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Postural Representations of the Hand in the Primate Sensorimotor Cortex

NEURON 2019年第5期104卷 1000-+页

作者： Goodman, James M. Tabot, Gregg A. Lee, Alex S. Suresh, Aneesha K. Rajan, Alexander T. Hatsopoulos, Nicholas G. Bensmaia, Sliman Univ Chicago Comm Computat Neurosci Chicago IL 60637 USA Univ Chicago Dept Organismal Biol & Anat 1025 E 57Th St Chicago IL 60637 USA Univ Chicago Grossman Inst Neurosci Quantitat Biol & Human Beh Chicago IL 60637 USA

Manual dexterity requires proprioceptive feedback about the state of the hand. To date, study of the neural basis of proprioception in the cortex has focused primarily on reaching movements to the exclusion of hand-specific behaviors such as grasping. To fill this gap, we record both time-varying hand kinematics and neural activity evoked in somatosensory and motor cortices as monkeys grasp a variety of objects. We find that neurons in the somatosensory cortex, as well as in the motor cortex, preferentially track time-varying postures of multi-joint combinations spanning the entire hand. This contrasts with neural responses during reaching movements, which preferentially track time-varying movement kinematics of the arm, such as velocity and speed of the limb, rather than its time-varying postural configuration. These results suggest different representations of arm and hand movements suited to the different functional roles of these two effectors.

关键词： cortex grasp hand motor neural coding proprioception somatosensory

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Mechanisms of Sensory Discrimination: Insights from Drosophila Olfaction

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ANNUAL REVIEW OF BIOPHYSICS, VOL 48 2019年第1期48卷 209-229页

作者： Groschner, Lukas N. Miesenbock, Gero Univ Oxford Ctr Neural Circuits & Behav Oxford OX1 3SR England

All an animal can do to infer the state of its environment is to observe the sensory-evoked activity of its own neurons. These inferences about the presence, quality, or similarity of objects are probabilistic and inform behavioral decisions that are often made in close to real time. neural systems employ several strategies to facilitate sensory discrimination: Biophysical mechanisms separate the neuronal response distributions in coding space, compress their variances, and combine information from sequential observations. We review how these strategies are implemented in the olfactory system of the fruit fly. The emerging principles of odor discrimination likely apply to other neural circuits of similar architecture.

关键词： decision making neural coding signal detection synapse dendrite inhibition

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Spatial resolution of local field potential signals in macaque V4

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JOURNAL OF neural ENGINEERING 2020年第2期17卷 026003-026003页

作者： Foroushani, Armin Najarpour Neupane, Sujaya Pastor, Pablo De Heredia Pack, Christopher C. Sawan, Mohamad Polytech Montreal Inst Biomed Engn PolyStim Neurotechnol Lab Montreal PQ Canada McGill Univ Montreal Neurol Inst & Hosp Montreal PQ Canada Westlake Univ Sch Engn Hangzhou 310024 Peoples R China Westlake Inst Adv Study Inst Adv Study Hangzhou 310024 Peoples R China MIT McGovern Inst Brain Res 77 Massachusetts Ave Cambridge MA 02139 USA Univ Politecn Madrid Escuela Tecn Ingn Ind E-28040 Madrid Spain

Objective. An important challenge for the development of cortical visual prostheses is to generate spatially localized percepts of light, using artificial stimulation. Such percepts are called phosphenes, and the goal of prosthetic applications is to generate a pattern of phosphenes that matches the structure of the retinal image. A preliminary step in this process is to understand how the spatial positions of phosphene-like visual stimuli are encoded in the distributed activity of cortical neurons. The spatial resolution with which the distributed responses discriminate positions puts a limit on the capability of visual prosthesis devices to induce phosphenes at multiple positions. While most previous prosthetic devices have targeted the primary visual cortex, the extrastriate cortex has the advantage of covering a large part of the visual field with a smaller amount of cortical tissue, providing the possibility of a more compact implant. Here, we studied how well ensembles of Local Field Potentials (LFPs) and Multiunit activity (MUA) responses from extrastriate cortical visual area V4 of a behaving macaque monkey can discriminate between two-dimensional spatial positions. Approach. We used support vector machines (SVM) to determine the capabilities of LFPs and MUA to discriminate responses to phosphene-like stimuli (probes) at different spatial separations. We proposed a selection strategy based on the combined responses of multiple electrodes and used the linear learning weights to find the minimum number of electrodes for fine and coarse discriminations. We also measured the contribution of correlated trial-to-trial variability in the responses to the discrimination performance for MUA and LFP. Main results. We found that despite the large receptive field sizes in V4, the combined responses from multiple sites, whether MUA or LFP, are capable of fine and coarse discrimination of positions. Our electrode selection procedure significantly increased discrimination

关键词： spatial discrimination local field potential V4 neural coding support vector machines correlation cortical visual prosthesis

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Neuronal coupling benefits the encoding of weak periodic signals in symbolic spike patterns

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2020年 82卷 105023-000页

作者： Masoliver, Maria Masoller, Cristina Univ Politecn Cataluna Dept Fis Edifici GaiaRambla de St Nebridi 22 Barcelona 08222 Spain

The biophysical mechanisms by which an input signal elicits a neuronal response are well known (sufficiently large inputs change the membrane potential of the neuron and generate electrical pulses, known as action potentials or spikes), yet, a good understanding of how neurons use these spikes to encode the signal information remains elusive. Recent theoretical studies have focused on how neurons encode a weak periodic signal (that by itself is unable to generate spikes) in a noisy environment, where stochastic electrical fluctuations that do not encode any information occur. Analyzing spike sequences generated by individual neurons and by two coupled neurons (that were simulated with the stochastic FitzHugh-Nagumo model), it has been found that the relative timing of the spikes can encode the signal information. Using a symbolic method to analyze the spike sequence, preferred and infrequent spike patterns were detected, whose probabilities vary with both, the amplitude and the frequency of the signal. To investigate if this encoding mechanism is plausible also for neuronal ensembles, here we analyze the activity of a group of neurons, when they all perceive a weak periodic signal. We find that, as in the case of one or two coupled neurons, the probabilities of the spike patterns, now computed from the spike sequences of all the neurons, depend on the signal's amplitude and period, and thus, the patterns' probabilities encode the information of the signal. We also find that the resonances with the period of the signal or with the noise level are more pronounced when a group of neurons perceive the signal, in comparison with when only one or two coupled neurons perceive it. Neuronal coupling is beneficial for signal encoding as a group of neurons is able to encode a small-amplitude signal, which could not be encoded when it is perceived by just one or two coupled neurons. Interestingly, we find that for a group of neurons, just a few connections with one another can

关键词： neural coding Excitability Spike train variability Neuronal noise Fitzhugh-Nagumo model Time series analysis Symbolic analysis Ordinal analysis

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Effect of scanning speed on texture-elicited vibrations

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JOURNAL OF THE ROYAL SOCIETY INTERFACE 2020年第167期17卷 20190892-20190892页

作者： Greenspon, Charles M. McLellan, Kristine R. Lieber, Justin D. Bensmaia, Sliman J. Univ Chicago Dept Organismal Biol & Anat 1025 E 57th St Chicago IL 60637 USA Univ Chicago Comm Computat Neurosci Chicago IL 60637 USA Univ Chicago Grossman Inst Neurosci Quantitat Biol & Human Beh Chicago IL 60637 USA

To sense the texture of a surface, we run our fingers across it, which leads to the elicitation of skin vibrations that depend both on the surface and on exploratory parameters, particularly scanning speed. The transduction and processing of these vibrations mediate the ability to discern fine surface features. The objective of the present study is to characterize the effect of changes in scanning speed on texture-elicited vibrations to better understand how the exploratory movements shape the neuronal representation of texture. To this end, we scanned a variety of textures across the fingertip of human participants at a variety of speeds (10-160 mm s(-1)) while measuring the resulting vibrations using a laser Doppler vibrometer. First, we found that the intensity of the vibrations-as indexed by root-mean-square velocity-increases with speed but that the skin displacement remains constant. Second, we found that the frequency composition of the vibrations shifts systematically to higher frequencies with increases in scanning speed. Finally, we show that the speed-dependent shift in frequency composition accounts for the speed-dependent change in intensity.

关键词： touch neural coding haptics somatosensory coding vibrotaction

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Inferring population statistics of receptor neurons sensitivities and firing-rates from general functional requirements

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BIOSYSTEMS 2020年 193卷 104153-104153页

作者： Mari, Carlo Fulvi

On the basis of the evident ability of neuronal olfactory systems to evaluate the intensity of an odorous stimulus and at the same time also recognise the identity of the odorant over a large range of concentrations, a few biologically-realistic hypotheses on some of the underlying neural processes are made. In particular, it is assumed that the receptor neurons mean firing-rate scale monotonically with odorant intensity, and that the receptor sensitivities range widely across odorants and receptor neurons hence leading to highly distributed representations of the stimuli. The mathematical implementation of the phenomenological postulates allows for inferring explicit functional relationships between some measurable quantities. It results that both the dependence of the mean firing-rate on odorant concentration and the statistical distribution of receptor sensitivity across the neuronal population are power-laws, whose respective exponents are in an arithmetic, testable relationship. In order to test quantitatively the prediction of power-law dependence of population mean firing-rate on odorant concentration, a probabilistic model is created to extract information from data available in the experimental literature. The values of the free parameters of the model are estimated by an info-geometric Bayesian maximum-likelihood inference which keeps into account the prior distribution of the parameters. The eventual goodness of fit is quantified by means of a distribution-independent test. The probabilistic model results to be accurate with high statistical significance, thus confirming the theoretical prediction of a power-law dependence on odorant concentration. The experimental data available about the distribution of sensitivities also agree with the other predictions, though they are not statistically sufficient for a very stringent verification. Furthermore, the theory suggests a potential evolutionary reason for the exponent of the sensitivity power-law to be sign

关键词： neural coding Distributed representation Olfaction Receptor sensitivity Affinity distribution Concentration invariance Power-law

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Development of a System Providing the Interaction of the Transducer with the Nervous System for Sensory Prosthetics

Development of a System Providing the Interaction of the Tra...

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IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus)

作者： Slepova, Liudmila O. Berkhova, Evdokiia M. ITMO Univ Fac Control Syst & Robot St Petersburg Russia St Petersburg State Marine Tech Univ Dept Marine Elect St Petersburg Russia

ISBN: (纸本)9781728103396

The problem of electronic sensor interaction with the nervous system of a living organism in sensory prosthetics devices is described. The processing, storing and transmission of information by a spiking neuron and a spiking neural network are analyzed. The basic principles of functioning of a neural cell, which uses an electric pulse for coding and transmission of information, are investigated. The possibility of developing an encoder for transmitting information from the sensor to the biological neuron of spiking neural networks is considered. The existing methods and means of sensory prosthetics and problems of hardware development for invasive and non-invasive systems are described.

关键词： nervous system sensory prosthetics neural coding spiking LIF-model

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A MULTI-SPIKE APPROACH FOR ROBUST SOUND RECOGNITION 44

A MULTI-SPIKE APPROACH FOR ROBUST SOUND RECOGNITION

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44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Yu, Qiang Yao, Yanli Wang, Longbiao Tang, Huajin Dang, Jianwu Tianjin Univ Tianjin Key Lab Cognit Comp & Applicat Coll Intelligence & Comp Tianjin Peoples R China Sichuan Univ Coll Comp Sci Chengdu Sichuan Peoples R China

ISBN: (纸本)9781479981311

The extraordinary performance of the brain on various cognitive tasks motivates the design of a biologically plausible system for the challenging task of environmental sound recognition. In this paper, we propose a novel approach based on multi-spike learning and key-point encoding. Our encoding extracts local temporal and spectral information from the sound and converts it into spatiotemporal spike pattern, which is further learned by the following spiking neural networks. Our experiments demonstrate the robustness and effectiveness of our approach across a variety of noise conditions, outperforming other conventional baseline methods in both mismatched and multi-condition scenarios.

关键词： Sound recognition neural coding multi-spike learning neuromorphic computing

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The Role of Cortical and Subcortical Auditory Pathways in Sound-Driven Behavior

The Role of Cortical and Subcortical Auditory Pathways in So...

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作者： Ponvert, Nicholas University of Oregon

学位级别：博士

For many species, the ability to use information about sound to guide behavior is important for obtaining rewards such as food, mates, or respite from danger. The neural pathways that associate sounds with actions that will produce reward are not well understood. The striatum, a brain region which receives sound information from the auditory cortex and auditory thalamus, and which can drive behavior via its outputs in the basal ganglia, represents a potential key hub in the pathway between sound and action. In this thesis, I investigate the role of striatal circuits in the context of sound-guided behavior, and compare parallel corticostriatal and thalamostriatal pathways that provide auditory information to the striatum. In Chapter II, I inactivate the striatum while animals perform a frequency discrimination task, and find that this manipulation leads to a strong deficit in task performance. In Chapter III, I compare the information about sounds sent to the striatum from the auditory cortex and auditory thalamus. I find that, while these pathways convey frequency information to the striatum with similar fidelity, they have different representations of temporal modulations in sound amplitude. In Chapter IV I present a behavioral task that could be used to evaluate the relative contribution of the corticostriatal and thalamostriatal pathways to discriminations of different sound features. Finally, Chapter V provides a review of the role of cortical and subcortical pathways in other behavioral contexts, especially in tasks that require rapid flexibility. This dissertation includes previously published co-authored material.

关键词： auditory cortex auditory decision making auditory thalamus neural coding pathway-specific striatum

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coding Properties of Firing Rate Models with Low-rank Synaptic Weight Matrices

Coding Properties of Firing Rate Models with Low-rank Synapt...

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作者： Collazos, Steven University of Minnesota

学位级别：Ph.D.

Hebbian theory proposes that ensembles of neurons, that is, groups of co-active neurons, form a basis for neural processing. We model the collection of all possible ensembles of neurons---known as \Def{permitted sets}, $\mathcal{P}_\Phi (W)$---as a collection of binary strings that indicate which neurons are deemed active. In this model, $\Phi$ is a function that prescribes how neurons respond to inputs, and $W$ is a matrix that captures the strengths of the connections among neurons in the network. We construct $\mathcal{P}_\Phi (W)$ by imposing a threshold on the responsiveness of the neuron to input at the steady state. We investigate how synaptic strengths shape $\mathcal{P}_\Phi (W)$. When the synaptic weight matrix is almost rank one, we prove two main results about $\mathcal{P}_\Phi (W)$. First, $\mathcal{P}_\Phi (W)$ is a convex code, which is a combinatorial neural code that arises from a pattern of intersections of convex sets. Second, $\mathcal{P}_\Phi (W)$ exhibits nesting, meaning that a permitted set with $k$ co-active neurons contains a permitted subset of $k-1$ co-active neurons. Our results are applicable to neuronal networks whose activation function is $C^1$ with finitely many discontinuities.

关键词： Asymptotically stable fixed points Differential Equations neural coding Neuronal networks

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