Distinct Patterns Of Brain Activity Research Articles

Differential Brain Activation for Four Emotions in VR-2D and VR-3D Modes.

Similar to traditional imaging, virtual reality (VR) imagery encompasses nonstereoscopic (VR-2D) and stereoscopic (VR-3D) modes. Currently, Russell's emotional model has been extensively studied in traditional 2D and VR-3D modes, but there is limited comparative research between VR-2D and VR-3D modes. In this study, we investigate whether Russell's emotional model exhibits stronger brain activation states in VR-3D mode compared to VR-2D mode. By designing an experiment covering four emotional categories (high arousal-high pleasure (HAHV), high arousal-low pleasure (HALV), low arousal-low pleasure (LALV), and low arousal-high pleasure (LAHV)), EEG signals were collected from 30 healthy undergraduate and graduate students while watching videos in both VR modes. Initially, power spectral density (PSD) computations revealed distinct brain activation patterns in different emotional states across the two modes, with VR-3D videos inducing significantly higher brainwave energy, primarily in the frontal, temporal, and occipital regions. Subsequently, Differential entropy (DE) feature sets, selected via a dual ten-fold cross-validation Support Vector Machine (SVM) classifier, demonstrate satisfactory classification accuracy, particularly superior in the VR-3D mode. The paper subsequently presents a deep learning-based EEG emotion recognition framework, adeptly utilizing the frequency, spatial, and temporal information of EEG data to improve recognition accuracy. The contribution of each individual feature to the prediction probabilities is discussed through machine-learning interpretability based on Shapley values. The study reveals notable differences in brain activation states for identical emotions between the two modes, with VR-3D mode showing more pronounced activation.

Mapping the unique neural engagement in deaf individuals during picture, word, and sign language processing: fMRI study.

Employing functional magnetic resonance imaging (fMRI) techniques, we conducted a comprehensive analysis of neural responses during sign language, picture, and word processing tasks in a cohort of 35 deaf participants and contrasted these responses with those of 35 hearing counterparts. Our voxel-based analysis unveiled distinct patterns of brain activation during language processing tasks. Deaf individuals exhibited robust bilateral activation in the superior temporal regions during sign language processing, signifying the profound neural adaptations associated with sign comprehension. Similarly, during picture processing, the deaf cohort displayed activation in the right angular, right calcarine, right middle temporal, and left angular gyrus regions, elucidating the neural dynamics engaged in visual processing tasks. Intriguingly, during word processing, the deaf group engaged the right insula and right fusiform gyrus, suggesting compensatory mechanisms at play during linguistic tasks. Notably, the control group failed to manifest additional or distinctive regions in any of the tasks when compared to the deaf cohort, underscoring the unique neural signatures within the deaf population. Multivariate Pattern Analysis (MVPA) of functional connectivity provided a more nuanced perspective on connectivity patterns across tasks. Deaf participants exhibited significant activation in a myriad of brain regions, including bilateral planum temporale (PT), postcentral gyrus, insula, and inferior frontal regions, among others. These findings underscore the intricate neural adaptations in response to auditory deprivation. Seed-based connectivity analysis, utilizing the PT as a seed region, revealed unique connectivity pattern across tasks. These connectivity dynamics provide valuable insights into the neural interplay associated with cross-modal plasticity.

Mechanisms of Action Anticipation in Table Tennis Players: A Multivoxel Pattern Analysis Study

An exceptional ability to accurately anticipate an opponent’s action is paramount for competitive athletes and highlights their experiential mastery. Despite conventional associations of action observation with specific brain regions, neuroimaging discrepancies persist. To explore the brain regions and neural mechanisms undergirding action anticipation, we compared distinct brain activation patterns involved in table tennis serve anticipation of expert table tennis athletes vs. non-experts by using both univariate analysis and multivoxel pattern analysis (MVPA). We collected functional magnetic resonance imaging data from 29 table tennis experts and 34 non-experts as they pressed a button to predict the trajectory of a ball in a table tennis serve video truncated at the moment of racket-ball contact vs. pressing any button while viewing a static image of the first video frame. MVPA was applied to assess whether it could accurately differentiate experts from non-experts. MVPA results indicated moderate accuracy (90.48%) for differentiating experts from non-experts. Brain regions contributing most to the differentiation included the left cerebellum, the vermis, the right middle temporal pole, the inferior parietal cortex, the bilateral paracentral lobule, and the left supplementary motor area. The findings suggest that brain regions associated with cognitive conflict monitoring and motor cognition contribute to the action anticipation ability of expert table tennis players.

The fear of COVID-19 contagion: an exploratory EEG-fMRI study

Pandemics have the potential to change how people behave and feel. The COVID-19 pandemic is no exception; thus, it may serve as a "challenging context" for understanding how pandemics affect people's minds. In this study, we used high-density electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to examine the neural correlates of fear of contagion during the most critical moments of COVID-19 in Italy (i.e., October 2020–May 2021). To do that, we stimulated participants (N = 17; nine females) with artificial-intelligence-generated faces of people presented as healthy, recovered from COVID-19, or infected by SARS-CoV-2. The fMRI results documented a modulation of large bilateral fronto-temporo-parietal functional brain networks. Critically, we found selective recruitment of cortical (e.g., frontal lobes) and subcortical fear-related structures (e.g., amygdala and putamen) of the so-called social brain network when participants observed COVID-19-related faces. Consistently, EEG results showed distinct patterns of brain activity selectively associated with infected and recovered faces (e.g., delta and gamma rhythm). Together, these results highlight how pandemic contexts may reverberate in the human brain, thus influencing most basic social and cognitive functioning. This may explain the emergence of a cluster of psychopathologies during and after the COVID-19 pandemic. Therefore, this study underscores the need for prompt interventions to address pandemics' short- and long-term consequences on mental health.

Patterns of Brain Activity in Aggressors: A Meta-Analysis Study of Functional Magnetic Resonance Imaging on Decision-Making and Emotional Regulation

The cognitive and emotional processes involved in criminal behavior are varied and complex. Decision-making, inhibitory control, emotional processing, empathy and theory of mind, and emotional regulation are some of the key processes involved. Studies using functional neuroimaging have identified distinct patterns of brain activity in regions associated with these processes, providing clues about the mechanisms underlying criminal behavior. For example, differences in activation of the prefrontal cortex and amygdala have been observed in aggressors compared to nonaggressors during tasks involving moral judgment and impulsivity. These findings underscore the importance of neuroscience in investigating the cognitive and emotional processes underlying criminal behavior, offering valuable insights for theory and practice in the fields of criminology and criminal justice.

Covariate-guided Bayesian mixture of spline experts for the analysis of multivariate high-density longitudinal data.

With rapid development of techniques to measure brain activity and structure, statistical methods for analyzing modern brain-imaging data play an important role in the advancement of science. Imaging data that measure brain function are usually multivariate high-density longitudinal data and are heterogeneous across both imaging sources and subjects, which lead to various statistical and computational challenges. In this article, we propose a group-based method to cluster a collection of multivariate high-density longitudinal data via a Bayesian mixture of smoothing splines. Our method assumes each multivariate high-density longitudinal trajectory is a mixture of multiple components with different mixing weights. Time-independent covariates are assumed to be associated with the mixture components and are incorporated via logistic weights of a mixture-of-experts model. We formulate this approach under a fully Bayesian framework using Gibbs sampling where the number of components is selected based on a deviance information criterion. The proposed method is compared to existing methods via simulation studies and is applied to a study on functional near-infrared spectroscopy, which aims to understand infant emotional reactivity and recovery from stress. The results reveal distinct patterns of brain activity, as well as associations between these patterns and selected covariates.

Distinct age-related brain activity patterns in the prefrontal cortex when increasing cognitive load: A functional near-infrared spectroscopy study

Researchers have long observed distinct brain activity patterns in older adults compared with younger adults that correlate with cognitive performance. Mainly, older adults tend to show over-recruitment of bilateral brain regions during lower task loads and improved performance interpreted as compensation, but not observed at higher loads. However, there are discrepancies about whether increases in activity are compensatory and whether older adults can show compensation at higher loads. Our aim was to examine age-related differences in prefrontal cortex (PFC) activity and cognitive performance using functional near-infrared spectroscopy (fNIRS) during single and dual N-back tasks. Twenty-seven young adults (18–27 years) and 31 older adults (64–84 yrs) took part in the study. We used a robust fNIRS data methodology consisting of channel and region of interest analyses. Results showed differences in performance between task load conditions and age-related differences in reaction times but no age-group effects for accuracy. Older adults exhibited more bilateral PFC activation compared with young adults across all tasks and showed increases in brain activity in high compared to low load conditions. Our findings further support previous reports showing that older adults use compensatory recruitment of additional brain regions in PFC to maintain cognitive performance but go against the notion that such compensation is not present at higher cognitive loads. Additionally, our results indicate that fNIRS is a sensitive tool that can characterize adaptive cortical changes in healthy aging.

Implicit Perception of Differences between NLP‐Produced and Human‐Produced Language in the Mentalizing Network (Adv. Sci. 12/2023)

Natural Language Processing Chatbots may be able to talk like humans, but they cannot fool our brains. Subjectively indistinguishable chatbot and human language elicits distinct patterns of brain activity in the mentalizing network regions. A promising blueprint emerges by adding neural data as an extra index to the assessment criteria for standard Turing tests. More details can be found in article number 2203990 by Xiaochu Zhang and co-workers.

The propensity to sign-track is associated with externalizing behavior and distinct patterns of reward-related brain activation in youth

Externalizing behaviors in childhood often predict impulse control disorders in adulthood; however, the underlying bio-behavioral risk factors are incompletely understood. In animals, the propensity to sign-track, or the degree to which incentive motivational value is attributed to reward cues, is associated with externalizing-type behaviors and deficits in executive control. Using a Pavlovian conditioned approach paradigm, we quantified sign-tracking in 40 healthy 9–12-year-olds. We also measured parent-reported externalizing behaviors and anticipatory neural activations to outcome-predicting cues using the monetary incentive delay fMRI task. Sign-tracking was associated with attentional and inhibitory control deficits and the degree of amygdala, but not cortical, activation during reward anticipation. These findings support the hypothesis that youth with a propensity to sign-track are prone to externalizing tendencies, with an over-reliance on subcortical cue-reactive brain systems. This research highlights sign-tracking as a promising experimental approach delineating the behavioral and neural circuitry of individuals at risk for externalizing disorders.

Implicit Perception of Differences between NLP-Produced and Human-Produced Language in the Mentalizing Network.

Natural language processing (NLP) is central to the communication with machines and among ourselves, and NLP research field has long sought to produce human-quality language. Identification of informative criteria for measuring NLP-produced language quality will support development of ever-better NLP tools. The authors hypothesize that mentalizing network neural activity may be used to distinguish NLP-produced language from human-produced language, even for cases where human judges cannot subjectively distinguish the language source. Using the social chatbots Google Meena in English and Microsoft XiaoIce in Chinese to generate NLP-produced language, behavioral tests which reveal that variance of personality perceived from chatbot chats is larger than for human chats are conducted, suggesting that chatbot language usage patterns are not stable. Using an identity rating task with functional magnetic resonance imaging, neuroimaging analyses which reveal distinct patterns of brain activity in the mentalizing network including the DMPFC and rTPJ in response to chatbot versus human chats that cannot be distinguished subjectively are conducted. This study illustrates a promising empirical basis for measuring the quality of NLP-produced language: adding a judge's implicit perception as an additional criterion.

Patterns of brain dynamic functional connectivity are linked with attention-deficit/hyperactivity disorder-related behavioral and cognitive dimensions.

Attention-deficit/hyperactivity disorder (ADHD) is a clinically heterogeneous neurodevelopmental disorder defined by characteristic behavioral and cognitive features. Abnormal brain dynamic functional connectivity (dFC) has been associated with the disorder. The full spectrum of ADHD-related variation of brain dynamics and its association with behavioral and cognitive features remain to be established. We sought to identify patterns of brain dynamics linked to specific behavioral and cognitive dimensions using sparse canonical correlation analysis across a cohort of children with and without ADHD (122 children in total, 63 with ADHD). Then, using mediation analysis, we tested the hypothesis that cognitive deficits mediate the relationship between brain dynamics and ADHD-associated behaviors. We identified four distinct patterns of dFC, each corresponding to a specific dimension of behavioral or cognitive function (r = 0.811-0.879). Specifically, the inattention/hyperactivity dimension was positively associated with dFC within the default mode network (DMN) and negatively associated with dFC between DMN and the sensorimotor network (SMN); the somatization dimension was positively associated with dFC within DMN and SMN; the inhibition and flexibility dimension and fluency and memory dimensions were both positively associated with dFC within DMN and between DMN and SMN, and negatively associated with dFC between DMN and the fronto-parietal network. Furthermore, we observed that cognitive functions of inhibition and flexibility mediated the relationship between brain dynamics and behavioral manifestations of inattention and hyperactivity. These findings document the importance of distinct patterns of dynamic functional brain activity for different cardinal behavioral and cognitive features related to ADHD.

Characterisation of the neural basis underlying appetitive extinction & renewal in Cacna1c rats

Recent studies have revealed impairments in Cacna1c ± heterozygous animals (a gene that encodes the Cav 1.2 L-type voltage-gated calcium channels and is implicated in risk for multiple neuropsychiatric disorders) in aversive forms of learning, such as latent inhibition, reversal learning or context discrimination. However, the role of Cav 1.2 L-type voltage-gated calcium channels in extinction of appetitive associations remains under-investigated. Here, we used an appetitive Pavlovian conditioning task and evaluated extinction learning (EL) with a change of context from that of training and test (ABA) and without such a change (AAA) in Cacna1c ± male rats versus their wild-type (WT) littermates. In addition, we used fluorescence in situ hybridization of somatic immediate early genes (IEGs) Arc and Homer1a expression to scrutinize associated changes in the medial prefrontal cortex and the amygdala. Cacna1c ± animals successfully adapt their responses by engaging in appetitive EL and renewal. However, the regional IEG expression profile changed. For the EL occurring in the same context, Cacna1c ± animals presented higher IEG expression in the infralimbic cortex and the central amygdala than controls. The prelimbic region presented a larger neural ensemble in Cacna1c ± than WT animals, co-labelled for the time window of EL in the original context and prolonged exposure to the unrewarded context. With a context change, the Cacna1c ± infralimbic region displayed higher IEG expression during renewal than controls. Taken together, our findings provide novel evidence of distinct brain activation patterns occurring in Cacna1c ± rats after appetitive extinction and renewal despite preserved behavioral responses.This article is part of the Special Issue on "L-type calcium channel mechanisms in neuropsychiatric disorders".

Vision- and touch-dependent brain correlates of body-related mental processing.

In humans, the nature of sensory input influences body-related mental processing. For instance, behavioral differences (e.g., response time) can be found between mental spatial transformations (e.g., mental rotation) of viewed and touched body parts. It can thus be hypothesized that distinct brain activation patterns are associated with such sensory-dependent body-related mental processing. However, direct evidence that the neural correlates of body-related mental processing can be modulated by the nature of the sensory stimuli is still missing. We thus analyzed event-related functional magnetic resonance imaging (fMRI) data from thirty-one healthy participants performing mental rotation of visually- (images) and haptically-presented (plastic) hands. We also dissociated the neural activity related to rotation or task-related performance using models that either regressed out or included the variance associated with response time. Haptically-mediated mental rotation recruited mostly the sensorimotor brain network. Visually-mediated mental rotation led to parieto-occipital activations. In addition, faster mental rotation was associated with sensorimotor activity, while slower mental rotation was associated with parieto-occipital activations. The fMRI results indicated that changing the type of sensory inputs modulates the neural correlates of body-related mental processing. These findings suggest that distinct sensorimotor brain dynamics can be exploited to execute similar tasks depending on the available sensory input. The present study can contribute to a better evaluation of body-related mental processing in experimental and clinical settings.

Does the TPJ fit it all? Representational similarity analysis of different forms of mentalizing

ABSTRACT Mentalizing is the key socio-cognitive ability. Its heterogeneous structure may result from a variety of forms of mental state inference, which may be based on lower-level processing of cues encoded in the observable behavior of others, or rather involve higher-level computations aimed at understanding another person’s perspective. Here we aimed to investigate the representational content of the brain regions engaged in mentalizing. To this end, 61 healthy adults took part in an fMRI study. We explored ROI activity patterns associated with five well-recognized ToM tasks that induce either decoding of mental states from motion kinematics or belief-reasoning. By using multivariate representational similarity analysis, we examined whether these examples of lower- and higher-level forms of social inference induced common or distinct patterns of brain activity. Distinct patterns of brain activity related to decoding of mental states from motion kinematics and belief-reasoning were found in lTPJp and the left IFG, but not the rTPJp. This may indicate that rTPJp supports a general mechanism for the representation of mental states. The divergent patterns of activation in lTPJp and frontal areas likely reflect differences in the degree of involvement of cognitive functions which support the basic mentalizing processes engaged by the two task groups.

A dynamic gradient architecture generates brain activity states

The human brain exhibits a diverse yet constrained range of activity states. While these states can be faithfully represented in a low-dimensional latent space, our understanding of the constitutive functional anatomy is still evolving. Here we applied dimensionality reduction to task-free and task fMRI data to address whether latent dimensions reflect intrinsic systems and if so, how these systems may interact to generate different activity states. We find that each dimension represents a dynamic activity gradient, including a primary unipolar sensory-association gradient underlying the global signal. The gradients appear stable across individuals and cognitive states, while recapitulating key functional connectivity properties including anticorrelation, modularity, and regional hubness. We then use dynamical systems modeling to show that gradients causally interact via state-specific coupling parameters to create distinct brain activity patterns. Together, these findings indicate that a set of dynamic, intrinsic spatial gradients interact to determine the repertoire of possible brain activity states.

Congenital Adrenal Hyperplasia and Brain Health: A Systematic Review of Structural, Functional, and Diffusion Magnetic Resonance Imaging (MRI) Investigations.

Congenital adrenal hyperplasia (CAH) is a group of genetic disorders that affects the adrenal glands and is the most common cause of primary adrenal insufficiency in children. In the past few decades, magnetic resonance imaging (MRI) has been implemented to investigate how the brain may be affected by CAH. A systematic review was conducted to evaluate and synthesize the reported evidence of brain findings related to CAH using structural, functional, and diffusion-weighted MRI. We searched bibliographical databases through July 2021 for brain MRI studies in individuals with CAH. Twenty-eight studies were identified, including 13 case reports or series, 10 studies that recruited and studied CAH patients vs unaffected controls, and 5 studies without a matched control group. Eleven studies used structural MRI to identify structural abnormalities or quantify brain volumes, whereas 3 studies implemented functional MRI to investigate brain activity, and 3 reported diffusion MRI findings to assess white matter microstructure. Some commonly reported findings across studies included cortical atrophy and differences in gray matter volumes, as well as white matter hyperintensities, altered white matter microstructure, and distinct patterns of emotion and reward-related brain activity. These findings suggest differences in brain structure and function in patients with CAH. Limitations of these studies highlight the need for CAH neuroimaging studies to incorporate larger sample sizes and follow best study design and MRI analytic practices, as well as clarify potential neurologic effects seen across the lifespan and in relation to clinical and behavioral CAH phenotypes.

Unique Brain Wave Pattern Detection Using Brain Electrical Oscillation Signature Profiling (BEOSP)

Abstract: When a person experiences a familiar stimulus, the brain emits a unique brain wave pattern, which is known as brain fingerprinting. The use of functional magnetic resonance imaging in lie detection stems from studies that reveal that people who are asked to lie have distinct patterns of brain activity than people who are telling the truth. The use of such evidence in courts is examined in detail. The author concludes that neither approach has adequate evidence of accuracy in identifying fraud to be used in court at this time. A new lie detector has been developed in the field of criminology in the United States of America. This is referred to as "brain fingerprinting." This innovation is said to be the greatest lie detector on the market right now. When a person experiences a familiar stimulus, the brain emits a unique brain wave pattern, which is known as brain fingerprinting. In order to identify lies, functional magnetic resonance imaging is used. This innovation is believed to be the finest lie detector accessible to date, detecting even slick crooks who easily pass the polygraph exam (the traditional lie detector test). The new technology uses brain waves to determine whether or not the person being tested remembers the finer details of the incident. According to scientists who are very pleased about the new kid on the block, even if the person voluntarily suppresses the vital knowledge, the brain wave will undoubtedly catch him. Keywords: Brain finger printing, sources of EEG, EEG Vs FMRI & PET, Four phases of brain fingerprinting, Applications

Associations between neighborhood socioeconomic status, parental education, and executive system activation in youth.

Socioeconomic status (SES) can impact cognitive performance, including working memory (WM). As executive systems that support WM undergo functional neurodevelopment during adolescence, environmental stressors at both individual and community levels may influence cognitive outcomes. Here, we sought to examine how SES at the neighborhood and family level impacts task-related activation of the executive system during adolescence and determine whether this effect mediates the relationship between SES and WM performance. To address these questions, we studied 1,150 youths (age 8-23) that completed a fractal n-back WM task during functional magnetic resonance imaging at 3T as part of the Philadelphia Neurodevelopmental Cohort. We found that both higher neighborhood SES and parental education were associated with greater activation of the executive system to WM load, including the bilateral dorsolateral prefrontal cortex, posterior parietal cortex, and precuneus. The association of neighborhood SES remained significant when controlling for task performance, or related factors like exposure to traumatic events. Furthermore, high-dimensional multivariate mediation analysis identified distinct patterns of brain activity within the executive system that significantly mediated the relationship between measures of SES and task performance. These findings underscore the importance of multilevel environmental factors in shaping executive system function and WM in youth.

Design Meets Neuroscience: A Preliminary Review of Design Research Using Neuroscience Tools

The past decade has witnessed a burgeoning interest in the intersection of neuroscience and design. Recent advancements in tools for measuring brain activity enable design researchers to investigate how brain function supports mental processes, complementing self–report and behavioral measures in exploring design cognition. With the aim of providing a preliminary understanding of how design researchers have approached neuroscience to date, we examined (1) previously explored neural research topics, (2) available tools and their contributions and limitations, and (3) the challenges of conducting design research using neuroscience tools. We start with a brief overview of major neuroscience tools measuring brain activation including electroencephalography (EEG), magnetic resonance imaging (MRI), near–infrared spectroscopy (NIRS), and positron emission tomography (PET). We then present a review of design research specifically on neural processes involved in design thinking and creativity. Consistencies of brain activity across studies are identified. Distinct patterns of brain activation associated with specific comparisons (e.g., design thinking vs. problem–solving) observed in previous studies are also summarized. An introductory review of design research using neuroscience tools on design evaluation and aesthetics is then provided. In addition to the promises of the fast–growing interdisciplinary collaboration of design and neuroscience, we outline technical, practical, and experimental difficulties caused by the limits of neuroscience tools for design research studies.

Effects of electrical brain stimulation on brain indices and presence experience in immersive, interactive virtual reality

The subjective presence experience in virtual reality (VR) is associated with distinct brain activation patterns. Particularly, the dorsolateral prefrontal cortex (DLPFC) seems to play a central role. We investigated the effects of electric brain stimulation (transcranial direct current, tDCS) on the presence experience as well as on brain activity and connectivity. Thirty-eight participants received either anodal (N = 18) or cathodal (N = 20) stimulation of the DLPFC before interacting in an immersive VR as well as sham stimulation. During VR interaction, EEG and heart rate were recorded. After VR interaction, participants rated their subjective presence experience using standardized questionnaires. Cathodal stimulation led to stronger brain connectivity than sham stimulation. Increased brain connectivity was associated with numerically lower levels of subjective presence. Anodal stimulation did not lead to changes in brain connectivity, and no differences in subjective presence ratings were found between the anodal and sham stimulation. These results indicate that cathodal tDCS over the DLPFC leads to a more synchronized brain state, which might hamper the activity in networks, which are generally associated with the evolvement of the subjective presence experience. Our results underline the importance of the DLPFC for the presence experience in VR.