A guide to group effective connectivity analysis, part 1: First level analysis with DCM for fMRI

Altered effective connectivity within brain lesioned regions and cognitive impairment after stroke

Poststroke cognitive impairments (PSCI) reflect widespread network dysfunction due to structural damage, abnormal neural activity, or abnormal connections in affected brain regions. The exact influence of these lesioned regions on the related functional network and their role in PSCI remains unclear. We recruited 35 first-time stroke patients who had basal ganglia infarcts and PSCI, along with 29 age-matched healthy controls. We utilized T1-weighted imaging to inspect structural damage with regional gray matter volume (GMV). Resting-state fMRI data were utilized to examine spontaneous activities with regional Wavelet-ALFF metric, investigate dynamic functional connectivity (dFC) by seeding the region with damaged GMV, and further study effective connectivity within the abnormal dFC network and its impact on PSCI. In comparison to HC, patients showed significant reduced GMV in the bilateral Rolandic operculum (ROL), along with notable abnormal Wavelet-ALFF values in the right Precuneus (PCUN) and left Cerebellum_9 (CER9). Particularly, an abnormal dFC network seeded in the left ROL, demonstrating significantly differential between PSCI and HC groups and remaining consistent across all time windows, was observed. This abnormal dFC network comprised the left ROL as the seed region, the right ROL, bilateral PCUN, bilateral CER9, right Superior Temporal Gyrus (STG), and right Parahippocampal Gyrus (PHG). Notably, in patients, impaired functions across various cognitive domains significantly influenced the altered effective connections among the abnormal regions, particularly impacting the connections between structurally damaged regions and those with abnormal spontaneous activity. These findings suggest that altered effective connectivity networks within lesioned regions may contribute to deficits in various cognitive domains in PSCI.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-024-10209-7.

Neural mechanisms of disease pathology and cognition in young-onset Alzheimer's disease variants

BackgroundLate-onset Alzheimer's disease is consistently associated with alterations in the default-mode network (DMN)-a large-scale brain network associated with self-related processing and memory. However, the functional organization of DMN is far less clear in young-onset Alzheimer's disease (YOAD).ObjectiveThe current study aimed to identify effective connectivity changes in the core DMN nodes between YOAD variants and healthy controls.MethodsWe assessed resting-state DMN effective connectivity in two common YOAD variants (i.e., amnestic variant (n = 26) and posterior cortical atrophy (n = 13) and healthy participants (n = 24) to identify disease- and variant-specific connectivity differences using spectral dynamic causal modelling.ResultsPatients with the amnestic variant showed increased connectivity from prefrontal cortex to posterior DMN nodes relative to healthy controls, whereas patients with posterior cortical atrophy exhibited decreased posterior DMN connectivity. Right hippocampus connectivity differentiated the two patient groups. Furthermore, disease-related connectivity alterations were also predictive of group membership and cognitive performance.ConclusionsThese findings suggest that resting-state DMN effective connectivity provides a new understanding of neural mechanisms underlying the disease pathology and cognition in YOAD.

Social stress enhances intuitive prosocial behavior in males while disrupting self-reward processing: Evidence from behavioral, computational, and neuroimaging studies

In this study, we present behavioral, computational, and neuroimaging evidence that social stress enhances intuitive prosocial value processing while impairing self-reward processing. When deciding on monetary rewards for individuals at various social distances, participants who exhibited elevated cortisol levels following a social stress task were more inclined to choose a disadvantageous unequal option. Neuroimaging data revealed that participants more likely to choose the disadvantageous unequal option exhibited increased encoding of other-regarding rewards in the ventral medial prefrontal cortex (mPFC), whereas the dorsal mPFC exhibited a decrease in encoding. Mediation analyses further indicated that both the ventral and dorsal mPFC indirectly mediated the relationship between heightened cortisol levels and a greater likelihood of choosing a disadvantageous unequal option. Additionally, effective connectivity analysis results demonstrated that cortisol has an excitatory effect on the dorsal mPFC via the ventral striatum, while simultaneously sending inhibitory signals to the dorsal mPFC via the dorsal striatum. These findings provide empirical evidence to clarify the ambiguity surrounding the effects of stress on prosocial decision-making, suggesting that social stress disrupts deliberative decision-making while simultaneously promoting intuitive prosocial motivation through the differential modulation of hierarchically organized cortico-striatal loops.

Habenula contributions to negative self-cognitions

Self-related cognitions are integral to personal identity and psychological wellbeing. Persistent engagement with negative self-cognitions can precipitate mental ill health; whereas the ability to restructure them is protective. Here, we leverage ultra-high field 7T fMRI and dynamic causal modelling to characterise a negative self-cognition network centred on the habenula - a small midbrain region linked to the encoding of punishment and negative outcomes. We model habenula effective connectivity in a discovery sample of healthy young adults (n = 45) and in a replication cohort (n = 56) using a cognitive restructuring task during which participants repeated or restructured negative self-cognitions. The restructuring of negative self-cognitions elicits an excitatory effect from the habenula to the posterior orbitofrontal cortex that is reliably observed across both samples. Furthermore, we identify an excitatory effect of the habenula on the posterior cingulate cortex during both the repeating and restructuring of self-cognitions. Our study provides evidence demonstrating the habenula's contribution to processing self-cognitions. These findings yield unique insights into habenula's function beyond processing external reward/punishment to include abstract internal experiences.

Thalamic burst and tonic firing selectively indicate patients' consciousness level and recovery

Patients with disorders of consciousness suffer from severe impairments in arousal and awareness alongside anomalous brain connections and aberrant neuronal activities. The thalamus, a crucial hub in the brain connectome, has been empirically inferred to maintain consciousness and wakefulness. Here, we investigated thalamic spiking, brain connectivity, consciousness states, and recovery outcomes following deep brain stimulation in 29 patients. Our study reveals that thalamic neuronal activity serves as a marker of consciousness state. Patients diagnosed with vegetative state/unresponsive wakefulness syndrome exhibited less-active neurons, with longer and more variable burst discharges, than those in a minimally conscious state. Furthermore, neuronal profiles in the intralaminar thalamus, the direct stimulation site, predicted whether electrostimulation here improved recovery. Stronger tonic firing was correlated with enhanced thalamocortical connectivity and better recovery outcomes in patients. These findings suggest that thalamic spiking signatures, including single-neuron burst discharge and tonic firing, selectively indicate the representation and alteration of consciousness.

7 Tesla magnetic resonance spectroscopy estimates of GABA concentration relate to physiological measures of tonic inhibition in the human motor cortex

GABAergic neurotransmission within the cortex plays a key role in learning and is altered in several brain diseases. Quantification of bulk GABA in the human brain is typically obtained by magnetic resonance spectroscopy (MRS). However, the interpretation of MRS-GABA is still debated. A recent mathematical simulation contends that MRS detects extrasynaptic GABA, mediating tonic inhibition. Nevertheless, no empirical data have yet confirmed this hypothesis. Here we collected ultra-high-field 7 Tesla MRS and transcranial magnetic stimulation coupled with high-density electroencephalography (TMS-hdEEG) from the motor cortex of 20 healthy participants (age 23.95 ± 6.4 years), while they were at rest. We first applied a neural mass model (NMM) to TMS-evoked potentials to disentangle the contribution of different GABAergic pools. We then assessed to which of these different pools MRS-GABA was related to by means of parametric empirical Bayesian (PEB) analysis. We found that MRS-GABA was mostly positively related to the NMM-derived measures of tonic inhibition and overall functionality of the GABAergic synapse. This relationship was reliable enough to predict MRS-GABA from NMM-GABA. These findings clarify the mesoscopic underpinnings of GABA levels measured by MRS. Our work will help fulfil the promises of MRS-GABA, enhancing our understanding of human behaviour, brain physiology and pathophysiology. KEY POINTS: GABA neurotransmission is essential for synaptic plasticity and learning (especially motor learning) and is altered in several brain disorders, such as epilepsy and stroke. Quantification of GABA in the human brain is typically obtained by magnetic resonance spectroscopy (MRS). However, the interpretation of MRS-GABA is still debated. By using a biophysical neural mass model, here we show that MRS-GABA relates to physiological measures of tonic inhibition in the human cortex.

The neural representation of body orientation and emotion from biological motion

The perception of human body orientation and emotion in others provides crucial insights into their intentions. While significant research has explored the brain's representation of body orientation and emotion processing, their possible combined representation remains less well understood. In this study, functional magnetic resonance imaging was employed to investigate this issue. Participants were shown point-light displays and tasked with recognizing both body emotion and orientation. The analysis of functional activation revealed that the extrastriate body area encodesd emotion, while the precentral gyrus and postcentral gyrus encoded body orientation. Additionally, results from multivariate pattern analysis and representational similarity analysis demonstrated that the lingual gyrus, precentral gyrus, and postcentral gyrus played a critical role in processing body orientation, whereas the lingual gyrus and extrastriate body area were crucial for processing emotion. Furthermore, the commonality analysis found that the neural representations of emotion and body orientation in the lingual and precentral gyrus were not interacting, but rather competing. Lastly, a remarkable interaction between hemisphere and body orientation revealed in the connection analysis showed that the coupling between the inferior parietal lobule and the left precentral gyrus was more sensitive to a 90° body orientation, while the coupling between the inferior parietal lobule and the right precentral gyrus was sensitive to 0° and 45° body orientation. Overall, these findings suggest that the conflicted relationship between the neural representation of body orientation and emotion in LING and PreCG when point-light displays were shown, and the different hemispheres play different role in encoding different body orientations.

Disrupted coordination between primary and high-order cognitive networks in Parkinson's disease based on morphological and functional analysis

Patients with Parkinson's disease (PD) exhibit structural and functional alterations in both primary and high-order cognitive networks, but the interactions within aberrant functional networks and relevant structural foundation remains unexplored. In this study, the functional networks (FN) and the morphometric similarity networks (MSN) were constructed respectively based on the time-series data and gray matter volume from the MRI data of PD patients and controls. The efficiency, average controllability and k-shell values of the FN and MSN were calculated to evaluate their ability of information transmission and identify structural and functional abnormalities in PD. The abnormal regions were categorized into five types: regions with MSN abnormalities, regions with FN abnormalities, regions with both MSN and FN abnormalities, regions with abnormalities only in MSN but not in FN and regions with abnormalities only in FN but not in MSN. Further, the dynamic causal model (DCM) was used to evaluate the causal relationship of information flow between the identified regions. In the network property analysis of the FN, PD patients showed decreased global efficiency and connectivity in the visual network (VIS) and increased global efficiency in higher-order cognitive networks, including the ventral attention network (VAN), default mode network (DMN), and the limbic network (LIM) but no difference in MSN. In the DCM analysis of the regions, PD patients exhibited increased excitatory transition from the visual areas to the superior frontal gyrus, whereas had disturbed information flow from the visual areas to the insula and the orbitofrontal cortex. These findings suggest changes in structural and functional brain of PD patients, and advance our understanding of PD pathogenesis from different neural dimensions.

Neural correlates of suppressing and imagining future threat

Suppressing upsetting thoughts can cause psychological distress but might also enhance mental health when used flexibly to suppress the imagination of future threat during challenging times. To investigate the neural correlates of suppressing and imagining future threat, a cohort of 65 participants underwent a previously examined "Imagine/No-Imagine" paradigm while examining brain activation using magnetic resonance imaging. We observed activity of the inferior frontal gyrus, middle frontal gyrus (MFG), superior parietal lobule, and superior occipital sulcus during thought suppression, whereas imagining future threat elicited activation in the bilateral posterior cingulate cortex (PCC) and ventromedial prefrontal cortex (vmPFC). Subjective levels of anxiety, stress, and depression as covariates did not alter these results. To further examine the group and individual-level network dynamics, we conducted dynamic causal modeling (DCM) and group iterative multiple model estimations (GIMME). The DCM model showed that during suppression, the MFG positively influenced the vmPFC and right PCC. In contrast, the vmPFC and the left and right PCC showed positive connections to the MFG during imagining. This suggests that the neural correlates of self-regulation involve an information flow between the PCC and the PFC. In addition, GIMME identified group-level connections between the right and left PCC and between the left PCC and vmPFC, reflecting the information flow during suppression and imagination of future threat, respectively. Considerable interindividual heterogeneity in the connectivity patterns became apparent, pointing to the existence of different biotypes.

Weaker top-down cognitive control and stronger bottom-up signaling transmission as a pathogenesis of schizophrenia

The clinical symptoms of schizophrenia are highly heterogeneous, with the most striking symptoms being cognitive deficits and perceptual disturbances. Cognitive deficits are typically linked to abnormalities in top-down mechanisms, whereas perceptual disturbances stem from dysfunctions in bottom-up processing. However, it remains unclear whether schizophrenia is primarily driven by top-down control mechanisms, bottom-up perceptual processes, or their interaction. We hypothesized that abnormal top-down and bottom-up interactions constitute the neural mechanisms of schizophrenia. Considering that autoencoders can identify hidden data features and support vector machines are capable of automatically locating the classification hyperplane, we developed an improved stacked autoencoder-support vector machine (ISAE-SVM) model for diagnosing schizophrenia based on resting-state functional magnetic resonance imaging data. A permutation test was used to identify the 213 most discriminative functional connections from the model's output features. Functional connections linking regions of higher cognitive functions and lower perceptual tasks were extracted to further examine their relevance to clinical symptoms. Finally, spectral dynamic causal modeling (sDCM) was used to analyze the dynamic causal interaction between brain regions corresponding to these functional connections. Our results showed that the ISAE-SVM model achieved an average classification accuracy of 82%. Notably, five resting-state functional connections spanning both cognitive and sensory brain areas were significantly correlated with Positive and Negative Syndrome Scale scores. Furthermore, sDCM analysis revealed weakened top-down regulation and enhanced bottom-up signaling in schizophrenia. These findings support our hypothesis that impaired top-down regulation and enhanced bottom-up signaling contribute to the neural mechanisms of schizophrenia.

Attenuation processes in positive social emotion upregulation: Disentangling functional role of ventrolateral prefrontal cortex

Positive emotions determine individual well-being and sustainable social relationships. Here, we examined the neural processes mediating upregulation of positive social emotions using functional magnetic resonance imaging in healthy female volunteers. We identified brain regions engaged in upregulation of positive social emotions and applied a parametric empirical Bayes approach to isolate modulated network connectivity patterns and assess how these effects relate to individual measures of social perception. Our findings indicate that upregulation of positive social emotions shapes the functional interplay between affective valuation and cognitive control functions. We revealed a selective increase of bilateral posterior ventrolateral prefrontal cortex (vlPFC) activity and attenuation of activity in right anterior vlPFC under control influences from more superior prefrontal regions. We also found that individual perception of sociality modulates connectivity between affective and social networks. This study expands our understanding of neural circuits required to balance positive emotions in social situations and their rehabilitative potential.

Dysregulated connectivity configuration of triple-network model in obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is signified by altered functional network connectivity (FNC), particularly within the default mode network (DMN), salience network (SAL), and fronto-parietal network (FPN). While previous studies suggest disruptions within triple networks, dynamic causal interactions across networks remain unaddressed. This study seeks to validate previous findings of static dysconnectivity between triple networks and further delineate the time-varying interactions and causal relationships among these networks in OCD. A resting-state functional magnetic resonance imaging study was performed on a relatively large and well-characterized clinical sample, comprising 88 medication-free OCD patients and 93 healthy controls (HC). Group independent component analysis, combined with a sliding window approach and k-means clustering analysis, was used to assess static and dynamic time-varying FNC within triple networks. Spectral dynamic causal modelling and parametric empirical Bayes framework were utilized to explore the abnormal effective connectivity among these networks in OCD patients. Our results proposed a novel dysregulated connectivity configuration of the triple-network model for OCD. With the self-inhibition increase in the left FPN, the excitatory effect onto the right FPN decrease, resulting in a weakened static connectivity between the left and right FPNs. Concurrently, time-varying hypoconnectivity patterns are observed between the left FPN and DMN, as well as the right FPN and SAL in OCD. Additionally, the excitatory influence from the DMN to the SAL suggests an atypical modulation within OCD's network pathology. These findings advance our understanding of the dysregulated information transfer and the complex interplay of brain networks in OCD, potentially guiding future therapeutic strategies.

Striatal and cerebellar interactions during reward-based motor performance

Goal-directed motor performance relies on the brain's ability to distinguish between actions that lead to successful and unsuccessful outcomes. The basal ganglia (BG) and cerebellum (CBL) are integral to processing performance outcomes, yet their functional interactions remain underexplored. This study scanned participants' brains with functional magnetic imaging (fMRI) while they performed a skilled motor task for monetary rewards, where outcomes depended on their motor performance and also probabilistic events that were not contingent on their performance. We found successful motor outcomes increased activity in the ventral striatum (VS), a functional sub-region of the BG, whereas unsuccessful motor outcomes engaged the CBL. In contrast, for probabilistic outcomes unrelated to motor performance, the BG and CBL exhibited no differences in activity between successful and unsuccessful outcomes. Dynamic causal modeling revealed that VS-to-CBL connectivity was inhibitory following successful motor outcomes, suggesting that the VS may suppress CBL error processing for correct actions. Conversely, CBL-to-VS connectivity was inhibitory after unsuccessful motor outcomes, potentially preventing reinforcement of erroneous actions. Additionally, interindividual differences in task preference, assessed by having participants choose between performing the motor task or flipping a coin for monetary rewards, were related to inhibitory VS-CBL connectivity. These findings highlight a performance-mediated functional network between the VS and CBL, modulated by motivation and subjective preferences, supporting goal-directed behavior.

Neurostimulation improves reading and alters communication within reading networks in dyslexia

The left temporo-parietal cortex (TPC) is critical for phonological decoding during reading and appears hypoactive in dyslexia. Therefore, a promising approach to alleviating phonological deficits in dyslexia is to modulate left TPC functioning. However, it is unclear how neurostimulation alters activity and network interactions in dyslexia. To address this gap, we combined facilitatory transcranial magnetic stimulation (TMS) to the left TPC in adults with dyslexia with an overt word and pseudoword reading task during functional neuroimaging. We found TMS-induced improvements in pseudoword reading, reduced contributions of right-hemispheric regions during reading, and substantial changes between the core reading nodes and an extended network involving the right cerebellum. Stronger coupling between temporo-occipital and frontal cortices was further directly linked to improvements in pseudoword reading. Collectively, we provide evidence for a crucial role of the left TPC for phonological decoding and show that TMS can successfully modulate reading networks to improve reading in dyslexia.

Altered Effective Connectivity During Threat Anticipation in Individuals With Alcohol Use Disorder

BACKGROUND

A developing theory and recent research suggest that heightened reactivity to uncertain stressors or threats may be an important individual difference factor that facilitates excessive drinking as a means of avoidance-based coping and characterizes individuals with current and past alcohol use disorder (AUD). Neuroimaging studies of unpredictable threat processing have repeatedly demonstrated activation of the anterior insula, anteromedial thalamus, and dorsal anterior cingulate cortex. In the current study, we aimed to understand how these 3 regions function as a network during anticipation of unpredictable threat (and predictable threat).

METHODS

Participants were 43 adults (ages 21-30) with AUD and 26 healthy control participants. Functional magnetic resonance imaging and dynamic causal modeling were used to study interregional effective connectivities and predictable and unpredictable threat-related modulations thereof within this network. Parametric empirical Bayesian modeling was used to conduct between-group comparisons in effective connectivities.

RESULTS

During unpredictable threat trials, the increased projection from the right anteromedial thalamus to the right anterior insula was significantly present only in the AUD group. This directional influence was stronger among individuals who consumed more drinks per week on average. As expected, we found no group differences in modulatory changes to effective connectivities during predictable threat trials.

CONCLUSIONS

To our knowledge, this is the first study to examine directional interactions between key frontolimbic regions during anticipation of unpredictable and predictable threat and demonstrate the importance of bottom-up thalamic-insular projections during unpredictable threat processing in AUD. Prospective studies are warranted to determine whether this association is causal.

Altered Effective Connectivity Within a Thalamocortical Corollary Discharge Network in Individuals With Schizophrenia

BACKGROUND AND HYPOTHESIS

Sequential saccade planning requires corollary discharge (CD) signals that provide information about the planned landing location of an eye movement. These CD signals may be altered among individuals with schizophrenia (SZ), providing a potential mechanism to explain passivity and anomalous self-experiences broadly. In healthy controls (HC), a key oculomotor CD network transmits CD signals from the thalamus to the frontal eye fields (FEF) and the intraparietal sulcus (IPS) and also remaps signals from FEF to IPS.

STUDY DESIGN

Here, we modeled fMRI data using dynamic causal modeling (DCM) to examine patient-control differences in effective connectivity evoked by a double-step (DS) task (30 SZ, 29 HC). The interrogated network was formed from a combination of (1) functionally identified FEF and IPS regions that robustly responded on DS trials and (2) anatomically identified thalamic regions involved in CD transmission. We also examined the relationship between clinical symptoms and effective connectivity parameters associated with task modulation of network pathways.

STUDY RESULTS

Network connectivity was indeed modulated by the DS task, which involves CD transmission. More importantly, we found reduced effective connectivity from thalamus to IPS in SZ, which was further correlated with passivity symptom severity.

CONCLUSIONS

These results reaffirm the importance of IPS and thalamocortical connections in oculomotor CD signaling and provide mechanistic insights into CD alterations and consequently agency disturbances in schizophrenia.

Functional and effective connectivity between reward and inhibitory control networks underlying subclinical binge eating

BACKGROUND

Knowledge is growing on the essential role of neural circuits involved in aberrant cognitive control and reward sensitivity for the onset and maintenance of binge eating.

AIMS

To investigate how the brain's reward (bottom-up) and inhibition control (top-down) systems potentially and dynamically interact to contribute to subclinical binge eating.

METHOD

Functional magnetic resonance imaging data were acquired from 30 binge eaters and 29 controls while participants performed a food reward Go/NoGo task. Dynamic causal modelling with the parametric empirical Bayes framework, a novel brain connectivity technique, was used to examine between-group differences in the directional influence between reward and executive control regions. We explored the proximal risk factors for binge eating and its neural basis, and assessed the predictive ability of neural indices on future disordered eating and body weight.

RESULTS

The binge eating group relative to controls displayed fewer reward-inhibition undirectional and directional synchronisations (i.e. medial orbitofrontal cortex [mOFC]-superior parietal gyrus [SPG] connectivity, mOFC → SPG excitatory connectivity) during food reward_nogo condition. Trait impulsivity is a key proximal factor that could weaken the mOFC-SPG connectivity and exacerbate binge eating. Crucially, this core mOFC-SPG connectivity successfully predicted binge eating frequency 6 months later.

CONCLUSIONS

These findings point to a particularly important role of the bottom-up interactions between cortical reward and frontoparietal control circuits in subclinical binge eating, which offers novel insights into the neural hierarchical mechanisms underlying problematic eating, and may have implications for the early identification of individuals suffering from strong binge eating-associated symptomatology in the general population.

Inter-network Effective Connectivity During An Emotional Working Memory Task in Two Independent Samples of Young Adults

BACKGROUND

Effective connectivity (EC) analysis provides valuable insights into the directionality of neural interactions, which are crucial for understanding the mechanisms underlying cognitive and emotional regulation in depressive and anxiety disorders. In this study, we examined EC within key neural networks during working memory (WM) and emotional regulation (ER) tasks in young adults, both healthy individuals and those seeking help from mental health professionals for emotional distress.

METHODS

Dynamic causal modeling was used to analyze EC in 2 independent samples (n = 97 and n = 94). Participants performed an emotional n-back task to assess EC across the central executive network (CEN), default mode network (DMN), salience network (SN), and face processing network. Group-level parametric empirical Bayes analyses were conducted to examine EC patterns, with subanalyses comparing individuals with and without depression and anxiety.

RESULTS

Consistent patterns of positive (posterior probability > .95) DMN→CEN and DMN→SN EC were observed in both samples, predominantly in low and high WM conditions without ER. However, individuals without depressive or anxiety disorders exhibited a significantly greater number of preserved connections that were replicated across both samples.

CONCLUSIONS

This study highlights the different patterns of DMN→CEN EC in conditions with high and low WM loads with and without ER, suggesting that in higher WM loads with ER, the integration of the DMN with the CEN is reduced to facilitate successful cognitive task performance. The findings also suggest that DMN→CEN and DMN→SN EC are significantly reduced in depressive and anxiety disorders, highlighting this pattern of reduced EC as a potential neural marker of these disorders.

Changes in Brain Functional Connectivity Underlying the Space-Number Association

Whether small number magnitudes are inherently represented as lying to the left of larger ones, the space-number association (SNA), is an important issue in mathematical cognition. In this fMRI study, we used a go/no-go implicit association task to investigate the brain activity and functional connectivity underlying the SNA. Arabic digits lower or higher than 5 and left- or right-pointing arrows were alternated as central targets. In a single-code task condition, participants responded to a specific number magnitude and to all arrows or to a specific arrow direction and to all number magnitudes. In a joint-code (JC) condition, responses were provided after congruent, for example, "go when a number is lower than 5 or an arrow points left," or incongruent, for example, "go when a number is lower than 5 or an arrow points right," SNAs. The SNA was only found in the JC condition, where responses were faster with congruent instructions. Analyses of fMRI functional connectivity showed that the SNA was matched with enhanced excitatory inputs from ACC, the left TPJ, and the left inferior frontal gyrus to the left and right intraparietal sulcus (IPS). Incongruent JC trials were associated with enhanced excitatory modulation from ACC to the left and right IPS. These results show that the SNA is associated with enhanced activation of top-down brain control and changes in the functional interaction between the left and right IPS. We conclude that the SNA does not depend on an inherent and bottom-up spatial coding of number magnitudes.

Altered hippocampal effective connectivity predicts BMI and food approach behavior in children with obesity

Objective

The vicious circle model of obesity proposes that the hippocampus plays a crucial role in food reward processing and obesity. However, few studies focused on whether and how pediatric obesity influences the potential direction of information exchange between the hippocampus and key regions, as well as whether these alterations in neural interaction could predict future BMI and eating behaviors.

Methods

In this longitudinal study, a total of 39 children with excess weight (overweight/obesity) and 51 children with normal weight, aged 8 to 12, underwent resting-state fMRI. One year later, we conducted follow-up assessments of eating behaviors and BMI. Resting-state functional connectivity and spectral dynamic casual modeling (spDCM) technique were used to examine altered functional and effective connectivity (EC) of the hippocampus in children with overweight/obesity. Linear support vector regression, a machine learning method, was employed to further investigate whether these sensitive hippocampal connections at baseline could predict future BMI and eating behaviors.

Results

Compared to controls, children with excess weight displayed abnormal bidirectional inhibitory effects between the right hippocampus and left postcentral gyrus (PoCG), that is, stronger inhibitory hippocampus→PoCG EC but weaker inhibitory PoCG→hippocampus EC, which further predicted BMI and food approach behavior one year later.

Conclusion

These findings point to a particularly important role of abnormal information exchange between the hippocampus and somatosensory cortex in pediatric obesity and future food approach behavior, which provide novel insights into the neural hierarchical mechanisms underlying childhood obesity and further expand the spDCM model of adult obesity by identifying the directionality of abnormal influences between crucial circuits associated with appetitive regulation.

Revealing the Spatial Pattern of Brain Hemodynamic Sensitivity to Healthy Aging through Sparse Dynamic Causal Model

Age-related changes in the BOLD response could reflect neurovascular coupling modifications rather than simply impairments in neural functioning. In this study, we propose the use of a sparse dynamic causal model (sDCM) to decouple neuronal and vascular factors in the BOLD signal, with the aim of characterizing the whole-brain spatial pattern of hemodynamic sensitivity to healthy aging, as well as to test the role of hemodynamic features as independent predictors in an age-classification model. sDCM was applied to the resting-state functional magnetic resonance imaging data of a cohort of 126 healthy individuals in a wide age range (31 females), providing reliable estimates of the hemodynamic response function (HRF) for each subject and each region of interest. Then, some features characterizing each HRF curve were extracted and used to fit a multivariate logistic regression model predicting the age class of each individual. Ultimately, we tested the final predictive model on an independent dataset of 338 healthy subjects (173 females) selected from the Human Connectome Project in Aging and Development cohorts. Our results entail the spatial heterogeneity of the age effects on the hemodynamic component, since its impact resulted to be strongly region- and population-specific, discouraging any space-invariant-corrective procedures that attempt to correct for vascular factors when carrying out functional studies involving groups with different ages. Moreover, we demonstrated that a strong interaction exists between certain right-hemisphere hemodynamic features and age, further supporting the essential role of the hemodynamic factor as independent predictor of biological aging, rather than a simple confounding variable.

Lattice physics approaches for neural networks

Modern neuroscience has evolved into a frontier field that draws on numerous disciplines, resulting in the flourishing of novel conceptual frames primarily inspired by physics and complex systems science. Contributing in this direction, we recently introduced a mathematical framework to describe the spatiotemporal interactions of systems of neurons using lattice field theory, the reference paradigm for theoretical particle physics. In this note, we provide a concise summary of the basics of the theory, aiming to be intuitive to the interdisciplinary neuroscience community. We contextualize our methods, illustrating how to readily connect the parameters of our formulation to experimental variables using well-known renormalization procedures. This synopsis yields the key concepts needed to describe neural networks using lattice physics. Such classes of methods are attention-worthy in an era of blistering improvements in numerical computations, as they can facilitate relating the observation of neural activity to generative models underpinned by physical principles.

Causal mechanisms of quadruple networks in pediatric bipolar disorder

BACKGROUND

Pediatric bipolar disorder (PBD) is characterized by abnormal functional connectivity among distributed brain regions. Increasing evidence suggests a role for the limbic network (LN) and the triple network model in the pathophysiology of bipolar disorder (BD). However, the specific relationship between the LN and the triple network in PBD remains unclear. This study aimed to investigate the aberrant causal connections among these four core networks in PBD.

METHOD

Resting-state functional MRI scans from 92 PBD patients and 40 healthy controls (HCs) were analyzed. Dynamic Causal Modeling (DCM) was employed to assess effective connectivity (EC) among the four core networks. Parametric empirical Bayes (PEB) analysis was conducted to identify ECs associated with group differences, as well as depression and mania severity. Leave-one-out cross-validation (LOOCV) was used to test predictive accuracy.

RESULT

Compared to HCs, PBD patients exhibited primarily excitatory bottom-up connections from the LN to the salience network (SN) and bidirectional excitatory connections between the default mode network (DMN) and SN. In PBD, top-down connectivity from the triple network to the LN was excitatory in individuals with higher depression severity but inhibitory in those with higher mania severity. LOOCV identified dysconnectivity circuits involving the caudate and hippocampus as being associated with mania and depression severity, respectively.

CONCLUSIONS

Disrupted bottom-up connections from the LN to the triple network distinguish PBD patients from healthy controls, while top-down disruptions from the triple network to LN relate to mood state differences. These findings offer insight into the neural mechanisms of PBD.

Identification of a cognitive network with effective connectivity to post-stroke cognitive impairment

Altered connectivity within complex functional networks has been observed in individuals with post-stroke cognitive impairment (PSCI) and during cognitive tasks. This study aimed to identify a cognitive function network that is responsive to cognitive changes during cognitive tasks and also sensitive to PSCI. To explore the network, we analyzed resting-state fMRI data from 20 PSCI patients and task-state fMRI data from 100 unrelated healthy young adults using functional connectivity analysis. We further employed spectral dynamic causal modeling to examine the effective connectivity among the pivotal regions within the network. Our findings revealed a common cognitive network that encompassed the hub regions 231 in the Subcortical network (SC), 70, 199, 242 in the Frontoparietal network (FP), 214 in the Visual II network, and 253 in the Cerebellum network (CBL). These hubs' effective connectivity, which showed reliable but slight changes during different cognitive tasks, exhibited notable alterations when comparing post-stroke cognitive impairment and improvement statuses. Decreased coupling strengths were observed in effective connections to CBL253 and from SC231 and FP70 in the improvement status. Increased connections to SC231 and FP70, from CBL253 and FP242, as well as from FP199 and FP242 to FP242 were observed in this status. These alterations exhibited a high sensitivity to signs of recovery, ranging from 80 to 100%. The effective connectivity pattern in both post-stroke cognitive statuses also reflected the influence of the MoCA score. This research succeeded in identifying a cognitive network with sensitive effective connectivity to cognitive changes after stroke, presenting a potential neuroimaging biomarker for forthcoming interventional studies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-024-10139-4.

Modality-specific and modality-general representations of subjective value in frontal cortex

Neuroeconomics theories propose that the value associated with diverse rewards or reward-predicting stimuli is encoded along a common reference scale, irrespective of their sensory properties. However, in a dynamic environment with changing stimulus-reward pairings, the brain must also represent the sensory features of rewarding stimuli. The mechanism by which the brain balances these needs-deriving a common reference scale for valuation while maintaining sensitivity to sensory contexts-remains unclear. To investigate this, we conducted an fMRI study with human participants engaged in a dynamic foraging task, which required integrating the reward history of auditory or visual choice options and updating the subjective value for each sensory modality. Univariate fMRI analysis revealed modality-specific value representations in the orbitofrontal cortex (OFC) and modality-general value representations in the ventromedial prefrontal cortex (vmPFC), confirmed by an exploratory multivariate pattern classification approach. Crucially, modality-specific value representations were absent when the task involved instruction-based rather than value-based choices. Effective connectivity analysis showed that modality-specific value representations emerged from selective bidirectional interactions across the auditory and visual sensory cortices, the corresponding OFC clusters, and the vmPFC. These results illustrate how the brain enables a valuation process that is sensitive to the sensory context of rewarding stimuli.

Effective connectivity of default mode network subsystems and automatic smoking behaviour among males

BACKGROUND

The default mode network (DMN) is not a single system, but rather is composed of smaller and distinct functional subsystems that interact with each other. The functional relevance of these subsystems in tobacco use disorder (TUD) and the neurobiological features associated with smoking motivation are still unclear; thus, we sought to assess causal or direct connectivity alterations within 3 subsystems of the DMN among people with TUD.

METHODS

We recruited male smokers and nonsmokers. We conducted resting-state functional magnetic resonance imaging (rs-fMRI) and collected ratings on smoking-related clinical scales. We applied dynamic causal modelling (DCM) to rs-fMRI to characterize changes of effective connectivity in TUD from 3 DMN subsystems, including the midline core network (i.e., the posterior cingulate cortex and the anterior medial prefrontal cortex [PCC-aMPFC] core DMN), the medial temporal subsystem (MTL-DMN), and the dorsal medial prefrontal cortex subsystem (dMPFC-DMN). We used leave-one-out cross-validation to investigate whether the neural response could predict smoking reasons, evaluated using the Russell Reason for Smoking Questionnaire).

RESULTS

We recruited 88 smokers and 54 nonsmokers. Among people with TUD, the parahippocampal cortex (PHC) region showed enhanced self-connection, which was associated with the severity of TUD after nighttime withdrawal. Compared with nonsmokers, people with TUD displayed significant increased effective connectivity within the dMPFC-DMN, and decreased effective connectivity from the dMPFC-DMN to the PCC-aMPFC core DMN. Moreover, decreased effective connectivity from the lateral temporal cortex to the dMPFC could predict the smoking reason related to automatic behaviour.

LIMITATIONS

Although we found aberrance in causal connections in DMN subsystems among people with TUD, our cross-sectional study could not be used to investigate changes in effective connectivity over time and their relationship with clinical features.

CONCLUSION

This study emphasized the aberrant causal connections of different functional subsystems of the DMN in TUD and revealed the neural correlates of automatic smoking behaviours. These findings suggested DMN subsystem-derived indicators could be a potential biomarker for TUD and could be used to identify the heterogeneity in motivation for smoking behaviour.

Relationship between central autonomic effective connectivity and heart rate variability: A Resting-state fMRI dynamic causal modeling study

The central autonomic network (CAN) serves as a regulatory hub with top-down regulatory control and integration of bottom-up physiological feedback via the autonomic nervous system. Heart rate variability (HRV)-the time variance of the heart's beat-to-beat intervals-is an index of the CAN's affective and behavioral regulatory capacity. Although neural functional connectivities that are associated with HRV and CAN have been well studied, no published report to date has studied effective (directional) connectivities (EC) that are associated with HRV and CAN. Better understanding of neural EC in the brain has the potential to improve our understanding of how the CAN sub-regions regulate HRV. To begin to address this knowledge gap, we employed resting-state functional magnetic resonance imaging and dynamic causal modeling (DCM) with parametric empirical Bayes analyses in 34 healthy adults (19 females; mean age= 32.68 years [SD= 14.09], age range 18-68 years) to examine the bottom-up and top-down neural circuits associated with HRV. Throughout the whole brain, we identified 12 regions associated with HRV. DCM analyses revealed that the ECs from the right amygdala to the anterior cingulate cortex and to the ventrolateral prefrontal cortex had a negative linear relationship with HRV and a positive linear relationship with heart rate. These findings suggest that ECs from the amygdala to the prefrontal cortex may represent a neural circuit associated with regulation of cardiodynamics.

Distinct neural pathway and its information flow for blind individual's Braille reading

Natural Braille reading presents significant challenges to the brain networks of late blind individuals, yet its underlying neural mechanisms remain largely unexplored. Using natural Braille texts in behavioral assessments and functional MRI, we sought to pinpoint the neural pathway and information flow crucial for Braille reading performance in late blind individuals. In the resting state, we discovered a unique neural connection between the higher-order 'visual' cortex, the lateral occipital cortex (LOC), and the inferior frontal cortex (IFC) in late blind individuals, but not in sighted controls. The left-lateralized LOC-IFC connectivity was correlated with individual Braille reading proficiency. Prolonged Braille reading practice led to increased strength of this connectivity. During a natural Braille reading task, bidirectional information flow between the LOC and the IFC was positively modulated, with a predominantly stronger top-down modulation from the IFC to the LOC. This stronger top-down modulation contributed to higher Braille reading proficiency. We thus proposed a two-predictor multiple regression model to predict individual Braille reading proficiency, incorporating both static connectivity and dynamic top-down communication between the LOC-IFC link. This work highlights the dual contributions of the occipito-frontal neural pathway and top-down cognitive strategy to superior natural Braille reading performance, offering guidance for training late blind individuals.

Neural Representations of Emotions in Visual, Auditory, and Modality-Independent Regions Reflect Idiosyncratic Conceptual Knowledge

Growing evidence suggests that conceptual knowledge influences emotion perception, yet the neural mechanisms underlying this effect are not fully understood. Recent studies have shown that brain representations of facial emotion categories in visual-perceptual areas are predicted by conceptual knowledge, but it remains to be seen if auditory regions are similarly affected. Moreover, it is not fully clear whether these conceptual influences operate at a modality-independent level. To address these questions, we conducted a functional magnetic resonance imaging study presenting participants with both facial and vocal emotional stimuli. This dual-modality approach allowed us to investigate effects on both modality-specific and modality-independent brain regions. Using univariate and representational similarity analyses, we found that brain representations in both visual (middle and lateral occipital cortices) and auditory (superior temporal gyrus) regions were predicted by conceptual understanding of emotions for faces and voices, respectively. Additionally, we discovered that conceptual knowledge also influenced supra-modal representations in the superior temporal sulcus. Dynamic causal modeling revealed a brain network showing both bottom-up and top-down flows, suggesting a complex interplay of modality-specific and modality-independent regions in emotional processing. These findings collectively indicate that the neural representations of emotions in both sensory-perceptual and modality-independent regions are likely shaped by each individual's conceptual knowledge.

Psychiatric phenotype in neurodevelopmental myoclonus-dystonia is underpinned by abnormality of cerebellar modulation on the cerebral cortex

Psychiatric symptoms are common in neurodevelopmental movement disorders, including some types of dystonia. However, research has mainly focused on motor manifestations and underlying circuits. Myoclonus-dystonia is a rare and homogeneous neurodevelopmental condition serving as an illustrative paradigm of childhood-onset dystonias, associated with psychiatric symptoms. Here, we assessed the prevalence of psychiatric disorders and the severity of depressive symptoms in patients with myoclonus-dystonia and healthy volunteers (HV). Using resting-state functional neuroimaging, we compared the effective connectivity within and among non-motor and motor brain networks between patients and HV. We further explored the hierarchical organization of these networks and examined the relationship between their connectivity and the depressive symptoms. Comparing 19 patients to 25 HV, we found a higher prevalence of anxiety disorders and more depressive symptoms in the patient group. Patients exhibited abnormal modulation of the cerebellum on the cerebral cortex in the sensorimotor, dorsal attention, salience, and default mode networks. Moreover, the salience network activity was directed by the cerebellum in patients and was related to depressive symptoms. Altogether, our findings highlight the role of the cerebellar drive on both motor and non-motor cortical areas in this disorder, suggesting cerebellar involvement in the complex phenotype of such neurodevelopmental movement disorders.

iTBS reveals the roles of domain-general cognitive control and language-specific brain regions during word formation rule learning

Repeated exposure to word forms and meanings improves lexical knowledge acquisition. However, the roles of domain-general and language-specific brain regions during this process remain unclear. To investigate this, we applied intermittent theta burst stimulation over the domain-general (group left dorsolateral prefrontal cortex) and domain-specific (Group L IFG) brain regions, with a control group receiving sham intermittent theta burst stimulation. Intermittent theta burst stimulation effects were subsequently assessed in functional magnetic resonance imaging using an artificial word learning task which consisted of 3 learning phases. A generalized psychophysiological interaction analysis explored the whole brain functional connectivity, while dynamic causal modeling estimated causal interactions in specific brain regions modulated by intermittent theta burst stimulation during repeated exposure. Compared to sham stimulation, active intermittent theta burst stimulation improved word learning performance and reduced activation of the left insula in learning phase 2. Active intermittent theta burst stimulation over the domain-general region increased whole-brain functional connectivity and modulated effective connectivity between brain regions during repeated exposure. This effect was not observed when active intermittent theta burst stimulation was applied to the language-specific region. These findings suggest that the domain-general region plays a crucial role in word formation rule learning, with intermittent theta burst stimulation enhancing whole-brain connectivity and facilitating efficient information exchange between key brain regions during new word learning.

Abnormal hypothalamic functional connectivity associated with cognitive impairment in craniopharyngiomas

OBJECTIVE

This study sought to characterize resting-state functional connectivity (rsFC) patterns of the hypothalamic and extrahypothalamic nuclei in craniopharyngioma (CP) patients, and to investigate potential correlations between hypothalamic and extrahypothalamic rsFC maps and neurocognitive performance.

METHODS

Ninety-two CP patients and 40 demographically-matched healthy controls were included. Whole-brain seed-to-voxel analyses were used to test for between-group rsFC differences, and regression analyses were used to correlate neurocognitive performance with voxel-wise hypothalamic and extrahypothalamic rsFC maps for CP patients. Finally, spectral DCM analysis was used to explore the hypothalamus circuit associated with neurocognitive performance.

RESULTS

The seed-to-voxel analyses demonstrated that the hypothalamic nuclei showed mainly significant rsFC reduction in brain areas overlayed with the cortical regions of default mode network (DMN), notably in the bilateral anterior cingulate cortices and posterior cingulate cortices. The extrahypothalamic nuclei showed significant rsFC reduction in the limbic system of bilateral caudate nuclei, corpus callosum, fornix, and thalamus. Regression analyses revealed that worse cognitive performance was correlated with abnormal hypothalamic rsFC with brain areas in DMN, and DCM analysis revealed a hypothalamus-DMN circuit responsible for functional modulation of cognitive impairment in CP patients.

CONCLUSIONS

Our study demonstrated that CPs invading into hypothalamus impacted hypothalamic and extrahypothalamic rsFC with brain areas of DMN and limbic system, the severity of which was parallel with the grading system of hypothalamus involvement. In addition to the CP-induced structural damage to the hypothalamus alone, abnormal functional connectivity within the hypothalamus-DMN circuit might be a functional mechanism leading to the cognitive impairment in CP patients.

Direct Retrieval of Orthographic Representations in Chinese Handwritten Production: Evidence from a Dynamic Causal Modeling Study

This present study identified an optimal model representing the relationship between orthography and phonology in Chinese handwritten production using dynamic causal modeling, and further explored how this model was modulated by word frequency and syllable frequency. Each model contained five volumes of interest in the left hemisphere (angular gyrus [AG], inferior frontal gyrus [IFG], middle frontal gyrus [MFG], superior frontal gyrus [SFG], and supramarginal gyrus [SMG]), with the IFG as the driven input area. Results showed the superiority of a model in which both the MFG and the AG connected with the IFG, supporting the orthography autonomy hypothesis. Word frequency modulated the AG → SFG connection (information flow from the orthographic lexicon to the orthographic buffer), and syllable frequency affected the IFG → MFG connection (information transmission from the semantic system to the phonological lexicon). This study thus provides new insights into the connectivity architecture of neural substrates involved in writing.

Inferring occluded projectile motion changes connectivity within a visuo-fronto-parietal network

Anticipating the behaviour of moving objects in the physical environment is essential for a wide range of daily actions. This ability is thought to rely on mental simulations and has been shown to involve frontoparietal and early visual areas. Yet, the connectivity patterns between these regions during intuitive physical inference remain largely unknown. In this study, participants underwent fMRI while performing a task requiring them to infer the parabolic trajectory of an occluded ball falling under Newtonian physics, and a control task. Building on our previous research showing that when solving the physical inference task, early visual areas encode task-specific and perception-like information about the inferred trajectory, the present study aimed to (i) identify regions that are functionally coupled with early visual areas during the physical inference task, and (ii) investigate changes in effective connectivity within this network of regions. We found that early visual areas are functionally connected to a set of parietal and premotor regions when inferring occluded trajectories. Using dynamic causal modelling, we show that predicting occluded trajectories is associated with changes in effective connectivity within a parieto-premotor network, which may drive internally generated early visual activity in a top-down fashion. These findings offer new insights into the interaction between early visual and frontoparietal regions during physical inference, contributing to our understanding of the neural mechanisms underlying the ability to predict physical outcomes.

Neural activity and connectivity are related to food preference changes induced by food go/no-go training

Simply withholding a response while viewing an appetizing food, over the course of many presentations (i.e., during food go/no-go training) can modify individuals' food preferences-which could, in turn, promote healthier eating behaviors. However, the neural mechanisms underlying this food go/no-go training-induced change in food preferences are still relatively unclear. We addressed this issue in the present functional magnetic resonance imaging (fMRI) study. To this end, we administered a novel passive viewing task before and after food go/no-go training to 91 participants in the scanner. Participants' food preferences were measured with a binary food choice task. At the behavioral level, we found the expected training effect on food preferences: Participants preferred go over no-go foods following training. At the neural level, we found that changes in food preferences were associated with training-related go vs. no-go differences in activity and functional connectivity, such as less activity in the anterior cingulate cortex and superior frontal gyrus but greater functional connectivity between the superior frontal gyrus and middle occipital gyrus. Critically, Dynamic causal modeling showed that this preference change effect was largely driven by top-down influence from the superior frontal gyrus to the middle occipital gyrus. Together, these findings suggest a neural mechanism of the food go/no-go training effect-namely, that the food-viewing-related interplay between prefrontal regions and visual regions might be related to the food preference change following food go/no-go training.

Evaluation of potential alterations related to ADHD in the effective connectivity between the default mode network and cerebellum, hippocampus, thalamus, and primary visual cortex

Hyperactivity in children with attention-deficit/hyperactivity disorder (ADHD) leads to restlessness and impulse-control impairments. Nevertheless, the relation between ADHD symptoms and brain regions interactions remains unclear. We focused on dynamic causal modeling to study the effective connectivity in a fully connected network comprised of four regions of the default mode network (DMN) (linked to response control behaviors) and four other regions with previously-reported structural alterations due to ADHD. Then, via the parametric empirical Bayes analysis, the most significant connections, with the highest correlation to the covariates ADHD/control, age, and sex were extracted. Our results demonstrated a positive correlation between ADHD and effective connectivity between the right cerebellum and three DMN nodes (intrinsically inhibitory connections). Therefore, an increase in the effective connectivity leads to more inhibition imposition from the right cerebellum to DMN that reduces this network activation. The lower DMN activity makes leaving the resting-state easier, which may be involved in the restlessness symptom. Furthermore, our results indicated a negative correlation between age and these connections. We showed that the difference between the average of effective connectivities of ADHD and control groups in the age-range of 7-11 years disappeared after 14 years-old. Therefore, aging tends to alleviate ADHD-specific symptoms.

Perplexity of utterances in untreated first-episode psychosis: an ultra-high field MRI dynamic causal modelling study of the semantic network

BACKGROUND

Psychosis involves a distortion of thought content, which is partly reflected in anomalous ways in which words are semantically connected into utterances in speech. We sought to explore how these linguistic anomalies are realized through putative circuit-level abnormalities in the brain's semantic network.

METHODS

Using a computational large-language model, Bidirectional Encoder Representations from Transformers (BERT), we quantified the contextual expectedness of a given word sequence (perplexity) across 180 samples obtained from descriptions of 3 pictures by patients with first-episode schizophrenia (FES) and controls matched for age, parental social status, and sex, scanned with 7 T ultra-high field functional magnetic resonance imaging (fMRI). Subsequently, perplexity was used to parametrize a spectral dynamic causal model (DCM) of the effective connectivity within (intrinsic) and between (extrinsic) 4 key regions of the semantic network at rest, namely the anterior temporal lobe, the inferior frontal gyrus (IFG), the posterior middle temporal gyrus (MTG), and the angular gyrus.

RESULTS

We included 60 participants, including 30 patients with FES and 30 controls. We observed higher perplexity in the FES group, indicating that speech was less predictable by the preceding context among patients. Results of Bayesian model comparisons showed that a DCM including the group by perplexity interaction best explained the underlying patterns of neural activity. We observed an increase of self-inhibitory effective connectivity within the IFG, as well as reduced self-inhibitory tone within the pMTG, in the FES group. An increase in self-inhibitory tone in the IFG correlated strongly and positively with inter-regional excitation between the IFG and posterior MTG, while self-inhibition of the posterior MTG was negatively correlated with this interregional excitation.

LIMITATION

Our design did not address connectivity in the semantic network during tasks that selectively activated the semantic network, which could corroborate findings from this resting-state fMRI study. Furthermore, we do not present a replication study, which would ideally use speech in a different language.

CONCLUSION

As an explanation for peculiar speech in psychosis, these results index a shift in the excitatory-inhibitory balance regulating information flow across the semantic network, confined to 2 regions that were previously linked specifically to the executive control of meaning. Based on our approach of combining a large language model with causal connectivity estimates, we propose loss in semantic control as a potential neurocognitive mechanism contributing to disorganization in psychosis.

Two distinct networks for encoding goals and forms of action: An effective connectivity study

Goal-directed actions are characterized by two main features: the content (i.e., the action goal) and the form, called vitality forms (VF) (i.e., how actions are executed). It is well established that both the action content and the capacity to understand the content of another's action are mediated by a network formed by a set of parietal and frontal brain areas. In contrast, the neural bases of action forms (e.g., gentle or rude actions) have not been characterized. However, there are now studies showing that the observation and execution of actions endowed with VF activate, in addition to the parieto-frontal network, the dorso-central insula (DCI). In the present study, we established-using dynamic causal modeling (DCM)-the direction of information flow during observation and execution of actions endowed with gentle and rude VF in the human brain. Based on previous fMRI studies, the selected nodes for the DCM comprised the posterior superior temporal sulcus (pSTS), the inferior parietal lobule (IPL), the premotor cortex (PM), and the DCI. Bayesian model comparison showed that, during action observation, two streams arose from pSTS: one toward IPL, concerning the action goal, and one toward DCI, concerning the action vitality forms. During action execution, two streams arose from PM: one toward IPL, concerning the action goal and one toward DCI concerning action vitality forms. This last finding opens an interesting question concerning the possibility to elicit VF in two distinct ways: cognitively (from PM to DCI) and affectively (from DCI to PM).

Posterior default mode network is associated with the social performance in male children with autism spectrum disorder: A dynamic causal modeling analysis based on triple-network model

The triple-network model has been widely applied in neuropsychiatric disorders including autism spectrum disorder (ASD). However, the mechanism of causal regulations within the triple-network and their relations with symptoms of ASD remains unclear. 81 male ASD and 80 well matched typically developing control (TDC) were included in this study, recruited from Autism Brain Image Data Exchange-I datasets. Spatial reference-based independent component analysis was used to identify the anterior and posterior part of default-mode network (aDMN and pDMN), salience network (SN), and bilateral executive-control network (ECN) from resting-state functional magnetic resonance imaging data. Spectral dynamic causal model and parametric empirical Bayes with Bayesian model reduction/average were adopted to explore the effective connectivity (EC) within triple-network and the relationship between EC and autism diagnostic observation schedule (ADOS) scores. After adjusting for age and site effect, ASD and TDC groups both showed inhibition patterns. Compared with TDC, ASD group showed weaker self-inhibition in aDMN and pDMN, stronger inhibition in pDMN→aDMN, weaker inhibition in aDMN→LECN, pDMN→SN, LECN→SN, and LECN→RECN. Furthermore, negative relationships between ADOS scores and pDMN self-inhibition strength, as well as with the EC of pDMN→aDMN were observed in ASD group. The present study reveals imbalanced effective connections within triple-networks in ASD children. More attentions should be focused at the pDMN, which modulates the core symptoms of ASD and may serve as an important region for ASD diagnosis and the target region for ASD treatments.

Dynamic causal modeling analysis reveals the modulation of motor cortex and integration in superior temporal gyrus during multisensory speech perception

The processing of speech information from various sensory modalities is crucial for human communication. Both left posterior superior temporal gyrus (pSTG) and motor cortex importantly involve in the multisensory speech perception. However, the dynamic integration of primary sensory regions to pSTG and the motor cortex remain unclear. Here, we implemented a behavioral experiment of classical McGurk effect paradigm and acquired the task functional magnetic resonance imaging (fMRI) data during synchronized audiovisual syllabic perception from 63 normal adults. We conducted dynamic causal modeling (DCM) analysis to explore the cross-modal interactions among the left pSTG, left precentral gyrus (PrG), left middle superior temporal gyrus (mSTG), and left fusiform gyrus (FuG). Bayesian model selection favored a winning model that included modulations of connections to PrG (mSTG → PrG, FuG → PrG), from PrG (PrG → mSTG, PrG → FuG), and to pSTG (mSTG → pSTG, FuG → pSTG). Moreover, the coupling strength of the above connections correlated with behavioral McGurk susceptibility. In addition, significant differences were found in the coupling strength of these connections between strong and weak McGurk perceivers. Strong perceivers modulated less inhibitory visual influence, allowed less excitatory auditory information flowing into PrG, but integrated more audiovisual information in pSTG. Taken together, our findings show that the PrG and pSTG interact dynamically with primary cortices during audiovisual speech, and support the motor cortex plays a specifically functional role in modulating the gain and salience between auditory and visual modalities.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-09945-z.

Impact of data processing varieties on DCM estimates of effective connectivity from task-fMRI

Effective connectivity (EC) refers to directional or causal influences between interacting neuronal populations or brain regions and can be estimated from functional magnetic resonance imaging (fMRI) data via dynamic causal modeling (DCM). In contrast to functional connectivity, the impact of data processing varieties on DCM estimates of task-evoked EC has hardly ever been addressed. We therefore investigated how task-evoked EC is affected by choices made for data processing. In particular, we considered the impact of global signal regression (GSR), block/event-related design of the general linear model (GLM) used for the first-level task-evoked fMRI analysis, type of activation contrast, and significance thresholding approach. Using DCM, we estimated individual and group-averaged task-evoked EC within a brain network related to spatial conflict processing for all the parameters considered and compared the differences in task-evoked EC between any two data processing conditions via between-group parametric empirical Bayes (PEB) analysis and Bayesian data comparison (BDC). We observed strongly varying patterns of the group-averaged EC depending on the data processing choices. In particular, task-evoked EC and parameter certainty were strongly impacted by GLM design and type of activation contrast as revealed by PEB and BDC, respectively, whereas they were little affected by GSR and the type of significance thresholding. The event-related GLM design appears to be more sensitive to task-evoked modulations of EC, but provides model parameters with lower certainty than the block-based design, while the latter is more sensitive to the type of activation contrast than is the event-related design. Our results demonstrate that applying different reasonable data processing choices can substantially alter task-evoked EC as estimated by DCM. Such choices should be made with care and, whenever possible, varied across parallel analyses to evaluate their impact and identify potential convergence for robust outcomes.

Pathological claustrum activity drives aberrant cognitive network processing in human chronic pain

Aberrant cognitive network activity and cognitive deficits are established features of chronic pain. However, the nature of cognitive network alterations associated with chronic pain and their underlying mechanisms require elucidation. Here, we report that the claustrum, a subcortical nucleus implicated in cognitive network modulation, is activated by acute painful stimulation and pain-predictive cues in healthy participants. Moreover, we discover pathological activity of the claustrum and a region near the posterior inferior frontal sulcus of the right dorsolateral prefrontal cortex (piDLPFC) in migraine patients during acute pain and cognitive task performance. Dynamic causal modeling suggests a directional influence of the claustrum on activity in this piDLPFC region, and diffusion weighted imaging verifies their structural connectivity. These findings advance understanding of claustrum function during acute pain and provide evidence of a possible circuit mechanism driving cognitive impairments in chronic pain.

Altered effective connectivity among face-processing systems in major depressive disorder

BACKGROUND

Neuroimaging studies have revealed abnormal functional interaction during the processing of emotional faces in patients with major depressive disorder (MDD), thereby enhancing our comprehension of the pathophysiology of MDD. However, it is unclear whether there is abnormal directional interaction among face-processing systems in patients with MDD.

METHODS

A group of patients with MDD and a healthy control group underwent a face-matching task during functional magnetic resonance imaging. Dynamic causal modelling (DCM) analysis was used to investigate effective connectivity between 7 regions in the face-processing systems. We used a Parametric Empirical Bayes model to compare effective connectivity between patients with MDD and controls.

RESULTS

We included 48 patients and 44 healthy controls in our analyses. Both groups showed higher accuracy and faster reaction time in the shape-matching condition than in the face-matching condition. However, no significant behavioural or brain activation differences were found between the groups. Using DCM, we found that, compared with controls, patients with MDD showed decreased self-connection in the right dorsolateral prefrontal cortex (DLPFC), amygdala, and fusiform face area (FFA) across task conditions; increased intrinsic connectivity from the right amygdala to the bilateral DLPFC, right FFA, and left amygdala, suggesting an increased intrinsic connectivity centred in the amygdala in the right side of the face-processing systems; both increased and decreased positive intrinsic connectivity in the left side of the face-processing systems; and comparable task modulation effect on connectivity.

LIMITATIONS

Our study did not include longitudinal neuroimaging data, and there was limited region of interest selection in the DCM analysis.

CONCLUSION

Our findings provide evidence for a complex pattern of alterations in the face-processing systems in patients with MDD, potentially involving the right amygdala to a greater extent. The results confirm some previous findings and highlight the crucial role of the regions on both sides of face-processing systems in the pathophysiology of MDD.

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

BACKGROUND

While the exploration of serotonergic psychedelics as psychiatric medicines deepens, so does the pressure to better understand how these compounds act on the brain.

METHODS

We 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.

RESULTS

Compared 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.

CONCLUSIONS

The results advance our knowledge about the action of psychedelics on the brain and refine current models aiming to explain the underlying neurobiological processes.

Effect of scanning duration and sample size on reliability in resting state fMRI dynamic causal modeling analysis

Despite its widespread use, resting-state functional magnetic resonance imaging (rsfMRI) has been criticized for low test-retest reliability. To improve reliability, researchers have recommended using extended scanning durations, increased sample size, and advanced brain connectivity techniques. However, longer scanning runs and larger sample sizes may come with practical challenges and burdens, especially in rare populations. Here we tested if an advanced brain connectivity technique, dynamic causal modeling (DCM), can improve reliability of fMRI effective connectivity (EC) metrics to acceptable levels without extremely long run durations or extremely large samples. Specifically, we employed DCM for EC analysis on rsfMRI data from the Human Connectome Project. To avoid bias, we assessed four distinct DCMs and gradually increased sample sizes in a randomized manner across ten permutations. We employed pseudo true positive and pseudo false positive rates to assess the efficacy of shorter run durations (3.6, 7.2, 10.8, 14.4 min) in replicating the outcomes of the longest scanning duration (28.8 min) when the sample size was fixed at the largest (n = 160 subjects). Similarly, we assessed the efficacy of smaller sample sizes (n = 10, 20, …, 150 subjects) in replicating the outcomes of the largest sample (n = 160 subjects) when the scanning duration was fixed at the longest (28.8 min). Our results revealed that the pseudo false positive rate was below 0.05 for all the analyses. After the scanning duration reached 10.8 min, which yielded a pseudo true positive rate of 92%, further extensions in run time showed no improvements in pseudo true positive rate. Expanding the sample size led to enhanced pseudo true positive rate outcomes, with a plateau at n = 70 subjects for the targeted top one-half of the largest ECs in the reference sample, regardless of whether the longest run duration (28.8 min) or the viable run duration (10.8 min) was employed. Encouragingly, smaller sample sizes exhibited pseudo true positive rates of approximately 80% for n = 20, and 90% for n = 40 subjects. These data suggest that advanced DCM analysis may be a viable option to attain reliable metrics of EC when larger sample sizes or run times are not feasible.

Weakened effective connectivity between salience network and default mode network during resting state in adolescent depression

Adolescent major depressive disorder (MDD) is associated with altered resting-state connectivity between the default mode network (DMN) and the salience network (SN), which are involved in self-referential processing and detecting and filtering salient stimuli, respectively. Using spectral dynamical causal modelling, we investigated the effective connectivity and input sensitivity between key nodes of these networks in 30 adolescents with MDD and 32 healthy controls while undergoing resting-state fMRI. We found that the DMN received weaker inhibition from the SN and that the medial prefrontal cortex and the anterior cingulate cortex showed reduced self-inhibition in MDD, making them more prone to external influences. Moreover, we found that selective serotonin reuptake inhibitor (SSRI) intake was associated with decreased and increased self-inhibition of the SN and DMN, respectively, in patients. Our findings suggest that adolescent MDD is characterized by a hierarchical imbalance between the DMN and the SN, which could affect the integration of emotional and self-related information. We propose that SSRIs may help restore network function by modulating excitatory/inhibitory balance in the DMN and the SN. Our study highlights the potential of prefrontal-amygdala interactions as a biomarker and a therapeutic target for adolescent depression.

Effects of escitalopram therapy on effective connectivity among core brain networks in major depressive disorder

BACKGROUND

Patients with major depressive disorder (MDD) have abnormal functional interaction among large-scale brain networks, indicated by aberrant effective connectivity of the default mode network (DMN), salience network (SN), and dorsal attention network (DAN). However, it remains unclear whether antidepressants can normalize the altered effective connectivity in MDD.

METHODS

In this study, we collected resting-state functional magnetic resonance imaging data from 46 unmedicated patients with MDD at baseline and after 12 weeks of escitalopram treatment. We also collected data from 58 healthy controls (HCs) at the same time point with the same interval. Using spectral dynamic causal modeling and parametric empirical Bayes, we examined group differences, time effect and their interaction on the casual interactions among the regions of interest in the three networks.

RESULTS

Compared with HCs, patients with MDD showed increased positive (excitatory) connections within the DMN, decreased positive connections within the SN and DAN, decreased absolute value of negative (inhibitory) connectivity from the SN and DAN to the DMN, and decreased positive connections between the DAN and the SN. Furthermore, we found that six connections related to the DAN showed decreased group differences in effective connectivity between MDD and HCs during follow-up compared to the baseline.

CONCLUSIONS

Our findings suggest that escitalopram therapy can partly improve the disrupted effective connectivity among high-order brain functional networks in MDD. These findings deepened our understanding of the neural basis of antidepressants' effect on brain function in patients with MDD.

Spectral dynamic causal modeling: A didactic introduction and its relationship with functional connectivity

We present a didactic introduction to spectral dynamic causal modeling (DCM), a Bayesian state-space modeling approach used to infer effective connectivity from noninvasive neuroimaging data. Spectral DCM is currently the most widely applied DCM variant for resting-state functional MRI analysis. Our aim is to explain its technical foundations to an audience with limited expertise in state-space modeling and spectral data analysis. Particular attention will be paid to cross-spectral density, which is the most distinctive feature of spectral DCM and is closely related to functional connectivity, as measured by (zero-lag) Pearson correlations. In fact, the model parameters estimated by spectral DCM are those that best reproduce the cross-correlations between all measurements-at all time lags-including the zero-lag correlations that are usually interpreted as functional connectivity. We derive the functional connectivity matrix from the model equations and show how changing a single effective connectivity parameter can affect all pairwise correlations. To complicate matters, the pairs of brain regions showing the largest changes in functional connectivity do not necessarily coincide with those presenting the largest changes in effective connectivity. We discuss the implications and conclude with a comprehensive summary of the assumptions and limitations of spectral DCM.

Association of abnormal explicit sense of agency with cerebellar impairment in myoclonus-dystonia

Non-motor aspects in dystonia are now well recognized. The sense of agency, which refers to the experience of controlling one's own actions, has been scarcely studied in dystonia, even though its disturbances can contribute to movement disorders. Among various brain structures, the cerebral cortex, the cerebellum, and the basal ganglia are involved in shaping the sense of agency. In myoclonus dystonia, resulting from a dysfunction of the motor network, an altered sense of agency may contribute to the clinical phenotype of the condition. In this study, we compared the explicit and implicit sense of agency in patients with myoclonus dystonia caused by a pathogenic variant of SGCE (DYT-SGCE) and control participants. We utilized behavioural tasks to assess the sense of agency and performed neuroimaging analyses, including structural, resting-state functional connectivity, and dynamic causal modelling, to explore the relevant brain regions involved in the sense of agency. Additionally, we examined the relationship between behavioural performance, symptom severity, and neuroimaging findings. We compared 19 patients with DYT-SGCE and 24 healthy volunteers. Our findings revealed that patients with myoclonus-dystonia exhibited a specific impairment in explicit sense of agency, particularly when implicit motor learning was involved. However, their implicit sense of agency remained intact. These patients also displayed grey-matter abnormalities in the motor cerebellum, as well as increased functional connectivity between the cerebellum and pre-supplementary motor area. Dynamic causal modelling analysis further identified reduced inhibitory effects of the cerebellum on the pre-supplementary motor area, decreased excitatory effects of the pre-supplementary motor area on the cerebellum, and increased self-inhibition within the pre-supplementary motor area. Importantly, both cerebellar grey-matter alterations and functional connectivity abnormalities between the cerebellum and pre-supplementary motor area were found to correlate with explicit sense of agency impairment. Increased self-inhibition within the pre-supplementary motor area was associated with less severe myoclonus symptoms. These findings highlight the disruption of higher-level cognitive processes in patients with myoclonus-dystonia, further expanding the spectrum of neurological and psychiatric dysfunction already identified in this disorder.

Reduced default mode network effective connectivity in healthy aging is modulated by years of education

Aging is a major risk factor for neurodegenerative diseases like dementia and Alzheimer's disease. Even in non-pathological aging, decline in cognitive functioning is observed in the majority of the elderly population, necessitating the importance of studying the processes involved in healthy aging in order to identify brain biomarkers that promote the conservation of functioning. The default mode network (DMN) has been of special interest to aging research due to its vulnerability to atrophy and functional decline over the course of aging. Prior work has focused almost exclusively on functional (i.e. undirected) connectivity, yet converging findings are scarce. Therefore, we set out to use spectral dynamic causal modeling to investigate changes in the effective (i.e. directed) connectivity within the DMN and to discover changes in information flow in a sample of cognitively normal adults spanning from 48 to 89 years (n = 63). Age was associated to reduced verbal memory performance. Modeling of effective connectivity revealed a pattern of age-related downregulation of posterior DMN regions driven by inhibitory connections from the hippocampus and middle temporal gyrus. Additionally, there was an observed decline in the hippocampus' susceptibility to network inputs with age, effectively disconnecting itself from other regions. The estimated effective connectivity parameters were robust and able to predict the age in out of sample estimates in a leave-one-out cross-validation. Attained education moderated the effects of aging, largely reversing the observed pattern of inhibitory connectivity. Thus, medial prefrontal cortex, hippocampus and posterior DMN regions formed an excitatory cycle of extrinsic connections related to the interaction of age and education. This suggests a compensatory role of years of education in effective connectivity, stressing a possible target for interventions. Our findings suggest a connection to the concept of cognitive reserve, which attributes a protective effect of educational level on cognitive decline in aging (Stern, 2009).