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Semantic verbal fluency (SVF) impairment is present in several neurological disorders. Although activation in SVF-related areas has been reported, how these regions are connected and their functional roles in the network remain divergent. We assessed SVF static and dynamic functional connectivity (FC) and effective connectivity in healthy participants using functional magnetic resonance imaging. We observed activation in the inferior frontal (IFG), middle temporal (pMTG) and angular gyri (AG), anterior cingulate (AC), insular cortex, and regions of the superior, middle, and medial frontal gyri (SFG, MFG, MidFG). Our static FC analysis showed a highly interconnected task and resting state network. Increased connectivity of AC with the pMTG and AG was observed for the task. The dynamic FC analysis provided circuits with connections similarly modulated across time and regions related to category identification, language comprehension, word selection and recovery, word generation, inhibition of speaking, speech planning, and articulatory planning of orofacial movements. Finally, the effective connectivity analysis provided a network that best explained our data, starting at the AG and going to the pMTG, from which there was a division between the ventral and dorsal streams. The SFG and MFG regions were connected and modulated by the MidFG, while the inferior regions formed the ventral stream. Therefore, we successfully assessed the SVF network, exploring regions associated with the entire processing, from category identification to word generation. The methodological approach can be helpful for further investigation of the SVF network in neurological disorders.

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In recent years, Artificial Intelligence has been used to assist healthcare professionals in detecting and diagnosing neurodegenerative diseases. In this study, we propose a methodology to analyze functional Magnetic Resonance Imaging signals and perform classification between Parkinson's disease patients and healthy participants using Machine Learning algorithms. In addition, the proposed approach provides insights into the brain regions affected by the disease. The functional Magnetic Resonance Imaging from the PPMI and 1000-FCP datasets were pre-processed to extract time series from 200 brain regions per participant, resulting in 11,600 features. Causal Forest and Wrapper Feature Subset Selection algorithms were used for dimensionality reduction, resulting in a subset of features based on their heterogeneity and association with the disease. We utilized Logistic Regression and XGBoost algorithms to perform PD detection, achieving 97.6% accuracy, 97.5% F1 score, 97.9% precision, and 97.7%recall by analyzing sets with fewer than 300 features in a population including men and women. Finally, Multiple Correspondence Analysis was employed to visualize the relationships between brain regions and each group (women with Parkinson, female controls, men with Parkinson, male controls). Associations between the Unified Parkinson's Disease Rating Scale questionnaire results and affected brain regions in different groups were also obtained to show another use case of the methodology. This work proposes a methodology to (1) classify patients and controls with Machine Learning and Causal Forest algorithm and (2) visualize associations between brain regions and groups, providing high-accuracy classification and enhanced interpretability of the correlation between specific brain regions and the disease across different groups.

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OBJECTIVES: This study aims to describe resting state networks (RSN) in patients with disorders of consciousness (DOC)s after acute severe traumatic brain injury (TBI). METHODS: Adult patients with TBI with a GCS score <8 who remained in a coma, minimally conscious state (MCS), or unresponsive wakefulness syndrome (UWS), between 2017 and 2020 were included. Blood-oxygen-level dependent imaging was performed to compare their RSN with 10 healthy volunteers. RESULTS: Of a total of 293 patients evaluated, only 13 patients were included according to inclusion criteria: 7 in coma (54%), 2 in MCS (15%), and 4 (31%) had an UWS. RSN analysis showed that the default mode network (DMN) was present and symmetric in 6 patients (46%), absent in 1 (8%), and asymmetric in 6 (46%). The executive control network (ECN) was present in all patients but was asymmetric in 3 (23%). The right ECN was absent in 2 patients (15%) and the left ECN in 1 (7%). The medial visual network was present in 11 (85%) patients. Finally, the cerebellar network was symmetric in 8 patients (62%), asymmetric in 1 (8%), and absent in 4 (30%). CONCLUSIONS: A substantial impairment in activation of RSN is demonstrated in patients with DOC after severe TBI in comparison with healthy subjects. Three patterns of activation were found: normal/complete activation, 2) asymmetric activation or partially absent, and 3) absent activation.

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OBJECTIVE: To investigate the association between left epileptiform activity and language laterality indices (LI) in patients with right mesial temporal sclerosis (MTS). METHODS: Twenty-two patients with right MTS and 22 healthy subjects underwent fMRI scanning while performing a language task. LI was calculated in multiple regions of interest (ROI). Data on the presence of left epileptiform abnormalities were obtained during prolonged video-EEG monitoring. RESULTS: After correction for multiple comparisons, LI was reduced in the middle temporal gyrus in the left interictal epileptiform discharges (IED+) group, compared with the left IED- group (p < 0.05). SIGNIFICANCE: Using a responsive reading naming fMRI paradigm, right MTS patients who presented left temporal interictal epileptiform abnormalities on video-EEG showed decreased LI in the middle temporal gyrus, indicating decreased left middle temporal gyrus activation, increased right middle temporal gyrus activation or a combination of both, demonstrative of language network reorganization, specially in the MTG, in this patient population. PLAIN LANGUAGE SUMMARY: This research studied 22 patients with right mesial temporal sclerosis (a specific type of epilepsy) comparing them to 22 healthy individuals. Participants were asked to perform a language task while undergoing a special brain imaging technique (fMRI). The findings showed that patients with epilepsy displayed a change in the area of the brain typically responsible for language processing. This suggests that their brains may have adapted due to their condition, altering the way language is processed.

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OBJECTIVE: Patients with multifocal or generalized epilepsies manifesting with drop attacks have severe refractory seizures and significant cognitive and behavioural abnormalities. It is unclear to what extent these features relate to network abnormalities and how networks in sensorimotor cortex differ from those in patients with refractory focal epilepsies. Thus, in this study we sought to provide preliminary data on connectivity of sensorimotor cortex in patients with epileptic drop attacks, in comparison to patients with focal refractory epilepsies. METHODS: Resting-state fMRI (rs-fMRI) data was available for 5 patients with epileptic drop attacks and 15 with refractory focal epilepsies undergoing presurgical evaluation. Functional connectivity was analyzed with a seed-based protocol, with primary seeds placed at the precentral gyrus, the postcentral gyrus and the premotor cortex. For each seed, the subjects' timeseries were extracted and transformed to Z scores. Between-group analysis was then performed using the 3dttest+ + AFNI program. RESULTS: Two clusters of reduced connectivity in the group with drop attacks (DA group) in relation to those with focal epilepsies were found in the between-group analysis: the precentral seed showed reduced connectivity in the surrounding motor area, and the postcentral seed, reduced connectivity with the ipsilateral posterior cingulate gyrus. In the intra-group analyses, sensorimotor and premotor networks were abnormal in the DA group, whereas patients with focal epilepsies had the usual connectivity maps with each seed. CONCLUSION: This pilot study shows differences in the cerebral connectivity in the sensorimotor cortex of patients with generalized epilepsies and drop attacks which should be further explored to better understand the biological bases of the seizure generation and cognitive changes in these people.

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RESUMEN Las técnicas de neuroimagenología otorgan información relevante del estado funcional y anatómico del cerebro humano. Esta información es particularmente importante cuando existe una lesión cerebral causada por alguna patología, tal como la enfermedad vascular cerebral (EVC). En pacientes afectados por esta enfermedad, se ha determinado que la neuroplasticidad es el mecanismo principal de recuperación de la función motora perdida. Debido a la alta prevalencia de la EVC a nivel mundial y especialmente en países en vías de desarrollo, es necesario continuar investigando los mecanismos de recuperación involucrados en esta patología. La resonancia magnética funcional (RMF) y la imagenología por tensor de difusión (ITD) son dos de las técnicas de neuroimagenología más utilizadas con este fin. La RMF permite analizar la actividad neuronal generada al ejecutar tareas de movimiento, mientras que la ITD proporciona información estructural de la anatomía cerebral. En esta revisión narrativa, se presentan diversos estudios que han utilizado estas técnicas de neuroimagenología en la cuantificación de los cambios de neuroplasticidad en pacientes con EVC tras participar en algún programa de neurorrehabilitación. Comprender mejor estos cambios de neuroplasticidad permitiría diseñar esquemas de rehabilitación que proporcionen un mayor beneficio a los pacientes con EVC.

ABSTRACT Neuroimaging techniques provide relevant information of the functional and anatomical status of the human brain. This information is of particular importance when a pathology, like stroke, produces a brain injury. In stroke patients, it has been determined that neuroplasticity is the primary recovery mechanism of the lost motor function. Due to worldwide high prevalence, especially in developing countries, it is necessary to continue the research of the recovery mechanisms involved in this pathology. To this end, functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) are two of the most used neuroimaging techniques. In stroke patients, fMRI allows the analysis of the neural activity produced by the execution of motor tasks, whereas DTI provides structural information of the brain anatomy. In this narrative review, multiple studies that employ these neuroimaging techniques for quantification of neuroplasticity changes in stroke patients after undergoing a neurorehabilitation program are presented. Better understanding of these neuroplasticity changes would allow researchers to design and provide more beneficial rehabilitation schemes to stroke patients.

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Resumen Objetivo: Explorar si voluntarios sanos presentarían correlación entre su puntaje en un test psicológico emocional y las activaciones de áreas cerebrales relacionadas con las emociones medidas con resonancia magnética funcional (RMf). Material y métodos: Estudio exploratorio de prueba diagnóstica, prospectivo, con diseño del propio individuo como control, con muestra de 12 participantes. Se categorizó a cada participante con un puntaje de estabilidad emocional derivado de un test psicológico y se utilizaron estímulos emocionales audiovisuales durante las adquisiciones de RMf. Resultados: La sumatoria de clusters de activación medidos en cantidad total de vóxeles durante los estímulos negativos en áreas cerebrales relacionadas con las emociones mostró una correlación negativa estadísticamente significativa para nuestro tamaño de muestra respecto de los puntajes en el test emocional, con rho de Spearman de −0,623 y p = 0,0428. Conclusiones: Los paradigmas de RMf utilizados permitieron cuantificar las activaciones cerebrales ante estímulos emocionales de valencia positiva y negativa, y los resultados obtenidos abren una perspectiva hacia la posibilidad de utilizar test psicológicos y secuencias de RMf para predecir la posibilidad de aparición de síntomas de patologías psicológicas o psiquiátricas ante factores desencadenantes en población sana que presente en estos test valores cercanos al límite de la normalidad.

Abstract Objective: To explore if healthy volunteers would present a correlation between their score in emotional psychological test and the activations of brain areas related to emotions measured with functional magnetic resonance imaging (fMRI). Material and methods: Exploratory study of a prospective diagnostic test, with the individual’s own design as a control, with a sample of 12 participants. Each participant was categorized with an emotional stability score derived from a psychological test and audiovisual emotional stimuli were used during fMRI acquisitions. Results: The sum of activation clusters measured in total number of voxels during negative stimuli in brain areas related to emotions showed a statistically significant negative correlation for our sample size with respect to the scores in the emotional test, with Spearman’s rho of −0.623 and p = 0.0428. Conclusions: The fMRI paradigms used made it possible to quantify brain activations in response to emotional stimuli of positive and negative valence, and the results obtained open a perspective towards the possibility of using psychological tests and fMRI sequences to predict the possibility of the appearance of symptoms of psychological or psychiatric pathologies in response to triggering factors in a healthy population that present values close to the normal limit in these tests.

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Graphical modeling of multivariate functional data is becoming increasingly important in a wide variety of applications. The changes of graph structure can often be attributed to external variables, such as the diagnosis status or time, the latter of which gives rise to the problem of dynamic graphical modeling. Most existing methods focus on estimating the graph by aggregating samples, but largely ignore the subject-level heterogeneity due to the external variables. In this article, we introduce a conditional graphical model for multivariate random functions, where we treat the external variables as conditioning set, and allow the graph structure to vary with the external variables. Our method is built on two new linear operators, the conditional precision operator and the conditional partial correlation operator, which extend the precision matrix and the partial correlation matrix to both the conditional and functional settings. We show that their nonzero elements can be used to characterize the conditional graphs, and develop the corresponding estimators. We establish the uniform convergence of the proposed estimators and the consistency of the estimated graph, while allowing the graph size to grow with the sample size, and accommodating both completely and partially observed data. We demonstrate the efficacy of the method through both simulations and a study of brain functional connectivity network.

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Around 30% of the general population experience subjective tinnitus, characterized by conscious attended awareness perception of sound without an external source. Clinical distress tinnitus is more than just experiencing a phantom sound, as it can be highly disruptive and debilitating, leading those affected to seek clinical help. Effective tinnitus treatments are crucial for psychological well-being, but our limited understanding of the underlying neural mechanisms and a lack of a universal cure necessitate further treatment development. In light of the neurofunctional tinnitus model predictions and transcranial electrical stimulation, we conducted an open-label, single-arm, pilot study that utilized high-definition transcranial direct current stimulation (HD-tDCS) concurrent with positive emotion induction (PEI) techniques for ten consecutive sessions to down-regulate tinnitus negative valence in patients with clinical distress tinnitus. We acquired resting-state functional magnetic resonance imaging scans of 12 tinnitus patients (7 females, mean age = 51.25 ± 12.90 years) before and after the intervention to examine resting-state functional connectivity (rsFC) alterations in specific seed regions. The results showed reduced rsFC at post-intervention between the attention and emotion processing regions as follows: (1) bilateral amygdala and left superior parietal lobule (SPL), (2) left amygdala and right SPL, (3) bilateral dorsolateral prefrontal cortex (dlPFC) and bilateral pregenual anterior cingulate cortex (pgACC), and (4) left dlPFC and bilateral pgACC (FWE corrected p < 0.05). Furthermore, the post-intervention tinnitus handicap inventory scores were significantly lower than the pre-intervention scores (p < 0.05). We concluded that concurrent HD-tDCS and PEI might be effective in reducing tinnitus negative valence, thus alleviating tinnitus distress.

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The belief that learning can be modulated by social context is mainly supported by high-level value-based learning studies. However, whether social context can even modulate low-level learning such as visual perceptual learning (VPL) is still unknown. Unlike traditional VPL studies in which participants were trained singly, here, we developed a novel dyadic VPL paradigm in which paired participants were trained with the same orientation discrimination task and could monitor each other's performance. We found that the social context (i.e., dyadic training) led to a greater behavioral performance improvement and a faster learning rate compared with the single training. Interestingly, the facilitating effects could be modulated by the performance difference between paired participants. Functional magnetic resonance imaging (fMRI) results showed that, compared with the single training, social cognition areas including bilateral parietal cortex and dorsolateral prefrontal cortex displayed a different activity pattern and enhanced functional connectivities to early visual cortex (EVC) during the dyadic training. Furthermore, the dyadic training resulted in more refined orientation representation in primary visual cortex (V1), which was closely associated with the greater behavioral performance improvement. Taken together, we demonstrate that the social context, learning with a partner, can remarkably augment the plasticity of low-level visual information process by means of reshaping the neural activities in EVC and social cognition areas, as well as their functional interplays.

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Significance: Brain fingerprinting refers to identifying participants based on their functional patterns. Despite its success with functional magnetic resonance imaging (fMRI), brain fingerprinting with functional near-infrared spectroscopy (fNIRS) still lacks adequate validation. Aim: We investigated how fNIRS-specific acquisition features (limited spatial information and nonneural contributions) influence resting-state functional connectivity (rsFC) patterns at the intra-subject level and, therefore, brain fingerprinting. Approach: We performed multiple simultaneous fNIRS and fMRI measurements in 29 healthy participants at rest. Data were preprocessed following the best practices, including the removal of motion artifacts and global physiology. The rsFC maps were extracted with the Pearson correlation coefficient. Brain fingerprinting was tested with pairwise metrics and a simple linear classifier. Results: Our results show that average classification accuracy with fNIRS ranges from 75% to 98%, depending on the number of runs and brain regions used for classification. Under the right conditions, brain fingerprinting with fNIRS is close to the 99.9% accuracy found with fMRI. Overall, the classification accuracy is more impacted by the number of runs and the spatial coverage than the choice of the classification algorithm. Conclusions: This work provides evidence that brain fingerprinting with fNIRS is robust and reliable for extracting unique individual features at the intra-subject level once relevant spatiotemporal constraints are correctly employed.

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Cerebral small vessel disease (cSVD) has been widely studied using conventional magnetic resonance imaging (MRI) methods, although the association between MRI findings and clinical features of cSVD is not always concordant. We assessed the additional contribution of contrast agent-free, state-of-the-art MRI techniques, particularly diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI), to understand brain damage and structural and functional connectivity impairment related to cSVD. We performed a review following the PICOS worksheet and Search Strategy, including 152 original papers in English, published from 2000 to 2022. For each MRI method, we extracted information about their contributions regarding the origins, pathology, markers, and clinical outcomes in cSVD. In general, DTI studies have shown that changes in mean, radial, and axial diffusivity measures are related to the presence of cSVD. In addition to the classical deficit in executive functions and processing speed, fMRI studies indicate connectivity dysfunctions in other domains, such as sensorimotor, memory, and attention. Neuroimaging metrics have been correlated with the diagnosis, prognosis, and rehabilitation of patients with cSVD. In short, the application of contrast agent-free, state-of-the-art MRI techniques has provided a complete picture of cSVD markers and tools to explore questions that have not yet been clarified about this clinical condition. Longitudinal studies are desirable to look for causal relationships between image biomarkers and clinical outcomes.

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BACKGROUND AND PURPOSE: The digiti quinti sign (DQS) consists of a wider angle between the fourth and fifth fingers (ANG) indicative of subtle hemiparesis that has been found interictally in hemiplegic migraine (HM), suggesting a permanent subtle motor dysfunction. The aim of this study was to find a possible cortical origin for the DQS using blood oxygen level dependent (BOLD) functional (f) MRI. METHODS: Eight HM patients and 13 controls entered the cross-sectional study. We examined hand dominance, performed handgrip tests with dynamometry, documented the DQS graphically in two consecutive sessions, and used BOLD-fMRI during a motor task specifically designed to measure the evoked activation in the motor cortex (M1). The brain activation at the symptomatic side was compared with the contralateral hemisphere and with both correspondent hemispheres in controls. RESULTS: Subjects had a normal neurological examination, except for DQS in all HM patients. The activation amplitude (beta values) and the cluster extension (mm3 ) of the activation area in M1 was smaller at the affected side. Besides, the cluster extension correlated negatively with the disease time span. The ANG was wider bilaterally in patients and the fMRI signals were reduced in the patient's group. CONCLUSION: The DQS, a relevant clinical finding in HM, indicates a disrupted cortical activation.

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Relating brain dynamics acting on time scales that differ by at least an order of magnitude is a fundamental issue in brain research. The same is true for the observation of stable dynamical structures in otherwise highly non-stationary signals. The present study addresses both problems by the analysis of simultaneous resting state EEG-fMRI recordings of 53 patients with epilepsy. Confirming previous findings, we observe a generic and temporally stable average correlation pattern in EEG recordings. We design a predictor for the General Linear Model describing fluctuations around the stationary EEG correlation pattern and detect resting state networks in fMRI data. The acquired statistical maps are contrasted to several surrogate tests and compared with maps derived by spatial Independent Component Analysis of the fMRI data. By means of the proposed EEG-predictor we observe core nodes of known fMRI resting state networks with high specificity in the default mode, the executive control and the salience network. Our results suggest that both, the stationary EEG pattern as well as resting state fMRI networks are different expressions of the same brain activity. This activity is interpreted as the dynamics on (or close to) a stable attractor in phase space that is necessary to maintain the brain in an efficient operational mode. We discuss that this interpretation is congruent with the theoretical framework of complex systems as well as with the brain's energy balance.

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Abstract This study aimed to describe the cerebral activation patterns using fMRI (Functional Magnetic Resonance Imaging) technology in a sample of 15 children with Posttraumatic Stress Disorder (PTSD) and 7 with no PTSD. The study used a Quasi-experimental methodology where two experimental tasks were applied: an emotional face task and a version of an emotional Stroop task. The results point out differences in the group of PTSD on the processing of negative stimuli and changes in their frontal lobe activation. These preliminary results suggest that early traumatic experiences affect typical brain development patterns. And explicit and implicit variables involved in the traumatic experiences are discussed as a part of any intervention process.

Resumen El presente estudio tuvo como objetivo describir patrones de activación cerebral mediante una técnica de Imagen por resonancia magnética funcional -fMRI- (abreviatura en inglés de Functional Magnetic Resonance Imaging) en una muestra de niños con Trastorno de estrés postraumático (TEPT) y compararlos con un grupo de controles. Estudio cuasi-experimental en el que se tomó un grupo de 15 niños con TEPT y se comparó con un grupo de 7 niños sin TEPT. Se emplearon dos tareas experimentales: una prueba de caras y una versión del Stroop emocional. Los resultados preliminares, señalan diferencias en el procesamiento de estímulos, principalmente de carácter negativo en los niños con TEPT y cambios en los patrones de activación a nivel de estructuras frontales. Se concluye que el trauma a edad temprana afecta el curso normal del desarrollo cerebral y se evidencia la importancia de abordar los aspectos explícitos e implícitos asociados a la experiencia traumática como parte de la intervención.

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Abstract Introduction Persistent postural-perceptual dizziness (PPPD) is a functional vestibular disorder characterized by chronic dizziness, unsteadiness, and hypersensitivity to motion. Preexisting anxiety disorders and neurotic personality traits confer vulnerability to PPPD. High anxiety during acute vertigo or dizziness incites it. A functional magnetic resonance imaging (fMRI) study of chronic subjective dizziness found unexpectedly hypoactive responses to vestibular stimulation in cortical regions that integrate threat assessment and spatial perception. Objective This fMRI study used non-moving, but emotionally charged visual stimuli to investigate the brain's activity of PPPD patients and control subjects. Methods The participants included 16 women with PPPD and 16 age-matched women who recovered completely from acute episodes of vertigo or dizziness capable of triggering PPPD. Brain responses to positive, neutral, and negative figures from the International Affective Picture System were measured with fMRI and compared between the groups. Dizziness handicap, anxiety, and depression were assessed with validated questionnaires. Results Between group analyses: Participants with PPPD showed reduced activity in anterior cingulate cortex and increased activity in left angular gyrus in response to negative versus positive stimuli, which was not observed in recovered individuals. Within group analyses: Participants with PPPD had increased activity in visuospatial areas (parahippocampal gyrus, intraparietal sulcus) in negative versus positive and negative versus neutral contrasts, whereas recovered individuals had increased activity in anxiety regions (amygdala, orbitofrontal cortex). Conclusion Patients with PPPD may be more attuned to spatial elements than to the content of emotionally charged visual stimuli.

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Introduction Persistent postural-perceptual dizziness (PPPD) is a functional vestibular disorder characterized by chronic dizziness, unsteadiness, and hypersensitivity to motion. Preexisting anxiety disorders and neurotic personality traits confer vulnerability to PPPD. High anxiety during acute vertigo or dizziness incites it. A functional magnetic resonance imaging (fMRI) study of chronic subjective dizziness found unexpectedly hypoactive responses to vestibular stimulation in cortical regions that integrate threat assessment and spatial perception. Objective This fMRI study used non-moving, but emotionally charged visual stimuli to investigate the brain's activity of PPPD patients and control subjects. Methods The participants included 16 women with PPPD and 16 age-matched women who recovered completely from acute episodes of vertigo or dizziness capable of triggering PPPD. Brain responses to positive, neutral, and negative figures from the International Affective Picture System were measured with fMRI and compared between the groups. Dizziness handicap, anxiety, and depression were assessed with validated questionnaires. Results Between group analyses: Participants with PPPD showed reduced activity in anterior cingulate cortex and increased activity in left angular gyrus in response to negative versus positive stimuli, which was not observed in recovered individuals. Within group analyses: Participants with PPPD had increased activity in visuospatial areas (parahippocampal gyrus, intraparietal sulcus) in negative versus positive and negative versus neutral contrasts, whereas recovered individuals had increased activity in anxiety regions (amygdala, orbitofrontal cortex). Conclusion Patients with PPPD may be more attuned to spatial elements than to the content of emotionally charged visual stimuli.

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BACKGROUND: Graph theory (GT) is a mathematical field that analyses complex networks that can be applied to neuroimaging to quantify brain's functional systems in Parkinson's disease (PD) and essential tremor (ET). OBJECTIVES: To evaluate the functional connectivity (FC) measured by the global efficiency (GE) of the motor network in PD and compare it to ET and healthy controls (HC), and correlate it to clinical parameters. METHODS: 103 subjects (54PD, 18ET, 31HC) were submitted to structural and functional MRI. A network was designed with regions of interest (ROIs) involved in motor function, and GT was applied to determine its GE. Clinical parameters were analyzed as covariates to estimate the impact of disease severity and medication on GE. RESULTS: GE of the motor circuit was reduced in PD in comparison with HC (p .042). Areas that most contributed to it were left supplementary motor area (SMA) and bilateral postcentral gyrus. Tremor scores correlated positively with GE of the motor network in PD subgroups. For ET, there was an increase in the connectivity of the anterior cerebellar network to the other ROIs of the motor circuit in comparison with PD. CONCLUSIONS: FC measured by the GE of the motor network is diminished in PD in comparison with HC, especially due to decreased connectivity of left SMA and bilateral postcentral gyrus. This finding supports the theory that there is a global impairment of the motor network in PD, and it does not affect just the basal ganglia, but also areas associated with movement modulation. The ET group presented an increased connectivity of the anterior cerebellar network to the other ROIs of the motor circuit when compared to PD, which reinforces what it is known about its role in this pathology.

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Background: Brain interdependencies can be studied from either a structural/anatomical perspective ("structural connectivity") or by considering statistical interdependencies ("functional connectivity" [FC]). Interestingly, while structural connectivity is by definition pairwise (white-matter fibers project from one region to another), FC is not. However, most FC analyses only focus on pairwise statistics and they neglect higher order interactions. A promising tool to study high-order interdependencies is the recently proposed O-Information, which can quantify the intrinsic statistical synergy and the redundancy in groups of three or more interacting variables. Methods: We analyzed functional magnetic resonance imaging (fMRI) data obtained at rest from 164 healthy subjects with ages ranging in 10 to 80 years and used O-Information to investigate how high-order statistical interdependencies are affected by age. Results: Older participants (from 60 to 80 years old) exhibited a higher predominance of redundant dependencies compared with younger participants, an effect that seems to be pervasive as it is evident for all orders of interaction. In addition, while there is strong heterogeneity across brain regions, we found a "redundancy core" constituted by the prefrontal and motor cortices in which redundancy was evident at all the interaction orders studied. Discussion: High-order interdependencies in fMRI data reveal a dominant redundancy in functions such as working memory, executive, and motor functions. Our methodology can be used for a broad range of applications, and the corresponding code is freely available. Impact statement Past research has showcased multiple changes to the brain's structural and functional properties caused by aging. Here we expand prior work through recent advancements in multivariate information theory, which provide richer and more theoretically principled analyses than existing alternatives. We show that the brains of older participants contain more redundant information at multiple spatial scales-that is, activation in different brain regions is less diverse, compared with younger participants-and identify a "redundancy core" constituted by prefrontal and motor cortices, which might explained impaired performance in the old population in functions such as working memory and executive control.

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Objective: To investigate whether poor antidepressant tolerability is associated with functional brain changes in children and adolescents of parents with bipolar I disorder (at-risk youth). Methods: Seventy-three at-risk youth (ages 9-20 years old) who participated in a prospective study and had an available baseline functional magnetic resonance imaging (fMRI) scan were included. Research records were reviewed for the incidence of adverse reactions related to antidepressant exposure during follow-up. The sample was divided among at-risk youth without antidepressant exposure (n=21), at-risk youth with antidepressant exposure and no adverse reaction (n=12), at-risk youth with antidepressant-related adverse reaction (n=21), and healthy controls (n=20). The fMRI task was a continuous performance test with emotional distracters. Region-of-interest mean activation in brain areas of the fronto-limbic emotional circuit was compared among groups. Results: Right amygdala activation in response to emotional distracters significantly differed among groups (F3,66 = 3.1, p = 0.03). At-risk youth with an antidepressant-related adverse reaction had the lowest amygdala activation, while at-risk youth without antidepressant exposure had the highest activation (p = 0.004). Conclusions: Decreased right amygdala activation in response to emotional distracters is associated with experiencing an antidepressant-related adverse reaction in at-risk youth. Further studies to determine whether amygdala activation is a useful biomarker for antidepressant-related adverse events are needed.

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