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Cerebral Cortex

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Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders.

NeuroImage
Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these models are applied to discriminating clinical groups such as schizophrenic patients from healthy co...

Classification of first-episode psychosis in a large cohort of patients using support vector machine and multiple kernel learning techniques.

NeuroImage
First episode psychosis (FEP) patients are of particular interest for neuroimaging investigations because of the absence of confounding effects due to medications and chronicity. Nonetheless, imaging data are prone to heterogeneity because for exampl...

Early Childhood Behavioral Inhibition Predicts Cortical Thickness in Adulthood.

Journal of the American Academy of Child and Adolescent Psychiatry
OBJECTIVE: Behavioral inhibition (BI) during early childhood predicts risk for anxiety disorders and altered cognitive control in adolescence. Although BI has been linked to variation in brain function through adulthood, few studies have examined rel...

Reduction of Trial-to-Trial Perceptual Variability by Intracortical Tonic Inhibition.

Neural computation
Variability is a prominent characteristic of cognitive brain function. For instance, different trials of presentation of the same stimulus yield higher variability in its perception: subjects sometimes fail in perceiving the same stimulus. Perceptual...

Coherent and intermittent ensemble oscillations emerge from networks of irregular spiking neurons.

Journal of neurophysiology
Local field potential (LFP) recordings from spatially distant cortical circuits reveal episodes of coherent gamma oscillations that are intermittent, and of variable peak frequency and duration. Concurrently, single neuron spiking remains largely irr...

Long-range recruitment of Martinotti cells causes surround suppression and promotes saliency in an attractor network model.

Frontiers in neural circuits
Although the importance of long-range connections for cortical information processing has been acknowledged for a long time, most studies focused on the long-range interactions between excitatory cortical neurons. Inhibitory interneurons play an impo...

Enhancement of Spike-Timing-Dependent Plasticity in Spiking Neural Systems with Noise.

International journal of neural systems
Synaptic plasticity is widely recognized to support adaptable information processing in the brain. Spike-timing-dependent plasticity, one subtype of plasticity, can lead to synchronous spike propagation with temporal spiking coding information. Recen...

Firing rate dynamics in recurrent spiking neural networks with intrinsic and network heterogeneity.

Journal of computational neuroscience
Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studi...

Impact of sub and supra-threshold adaptation currents in networks of spiking neurons.

Journal of computational neuroscience
Neuronal adaptation is the intrinsic capacity of the brain to change, by various mechanisms, its dynamical responses as a function of the context. Such a phenomena, widely observed in vivo and in vitro, is known to be crucial in homeostatic regulatio...

Corticostriatal response selection in sentence production: Insights from neural network simulation with reservoir computing.

Brain and language
Language production requires selection of the appropriate sentence structure to accommodate the communication goal of the speaker - the transmission of a particular meaning. Here we consider event meanings, in terms of predicates and thematic roles, ...