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Brain-inspired learning models attempt to mimic the cortical architecture and computations performed in the neurons and synapses constituting the human brain to achieve its efficiency in cognitive tasks. In this work, we present…

Neural and Evolutionary Computing · Computer Science 2017-03-21 Priyadarshini Panda , Gopalakrishnan Srinivasan , Kaushik Roy

Recent studies have shown how spiking networks can learn complex functionality through error-correcting plasticity, but the resulting structures and dynamics remain poorly studied. To elucidate how these models may link to observed dynamics…

Neurons and Cognition · Quantitative Biology 2025-08-19 Jonas Oberste-Frielinghaus , Anno C. Kurth , Julian Göltz , Laura Kriener , Junji Ito , Mihai A. Petrovici , Sonja Grün

Spike Timing Dependent Plasticity is form of learning that has been demonstrated in real cortical tissue, but attempts to use it for artificial systems have not produced good results. This paper seeks to remedy this with two significant…

Neural and Evolutionary Computing · Computer Science 2020-07-01 Simon Davidson , Stephen B. Furber , Oliver Rhodes

We present the mathematical basis of a new approach to the analysis of temporal coding. The foundation of the approach is the construction of several families of novel distances (metrics) between neuronal impulse trains. In contrast to most…

Neurons and Cognition · Quantitative Biology 2007-05-23 Jonathan D. Victor , Keith P. Purpura

Spike synchrony, which occurs in various cortical areas in response to specific perception, action and memory tasks, has sparked a long-standing debate on the nature of temporal organization in cortex. One prominent view is that this type…

Neurons and Cognition · Quantitative Biology 2017-12-18 Clemens Korndörfer , Ekkehard Ullner , Jordi García-Ojalvo , Gordon Pipa

It is now widely accepted that one of the roles of the hippocampus is to maintain episodic spatial representations, while parallel striatal pathways contribute to both declarative and procedural value computations by encoding different…

Neurons and Cognition · Quantitative Biology 2014-12-10 Fabian Chersi

Primary vestibular neurons are categorized as either regularly or irregularly firing afferents that use rate and temporal sensory encoding strategies, respectively. While many factors influence firing in these neurons, recent work in…

Neurons and Cognition · Quantitative Biology 2021-08-03 Selina Baeza Loya

Maintaining the ability to fire sparsely is crucial for information encoding in neural networks. Additionally, spiking homeostasis is vital for spiking neural networks with changing numbers of weights and neurons. We discuss a range of…

Neural and Evolutionary Computing · Computer Science 2019-10-02 Katarzyna Kozdon , Peter Bentley

Spike-timing-dependent plasticity(STDP) is a biological process in which the precise order and timing of neuronal spikes affect the degree of synaptic modification. While there have been numerous research focusing on the role of STDP in…

Neurons and Cognition · Quantitative Biology 2021-08-10 Hong-Gyu Yoon , Pilwon Kim

The coding properties of cells with different types of receptive fields have been studied for decades. ON-type neurons fire in response to positive fluctuations of the time-dependent stimulus, whereas OFF cells are driven by negative…

Neurons and Cognition · Quantitative Biology 2009-09-10 Eugenio Urdapilleta , Ines Samengo

We investigate the modes of oscillation of heterogeneous ring-networks of quadratic integrate-and-fire neurons with non-local, space-dependent coupling. Perturbations of the equilibrium state with a particular wave number produce transient…

Neurons and Cognition · Quantitative Biology 2017-11-15 Jose M. Esnaola-Acebes , Alex Roxin , Daniele Avitabile , Ernest Montbrió

The hippocampus has been associated with both spatial cognition and episodic memory formation, but integrating these functions into a unified framework remains challenging. Here, we demonstrate that forming discrete memories of visual…

Artificial Intelligence · Computer Science 2024-05-24 Adrian F. Amil , Ismael T. Freire , Paul F. M. J. Verschure

This paper investigates whether the hexagonal structure of grid cells provides any performance benefits or if it merely represents a biologically convenient configuration. Utilizing the Vector-HaSH content addressable memory model as a…

Neurons and Cognition · Quantitative Biology 2024-10-17 Taahaa Mir , Peipei Yao , Kateri Duranceau , Isabeau Prémont-Schwarz

In this work, we present an additive model for space-time data that splits the data into a temporally correlated component and a spatially correlated component. We model the spatially correlated portion using a time-varying Gaussian…

Methodology · Statistics 2017-11-13 Kristjan Greenewald , Seyoung Park , Shuheng Zhou , Alexander Giessing

Firing rate models are dynamical systems widely used in applied and theoretical neuroscience to describe local cortical dynamics in neuronal populations. By providing a macroscopic perspective of neuronal activity, these models are…

Neurons and Cognition · Quantitative Biology 2025-09-03 Simone Betteti , Giacomo Baggio , Francesco Bullo , Sandro Zampieri

In the last century, most sensorimotor studies of cortical neurons relied on average firing rates. Rate coding is efficient for fast sensorimotor processing that occurs within a few seconds. Much less is known about the neural mechanisms…

Neurons and Cognition · Quantitative Biology 2026-05-01 Terrence J. Sejnowski

Spike Timing Dependent Plasticity (STDP) is a Hebbian like synaptic learning rule. The basis of STDP has strong experimental evidences and it depends on precise input and output spike timings. In this paper we show that under biologically…

Neurons and Cognition · Quantitative Biology 2015-04-14 Subhajit Sengupta , Karthik S. Gurumoorthy , Arunava Banerjee

We investigate different dynamical regimes of neuronal network in the CA3 area of the hippocampus. The proposed neuronal circuit includes two fast- and two slowly-spiking cells which are interconnected by means of dynamical synapses. On the…

Neurons and Cognition · Quantitative Biology 2015-11-20 Anastasia I. Lavrova , Michael A. Zaks , Lutz Schimansky-Geier

We study a learning rule based upon the temporal correlation (weighted by a learning kernel) between incoming spikes and the internal state of the postsynaptic neuron, building upon previous studies of spike timing dependent synaptic…

Neurons and Cognition · Quantitative Biology 2007-05-23 Juergen Jost

How the brain co-ordinates the actions of distant regions in an efficient manner is an open problem. Many believe that cross-frequency coupling between the amplitude of high frequency local field potential oscillations in one region and the…

Neurons and Cognition · Quantitative Biology 2016-04-04 Thomas E. Gorochowski , Rafal Bogacz , Matthew Jones