Results 1 to 10 of about 34,208 (235)

Assessing the synaptic transmission speed (ms) and action potential frequency (Hz) of water in relation to its behaviour in theoretical and computational neuroscience field 

Journal of Multidisciplinary & Translational Research
The study quantified water concentration (%) effects on synaptic transmission speed (ms) and action potential (AP) frequency (Hz) in silico. NEURON-simulated pyramidal neuron under controlled water levels (40–100%) was undertaken. Linear regression (SciPy) was applied to analyzed relationships.
Monday Sunday Adiaha
openaire   +2 more sources

Book Review: "Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems", P. Dayan and L. F. Abbott, eds., (2001)

Journal of Integrative Neuroscience, 2006
Roman R. Poznański
openaire   +2 more sources

Spatial Structure and Information Transfer in Visual Networks

Frontiers in Physics, 2021
In human and animal groups, social interactions often rely on the transmission of information via visual observation of the behavior of others. These visual interactions are governed by the laws of physics and sensory limits.
Winnie Poel, Winnie Poel, Claudia Winklmayr, Claudia Winklmayr, Pawel Romanczuk, Pawel Romanczuk   +5 more
doaj   +1 more source

Time as a supervisor: temporal regularity and auditory object learning

Frontiers in Computational Neuroscience, 2023
Sensory systems appear to learn to transform incoming sensory information into perceptual representations, or “objects,” that can inform and guide behavior with minimal explicit supervision. Here, we propose that the auditory system can achieve this goal
Ronald W. DiTullio, Ronald W. DiTullio, Ronald W. DiTullio, Chetan Parthiban, Eugenio Piasini, Eugenio Piasini, Pratik Chaudhari, Vijay Balasubramanian, Vijay Balasubramanian, Vijay Balasubramanian, Yale E. Cohen   +10 more
doaj   +1 more source

Retinal input integration in excitatory and inhibitory neurons in the mouse superior colliculus in vivo

eLife, 2023
The superior colliculus (SC) is a midbrain structure that receives inputs from retinal ganglion cells (RGCs). The SC contains one of the highest densities of inhibitory neurons in the brain but whether excitatory and inhibitory SC neurons differentially ...
Carolin Gehr, Jeremie Sibille, Jens Kremkow   +2 more
doaj   +1 more source

A reanalysis of “Two types of asynchronous activity in networks of excitatory and inhibitory spiking neurons” [version 1; referees: 2 approved]

F1000Research, 2016
Neuronal activity in the central nervous system varies strongly in time and across neuronal populations. It is a longstanding proposal that such fluctuations generically arise from chaotic network dynamics.
Rainer Engelken, Farzad Farkhooi, David Hansel, Carl van Vreeswijk, Fred Wolf   +4 more
doaj   +1 more source

Predictive learning as a network mechanism for extracting low-dimensional latent space representations

Nature Communications, 2021
Neural networks trained using predictive models generate representations that recover the underlying low-dimensional latent structure in the data. Here, the authors demonstrate that a network trained on a spatial navigation task generates place-related ...
Stefano Recanatesi, Matthew Farrell, Guillaume Lajoie, Sophie Deneve, Mattia Rigotti, Eric Shea-Brown   +5 more
doaj   +1 more source

Place-cell capacity and volatility with grid-like inputs

eLife, 2021
What factors constrain the arrangement of the multiple fields of a place cell? By modeling place cells as perceptrons that act on multiscale periodic grid-cell inputs, we analytically enumerate a place cell’s repertoire – how many field arrangements it ...
Man Yi Yim, Lorenzo A Sadun, Ila R Fiete, Thibaud Taillefumier   +3 more
doaj   +1 more source

A multi-scale computational model of the effects of TMS on motor cortex [version 3; referees: 2 approved]

F1000Research, 2017
The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different ...
Hyeon Seo, Natalie Schaworonkow, Sung Chan Jun, Jochen Triesch   +3 more
doaj   +1 more source

A multi-scale computational model of the effects of TMS on motor cortex [version 2; referees: 2 approved]

F1000Research, 2017
The detailed biophysical mechanisms through which transcranial magnetic stimulation (TMS) activates cortical circuits are still not fully understood. Here we present a multi-scale computational model to describe and explain the activation of different ...
Hyeon Seo, Natalie Schaworonkow, Sung Chan Jun, Jochen Triesch   +3 more
doaj   +1 more source