TY - JOUR
T1 - Temporal Dynamics of Neural Responses in Human Visual Cortex
AU - Groen, Iris I.A.
AU - Piantoni, Giovanni
AU - Montenegro, Stephanie
AU - Flinker, Adeen
AU - Devore, Sasha
AU - Devinsky, Orrin
AU - Doyle, Werner
AU - Dugan, Patricia
AU - Friedman, Daniel
AU - Ramsey, Nick F.
AU - Petridou, Natalia
AU - Winawer, Jonathan
N1 - Publisher Copyright:
Copyright © 2022 the authors.
PY - 2022/10/5
Y1 - 2022/10/5
N2 - Neural responses to visual stimuli exhibit complex temporal dynamics, including subadditive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low contrast. These phenomena are often studied independently. Here, we demonstrate these phenomena within the same experiment and model the underlying neural computations with a single computational model. We extracted time-varying responses from electrocorticographic recordings from patients presented with stimuli that varied in duration, interstimulus interval (ISI) and contrast. Aggregating data across patients from both sexes yielded 98 electrodes with robust visual responses, covering both earlier (V1-V3) and higher-order (V3a/b, LO, TO, IPS) retinotopic maps. In all regions, the temporal dynamics of neural responses exhibit several nonlinear features. Peak response amplitude saturates with high contrast and longer stimulus durations, the response to a second stimulus is suppressed for short ISIs and recovers for longer ISIs, and response latency decreases with increasing contrast. These features are accurately captured by a computational model composed of a small set of canonical neuronal operations, that is, linear filtering, rectification, exponentiation, and a delayed divisive normalization. We find that an increased normalization term captures both contrast- and adaptation-related response reductions, suggesting potentially shared underlying mechanisms. We additionally demonstrate both changes and invariance in temporal response dynamics between earlier and higher-order visual areas. Together, our results reveal the presence of a wide range of temporal and contrast-dependent neuronal dynamics in the human visual cortex and demonstrate that a simple model captures these dynamics at millisecond resolution.
AB - Neural responses to visual stimuli exhibit complex temporal dynamics, including subadditive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low contrast. These phenomena are often studied independently. Here, we demonstrate these phenomena within the same experiment and model the underlying neural computations with a single computational model. We extracted time-varying responses from electrocorticographic recordings from patients presented with stimuli that varied in duration, interstimulus interval (ISI) and contrast. Aggregating data across patients from both sexes yielded 98 electrodes with robust visual responses, covering both earlier (V1-V3) and higher-order (V3a/b, LO, TO, IPS) retinotopic maps. In all regions, the temporal dynamics of neural responses exhibit several nonlinear features. Peak response amplitude saturates with high contrast and longer stimulus durations, the response to a second stimulus is suppressed for short ISIs and recovers for longer ISIs, and response latency decreases with increasing contrast. These features are accurately captured by a computational model composed of a small set of canonical neuronal operations, that is, linear filtering, rectification, exponentiation, and a delayed divisive normalization. We find that an increased normalization term captures both contrast- and adaptation-related response reductions, suggesting potentially shared underlying mechanisms. We additionally demonstrate both changes and invariance in temporal response dynamics between earlier and higher-order visual areas. Together, our results reveal the presence of a wide range of temporal and contrast-dependent neuronal dynamics in the human visual cortex and demonstrate that a simple model captures these dynamics at millisecond resolution.
KW - ECOG
KW - adaptation
KW - broadband
KW - contrast
KW - temporal dynamics
KW - vision
UR - http://www.scopus.com/inward/record.url?scp=85140362553&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85140362553&partnerID=8YFLogxK
U2 - 10.1523/JNEUROSCI.1812-21.2022
DO - 10.1523/JNEUROSCI.1812-21.2022
M3 - Article
C2 - 35999054
AN - SCOPUS:85140362553
SN - 0270-6474
VL - 42
SP - 7562
EP - 7580
JO - Journal of Neuroscience
JF - Journal of Neuroscience
IS - 40
ER -