Synaptic Input Selectivity
Synaptic Input Selectivity is a neurocomputational mechanism that, as a subset of synaptic integration processes, selectively amplifies or attenuates specific incoming neural signals based on their spatial and temporal patterns, thereby enabling neurons to differentially respond to distinct synaptic inputs according to their functional relevance.
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2017–2026
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Catherine S. Woolley, Nancy G. Weiland, Bruce S. McEwen et al. · Journal of Neuroscience · 1997 · 696 citations · Full text
Dendritic organization of sensory input to cortical neurons in vivo
Hongbo Jia, Nathalie L. Rochefort, Xiaowei Chen et al. · Nature · 2010 · 552 citations
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Max Planck Florida Institute for Neuroscience, United States
4 publications · 574 citations
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University of Washington
Seattle, United States
11 h-index
27 publications
2.8K citations
Columbia University
New York, United States
8 h-index
26 publications
1.1K citations
University of California San Diego
San Diego, United States
6 h-index
8 publications
1.2K citations
Harvard University
Cambridge, United States
6 h-index
40 publications
2.9K citations
Technical University of Munich
Munich, Germany
5 h-index
7 publications
672 citations
University College London
London, United Kingdom
5 h-index
8 publications
363 citations
University of Oxford
Oxford, United Kingdom
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9 publications
2.2K citations

Howard Hughes Medical Institute
Chevy Chase, United States
4 h-index
15 publications
5.9K citations
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JN · 19 publications · 2.6K citations
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EJN · 8 publications · 630 citations
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