20 papers · ranked by Valyu relevance
Stefano Panzeri, Jakob H. Macke, Joachim Gross, Christoph Kayser
Title: Highlights 1. • Neural population codes are organized at multiple spatial scales. 2. • Microscopic organization of neural codes reveals a key role of neural heterogeneity. 3. • Microscopic and population dynamics interact to make processing state-dependent. 4. • Additional computational analyses of neural…
Thomas E. Yerxa, Eric Kee, Michael R. DeWeese, Emily A. Cooper + 1 more
'Alan Alfred Stocker'] According to the efficient coding hypothesis, sensory systems are adapted to maximize their ability to encode information about the environment. Sensory neurons play a key role in encoding by selectively modulating their firing rate for a subset of all possible stimuli. This pattern of modulation…
Richard Naud, Wulfram Gerstner, Olaf Sporns
The response of a neuron to a time-dependent stimulus, as measured in a Peri-Stimulus-Time-Histogram (PSTH), exhibits an intricate temporal structure that reflects potential temporal coding principles. Here we analyze the encoding and decoding of PSTHs for spiking neurons with arbitrary refractoriness and adaptation.…
Omer Revah, Fred Wolf, Michael J. Gutnick, Andreas Neef
Sixty years after the concept of population coding in neuronal networks was introduced, we still lack a comprehensive understanding of its performance limits and the role of neuronal physiology. Here, we use dynamic gain analysis in a general model of population coding and demonstrate that disparate parameters of…
Huanqiu Zhang, Israel Nelken, Tatyana Sharpee
Deciphering the neural code requires identifying its fundamental symbols or code-words. Neural activity is usually interpreted either as a rate code – based on average spike counts – or as a temporal code, which distinguishes patterns with identical counts. Yet, the symbols of the code remain undefined. Here we show…
Omer Revah, Fred Wolf, Michael J. Gutnick, Andreas Neef
Cortical function reflects the coordinated activities of populations of neurons, which, in turn, depend on the speed with which each neuron can respond to input, as revealed by dynamic gain analysis. In Layer 4 of the rodent barrel cortex, a finite population of interconnected, small, excitatory neurons rapidly and…
R. Becket Ebitz, Benjamin Y. Hayden
A major shift is happening within neurophysiology: a population doctrine is drawing level with the single-neuron doctrine that has long dominated the field. Population-level ideas have so far had their greatest impact in motor neuroscience, but they hold great promise for resolving open questions in cognition as well.…
Adrianna Loback, Jason Prentice, Mark L. Ioffe, Michael J. Berry
An appealing new principle for neural population codes is that correlations among neurons organize neural activity patterns into a discrete set of clusters, which can each be viewed as a noise-robust population codeword. Previous studies assumed that these codewords corresponded geometrically with local peaks in the…
Michael J. Berry II, Gašper Tkačik
We propose that correlations among neurons are generically strong enough to organize neural activity patterns into a discrete set of clusters, which can each be viewed as a population codeword. Our reasoning starts with the analysis of retinal ganglion cell data using maximum entropy models, showing that the population…
Stefano Panzeri, Ella Janotte, Alejandro Pequeño-Zurro, Jacopo Bonato + 1 more
'Jacopo Bonato' 'Chiara Bartolozzi'] In the brain, information is encoded, transmitted and used to inform behaviour at the level of timing of action potentials distributed over population of neurons. To implement neural-like systems in silico, to emulate neural function, and to interface successfully with the brain…
Jacob L. Yates, Benjamin Scholl
The synaptic inputs to single cortical neurons exhibit substantial diversity in their sensory-driven activity. What this diversity reflects is unclear, and appears counter-productive in generating selective somatic responses to specific stimuli. We propose that synaptic diversity arises because neurons decode…
Jorrit S. Montijn, J. Alexander Heimel
The brain processes, computes, and categorizes sensory input. But even in sensory brain areas, the relationship between input signals and neuronal spiking activity is complex and non-linear. Fast subsecond fluctuations in neuronal population responses dominate the temporal dynamics of neural circuits. Traditional…
Hao Si, Xiaojuan Sun
Neural coding is a key problem in neuroscience, which can promote people's understanding of the mechanism that brain processes information. Among the classical theories of neural coding, the population rate coding has been studied widely in many works. Most computational studies considered the neurons and the…
Mikhail V. Kiselev
At present, it is obvious that different sections of nervous system utilize different methods for information coding. Primary afferent signals in most cases are represented in form of spike trains using a combination of rate coding and population coding while there are clear evidences that temporal coding is used in…
Lars Schutzeichel, Jan Bauer, Peter Bouss, Simon Musall + 2 more
Brain networks are high-dimensional and interacting complex systems that exhibit substantial structural heterogeneity as well as temporal variability. Yet, when exposed to a stimulus, their recurrent circuits perform reliable computations. The mechanisms underlying this robustness are, however, still mostly unknown.…
Luyao Chen, Zhiqiang Chen, Longsheng Jiang, Xiang Liu + 12 more
'Bo Zhang' 'Xiaolong Zou' 'Jinying Gao' 'Yu Zhu' 'Xizi Gong' 'Shan Yu' 'Sen Song' 'Liangyi Chen' 'Fang Fang' 'Si Wu' 'Jia Liu'] - 1. AI of Brain and Cognitive Sciences Research Group, Beijing Academy of Artificial Intelligence, Beijing 100084, China - 2. School of Psychology and Cognitive Sciences, Peking University…
Joel Zylberberg
In the sensory systems, most neurons’ firing rates are tuned to at least one aspect of the stimulus. Other neurons are untuned, meaning that their firing rates appear not to depend on the stimulus. Previous work on information coding in neural populations has ignored the untuned neurons, based on the tacit assumption…
Meng Li, Joe Z. Tsien
A major stumbling block to cracking the real-time neural code is neuronal variability - neurons discharge spikes with enormous variability not only across trials within the same experiments but also in resting states. Such variability is widely regarded as a noise which is often deliberately averaged out during data…
He Chen, Jun Kunimatsu, Tomomichi Oya, Yuri Imaizumi + 5 more
'Masayuki Matsumoto' 'Takafumi Minamimoto' 'Yuji Naya' 'Hiroshi Yamada'] Title: Abstract Neural population dynamics provide a key computational framework for understanding information processing in the sensory, cognitive, and motor functions of the brain. They systematically depict complex neural population activity…
Doo Seok Jeong
Spiking neural networks (SNN) as time-dependent hypotheses consisting of spiking nodes (neurons) and directed edges (synapses) are believed to offer unique solutions to reward prediction tasks and the related feedback that are classified as reinforcement learning. Generally, temporal difference (TD) learning renders it…