- Home
- Search Results
- Page 1 of 1
Search for: All records
-
Total Resources3
- Resource Type
-
0000000003000000
- More
- Availability
-
21
- Author / Contributor
- Filter by Author / Creator
-
-
Smith, Elliot H (2)
-
Abbott, LF (1)
-
Bateman, Lisa M (1)
-
Brandmeir, Nicholas J (1)
-
Bruce, Samuel L (1)
-
Brunner, Peter (1)
-
Cao, Runnan (1)
-
Chakravarthula, Puneeth N (1)
-
Emerson, Ronald G (1)
-
Goodman, Robert R (1)
-
Gross, Robert E. (1)
-
Inman, Cory (1)
-
Inman, Cory S. (1)
-
Jacobs, Joshua (1)
-
Li, Xin (1)
-
Liou, Jyun-you (1)
-
Mamelak, Adam N (1)
-
McKhann, Guy M (1)
-
Miller, Jonathan (1)
-
Qasim, Salman E. (1)
-
- Filter by Editor
-
-
& Spizer, S. M. (0)
-
& . Spizer, S. (0)
-
& Ahn, J. (0)
-
& Bateiha, S. (0)
-
& Bosch, N. (0)
-
& Brennan K. (0)
-
& Brennan, K. (0)
-
& Chen, B. (0)
-
& Chen, Bodong (0)
-
& Drown, S. (0)
-
& Ferretti, F. (0)
-
& Higgins, A. (0)
-
& J. Peters (0)
-
& Kali, Y. (0)
-
& Ruiz-Arias, P.M. (0)
-
& S. Spitzer (0)
-
& Sahin. I. (0)
-
& Spitzer, S. (0)
-
& Spitzer, S.M. (0)
-
(submitted - in Review for IEEE ICASSP-2024) (0)
-
-
Have feedback or suggestions for a way to improve these results?
!
Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
Abstract How the brain encodes, recognizes, and memorizes general visual objects is a fundamental question in neuroscience. Here, we investigated the neural processes underlying visual object perception and memory by recording from 3173 single neurons in the human amygdala and hippocampus across four experiments. We employed both passive-viewing and recognition memory tasks involving a diverse range of naturalistic object stimuli. Our findings reveal a region-based feature code for general objects, where neurons exhibit receptive fields in the high-level visual feature space. This code can be validated by independent new stimuli and replicated across all experiments, including fixation-based analyses with large natural scenes. This region code explains the long-standing visual category selectivity, preferentially enhances memory of encoded stimuli, predicts memory performance, encodes image memorability, and exhibits intricate interplay with memory contexts. Together, region-based feature coding provides an important mechanism for visual object processing in the human brain.more » « lessFree, publicly-accessible full text available December 1, 2026
-
Liou, Jyun-you; Smith, Elliot H; Bateman, Lisa M; Bruce, Samuel L; McKhann, Guy M; Goodman, Robert R; Emerson, Ronald G; Schevon, Catherine A; Abbott, LF (, eLife)We developed a neural network model that can account for major elements common to human focal seizures. These include the tonic-clonic transition, slow advance of clinical semiology and corresponding seizure territory expansion, widespread EEG synchronization, and slowing of the ictal rhythm as the seizure approaches termination. These were reproduced by incorporating usage-dependent exhaustion of inhibition in an adaptive neural network that receives global feedback inhibition in addition to local recurrent projections. Our model proposes mechanisms that may underline common EEG seizure onset patterns and status epilepticus, and postulates a role for synaptic plasticity in the emergence of epileptic foci. Complex patterns of seizure activity and bi-stable seizure end-points arise when stochastic noise is included. With the rapid advancement of clinical and experimental tools, we believe that this model can provide a roadmap and potentially an in silico testbed for future explorations of seizure mechanisms and clinical therapies.more » « less
-
Tsitsiklis, Melina; Miller, Jonathan; Qasim, Salman E.; Inman, Cory S.; Gross, Robert E.; Willie, Jon T.; Smith, Elliot H.; Sheth, Sameer A.; Schevon, Catherine A.; Sperling, Michael R.; et al (, Current Biology)
An official website of the United States government
