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population coding of motion patterns in the early visual system

JOURNAL OF COMPARATIVE PHYSIOLOGY A-SENSORY NEURAL AND BEHAVIORAL PHYSIOLOGY 2001年第7期187卷 549-558页

作者： Wilke, SD Thiel, A Eurich, CW Greschner, M Bongard, M Ammermüller, J Schwegler, H Univ Bremen Inst Theoret Phys D-28334 Bremen Germany Univ Oldenburg FB7 AG Neurobiol D-26111 Oldenburg Germany

Using extracellular recordings and computational modeling, we study the responses of a population of turtle (Pseudemys scripta elegans) retinal ganglion cells to different motion patterns. The onset of motion of a bright bar is signaled by a rise of the population activity that occurs within less than 100 ms. Correspondingly, more complex stimulus movement patterns are reflected by rapid variations of the firing rate of the retinal ganglion cell population. This behavior is reproduced by a computational model that generates ganglion cell activity from the spatio-temporal stimulus pattern using a Wiener model complemented by a lion-linear contrast gain control feedback loop responsible for the sharp transients in response to motion onset. This study demonstrates that contrast gain control strongly influences the temporal course of retinal population activity, and thereby plays a major role in the formation of a population code for stimulus movement patterns.

关键词： retina motion processing population coding contrast gain control

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

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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 Can Greatly Improve Performance of Neural Networks: A Comparison 32nd

Population Coding Can Greatly Improve Performance of Neural ...

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32nd International Conference on Artificial Neural Networks (ICANN)

作者： Jahrens, Marius Hansen, Hans-Oliver Koehler, Rebecca Martinetz, Thomas Univ Lubeck Inst Neuro & Bioinformat Lubeck Germany

ISBN: (纸本)9783031441912;9783031441929

Artificial neural networks oftentimes operate on continuous inputs. While biological neural networks usually represent information through the activity of a population of neurons, the inputs of an artificial neural network are typically provided as a list of scalars. As the information content of each of the input scalars depends heavily on the problem domain, representing them as individual scalar inputs, irrespective of the amount of information they contain, may prove to be suboptimal for the network. We therefore compare and examine four different population coding schemes and demonstrate on two toy datasets and one real world benchmark that applying population coding to information rich, low dimensional inputs can vastly improve a network's performance.

关键词： Machine Learning population coding Information Representation

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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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Triplet correlations among similarly tuned cells impact population coding

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FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 2015年第MAY期9卷 57页

作者： Cayco-Gajic, Natasha A. Zylberberg, Joel Shea-Brown, Eric Univ Washington Dept Appl Math Seattle WA 98195 USA

Which statistical features of spiking activity matter for how stimuli are encoded in neural populations? A vast body of work has explored how firing rates in individual cells and correlations in the spikes of cell pairs impact coding. Recent experiments have shown evidence for the existence of higher-order spiking correlations, which describe simultaneous firing in triplets and larger ensembles of cells;however, little is known about their impact on encoded stimulus information. Here, we take a first step toward closing this gap. We vary triplet correlations in small (approximately 10 cell) neural populations while keeping single cell and pairwise statistics fixed at typically reported values. This connection with empirically observed lower-order statistics is important, as it places strong constraints on the level of triplet correlations that can occur. For each value of triplet correlations, we estimate the performance of the neural population on a two-stimulus discrimination task. We find that the allowed changes in the level of triplet correlations can significantly enhance coding, in particular if triplet correlations differ for the two stimuli. In this scenario, triplet correlations must be included in order to accurately quantify the functionality of neural populations. When both stimuli elicit similar triplet correlations, however, pairwise models provide relatively accurate descriptions of coding accuracy. We explain our findings geometrically via the skew that triplet correlations induce in population-wide distributions of neural responses. Finally, we calculate how many samples are necessary to accurately measure spiking correlations of this type, providing an estimate of the necessary recording times in future experiments.

关键词： higher-order correlations maximum entropy model population coding Ising model information theory

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Valence and State-Dependent population coding in Dopaminergic Neurons in the Fly Mushroom Body

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CURRENT BIOLOGY 2020年第11期30卷 2104-+页

作者： Siju, K. P. Stih, Vilim Aimon, Sophie Gjorgjieva, Julijana Portugues, Ruben Kadow, Ilona C. Grunwald Tech Univ Munich TUM Sch Life Sci D-85354 Freising Weihenstephan Germany Max Planck Inst Neurobiol Sensorimotor Control Grp D-82152 Martinsried Germany Max Planck Inst Brain Res Computat Neural Circuits Grp D-60438 Frankfurt Germany Tech Univ Munich Inst Neurosci D-80802 Munich Germany Munich Cluster Syst Neurol SyNergy D-80802 Munich Germany Tech Univ Munich ZIEL Inst Food & Hlth D-85354 Freising Weihenstephan Germany

Neuromodulation permits flexibility of synapses, neural circuits, and ultimately behavior. One neuromodulator, dopamine, has been studied extensively in its role as a reward signal during learning and memory across animal species. Newer evidence suggests that dopaminergic neurons (DANs) can modulate sensory perception acutely, thereby allowing an animal to adapt its behavior and decision making to its internal and behavioral state. In addition, some data indicate that DANs are not homogeneous but rather convey different types of information as a heterogeneous population. We have investigated DAN population activity and how it could encode relevant information about sensory stimuli and state by taking advantage of the confined anatomy of DANs innervating the mushroom body (MB) of the fly Drosophila melanogaster. Using in vivo calcium imaging and a custom 3D image registration method, we found that the activity of the population of MB DANs encodes innate valence information of an odor or taste as well as the physiological state of the animal. Furthermore, DAN population activity is strongly correlated with movement, consistent with a role of dopamine in conveying behavioral state to the MB. Altogether, our data and analysis suggest that DAN population activities encode innate odor and taste valence, movement, and physiological state in a MB-compartment-specific manner. We propose that dopamine shapes innate perception through combinatorial population coding of sensory valence, physiological, and behavioral context.

关键词： dopamine Drosophila mushroom body olfactory system valence metabolic state behavioral state calcium imaging population coding taste

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Accuracy in Estimating Motor Commands Using Neuronal population coding

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CHINESE JOURNAL OF PHYSIOLOGY 2010年第6期53卷 417-422页

作者： Hata, Shigefumi Kyoto Univ Dept Phys Kyoto 6068502 Japan

We consider the problem of estimating motor commands from an ensemble of neuronal activities. The population vector algorithm proposed by Georgopoulos provides largely biased estimations when preferred directions of neurons are non-uniformly distributed. To improve this, various decoding methods have been proposed. However, dependence of decoding accuracy on the motor command and other features of neural activities, such as baseline firing rates or amplitudes of tuning curves, have not been quantitatively discussed. In this study, we propose a new method to estimate the motor command in the maximum likelihood estimation framework, which is analytically tractable. We find that the estimation accuracy is independent of the motor command. Using our estimation method, we can estimate the motor command with equal accuracy in all directions.

关键词： population coding population vector optimal linear estimator probability density estimation

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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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