Terrence J Sejnowski
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Explore the profile of Terrence J Sejnowski including associated specialties, affiliations and a list of published articles.
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284
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11335
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Recent Articles
1.
Rungratsameetaweemana N, Kim R, Chotibut T, Sejnowski T
Proc Natl Acad Sci U S A
. 2025 Jan;
122(3):e2316745122.
PMID: 39819216
Recurrent neural networks (RNNs) based on model neurons that communicate via continuous signals have been widely used to study how cortical neural circuits perform cognitive tasks. Training such networks to...
2.
Hirakis S, Bartol T, Autin L, Amaro R, Sejnowski T
Biophys J
. 2024 Oct;
123(21):3812-3831.
PMID: 39369273
We present the first-ever, fully discrete, stochastic model of triggered cardiac Ca dynamics. Using anatomically accurate subcellular cardiac myocyte geometries, we simulate the molecular players involved in Ca handling using...
3.
Muller L, Churchland P, Sejnowski T
Trends Neurosci
. 2024 Sep;
47(10):788-802.
PMID: 39341729
The capabilities of transformer networks such as ChatGPT and other large language models (LLMs) have captured the world's attention. The crucial computational mechanism underlying their performance relies on transforming a...
4.
Comstock L, Carvalho V, Lainscsek C, Fallah A, Sejnowski T
Brain Sci
. 2024 Sep;
14(9).
PMID: 39335391
Transcranial magnetic stimulation (TMS) has been widely used to study the mechanisms that underlie motor output. Yet, the extent to which TMS acts upon the cortical neurons implicated in volitional...
5.
Carvalho V, Mendes E, Fallah A, Sejnowski T, Comstock L, Lainscsek C
Front Hum Neurosci
. 2024 Jun;
18():1398065.
PMID: 38826617
Speech decoding from non-invasive EEG signals can achieve relatively high accuracy (70-80%) for strictly delimited classification tasks, but for more complex tasks non-invasive speech decoding typically yields a 20-50% classification...
6.
Samavat M, Bartol T, Harris K, Sejnowski T
Neural Comput
. 2024 Apr;
36(5):781-802.
PMID: 38658027
Variation in the strength of synapses can be quantified by measuring the anatomical properties of synapses. Quantifying precision of synaptic plasticity is fundamental to understanding information storage and retrieval in...
7.
Husar A, Ordyan M, Garcia G, Yancey J, Saglam A, Faeder J, et al.
PLoS Comput Biol
. 2024 Apr;
20(4):e1011800.
PMID: 38656994
Biochemical signaling pathways in living cells are often highly organized into spatially segregated volumes, membranes, scaffolds, subcellular compartments, and organelles comprising small numbers of interacting molecules. At this level of...
8.
Bartol T, Ordyan M, Sejnowski T, Rangamani P, Kennedy M
bioRxiv
. 2024 Feb;
PMID: 38352446
Long-term potentiation (LTP) is a biochemical process that underlies learning in excitatory glutamatergic synapses in the Central Nervous System (CNS). The critical early driver of LTP is autophosphorylation of the...
9.
Samavat M, Bartol T, Bromer C, Hubbard D, Hanka D, Kuwajima M, et al.
bioRxiv
. 2024 Jan;
PMID: 38260636
Long-term potentiation (LTP) has become a standard model for investigating synaptic mechanisms of learning and memory. Increasingly, it is of interest to understand how LTP affects the synaptic information storage...
10.
Sameni S, Bartol Jr T, Corey-Bloom J, Sejnowski T
PNAS Nexus
. 2024 Jan;
3(1):pgad443.
PMID: 38222468
One of the early hallmarks of Huntington's disease (HD) is neuronal cell atrophy, especially in the striatum, underlying motor dysfunction in HD. Here using a computer model, we have predicted...