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population coding is essential for rapid information processing in the moth antennal lobe

BRAIN RESEARCH 2013年 1536卷 88-96页

作者： Kobayashi, Ryota Namiki, Shigehiro Kanzaki, Ryohei Kitano, Katsunori Nishikawa, Ikuko Lansky, Petr Ritsumeikan Univ Dept Human & Comp Intelligence Shiga 5258577 Japan Univ Tokyo Adv Sci & Technol Res Ctr Tokyo 1538904 Japan Acad Sci Czech Republ Inst Physiol CR-14220 Prague 4 Czech Republic

We investigated how odorant information is transmitted by neurons in the moth antennal lobe (AL). The neurons were repeatedly stimulated by three different odorants and their activity was intracellularly recorded. First, the response properties of single neurons were analyzed. The neurons exhibited highly reliable responses to the odorants and 43% of AL neurons responded to two or three odorants. The population distribution of firing rates in response to odorant stimulation was relatively broad in moth AL neurons, which is consistent across insects. Second, we attempted to decode the odorant identity from the activity of the recorded neurons using the maximum likelihood method. The decoding performance rapidly improves with increasing the number of neurons. Notably, an increase in the size of neural population results in faster transfer of information and increased the duration to retain odorant information. In conclusion, the AL neurons encode odorant information reliably and the population coding can transmit odorant information to olfactory centers. population coding allows AL to encode and transmit olfactory information faster than the discrimination latency demonstrated in behavioral experiments. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Olfactory information processing Antennal lobe population coding Decoding analysis Intracellular recording

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population coding in cortical area MST

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NEUROBIOLOGY OF EYE MOVEMENTS: FROM MOLECULES TO BEHAVIOR 2002年第1期956卷 284-296页

作者： Takemura, A Kawano, K Quaia, C Miles, FA NEI Sensorimotor Res Lab NIH Bethesda MD 20892 USA Natl Inst Adv Ind Sci & Technol AIST Neurosci Res Inst Tsukuba Ibaraki 3058568 Japan Univ Trieste Dipartimento Elettron Elettrotecn & Informat I-34100 Trieste Italy

Disparity steps applied to large patterns elicit vergence eye movements at ultrashort latencies. Disparity tuning curves, describing the dependence of the amplitude of the initial vergence responses on the amplitude of the disparity steps, resemble the derivative of a gaussian and indicate that appropriate servo-like behavior occurs only with small disparity steps (<1 degree). Lesion data from monkeys suggest that these vergence responses are mediated, at least in part, by neurons in the medial superior temporal area of the cerebral cortex, and we here review a recent study of the associated single unit activity in that area. Few medial superior temporal neurons have disparity tuning curves whose shapes resemble the tuning curve for vergence. Yet, when the disparity tuning curves for all of the disparity-sensitive cells recorded from a given monkey are summed together, they match the tuning curves for the vergence responses of that monkey very closely, even reproducing that animal's idiosyncracies. When all of the spike trains elicited by a given disparity step are summed together to give an average discharge profile for the whole population of recorded cells, many are noisy, but others that are less so match the temporal profile of the motor response, vergence velocity, quite well. We conclude that the discharges of the disparity-sensitive cells in the medial superior temporal area each represent only a very limited aspect of the sensory stimulus (and/or associated motor response?), but when pooled together, they provide a complete description of the vergence velocity motor response: population coding.

关键词： vergence eye movements disparity-selective neurons population coding

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population coding of Goal Directed Movements 1

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25th International Conference on Artificial Neural Networks (ICANN)

作者： Fleischer, Andreas G. Univ Hamburg Dept Biol Modelling Biol Syst Informatikum Vogt Kolln Str 30 D-22527 Hamburg Germany

ISBN: (数字)9783319447780

ISBN: (纸本)9783319447780;9783319447773

In order to intercept a moving target a motor schema causes the hand to aim ahead and to adapt to the target trajectory. During the performance of perception-action-cycles, a pre-programmed prototypical movement trajectory, a motor schema, may highly reduce the control load. From a modelling point of view, a neural network may allow the implementation of a motor schema interacting with feedback control in an iterative manner. A neural population net of the Wilson-Cowan type was allowing the generation of a moving bubble. This activation bubble runs down an eye-centered motor schema and causes a planar arm model to move towards the target. The bubble provides local integration and straightening of the trajectory during repetitive moves. The schema adapts to task demands by learning and serves as a forward controller.

关键词： population coding Neural field Recurrent nets Attractor state Convolution kernel Motor control Inverse dynamics Schema theory

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Temporally precise population coding of dynamic sounds by auditory cortex

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JOURNAL OF NEUROPHYSIOLOGY 2021年第1期126卷 148-169页

作者： Downer, Joshua D. Bigelow, James Runfeldt, Melissa J. Malone, Brian J. Univ Calif San Francisco Dept Otolaryngol Head & Neck Surg San Francisco CA 94143 USA Univ Calif San Francisco Kavli Inst Fundamental Neurosci San Francisco CA 94143 USA

Fluctuations in the amplitude envelope of complex sounds provide critical cues for hearing, particularly for speech and animal vocalizations. Responses to amplitude modulation (AM) in the ascending auditory pathway have chiefly been described for single neurons. How neural populations might collectively encode and represent information about AM remains poorly characterized, even in primary auditory cortex (A1). We modeled population responses to AM based on data recorded from A1 neurons in awake squirrel monkeys and evaluated how accurately single trial responses to modulation frequencies from 4 to 512 Hz could be decoded as functions of population size, composition, and correlation structure. We found that a population-based decoding model that simulated convergent, equally weighted inputs was highly accurate and remarkably robust to the inclusion of neurons that were individually poor decoders. By contrast, average rate codes based on convergence performed poorly;effective decoding using average rates was only possible when the responses of individual neurons were segregated, as in classical population decoding models using labeled Ones. The relative effectiveness of dynamic rate coding in auditory cortex was explained by shared modulation phase preferences among cortical neurons, despite heterogeneity in rate-based modulation frequency tuning. Our results indicate significant population-based synchrony in primary auditory cortex and suggest that robust population coding of the sound envelope information present in animal vocalizations and speech can be reliably achieved even with indiscriminate pooling of cortical responses. These findings highlight the importance of firing rate dynamics in population-based sensory coding. NEW & NOTEWORTHY Fundamental questions remain about population coding in primary auditory cortex (A1). In particular, issues of spike timing in models of neural populations have been largely ignored. We find that spike-timing in response to sou

关键词： auditory cortex decoding hearing population coding

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Demonstration of Stochastic Resonance, population coding, and population Voting Using Artificial MoS2 Based Synapses

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ACS NANO 2021年第10期15卷 16172-16182页

作者： Dodda, Akhil Das, Saptarshi Penn State Univ Dept Engn Sci & Mech University Pk PA 16802 USA Penn State Univ Dept Engn Sci & Mech Dept Mat Sci & Engn University Pk PA 16802 USA Penn State Univ Mat Res Inst University Pk PA 16802 USA

Fast detection of weak signals at low energy expenditure is a challenging but inescapable task for the evolutionary success of animals that survive in resource constrained environments. This task is accomplished by the sensory nervous system by exploiting the synergy between three astounding neural phenomena, namely, stochastic resonance (SR), population coding (PC), and population voting (PV). In SR, the constructive role of synaptic noise is exploited for the detection of otherwise invisible signals. In PC, the redundancy in neural population is exploited to reduce the detection latency. Finally, PV ensures unambiguous signal detection even in the presence of excessive noise. Here we adopt a similar strategies and experimentally demonstrate how a population of stochastic artificial neurons based on monolayer MoS2 field effect transistors (FETs) can use an optimum amount of white Gaussian noise and population voting to detect invisible signals at a frugal energy expenditure (similar to 10s of nano-Joules). Our findings can aid remote sensing in the emerging era of the Internet of things (IoT) that thrive on energy efficiency.

关键词： two-dimensional materials stochastic resonance population coding population voting subthreshold signal detection low-power sensors monolayer MoS2 field effect transistors

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Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex

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PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2017年第2期114卷 394-399页

作者： Murray, John D. Bernacchia, Alberto Roy, Nicholas A. Constantinidis, Christos Romo, Ranulfo Wang, Xiao-Jing Yale Univ Sch Med Dept Psychiat New Haven CT 06510 USA Univ Cambridge Dept Engn Cambridge CB2 1PZ England Princeton Univ Princeton Neurosci Inst Princeton NJ 08544 USA Wake Forest Univ Sch Med Dept Neurobiol & Anat Winston Salem NC 27157 USA Univ Nacl Autonoma Mexico Inst Fisiol Celular Neurociencias Mexico City 04510 DF Mexico El Colegio Nacl Mexico City 06020 DF Mexico NYU Ctr Neural Sci New York NY 10012 USA NYU East China Normal Univ Inst Brain & Cognit Sci Shanghai 200122 Peoples R China

Working memory (WM) is a cognitive function for temporary maintenance and manipulation of information, which requires conversion of stimulus-driven signals into internal representations that are maintained across seconds-long mnemonic delays. Within primate prefrontal cortex (PFC), a critical node of the brain's WM network, neurons show stimulus-selective persistent activity during WM, but many of them exhibit strong temporal dynamics and heterogeneity, raising the questions of whether, and how, neuronal populations in PFC maintain stable mnemonic representations of stimuli during WM. Here we show that despite complex and heterogeneous temporal dynamics in single-neuron activity, PFC activity is endowed with a population-level coding of the mnemonic stimulus that is stable and robust throughout WM maintenance. We applied population-level analyses to hundreds of recorded single neurons from lateral PFC of monkeys performing two seminal tasks that demand parametric WM: oculomotor delayed response and vibrotactile delayed discrimination. We found that the high-dimensional state space of PFC population activity contains a low-dimensional subspace in which stimulus representations are stable across time during the cue and delay epochs, enabling robust and generalizable decoding compared with time-optimized subspaces. To explore potential mechanisms, we applied these same population-level analyses to theoretical neural circuit models of WM activity. Three previously proposed models failed to capture the key population-level features observed empirically. We propose network connectivity properties, implemented in a linear network model, which can underlie these features. This work uncovers stable population-level WM representations in PFC, despite strong temporal neural dynamics, thereby providing insights into neural circuit mechanisms supporting WM.

关键词： working memory prefrontal cortex population coding

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The effect of neural adaptation on population coding accuracy

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JOURNAL OF COMPUTATIONAL NEUROSCIENCE 2012年第3期32卷 387-402页

作者： Cortes, Jesus M. Marinazzo, Daniele Series, Peggy Oram, Mike W. Sejnowski, Terry J. van Rossum, Mark C. W. Univ Edinburgh Inst Adapt & Neural Computat Sch Informat Edinburgh Midlothian Scotland Univ Paris 05 Lab Neurophys & Physiol CNRS UMR 8119 Paris France Univ St Andrews Sch Psychol St Andrews Fife Scotland Salk Inst Howard Hughes Med Inst San Diego CA 92037 USA Univ Calif San Diego Div Biol Sci San Diego CA 92093 USA

Most neurons in the primary visual cortex initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. The functional consequences of adaptation are unclear. Typically a reduction of firing rate would reduce single neuron accuracy as less spikes are available for decoding, but it has been suggested that on the population level, adaptation increases coding accuracy. This question requires careful analysis as adaptation not only changes the firing rates of neurons, but also the neural variability and correlations between neurons, which affect coding accuracy as well. We calculate the coding accuracy using a computational model that implements two forms of adaptation: spike frequency adaptation and synaptic adaptation in the form of short-term synaptic plasticity. We find that the net effect of adaptation is subtle and heterogeneous. Depending on adaptation mechanism and test stimulus, adaptation can either increase or decrease coding accuracy. We discuss the neurophysiological and psychophysical implications of the findings and relate it to published experimental data.

关键词： Visual adaptation Primary visual cortex population coding Fisher Information Cortical circuit Computational model Short-term synaptic depression Spike-frequency adaptation

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Single and population coding of taste in the gustatory cortex of awake mice

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JOURNAL OF NEUROPHYSIOLOGY 2019年第4期122卷 1342-1356页

作者： Levitan, David Lin, Jian-You Wachutka, Joseph Mukherjee, Narendra Nelson, Sacha B. Katz, Donald B. Brandeis Univ Dept Psychol MS 062415 South St Waltham MA 02454 USA Brandeis Univ Dept Biol Waltham MA 02254 USA Brandeis Univ Volen Ctr Complex Syst Waltham MA USA

Electrophysiological analysis has revealed much about the broad coding and neural ensemble dynamics that characterize gustatory cortical (GC) taste processing in awake rats and about how these dynamics relate to behavior. With regard to mice, however, data concerning cortical taste coding have largely been restricted to imaging, a technique that reveals average levels of neural responsiveness but that (currently) lacks the temporal sensitivity necessary for evaluation of fast response dynamics;furthermore, the few extant studies have thus far failed to provide consensus on basic features of coding. We have recorded the spiking activity of ensembles of GC neurons while presenting representatives of the basic taste modalities (sweet, salty, sour, and bitter) to awake mice. Our first central result is the identification of similarities between rat and mouse taste processing: most mouse GC neurons (similar to 66%) responded distinctly to multiple (3-4) tastes;temporal coding analyses further reveal, for the first time, that single mouse GC neurons sequentially code taste identity and palatability, the latter responses emerging similar to 0.5 s after the former, with whole GC ensembles transitioning suddenly and coherently from coding taste identity to coding taste palatability. The second finding is that spatial location plays very little role in any aspect of taste responses: neither between(anterior-posterior) nor within-mouse (dorsal-ventral) mapping revealed anatomic regions with narrow or temporally simple taste responses. These data confirm recent results showing that mouse cortical taste responses are not "gustotopic" but also go beyond these imaging results to show that mice process tastes through time. NEW & NOTEWORTHY Here, we analyzed taste-related spiking activity in awake mouse gustatory cortical (GC) neural ensembles, revealing deep similarities between mouse cortical taste processing and that repeatedly demonstrated in rat: mouse GC ensembles code multipl

关键词： gustatory cortex mice population coding taste

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DYNAMICS OF population coding FOR OBJECT VIEWS FOLLOWING OBJECT DISCRIMINATION TRAINING

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NEUROSCIENCE 2016年 330卷 109-120页

作者： Yamaguchi, Reona Okamura, Jun-ya Wang, Gang Kagoshima Univ Grad Sch Sci & Engn Dept Informat Sci & Biomed Engn Kagoshima 8900065 Japan Weifang Med Univ Lab Cognit Neurosci Weifang Shandong Peoples R China

We have previously demonstrated that inferotemporal neurons respond to objects viewed from a range of angles, even without any prior experience in learning the associations among the views. Several models have been proposed to explain object recognition across disparate views. However, direct neuronal evidence is rare. In the present study, we focused on the response similarity of a population of inferotemporal cells to object views, following different prior experiences. Two monkeys were subjected to a task in which object discrimination across views was required. We found significantly higher neural response similarity to 30 degrees separated views, 190 ms after object image presentation, than without any prior discrimination experience across views. The time period over which the similarity was significant began and endured similarly for 60 degrees separated views at 190-850 ms. For 90 degrees separated views, the time period over which the similarity was significant was shorter and started later, at 230-550 ms. The results demonstrate the dynamics of cell population activity and suggest a possible explanation for object recognition across disparate views. (C) 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

关键词： monkey inferotemporal cortex object recognition view invariance population coding

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Compression for Quantum population coding

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IEEE TRANSACTIONS ON INFORMATION THEORY 2018年第7期64卷 4766-4783页

作者： Yang, Yuxiang Bai, Ge Chiribella, Giulio Hayashi, Masahito Univ Hong Kong Dept Comp Sci Hong Kong Hong Kong Peoples R China HKU Shenzhen Inst Res & Innovat Shenzhen 518057 Peoples R China Univ Oxford Dept Comp Sci Oxford OX1 2JD England Canadian Inst Adv Res Toronto ON M5G 1M1 Canada Nagoya Univ Grad Sch Math Nagoya Aichi 4648602 Japan Natl Univ Singapore Ctr Quantum Technol Singapore 117542 Singapore

We study the compression of n quantum systems, each prepared in the same state belonging to a given parametric family of quantum states. For a family of states with f independent parameters, we devise an asymptotically faithful protocol that requires a hybrid memory of size (f/2) log n, including both quantum and classical bits. Our construction uses a quantum version of local asymptotic normality and, as an intermediate step, solves the problem of compressing displaced thermal states of n identically prepared modes. In both cases, we show that (f/2) log n is the minimum amount of memory needed to achieve asymptotic faithfulness. In addition, we analyze how much of the memory needs to be quantum. We find that the ratio between quantum and classical bits can be made arbitrarily small, but cannot reach zero: unless all the quantum states in the family commute, no protocol using only classical bits can be faithful, even if it uses an arbitrarily large number of classical bits.

关键词： population coding compression quantum system local asymptotic normality identically prepared state

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