Results 41 to 50 of about 126,855 (275)

Opening Computational Neuroscience to a Wider Audience: Virtual Escape Room for Kids [PDF]

, 2023
As researchers it is vital that we increase the accessibility, transparency, diversity, and inclusivity of our work. One-way Neuromatch has championed this is by having outreach sessions for children (8+) to explain computational-neuroscience concepts ...
Hoxha, Isabelle, Urai, Anne E, Kienigiel, Dante, Lu, Xinquan, Zhang, Ru-Yuan, Halper, Nick, Mudrik, Noga, Butler, John S, Abdelhack, Mohamed, Forest, Jeremy, Peters, Megan   +10 more
core  

Building on models-a perspective for computational neuroscience. [PDF]

Cereb Cortex
Neural circuit models are essential for integrating observations of the nervous system into a consistent whole. Public sharing of well-documented codes for such models facilitates further development.
Plesser HE, Davison AP, Diesmann M, Fukai T, Gemmeke T, Gleeson P, Knight JC, Nowotny T, René A, Rhodes O, Roque AC, Senk J, Schwalger T, Stadtmann T, Tiddia G, van Albada SJ.   +15 more
europepmc   +2 more sources

Computational Logic for Biomedicine and Neurosciences

CoRR, 2020
We advocate here the use of computational logic for systems biology, as a \emph{unified and safe} framework well suited for both modeling the dynamic behaviour of biological systems, expressing properties of them, and verifying these properties.
De Maria E., Despeyroux J., Felty A., Lio P., Olarte C., Bahrami A.   +5 more
openaire   +3 more sources

Nonlinear Dynamics in Computational Neuroscience

, 2019
This book provides an essential overview of computational neuroscience. It addresses a broad range of aspects, from physiology to nonlinear dynamical approaches to understanding neural computation, and from the simulation of brain circuits to the ...

core   +1 more source

Neural network based successor representations to form cognitive maps of space and language

Scientific Reports, 2022
How does the mind organize thoughts? The hippocampal-entorhinal complex is thought to support domain-general representation and processing of structural knowledge of arbitrary state, feature and concept spaces.
Paul Stoewer, Christian Schlieker, Achim Schilling, Claus Metzner, Andreas Maier, Patrick Krauss   +5 more
doaj   +1 more source

Computational Neuroscience: Mathematical and Statistical Perspectives. [PDF]

Annu Rev Stat Appl, 2018
Mathematical and statistical models have played important roles in neuroscience, especially by describing the electrical activity of neurons recorded individually, or collectively across large networks.
Kass RE, Amari SI, Arai K, Brown EN, Diekman CO, Diesmann M, Doiron B, Eden UT, Fairhall AL, Fiddyment GM, Fukai T, Grün S, Harrison MT, Helias M, Nakahara H, Teramae JN, Thomas PJ, Reimers M, Rodu J, Rotstein HG, Shea-Brown E, Shimazaki H, Shinomoto S, Yu BM, Kramer MA.   +24 more
europepmc   +3 more sources

Neuromodulator-dependent synaptic tagging and capture retroactively controls neural coding in spiking neural networks

Scientific Reports, 2022
Events that are important to an individual’s life trigger neuromodulator release in brain areas responsible for cognitive and behavioral function. While it is well known that the presence of neuromodulators such as dopamine and norepinephrine is required
Andrew B. Lehr, Jannik Luboeinski, Christian Tetzlaff   +2 more
doaj   +1 more source

Context-sensitive computational mechanistic explanation in cognitive neuroscience

Frontiers in Psychology, 2022
Mainstream cognitive neuroscience aims to build mechanistic explanations of behavior by mapping abilities described at the organismal level via the subpersonal level of computation onto specific brain networks.
Matthieu M. de Wit, Heath E. Matheson
doaj   +1 more source

Computational Cognitive Neuroscience [PDF]

, 2018
This chapter provides an overview of the basic research strategies and analytic techniques deployed in computational cognitive neuroscience. On the one hand, “top-down” (or reverse-engineering) strategies are used to infer, from formal characterizations ...
Carlos Zednik, Zednik, Carlos
core   +1 more source

Data-driven computational neuroscience: machine learning and statistical models

, 2021
This book describes statistical and machine learning methods to build computational models learned from real-world neuroscience data. These methods cover supervised and unsupervised classification with probabilistic and non-probabilistic models ...
Bielza Lozoya, María Concepción, Larrañaga Múgica, Pedro María   +1 more
core   +1 more source