Zobrazeno 1 - 10
of 259
pro vyhledávání: '"ERIK DE SCHUTTER"'
Autor:
Iain Hepburn, Jules Lallouette, Weiliang Chen, Andrew R. Gallimore, Sarah Y. Nagasawa-Soeda, Erik De Schutter
Publikováno v:
Communications Biology, Vol 7, Iss 1, Pp 1-15 (2024)
Abstract Vesicles carry out many essential functions within cells through the processes of endocytosis, exocytosis, and passive and active transport. This includes transporting and delivering molecules between different parts of the cell, and storing
Externí odkaz:
https://doaj.org/article/dc8124eb166c457e9811be8367031a6f
Autor:
Gabriela Cirtala, Erik De Schutter
Publikováno v:
iScience, Vol 27, Iss 9, Pp 110756- (2024)
Summary: Most central neurons have intricately branched dendritic trees that integrate massive numbers of synaptic inputs. Intrinsic active mechanisms in dendrites can be heterogeneous and be modulated in a branch-specific way. However, it remains po
Externí odkaz:
https://doaj.org/article/ebfe299278884838840f672bc823ff05
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-16 (2023)
Abstract Both the environment and our body keep changing dynamically. Hence, ensuring movement precision requires adaptation to multiple demands occurring simultaneously. Here we show that the cerebellum performs the necessary multi-dimensional compu
Externí odkaz:
https://doaj.org/article/da9f32ce58804615bce4946703f744b8
Autor:
Mizuki Kato, Erik De Schutter
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 7, p e1011320 (2023)
We investigate the relationship between primary dendrite selection of Purkinje cells and migration of their presynaptic partner granule cells during early cerebellar development. During postnatal development, each Purkinje cell grows more than three
Externí odkaz:
https://doaj.org/article/f9d9a4c8bcc04c568f65e4971c608822
Autor:
Erik De Schutter
Publikováno v:
Frontiers in Neuroinformatics, Vol 17 (2023)
The Neural Development Simulator, NeuroDevSim, is a Python module that simulates the most important aspects of brain development: morphological growth, migration, and pruning. It uses an agent-based modeling approach inherited from the NeuroMaC softw
Externí odkaz:
https://doaj.org/article/3a7b934c9edd4004882cc1a685b22fe0
Publikováno v:
eLife, Vol 11 (2022)
How dynamic interactions between nervous system regions in mammals performs online motor control remains an unsolved problem. In this paper, we show that feedback control is a simple, yet powerful way to understand the neural dynamics of sensorimotor
Externí odkaz:
https://doaj.org/article/9681c2e1d7404704a22d4de6f4fc5dc0
Autor:
Weiliang Chen, Tristan Carel, Omar Awile, Nicola Cantarutti, Giacomo Castiglioni, Alessandro Cattabiani, Baudouin Del Marmol, Iain Hepburn, James G. King, Christos Kotsalos, Pramod Kumbhar, Jules Lallouette, Samuel Melchior, Felix Schürmann, Erik De Schutter
Publikováno v:
Frontiers in Neuroinformatics, Vol 16 (2022)
Recent advances in computational neuroscience have demonstrated the usefulness and importance of stochastic, spatial reaction-diffusion simulations. However, ever increasing model complexity renders traditional serial solvers, as well as naive parall
Externí odkaz:
https://doaj.org/article/c0dc5b1feb324673a405041b6bc03ea8
Publikováno v:
eLife, Vol 9 (2020)
Both spike rate and timing can transmit information in the brain. Phase response curves (PRCs) quantify how a neuron transforms input to output by spike timing. PRCs exhibit strong firing-rate adaptation, but its mechanism and relevance for network o
Externí odkaz:
https://doaj.org/article/651c71a901814051ac2b0ceb80d391df
Publikováno v:
Frontiers in Neuroinformatics, Vol 14 (2020)
Physiologically detailed models of neural networks are an important tool for studying how biophysical mechanisms impact neural information processing. An important, fundamental step in constructing such a model is determining where neurons are placed
Externí odkaz:
https://doaj.org/article/aec4b29a23ed40309340e421691d879f
Publikováno v:
Cell Reports, Vol 24, Iss 6, Pp 1536-1549 (2018)
Summary: Climbing fibers (CFs) provide instructive signals driving cerebellar learning, but mechanisms causing the variable CF responses in Purkinje cells (PCs) are not fully understood. Using a new experimentally validated PC model, we unveil the io
Externí odkaz:
https://doaj.org/article/a16eace3036c4b2fa540bcd0aea56064