When Maturation is Not Linear: Brain Oscillatory Activity in the Process of Aging as Measured by Electrophysiology.

Changes in brain oscillatory activity are commonly used as biomarkers both in cognitive neuroscience and in neuropsychiatric conditions. However, little is known about how its profile changes across maturation. Here we use regression models to characterize magnetoencephalography power changes within classical frequency bands in a sample of 792 healthy participants, covering the range 13 to 80 years old. Our findings unveil complex, non-linear power trajectories that defy the traditional linear paradigm, with notable cortical region variations. Interestingly, slow wave activity increases correlate with improved cognitive performance throughout life and larger gray matter volume in the elderly. Conversely, fast wave activity diminishes in adulthood. Elevated low-frequency activity during aging, traditionally seen as compensatory, may also signify neural deterioration. This dual interpretation, highlighted by our study, reveals the intricate dynamics between brain oscillations, cognitive performance, and aging. It advances our understanding of neurodevelopment and aging by emphasizing the regional specificity and complexity of brain rhythm changes, with implications for cognitive and structural integrity.

Trying to forget alcohol: Brain mechanisms underlying memory suppression in young binge drinkers.

People are able to voluntarily suppress unwanted thoughts or memories, a phenomenon known as suppression-induced forgetting or memory suppression. Despite harmful alcohol use, such as binge drinking, has been linked to impaired inhibitory control (IC) and augmented alcohol-cue reactivity, no study to date has assessed memory inhibition abilities towards alcohol-related cues in binge drinkers (BDs). Thus, the present preregistered study aimed to evaluate the behavioral and neurofunctional mechanisms associated with memory inhibition, specifically those related to the suppression of alcohol-related memories, in young BDs. For this purpose, electroencephalographic activity was recorded in eighty-two college students aged between 18 and 24 years old from the University of Minho (50% females; 40 non/low-drinkers [N/LDS] and 42 BDs) while they performed the Think/No-Think Alcohol task. Brain functional connectivity (FC) was calculated using the phase locking value and, subsequently, a dynamic seed-based analysis was conducted to explore the FC patterns between IC and memory networks. Comparatively to N/LDs, BDs exhibited decreased alpha-band FC between the anterior cingulate cortex and the left fusiform gyrus during attempts to suppress non-alcohol memories, accompanied by unsuccessful forgetting of those memories. Conversely, BDs displayed augmented gamma-band FC between the IC network and memory regions -i.e., hippocampus, parahippocampus and fusiform gyrus- during suppression of alcohol-related memories. Inhibitory abnormalities in BDs may lead to hypoconnectivity between IC and memory networks and deficient suppression of non-alcohol-related memories. However, while suppressing highly salient and reward-predicting stimuli, such as alcohol-related memories, BDs display a hyperconnectivity pattern between IC and memory networks, likely due to their augmented attention towards intrusive alcoholic memories and the attempts to compensate for potential underlying IC deficits. These findings hold important implications for alcohol research and treatment, as they open up new avenues for reducing alcohol use by shifting the focus to empowering suppression/control over alcohol-related memories. CLINICAL TRIAL REGISTRATION: [http://www.ClinicalTrials.gov], identifier [NCT05237414].

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. In this work we consider typically deductive logico-probabilistically valid inferences and aim to verify or refute their electrophysiological functional connectivity differences from invalid inferences with the same content (same relational variables, same stimuli, same relevant and salient features). We recorded the brain electrophysiological activity of 20 participants (age = 20.35 ± 3.23) by means of an MEG system during two consecutive reasoning tasks: a search task (invalid condition) without any specific deductive rules to follow, and a logically valid deductive task (valid condition) with explicit deductive rules as instructions. We calculated the functional connectivity (FC) for each condition and conducted a seed-based analysis in a set of cortical regions of interest. Finally, we used a cluster-based permutation test to compare the differences between logically valid and invalid conditions in terms of FC. As a first novel result we found higher FC for valid condition in beta band between regions of interest and left prefrontal, temporal, parietal, and cingulate structures. FC analysis allows a second novel result which is the definition of a propositional network with operculo-cingular, parietal and medial nodes, specifically including disputed medial deductive "core" areas. The experiment discloses measurable cortical processes which do not depend on content but on truth-functional propositional operators. These experimental novelties may contribute to understand the cortical bases of deductive processes.

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. Methods: We performed a two-year longitudinal protocol with two stages. In the first stage, before the onset of HD, we recorded brain electrophysiological activity from a sample of 67 adolescents (mean age = 14.6 ± 0.7) during an IC task. Alcohol consumption was measured using the AUDIT test and a semi-structured interview. Two years later, in the second stage, 32 of the 67 participants (mean age 16.7 ± 0.7) completed a similar protocol. As for the analysis in the first stage, the source-space FC matrix was calculated, and then, using a cluster-based permutation test (CBPT) based on Spearman's correlation, we calculated the correlation between the FC of each cortical source and the number of standard alcohol units consumed two years later. For the analysis of longitudinal change, we followed a similar approach. We calculated the symmetrized percentage change (SPC) between FC at both stages and performed a CBPT analysis, analyzing the correlation between FC change and the level of alcohol consumed in a regular session. Results: The results revealed an association between higher beta-band FC in the prefrontal and temporal regions and higher consumption years later. Longitudinal results showed that greater future alcohol consumption was associated with an exacerbated reduction in the FC of the same areas. Discussion: These results underline the existence of several brain functional differences prior to alcohol misuse and their 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. In a sample of 67 alcohol-naïve adolescents (age = 14.5 ± 0.9), we measured resting-state activity using MEG. Additionally, we evaluated their neuropsychological traits using self-report ecological scales (BIS-11, SSS-V, BDEFS, BRIEF-SR and DEX). In a second evaluation, 2 years later, we measured participant's alcohol consumption, sub-dividing the original sample in two groups: future binge drinkers (22 individuals, age 14.6 ± 0.8; eight females) and future light/no drinkers (17 individuals, age 14.5 ± 0.8; eight females). Then, we searched for differences predating alcohol BD intake. We found abnormalities in MEG resting state, in a form of gamma band hyperconnectivity, in those adolescents who transitioned into BD years later. Furthermore, they showed higher impulsivity, dysexecutive behaviours and sensation seeking, positively correlated with functional connectivity (FC). Sensation seeking and impulsivity mainly predicted BD severity in the future, while the relationship between dysexecutive trait and FC with future BD was mediated by sensation seeking. These findings shed light to electrophysiological and neuropsychological traits of vulnerability towards alcohol consumption. We hypothesise that these differences may rely on divergent neurobiological development of inhibitory neurotransmission pathways and executive prefrontal circuits.

Alpha-band power increases in posterior brain regions in attention deficit hyperactivity disorder after digital cognitive stimulation treatment: randomized controlled study.

The changes triggered by pharmacological treatments in resting-state alpha-band (8-14 Hz) oscillations have been widely studied in attention deficit hyperactivity disorder. However, to date, there has been no evidence regarding the possible changes in cognitive stimulation treatments on these oscillations. This paper sets out to verify whether cognitive stimulation treatments based on progressive increases in cognitive load can be effective in triggering changes in alpha-band power in attention deficit hyperactivity disorder. With this objective, we compared a cognitive stimulation treatment (n = 12) to a placebo treatment (n = 14) for 12 weeks (36 sessions of 15 min) in child patients (8-11 years old) with attention deficit hyperactivity disorder. Two magnetoencephalographic recordings were acquired for all participants. In order to extract the areas with changes in alpha power between both magnetoencephalographic recordings, the differences in the power ratio (pre/post-condition) were calculated using an analysis of covariance test adjusted for the age variable. The results show an increase in the post-treatment alpha power in the experimental group versus the placebo group (P < 0.01) in posterior regions. In addition, these changes were related to measures of attention, working memory and flexibility. The results seem to indicate that cognitive stimulation treatment based on progressive increases in cognitive load triggers alpha-band power changes in children diagnosed with attention deficit hyperactivity disorder in the direction of their peers without this disorder.

"It's a beer!": Brain functional hyperconnectivity during processing of alcohol-related images in young binge drinkers.

Alcohol attentional bias has been pointed as a major marker of alcohol misuse. Recent evidence has revealed that brain functional connectivity (FC) may be a valuable index of the brain networks' integrity in young binge drinkers (BDs). However, there is no study to date examining the FC networks linked to the processing of alcohol-related images in this population. The present study aimed to explore the FC signatures underlying alcohol attention bias in young BDs. Thus, electroencephalographic (EEG) activity was recorded in 54 college students (55.5% females; 27 non/low-drinkers and 27 BDs) while performing a visual alcohol cue-reactivity task. We evaluated whole-brain FC profiles during the processing of alcoholic and non-alcoholic cues, as well as their potential relationship with craving and severity of alcohol use. Results showed that, at the behavioural level, BDs rated alcohol-related images as more pleasant/attractive than non/low-drinkers. Furthermore, at the electrophysiological level, BDs exhibited increased beta-band FC-particularly in the fronto-parieto-occipital network-when processing alcoholic cues. Conversely, they displayed reduced theta-band FC relatively to non/low-drinkers for non-alcoholic images. These hyper-/hypo-connectivity patterns were associated with higher alcohol craving levels. Findings are congruent with previous neurofunctional studies reporting an attentional bias towards alcohol-related information in BDs. These results may have important clinical implications as this neural reactivity to alcoholic cues may contribute to the maintenance and/or escalation of the drinking pattern. Finally, the present study constitutes the first evidence showing that FC networks may be a sensitive indicator to alcohol attentional bias in BDs.

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. The present study aimed to investigate the influence of the motivational value of alcohol-related stimuli on brain functional networks devoted to response inhibition in young BDs. Sixty eight BDs and 78 control participants performed a beverage Go/NoGo task while undergoing electrophysiological recording. Whole cortical brain functional connectivity (FC) was evaluated during successful response inhibition trials (NoGo). BDs exhibited fast-beta and theta hyperconnectivity in regions related to cognitive control. These responses were modulated differently depending on the motivational content of the stimuli. The increased salience of alcohol-related stimuli may lead to overactivation of the affective-automatic system in BDs, and compensatory neural resources of the reflective system will thus be required during response inhibition. In BDs, inhibition of the response to alcohol stimuli may require higher theta FC to facilitate integration of information related to the task goal (withholding a response), while during inhibition of the response to no-alcoholic stimuli, higher fast-beta FC would allow to apply top-down inhibitory control of the information related to the prepotent response.

Electrophysiological Brain Changes Associated With Cognitive Improvement in a Pediatric Attention Deficit Hyperactivity Disorder Digital Artificial Intelligence-Driven Intervention: Randomized Controlled Trial.

BACKGROUND: Cognitive stimulation therapy appears to show promising results in the rehabilitation of impaired cognitive processes in attention deficit hyperactivity disorder. OBJECTIVE: Encouraged by this evidence and the ever-increasing use of technology and artificial intelligence for therapeutic purposes, we examined whether cognitive stimulation therapy implemented on a mobile device and controlled by an artificial intelligence engine can be effective in the neurocognitive rehabilitation of these patients. METHODS: In this randomized study, 29 child participants (25 males) underwent training with a smart, digital, cognitive stimulation program (KAD_SCL_01) or with 3 commercial video games for 12 weeks, 3 days a week, 15 minutes a day. Participants completed a neuropsychological assessment and a preintervention and postintervention magnetoencephalography study in a resting state with their eyes closed. In addition, information on clinical symptoms was collected from the child´s legal guardians. RESULTS: In line with our main hypothesis, we found evidence that smart, digital, cognitive treatment results in improvements in inhibitory control performance. Improvements were also found in visuospatial working memory performance and in the cognitive flexibility, working memory, and behavior and general executive functioning behavioral clinical indexes in this group of participants. Finally, the improvements found in inhibitory control were related to increases in alpha-band power in all participants in the posterior regions, including 2 default mode network regions of the interest: the bilateral precuneus and the bilateral posterior cingulate cortex. However, only the participants who underwent cognitive stimulation intervention (KAD_SCL_01) showed a significant increase in this relationship. CONCLUSIONS: The results seem to indicate that smart, digital treatment can be effective in the inhibitory control and visuospatial working memory rehabilitation in patients with attention deficit hyperactivity disorder. Furthermore, the relation of the inhibitory control with alpha-band power changes could mean that these changes are a product of plasticity mechanisms or changes in the neuromodulatory dynamics. TRIAL REGISTRATION: ISRCTN Registry ISRCTN71041318; https://www.isrctn.com/ISRCTN71041318.

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 20.35 years were registered with MEG and placed into a two conditions paradigm (100 trials for each condition) which each presented the exact same relational complexity (same variables and content) but had distinct logical complexity. Both conditions show the same electromagnetic components (P3, N4) in the early temporal window (250-525 ms) and P6 in the late temporal window (500-775 ms). The significant activity in both valid and invalid conditions is found in sensors from medial prefrontal regions, probably corresponding to the ACC or to the medial prefrontal cortex. The amplitude and intensity of valid deductions is significantly lower in both temporal windows (p = 0.0003). The reaction time was 54.37% slower in the valid condition. Validity leaves a minimal but measurable hypoactive electrical trait in brain processing. The minor electrical demand is attributable to the recursive and automatable character of valid deductions, suggesting a physical indicator of computational deductive properties. It is hypothesized that all valid deductions are recursive and hypoactive.

nMNSD-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. The mathematical framework of the structure is introduced, together with the "trapezoid method," that is a reduced method to analyze the recognition mechanism operated by the nMNSD in response to a specific input parallel spike train. We apply the nMNSD to a classification problem previously faced with the classical MNSD from the same authors, showing the new possibilities the nMNSD opens, with associated improvement in classification performances. Finally, we benchmark the nMNSD on the classification of static inputs (MNIST database) obtaining state-of-the-art accuracies together with advantageous aspects in terms of time- and energy-efficiency if compared to similar classification methods.

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. METHODS: Sixty-seven participant's inhibitory functional networks, and dysexecutive/impulsivity traits were measured by means of inhibitory task (go/no-go) and questionnaires battery. After a follow-up period of two years, we evaluated their alcohol consumption habits, sub-dividing them in two groups according to their alcohol intake patterns: future binge drinkers (fBD): n = 22; future Light/non-drinkers (fLD): n = 17. We evaluated whole-brain and seed-based functional connectivity profiles, as well as its correlation with impulsive and dysexecutive behaviours, searching for early abnormalities before consumption onset. RESULTS: For the first time, abnormalities in MEG functional networks and higher dysexecutive and impulsivity profiles were detected in alcohol-naïve adolescents who two years later became binge drinkers. Concretely, fBD exhibit a distinctive pattern of beta band hyperconnectivity among crucial regions of inhibitory control networks, positively correlated with behavioral traits and future alcohol intake rate. CONCLUSIONS: These findings strongly support the idea of early neurobiological vulnerabilities for substances consumption initiation, with inhibitory functional networks' abnormalities as a relevant neurophysiological marker of subjects at risk- we hypothesize this profile is due to neurodevelopmental and neurobiological differences involving cognitive control networks and neurotransmission pathways.

A Neuro-Inspired System for Online Learning and Recognition of Parallel Spike Trains, Based on Spike Latency, and Heterosynaptic STDP.

Humans perform remarkably well in many cognitive tasks including pattern recognition. However, the neuronal mechanisms underlying this process are not well understood. Nevertheless, artificial neural networks, inspired in brain circuits, have been designed and used to tackle spatio-temporal pattern recognition tasks. In this paper we present a multi-neuronal spike pattern detection structure able to autonomously implement online learning and recognition of parallel spike sequences (i.e., sequences of pulses belonging to different neurons/neural ensembles). The operating principle of this structure is based on two spiking/synaptic neurocomputational characteristics: spike latency, which enables neurons to fire spikes with a certain delay and heterosynaptic plasticity, which allows the own regulation of synaptic weights. From the perspective of the information representation, the structure allows mapping a spatio-temporal stimulus into a multi-dimensional, temporal, feature space. In this space, the parameter coordinate and the time at which a neuron fires represent one specific feature. In this sense, each feature can be considered to span a single temporal axis. We applied our proposed scheme to experimental data obtained from a motor-inhibitory cognitive task. The results show that out method exhibits similar performance compared with other classification methods, indicating the effectiveness of our approach. In addition, its simplicity and low computational cost suggest a large scale implementation for real time recognition applications in several areas, such as brain computer interface, personal biometrics authentication, or early detection of diseases.

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. This makes the ANN an efficient computational core for brain-machine systems. However, despite significant achievements of artificial intelligence in recognition and classification of well-reproducible patterns of neural activity, the use of ANNs for recognition and classification of patterns in neural networks still requires additional attention, especially in ambiguous situations. According to this, in this research, we demonstrate the efficiency of application of the ANN for classification of human MEG trials corresponding to the perception of bistable visual stimuli with different degrees of ambiguity. We show that along with classification of brain states associated with multistable image interpretations, in the case of significant ambiguity, the ANN can detect an uncertain state when the observer doubts about the image interpretation. With the obtained results, we describe the possible application of ANNs for detection of bistable brain activity associated with difficulties in the decision-making process.