Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Michel Besserve"'
Autor:
Shervin Safavi, Theofanis I Panagiotaropoulos, Vishal Kapoor, Juan F Ramirez-Villegas, Nikos K Logothetis, Michel Besserve
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 4, p e1010983 (2023)
Despite the considerable progress of in vivo neural recording techniques, inferring the biophysical mechanisms underlying large scale coordination of brain activity from neural data remains challenging. One obstacle is the difficulty to link high dim
Externí odkaz:
https://doaj.org/article/e7be98aaff554251a8e830391800d939
Autor:
Vishal Kapoor, Abhilash Dwarakanath, Shervin Safavi, Joachim Werner, Michel Besserve, Theofanis I. Panagiotaropoulos, Nikos K. Logothetis
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-16 (2022)
The role of the prefrontal cortex in conscious perception is debated because of its involvement in task relevant behaviour, such as subjective perceptual reports. Here, the authors show that prefrontal activity in rhesus macaques correlates with subj
Externí odkaz:
https://doaj.org/article/ee7fe8b5785445089a5e3688a5207899
Publikováno v:
Frontiers in Network Physiology
Introduction: Transient phenomena play a key role in coordinating brain activity at multiple scales, however their underlying mechanisms remain largely unknown. A key challenge for neural data science is thus to characterize the network interactions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd21afb7336df0c5ace71310e69220bb
http://arxiv.org/abs/2209.07508
http://arxiv.org/abs/2209.07508
Autor:
Theofanis I Panagiotaropoulos, Vishal Kapoor, S Safavi, Juan F. Ramirez-Villegas, Michel Besserve, Nikos K. Logothetis
Publikováno v:
PLoS Computational Biology
Despite the considerable progress ofin vivoneural recording techniques, inferring the biophysical mechanisms underlying large scale coordination of brain activity from neural data remains challenging. One obstacle is the difficulty to link high dimen
Autor:
Henry C. Evrard, Yusuke Murayama, Nikos K. Logothetis, Axel Oeltermann, Juan F. Ramirez-Villegas, Michel Besserve
Publikováno v:
Nature
The hippocampus has a major role in encoding and consolidating long-term memories, and undergoes plastic changes during sleep1. These changes require precise homeostatic control by subcortical neuromodulatory structures2. The underlying mechanisms of
Autor:
Rikkert Hindriks, Xerxes D Arsiwalla, Theofanis Panagiotaropoulos, Michel Besserve, Paul F.M.J. Verschure, Nikos K Logothetis, Gustavo Deco
Publikováno v:
Frontiers in Neural Circuits, Vol 10 (2016)
Multi-electrode recordings of local field potentials (LFP's) provide the opportunity to investigate the spatiotemporal organization of neural activity on the scale of several millimeters. In particular, the phases of oscillatory LFP's allow studying
Externí odkaz:
https://doaj.org/article/892ddd750cbc43478ae6f01c08d0a9f7
Autor:
MICHEL BESSERVE, KARIM JERBI, FRANCOIS LAURENT, SYLVAIN BAILLET, JACQUES MARTINERIE, LINE GARNERO
Publikováno v:
Biological Research, Vol 40, Iss 4, Pp 415-437 (2007)
Classification algorithms help predict the qualitative properties of a subject's mental state by extracting useful information from the highly multivariate non-invasive recordings of his brain activity. In particular, applying them to Magneto-encepha
Externí odkaz:
https://doaj.org/article/dba3a17828394a2491e60ca394fd3999
Publikováno v:
PLoS Biology, Vol 13, Iss 9, p e1002257 (2015)
Distributed neural processing likely entails the capability of networks to reconfigure dynamically the directionality and strength of their functional connections. Yet, the neural mechanisms that may allow such dynamic routing of the information flow
Externí odkaz:
https://doaj.org/article/a90ef16735bf4279866d37c6f967bb7e
During sleep, cortical network connectivity likely undergoes both synaptic potentiation and depression through system consolidation and homeostatic processes. However, how these modifications are coordinated across sleep stages remains largely unknow
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::070b037fc75de502935b19244dbfcea2
https://hdl.handle.net/21.11116/0000-0008-2B4C-4
https://hdl.handle.net/21.11116/0000-0008-2B4C-4
Publikováno v:
Neural computation
Time series datasets often contain heterogeneous signals, composed of both continuously changing quantities and discretely occurring events. The coupling between these measurements may provide insights into key underlying mechanisms of the systems un