AIMC Topic: Neural Pathways

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Comparative analysis of functional network dynamics in high and low alcohol preference mice.

Experimental neurology
Individual variability preference is a typical characteristic of alcohol drinking behaviors, with a higher risk for the development of alcohol use disorders (AUDs) in high alcohol preference (HP) populations. Here, we created a map of alcohol-related...

Sparse connectivity enables efficient information processing in cortex-like artificial neural networks.

Frontiers in neural circuits
Neurons in cortical networks are very sparsely connected; even neurons whose axons and dendrites overlap are highly unlikely to form a synaptic connection. What is the relevance of such sparse connectivity for a network's function? Surprisingly, it h...

Neuroevolution insights into biological neural computation.

Science (New York, N.Y.)
This article reviews existing work and future opportunities in neuroevolution, an area of machine learning in which evolutionary optimization methods such as genetic algorithms are used to construct neural networks to achieve desired behavior. The ar...

Differentiating Functional Connectivity Patterns in ADHD and Autism Among the Young People: A Machine Learning Solution.

Journal of attention disorders
OBJECTIVE: ADHD and autism are complex and frequently co-occurring neurodevelopmental conditions with shared etiological and pathophysiological elements. In this paper, we attempt to differentiate these conditions among the young people in terms of i...

Classification of Irritable Bowel Syndrome Using Brain Functional Connectivity Strength and Machine Learning.

Neurogastroenterology and motility
BACKGROUND: Irritable Bowel Syndrome (IBS) is a prevalent condition characterized by dysregulated brain-gut interactions. Despite its widespread impact, the brain mechanism of IBS remains incompletely understood, and there is a lack of objective diag...

Identifying ADHD-Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network.

Neural plasticity
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that is characterized by inattention, hyperactivity, and impulsivity. The neural mechanisms underlying ADHD remain inadequately understood, and current approaches...

A Stepwise Multivariate Granger Causality Method for Constructing Hierarchical Directed Brain Functional Network.

IEEE transactions on neural networks and learning systems
The directed brain functional network construction gives us the new insights into the relationships between brain regions from the causality point of view. The Granger causality analysis is one of the powerful methods to model the directed network. T...

TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance.

Medical image analysis
We propose a geometric deep-learning-based framework, TractGeoNet, for performing regression using diffusion magnetic resonance imaging (dMRI) tractography and associated pointwise tissue microstructure measurements. By employing a point cloud repres...

Mode combinability: Exploring convex combinations of permutation aligned models.

Neural networks : the official journal of the International Neural Network Society
We explore element-wise convex combinations of two permutation-aligned neural network parameter vectors Θ and Θ of size d. We conduct extensive experiments by examining various distributions of such model combinations parametrized by elements of the ...

A deep learning approach for mental health quality prediction using functional network connectivity and assessment data.

Brain imaging and behavior
While one can characterize mental health using questionnaires, such tools do not provide direct insight into the underlying biology. By linking approaches that visualize brain activity to questionnaires in the context of individualized prediction, we...