AIMC Topic: Neural Pathways

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Spatiotemporal discrimination in attractor networks with short-term synaptic plasticity.

Journal of computational neuroscience
We demonstrate that a randomly connected attractor network with dynamic synapses can discriminate between similar sequences containing multiple stimuli suggesting such networks provide a general basis for neural computations in the brain. The network...

A Computational Perspective of the Role of the Thalamus in Cognition.

Neural computation
The thalamus has traditionally been considered as only a relay source of cortical inputs, with hierarchically organized cortical circuits serially transforming thalamic signals to cognitively relevant representations. Given the absence of local excit...

A self-organized recurrent neural network for estimating the effective connectivity and its application to EEG data.

Computers in biology and medicine
OBJECTIVE: Effective connectivity is an important notion in neuroscience research, useful for detecting the interactions between regions of the brain.

Membrane potential resonance in non-oscillatory neurons interacts with synaptic connectivity to produce network oscillations.

Journal of computational neuroscience
Several neuron types have been shown to exhibit (subthreshold) membrane potential resonance (MPR), defined as the occurrence of a peak in their voltage amplitude response to oscillatory input currents at a preferred (resonant) frequency. MPR has been...

Resting-state anticorrelated networks in Schizophrenia.

Psychiatry research. Neuroimaging
Converging evidences from different lines of research suggest abnormalities in functional brain connectivity in schizophrenia. While positively correlated brain networks have been well researched, anticorrelated functional connectivity remains under ...

The Complex Behaviour of a Simple Neural Oscillator Model in the Human Cortex.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The brain is a complex organ responsible for memory storage and reasoning; however, the mechanisms underlying these processes remain unknown. This paper forms a contribution to a lot of theoretical studies devoted to regular or chaotic oscillations o...

Machine learning multivariate pattern analysis predicts classification of posttraumatic stress disorder and its dissociative subtype: a multimodal neuroimaging approach.

Psychological medicine
BACKGROUND: The field of psychiatry would benefit significantly from developing objective biomarkers that could facilitate the early identification of heterogeneous subtypes of illness. Critically, although machine learning pattern recognition method...

Image categorization from functional magnetic resonance imaging using functional connectivity.

Journal of neuroscience methods
BACKGROUND: Previous studies have attempted to infer the category of objects in a stimulus image from functional magnetic resonance imaging (fMRI) data recoded during image-viewing. Most studies focus on extracting activity patterns within a given re...

Machine learning in major depression: From classification to treatment outcome prediction.

CNS neuroscience & therapeutics
AIMS: Major depression disorder (MDD) is the single greatest cause of disability and morbidity, and affects about 10% of the population worldwide. Currently, there are no clinically useful diagnostic biomarkers that are able to confirm a diagnosis of...

Deep learning applied to whole-brain connectome to determine seizure control after epilepsy surgery.

Epilepsia
OBJECTIVE: We evaluated whether deep learning applied to whole-brain presurgical structural connectomes could be used to predict postoperative seizure outcome more accurately than inference from clinical variables in patients with mesial temporal lob...