. Similarly, recent human functional magnetic resonance imaging (fMRI) revealed widespread, spontaneously emerging cortical fluctuations. However, it is unknown what neuronal dynamics underlie this spontaneous activity in the human brain. Here we studied this issue by combining bilateral single-unit, local field potentials (LFPs) and intracranial electrocorticography (ECoG) recordings in individuals undergoing clinical monitoring. We found slow (<0.1 Hz, following 1/f-like profiles) spontaneous fluctuations of neuronal activity with significant interhemispheric correlations. These fluctuations were evident mainly in neuronal firing rates and in gamma (40–100 Hz) LFP power modulations. Notably, the interhemispheric correlations were enhanced during rapid eye movement and stage 2 sleep. Multiple intracranial ECoG recordings revealed clear selectivity for functional networks in the spontaneous gamma LFP power modulations. Our results point to slow spontaneous modulations in firing rate and gamma LFP as the likely correlates of spontaneous fMRI fluctuations in the human sensory cortex. PMID:19160509
Deep learning and shapes similarity for joint segmentation and tracing single neurons in SEM images
NASA Astrophysics Data System (ADS)
Rao, Qiang; Xiao, Chi; Han, Hua; Chen, Xi; Shen, Lijun; Xie, Qiwei
2017-02-01
Extracting the structure of single neurons is critical for understanding how they function within the neural circuits. Recent developments in microscopy techniques, and the widely recognized need for openness and standardization provide a community resource for automated reconstruction of dendritic and axonal morphology of single neurons. In order to look into the fine structure of neurons, we use the Automated Tape-collecting Ultra Microtome Scanning Electron Microscopy (ATUM-SEM) to get images sequence of serial sections of animal brain tissue that densely packed with neurons. Different from other neuron reconstruction method, we propose a method that enhances the SEM images by detecting the neuronal membranes with deep convolutional neural network (DCNN) and segments single neurons by active contour with group shape similarity. We joint the segmentation and tracing together and they interact with each other by alternate iteration that tracing aids the selection of candidate region patch for active contour segmentation while the segmentation provides the neuron geometrical features which improve the robustness of tracing. The tracing model mainly relies on the neuron geometrical features and is updated after neuron being segmented on the every next section. Our method enables the reconstruction of neurons of the drosophila mushroom body which is cut to serial sections and imaged under SEM. Our method provides an elementary step for the whole reconstruction of neuronal networks.
Lee, Alice J.; Wang, Guangfu; Jiang, Xiaolong; Johnson, Seraphina M.; Hoang, Elizabeth T.; Lanté, Fabien; Stornetta, Ruth L.; Beenhakker, Mark P.; Shen, Ying; Julius Zhu, J.
2015-01-01
Interneurons play a key role in cortical function and dysfunction, yet organization of cortical interneuronal circuitry remains poorly understood. Cortical Layer 1 (L1) contains 2 general GABAergic interneuron groups, namely single bouquet cells (SBCs) and elongated neurogliaform cells (ENGCs). SBCs predominantly make unidirectional inhibitory connections (SBC→) with L2/3 interneurons, whereas ENGCs frequently form reciprocal inhibitory and electric connections (ENGC↔) with L2/3 interneurons. Here, we describe a systematic investigation of the pyramidal neuron targets of L1 neuron-led interneuronal circuits in the rat barrel cortex with simultaneous octuple whole-cell recordings and report a simple organizational scheme of the interneuronal circuits. Both SBCs→ and ENGC ↔ L2/3 interneuronal circuits connect to L2/3 and L5, but not L6, pyramidal neurons. SBC → L2/3 interneuronal circuits primarily inhibit the entire dendritic–somato–axonal axis of a few L2/3 and L5 pyramidal neurons located within the same column. In contrast, ENGC ↔ L2/3 interneuronal circuits generally inhibit the distal apical dendrite of many L2/3 and L5 pyramidal neurons across multiple columns. Finally, L1 interneuron-led circuits target distinct subcellular compartments of L2/3 and L5 pyramidal neurons in a L2/3 interneuron type-dependent manner. These results suggest that L1 neurons form canonical interneuronal circuits to control information processes in both supra- and infragranular cortical layers. PMID:24554728
Cnidarian Cell Type Diversity and Regulation Revealed by Whole-Organism Single-Cell RNA-Seq.
Sebé-Pedrós, Arnau; Saudemont, Baptiste; Chomsky, Elad; Plessier, Flora; Mailhé, Marie-Pierre; Renno, Justine; Loe-Mie, Yann; Lifshitz, Aviezer; Mukamel, Zohar; Schmutz, Sandrine; Novault, Sophie; Steinmetz, Patrick R H; Spitz, François; Tanay, Amos; Marlow, Heather
2018-05-31
The emergence and diversification of cell types is a leading factor in animal evolution. So far, systematic characterization of the gene regulatory programs associated with cell type specificity was limited to few cell types and few species. Here, we perform whole-organism single-cell transcriptomics to map adult and larval cell types in the cnidarian Nematostella vectensis, a non-bilaterian animal with complex tissue-level body-plan organization. We uncover eight broad cell classes in Nematostella, including neurons, cnidocytes, and digestive cells. Each class comprises different subtypes defined by the expression of multiple specific markers. In particular, we characterize a surprisingly diverse repertoire of neurons, which comparative analysis suggests are the result of lineage-specific diversification. By integrating transcription factor expression, chromatin profiling, and sequence motif analysis, we identify the regulatory codes that underlie Nematostella cell-specific expression. Our study reveals cnidarian cell type complexity and provides insights into the evolution of animal cell-specific genomic regulation. Copyright © 2018 Elsevier Inc. All rights reserved.
Multiple Approaches to the Investigation of Cell Assembly in Memory Research-Present and Future.
Sakurai, Yoshio; Osako, Yuma; Tanisumi, Yuta; Ishihara, Eriko; Hirokawa, Junya; Manabe, Hiroyuki
2018-01-01
In this review article we focus on research methodologies for detecting the actual activity of cell assemblies, which are populations of functionally connected neurons that encode information in the brain. We introduce and discuss traditional and novel experimental methods and those currently in development and briefly discuss their advantages and disadvantages for the detection of cell-assembly activity. First, we introduce the electrophysiological method, i.e., multineuronal recording, and review former and recent examples of studies showing models of dynamic coding by cell assemblies in behaving rodents and monkeys. We also discuss how the firing correlation of two neurons reflects the firing synchrony among the numerous surrounding neurons that constitute cell assemblies. Second, we review the recent outstanding studies that used the novel method of optogenetics to show causal relationships between cell-assembly activity and behavioral change. Third, we review the most recently developed method of live-cell imaging, which facilitates the simultaneous observation of firings of a large number of neurons in behaving rodents. Currently, all these available methods have both advantages and disadvantages, and no single measurement method can directly and precisely detect the actual activity of cell assemblies. The best strategy is to combine the available methods and utilize each of their advantages with the technique of operant conditioning of multiple-task behaviors in animals and, if necessary, with brain-machine interface technology to verify the accuracy of neural information detected as cell-assembly activity.
Wootla, Bharath; Denic, Aleksandar; Watzlawik, Jens O; Warrington, Arthur E; Rodriguez, Moses
2015-04-29
Intracerebral infection of susceptible mouse strains with Theiler's murine encephalomyelitis virus (TMEV) results in chronic demyelinating disease with progressive axonal loss and neurologic dysfunction similar to progressive forms of multiple sclerosis (MS). We previously showed that as the disease progresses, a marked decrease in brainstem N-acetyl aspartate (NAA; metabolite associated with neuronal integrity) concentrations, reflecting axon health, is measured. We also demonstrated stimulation of neurite outgrowth by a neuron-binding natural human antibody, IgM12. Treatment with either the serum-derived or recombinant human immunoglobulin M 12 (HIgM12) preserved functional motor activity in the TMEV model. In this study, we examined IgM-mediated changes in brainstem NAA concentrations and central nervous system (CNS) pathology. (1)H-magnetic resonance spectroscopy (MRS) showed that treatment with HIgM12 significantly increased brainstem NAA concentrations compared to controls in TMEV-infected mice. Pathologic analysis demonstrated a significant preservation of axons in the spinal cord of animals treated with HIgM12. This study links drug efficacy of slowing deficits with axon preservation and NAA concentrations in the brainstem in a model of progressive MS. HIgM12-mediated changes of NAA concentrations in the brainstem are a surrogate marker of axon injury/preservation throughout the spinal cord. This study provides proof-of-concept that a neuron-reactive human IgM can be therapeutic and provides a biomarker for clinical trials.
Bitter Taste Stimuli Induce Differential Neural Codes in Mouse Brain
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
Moore, Adrian W; Roegiers, Fabrice; Jan, Lily Y; Jan, Yuh-Nung
2004-03-15
The Drosophila external sensory organ forms in a lineage elaborating from a single precursor cell via a stereotypical series of asymmetric divisions. HAMLET transcription factor expression demarcates the lineage branch that generates two internal cell types, the external sensory neuron and thecogen. In HAMLET mutant organs, these internal cells are converted to external cells via an unprecedented cousin-cousin cell-fate respecification event. Conversely, ectopic HAMLET expression in the external cell branch leads to internal cell production. The fate-determining signals NOTCH and PAX2 act at multiple stages of lineage elaboration and HAMLET acts to modulate their activity in a branch-specific manner.
Li, Chang-Lin; Li, Kai-Cheng; Wu, Dan; Chen, Yan; Luo, Hao; Zhao, Jing-Rong; Wang, Sa-Shuang; Sun, Ming-Ming; Lu, Ying-Jin; Zhong, Yan-Qing; Hu, Xu-Ye; Hou, Rui; Zhou, Bei-Bei; Bao, Lan; Xiao, Hua-Sheng; Zhang, Xu
2016-01-01
Sensory neurons are distinguished by distinct signaling networks and receptive characteristics. Thus, sensory neuron types can be defined by linking transcriptome-based neuron typing with the sensory phenotypes. Here we classify somatosensory neurons of the mouse dorsal root ganglion (DRG) by high-coverage single-cell RNA-sequencing (10 950 ± 1 218 genes per neuron) and neuron size-based hierarchical clustering. Moreover, single DRG neurons responding to cutaneous stimuli are recorded using an in vivo whole-cell patch clamp technique and classified by neuron-type genetic markers. Small diameter DRG neurons are classified into one type of low-threshold mechanoreceptor and five types of mechanoheat nociceptors (MHNs). Each of the MHN types is further categorized into two subtypes. Large DRG neurons are categorized into four types, including neurexophilin 1-expressing MHNs and mechanical nociceptors (MNs) expressing BAI1-associated protein 2-like 1 (Baiap2l1). Mechanoreceptors expressing trafficking protein particle complex 3-like and Baiap2l1-marked MNs are subdivided into two subtypes each. These results provide a new system for cataloging somatosensory neurons and their transcriptome databases. PMID:26691752
Duque, Daniel; Wang, Xin; Nieto-Diego, Javier; Krumbholz, Katrin; Malmierca, Manuel S.
2016-01-01
Electrophysiological and psychophysical responses to a low-intensity probe sound tend to be suppressed by a preceding high-intensity adaptor sound. Nevertheless, rare low-intensity deviant sounds presented among frequent high-intensity standard sounds in an intensity oddball paradigm can elicit an electroencephalographic mismatch negativity (MMN) response. This has been taken to suggest that the MMN is a correlate of true change or “deviance” detection. A key question is where in the ascending auditory pathway true deviance sensitivity first emerges. Here, we addressed this question by measuring low-intensity deviant responses from single units in the inferior colliculus (IC) of anesthetized rats. If the IC exhibits true deviance sensitivity to intensity, IC neurons should show enhanced responses to low-intensity deviant sounds presented among high-intensity standards. Contrary to this prediction, deviant responses were only enhanced when the standards and deviants differed in frequency. The results could be explained with a model assuming that IC neurons integrate over multiple frequency-tuned channels and that adaptation occurs within each channel independently. We used an adaptation paradigm with multiple repeated adaptors to measure the tuning widths of these adaption channels in relation to the neurons’ overall tuning widths. PMID:27066835
Spatial attention improves the quality of population codes in human visual cortex.
Saproo, Sameer; Serences, John T
2010-08-01
Selective attention enables sensory input from behaviorally relevant stimuli to be processed in greater detail, so that these stimuli can more accurately influence thoughts, actions, and future goals. Attention has been shown to modulate the spiking activity of single feature-selective neurons that encode basic stimulus properties (color, orientation, etc.). However, the combined output from many such neurons is required to form stable representations of relevant objects and little empirical work has formally investigated the relationship between attentional modulations on population responses and improvements in encoding precision. Here, we used functional MRI and voxel-based feature tuning functions to show that spatial attention induces a multiplicative scaling in orientation-selective population response profiles in early visual cortex. In turn, this multiplicative scaling correlates with an improvement in encoding precision, as evidenced by a concurrent increase in the mutual information between population responses and the orientation of attended stimuli. These data therefore demonstrate how multiplicative scaling of neural responses provides at least one mechanism by which spatial attention may improve the encoding precision of population codes. Increased encoding precision in early visual areas may then enhance the speed and accuracy of perceptual decisions computed by higher-order neural mechanisms.
Pérez, C; Limón, A; Vega, R; Soto, E
2009-02-18
There is consensus that muscarinic and nicotinic receptors expressed in vestibular hair cells and afferent neurons are involved in the efferent modulation of the electrical activity of the afferent neurons. However the underlying mechanisms of postsynaptic control in neurons are not well understood. In our work we show that the activation of muscarinic receptors in the vestibular neurons modulates the potassium M-current modifying the activity of afferent neurons. Whole-cell patch-clamp recordings were made on vestibular-afferent neurons isolated from Wistar rats (postnatal days 7-10) and held in primary culture (18-24 h). The M-current was studied during its deactivation after depolarizing voltage-clamp pulses. In 68% of the cells studied, those of larger capacitance, the M-current antagonists linopirdine and XE-991 reduced the amplitude of the M-current by 54%+/-7% and 50%+/-3%. The muscarinic-receptor agonist oxotremorine-M also significantly reduced the M-current by 58%+/-12% in the cells. The action of oxotremorine-M was blocked by atropine, thus indicating its cholinergic nature. The erg-channel blocker E-4031 did not significantly modify the M-current amplitude. In current-clamp experiments, linopirdine, XE-991, and oxotremorine-M modified the discharge response to current pulses from single spike to multiple spiking, reducing the adaptation of the electrical discharge. Our results indicate that large soma-size cultured vestibular-afferent neurons (most probably calyx-bearing neurons) express the M-current and that the modulation of this current by activation of muscarinic-receptor reduces its spike-frequency adaptation.
Single CA3 pyramidal cells trigger sharp waves in vitro by exciting interneurones.
Bazelot, Michaël; Teleńczuk, Maria T; Miles, Richard
2016-05-15
The CA3 hippocampal region generates sharp waves (SPW), a population activity associated with neuronal representations. The synaptic mechanisms responsible for the generation of these events still require clarification. Using slices maintained in an interface chamber, we found that the firing of single CA3 pyramidal cells triggers SPW like events at short latencies, similar to those for the induction of firing in interneurons. Multi-electrode records from the CA3 stratum pyramidale showed that pyramidal cells triggered events consisting of putative interneuron spikes followed by field IPSPs. SPW fields consisted of a repetition of these events at intervals of 4-8 ms. Although many properties of induced and spontaneous SPWs were similar, the triggered events tended to be initiated close to the stimulated cell. These data show that the initiation of SPWs in vitro is mediated via pyramidal cell synapses that excite interneurons. They do not indicate why interneuron firing is repeated during a SPW. Sharp waves (SPWs) are a hippocampal population activity that has been linked to neuronal representations. We show that SPWs in the CA3 region of rat hippocampal slices can be triggered by the firing of single pyramidal cells. Single action potentials in almost one-third of pyramidal cells initiated SPWs at latencies of 2-5 ms with probabilities of 0.07-0.76. Initiating pyramidal cells evoked field IPSPs (fIPSPs) at similar latencies when SPWs were not initiated. Similar spatial profiles for fIPSPs and middle components of SPWs suggested that SPW fields reflect repeated fIPSPs. Multiple extracellular records showed that the initiated SPWs tended to start near the stimulated pyramidal cell, whereas spontaneous SPWs could emerge at multiple sites. Single pyramidal cells could initiate two to six field IPSPs with distinct amplitude distributions, typically preceeded by a short-duration extracellular action potential. Comparison of these initiated fields with spontaneously occurring inhibitory field motifs allowed us to identify firing in different interneurones during the spread of SPWs. Propagation away from an initiating pyramidal cell was typically associated with the recruitment of interneurones and field IPSPs that were not activated by the stimulated pyramidal cell. SPW fields initiated by single cells were less variable than spontaneous events, suggesting that more stereotyped neuronal ensembles were activated, although neither the spatial profiles of fields, nor the identities of interneurone firing were identical for initiated events. The effects of single pyramidal cell on network events are thus mediated by different sequences of interneurone firing. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.
Mechanisms and use of neural transplants for brain repair.
Dunnett, Stephen B; Björklund, Anders
2017-01-01
Under appropriate conditions, neural tissues transplanted into the adult mammalian brain can survive, integrate, and function so as to influence the behavior of the host, opening the prospect of repairing neuronal damage, and alleviating symptoms associated with neuronal injury or neurodegenerative disease. Alternative mechanisms of action have been postulated: nonspecific effects of surgery; neurotrophic and neuroprotective influences on disease progression and host plasticity; diffuse or locally regulated pharmacological delivery of deficient neurochemicals, neurotransmitters, or neurohormones; restitution of the neuronal and glial environment necessary for proper host neuronal support and processing; promoting local and long-distance host and graft axon growth; formation of reciprocal connections and reconstruction of local circuits within the host brain; and up to full integration and reconstruction of fully functional host neuronal networks. Analysis of neural transplants in a broad range of anatomical systems and disease models, on simple and complex classes of behavioral function and information processing, have indicated that all of these alternative mechanisms are likely to contribute in different circumstances. Thus, there is not a single or typical mode of graft function; rather grafts can and do function in multiple ways, specific to each particular context. Consequently, to develop an effective cell-based therapy, multiple dimensions must be considered: the target disease pathogenesis; the neurodegenerative basis of each type of physiological dysfunction or behavioral symptom; the nature of the repair required to alleviate or remediate the functional impairments of particular clinical relevance; and identification of a suitable cell source or delivery system, along with the site and method of implantation, that can achieve the sought for repair and recovery. © 2017 Elsevier B.V. All rights reserved.
Information-geometric measures estimate neural interactions during oscillatory brain states
Nie, Yimin; Fellous, Jean-Marc; Tatsuno, Masami
2014-01-01
The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain. PMID:24605089
Information-geometric measures estimate neural interactions during oscillatory brain states.
Nie, Yimin; Fellous, Jean-Marc; Tatsuno, Masami
2014-01-01
The characterization of functional network structures among multiple neurons is essential to understanding neural information processing. Information geometry (IG), a theory developed for investigating a space of probability distributions has recently been applied to spike-train analysis and has provided robust estimations of neural interactions. Although neural firing in the equilibrium state is often assumed in these studies, in reality, neural activity is non-stationary. The brain exhibits various oscillations depending on cognitive demands or when an animal is asleep. Therefore, the investigation of the IG measures during oscillatory network states is important for testing how the IG method can be applied to real neural data. Using model networks of binary neurons or more realistic spiking neurons, we studied how the single- and pairwise-IG measures were influenced by oscillatory neural activity. Two general oscillatory mechanisms, externally driven oscillations and internally induced oscillations, were considered. In both mechanisms, we found that the single-IG measure was linearly related to the magnitude of the external input, and that the pairwise-IG measure was linearly related to the sum of connection strengths between two neurons. We also observed that the pairwise-IG measure was not dependent on the oscillation frequency. These results are consistent with the previous findings that were obtained under the equilibrium conditions. Therefore, we demonstrate that the IG method provides useful insights into neural interactions under the oscillatory condition that can often be observed in the real brain.
Two-dimensional adaptation in the auditory forebrain
Nagel, Katherine I.; Doupe, Allison J.
2011-01-01
Sensory neurons exhibit two universal properties: sensitivity to multiple stimulus dimensions, and adaptation to stimulus statistics. How adaptation affects encoding along primary dimensions is well characterized for most sensory pathways, but if and how it affects secondary dimensions is less clear. We studied these effects for neurons in the avian equivalent of primary auditory cortex, responding to temporally modulated sounds. We showed that the firing rate of single neurons in field L was affected by at least two components of the time-varying sound log-amplitude. When overall sound amplitude was low, neural responses were based on nonlinear combinations of the mean log-amplitude and its rate of change (first time differential). At high mean sound amplitude, the two relevant stimulus features became the first and second time derivatives of the sound log-amplitude. Thus a strikingly systematic relationship between dimensions was conserved across changes in stimulus intensity, whereby one of the relevant dimensions approximated the time differential of the other dimension. In contrast to stimulus mean, increases in stimulus variance did not change relevant dimensions, but selectively increased the contribution of the second dimension to neural firing, illustrating a new adaptive behavior enabled by multidimensional encoding. Finally, we demonstrated theoretically that inclusion of time differentials as additional stimulus features, as seen so prominently in the single-neuron responses studied here, is a useful strategy for encoding naturalistic stimuli, because it can lower the necessary sampling rate while maintaining the robustness of stimulus reconstruction to correlated noise. PMID:21753019
Xiao, Jianbo
2015-01-01
Segmenting visual scenes into distinct objects and surfaces is a fundamental visual function. To better understand the underlying neural mechanism, we investigated how neurons in the middle temporal cortex (MT) of macaque monkeys represent overlapping random-dot stimuli moving transparently in slightly different directions. It has been shown that the neuronal response elicited by two stimuli approximately follows the average of the responses elicited by the constituent stimulus components presented alone. In this scheme of response pooling, the ability to segment two simultaneously presented motion directions is limited by the width of the tuning curve to motion in a single direction. We found that, although the population-averaged neuronal tuning showed response averaging, subgroups of neurons showed distinct patterns of response tuning and were capable of representing component directions that were separated by a small angle—less than the tuning width to unidirectional stimuli. One group of neurons preferentially represented the component direction at a specific side of the bidirectional stimuli, weighting one stimulus component more strongly than the other. Another group of neurons pooled the component responses nonlinearly and showed two separate peaks in their tuning curves even when the average of the component responses was unimodal. We also show for the first time that the direction tuning of MT neurons evolved from initially representing the vector-averaged direction of slightly different stimuli to gradually representing the component directions. Our results reveal important neural processes underlying image segmentation and suggest that information about slightly different stimulus components is computed dynamically and distributed across neurons. SIGNIFICANCE STATEMENT Natural scenes often contain multiple entities. The ability to segment visual scenes into distinct objects and surfaces is fundamental to sensory processing and is crucial for generating the perception of our environment. Because cortical neurons are broadly tuned to a given visual feature, segmenting two stimuli that differ only slightly is a challenge for the visual system. In this study, we discovered that many neurons in the visual cortex are capable of representing individual components of slightly different stimuli by selectively and nonlinearly pooling the responses elicited by the stimulus components. We also show for the first time that the neural representation of individual stimulus components developed over a period of ∼70–100 ms, revealing a dynamic process of image segmentation. PMID:26658869
A single-neuron tracing study of arkypallidal and prototypic neurons in healthy rats.
Fujiyama, Fumino; Nakano, Takashi; Matsuda, Wakoto; Furuta, Takahiro; Udagawa, Jun; Kaneko, Takeshi
2016-12-01
The external globus pallidus (GP) is known as a relay nucleus of the indirect pathway of the basal ganglia. Recent studies in dopamine-depleted and healthy rats indicate that the GP comprises two main types of pallidofugal neurons: the so-called "prototypic" and "arkypallidal" neurons. However, the reconstruction of complete arkypallidal neurons in healthy rats has not been reported. Here we visualized the entire axonal arborization of four single arkypallidal neurons and six single prototypic neurons in rat brain using labeling with a viral vector expressing membrane-targeted green fluorescent protein and examined the distribution of axon boutons in the target nuclei. Results revealed that not only the arkypallidal neurons but nearly all of the prototypic neurons projected to the striatum with numerous axon varicosities. Thus, the striatum is a major target nucleus for pallidal neurons. Arkypallidal and prototypic GP neurons located in the calbindin-positive and calbindin-negative regions mainly projected to the corresponding positive and negative regions in the striatum. Because the GP and striatum calbindin staining patterns reflect the topographic organization of the striatopallidal projection, the striatal neurons in the sensorimotor and associative regions constitute the reciprocal connection with the GP neurons in the corresponding regions.
Self-organized criticality in single-neuron excitability
NASA Astrophysics Data System (ADS)
Gal, Asaf; Marom, Shimon
2013-12-01
We present experimental and theoretical arguments, at the single-neuron level, suggesting that neuronal response fluctuations reflect a process that positions the neuron near a transition point that separates excitable and unexcitable phases. This view is supported by the dynamical properties of the system as observed in experiments on isolated cultured cortical neurons, as well as by a theoretical mapping between the constructs of self-organized criticality and membrane excitability biophysics.
A computational relationship between thalamic sensory neural responses and contrast perception.
Jiang, Yaoguang; Purushothaman, Gopathy; Casagrande, Vivien A
2015-01-01
Uncovering the relationship between sensory neural responses and perceptual decisions remains a fundamental problem in neuroscience. Decades of experimental and modeling work in the sensory cortex have demonstrated that a perceptual decision pool is usually composed of tens to hundreds of neurons, the responses of which are significantly correlated not only with each other, but also with the behavioral choices of an animal. Few studies, however, have measured neural activity in the sensory thalamus of awake, behaving animals. Therefore, it remains unclear how many thalamic neurons are recruited and how the information from these neurons is pooled at subsequent cortical stages to form a perceptual decision. In a previous study we measured neural activity in the macaque lateral geniculate nucleus (LGN) during a two alternative forced choice (2AFC) contrast detection task, and found that single LGN neurons were significantly correlated with the monkeys' behavioral choices, despite their relatively poor contrast sensitivity and a lack of overall interneuronal correlations. We have now computationally tested a number of specific hypotheses relating these measured LGN neural responses to the contrast detection behavior of the animals. We modeled the perceptual decisions with different numbers of neurons and using a variety of pooling/readout strategies, and found that the most successful model consisted of about 50-200 LGN neurons, with individual neurons weighted differentially according to their signal-to-noise ratios (quantified as d-primes). These results supported the hypothesis that in contrast detection the perceptual decision pool consists of multiple thalamic neurons, and that the response fluctuations in these neurons can influence contrast perception, with the more sensitive thalamic neurons likely to exert a greater influence.
Fujita, Satoshi; Toyoda, Izumi; Thamattoor, Ajoy K.
2014-01-01
Previous studies suggest that spontaneous seizures in patients with temporal lobe epilepsy might be preceded by increased action potential firing of hippocampal neurons. Preictal activity is potentially important because it might provide new opportunities for predicting when a seizure is about to occur and insight into how spontaneous seizures are generated. We evaluated local field potentials and unit activity of single, putative excitatory neurons in the subiculum, CA1, CA3, and dentate gyrus of the dorsal hippocampus in epileptic pilocarpine-treated rats as they experienced spontaneous seizures. Average action potential firing rates of neurons in the subiculum, CA1, and dentate gyrus, but not CA3, increased significantly and progressively beginning 2–4 min before locally recorded spontaneous seizures. In the subiculum, CA1, and dentate gyrus, but not CA3, 41–57% of neurons displayed increased preictal activity with significant consistency across multiple seizures. Much of the increased preictal firing of neurons in the subiculum and CA1 correlated with preictal theta activity, whereas preictal firing of neurons in the dentate gyrus was independent of theta. In addition, some CA1 and dentate gyrus neurons displayed reduced firing rates preictally. These results reveal that different hippocampal subregions exhibit differences in the extent and potential underlying mechanisms of preictal activity. The finding of robust and significantly consistent preictal activity of subicular, CA1, and dentate neurons in the dorsal hippocampus, despite the likelihood that many seizures initiated in other brain regions, suggests the existence of a broader neuronal network whose activity changes minutes before spontaneous seizures initiate. PMID:25505320
The Physiology of Bone Pain. How Much Do We Really Know?
Nencini, Sara; Ivanusic, Jason J.
2016-01-01
Pain is associated with most bony pathologies. Clinical and experimental observations suggest that bone pain can be derived from noxious stimulation of the periosteum or bone marrow. Sensory neurons are known to innervate the periosteum and marrow cavity, and most of these have a morphology and molecular phenotype consistent with a role in nociception. However, little is known about the physiology of these neurons, and therefore information about mechanisms that generate and maintain bone pain is lacking. The periosteum has received greater attention relative to the bone marrow, reflecting the easier access of the periosteum for experimental assessment. With the electrophysiological preparations used, investigators have been able to record from single periosteal units in isolation, and there is a lot of information available about how they respond to different stimuli, including those that are noxious. In contrast, preparations used to study sensory neurons that innervate the bone marrow have been limited to recording multi-unit activity in whole nerves, and whilst they clearly report responses to noxious stimulation, it is not possible to define responses for single sensory neurons that innervate the bone marrow. There is only limited evidence that peripheral sensory neurons that innervate bone can be sensitized or that they can be activated by multiple stimulus types, and at present this only exists in part for periosteal units. In the central nervous system, it is clear that spinal dorsal horn neurons can be activated by noxious stimuli applied to bone. Some can be sensitized under pathological conditions and may contribute in part to secondary or referred pain associated with bony pathology. Activity related to stimulation of sensory nerves that innervate bone has also been reported in neurons of the spinoparabrachial pathway and the somatosensory cortices, both known for roles in coding information about pain. Whilst these provide some clues as to the way information about bone pain is centrally coded, they need to be expanded to further our understanding of other central territories involved. There is a lot more to learn about the physiology of peripheral sensory neurons that innervate bone and their central projections. PMID:27199772
Ma, Hongtao; Harris, Samuel; Rahmani, Redi; Lacefield, Clay O.; Zhao, Mingrui; Daniel, Andy G. S.; Zhou, Zhiping; Bruno, Randy M.; Berwick, Jason; Schwartz, Theodore H.
2014-01-01
Abstract. In vivo calcium imaging is an incredibly powerful technique that provides simultaneous information on fast neuronal events, such as action potentials and subthreshold synaptic activity, as well as slower events that occur in the glia and surrounding neuropil. Bulk-loading methods that involve multiple injections can be used for single-cell as well as wide-field imaging studies. However, multiple injections result in inhomogeneous loading as well as multiple sites of potential cortical injury. We used convection-enhanced delivery to create smooth, continuous loading of a large area of the cortical surface through a solitary injection site and demonstrated the efficacy of the technique using confocal microscopy imaging of single cells and physiological responses to single-trial events of spontaneous activity, somatosensory-evoked potentials, and epileptiform events. Combinations of calcium imaging with voltage-sensitive dye and intrinsic signal imaging demonstrate the utility of this technique in neurovascular coupling investigations. Convection-enhanced loading of calcium dyes may be a useful technique to advance the study of cortical processing when widespread loading of a wide-field imaging is required. PMID:25525611
Ma, Hongtao; Harris, Samuel; Rahmani, Redi; Lacefield, Clay O; Zhao, Mingrui; Daniel, Andy G S; Zhou, Zhiping; Bruno, Randy M; Berwick, Jason; Schwartz, Theodore H
2014-07-24
In vivo calcium imaging is an incredibly powerful technique that provides simultaneous information on fast neuronal events, such as action potentials and subthreshold synaptic activity, as well as slower events that occur in the glia and surrounding neuropil. Bulk-loading methods that involve multiple injections can be used for single-cell as well as wide-field imaging studies. However, multiple injections result in inhomogeneous loading as well as multiple sites of potential cortical injury. We used convection-enhanced delivery to create smooth, continuous loading of a large area of the cortical surface through a solitary injection site and demonstrated the efficacy of the technique using confocal microscopy imaging of single cells and physiological responses to single-trial events of spontaneous activity, somatosensory-evoked potentials, and epileptiform events. Combinations of calcium imaging with voltage-sensitive dye and intrinsic signal imaging demonstrate the utility of this technique in neurovascular coupling investigations. Convection-enhanced loading of calcium dyes may be a useful technique to advance the study of cortical processing when widespread loading of a wide-field imaging is required.
Dhumale, Pratibha; Menon, Sindhu; Chiang, Joanna; Püschel, Andreas W
2018-01-01
The neurons that form the mammalian neocortex originate from progenitor cells in the ventricular (VZ) and subventricular zone (SVZ). Newborn neurons are multipolar but become bipolar during their migration from the germinal layers to the cortical plate (CP) by forming a leading process and an axon that extends in the intermediate zone (IZ). Once they settle in the CP, neurons assume a highly polarized morphology with a single axon and multiple dendrites. The AMPK-related kinases SadA and SadB are intrinsic factors that are essential for axon formation during neuronal development downstream of Lkb1. The knockout of both genes encoding Sad kinases (Sada and Sadb) results not only in a loss of axons but also a decrease in the size of the cortical plate. The defect in axon formation has been linked to a function of Sad kinases in the regulation of microtubule binding proteins. However, the causes for the reduced size of the cortical plate in the Sada-/-;Sadb-/- knockout remain to be analyzed in detail. Here we show that neuronal cell death is increased and the number of neural progenitors is decreased in the Sada-/-;Sadb-/- CP. The reduced number of progenitors is a non-cell autonomous defect since they do not express Sad kinases. These defects are restricted to the neocortex while the hippocampus remains unaffected.
Investigation of Neural Strategies of Visual Search
NASA Technical Reports Server (NTRS)
Krauzlis, Richard J.
2003-01-01
The goal of this project was to measure how neurons in the superior colliculus (SC) change their activity during a visual search task. Specifically, we proposed to measure how the activity of these neurons was altered by the discriminability of visual targets and to test how these changes might predict the changes in the subjects performance. The primary rationale for this study was that understanding how the information encoded by these neurons constrains overall search performance would foster the development of better models of human performance. Work performed during the period supported by this grant has achieved these aims. First, we have recorded from neurons in the superior colliculus (SC) during a visual search task in which the difficulty of the task and the performance of the subject was systematically varied. The results from these single-neuron physiology experiments shows that prior to eye movement onset, the difference in activity across the ensemble of neurons reaches a fixed threshold value, reflecting the operation of a winner-take-all mechanism. Second, we have developed a model of eye movement decisions based on the principle of winner-take-all . The model incorporates the idea that the overt saccade choice reflects only one of the multiple saccades prepared during visual discrimination, consistent with our physiological data. The value of the model is that, unlike previous models, it is able to account for both the latency and the percent correct of saccade choices.
Diode probes for spatiotemporal optical control of multiple neurons in freely moving animals
Koos, Tibor; Buzsáki, György
2012-01-01
Neuronal control with high temporal precision is possible with optogenetics, yet currently available methods do not enable to control independently multiple locations in the brains of freely moving animals. Here, we describe a diode-probe system that allows real-time and location-specific control of neuronal activity at multiple sites. Manipulation of neuronal activity in arbitrary spatiotemporal patterns is achieved by means of an optoelectronic array, manufactured by attaching multiple diode-fiber assemblies to high-density silicon probes or wire tetrodes and implanted into the brains of animals that are expressing light-responsive opsins. Each diode can be controlled separately, allowing localized light stimulation of neuronal activators and silencers in any temporal configuration and concurrent recording of the stimulated neurons. Because the only connections to the animals are via a highly flexible wire cable, unimpeded behavior is allowed for circuit monitoring and multisite perturbations in the intact brain. The capacity of the system to generate unique neural activity patterns facilitates multisite manipulation of neural circuits in a closed-loop manner and opens the door to addressing novel questions. PMID:22496529
Multiple target of hAmylin on rat primary hippocampal neurons.
Zhang, Nan; Yang, Shengchang; Wang, Chang; Zhang, Jianghua; Huo, Lifang; Cheng, Yiru; Wang, Chuan; Jia, Zhanfeng; Ren, Leiming; Kang, Lin; Zhang, Wei
2017-02-01
Alzheimer's disease (AD) and type II diabetes mellitus (DM2) are the most common aging-related diseases and are characterized by β-amyloid and amylin accumulation, respectively. Multiple studies have indicated a strong correlation between these two diseases. Amylin oligomerization in the brain appears to be a novel risk factor for developing AD. Although amylin aggregation has been demonstrated to induce cytotoxicity in neurons through altering Ca 2+ homeostasis, the underlying mechanisms have not been fully explored. In this study, we investigated the effects of amylin on rat hippocampal neurons using calcium imaging and whole-cell patch clamp recordings. We demonstrated that the amylin receptor antagonist AC187 abolished the Ca 2+ response induced by low concentrations of human amylin (hAmylin). However, the Ca 2+ response induced by higher concentrations of hAmylin was independent of the amylin receptor. This effect was dependent on extracellular Ca 2+ . Additionally, blockade of L-type Ca 2+ channels partially reduced hAmylin-induced Ca 2+ response. In whole-cell recordings, hAmylin depolarized the membrane potential. Moreover, application of the transient receptor potential (TRP) channel antagonist ruthenium red (RR) attenuated the hAmylin-induced increase in Ca 2+ . Single-cell RT-PCR demonstrated that transient receptor potential vanilloid 4 (TRPV4) mRNA was expressed in most of the hAmylin-responsive neurons. In addition, selective knockdown of TRPV4 channels inhibited the hAmylin-evoked Ca 2+ response. These results indicated that different concentrations of hAmylin act through different pathways. The amylin receptor mediates the excitatory effects of low concentrations of hAmylin. In contrast, for high concentrations of hAmylin, hAmylin aggregates precipitated on the neuronal membrane, activated TRPV4 channels and subsequently triggered membrane voltage-gated calcium channel opening followed by membrane depolarization. Therefore, our data suggest that TRPV4 is a key molecular mediator for the cytotoxic effects of hAmylin on hippocampal neurons. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Broccard, Frédéric D.; Joshi, Siddharth; Wang, Jun; Cauwenberghs, Gert
2017-08-01
Objective. Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model. Approach. This article highlights the current efforts to interface neuromorphic systems with neural systems at multiple levels of biological organization, from the synaptic to the system level, and discusses the prospects for future biohybrid systems with neuromorphic circuits of greater complexity. Main results. Single silicon neurons have been interfaced successfully with invertebrate and vertebrate neural networks. This approach allowed the investigation of neural properties that are inaccessible with traditional techniques while providing a realistic biological context not achievable with traditional numerical modeling methods. At the network level, populations of neurons are envisioned to communicate bidirectionally with neuromorphic processors of hundreds or thousands of silicon neurons. Recent work on brain-machine interfaces suggests that this is feasible with current neuromorphic technology. Significance. Biohybrid interfaces between biological neurons and VLSI neuromorphic systems of varying complexity have started to emerge in the literature. Primarily intended as a computational tool for investigating fundamental questions related to neural dynamics, the sophistication of current neuromorphic systems now allows direct interfaces with large neuronal networks and circuits, resulting in potentially interesting clinical applications for neuroengineering systems, neuroprosthetics and neurorehabilitation.
Ardid, Salva; Wang, Xiao-Jing
2013-12-11
A hallmark of executive control is the brain's agility to shift between different tasks depending on the behavioral rule currently in play. In this work, we propose a "tweaking hypothesis" for task switching: a weak rule signal provides a small bias that is dramatically amplified by reverberating attractor dynamics in neural circuits for stimulus categorization and action selection, leading to an all-or-none reconfiguration of sensory-motor mapping. Based on this principle, we developed a biologically realistic model with multiple modules for task switching. We found that the model quantitatively accounts for complex task switching behavior: switch cost, congruency effect, and task-response interaction; as well as monkey's single-neuron activity associated with task switching. The model yields several testable predictions, in particular, that category-selective neurons play a key role in resolving sensory-motor conflict. This work represents a neural circuit model for task switching and sheds insights in the brain mechanism of a fundamental cognitive capability.
NeuroGrid: recording action potentials from the surface of the brain.
Khodagholy, Dion; Gelinas, Jennifer N; Thesen, Thomas; Doyle, Werner; Devinsky, Orrin; Malliaras, George G; Buzsáki, György
2015-02-01
Recording from neural networks at the resolution of action potentials is critical for understanding how information is processed in the brain. Here, we address this challenge by developing an organic material-based, ultraconformable, biocompatible and scalable neural interface array (the 'NeuroGrid') that can record both local field potentials(LFPs) and action potentials from superficial cortical neurons without penetrating the brain surface. Spikes with features of interneurons and pyramidal cells were simultaneously acquired by multiple neighboring electrodes of the NeuroGrid, allowing for the isolation of putative single neurons in rats. Spiking activity demonstrated consistent phase modulation by ongoing brain oscillations and was stable in recordings exceeding 1 week's duration. We also recorded LFP-modulated spiking activity intraoperatively in patients undergoing epilepsy surgery. The NeuroGrid constitutes an effective method for large-scale, stable recording of neuronal spikes in concert with local population synaptic activity, enhancing comprehension of neural processes across spatiotemporal scales and potentially facilitating diagnosis and therapy for brain disorders.
A hierarchical graph neuron scheme for real-time pattern recognition.
Nasution, B B; Khan, A I
2008-02-01
The hierarchical graph neuron (HGN) implements a single cycle memorization and recall operation through a novel algorithmic design. The HGN is an improvement on the already published original graph neuron (GN) algorithm. In this improved approach, it recognizes incomplete/noisy patterns. It also resolves the crosstalk problem, which is identified in the previous publications, within closely matched patterns. To accomplish this, the HGN links multiple GN networks for filtering noise and crosstalk out of pattern data inputs. Intrinsically, the HGN is a lightweight in-network processing algorithm which does not require expensive floating point computations; hence, it is very suitable for real-time applications and tiny devices such as the wireless sensor networks. This paper describes that the HGN's pattern matching capability and the small response time remain insensitive to the increases in the number of stored patterns. Moreover, the HGN does not require definition of rules or setting of thresholds by the operator to achieve the desired results nor does it require heuristics entailing iterative operations for memorization and recall of patterns.
Optogenetic activation of neocortical neurons in vivo with a sapphire-based micro-scale LED probe.
McAlinden, Niall; Gu, Erdan; Dawson, Martin D; Sakata, Shuzo; Mathieson, Keith
2015-01-01
Optogenetics has proven to be a revolutionary technology in neuroscience and has advanced continuously over the past decade. However, optical stimulation technologies for in vivo need to be developed to match the advances in genetics and biochemistry that have driven this field. In particular, conventional approaches for in vivo optical illumination have a limitation on the achievable spatio-temporal resolution. Here we utilize a sapphire-based microscale gallium nitride light-emitting diode (μLED) probe to activate neocortical neurons in vivo. The probes were designed to contain independently controllable multiple μLEDs, emitting at 450 nm wavelength with an irradiance of up to 2 W/mm(2). Monte-Carlo stimulations predicted that optical stimulation using a μLED can modulate neural activity within a localized region. To validate this prediction, we tested this probe in the mouse neocortex that expressed channelrhodopsin-2 (ChR2) and compared the results with optical stimulation through a fiber at the cortical surface. We confirmed that both approaches reliably induced action potentials in cortical neurons and that the μLED probe evoked strong responses in deep neurons. Due to the possibility to integrate many optical stimulation sites onto a single shank, the μLED probe is thus a promising approach to control neurons locally in vivo.
Koh, H Y; Vilim, F S; Jing, J; Weiss, K R
2003-09-01
In many neurons more than one peptide is colocalized with a classical neurotransmitter. The functional consequence of such an arrangement has been rarely investigated. Here, within the feeding circuit of Aplysia, we investigate at a single synapse the actions of two modulatory neuropeptides that are present in a cholinergic interneuron. In combination with previous work, our study shows that the command-like neuron for feeding, CBI-2, contains two neuropeptides, feeding circuit activating peptide (FCAP) and cerebral peptide 2 (CP2). Previous studies showed that high-frequency prestimulation or repeated stimulation of CBI-2 increases the size of CBI-2 to B61/62 excitatory postsynaptic potentials (EPSPs) and shortens the latency of firing of neuron B61/62 in response to CBI-2 stimulation. We find that both FCAP and CP2 mimic these two effects. The variance method of quantal analysis indicates that FCAP increases the calculated quantal size (q) and CP2 increases the calculated quantal content (m) of EPSPs. Since the PSP amplitude represents the product of q and m, the joint action of the two peptides is expected to be cooperative. This observation suggests a possible functional implication for multiple neuropeptides colocalized with a classical neurotransmitter in one neuron.
Command and Compensation in a Neuromodulatory Decision Network
Luan, Haojiang; Diao, Fengqiu; Peabody, Nathan C.; White, Benjamin H.
2012-01-01
The neural circuits that mediate behavioral choices must not only weigh internal demands and environmental circumstances, but also select and implement specific actions, including associated visceral or neuroendocrine functions. Coordinating these multiple processes suggests considerable complexity. As a consequence, even circuits that support simple behavioral decisions remain poorly understood. Here we show that the environmentally-sensitive wing expansion decision of adult fruit flies is coordinated by a single pair of neuromodulatory neurons with command-like function. Targeted suppression of these neurons using the Split Gal4 system abrogates the fly's ability to expand its wings in the face of environmental challenges, while stimulating them forces expansion by coordinately activating both motor and neuroendocrine outputs. The arbitration and implementation of the wing expansion decision by this neuronal pair may illustrate a general strategy by which neuromodulatory neurons orchestrate behavior. Interestingly, the decision network shows a behavioral plasticity that is unmasked under conducive environmental conditions in flies lacking the function of the command-like neuromodulatory neurons. Such flies can often expand their wings using a motor program distinct from that of wildtype animals and controls. This compensatory program may be the vestige of an ancestral, environmentally-insensitive program used for wing expansion that existed prior to the evolution of the environmentally-adaptive program currently used by Drosophila and other cyclorrhaphan flies. PMID:22262886
Santos, Lucas; Opris, Ioan; Fuqua, Joshua; Hampson, Robert E; Deadwyler, Sam A
2012-04-15
A unique custom-made tetrode microdrive for recording from large numbers of neurons in several areas of primate brain is described as a means for assessing simultaneous neural activity in cortical and subcortical structures in nonhuman primates (NHPs) performing behavioral tasks. The microdrive device utilizes tetrode technology with up to six ultra-thin microprobe guide tubes (0.1mm) that can be independently positioned, each containing reduced diameter tetrode and/or hexatrode microwires (0.02 mm) for recording and isolating single neuron activity. The microdrive device is mounted within the standard NHP cranial well and allows traversal of brain depths up to 40.0 mm. The advantages of this technology are demonstrated via simultaneously recorded large populations of neurons with tetrode type probes during task performance from a) primary motor cortex and deep brain structures (caudate-putamen and hippocampus) and b) multiple layers within the prefrontal cortex. The means to characterize interactions of well-isolated ensembles of neurons recorded simultaneously from different regions, as shown with this device, has not been previously available for application in primate brain. The device has extensive application to primate models for the detection and study of inoperative or maladaptive neural circuits related to human neurological disorders. Published by Elsevier B.V.
Moreno, A; de Felipe, J; García Sola, R; Navarro, A; Ramón y Cajal, S
2001-04-01
The group of brain tumors with mature components encompasses several pathological entities including: the ganglioneuroma; the gangliocytoma; the ganglioglioma; the desmoplastic ganglioglioma; the neurocitoma and a group of glioneuronal hamartomatous tumorous lesions, such as meningoangiomatosis. The dysembryoplastic neuroepithelial tumor is characterized by the presence of multiple cortical nodules made up of small, oligo-like cells and a myxoid pattern rich in mucopolysaccharides. Mature neuronal cells are frequently detected throughout the tumor. Most of them are associated with microhamartias in the adjacent brain and pharmacoresistant epilepsy. The excellent prognosis of the majority of these tumors and the potential for malignant transformation of the glial component in the ganglioglioma are the two most remarkable findings. Histological signs of anaplasia and greater mitotic and proliferative activities are associated with local recurrences. Atypical neurocytomas occur only exceptionally. Treatment choices are surgical resectioning and, in those cases presenting greater proliferative activity and cytological atypia, postoperative radiotherapy may be recommended. This paper reviews this heterogeneous group of neoplasms and hamartomatous lesions, pointing out presumable transitions among the different types of mixed neuronal and glial brain tumors. A single term of "mixed neuronal-glial tumors" is defended, distinguishing different subgroups of tumors, depending on the predominant cellular component.
A Novel Form of Compensation in the Tg2576 Amyloid Mouse Model of Alzheimer’s Disease
Somogyi, Attila; Katonai, Zoltán; Alpár, Alán; Wolf, Ervin
2016-01-01
One century after its first description, pathology of Alzheimer’s disease (AD) is still poorly understood. Amyloid-related dendritic atrophy and membrane alterations of susceptible brain neurons in AD, and in animal models of AD are widely recognized. However, little effort has been made to study the potential effects of combined morphological and membrane alterations on signal transfer and synaptic integration in neurons that build up affected neural networks in AD. In this study spatial reconstructions and electrophysiological measurements of layer II/III pyramidal neurons of the somatosensory cortex from wild-type (WT) and transgenic (TG) human amyloid precursor protein (hAPP) overexpressing Tg2576 mice were used to build faithful segmental cable models of these neurons. Local synaptic activities were simulated in various points of the dendritic arbors and properties of subthreshold dendritic impulse propagation and predictors of synaptic input pattern recognition ability were quantified and compared in modeled WT and TG neurons. Despite the widespread dendritic degeneration and membrane alterations in mutant mouse neurons, surprisingly little, or no change was detected in steady-state and 50 Hz sinusoidal voltage transfers, current transfers, and local and propagation delays of PSPs traveling along dendrites of TG neurons. Synaptic input pattern recognition ability was also predicted to be unaltered in TG neurons in two different soma-dendritic membrane models investigated. Our simulations predict the way how subthreshold dendritic signaling and pattern recognition are preserved in TG neurons: amyloid-related membrane alterations compensate for the pathological effects that dendritic atrophy has on subthreshold dendritic signal transfer and integration in layer II/III somatosensory neurons of this hAPP mouse model for AD. Since neither propagation of single PSPs nor integration of multiple PSPs (pattern recognition) changes in TG neurons, we conclude that AD-related neuronal hyperexcitability cannot be accounted for by altered subthreshold dendritic signaling in these neurons but hyperexcitability is related to changes in active membrane properties and network connectivity. PMID:27378850
A Novel Form of Compensation in the Tg2576 Amyloid Mouse Model of Alzheimer's Disease.
Somogyi, Attila; Katonai, Zoltán; Alpár, Alán; Wolf, Ervin
2016-01-01
One century after its first description, pathology of Alzheimer's disease (AD) is still poorly understood. Amyloid-related dendritic atrophy and membrane alterations of susceptible brain neurons in AD, and in animal models of AD are widely recognized. However, little effort has been made to study the potential effects of combined morphological and membrane alterations on signal transfer and synaptic integration in neurons that build up affected neural networks in AD. In this study spatial reconstructions and electrophysiological measurements of layer II/III pyramidal neurons of the somatosensory cortex from wild-type (WT) and transgenic (TG) human amyloid precursor protein (hAPP) overexpressing Tg2576 mice were used to build faithful segmental cable models of these neurons. Local synaptic activities were simulated in various points of the dendritic arbors and properties of subthreshold dendritic impulse propagation and predictors of synaptic input pattern recognition ability were quantified and compared in modeled WT and TG neurons. Despite the widespread dendritic degeneration and membrane alterations in mutant mouse neurons, surprisingly little, or no change was detected in steady-state and 50 Hz sinusoidal voltage transfers, current transfers, and local and propagation delays of PSPs traveling along dendrites of TG neurons. Synaptic input pattern recognition ability was also predicted to be unaltered in TG neurons in two different soma-dendritic membrane models investigated. Our simulations predict the way how subthreshold dendritic signaling and pattern recognition are preserved in TG neurons: amyloid-related membrane alterations compensate for the pathological effects that dendritic atrophy has on subthreshold dendritic signal transfer and integration in layer II/III somatosensory neurons of this hAPP mouse model for AD. Since neither propagation of single PSPs nor integration of multiple PSPs (pattern recognition) changes in TG neurons, we conclude that AD-related neuronal hyperexcitability cannot be accounted for by altered subthreshold dendritic signaling in these neurons but hyperexcitability is related to changes in active membrane properties and network connectivity.
Zhu, Hongying; Zou, Guichang; Wang, Ning; Zhuang, Meihui; Xiong, Wei; Huang, Guangming
2017-03-07
The use of single-cell assays has emerged as a cutting-edge technique during the past decade. Although single-cell mass spectrometry (MS) has recently achieved remarkable results, deep biological insights have not yet been obtained, probably because of various technical issues, including the unavoidable use of matrices, the inability to maintain cell viability, low throughput because of sample pretreatment, and the lack of recordings of cell physiological activities from the same cell. In this study, we describe a patch clamp/MS-based platform that enables the sensitive, rapid, and in situ chemical profiling of single living neurons. This approach integrates modified patch clamp technique and modified MS measurements to directly collect and detect nanoliter-scale samples from the cytoplasm of single neurons in mice brain slices. Abundant possible cytoplasmic constituents were detected in a single neuron at a relatively fast rate, and over 50 metabolites were identified in this study. The advantages of direct, rapid, and in situ sampling and analysis enabled us to measure the biological activities of the cytoplasmic constituents in a single neuron, including comparing neuron types by cytoplasmic chemical constituents; observing changes in constituent concentrations as the physiological conditions, such as age, vary; and identifying the metabolic pathways of small molecules.
Zhu, Hongying; Zou, Guichang; Wang, Ning; Zhuang, Meihui; Xiong, Wei; Huang, Guangming
2017-01-01
The use of single-cell assays has emerged as a cutting-edge technique during the past decade. Although single-cell mass spectrometry (MS) has recently achieved remarkable results, deep biological insights have not yet been obtained, probably because of various technical issues, including the unavoidable use of matrices, the inability to maintain cell viability, low throughput because of sample pretreatment, and the lack of recordings of cell physiological activities from the same cell. In this study, we describe a patch clamp/MS-based platform that enables the sensitive, rapid, and in situ chemical profiling of single living neurons. This approach integrates modified patch clamp technique and modified MS measurements to directly collect and detect nanoliter-scale samples from the cytoplasm of single neurons in mice brain slices. Abundant possible cytoplasmic constituents were detected in a single neuron at a relatively fast rate, and over 50 metabolites were identified in this study. The advantages of direct, rapid, and in situ sampling and analysis enabled us to measure the biological activities of the cytoplasmic constituents in a single neuron, including comparing neuron types by cytoplasmic chemical constituents; observing changes in constituent concentrations as the physiological conditions, such as age, vary; and identifying the metabolic pathways of small molecules. PMID:28223513
Multiplexed aberration measurement for deep tissue imaging in vivo
Wang, Chen; Liu, Rui; Milkie, Daniel E.; Sun, Wenzhi; Tan, Zhongchao; Kerlin, Aaron; Chen, Tsai-Wen; Kim, Douglas S.; Ji, Na
2014-01-01
We describe a multiplexed aberration measurement method that modulates the intensity or phase of light rays at multiple pupil segments in parallel to determine their phase gradients. Applicable to fluorescent-protein-labeled structures of arbitrary complexity, it allows us to obtain diffraction-limited resolution in various samples in vivo. For the strongly scattering mouse brain, a single aberration correction improves structural and functional imaging of fine neuronal processes over a large imaging volume. PMID:25128976
Xiao, Jianbo; Niu, Yu-Qiong; Wiesner, Steven
2014-01-01
Multiple visual stimuli are common in natural scenes, yet it remains unclear how multiple stimuli interact to influence neuronal responses. We investigated this question by manipulating relative signal strengths of two stimuli moving simultaneously within the receptive fields (RFs) of neurons in the extrastriate middle temporal (MT) cortex. Visual stimuli were overlapping random-dot patterns moving in two directions separated by 90°. We first varied the motion coherence of each random-dot pattern and characterized, across the direction tuning curve, the relationship between neuronal responses elicited by bidirectional stimuli and by the constituent motion components. The tuning curve for bidirectional stimuli showed response normalization and can be accounted for by a weighted sum of the responses to the motion components. Allowing nonlinear, multiplicative interaction between the two component responses significantly improved the data fit for some neurons, and the interaction mainly had a suppressive effect on the neuronal response. The weighting of the component responses was not fixed but dependent on relative signal strengths. When two stimulus components moved at different coherence levels, the response weight for the higher-coherence component was significantly greater than that for the lower-coherence component. We also varied relative luminance levels of two coherently moving stimuli and found that MT response weight for the higher-luminance component was also greater. These results suggest that competition between multiple stimuli within a neuron's RF depends on relative signal strengths of the stimuli and that multiplicative nonlinearity may play an important role in shaping the response tuning for multiple stimuli. PMID:24899674
Three-dimensional spatiotemporal focusing of holographic patterns
Hernandez, Oscar; Papagiakoumou, Eirini; Tanese, Dimitrii; Fidelin, Kevin; Wyart, Claire; Emiliani, Valentina
2016-01-01
Two-photon excitation with temporally focused pulses can be combined with phase-modulation approaches, such as computer-generated holography and generalized phase contrast, to efficiently distribute light into two-dimensional, axially confined, user-defined shapes. Adding lens-phase modulations to 2D-phase holograms enables remote axial pattern displacement as well as simultaneous pattern generation in multiple distinct planes. However, the axial confinement linearly degrades with lateral shape area in previous reports where axially shifted holographic shapes were not temporally focused. Here we report an optical system using two spatial light modulators to independently control transverse- and axial-target light distribution. This approach enables simultaneous axial translation of single or multiple spatiotemporally focused patterns across the sample volume while achieving the axial confinement of temporal focusing. We use the system's capability to photoconvert tens of Kaede-expressing neurons with single-cell resolution in live zebrafish larvae. PMID:27306044
Ikeda, Ryo; Gu, Jianguo
2016-01-01
Whisker hair follicles are sensory organs that sense touch and perform tactile discrimination in animals, and they are sites where sensory impulses are initiated when whisker hairs touch an object. The sensory signals are then conveyed by whisker afferent fibers to the brain for sensory perception. Electrophysiological property and chemical sensitivity of whisker afferent fibers, important factors affecting whisker sensory processing, are largely not known. In the present study, we performed patch-clamp recordings from pre-identified whisker afferent neurons in whole-mount trigeminal ganglion preparations and characterized their electrophysiological property and sensitivity to ATP, serotonin and glutamate. Of 97 whisker afferent neurons examined, 67% of them are found to be large-sized (diameter ≥45 µm) cells and 33% of them are medium- to small-sized (diameter <45 µm) cells. Almost every large-sized whisker afferent neuron fires a single action potential but many (40%) small/medium-sized whisker afferent neurons fire multiple action potentials in response to prolonged stepwise depolarization. Other electrophysiological properties including resting membrane potential, action potential threshold, and membrane input resistance are also significantly different between large-sized and small/medium-sized whisker afferent neurons. Most large-sized and many small/medium-sized whisker afferent neurons are sensitive to ATP and/or serotonin, and ATP and/or serotonin could evoke strong inward currents in these cells. In contrast, few whisker afferent neurons are sensitive to glutamate. Our results raise a possibility that ATP and/or serotonin may be chemical messengers involving sensory signaling for different types of rat whisker afferent fibers.
Encoding of Spatial Attention by Primate Prefrontal Cortex Neuronal Ensembles
Treue, Stefan
2018-01-01
Abstract Single neurons in the primate lateral prefrontal cortex (LPFC) encode information about the allocation of visual attention and the features of visual stimuli. However, how this compares to the performance of neuronal ensembles at encoding the same information is poorly understood. Here, we recorded the responses of neuronal ensembles in the LPFC of two macaque monkeys while they performed a task that required attending to one of two moving random dot patterns positioned in different hemifields and ignoring the other pattern. We found single units selective for the location of the attended stimulus as well as for its motion direction. To determine the coding of both variables in the population of recorded units, we used a linear classifier and progressively built neuronal ensembles by iteratively adding units according to their individual performance (best single units), or by iteratively adding units based on their contribution to the ensemble performance (best ensemble). For both methods, ensembles of relatively small sizes (n < 60) yielded substantially higher decoding performance relative to individual single units. However, the decoder reached similar performance using fewer neurons with the best ensemble building method compared with the best single units method. Our results indicate that neuronal ensembles within the LPFC encode more information about the attended spatial and nonspatial features of visual stimuli than individual neurons. They further suggest that efficient coding of attention can be achieved by relatively small neuronal ensembles characterized by a certain relationship between signal and noise correlation structures. PMID:29568798
Is realistic neuronal modeling realistic?
Almog, Mara
2016-01-01
Scientific models are abstractions that aim to explain natural phenomena. A successful model shows how a complex phenomenon arises from relatively simple principles while preserving major physical or biological rules and predicting novel experiments. A model should not be a facsimile of reality; it is an aid for understanding it. Contrary to this basic premise, with the 21st century has come a surge in computational efforts to model biological processes in great detail. Here we discuss the oxymoronic, realistic modeling of single neurons. This rapidly advancing field is driven by the discovery that some neurons don't merely sum their inputs and fire if the sum exceeds some threshold. Thus researchers have asked what are the computational abilities of single neurons and attempted to give answers using realistic models. We briefly review the state of the art of compartmental modeling highlighting recent progress and intrinsic flaws. We then attempt to address two fundamental questions. Practically, can we realistically model single neurons? Philosophically, should we realistically model single neurons? We use layer 5 neocortical pyramidal neurons as a test case to examine these issues. We subject three publically available models of layer 5 pyramidal neurons to three simple computational challenges. Based on their performance and a partial survey of published models, we conclude that current compartmental models are ad hoc, unrealistic models functioning poorly once they are stretched beyond the specific problems for which they were designed. We then attempt to plot possible paths for generating realistic single neuron models. PMID:27535372
Hammer, Jiří; Pistohl, Tobias; Fischer, Jörg; Kršek, Pavel; Tomášek, Martin; Marusič, Petr; Schulze-Bonhage, Andreas; Aertsen, Ad; Ball, Tonio
2016-01-01
How neuronal activity of motor cortex is related to movement is a central topic in motor neuroscience. Motor-cortical single neurons are more closely related to hand movement velocity than speed, that is, the magnitude of the (directional) velocity vector. Recently, there is also increasing interest in the representation of movement parameters in neuronal population activity, such as reflected in the intracranial EEG (iEEG). We show that in iEEG, contrasting to what has been previously found on the single neuron level, speed predominates over velocity. The predominant speed representation was present in nearly all iEEG signal features, up to the 600–1000 Hz range. Using a model of motor-cortical signals arising from neuronal populations with realistic single neuron tuning properties, we show how this reversal can be understood as a consequence of increasing population size. Our findings demonstrate that the information profile in large population signals may systematically differ from the single neuron level, a principle that may be helpful in the interpretation of neuronal population signals in general, including, for example, EEG and functional magnetic resonance imaging. Taking advantage of the robust speed population signal may help in developing brain–machine interfaces exploiting population signals. PMID:26984895
Specific excitatory connectivity for feature integration in mouse primary visual cortex
Molina-Luna, Patricia; Roth, Morgane M.
2017-01-01
Local excitatory connections in mouse primary visual cortex (V1) are stronger and more prevalent between neurons that share similar functional response features. However, the details of how functional rules for local connectivity shape neuronal responses in V1 remain unknown. We hypothesised that complex responses to visual stimuli may arise as a consequence of rules for selective excitatory connectivity within the local network in the superficial layers of mouse V1. In mouse V1 many neurons respond to overlapping grating stimuli (plaid stimuli) with highly selective and facilitatory responses, which are not simply predicted by responses to single gratings presented alone. This complexity is surprising, since excitatory neurons in V1 are considered to be mainly tuned to single preferred orientations. Here we examined the consequences for visual processing of two alternative connectivity schemes: in the first case, local connections are aligned with visual properties inherited from feedforward input (a ‘like-to-like’ scheme specifically connecting neurons that share similar preferred orientations); in the second case, local connections group neurons into excitatory subnetworks that combine and amplify multiple feedforward visual properties (a ‘feature binding’ scheme). By comparing predictions from large scale computational models with in vivo recordings of visual representations in mouse V1, we found that responses to plaid stimuli were best explained by assuming feature binding connectivity. Unlike under the like-to-like scheme, selective amplification within feature-binding excitatory subnetworks replicated experimentally observed facilitatory responses to plaid stimuli; explained selective plaid responses not predicted by grating selectivity; and was consistent with broad anatomical selectivity observed in mouse V1. Our results show that visual feature binding can occur through local recurrent mechanisms without requiring feedforward convergence, and that such a mechanism is consistent with visual responses and cortical anatomy in mouse V1. PMID:29240769
The metabolic response to excitotoxicity - lessons from single-cell imaging.
Connolly, Niamh M C; Prehn, Jochen H M
2015-04-01
Excitotoxicity is a pathological process implicated in neuronal death during ischaemia, traumatic brain injuries and neurodegenerative diseases. Excitotoxicity is caused by excess levels of glutamate and over-activation of NMDA or calcium-permeable AMPA receptors on neuronal membranes, leading to ionic influx, energetic stress and potential neuronal death. The metabolic response of neurons to excitotoxicity is complex and plays a key role in the ability of the neuron to adapt and recover from such an insult. Single-cell imaging is a powerful experimental technique that can be used to study the neuronal metabolic response to excitotoxicity in vitro and, increasingly, in vivo. Here, we review some of the knowledge of the neuronal metabolic response to excitotoxicity gained from in vitro single-cell imaging, including calcium and ATP dynamics and their effects on mitochondrial function, along with the contribution of glucose metabolism, oxidative stress and additional neuroprotective signalling mechanisms. Future work will combine knowledge gained from single-cell imaging with data from biochemical and computational techniques to garner holistic information about the metabolic response to excitotoxicity at the whole brain level and transfer this knowledge to a clinical setting.
Pure state consciousness and its local reduction to neuronal space
NASA Astrophysics Data System (ADS)
Duggins, A. J.
2013-01-01
The single neuronal state can be represented as a vector in a complex space, spanned by an orthonormal basis of integer spike counts. In this model a scalar element of experience is associated with the instantaneous firing rate of a single sensory neuron over repeated stimulus presentations. Here the model is extended to composite neural systems that are tensor products of single neuronal vector spaces. Depiction of the mental state as a vector on this tensor product space is intended to capture the unity of consciousness. The density operator is introduced as its local reduction to the single neuron level, from which the firing rate can again be derived as the objective correlate of a subjective element. However, the relational structure of perceptual experience only emerges when the non-local mental state is considered. A metric of phenomenal proximity between neuronal elements of experience is proposed, based on the cross-correlation function of neurophysiology, but constrained by the association of theoretical extremes of correlation/anticorrelation in inseparable 2-neuron states with identical and opponent elements respectively.
... muscular problems, such as multiple sclerosis, stroke, and cerebral palsy; motor neuron disorders such as polio, some forms ... muscular problems, such as multiple sclerosis, stroke, and cerebral palsy; motor neuron disorders such as polio, some forms ...
Wheeler, Scott R.; Stagg, Stephanie B.; Crews, Stephen T.
2009-01-01
The study of how transcriptional control and cell signaling influence neurons and glia to acquire their differentiated properties is fundamental to understanding CNS development and function. The Drosophila CNS midline cells are an excellent system for studying these issues because they consist of a small population of diverse cells with well-defined gene expression profiles. In this paper, the origins and differentiation of midline neurons and glia were analyzed. Midline precursor (MP) cells each divide once giving rise to two neurons; here, we use a combination of single-cell gene expression mapping and time-lapse imaging to identify individual MPs, their locations, movements and stereotyped patterns of division. The role of Notch signaling was investigated by analyzing 37 midline-expressed genes in Notch pathway mutant and misexpression embryos. Notch signaling had opposing functions: it inhibited neurogenesis in MP1,3,4 and promoted neurogenesis in MP5,6. Notch signaling also promoted midline glial and median neuroblast cell fate. This latter result suggests that the median neuroblast resembles brain neuroblasts that require Notch signaling, rather than nerve cord neuroblasts, the formation of which is inhibited by Notch signaling. Asymmetric MP daughter cell fates also depend on Notch signaling. One member of each pair of MP3–6 daughter cells was responsive to Notch signaling. By contrast, the other daughter cell asymmetrically acquired Numb, which inhibited Notch signaling, leading to a different fate choice. In summary, this paper describes the formation and division of MPs and multiple roles for Notch signaling in midline cell development, providing a foundation for comprehensive molecular analyses. PMID:18701546
Law, Andrew J.; Rivlis, Gil
2014-01-01
Pioneering studies demonstrated that novel degrees of freedom could be controlled individually by directly encoding the firing rate of single motor cortex neurons, without regard to each neuron's role in controlling movement of the native limb. In contrast, recent brain-computer interface work has emphasized decoding outputs from large ensembles that include substantially more neurons than the number of degrees of freedom being controlled. To bridge the gap between direct encoding by single neurons and decoding output from large ensembles, we studied monkeys controlling one degree of freedom by comodulating up to four arbitrarily selected motor cortex neurons. Performance typically exceeded random quite early in single sessions and then continued to improve to different degrees in different sessions. We therefore examined factors that might affect performance. Performance improved with larger ensembles. In contrast, other factors that might have reflected preexisting synaptic architecture—such as the similarity of preferred directions—had little if any effect on performance. Patterns of comodulation among ensemble neurons became more consistent across trials as performance improved over single sessions. Compared with the ensemble neurons, other simultaneously recorded neurons showed less modulation. Patterns of voluntarily comodulated firing among small numbers of arbitrarily selected primary motor cortex (M1) neurons thus can be found and improved rapidly, with little constraint based on the normal relationships of the individual neurons to native limb movement. This rapid flexibility in relationships among M1 neurons may in part underlie our ability to learn new movements and improve motor skill. PMID:24920030
Single-Cell Detection of Secreted Aβ and sAPPα from Human IPSC-Derived Neurons and Astrocytes.
Liao, Mei-Chen; Muratore, Christina R; Gierahn, Todd M; Sullivan, Sarah E; Srikanth, Priya; De Jager, Philip L; Love, J Christopher; Young-Pearse, Tracy L
2016-02-03
Secreted factors play a central role in normal and pathological processes in every tissue in the body. The brain is composed of a highly complex milieu of different cell types and few methods exist that can identify which individual cells in a complex mixture are secreting specific analytes. By identifying which cells are responsible, we can better understand neural physiology and pathophysiology, more readily identify the underlying pathways responsible for analyte production, and ultimately use this information to guide the development of novel therapeutic strategies that target the cell types of relevance. We present here a method for detecting analytes secreted from single human induced pluripotent stem cell (iPSC)-derived neural cells and have applied the method to measure amyloid β (Aβ) and soluble amyloid precursor protein-alpha (sAPPα), analytes central to Alzheimer's disease pathogenesis. Through these studies, we have uncovered the dynamic range of secretion profiles of these analytes from single iPSC-derived neuronal and glial cells and have molecularly characterized subpopulations of these cells through immunostaining and gene expression analyses. In examining Aβ and sAPPα secretion from single cells, we were able to identify previously unappreciated complexities in the biology of APP cleavage that could not otherwise have been found by studying averaged responses over pools of cells. This technique can be readily adapted to the detection of other analytes secreted by neural cells, which would have the potential to open new perspectives into human CNS development and dysfunction. We have established a technology that, for the first time, detects secreted analytes from single human neurons and astrocytes. We examine secretion of the Alzheimer's disease-relevant factors amyloid β (Aβ) and soluble amyloid precursor protein-alpha (sAPPα) and present novel findings that could not have been observed without a single-cell analytical platform. First, we identify a previously unappreciated subpopulation that secretes high levels of Aβ in the absence of detectable sAPPα. Further, we show that multiple cell types secrete high levels of Aβ and sAPPα, but cells expressing GABAergic neuronal markers are overrepresented. Finally, we show that astrocytes are competent to secrete high levels of Aβ and therefore may be a significant contributor to Aβ accumulation in the brain. Copyright © 2016 the authors 0270-6474/16/361730-17$15.00/0.
Daily, Neil J.; Du, Zhong-Wei
2017-01-01
Abstract Electrophysiology of excitable cells, including muscle cells and neurons, has been measured by making direct contact with a single cell using a micropipette electrode. To increase the assay throughput, optical devices such as microscopes and microplate readers have been used to analyze electrophysiology of multiple cells. We have established a high-throughput (HTP) analysis of action potentials (APs) in highly enriched motor neurons and cardiomyocytes (CMs) that are differentiated from human induced pluripotent stem cells (iPSCs). A multichannel electric field stimulation (EFS) device enabled the ability to electrically stimulate cells and measure dynamic changes in APs of excitable cells ultra-rapidly (>100 data points per second) by imaging entire 96-well plates. We found that the activities of both neurons and CMs and their response to EFS and chemicals are readily discerned by our fluorescence imaging-based HTP phenotyping assay. The latest generation of calcium (Ca2+) indicator dyes, FLIPR Calcium 6 and Cal-520, with the HTP device enables physiological analysis of human iPSC-derived samples highlighting its potential application for understanding disease mechanisms and discovering new therapeutic treatments. PMID:28525289
Neuronal spike-train responses in the presence of threshold noise.
Coombes, S; Thul, R; Laudanski, J; Palmer, A R; Sumner, C J
2011-03-01
The variability of neuronal firing has been an intense topic of study for many years. From a modelling perspective it has often been studied in conductance based spiking models with the use of additive or multiplicative noise terms to represent channel fluctuations or the stochastic nature of neurotransmitter release. Here we propose an alternative approach using a simple leaky integrate-and-fire model with a noisy threshold. Initially, we develop a mathematical treatment of the neuronal response to periodic forcing using tools from linear response theory and use this to highlight how a noisy threshold can enhance downstream signal reconstruction. We further develop a more general framework for understanding the responses to large amplitude forcing based on a calculation of first passage times. This is ideally suited to understanding stochastic mode-locking, for which we numerically determine the Arnol'd tongue structure. An examination of data from regularly firing stellate neurons within the ventral cochlear nucleus, responding to sinusoidally amplitude modulated pure tones, shows tongue structures consistent with these predictions and highlights that stochastic, as opposed to deterministic, mode-locking is utilised at the level of the single stellate cell to faithfully encode periodic stimuli.
Dscam2 mediates axonal tiling in the Drosophila visual system
Millard, S. Sean; Flanagan, John J.; Pappu, Kartik S.; Wu, Wei; Zipursky, S. Lawrence
2009-01-01
Sensory processing centres in both the vertebrate and the invertebrate brain are often organized into reiterated columns, thus facilitating an internal topographic representation of the external world. Cells within each column are arranged in a stereotyped fashion and form precise patterns of synaptic connections within discrete layers. These connections are largely confined to a single column, thereby preserving the spatial information from the periphery. Other neurons integrate this information by connecting to multiple columns. Restricting axons to columns is conceptually similar to tiling. Axons and dendrites of neighbouring neurons of the same class use tiling to form complete, yet non-overlapping, receptive fields1-3. It is thought that, at the molecular level, cell-surface proteins mediate tiling through contact-dependent repulsive interactions1,2,4,5, but proteins serving this function have not yet been identified. Here we show that the immunoglobulin superfamily member Dscam2 restricts the connections formed by L1 lamina neurons to columns in the Drosophila visual system. Our data support a model in which Dscam2 homophilic interactions mediate repulsion between neurites of L1 cells in neighbouring columns. We propose that Dscam2 is a tiling receptor for L1 neurons. PMID:17554308
Jayakumar, Jaikishan; Roy, Sujata; Dreher, Bogdan; Martin, Paul R; Vidyasagar, Trichur R
2013-01-01
We recorded spike activity of single neurones in the middle temporal visual cortical area (MT or V5) of anaesthetised macaque monkeys. We used flashing, stationary spatially circumscribed, cone-isolating and luminance-modulated stimuli of uniform fields to assess the effects of signals originating from the long-, medium- or short- (S) wavelength-sensitive cone classes. Nearly half (41/86) of the tested MT neurones responded reliably to S-cone-isolating stimuli. Response amplitude in the majority of the neurones tested further (19/28) was significantly reduced, though not always completely abolished, during reversible inactivation of visuotopically corresponding regions of the ipsilateral primary visual cortex (striate cortex, area V1). Thus, the present data indicate that signals originating in S-cones reach area MT, either via V1 or via a pathway that does not go through area V1. We did not find a significant difference between the mean latencies of spike responses of MT neurones to signals that bypass V1 and those that do not; the considerable overlap we observed precludes the use of spike-response latency as a criterion to define the routes through which the signals reach MT.
Nitabach, Michael N.; Wu, Ying; Sheeba, Vasu; Lemon, William C.; Strumbos, John; Zelensky, Paul K.; White, Benjamin H.; Holmes, Todd C.
2008-01-01
Coupling of autonomous cellular oscillators is an essential aspect of circadian clock function but little is known about its circuit requirements. Functional ablation of the pigment-dispersing factor-expressing lateral ventral subset (LNV ) of Drosophila clock neurons abolishes circadian rhythms of locomotor activity. The hypothesis that LNVs synchronize oscillations in downstream clock neurons was tested by rendering the LNVs hyperexcitable via transgenic expression of a low activation threshold voltage-gated sodium channel. When the LNVs are made hyperexcitable, free-running behavioral rhythms decompose into multiple independent superimposed oscillations and the clock protein oscillations in the dorsal neuron 1 and 2 subgroups of clock neurons are phase-shifted. Thus, regulated electrical activity of the LNVs synchronize multiple oscillators in the fly circadian pacemaker circuit. PMID:16407545
Expanding the spectrum of neuronal pathology in multiple system atrophy
Cykowski, Matthew D.; Coon, Elizabeth A.; Powell, Suzanne Z.; Jenkins, Sarah M.; Benarroch, Eduardo E.; Low, Phillip A.; Schmeichel, Ann M.
2015-01-01
Multiple system atrophy is a sporadic alpha-synucleinopathy that typically affects patients in their sixth decade of life and beyond. The defining clinical features of the disease include progressive autonomic failure, parkinsonism, and cerebellar ataxia leading to significant disability. Pathologically, multiple system atrophy is characterized by glial cytoplasmic inclusions containing filamentous alpha-synuclein. Neuronal inclusions also have been reported but remain less well defined. This study aimed to further define the spectrum of neuronal pathology in 35 patients with multiple system atrophy (20 male, 15 female; mean age at death 64.7 years; median disease duration 6.5 years, range 2.2 to 15.6 years). The morphologic type, topography, and frequencies of neuronal inclusions, including globular cytoplasmic (Lewy body-like) neuronal inclusions, were determined across a wide spectrum of brain regions. A correlation matrix of pathologic severity also was calculated between distinct anatomic regions of involvement (striatum, substantia nigra, olivary and pontine nuclei, hippocampus, forebrain and thalamus, anterior cingulate and neocortex, and white matter of cerebrum, cerebellum, and corpus callosum). The major finding was the identification of widespread neuronal inclusions in the majority of patients, not only in typical disease-associated regions (striatum, substantia nigra), but also within anterior cingulate cortex, amygdala, entorhinal cortex, basal forebrain and hypothalamus. Neuronal inclusion pathology appeared to follow a hierarchy of region-specific susceptibility, independent of the clinical phenotype, and the severity of pathology was duration-dependent. Neuronal inclusions also were identified in regions not previously implicated in the disease, such as within cerebellar roof nuclei. Lewy body-like inclusions in multiple system atrophy followed the stepwise anatomic progression of Lewy body-spectrum disease inclusion pathology in 25.7% of patients with multiple system atrophy, including a patient with visual hallucinations. Further, the presence of Lewy body-like inclusions in neocortex, but not hippocampal alpha-synuclein pathology, was associated with cognitive impairment (P = 0.002). However, several cases had the presence of isolated Lewy body-like inclusions at atypical sites (e.g. thalamus, deep cerebellar nuclei) that are not typical for Lewy body-spectrum disease. Finally, interregional correlations (rho ≥ 0.6) in pathologic glial and neuronal lesion burden suggest shared mechanisms of disease progression between both discrete anatomic regions (e.g. basal forebrain and hippocampus) and cell types (neuronal and glial inclusions in frontal cortex and white matter, respectively). These findings suggest that in addition to glial inclusions, neuronal pathology plays an important role in the developmental and progression of multiple system atrophy. See Halliday (doi:10.1093/brain/awv151) for a scientific commentary on this article. PMID:25981961
Conserved mechanisms of vocalization coding in mammalian and songbird auditory midbrain.
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.
Teriakidis, Adrianna; Willshaw, David J; Ribchester, Richard R
2012-10-01
During development, neurons form supernumerary synapses, most of which are selectively pruned leading to stereotyped patterns of innervation. During the development of skeletal muscle innervation, or its regeneration after nerve injury, each muscle fiber is transiently innervated by multiple motor axon branches but eventually by a single branch. The selective elimination of all but one branch is the result of competition between the converging arbors. It is thought that motor neurons initially innervate muscle fibers randomly, but that axon branches from the same neuron (sibling branches) do not converge to innervate the same muscle fiber. However, random innervation would result in many neonatal endplates that are co-innervated by sibling branches. To investigate whether this occurs we examined neonatal levator auris longus (LAL) and 4th deep lumbrical (4DL) muscles, as well as adult reinnervated deep lumbrical muscles (1-4) in transgenic mice expressing yellow fluorescent protein (YFP) as a reporter. We provide direct evidence of convergence of sibling neurites within single fluorescent motor units, both during development and during regeneration after nerve crush. The incidence of sibling neurite convergence was 40% lower in regeneration and at least 75% lower during development than expected by chance. Therefore, there must be a mechanism that decreases the probability of its occurrence. As sibling neurite convergence is not seen in normal adults, or at later timepoints in regeneration, synapse elimination must also remove convergent synaptic inputs derived from the same motor neuron. Mechanistic theories of synaptic competition should now accommodate this form of isoaxonal plasticity. Copyright © 2012 Wiley Periodicals, Inc.
Multiple zebrafish atoh1 genes specify a diversity of neuronal types in the zebrafish cerebellum.
Kidwell, Chelsea U; Su, Chen-Ying; Hibi, Masahiko; Moens, Cecilia B
2018-06-01
A single Atoh1 basic-helix-loop-helix transcription factor specifies multiple neuron types in the mammalian cerebellum and anterior hindbrain. The zebrafish genome encodes three paralagous atoh1 genes whose functions in cerebellum and anterior hindbrain development we explore here. With use of a transgenic reporter, we report that zebrafish atoh1c-expressing cells are organized in two distinct domains that are separated both by space and developmental time. An early isthmic expression domain gives rise to an extracerebellar population in rhombomere 1 and an upper rhombic lip domain gives rise to granule cell progenitors that migrate to populate all four granule cell territories of the fish cerebellum. Using genetic mutants we find that of the three zebrafish atoh1 paralogs, atoh1c and atoh1a are required for the full complement of granule neurons. Surprisingly, the two genes are expressed in non-overlapping granule cell progenitor populations, indicating that fish use duplicate atoh1 genes to generate granule cell diversity that is not detected in mammals. Finally, live imaging of granule cell migration in wildtype and atoh1c mutant embryos reveals that while atoh1c is not required for granule cell specification per se, it is required for granule cells to delaminate and migrate away from the rhombic lip. Copyright © 2018 Elsevier Inc. All rights reserved.
VERSATILE, HIGH-RESOLUTION ANTEROGRADE LABELING OF VAGAL EFFERENT PROJECTIONS WITH DEXTRAN AMINES
Walter, Gary C.; Phillips, Robert J.; Baronowsky, Elizabeth A.; Powley, Terry L.
2009-01-01
None of the anterograde tracers used to label and investigate vagal preganglionic neurons projecting to the viscera has proved optimal for routine and extensive labeling of autonomic terminal fields. To identify an alternative tracer protocol, the present experiment evaluated whether dextran conjugates, which have produced superior results in the CNS, might yield widespread and effective labeling of long, fine-caliber vagal efferents in the peripheral nervous system. The dextran conjugates that were evaluated proved reliable and versatile for labeling the motor neuron pool in its entirety, for single- and multiple-labeling protocols, for both conventional and confocal fluorescence microscopy, and for permanent labeling protocols for brightfield microscopy of the projections to the gastrointestinal (GI) tract. Using a standard ABC kit followed by visualization with DAB as the chromagen, Golgi-like labeling of the vagal efferent terminal fields in the GI wall was achieved with the biotinylated dextrans. The definition of individual terminal varicosities was so sharp and detailed that it was routinely practical to examine the relationship of putative vagal efferent contacts (by the criteria of high magnification light microscopy) with the dendritic and somatic architecture of counterstained neurons in the myenteric plexus. Overall, dextran conjugates provide high-definition labeling of an extensive vagal motor pool in the GI tract, and offer considerable versatility when multiple-staining protocols are needed to elucidate the complexities of the innervation of the gut. PMID:19056424
Neuronal substrates of sleep homeostasis; lessons from flies, rats and mice.
Donlea, Jeffrey M; Alam, Md Noor; Szymusiak, Ronald
2017-06-01
Sleep homeostasis is a fundamental property of vigilance state regulation that is highly conserved across species. Neuronal systems and circuits that underlie sleep homeostasis are not well understood. In Drosophila, a neuronal circuit involving neurons in the ellipsoid body and in the dorsal Fan-shaped body is a candidate for both tracing sleep need during waking and translating it to increased sleep drive and expression. Sleep homeostasis in rats and mice involves multiple neuromodulators acting on multiple wake- and sleep-promoting neuronal systems. A functional central homeostat emerges from A 1 receptor mediated actions of adenosine on wake-promoting neurons in the basal forebrain and hypothalamus, and A 2A adenosine receptor-mediated actions on sleep-promoting neurons in the preoptic hypothalamus and nucleus accumbens. Copyright © 2017. Published by Elsevier Ltd.
Neuronal activity determines distinct gliotransmitter release from a single astrocyte
Covelo, Ana
2018-01-01
Accumulating evidence indicates that astrocytes are actively involved in brain function by regulating synaptic activity and plasticity. Different gliotransmitters, such as glutamate, ATP, GABA or D-serine, released form astrocytes have been shown to induce different forms of synaptic regulation. However, whether a single astrocyte may release different gliotransmitters is unknown. Here we show that mouse hippocampal astrocytes activated by endogenous (neuron-released endocannabinoids or GABA) or exogenous (single astrocyte Ca2+ uncaging) stimuli modulate putative single CA3-CA1 hippocampal synapses. The astrocyte-mediated synaptic modulation was biphasic and consisted of an initial glutamate-mediated potentiation followed by a purinergic-mediated depression of neurotransmitter release. The temporal dynamic properties of this biphasic synaptic regulation depended on the firing frequency and duration of the neuronal activity that stimulated astrocytes. Present results indicate that single astrocytes can decode neuronal activity and, in response, release distinct gliotransmitters to differentially regulate neurotransmission at putative single synapses. PMID:29380725
Pollen, Alex A; Nowakowski, Tomasz J; Shuga, Joe; Wang, Xiaohui; Leyrat, Anne A; Lui, Jan H; Li, Nianzhen; Szpankowski, Lukasz; Fowler, Brian; Chen, Peilin; Ramalingam, Naveen; Sun, Gang; Thu, Myo; Norris, Michael; Lebofsky, Ronald; Toppani, Dominique; Kemp, Darnell W; Wong, Michael; Clerkson, Barry; Jones, Brittnee N; Wu, Shiquan; Knutsson, Lawrence; Alvarado, Beatriz; Wang, Jing; Weaver, Lesley S; May, Andrew P; Jones, Robert C; Unger, Marc A; Kriegstein, Arnold R; West, Jay A A
2014-10-01
Large-scale surveys of single-cell gene expression have the potential to reveal rare cell populations and lineage relationships but require efficient methods for cell capture and mRNA sequencing. Although cellular barcoding strategies allow parallel sequencing of single cells at ultra-low depths, the limitations of shallow sequencing have not been investigated directly. By capturing 301 single cells from 11 populations using microfluidics and analyzing single-cell transcriptomes across downsampled sequencing depths, we demonstrate that shallow single-cell mRNA sequencing (~50,000 reads per cell) is sufficient for unbiased cell-type classification and biomarker identification. In the developing cortex, we identify diverse cell types, including multiple progenitor and neuronal subtypes, and we identify EGR1 and FOS as previously unreported candidate targets of Notch signaling in human but not mouse radial glia. Our strategy establishes an efficient method for unbiased analysis and comparison of cell populations from heterogeneous tissue by microfluidic single-cell capture and low-coverage sequencing of many cells.
Lapish, Christopher C.; Durstewitz, Daniel; Chandler, L. Judson; Seamans, Jeremy K.
2008-01-01
Successful decision making requires an ability to monitor contexts, actions, and outcomes. The anterior cingulate cortex (ACC) is thought to be critical for these functions, monitoring and guiding decisions especially in challenging situations involving conflict and errors. A number of different single-unit correlates have been observed in the ACC that reflect the diverse cognitive components involved. Yet how ACC neurons function as an integrated network is poorly understood. Here we show, using advanced population analysis of multiple single-unit recordings from the rat ACC during performance of an ecologically valid decision-making task, that ensembles of neurons move through different coherent and dissociable states as the cognitive requirements of the task change. This organization into distinct network patterns with respect to both firing-rate changes and correlations among units broke down during trials with numerous behavioral errors, especially at choice points of the task. These results point to an underlying functional organization into cell assemblies in the ACC that may monitor choices, outcomes, and task contexts, thus tracking the animal's progression through “task space.” PMID:18708525
Stable long-term chronic brain mapping at the single-neuron level.
Fu, Tian-Ming; Hong, Guosong; Zhou, Tao; Schuhmann, Thomas G; Viveros, Robert D; Lieber, Charles M
2016-10-01
Stable in vivo mapping and modulation of the same neurons and brain circuits over extended periods is critical to both neuroscience and medicine. Current electrical implants offer single-neuron spatiotemporal resolution but are limited by such factors as relative shear motion and chronic immune responses during long-term recording. To overcome these limitations, we developed a chronic in vivo recording and stimulation platform based on flexible mesh electronics, and we demonstrated stable multiplexed local field potentials and single-unit recordings in mouse brains for at least 8 months without probe repositioning. Properties of acquired signals suggest robust tracking of the same neurons over this period. This recording and stimulation platform allowed us to evoke stable single-neuron responses to chronic electrical stimulation and to carry out longitudinal studies of brain aging in freely behaving mice. Such advantages could open up future studies in mapping and modulating changes associated with learning, aging and neurodegenerative diseases.
Single photon emission computed tomography in motor neuron disease with dementia.
Sawada, H; Udaka, F; Kishi, Y; Seriu, N; Mezaki, T; Kameyama, M; Honda, M; Tomonobu, M
1988-01-01
Single photon emission computed tomography with [123 I] isopropylamphetamine was carried out on a patient with motor neuron disease with dementia. [123 I] uptake was decreased in the frontal lobes. This would reflect the histopathological findings such as neuronal loss and gliosis in the frontal lobes.
Neurons as sensors: individual and cascaded chemical sensing.
Prasad, Shalini; Zhang, Xuan; Yang, Mo; Ozkan, Cengiz S; Ozkan, Mihrimah
2004-07-15
A single neuron sensor has been developed based on the interaction of gradient electric fields and the cell membrane. Single neurons are rapidly positioned over individual microelectrodes using positive dielectrophoretic traps. This enables the continuous extracellular electrophysiological measurements from individual neurons. The sensor developed using this technique provides the first experimental method for determining single cell sensitivity; the speed of response and the associated physiological changes to a broad spectrum of chemical agents. Binding of specific chemical agents to a specific combination of receptors induces changes to the extracellular membrane potential of a single neuron, which can be translated into unique "signature patterns" (SP), which function as identification tags. Signature patterns are derived using Fast Fourier Transformation (FFT) analysis and Wavelet Transformation (WT) analysis of the modified extracellular action potential. The validity and the sensitivity of the system are demonstrated for a variety of chemical agents ranging from behavior altering chemicals (ethanol), environmentally hazardous agents (hydrogen peroxide, EDTA) to physiologically harmful agents (pyrethroids) at pico- and femto-molar concentrations. The ability of a single neuron to selectively identify specific chemical agents when injected in a serial manner is demonstrated in "cascaded sensing".
Gender differences in human single neuron responses to male emotional faces.
Newhoff, Morgan; Treiman, David M; Smith, Kris A; Steinmetz, Peter N
2015-01-01
Well-documented differences in the psychology and behavior of men and women have spurred extensive exploration of gender's role within the brain, particularly regarding emotional processing. While neuroanatomical studies clearly show differences between the sexes, the functional effects of these differences are less understood. Neuroimaging studies have shown inconsistent locations and magnitudes of gender differences in brain hemodynamic responses to emotion. To better understand the neurophysiology of these gender differences, we analyzed recordings of single neuron activity in the human brain as subjects of both genders viewed emotional expressions. This study included recordings of single-neuron activity of 14 (6 male) epileptic patients in four brain areas: amygdala (236 neurons), hippocampus (n = 270), anterior cingulate cortex (n = 256), and ventromedial prefrontal cortex (n = 174). Neural activity was recorded while participants viewed a series of avatar male faces portraying positive, negative or neutral expressions. Significant gender differences were found in the left amygdala, where 23% (n = 15∕66) of neurons in men were significantly affected by facial emotion, vs. 8% (n = 6∕76) of neurons in women. A Fisher's exact test comparing the two ratios found a highly significant difference between the two (p < 0.01). These results show specific differences between genders at the single-neuron level in the human amygdala. These differences may reflect gender-based distinctions in evolved capacities for emotional processing and also demonstrate the importance of including subject gender as an independent factor in future studies of emotional processing by single neurons in the human amygdala.
Transcriptional regulation of neuronal polarity and morphogenesis in the mammalian brain
de la Torre-Ubieta, Luis; Bonni, Azad
2012-01-01
The highly specialized morphology of a neuron, typically consisting of a long axon and multiple branching dendrites, lies at the core of the principle of dynamic polarization, whereby information flows from dendrites toward the soma and to the axon. For more than a century neuroscientists have been fascinated by how shape is important for neuronal function and how neurons acquire their characteristic morphology. During the past decade, substantial progress has been made in our understanding of the molecular underpinnings of neuronal polarity and morphogenesis. In these studies, transcription factors have emerged as key players governing multiple aspects of neuronal morphogenesis from neuronal polarization and migration to axon growth and pathfinding to dendrite growth and branching to synaptogenesis. In this review, we will highlight the role of transcription factors in shaping neuronal morphology with emphasis on recent literature in mammalian systems. PMID:21982366
Regalia, Giulia; Biffi, Emilia; Achilli, Silvia; Ferrigno, Giancarlo; Menegon, Andrea; Pedrocchi, Alessandra
2016-02-01
Two binding requirements for in vitro studies on long-term neuronal networks dynamics are (i) finely controlled environmental conditions to keep neuronal cultures viable and provide reliable data for more than a few hours and (ii) parallel operation on multiple neuronal cultures to shorten experimental time scales and enhance data reproducibility. In order to fulfill these needs with a Microelectrode Arrays (MEA)-based system, we designed a stand-alone device that permits to uninterruptedly monitor neuronal cultures activity over long periods, overcoming drawbacks of existing MEA platforms. We integrated in a single device: (i) a closed chamber housing four MEAs equipped with access for chemical manipulations, (ii) environmental control systems and embedded sensors to reproduce and remotely monitor the standard in vitro culture environment on the lab bench (i.e. in terms of temperature, air CO2 and relative humidity), and (iii) a modular MEA interface analog front-end for reliable and parallel recordings. The system has been proven to assure environmental conditions stable, physiological and homogeneos across different cultures. Prolonged recordings (up to 10 days) of spontaneous and pharmacologically stimulated neuronal culture activity have not shown signs of rundown thanks to the environmental stability and have not required to withdraw the cells from the chamber for culture medium manipulations. This system represents an effective MEA-based solution to elucidate neuronal network phenomena with slow dynamics, such as long-term plasticity, effects of chronic pharmacological stimulations or late-onset pathological mechanisms. © 2015 Wiley Periodicals, Inc.
Pulse-coupled neural network sensor fusion
NASA Astrophysics Data System (ADS)
Johnson, John L.; Schamschula, Marius P.; Inguva, Ramarao; Caulfield, H. John
1998-03-01
Perception is assisted by sensed impressions of the outside world but not determined by them. The primary organ of perception is the brain and, in particular, the cortex. With that in mind, we have sought to see how a computer-modeled cortex--the PCNN or Pulse Coupled Neural Network--performs as a sensor fusing element. In essence, the PCNN is comprised of an array of integrate-and-fire neurons with one neuron for each input pixel. In such a system, the neurons corresponding to bright pixels reach firing threshold faster than the neurons corresponding to duller pixels. Thus, firing rate is proportional to brightness. In PCNNs, when a neuron fires it sends some of the resulting signal to its neighbors. This linking can cause a near-threshold neuron to fire earlier than it would have otherwise. This leads to synchronization of the pulses across large regions of the image. We can simplify the 3D PCNN output by integrating out the time dimension. Over a long enough time interval, the resulting 2D (x,y) pattern IS the input image. The PCNN has taken it apart and put it back together again. The shorter- term time integrals are interesting in themselves and will be commented upon in the paper. The main thrust of this paper is the use of multiple PCNNs mutually coupled in various ways to assemble a single 2D pattern or fused image. Results of experiments on PCNN image fusion and an evaluation of its advantages are our primary objectives.
Gertz, Monica L; Baker, Zachary; Jose, Sharon; Peixoto, Nathalia
2017-05-29
Micro-electrode arrays (MEAs) can be used to investigate drug toxicity, design paradigms for next-generation personalized medicine, and study network dynamics in neuronal cultures. In contrast with more traditional methods, such as patch-clamping, which can only record activity from a single cell, MEAs can record simultaneously from multiple sites in a network, without requiring the arduous task of placing each electrode individually. Moreover, numerous control and stimulation configurations can be easily applied within the same experimental setup, allowing for a broad range of dynamics to be explored. One of the key dynamics of interest in these in vitro studies has been the extent to which cultured networks display properties indicative of learning. Mouse neuronal cells cultured on MEAs display an increase in response following training induced by electrical stimulation. This protocol demonstrates how to culture neuronal cells on MEAs; successfully record from over 95% of the plated dishes; establish a protocol to train the networks to respond to patterns of stimulation; and sort, plot, and interpret the results from such experiments. The use of a proprietary system for stimulating and recording neuronal cultures is demonstrated. Software packages are also used to sort neuronal units. A custom-designed graphical user interface is used to visualize post-stimulus time histograms, inter-burst intervals, and burst duration, as well as to compare the cellular response to stimulation before and after a training protocol. Finally, representative results and future directions of this research effort are discussed.
Desynchronization of slow oscillations in the basal ganglia during natural sleep.
Mizrahi-Kliger, Aviv D; Kaplan, Alexander; Israel, Zvi; Bergman, Hagai
2018-05-01
Slow oscillations of neuronal activity alternating between firing and silence are a hallmark of slow-wave sleep (SWS). These oscillations reflect the default activity present in all mammalian species, and are ubiquitous to anesthesia, brain slice preparations, and neuronal cultures. In all these cases, neuronal firing is highly synchronous within local circuits, suggesting that oscillation-synchronization coupling may be a governing principle of sleep physiology regardless of anatomical connectivity. To investigate whether this principle applies to overall brain organization, we recorded the activity of individual neurons from basal ganglia (BG) structures and the thalamocortical (TC) network over 70 full nights of natural sleep in two vervet monkeys. During SWS, BG neurons manifested slow oscillations (∼0.5 Hz) in firing rate that were as prominent as in the TC network. However, in sharp contrast to any neural substrate explored thus far, the slow oscillations in all BG structures were completely desynchronized between individual neurons. Furthermore, whereas in the TC network single-cell spiking was locked to slow oscillations in the local field potential (LFP), the BG LFP exhibited only weak slow oscillatory activity and failed to entrain nearby cells. We thus show that synchrony is not inherent to slow oscillations, and propose that the BG desynchronization of slow oscillations could stem from its unique anatomy and functional connectivity. Finally, we posit that BG slow-oscillation desynchronization may further the reemergence of slow-oscillation traveling waves from multiple independent origins in the frontal cortex, thus significantly contributing to normal SWS.
NASA Astrophysics Data System (ADS)
Michon, Frédéric; Aarts, Arno; Holzhammer, Tobias; Ruther, Patrick; Borghs, Gustaaf; McNaughton, Bruce; Kloosterman, Fabian
2016-08-01
Objective. Understanding how neuronal assemblies underlie cognitive function is a fundamental question in system neuroscience. It poses the technical challenge to monitor the activity of populations of neurons, potentially widely separated, in relation to behaviour. In this paper, we present a new system which aims at simultaneously recording from a large population of neurons from multiple separated brain regions in freely behaving animals. Approach. The concept of the new device is to combine the benefits of two existing electrophysiological techniques, i.e. the flexibility and modularity of micro-drive arrays and the high sampling ability of electrode-dense silicon probes. Main results. Newly engineered long bendable silicon probes were integrated into a micro-drive array. The resulting device can carry up to 16 independently movable silicon probes, each carrying 16 recording sites. Populations of neurons were recorded simultaneously in multiple cortical and/or hippocampal sites in two freely behaving implanted rats. Significance. Current approaches to monitor neuronal activity either allow to flexibly record from multiple widely separated brain regions (micro-drive arrays) but with a limited sampling density or to provide denser sampling at the expense of a flexible placement in multiple brain regions (neural probes). By combining these two approaches and their benefits, we present an alternative solution for flexible and simultaneous recordings from widely distributed populations of neurons in freely behaving rats.
NASA Astrophysics Data System (ADS)
Li, Yu-Ye; Ding, Xue-Li
2014-12-01
Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns.
Ghosal, Sriparna; Packard, Amy E B; Mahbod, Parinaz; McKlveen, Jessica M; Seeley, Randy J; Myers, Brent; Ulrich-Lai, Yvonne; Smith, Eric P; D'Alessio, David A; Herman, James P
2017-01-04
Organismal stress initiates a tightly orchestrated set of responses involving complex physiological and neurocognitive systems. Here, we present evidence for glucagon-like peptide 1 (GLP-1)-mediated paraventricular hypothalamic circuit coordinating the global stress response. The GLP-1 receptor (Glp1r) in mice was knocked down in neurons expressing single-minded 1, a transcription factor abundantly expressed in the paraventricular nucleus (PVN) of the hypothalamus. Mice with single-minded 1-mediated Glp1r knockdown had reduced hypothalamic-pituitary-adrenal axis responses to both acute and chronic stress and were protected against weight loss associated with chronic stress. In addition, regional Glp1r knockdown attenuated stress-induced cardiovascular responses accompanied by decreased sympathetic drive to the heart. Finally, Glp1r knockdown reduced anxiety-like behavior, implicating PVN GLP-1 signaling in behavioral stress reactivity. Collectively, these findings support a circuit whereby brainstem GLP-1 activates PVN signaling to mount an appropriate whole-organism response to stress. These results raise the possibility that dysfunction of this system may contribute to stress-related pathologies, and thereby provide a novel target for intervention. Dysfunctional stress responses are linked to a number of somatic and psychiatric diseases, emphasizing the importance of precise neuronal control of effector pathways. Pharmacological evidence suggests a role for glucagon-like peptide-1 (GLP-1) in modulating stress responses. Using a targeted knockdown of the GLP-1 receptor in the single-minded 1 neurons, we show dependence of paraventricular nucleus GLP-1 signaling in the coordination of neuroendocrine, autonomic, and behavioral responses to acute and chronic stress. To our knowledge, this is the first direct demonstration of an obligate brainstem-to-hypothalamus circuit orchestrating general stress excitation across multiple effector systems. These findings provide novel information regarding signaling pathways coordinating central control of whole-body stress reactivity. Copyright © 2017 the authors 0270-6474/17/370184-10$15.00/0.
Dann, Benjamin; Michaels, Jonathan A; Schaffelhofer, Stefan; Scherberger, Hansjörg
2016-08-15
The functional communication of neurons in cortical networks underlies higher cognitive processes. Yet, little is known about the organization of the single neuron network or its relationship to the synchronization processes that are essential for its formation. Here, we show that the functional single neuron network of three fronto-parietal areas during active behavior of macaque monkeys is highly complex. The network was closely connected (small-world) and consisted of functional modules spanning these areas. Surprisingly, the importance of different neurons to the network was highly heterogeneous with a small number of neurons contributing strongly to the network function (hubs), which were in turn strongly inter-connected (rich-club). Examination of the network synchronization revealed that the identified rich-club consisted of neurons that were synchronized in the beta or low frequency range, whereas other neurons were mostly non-oscillatory synchronized. Therefore, oscillatory synchrony may be a central communication mechanism for highly organized functional spiking networks.
Li, Cheng-Shu; Lu, Da-Peng; Cho, Young K
2015-06-01
The nucleus of the solitary tract (NST) and the parabrachial nuclei (PbN) are the first and second relays in the rodent central taste pathway. A series of electrophysiological experiments revealed that spontaneous and taste-evoked activities of brain stem gustatory neurons are altered by descending input from multiple forebrain nuclei in the central taste pathway. The nucleus accumbens shell (NAcSh) is a key neural substrate of reward circuitry, but it has not been verified as a classical gustatory nucleus. A recent in vivo electrophysiological study demonstrated that the NAcSh modulates the spontaneous and gustatory activities of hamster pontine taste neurons. In the present study, we investigated whether activation of the NAcSh modulates gustatory responses of the NST neurons. Extracellular single-unit activity was recorded from medullary neurons in urethane-anesthetized hamsters. After taste response was confirmed by delivery of sucrose, NaCl, citric acid, and quinine hydrochloride to the anterior tongue, the NAcSh was stimulated bilaterally with concentric bipolar stimulating electrodes. Stimulation of the ipsilateral and contralateral NAcSh induced firings from 54 and 37 of 90 medullary taste neurons, respectively. Thirty cells were affected bilaterally. No inhibitory responses or antidromic invasion was observed after NAcSh activation. In the subset of taste cells tested, high-frequency electrical stimulation of the NAcSh during taste delivery enhanced taste-evoked neuronal firing. These results demonstrate that two-thirds of the medullary gustatory neurons are under excitatory descending influence from the NAcSh, which is a strong indication of communication between the gustatory pathway and the mesolimbic reward pathway. Copyright © 2015 the American Physiological Society.
Staffend, Nancy A; Meisel, Robert L
2011-01-01
Fine neuronal morphology, such as dendritic spines, classically has been studied using the Golgi technique; however, Golgi staining is difficult to combine with other histological techniques. With the increasing popularity of fluorescent imaging, a number of fluorescent dyes have been developed that enable the coupling of multiple fluorescent labels in a single preparation. These fluorescent dyes include the lipophilic dialkylcarbocyanine, DiI; traditionally used for anterograde and retrograde neuronal tracing. More recently, DiI labeling has been used in combination with the Gene Gun for "DiOlistic" labeling of neurons in slice preparations. DiI sequesters itself within and diffuses laterally along the neuronal membrane, however once the cell is permeabilized, the DiI begins to leak from the cell membrane. A DiI derivative, Cell Tracker™ CM-DiI, increases dye stability and labeling half-life in permeabilized tissue, however at much greater expense. Here, the DiI and CM-DiI DiOlistic labeling techniques were tested in side-by-side experiments evaluating dye stability within dendritic architecture in medium spiny neurons of the dorsal stratum in both non-permeabilized and permeabilized tissue sections. In tissue sections that were not permeabilized, spine density in DiI labeled sections was higher than in CM-DiI labeling. In contrast, tissue sections that were permeabilized had higher spine densities in CM-DiI labeled neurons. These results suggest that for experiments involving non-permeabilized tissue, traditional DiI will suffice, however for experiments involving permeabilized tissue CM-DiI provides more consistent data. These experiments provide the first quantitative analyses of the impact of methodological permutations on neuronal labeling with DiI.
Nikolaev, Yury A; Dosen, Peter J; Laver, Derek R; van Helden, Dirk F; Hamill, Owen P
2015-05-22
The mammalian brain is a mechanosensitive organ that responds to different mechanical forces ranging from intrinsic forces implicated in brain morphogenesis to extrinsic forces that can cause concussion and traumatic brain injury. However, little is known of the mechanosensors that transduce these forces. In this study we use cell-attached patch recording to measure single mechanically-gated (MG) channel currents and their affects on spike activity in identified neurons in neonatal mouse brain slices. We demonstrate that both neocortical and hippocampal pyramidal neurons express stretch-activated MG cation channels that are activated by suctions of ~25mm Hg, have a single channel conductance for inward current of 50-70pS and show weak selectivity for alkali metal cations (i.e., Na(+)
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.
High-Throughput Mapping of Single-Neuron Projections by Sequencing of Barcoded RNA.
Kebschull, Justus M; Garcia da Silva, Pedro; Reid, Ashlan P; Peikon, Ian D; Albeanu, Dinu F; Zador, Anthony M
2016-09-07
Neurons transmit information to distant brain regions via long-range axonal projections. In the mouse, area-to-area connections have only been systematically mapped using bulk labeling techniques, which obscure the diverse projections of intermingled single neurons. Here we describe MAPseq (Multiplexed Analysis of Projections by Sequencing), a technique that can map the projections of thousands or even millions of single neurons by labeling large sets of neurons with random RNA sequences ("barcodes"). Axons are filled with barcode mRNA, each putative projection area is dissected, and the barcode mRNA is extracted and sequenced. Applying MAPseq to the locus coeruleus (LC), we find that individual LC neurons have preferred cortical targets. By recasting neuroanatomy, which is traditionally viewed as a problem of microscopy, as a problem of sequencing, MAPseq harnesses advances in sequencing technology to permit high-throughput interrogation of brain circuits. Copyright © 2016 Elsevier Inc. All rights reserved.
Zimmermann, H; Tashiro, T; Komiya, Y; Kurokawa, M
1989-02-01
Axonal transport was studied using a single vertebrate neuron, the giant electromotor neuron of the electric catfish, Malapterurus electricus. The electric organs of this strongly electric fish are innervated by two neurons whose axons form one electric nerve each. After injection of [35S]methionine into the spinal cord at the level of the two perikarya radioactively labelled material is exported by fast flow as a small wave with a velocity of 5.8 mm/h and a somal release time of 91 min (29 degrees C). Slow flow investigated between 15 and 39 days had a velocity of 1.36 mm/d at 29 degrees C. Analysis of radiolabelled proteins by polyacrylamide gel electrophoresis revealed different patterns of labelling between slow and fast flow. The relative molecular mass of the two major proteins labelled on slow flow correspond to actin and tubulin. Labelled proteins of higher relative molecular mass may correspond to neurofilament proteins. Our results suggest that this vertebrate single-neuron and single-axon system can be used successfully for axonal transport studies.
Han, Xue; Boyden, Edward S.
2007-01-01
The quest to determine how precise neural activity patterns mediate computation, behavior, and pathology would be greatly aided by a set of tools for reliably activating and inactivating genetically targeted neurons, in a temporally precise and rapidly reversible fashion. Having earlier adapted a light-activated cation channel, channelrhodopsin-2 (ChR2), for allowing neurons to be stimulated by blue light, we searched for a complementary tool that would enable optical neuronal inhibition, driven by light of a second color. Here we report that targeting the codon-optimized form of the light-driven chloride pump halorhodopsin from the archaebacterium Natronomas pharaonis (hereafter abbreviated Halo) to genetically-specified neurons enables them to be silenced reliably, and reversibly, by millisecond-timescale pulses of yellow light. We show that trains of yellow and blue light pulses can drive high-fidelity sequences of hyperpolarizations and depolarizations in neurons simultaneously expressing yellow light-driven Halo and blue light-driven ChR2, allowing for the first time manipulations of neural synchrony without perturbation of other parameters such as spiking rates. The Halo/ChR2 system thus constitutes a powerful toolbox for multichannel photoinhibition and photostimulation of virally or transgenically targeted neural circuits without need for exogenous chemicals, enabling systematic analysis and engineering of the brain, and quantitative bioengineering of excitable cells. PMID:17375185
Processing of band-passed noise in the lateral auditory belt cortex of the rhesus monkey.
Rauschecker, Josef P; Tian, Biao
2004-06-01
Neurons in the lateral belt areas of rhesus monkey auditory cortex were stimulated with band-passed noise (BPN) bursts of different bandwidths and center frequencies. Most neurons responded much more vigorously to these sounds than to tone bursts of a single frequency, and it thus became possible to elicit a clear response in 85% of lateral belt neurons. Tuning to center frequency and bandwidth of the BPN bursts was analyzed. Best center frequency varied along the rostrocaudal direction, with 2 reversals defining borders between areas. We confirmed the existence of 2 belt areas (AL and ML) that were laterally adjacent to the core areas (R and A1, respectively) and a third area (CL) adjacent to area CM on the supratemporal plane (STP). All 3 lateral belt areas were cochleotopically organized with their frequency gradients collinear to those of the adjacent STP areas. Although A1 neurons responded best to pure tones and their responses decreased with increasing bandwidth, 63% of the lateral belt neurons were tuned to bandwidths between 1/3 and 2 octaves and showed either one or multiple peaks. The results are compared with previous data from visual cortex and are discussed in the context of spectral integration, whereby the lateral belt forms a relatively early stage of processing in the cortical hierarchy, giving rise to parallel streams for the identification of auditory objects and their localization in space.
Perceptual decision related activity in the lateral geniculate nucleus
Jiang, Yaoguang; Yampolsky, Dmitry; Purushothaman, Gopathy
2015-01-01
Fundamental to neuroscience is the understanding of how the language of neurons relates to behavior. In the lateral geniculate nucleus (LGN), cells show distinct properties such as selectivity for particular wavelengths, increments or decrements in contrast, or preference for fine detail versus rapid motion. No studies, however, have measured how LGN cells respond when an animal is challenged to make a perceptual decision using information within the receptive fields of those LGN cells. In this study we measured neural activity in the macaque LGN during a two-alternative, forced-choice (2AFC) contrast detection task or during a passive fixation task and found that a small proportion (13.5%) of single LGN parvocellular (P) and magnocellular (M) neurons matched the psychophysical performance of the monkey. The majority of LGN neurons measured in both tasks were not as sensitive as the monkey. The covariation between neural response and behavior (quantified as choice probability) was significantly above chance during active detection, even when there was no external stimulus. Interneuronal correlations and task-related gain modulations were negligible under the same condition. A bottom-up pooling model that used sensory neural responses to compute perceptual choices in the absence of interneuronal correlations could fully explain these results at the level of the LGN, supporting the hypothesis that the perceptual decision pool consists of multiple sensory neurons and that response fluctuations in these neurons can influence perception. PMID:26019309
Xu, Xinyu; Tian, Yu; Wang, Guolin; Tian, Xin
2014-08-15
Working memory (WM) refers to the temporary storage and manipulation of information necessary for performance of complex cognitive tasks. There is a growing interest in whether and how propofol anesthesia inhibits WM function. The aim of this study is to investigate the possible inhibition mechanism of propofol anesthesia from the view of single neuron and neuronal ensemble activities. Adult SD rats were randomly divided into two groups: propofol group (0.9 mg kg(-1)min(-1), 2h via a tail vein catheter) and control group. All the rats were tested for working memory performances in a Y-maze-rewarded alternation task (a task of delayed non-matched-to-sample) at 24, 48, 72 h after propofol anesthesia, and the behavior results of WM tasks were recorded at the same time. Spatio-temporal trains of action potentials were obtained from the original signals. Single neuron activity was characterized by peri-event time histograms analysis and neuron ensemble activities were characterized by Granger causality to describe the interactions within the neuron ensemble. The results show that: comparing with the control group, the percentage of neurons excited and related to WM was significantly decreased (p<0.01 in 24h, p<0.05 in 48 h); the interactions within neuron ensemble were significantly weakened (p<0.01 in 24h, p<0.05 in 48 h), whereas no significant difference in 72 h (p>0.05), which were consistent with the behavior results. These findings could lead to improved understanding of the mechanism of anesthesia inhibition on WM functions from the view of single neuron activity and neuron ensemble interactions. Copyright © 2014 Elsevier B.V. All rights reserved.
Expanding the spectrum of neuronal pathology in multiple system atrophy.
Cykowski, Matthew D; Coon, Elizabeth A; Powell, Suzanne Z; Jenkins, Sarah M; Benarroch, Eduardo E; Low, Phillip A; Schmeichel, Ann M; Parisi, Joseph E
2015-08-01
Multiple system atrophy is a sporadic alpha-synucleinopathy that typically affects patients in their sixth decade of life and beyond. The defining clinical features of the disease include progressive autonomic failure, parkinsonism, and cerebellar ataxia leading to significant disability. Pathologically, multiple system atrophy is characterized by glial cytoplasmic inclusions containing filamentous alpha-synuclein. Neuronal inclusions also have been reported but remain less well defined. This study aimed to further define the spectrum of neuronal pathology in 35 patients with multiple system atrophy (20 male, 15 female; mean age at death 64.7 years; median disease duration 6.5 years, range 2.2 to 15.6 years). The morphologic type, topography, and frequencies of neuronal inclusions, including globular cytoplasmic (Lewy body-like) neuronal inclusions, were determined across a wide spectrum of brain regions. A correlation matrix of pathologic severity also was calculated between distinct anatomic regions of involvement (striatum, substantia nigra, olivary and pontine nuclei, hippocampus, forebrain and thalamus, anterior cingulate and neocortex, and white matter of cerebrum, cerebellum, and corpus callosum). The major finding was the identification of widespread neuronal inclusions in the majority of patients, not only in typical disease-associated regions (striatum, substantia nigra), but also within anterior cingulate cortex, amygdala, entorhinal cortex, basal forebrain and hypothalamus. Neuronal inclusion pathology appeared to follow a hierarchy of region-specific susceptibility, independent of the clinical phenotype, and the severity of pathology was duration-dependent. Neuronal inclusions also were identified in regions not previously implicated in the disease, such as within cerebellar roof nuclei. Lewy body-like inclusions in multiple system atrophy followed the stepwise anatomic progression of Lewy body-spectrum disease inclusion pathology in 25.7% of patients with multiple system atrophy, including a patient with visual hallucinations. Further, the presence of Lewy body-like inclusions in neocortex, but not hippocampal alpha-synuclein pathology, was associated with cognitive impairment (P = 0.002). However, several cases had the presence of isolated Lewy body-like inclusions at atypical sites (e.g. thalamus, deep cerebellar nuclei) that are not typical for Lewy body-spectrum disease. Finally, interregional correlations (rho ≥ 0.6) in pathologic glial and neuronal lesion burden suggest shared mechanisms of disease progression between both discrete anatomic regions (e.g. basal forebrain and hippocampus) and cell types (neuronal and glial inclusions in frontal cortex and white matter, respectively). These findings suggest that in addition to glial inclusions, neuronal pathology plays an important role in the developmental and progression of multiple system atrophy. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Gender differences in human single neuron responses to male emotional faces
Newhoff, Morgan; Treiman, David M.; Smith, Kris A.; Steinmetz, Peter N.
2015-01-01
Well-documented differences in the psychology and behavior of men and women have spurred extensive exploration of gender's role within the brain, particularly regarding emotional processing. While neuroanatomical studies clearly show differences between the sexes, the functional effects of these differences are less understood. Neuroimaging studies have shown inconsistent locations and magnitudes of gender differences in brain hemodynamic responses to emotion. To better understand the neurophysiology of these gender differences, we analyzed recordings of single neuron activity in the human brain as subjects of both genders viewed emotional expressions. This study included recordings of single-neuron activity of 14 (6 male) epileptic patients in four brain areas: amygdala (236 neurons), hippocampus (n = 270), anterior cingulate cortex (n = 256), and ventromedial prefrontal cortex (n = 174). Neural activity was recorded while participants viewed a series of avatar male faces portraying positive, negative or neutral expressions. Significant gender differences were found in the left amygdala, where 23% (n = 15∕66) of neurons in men were significantly affected by facial emotion, vs. 8% (n = 6∕76) of neurons in women. A Fisher's exact test comparing the two ratios found a highly significant difference between the two (p < 0.01). These results show specific differences between genders at the single-neuron level in the human amygdala. These differences may reflect gender-based distinctions in evolved capacities for emotional processing and also demonstrate the importance of including subject gender as an independent factor in future studies of emotional processing by single neurons in the human amygdala. PMID:26441597
Shape Selectivity of Middle Superior Temporal Sulcus Body Patch Neurons
2017-01-01
Abstract Functional MRI studies in primates have demonstrated cortical regions that are strongly activated by visual images of bodies. The presence of such body patches in macaques allows characterization of the stimulus selectivity of their single neurons. Middle superior temporal sulcus body (MSB) patch neurons showed similar stimulus selectivity for natural, shaded, and textured images compared with their silhouettes, suggesting that shape is an important determinant of MSB responses. Here, we examined and modeled the shape selectivity of single MSB neurons. We measured the responses of single MSB neurons to a variety of shapes producing a wide range of responses. We used an adaptive stimulus sampling procedure, selecting and modifying shapes based on the responses of the neuron. Forty percent of shapes that produced the maximal response were rated by humans as animal-like, but the top shape of many MSB neurons was not judged as resembling a body. We fitted the shape selectivity of MSB neurons with a model that parameterizes shapes in terms of curvature and orientation of contour segments, with a pixel-based model, and with layers of units of convolutional neural networks (CNNs). The deep convolutional layers of CNNs provided the best goodness-of-fit, with a median explained explainable variance of the neurons’ responses of 77%. The goodness-of-fit increased along the convolutional layers’ hierarchy but was lower for the fully connected layers. Together with demonstrating the successful modeling of single unit shape selectivity with deep CNNs, the data suggest that semantic or category knowledge determines only slightly the single MSB neuron’s shape selectivity. PMID:28660250
Fiáth, Richárd; Beregszászi, Patrícia; Horváth, Domonkos; Wittner, Lucia; Aarts, Arno A. A.; Ruther, Patrick; Neves, Hercules P.; Bokor, Hajnalka; Acsády, László
2016-01-01
Recording simultaneous activity of a large number of neurons in distributed neuronal networks is crucial to understand higher order brain functions. We demonstrate the in vivo performance of a recently developed electrophysiological recording system comprising a two-dimensional, multi-shank, high-density silicon probe with integrated complementary metal-oxide semiconductor electronics. The system implements the concept of electronic depth control (EDC), which enables the electronic selection of a limited number of recording sites on each of the probe shafts. This innovative feature of the system permits simultaneous recording of local field potentials (LFP) and single- and multiple-unit activity (SUA and MUA, respectively) from multiple brain sites with high quality and without the actual physical movement of the probe. To evaluate the in vivo recording capabilities of the EDC probe, we recorded LFP, MUA, and SUA in acute experiments from cortical and thalamic brain areas of anesthetized rats and mice. The advantages of large-scale recording with the EDC probe are illustrated by investigating the spatiotemporal dynamics of pharmacologically induced thalamocortical slow-wave activity in rats and by the two-dimensional tonotopic mapping of the auditory thalamus. In mice, spatial distribution of thalamic responses to optogenetic stimulation of the neocortex was examined. Utilizing the benefits of the EDC system may result in a higher yield of useful data from a single experiment compared with traditional passive multielectrode arrays, and thus in the reduction of animals needed for a research study. PMID:27535370
A passive exoskeleton can push your life up: application on multiple sclerosis patients.
Di Russo, Francesco; Berchicci, Marika; Perri, Rinaldo Livio; Ripani, Francesca Romana; Ripani, Maurizio
2013-01-01
In the present study, we report the benefits of a passive and fully articulated exoskeleton on multiple sclerosis patients by means of behavioral and electrophysiological measures, paying particular attention to the prefrontal cortex activity. Multiple sclerosis is a neurological condition characterized by lesions of the myelin sheaths that encapsulate the neurons of the brain, spine and optic nerve, and it causes transient or progressive symptoms and impairments in gait and posture. Up to 50% of multiple sclerosis patients require walking aids and 10% are wheelchair-bound 15 years following the initial diagnosis. We tested the ability of a new orthosis, the "Human Body Posturizer", designed to improve the structural and functional symmetry of the body through proprioception, in multiple sclerosis patients. We observed that a single Human Body Posturizer application improved mobility, ambulation and response accuracy, in all of the tested patients. Most importantly, we associated these clinical observations and behavioral effects to changes in brain activity, particularly in the prefrontal cortex.
Optical magnetic detection of single-neuron action potentials using quantum defects in diamond
Barry, John F.; Turner, Matthew J.; Schloss, Jennifer M.; Glenn, David R.; Song, Yuyu; Lukin, Mikhail D.; Park, Hongkun; Walsworth, Ronald L.
2016-01-01
Magnetic fields from neuronal action potentials (APs) pass largely unperturbed through biological tissue, allowing magnetic measurements of AP dynamics to be performed extracellularly or even outside intact organisms. To date, however, magnetic techniques for sensing neuronal activity have either operated at the macroscale with coarse spatial and/or temporal resolution—e.g., magnetic resonance imaging methods and magnetoencephalography—or been restricted to biophysics studies of excised neurons probed with cryogenic or bulky detectors that do not provide single-neuron spatial resolution and are not scalable to functional networks or intact organisms. Here, we show that AP magnetic sensing can be realized with both single-neuron sensitivity and intact organism applicability using optically probed nitrogen-vacancy (NV) quantum defects in diamond, operated under ambient conditions and with the NV diamond sensor in close proximity (∼10 µm) to the biological sample. We demonstrate this method for excised single neurons from marine worm and squid, and then exterior to intact, optically opaque marine worms for extended periods and with no observed adverse effect on the animal. NV diamond magnetometry is noninvasive and label-free and does not cause photodamage. The method provides precise measurement of AP waveforms from individual neurons, as well as magnetic field correlates of the AP conduction velocity, and directly determines the AP propagation direction through the inherent sensitivity of NVs to the associated AP magnetic field vector. PMID:27911765
Optical magnetic detection of single-neuron action potentials using quantum defects in diamond.
Barry, John F; Turner, Matthew J; Schloss, Jennifer M; Glenn, David R; Song, Yuyu; Lukin, Mikhail D; Park, Hongkun; Walsworth, Ronald L
2016-12-06
Magnetic fields from neuronal action potentials (APs) pass largely unperturbed through biological tissue, allowing magnetic measurements of AP dynamics to be performed extracellularly or even outside intact organisms. To date, however, magnetic techniques for sensing neuronal activity have either operated at the macroscale with coarse spatial and/or temporal resolution-e.g., magnetic resonance imaging methods and magnetoencephalography-or been restricted to biophysics studies of excised neurons probed with cryogenic or bulky detectors that do not provide single-neuron spatial resolution and are not scalable to functional networks or intact organisms. Here, we show that AP magnetic sensing can be realized with both single-neuron sensitivity and intact organism applicability using optically probed nitrogen-vacancy (NV) quantum defects in diamond, operated under ambient conditions and with the NV diamond sensor in close proximity (∼10 µm) to the biological sample. We demonstrate this method for excised single neurons from marine worm and squid, and then exterior to intact, optically opaque marine worms for extended periods and with no observed adverse effect on the animal. NV diamond magnetometry is noninvasive and label-free and does not cause photodamage. The method provides precise measurement of AP waveforms from individual neurons, as well as magnetic field correlates of the AP conduction velocity, and directly determines the AP propagation direction through the inherent sensitivity of NVs to the associated AP magnetic field vector.
Michel, K; Michaelis, M; Mazzuoli, G; Mueller, K; Vanden Berghe, P; Schemann, M
2011-12-15
Slow changes in [Ca(2+)](i) reflect increased neuronal activity. Our study demonstrates that single-trial fast [Ca(2+)](i) imaging (≥200 Hz sampling rate) revealed peaks each of which are associated with single spike discharge recorded by consecutive voltage-sensitive dye (VSD) imaging in enteric neurones and nerve fibres. Fast [Ca(2+)](i) imaging also revealed subthreshold fast excitatory postsynaptic potentials. Nicotine-evoked [Ca(2+)](i) peaks were reduced by -conotoxin and blocked by ruthenium red or tetrodotoxin. Fast [Ca(2+)](i) imaging can be used to directly record single action potentials in enteric neurones. [Ca(2+)](i) peaks required opening of voltage-gated sodium and calcium channels as well as Ca(2+) release from intracellular stores.
Human single-neuron responses at the threshold of conscious recognition
Quiroga, R. Quian; Mukamel, R.; Isham, E. A.; Malach, R.; Fried, I.
2008-01-01
We studied the responses of single neurons in the human medial temporal lobe while subjects viewed familiar faces, animals, and landmarks. By progressively shortening the duration of stimulus presentation, coupled with backward masking, we show two striking properties of these neurons. (i) Their responses are not statistically different for the 33-ms, 66-ms, and 132-ms stimulus durations, and only for the 264-ms presentations there is a significantly higher firing. (ii) These responses follow conscious perception, as indicated by the subjects' recognition report. Remarkably, when recognized, a single snapshot as brief as 33 ms was sufficient to trigger strong single-unit responses far outlasting stimulus presentation. These results suggest that neurons in the medial temporal lobe can reflect conscious recognition by “all-or-none” responses. PMID:18299568
El Filali, Z; de Boer, P A C M; Pieneman, A W; de Lange, R P J; Jansen, R F; Ter Maat, A; van der Schors, R C; Li, K W; van Straalen, N M; Koene, J M
2015-12-01
Male copulation is a complex behavior that requires coordinated communication between the nervous system and the peripheral reproductive organs involved in mating. In hermaphroditic animals, such as the freshwater snail Lymnaea stagnalis, this complexity increases since the animal can behave both as male and female. The performance of the sexual role as a male is coordinated via a neuronal communication regulated by many peptidergic neurons, clustered in the cerebral and pedal ganglia and dispersed in the pleural and parietal ganglia. By combining single-cell matrix-assisted laser mass spectrometry with retrograde staining and electrophysiology, we analyzed neuropeptide expression of single neurons of the right parietal ganglion and their axonal projections into the penial nerve. Based on the neuropeptide profile of these neurons, we were able to reconstruct a chemical map of the right parietal ganglion revealing a striking correlation with the earlier electrophysiological and neuroanatomical studies. Neurons can be divided into two main groups: (i) neurons that express heptapeptides and (ii) neurons that do not. The neuronal projection of the different neurons into the penial nerve reveals a pattern where (spontaneous) activity is related to branching pattern. This heterogeneity in both neurochemical anatomy and branching pattern of the parietal neurons reflects the complexity of the peptidergic neurotransmission involved in the regulation of male mating behavior in this simultaneous hermaphrodite.
Nikaido, Y; Nakashima, T
2011-03-17
The medial prefrontal cortex (mPFC) is involved in stimulus perception, attentional control, emotional behavior, and the stress response. These functions are thought to be mediated by the infralimbic (IL) and prelimbic (PL) subregions of mPFC; however, few studies have examined the roles of IL and PL cortices in olfactory cognition. In the present study, we investigated the acute effects of two odors, 2,5-dihydro-2,4,5-trimethylthiazoline (TMT) and a mixture of cis-3-hexenol and trans-2-hexenal (green odor: GO), on behavioral responses and IL and PL neuronal activities using extracellular single-unit recordings in a freely moving rat. We found that the total number of spike firings in IL and PL neurons did not change with 10s presentation of odors. TMT presentation induced significant changes in burst firing activity in IL and PL neurons, while GO presentation induced changes in burst firing only in IL neurons. In the temporal profile of the firing activity of IL neurons, TMT exposure induced transient activation and GO exposure induced sustained activation. Those of PL neurons showed sustained activation during TMT exposure and transient activations during GO exposure. GO exposure induced a stretch-attend posture, whereas TMT exposure induced immobility. Furthermore, multiple regression analysis indicated that the property of the odor and neuronal activities of IL and PL regions were correlated with behavioral responses. These findings reveal that olfaction-related neurons exist in IL and PL regions, and that the neurons in these regions might temporarily encode odor information in order to modulate motor outputs by tuning firing properties in the early stage of cognition according to the odor property. Copyright © 2010 Elsevier B.V. All rights reserved.
Label-free optical detection of action potential in mammalian neurons (Conference Presentation)
NASA Astrophysics Data System (ADS)
Batabyal, Subrata; Satpathy, Sarmishtha; Bui, Loan; Kim, Young-Tae; Mohanty, Samarendra K.; Davé, Digant P.
2017-02-01
Electrophysiology techniques are the gold standard in neuroscience for studying functionality of a single neuron to a complex neuronal network. However, electrophysiology techniques are not flawless, they are invasive nature, procedures are cumbersome to implement with limited capability of being used as a high-throughput recording system. Also, long term studies of neuronal functionality with aid of electrophysiology is not feasible. Non-invasive stimulation and detection of neuronal electrical activity has been a long standing goal in neuroscience. Introduction of optogenetics has ushered in the era of non-invasive optical stimulation of neurons, which is revolutionizing neuroscience research. Optical detection of neuronal activity that is comparable to electro-physiology is still elusive. A number of optical techniques have been reported recording of neuronal electrical activity but none is capable of reliably measuring action potential spikes that is comparable to electro-physiology. Optical detection of action potential with voltage sensitive fluorescent reporters are potential alternatives to electrophysiology techniques. The heavily rely on secondary reporters, which are often toxic in nature with background fluorescence, with slow response and low SNR making them far from ideal. The detection of one shot (without averaging)-single action potential in a true label-free way has been elusive so far. In this report, we demonstrate the optical detection of single neuronal spike in a cultured mammalian neuronal network without using any exogenous labels. To the best of our knowledge, this is the first demonstration of label free optical detection of single action potentials in a mammalian neuronal network, which was achieved using a high-speed phase sensitive interferometer. We have carried out stimulation and inhibition of neuronal firing using Glutamate and Tetrodotoxin respectively to demonstrate the different outcome (stimulation and inhibition) revealed in optical signal. We hypothesize that the interrogating optical beam is modulated during neuronal firing by electro-motility driven membrane fluctuation in conjunction with electrical wave propagation in cellular system.
Knowlton, Chris; Meliza, C Daniel; Margoliash, Daniel; Abarbanel, Henry D I
2014-06-01
Estimating the behavior of a network of neurons requires accurate models of the individual neurons along with accurate characterizations of the connections among them. Whereas for a single cell, measurements of the intracellular voltage are technically feasible and sufficient to characterize a useful model of its behavior, making sufficient numbers of simultaneous intracellular measurements to characterize even small networks is infeasible. This paper builds on prior work on single neurons to explore whether knowledge of the time of spiking of neurons in a network, once the nodes (neurons) have been characterized biophysically, can provide enough information to usefully constrain the functional architecture of the network: the existence of synaptic links among neurons and their strength. Using standardized voltage and synaptic gating variable waveforms associated with a spike, we demonstrate that the functional architecture of a small network of model neurons can be established.
Single-Cell Memory Regulates a Neural Circuit for Sensory Behavior.
Kobayashi, Kyogo; Nakano, Shunji; Amano, Mutsuki; Tsuboi, Daisuke; Nishioka, Tomoki; Ikeda, Shingo; Yokoyama, Genta; Kaibuchi, Kozo; Mori, Ikue
2016-01-05
Unveiling the molecular and cellular mechanisms underlying memory has been a challenge for the past few decades. Although synaptic plasticity is proven to be essential for memory formation, the significance of "single-cell memory" still remains elusive. Here, we exploited a primary culture system for the analysis of C. elegans neurons and show that a single thermosensory neuron has an ability to form, retain, and reset a temperature memory. Genetic and proteomic analyses found that the expression of the single-cell memory exhibits inter-individual variability, which is controlled by the evolutionarily conserved CaMKI/IV and Raf pathway. The variable responses of a sensory neuron influenced the neural activity of downstream interneurons, suggesting that modulation of the sensory neurons ultimately determines the behavioral output in C. elegans. Our results provide proof of single-cell memory and suggest that the individual differences in neural responses at the single-cell level can confer individuality. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Correlates of a single cortical action potential in the epidural EEG
Teleńczuk, Bartosz; Baker, Stuart N; Kempter, Richard; Curio, Gabriel
2015-01-01
To identify the correlates of a single cortical action potential in surface EEG, we recorded simultaneously epidural EEG and single-unit activity in the primary somatosensory cortex of awake macaque monkeys. By averaging over EEG segments coincident with more than hundred thousand single spikes, we found short-lived (≈ 0.5 ms) triphasic EEG deflections dominated by high-frequency components > 800 Hz. The peak-to-peak amplitude of the grand-averaged spike correlate was 80 nV, which matched theoretical predictions, while single-neuron amplitudes ranged from 12 to 966 nV. Combining these estimates with post-stimulus-time histograms of single-unit responses to median-nerve stimulation allowed us to predict the shape of the evoked epidural EEG response and to estimate the number of contributing neurons. These findings establish spiking activity of cortical neurons as a primary building block of high-frequency epidural EEG, which thus can serve as a quantitative macroscopic marker of neuronal spikes. PMID:25554430
Colvin, Robert A; Lai, Barry; Holmes, William R; Lee, Daewoo
2015-07-01
The purpose of this study was to demonstrate how single cell quantitative and subcellular metallomics inform us about both the spatial distribution and cellular mechanisms of metal buffering and homeostasis in primary cultured neurons from embryonic rat brain, which are often used as models of human disease involving metal dyshomeostasis. The present studies utilized synchrotron radiation X-ray fluorescence (SRXRF) and focused primarily on zinc and iron, two abundant metals in neurons that have been implicated in the pathogenesis of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. Total single cell contents for calcium, iron, zinc, copper, manganese, and nickel were determined. Resting steady state zinc showed a diffuse distribution in both soma and processes, best defined by the mass profile of the neuron with an enrichment in the nucleus compared with the cytoplasm. Zinc buffering and homeostasis was studied using two modes of cellular zinc loading - transporter and ionophore (pyrithione) mediated. Single neuron zinc contents were shown to statistically significantly increase by either loading method - ionophore: 160 million to 7 billion; transporter 160 million to 280 million atoms per neuronal soma. The newly acquired and buffered zinc still showed a diffuse distribution. Soma and processes have about equal abilities to take up zinc via transporter mediated pathways. Copper levels are distributed diffusely as well, but are relatively higher in the processes relative to zinc levels. Prior studies have observed iron puncta in certain cell types, but others have not. In the present study, iron puncta were characterized in several primary neuronal types. The results show that iron puncta could be found in all neuronal types studied and can account for up to 50% of the total steady state content of iron in neuronal soma. Although other metals can be present in iron puncta, they are predominantly iron containing and do not appear to be associated with ferritin cages or transferrin receptor endosomes. The iron content and its distribution in puncta were similar in all neuron types studied including primary dopaminergic neurons. In summary, quantitative measurements of steady state metal levels in single primary cultured neurons made possible by SRXRF analyses provide unique information on the relative levels of each metal in neuronal soma and processes, subcellular location of zinc loads, and have confirmed and extended the characterization of heretofore poorly understood cytoplasmic iron puncta.
A Diffusion MRI Tractography Connectome of the Mouse Brain and Comparison with Neuronal Tracer Data
Calabrese, Evan; Badea, Alexandra; Cofer, Gary; Qi, Yi; Johnson, G. Allan
2015-01-01
Interest in structural brain connectivity has grown with the understanding that abnormal neural connections may play a role in neurologic and psychiatric diseases. Small animal connectivity mapping techniques are particularly important for identifying aberrant connectivity in disease models. Diffusion magnetic resonance imaging tractography can provide nondestructive, 3D, brain-wide connectivity maps, but has historically been limited by low spatial resolution, low signal-to-noise ratio, and the difficulty in estimating multiple fiber orientations within a single image voxel. Small animal diffusion tractography can be substantially improved through the combination of ex vivo MRI with exogenous contrast agents, advanced diffusion acquisition and reconstruction techniques, and probabilistic fiber tracking. Here, we present a comprehensive, probabilistic tractography connectome of the mouse brain at microscopic resolution, and a comparison of these data with a neuronal tracer-based connectivity data from the Allen Brain Atlas. This work serves as a reference database for future tractography studies in the mouse brain, and demonstrates the fundamental differences between tractography and neuronal tracer data. PMID:26048951
Functional identification and reconstitution of an odorant receptor in single olfactory neurons
Touhara, Kazushige; Sengoku, Shintaro; Inaki, Koichiro; Tsuboi, Akio; Hirono, Junzo; Sato, Takaaki; Sakano, Hitoshi; Haga, Tatsuya
1999-01-01
The olfactory system is remarkable in its capacity to discriminate a wide range of odorants through a series of transduction events initiated in olfactory receptor neurons. Each olfactory neuron is expected to express only a single odorant receptor gene that belongs to the G protein coupled receptor family. The ligand–receptor interaction, however, has not been clearly characterized. This study demonstrates the functional identification of olfactory receptor(s) for specific odorant(s) from single olfactory neurons by a combination of Ca2+-imaging and reverse transcription–coupled PCR analysis. First, a candidate odorant receptor was cloned from a single tissue-printed olfactory neuron that displayed odorant-induced Ca2+ increase. Next, recombinant adenovirus-mediated expression of the isolated receptor gene was established in the olfactory epithelium by using green fluorescent protein as a marker. The infected neurons elicited external Ca2+ entry when exposed to the odorant that originally was used to identify the receptor gene. Experiments performed to determine ligand specificity revealed that the odorant receptor recognized specific structural motifs within odorant molecules. The odorant receptor-mediated signal transduction appears to be reconstituted by this two-step approach: the receptor screening for given odorant(s) from single neurons and the functional expression of the receptor via recombinant adenovirus. The present approach should enable us to examine not only ligand specificity of an odorant receptor but also receptor specificity and diversity for a particular odorant of interest. PMID:10097159
3D plasmonic nanoantennas integrated with MEA biosensors
NASA Astrophysics Data System (ADS)
Dipalo, Michele; Messina, Gabriele C.; Amin, Hayder; La Rocca, Rosanna; Shalabaeva, Victoria; Simi, Alessandro; Maccione, Alessandro; Zilio, Pierfrancesco; Berdondini, Luca; de Angelis, Francesco
2015-02-01
Neuronal signaling in brain circuits occurs at multiple scales ranging from molecules and cells to large neuronal assemblies. However, current sensing neurotechnologies are not designed for parallel access of signals at multiple scales. With the aim of combining nanoscale molecular sensing with electrical neural activity recordings within large neuronal assemblies, in this work three-dimensional (3D) plasmonic nanoantennas are integrated with multielectrode arrays (MEA). Nanoantennas are fabricated by fast ion beam milling on optical resist; gold is deposited on the nanoantennas in order to connect them electrically to the MEA microelectrodes and to obtain plasmonic behavior. The optical properties of these 3D nanostructures are studied through finite elements method (FEM) simulations that show a high electromagnetic field enhancement. This plasmonic enhancement is confirmed by surface enhancement Raman spectroscopy of a dye performed in liquid, which presents an enhancement of almost 100 times the incident field amplitude at resonant excitation. Finally, the reported MEA devices are tested on cultured rat hippocampal neurons. Neurons develop by extending branches on the nanostructured electrodes and extracellular action potentials are recorded over multiple days in vitro. Raman spectra of living neurons cultured on the nanoantennas are also acquired. These results highlight that these nanostructures could be potential candidates for combining electrophysiological measures of large networks with simultaneous spectroscopic investigations at the molecular level.Neuronal signaling in brain circuits occurs at multiple scales ranging from molecules and cells to large neuronal assemblies. However, current sensing neurotechnologies are not designed for parallel access of signals at multiple scales. With the aim of combining nanoscale molecular sensing with electrical neural activity recordings within large neuronal assemblies, in this work three-dimensional (3D) plasmonic nanoantennas are integrated with multielectrode arrays (MEA). Nanoantennas are fabricated by fast ion beam milling on optical resist; gold is deposited on the nanoantennas in order to connect them electrically to the MEA microelectrodes and to obtain plasmonic behavior. The optical properties of these 3D nanostructures are studied through finite elements method (FEM) simulations that show a high electromagnetic field enhancement. This plasmonic enhancement is confirmed by surface enhancement Raman spectroscopy of a dye performed in liquid, which presents an enhancement of almost 100 times the incident field amplitude at resonant excitation. Finally, the reported MEA devices are tested on cultured rat hippocampal neurons. Neurons develop by extending branches on the nanostructured electrodes and extracellular action potentials are recorded over multiple days in vitro. Raman spectra of living neurons cultured on the nanoantennas are also acquired. These results highlight that these nanostructures could be potential candidates for combining electrophysiological measures of large networks with simultaneous spectroscopic investigations at the molecular level. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr05578k
morphforge: a toolbox for simulating small networks of biologically detailed neurons in Python
Hull, Michael J.; Willshaw, David J.
2014-01-01
The broad structure of a modeling study can often be explained over a cup of coffee, but converting this high-level conceptual idea into graphs of the final simulation results may require many weeks of sitting at a computer. Although models themselves can be complex, often many mental resources are wasted working around complexities of the software ecosystem such as fighting to manage files, interfacing between tools and data formats, finding mistakes in code or working out the units of variables. morphforge is a high-level, Python toolbox for building and managing simulations of small populations of multicompartmental biophysical model neurons. An entire in silico experiment, including the definition of neuronal morphologies, channel descriptions, stimuli, visualization and analysis of results can be written within a single short Python script using high-level objects. Multiple independent simulations can be created and run from a single script, allowing parameter spaces to be investigated. Consideration has been given to the reuse of both algorithmic and parameterizable components to allow both specific and stochastic parameter variations. Some other features of the toolbox include: the automatic generation of human-readable documentation (e.g., PDF files) about a simulation; the transparent handling of different biophysical units; a novel mechanism for plotting simulation results based on a system of tags; and an architecture that supports both the use of established formats for defining channels and synapses (e.g., MODL files), and the possibility to support other libraries and standards easily. We hope that this toolbox will allow scientists to quickly build simulations of multicompartmental model neurons for research and serve as a platform for further tool development. PMID:24478690
Serotonergic neurons signal reward and punishment on multiple timescales
Cohen, Jeremiah Y; Amoroso, Mackenzie W; Uchida, Naoshige
2015-01-01
Serotonin's function in the brain is unclear. One challenge in testing the numerous hypotheses about serotonin's function has been observing the activity of identified serotonergic neurons in animals engaged in behavioral tasks. We recorded the activity of dorsal raphe neurons while mice experienced a task in which rewards and punishments varied across blocks of trials. We ‘tagged’ serotonergic neurons with the light-sensitive protein channelrhodopsin-2 and identified them based on their responses to light. We found three main features of serotonergic neuron activity: (1) a large fraction of serotonergic neurons modulated their tonic firing rates over the course of minutes during reward vs punishment blocks; (2) most were phasically excited by punishments; and (3) a subset was phasically excited by reward-predicting cues. By contrast, dopaminergic neurons did not show firing rate changes across blocks of trials. These results suggest that serotonergic neurons signal information about reward and punishment on multiple timescales. DOI: http://dx.doi.org/10.7554/eLife.06346.001 PMID:25714923
Panier, Thomas; Romano, Sebastián A; Olive, Raphaël; Pietri, Thomas; Sumbre, Germán; Candelier, Raphaël; Debrégeas, Georges
2013-01-01
The optical transparency and the small dimensions of zebrafish at the larval stage make it a vertebrate model of choice for brain-wide in-vivo functional imaging. However, current point-scanning imaging techniques, such as two-photon or confocal microscopy, impose a strong limit on acquisition speed which in turn sets the number of neurons that can be simultaneously recorded. At 5 Hz, this number is of the order of one thousand, i.e., approximately 1-2% of the brain. Here we demonstrate that this limitation can be greatly overcome by using Selective-plane Illumination Microscopy (SPIM). Zebrafish larvae expressing the genetically encoded calcium indicator GCaMP3 were illuminated with a scanned laser sheet and imaged with a camera whose optical axis was oriented orthogonally to the illumination plane. This optical sectioning approach was shown to permit functional imaging of a very large fraction of the brain volume of 5-9-day-old larvae with single- or near single-cell resolution. The spontaneous activity of up to 5,000 neurons was recorded at 20 Hz for 20-60 min. By rapidly scanning the specimen in the axial direction, the activity of 25,000 individual neurons from 5 different z-planes (approximately 30% of the entire brain) could be simultaneously monitored at 4 Hz. Compared to point-scanning techniques, this imaging strategy thus yields a ≃20-fold increase in data throughput (number of recorded neurons times acquisition rate) without compromising the signal-to-noise ratio (SNR). The extended field of view offered by the SPIM method allowed us to directly identify large scale ensembles of neurons, spanning several brain regions, that displayed correlated activity and were thus likely to participate in common neural processes. The benefits and limitations of SPIM for functional imaging in zebrafish as well as future developments are briefly discussed.
Dann, Benjamin; Michaels, Jonathan A; Schaffelhofer, Stefan; Scherberger, Hansjörg
2016-01-01
The functional communication of neurons in cortical networks underlies higher cognitive processes. Yet, little is known about the organization of the single neuron network or its relationship to the synchronization processes that are essential for its formation. Here, we show that the functional single neuron network of three fronto-parietal areas during active behavior of macaque monkeys is highly complex. The network was closely connected (small-world) and consisted of functional modules spanning these areas. Surprisingly, the importance of different neurons to the network was highly heterogeneous with a small number of neurons contributing strongly to the network function (hubs), which were in turn strongly inter-connected (rich-club). Examination of the network synchronization revealed that the identified rich-club consisted of neurons that were synchronized in the beta or low frequency range, whereas other neurons were mostly non-oscillatory synchronized. Therefore, oscillatory synchrony may be a central communication mechanism for highly organized functional spiking networks. DOI: http://dx.doi.org/10.7554/eLife.15719.001 PMID:27525488
Morra, Joshua T.; Glick, Stanley D.; Cheer, Joseph F.
2012-01-01
Patients suffering from amphetamine---induced psychosis display repetitive behaviors, partially alleviated by antipsychotics, which are reminiscent of rodent stereotypies. Due to recent evidence implicating endocannabinoid involvement in brain disorders, including psychosis, we studied the effects of endocannabinoid signaling on neuronal oscillations of rats exhibiting methamphetamine stereotypy. Neuronal network oscillations were recorded with multiple single electrode arrays aimed at the nucleus accumbens of freely moving rats. During the experiments, animals were dosed intravenously with the CB1 receptor antagonist rimonabant (0.3 mg/kg) or vehicle followed by an ascending dose regimen of methamphetamine (0.01, 0.1, 1, and 3 mg/kg; cumulative dosing). The effects of drug administration on stereotypy and local gamma oscillations were evaluated. Methamphetamine treatment significantly increased high frequency gamma oscillations (~ 80 Hz). Entrainment of a subpopulation of nucleus accumbens neurons to high frequency gamma was associated with stereotypy encoding in putative fast-spiking interneurons, but not in putative medium spiny neurons. The observed ability of methamphetamine to induce both stereotypy and high frequency gamma power was potently disrupted following CB1 receptor blockade. The present data suggest that CB1 receptor-dependent mechanisms are recruited by methamphetamine to modify striatal interneuron oscillations that accompany changes in psychomotor state, further supporting the link between endocannabinoids and schizophrenia spectrum disorders. PMID:22609048
Seol, Min; Kuner, Thomas
2015-12-01
The properties and molecular determinants of synaptic transmission at giant synapses connecting layer 5B (L5B) neurons of the somatosensory cortex (S1) with relay neurons of the posteriomedial nucleus (POm) of the thalamus have not been investigated in mice. We addressed this by using direct electrical stimulation of fluorescently labelled single corticothalamic terminals combined with molecular perturbations and whole-cell recordings from POm relay neurons. Consistent with their function as drivers, we found large-amplitude excitatory postsynaptic currents (EPSCs) and multiple postsynaptic action potentials triggered by a single presynaptic action potential. To study the molecular basis of these two features, ionotropic glutamate receptors and low voltage-gated T-type calcium channels were probed by virus-mediated genetic perturbation. Loss of GluA4 almost abolished the EPSC amplitude, strongly delaying the onset of action potential generation, but maintaining the number of action potentials generated per presynaptic action potential. In contrast, knockdown of the Cav 3.1 subunit abrogated the driver function of the synapse at a typical resting membrane potential of -70 mV. However, when depolarizing the membrane potential to -60 mV, the synapse relayed single action potentials. Hence, GluA4 subunits are required to produce an EPSC sufficiently large to trigger postsynaptic action potentials within a defined time window after the presynaptic action potential, while Cav 3.1 expression is essential to establish the driver function of L5B-POm synapses at hyperpolarized membrane potentials. © 2015 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Stimulus features coded by single neurons of a macaque body category selective patch.
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).
Chronic multiunit recordings in behaving animals: advantages and limitations.
Supèr, Hans; Roelfsema, Pieter R
2005-01-01
By simultaneous recording from neural responses at many different loci at the same time, we can understand the interaction between neurons, and thereby gain insight into the network properties of neural processing, instead of the functioning of individual neurons. Here we will discuss a method for recording in behaving animals that uses chronically implanted micro-electrodes that allow one to track neural responses over a long period of time. In a majority of cases, multiunit activity, which is the aggregate spiking activity of a number of neurons in the vicinity of an electrode tip, is recorded through these electrodes, and occasionally single neurons can be isolated. Here we compare the properties of multiunit responses to the responses of single neurons in the primary visual cortex. We also discuss the advantages and disadvantages of the multiunit signal as opposed to a signal of single neurons. We demonstrate that multiunit recording provides a reliable and useful technique in cases where the neurons at the electrodes have similar response properties. Multiunit recording is therefore especially valuable when task variables have an effect that is consistent across the population of neurons. In the primary visual cortex, this is the case for figure-ground segregation and visual attention. Multiunit recording also has clear advantages for cross-correlation analysis. We show that the cross-correlation function between multiunit signals gives a reliable estimate of the average single-unit cross-correlation function. By the use of multiunit recording, it becomes much easier to detect relatively weak interactions between neurons at different cortical locations.
Brain Connectivity as a DNA Sequencing Problem
NASA Astrophysics Data System (ADS)
Zador, Anthony
The mammalian cortex consists of millions or billions of neurons, each connected to thousands of other neurons. Traditional methods for determining the brain connectivity rely on microscopy to visualize neuronal connections, but such methods are slow, labor-intensive and often lack single neuron resolution. We have recently developed a new method, MAPseq, to recast the determination of brain wiring into a form that can exploit the tremendous recent advances in high-throughput DNA sequencing. DNA sequencing technology has outpaced even Moore's law, so that the cost of sequencing the human genome has dropped from a billion dollars in 2001 to below a thousand dollars today. MAPseq works by introducing random sequences of DNA-``barcodes''-to tag neurons uniquely. With MAPseq, we can determine the connectivity of over 50K single neurons in a single mouse cortex in about a week, an unprecedented throughput, ushering in the era of ``big data'' for brain wiring. We are now developing analytical tools and algorithms to make sense of these novel data sets.
Sahasranamam, Ajith; Vlachos, Ioannis; Aertsen, Ad; Kumar, Arvind
2016-01-01
Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relationship. Using this model, we show that the effect of single neuron spiking on the network dynamics is contingent on the network activity state. While spike bursting can both generate and disrupt oscillations, these patterns are ineffective in large regions of the network state space in changing the network activity qualitatively. Finally, we show that when single-neuron properties are made dependent on the population activity, a hysteresis like dynamics emerges. This novel phenomenon has important implications for determining the network response to time-varying inputs and for the network sensitivity at different operating points. PMID:27212008
Sahasranamam, Ajith; Vlachos, Ioannis; Aertsen, Ad; Kumar, Arvind
2016-05-23
Spike patterns are among the most common electrophysiological descriptors of neuron types. Surprisingly, it is not clear how the diversity in firing patterns of the neurons in a network affects its activity dynamics. Here, we introduce the state-dependent stochastic bursting neuron model allowing for a change in its firing patterns independent of changes in its input-output firing rate relationship. Using this model, we show that the effect of single neuron spiking on the network dynamics is contingent on the network activity state. While spike bursting can both generate and disrupt oscillations, these patterns are ineffective in large regions of the network state space in changing the network activity qualitatively. Finally, we show that when single-neuron properties are made dependent on the population activity, a hysteresis like dynamics emerges. This novel phenomenon has important implications for determining the network response to time-varying inputs and for the network sensitivity at different operating points.
Conway, Bevil R.; Tsao, Doris Y.
2009-01-01
Large islands of extrastriate cortex that are enriched for color-tuned neurons have recently been described in alert macaque using a combination of functional magnetic resonance imaging (fMRI) and single-unit recording. These millimeter-sized islands, dubbed “globs,” are scattered throughout the posterior inferior temporal cortex (PIT), a swath of brain anterior to area V3, including areas V4, PITd, and posterior TEO. We investigated the micro-organization of neurons within the globs. We used fMRI to identify the globs and then used MRI-guided microelectrodes to test the color properties of single glob cells. We used color stimuli that sample the CIELUV perceptual color space at regular intervals to test the color tuning of single units, and make two observations. First, color-tuned neurons of various color preferences were found within single globs. Second, adjacent glob cells tended to have the same color tuning, demonstrating that glob cells are clustered by color preference and suggesting that they are arranged in color columns. Neurons separated by 50 μm, measured parallel to the cortical sheet, had more similar color tuning than neurons separated by 100 μm, suggesting that the scale of the color columns is <100 μm. These results show that color-tuned neurons in PIT are organized by color preference on a finer scale than the scale of single globs. Moreover, the color preferences of neurons recorded sequentially along a given electrode penetration shifted gradually in many penetrations, suggesting that the color columns are arranged according to a chromotopic map reflecting perceptual color space. PMID:19805195
Ryu, Vitaly; Watts, Alan G; Xue, Bingzhong; Bartness, Timothy J
2017-03-01
The brain networks connected to the sympathetic motor and sensory innervations of brown (BAT) and white (WAT) adipose tissues were originally described using two transneuronally transported viruses: the retrogradely transported pseudorabies virus (PRV), and the anterogradely transported H129 strain of herpes simplex virus-1 (HSV-1 H129). Further complexity was added to this network organization when combined injections of PRV and HSV-1 H129 into either BAT or WAT of the same animal generated sets of coinfected neurons in the brain, spinal cord, and sympathetic and dorsal root ganglia. These neurons are well positioned to act as sensorimotor links in the feedback circuits that control each fat pad. We have now determined the extent of sensorimotor crosstalk between interscapular BAT (IBAT) and inguinal WAT (IWAT). PRV152 and HSV-1 H129 were each injected into IBAT or IWAT of the same animal: H129 into IBAT and PRV152 into IWAT. The reverse configuration was applied in a different set of animals. We found single-labeled neurons together with H129+PRV152 coinfected neurons in multiple brain sites, with lesser numbers in the sympathetic and dorsal root ganglia that innervate IBAT and IWAT. We propose that these coinfected neurons mediate sensory-sympathetic motor crosstalk between IBAT and IWAT. Comparing the relative numbers of coinfected neurons between the two injection configurations showed a bias toward IBAT-sensory and IWAT-sympathetic motor feedback loops. These coinfected neurons provide a neuroanatomical framework for functional interactions between IBAT thermogenesis and IWAT lipolysis that occurs with cold exposure, food restriction/deprivation, exercise, and more generally with alterations in adiposity. Copyright © 2017 the American Physiological Society.
Lu, Ting; Wade, Kirstie; Sanchez, Jason Tait
2017-01-01
ABSTRACT We have previously shown that late-developing avian nucleus magnocellularis (NM) neurons (embryonic [E] days 19–21) fire action potentials (APs) that resembles a band-pass filter in response to sinusoidal current injections of varying frequencies. NM neurons located in the mid- to high-frequency regions of the nucleus fire preferentially at 75 Hz, but only fire a single onset AP to frequency inputs greater than 200 Hz. Surprisingly, NM neurons do not fire APs to sinusoidal inputs less than 20 Hz regardless of the strength of the current injection. In the present study we evaluated intrinsic mechanisms that prevent AP generation to low frequency inputs. We constructed a computational model to simulate the frequency-firing patterns of NM neurons based on experimental data at both room and near physiologic temperatures. The results from our model confirm that the interaction among low- and high-voltage activated potassium channels (KLVA and KHVA, respectively) and voltage dependent sodium channels (NaV) give rise to the frequency-firing patterns observed in vitro. In particular, we evaluated the regulatory role of KLVA during low frequency sinusoidal stimulation. The model shows that, in response to low frequency stimuli, activation of large KLVA current counterbalances the slow-depolarizing current injection, likely permitting NaV closed-state inactivation and preventing the generation of APs. When the KLVA current density was reduced, the model neuron fired multiple APs per sinusoidal cycle, indicating that KLVA channels regulate low frequency AP firing of NM neurons. This intrinsic property of NM neurons may assist in optimizing response to different rates of synaptic inputs. PMID:28481659
Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering
2012-01-01
Background Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Results Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike sorting algorithms. Conclusions This new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity. This feature could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces. PMID:22871125
Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering.
Oliynyk, Andriy; Bonifazzi, Claudio; Montani, Fernando; Fadiga, Luciano
2012-08-08
Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike sorting algorithms. This new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity. This feature could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces.
Large-scale recording of neuronal ensembles.
Buzsáki, György
2004-05-01
How does the brain orchestrate perceptions, thoughts and actions from the spiking activity of its neurons? Early single-neuron recording research treated spike pattern variability as noise that needed to be averaged out to reveal the brain's representation of invariant input. Another view is that variability of spikes is centrally coordinated and that this brain-generated ensemble pattern in cortical structures is itself a potential source of cognition. Large-scale recordings from neuronal ensembles now offer the opportunity to test these competing theoretical frameworks. Currently, wire and micro-machined silicon electrode arrays can record from large numbers of neurons and monitor local neural circuits at work. Achieving the full potential of massively parallel neuronal recordings, however, will require further development of the neuron-electrode interface, automated and efficient spike-sorting algorithms for effective isolation and identification of single neurons, and new mathematical insights for the analysis of network properties.
Multiscale modeling of brain dynamics: from single neurons and networks to mathematical tools.
Siettos, Constantinos; Starke, Jens
2016-09-01
The extreme complexity of the brain naturally requires mathematical modeling approaches on a large variety of scales; the spectrum ranges from single neuron dynamics over the behavior of groups of neurons to neuronal network activity. Thus, the connection between the microscopic scale (single neuron activity) to macroscopic behavior (emergent behavior of the collective dynamics) and vice versa is a key to understand the brain in its complexity. In this work, we attempt a review of a wide range of approaches, ranging from the modeling of single neuron dynamics to machine learning. The models include biophysical as well as data-driven phenomenological models. The discussed models include Hodgkin-Huxley, FitzHugh-Nagumo, coupled oscillators (Kuramoto oscillators, Rössler oscillators, and the Hindmarsh-Rose neuron), Integrate and Fire, networks of neurons, and neural field equations. In addition to the mathematical models, important mathematical methods in multiscale modeling and reconstruction of the causal connectivity are sketched. The methods include linear and nonlinear tools from statistics, data analysis, and time series analysis up to differential equations, dynamical systems, and bifurcation theory, including Granger causal connectivity analysis, phase synchronization connectivity analysis, principal component analysis (PCA), independent component analysis (ICA), and manifold learning algorithms such as ISOMAP, and diffusion maps and equation-free techniques. WIREs Syst Biol Med 2016, 8:438-458. doi: 10.1002/wsbm.1348 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.
NASA Technical Reports Server (NTRS)
Shah, Ankoor S.; Knuth, Kevin H.; Truccolo, Wilson A.; Ding, Ming-Zhou; Bressler, Steven L.; Schroeder, Charles E.; Clancy, Daniel (Technical Monitor)
2002-01-01
Accurate measurement of single-trial responses is key to a definitive use of complex electromagnetic and hemodynamic measurements in the investigation of brain dynamics. We developed the multiple component, Event-Related Potential (mcERP) approach to single-trial response estimation. To improve our resolution of dynamic interactions between neuronal ensembles located in different layers within a cortical region and/or in different cortical regions. The mcERP model assets that multiple components defined as stereotypic waveforms comprise the stimulus-evoked response and that these components may vary in amplitude and latency from trial to trial. Maximum a posteriori (MAP) solutions for the model are obtained by iterating a set of equations derived from the posterior probability. Our first goal was to use the ANTWERP algorithm to analyze interactions (specifically latency and amplitude correlation) between responses in different layers within a cortical region. Thus, we evaluated the model by applying the algorithm to synthetic data containing two correlated local components and one independent far-field component. Three cases were considered: the local components were correlated by an interaction in their single-trial amplitudes, by an interaction in their single-trial latencies, or by an interaction in both amplitude and latency. We then analyzed the accuracy with which the algorithm estimated the component waveshapes and the single-trial parameters as a function of the linearity of each of these relationships. Extensions of these analyses to real data are discussed as well as ongoing work to incorporate more detailed prior information.
Cymerys, Joanna; Słońska, A; Tucholska, A; Golke, A; Chmielewska, A; Bańbura, M W
2018-01-01
Equine herpesvirus 1 (EHV-1), like other members of the Alphaherpesvirinae subfamily, is a neurotropic virus causing latent infections in the nervous system of the natural host. In the present study, we have investigated EHV-1 replication (wild-type Jan-E strain and Rac-H laboratory strain) during long-term infection and during the passages of the virus in cultured neurons. The studies were performed on primary murine neurons, which are an excellent in vitro model for studying neurotropism and neurovirulence of EHV-1. Using real-time cell growth analysis, we have demonstrated for the first time that primary murine neurons are able to survive long-term EHV-1 infection. Positive results of real-time PCR test indicated a high level of virus DNA in cultured neurons, and during long-term infection, these neurons were still able to transmit the virus to the other cells. We also compared the neurovirulence of Rac-H and Jan-E EHV-1 strains after multiple passages of these strains in neuron cell culture. The results showed that multiple passages of EHV-1 in neurons lead to the inhibition of viral replication as early as in the third passage. Interestingly, the inhibition of the EHV-1 replication occurred exclusively in neurons, because the equine dermal (ED) cells co-cultivated with neuroculture medium from the third passage showed the presence of large amount of viral DNA. In conclusion, our results showed that certain balance between EHV-1 and neurons has been established during in vitro infection allowing neurons to survive long-term infection.
Sakai, Atsushi; Saitow, Fumihito; Maruyama, Motoyo; Miyake, Noriko; Miyake, Koichi; Shimada, Takashi; Okada, Takashi; Suzuki, Hidenori
2017-01-01
miR-17-92 is a microRNA cluster with six distinct members. Here, we show that the miR-17-92 cluster and its individual members modulate chronic neuropathic pain. All cluster members are persistently upregulated in primary sensory neurons after nerve injury. Overexpression of miR-18a, miR-19a, miR-19b and miR-92a cluster members elicits mechanical allodynia in rats, while their blockade alleviates mechanical allodynia in a rat model of neuropathic pain. Plausible targets for the miR-17-92 cluster include genes encoding numerous voltage-gated potassium channels and their modulatory subunits. Single-cell analysis reveals extensive co-expression of miR-17-92 cluster and its predicted targets in primary sensory neurons. miR-17-92 downregulates the expression of potassium channels, and reduced outward potassium currents, in particular A-type currents. Combined application of potassium channel modulators synergistically alleviates mechanical allodynia induced by nerve injury or miR-17-92 overexpression. miR-17-92 cluster appears to cooperatively regulate the function of multiple voltage-gated potassium channel subunits, perpetuating mechanical allodynia. PMID:28677679
Acquisition of neural learning in cerebellum and cerebral cortex for smooth pursuit eye movements
Li, Jennifer X.; Medina, Javier F.; Frank, Loren M.; Lisberger, Stephen G.
2011-01-01
We have evaluated the emergence of neural learning in the frontal eye fields (FEFSEM) and the floccular complex of the cerebellum while monkeys learned a precisely-timed change in the direction of pursuit eye movement. For each neuron, we measured the time course of changes in neural response across a learning session that comprised at least 100 repetitions of an instructive change in target direction. In both areas, the average population learning curves tracked the behavioral changes with high fidelity, consistent with possible roles in driving learning. However, the learning curves of individual neurons sometimes bore little relation to the smooth, monotonic progression of behavioral learning. In the FEFSEM, neural learning was episodic. For individual neurons, learning appeared at different times during the learning session and sometimes disappeared by the end of the session. Different FEFSEM neurons expressed maximal learning at different times relative to the acquisition of behavioral learning. In the floccular complex, many Purkinje cells acquired learned simple-spike responses according to the same time course as behavioral learning and retained their learned responses throughout the learning session. A minority of Purkinje cells acquired learned responses late in the learning session, after behavioral learning had reached an asymptote. We conclude that learning in single neurons can follow a very different time course from behavioral learning. Both the FEFSEM and the floccular complex contain representations of multiple temporal components of learning, with different neurons contributing to learning at different times during the acquisition of a learned movement. PMID:21900551
Mandelblat-Cerf, Yael; Ramesh, Rohan N; Burgess, Christian R; Patella, Paola; Yang, Zongfang; Lowell, Bradford B; Andermann, Mark L
2015-01-01
Agouti-related-peptide (AgRP) neurons—interoceptive neurons in the arcuate nucleus of the hypothalamus (ARC)—are both necessary and sufficient for driving feeding behavior. To better understand the functional roles of AgRP neurons, we performed optetrode electrophysiological recordings from AgRP neurons in awake, behaving AgRP-IRES-Cre mice. In free-feeding mice, we observed a fivefold increase in AgRP neuron firing with mounting caloric deficit in afternoon vs morning recordings. In food-restricted mice, as food became available, AgRP neuron firing dropped, yet remained elevated as compared to firing in sated mice. The rapid drop in spiking activity of AgRP neurons at meal onset may reflect a termination of the drive to find food, while residual, persistent spiking may reflect a sustained drive to consume food. Moreover, nearby neurons inhibited by AgRP neuron photostimulation, likely including satiety-promoting pro-opiomelanocortin (POMC) neurons, demonstrated opposite changes in spiking. Finally, firing of ARC neurons was also rapidly modulated within seconds of individual licks for liquid food. These findings suggest novel roles for antagonistic AgRP and POMC neurons in the regulation of feeding behaviors across multiple timescales. DOI: http://dx.doi.org/10.7554/eLife.07122.001 PMID:26159614
Scheff, N N; Yilmaz, E; Gold, M S
2014-01-01
The Na+–Ca2+ exchanger (NCX) appears to play an important role in the regulation of the high K+-evoked Ca2+ transient in putative nociceptive dorsal root ganglion (DRG) neurons. The purpose of the present study was to (1) characterize the properties of NCX activity in subpopulations of DRG neurons, (2) identify the isoform(s) underlying NCX activity, and (3) begin to assess the function of the isoform(s) in vivo. In retrogradely labelled neurons from the glabrous skin of adult male Sprague–Dawley rats, NCX activity, as assessed with fura-2-based microfluorimetry, was only detected in putative nociceptive IB4+ neurons. There were two modes of NCX activity: one was evoked in response to relatively large and long lasting (∼325 nm for >12 s) increases in the concentration of intracellular Ca2+ ([Ca2+]i), and a second was active at resting [Ca2+]i > ∼150 nm. There also were two modes of evoked activity: one that decayed relatively rapidly (<5 min) and a second that persisted (>10 min). Whereas mRNA encoding all three NCX isoforms (NCX1–3) was detected in putative nociceptive cutaneous neurons with single cell PCR, pharmacological analysis and small interfering RNA (siRNA) knockdown of each isoform in vivo suggested that NCX2 and 3 were responsible for NCX activity. Western blot analyses suggested that NCX isoforms were differentially distributed within sensory neurons. Functional assays of excitability, action potential propagation, and nociceptive behaviour suggest NCX activity has little influence on excitability per se, but instead influences axonal conduction velocity, resting membrane potential, and nociceptive threshold. Together these results indicate that the function of NCX in the regulation of [Ca2+]i in putative nociceptive neurons may be unique relative to other cells in which these exchanger isoforms have been characterized and it has the potential to influence sensory neuron properties at multiple levels. PMID:25239455
Engel, Tobias; Plesnila, Nikolaus; Prehn, Jochen H M; Henshall, David C
2011-01-01
The Bcl-2 homology (BH) domain 3-only proteins are a proapoptotic subgroup of the Bcl-2 gene family, which regulate cell death via effects on mitochondria. The BH3-only proteins react to various cell stressors and promote cell death by binding and inactivating antiapoptotic Bcl-2 family members and direct activation of proapoptotic multi-BH domain proteins such as Bax. Here, we review the in vivo evidence for their involvement in the pathophysiology of status epilepticus and contrast it to ischemia and traumatic brain injury. Seizures in rodents activate three potent proapoptotic BH3-only proteins: Bid, Bim, and Puma. Analysis of damage after seizures in mice singly deficient for each BH3-only protein supports a causal role for Puma and to a lesser extent Bim but, surprisingly, not Bid. In ischemia and trauma, where core aspects of the pathophysiology of cell death overlap, multiple BH3-only proteins are also activated and Bid has been shown to be required for neuronal death. The findings suggest that while each neurologic insult activates multiple BH3-only proteins, there may be specificity in their functional contribution. Future challenges include evaluating the remaining BH3-only proteins, explaining different causal contributions, and, if possible, exploring neurologic outcomes in mouse models deficient for multiple BH3-only proteins. PMID:21364604
Costa, Marta; Manton, James D; Ostrovsky, Aaron D; Prohaska, Steffen; Jefferis, Gregory S X E
2016-07-20
Neural circuit mapping is generating datasets of tens of thousands of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches. We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1,052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types, including searching neurons against transgene expression patterns. Finally, we show that NBLAST is effective with data from other invertebrates and zebrafish. VIDEO ABSTRACT. Copyright © 2016 MRC Laboratory of Molecular Biology. Published by Elsevier Inc. All rights reserved.
Hierarchical Address Event Routing for Reconfigurable Large-Scale Neuromorphic Systems.
Park, Jongkil; Yu, Theodore; Joshi, Siddharth; Maier, Christoph; Cauwenberghs, Gert
2017-10-01
We present a hierarchical address-event routing (HiAER) architecture for scalable communication of neural and synaptic spike events between neuromorphic processors, implemented with five Xilinx Spartan-6 field-programmable gate arrays and four custom analog neuromophic integrated circuits serving 262k neurons and 262M synapses. The architecture extends the single-bus address-event representation protocol to a hierarchy of multiple nested buses, routing events across increasing scales of spatial distance. The HiAER protocol provides individually programmable axonal delay in addition to strength for each synapse, lending itself toward biologically plausible neural network architectures, and scales across a range of hierarchies suitable for multichip and multiboard systems in reconfigurable large-scale neuromorphic systems. We show approximately linear scaling of net global synaptic event throughput with number of routing nodes in the network, at 3.6×10 7 synaptic events per second per 16k-neuron node in the hierarchy.
Signaling of the strongest stimulus in the owl optic tectum
Mysore, Shreesh P.; Asadollahi, Ali; Knudsen, Eric I.
2011-01-01
Essential to the selection of the next target for gaze or attention is the ability to compare the strengths of multiple competing stimuli (bottom-up information), and to signal the strongest one. Though the optic tectum (OT) has been causally implicated in stimulus selection, how it computes the strongest stimulus is unknown. Here, we demonstrate that OT neurons in the barn owl systematically encode the relative strengths of simultaneously occurring stimuli independently of sensory modality. Moreover, special “switch-like” responses of a subset of neurons abruptly increase when the stimulus inside their receptive field becomes the strongest one. Such responses are not predicted by responses to single stimuli and, indeed, are eliminated in the absence of competitive interactions. We demonstrate that this sensory transformation substantially boosts the representation of the strongest stimulus by creating a binary discrimination signal, thereby setting the stage for potential winner-take-all target selection for gaze and attention. PMID:21471353
Emotion, Cognition, and Mental State Representation in Amygdala and Prefrontal Cortex
Salzman, C. Daniel; Fusi, Stefano
2011-01-01
Neuroscientists have often described cognition and emotion as separable processes implemented by different regions of the brain, such as the amygdala for emotion and the prefrontal cortex for cognition. In this framework, functional interactions between the amygdala and prefrontal cortex mediate emotional influences on cognitive processes such as decision-making, as well as the cognitive regulation of emotion. However, neurons in these structures often have entangled representations, whereby single neurons encode multiple cognitive and emotional variables. Here we review studies using anatomical, lesion, and neurophysiological approaches to investigate the representation and utilization of cognitive and emotional parameters. We propose that these mental state parameters are inextricably linked and represented in dynamic neural networks composed of interconnected prefrontal and limbic brain structures. Future theoretical and experimental work is required to understand how these mental state representations form and how shifts between mental states occur, a critical feature of adaptive cognitive and emotional behavior. PMID:20331363
Jády, Attila Gy; Nagy, Ádám M; Kőhidi, Tímea; Ferenczi, Szilamér; Tretter, László; Madarász, Emília
2016-07-01
While it is evident that the metabolic machinery of stem cells should be fairly different from that of differentiated neurons, the basic energy production pathways in neural stem cells (NSCs) or in neurons are far from clear. Using the model of in vitro neuron production by NE-4C NSCs, this study focused on the metabolic changes taking place during the in vitro neuronal differentiation. O2 consumption, H(+) production, and metabolic responses to single metabolites were measured in cultures of NSCs and in their neuronal derivatives, as well as in primary neuronal and astroglial cultures. In metabolite-free solutions, NSCs consumed little O2 and displayed a higher level of mitochondrial proton leak than neurons. In stem cells, glycolysis was the main source of energy for the survival of a 2.5-h period of metabolite deprivation. In contrast, stem cell-derived or primary neurons sustained a high-level oxidative phosphorylation during metabolite deprivation, indicating the consumption of own cellular material for energy production. The stem cells increased O2 consumption and mitochondrial ATP production in response to single metabolites (with the exception of glucose), showing rapid adaptation of the metabolic machinery to the available resources. In contrast, single metabolites did not increase the O2 consumption of neurons or astrocytes. In "starving" neurons, neither lactate nor pyruvate was utilized for mitochondrial ATP production. Gene expression studies also suggested that aerobic glycolysis and rapid metabolic adaptation characterize the NE-4C NSCs, while autophagy and alternative glucose utilization play important roles in the metabolism of stem cell-derived neurons.
Marin-Valencia, Isaac; Hooshyar, M Ali; Pichumani, Kumar; Sherry, A Dean; Malloy, Craig R
2015-01-01
The (13) C-labeling patterns in glutamate and glutamine from brain tissue are quite different after infusion of a mixture of (13) C-enriched glucose and acetate. Two processes contribute to this observation, oxidation of acetate by astrocytes but not neurons, and preferential incorporation of α-ketoglutarate into glutamate in neurons, and incorporation of α-ketoglutarate into glutamine in astrocytes. The acetate:glucose ratio, introduced previously for analysis of a single (13) C NMR spectrum, provides a useful index of acetate and glucose oxidation in the brain tissue. However, quantitation of relative substrate oxidation at the cell compartment level has not been reported. A simple mathematical method is presented to quantify the ratio of acetate-to-glucose oxidation in astrocytes, based on the standard assumption that neurons do not oxidize acetate. Mice were infused with [1,2-(13) C]acetate and [1,6-(13) C]glucose, and proton decoupled (13) C NMR spectra of cortex extracts were acquired. A fit of those spectra to the model indicated that (13) C-labeled acetate and glucose contributed approximately equally to acetyl-CoA (0.96) in astrocytes. As this method relies on a single (13) C NMR spectrum, it can be readily applied to multiple physiologic and pathologic conditions. Differences in (13) C labeling of brain glutamate and glutamine have been attributed to metabolic compartmentation. The acetate:glucose ratio, introduced for description of a (13) C NMR (nuclear magnetic resonance) spectrum, is an index of glucose and acetate oxidation in brain tissue. A simple mathematical method is presented to quantify the ratio of acetate-to-glucose oxidation in astrocytes from a single NMR spectrum. As kinetic analysis is not required, the method is readily applicable to analysis of tissue extracts. α-KG = alpha-ketoglutarate; CAC = citric acid cycle; GLN = glutamine; GLU = glutamate. © 2014 International Society for Neurochemistry.
Moro, Nobuhiro; Ghavim, Sima; Harris, Neil G.; Hovda, David A.; Sutton, Richard L.
2013-01-01
Clinical studies have indicated an association between acute hyperglycemia and poor outcomes in patients with traumatic brain injury (TBI), although optimal blood glucose levels needed to maximize outcomes for these patients’ remains under investigation. Previous results from experimental animal models suggest that post-TBI hyperglycemia may be harmful, neutral, or beneficial. The current studies determined the effects of single or multiple episodes of acute hyperglycemia on cerebral glucose metabolism and neuronal injury in a rodent model of unilateral controlled cortical impact (CCI) injury. In Experiment 1, a single episode of hyperglycemia (50% glucose at 2 g/kg, i.p.) initiated immediately after CCI was found to significantly attenuate a TBI-induced depression of glucose metabolism in cerebral cortex (4 of 6 regions) and subcortical regions (2 of 7) as well as to significantly reduce the number of dead/dying neurons in cortex and hippocampus at 24 h post-CCI. Experiment 2 examined effects of more prolonged and intermittent hyperglycemia induced by glucose administrations (2 g/kg, i.p.) at 0, 1, 3 and 6 h post-CCI. The latter study also found significantly improved cerebral metabolism (in 3 of 6 cortical and 3 of 7 subcortical regions) and significant neuroprotection in cortex and hippocampus 1 day after CCI and glucose administration. These results indicate that acute episodes of post-TBI hyperglycemia can be beneficial and are consistent with other recent studies showing benefits of providing exogenous energy substrates during periods of increased cerebral metabolic demand. PMID:23994447
Neurophysiological and Computational Principles of Cortical Rhythms in Cognition
Wang, Xiao-Jing
2010-01-01
Synchronous rhythms represent a core mechanism for sculpting temporal coordination of neural activity in the brainwide network. This review focuses on oscillations in the cerebral cortex that occur during cognition, in alert behaving conditions. Over the last two decades, experimental and modeling work has made great strides in elucidating the detailed cellular and circuit basis of these rhythms, particularly gamma and theta rhythms. The underlying physiological mechanisms are diverse (ranging from resonance and pacemaker properties of single cells, to multiple scenarios for population synchronization and wave propagation), but also exhibit unifying principles. A major conceptual advance was the realization that synaptic inhibition plays a fundamental role in rhythmogenesis, either in an interneuronal network or in a recipropocal excitatory-inhibitory loop. Computational functions of synchronous oscillations in cognition are still a matter of debate among systems neuroscientists, in part because the notion of regular oscillation seems to contradict the common observation that spiking discharges of individual neurons in the cortex are highly stochastic and far from being clock-like. However, recent findings have led to a framework that goes beyond the conventional theory of coupled oscillators, and reconciles the apparent dichotomy between irregular single neuron activity and field potential oscillations. From this perspective, a plethora of studies will be reviewed on the involvement of long-distance neuronal coherence in cognitive functions such as multisensory integration, working memory and selective attention. Finally, implications of abnormal neural synchronization are discussed as they relate to mental disorders like schizophrenia and autism. PMID:20664082
Sensation in a single neuron pair represses male behavior in hermaphrodites
White, Jamie Q.; Jorgensen, Erik M.
2012-01-01
Summary Pheromones elicit innate sex-specific mating behaviors in many species. We demonstrate that in C. elegans, male-specific sexual attraction behavior is programmed in both sexes but repressed in hermaphrodites. Repression requires a single sensory neuron pair, the ASIs. To represses attraction in adults, the ASIs must be present, active, and capable of sensing the environment during development. The ASIs release TGF-β, and ASI function can be bypassed by experimental activation of TGF-β signaling. Sexual attraction in de-repressed hermaphrodites requires the same sensory neurons as in males. The sexual identity of both these sensory neurons and a distinct subset of interneurons must be male to relieve repression and release attraction. TGF-β may therefore act to change connections between sensory- and interneurons during development to engage repression. Thus, sensation in a single sensory neuron pair during development reprograms a common neural circuit from male to female behavior. PMID:22920252
NASA Astrophysics Data System (ADS)
Zhang, Xianxia; Wang, Jian; Qin, Tinggao
2003-09-01
Intelligent control algorithms are introduced into the control system of temperature and humidity. A multi-mode control algorithm of PI-Single Neuron is proposed for single loop control of temperature and humidity. In order to remove the coupling between temperature and humidity, a new decoupling method is presented, which is called fuzzy decoupling. The decoupling is achieved by using a fuzzy controller that dynamically modifies the static decoupling coefficient. Taking the control algorithm of PI-Single Neuron as the single loop control of temperature and humidity, the paper provides the simulated output response curves with no decoupling control, static decoupling control and fuzzy decoupling control. Those control algorithms are easily implemented in singlechip-based hardware systems.
Hira, Riichiro; Ohkubo, Fuki; Masamizu, Yoshito; Ohkura, Masamichi; Nakai, Junichi; Okada, Takashi; Matsuzaki, Masanori
2014-11-24
Animals rapidly adapt to environmental change. To reveal how cortical microcircuits are rapidly reorganized when an animal recognizes novel reward contingency, we conduct two-photon calcium imaging of layer 2/3 motor cortex neurons in mice and simultaneously reinforce the activity of a single cortical neuron with water delivery. Here we show that when the target neuron is not relevant to a pre-trained forelimb movement, the mouse increases the target neuron activity and the number of rewards delivered during 15-min operant conditioning without changing forelimb movement behaviour. The reinforcement bidirectionally modulates the activity of subsets of non-target neurons, independent of distance from the target neuron. The bidirectional modulation depends on the relative timing between the reward delivery and the neuronal activity, and is recreated by pairing reward delivery and photoactivation of a subset of neurons. Reward-timing-dependent bidirectional modulation may be one of the fundamental processes in microcircuit reorganization for rapid adaptation.
Sieger, Tomáš; Serranová, Tereza; Růžička, Filip; Vostatek, Pavel; Wild, Jiří; Štastná, Daniela; Bonnet, Cecilia; Novák, Daniel; Růžička, Evžen; Urgošík, Dušan; Jech, Robert
2015-03-10
Both animal studies and studies using deep brain stimulation in humans have demonstrated the involvement of the subthalamic nucleus (STN) in motivational and emotional processes; however, participation of this nucleus in processing human emotion has not been investigated directly at the single-neuron level. We analyzed the relationship between the neuronal firing from intraoperative microrecordings from the STN during affective picture presentation in patients with Parkinson's disease (PD) and the affective ratings of emotional valence and arousal performed subsequently. We observed that 17% of neurons responded to emotional valence and arousal of visual stimuli according to individual ratings. The activity of some neurons was related to emotional valence, whereas different neurons responded to arousal. In addition, 14% of neurons responded to visual stimuli. Our results suggest the existence of neurons involved in processing or transmission of visual and emotional information in the human STN, and provide evidence of separate processing of the affective dimensions of valence and arousal at the level of single neurons as well.
A survey of human brain transcriptome diversity at the single cell level.
Darmanis, Spyros; Sloan, Steven A; Zhang, Ye; Enge, Martin; Caneda, Christine; Shuer, Lawrence M; Hayden Gephart, Melanie G; Barres, Ben A; Quake, Stephen R
2015-06-09
The human brain is a tissue of vast complexity in terms of the cell types it comprises. Conventional approaches to classifying cell types in the human brain at single cell resolution have been limited to exploring relatively few markers and therefore have provided a limited molecular characterization of any given cell type. We used single cell RNA sequencing on 466 cells to capture the cellular complexity of the adult and fetal human brain at a whole transcriptome level. Healthy adult temporal lobe tissue was obtained during surgical procedures where otherwise normal tissue was removed to gain access to deeper hippocampal pathology in patients with medical refractory seizures. We were able to classify individual cells into all of the major neuronal, glial, and vascular cell types in the brain. We were able to divide neurons into individual communities and show that these communities preserve the categorization of interneuron subtypes that is typically observed with the use of classic interneuron markers. We then used single cell RNA sequencing on fetal human cortical neurons to identify genes that are differentially expressed between fetal and adult neurons and those genes that display an expression gradient that reflects the transition between replicating and quiescent fetal neuronal populations. Finally, we observed the expression of major histocompatibility complex type I genes in a subset of adult neurons, but not fetal neurons. The work presented here demonstrates the applicability of single cell RNA sequencing on the study of the adult human brain and constitutes a first step toward a comprehensive cellular atlas of the human brain.
Braeken, Dries; Huys, Roeland; Loo, Josine; Bartic, Carmen; Borghs, Gustaaf; Callewaert, Geert; Eberle, Wolfgang
2010-12-15
The investigation of single-neuron parameters is of great interest because many aspects in the behavior and communication of neuronal networks still remain unidentified. However, the present available techniques for single-cell measurements are slow and do not allow for a high-throughput approach. We present here a CMOS compatible microelectrode array with 84 electrodes (with diameters ranging from 1.2 to 4.2 μm) that are smaller than the size of cell, thereby supporting single-cell addressability. We show controllable electroporation of a single cell by an underlying electrode while monitoring changes in the intracellular membrane potential. Further, by applying a localized electrical field between two electrodes close to a neuron while recording changes in the intracellular calcium concentration, we demonstrate activation of a single cell (∼270%, DF/F(0)), followed by a network response of the neighboring cells. The technology can be easily scaled up to larger electrode arrays (theoretically up to 137,000 electrodes/mm(2)) with active CMOS electronics integration able to perform high-throughput measurements on single cells. Copyright © 2010 Elsevier B.V. All rights reserved.
Rule, Michael E.; Vargas-Irwin, Carlos E.; Donoghue, John P.
2017-01-01
Determining the relationship between single-neuron spiking and transient (20 Hz) β-local field potential (β-LFP) oscillations is an important step for understanding the role of these oscillations in motor cortex. We show that whereas motor cortex firing rates and beta spiking rhythmicity remain sustained during steady-state movement preparation periods, β-LFP oscillations emerge, in contrast, as short transient events. Single-neuron mean firing rates within and outside transient β-LFP events showed no differences, and no consistent correlation was found between the beta oscillation amplitude and firing rates, as was the case for movement- and visual cue-related β-LFP suppression. Importantly, well-isolated single units featuring beta-rhythmic spiking (43%, 125/292) showed no apparent or only weak phase coupling with the transient β-LFP oscillations. Similar results were obtained for the population spiking. These findings were common in triple microelectrode array recordings from primary motor (M1), ventral (PMv), and dorsal premotor (PMd) cortices in nonhuman primates during movement preparation. Although beta spiking rhythmicity indicates strong membrane potential fluctuations in the beta band, it does not imply strong phase coupling with β-LFP oscillations. The observed dissociation points to two different sources of variation in motor cortex β-LFPs: one that impacts single-neuron spiking dynamics and another related to the generation of mesoscopic β-LFP signals. Furthermore, our findings indicate that rhythmic spiking and diverse neuronal firing rates, which encode planned actions during movement preparation, may naturally limit the ability of different neuronal populations to strongly phase-couple to a single dominant oscillation frequency, leading to the observed spiking and β-LFP dissociation. NEW & NOTEWORTHY We show that whereas motor cortex spiking rates and beta (~20 Hz) spiking rhythmicity remain sustained during steady-state movement preparation periods, β-local field potential (β-LFP) oscillations emerge, in contrast, as transient events. Furthermore, the β-LFP phase at which neurons spike drifts: phase coupling is typically weak or absent. This dissociation points to two sources of variation in the level of motor cortex beta: one that impacts single-neuron spiking and another related to the generation of measured mesoscopic β-LFPs. PMID:28100654
Correlation between diffusion kurtosis and NODDI metrics in neonates and young children
NASA Astrophysics Data System (ADS)
Ahmed, Shaheen; Wang, Zhiyue J.; Chia, Jonathan M.; Rollins, Nancy K.
2016-03-01
Diffusion Tensor Imaging (DTI) uses single shell gradient encoding scheme for studying brain tissue diffusion. NODDI (Neurite Orientation Dispersion and Density Imaging) incorporates a gradient scheme with multiple b-values which is used to characterize neurite density and coherence of neuron fiber orientations. Similarly, the diffusion kurtosis imaging also uses a multiple shell scheme to quantify non-Gaussian diffusion but does not assume a tissue model like NODDI. In this study we investigate the connection between metrics derived by NODDI and DKI in children with ages from 46 weeks to 6 years. We correlate the NODDI metrics and Kurtosis measures from the same ROIs in multiple brain regions. We compare the range of these metrics between neonates (46 - 47 weeks), infants (2 -10 months) and young children (2 - 6 years). We find that there exists strong correlation between neurite density vs. mean kurtosis, orientation dispersion vs. kurtosis fractional anisotropy (FA) in pediatric brain imaging.
From a meso- to micro-scale connectome: array tomography and mGRASP
Rah, Jong-Cheol; Feng, Linqing; Druckmann, Shaul; Lee, Hojin; Kim, Jinhyun
2015-01-01
Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors. PMID:26089781
Thomsen, Gretchen M.
2015-01-01
Abstract Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease in which upper and lower motor neurons degenerate, leading to muscle atrophy, paralysis, and death within 3 to 5 years of onset. While a small percentage of ALS cases are genetically linked, the majority are sporadic with unknown origin. Currently, etiological links are associated with disease onset without mechanistic understanding. Of all the putative risk factors, however, head trauma has emerged as a consistent candidate for initiating the molecular cascades of ALS. Here, we test the hypothesis that traumatic brain injury (TBI) in the SOD1 G93A transgenic rat model of ALS leads to early disease onset and shortened lifespan. We demonstrate, however, that a one-time acute focal injury caused by controlled cortical impact does not affect disease onset or survival. Establishing the negligible involvement of a single acute focal brain injury in an ALS rat model increases the current understanding of the disease. Critically, untangling a single focal TBI from multiple mild injuries provides a rationale for scientists and physicians to increase focus on repeat injuries to hopefully pinpoint a contributing cause of ALS. PMID:26464984
Ensemble stacking mitigates biases in inference of synaptic connectivity.
Chambers, Brendan; Levy, Maayan; Dechery, Joseph B; MacLean, Jason N
2018-01-01
A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches.
A Probabilistic Palimpsest Model of Visual Short-term Memory
Matthey, Loic; Bays, Paul M.; Dayan, Peter
2015-01-01
Working memory plays a key role in cognition, and yet its mechanisms remain much debated. Human performance on memory tasks is severely limited; however, the two major classes of theory explaining the limits leave open questions about key issues such as how multiple simultaneously-represented items can be distinguished. We propose a palimpsest model, with the occurrent activity of a single population of neurons coding for several multi-featured items. Using a probabilistic approach to storage and recall, we show how this model can account for many qualitative aspects of existing experimental data. In our account, the underlying nature of a memory item depends entirely on the characteristics of the population representation, and we provide analytical and numerical insights into critical issues such as multiplicity and binding. We consider representations in which information about individual feature values is partially separate from the information about binding that creates single items out of multiple features. An appropriate balance between these two types of information is required to capture fully the different types of error seen in human experimental data. Our model provides the first principled account of misbinding errors. We also suggest a specific set of stimuli designed to elucidate the representations that subjects actually employ. PMID:25611204
A probabilistic palimpsest model of visual short-term memory.
Matthey, Loic; Bays, Paul M; Dayan, Peter
2015-01-01
Working memory plays a key role in cognition, and yet its mechanisms remain much debated. Human performance on memory tasks is severely limited; however, the two major classes of theory explaining the limits leave open questions about key issues such as how multiple simultaneously-represented items can be distinguished. We propose a palimpsest model, with the occurrent activity of a single population of neurons coding for several multi-featured items. Using a probabilistic approach to storage and recall, we show how this model can account for many qualitative aspects of existing experimental data. In our account, the underlying nature of a memory item depends entirely on the characteristics of the population representation, and we provide analytical and numerical insights into critical issues such as multiplicity and binding. We consider representations in which information about individual feature values is partially separate from the information about binding that creates single items out of multiple features. An appropriate balance between these two types of information is required to capture fully the different types of error seen in human experimental data. Our model provides the first principled account of misbinding errors. We also suggest a specific set of stimuli designed to elucidate the representations that subjects actually employ.
Single neuron computation: from dynamical system to feature detector.
Hong, Sungho; Agüera y Arcas, Blaise; Fairhall, Adrienne L
2007-12-01
White noise methods are a powerful tool for characterizing the computation performed by neural systems. These methods allow one to identify the feature or features that a neural system extracts from a complex input and to determine how these features are combined to drive the system's spiking response. These methods have also been applied to characterize the input-output relations of single neurons driven by synaptic inputs, simulated by direct current injection. To interpret the results of white noise analysis of single neurons, we would like to understand how the obtained feature space of a single neuron maps onto the biophysical properties of the membrane, in particular, the dynamics of ion channels. Here, through analysis of a simple dynamical model neuron, we draw explicit connections between the output of a white noise analysis and the underlying dynamical system. We find that under certain assumptions, the form of the relevant features is well defined by the parameters of the dynamical system. Further, we show that under some conditions, the feature space is spanned by the spike-triggered average and its successive order time derivatives.
A synaptic organizing principle for cortical neuronal groups
Perin, Rodrigo; Berger, Thomas K.; Markram, Henry
2011-01-01
Neuronal circuitry is often considered a clean slate that can be dynamically and arbitrarily molded by experience. However, when we investigated synaptic connectivity in groups of pyramidal neurons in the neocortex, we found that both connectivity and synaptic weights were surprisingly predictable. Synaptic weights follow very closely the number of connections in a group of neurons, saturating after only 20% of possible connections are formed between neurons in a group. When we examined the network topology of connectivity between neurons, we found that the neurons cluster into small world networks that are not scale-free, with less than 2 degrees of separation. We found a simple clustering rule where connectivity is directly proportional to the number of common neighbors, which accounts for these small world networks and accurately predicts the connection probability between any two neurons. This pyramidal neuron network clusters into multiple groups of a few dozen neurons each. The neurons composing each group are surprisingly distributed, typically more than 100 μm apart, allowing for multiple groups to be interlaced in the same space. In summary, we discovered a synaptic organizing principle that groups neurons in a manner that is common across animals and hence, independent of individual experiences. We speculate that these elementary neuronal groups are prescribed Lego-like building blocks of perception and that acquired memory relies more on combining these elementary assemblies into higher-order constructs. PMID:21383177
Lee, Gyunghee; Sehgal, Ritika; Wang, Zixing; Nair, Sudershana; Kikuno, Keiko; Chen, Chun-Hong; Hay, Bruce; Park, Jae H
2013-03-15
In Drosophila melanogaster, combinatorial activities of four death genes, head involution defective (hid), reaper (rpr), grim, and sickle (skl), have been known to play crucial roles in the developmentally regulated programmed cell death (PCD) of various tissues. However, different expression patterns of the death genes also suggest distinct functions played by each. During early metamorphosis, a great number of larval neurons unfit for adult life style are removed by PCD. Among them are eight pairs of corazonin-expressing larval peptidergic neurons in the ventral nerve cord (vCrz). To reveal death genes responsible for the PCD of vCrz neurons, we examined extant and recently available mutations as well as RNA interference that disrupt functions of single or multiple death genes. We found grim as a chief proapoptotic gene and skl and rpr as minor ones. The function of grim is also required for PCD of the mitotic sibling cells of the vCrz neuronal precursors (EW3-sib) during embryonic neurogenesis. An intergenic region between grim and rpr, which, it has been suggested, may enhance expression of three death genes in embryonic neuroblasts, appears to play a role for the vCrz PCD, but not for the EW3-sib cell death. The death of vCrz neurons and EW3-sib is triggered by ecdysone and the Notch signaling pathway, respectively, suggesting distinct regulatory mechanisms of grim expression in a cell- and developmental stage-specific manner.
Mitsui, Shinichi; Yamaguchi, Nozomi; Osako, Yoji; Yuri, Kazunari
2007-03-09
Motopsin (PRSS12) is a mosaic protease expressed in the central nervous system. Truncation of the human motopsin gene causes nonsyndromic mental retardation. Understanding the enzymatic properties and localization of motopsin protein in the central nervous system will help identify the molecular mechanism by which the loss of motopsin function causes mental retardation. Recombinant motopsin showed amidolytic activity against the synthetic substrate benzyloxycarbonyl-l-phenylalanyl-l-arginine 4-methyl-coumaryl-7-amide. Motopsin activated the single-chain tissue plasminogen activator precursor and exhibited gelatinolytic activity. This enzymatic activity was inhibited by typical serine protease inhibitors such as aprotinin, leupeptin, and (4-amidinophenyl) methanesulfonyl fluoride. Immunocytochemistry using anti-motopsin IgG revealed that both human and mouse motopsin proteins were distributed in discrete puncta along the dendrites and soma as well as axons in cultured hippocampal neurons. In the limbic system, including the cingulate and hippocampal pyramidal neurons and piriform cortex, high level of motopsin protein was expressed at postnatal day 10, but a very low level at 10-week-old mice. Motopsin and tissue plasminogen activator were co-expressed in the cingulate pyramidal neurons at postnatal day 10 and were distributed along dendrites of cultured pyramidal neurons. In cranial nuclei, a moderate level of motopsin protein was detected independently on the developmental stage. Our results suggest that motopsin has multiple functions, such as axon outgrowth, arranging perineuronal environment, and maintaining neuronal plasticity, partly in coordination with other proteases including tissue plasminogen activator.
Sun, Ying-Jie; Nishikawa, Kaori; Yuda, Hideki; Wang, Yu-Lai; Osaka, Hitoshi; Fukazawa, Nobuna; Naito, Akira; Kudo, Yoshihisa; Wada, Keiji; Aoki, Shunsuke
2006-09-01
With DNA microarrays, we identified a gene, termed Solo, that is downregulated in the cerebellum of Purkinje cell degeneration mutant mice. Solo is a mouse homologue of rat Trio8-one of multiple Trio isoforms recently identified in rat brain. Solo/Trio8 contains N-terminal sec14-like and spectrin-like repeat domains followed by a single guanine nucleotide exchange factor 1 (GEF1) domain, but it lacks the C-terminal GEF2, immunoglobulin-like, and kinase domains that are typical of Trio. Solo/Trio8 is predominantly expressed in Purkinje neurons of the mouse brain, and expression begins following birth and increases during Purkinje neuron maturation. We identified a novel C-terminal membrane-anchoring domain in Solo/Trio8 that is required for enhanced green fluorescent protein-Solo/Trio8 localization to early endosomes (positive for both early-endosome antigen 1 [EEA1] and Rab5) in COS-7 cells and primary cultured neurons. Solo/Trio8 overexpression in COS-7 cells augmented the EEA1-positive early-endosome pool, and this effect was abolished via mutation and inactivation of the GEF domain or deletion of the C-terminal membrane-anchoring domain. Moreover, primary cultured neurons transfected with Solo/Trio8 showed increased neurite elongation that was dependent on these domains. These results suggest that Solo/Trio8 acts as an early-endosome-specific upstream activator of Rho family GTPases for neurite elongation of developing Purkinje neurons.
Stimulus features coded by single neurons of a macaque body category selective patch
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
Relating normalization to neuronal populations across cortical areas.
Ruff, Douglas A; Alberts, Joshua J; Cohen, Marlene R
2016-09-01
Normalization, which divisively scales neuronal responses to multiple stimuli, is thought to underlie many sensory, motor, and cognitive processes. In every study where it has been investigated, neurons measured in the same brain area under identical conditions exhibit a range of normalization, ranging from suppression by nonpreferred stimuli (strong normalization) to additive responses to combinations of stimuli (no normalization). Normalization has been hypothesized to arise from interactions between neuronal populations, either in the same or different brain areas, but current models of normalization are not mechanistic and focus on trial-averaged responses. To gain insight into the mechanisms underlying normalization, we examined interactions between neurons that exhibit different degrees of normalization. We recorded from multiple neurons in three cortical areas while rhesus monkeys viewed superimposed drifting gratings. We found that neurons showing strong normalization shared less trial-to-trial variability with other neurons in the same cortical area and more variability with neurons in other cortical areas than did units with weak normalization. Furthermore, the cortical organization of normalization was not random: neurons recorded on nearby electrodes tended to exhibit similar amounts of normalization. Together, our results suggest that normalization reflects a neuron's role in its local network and that modulatory factors like normalization share the topographic organization typical of sensory tuning properties. Copyright © 2016 the American Physiological Society.
Relating normalization to neuronal populations across cortical areas
Alberts, Joshua J.; Cohen, Marlene R.
2016-01-01
Normalization, which divisively scales neuronal responses to multiple stimuli, is thought to underlie many sensory, motor, and cognitive processes. In every study where it has been investigated, neurons measured in the same brain area under identical conditions exhibit a range of normalization, ranging from suppression by nonpreferred stimuli (strong normalization) to additive responses to combinations of stimuli (no normalization). Normalization has been hypothesized to arise from interactions between neuronal populations, either in the same or different brain areas, but current models of normalization are not mechanistic and focus on trial-averaged responses. To gain insight into the mechanisms underlying normalization, we examined interactions between neurons that exhibit different degrees of normalization. We recorded from multiple neurons in three cortical areas while rhesus monkeys viewed superimposed drifting gratings. We found that neurons showing strong normalization shared less trial-to-trial variability with other neurons in the same cortical area and more variability with neurons in other cortical areas than did units with weak normalization. Furthermore, the cortical organization of normalization was not random: neurons recorded on nearby electrodes tended to exhibit similar amounts of normalization. Together, our results suggest that normalization reflects a neuron's role in its local network and that modulatory factors like normalization share the topographic organization typical of sensory tuning properties. PMID:27358313
Sidorina, V V; Gerasimova, Yu A; Kuleshova, E P; Merzhanova, G Kh
2015-01-01
During our experiments on cats was investigated the subthalamic neuron activity at different types of behavior in case of reinforcement choice depending on its value and availability. In chronic experiences the multiunit activity in subthalamic nucleus (STN) and orbitofrontal cortex (FC) has been recorded. Multiunit activity was analyzed over frequency and network properties of spikes. It was shown, that STN neurons reaction to different reinforcements and conditional stimulus at short- or long-delay reactions was represented by increasing or decreasing of frequency of single neurons. However the same STN neu- rons responded with increasing of frequency of single neuron during expectation of mix-bread-meat and decreasing--during the meat expectation. It has been revealed, that the number of STN interneuron interactions was authentic more at impulsive behavior than at self-control choice of behavior. The number of interactions between FC and STN neurons within intervals of 0-30 Ms was authentic more at display impulsive than during self-control behavior. These results suppose that FC and STN neurons participate in integration of reinforcement estimation; and distinctions in a choice of behavior are defined by the local and distributed interneuron interactions of STN and FC.
Lhx6-positive GABA-releasing neurons of the zona incerta promote sleep
Liu, Kai; Kim, Juhyun; Kim, Dong Won; Zhang, Yi Stephanie; Bao, Hechen; Denaxa, Myrto; Lim, Szu-Aun; Kim, Eileen; Liu, Chang; Wickersham, Ian R.; Pachnis, Vassilis; Hattar, Samer; Song, Juan; Brown, Solange P.; Blackshaw, Seth
2017-01-01
Multiple populations of wake-promoting neurons have been characterized in mammals, but few sleep-promoting neurons have been identified1. Wake-promoting cell types include hypocretin and GABA (γ-aminobutyric-acid)-releasing neurons of the lateral hypothalamus, which promote the transition to wakefulness from non-rapid eye movement (NREM) and rapid eye movement (REM) sleep2,3. Here we show that a subset of GABAergic neurons in the mouse ventral zona incerta, which express the LIM homeodomain factor Lhx6 and are activated by sleep pressure, both directly inhibit wake-active hypocretin and GABAergic cells in the lateral hypothalamus and receive inputs from multiple sleep–wake-regulating neurons. Conditional deletion of Lhx6 from the developing diencephalon leads to decreases in both NREM and REM sleep. Furthermore, selective activation and inhibition of Lhx6-positive neurons in the ventral zona incerta bidirectionally regulate sleep time in adult mice, in part through hypocretin-dependent mechanisms. These studies identify a GABAergic subpopulation of neurons in the ventral zona incerta that promote sleep. PMID:28847002
Dynamic range in small-world networks of Hodgkin-Huxley neurons with chemical synapses
NASA Astrophysics Data System (ADS)
Batista, C. A. S.; Viana, R. L.; Lopes, S. R.; Batista, A. M.
2014-09-01
According to Stevens' law the relationship between stimulus and response is a power-law within an interval called the dynamic range. The dynamic range of sensory organs is found to be larger than that of a single neuron, suggesting that the network structure plays a key role in the behavior of both the scaling exponent and the dynamic range of neuron assemblies. In order to verify computationally the relationships between stimulus and response for spiking neurons, we investigate small-world networks of neurons described by the Hodgkin-Huxley equations connected by chemical synapses. We found that the dynamic range increases with the network size, suggesting that the enhancement of the dynamic range observed in sensory organs, with respect to single neurons, is an emergent property of complex network dynamics.
Rice, Ann C; Keeney, Paula M; Algarzae, Norah K; Ladd, Amy C; Thomas, Ravindar R; Bennett, James P
2014-01-01
Alzheimer's disease (AD) is the major cause of adult-onset dementia and is characterized in its pre-diagnostic stage by reduced cerebral cortical glucose metabolism and in later stages by reduced cortical oxygen uptake, implying reduced mitochondrial respiration. Using quantitative PCR we determined the mitochondrial DNA (mtDNA) gene copy numbers from multiple groups of 15 or 20 pyramidal neurons, GFAP(+) astrocytes and dentate granule neurons isolated using laser capture microdissection, and the relative expression of mitochondrial biogenesis (mitobiogenesis) genes in hippocampi from 10 AD and 9 control (CTL) cases. AD pyramidal but not dentate granule neurons had significantly reduced mtDNA copy numbers compared to CTL neurons. Pyramidal neuron mtDNA copy numbers in CTL, but not AD, positively correlated with cDNA levels of multiple mitobiogenesis genes. In CTL, but not in AD, hippocampal cDNA levels of PGC1α were positively correlated with multiple downstream mitobiogenesis factors. Mitochondrial DNA copy numbers in pyramidal neurons did not correlate with hippocampal Aβ1-42 levels. After 48 h exposure of H9 human neural stem cells to the neurotoxic fragment Aβ25-35, mtDNA copy numbers were not significantly altered. In summary, AD postmortem hippocampal pyramidal neurons have reduced mtDNA copy numbers. Mitochondrial biogenesis pathway signaling relationships are disrupted in AD, but are mostly preserved in CTL. Our findings implicate complex alterations of mitochondria-host cell relationships in AD.
Fried, Itzhak; Mukamel, Roy; Kreiman, Gabriel
2011-01-01
Understanding how self-initiated behavior is encoded by neuronal circuits in the human brain remains elusive. We recorded the activity of 1019 neurons while twelve subjects performed self-initiated finger movement. We report progressive neuronal recruitment over ~1500 ms before subjects report making the decision to move. We observed progressive increase or decrease in neuronal firing rate, particularly in the supplementary motor area (SMA), as the reported time of decision was approached. A population of 256 SMA neurons is sufficient to predict in single trials the impending decision to move with accuracy greater than 80% already 700 ms prior to subjects’ awareness. Furthermore, we predict, with a precision of a few hundred ms, the actual time point of this voluntary decision to move. We implement a computational model whereby volition emerges once a change in internally generated firing rate of neuronal assemblies crosses a threshold. PMID:21315264
Jády, Attila Gy.; Nagy, Ádám M.; Kőhidi, Tímea; Ferenczi, Szilamér; Tretter, László
2016-01-01
While it is evident that the metabolic machinery of stem cells should be fairly different from that of differentiated neurons, the basic energy production pathways in neural stem cells (NSCs) or in neurons are far from clear. Using the model of in vitro neuron production by NE-4C NSCs, this study focused on the metabolic changes taking place during the in vitro neuronal differentiation. O2 consumption, H+ production, and metabolic responses to single metabolites were measured in cultures of NSCs and in their neuronal derivatives, as well as in primary neuronal and astroglial cultures. In metabolite-free solutions, NSCs consumed little O2 and displayed a higher level of mitochondrial proton leak than neurons. In stem cells, glycolysis was the main source of energy for the survival of a 2.5-h period of metabolite deprivation. In contrast, stem cell-derived or primary neurons sustained a high-level oxidative phosphorylation during metabolite deprivation, indicating the consumption of own cellular material for energy production. The stem cells increased O2 consumption and mitochondrial ATP production in response to single metabolites (with the exception of glucose), showing rapid adaptation of the metabolic machinery to the available resources. In contrast, single metabolites did not increase the O2 consumption of neurons or astrocytes. In “starving” neurons, neither lactate nor pyruvate was utilized for mitochondrial ATP production. Gene expression studies also suggested that aerobic glycolysis and rapid metabolic adaptation characterize the NE-4C NSCs, while autophagy and alternative glucose utilization play important roles in the metabolism of stem cell-derived neurons. PMID:27116891
Fiáth, Richárd; Beregszászi, Patrícia; Horváth, Domonkos; Wittner, Lucia; Aarts, Arno A A; Ruther, Patrick; Neves, Hercules P; Bokor, Hajnalka; Acsády, László; Ulbert, István
2016-11-01
Recording simultaneous activity of a large number of neurons in distributed neuronal networks is crucial to understand higher order brain functions. We demonstrate the in vivo performance of a recently developed electrophysiological recording system comprising a two-dimensional, multi-shank, high-density silicon probe with integrated complementary metal-oxide semiconductor electronics. The system implements the concept of electronic depth control (EDC), which enables the electronic selection of a limited number of recording sites on each of the probe shafts. This innovative feature of the system permits simultaneous recording of local field potentials (LFP) and single- and multiple-unit activity (SUA and MUA, respectively) from multiple brain sites with high quality and without the actual physical movement of the probe. To evaluate the in vivo recording capabilities of the EDC probe, we recorded LFP, MUA, and SUA in acute experiments from cortical and thalamic brain areas of anesthetized rats and mice. The advantages of large-scale recording with the EDC probe are illustrated by investigating the spatiotemporal dynamics of pharmacologically induced thalamocortical slow-wave activity in rats and by the two-dimensional tonotopic mapping of the auditory thalamus. In mice, spatial distribution of thalamic responses to optogenetic stimulation of the neocortex was examined. Utilizing the benefits of the EDC system may result in a higher yield of useful data from a single experiment compared with traditional passive multielectrode arrays, and thus in the reduction of animals needed for a research study. Copyright © 2016 the American Physiological Society.
Kim, Ju Young; Duan, Xin; Liu, Cindy Y; Jang, Mi-Hyeon; Guo, Junjie U; Pow-anpongkul, Nattapol; Kang, Eunchai; Song, Hongjun; Ming, Guo-li
2009-09-24
Disrupted-in-schizophrenia 1 (DISC1), a susceptibility gene for major mental illnesses, regulates multiple aspects of embryonic and adult neurogenesis. Here, we show that DISC1 suppression in newborn neurons of the adult hippocampus leads to overactivated signaling of AKT, another schizophrenia susceptibility gene. Mechanistically, DISC1 directly interacts with KIAA1212, an AKT binding partner that enhances AKT signaling in the absence of DISC1, and DISC1 binding to KIAA1212 prevents AKT activation in vitro. Functionally, multiple genetic manipulations to enhance AKT signaling in adult-born neurons in vivo exhibit similar defects as DISC1 suppression in neuronal development that can be rescued by pharmacological inhibition of mammalian target of rapamycin (mTOR), an AKT downstream effector. Our study identifies the AKT-mTOR signaling pathway as a critical DISC1 target in regulating neuronal development and provides a framework for understanding how multiple susceptibility genes may functionally converge onto a common pathway in contributing to the etiology of certain psychiatric disorders.
Burnett, James C.; Nuss, Jonathan E.; Wanner, Laura M.; Peyser, Brian D.; Du, Hao T.; Gomba, Glenn Y.; Kota, Krishna P.; Panchal, Rekha G.; Gussio, Rick; Kane, Christopher D.; Tessarollo, Lino
2015-01-01
Botulinum neurotoxins (BoNTs), the causative agents of botulism, are potent inhibitors of neurotransmitter release from motor neurons. There are currently no drugs to treat BoNT intoxication after the onset of the disease symptoms. In this study, we explored how modulation of key host pathways affects the process of BoNT intoxication in human motor neurons, focusing on Src family kinase (SFK) signaling. Motor neurons derived from human embryonic stem (hES) cells were treated with a panel of SFK inhibitors and intoxicated with BoNT serotypes A, B, or E (which are responsible for >95 % of human botulism cases). Subsequently, it was found that bosutinib, dasatinib, KX2-391, PP1, PP2, Src inhibitor-1, and SU6656 significantly antagonized all three of the serotypes. Furthermore, the data indicated that the treatment of hES-derived motor neurons with multiple SFK inhibitors increased the antagonistic effect synergistically. Mechanistically, the small molecules appear to inhibit BoNTs by targeting host pathways necessary for intoxication and not by directly inhibiting the toxins’ proteolytic activity. Importantly, the identified inhibitors are all well-studied with some in clinical trials while others are FDA-approved drugs. Overall, this study emphasizes the importance of targeting host neuronal pathways, rather than the toxin’s enzymatic components, to antagonize multiple BoNT serotypes in motor neurons. PMID:25782580
A dynamic code for economic object valuation in prefrontal cortex neurons
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
Multifocal Neuropathy: Expanding the Scope of Double Crush Syndrome.
Cohen, Brian H; Gaspar, Michael P; Daniels, Alan H; Akelman, Edward; Kane, Patrick M
2016-12-01
Double crush syndrome (DCS), as it is classically defined, is a clinical condition composed of neurological dysfunction due to compressive pathology at multiple sites along a single peripheral nerve. The traditional definition of DCS is narrow in scope because many systemic pathologic processes, such as diabetes mellitus, drug-induced neuropathy, vascular disease and autoimmune neuronal damage, can have deleterious effects on nerve function. Multifocal neuropathy is a more appropriate term describing the multiple etiologies (including compressive lesions) that may synergistically contribute to nerve dysfunction and clinical symptoms. This paper examines the history of DCS and multifocal neuropathy, including the epidemiology and pathophysiology in addition to principles of evaluation and management. Copyright © 2016 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.
Evoking prescribed spike times in stochastic neurons
NASA Astrophysics Data System (ADS)
Doose, Jens; Lindner, Benjamin
2017-09-01
Single cell stimulation in vivo is a powerful tool to investigate the properties of single neurons and their functionality in neural networks. We present a method to determine a cell-specific stimulus that reliably evokes a prescribed spike train with high temporal precision of action potentials. We test the performance of this stimulus in simulations for two different stochastic neuron models. For a broad range of parameters and a neuron firing with intermediate firing rates (20-40 Hz) the reliability in evoking the prescribed spike train is close to its theoretical maximum that is mainly determined by the level of intrinsic noise.
Stein, Wolfgang
2014-01-01
Locating circuit neurons and recording from them with single-cell resolution is a prerequisite for studying neural circuits. Determining neuron location can be challenging even in small nervous systems because neurons are densely packed, found in different layers, and are often covered by ganglion and nerve sheaths that impede access for recording electrodes and neuronal markers. We revisited the voltage-sensitive dye RH795 for its ability to stain and record neurons through the ganglion sheath. Bath-application of RH795 stained neuronal membranes in cricket, earthworm and crab ganglia without removing the ganglion sheath, revealing neuron cell body locations in different ganglion layers. Using the pyloric and gastric mill central pattern generating neurons in the stomatogastric ganglion (STG) of the crab, Cancer borealis, we found that RH795 permeated the ganglion without major residue in the sheath and brightly stained somatic, axonal and dendritic membranes. Visibility improved significantly in comparison to unstained ganglia, allowing the identification of somata location and number of most STG neurons. RH795 also stained axons and varicosities in non-desheathed nerves, and it revealed the location of sensory cell bodies in peripheral nerves. Importantly, the spike activity of the sensory neuron AGR, which influences the STG motor patterns, remained unaffected by RH795, while desheathing caused significant changes in AGR activity. With respect to recording neural activity, RH795 allowed us to optically record membrane potential changes of sub-sheath neuronal membranes without impairing sensory activity. The signal-to-noise ratio was comparable with that previously observed in desheathed preparations and sufficiently high to identify neurons in single-sweep recordings and synaptic events after spike-triggered averaging. In conclusion, RH795 enabled staining and optical recording of neurons through the ganglion sheath and is therefore both a good anatomical marker for living neural tissue and a promising tool for studying neural activity of an entire network with single-cell resolution. PMID:25062029
Saez, Ignacio; Friedlander, Michael J
2016-01-01
Layer 4 (L4) of primary visual cortex (V1) is the main recipient of thalamocortical fibers from the dorsal lateral geniculate nucleus (LGNd). Thus, it is considered the main entry point of visual information into the neocortex and the first anatomical opportunity for intracortical visual processing before information leaves L4 and reaches supra- and infragranular cortical layers. The strength of monosynaptic connections from individual L4 excitatory cells onto adjacent L4 cells (unitary connections) is highly malleable, demonstrating that the initial stage of intracortical synaptic transmission of thalamocortical information can be altered by previous activity. However, the inhibitory network within L4 of V1 may act as an internal gate for induction of excitatory synaptic plasticity, thus providing either high fidelity throughput to supragranular layers or transmittal of a modified signal subject to recent activity-dependent plasticity. To evaluate this possibility, we compared the induction of synaptic plasticity using classical extracellular stimulation protocols that recruit a combination of excitatory and inhibitory synapses with stimulation of a single excitatory neuron onto a L4 cell. In order to induce plasticity, we paired pre- and postsynaptic activity (with the onset of postsynaptic spiking leading the presynaptic activation by 10ms) using extracellular stimulation (ECS) in acute slices of primary visual cortex and comparing the outcomes with our previously published results in which an identical protocol was used to induce synaptic plasticity between individual pre- and postsynaptic L4 excitatory neurons. Our results indicate that pairing of ECS with spiking in a L4 neuron fails to induce plasticity in L4-L4 connections if synaptic inhibition is intact. However, application of a similar pairing protocol under GABAARs inhibition by bath application of 2μM bicuculline does induce robust synaptic plasticity, long term potentiation (LTP) or long term depression (LTD), similar to our results with pairing of pre- and postsynaptic activation between individual excitatory L4 neurons in which inhibitory connections are not activated. These results are consistent with the well-established observation that inhibition limits the capacity for induction of plasticity at excitatory synapses and that pre- and postsynaptic activation at a fixed time interval can result in a variable range of plasticity outcomes. However, in the current study by virtue of having two sets of experimental data, we have provided a new insight into these processes. By randomly mixing the assorting of individual L4 neurons according to the frequency distribution of the experimentally determined plasticity outcome distribution based on the calculated convergence of multiple individual L4 neurons onto a single postsynaptic L4 neuron, we were able to compare then actual ECS plasticity outcomes to those predicted by randomly mixing individual pairs of neurons. Interestingly, the observed plasticity profiles with ECS cannot account for the random assortment of plasticity behaviors of synaptic connections between individual cell pairs. These results suggest that connections impinging onto a single postsynaptic cell may be grouped according to plasticity states.
Sieger, Tomáš; Serranová, Tereza; Růžička, Filip; Vostatek, Pavel; Wild, Jiří; Šťastná, Daniela; Bonnet, Cecilia; Novák, Daniel; Růžička, Evžen; Urgošík, Dušan; Jech, Robert
2015-01-01
Both animal studies and studies using deep brain stimulation in humans have demonstrated the involvement of the subthalamic nucleus (STN) in motivational and emotional processes; however, participation of this nucleus in processing human emotion has not been investigated directly at the single-neuron level. We analyzed the relationship between the neuronal firing from intraoperative microrecordings from the STN during affective picture presentation in patients with Parkinson’s disease (PD) and the affective ratings of emotional valence and arousal performed subsequently. We observed that 17% of neurons responded to emotional valence and arousal of visual stimuli according to individual ratings. The activity of some neurons was related to emotional valence, whereas different neurons responded to arousal. In addition, 14% of neurons responded to visual stimuli. Our results suggest the existence of neurons involved in processing or transmission of visual and emotional information in the human STN, and provide evidence of separate processing of the affective dimensions of valence and arousal at the level of single neurons as well. PMID:25713375
CFTR mediates noradrenaline-induced ATP efflux from DRG neurons.
Kanno, Takeshi; Nishizaki, Tomoyuki
2011-09-24
In our earlier study, noradrenaline (NA) stimulated ATP release from dorsal root ganglion (DRG) neurons as mediated via β(3) adrenoceptors linked to G(s) protein involving protein kinase A (PKA) activation, to cause allodynia. The present study was conducted to understand how ATP is released from DRG neurons. In an outside-out patch-clamp configuration from acutely dissociated rat DRG neurons, single-channel currents, sensitive to the P2X receptor inhibitor PPADS, were evoked by approaching the patch-electrode tip close to a neuron, indicating that ATP is released from DRG neurons, to activate P2X receptor. NA increased the frequency of the single-channel events, but such NA effect was not found for DRG neurons transfected with the siRNA to silence the cystic fibrosis transmembrane conductance regulator (CFTR) gene. In the immunocytochemical study using acutely dissociated rat DRG cells, CFTR was expressed in neurons alone, but not satellite cells, fibroblasts, or Schwann cells. It is concluded from these results that CFTR mediates NA-induced ATP efflux from DRG neurons as an ATP channel.
Gutierrez, Gabrielle J; O'Leary, Timothy; Marder, Eve
2013-03-06
Rhythmic oscillations are common features of nervous systems. One of the fundamental questions posed by these rhythms is how individual neurons or groups of neurons are recruited into different network oscillations. We modeled competing fast and slow oscillators connected to a hub neuron with electrical and inhibitory synapses. We explore the patterns of coordination shown in the network as a function of the electrical coupling and inhibitory synapse strengths with the help of a novel visualization method that we call the "parameterscape." The hub neuron can be switched between the fast and slow oscillators by multiple network mechanisms, indicating that a given change in network state can be achieved by degenerate cellular mechanisms. These results have importance for interpreting experiments employing optogenetic, genetic, and pharmacological manipulations to understand circuit dynamics. Copyright © 2013 Elsevier Inc. All rights reserved.
Hondebrink, L; Verboven, A H A; Drega, W S; Schmeink, S; de Groot, M W G D M; van Kleef, R G D M; Wijnolts, F M J; de Groot, A; Meulenbelt, J; Westerink, R H S
2016-07-01
Annual prevalence of the use of common illicit drugs and new psychoactive substances (NPS) is high, despite the often limited knowledge on the health risks of these substances. Recently, cortical cultures grown on multi-well microelectrode arrays (mwMEAs) have been used for neurotoxicity screening of chemicals, pharmaceuticals, and toxins with a high sensitivity and specificity. However, the use of mwMEAs to investigate the effects of illicit drugs on neuronal activity is largely unexplored. We therefore first characterised the cortical cultures using immunocytochemistry and show the presence of astrocytes, glutamatergic and GABAergic neurons. Neuronal activity is concentration-dependently affected following exposure to six neurotransmitters (glutamate, GABA, serotonin, dopamine, acetylcholine and nicotine). Most neurotransmitters inhibit neuronal activity, although glutamate and acetylcholine transiently increase activity at specific concentrations. These transient effects are not detected when activity is determined during the entire 30min exposure window, potentially resulting in false-negative results. As expected, exposure to the GABAA-receptor antagonist bicuculline increases neuronal activity. Exposure to a positive allosteric modulator of the GABAA-receptor (diazepam) or to glutamate receptor antagonists (CNQX and MK-801) reduces neuronal activity. Further, we demonstrate that exposure to common drugs (3,4-methylenedioxymethamphetamine (MDMA) and amphetamine) and NPS (1-(3-chlorophenyl)piperazine (mCPP), 4-fluoroamphetamine (4-FA) and methoxetamine (MXE)) decreases neuronal activity. MXE most potently inhibits neuronal activity with an IC50 of 0.5μM, whereas 4-FA is least potent with an IC50 of 113μM. Our data demonstrate the importance of analysing neuronal activity within different time windows during exposure to prevent false-negative results. We also show that cortical cultures grown on mwMEAs can successfully be applied to investigate the effects of different (illicit) drugs on neuronal activity. Compared to investigating multiple single endpoints for neurotoxicity or neuromodulation, such as receptor activation or calcium channel function, mwMEAs can provide information on integrated aspects of drug-induced neurotoxicity more rapidly. Therefore, this approach could contribute to a faster insight in possible health risks and shorten the regulation process. Copyright © 2016 Elsevier B.V. All rights reserved.
Induction of specific neuron types by overexpression of single transcription factors.
Teratani-Ota, Yusuke; Yamamizu, Kohei; Piao, Yulan; Sharova, Lioudmila; Amano, Misa; Yu, Hong; Schlessinger, David; Ko, Minoru S H; Sharov, Alexei A
2016-10-01
Specific neuronal types derived from embryonic stem cells (ESCs) can facilitate mechanistic studies and potentially aid in regenerative medicine. Existing induction methods, however, mostly rely on the effects of the combined action of multiple added growth factors, which generally tend to result in mixed populations of neurons. Here, we report that overexpression of specific transcription factors (TFs) in ESCs can rather guide the differentiation of ESCs towards specific neuron lineages. Analysis of data on gene expression changes 2 d after induction of each of 185 TFs implicated candidate TFs for further ESC differentiation studies. Induction of 23 TFs (out of 49 TFs tested) for 6 d facilitated neural differentiation of ESCs as inferred from increased proportion of cells with neural progenitor marker PSA-NCAM. We identified early activation of the Notch signaling pathway as a common feature of most potent inducers of neural differentiation. The majority of neuron-like cells generated by induction of Ascl1, Smad7, Nr2f1, Dlx2, Dlx4, Nr2f2, Barhl2, and Lhx1 were GABA-positive and expressed other markers of GABAergic neurons. In the same way, we identified Lmx1a and Nr4a2 as inducers for neurons bearing dopaminergic markers and Isl1, Fezf2, and St18 for cholinergic motor neurons. A time-course experiment with induction of Ascl1 showed early upregulation of most neural-specific messenger RNA (mRNA) and microRNAs (miRNAs). Sets of Ascl1-induced mRNAs and miRNAs were enriched in Ascl1 targets. In further studies, enrichment of cells obtained with the induction of Ascl1, Smad7, and Nr2f1 using microbeads resulted in essentially pure population of neuron-like cells with expression profiles similar to neural tissues and expressed markers of GABAergic neurons. In summary, this study indicates that induction of transcription factors is a promising approach to generate cultures that show the transcription profiles characteristic of specific neural cell types.
Nitta, Yohei; Yamazaki, Daisuke; Sugie, Atsushi; Hiroi, Makoto; Tabata, Tetsuya
2017-01-15
Axonal branching is one of the key processes within the enormous complexity of the nervous system to enable a single neuron to send information to multiple targets. However, the molecular mechanisms that control branch formation are poorly understood. In particular, previous studies have rarely addressed the mechanisms underlying axonal bifurcation, in which axons form new branches via splitting of the growth cone. We demonstrate that DISCO Interacting Protein 2 (DIP2) is required for precise axonal bifurcation in Drosophila mushroom body (MB) neurons by suppressing ectopic bifurcation and regulating the guidance of sister axons. We also found that DIP2 localize to the plasma membrane. Domain function analysis revealed that the AMP-synthetase domains of DIP2 are essential for its function, which may involve exerting a catalytic activity that modifies fatty acids. Genetic analysis and subsequent biochemical analysis suggested that DIP2 is involved in the fatty acid metabolization of acyl-CoA. Taken together, our results reveal a function of DIP2 in the developing nervous system and provide a potential functional relationship between fatty acid metabolism and axon morphogenesis. Copyright © 2016 Elsevier Inc. All rights reserved.
The physics of mental acts: coherence and creativity
NASA Astrophysics Data System (ADS)
Tito Arecchi, F.
2009-06-01
Coherence is a long range order absent at thermal equilibrium, where a system is the superposition of many uncorrelated components. To build non-trivial correlations, the system must enter a nonlinear dynamical regime. The nonlinearity leads to a multiplicity of equilibrium states, the number of which increases exponentially with the number of partners; we call complexity such a situation. Complete exploration of complexity would require a very large amount of time. On the contrary, in cognitive tasks, one reaches a decision within a few hundred milliseconds. Neuron synchronization lasting around 301 msec is the indicator of a conscious perception (Gestalt); however, the loss of information in the chaotic spike train of a single neuron takes a few msec, thus a conscious perception implies a control of chaos, whereby the information stored in a brain area survives for a time sufficient to elicit an action. Control of chaos is achieved by the interaction of a bottom-up stimulus with a top-down control (induced by the semantic memory). We call creativity this optimal control of neuronal chaos; it goes beyond the Bayesian inference, which is the way a computer operates, thus it represent a non-algorithmic step.
Coding and decoding with dendrites.
Papoutsi, Athanasia; Kastellakis, George; Psarrou, Maria; Anastasakis, Stelios; Poirazi, Panayiota
2014-02-01
Since the discovery of complex, voltage dependent mechanisms in the dendrites of multiple neuron types, great effort has been devoted in search of a direct link between dendritic properties and specific neuronal functions. Over the last few years, new experimental techniques have allowed the visualization and probing of dendritic anatomy, plasticity and integrative schemes with unprecedented detail. This vast amount of information has caused a paradigm shift in the study of memory, one of the most important pursuits in Neuroscience, and calls for the development of novel theories and models that will unify the available data according to some basic principles. Traditional models of memory considered neural cells as the fundamental processing units in the brain. Recent studies however are proposing new theories in which memory is not only formed by modifying the synaptic connections between neurons, but also by modifications of intrinsic and anatomical dendritic properties as well as fine tuning of the wiring diagram. In this review paper we present previous studies along with recent findings from our group that support a key role of dendrites in information processing, including the encoding and decoding of new memories, both at the single cell and the network level. Copyright © 2013 Elsevier Ltd. All rights reserved.
Analysis of neuronal cells of dissociated primary culture on high-density CMOS electrode array
Matsuda, Eiko; Mita, Takeshi; Hubert, Julien; Bakkum, Douglas; Frey, Urs; Hierlemann, Andreas; Takahashi, Hirokazu; Ikegami, Takashi
2017-01-01
Spontaneous development of neuronal cells was recorded around 4–34 days in vitro (DIV) with high-density CMOS array, which enables detailed study of the spatio-temporal activity of neuronal culture. We used the CMOS array to characterize the evolution of the inter-spike interval (ISI) distribution from putative single neurons, and estimate the network structure based on transfer entropy analysis, where each node corresponds to a single neuron. We observed that the ISI distributions gradually obeyed the power law with maturation of the network. The amount of information transferred between neurons increased at the early stage of development, but decreased as the network matured. These results suggest that both ISI and transfer entropy were very useful for characterizing the dynamic development of cultured neural cells over a few weeks. PMID:24109870
3D plasmonic nanoantennas integrated with MEA biosensors.
Dipalo, Michele; Messina, Gabriele C; Amin, Hayder; La Rocca, Rosanna; Shalabaeva, Victoria; Simi, Alessandro; Maccione, Alessandro; Zilio, Pierfrancesco; Berdondini, Luca; De Angelis, Francesco
2015-02-28
Neuronal signaling in brain circuits occurs at multiple scales ranging from molecules and cells to large neuronal assemblies. However, current sensing neurotechnologies are not designed for parallel access of signals at multiple scales. With the aim of combining nanoscale molecular sensing with electrical neural activity recordings within large neuronal assemblies, in this work three-dimensional (3D) plasmonic nanoantennas are integrated with multielectrode arrays (MEA). Nanoantennas are fabricated by fast ion beam milling on optical resist; gold is deposited on the nanoantennas in order to connect them electrically to the MEA microelectrodes and to obtain plasmonic behavior. The optical properties of these 3D nanostructures are studied through finite elements method (FEM) simulations that show a high electromagnetic field enhancement. This plasmonic enhancement is confirmed by surface enhancement Raman spectroscopy of a dye performed in liquid, which presents an enhancement of almost 100 times the incident field amplitude at resonant excitation. Finally, the reported MEA devices are tested on cultured rat hippocampal neurons. Neurons develop by extending branches on the nanostructured electrodes and extracellular action potentials are recorded over multiple days in vitro. Raman spectra of living neurons cultured on the nanoantennas are also acquired. These results highlight that these nanostructures could be potential candidates for combining electrophysiological measures of large networks with simultaneous spectroscopic investigations at the molecular level.
NASA Astrophysics Data System (ADS)
Sikora, Grzegorz; Wyłomańska, Agnieszka; Gajda, Janusz; Solé, Laura; Akin, Elizabeth J.; Tamkun, Michael M.; Krapf, Diego
2017-12-01
Protein and lipid nanodomains are prevalent on the surface of mammalian cells. In particular, it has been recently recognized that ion channels assemble into surface nanoclusters in the soma of cultured neurons. However, the interactions of these molecules with surface nanodomains display a considerable degree of heterogeneity. Here, we investigate this heterogeneity and develop statistical tools based on the recurrence of individual trajectories to identify subpopulations within ion channels in the neuronal surface. We specifically study the dynamics of the K+ channel Kv1.4 and the Na+ channel Nav1.6 on the surface of cultured hippocampal neurons at the single-molecule level. We find that both these molecules are expressed in two different forms with distinct kinetics with regards to surface interactions, emphasizing the complex proteomic landscape of the neuronal surface. Further, the tools presented in this work provide new methods for the analysis of membrane nanodomains, transient confinement, and identification of populations within single-particle trajectories.
Schwalger, Tilo; Deger, Moritz; Gerstner, Wulfram
2017-04-01
Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50-2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations.
Do Val-da Silva, Raquel A; Peixoto-Santos, Jose E; Kandratavicius, Ludmyla; De Ross, Jana B; Esteves, Ingrid; De Martinis, Bruno S; Alves, Marcela N R; Scandiuzzi, Renata C; Hallak, Jaime E C; Zuardi, Antonio W; Crippa, Jose A; Leite, Joao P
2017-01-01
The present study reports the behavioral, electrophysiological, and neuropathological effects of cannabidiol (CBD), a major non-psychotropic constituent of Cannabis sativa , in the intrahippocampal pilocarpine-induced status epilepticus (SE) rat model. CBD was administered before pilocarpine-induced SE (group SE+CBDp) or before and after SE (group SE+CBDt), and compared to rats submitted only to SE (SE group), CBD, or vehicle (VH group). Groups were evaluated during SE (behavioral and electrophysiological analysis), as well as at days one and three post-SE (exploratory activity, electrophysiological analysis, neuron density, and neuron degeneration). Compared to SE group, SE+CBD groups (SE+CBDp and SE+CBDt) had increased SE latency, diminished SE severity, increased contralateral afterdischarge latency and decreased relative powers in delta (0.5-4 Hz) and theta (4-10 Hz) bands. Only SE+CBDp had increased vertical exploratory activity 1-day post SE and decreased contralateral relative power in delta 3 days after SE, when compared to SE group. SE+CBD groups also showed decreased neurodegeneration in the hilus and CA3, and higher neuron density in granule cell layer, hilus, CA3, and CA1, when compared to SE group. Our findings demonstrate anticonvulsant and neuroprotective effects of CBD preventive treatment in the intrahippocampal pilocarpine epilepsy model, either as single or multiple administrations, reinforcing the potential role of CBD in the treatment of epileptic disorders.
Retinal input to efferent target amacrine cells in the avian retina
Lindstrom, Sarah H.; Azizi, Nason; Weller, Cynthia; Wilson, Martin
2012-01-01
The bird visual system includes a substantial projection, of unknown function, from a midbrain nucleus to the contralateral retina. Every centrifugal, or efferent, neuron originating in the midbrain nucleus makes synaptic contact with the soma of a single, unique amacrine cell, the target cell (TC). By labeling efferent neurons in the midbrain we have been able to identify their terminals in retinal slices and make patch clamp recordings from TCs. TCs generate Na+ based action potentials triggered by spontaneous EPSPs originating from multiple classes of presynaptic neurons. Exogenously applied glutamate elicited inward currents having the mixed pharmacology of NMDA, kainate and inward rectifying AMPA receptors. Exogenously applied GABA elicited currents entirely suppressed by GABAzine, and therefore mediated by GABAA receptors. Immunohistochemistry showed the vesicular glutamate transporter, vGluT2, to be present in the characteristic synaptic boutons of efferent terminals, whereas the GABA synthetic enzyme, GAD, was present in much smaller processes of intrinsic retinal neurons. Extracellular recording showed that exogenously applied GABA was directly excitatory to TCs and, consistent with this, NKCC, the Cl− transporter often associated with excitatory GABAergic synapses, was identified in TCs by antibody staining. The presence of excitatory retinal input to TCs implies that TCs are not merely slaves to their midbrain input; instead, their output reflects local retinal activity and descending input from the midbrain. PMID:20650017
Cognitive Consilience: Primate Non-Primary Neuroanatomical Circuits Underlying Cognition
Solari, Soren Van Hout; Stoner, Rich
2011-01-01
Interactions between the cerebral cortex, thalamus, and basal ganglia form the basis of cognitive information processing in the mammalian brain. Understanding the principles of neuroanatomical organization in these structures is critical to understanding the functions they perform and ultimately how the human brain works. We have manually distilled and synthesized hundreds of primate neuroanatomy facts into a single interactive visualization. The resulting picture represents the fundamental neuroanatomical blueprint upon which cognitive functions must be implemented. Within this framework we hypothesize and detail 7 functional circuits corresponding to psychological perspectives on the brain: consolidated long-term declarative memory, short-term declarative memory, working memory/information processing, behavioral memory selection, behavioral memory output, cognitive control, and cortical information flow regulation. Each circuit is described in terms of distinguishable neuronal groups including the cerebral isocortex (9 pyramidal neuronal groups), parahippocampal gyrus and hippocampus, thalamus (4 neuronal groups), basal ganglia (7 neuronal groups), metencephalon, basal forebrain, and other subcortical nuclei. We focus on neuroanatomy related to primate non-primary cortical systems to elucidate the basis underlying the distinct homotypical cognitive architecture. To display the breadth of this review, we introduce a novel method of integrating and presenting data in multiple independent visualizations: an interactive website (http://www.frontiersin.org/files/cognitiveconsilience/index.html) and standalone iPhone and iPad applications. With these tools we present a unique, annotated view of neuroanatomical consilience (integration of knowledge). PMID:22194717
Nanotools for Neuroscience and Brain Activity Mapping
Alivisatos, A. Paul; Andrews, Anne M.; Boyden, Edward S.; Chun, Miyoung; Church, George M.; Deisseroth, Karl; Donoghue, John P.; Fraser, Scott E.; Lippincott-Schwartz, Jennifer; Looger, Loren L.; Masmanidis, Sotiris; McEuen, Paul L.; Nurmikko, Arto V.; Park, Hongkun; Peterka, Darcy S.; Reid, Clay; Roukes, Michael L.; Scherer, Axel; Schnitzer, Mark; Sejnowski, Terrence J.; Shepard, Kenneth L.; Tsao, Doris; Turrigiano, Gina; Weiss, Paul S.; Xu, Chris; Yuste, Rafael; Zhuang, Xiaowei
2013-01-01
Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function. PMID:23514423
Representation of numerosity in posterior parietal cortex
Roitman, Jamie D.; Brannon, Elizabeth M.; Platt, Michael L.
2012-01-01
Humans and animals appear to share a similar representation of number as an analog magnitude on an internal, subjective scale. Neurological and neurophysiological data suggest that posterior parietal cortex (PPC) is a critical component of the circuits that form the basis of numerical abilities in humans. Patients with parietal lesions are impaired in their ability to access the deep meaning of numbers. Acalculiac patients with inferior parietal damage often have difficulty performing arithmetic (2 + 4?) or number bisection (what is between 3 and 5?) tasks, but are able to recite multiplication tables and read or write numerals. Functional imaging studies of neurologically intact humans performing subtraction, number comparison, and non-verbal magnitude comparison tasks show activity in areas within the intraparietal sulcus (IPS). Taken together, clinical cases and imaging studies support a critical role for parietal cortex in the mental manipulation of numerical quantities. Further, responses of single PPC neurons in non-human primates are sensitive to the numerosity of visual stimuli independent of low-level stimulus qualities. When monkeys are trained to make explicit judgments about the numerical value of such stimuli, PPC neurons encode their cardinal numerical value; without such training PPC neurons appear to encode numerical magnitude in an analog fashion. Here we suggest that the spatial and integrative properties of PPC neurons contribute to their critical role in numerical cognition. PMID:22666194
Morra, Joshua T; Glick, Stanley D; Cheer, Joseph F
2012-09-01
Patients suffering from amphetamine-induced psychosis display repetitive behaviors, partially alleviated by antipsychotics, which are reminiscent of rodent stereotypies. Due to recent evidence implicating endocannabinoid involvement in brain disorders, including psychosis, we studied the effects of endocannabinoid signaling on neuronal oscillations of rats exhibiting methamphetamine stereotypy. Neuronal network oscillations were recorded with multiple single electrode arrays aimed at the nucleus accumbens of freely-moving rats. During the experiments, animals were dosed intravenously with the CB1 receptor antagonist rimonabant (0.3 mg/kg) or vehicle followed by an ascending dose regimen of methamphetamine (0.01, 0.1, 1, and 3 mg/kg; cumulative dosing). The effects of drug administration on stereotypy and local gamma oscillations were evaluated. Methamphetamine treatment significantly increased high frequency gamma oscillations (∼80 Hz). Entrainment of a subpopulation of nucleus accumbens neurons to high frequency gamma was associated with stereotypy encoding in putative fast-spiking interneurons, but not in putative medium spiny neurons. The observed ability of methamphetamine to induce both stereotypy and high frequency gamma power was potently disrupted following CB1 receptor blockade. The present data suggest that CB1 receptor-dependent mechanisms are recruited by methamphetamine to modify striatal interneuron oscillations that accompany changes in psychomotor state, further supporting the link between endocannabinoids and schizophrenia spectrum disorders. Copyright © 2012 Elsevier Ltd. All rights reserved.
Simple and effective graphene laser processing for neuron patterning application
NASA Astrophysics Data System (ADS)
Lorenzoni, Matteo; Brandi, Fernando; Dante, Silvia; Giugni, Andrea; Torre, Bruno
2013-06-01
A straightforward fabrication technique to obtain patterned substrates promoting ordered neuron growth is presented. Chemical vapor deposition (CVD) single layer graphene (SLG) was machined by means of single pulse UV laser ablation technique at the lowest effective laser fluence in order to minimize laser damage effects. Patterned substrates were then coated with poly-D-lysine by means of a simple immersion in solution. Primary embryonic hippocampal neurons were cultured on our substrate, demonstrating an ordered interconnected neuron pattern mimicking the pattern design. Surprisingly, the functionalization is more effective on the SLG, resulting in notably higher alignment for neuron adhesion and growth. Therefore the proposed technique should be considered a valuable candidate to realize a new generation of highly specialized biosensors.
Simple and effective graphene laser processing for neuron patterning application
Lorenzoni, Matteo; Brandi, Fernando; Dante, Silvia; Giugni, Andrea; Torre, Bruno
2013-01-01
A straightforward fabrication technique to obtain patterned substrates promoting ordered neuron growth is presented. Chemical vapor deposition (CVD) single layer graphene (SLG) was machined by means of single pulse UV laser ablation technique at the lowest effective laser fluence in order to minimize laser damage effects. Patterned substrates were then coated with poly-D-lysine by means of a simple immersion in solution. Primary embryonic hippocampal neurons were cultured on our substrate, demonstrating an ordered interconnected neuron pattern mimicking the pattern design. Surprisingly, the functionalization is more effective on the SLG, resulting in notably higher alignment for neuron adhesion and growth. Therefore the proposed technique should be considered a valuable candidate to realize a new generation of highly specialized biosensors. PMID:23739674
Convergence of Cortical and Sensory Driver Inputs on Single Thalamocortical Cells
Groh, Alexander; Bokor, Hajnalka; Mease, Rebecca A.; Plattner, Viktor M.; Hangya, Balázs; Stroh, Albrecht; Deschenes, Martin; Acsády, László
2014-01-01
Ascending and descending information is relayed through the thalamus via strong, “driver” pathways. According to our current knowledge, different driver pathways are organized in parallel streams and do not interact at the thalamic level. Using an electron microscopic approach combined with optogenetics and in vivo physiology, we examined whether driver inputs arising from different sources can interact at single thalamocortical cells in the rodent somatosensory thalamus (nucleus posterior, POm). Both the anatomical and the physiological data demonstrated that ascending driver inputs from the brainstem and descending driver inputs from cortical layer 5 pyramidal neurons converge and interact on single thalamocortical neurons in POm. Both individual pathways displayed driver properties, but they interacted synergistically in a time-dependent manner and when co-activated, supralinearly increased the output of thalamus. As a consequence, thalamocortical neurons reported the relative timing between sensory events and ongoing cortical activity. We conclude that thalamocortical neurons can receive 2 powerful inputs of different origin, rather than only a single one as previously suggested. This allows thalamocortical neurons to integrate raw sensory information with powerful cortical signals and transfer the integrated activity back to cortical networks. PMID:23825316
Faghihi, Faramarz; Moustafa, Ahmed A.
2015-01-01
Information processing in the hippocampus begins by transferring spiking activity of the entorhinal cortex (EC) into the dentate gyrus (DG). Activity pattern in the EC is separated by the DG such that it plays an important role in hippocampal functions including memory. The structural and physiological parameters of these neural networks enable the hippocampus to be efficient in encoding a large number of inputs that animals receive and process in their life time. The neural encoding capacity of the DG depends on its single neurons encoding and pattern separation efficiency. In this study, encoding by the DG is modeled such that single neurons and pattern separation efficiency are measured using simulations of different parameter values. For this purpose, a probabilistic model of single neurons efficiency is presented to study the role of structural and physiological parameters. Known neurons number of the EC and the DG is used to construct a neural network by electrophysiological features of granule cells of the DG. Separated inputs as activated neurons in the EC with different firing probabilities are presented into the DG. For different connectivity rates between the EC and DG, pattern separation efficiency of the DG is measured. The results show that in the absence of feedback inhibition on the DG neurons, the DG demonstrates low separation efficiency and high firing frequency. Feedback inhibition can increase separation efficiency while resulting in very low single neuron’s encoding efficiency in the DG and very low firing frequency of neurons in the DG (sparse spiking). This work presents a mechanistic explanation for experimental observations in the hippocampus, in combination with theoretical measures. Moreover, the model predicts a critical role for impaired inhibitory neurons in schizophrenia where deficiency in pattern separation of the DG has been observed. PMID:25859189
Tucker, Thomas R; Katz, Lawrence C
2003-01-01
To investigate how neurons in cortical layer 2/3 integrate horizontal inputs arising from widely distributed sites, we combined intracellular recording and voltage-sensitive dye imaging to visualize the spatiotemporal dynamics of neuronal activity evoked by electrical stimulation of multiple sites in visual cortex. Individual stimuli evoked characteristic patterns of optical activity, while delivering stimuli at multiple sites generated interacting patterns in the regions of overlap. We observed that neurons in overlapping regions received convergent horizontal activation that generated nonlinear responses due to the emergence of large inhibitory potentials. The results indicate that co-activation of multiple sets of horizontal connections recruit strong inhibition from local inhibitory networks, causing marked deviations from simple linear integration.
Safari, Mir-Shahram; Mirnajafi-Zadeh, Javad; Hioki, Hiroyuki; Tsumoto, Tadaharu
2017-10-06
Neural circuits in the cerebral cortex consist primarily of excitatory pyramidal (Pyr) cells and inhibitory interneurons. Interneurons are divided into several subtypes, in which the two major groups are those expressing parvalbumin (PV) or somatostatin (SOM). These subtypes of interneurons are reported to play distinct roles in tuning and/or gain of visual response of pyramidal cells in the visual cortex. It remains unclear whether there is any quantitative and functional difference between the PV → Pyr and SOM → Pyr connections. We compared unitary inhibitory postsynaptic currents (uIPSCs) evoked by electrophysiological activation of single presynaptic interneurons with population IPSCs evoked by photo-activation of a mass of interneurons in vivo and in vitro in transgenic mice in which PV or SOM neurons expressed channelrhodopsin-2, and found that at least about 14 PV neurons made strong connections with a postsynaptic Pyr cell while a much larger number of SOM neurons made weak connections. Activation or suppression of single PV neurons modified visual responses of postsynaptic Pyr cells in 6 of 7 pairs whereas that of single SOM neurons showed no significant modification in 8 of 11 pairs, suggesting that PV neurons can act solo whereas most of SOM neurons may act in chorus on Pyr cells.
Identification of a Drosophila glucose receptor using Ca2+ imaging of single chemosensory neurons.
Miyamoto, Tetsuya; Chen, Yan; Slone, Jesse; Amrein, Hubert
2013-01-01
Evaluation of food compounds by chemosensory cells is essential for animals to make appropriate feeding decisions. In the fruit fly Drosophila melanogaster, structurally diverse chemicals are detected by multimeric receptors composed of members of a large family of Gustatory receptor (Gr) proteins. Putative sugar and bitter receptors are expressed in distinct subsets of Gustatory Receptor Neurons (GRN) of taste sensilla, thereby assigning distinct taste qualities to sugars and bitter tasting compounds, respectively. Here we report a Ca(2+) imaging method that allows association of ligand-mediated responses to a single GRN. We find that different sweet neurons exhibit distinct response profiles when stimulated with various sugars, and likewise, different bitter neurons exhibit distinct response profiles when stimulated with a set of bitter chemicals. These observations suggest that individual neurons within a taste modality are represented by distinct repertoires of sweet and bitter taste receptors, respectively. Furthermore, we employed this novel method to identify glucose as the primary ligand for the sugar receptor Gr61a, which is not only expressed in sweet sensing neurons of classical chemosensory sensilla, but also in two supersensitive neurons of atypical taste sensilla. Thus, single cell Ca(2+) imaging can be employed as a powerful tool to identify ligands for orphan Gr proteins.
Ito, Hidekatsu; Minoshima, Wataru; Kudoh, Suguru N
2015-08-01
To investigate relationships between neuronal network activity and electrical stimulus, we analyzed autonomous activity before and after electrical stimulus. Recordings of autonomous activity were performed using dissociated culture of rat hippocampal neurons on a multi-electrodes array (MEA) dish. Single stimulus and pared stimuli were applied to a cultured neuronal network. Single stimulus was applied every 1 min, and paired stimuli was performed by two sequential stimuli every 1 min. As a result, the patterns of synchronized activities of a neuronal network were changed after stimulus. Especially, long range synchronous activities were induced by paired stimuli. When 1 s inter-stimulus-intervals (ISI) and 1.5 s ISI paired stimuli are applied to a neuronal network, relatively long range synchronous activities expressed in case of 1.5 s ISI. Temporal synchronous activity of neuronal network is changed according to inter-stimulus-intervals (ISI) of electrical stimulus. In other words, dissociated neuronal network can maintain given information in temporal pattern and a certain type of an information maintenance mechanism was considered to be implemented in a semi-artificial dissociated neuronal network. The result is useful toward manipulation technology of neuronal activity in a brain system.
Ratan Murty, N. Apurva
2016-01-01
We have no difficulty seeing a straight line drawn on a paper even when the paper is bent, but this inference is in fact nontrivial. Doing so requires either matching local features or representing the pattern after factoring out the surface shape. Here we show that single neurons in the monkey inferior temporal (IT) cortex show invariant responses to patterns across rigid and nonrigid changes of surfaces. We recorded neuronal responses to stimuli in which the pattern and the surrounding surface were varied independently. In a subset of neurons, we found pattern-surface interactions that produced similar responses to stimuli across congruent pattern and surface transformations. These interactions produced systematic shifts in curvature tuning of patterns when overlaid on convex and flat surfaces. Our results show that surfaces are factored out of patterns by single neurons, thereby enabling complex perceptual inferences. NEW & NOTEWORTHY We have no difficulty seeing a straight line on a curved piece of paper, but in fact, doing so requires decoupling the shape of the surface from the pattern itself. Here we report a novel form of invariance in the visual cortex: single neurons in monkey inferior temporal cortex respond similarly to congruent transformations of patterns and surfaces, in effect decoupling patterns from the surface on which they are overlaid. PMID:27733595
Eberwine, James; Bartfai, Tamas
2011-01-01
We report on an ‘unbiased’ molecular characterization of individual, adult neurons, active in a central, anterior hypothalamic neuronal circuit, by establishing cDNA libraries from each individual, electrophysiologically identified warm sensitive neuron (WSN). The cDNA libraries were analyzed by Affymetrix microarray. The presence and frequency of cDNAs was confirmed and enhanced with Illumina sequencing of each single cell cDNA library. cDNAs encoding the GABA biosynthetic enzyme. GAD1 and of adrenomedullin, galanin, prodynorphin, somatostatin, and tachykinin were found in the WSNs. The functional cellular and in vivo studies on dozens of the more than 500 neurotransmitter -, hormone- receptors and ion channels, whose cDNA was identified and sequence confirmed, suggest little or no discrepancy between the transcriptional and functional data in WSNs; whenever agonists were available for a receptor whose cDNA was identified, a functional response was found.. Sequencing single neuron libraries permitted identification of rarely expressed receptors like the insulin receptor, adiponectin receptor2 and of receptor heterodimers; information that is lost when pooling cells leads to dilution of signals and mixing signals. Despite the common electrophysiological phenotype and uniform GAD1 expression, WSN- transcriptomes show heterogenity, suggesting strong epigenetic influence on the transcriptome. Our study suggests that it is well-worth interrogating the cDNA libraries of single neurons by sequencing and chipping. PMID:20970451
Kubota, Kenta; Seno, Takeshi; Konishi, Yoshiyuki
2013-11-20
Cerebellar granule neuronal cultures have been used to study the molecular mechanisms underlying neuronal functions, including neuronal morphogenesis. However, a limitation of this system is the difficulty to analyze isolated neurons because these are required to be maintained at a high density. Therefore, in the present study, we aimed to develop a simple and cost-effective method for culturing low-density cerebellar granule neurons. Cerebellar granule cells at two different densities (low- and high-density) were co-cultivated in order for the low-density culture to be supported by the paracrine signals from the high-density culture. This method enabled morphology analysis of isolated cerebellar granule neurons without astrocytic feeder cultures or supplements such as B27. Using this method, we investigated the function of a polarity factor. Studies using hippocampal neurons suggested that glycogen synthase kinase-3 (GSK-3) is an essential regulator of neuronal polarity, and inhibition of GSK-3 results in the formation of multiple axons. Pharmacological inhibitors for GSK-3 (6-bromoindirubin-3'-oxime and lithium chloride) did not cause the formation of multiple axons of cerebellar granule neurons but significantly reduced their length. Consistent results were obtained by introducing kinase-dead form of GSK-3 beta (K85A). These results indicated that GSK-3 is not directly involved in the control of neuronal polarity in cerebellar granule neurons. Overall, this study provides a simple method for culturing low-density cerebellar granule neurons and insights in to the neuronal-type dependent function of GSK-3 in neuronal morphogenesis. © 2013 Elsevier B.V. All rights reserved.
Zou, Wenjuan; Cheng, Hankui; Li, Shitian; Yue, Xiaomin; Xue, Yadan; Chen, Sixi; Kang, Lijun
2017-01-01
Animals utilize specialized sensory neurons enabling the detection of a wide range of environmental stimuli from the presence of toxic chemicals to that of touch. However, how these neurons discriminate between different kinds of stimuli remains poorly understood. By combining in vivo calcium imaging and molecular genetic manipulation, here we investigate the response patterns and the underlying mechanisms of the C. elegans phasmid neurons PHA/PHB to a variety of sensory stimuli. Our observations demonstrate that PHA/PHB neurons are polymodal sensory neurons which sense harmful chemicals, hyperosmotic solutions and mechanical stimulation. A repulsive concentration of IAA induces calcium elevations in PHA/PHB and both OSM-9 and TAX-4 are essential for IAA-sensing in PHA/PHB. Nevertheless, the PHA/PHB neurons are inhibited by copper and post-synaptically activated by copper removal. Neuropeptide is likely involved in copper removal-induced calcium elevations in PHA/PHB. Furthermore, mechanical stimulation activates PHA/PHB in an OSM-9-dependent manner. Our work demonstrates how PHA/PHB neurons respond to multiple environmental stimuli and lays a foundation for the further understanding of the mechanisms of polymodal signaling, such as nociception, in more complex organisms. PMID:28195191
Processing of Intraoral Olfactory and Gustatory Signals in the Gustatory Cortex of Awake Rats
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
Ma, Xiaofeng; Kohashi, Tsunehiko; Carlson, Bruce A
2013-07-01
Many sensory brain regions are characterized by extensive local network interactions. However, we know relatively little about the contribution of this microcircuitry to sensory coding. Detailed analyses of neuronal microcircuitry are usually performed in vitro, whereas sensory processing is typically studied by recording from individual neurons in vivo. The electrosensory pathway of mormyrid fish provides a unique opportunity to link in vitro studies of synaptic physiology with in vivo studies of sensory processing. These fish communicate by actively varying the intervals between pulses of electricity. Within the midbrain posterior exterolateral nucleus (ELp), the temporal filtering of afferent spike trains establishes interval tuning by single neurons. We characterized pairwise neuronal connectivity among ELp neurons with dual whole cell recording in an in vitro whole brain preparation. We found a densely connected network in which single neurons influenced the responses of other neurons throughout the network. Similarly tuned neurons were more likely to share an excitatory synaptic connection than differently tuned neurons, and synaptic connections between similarly tuned neurons were stronger than connections between differently tuned neurons. We propose a general model for excitatory network interactions in which strong excitatory connections both reinforce and adjust tuning and weak excitatory connections make smaller modifications to tuning. The diversity of interval tuning observed among this population of neurons can be explained, in part, by each individual neuron receiving a different complement of local excitatory inputs.
Reconfigurable visible nanophotonic switch for optogenetic applications (Conference Presentation)
NASA Astrophysics Data System (ADS)
Mohanty, Aseema; Li, Qian; Tadayon, Mohammad Amin; Bhatt, Gaurang R.; Cardenas, Jaime; Miller, Steven A.; Kepecs, Adam; Lipson, Michal
2017-02-01
High spatiotemporal resolution deep-brain optical excitation for optogenetics would enable activation of specific neural populations and in-depth study of neural circuits. Conventionally, a single fiber is used to flood light into a large area of the brain with limited resolution. The scalability of silicon photonics could enable neural excitation over large areas with single-cell resolution similar to electrical probes. However, active control of these optical circuits has yet to be demonstrated for optogenetics. Here we demonstrate the first active integrated optical switch for neural excitation at 473 nm, enabling control of multiple beams for deep-brain neural stimulation. Using a silicon nitride waveguide platform, we develop a cascaded Mach-Zehnder interferometer (MZI) network located outside the brain to direct light to 8 different grating emitters located at the tip of the neural probe. We use integrated platinum microheaters to induce a local thermo-optic phase shift in the MZI to control the switch output. We measure an ON/OFF extinction ratio of >8dB for a single switch and a switching speed of 20 microseconds. We characterize the optical output of the switch by imaging its excitation of fluorescent dye. Finally, we demonstrate in vivo single-neuron optical activation from different grating emitters using a fully packaged device inserted into a mouse brain. Directly activated neurons showed robust spike firing activities with low first-spike latency and small jitter. Active switching on a nanophotonic platform is necessary for eventually controlling highly-multiplexed reconfigurable optical circuits, enabling high-resolution optical stimulation in deep-brain regions.
Kordes, Sebastian; Kössl, Manfred
2017-01-01
Abstract For the purpose of orientation, echolocating bats emit highly repetitive and spatially directed sonar calls. Echoes arising from call reflections are used to create an acoustic image of the environment. The inferior colliculus (IC) represents an important auditory stage for initial processing of echolocation signals. The present study addresses the following questions: (1) how does the temporal context of an echolocation sequence mimicking an approach flight of an animal affect neuronal processing of distance information to echo delays? (2) how does the IC process complex echolocation sequences containing echo information from multiple objects (multiobject sequence)? Here, we conducted neurophysiological recordings from the IC of ketamine-anaesthetized bats of the species Carollia perspicillata and compared the results from the IC with the ones from the auditory cortex (AC). Neuronal responses to an echolocation sequence was suppressed when compared to the responses to temporally isolated and randomized segments of the sequence. The neuronal suppression was weaker in the IC than in the AC. In contrast to the cortex, the time course of the acoustic events is reflected by IC activity. In the IC, suppression sharpens the neuronal tuning to specific call-echo elements and increases the signal-to-noise ratio in the units’ responses. When presenting multiple-object sequences, despite collicular suppression, the neurons responded to each object-specific echo. The latter allows parallel processing of multiple echolocation streams at the IC level. Altogether, our data suggests that temporally-precise neuronal responses in the IC could allow fast and parallel processing of multiple acoustic streams. PMID:29242823
Beetz, M Jerome; Kordes, Sebastian; García-Rosales, Francisco; Kössl, Manfred; Hechavarría, Julio C
2017-01-01
For the purpose of orientation, echolocating bats emit highly repetitive and spatially directed sonar calls. Echoes arising from call reflections are used to create an acoustic image of the environment. The inferior colliculus (IC) represents an important auditory stage for initial processing of echolocation signals. The present study addresses the following questions: (1) how does the temporal context of an echolocation sequence mimicking an approach flight of an animal affect neuronal processing of distance information to echo delays? (2) how does the IC process complex echolocation sequences containing echo information from multiple objects (multiobject sequence)? Here, we conducted neurophysiological recordings from the IC of ketamine-anaesthetized bats of the species Carollia perspicillata and compared the results from the IC with the ones from the auditory cortex (AC). Neuronal responses to an echolocation sequence was suppressed when compared to the responses to temporally isolated and randomized segments of the sequence. The neuronal suppression was weaker in the IC than in the AC. In contrast to the cortex, the time course of the acoustic events is reflected by IC activity. In the IC, suppression sharpens the neuronal tuning to specific call-echo elements and increases the signal-to-noise ratio in the units' responses. When presenting multiple-object sequences, despite collicular suppression, the neurons responded to each object-specific echo. The latter allows parallel processing of multiple echolocation streams at the IC level. Altogether, our data suggests that temporally-precise neuronal responses in the IC could allow fast and parallel processing of multiple acoustic streams.
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.
Moro, Nobuhiro; Ghavim, Sima; Harris, Neil G; Hovda, David A; Sutton, Richard L
2013-10-16
Clinical studies have indicated an association between acute hyperglycemia and poor outcomes in patients with traumatic brain injury (TBI), although optimal blood glucose levels needed to maximize outcomes for these patients' remain under investigation. Previous results from experimental animal models suggest that post-TBI hyperglycemia may be harmful, neutral, or beneficial. The current studies determined the effects of single or multiple episodes of acute hyperglycemia on cerebral glucose metabolism and neuronal injury in a rodent model of unilateral controlled cortical impact (CCI) injury. In Experiment 1, a single episode of hyperglycemia (50% glucose at 2 g/kg, i.p.) initiated immediately after CCI was found to significantly attenuate a TBI-induced depression of glucose metabolism in cerebral cortex (4 of 6 regions) and subcortical regions (2 of 7) as well as to significantly reduce the number of dead/dying neurons in cortex and hippocampus at 24 h post-CCI. Experiment 2 examined effects of more prolonged and intermittent hyperglycemia induced by glucose administrations (2 g/kg, i.p.) at 0, 1, 3 and 6h post-CCI. The latter study also found significantly improved cerebral metabolism (in 3 of 6 cortical and 3 of 7 subcortical regions) and significant neuroprotection in cortex and hippocampus 1 day after CCI and glucose administration. These results indicate that acute episodes of post-TBI hyperglycemia can be beneficial and are consistent with other recent studies showing benefits of providing exogenous energy substrates during periods of increased cerebral metabolic demand. © 2013 Elsevier B.V. All rights reserved.
Elevated correlations in neuronal ensembles of mouse auditory cortex following parturition.
Rothschild, Gideon; Cohen, Lior; Mizrahi, Adi; Nelken, Israel
2013-07-31
The auditory cortex is malleable by experience. Previous studies of auditory plasticity have described experience-dependent changes in response profiles of single neurons or changes in global tonotopic organization. However, experience-dependent changes in the dynamics of local neural populations have remained unexplored. In this study, we examined the influence of a dramatic yet natural experience in the life of female mice, giving birth and becoming a mother on single neurons and neuronal ensembles in the primary auditory cortex (A1). Using in vivo two-photon calcium imaging and electrophysiological recordings from layer 2/3 in A1 of mothers and age-matched virgin mice, we monitored changes in the responses to a set of artificial and natural sounds. Population dynamics underwent large changes as measured by pairwise and higher-order correlations, with noise correlations increasing as much as twofold in lactating mothers. Concomitantly, changes in response properties of single neurons were modest and selective. Remarkably, despite the large changes in correlations, information about stimulus identity remained essentially the same in the two groups. Our results demonstrate changes in the correlation structure of neuronal activity as a result of a natural life event.
Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging
Patel, Tapan P.; Man, Karen; Firestein, Bonnie L.; Meaney, David F.
2017-01-01
Background Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s–1000 +neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. New method Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. Results We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. Comparison with existing method(s) We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. Conclusions We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. PMID:25629800
Neuronal and BBB damage induced by sera from patients with secondary progressive multiple sclerosis.
Proia, Patrizia; Schiera, Gabriella; Salemi, Giuseppe; Ragonese, Paolo; Savettieri, Giovanni; Di Liegro, Italia
2009-12-01
An important component of the pathogenic process of multiple sclerosis (MS) is the blood-brain barrier (BBB) damage. We recently set an in vitro model of BBB, based on a three-cell-type co-culture system, in which rat neurons and astrocytes synergistically induce brain capillary endothelial cells to form a monolayer with permeability properties resembling those of the physiological BBB. Herein we report that the serum from patients with secondary progressive multiple sclerosis (SPMS) has a damaging effect on isolated neurons. This finding suggests that neuronal damaging in MS could be a primary event and not only secondary to myelin damage, as generally assumed. SPMS serum affects the permeability of the BBB model, as indicated by the decrease of the transendothelial electrical resistance (TEER). Moreover, as shown by both immunofluorescence and Western blot analyses, BBB breaking is accompanied by a decrease of the synthesis as well as the peripheral localization of occludin, a structural protein of the tight junctions that are responsible for BBB properties.
Young, Gareth T; Gutteridge, Alex; Fox, Heather DE; Wilbrey, Anna L; Cao, Lishuang; Cho, Lily T; Brown, Adam R; Benn, Caroline L; Kammonen, Laura R; Friedman, Julia H; Bictash, Magda; Whiting, Paul; Bilsland, James G; Stevens, Edward B
2014-01-01
The generation of human sensory neurons by directed differentiation of pluripotent stem cells opens new opportunities for investigating the biology of pain. The inability to generate this cell type has meant that up until now their study has been reliant on the use of rodent models. Here, we use a combination of population and single-cell techniques to perform a detailed molecular, electrophysiological, and pharmacological phenotyping of sensory neurons derived from human embryonic stem cells. We describe the evolution of cell populations over 6 weeks of directed differentiation; a process that results in the generation of a largely homogeneous population of neurons that are both molecularly and functionally comparable to human sensory neurons derived from mature dorsal root ganglia. This work opens the prospect of using pluripotent stem-cell–derived sensory neurons to study human neuronal physiology and as in vitro models for drug discovery in pain and sensory disorders. PMID:24832007
Young, Gareth T; Gutteridge, Alex; Fox, Heather DE; Wilbrey, Anna L; Cao, Lishuang; Cho, Lily T; Brown, Adam R; Benn, Caroline L; Kammonen, Laura R; Friedman, Julia H; Bictash, Magda; Whiting, Paul; Bilsland, James G; Stevens, Edward B
2014-08-01
The generation of human sensory neurons by directed differentiation of pluripotent stem cells opens new opportunities for investigating the biology of pain. The inability to generate this cell type has meant that up until now their study has been reliant on the use of rodent models. Here, we use a combination of population and single-cell techniques to perform a detailed molecular, electrophysiological, and pharmacological phenotyping of sensory neurons derived from human embryonic stem cells. We describe the evolution of cell populations over 6 weeks of directed differentiation; a process that results in the generation of a largely homogeneous population of neurons that are both molecularly and functionally comparable to human sensory neurons derived from mature dorsal root ganglia. This work opens the prospect of using pluripotent stem-cell-derived sensory neurons to study human neuronal physiology and as in vitro models for drug discovery in pain and sensory disorders.
Interplay between population firing stability and single neuron dynamics in hippocampal networks
Slomowitz, Edden; Styr, Boaz; Vertkin, Irena; Milshtein-Parush, Hila; Nelken, Israel; Slutsky, Michael; Slutsky, Inna
2015-01-01
Neuronal circuits' ability to maintain the delicate balance between stability and flexibility in changing environments is critical for normal neuronal functioning. However, to what extent individual neurons and neuronal populations maintain internal firing properties remains largely unknown. In this study, we show that distributions of spontaneous population firing rates and synchrony are subject to accurate homeostatic control following increase of synaptic inhibition in cultured hippocampal networks. Reduction in firing rate triggered synaptic and intrinsic adaptive responses operating as global homeostatic mechanisms to maintain firing macro-stability, without achieving local homeostasis at the single-neuron level. Adaptive mechanisms, while stabilizing population firing properties, reduced short-term facilitation essential for synaptic discrimination of input patterns. Thus, invariant ongoing population dynamics emerge from intrinsically unstable activity patterns of individual neurons and synapses. The observed differences in the precision of homeostatic control at different spatial scales challenge cell-autonomous theory of network homeostasis and suggest the existence of network-wide regulation rules. DOI: http://dx.doi.org/10.7554/eLife.04378.001 PMID:25556699
Dasen, Jeremy S; De Camilli, Alessandro; Wang, Bin; Tucker, Philip W; Jessell, Thomas M
2008-07-25
The precision with which motor neurons innervate target muscles depends on a regulatory network of Hox transcription factors that translates neuronal identity into patterns of connectivity. We show that a single transcription factor, FoxP1, coordinates motor neuron subtype identity and connectivity through its activity as a Hox accessory factor. FoxP1 is expressed in Hox-sensitive motor columns and acts as a dose-dependent determinant of columnar fate. Inactivation of Foxp1 abolishes the output of the motor neuron Hox network, reverting the spinal motor system to an ancestral state. The loss of FoxP1 also changes the pattern of motor neuron connectivity, and in the limb motor axons appear to select their trajectories and muscle targets at random. Our findings show that FoxP1 is a crucial determinant of motor neuron diversification and connectivity, and clarify how this Hox regulatory network controls the formation of a topographic neural map.
NASA Astrophysics Data System (ADS)
Huber, Ludwig
2014-09-01
This comment addresses the first component of Fitch's framework: the computational power of single neurons [3]. Although I agree that traditional models of neural computation have vastly underestimated the computational power of single neurons, I am hesitant to follow him completely. The exclusive focus on neurons is likely to underestimate the importance of other cells in the brain. In the last years, two such cell types have received appropriate attention by neuroscientists: interneurons and glia. Interneurons are small, tightly packed cells involved in the control of information processing in learning and memory. Rather than transmitting externally (like motor or sensory neurons), these neurons process information within internal circuits of the brain (therefore also called 'relay neurons'). Some specialized interneuron subtypes temporally regulate the flow of information in a given cortical circuit during relevant behavioral events [4]. In the human brain approx. 100 billion interneurons control information processing and are implicated in disorders such as epilepsy and Parkinson's.
Tonomura, W; Moriguchi, H; Jimbo, Y; Konishi, S
2008-01-01
This paper describes an advanced Micro Channel Array (MCA) so as to record neuronal network at multiple points simultaneously. Developed MCA is designed for neuronal network analysis which has been studied by co-authors using MEA (Micro Electrode Arrays) system. The MCA employs the principle of the extracellular recording. Presented MCA has the following advantages. First of all, the electrodes integrated around individual micro channels are electrically isolated for parallel multipoint recording. Sucking and clamping of cells through micro channels is expected to improve the cellular selectivity and S/N ratio. In this study, hippocampal neurons were cultured on the developed MCA. As a result, the spontaneous and evoked spike potential could be recorded by sucking and clamping the cells at multiple points. Herein, we describe the successful experimental results together with the design and fabrication of the advanced MCA toward on-chip analysis of neuronal network.
Lee, Gyunghee; Sehgal, Ritika; Wang, Zixing; Nair, Sudershana; Kikuno, Keiko; Chen, Chun-Hong; Hay, Bruce; Park, Jae H.
2013-01-01
Summary In Drosophila melanogaster, combinatorial activities of four death genes, head involution defective (hid), reaper (rpr), grim, and sickle (skl), have been known to play crucial roles in the developmentally regulated programmed cell death (PCD) of various tissues. However, different expression patterns of the death genes also suggest distinct functions played by each. During early metamorphosis, a great number of larval neurons unfit for adult life style are removed by PCD. Among them are eight pairs of corazonin-expressing larval peptidergic neurons in the ventral nerve cord (vCrz). To reveal death genes responsible for the PCD of vCrz neurons, we examined extant and recently available mutations as well as RNA interference that disrupt functions of single or multiple death genes. We found grim as a chief proapoptotic gene and skl and rpr as minor ones. The function of grim is also required for PCD of the mitotic sibling cells of the vCrz neuronal precursors (EW3-sib) during embryonic neurogenesis. An intergenic region between grim and rpr, which, it has been suggested, may enhance expression of three death genes in embryonic neuroblasts, appears to play a role for the vCrz PCD, but not for the EW3-sib cell death. The death of vCrz neurons and EW3-sib is triggered by ecdysone and the Notch signaling pathway, respectively, suggesting distinct regulatory mechanisms of grim expression in a cell- and developmental stage-specific manner. PMID:23519152
Rybak, I A; O'Connor, R; Ross, A; Shevtsova, N A; Nuding, S C; Segers, L S; Shannon, R; Dick, T E; Dunin-Barkowski, W L; Orem, J M; Solomon, I C; Morris, K F; Lindsey, B G
2008-10-01
A large body of data suggests that the pontine respiratory group (PRG) is involved in respiratory phase-switching and the reconfiguration of the brain stem respiratory network. However, connectivity between the PRG and ventral respiratory column (VRC) in computational models has been largely ad hoc. We developed a network model with PRG-VRC connectivity inferred from coordinated in vivo experiments. Neurons were modeled in the "integrate-and-fire" style; some neurons had pacemaker properties derived from the model of Breen et al. We recapitulated earlier modeling results, including reproduction of activity profiles of different respiratory neurons and motor outputs, and their changes under different conditions (vagotomy, pontine lesions, etc.). The model also reproduced characteristic changes in neuronal and motor patterns observed in vivo during fictive cough and during hypoxia in non-rapid eye movement sleep. Our simulations suggested possible mechanisms for respiratory pattern reorganization during these behaviors. The model predicted that network- and pacemaker-generated rhythms could be co-expressed during the transition from gasping to eupnea, producing a combined "burst-ramp" pattern of phrenic discharges. To test this prediction, phrenic activity and multiple single neuron spike trains were monitored in vagotomized, decerebrate, immobilized, thoracotomized, and artificially ventilated cats during hypoxia and recovery. In most experiments, phrenic discharge patterns during recovery from hypoxia were similar to those predicted by the model. We conclude that under certain conditions, e.g., during recovery from severe brain hypoxia, components of a distributed network activity present during eupnea can be co-expressed with gasp patterns generated by a distinct, functionally "simplified" mechanism.
Chen, Audrey; Ng, Fanny; Lebestky, Tim; Grygoruk, Anna; Djapri, Christine; Lawal, Hakeem O.; Zaveri, Harshul A.; Mehanzel, Filmon; Najibi, Rod; Seidman, Gabriel; Murphy, Niall P.; Kelly, Rachel L.; Ackerson, Larry C.; Maidment, Nigel T.; Jackson, F. Rob; Krantz, David E.
2013-01-01
To investigate the regulation of Drosophila melanogaster behavior by biogenic amines, we have exploited the broad requirement of the vesicular monoamine transporter (VMAT) for the vesicular storage and exocytotic release of all monoamine neurotransmitters. We used the Drosophila VMAT (dVMAT) null mutant to globally ablate exocytotic amine release and then restored DVMAT activity in either individual or multiple aminergic systems, using transgenic rescue techniques. We find that larval survival, larval locomotion, and female fertility rely predominantly on octopaminergic circuits with little apparent input from the vesicular release of serotonin or dopamine. In contrast, male courtship and fertility can be rescued by expressing DVMAT in octopaminergic or dopaminergic neurons, suggesting potentially redundant circuits. Rescue of major aspects of adult locomotion and startle behavior required octopamine, but a complementary role was observed for serotonin. Interestingly, adult circadian behavior could not be rescued by expression of DVMAT in a single subtype of aminergic neurons, but required at least two systems, suggesting the possibility of unexpected cooperative interactions. Further experiments using this model will help determine how multiple aminergic systems may contribute to the regulation of other behaviors. Our data also highlight potential differences between behaviors regulated by standard exocytotic release and those regulated by other mechanisms. PMID:23086220
Lee, Norman; Schrode, Katrina M; Bee, Mark A
2017-09-01
Diverse animals communicate using multicomponent signals. How a receiver's central nervous system integrates multiple signal components remains largely unknown. We investigated how female green treefrogs (Hyla cinerea) integrate the multiple spectral components present in male advertisement calls. Typical calls have a bimodal spectrum consisting of formant-like low-frequency (~0.9 kHz) and high-frequency (~2.7 kHz) components that are transduced by different sensory organs in the inner ear. In behavioral experiments, only bimodal calls reliably elicited phonotaxis in no-choice tests, and they were selectively chosen over unimodal calls in two-alternative choice tests. Single neurons in the inferior colliculus of awake, passively listening subjects were classified as combination-insensitive units (27.9%) or combination-sensitive units (72.1%) based on patterns of relative responses to the same bimodal and unimodal calls. Combination-insensitive units responded similarly to the bimodal call and one or both unimodal calls. In contrast, combination-sensitive units exhibited both linear responses (i.e., linear summation) and, more commonly, nonlinear responses (e.g., facilitation, compressive summation, or suppression) to the spectral combination in the bimodal call. These results are consistent with the hypothesis that nonlinearities play potentially critical roles in spectral integration and in the neural processing of multicomponent communication signals.
Creation of defined single cell resolution neuronal circuits on microelectrode arrays
NASA Astrophysics Data System (ADS)
Pirlo, Russell Kirk
2009-12-01
The way cell-cell organization of neuronal networks influences activity and facilitates function is not well understood. Microelectrode arrays (MEAs) and advancing cell patterning technologies have enabled access to and control of in vitro neuronal networks spawning much new research in neuroscience and neuroengineering. We propose that small, simple networks of neurons with defined circuitry may serve as valuable research models where every connection can be analyzed, controlled and manipulated. Towards the goal of creating such neuronal networks we have applied microfabricated elastomeric membranes, surface modification and our unique laser cell patterning system to create defined neuronal circuits with single-cell precision on MEAs. Definition of synaptic connectivity was imposed by the 3D physical constraints of polydimethylsiloxane elastomeric membranes. The membranes had 20mum clear-through holes and 2-3mum deep channels which when applied to the surface of the MEA formed microwells to confine neurons to electrodes connected via shallow tunnels to direct neurite outgrowth. Tapering and turning of channels was used to influence neurite polarity. Biocompatibility of the membranes was increased by vacuum baking, oligomer extraction, and autoclaving. Membranes were bound to the MEA by oxygen plasma treatment and heated pressure. The MEA/membrane surface was treated with oxygen plasma, poly-D-lysine and laminin to improve neuron attachment, survival and neurite outgrowth. Prior to cell patterning the outer edge of culture area was seeded with 5x10 5 cells per cm and incubated for 2 days. Single embryonic day 7 chick forebrain neurons were then patterned into the microwells and onto the electrodes using our laser cell patterning system. Patterned neurons successfully attached to and were confined to the electrodes. Neurites extended through the interconnecting channels and connected with adjacent neurons. These results demonstrate that neuronal circuits can be created with clearly defined circuitry and a one-to-one neuron-electrode ratio. The techniques and processes described here may be used in future research to create defined neuronal circuits to model in vivo circuits and study neuronal network processing.
Takizawa, Tsubasa; Shibata, Mamoru; Kayama, Yohei; Shimizu, Toshihiko; Toriumi, Haruki; Ebine, Taeko; Unekawa, Miyuki; Koh, Anri; Yoshimura, Akihiko; Suzuki, Norihiro
2017-03-01
Single episodes of cortical spreading depression (CSD) are believed to cause typical migraine aura, whereas clusters of spreading depolarizations have been observed in cerebral ischemia and subarachnoid hemorrhage. We recently demonstrated that the release of high-mobility group box 1 (HMGB1) from cortical neurons after CSD in a rodent model is dependent on the number of CSD episodes, such that only multiple CSD episodes can induce significant HMGB1 release. Here, we report that only multiple CSD inductions caused microglial hypertrophy (activation) accompanied by a greater impact on the transcription activity of the HMGB1 receptor genes, TLR2 and TLR4, while the total number of cortical microglia was not affected. Both an HMGB1-neurtalizing antibody and the HMGB1 inhibitor glycyrrhizin abrogated multiple CSD-induced microglial hypertrophy. Moreover, multiple CSD inductions failed to induce microglial hypertrophy in TLR2/4 double knockout mice. These results strongly implicate the HMGB1-TLR2/4 axis in the activation of microglia following multiple CSD inductions. Increased expression of the lysosomal acid hydrolase cathepsin D was detected in activated microglia by immunostaining, suggesting that lysosomal phagocytic activity may be enhanced in multiple CSD-activated microglia.
Chiu, Isaac M; Barrett, Lee B; Williams, Erika K; Strochlic, David E; Lee, Seungkyu; Weyer, Andy D; Lou, Shan; Bryman, Gregory S; Roberson, David P; Ghasemlou, Nader; Piccoli, Cara; Ahat, Ezgi; Wang, Victor; Cobos, Enrique J; Stucky, Cheryl L; Ma, Qiufu; Liberles, Stephen D; Woolf, Clifford J
2014-01-01
The somatosensory nervous system is critical for the organism's ability to respond to mechanical, thermal, and nociceptive stimuli. Somatosensory neurons are functionally and anatomically diverse but their molecular profiles are not well-defined. Here, we used transcriptional profiling to analyze the detailed molecular signatures of dorsal root ganglion (DRG) sensory neurons. We used two mouse reporter lines and surface IB4 labeling to purify three major non-overlapping classes of neurons: 1) IB4+SNS-Cre/TdTomato+, 2) IB4−SNS-Cre/TdTomato+, and 3) Parv-Cre/TdTomato+ cells, encompassing the majority of nociceptive, pruriceptive, and proprioceptive neurons. These neurons displayed distinct expression patterns of ion channels, transcription factors, and GPCRs. Highly parallel qRT-PCR analysis of 334 single neurons selected by membership of the three populations demonstrated further diversity, with unbiased clustering analysis identifying six distinct subgroups. These data significantly increase our knowledge of the molecular identities of known DRG populations and uncover potentially novel subsets, revealing the complexity and diversity of those neurons underlying somatosensation. DOI: http://dx.doi.org/10.7554/eLife.04660.001 PMID:25525749
Patterns of fast synaptic cholinergic activation of neurons in the celiac ganglia of cats.
Niel, J P; Clerc, N; Jule, Y
1988-12-01
Fast nicotinic transmission was studied in vitro in neurons of isolated cat celiac ganglia. In the absence of nerve stimulation, neurons could be classified into three types: silent neurons, synaptically activated neurons, and spontaneously discharging neurons. In all three types, fast synaptic activation could be obtained in single neurons by stimulating with a single pulse both the splanchnic nerves or one of the peripheral nerves connected to the ganglia. During repetitive nerve stimulation, a gradual depression of the central and peripheral fast nicotinic activation occurred, which was not affected by phentolamine plus propranolol, domperidone, atropine, or naloxone. Repetitive nerve stimulation was followed by a long lasting discharge of excitatory postsynaptic potentials and action potentials that decreased gradually with time. This discharge, which was probably due to presynaptic or prejunctional facilitation of acetylcholine release from cholinergic terminals, was reduced by the application of phentolamine plus propranolol, domperidone, or atropine and increased with naloxone. The existence of the mechanisms described in this study reflects the complexity of the integrative processes at work in neurons of the cat celiac ganglia that involve fast synaptic cholinergic activation.
Hou, Baohua; Chen, Hengling; Qu, Xiangwei; Lin, Xianguang; Luo, Fang; Li, Chenhong
2015-11-11
In rat's sensory neurons, hyperpolarization-activated inward currents (Ih) play an essential role in mediating action potentials and contributing to neuronal excitability. Classified by the size of neurons and ages, we studied the Ih and transcription levels of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels using electrophysiology and the single-cell RT-PCR. In voltage-clamp studies, Ih and half-maximal activation voltage (V1/2) changed with age and size. An analysis of all HCN subtypes in dorsal root ganglion (DRG) neurons by single-cell RT-PCR was carried out. HCN1 and HCN3 in medium-small elderly neurons had a weak expression. HCN2 in newborns and HCN4 in elderly rats also had a weak expression. The aim of this study is to examine the age-related Ih and HCN channels subunits in different ages and sizes of DRG neurons. The results would be significant in understanding the physiological and pathophysiological function of different sizes of DRG neurons in different age periods.
NASA Astrophysics Data System (ADS)
Leifer, Andrew Michael
2011-07-01
This work presents optogenetics and real-time computer vision techniques to non-invasively manipulate and monitor neural activity with high spatiotemporal resolution in awake behaving Caenorhabditis elegans. These methods were employed to dissect the nematode's mechanosensory and motor circuits and to elucidate the neural control of wave propagation during forward locomotion. Additionally, similar computer vision methods were used to automatically detect and decode fluorescing DNA origami nanobarcodes, a new class of fluorescent reporter constructs. An optogenetic instrument capable of real-time light delivery with high spatiotemporal resolution to specified targets in freely moving C. elegans, the first such instrument of its kind, was developed. The instrument was used to probe the nematode's mechanosensory circuit, demonstrating that stimulation of a single mechanosensory neuron suffices to induce reversals. The instrument was also used to probe the motor circuit, demonstrating that inhibition of regions of cholinergic motor neurons blocks undulatory wave propagation and that muscle contractions can persist even without inputs from the motor neurons. The motor circuit was further probed using optogenetics and microfluidic techniques. Undulatory wave propagation during forward locomotion was observed to depend on stretch-sensitive signaling mediated by cholinergic motor neurons. Specifically, posterior body segments are compelled, through stretch-sensitive feedback, to bend in the same direction as anterior segments. This is the first explicit demonstration of such feedback and serves as a foundation for understanding motor circuits in other organisms. A real-time tracking system was developed to record intracellular calcium transients in single neurons while simultaneously monitoring macroscopic behavior of freely moving C. elegans. This was used to study the worm's stereotyped reversal behavior, the omega turn. Calcium transients corresponding to temporal features of the omega turn were observed in interneurons AVA and AVB. Optics and computer vision techniques similar to those developed for the C. elegans experiments were also used to detect DNA origami nanorod barcodes. An optimal Bayesian multiple hypothesis test was deployed to unambiguously classify each barcode as a member of one of 216 distinct barcode species. Overall, this set of experiments demonstrates the powerful role that optogenetics and computer vision can play in behavioral neuroscience and quantitative biophysics.
Patel, Tapan P.; Ventre, Scott C.; Geddes-Klein, Donna; Singh, Pallab K.
2014-01-01
Alterations in the activity of neural circuits are a common consequence of traumatic brain injury (TBI), but the relationship between single-neuron properties and the aggregate network behavior is not well understood. We recently reported that the GluN2B-containing NMDA receptors (NMDARs) are key in mediating mechanical forces during TBI, and that TBI produces a complex change in the functional connectivity of neuronal networks. Here, we evaluated whether cell-to-cell heterogeneity in the connectivity and aggregate contribution of GluN2B receptors to [Ca2+]i before injury influenced the functional rewiring, spontaneous activity, and network plasticity following injury using primary rat cortical dissociated neurons. We found that the functional connectivity of a neuron to its neighbors, combined with the relative influx of calcium through distinct NMDAR subtypes, together contributed to the individual neuronal response to trauma. Specifically, individual neurons whose [Ca2+]i oscillations were largely due to GluN2B NMDAR activation lost many of their functional targets 1 h following injury. In comparison, neurons with large GluN2A contribution or neurons with high functional connectivity both independently protected against injury-induced loss in connectivity. Mechanistically, we found that traumatic injury resulted in increased uncorrelated network activity, an effect linked to reduction of the voltage-sensitive Mg2+ block of GluN2B-containing NMDARs. This uncorrelated activation of GluN2B subtypes after injury significantly limited the potential for network remodeling in response to a plasticity stimulus. Together, our data suggest that two single-cell characteristics, the aggregate contribution of NMDAR subtypes and the number of functional connections, influence network structure following traumatic injury. PMID:24647941
Crewther, D P; Crewther, S G
2015-09-01
Although the neural locus of strabismic amblyopia has been shown to lie at the first site of binocular integration, first in cat and then in primate, an adequate mechanism is still lacking. Here we hypothesise that increased temporal dispersion of LGN X-cell afferents driven by the deviating eye onto single cortical neurons may provide a neural mechanism for strabismic amblyopia. This idea was investigated via single cell extracellular recordings of 93 X and 50 Y type LGN neurons from strabismic and normal cats. Both X and Y neurons driven by the non-deviating eye showed shorter latencies than those driven by either the strabismic or normal eyes. Also the mean latency difference between X and Y neurons was much greater for the strabismic cells compared with the other two groups. The incidence of lagged X-cells driven by the deviating eye of the strabismic cats was higher than that of LGN X-cells from normal animals. Remarkably, none of the cells recorded from the laminae driven by the non-deviating eye were of the lagged class. A simple computational model was constructed in which a mixture of lagged and non-lagged afferents converge on to single cortical neurons. Model cut-off spatial frequencies to a moving grating stimulus were sensitive to the temporal dispersion of the geniculate afferents. Thus strabismic amblyopia could be viewed as a lack of developmental tuning of geniculate lags for neurons driven by the amblyopic eye. Monocular control of fixation by the non-deviating eye is associated with reduced incidence of lagged neurons, suggesting that in normal vision, lagged neurons might play a role in maintaining binocular connections for cortical neurons. Copyright © 2014 Elsevier Ltd. All rights reserved.
Takahashi, Susumu; Anzai, Yuichiro; Sakurai, Yoshio
2003-07-01
Multi-neuronal recording with a tetrode is a powerful technique to reveal neuronal interactions in local circuits. However, it is difficult to detect precise spike timings among closely neighboring neurons because the spike waveforms of individual neurons overlap on the electrode when more than two neurons fire simultaneously. In addition, the spike waveforms of single neurons, especially in the presence of complex spikes, are often non-stationary. These problems limit the ability of ordinary spike sorting to sort multi-neuronal activities recorded using tetrodes into their single-neuron components. Though sorting with independent component analysis (ICA) can solve these problems, it has one serious limitation that the number of separated neurons must be less than the number of electrodes. Using a combination of ICA and the efficiency of ordinary spike sorting technique (k-means clustering), we developed an automatic procedure to solve the spike-overlapping and the non-stationarity problems with no limitation on the number of separated neurons. The results for the procedure applied to real multi-neuronal data demonstrated that some outliers which may be assigned to distinct clusters if ordinary spike-sorting methods were used can be identified as overlapping spikes, and that there are functional connections between a putative pyramidal neuron and its putative dendrite. These findings suggest that the combination of ICA and k-means clustering can provide insights into the precise nature of functional circuits among neurons, i.e. cell assemblies.
Hu, Peng; Fabyanic, Emily; Kwon, Deborah Y; Tang, Sheng; Zhou, Zhaolan; Wu, Hao
2017-12-07
Massively parallel single-cell RNA sequencing can precisely resolve cellular diversity in a high-throughput manner at low cost, but unbiased isolation of intact single cells from complex tissues such as adult mammalian brains is challenging. Here, we integrate sucrose-gradient-assisted purification of nuclei with droplet microfluidics to develop a highly scalable single-nucleus RNA-seq approach (sNucDrop-seq), which is free of enzymatic dissociation and nucleus sorting. By profiling ∼18,000 nuclei isolated from cortical tissues of adult mice, we demonstrate that sNucDrop-seq not only accurately reveals neuronal and non-neuronal subtype composition with high sensitivity but also enables in-depth analysis of transient transcriptional states driven by neuronal activity, at single-cell resolution, in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.
Neuron-Type-Specific Utility in a Brain-Machine Interface: a Pilot Study.
Garcia-Garcia, Martha G; Bergquist, Austin J; Vargas-Perez, Hector; Nagai, Mary K; Zariffa, Jose; Marquez-Chin, Cesar; Popovic, Milos R
2017-11-01
Firing rates of single cortical neurons can be volitionally modulated through biofeedback (i.e. operant conditioning), and this information can be transformed to control external devices (i.e. brain-machine interfaces; BMIs). However, not all neurons respond to operant conditioning in BMI implementation. Establishing criteria that predict neuron utility will assist translation of BMI research to clinical applications. Single cortical neurons (n=7) were recorded extracellularly from primary motor cortex of a Long-Evans rat. Recordings were incorporated into a BMI involving up-regulation of firing rate to control the brightness of a light-emitting-diode and subsequent reward. Neurons were classified as 'fast-spiking', 'bursting' or 'regular-spiking' according to waveform-width and intrinsic firing patterns. Fast-spiking and bursting neurons were found to up-regulate firing rate by a factor of 2.43±1.16, demonstrating high utility, while regular-spiking neurons decreased firing rates on average by a factor of 0.73±0.23, demonstrating low utility. The ability to select neurons with high utility will be important to minimize training times and maximize information yield in future clinical BMI applications. The highly contrasting utility observed between fast-spiking and bursting neurons versus regular-spiking neurons allows for the hypothesis to be advanced that intrinsic electrophysiological properties may be useful criteria that predict neuron utility in BMI implementation.
Intrinsic, nondeterministic circadian rhythm generation in identified mammalian neurons.
Webb, Alexis B; Angelo, Nikhil; Huettner, James E; Herzog, Erik D
2009-09-22
Circadian rhythms are modeled as reliable and self-sustained oscillations generated by single cells. The mammalian suprachiasmatic nucleus (SCN) keeps near 24-h time in vivo and in vitro, but the identity of the individual cellular pacemakers is unknown. We tested the hypothesis that circadian cycling is intrinsic to a unique class of SCN neurons by measuring firing rate or Period2 gene expression in single neurons. We found that fully isolated SCN neurons can sustain circadian cycling for at least 1 week. Plating SCN neurons at <100 cells/mm(2) eliminated synaptic inputs and revealed circadian neurons that contained arginine vasopressin (AVP) or vasoactive intestinal polypeptide (VIP) or neither. Surprisingly, arrhythmic neurons (nearly 80% of recorded neurons) also expressed these neuropeptides. Furthermore, neurons were observed to lose or gain circadian rhythmicity in these dispersed cell cultures, both spontaneously and in response to forskolin stimulation. In SCN explants treated with tetrodotoxin to block spike-dependent signaling, neurons gained or lost circadian cycling over many days. The rate of PERIOD2 protein accumulation on the previous cycle reliably predicted the spontaneous onset of arrhythmicity. We conclude that individual SCN neurons can generate circadian oscillations; however, there is no evidence for a specialized or anatomically localized class of cell-autonomous pacemakers. Instead, these results indicate that AVP, VIP, and other SCN neurons are intrinsic but unstable circadian oscillators that rely on network interactions to stabilize their otherwise noisy cycling.
Mean-field equations for neuronal networks with arbitrary degree distributions.
Nykamp, Duane Q; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex
2017-04-01
The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.
Mean-field equations for neuronal networks with arbitrary degree distributions
NASA Astrophysics Data System (ADS)
Nykamp, Duane Q.; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex
2017-04-01
The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.
Inferring Single Neuron Properties in Conductance Based Balanced Networks
Pool, Román Rossi; Mato, Germán
2011-01-01
Balanced states in large networks are a usual hypothesis for explaining the variability of neural activity in cortical systems. In this regime the statistics of the inputs is characterized by static and dynamic fluctuations. The dynamic fluctuations have a Gaussian distribution. Such statistics allows to use reverse correlation methods, by recording synaptic inputs and the spike trains of ongoing spontaneous activity without any additional input. By using this method, properties of the single neuron dynamics that are masked by the balanced state can be quantified. To show the feasibility of this approach we apply it to large networks of conductance based neurons. The networks are classified as Type I or Type II according to the bifurcations which neurons of the different populations undergo near the firing onset. We also analyze mixed networks, in which each population has a mixture of different neuronal types. We determine under which conditions the intrinsic noise generated by the network can be used to apply reverse correlation methods. We find that under realistic conditions we can ascertain with low error the types of neurons present in the network. We also find that data from neurons with similar firing rates can be combined to perform covariance analysis. We compare the results of these methods (that do not requite any external input) to the standard procedure (that requires the injection of Gaussian noise into a single neuron). We find a good agreement between the two procedures. PMID:22016730
Gerstner, Wulfram
2017-01-01
Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a microscopic model of randomly connected generalized integrate-and-fire neuron models. Each population consists of 50–2000 neurons of the same type but different populations account for different neuron types. The stochastic population equations that we find reveal how spike-history effects in single-neuron dynamics such as refractoriness and adaptation interact with finite-size fluctuations on the population level. Efficient integration of the stochastic mesoscopic equations reproduces the statistical behavior of the population activities obtained from microscopic simulations of a full spiking neural network model. The theory describes nonlinear emergent dynamics such as finite-size-induced stochastic transitions in multistable networks and synchronization in balanced networks of excitatory and inhibitory neurons. The mesoscopic equations are employed to rapidly integrate a model of a cortical microcircuit consisting of eight neuron types, which allows us to predict spontaneous population activities as well as evoked responses to thalamic input. Our theory establishes a general framework for modeling finite-size neural population dynamics based on single cell and synapse parameters and offers an efficient approach to analyzing cortical circuits and computations. PMID:28422957
NASA Astrophysics Data System (ADS)
Vardi, Roni; Goldental, Amir; Sardi, Shira; Sheinin, Anton; Kanter, Ido
2016-11-01
The increasing number of recording electrodes enhances the capability of capturing the network’s cooperative activity, however, using too many monitors might alter the properties of the measured neural network and induce noise. Using a technique that merges simultaneous multi-patch-clamp and multi-electrode array recordings of neural networks in-vitro, we show that the membrane potential of a single neuron is a reliable and super-sensitive probe for monitoring such cooperative activities and their detailed rhythms. Specifically, the membrane potential and the spiking activity of a single neuron are either highly correlated or highly anti-correlated with the time-dependent macroscopic activity of the entire network. This surprising observation also sheds light on the cooperative origin of neuronal burst in cultured networks. Our findings present an alternative flexible approach to the technique based on a massive tiling of networks by large-scale arrays of electrodes to monitor their activity.
Vardi, Roni; Goldental, Amir; Sardi, Shira; Sheinin, Anton; Kanter, Ido
2016-11-08
The increasing number of recording electrodes enhances the capability of capturing the network's cooperative activity, however, using too many monitors might alter the properties of the measured neural network and induce noise. Using a technique that merges simultaneous multi-patch-clamp and multi-electrode array recordings of neural networks in-vitro, we show that the membrane potential of a single neuron is a reliable and super-sensitive probe for monitoring such cooperative activities and their detailed rhythms. Specifically, the membrane potential and the spiking activity of a single neuron are either highly correlated or highly anti-correlated with the time-dependent macroscopic activity of the entire network. This surprising observation also sheds light on the cooperative origin of neuronal burst in cultured networks. Our findings present an alternative flexible approach to the technique based on a massive tiling of networks by large-scale arrays of electrodes to monitor their activity.
Vardi, Roni; Goldental, Amir; Sardi, Shira; Sheinin, Anton; Kanter, Ido
2016-01-01
The increasing number of recording electrodes enhances the capability of capturing the network’s cooperative activity, however, using too many monitors might alter the properties of the measured neural network and induce noise. Using a technique that merges simultaneous multi-patch-clamp and multi-electrode array recordings of neural networks in-vitro, we show that the membrane potential of a single neuron is a reliable and super-sensitive probe for monitoring such cooperative activities and their detailed rhythms. Specifically, the membrane potential and the spiking activity of a single neuron are either highly correlated or highly anti-correlated with the time-dependent macroscopic activity of the entire network. This surprising observation also sheds light on the cooperative origin of neuronal burst in cultured networks. Our findings present an alternative flexible approach to the technique based on a massive tiling of networks by large-scale arrays of electrodes to monitor their activity. PMID:27824075
A wireless neural recording system with a precision motorized microdrive for freely behaving animals
Hasegawa, Taku; Fujimoto, Hisataka; Tashiro, Koichiro; Nonomura, Mayu; Tsuchiya, Akira; Watanabe, Dai
2015-01-01
The brain is composed of many different types of neurons. Therefore, analysis of brain activity with single-cell resolution could provide fundamental insights into brain mechanisms. However, the electrical signal of an individual neuron is very small, and precise isolation of single neuronal activity from moving subjects is still challenging. To measure single-unit signals in actively behaving states, establishment of technologies that enable fine control of electrode positioning and strict spike sorting is essential. To further apply such a single-cell recording approach to small brain areas in naturally behaving animals in large spaces or during social interaction, we developed a compact wireless recording system with a motorized microdrive. Wireless control of electrode placement facilitates the exploration of single neuronal activity without affecting animal behaviors. Because the system is equipped with a newly developed data-encoding program, the recorded data are readily compressed almost to theoretical limits and securely transmitted to a host computer. Brain activity can thereby be stably monitored in real time and further analyzed using online or offline spike sorting. Our wireless recording approach using a precision motorized microdrive will become a powerful tool for studying brain mechanisms underlying natural or social behaviors. PMID:25597933
Izzo, Nicholas J.; Staniszewski, Agnes; To, Lillian; Fa, Mauro; Teich, Andrew F.; Saeed, Faisal; Wostein, Harrison; Walko, Thomas; Vaswani, Anisha; Wardius, Meghan; Syed, Zanobia; Ravenscroft, Jessica; Mozzoni, Kelsie; Silky, Colleen; Rehak, Courtney; Yurko, Raymond; Finn, Patricia; Look, Gary; Rishton, Gilbert; Safferstein, Hank; Miller, Miles; Johanson, Conrad; Stopa, Edward; Windisch, Manfred; Hutter-Paier, Birgit; Shamloo, Mehrdad; Arancio, Ottavio; LeVine, Harry; Catalano, Susan M.
2014-01-01
Synaptic dysfunction and loss caused by age-dependent accumulation of synaptotoxic beta amyloid (Abeta) 1–42 oligomers is proposed to underlie cognitive decline in Alzheimer's disease (AD). Alterations in membrane trafficking induced by Abeta oligomers mediates reduction in neuronal surface receptor expression that is the basis for inhibition of electrophysiological measures of synaptic plasticity and thus learning and memory. We have utilized phenotypic screens in mature, in vitro cultures of rat brain cells to identify small molecules which block or prevent the binding and effects of Abeta oligomers. Synthetic Abeta oligomers bind saturably to a single site on neuronal synapses and induce deficits in membrane trafficking in neuronal cultures with an EC50 that corresponds to its binding affinity. The therapeutic lead compounds we have found are pharmacological antagonists of Abeta oligomers, reducing the binding of Abeta oligomers to neurons in vitro, preventing spine loss in neurons and preventing and treating oligomer-induced deficits in membrane trafficking. These molecules are highly brain penetrant and prevent and restore cognitive deficits in mouse models of Alzheimer's disease. Counter-screening these compounds against a broad panel of potential CNS targets revealed they are highly potent and specific ligands of the sigma-2/PGRMC1 receptor. Brain concentrations of the compounds corresponding to greater than 80% receptor occupancy at the sigma-2/PGRMC1 receptor restore cognitive function in transgenic hAPP Swe/Ldn mice. These studies demonstrate that synthetic and human-derived Abeta oligomers act as pharmacologically-behaved ligands at neuronal receptors - i.e. they exhibit saturable binding to a target, they exert a functional effect related to their binding and their displacement by small molecule antagonists blocks their functional effect. The first-in-class small molecule receptor antagonists described here restore memory to normal in multiple AD models and sustain improvement long-term, representing a novel mechanism of action for disease-modifying Alzheimer's therapeutics. PMID:25390368
Izzo, Nicholas J; Staniszewski, Agnes; To, Lillian; Fa, Mauro; Teich, Andrew F; Saeed, Faisal; Wostein, Harrison; Walko, Thomas; Vaswani, Anisha; Wardius, Meghan; Syed, Zanobia; Ravenscroft, Jessica; Mozzoni, Kelsie; Silky, Colleen; Rehak, Courtney; Yurko, Raymond; Finn, Patricia; Look, Gary; Rishton, Gilbert; Safferstein, Hank; Miller, Miles; Johanson, Conrad; Stopa, Edward; Windisch, Manfred; Hutter-Paier, Birgit; Shamloo, Mehrdad; Arancio, Ottavio; LeVine, Harry; Catalano, Susan M
2014-01-01
Synaptic dysfunction and loss caused by age-dependent accumulation of synaptotoxic beta amyloid (Abeta) 1-42 oligomers is proposed to underlie cognitive decline in Alzheimer's disease (AD). Alterations in membrane trafficking induced by Abeta oligomers mediates reduction in neuronal surface receptor expression that is the basis for inhibition of electrophysiological measures of synaptic plasticity and thus learning and memory. We have utilized phenotypic screens in mature, in vitro cultures of rat brain cells to identify small molecules which block or prevent the binding and effects of Abeta oligomers. Synthetic Abeta oligomers bind saturably to a single site on neuronal synapses and induce deficits in membrane trafficking in neuronal cultures with an EC50 that corresponds to its binding affinity. The therapeutic lead compounds we have found are pharmacological antagonists of Abeta oligomers, reducing the binding of Abeta oligomers to neurons in vitro, preventing spine loss in neurons and preventing and treating oligomer-induced deficits in membrane trafficking. These molecules are highly brain penetrant and prevent and restore cognitive deficits in mouse models of Alzheimer's disease. Counter-screening these compounds against a broad panel of potential CNS targets revealed they are highly potent and specific ligands of the sigma-2/PGRMC1 receptor. Brain concentrations of the compounds corresponding to greater than 80% receptor occupancy at the sigma-2/PGRMC1 receptor restore cognitive function in transgenic hAPP Swe/Ldn mice. These studies demonstrate that synthetic and human-derived Abeta oligomers act as pharmacologically-behaved ligands at neuronal receptors--i.e. they exhibit saturable binding to a target, they exert a functional effect related to their binding and their displacement by small molecule antagonists blocks their functional effect. The first-in-class small molecule receptor antagonists described here restore memory to normal in multiple AD models and sustain improvement long-term, representing a novel mechanism of action for disease-modifying Alzheimer's therapeutics.
A RET-ER81-NRG1 Signaling Pathway Drives the Development of Pacinian Corpuscles.
Fleming, Michael S; Li, Jian J; Ramos, Daniel; Li, Tong; Talmage, David A; Abe, Shin-Ichi; Arber, Silvia; Luo, Wenqin
2016-10-05
Axon-Schwann cell interactions are crucial for the development, function, and repair of the peripheral nervous system, but mechanisms underlying communication between axons and nonmyelinating Schwann cells are unclear. Here, we show that ER81 is functionally required in a subset of mouse RET + mechanosensory neurons for formation of Pacinian corpuscles, which are composed of a single myelinated axon and multiple layers of nonmyelinating Schwann cells, and Ret is required for the maintenance of Er81 expression. Interestingly, Er81 mutants have normal myelination but exhibit deficient interactions between axons and corpuscle-forming nonmyelinating Schwann cells. Finally, ablating Neuregulin-1 (Nrg1) in mechanosensory neurons results in no Pacinian corpuscles, and an Nrg1 isoform not required for communication with myelinating Schwann cells is specifically decreased in Er81-null somatosensory neurons. Collectively, our results suggest that a RET-ER81-NRG1 signaling pathway promotes axon communication with nonmyelinating Schwann cells, and that neurons use distinct mechanisms to interact with different types of Schwann cells. Communication between neurons and Schwann cells is critical for development, normal function, and regeneration of the peripheral nervous system. Despite many studies about axonal communication with myelinating Schwann cells, mostly via a specific isoform of Neuregulin1, the molecular nature of axonal communication with nonmyelinating Schwann cells is poorly understood. Here, we described a RET-ER81-Neuregulin1 signaling pathway in neurons innervating Pacinian corpuscle somatosensory end organs, which is essential for communication between the innervating axon and the end organ nonmyelinating Schwann cells. We also showed that this signaling pathway uses isoforms of Neuregulin1 that are not involved in myelination, providing evidence that neurons use different isoforms of Neuregulin1 to interact with different types of Schwann cells. Copyright © 2016 the authors 0270-6474/16/3610337-19$15.00/0.
Vavoulis, Dimitrios V.; Straub, Volko A.; Aston, John A. D.; Feng, Jianfeng
2012-01-01
Traditional approaches to the problem of parameter estimation in biophysical models of neurons and neural networks usually adopt a global search algorithm (for example, an evolutionary algorithm), often in combination with a local search method (such as gradient descent) in order to minimize the value of a cost function, which measures the discrepancy between various features of the available experimental data and model output. In this study, we approach the problem of parameter estimation in conductance-based models of single neurons from a different perspective. By adopting a hidden-dynamical-systems formalism, we expressed parameter estimation as an inference problem in these systems, which can then be tackled using a range of well-established statistical inference methods. The particular method we used was Kitagawa's self-organizing state-space model, which was applied on a number of Hodgkin-Huxley-type models using simulated or actual electrophysiological data. We showed that the algorithm can be used to estimate a large number of parameters, including maximal conductances, reversal potentials, kinetics of ionic currents, measurement and intrinsic noise, based on low-dimensional experimental data and sufficiently informative priors in the form of pre-defined constraints imposed on model parameters. The algorithm remained operational even when very noisy experimental data were used. Importantly, by combining the self-organizing state-space model with an adaptive sampling algorithm akin to the Covariance Matrix Adaptation Evolution Strategy, we achieved a significant reduction in the variance of parameter estimates. The algorithm did not require the explicit formulation of a cost function and it was straightforward to apply on compartmental models and multiple data sets. Overall, the proposed methodology is particularly suitable for resolving high-dimensional inference problems based on noisy electrophysiological data and, therefore, a potentially useful tool in the construction of biophysical neuron models. PMID:22396632
NASA Technical Reports Server (NTRS)
Knuth, Kevin H.; Shah, Ankoor S.; Truccolo, Wilson; Ding, Ming-Zhou; Bressler, Steven L.; Schroeder, Charles E.
2003-01-01
Electric potentials and magnetic fields generated by ensembles of synchronously active neurons in response to external stimuli provide information essential to understanding the processes underlying cognitive and sensorimotor activity. Interpreting recordings of these potentials and fields is difficult as each detector records signals simultaneously generated by various regions throughout the brain. We introduce the differentially Variable Component Analysis (dVCA) algorithm, which relies on trial-to-trial variability in response amplitude and latency to identify multiple components. Using simulations we evaluate the importance of response variability to component identification, the robustness of dVCA to noise, and its ability to characterize single-trial data. Finally, we evaluate the technique using visually evoked field potentials recorded at incremental depths across the layers of cortical area VI, in an awake, behaving macaque monkey.
Electrical excitability: a spectrum of properties in the progeny of a single embryonic neuroblast.
Goodman, C S; Pearson, K G; Spitzer, N C
1980-01-01
We have examined the range of some properties of the progeny of a single embryonic precursor cell in the grasshopper. The approximately 100 progeny of this single neuroblast share certain features such as their transmitter and some aspects of their morphology; at the same time, however, they demonstrate a broad spectrum of electrical properties, from spiking to non-spiking neurons. The first-born progeny are spiking neurons with peripheral axons. Many of the progeny, including all of the last-born, do not generate action potentials. The nonspiking progeny are local intraganglionic neurons and appear to compose a major proportion of the progeny of this neuroblast. All of the nonspiking neurons have calcium inward current channels and can make action potentials when outward current channels are blocked. We propose a model for grasshopper neurogenesis based on cell lineage such that (i) certain features (e.g., transmitter) are shared by the progeny of all cell divisions from a single neuroblast, and (ii) other features (e.g., electrical properties) are shared by the progeny of a given birth position (e.g., first versus last born) from all of the neuroblasts. According to this model, the first-born progeny from all neuroblasts are spiking neurons, whereas the last-born are nonspiking. Images PMID:6246499
Geed, Shashwati; McCurdy, Martha L.; van Kan, Peter L. E.
2017-01-01
Coordinated reach-to-grasp movements require precise spatiotemporal synchrony between proximal forelimb muscles (shoulder, elbow) that transport the hand toward a target during reach, and distal muscles (wrist, digit) that simultaneously preshape and orient the hand for grasp. The precise mechanisms through which the redundant neuromuscular circuitry coordinates reach with grasp, however, remain unclear. Recently, Geed and Van Kan (2016) demonstrated, using exploratory factor analysis (EFA), that limited numbers of global, template-like transport/preshape- and grasp-related muscle components underlie the complexity and variability of intramuscular electromyograms (EMGs) of up to 21 distal and proximal muscles recorded while monkeys performed reach-to-grasp tasks. Importantly, transport/preshape- and grasp-related muscle components showed invariant spatiotemporal coupling, which provides a potential mechanism for coordinating forelimb muscles during reach-to-grasp movements. In the present study, we tested whether ensemble discharges of forelimb neurons in the cerebellar nucleus interpositus (NI) and its target, the magnocellular red nucleus (RNm), a source of rubrospinal fibers, function as neuronal correlates of the transport/preshape- and grasp-related muscle components we identified. EFA applied to single-unit discharges of populations of NI and RNm neurons recorded while the same monkeys that were used previously performed the same reach-to-grasp tasks, revealed neuronal components in the ensemble discharges of both NI and RNm neuronal populations with characteristics broadly similar to muscle components. Subsets of NI and RNm neuronal components were strongly and significantly crosscorrelated with subsets of muscle components, suggesting that similar functional units of reach-to-grasp behavior are expressed by NI and RNm neuronal populations and forelimb muscles. Importantly, like transport/preshape- and grasp-related muscle components, their NI and RNm neuronal correlates showed invariant spatiotemporal coupling. Clinical and lesion studies have reported disruption of coupling between reach and grasp following cerebellar damage; the present results expand on those studies by identifying a neuronal mechanism that may underlie cerebellar contributions to spatiotemporal coordination of distal and proximal limb muscles during reaching to grasp. We conclude that finding similar functional units of behavior expressed at multiple levels of information processing along interposito-rubrospinal pathways and forelimb muscles supports the hypothesis that functionally related populations of NI and RNm neurons act synergistically in the control of complex coordinated motor behaviors. PMID:28270752
Neural plasticity explored by correlative two-photon and electron/SPIM microscopy
NASA Astrophysics Data System (ADS)
Allegra Mascaro, A. L.; Silvestri, L.; Costantini, I.; Sacconi, L.; Maco, B.; Knott, G. W.; Pavone, F. S.
2013-06-01
Plasticity of the central nervous system is a complex process which involves the remodeling of neuronal processes and synaptic contacts. However, a single imaging technique can reveal only a small part of this complex machinery. To obtain a more complete view, complementary approaches should be combined. Two-photon fluorescence microscopy, combined with multi-photon laser nanosurgery, allow following the real-time dynamics of single neuronal processes in the cerebral cortex of living mice. The structural rearrangement elicited by this highly confined paradigm of injury can be imaged in vivo first, and then the same neuron could be retrieved ex-vivo and characterized in terms of ultrastructural features of the damaged neuronal branch by means of electron microscopy. Afterwards, we describe a method to integrate data from in vivo two-photon fluorescence imaging and ex vivo light sheet microscopy, based on the use of major blood vessels as reference chart. We show how the apical dendritic arbor of a single cortical pyramidal neuron imaged in living mice can be found in the large-scale brain reconstruction obtained with light sheet microscopy. Starting from its apical portion, the whole pyramidal neuron can then be segmented and located in the correct cortical layer. With the correlative approach presented here, researchers will be able to place in a three-dimensional anatomic context the neurons whose dynamics have been observed with high detail in vivo.
Functional magnetic resonance microscopy at single-cell resolution in Aplysia californica
Radecki, Guillaume; Nargeot, Romuald; Jelescu, Ileana Ozana; Le Bihan, Denis; Ciobanu, Luisa
2014-01-01
In this work, we show the feasibility of performing functional MRI studies with single-cell resolution. At ultrahigh magnetic field, manganese-enhanced magnetic resonance microscopy allows the identification of most motor neurons in the buccal network of Aplysia at low, nontoxic Mn2+ concentrations. We establish that Mn2+ accumulates intracellularly on injection into the living Aplysia and that its concentration increases when the animals are presented with a sensory stimulus. We also show that we can distinguish between neuronal activities elicited by different types of stimuli. This method opens up a new avenue into probing the functional organization and plasticity of neuronal networks involved in goal-directed behaviors with single-cell resolution. PMID:24872449
Dynamics of Multistable States during Ongoing and Evoked Cortical Activity
Mazzucato, Luca
2015-01-01
Single-trial analyses of ensemble activity in alert animals demonstrate that cortical circuits dynamics evolve through temporal sequences of metastable states. Metastability has been studied for its potential role in sensory coding, memory, and decision-making. Yet, very little is known about the network mechanisms responsible for its genesis. It is often assumed that the onset of state sequences is triggered by an external stimulus. Here we show that state sequences can be observed also in the absence of overt sensory stimulation. Analysis of multielectrode recordings from the gustatory cortex of alert rats revealed ongoing sequences of states, where single neurons spontaneously attain several firing rates across different states. This single-neuron multistability represents a challenge to existing spiking network models, where typically each neuron is at most bistable. We present a recurrent spiking network model that accounts for both the spontaneous generation of state sequences and the multistability in single-neuron firing rates. Each state results from the activation of neural clusters with potentiated intracluster connections, with the firing rate in each cluster depending on the number of active clusters. Simulations show that the model's ensemble activity hops among the different states, reproducing the ongoing dynamics observed in the data. When probed with external stimuli, the model predicts the quenching of single-neuron multistability into bistability and the reduction of trial-by-trial variability. Both predictions were confirmed in the data. Together, these results provide a theoretical framework that captures both ongoing and evoked network dynamics in a single mechanistic model. PMID:26019337
Eberwine, James; Bartfai, Tamas
2011-03-01
We report on an 'unbiased' molecular characterization of individual, adult neurons, active in a central, anterior hypothalamic neuronal circuit, by establishing cDNA libraries from each individual, electrophysiologically identified warm sensitive neuron (WSN). The cDNA libraries were analyzed by Affymetrix microarray. The presence and frequency of cDNAs were confirmed and enhanced with Illumina sequencing of each single cell cDNA library. cDNAs encoding the GABA biosynthetic enzyme Gad1 and of adrenomedullin, galanin, prodynorphin, somatostatin, and tachykinin were found in the WSNs. The functional cellular and in vivo studies on dozens of the more than 500 neurotransmitters, hormone receptors and ion channels, whose cDNA was identified and sequence confirmed, suggest little or no discrepancy between the transcriptional and functional data in WSNs; whenever agonists were available for a receptor whose cDNA was identified, a functional response was found. Sequencing single neuron libraries permitted identification of rarely expressed receptors like the insulin receptor, adiponectin receptor 2 and of receptor heterodimers; information that is lost when pooling cells leads to dilution of signals and mixing signals. Despite the common electrophysiological phenotype and uniform Gad1 expression, WSN transcriptomes show heterogeneity, suggesting strong epigenetic influence on the transcriptome. Our study suggests that it is well-worth interrogating the cDNA libraries of single neurons by sequencing and chipping. Copyright © 2010 Elsevier Inc. All rights reserved.
Generation and expansion of highly pure motor neuron progenitors from human pluripotent stem cells.
Du, Zhong-Wei; Chen, Hong; Liu, Huisheng; Lu, Jianfeng; Qian, Kun; Huang, CindyTzu-Ling; Zhong, Xiaofen; Fan, Frank; Zhang, Su-Chun
2015-03-25
Human pluripotent stem cells (hPSCs) have opened new opportunities for understanding human development, modelling disease processes and developing new therapeutics. However, these applications are hindered by the low efficiency and heterogeneity of cell types, such as motorneurons (MNs), differentiated from hPSCs as well as our inability to maintain the potency of lineage-committed progenitors. Here by using a combination of small molecules that regulate multiple signalling pathways, we develop a method to guide human embryonic stem cells to a near-pure population (>95%) of motor neuron progenitors (MNPs) in 12 days, and an enriched population (>90%) of functionally mature MNs in an additional 16 days. More importantly, the MNPs can be expanded for at least five passages so that a single MNP can be amplified to 1 × 10(4). This method is reproducible in human-induced pluripotent stem cells and is applied to model MN-degenerative diseases and in proof-of-principle drug-screening assays.
Dopaminergic neurons write and update memories with cell-type-specific rules
Aso, Yoshinori; Rubin, Gerald M
2016-01-01
Associative learning is thought to involve parallel and distributed mechanisms of memory formation and storage. In Drosophila, the mushroom body (MB) is the major site of associative odor memory formation. Previously we described the anatomy of the adult MB and defined 20 types of dopaminergic neurons (DANs) that each innervate distinct MB compartments (Aso et al., 2014a, 2014b). Here we compare the properties of memories formed by optogenetic activation of individual DAN cell types. We found extensive differences in training requirements for memory formation, decay dynamics, storage capacity and flexibility to learn new associations. Even a single DAN cell type can either write or reduce an aversive memory, or write an appetitive memory, depending on when it is activated relative to odor delivery. Our results show that different learning rules are executed in seemingly parallel memory systems, providing multiple distinct circuit-based strategies to predict future events from past experiences. DOI: http://dx.doi.org/10.7554/eLife.16135.001 PMID:27441388
Democracy-independence trade-off in oscillating dendrites and its implications for grid cells.
Remme, Michiel W H; Lengyel, Máté; Gutkin, Boris S
2010-05-13
Dendritic democracy and independence have been characterized for near-instantaneous processing of synaptic inputs. However, a wide class of neuronal computations requires input integration on long timescales. As a paradigmatic example, entorhinal grid fields have been thought to be generated by the democratic summation of independent dendritic oscillations performing direction-selective path integration. We analyzed how multiple dendritic oscillators embedded in the same neuron integrate inputs separately and determine somatic membrane voltage jointly. We found that the interaction of dendritic oscillations leads to phase locking, which sets an upper limit on the timescale for independent input integration. Factors that increase this timescale also decrease the influence that the dendritic oscillations exert on somatic voltage. In entorhinal stellate cells, interdendritic coupling dominates and causes these cells to act as single oscillators. Our results suggest a fundamental trade-off between local and global processing in dendritic trees integrating ongoing signals. Copyright 2010 Elsevier Inc. All rights reserved.
Wang, Yangyang; Rubin, Jonathan E
2017-12-01
Neural networks generate a variety of rhythmic activity patterns, often involving different timescales. One example arises in the respiratory network in the pre-Bötzinger complex of the mammalian brainstem, which can generate the eupneic rhythm associated with normal respiration as well as recurrent low-frequency, large-amplitude bursts associated with sighing. Two competing hypotheses have been proposed to explain sigh generation: the recruitment of a neuronal population distinct from the eupneic rhythm-generating subpopulation or the reconfiguration of activity within a single population. Here, we consider two recent computational models, one of which represents each of the hypotheses. We use methods of dynamical systems theory, such as fast-slow decomposition, averaging, and bifurcation analysis, to understand the multiple-timescale mechanisms underlying sigh generation in each model. In the course of our analysis, we discover that a third timescale is required to generate sighs in both models. Furthermore, we identify the similarities of the underlying mechanisms in the two models and the aspects in which they differ.
A Fully Automated Approach to Spike Sorting.
Chung, Jason E; Magland, Jeremy F; Barnett, Alex H; Tolosa, Vanessa M; Tooker, Angela C; Lee, Kye Y; Shah, Kedar G; Felix, Sarah H; Frank, Loren M; Greengard, Leslie F
2017-09-13
Understanding the detailed dynamics of neuronal networks will require the simultaneous measurement of spike trains from hundreds of neurons (or more). Currently, approaches to extracting spike times and labels from raw data are time consuming, lack standardization, and involve manual intervention, making it difficult to maintain data provenance and assess the quality of scientific results. Here, we describe an automated clustering approach and associated software package that addresses these problems and provides novel cluster quality metrics. We show that our approach has accuracy comparable to or exceeding that achieved using manual or semi-manual techniques with desktop central processing unit (CPU) runtimes faster than acquisition time for up to hundreds of electrodes. Moreover, a single choice of parameters in the algorithm is effective for a variety of electrode geometries and across multiple brain regions. This algorithm has the potential to enable reproducible and automated spike sorting of larger scale recordings than is currently possible. Copyright © 2017 Elsevier Inc. All rights reserved.
Block-Cell-Printing for live single-cell printing
Zhang, Kai; Chou, Chao-Kai; Xia, Xiaofeng; Hung, Mien-Chie; Qin, Lidong
2014-01-01
A unique live-cell printing technique, termed “Block-Cell-Printing” (BloC-Printing), allows for convenient, precise, multiplexed, and high-throughput printing of functional single-cell arrays. Adapted from woodblock printing techniques, the approach employs microfluidic arrays of hook-shaped traps to hold cells at designated positions and directly transfer the anchored cells onto various substrates. BloC-Printing has a minimum turnaround time of 0.5 h, a maximum resolution of 5 µm, close to 100% cell viability, the ability to handle multiple cell types, and efficiently construct protrusion-connected single-cell arrays. The approach enables the large-scale formation of heterotypic cell pairs with controlled morphology and allows for material transport through gap junction intercellular communication. When six types of breast cancer cells are allowed to extend membrane protrusions in the BloC-Printing device for 3 h, multiple biophysical characteristics of cells—including the protrusion percentage, extension rate, and cell length—are easily quantified and found to correlate well with their migration levels. In light of this discovery, BloC-Printing may serve as a rapid and high-throughput cell protrusion characterization tool to measure the invasion and migration capability of cancer cells. Furthermore, primary neurons are also compatible with BloC-Printing. PMID:24516129
Neural Computations in a Dynamical System with Multiple Time Scales.
Mi, Yuanyuan; Lin, Xiaohan; Wu, Si
2016-01-01
Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.
An NV-Diamond Magnetic Imager for Neuroscience
NASA Astrophysics Data System (ADS)
Turner, Matthew; Schloss, Jennifer; Bauch, Erik; Hart, Connor; Walsworth, Ronald
2017-04-01
We present recent progress towards imaging time-varying magnetic fields from neurons using nitrogen-vacancy centers in diamond. The diamond neuron imager is noninvasive, label-free, and achieves single-cell resolution and state-of-the-art broadband sensitivity. By imaging magnetic fields from injected currents in mammalian neurons, we will map functional neuronal network connections and illuminate biophysical properties of neurons invisible to traditional electrophysiology. Furthermore, through enhancing magnetometer sensitivity, we aim to demonstrate real-time imaging of action potentials from networks of mammalian neurons.
Optimal Detection of a Localized Perturbation in Random Networks of Integrate-and-Fire Neurons.
Bernardi, Davide; Lindner, Benjamin
2017-06-30
Experimental and theoretical studies suggest that cortical networks are chaotic and coding relies on averages over large populations. However, there is evidence that rats can respond to the short stimulation of a single cortical cell, a theoretically unexplained fact. We study effects of single-cell stimulation on a large recurrent network of integrate-and-fire neurons and propose a simple way to detect the perturbation. Detection rates obtained from simulations and analytical estimates are similar to experimental response rates if the readout is slightly biased towards specific neurons. Near-optimal detection is attained for a broad range of intermediate values of the mean coupling between neurons.
Optimal Detection of a Localized Perturbation in Random Networks of Integrate-and-Fire Neurons
NASA Astrophysics Data System (ADS)
Bernardi, Davide; Lindner, Benjamin
2017-06-01
Experimental and theoretical studies suggest that cortical networks are chaotic and coding relies on averages over large populations. However, there is evidence that rats can respond to the short stimulation of a single cortical cell, a theoretically unexplained fact. We study effects of single-cell stimulation on a large recurrent network of integrate-and-fire neurons and propose a simple way to detect the perturbation. Detection rates obtained from simulations and analytical estimates are similar to experimental response rates if the readout is slightly biased towards specific neurons. Near-optimal detection is attained for a broad range of intermediate values of the mean coupling between neurons.
Kahan, Anat; Ben-Shaul, Yoram
2016-01-01
For many animals, chemosensation is essential for guiding social behavior. However, because multiple factors can modulate levels of individual chemical cues, deriving information about other individuals via natural chemical stimuli involves considerable challenges. How social information is extracted despite these sources of variability is poorly understood. The vomeronasal system provides an excellent opportunity to study this topic due to its role in detecting socially relevant traits. Here, we focus on two such traits: a female mouse’s strain and reproductive state. In particular, we measure stimulus-induced neuronal activity in the accessory olfactory bulb (AOB) in response to various dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus female mice from two different strains. We first show that all tested secretions provide information about a female’s receptivity and genotype. Next, we investigate how these traits can be decoded from neuronal activity despite multiple sources of variability. We show that individual neurons are limited in their capacity to allow trait classification across multiple sources of variability. However, simple linear classifiers sampling neuronal activity from small neuronal ensembles can provide a substantial improvement over that attained with individual units. Furthermore, we show that some traits are more efficiently detected than others, and that particular secretions may be optimized for conveying information about specific traits. Across all tested stimulus sources, discrimination between strains is more accurate than discrimination of receptivity, and detection of receptivity is more accurate with vaginal secretions than with urine. Our findings highlight the challenges of chemosensory processing of natural stimuli, and suggest that downstream readout stages decode multiple behaviorally relevant traits by sampling information from distinct but overlapping populations of AOB neurons. PMID:26938460
Kahan, Anat; Ben-Shaul, Yoram
2016-03-01
For many animals, chemosensation is essential for guiding social behavior. However, because multiple factors can modulate levels of individual chemical cues, deriving information about other individuals via natural chemical stimuli involves considerable challenges. How social information is extracted despite these sources of variability is poorly understood. The vomeronasal system provides an excellent opportunity to study this topic due to its role in detecting socially relevant traits. Here, we focus on two such traits: a female mouse's strain and reproductive state. In particular, we measure stimulus-induced neuronal activity in the accessory olfactory bulb (AOB) in response to various dilutions of urine, vaginal secretions, and saliva, from estrus and non-estrus female mice from two different strains. We first show that all tested secretions provide information about a female's receptivity and genotype. Next, we investigate how these traits can be decoded from neuronal activity despite multiple sources of variability. We show that individual neurons are limited in their capacity to allow trait classification across multiple sources of variability. However, simple linear classifiers sampling neuronal activity from small neuronal ensembles can provide a substantial improvement over that attained with individual units. Furthermore, we show that some traits are more efficiently detected than others, and that particular secretions may be optimized for conveying information about specific traits. Across all tested stimulus sources, discrimination between strains is more accurate than discrimination of receptivity, and detection of receptivity is more accurate with vaginal secretions than with urine. Our findings highlight the challenges of chemosensory processing of natural stimuli, and suggest that downstream readout stages decode multiple behaviorally relevant traits by sampling information from distinct but overlapping populations of AOB neurons.
Single neuronal recordings using surface micromachined polysilicon microelectrodes.
Muthuswamy, Jit; Okandan, Murat; Jackson, Nathan
2005-03-15
Bulk micromachining techniques of silicon have been used successfully in the past several years to microfabricate microelectrodes for monitoring single neurons in acute and chronic experiments. In this study we report for the first time a novel surface micromachining technique to microfabricate a very thin polysilicon microelectrode that can be used for monitoring single-unit activity in the central nervous system. The microelectrodes are 3 mm long and 50 microm x 3.75 microm in cross-section. Excellent signal to noise ratios in the order of 25-35 dB were obtained while recording neuronal action potentials. The microelectrodes successfully penetrated the brains after a microincision of the dura mater. Chronic implantation of the microprobe for up to 33 days produced only minor gliosis. Since the polysilicon shank acts as a conductor, additional processing steps involved in laying conductor lines on silicon substrates are avoided. Further, surface micromachining allows for fabricating extremely thin microelectrodes which could result in decreased inflammatory responses. We conclude that the polysilicon microelectrode reported here could be a complementary approach to bulk-micromachined silicon microelectrodes for chronic monitoring of single neurons in the central nervous system.
Local structure of subcellular input retinotopy in an identified visual interneuron
NASA Astrophysics Data System (ADS)
Zhu, Ying; Gabbiani, Fabrizio; Fabrizio Gabbiani's lab Team
2015-03-01
How does the spatial layout of the projections that a neuron receives impact its synaptic integration and computation? What is the mapping topography of subcellular wiring at the single neuron level? The LGMD (lobula giant movement detector) neuron in the locust is an identified neuron that responds preferentially to objects approaching on a collision course. It receives excitatory inputs from the entire visual hemifield through calcium-permeable nicotinic acetylcholine receptors. Previous work showed that the projection from the locust compound eye to the LGMD preserved retinotopy down to the level of a single ommatidium (facet) by employing in vivo widefield calcium imaging. Because widefield imaging relies on global excitation of the preparation and has a relatively low resolution, previous work could not investigate this retinotopic mapping at the level of individual thin dendritic branches. Our current work employs a custom-built two-photon microscope with sub-micron resolution in conjunction with a single-facet stimulation setup that provides visual stimuli to the single ommatidium of locust adequate to explore the local structure of this retinotopy at a finer level. We would thank NIMH for funding this research.
Resolving rates of mutation in the brain using single-neuron genomics
Evrony, Gilad D; Lee, Eunjung; Park, Peter J; Walsh, Christopher A
2016-01-01
Whether somatic mutations contribute functional diversity to brain cells is a long-standing question. Single-neuron genomics enables direct measurement of somatic mutation rates in human brain and promises to answer this question. A recent study (Upton et al., 2015) reported high rates of somatic LINE-1 element (L1) retrotransposition in the hippocampus and cerebral cortex that would have major implications for normal brain function, and suggested that these events preferentially impact genes important for neuronal function. We identify aspects of the single-cell sequencing approach, bioinformatic analysis, and validation methods that led to thousands of artifacts being interpreted as somatic mutation events. Our reanalysis supports a mutation frequency of approximately 0.2 events per cell, which is about fifty-fold lower than reported, confirming that L1 elements mobilize in some human neurons but indicating that L1 mosaicism is not ubiquitous. Through consideration of the challenges identified, we provide a foundation and framework for designing single-cell genomics studies. DOI: http://dx.doi.org/10.7554/eLife.12966.001 PMID:26901440
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.
Seiler, Stefanie; Di Santo, Stefano; Sahli, Sebastian; Andereggen, Lukas; Widmer, Hans Rudolf
2017-08-01
Cell transplantation using ventral mesencephalic tissue is an experimental approach to treat Parkinson's disease. This approach is limited by poor survival of the transplants and the high number of dopaminergic neurons needed for grafting. Increasing the yield of dopaminergic neurons in donor tissue is of great importance. We have previously shown that antagonization of the Nogo-receptor 1 by NEP1-40 promoted survival of cultured dopaminergic neurons and exposure to neurotrophin-4/5 increased dopaminergic cell densities in organotypic midbrain cultures. We investigated whether a combination of both treatments offers a novel tool to further improve dopaminergic neuron survival. Rat embryonic ventral mesencephalic neurons grown as organotypic free-floating roller tube or primary dissociated cultures were exposed to neurotrophin-4/5 and NEP1-40. The combined and single factor treatment resulted in significantly higher numbers of tyrosine hydroxylase positive neurons compared to controls. Significantly stronger tyrosine hydroxylase signal intensity was detected by Western blotting in the combination-treated cultures compared to controls but not compared to single factor treatments. Neurotrophin-4/5 and the combined treatment showed significantly higher signals for the neuronal marker microtubule-associated protein 2 in Western blots compared to control while no effects were observed for the astroglial marker glial fibrillary acidic protein between groups, suggesting that neurotrophin-4/5 targets mainly neuronal cells. Finally, NEP1-40 and the combined treatment significantly augmented tyrosine hydroxylase positive neurite length. Summarizing, our findings substantiate that antagonization of the Nogo-receptor 1 promotes dopaminergic neurons but does not further increase the yield of dopaminergic neurons and their morphological complexity when combined with neurotrophin-4/5 hinting to the idea that these treatments might exert their effects by activating common downstream pathways. Copyright © 2017 Elsevier B.V. All rights reserved.
Self-Consistent Scheme for Spike-Train Power Spectra in Heterogeneous Sparse Networks.
Pena, Rodrigo F O; Vellmer, Sebastian; Bernardi, Davide; Roque, Antonio C; Lindner, Benjamin
2018-01-01
Recurrent networks of spiking neurons can be in an asynchronous state characterized by low or absent cross-correlations and spike statistics which resemble those of cortical neurons. Although spatial correlations are negligible in this state, neurons can show pronounced temporal correlations in their spike trains that can be quantified by the autocorrelation function or the spike-train power spectrum. Depending on cellular and network parameters, correlations display diverse patterns (ranging from simple refractory-period effects and stochastic oscillations to slow fluctuations) and it is generally not well-understood how these dependencies come about. Previous work has explored how the single-cell correlations in a homogeneous network (excitatory and inhibitory integrate-and-fire neurons with nearly balanced mean recurrent input) can be determined numerically from an iterative single-neuron simulation. Such a scheme is based on the fact that every neuron is driven by the network noise (i.e., the input currents from all its presynaptic partners) but also contributes to the network noise, leading to a self-consistency condition for the input and output spectra. Here we first extend this scheme to homogeneous networks with strong recurrent inhibition and a synaptic filter, in which instabilities of the previous scheme are avoided by an averaging procedure. We then extend the scheme to heterogeneous networks in which (i) different neural subpopulations (e.g., excitatory and inhibitory neurons) have different cellular or connectivity parameters; (ii) the number and strength of the input connections are random (Erdős-Rényi topology) and thus different among neurons. In all heterogeneous cases, neurons are lumped in different classes each of which is represented by a single neuron in the iterative scheme; in addition, we make a Gaussian approximation of the input current to the neuron. These approximations seem to be justified over a broad range of parameters as indicated by comparison with simulation results of large recurrent networks. Our method can help to elucidate how network heterogeneity shapes the asynchronous state in recurrent neural networks.
Burst firing and modulation of functional connectivity in cat striate cortex.
Snider, R K; Kabara, J F; Roig, B R; Bonds, A B
1998-08-01
We studied the influences of the temporal firing patterns of presynaptic cat visual cortical cells on spike generation by postsynaptic cells. Multiunit recordings were dissected into the activity of individual neurons within the recorded group. Cross-correlation analysis was then used to identify directly coupled neuron pairs. The 22 multiunit groups recorded typically showed activity from two to six neurons, each containing between 1 and 15 neuron pairs. From a total of 241 neuron pairs, 91 (38%) had a shifted cross-correlation peak, which indicated a possible direct connection. Only two multiunit groups contained no shifted peaks. Burst activity, defined by groups of two or more spikes with intervals of =8 ms from any single neuron, was analyzed in terms of its effectiveness in eliciting a spike from a second, driven neuron. We defined effectiveness as the percentage of spikes from the driving neuron that are time related to spikes of the driven neuron. The effectiveness of bursts (of any length) in eliciting a time-related response spike averaged 18.53% across all measurements as compared with the effectiveness of single spikes, which averaged 9.53%. Longer bursts were more effective than shorter ones. Effectiveness was reduced with spatially nonoptimal, as opposed to optimal, stimuli. The effectiveness of both bursts and single spikes decreased by the same amount across measurements with nonoptimal orientations, spatial frequencies and contrasts. At similar firing rates and burst lengths, the decrease was more pronounced for nonoptimal orientations than for lower contrasts, suggesting the existence of a mechanism that reduces effectiveness at nonoptimal orientations. These results support the hypothesis that neural information can be emphasized via instantaneous rate coding that is not preserved over long intervals or over trials. This is consistent with the integrate and fire model, where bursts participate in temporal integration.
Processing of Intraoral Olfactory and Gustatory Signals in the Gustatory Cortex of Awake Rats.
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.
Wang, Chi Chiu; Kadota, Mitsutaka; Nishigaki, Ryuichi; Kazuki, Yasuhiro; Shirayoshi, Yasuaki; Rogers, Michael Scott; Gojobori, Takashi; Ikeo, Kazuho; Oshimura, Mitsuo
2004-02-06
Defects in neurogenesis and neuronal differentiation in the fetal brain of Down syndrome (DS) patients lead to the apparent neuropathological abnormalities and contribute to the phenotypic characters of mental retardation, and premature development of Alzheimer's disease, those being the most common phenotype in DS. In order to understand the molecular mechanism underlying the cause of phenotypic abnormalities in the DS brain, we have utilized an in vitro model of TT2F mouse embryonic stem cells containing a single human chromosome 21 (hChr21) to study neuron development and neuronal differentiation by microarray containing 15K developmentally expressed cDNAs. Defective neuronal differentiation in the presence of extra hChr21 manifested primarily the post-transcriptional and translational modification, such as Mrpl10, SNAPC3, Srprb, SF3a60 in the early neuronal stem cell stage, and Mrps18a, Eef1g, and Ubce8 in the late differentiated stage. Hierarchical clustering patterned specific expression of hChr21 gene dosage effects on neuron outgrowth, migration, and differentiation, such as Syngr2, Dncic2, Eif3sf, and Peg3.
Single neuron modeling and data assimilation in BNST neurons
NASA Astrophysics Data System (ADS)
Farsian, Reza
Neurons, although tiny in size, are vastly complicated systems, which are responsible for the most basic yet essential functions of any nervous system. Even the most simple models of single neurons are usually high dimensional, nonlinear, and contain many parameters and states which are unobservable in a typical neurophysiological experiment. One of the most fundamental problems in experimental neurophysiology is the estimation of these parameters and states, since knowing their values is essential in identification, model construction, and forward prediction of biological neurons. Common methods of parameter and state estimation do not perform well for neural models due to their high dimensionality and nonlinearity. In this dissertation, two alternative approaches for parameters and state estimation of biological neurons have been demonstrated: dynamical parameter estimation (DPE) and a Markov Chain Monte Carlo (MCMC) method. The first method uses elements of chaos control and synchronization theory for parameter and state estimation. MCMC is a statistical approach which uses a path integral formulation to evaluate a mean and an error bound for these unobserved parameters and states. These methods have been applied to biological system of neurons in Bed Nucleus of Stria Termialis neurons (BNST) of rats. State and parameters of neurons in both systems were estimated, and their value were used for recreating a realistic model and predicting the behavior of the neurons successfully. The knowledge of biological parameters can ultimately provide a better understanding of the internal dynamics of a neuron in order to build robust models of neuron networks.