AIMC Topic: Neural Pathways

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Phenomenological network models: Lessons for epilepsy surgery.

Epilepsia
The current opinion in epilepsy surgery is that successful surgery is about removing pathological cortex in the anatomic sense. This contrasts with recent developments in epilepsy research, where epilepsy is seen as a network disease. Computational m...

Abnormal regional homogeneity as a potential imaging biomarker for adolescent-onset schizophrenia: A resting-state fMRI study and support vector machine analysis.

Schizophrenia research
OBJECTIVE: Structural and functional abnormalities have been reported in the brain of patients with adolescent-onset schizophrenia (AOS). The brain regional functional synchronization in patients with AOS remains unclear.

Familiarity Detection is an Intrinsic Property of Cortical Microcircuits with Bidirectional Synaptic Plasticity.

eNeuro
Humans instantly recognize a previously seen face as "familiar." To deepen our understanding of familiarity-novelty detection, we simulated biologically plausible neural network models of generic cortical microcircuits consisting of spiking neurons w...

Mapping brain structure and function: cellular resolution, global perspective.

Journal of comparative physiology. A, Neuroethology, sensory, neural, and behavioral physiology
A comprehensive understanding of the brain requires analysis, although from a global perspective, with cellular, and even subcellular, resolution. An important step towards this goal involves the establishment of three-dimensional high-resolution bra...

Cracking the barcode of fullerene-like cortical microcolumns.

Neuroscience letters
Artificial neural systems and nervous graph theoretical analysis rely upon the stance that the neural code is embodied in logic circuits, e.g., spatio-temporal sequences of ON/OFF spiking neurons. Nevertheless, this assumption does not fully explain ...

Deep dreaming, aberrant salience and psychosis: Connecting the dots by artificial neural networks.

Schizophrenia research
Why some individuals, when presented with unstructured sensory inputs, develop altered perceptions not based in reality, is not well understood. Machine learning approaches can potentially help us understand how the brain normally interprets sensory ...

The Default Mode Network in Healthy Individuals: A Systematic Review and Meta-Analysis.

Brain connectivity
When the brain is not engaged in goal-directed activities and at rest, there are still measureable patterns of activity. One resting-state network, the default mode network (DMN) is responsible for a self-referential introspective state. There are ma...

Efficient implementation of a real-time estimation system for thalamocortical hidden Parkinsonian properties.

Scientific reports
Real-time estimation of dynamical characteristics of thalamocortical cells, such as dynamics of ion channels and membrane potentials, is useful and essential in the study of the thalamus in Parkinsonian state. However, measuring the dynamical propert...

Exponentially Long Orbits in Hopfield Neural Networks.

Neural computation
We show that Hopfield neural networks with synchronous dynamics and asymmetric weights admit stable orbits that form sequences of maximal length. For [Formula: see text] units, these sequences have length [Formula: see text]; that is, they cover the ...