AIMC Topic: Neural Pathways

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Inferences on the Watts-Strogatz Model: A Study on Brain Functional Connectivity.

Neuroinformatics
Modelling real-world networks allows investigating the structure and the dynamics of such networks, which led to significant developments in various scientific fields. One of the most used models in these investigations is the Watts-Strogatz, with a ...

Electroencephalography source-space functional connectivity reveals frequency-specific brain network dysfunctions in obsessive-compulsive disorder.

Progress in neuro-psychopharmacology & biological psychiatry
BACKGROUND: Obsessive-compulsive disorder (OCD) is characterized by disruptions in large-scale brain networks. However, the role of high-frequency neural synchrony in these abnormalities remains unclear. Elucidating frequency-specific alterations may...

Heterogeneity of human insular cortex: five principles of functional organization across multiple cognitive domains.

Brain structure & function
The insular cortex serves as a critical hub for human cognition, but how its anatomically distinct subregions coordinate diverse cognitive, emotional, and social functions remains unclear. Using the Human Connectome Project's multi-task fMRI dataset ...

Beyond tractography in brain connectivity mapping with dMRI morphometry and functional networks.

Brain structure & function
Traditional brain connectivity studies have focused mainly on structural connectivity, often relying on tractography with diffusion MRI (dMRI) to reconstruct white matter pathways. In parallel, studies of functional connectivity have examined correla...

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...

Deep adversarial learning identifies ADHD-specific associations between apoptotic genes and white matter microstructure in frontal-striatum-cerebellum circuit.

Translational psychiatry
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by genetic predisposition and alterations in brain structural connectivity. While existing studies have established associations between genetic variants a...

Assessing changes in whole-brain structural connectivity in the unilateral 6-hydroxydopamine rat model of Parkinson's disease using diffusion imaging and tractography.

Journal of neural engineering
Parkinson's disease (PD) is a multifactorial, progressive neurodegenerative disease that has a profound impact on those it afflicts. Its hallmark pathophysiology is characterized by degeneration of dopaminergic (DA) neurons in the midbrain which trig...

Brain-wide input-output analysis of tuberal nucleus somatostatin neurons reveals hierarchical circuits for orchestrating feeding behavior.

Nature communications
Feeding is an innate behavior critical for survival but is also influenced by many non-nutritional factors such as emotion, social context and environmental conditions. Recently, tuberal nucleus somatostatin (SST) neurons have been identified as a ke...

BrainTract: segmentation of white matter fiber tractography and analysis of structural connectivity using hybrid convolutional neural network.

Neuroscience
Tractography uses diffusion Magnetic Resonance Imaging (dMRI) to noninvasively reconstruct brain white matter (WM) tracts, with Convolutional Neural Network (CNNs) like U-Net significantly advancing accuracy in medical image segmentation. This work p...