Dynamic Causal Modeling Research Articles

Self-regulation learning as active inference: dynamic causal modeling of an fMRI neurofeedback task.

Learning to self-regulate brain activity by neurofeedback has been shown to lead to changes in the brain and behavior, with beneficial clinical and non-clinical outcomes. Neurofeedback uses a brain-computer interface to guide participants to change some feature of their brain activity. However, the neural mechanism of self-regulation learning remains unclear, with only 50% of the participants succeeding in achieving it. To bridge this knowledge gap, our study delves into the neural mechanisms of self-regulation learning via neurofeedback and investigates the brain processes associated with successful brain self-regulation. We study the neural underpinnings of self-regulation learning by employing dynamical causal modeling (DCM) in conjunction with real-time functional MRI data. The study involved a cohort of 18 participants undergoing neurofeedback training targeting the supplementary motor area. A critical focus was the comparison between top-down hierarchical connectivity models proposed by Active Inference and alternative bottom-up connectivity models like reinforcement learning. Our analysis revealed a crucial distinction in brain connectivity patterns between successful and non-successful learners. Particularly, successful learners evinced a significantly stronger top-down effective connectivity towards the target area implicated in self-regulation. This heightened top-down network engagement closely resembles the patterns observed in goal-oriented and cognitive control studies, shedding light on the intricate cognitive processes intertwined with self-regulation learning. The findings from our investigation underscore the significance of cognitive mechanisms in the process of self-regulation learning through neurofeedback. The observed stronger top-down effective connectivity in successful learners indicates the involvement of hierarchical cognitive control, which aligns with the tenets of Active Inference. This study contributes to a deeper understanding of the neural dynamics behind successful self-regulation learning and provides insights into the potential cognitive architecture underpinning this process.

Task-residual effective connectivity of motor network in transient ischemic attack

Transient ischemic attack (TIA) is a temporary episode of neurological dysfunction that results from focal brain ischemia. Although TIA symptoms are quickly resolved, patients with TIA have a high risk of stroke and persistent impairments in multiple domains of cognitive and motor functions. In this study, using spectral dynamic causal modeling, we investigate the changes in task-residual effective connectivity of patients with TIA during fist-closing movements. 28 healthy participants and 15 age-matched patients with TIA undergo functional magnetic resonance imaging at 7T. Here we show that during visually cued motor movement, patients with TIA have significantly higher effective connectivity toward the ipsilateral primary motor cortex and lower connectivity to the supplementary motor area than healthy controls. Our results imply that TIA patients have aberrant connections among motor regions, and these changes may reflect the decreased efficiency of primary motor function and disrupted control of voluntary movement in patients with TIA.

Fixation-related fMRI analysis reveals the neural basis of natural reading of unspaced and spaced Chinese sentences.

Although there are many eye-movement studies focusing on natural sentence reading and functional magnetic resonance imaging research on reading with serial visual presentation paradigms, there is a scarcity of investigations into the neural mechanism of natural sentence reading. The present study recruited 33 adults to read unspaced and spaced Chinese sentences with the eye tracking and functional magnetic resonance imaging data recorded simultaneously. By using fixation-related functional magnetic resonance imaging analysis, this study showed that natural reading of Chinese sentences produced activations in ventral visual, dorsal attention, and semantic brain regions, which were modulated by the properties of words such as word length and word frequency. The multivoxel pattern analysis showed that the activity pattern in the left middle temporal gyrus could significantly predict the visual layout categories (i.e. unspaced vs. spaced conditions). Dynamic causal modeling analysis showed that there were bidirectional brain connections between the left middle temporal gyrus and the left inferior occipital cortex in the unspaced Chinese sentence reading but not in the spaced reading. These results provide a neural mechanism for the natural reading of Chinese sentences from the perspective of word segmentation.

Arousal modulates the amygdala-insula reciprocal connectivity during naturalistic emotional movie watching

Emotional arousal is a complex state recruiting distributed cortical and subcortical structures, in which the amygdala and insula play an important role. Although previous neuroimaging studies have showed that the amygdala and insula manifest reciprocal connectivity, the effective connectivities and modulatory patterns on the amygdala-insula interactions underpinning arousal are still largely unknown. One of the reasons may be attributed to static and discrete laboratory brain imaging paradigms used in most existing studies. In this study, by integrating naturalistic-paradigm (i.e., movie watching) functional magnetic resonance imaging (fMRI) with a computational affective model that predicts dynamic arousal for the movie stimuli, we investigated the effective amygdala-insula interactions and the modulatory effect of the input arousal on the effective connections. Specifically, the predicted dynamic arousal of the movie served as regressors in general linear model (GLM) analysis and brain activations were identified accordingly. The regions of interest (i.e., the bilateral amygdala and insula) were localized according to the GLM activation map. The effective connectivity and modulatory effect were then inferred by using dynamic causal modeling (DCM). Our experimental results demonstrated that amygdala was the site of driving arousal input and arousal had a modulatory effect on the reciprocal connections between amygdala and insula. Our study provides novel evidence to the underlying neural mechanisms of arousal in a dynamical naturalistic setting.

Altered resting-state effective connectivity of trigeminal vascular system in migraine without aura: A spectral dynamic causal modeling study.

The trigeminal vascular system is an important part of the anatomical and physiological basis of migraine. The effective connectivity (EC) among the regions of interest (ROIs) in the trigeminal vascular system involved in migraine without aura (MWoA) remains unclear. In this cross-sectional study, 48 patients (mean [SD] age 38.06 [10.35] years; male, 14/48 [29%]) with MWoA during the interictal phase and 48 healthy controls of similar age and sex (mean [SD] age 38.96 [10.96] years; male, 14/48 [29%]) underwent resting-state functional magnetic resonance imaging (fMRI). Dynamic causal modeling analysis was conducted to investigate directional EC among ROIs in the trigeminal vascular system including the bilateral brainstem, the primary somatosensory cortex (S1), the thalamus, and the insula. Compared with the healthy control group, MWoA represented significantly reduced EC from the left brainstem (Brainstem.L) to the left insula (MWoA: mean [SD] -0.16 [0.36]; healthy controls: mean [SD] 0.11 [0.41]; Pcorrected = 0.021), reduced EC from the Brainstem.L to the right insula (MWoA: mean [SD] -0.15 [0.39]; healthy controls: mean [SD] 0.03 [0.35]; Pcorrected = 0.021), and decreased EC from the left thalamus (Thalamus.L) to the Brainstem.L (MWoA: mean [SD] -0.13 [0.56]; healthy controls: mean [SD] 0.10 [0.45]; Pcorrected = 0.021). Altered EC parameters were not significantly correlated with MWoA clinical data. These results further provide increasing evidence that disturbed homeostasis of the trigeminovascular nociceptive pathway is involved in the pathophysiological mechanisms of migraine. Patients with MWoA exhibited a regional interaction distinct from healthy controls in the neural pathway of the Bilateral Insula-Brainstem.L-Thalamus.L, which may shed light on the future understanding of brain mechanisms for MWoA. Future brain-based interventions are suggested to consider the dysregulation in the Bilateral Insula-Brainstem.L-Thalamus.L circuits.

Dynamic fronto-amygdalar interactions underlying emotion-regulation deficits in women at higher weight.

The regulation of negative emotions entails the modulation of subcortical regions, such as the amygdala, by prefrontal regions. There is preliminary evidence suggesting that individuals at higher weight may present with hypoactivity in prefrontal regulatory systems during emotional regulation, although the directionality of these pathways has not been tested. In this study, we compared fronto-amygdalar effective connectivity during cognitive reappraisal as a function of BMI in 48 adult women with obesity and 54 control participants. Dynamic causal modeling and parametric empirical Bayes were used to map effective connectivity between the dorsomedial prefrontal cortex, orbitofrontal cortex, dorsolateral prefrontal cortex, and the amygdala. Difficulty in Emotion Regulation Scale scores were higher in the obesity group compared with control participants (p < 0.001). A top-down cortical model best explained our functional magnetic resonance imaging data (posterior probability = 86%). Participants at higher BMI were less effective at inhibiting activity in the amygdala via the orbitofrontal cortex and dorsomedial prefrontal cortex during reappraisal compared with those at lower BMI. In contrast, increased excitatory modulation of dorsolateral prefrontal cortex-to-amygdalar connectivity was found in participants at lower BMI. These findings support a framework involving alterations in fronto-amygdalar connectivity contributing to difficulties in regulating negative affect in individuals at higher weight.

Disruptions of salience network during uncertain anticipation of conflict control in anxiety

BackgroundAnxiety has been characterized by disrupted processing of conflict control, while little is known about anticipatory processing of conflicts in anxiety. Anticipation is the key factor in both anxiety and cognitive control, especially under uncertain conditions. The current study therefore examined neurocomputational mechanisms of uncertain anticipation of conflict control in anxiety. MethodsTwenty-six participants with high-trait anxiety and twenty-nine low-trait anxiety participants completed a cue-flanker task with functional magnetic resonance imaging. The hierarchical drift diffusion model (HDDM) was used to measure the cognitive computations during the task. To identify the neurocomputational mechanism of anticipatory control in anxiety, mediation analysis and dynamic causal modelling (DCM) analysis were conducted to examine the relationship between functional connectivity of brain networks and the parameters of HDDM. ResultsWe found influences of regulatory signals from the dorsolateral prefrontal cortex to dorsal anterior cingulate cortex on decision threshold in low-trait anxiety (LTA), but not in high-trait anxiety (HTA), especially for the condition with uncertain cues. The results indicate deficient top-down anticipatory control of upcoming conflicts in anxious individuals. DCM and HDDM analyses revealed that lower decision threshold was associated with higher intrinsic connectivity of salience network (SN) in anxious individuals, suggesting that dysfunctional SN disrupts anticipation of conflict control under uncertainty in anxiety. ConclusionsOur results suggest hyperfunction of the SN underlies the deficient information accumulation during uncertain anticipation of upcoming conflicts in anxiety. Our findings shed new light on the mechanisms of anticipation processing and the psychopathology of anxiety.

Dynamic causal modeling for nonstationary industrial process performance degradation analysis and fault prognosis

Performance degradation analysis and fault prognosis of industrial processes refer to distinguish different degradation stage and raise warnings before a failure occurs, which are crucial to ensure the operation efficiency and safety. However, processes usually have nonstationarity caused by operating condition switching, which may be confused with the underlying temporal variations in the degradation process. Considering that the degradation process is essentially the changes in short-term temporal information transmission between variables, we propose a dynamic causal graph-driven performance degradation analysis and fault prognosis framework (DCG-PDA), which can reveal the intrinsic connection between causality and degradation mechanism. First, a dynamic causal graph framework is constructed, in which the nonstationarity is removed by transfer entropy-guided symbolization, to extract significant short-term causal information transmission. Second, changes in causality are effectively captured and quantified, and the causal graphs corresponding to some time points with larger changes in causality are selected to characterize the representative causal patterns in the degradation process. Finally, a node anomaly score is designed to consider the accumulation of causal structural changes at anomaly time points and measure variable-wise degradation contributions, so as to realize accurate locations for key variables in the degradation process. The validity of the proposed method is illustrated through a real compressor fouling process.

A novel method for modeling effective connections between brain regions based on EEG signals and graph neural networks for motor imagery detection

Classified as biomedical signal processing, cerebral signal processing plays a key role in human-computer interaction (HCI) and medical diagnosis. The motor imagery (MI) problem is an important research area in this field. Accurate solutions to this problem will greatly affect real-world applications. Most of the proposed methods are based on raw signal processing techniques. Known as prior knowledge, the structural-functional information and interregional connections can improve signal processing accuracy. It is possible to correctly perceive the generated signals by considering the brain structure (i.e. anatomical units), the source of signals, and the structural-functional dependence of different brain regions (i.e. effective connection) that are the semantic generators of signals. This study employed electroencephalograph (EEG) signals based on the activity of brain regions (cortex) and effective connections between brain regions based on dynamic causal modeling to solve the MI problem. EEG signals, as well as effective connections between brain regions to improve the interpretability of MI action, were fed into the architecture of Graph Convolutional Neural Network (GCN). The proposed model allowed GCN to extract more discriminative features. The results indicated that the proposed method was successful in developing a model with a MI detection accuracy of 93.73%.

Introduction to Effective Connectivity and Analysis Methods: Psychophysiological Interaction and Dynamic Causal Modeling

Introduction to Effective Connectivity and Analysis Methods: Psychophysiological Interaction and Dynamic Causal Modeling

Effective Connectivity of Thalamocortical Interactions Following d-Amphetamine, LSD, and MDMA Administration

BackgroundWhile the exploration of serotonergic psychedelics as psychiatric medicines deepens, so does the pressure to better understand how these compounds act on the brain. MethodsWe used a double-blind, placebo-controlled, crossover design and administered lysergic acid diethylamide (LSD), 3,4-methylenedioxymethamphetamine (MDMA), and d-amphetamine in 25 healthy participants. By using spectral dynamic causal modeling, we mapped substance-induced changes in effective connectivity between the thalamus and different cortex types (unimodal vs. transmodal) derived from a previous study with resting-state functional magnetic resonance imaging data. Due to the distinct pharmacological modes of action of the 3 substances, we were able to investigate specific effects mainly driven by different neurotransmitter systems on thalamocortical and corticothalamic interactions. ResultsCompared with placebo, all 3 substances increased the effective connectivity from the thalamus to specific unimodal cortices, whereas the influence of these cortices on the thalamus was reduced. These results indicate increased bottom-up and decreased top-down information flow between the thalamus and some unimodal cortices. However, for the amphetamines, we found the opposite effects when examining the effective connectivity with transmodal cortices, including parts of the salience network. Intriguingly, LSD increased the effective connectivity from the thalamus to both unimodal and transmodal cortices, indicating a breach in the hierarchical organization of ongoing brain activity. ConclusionsThe results advance our knowledge about the action of psychedelics on the brain and refine current models aiming to explain the underlying neurobiological processes.

A single case neuroimaging study of tickertape synesthesia

Reading acquisition is enabled by deep changes in the brain’s visual system and language areas, and in the links subtending their collaboration. Disruption of those plastic processes commonly results in developmental dyslexia. However, atypical development of reading mechanisms may occasionally result in ticker-tape synesthesia (TTS), a condition described by Francis Galton in 1883 wherein individuals “see mentally in print every word that is uttered (…) as from a long imaginary strip of paper”. While reading is the bottom–up translation of letters into speech, TTS may be viewed as its opposite, the top–down translation of speech into internally visualized letters. In a series of functional MRI experiments, we studied MK, a man with TTS. We showed that a set of left-hemispheric areas were more active in MK than in controls during the perception of normal than reversed speech, including frontoparietal areas involved in speech processing, and the Visual Word Form Area, an occipitotemporal region subtending orthography. Those areas were identical to those involved in reading, supporting the construal of TTS as upended reading. Using dynamic causal modeling, we further showed that, parallel to reading, TTS induced by spoken words and pseudowords relied on top–down flow of information along distinct lexical and phonological routes, involving the middle temporal and supramarginal gyri, respectively. Future studies of TTS should shed new light on the neurodevelopmental mechanisms of reading acquisition, their variability and their disorders.

The influence of sex steroid treatment on insular connectivity in gender dysphoria

BackgroundSex-specific differences in brain connectivity were found in various neuroimaging studies, though little is known about sex steroid effects on insular functioning. Based on well-characterized sex differences in emotion regulation, interoception and higher-level cognition, gender-dysphoric individuals receiving gender-affirming hormone therapy represent an interesting cohort to investigate how sex hormones might influence insular connectivity and related brain functions. MethodsTo analyze the potential effect of sex steroids on insular connectivity at rest, 11 transgender women, 14 transgender men, 20 cisgender women, and 11 cisgender men were recruited. All participants underwent two magnetic resonance imaging sessions involving resting-state acquisitions separated by a median time period of 4.5 months and also completed the Bermond-Vorst alexithymia questionnaire at the initial and final examination. Between scans, transgender subjects received gender-affirming hormone therapy. ResultsA seed based functional connectivity analysis revealed a significant 2-way interaction effect of group-by-time between right insula, cingulum, left middle frontal gyrus and left angular gyrus. Post-hoc tests demonstrated an increase in connectivity for transgender women when compared to cisgender men. Furthermore, spectral dynamic causal modelling showed reduced effective connectivity from the posterior cingulum and left angular gyrus to the left middle frontal gyrus as well as from the right insula to the left middle frontal gyrus. Alexithymia changes were found after gender-affirming hormone therapy for transgender women in both fantasizing and identifying. ConclusionThese findings suggest a considerable influence of estrogen administration and androgen suppression on brain networks implicated in interoception, own-body perception and higher-level cognition.

Altered effective connectivity between reward and inhibitory control networks in people with binge eating episodes: A spectral dynamic causal modeling study

BackgroundConverging evidence points to the crucial role of brain connectivity involved in aberrant behavioral control and reward reactivity in the onset and maintenance of binge eating. However, the directional interaction pattern between brain's reward and inhibitory control systems in people with binge eating episodes is largely unknown. MethodsResting-state fMRI data were collected from 36 adults with binge eating episodes (age: 19.05 ± 0.90) and 36 well-matched controls (age: 18.88 ± 0.78). We applied spectral dynamic causal modeling approach to estimate effective connectivity of the executive control network (ECN) and reward network (RN) with 15 predefined regions of interest, and investigate the between-group differences in directional connectivity. ResultsCompared with controls, the positive connections within the ECN were significantly strengthened in individuals with binge eating episodes, while the negative connections from the ECN to RN and from the RN to ECN were significantly weakened. In adults with binge eating episodes, the RN→ECN connectivity was positively related to binge frequency even controlling for age, sex, and body mass index. ConclusionThis study represents an important first step in addressing the role of directional integration between reward and inhibitory control networks in binge eating, and provides novel evidence that the ability of people with binge eating episodes to maintain a balance between inhibitory control and reward reactivity is decreased, as reflected by diminished bidirectional negative effects of prefrontal-subcortical circuitry at rest.

Differential processing of intrinsic vs. extrinsic coordinates in wrist movement: connectivity and chronometry perspectives.

This study explores brain-network differences between the intrinsic and extrinsic motor coordinate frames. A connectivity model showing the coordinate frames difference was obtained using brain fMRI data of right wrist isometric flexions and extensions movements, performed in two forearm postures. The connectivity model was calculated by machine-learning-based neural representation and effective functional connectivity using psychophysiological interaction and dynamic causal modeling analyses. The model indicated the network difference wherein the inferior parietal lobule receives extrinsic information from the rostral lingual gyrus through the superior parietal lobule and transmits intrinsic information to the Handknob, whereas extrinsic information is transmitted to the Handknob directly from the rostral lingual gyrus. A behavioral experiment provided further evidence on the difference between motor coordinate frames showing onset timing delay of muscle activity of intrinsic coordinate-directed wrist movement compared to extrinsic one. These results suggest that, if the movement is externally directed, intrinsic coordinate system information is bypassed to reach the primary motor area.

Impaired salience network switching in psychopathy

Growing evidence suggests that psychopathy is related to altered connectivity within and between three large-scale brain networks that support core cognitive functions, including allocation of attention. In healthy individuals, default mode network (DMN) is involved in internally-focused attention and cognition such as self-reference. Frontoparietal network (FPN) is anticorrelated with DMN and is involved in externally-focused attention to cognitively demanding tasks. A third network, salience network (SN), is involved in detecting salient cues and, crucially, appears to play a role in switching between the two anticorrelated networks, DMN and FPN, to efficiently allocate attentional resources. Psychopathy has been related to reduced anticorrelation between DMN and FPN, suggesting SN’s role in switching between these two networks may be diminished in the disorder. To test this hypothesis, we used independent component analysis to derive DMN, FPN, and SN activity in resting-state fMRI data in a sample of incarcerated men (N = 148). We entered the activity of the three networks into dynamic causal modeling to test SN’s switching role. The previously established switching effect of SN among young, healthy adults was replicated in a group of low psychopathy participants (posterior model probability = 0.38). As predicted, SN’s switching role was significantly diminished in high psychopathy participants (t(145) = 26.39, p < .001). These findings corroborate a novel theory of brain function in psychopathy. Future studies may use this model to test whether disrupted SN switching is related to high psychopathy individuals’ abnormal allocation of attention.

Neural mechanisms of emotional health in traumatic brain injury patients undergoing rTMS treatment

Emotional dysregulation such as that seen in depression, are a long-term consequence of mild traumatic brain injury (TBI), that can be improved by using neuromodulation treatments such as repetitive transcranial magnetic stimulation (rTMS). Previous studies provide insights into the changes in functional connectivity related to general emotional health after the application of rTMS procedures in patients with TBI. However, these studies provide little understanding of the underlying neuronal mechanisms that drive the improvement of the emotional health in these patients. The current study focuses on inferring the effective (causal) connectivity changes and their association with emotional health, after rTMS treatment of cognitive problems in TBI patients (N = 32). Specifically, we used resting state functional magnetic resonance imaging (fMRI) together with spectral dynamic causal model (spDCM) to investigate changes in brain effective connectivity, before and after the application of high frequency (10 Hz) rTMS over left dorsolateral prefrontal cortex. We investigated the effective connectivity of the cortico-limbic network comprised of 11 regions of interest (ROIs) which are part of the default mode, salience, and executive control networks, known to be implicated in emotional processing. The results indicate that overall, among extrinsic connections, the strength of excitatory connections decreased while that of inhibitory connections increased after the neuromodulation. The cardinal region in the analysis was dorsal anterior cingulate cortex (dACC) which is considered to be the most influenced during emotional health disorders. Our findings implicate the altered connectivity of dACC with left anterior insula and medial prefrontal cortex, after the application of rTMS, as a potential neural mechanism underlying improvement of emotional health. Our investigation highlights the importance of these brain regions as treatment targets in emotional processing in TBI.

Effective resting-state connectivity in severe unipolar depression before and after electroconvulsive therapy

BackgroundElectroconvulsive therapy (ECT) is one of the most effective treatments for severe depressive disorders. A recent multi-center study found no consistent changes in correlation-based (undirected) resting-state connectivity after ECT. Effective (directed) connectivity may provide more insight into the working mechanism of ECT. ObjectiveWe investigated whether there are consistent changes in effective resting-state connectivity. MethodsThis multi-center study included data from 189 patients suffering from severe unipolar depression and 59 healthy control participants. Longitudinal data were available for 81 patients and 24 healthy controls. We used dynamic causal modeling for resting-state functional magnetic resonance imaging to determine effective connectivity in the default mode, salience and central executive networks before and after a course of ECT. Bayesian general linear models were used to examine differences in baseline and longitudinal effective connectivity effects associated with ECT and its effectiveness. ResultsCompared to controls, depressed patients showed many differences in effective connectivity at baseline, which varied according to the presence of psychotic features and later treatment outcome. Additionally, effective connectivity changed after ECT, which was related to ECT effectiveness. Notably, treatment effectiveness was associated with decreasing and increasing effective connectivity from the posterior default mode network to the left and right insula, respectively. No effects were found using correlation-based (undirected) connectivity. ConclusionsA beneficial response to ECT may depend on how brain regions influence each other in networks important for emotion and cognition. These findings further elucidate the working mechanisms of ECT and may provide directions for future non-invasive brain stimulation research.

An information-theoretic analysis of resting-state versus task fMRI.

Resting-state fMRI is an increasingly popular alternative to task-based fMRI. However, a formal quantification of the amount of information provided by resting-state fMRI as opposed to active task conditions about neural responses is lacking. We conducted a systematic comparison of the quality of inferences derived from a resting-state and a task fMRI paradigm by means of Bayesian Data Comparison. In this framework, data quality is formally quantified in information-theoretic terms as the precision and amount of information provided by the data on the parameters of interest. Parameters of effective connectivity, estimated from the cross-spectral densities of resting-state- and task time series by means of dynamic causal modelling (DCM), were subjected to the analysis. Data from 50 individuals undergoing resting-state and a Theory-of-Mind task were compared, both datasets provided by the Human Connectome Project. A threshold of very strong evidence was reached in favour of the Theory-of-Mind task (>10 bits or natural units) regarding information gain, which could be attributed to the active task condition eliciting stronger effective connectivity. Extending these analyses to other tasks and cognitive systems will reveal whether the superior informative value of task-based fMRI observed here is case specific or a more general trend.

Children at Familial High risk of Schizophrenia and Bipolar Disorder Exhibit Altered Connectivity Patterns During Pre-attentive Processing of an Auditory Prediction Error.

Individuals with schizophrenia or bipolar disorder have attenuated auditory mismatch negativity (MMN) responses, indicating impaired sensory information processing. Computational models of effective connectivity between brain areas underlying MMN responses show reduced connectivity between fronto-temporal areas in individuals with schizophrenia. Here we ask whether children at familial high risk (FHR) of developing a serious mental disorder show similar alterations. We recruited 67 children at FHR for schizophrenia, 47 children at FHR for bipolar disorder as well as 59 matched population-based controls from the Danish High Risk and Resilience study. The 11-12-year-old participants engaged in a classical auditory MMN paradigm with deviations in frequency, duration, or frequency and duration, while we recorded their EEG. We used dynamic causal modeling (DCM) to infer on the effective connectivity between brain areas underlying MMN. DCM yielded strong evidence for differences in effective connectivity among groups in connections from right inferior frontal gyrus (IFG) to right superior temporal gyrus (STG), along with differences in intrinsic connectivity within primary auditory cortex (A1). Critically, the 2 high-risk groups differed in intrinsic connectivity in left STG and IFG as well as effective connectivity from right A1 to right STG. Results persisted even when controlling for past or present psychiatric diagnoses. We provide novel evidence that connectivity underlying MMN responses in children at FHR for schizophrenia and bipolar disorder is altered at the age of 11-12, echoing findings that have been found in individuals with manifest schizophrenia.