1,720,993 research outputs found
Vicarious Function in the Motor Cortex. A Computational Investigation
No full textThis paper presents a computational investigation of the vicarious function in the motor cortex (c/o the ability to reorganise its functioning by virtue of a shift of the lost function in the surrounding cortex which becomes able to vicariate). Several experimental studies in animals and humans have shown that motor recovery after partial destruction of the motor cortex is based on adjacent motor reorganisation. This study provides phenomenological evidence of this vicarious function. We tested the hypothesis according to which the vicarious function is possible because there is a synaptic rearrangement of the weights (which are comparable to the synapses of the brain) of the lesioned layer (unmasking of previous silent synapses hypothesis), and our results confirm this hypothesis. We argue that functional recovery is possible only when having bidirectional connections and that it is facilitated when non-M1 areas can guide the layer to relearn the lost movement
La regolazione emozionale sociale e non sociale. Uno studio di morfometria cerebrale. (Social and non social emotion regulation: A brain morphometry study)
No full textIn questo studio, presentiamo i risultati di uno studio sulle differenze comportamentali e neurali relativi alla capacità di regolare emozioni sociali (RES) e non sociali (RENS). Ad oggi non sappiamo se la RES e la RENS siano sovrapponibili dal punto di vista psicologico e delle basi cerebrale, o se esse siano capacità indipendenti. Lo scopo dello studio è stato di testare queste ipotesi. Dallo studio è emerso che: 1) la RES e la RENS sono capacità tra loro indipendenti (mancata correlazione degli indici comportamentali); 2) e tramite una innovativa analisi di morfometria cerebrale (Morfometria basata sulla Sorgente), abbiamo dimostrato che la RES e la RENS hanno differenti basi neurali. Nella RES le principali strutture coinvolte riguardano un'ampia zona ventro-mediale prefrontale, la giunzione temporo-parietale, il giro fusiforme e la corteccia cingolata anteriore, mentre nella RENS si è evinto un coinvolgimento maggiore del giro superiore e medio frontale, e del giro temporale superiore
Mindful emotion regulation: exploring the neurocognitive mechanisms behind mindfulness
Get PDFThe purpose of this paper is to review some of the psychological and neural mechanisms behind mindfulness practice in order to explore the unique factors that account for its positive impact on emotional regulation and health. After reviewing the mechanisms of mindfulness and its effects on clinical populations we will consider how the practice of mindfulness contributes to the regulation of emotions. We argue that mindfulness has achieved effective outcomes in the treatment of anxiety, depression, and other psychopathologies through the contribution of mindfulness to emotional regulation. We consider the unique factors that mindfulness meditation brings to the process of emotion regulation that may account for its effectiveness. We review experimental evidence that points towards the unique effects of mindfulness specifically operating over and above the regulatory effects of cognitive reappraisal mechanisms. A neuroanatomical circuit that leads to mindful emotion regulation is also suggested. This paper thereby aims to contribute to proposed models of mindfulness for research and theory building by proposing a specific model for the unique psychological and neural processes involved in mindful detachment that account for the effects of mindfulness over and above the effects accounted for by other well-established emotional regulation processes such as cognitive reappraisal
Uncovering the Social Deficits in the Autistic Brain. A Source-Based Morphometric Study
Get PDFAutism is a neurodevelopmental disorder that mainly affects social interaction and communication. Evidence from behavioral and functional MRI studies supports the hypothesis that dysfunctional mechanisms involving social brain structures play a major role in autistic symptomatology. However, the investigation of anatomical abnormalities in the brain of people with autism has led to inconsistent results. We investigated whether specific brain regions, known to display functional abnormalities in autism, may exhibit mutual and peculiar patterns of covariance in their gray-matter concentrations. We analyzed structural MRI images of 32 young men affected by autistic disorder (AD) and 50 healthy controls. Controls were matched for sex, age, handedness. IQ scores were also monitored to avoid confounding. A multivariate Source-Based Morphometry (SBM) was applied for the first time on AD and controls to detect maximally independent networks of gray matter. Group comparison revealed a gray-matter source that showed differences in AD compared to controls. This network includes broad temporal regions involved in social cognition and high-level visual processing, but also motor and executive areas of the frontal lobe. Notably, we found that gray matter differences, as reflected by SBM, significantly correlated with social and behavioral deficits displayed by AD individuals and encoded via the Autism Diagnostic Observation Schedule scores. These findings provide support for current hypotheses about the neural basis of atypical social and mental states information processing in autism
Decoding acceptance and reappraisal strategies from resting state macro networks
No full textAbstract Acceptance and reappraisal are considered adaptive emotion regulation strategies. While previous studies have explored the neural underpinnings of these strategies using task-based fMRI and sMRI, a gap exists in the literature concerning resting-state functional brain networks’ contributions to these abilities, especially regarding acceptance. Another intriguing question is whether these strategies rely on similar or different neural mechanisms. Building on the well-known improved emotion regulation and increased cognitive flexibility of individuals who rely on acceptance, we expected to find decreased activity inside the affective network and increased activity inside the executive and sensorimotor networks to be predictive of acceptance. We also expect that these networks may be associated at least in part with reappraisal, indicating a common mechanism behind different strategies. To test these hypotheses, we conducted a functional connectivity analysis of resting-state data from 134 individuals (95 females; mean age: 30.09 ± 12.87 years, mean education: 12.62 ± 1.41 years). To assess acceptance and reappraisal abilities, we used the Cognitive Emotion Regulation Questionnaire (CERQ) and a group-ICA unsupervised machine learning approach to identify resting-state networks. Subsequently, we conducted backward regression to predict acceptance and reappraisal abilities. As expected, results indicated that acceptance was predicted by decreased affective, and executive, and increased sensorimotor networks, while reappraisal was predicted by an increase in the sensorimotor network only. Notably, these findings suggest both distinct and overlapping brain contributions to acceptance and reappraisal strategies, with the sensorimotor network potentially serving as a core common mechanism. These results not only align with previous findings but also expand upon them, illustrating the complex interplay of cognitive, affective, and sensory abilities in emotion regulation
Structural and functional brain networks of individual differences in trait anger and anger control: an unsupervised machine learning study
Get PDFThe ability to experience, use and eventually control anger, is crucial to maintain well-being and build healthy relationships. Despite its relevance, the neural mechanisms behind individual differences in experiencing and controlling anger are poorly understood. To elucidate these points, we employed an unsupervised machine learning approach based on Independent Component Analysis, to test the hypothesis that specific functional and structural networks are associated with individual differences in trait anger and anger control. Structural and functional resting state images of 71 subjects as well as their scores from the State-Trait Anger Expression Inventory entered the analyses. At a structural level, the concentration of gray matter in a network including ventromedial temporal areas, posterior cingulate, fusiform gyrus and cerebellum was associated with trait anger. The higher the concentration, the higher the proneness to experience anger in daily life due to the greater tendency to orient attention toward aversive events and interpret them with higher hostility. At a functional level, the activity of the Default Mode Network was associated with anger control. The higher the DMN temporal frequency, the stronger the exerted control over anger, thus extending previous evidence on the role of the DMN in regulating cognitive and emotional functions in the domain of anger. Taken together, these results show, for the first time, two specialized brain networks for encoding individual differences in trait anger and anger control
Brain regions and functional interactions supporting early word recognition in the face of input variability
Get PDFPerception and cognition in infants have been traditionally investigated using habituation paradigms, assuming that babies' memories in laboratory contexts are best constructed after numerous repetitions of the very same stimulus in the absence of interference. A crucial, yet open, question regards how babies deal with stimuli experienced in a fashion similar to everyday learning situations-namely, in the presence of interfering stimuli. To address this question, we used functional near-infrared spectroscopy to test 40 healthy newborns on their ability to encode words presented in concomitance with other words. The results evidenced a habituation-like hemodynamic response during encoding in the left-frontal region, which was associated with a progressive decrement of the functional connections between this region and the left-temporal, right-temporal, and right-parietal regions. In a recognition test phase, a characteristic neural signature of recognition recruited first the right-frontal region and subsequently the right-parietal ones. Connections originating from the right-temporal regions to these areas emerged when newborns listened to the familiar word in the test phase. These findings suggest a neural specialization at birth characterized by the lateralization of memory functions: the interplay between temporal and left-frontal regions during encoding and between temporo-parietal and right-frontal regions during recognition of speech sounds. Most critically, the results show that newborns are capable of retaining the sound of specific words despite hearing other stimuli during encoding. Thus, habituation designs that include various items may be as effective for studying early memory as repeated presentation of a single word.European Research Council under European Union
269502
CONICYT-Chile Program PIA/BASAL
FB0003
"Progetto strategico NEURAT" from the University of Padua
CONICYT-Chile Program PAI/Academia
7913002
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Structural Features Related to Affective Instability Correctly Classify Patients With Borderline Personality Disorder. A Supervised Machine Learning Approach.
Get PDFPrevious morphometric studies of Borderline Personality Disorder (BPD) reported inconsistent alterations in cortical and subcortical areas. However, these studies have investigated the brain at the voxel level using mass univariate methods or region of interest approaches, which are subject to several artifacts and do not enable detection of more complex patterns of structural alterations that may separate BPD from other clinical populations and healthy controls (HC). Multiple Kernel Learning (MKL) is a whole-brain multivariate supervised machine learning method able to classify individuals and predict an objective diagnosis based on structural features. As such, this method can help identifying objective biomarkers related to BPD pathophysiology and predict new cases. To this aim, we applied MKL to structural images of patients with BPD and matched HCs. Moreover, to ensure that results are specific for BPD and not for general psychological disorders, we also applied MKL to BPD against a group of patients with bipolar disorder, for their similarities in affective instability. Results showed that a circuit, including basal ganglia, amygdala, and portions of the temporal lobes and of the orbitofrontal cortex, correctly classified BPD against HC (80%). Notably, this circuit positively correlates with the affective sector of the Zanarini questionnaire, thus indicating an involvement of this circuit with affective disturbances. Moreover, by contrasting BPD with BD, the spurious regions were excluded, and a specific circuit for BPD was outlined. These results support that BPD is characterized by anomalies in a cortico-subcortical circuit related to affective instability and that this circuit discriminates BPD from controls and from other clinical populations
- …
