[HTML][HTML] Local 5-HT signaling bi-directionally regulates the coincidence time window for associative learning
The coincidence between conditioned stimulus (CS) and unconditioned stimulus (US) is
essential for associative learning; however, the mechanism regulating the duration of this …
essential for associative learning; however, the mechanism regulating the duration of this …
[HTML][HTML] Transcriptomic evidence for dense peptidergic networks within forebrains of four widely divergent tetrapods
SJ Smith - Current opinion in neurobiology, 2021 - Elsevier
The primary function common to every neuron is communication with other neurons. Such
cell–cell signaling can take numerous forms, including fast synaptic transmission and slower …
cell–cell signaling can take numerous forms, including fast synaptic transmission and slower …
Thalamocortical contribution to flexible learning in neural systems
MB Wang, MM Halassa - Network neuroscience, 2022 - direct.mit.edu
Animal brains evolved to optimize behavior in dynamic environments, flexibly selecting
actions that maximize future rewards in different contexts. A large body of experimental work …
actions that maximize future rewards in different contexts. A large body of experimental work …
Thalamocortical contribution to solving credit assignment in neural systems
MB Wang, MM Halassa - arXiv preprint arXiv:2104.01474, 2021 - arxiv.org
Animal brains evolved to optimize behavior in dynamically changing environments,
selecting actions that maximize future rewards. A large body of experimental work indicates …
selecting actions that maximize future rewards. A large body of experimental work indicates …
An investigation into the deep learning approach in sentimental analysis using graph-based theories
M Kentour, J Lu - Plos one, 2021 - journals.plos.org
Sentiment analysis is a branch of natural language analytics that aims to correlate what is
expressed which comes normally within unstructured format with what is believed and …
expressed which comes normally within unstructured format with what is believed and …
Evaluating the Effects of Neural Noise in the Multidigraph Learning Rule
G Bressler, S Dackevall - 2023 - diva-portal.org
There exists a knowledge gap in the field of Computational Neuroscience, where many
learning models for neural networks fail to take into account the influence of neural noise …
learning models for neural networks fail to take into account the influence of neural noise …