检索结果-内蒙古大学图书馆

Selective synchronization of coupled bifurcating neurons for phase shift of background oscillation

JOURNAL OF ROBOTICS NETWORKING AND ARTIFICIAL LIFE 2018年第2期5卷 79-82页

作者： Yamaguchi, Akihiro Yamaguti, Yutaka Kubo, Masao Fukuoka Inst Technol Dept Informat & Syst Engn Higashi Ku 3-30-1 Wajiro Higashi Fukuoka Fukuoka 8110295 Japan Natl Def Acad Japan Dept Comp Sci 1-10-20 Hashirimizu Yokosuka Kanagawa 2398686 Japan

Synchronization in coupled bifurcating neurons was studied from the view point of the selective formation of cell assembly. The bifurcating neuron is a simple chaotic neuron that exhibits chaotic inter-spike interval dynamics via the addition of sinusoidal background oscillation. In this research, we introduced the phase shift of the background oscillation and several types of phase response to the input spike sequence. Sixteen coupled bifurcating neurons with complete bidirectional coupling were numerically simulated and their synchronized behaviors were analyzed. As a result, the formation of chaotically synchronized cell assemblies for the phase shift value were observed.

关键词： chaotic synchronization neural coding bifurcating neuron binding information

来源：评论

学校读者我要写书评

暂无评论

Mouse frontal cortex mediates additive multisensory decisions

引用

NEURON 2023年第15期111卷 2432-+页

作者： Coen, Philip Sit, Timothy P. H. Wells, Miles J. Carandini, Matteo Harris, Kenneth D. UCL UCL Queen Sq Inst Neurol London England UCL Sainsbury Wellcome Ctr London England UCL UCL Inst Ophthalmol London England

The brain can combine auditory and visual information to localize objects. However, the cortical substrates underlying audiovisual integration remain uncertain. Here, we show that mouse frontal cortex combines audi-tory and visual evidence;that this combination is additive, mirroring behavior;and that it evolves with learning. We trained mice in an audiovisual localization task. Inactivating frontal cortex impaired responses to either sensory modality, while inactivating visual or parietal cortex affected only visual stimuli. Recordings from >14,000 neurons indicated that after task learning, activity in the anterior part of frontal area MOs (sec-ondary motor cortex) additively encodes visual and auditory signals, consistent with the mice's behavioral strategy. An accumulator model applied to these sensory representations reproduced the observed choices and reaction times. These results suggest that frontal cortex adapts through learning to combine evidence across sensory cortices, providing a signal that is transformed into a binary decision by a downstream accumulator.

关键词： audiovisual decision-making neural coding mixed selectivity prefrontal cortex visual cortex parietal cortex optogenetics

来源：评论

学校读者我要写书评

暂无评论

Exploiting noise as a resource for computation and learning in spiking neural networks

引用

PATTERNS 2023年第10期4卷 100831页

作者： Ma, Gehua Yan, Rui Tang, Huajin Zhejiang Univ Coll Comp Sci & Technol Hangzhou Peoples R China Zhejiang Univ Technol Coll Comp Sci & Technol Hangzhou Peoples R China Zhejiang Univ State Key Lab Brain Machine Intelligence Hangzhou Peoples R China

Networks of spiking neurons underpin the extraordinary information-processing capabilities of the brain and have become pillar models in neuromorphic artificial intelligence. Despite extensive research on spiking neural networks (SNNs), most studies are established on deterministic models, overlooking the inherent nondeterministic, noisy nature of neural computations. This study introduces the noisy SNN (NSNN) and the noise-driven learning (NDL) rule by incorporating noisy neuronal dynamics to exploit the computational advantages of noisy neural processing. The NSNN provides a theoretical framework that yields scalable, flexible, and reliable computation and learning. We demonstrate that this framework leads to spiking neural models with competitive performance, improved robustness against challenging perturbations compared with deterministic SNNs, and better reproducing probabilistic computation in neural coding. Generally, this study offers a powerful and easy-to-use tool for machine learning, neuromorphic intelligence practitioners, and computational neuroscience researchers.

关键词： spiking neural network noisy spiking neural network surrogate gradient noise-driven learning neuromorphic intelligence neural coding probabilistic graphical model dynamic system DSML 2: Proof-of-concept: Data science output has been formulated, implemented, and tested for one domain/problem

来源：评论

学校读者我要写书评

暂无评论

Feature Linking using Synchronized Responses in Chaotic Cellar neural Networks for Visual Stimulus of Moving Objects

引用

JOURNAL OF ROBOTICS NETWORKING AND ARTIFICIAL LIFE 2016年第4期2卷 230-233页

作者： Yamaguchi, Akihiro Arakane, Satoshi Kubo, Masao Fukuoka Inst Technol Dept Informat & Syst Engn Higashi Ku 3-30-1 Wajiro Higashi Fukuoka 8110116 Japan Natl Def Acad Japan Dept Comp Sci 1-10-20 Hashirimizu Yokosuka Kanagawa 2398686 Japan

A feature-linking mechanism using the synchronized responses of neural assemblies was studied for chaotic cellar neural networks (Chaotic-CNN). Chaotic-CNNs consist of chaotic spike response neurons that show chaotic inter-spike-interval dynamics. In our scheme of feature linking, the features of the target objects are linked by the synchronized spike responses characterized by the temporal chaotic pattern of the spike sequence. In this paper, we analyze the synchronized spike responses invoked by the visual stimulus of moving bars. Consequently, the resulting neural assemblies have higher correlation for the visual stimulus of two bars moving in the same direction than in the opposite direction. We also discuss the possibility of feature linking using the chaotic synchronized responses.

关键词： chaotic synchronization neural coding spike response model feature linking

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Are movement parameters recognizably coded in the activity of single neurons?

引用

Behavioral and Brain Sciences 2011年第4期15卷 679-690页

作者： Eberhard E. Fetz Department of Physiology & Biophysics and Regional Primate Research Center University of Washington Seattle WA 98195 Electronic mail: fetz@locke.hs.washington.edu

To investigate neural mechanisms of movement, physiologists have analyzed the activity of task-related neurons in behaving animals. The relative onset latencies of neural activity have been scrutinized for evidence of a functional hierarchy of sequentially recruited centers, but experiments reveal that activity changes occur largely in parallel. Neurons whose activity covaries with movement parameters have been sought for evidence of explicit coding of parameters such as active force, limb displacement, and behavioral set. Neurons with recognizable relations to the task are typically selected from a larger population, ignoring those cells with complex relations to the task and unmodulated cells. Selective interpretations are also used to support the notion that different motor regions perform different motor functions; again, current evidence suggests that units with similar properties are distributed over widely different *** coding issues are reexamined for premotoneuronal (PreM) cells, whose correlational links with motoneurons are revealed by spike-triggered averages. PreM cells are recruited over long times relative to their target muscles; they show diverse response patterns relative to the muscle force they produce; functionally disparate PreM cells such as afferent fibers and descending corticomotoneuronal and rubromotoneuronal cells can exhibit similar patterns. neural mechanisms have been further elucidated by neural network simulations of sensorimotor behavior; the pre-output hidden units typically show diverse response patterns in relation to their target units. Thus, studies in which both the activity and the connectivity of the same units are known reveal that units with both simple and complex relations to the task contribute significantly to the output. This suggests that the search for explicit coding may be diverting us from understanding distributed neural mechanisms that operate without literal representations.

关键词： chronic recording motor cortex movement parameters neural coding neural computation neural networks parallel distributed processing premotoneuronal cells representation spike-triggered averages

来源：评论

学校读者我要写书评

暂无评论

Response variability and information transfer in directional neurons of the mammalian horizontal optokinetic system

引用

VISUAL NEUROSCIENCE 2000年第2期17卷 207-215页

作者： Clifford, CWG Ibbotson, MR Macquarie Univ Dept Psychol Sydney NSW 2109 Australia Australian Natl Univ Ctr Visual Sci Res Sch Biol Sci Canberra ACT 2601 Australia

This study is concerned with how information about the direction of visual motion is encoded by motion-sensitive neurons. Motion-sensitive neurons are usually studied using stimuli unchanging in speed and direction over several seconds. Recently, it has been suggested that neuronal responses to more naturalistic stimuli cannot be understood on the basis of experiments with constant-motion stimuli (de Ruyter van Steveninck et al., 1997). We measured the variability and information content of spike trains recorded from directional neurons in the nucleus of the optic tract (NOT) of the wallaby, Macropus eugenii, in response to constant and time-varying motion. While the NOT forms part of the mammalian optokinetic system, we have shown previously that the responses of its directional neurons resemble those of insect H1 in many respects (Ibbotson ct al., 1994). We find that directional neurons in the wallaby NOT respond with lower variability and higher rates of information transmission to time-varying stimuli than to constant motion. The difference in response variability is predicted by an inhomogeneous Poisson model of neuronal spiking incorporating an absolute refractory period of 2 ms during which no subsequent spike can be fired. Refractoriness imposes structure on the spike train, reducing variability (de Ruyter van Steveninck & Bialek, 1988;Berry & Meister, 1998). A given refractory period has a greater impact when firing rates are high, as for the responses of NOT neurons to time-varying stimuli. It is in just these cases that variability in experimentally observed spike trains is lowest. Thus, differences in response variability do not necessarily imply that different models are required to predict neuronal responses to constant- and time-varying motion stimuli.

关键词： vision motion nucleus of the optic tract wallaby neural coding

来源：评论

学校读者我要写书评

暂无评论

Movement-specific signaling is differentially distributed across motor cortex layer 5 projection neuron classes

引用

CELL REPORTS 2022年第6期39卷 000-000页

作者： Currie, Stephen P. Ammer, Julian J. Premchand, Brian Dacre, Joshua Wu, Yufei Eleftheriou, Constantinos Colligan, Matt Clarke, Thomas Mitchell, Leah Faisal, A. Aldo Hennig, Matthias H. Duguid, Ian Univ Edinburgh Edinburgh Med Sch Biomed Sci Ctr Discovery Brain Sci Hugh Robson BldgGeorge Sq Edinburgh EH8 9XD Midlothian Scotland Univ Edinburgh Edinburgh Med Sch Biomed Sci Patrick Wild Ctr Hugh Robson BldgGeorge Sq Edinburgh EH8 9XD Midlothian Scotland Univ Edinburgh Edinburgh Med Sch Biomed Sci Simons Initiat Developing Brain Edinburgh EH8 9XD Midlothian Scotland Imperial Coll London Dept Bioengn London SW7 2AZ England Imperial Coll London Dept Comp London SW7 2AZ England MRC London Inst Med Sci London W12 0NN England Univ Edinburgh Sch Informat Inst Adapt & Neural Computat Edinburgh EH8 9AB Midlothian Scotland Univ Freiburg Fac Biol Optophysiol D-79100 Freiburg Germany ASTAR Infocomm Res 1 Fusionopolis Way21-01 Connexis South Tower Singapore 138632 Singapore

Motor cortex generates descending output necessary for executing a wide range of limb movements. Although movement-related activity has been described throughout motor cortex, the spatiotemporal organization of movement-specific signaling in deep layers remains largely unknown. Here we record layer 5B population dynamics in the caudal forelimb area of motor cortex while mice perform a forelimb push/ pull task and find that most neurons show movement-invariant responses, with a minority displaying movement specificity. Using cell-type-specific imaging, we identify that invariant responses dominate pyramidal tract (PT) neuron activity, with a small subpopulation representing movement type, whereas a larger proportion of intratelencephalic (IT) neurons display movement-type-specific signaling. The proportion of IT neurons decoding movement-type peaks prior to movement initiation, whereas for PT neurons, this occurs during movement execution. Our data suggest that layer 5B population dynamics largely reflect movement-invariant signaling, with information related to movement-type being routed through relatively small, distributed subpopulations of projection neurons.

关键词： motor cortex action-specific calcium imaging motor control layer 5B neural coding motor behavior decoding object manipulation cortical silencing

来源：评论

学校读者我要写书评

暂无评论

Descending neurons of the hoverfly respond to pursuits of artificial targets

引用

CURRENT BIOLOGY 2023年第20期33卷 4392-+页

作者： Ogawa, Yuri Nicholas, Sarah Thyselius, Malin Leibbrandt, Richard Nowotny, Thomas Knight, James C. Nordstrom, Karin Flinders Univ S Australia Flinders Hlth & Med Res Inst GPO Box 2100 Adelaide SA 5001 Australia Uppsala Univ Dept Med Cell Biol S-75123 Uppsala Sweden Orebro Univ Sch Med Sci Fac Med & Hlth S-70182 Orebro Sweden Flinders Univ S Australia Coll Sci & Engn GPO Box 2100 Adelaide SA 5001 Australia Univ Sussex Sch Engn & Informat Brighton BN1 9QJ E Sussex England

Many animals use motion vision information to control dynamic behaviors. Predatory animals, for example, show an exquisite ability to detect rapidly moving prey, followed by pursuit and capture. Such target detec-tion is not only used by predators but is also important in conspecific interactions, such as for male hoverflies defending their territories against conspecific intruders. Visual target detection is believed to be subserved by specialized target-tuned neurons found in a range of species, including vertebrates and arthropods. How-ever, how these target-tuned neurons respond to actual pursuit trajectories is currently not well understood. To redress this, we recorded extracellularly from target-selective descending neurons (TSDNs) in male Eri-stalis tenax hoverflies. We show that they have dorso-frontal receptive fields with a preferred direction up and away from the visual midline. We reconstructed visual flow fields as experienced during pursuits of arti-ficial targets (black beads). We recorded TSDN responses to six reconstructed pursuits and found that each neuron responded consistently at remarkably specific time points but that these time points differed between neurons. We found that the observed spike probability was correlated with the spike probability predicted from each neuron's receptive field and size tuning. Interestingly, however, the overall response rate was low, with individual neurons responding to only a small part of each reconstructed pursuit. In contrast, the TSDN population responded to substantially larger proportions of the pursuits but with lower probability. This large variation between neurons could be useful if different neurons control different parts of the behav-ioral output.

关键词： target motion insect vision motion vision hoverfly descending neuron target pursuit neural coding naturalistic stimuli modeling prediction

来源：评论

学校读者我要写书评

暂无评论

Stimulus-invariant aspects of the retinal code drive discriminability of natural scenes

引用

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA 2024年第52期121卷 e2313676121页

作者： Hoshal, Benjamin D. Holmes, Caroline M. Bojanek, Kyle Salisbury, Jared M. Berry II, Michael J. Marre, Olivier Palmer, Stephanie E. Harvard Univ Dept Organism & Evolutionary Biol Cambridge MA 02138 USA Univ Chicago Comm Computat Neurosci Dept Organismal Biol & Anat Chicago IL 60637 USA Princeton Univ Dept Phys Princeton NJ 08540 USA Univ Chicago Dept Organismal Biol & Anat Chicago IL 60637 USA Univ Chicago Dept Phys Chicago IL 60637 USA Princeton Univ Princeton Neurosci Inst Dept Mol Biol Princeton NJ 08540 USA Sorbonne Univ Inst Vis INSERM F-75012 Paris France Princeton Univ Ctr Phys Biol Funct Dept Phys Princeton NJ 08540 USA

Everything that the brain sees must first be encoded by the retina, which maintains a reliable representation of the visual world in many different, complex natural scenes while also adapting to stimulus changes. This study quantifies whether and how the brain selectively encodes stimulus features about scene identity in complex naturalistic environments. While a wealth of previous work has dug into the static and dynamic features of the population code in retinal ganglion cells (RGCs), less is known about how populations form both flexible and reliable encoding in natural moving scenes. We record from the larval salamander retina responding to five different natural movies, over many repeats, and use these data to characterize the population code in terms of single-cell fluctuations in rate and pairwise couplings between cells. Decomposing the population code into independent and cell-cell interactions reveals how broad scene structure is encoded in the retinal output. while the single-cell activity adapts to different stimuli, the population structure captured in the sparse, strong couplings is consistent across natural movies as well as synthetic stimuli. We show that these interactions contribute to encoding scene identity. We also demonstrate that this structure likely arises in part from shared bipolar cell input as well as from gap junctions between RGCs and amacrine cells.

关键词： neural coding natural scenes retina neural computation population code

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：