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Christopher W Lynn

Showing results (1-10 of 27) with videos related to

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Nature Physics|June 29, 2026
Simple input-output dependencies explain neuronal activityChristopher W Lynn
Arxiv|March 27, 2026
Direct dependencies between neurons explain activityChristopher W Lynn
Proceedings of the National Academy of Sciences of the United States of America|August 5, 2021
Quantifying the compressibility of complex networksChristopher W Lynn, Danielle S Bassett
Proceedings of the National Academy of Sciences of the United States of America|October 8, 2025
Statistical physics of large-scale neural activity with loopsDavid P Carcamo, Christopher W Lynn
Proceedings of the National Academy of Sciences of the United States of America|November 24, 2020
How humans learn and represent networksChristopher W Lynn, Danielle S Bassett
PNAS Nexus|July 5, 2024
Emergent scale-free networksChristopher W Lynn, Caroline M Holmes, Stephanie E Palmer
Plos Computational Biology|September 4, 2020
Relations between large-scale brain connectivity and effects of regional stimulation depend on collective dynamical stateLia Papadopoulos, Christopher W Lynn, Demian Battaglia, et al.
Physical Review Letters|September 26, 2022
Decomposing the Local Arrow of Time in Interacting SystemsChristopher W Lynn, Caroline M Holmes, William Bialek, et al.
Arxiv|January 30, 2023
Information content of note transitions in the music of J. S. BachSuman Kulkarni, Sophia U David, Christopher W Lynn, et al.
Nature Communications|May 10, 2020
Abstract representations of events arise from mental errors in learning and memoryChristopher W Lynn, Ari E Kahn, Nathaniel Nyema, et al.
Pageof 3

Showing results (1-10 of 27) with videos related to

Sort By:
Pageof 3
Nature Physics|June 29, 2026
Simple input-output dependencies explain neuronal activityChristopher W Lynn
Arxiv|March 27, 2026
Direct dependencies between neurons explain activityChristopher W Lynn
Proceedings of the National Academy of Sciences of the United States of America|August 5, 2021
Quantifying the compressibility of complex networksChristopher W Lynn, Danielle S Bassett
Proceedings of the National Academy of Sciences of the United States of America|October 8, 2025
Statistical physics of large-scale neural activity with loopsDavid P Carcamo, Christopher W Lynn
Proceedings of the National Academy of Sciences of the United States of America|November 24, 2020
How humans learn and represent networksChristopher W Lynn, Danielle S Bassett
PNAS Nexus|July 5, 2024
Emergent scale-free networksChristopher W Lynn, Caroline M Holmes, Stephanie E Palmer
Plos Computational Biology|September 4, 2020
Relations between large-scale brain connectivity and effects of regional stimulation depend on collective dynamical stateLia Papadopoulos, Christopher W Lynn, Demian Battaglia, et al.
Physical Review Letters|September 26, 2022
Decomposing the Local Arrow of Time in Interacting SystemsChristopher W Lynn, Caroline M Holmes, William Bialek, et al.
Arxiv|January 30, 2023
Information content of note transitions in the music of J. S. BachSuman Kulkarni, Sophia U David, Christopher W Lynn, et al.
Nature Communications|May 10, 2020
Abstract representations of events arise from mental errors in learning and memoryChristopher W Lynn, Ari E Kahn, Nathaniel Nyema, et al.
Pageof 3