AIMC Topic: Nerve Net

Clear Filters Showing 51 to 60 of 641 articles

Neural dynamics of reversal learning in the prefrontal cortex and recurrent neural networks.

eLife
In probabilistic reversal learning, the choice option yielding reward with higher probability switches at a random trial. To perform optimally in this task, one has to accumulate evidence across trials to infer the probability that a reversal has occ...

Linking dynamic connectivity states to cognitive decline and anatomical changes in Alzheimer's disease.

NeuroImage
Alterations in brain connectivity provide early indications of neurodegenerative diseases like Alzheimer's disease (AD). Here, we present a novel framework that integrates a Hidden Markov Model (HMM) within the architecture of a convolutional neural ...

Brain stimulation preferentially influences long-range projections.

Science advances
Advances in brain stimulation have made it possible to target smaller and smaller regions for electromagnetic stimulation, in the hopes of producing increasingly focal neural effects. However, the brain is extensively interconnected, and the neurons ...

Cooperative actions of interneuron families support the hippocampal spatial code.

Science (New York, N.Y.)
Identifying the computational roles of different neuron families is crucial for understanding neural networks. Most neural diversity is embodied in various types of γ-aminobutyric acid-mediated (GABAergic) interneurons, grouped into four major famili...

Cognitive prediction using regional connectivities and network biomarkers in Alzheimer's disease.

Neuroscience
Achieving a deep understanding of brain mechanisms requires multi-scale perspectives to capture the architecture of complex networks. In this study, we focused on patients with cognitive impairment and constructed individual brain networks from neuro...

Stimulus Contingency and Task Context Encoding within the Anterior Cingulate-Amygdala-Cerebellum Associative Learning Network.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Cerebellum (CB) interactions with forebrain systems contribute to learning cognitive and motor tasks, but the nature of these interactions is unknown. Trace eyeblink conditioning (EBC) is an excellent associative learning paradigm for examining inter...

Increased GM-WM in a prefrontal network and decreased GM in the insula and the precuneus are associated with reappraisal usage and reduced perceived stress: A data fusion approach.

Neuropsychologia
Emotion regulation plays a crucial role in mental health, and difficulties in regulating emotions can contribute to psychological disorders. While reappraisal and suppression are well-studied strategies, the joint contributions of gray matter (GM) an...

Parallel trade-offs in human cognition and neural networks: The dynamic interplay between in-context and in-weight learning.

Proceedings of the National Academy of Sciences of the United States of America
Human learning embodies a striking duality: Sometimes, we can rapidly infer and compose logical rules, benefiting from structured curricula (e.g., in formal education), while other times, we rely on an incremental approach or trial-and-error, learnin...

High-resolution mapping of alcohol-related brain connectivity in adults using 7T fMRI and multivoxel pattern classification.

Psychiatry research. Neuroimaging
BACKGROUND: Emerging evidence suggests that alcohol use disrupts large-scale brain network interactions, particularly within the triple network model-comprising the Salience Network (SN), Default Mode Network (DMN), and Frontoparietal Network (FPN). ...

Dynamic neural network modulation associated with rumination in major depressive disorder: a prospective observational comparative analysis of cognitive behavioral therapy and pharmacotherapy.

Translational psychiatry
Cognitive behavioral therapy (CBT) and pharmacotherapy are primary treatments for major depressive disorder (MDD). However, their differential effects on the neural networks associated with rumination, or repetitive negative thinking, remain poorly u...