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1.
J Neural Eng ; 18(4)2021 09 03.
Artigo em Inglês | MEDLINE | ID: mdl-34475274

RESUMO

Objective.Transcranial magnetic stimulation (TMS) can be used to safely and noninvasively activate brain tissue. However, the characteristic parameters of the neuronal activation have been largely unclear. In this work, we propose a novel neuronal activation model and develop a method to infer its parameters from measured motor evoked potential signals.Approach.The connection between neuronal activation due to an induced electric field and a measured motor threshold is modeled. The posterior distribution of the model parameters are inferred from measurement data using Bayes' formula. The measurements are the active motor thresholds obtained with multiple stimulating coil locations, and the parameters of the model are the location, preferred direction of activation, and threshold electric field value of the activation site. The posterior distribution is sampled using a Markov chain Monte Carlo method. We quantify the plausibility of the model by calculating the marginal likelihood of the measured thresholds. The method is validated with synthetic data and applied to motor threshold measurements from the first dorsal interosseus muscle in five healthy participants.Main results.The method produces a probability distribution for the activation location, from which a minimal volume where the activation occurs with 95% probability can be derived. For eight or nine stimulating coil locations, the smallest such a volume obtained was approximately 100 mm3. The 95% probability volume intersected the pre-central gyral crown and the anterior wall of the central sulcus, and the preferred direction was perpendicular to the central sulcus, both findings being consistent with the literature. Furthermore, it was not possible to rule out if the activation occurred either in the white or grey matter. In one participant, two distinct activations sites were found while others exhibited a unique site.Significance.The method is both generic and robust, and it lays a foundation for a framework that enables accurate analysis and characterization of TMS activation mechanisms.


Assuntos
Córtex Motor , Estimulação Magnética Transcraniana , Teorema de Bayes , Mapeamento Encefálico , Potencial Evocado Motor , Humanos
2.
Neurocirugia (Astur : Engl Ed) ; 32(5): 217-223, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34493402

RESUMO

BACKGROUND: Complete resection of symptomatic supratentorial cavernoma (SCA) and removal of the surrounding gliotic area is recommended to minimize the risk of persistent seizures or (re)bleeding. Surgery of SCA located in an eloquent area, can carry out severe postoperative neurological morbidity. We report a study aimed to assess feasibility, extent of resection and outcome after surgical removal of CA by cortico-subcortical intraoperative brain stimulation (ioBS) in the awake patient. METHODS: Six patients diagnosed of symptomatic SCA located on an eloquent area and operated on while awake under local anaesthesia ioBS, were included. Preoperative planning included neuropsychologic assessment of language-related functions, sociocognitive functions and executive functions. Intraoperatively, we recorded the results achieved in the planned neuropsychological tasks when stimulation was applied (cortical and subcortical). Postoperative control 3D MRI was scheduled at 1 month after surgery to calculate extent of resection. Neuropsychological assessment at 6 months after surgery was performed in all cases. RESULTS: Six patients (5 females, 1 male) aged 24-48 years were included in our study. Locations of the lesions were right insular (n=1), left insular (n=1), left temporo-insular (n=1), left temporal (n=2) and left frontal (n=1). In all patients, positive findings were obtained during ioBS. In 5 patients, complete surgical resection was achieved. Two patients had postoperative transient neurological deficits, one case of hemiparesis, one case of dysnomia, both cleared over a 6-month period. Clinical follow-up revealed that all patients experienced complete recovery from preoperative symptoms within a year and five patients with seizures showed marked improvement and eventually quit antiepileptic drugs. Neuropsychological assessment at 6 months provided normal results compared to preoperative baseline in all domains. CONCLUSIONS: Our study suggests that ioBS in the awake surgery of symptomatic SCA located in eloquent areas, allows to increase the rate of complete resection, minimizing postoperative neurological and neuropsychological deficit, and improving postoperative seizures control.


Assuntos
Neoplasias Encefálicas , Hemangioma Cavernoso , Adulto , Mapeamento Encefálico , Neoplasias Encefálicas/diagnóstico por imagem , Feminino , Hemangioma Cavernoso/cirurgia , Humanos , Masculino , Pessoa de Meia-Idade , Monitorização Intraoperatória , Vigília , Adulto Jovem
3.
BMC Psychol ; 9(1): 133, 2021 Sep 03.
Artigo em Inglês | MEDLINE | ID: mdl-34479637

RESUMO

BACKGROUND: This study investigated the impact of semantic relevance on the ability to comprehend the appearance and function of a product, as presented in images. METHODS: The images used the constructs of Simile, Metaphor and Analogy to correspond to congruent, related and incongruent semantic structures, and measured the amplitude of Event-Related Potentials (ERPs) to compare these images with Landscape images. Sixteen participants with design-related educational backgrounds were invited to join in the ERP experiment. RESULTS: The results found that the image depicting the Metaphor showed a stronger N600 amplitude in the right anterior region of the brain than the Landscape image and the Analogy image induced a stronger N600 effect in the left anterior and right anterior part of the brain than the Landscape image. However, the Simile image did not trigger the N600. The N600 was triggered when the meaning of the Metaphor and Analogy being presented could not be understood. This indicates that a greater processing effort to comprehend them than was required for Simile. Analogy has a wider N600 distribution than Metaphor in the anterior area, suggesting that Analogy would require higher-level thinking processes and more complex semantic processing mechanisms than Metaphor. CONCLUSIONS: The N600 implicated that an assessment method to detect the semantic relationship between appearance and function of a product would assist in determining whether a symbol was suitable to be associated with a product.


Assuntos
Mapeamento Encefálico , Semântica , Encéfalo/diagnóstico por imagem , Compreensão , Eletroencefalografia , Potenciais Evocados , Humanos , Metáfora
4.
Sensors (Basel) ; 21(17)2021 Aug 29.
Artigo em Inglês | MEDLINE | ID: mdl-34502710

RESUMO

Autism spectrum disorder (ASD) is a neurodegenerative disorder characterized by lingual and social disabilities. The autism diagnostic observation schedule is the current gold standard for ASD diagnosis. Developing objective computer aided technologies for ASD diagnosis with the utilization of brain imaging modalities and machine learning is one of main tracks in current studies to understand autism. Task-based fMRI demonstrates the functional activation in the brain by measuring blood oxygen level-dependent (BOLD) variations in response to certain tasks. It is believed to hold discriminant features for autism. A novel computer aided diagnosis (CAD) framework is proposed to classify 50 ASD and 50 typically developed toddlers with the adoption of CNN deep networks. The CAD system includes both local and global diagnosis in a response to speech task. Spatial dimensionality reduction with region of interest selection and clustering has been utilized. In addition, the proposed framework performs discriminant feature extraction with continuous wavelet transform. Local diagnosis on cingulate gyri, superior temporal gyrus, primary auditory cortex and angular gyrus achieves accuracies ranging between 71% and 80% with a four-fold cross validation technique. The fused global diagnosis achieves an accuracy of 86% with 82% sensitivity, 92% specificity. A brain map indicating ASD severity level for each brain area is created, which contributes to personalized diagnosis and treatment plans.


Assuntos
Transtorno do Espectro Autista , Imageamento por Ressonância Magnética , Transtorno do Espectro Autista/diagnóstico por imagem , Encéfalo/diagnóstico por imagem , Mapeamento Encefálico , Humanos , Análise de Ondaletas
5.
Nat Commun ; 12(1): 4816, 2021 08 10.
Artigo em Inglês | MEDLINE | ID: mdl-34376652

RESUMO

Remapping refers to a decorrelation of hippocampal representations of similar spatial environments. While it has been speculated that remapping may contribute to the resolution of episodic memory interference in humans, direct evidence is surprisingly limited. We tested this idea using high-resolution, pattern-based fMRI analyses. Here we show that activity patterns in human CA3/dentate gyrus exhibit an abrupt, temporally-specific decorrelation of highly similar memory representations that is precisely coupled with behavioral expressions of successful learning. The magnitude of this learning-related decorrelation was predicted by the amount of pattern overlap during initial stages of learning, with greater initial overlap leading to stronger decorrelation. Finally, we show that remapped activity patterns carry relatively more information about learned episodic associations compared to competing associations, further validating the learning-related significance of remapping. Collectively, these findings establish a critical link between hippocampal remapping and episodic memory interference and provide insight into why remapping occurs.


Assuntos
Potenciais de Ação/fisiologia , Região CA3 Hipocampal/fisiologia , Giro Denteado/fisiologia , Aprendizagem/fisiologia , Memória/fisiologia , Adolescente , Adulto , Mapeamento Encefálico/métodos , Região CA3 Hipocampal/diagnóstico por imagem , Giro Denteado/diagnóstico por imagem , Feminino , Humanos , Imageamento por Ressonância Magnética/métodos , Masculino , Estimulação Luminosa/métodos , Adulto Jovem
6.
Nat Commun ; 12(1): 4830, 2021 08 10.
Artigo em Inglês | MEDLINE | ID: mdl-34376663

RESUMO

Choice-relevant brain regions in prefrontal cortex may progressively transform information about options into choices. Here, we examine responses of neurons in four regions of the medial prefrontal cortex as macaques performed two-option risky choices. All four regions encode economic variables in similar proportions and show similar putative signatures of key choice-related computations. We provide evidence to support a gradient of function that proceeds from areas 14 to 25 to 32 to 24. Specifically, we show that decodability of twelve distinct task variables increases along that path, consistent with the idea that regions that are higher in the anatomical hierarchy make choice-relevant variables more separable. We also show progressively longer intrinsic timescales in the same series. Together these results highlight the importance of the medial wall in choice, endorse a specific gradient-based organization, and argue against a modular functional neuroanatomy of choice.


Assuntos
Comportamento de Escolha/fisiologia , Macaca mulatta/fisiologia , Neurônios/fisiologia , Córtex Pré-Frontal/fisiologia , Potenciais de Ação/fisiologia , Algoritmos , Animais , Encéfalo/diagnóstico por imagem , Encéfalo/fisiologia , Mapeamento Encefálico , Imageamento por Ressonância Magnética/métodos , Modelos Neurológicos , Córtex Pré-Frontal/citologia
7.
J Neural Eng ; 18(4)2021 08 02.
Artigo em Inglês | MEDLINE | ID: mdl-34342270

RESUMO

Objective. Electroencephalography (EEG) cleaning has been a longstanding issue in the research community. In recent times, huge leaps have been made in the field, resulting in very promising techniques to address the issue. The most widespread ones rely on a family of mathematical methods known as blind source separation (BSS), ideally capable of separating artefactual signals from the brain originated ones. However, corruption of EEG data still remains a problem, especially in real life scenario where a mixture of artefact components affects the signal and thus correctly choosing the correct cleaning procedure can be non trivial. Our aim is here to evaluate and score the plethora of available BSS-based cleaning methods, providing an overview of their advantages and downsides and of their best field of application.Approach. To address this, we here first characterized and modeled different types of artefact, i.e. arising from muscular or blinking activity as well as from transcranial alternate current stimulation. We then tested and scored several BSS-based cleaning procedures on semi-synthetic datasets corrupted by the previously modeled noise sources. Finally, we built a lifelike dataset affected by many artefactual components. We tested an iterative multistep approach combining different BSS steps, aimed at sequentially removing each specific artefactual component.Main results. We did not find an overall best method, as different scenarios require different approaches. We therefore provided an overview of the performance in terms of both reconstruction accuracy and computational burden of each method in different use cases.Significance. Our work provides insightful guidelines for signal cleaning procedures in the EEG related field.


Assuntos
Algoritmos , Artefatos , Encéfalo , Mapeamento Encefálico , Eletroencefalografia , Processamento de Sinais Assistido por Computador
8.
Childs Nerv Syst ; 37(9): 2787-2797, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-34355257

RESUMO

PURPOSE: Diaschisis of cerebrocerebellar loops contributes to cognitive and motor deficits in pediatric cerebellar brain tumor survivors. We used a cerebellar white matter atlas and hypothesized that lesion symptom mapping may reveal the critical lesions of cerebellar tracts. METHODS: We examined 31 long-term survivors of pediatric posterior fossa tumors (13 pilocytic astrocytoma, 18 medulloblastoma). Patients underwent neuronal imaging, examination for ataxia, fine motor and cognitive function, planning abilities, and executive function. Individual consolidated cerebellar lesions were drawn manually onto patients' individual MRI and normalized into Montreal Neurologic Institute (MNI) space for further analysis with voxel-based lesion symptom mapping. RESULTS: Lesion symptom mapping linked deficits of motor function to the superior cerebellar peduncle (SCP), deep cerebellar nuclei (interposed nucleus (IN), fastigial nucleus (FN), ventromedial dentate nucleus (DN)), and inferior vermis (VIIIa, VIIIb, IX, X). Statistical maps of deficits of intelligence and executive function mapped with minor variations to the same cerebellar structures. CONCLUSION: We identified lesions to the SCP next to deep cerebellar nuclei as critical for limiting both motor and cognitive function in pediatric cerebellar tumor survivors. Future strategies safeguarding motor and cognitive function will have to identify patients preoperatively at risk for damage to these critical structures and adapt multimodal therapeutic options accordingly.


Assuntos
Neoplasias Cerebelares , Meduloblastoma , Substância Branca , Mapeamento Encefálico , Neoplasias Cerebelares/diagnóstico por imagem , Cerebelo/diagnóstico por imagem , Criança , Cognição , Humanos , Meduloblastoma/complicações , Meduloblastoma/diagnóstico por imagem , Sobreviventes , Substância Branca/diagnóstico por imagem
9.
Nat Commun ; 12(1): 5181, 2021 08 30.
Artigo em Inglês | MEDLINE | ID: mdl-34462435

RESUMO

Functional magnetic resonance imaging (fMRI) has become an indispensable tool for investigating the human brain. However, the inherently poor signal-to-noise-ratio (SNR) of the fMRI measurement represents a major barrier to expanding its spatiotemporal scale as well as its utility and ultimate impact. Here we introduce a denoising technique that selectively suppresses the thermal noise contribution to the fMRI experiment. Using 7-Tesla, high-resolution human brain data, we demonstrate improvements in key metrics of functional mapping (temporal-SNR, the detection and reproducibility of stimulus-induced signal changes, and accuracy of functional maps) while leaving the amplitude of the stimulus-induced signal changes, spatial precision, and functional point-spread-function unaltered. We demonstrate that the method enables the acquisition of ultrahigh resolution (0.5 mm isotropic) functional maps but is also equally beneficial for a large variety of fMRI applications, including supra-millimeter resolution 3- and 7-Tesla data obtained over different cortical regions with different stimulation/task paradigms and acquisition strategies.


Assuntos
Mapeamento Encefálico/métodos , Encéfalo/diagnóstico por imagem , Imageamento por Ressonância Magnética/métodos , Adulto , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Masculino
11.
Nat Commun ; 12(1): 4714, 2021 08 05.
Artigo em Inglês | MEDLINE | ID: mdl-34354071

RESUMO

Although the contents of working memory can be decoded from visual cortex activity, these representations may play a limited role if they are not robust to distraction. We used model-based fMRI to estimate the impact of distracting visual tasks on working memory representations in several visual field maps in visual and frontoparietal association cortex. Here, we show distraction causes the fidelity of working memory representations to briefly dip when both the memorandum and distractor are jointly encoded by the population activities. Distraction induces small biases in memory errors which can be predicted by biases in neural decoding in early visual cortex, but not other regions. Although distraction briefly disrupts working memory representations, the widespread redundancy with which working memory information is encoded may protect against catastrophic loss. In early visual cortex, the neural representation of information in working memory and behavioral performance are intertwined, solidifying its importance in visual memory.


Assuntos
Memória de Curto Prazo/fisiologia , Córtex Visual/fisiologia , Adulto , Atenção/fisiologia , Mapeamento Encefálico , Feminino , Neuroimagem Funcional , Humanos , Imageamento por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Modelos Neurológicos , Modelos Psicológicos , Estimulação Luminosa , Análise e Desempenho de Tarefas
12.
Neuroscience ; 472: 60-67, 2021 09 15.
Artigo em Inglês | MEDLINE | ID: mdl-34363870

RESUMO

Psychological resilience is always portrayed as the ability to rebound from adversity, which is essential for human mental health. Whereas thought control ability (TCA) is a reliable indicator of perceptual cognitive control and has a predictive effect on psychopathology. Whether and how resilience correlates with thought control are still unclear. The current study explored the whole-brain functional connectivity underlying resilience and its role in the association between resilience and TCA using resting-state fMRI. Results reveled a significant positive correlation between resilience and the functional connectivity of temporal cortex-insula, suggesting that individuals with high resilient ability exhibit flexible interaction between these two regions to facilitate emotional information processing. More importantly, a significant positive correlation between TCA and resilience was observed, and the functional connectivity of temporal cortex-insula has a significant mediation effect on the association between TCA and psychological resilience, revealing that individuals with high TCA show high levels of resilience ability through robust cognitive control on unwanted thoughts. In short, these results extended previous findings by shedding novel insights into the close relationship between resilience and TCA and the underlying neural mechanism.


Assuntos
Mapeamento Encefálico , Córtex Cerebral , Encéfalo , Córtex Cerebral/diagnóstico por imagem , Humanos , Imageamento por Ressonância Magnética , Lobo Temporal
13.
Artigo em Inglês | MEDLINE | ID: mdl-34398758

RESUMO

Mental disorders are a major source of disability, with few effective treatments. It has recently been argued that these diseases might be effectively treated by focusing on decision-making, and specifically remediating decision-making deficits that act as "ingredients" in these disorders. Prior work showed that direct electrical brain stimulation can enhance human cognitive control, and consequently decision-making. This raises a challenge of detecting cognitive control lapses directly from electrical brain activity. Here, we demonstrate approaches to overcome that challenge. We propose a novel method, referred to as maximal variance node merging (MVNM), that merges nodes within a brain region to construct informative inter-region brain networks. We employ this method to estimate functional (correlational) and effective (causal) networks using local field potentials (LFP) during a cognitive behavioral task. The effective networks computed using convergent cross mapping differentiate task engagement from background neural activity with 85% median classification accuracy. We also derive task engagement networks (TENs): networks that constitute the most discriminative inter-region connections. Subsequent graph analysis illustrates the crucial role of the dorsolateral prefrontal cortex (dlPFC) in task engagement, consistent with a widely accepted model for cognition. We also show that task engagement is linked to prefrontal cortex theta (4-8 Hz) oscillations. We, therefore, identify objective biomarkers associated with task engagement. These approaches may generalize to other cognitive functions, forming the basis of a network-based approach to detecting and rectifying decision deficits.


Assuntos
Encéfalo , Cognição , Mapeamento Encefálico , Humanos , Imageamento por Ressonância Magnética , Córtex Pré-Frontal
14.
Cogn Process ; 22(Suppl 1): 115-120, 2021 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-34448969

RESUMO

People in developed countries spend over 90% of their time in built environments. Yet, we know little about its pervasive and often hidden effects on our mental state and our brain. Despite growing interest in the neuroscience of architecture, much of this scholarship has been descriptive. The typical approach is to map knowledge of the brain onto constructs important to architecture. For a programmatic line of research, how might descriptive neuroarchitecture be transformed into an experimental science? We review the literature outlining how one might consider experimental architecture first by examining the role of natural features in architectural settings. We then turn to the human experience of occupants, and hypothesized that aesthetic responses to architectural interiors reduce to key psychological dimensions. Conducting Psychometric Network Analysis (PNA) and Principal Components Analysis (PCA) on responses to curated images, we identified three components: coherence (ease of organizing and comprehending a scene), fascination (informational richness and generated interest), and hominess (personal ease and comfort). Coherence and fascination are well-established dimensions for natural scenes. Hominess was a new dimension related to architectural interiors. Central to all three communities in the PNA was emotional valence. We also reanalyzed data from an earlier fMRI study in which participants made beauty and approach-avoidance decisions while viewing the same images. Regardless of task, the degree of fascination covaried with neural activity in the right lingual gyrus. In contrast, coherence covaried with neural activity in the left inferior occipital gyrus only when participants judged beauty, and hominess covaried with neural activity in the left cuneus only when they made approach-avoidance decisions. The visual brain harbours hidden sensitivities to architectural interiors that are captured by the dimensions of coherence, fascination, and hominess. These findings represent first steps towards an experimental neuroarchitecture.


Assuntos
Encéfalo , Imageamento por Ressonância Magnética , Beleza , Mapeamento Encefálico , Estética , Humanos
15.
Sensors (Basel) ; 21(16)2021 Aug 04.
Artigo em Inglês | MEDLINE | ID: mdl-34450699

RESUMO

The functional connectivity (FC) patterns of resting-state functional magnetic resonance imaging (rs-fMRI) play an essential role in the development of autism spectrum disorders (ASD) classification models. There are available methods in literature that have used FC patterns as inputs for binary classification models, but the results barely reach an accuracy of 80%. Additionally, the generalizability across multiple sites of the models has not been investigated. Due to the lack of ASD subtypes identification model, the multi-class classification is proposed in the present study. This study aims to develop automated identification of autism spectrum disorder (ASD) subtypes using convolutional neural networks (CNN) using dynamic FC as its inputs. The rs-fMRI dataset used in this study consists of 144 individuals from 8 independent sites, labeled based on three ASD subtypes, namely autistic disorder (ASD), Asperger's disorder (APD), and pervasive developmental disorder not otherwise specified (PDD-NOS). The blood-oxygen-level-dependent (BOLD) signals from 116 brain nodes of automated anatomical labeling (AAL) atlas are used, where the top-ranked node is determined based on one-way analysis of variance (ANOVA) of the power spectral density (PSD) values. Based on the statistical analysis of the PSD values of 3-level ASD and normal control (NC), putamen_R is obtained as the top-ranked node and used for the wavelet coherence computation. With good resolution in time and frequency domain, scalograms of wavelet coherence between the top-ranked node and the rest of the nodes are used as dynamic FC feature input to the convolutional neural networks (CNN). The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. Results of binary classification (ASD vs. NC) and multi-class classification (ASD vs. APD vs. PDD-NOS vs. NC) yielded, respectively, 89.8% accuracy and 82.1% macro-average accuracy, respectively. Findings from this study have illustrated the good potential of wavelet coherence technique in representing dynamic FC between brain nodes and open possibilities for its application in computer aided diagnosis of other neuropsychiatric disorders, such as depression or schizophrenia.


Assuntos
Transtorno do Espectro Autista , Transtorno Autístico , Transtorno do Espectro Autista/diagnóstico por imagem , Transtorno Autístico/diagnóstico por imagem , Encéfalo/diagnóstico por imagem , Mapeamento Encefálico , Humanos , Imageamento por Ressonância Magnética , Redes Neurais de Computação
16.
Neuropsychologia ; 160: 107982, 2021 09 17.
Artigo em Inglês | MEDLINE | ID: mdl-34364903

RESUMO

Cerebral visual impairment (CVI) often presents with deficits associated with higher order visual processing. We report a case of an individual with CVI who uses a verbal mediation strategy to perceive and interact with his visual surroundings. Visual perceptual performance was assessed using a virtual reality based visual search task combined with eye tracking. Functional magnetic resonance imaging (fMRI) was employed to identify the neural correlates associated with this strategy. We found that when using verbal mediation, the individual could readily detect and track the target within the visual scene which was associated with robust activation within a network of occipito-parieto-temporal visual cortical areas. In contrast, when not using verbal mediation, the individual was completely unable to perform the task, and this was associated with dramatically reduced visual cortical activation. This unique compensatory strategy may be related to the individual's use of verbal working memory for the purposes of understanding complex visual information.


Assuntos
Memória de Curto Prazo , Percepção Visual , Adolescente , Mapeamento Encefálico , Cognição , Humanos , Imageamento por Ressonância Magnética , Masculino , Transtornos da Visão
17.
Artigo em Russo | MEDLINE | ID: mdl-34460167

RESUMO

The review of publications on functional magnetic resonance imaging (fMRI) and its practical application in neurosurgery is presented. Advantages and disadvantages are selected taking pathogenesis into account. Results of surgical treatment with use of functional navigation are described. Separate attention is paid to fMRI precision by its comparing with direct cortical stimulation. New resting-state method of visualization is observed. Practical advices are given of fMRI application in neurooncology and surgery of arteriovenous malformations.


Assuntos
Neurocirurgia , Mapeamento Encefálico , Humanos , Imageamento por Ressonância Magnética , Procedimentos Neurocirúrgicos
18.
Commun Biol ; 4(1): 954, 2021 08 10.
Artigo em Inglês | MEDLINE | ID: mdl-34376799

RESUMO

Longitudinal menstrual cycle studies allow to investigate the effects of ovarian hormones on brain organization. Here, we use spectral dynamic causal modelling (spDCM) in a triple network model to assess effective connectivity changes along the menstrual cycle within and between the default mode, salience and executive control networks (DMN, SN, and ECN). Sixty healthy young women were scanned three times along their menstrual cycle, during early follicular, pre-ovulatory and mid-luteal phase. Related to estradiol, right before ovulation the left insula recruits the ECN, while the right middle frontal gyrus decreases its connectivity to the precuneus and the DMN decouples into anterior/posterior parts. Related to progesterone during the mid-luteal phase, the insulae (SN) engage to each other, while decreasing their connectivity to parietal ECN, which in turn engages the posterior DMN. When including the most confident connections in a leave-one out cross-validation, we find an above-chance prediction of the left-out subjects' cycle phase. These findings corroborate the plasticity of the female brain in response to acute hormone fluctuations and may help to further understand the neuroendocrine interactions underlying cognitive changes along the menstrual cycle.


Assuntos
Estradiol/metabolismo , Ciclo Menstrual/fisiologia , Vias Neurais/fisiologia , Progesterona/metabolismo , Adulto , Mapeamento Encefálico , Feminino , Humanos , Adulto Jovem
19.
Nature ; 597(7874): 39-40, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-34381223
20.
Neuropsychologia ; 160: 107978, 2021 09 17.
Artigo em Inglês | MEDLINE | ID: mdl-34339716

RESUMO

Self-compassion is an important emotion regulation strategy predicting positive psychological health and fewer psychopathological problems, but little is known about its structural neural basis. In the current study, we investigated the neurostructural correlates of dispositional self-compassion and its components using voxel-based morphometry (VBM). We found that self-compassion was inversely correlated with gray matter volume (GMV) in the left dorsolateral prefrontal cortex (DLPFC), which was primarily driven by the reduced self-judgment component. We also found that the mindfulness component was associated with greater GMV in the dorsomedial prefrontal cortex/anterior cingulate cortex and the left supplementary motor area, while the isolation and the over-identification components were both correlated with greater GMV in the right inferior temporal gyrus, and over-identification additionally related to less GMV in visual areas. Our findings suggest that dispositional self-compassion and its components are associated with brain structure in regions involved in emotion regulation, self-referential and emotion processing, with implications for the cognitive and neural mechanisms of self-compassion as well as those underlying the effects of self-compassion on its health outcomes.


Assuntos
Empatia , Imageamento por Ressonância Magnética , Encéfalo/diagnóstico por imagem , Mapeamento Encefálico , Substância Cinzenta/diagnóstico por imagem , Humanos
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