Biological Cybernetics最新文献_第4页

Fluctuation-response relations for integrate-and-fire models with an absolute refractory period. 具有绝对耐火期的积分燃烧模型的波动-响应关系。

IF 1.7 4区工程技术

Biological Cybernetics Pub Date : 2024-04-01 Epub Date: 2024-01-23 DOI: 10.1007/s00422-023-00982-9

Friedrich Puttkammer, Benjamin Lindner

引用次数: 0

Energy optimisation predicts the capacity of ion buffering in the brain 能量优化可预测大脑离子缓冲能力

IF 1.9 4区工程技术

Biological Cybernetics Pub Date : 2023-12-16 DOI: 10.1007/s00422-023-00980-x

Reinoud Maex

{"title":"Energy optimisation predicts the capacity of ion buffering in the brain","authors":"Reinoud Maex","doi":"10.1007/s00422-023-00980-x","DOIUrl":"https://doi.org/10.1007/s00422-023-00980-x","url":null,"abstract":"Neurons store energy in the ionic concentration gradients they build across their cell membrane. The amount of energy stored, and hence the work the ions can do by mixing, can be enhanced by the presence of ion buffers in extra- and intracellular space. Buffers act as sources and sinks of ions, however, and unless the buffering capacities for different ion species obey certain relationships, a complete mixing of the ions may be impeded by the physical conditions of charge neutrality and isotonicity. From these conditions, buffering capacities were calculated that enabled each ion species to mix completely. In all valid buffer distributions, the (hbox {Ca}^{2+}) ions were buffered most, with a capacity exceeding that of (hbox {Na}^+) and (hbox {K}^+) buffering by at least an order of magnitude. The similar magnitude of the (oppositely directed) (hbox {Na}^+) and (hbox {K}^+) gradients made extracellular space behave as a (hbox {Na}^+)–(hbox {K}^+) exchanger. Anions such as (hbox {Cl}^-) were buffered least. The great capacity of the extra- and intracellular (hbox {Ca}^{2+}) buffers caused a large influx of (hbox {Ca}^{2+}) ions as is typically observed during energy deprivation. These results explain many characteristics of the physiological buffer distributions but raise the question how the brain controls the capacity of its ion buffers. It is suggested that neurons and glial cells, by their great sensitivity to gradients of charge and osmolarity, respectively, sense deviations from electro-neutral and isotonic mixing, and use these signals to tune the chemical composition, and buffering capacity, of the extra- and intracellular matrices.","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":"86 1","pages":""},"PeriodicalIF":1.9,"publicationDate":"2023-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138690201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multistability in neural systems with random cross-connections. 具有随机交叉连接的神经系统的多稳定性

IF 1.7 4区工程技术

Biological Cybernetics Pub Date : 2023-12-01 Epub Date: 2023-12-22 DOI: 10.1007/s00422-023-00981-w

Jordan Breffle, Subhadra Mokashe, Siwei Qiu, Paul Miller

{"title":"Multistability in neural systems with random cross-connections.","authors":"Jordan Breffle, Subhadra Mokashe, Siwei Qiu, Paul Miller","doi":"10.1007/s00422-023-00981-w","DOIUrl":"10.1007/s00422-023-00981-w","url":null,"abstract":"Neural circuits with multiple discrete attractor states could support a variety of cognitive tasks according to both empirical data and model simulations. We assess the conditions for such multistability in neural systems using a firing rate model framework, in which clusters of similarly responsive neurons are represented as single units, which interact with each other through independent random connections. We explore the range of conditions in which multistability arises via recurrent input from other units while individual units, typically with some degree of self-excitation, lack sufficient self-excitation to become bistable on their own. We find many cases of multistability-defined as the system possessing more than one stable fixed point-in which stable states arise via a network effect, allowing subsets of units to maintain each others' activity because their net input to each other when active is sufficiently positive. In terms of the strength of within-unit self-excitation and standard deviation of random cross-connections, the region of multistability depends on the response function of units. Indeed, multistability can arise with zero self-excitation, purely through zero-mean random cross-connections, if the response function rises supralinearly at low inputs from a value near zero at zero input. We simulate and analyze finite systems, showing that the probability of multistability can peak at intermediate system size, and connect with other literature analyzing similar systems in the infinite-size limit. We find regions of multistability with a bimodal distribution for the number of active units in a stable state. Finally, we find evidence for a log-normal distribution of sizes of attractor basins, which produces Zipf's Law when enumerating the proportion of trials within which random initial conditions lead to a particular stable state of the system.","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":" ","pages":"485-506"},"PeriodicalIF":1.7,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11773687/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138833073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Four attributes of intelligence, a thousand questions. 智力的四种属性，一千个问题。

IF 1.9 4区工程技术

Biological Cybernetics Pub Date : 2023-12-01 Epub Date: 2023-12-07 DOI: 10.1007/s00422-023-00979-4

Matthieu Bardal, Eric Chalmers

引用次数: 0

Face detection based on a human attention guided multi-scale model. 基于人的注意力引导多尺度模型的人脸检测。

IF 1.9 4区工程技术

Biological Cybernetics Pub Date : 2023-12-01 DOI: 10.1007/s00422-023-00978-5

Marinella Cadoni, Andrea Lagorio, Enrico Grosso

{"title":"Face detection based on a human attention guided multi-scale model.","authors":"Marinella Cadoni, Andrea Lagorio, Enrico Grosso","doi":"10.1007/s00422-023-00978-5","DOIUrl":"10.1007/s00422-023-00978-5","url":null,"abstract":"Multiscale models are among the cutting-edge technologies used for face detection and recognition. An example is Deformable part-based models (DPMs), which encode a face as a multiplicity of local areas (parts) at different resolution scales and their hierarchical and spatial relationship. Although these models have proven successful and incredibly efficient in practical applications, the mutual position and spatial resolution of the parts involved are arbitrarily defined by a human specialist and the final choice of the optimal scales and parts is based on heuristics. This work seeks to understand whether a multi-scale model can take inspiration from human fixations to select specific areas and spatial scales. In more detail, it shows that a multi-scale pyramid representation can be adopted to extract interesting points, and that human attention can be used to select the points at the scales that lead to the best face detection performance. Human fixations can therefore provide a valid methodological basis on which to build a multiscale model, by selecting the spatial scales and areas of interest that are most relevant to humans.","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":" ","pages":"453-466"},"PeriodicalIF":1.9,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10752920/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138464514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Single-compartment model of a pyramidal neuron, fitted to recordings with current and conductance injection. 锥体神经元的单室模型，适用于电流和电导注入的记录。

IF 1.9 4区工程技术

Biological Cybernetics Pub Date : 2023-12-01 Epub Date: 2023-09-27 DOI: 10.1007/s00422-023-00976-7

Anton V Chizhov, Dmitry V Amakhin, A Erdem Sagtekin, Mathieu Desroches

{"title":"Single-compartment model of a pyramidal neuron, fitted to recordings with current and conductance injection.","authors":"Anton V Chizhov, Dmitry V Amakhin, A Erdem Sagtekin, Mathieu Desroches","doi":"10.1007/s00422-023-00976-7","DOIUrl":"10.1007/s00422-023-00976-7","url":null,"abstract":"For single neuron models, reproducing characteristics of neuronal activity such as the firing rate, amplitude of spikes, and threshold potentials as functions of both synaptic current and conductance is a challenging task. In the present work, we measure these characteristics of regular spiking cortical neurons using the dynamic patch-clamp technique, compare the data with predictions from the standard Hodgkin-Huxley and Izhikevich models, and propose a relatively simple five-dimensional dynamical system model, based on threshold criteria. The model contains a single sodium channel with slow inactivation, fast activation and moderate deactivation, as well as, two fast repolarizing and slow shunting potassium channels. The model quantitatively reproduces characteristics of steady-state activity that are typical for a cortical pyramidal neuron, namely firing rate not exceeding 30 Hz; critical values of the stimulating current and conductance which induce the depolarization block not exceeding 80 mV and 3, respectively (both values are scaled by the resting input conductance); extremum of hyperpolarization close to the midpoint between spikes. The analysis of the model reveals that the spiking regime appears through a saddle-node-on-invariant-circle bifurcation, and the depolarization block is reached through a saddle-node bifurcation of cycles. The model can be used for realistic network simulations, and it can also be implemented within the so-called mean-field, refractory density framework.","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":" ","pages":"433-451"},"PeriodicalIF":1.9,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41141601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Divisive normalization processors in the early visual system of the Drosophila brain. 果蝇大脑早期视觉系统中的分裂正常化处理器

IF 1.9 4区工程技术

Biological Cybernetics Pub Date : 2023-12-01 Epub Date: 2023-09-13 DOI: 10.1007/s00422-023-00972-x

Aurel A Lazar, Yiyin Zhou

{"title":"Divisive normalization processors in the early visual system of the Drosophila brain.","authors":"Aurel A Lazar, Yiyin Zhou","doi":"10.1007/s00422-023-00972-x","DOIUrl":"10.1007/s00422-023-00972-x","url":null,"abstract":"Divisive normalization is a model of canonical computation of brain circuits. We demonstrate that two cascaded divisive normalization processors (DNPs), carrying out intensity/contrast gain control and elementary motion detection, respectively, can model the robust motion detection realized by the early visual system of the fruit fly. We first introduce a model of elementary motion detection and rewrite its underlying phase-based motion detection algorithm as a feedforward divisive normalization processor. We then cascade the DNP modeling the photoreceptor/amacrine cell layer with the motion detection DNP. We extensively evaluate the DNP for motion detection in dynamic environments where light intensity varies by orders of magnitude. The results are compared to other bio-inspired motion detectors as well as state-of-the-art optic flow algorithms under natural conditions. Our results demonstrate the potential of DNPs as canonical building blocks modeling the analog processing of early visual systems. The model highlights analog processing for accurately detecting visual motion, in both vertebrates and invertebrates. The results presented here shed new light on employing DNP-based algorithms in computer vision.","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":" ","pages":"411-431"},"PeriodicalIF":1.9,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10752861/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10224341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning heterogeneous delays in a layer of spiking neurons for fast motion detection. 快速运动检测中尖峰神经元层的异构延迟学习。

IF 1.9 4区工程技术

Biological Cybernetics Pub Date : 2023-10-01 Epub Date: 2023-09-11 DOI: 10.1007/s00422-023-00975-8

Antoine Grimaldi, Laurent U Perrinet

{"title":"Learning heterogeneous delays in a layer of spiking neurons for fast motion detection.","authors":"Antoine Grimaldi, Laurent U Perrinet","doi":"10.1007/s00422-023-00975-8","DOIUrl":"10.1007/s00422-023-00975-8","url":null,"abstract":"The precise timing of spikes emitted by neurons plays a crucial role in shaping the response of efferent biological neurons. This temporal dimension of neural activity holds significant importance in understanding information processing in neurobiology, especially for the performance of neuromorphic hardware, such as event-based cameras. Nonetheless, many artificial neural models disregard this critical temporal dimension of neural activity. In this study, we present a model designed to efficiently detect temporal spiking motifs using a layer of spiking neurons equipped with heterogeneous synaptic delays. Our model capitalizes on the diverse synaptic delays present on the dendritic tree, enabling specific arrangements of temporally precise synaptic inputs to synchronize upon reaching the basal dendritic tree. We formalize this process as a time-invariant logistic regression, which can be trained using labeled data. To demonstrate its practical efficacy, we apply the model to naturalistic videos transformed into event streams, simulating the output of the biological retina or event-based cameras. To evaluate the robustness of the model in detecting visual motion, we conduct experiments by selectively pruning weights and demonstrate that the model remains efficient even under significantly reduced workloads. In conclusion, by providing a comprehensive, event-driven computational building block, the incorporation of heterogeneous delays has the potential to greatly improve the performance of future spiking neural network algorithms, particularly in the context of neuromorphic chips.","PeriodicalId":55374,"journal":{"name":"Biological Cybernetics","volume":" ","pages":"373-387"},"PeriodicalIF":1.9,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10571295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

What can computer vision learn from visual neuroscience? Introduction to the special issue. 计算机视觉可以从视觉神经科学中学到什么？特刊简介。

IF 1.9 4区工程技术

Biological Cybernetics Pub Date : 2023-10-01 DOI: 10.1007/s00422-023-00977-6

Kexin Chen, Hirak J Kashyap, Jeffrey L Krichmar, Xiumin Li

引用次数: 2

A Fundamental Inequality Governing the Rate Coding Response of Sensory Neurons. 控制感觉神经元速率编码反应的一个基本不等式。

IF 1.9 4区工程技术

Biological Cybernetics Pub Date : 2023-10-01 Epub Date: 2023-08-19 DOI: 10.1007/s00422-023-00971-y

Willy Wong

引用次数: 0