AIMC Topic: Nerve Net

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Predictive learning rules generate a cortical-like replay of probabilistic sensory experiences.

eLife
The brain is thought to construct an optimal internal model representing the probabilistic structure of the environment accurately. Evidence suggests that spontaneous brain activity gives such a model by cycling through activity patterns evoked by pr...

Thalamic neural activity and epileptic network analysis using stereoelectroencephalography: a prospective study protocol.

BMJ open
INTRODUCTION: Epilepsy is a prevalent chronic neurological disorder, with approximately one-third of patients experiencing intractable epilepsy, often necessitating surgical intervention. Deep brain stimulation (DBS) of the thalamus has been introduc...

A library of lineage-specific driver lines connects developing neuronal circuits to behavior in the ventral nerve cord.

eLife
Understanding developmental changes in neuronal lineages is crucial to elucidate how they assemble into functional neural networks. Studies investigating nervous system development in model systems have only focused on select regions of the CNS due t...

Decreased spinal inhibition leads to undiversified locomotor patterns.

Biological cybernetics
During walking and running, animals display rich and coordinated motor patterns that are generated and controlled within the central nervous system. Previous computational and experimental results suggest that the balance between excitation and inhib...

Dynamically weighted graph neural network for detection of early mild cognitive impairment.

PloS one
Alzheimer's disease (AD) is a prevalent neurodegenerative disease that primarily affects the elderly population. The early detection of mild cognitive impairment (MCI) holds significant clinical importance for prompt intervention and treatment of AD....

Concept transfer of synaptic diversity from biological to artificial neural networks.

Nature communications
Recent developments in artificial neural networks have drawn inspiration from biological neural networks, leveraging the concept of the artificial neuron to model the learning abilities of biological nerve cells. However, while neuroscience has provi...

Modeling Normal and Abnormal Circuit Development with Recurrent Neural Networks.

Cold Spring Harbor perspectives in biology
Neural development must construct neural circuits that can perform the computations necessary for survival. However, many theoretical models of development do not explicitly address the computational goals of the resulting networks, or computations t...

Hybrid neural networks in the mushroom body drive olfactory preference in .

Science advances
In , olfactory encoding in the mushroom body (MB) involves thousands of Kenyon cells (KCs) processing inputs from hundreds of projection neurons (PNs). Recent data challenge the notion of random PN-to-KC connectivity, revealing preferential connectio...

Decoding dynamic brain networks in Parkinson's disease with temporal attention.

Scientific reports
Detecting brief, clinically meaningful changes in brain activity is crucial for understanding neurological disorders. Conventional imaging analyses often overlook these subtle events due to computational demands. IMPACT (Integrative Multimodal Pipeli...

Contrastive functional connectivity defines neurophysiology-informed symptom dimensions in major depression.

Cell reports. Medicine
Major depressive disorder (MDD) is highly heterogeneous, posing challenges for effective treatment due to complex interactions between clinical symptoms and neurobiological features. To address this, we apply contrastive principal-component analysis ...