RESUMO
BACKGROUND AND HYPOTHESIS: Impaired speech-gesture matching has repeatedly been shown in patients with schizophrenia spectrum disorders. Here, we tested the hypothesis that schizotypal traits in the general population are related to reduced speech-gesture matching performance and reduced self-reports about gesture perception. We further explored the relationships between facets of schizotypy and gesture processing in a network model. STUDY DESIGN: Participants (1094 mainly healthy adults) were presented with concrete or abstract sentences accompanied with videos showing related or unrelated gestures. For each video, participants evaluated the alignment between speech and gesture. They also completed self-rating scales about the perception and production of gestures (Brief Assessment of Gesture scale) and schizotypal traits (Schizotypal Personality Questionnaire-Brief 22-item version). We analyzed bivariate associations and estimated a non-regularized partial Spearman correlation network. We characterized the network by analyzing bridge centrality and controllability metrics of nodes. STUDY RESULTS: We found a negative relationship between both concrete and abstract gesture-speech matching performance and overall schizotypy. In the network, disorganization had the highest average controllability and it was negatively related to abstract speech-gesture matching. Bridge centralities indicated that self-reported production of gestures to enhance communication in social interactions connects self-reported gesture perception, schizotypal traits, and gesture processing task performance. CONCLUSION: The association between impaired abstract speech-gesture matching and disorganization supports a continuum between schizophrenia and schizotypy. Using gestures to facilitate communication connects subjective and objective aspects of gesture processing and schizotypal traits. Future interventional studies in patients should test the potential causal pathways implied by this network model.
RESUMO
Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.
Assuntos
Transtorno Bipolar , Imageamento por Ressonância Magnética , Obesidade , Análise de Componente Principal , Humanos , Transtorno Bipolar/diagnóstico por imagem , Transtorno Bipolar/tratamento farmacológico , Transtorno Bipolar/patologia , Adulto , Feminino , Masculino , Imageamento por Ressonância Magnética/métodos , Pessoa de Meia-Idade , Obesidade/diagnóstico por imagem , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/patologia , Esquizofrenia/tratamento farmacológico , Esquizofrenia/fisiopatologia , Córtex Cerebral/diagnóstico por imagem , Córtex Cerebral/patologia , Análise por Conglomerados , Adulto Jovem , Encéfalo/diagnóstico por imagem , Encéfalo/patologiaRESUMO
Music and ketamine are both known to affect therapeutic outcomes, but few studies have investigated their co-administration. This scoping review describes the existing literature on the joint use of music and ketamine-or esketamine (the S(+) enantiomer of ketamine)-in humans. The review considers that extant studies have explored the intersection of ketamine/esketamine and music in healthy volunteers and in patients of various age groups, at different dosages, through different treatment processes, and have varied the sequence of playing music relative to ketamine/esketamine administration. Studies investigating the use of music during ketamine anesthesia are also included in the review because anesthesia and sedation were the early drivers of ketamine use. Studies pertaining to recreational ketamine use were omitted. The review was limited to articles published in the English language but not restricted by publication year. To the best of our knowledge, this scoping review is the first comprehensive exploration of the interplay between music and ketamine/esketamine and offers valuable insights to researchers interested in designing future studies.
Assuntos
Ketamina , Musicoterapia , Humanos , Anestésicos Dissociativos/administração & dosagem , Anestésicos Dissociativos/uso terapêutico , Ketamina/administração & dosagem , Ketamina/uso terapêutico , Depressão/tratamento farmacológico , Depressão/terapia , Manejo da DorRESUMO
Reduced processing speed is a core deficit in major depressive disorder (MDD) and has been linked to altered structural brain network connectivity. Ample evidence highlights the involvement of genetic-immunological processes in MDD and specific depressive symptoms. Here, we extended these findings by examining associations between polygenic scores for tumor necrosis factor-α blood levels (TNF-α PGS), structural brain connectivity, and processing speed in a large sample of MDD patients. Processing speed performance of n = 284 acutely depressed, n = 177 partially and n = 198 fully remitted patients, and n = 743 healthy controls (HC) was estimated based on five neuropsychological tests. Network-based statistic was used to identify a brain network associated with processing speed. We employed general linear models to examine the association between TNF-α PGS and processing speed. We investigated whether network connectivity mediates the association between TNF-α PGS and processing speed. We identified a structural network positively associated with processing speed in the whole sample. We observed a significant negative association between TNF-α PGS and processing speed in acutely depressed patients, whereas no association was found in remitted patients and HC. The mediation analysis revealed that brain connectivity partially mediated the association between TNF-α PGS and processing speed in acute MDD. The present study provides evidence that TNF-α PGS is associated with decreased processing speed exclusively in patients with acute depression. This association was partially mediated by structural brain connectivity. Using multimodal data, the current findings advance our understanding of cognitive dysfunction in MDD and highlight the involvement of genetic-immunological processes in its pathomechanisms.
RESUMO
BACKGROUND: Depressive symptoms seem to be interrelated in a complex and self-reinforcing way. To gain a better understanding of this complexity, the inclusion of theoretically relevant constructs (such as risk and protective factors) offers a comprehensive view into the complex mechanisms underlying depression. METHODS: Cross-sectional data from individuals diagnosed with a major depressive disorder (N = 986) and healthy controls (N = 1049) were analyzed. Participants self-reported their depressive symptoms, as well as several risk factors and protective factors. Regularized partial correlation networks were estimated for each group and compared using a network comparison test. RESULTS: Symptoms of depression were more strongly connected in the network of depressed patients than in healthy controls. Among the risk factors, perceived stress, the experience of negative life events, emotional neglect, and emotional abuse were the most centrally embedded in both networks. However, the centrality of risk factors did not significantly differ between the two groups. Among the protective factors, social support, personal competence, and acceptance were the most central in both networks, where the latter was significantly more strongly associated with the symptom of self-hate in depressed patients. CONCLUSION: The network analysis revealed that key symptoms of depression were more strongly connected for depressed patients than for healthy controls, and that risk and protective factors play an important role, particularly perceived stress in both groups and an accepting attitude for depressed patients. However, the purpose of this study is hypothesis generating and assisting in the potential selection of non-symptom nodes for future research.
Assuntos
Depressão , Transtorno Depressivo Maior , Humanos , Depressão/etiologia , Transtorno Depressivo Maior/epidemiologia , Fatores de Proteção , Estudos Transversais , AutorrelatoRESUMO
Patients with bipolar disorder (BD) show alterations in both gray matter volume (GMV) and white matter (WM) integrity compared with healthy controls (HC). However, it remains unclear whether the phenotypically distinct BD subtypes (BD-I and BD-II) also exhibit brain structural differences. This study investigated GMV and WM differences between HC, BD-I, and BD-II, along with clinical and genetic associations. N = 73 BD-I, n = 63 BD-II patients and n = 136 matched HC were included. Using voxel-based morphometry and tract-based spatial statistics, main effects of group in GMV and fractional anisotropy (FA) were analyzed. Associations between clinical and genetic features and GMV or FA were calculated using regression models. For FA but not GMV, we found significant differences between groups. BD-I patients showed lower FA compared with BD-II patients (ptfce-FWE = 0.006), primarily in the anterior corpus callosum. Compared with HC, BD-I patients exhibited lower FA in widespread clusters (ptfce-FWE < 0.001), including almost all major projection, association, and commissural fiber tracts. BD-II patients also demonstrated lower FA compared with HC, although less pronounced (ptfce-FWE = 0.049). The results remained unchanged after controlling for clinical and genetic features, for which no independent associations with FA or GMV emerged. Our findings suggest that, at a neurobiological level, BD subtypes may reflect distinct degrees of disease expression, with increasing WM microstructure disruption from BD-II to BD-I. This differential magnitude of microstructural alterations was not clearly linked to clinical and genetic variables. These findings should be considered when discussing the classification of BD subtypes within the spectrum of affective disorders.
Assuntos
Transtorno Bipolar , Substância Branca , Humanos , Transtorno Bipolar/diagnóstico por imagem , Transtorno Bipolar/genética , Substância Cinzenta/diagnóstico por imagem , Encéfalo , Substância Branca/diagnóstico por imagem , Córtex Cerebral , AnisotropiaRESUMO
Importance: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative biomarkers have been identified. Objective: To evaluate whether machine learning (ML) can identify a multivariate biomarker for MDD. Design, Setting, and Participants: This study used data from the Marburg-Münster Affective Disorders Cohort Study, a case-control clinical neuroimaging study. Patients with acute or lifetime MDD and healthy controls aged 18 to 65 years were recruited from primary care and the general population in Münster and Marburg, Germany, from September 11, 2014, to September 26, 2018. The Münster Neuroimaging Cohort (MNC) was used as an independent partial replication sample. Data were analyzed from April 2022 to June 2023. Exposure: Patients with MDD and healthy controls. Main Outcome and Measure: Diagnostic classification accuracy was quantified on an individual level using an extensive ML-based multivariate approach across a comprehensive range of neuroimaging modalities, including structural and functional magnetic resonance imaging and diffusion tensor imaging as well as a polygenic risk score for depression. Results: Of 1801 included participants, 1162 (64.5%) were female, and the mean (SD) age was 36.1 (13.1) years. There were a total of 856 patients with MDD (47.5%) and 945 healthy controls (52.5%). The MNC replication sample included 1198 individuals (362 with MDD [30.1%] and 836 healthy controls [69.9%]). Training and testing a total of 4 million ML models, mean (SD) accuracies for diagnostic classification ranged between 48.1% (3.6%) and 62.0% (4.8%). Integrating neuroimaging modalities and stratifying individuals based on age, sex, treatment, or remission status does not enhance model performance. Findings were replicated within study sites and also observed in structural magnetic resonance imaging within MNC. Under simulated conditions of perfect reliability, performance did not significantly improve. Analyzing model errors suggests that symptom severity could be a potential focus for identifying MDD subgroups. Conclusion and Relevance: Despite the improved predictive capability of multivariate compared with univariate neuroimaging markers, no informative individual-level MDD biomarker-even under extensive ML optimization in a large sample of diagnosed patients-could be identified.
Assuntos
Transtorno Depressivo Maior , Humanos , Feminino , Masculino , Transtorno Depressivo Maior/diagnóstico por imagem , Transtorno Depressivo Maior/patologia , Imagem de Tensor de Difusão , Estudos de Coortes , Reprodutibilidade dos Testes , Imageamento por Ressonância Magnética , BiomarcadoresRESUMO
Background: Controllability is a measure of the brain's ability to orchestrate neural activity which can be quantified in terms of properties of the brain's network connectivity. Evidence from the literature suggests that aging can exert a general effect on whole-brain controllability. Mounting evidence, on the other hand, suggests that parenthood and motherhood in particular lead to long-lasting changes in brain architecture that effectively slow down brain aging. We hypothesize that parenthood might preserve brain controllability properties from aging. Methods: In a sample of 814 healthy individuals (aged 33.9 ± 12.7 years, 522 females), we estimate whole-brain controllability and compare the aging effects in subjects with vs. those without children. We use diffusion tensor imaging (DTI) to estimate the brain structural connectome. The level of brain control is then calculated from the connectomic properties of the brain structure. Specifically, we measure the network control over many low-energy state transitions (average controllability) and the network control over difficult-to-reach states (modal controllability). Results and conclusion: In nulliparous females, whole-brain average controllability increases, and modal controllability decreases with age, a trend that we do not observe in parous females. Statistical comparison of the controllability metrics shows that modal controllability is higher and average controllability is lower in parous females compared to nulliparous females. In men, we observed the same trend, but the difference between nulliparous and parous males do not reach statistical significance. Our results provide strong evidence that parenthood contradicts aging effects on brain controllability and the effect is stronger in mothers.
RESUMO
Up to 70% of patients with major depressive disorder present with psychomotor disturbance (PmD), but at the present time understanding of its pathophysiology is limited. In this study, we capitalized on a large sample of patients to examine the neural correlates of PmD in depression. This study included 820 healthy participants and 699 patients with remitted (n = 402) or current (n = 297) depression. Patients were further categorized as having psychomotor retardation, agitation, or no PmD. We compared resting-state functional connectivity (ROI-to-ROI) between nodes of the cerebral motor network between the groups, including primary motor cortex, supplementary motor area, sensory cortex, superior parietal lobe, caudate, putamen, pallidum, thalamus, and cerebellum. Additionally, we examined network topology of the motor network using graph theory. Among the currently depressed 55% had PmD (15% agitation, 29% retardation, and 11% concurrent agitation and retardation), while 16% of the remitted patients had PmD (8% retardation and 8% agitation). When compared with controls, currently depressed patients with PmD showed higher thalamo-cortical and pallido-cortical connectivity, but no network topology alterations. Currently depressed patients with retardation only had higher thalamo-cortical connectivity, while those with agitation had predominant higher pallido-cortical connectivity. Currently depressed patients without PmD showed higher thalamo-cortical, pallido-cortical, and cortico-cortical connectivity, as well as altered network topology compared to healthy controls. Remitted patients with PmD showed no differences in single connections but altered network topology, while remitted patients without PmD did not differ from healthy controls in any measure. We found evidence for compensatory increased cortico-cortical resting-state functional connectivity that may prevent psychomotor disturbance in current depression, but may perturb network topology. Agitation and retardation show specific connectivity signatures. Motor network topology is slightly altered in remitted patients arguing for persistent changes in depression. These alterations in functional connectivity may be addressed with non-invasive brain stimulation.
RESUMO
Childhood maltreatment (CM) has been associated with changes in structural brain connectivity even in the absence of mental illness. Social support, an important protective factor in the presence of childhood maltreatment, has been positively linked to white matter integrity. However, the shared effects of current social support and CM and their association with structural connectivity remain to be investigated. They might shed new light on the neurobiological basis of the protective mechanism of social support. Using connectome-based predictive modeling (CPM), we analyzed structural connectomes of N = 904 healthy adults derived from diffusion-weighted imaging. CPM predicts phenotypes from structural connectivity through a cross-validation scheme. Distinct and shared networks of white matter tracts predicting childhood trauma questionnaire scores and the social support questionnaire were identified. Additional analyses were applied to assess the stability of the results. CM and social support were predicted significantly from structural connectome data (all rs ≥ 0.119, all ps ≤ 0.016). Edges predicting CM and social support were inversely correlated, i.e., positively correlated with CM and negatively with social support, and vice versa, with a focus on frontal and temporal regions including the insula and superior temporal lobe. CPM reveals the predictive value of the structural connectome for CM and current social support. Both constructs are inversely associated with connectivity strength in several brain tracts. While this underlines the interconnectedness of these experiences, it suggests social support acts as a protective factor following adverse childhood experiences, compensating for brain network alterations. Future longitudinal studies should focus on putative moderating mechanisms buffering these adverse experiences.
Assuntos
Maus-Tratos Infantis , Conectoma , Testes Psicológicos , Autorrelato , Substância Branca , Adulto , Humanos , Criança , Conectoma/métodos , Imageamento por Ressonância Magnética , EncéfaloRESUMO
Despite the growing deployment of network representation to comprehend psychological phenomena, the question of whether and how networks can effectively describe the effects of psychological interventions remains elusive. Network control theory, the engineering study of networked interventions, has recently emerged as a viable methodology to characterize and guide interventions. However, there is a scarcity of empirical studies testing the extent to which it can be useful within a psychological context. In this paper, we investigate a representative psychological intervention experiment, use network control theory to model the intervention and predict its effect. Using this data, we showed that: (1) the observed psychological effect, in terms of sensitivity and specificity, relates to the regional network control theoretic metrics (average and modal controllability), (2) the size of change following intervention negatively correlates with a whole-network topology that quantifies the "ease" of change as described by control theory (control energy), and (3) responses after intervention can be predicted based on formal results from control theory. These insights assert that network control theory has significant potential as a tool for investigating psychological interventions. Drawing on this specific example and the overarching framework of network control theory, we further elaborate on the conceptualization of psychological interventions, methodological considerations, and future directions in this burgeoning field.
Assuntos
Benchmarking , Intervenção Psicossocial , Formação de Conceito , Pesquisa Empírica , EngenhariaRESUMO
Syntax, the grammatical structure of sentences, is a fundamental aspect of language. It remains debated whether reduced syntactic complexity is unique to schizophrenia spectrum disorder (SSD) or whether it is also present in major depressive disorder (MDD). Furthermore, the association of syntax (including syntactic complexity and diversity) with language-related neuropsychology and psychopathological symptoms across disorders remains unclear. Thirty-four SSD patients and thirty-eight MDD patients diagnosed according to DSM-IV-TR as well as forty healthy controls (HC) were included and tasked with describing four pictures from the Thematic Apperception Test. We analyzed the produced speech regarding its syntax delineating measures for syntactic complexity (the total number of main clauses embedding subordinate clauses) and diversity (number of different types of complex sentences). We performed cluster analysis to identify clusters based on syntax and investigated associations of syntactic, to language-related neuropsychological (verbal fluency and verbal episodic memory), and psychopathological measures (positive and negative formal thought disorder) using network analyses. Syntax in SSD was significantly reduced in comparison to MDD and HC, whereas the comparison of HC and MDD revealed no significant differences. No associations were present between speech measures and current medication, duration and severity of illness, age or sex; the single association accounted for was education. A cluster analysis resulted in four clusters with different degrees of syntax across diagnoses. Subjects with less syntax exhibited pronounced positive and negative symptoms and displayed poorer performance in executive functioning, global functioning, and verbal episodic memory. All cluster-based networks indicated varying degrees of domain-specific and cross-domain connections. Measures of syntactic complexity were closely related while syntactic diversity appeared to be a separate node outside of the syntactic network. Cross-domain associations were more salient in more complex syntactic production.
RESUMO
BACKGROUND: Negative stressful life events and deprivation of social support play critical roles in the development and maintenance of major depressive disorder (MDD). The present study aimed to investigate in a large sample of patients with MDD and healthy control participants (HCs) whether these effects are also reflected in white matter (WM) integrity. METHODS: In this diffusion tensor imaging study, 793 patients with MDD and 793 age- and sex-matched HCs were drawn from the Marburg-Münster Affective Disorders Cohort Study (MACS) and completed the Life Events Questionnaire (LEQ) and Social Support Questionnaire (SSQ). Generalized linear models were performed to test voxelwise associations between fractional anisotropy (FA) and diagnosis (analysis 1), LEQ (analysis 2), and SSQ (analysis 3). We examined whether SSQ interacts with LEQ on FA or is independently associated with improved WM integrity (analysis 4). RESULTS: Patients with MDD showed lower FA in several frontotemporal association fibers compared with HCs (pTFCE-FWE = .028). Across both groups, LEQ correlated negatively with FA in widely distributed WM tracts (pTFCE-FWE = .023), while SSQ correlated positively with FA in the corpus callosum (pTFCE-FWE = .043). Modeling the combined association of both variables on FA revealed significant-and antagonistic-main effects of LEQ (pTFCE-FWE = .031) and SSQ (pTFCE-FWE = .037), but no interaction of SSQ × LEQ. CONCLUSIONS: Our results indicate that negative stressful life events and social support are both related to WM integrity in opposing directions. The associations did not differ between patients with MDD and HCs, suggesting more general, rather than depression-specific, mechanisms. Furthermore, social support appears to contribute to improved WM integrity independent of stressful life events.
Assuntos
Transtorno Depressivo Maior , Substância Branca , Humanos , Substância Branca/diagnóstico por imagem , Imagem de Tensor de Difusão , Transtorno Depressivo Maior/diagnóstico por imagem , Estudos de Coortes , Anisotropia , Apoio SocialRESUMO
Electroconvulsive Therapy (ECT) is arguably the most effective intervention for treatment-resistant depression. While large interindividual variability exists, a theory capable of explaining individual response to ECT remains elusive. To address this, we posit a quantitative, mechanistic framework of ECT response based on Network Control Theory (NCT). Then, we empirically test our approach and employ it to predict ECT treatment response. To this end, we derive a formal association between Postictal Suppression Index (PSI)-an ECT seizure quality index-and whole-brain modal and average controllability, NCT metrics based on white-matter brain network architecture, respectively. Exploiting the known association of ECT response and PSI, we then hypothesized an association between our controllability metrics and ECT response mediated by PSI. We formally tested this conjecture in N = 50 depressive patients undergoing ECT. We show that whole-brain controllability metrics based on pre-ECT structural connectome data predict ECT response in accordance with our hypotheses. In addition, we show the expected mediation effects via PSI. Importantly, our theoretically motivated metrics are at least on par with extensive machine learning models based on pre-ECT connectome data. In summary, we derived and tested a control-theoretic framework capable of predicting ECT response based on individual brain network architecture. It makes testable, quantitative predictions regarding individual therapeutic response, which are corroborated by strong empirical evidence. Our work might constitute a starting point for a comprehensive, quantitative theory of personalized ECT interventions rooted in control theory.
RESUMO
Many therapeutic interventions in psychiatry can be viewed as attempts to influence the brain's large-scale, dynamic network state transitions. Building on connectome-based graph analysis and control theory, Network Control Theory is emerging as a powerful tool to quantify network controllability-i.e., the influence of one brain region over others regarding dynamic network state transitions. If and how network controllability is related to mental health remains elusive. Here, from Diffusion Tensor Imaging data, we inferred structural connectivity and inferred calculated network controllability parameters to investigate their association with genetic and familial risk in patients diagnosed with major depressive disorder (MDD, n = 692) and healthy controls (n = 820). First, we establish that controllability measures differ between healthy controls and MDD patients while not varying with current symptom severity or remission status. Second, we show that controllability in MDD patients is associated with polygenic scores for MDD and psychiatric cross-disorder risk. Finally, we provide evidence that controllability varies with familial risk of MDD and bipolar disorder as well as with body mass index. In summary, we show that network controllability is related to genetic, individual, and familial risk in MDD patients. We discuss how these insights into individual variation of network controllability may inform mechanistic models of treatment response prediction and personalized intervention-design in mental health.
Assuntos
Conectoma , Transtorno Depressivo Maior , Humanos , Imagem de Tensor de Difusão , Predisposição Genética para Doença , Imageamento por Ressonância Magnética/métodos , EncéfaloRESUMO
Objective:Recent progress in network sciences has made it possible to apply key findings from control theory to the study of networks. Referred to as network control theory, this framework describes how the interactions between interconnected system elements and external energy sources, potentially constrained by different optimality criteria, result in complex network behavior. A typical example is the quantification of the functional role certain brain regions or symptoms play in shaping the temporal dynamics of brain activity or the clinical course of a disease, a property that is quantified in terms of the so-called controllability metrics. Critically though, contrary to the engineering context in which control theory was originally developed, a mathematical understanding of the network nodes and connections in neurosciences cannot be assumed. For instance, in the case of psychological systems such as those studied to understand psychiatric disorders, a potentially large set of related variables are unknown. As such, while the measures offered by network control theory would be mathematically correct, in that they can be calculated with high precision, they could have little translational values with respect to their putative role suggested by controllability metrics. It is therefore critical to understand if and how the controllability metrics estimated over subnetworks would deviate, if access to the complete set of variables, as is common in neurosciences, cannot be taken for granted.Approach:In this paper, we use a host of simulations based on synthetic as well as structural magnetic resonance imaging (MRI) data to study the potential deviation of controllability metrics in sub- compared to the full networks. Specifically, we estimate average- and modal-controllability, two of the most widely used controllability measures in neurosciences, in a large number of settings where we systematically vary network type, network size, and edge density.Main results:We find out, across all network types we test, that average and modal controllability are systematically, over- or underestimated depending on the number of nodes in the sub- and full network and the edge density.Significance:Finally, we provide formal theoretical proof that our observations generalize to any network type and discuss the ramifications of this systematic bias and potential solutions to alleviate the problem.
Assuntos
Encéfalo , Transtornos Mentais , Humanos , Imageamento por Ressonância MagnéticaRESUMO
Background: The basic functional organization of the resting brain, assessed as resting-state functional connectivity (rsFC), can be affected by previous stress experience and it represents the basis on which subsequent stress experience develops. Notably, the rsFC between the amygdala and the cortical regions associated with emotion regulation and anxiety are affected during stress. The multicomponent drug Neurexan® (Nx4) has previously demonstrated a reduction in amygdala activation in an emotional face matching task and it ameliorated stress-related symptoms. We, thus, investigated the effect of Nx4 on rsFC of the amygdala before stress induction compared with baseline in mildly to moderately stressed participants. Methods: In a randomized, placebo-controlled, double-blind, crossover trial 39 participants received a single dose of placebo or Nx4. Resting-state functional magnetic resonance imaging scans were performed pre-dose and 40 to 60 min post-dose, before any stress induction. First, highly connected functional hubs were identified by global functional connectivity density (gFCD) analysis. Second, by using a seed-based approach, rsFC maps of the left centromedial amygdala (CeMA) were created. The effect of Nx4 on both was evaluated. Results: The medial prefrontal cortex was identified as a relevant functional hub affected by Nx4 in an explorative whole brain gFCD analysis. Using the seed-based approach, we then demonstrated that Nx4 significantly enhanced the negative connectivity between the left CeMA and two cortical regions: the dorsolateral and medial prefrontal cortices. Conclusions: In a resting-state condition, Nx4 reduced the prefrontal cortex gFCD and strengthened the functional coupling between the amygdala and the prefrontal cortex that is relevant for emotion regulation and the stress response. Further studies should elaborate whether this mechanism represents enhanced regulatory control of the amygdala at rest and, consequently, to a diminished susceptibility to stress. ClinicalTrials.gov ID: NCT02602275.
Assuntos
Tonsila do Cerebelo , Encéfalo , Humanos , Estudos Cross-Over , Vias Neurais/fisiologia , Tonsila do Cerebelo/diagnóstico por imagem , Tonsila do Cerebelo/fisiologia , Córtex Pré-Frontal/diagnóstico por imagem , Córtex Pré-Frontal/fisiologia , Imageamento por Ressonância MagnéticaRESUMO
[This corrects the article DOI: 10.1016/j.ibneur.2021.09.002.].
RESUMO
Processing of sensory information is embedded into ongoing neural processes which contribute to brain states. Electroencephalographic microstates are semi-stable short-lived power distributions which have been associated with subsystem activity such as auditory, visual and attention networks. Here we explore changes in electrical brain states in response to an audiovisual perception and memorization task under conditions of auditory distraction. We discovered changes in brain microstates reflecting a weakening of states representing activity of the auditory system and strengthening of salience networks, supporting the idea that salience networks are active after audiovisual encoding and during memorization to protect memories and concentrate on upcoming behavioural response.
RESUMO
Background: Stress adversely affects the attentional focus, the active concentration on stimuli, and increases susceptibility to distraction. To experimentally explore the susceptibility to distraction, the Attention Modulation by Salience Task (AMST) is a validated paradigm measuring reaction times (RT) for processing auditory information while presenting task-irrelevant visual distractors of high or low salience. We extended the AMST by an emotional dimension of distractors and an EEG-based evaluation. We then investigated the effect of the stress-relieving medication Neurexan (Nx4) on the participants' susceptibility to distraction. Methods: Data from a randomized, placebo-controlled, crossover trial (NEURIM study; ClinicalTrials.gov: NCT02602275) were exploratively reanalyzed post-hoc. In this trial, 39 participants received a single dose of placebo or Nx4 immediately before the AMST. Participants had to discriminate two different tone modulations (ascending or descending) while simultaneously perceiving task-irrelevant pictures of different salience (high or low) or valence (negative or positive) as distractors. Using EEG recordings, RT and the event-related potential (ERP) components N1, N2, and N3 were analyzed as markers for susceptibility to distraction. Results: In the placebo condition, we could replicate the previously reported task effects of salient distractors with longer RT for high salient distractors on the behavioral level. On the electrophysiological level, we observed significantly increased amplitudes of the N2 and N3 ERP components for positive emotional pictures. In terms of drug effect, we found evidence that Nx4 reduced distractibility by emotional distractors. The effect was shown by significantly reduced amplitudes of N2 and N3 ERP components and reduced RT for the positive valence domain under Nx4 compared to placebo. The Nx4 effects on RT and ERP components also showed a significant correlation. Conclusion: Emotional distractors in addition to the previously used salience distractors and the EEG based evaluation of ERPs valuably complement the AMST. Salient distractors were affecting attentional processes earlier, while valent distractors show modulatory effects later. Our results suggest that Nx4 has beneficial effects on attention by inhibiting the effect of task-irrelevant information and reducing susceptibility to emotionally distracting stimuli. The observation of a beneficial impact of Nx4 on attention regulation is supportive of Nx4's claim as a stress-relieving medication.