Clustering Electrophysiological Predisposition to Binge Drinking: An Unsupervised Machine Learning Analysis.

Background: The demand for fresh strategies to analyze intricate multidimensional data in neuroscience is increasingly evident. One of the most complex events during our neurodevelopment is adolescence, where our nervous system suffers constant changes, not only in neuroanatomical traits but also in neurophysiological components. One of the most impactful factors we deal with during this time is our environment, especially when encountering external factors such as social behaviors or substance consumption.

Electrophysiological connectivity of logical deduction: Early cortical MEG study.

Complex human reasoning involves minimal abilities to extract conclusions implied in the available information. These abilities are considered "deductive" because they exemplify certain abstract relations among propositions or probabilities called deductive arguments. However, the electrophysiological dynamics which supports such complex cognitive processes has not been addressed yet.

Longitudinal change of inhibitory control functional connectivity associated with the development of heavy alcohol drinking.

Introduction: Heavy drinking (HD) prevalent pattern of alcohol consumption among adolescents, particularly concerning because of their critical vulnerability to the neurotoxic effects of ethanol. Adolescent neurodevelopment is characterized by critical neurobiological changes of the prefrontal, temporal and parietal regions, important for the development of executive control processes, such as inhibitory control (IC). In the present Magnetoencephalography (MEG) study, we aimed to describe the relationship between electrophysiological Functional Connectivity (FC) during an IC task and HD development, as well as its impact on functional neuromaturation.

Electrophysiological resting-state hyperconnectivity and poorer behavioural regulation as predisposing profiles of adolescent binge drinking.

Adolescent Binge Drinking (BD) has become an increasing health and social concern, with detrimental consequences for brain development and functional integrity. However, research on neurophysiological and neuropsychological traits predisposing to BD are limited at this time. In this work, we conducted a 2-year longitudinal magnetoencephalography (MEG) study over a cohort of initially alcohol-naïve adolescents with the purpose of exploring anomalies in resting-state electrophysiological networks, impulsivity, sensation-seeking, and dysexecutive behaviour able to predict future BD patterns.

Alcohol-related stimuli modulate functional connectivity during response inhibition in young binge drinkers.

Binge drinking is a pattern of intermittent excessive alcohol consumption that is highly prevalent in young people. Neurocognitive dual-process models have described substance abuse and adolescence risk behaviours as the result of an imbalance between an overactivated affective-automatic system (related to motivational processing) and damaged and/or immature reflective system (related to cognitive control abilities). Previous studies have evaluated the reflective system of binge drinkers (BDs) through neutral response inhibition tasks and have reported anomalies in theta (4-8 Hz) and beta (12-30 Hz) bands.

Brain electrical traits of logical validity.

Neuroscience has studied deductive reasoning over the last 20 years under the assumption that deductive inferences are not only de jure but also de facto distinct from other forms of inference. The objective of this research is to verify if logically valid deductions leave any cerebral electrical trait that is distinct from the trait left by non-valid deductions. 23 subjects with an average age of 20.

-A Spiking Neuron-Based Classifier That Combines Weight-Adjustment and Delay-Shift.

The recent "multi-neuronal spike sequence detector" (MNSD) architecture integrates the weight- and delay-adjustment methods by combining heterosynaptic plasticity with the neurocomputational feature spike latency, representing a new opportunity to understand the mechanisms underlying biological learning. Unfortunately, the range of problems to which this topology can be applied is limited because of the low cardinality of the parallel spike trains that it can process, and the lack of a visualization mechanism to understand its internal operation. We present here the nMNSD structure, which is a generalization of the MNSD to any number of inputs.

Abnormal organization of inhibitory control functional networks in future binge drinkers.

Background And Aims: Adolescent Binge drinking has become an increasing health and social concern, which cause several detrimental consequences for brain integrity. However, research on neurophysiological traits of vulnerability for binge drinking predisposition is limited at this time. In this work, we conducted a two-year longitudinal study with magnetoencephalography (MEG) over a cohort of initially alcohol-naive adolescents with the purpose of characterize inhibitory cortical networks' anomalies prior to alcohol consumption onset in those youths who will transit into binge drinkers years later.

Artificial neural network detects human uncertainty.

Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allow the recognition of specific forms of brain activity from multichannel EEG or MEG data.