Input-output Transformation
Input-Output Transformation is a computational framework in neuroscience that characterizes how a neuron integrates synaptic inputs across its dendritic tree to generate a specific pattern of action potential output, distinguishing it from simpler activation models by explicitly accounting for the spatiotemporal dynamics and nonlinear interactions of dendritic processing.
179
Publications
8.6K
Citations
508
Authors
275
Institutions
Publications per year
2017–2026
61
Parents
179
Squeezing as an irreducible resource
Samuel L. Braunstein · Physical Review A · 2005 · 508 citations · Full text
Natural Sciences, Physics, Optics +16
Numerical representation for action in the parietal cortex of the monkey
Hiromasa Sawamura, Keisetsu Shima, Jun Tanji · Nature · 2002 · 327 citations · Full text
Gal Ariav, Alon Poleg-Polsky, Jackie Schiller · Journal of Neuroscience · 2003 · 286 citations · Full text
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275

Centre National de la Recherche Scientifique
Paris, France
7 h-index
17 publications
1.8K citations
HUN-REN Institute of Experimental Medicine
Budapest, Hungary
4 h-index
17 publications
895 citations

Sorbonne Université
Paris, France
4 h-index
9 publications
381 citations
Georgia Institute of Technology
Atlanta, United States
3 h-index
17 publications
289 citations
University of Sussex
Brighton, United Kingdom
3 h-index
6 publications
156 citations

Hungarian Academy of Sciences
Budapest, Hungary
3 h-index
10 publications
562 citations

Cornell University
Ithaca, United States
3 h-index
3 publications
197 citations
Semmelweis University
Budapest, Hungary
3 h-index
3 publications
136 citations
1–8 of 275
Repository · 12 publications · 476 citations
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6 publications · 290 citations
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4 publications · 109 citations
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JN · 3 publications · 86 citations
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3 publications · 54 citations
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