Maximizing negative correlations in resting-state functional connectivity MRI by time-lag

Competitive interactions shape brain dynamics and computation across species

Adaptive cognition relies on cooperation across anatomically distributed brain circuits. However, specialised neural systems are also in constant competition for limited processing resources. How does the brain's network architecture enable it to balance these cooperative and competitive tendencies? Here we use computational whole-brain modelling to examine the dynamical and computational relevance of cooperative and competitive interactions in the mammalian connectome. Across human, macaque, and mouse we show that the architecture of the models that most faithfully reproduce brain activity, consistently combines modular cooperative interactions with diffuse, long-range competitive interactions. The model with competitive interactions consistently outperforms the cooperative-only model, with excellent fit to both spatial and dynamical properties of the living brain, which were not explicitly optimised but rather emerge spontaneously. Competitive interactions in the effective connectivity produce greater levels of synergistic information and local-global hierarchy, and lead to superior computational capacity when used for neuromorphic computing. Altogether, this work provides a mechanistic link between network architecture, dynamical properties, and computation in the mammalian brain.

Distinct connectivity patterns in bipolar and unipolar depression: a functional connectivity multivariate pattern analysis study

BACKGROUND

Patients with bipolar disorder (BD) and major depressive disorder (MDD) exhibit depressive episodes with similar symptoms despite having different and poorly understood underlying neurobiology, often leading to misdiagnosis and improper treatment. This exploratory study examined whole-brain functional connectivity (FC) using FC multivariate pattern analysis (fc-MVPA) to identify the FC patterns with the greatest ability to distinguish between currently depressed patients with BD type I (BD I) and those with MDD.

METHODOLOGY

In a cross-sectional design, 41 BD I, 40 MDD patients and 63 control participants completed resting state functional magnetic resonance imaging scans. Data-driven fc-MVPA, as implemented in the CONN toolbox, was used to identify clusters with differential FC patterns between BD patients and MDD patients. The identified cluster was used as a seed in a post hoc seed-based analysis (SBA) to reveal associated connectivity patterns, followed by a secondary ROI-to-ROI analysis to characterize differences in connectivity between these patterns among BD I patients, MDD patients and controls.

RESULTS

FC-MVPA identified one cluster located in the right frontal pole (RFP). The subsequent SBA revealed greater FC between the RFP and posterior cingulate cortex (PCC) and between the RFP and the left inferior/middle temporal gyrus (LI/MTG) and lower FC between the RFP and the left precentral gyrus (LPCG), left lingual gyrus/occipital cortex (LLG/OCC) and right occipital cortex (ROCC) in MDD patients than in BD patients. Compared with the controls, ROI-to-ROI analysis revealed lower FC between the RFP and the PCC and greater FC between the RFP and the LPCG, LLG/OCC and ROCC in BD patients; in MDD patients, the analysis revealed lower FC between the RFP and the LLG/OCC and ROCC and greater FC between the RFP and the LI/MTG.

CONCLUSIONS

Differences in the RFP FC patterns between currently depressed patients with BD and those with MDD suggest potential neuroimaging markers that should be further examined. Specifically, BD patients exhibit increased FC between the RFP and the motor and visual networks, which is associated with psychomotor symptoms and heightened compensatory frontoparietal FC to counter distractibility. In contrast, MDD patients exhibit increased FC between the RFP and the default mode network, corresponding to sustained self-focus and rumination.

Mapping functional traces of opioid memories in the rat brain

Addiction to psychoactive substances is a maladaptive learned behaviour. Contexts surrounding drug use integrate this aberrant mnemonic process and hold strong relapse-triggering ability. Here, we asked where context and salience might be concurrently represented in the brain during retrieval of drug-context paired associations. For this, we developed a morphine-conditioned place preference protocol that allows contextual stimuli presentation inside a magnetic resonance imaging scanner and investigated differences in activity and connectivity at context recall. We found context-specific responses to stimulus onset in multiple brain regions, namely, limbic, sensory and striatal. Differences in functional interconnectivity were found among amygdala, lateral habenula, and lateral septum. We also investigated alterations to resting-state functional connectivity and found increased centrality of the lateral septum in a proposed limbic network, as well as increased functional connectivity of the lateral habenula and hippocampal 'cornu ammonis' 1 region, after a protocol of associative drug-context. Finally, we found that pre- conditioned place preference resting-state connectivity of the lateral habenula and amygdala was predictive of inter-individual conditioned place preference score differences. Overall, our findings show that drug and saline-paired contexts establish distinct memory traces in overlapping functional brain microcircuits and that intrinsic connectivity of the habenula, septum, and amygdala likely underlies the individual maladaptive contextual learning to opioid exposure. We have identified functional maps of acquisition and retrieval of drug-related memory that may support the relapse-triggering ability of opioid-associated sensory and contextual cues. These findings may clarify the inter-individual sensitivity and vulnerability seen in addiction to opioids found in humans.

Structural parameters are superior to eigenvector centrality in detecting progressive supranuclear palsy with machine learning & multimodal MRI

Progressive supranuclear palsy (PSP) is an atypical Parkinsonian syndrome characterized initially by falls and eye movement impairment. This multimodal imaging study aimed at eliciting structural and functional disease-specific brain alterations. T1-weighted and resting-state functional MRI were applied in multi-centric cohorts of PSP and matched healthy controls. Midbrain, cerebellum, and cerebellar peduncles showed severely low gray/white matter volume, whereas thinner cortical gray matter was observed in cingulate cortex, medial and temporal gyri, and insula. Eigenvector centrality analyses revealed regionally specific alterations. Multivariate pattern recognition classified patients correctly based on gray and white matter segmentations with up to 98 % accuracy. Highest accuracies were obtained when restricting feature selection to the midbrain. Eigenvector centrality indices yielded an accuracy around 70 % in this comparison; however, this result did not reach significance. In sum, the study reveals multimodal, widespread brain changes in addition to the well-known midbrain atrophy in PSP. Alterations in brain structure seem to be superior to eigenvector centrality parameters, in particular for prediction with machine learning approaches.

A systematic review of childhood maltreatment and resting state functional connectivity

Resting-state functional connectivity (rsFC) has the potential to shed light on how childhood abuse and neglect relates to negative psychiatric outcomes. However, a comprehensive review of the impact of childhood maltreatment on the brain's resting state functional organization has not yet been undertaken. We systematically searched rsFC studies in children and youth exposed to maltreatment. Nineteen studies (total n = 3079) met our inclusion criteria. Two consistent findings were observed. Childhood maltreatment was linked to reduced connectivity between the anterior insula and dorsal anterior cingulate cortex, and with widespread heightened amygdala connectivity with key structures in the salience, default mode, and prefrontal regulatory networks. Other brain regions showing altered connectivity included the ventral anterior cingulate cortex, dorsolateral prefrontal cortex, and hippocampus. These patterns of altered functional connectivity associated with maltreatment exposure were independent of symptoms, yet comparable to those seen in individuals with overt clinical disorder. Summative findings indicate that rsFC alterations associated with maltreatment experience are related to poor cognitive and social functioning and are prognostic of future symptoms. In conclusion, maltreatment is associated with altered rsFC in emotional reactivity, regulation, learning, and salience detection brain circuits. This indicates patterns of recalibration of putative mechanisms implicated in maladaptive developmental outcomes.

Peripheral inflammatory subgroup differences in anterior Default Mode network and multiplex functional network topology are associated with cognition in psychosis

INTRODUCTION

High-inflammation subgroups of patients with psychosis demonstrate cognitive deficits and neuroanatomical alterations. Systemic inflammation assessed using IL-6 and C-reactive protein may alter functional connectivity within and between resting-state networks, but the cognitive and clinical implications of these alterations remain unknown. We aim to determine the relationships of elevated peripheral inflammation subgroups with resting-state functional networks and cognition in psychosis spectrum disorders.

METHODS

Serum and resting-state fMRI were collected from psychosis probands (schizophrenia, schizoaffective, psychotic bipolar disorder) and healthy controls (HC) from the B-SNIP1 (Chicago site) study who were stratified into inflammatory subgroups based on factor and cluster analyses of 13 cytokines (HC Low n = 32, Proband Low n = 65, Proband High n = 29). Nine resting-state networks derived from independent component analysis were used to assess functional and multilayer connectivity. Inter-network connectivity was measured using Fisher z-transformation of correlation coefficients. Network organization was assessed by investigating networks of positive and negative connections separately, as well as investigating multilayer networks using both positive and negative connections. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia. Linear regressions, Spearman correlations, permutations tests and multiple comparison corrections were used for analyses in R.

RESULTS

Anterior default mode network (DMNa) connectivity was significantly reduced in the Proband High compared to Proband Low (Cohen's d = -0.74, p = 0.002) and HC Low (d = -0.85, p = 0.0008) groups. Inter-network connectivity between the DMNa and the right-frontoparietal networks was lower in Proband High compared to Proband Low (d = -0.66, p = 0.004) group. Compared to Proband Low, the Proband High group had lower negative (d = 0.54, p = 0.021) and positive network (d = 0.49, p = 0.042) clustering coefficient, and lower multiplex network participation coefficient (d = -0.57, p = 0.014). Network findings in high inflammation subgroups correlate with worse verbal fluency, verbal memory, symbol coding, and overall cognition.

CONCLUSION

These results expand on our understanding of the potential effects of peripheral inflammatory signatures and/or subgroups on network dysfunction in psychosis and how they relate to worse cognitive performance. Additionally, the novel multiplex approach taken in this study demonstrated how inflammation may disrupt the brain's ability to maintain healthy co-activation patterns between the resting-state networks while inhibiting certain connections between them.

Longitudinal study in adolescent anorexia nervosa: evaluation of cortico-striatal and default mode network resting-state brain circuits

Anorexia nervosa (AN) typically emerges in adolescence. The cortico-striatal system (CSTS) and the default mode network (DMN) are brain circuits with a crucial development during this period. These circuits underlie cognitive functions that are impaired in AN, such as cognitive flexibility and inhibition, among others. Little is known about their involvement in adolescent AN and how weight and symptom improvement might modulate potential alterations in these circuits. Forty-seven adolescent females (30 AN, 17 healthy control) were clinically/neuropsychologically evaluated and scanned during a 3T-MRI resting-state session on two occasions, before and after a 6-month multidisciplinary treatment of the AN patients. Baseline and baseline-to-follow-up between-group differences in CSTS and DMN resting-state connectivity were evaluated, as well as their association with clinical/neuropsychological variables. Increased connectivity between the left dorsal putamen and the left precuneus was found in AN at baseline. At follow-up, body mass index and clinical symptoms had improved in the AN group. An interaction effect was found in the connectivity between the right dorsal caudate to right mid-anterior insular cortex, with lower baseline AN connectivity that improved at follow-up; this improvement was weakly associated with changes in neuropsychological (Stroop test) performance. These results support the presence of CSTS connectivity alterations in adolescents with AN, which improve with weight and symptom improvement. In addition, at the level of caudate-insula connectivity, they might be associated with inhibitory processing performance. Alterations in CSTS pathways might be involved in AN from the early stages of the disorder.

Sex differences in multilayer functional network topology over the course of aging in 37543 UK Biobank participants

Aging is a major risk factor for cardiovascular and neurodegenerative disorders, with considerable societal and economic implications. Healthy aging is accompanied by changes in functional connectivity between and within resting-state functional networks, which have been associated with cognitive decline. However, there is no consensus on the impact of sex on these age-related functional trajectories. Here, we show that multilayer measures provide crucial information on the interaction between sex and age on network topology, allowing for better assessment of cognitive, structural, and cardiovascular risk factors that have been shown to differ between men and women, as well as providing additional insights into the genetic influences on changes in functional connectivity that occur during aging. In a large cross-sectional sample of 37,543 individuals from the UK Biobank cohort, we demonstrate that such multilayer measures that capture the relationship between positive and negative connections are more sensitive to sex-related changes in the whole-brain connectivity patterns and their topological architecture throughout aging, when compared to standard connectivity and topological measures. Our findings indicate that multilayer measures contain previously unknown information on the relationship between sex and age, which opens up new avenues for research into functional brain connectivity in aging.

Cognitive enhancement: Effects of methylphenidate, modafinil, and caffeine on latent memory and resting state functional connectivity in healthy adults

Stimulants like methylphenidate, modafinil, and caffeine have repeatedly shown to enhance cognitive processes such as attention and memory. However, brain-functional mechanisms underlying such cognitive enhancing effects of stimulants are still poorly characterized. Here, we utilized behavioral and resting-state fMRI data from a double-blind randomized placebocontrolled study of methylphenidate, modafinil, and caffeine in 48 healthy male adults. The results show that performance in different memory tasks is enhanced, and functional connectivity (FC) specifically between the frontoparietal network (FPN) and default mode network (DMN) is modulated by the stimulants in comparison to placebo. Decreased negative connectivity between right prefrontal and medial parietal but also between medial temporal lobe and visual brain regions predicted stimulant-induced latent memory enhancement. We discuss dopamine's role in attention and memory as well as its ability to modulate FC between large-scale neural networks (e.g., FPN and DMN) as a potential cognitive enhancement mechanism.

Vestibular Morphological Asymmetry Associated With Motion Sickness Susceptibility

Sensory conflicts leading to motion sickness can occur not only between but also within sensory modalities. The vestibular organs are located in both left and right inner ears, and their misalignment can be a source of self-motion related sensory conflicts. In the current study, using inner ear magnetic resonance imaging, we examined whether morphological asymmetry of the bilateral vestibular organs was associated with motion sickness susceptibility. The results showed a larger position asymmetry of bilateral vestibular organs in individuals with high rather than low susceptibility. In addition, vestibular position asymmetry was associated with reciprocal interaction (negative resting state functional connectivity) between vestibular and visuocortical regions in lowly, but not highly, susceptible individuals. In conclusion, these findings suggest that vestibular morphological asymmetry can be a source of sensory conflicts in individuals with dysfunctional reciprocal visuo-vestibular interactions, a putative neural mechanism for resolving sensory conflicts.

Constructing Multi-view High-order Functional Connectivity Networks for Diagnosis of Autism Spectrum Disorder

Brain functional connectivity network (FCN) based on resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used to identify neuropsychiatric disorders such as autism spectrum disorder (ASD). Most existing FCN-based methods only estimate the correlation between brain regions of in terest (ROIs), without exploring more informative higher-level inter actions among multiple ROIs which could be beneficial to disease diagnosis. To fully explore the discriminative information provided by different brain networks, a cluster-based multi-view high-order FCN (Ho-FCN) framework is proposed in this paper. Specifically, we first group the functional connectivity (FC) time series into different clusters and compute the multi-order central moment series for the FC time series in each cluster. Then we utilize the correlation of central moment series between different clusters to reveal the high-order FC relationships among multiple ROIs. In addition, to address the phase mismatch issue in conventional FCNs, we also adopt the central moments of the correlation time series as the temporal-invariance features to capture the dynamic characteristics of low-order dynamic FCN (Lo-D-FCN). Experimental results on the ABIDE dataset validate that: 1) the proposed multi-view Ho-FCNs is able to explore rich discriminative information for ASD diagnosis; 2) the phase mismatch issue can be well circumvented by using central moments; and 3) the combination of different types of FCNs can significantly improve the diagnostic accuracy of ASD (86.2%).

Salience network glutamate and brain connectivity in medication-naïve first episode patients - A multimodal magnetic resonance spectroscopy and resting state functional connectivity MRI study

BACKGROUND

Salience network (SN) connectivity is altered in schizophrenia, but the pathophysiological origin remains poorly understood. The goal of this multimodal neuroimaging study was to investigate the role of glutamatergic metabolism as putative mechanism underlying SN dysconnectivity in first episode psychosis (FEP) subjects.

METHODS

We measured glutamate + glutamine (Glx) in the dorsal anterior cingulate cortex (dACC) from 70 antipsychotic-naïve FEP subjects and 52 healthy controls (HC). The dACC was then used as seed to define positive and negative resting state functional connectivity (FC) of the SN. We used multiple regression analyses to test main effects and group interactions of Glx and FC associations.

RESULTS

dACC Glx levels did not differ between groups. Positive FC was significantly reduced in FEP compared to HC, and no group differences were found in negative FC. Group interactions of Glx-FC associations were found within the SN for positive FC, and in parietal cortices for negative FC. In HC, higher Glx levels predicted greater positive FC in the dACC and insula, and greater negative FC of the lateral parietal cortex. These relationships were weaker or absent in FEP.

CONCLUSIONS

Here, we found that positive FC in the SN is already altered in medication-naïve FEP, underscoring the importance of considering both correlations and anticorrelations for characterization of pathology. Our data demonstrate that Glx and functional connectivity work differently in FEP than in HC, pointing to a possible mechanism underlying dysconnectivity in psychosis.

Constructing high-order functional connectivity network based on central moment features for diagnosis of autism spectrum disorder

The sliding-window-based dynamic functional connectivity network (D-FCN) has been becoming an increasingly useful tool for understanding the changes of brain connectivity patterns and the association of neurological diseases with these dynamic variations. However, conventional D-FCN is essentially low-order network, which only reflects the pairwise interaction pattern between brain regions and thus overlooking the high-order interactions among multiple brain regions. In addition, D-FCN is innate with temporal sensitivity issue, i.e., D-FCN is sensitive to the chronological order of its subnetworks. To deal with the above issues, we propose a novel high-order functional connectivity network framework based on the central moment feature of D-FCN. Specifically, we firstly adopt a central moment approach to extract multiple central moment feature matrices from D-FCN. Furthermore, we regard the matrices as the profiles to build multiple high-order functional connectivity networks which further capture the higher level and more complex interaction relationships among multiple brain regions. Finally, we use the voting strategy to combine the high-order networks with D-FCN for autism spectrum disorder diagnosis. Experimental results show that the combination of multiple functional connectivity networks achieves accuracy of 88.06%, and the best single network achieves accuracy of 79.5%.

Central amygdala circuitry modulates nociceptive processing through differential hierarchical interaction with affective network dynamics

The central amygdala (CE) emerges as a critical node for affective processing. However, how CE local circuitry interacts with brain wide affective states is yet uncharted. Using basic nociception as proxy, we find that gene expression suggests diverging roles of the two major CE neuronal populations, protein kinase C δ-expressing (PKCδ⁺) and somatostatin-expressing (SST⁺) cells. Optogenetic (o)fMRI demonstrates that PKCδ⁺/SST⁺ circuits engage specific separable functional subnetworks to modulate global brain dynamics by a differential bottom-up vs. top-down hierarchical mesoscale mechanism. This diverging modulation impacts on nocifensive behavior and may underly CE control of affective processing.

In order to examine how central amygdala (CE) local circuitry interacts with brain-wide affective states, Wank et al performed gene expression analysis and optogenetic fMRI in mice, using basic nociception as a proxy. They found evidence for diverging roles of two major CE neuronal populations in modulating global brain states, which impacts on aversive processing and nocifensive behaviour.

Functional connectivity of the anterior cingulate cortex with pain-related regions in children with post-traumatic headache

Introduction:

Post-traumatic headaches (PTH) are common following mild traumatic brain injury (mTBI). There is evidence of altered central pain processing in adult PTH; however, little is known about how children with PTH process pain. The anterior cingulate cortex (ACC) plays a critical role in descending central pain modulation. In this study, we explored whether the functional connectivity (FC) of the ACC is altered in children with PTH.

Methods:

In this case-control study, we investigated resting-state FC of 5 ACC seeds (caudal, dorsal, rostral, perigenual, and subgenual) in children with PTH ( n = 73) and without PTH ( n = 29) following mTBI, and healthy controls ( n = 27). Post-concussion symptoms were assessed using the Post-Concussion Symptom Inventory and the Child Health Questionnaire. Resting-state functional Magnetic Resonance Imaging (fMRI) data were used to generate maps of ACC FC. Group-level comparisons were performed within a target mask comprised of pain-related regions using FSL Randomise.

Results:

We found decreased FC between the right perigenual ACC and the left cerebellum, and increased FC between the right subgenual ACC and the left dorsolateral prefrontal cortex in children with PTH compared to healthy controls. The ACC FC in children without PTH following mTBI did not differ from the group with PTH or healthy controls. FC between rostral and perigenual ACC seeds and the cerebellum was increased in children with PTH with pre-injury headaches compared to those with PTH without pre-injury headaches. There was a positive relationship between PTH severity and rostral ACC FC with the bilateral thalamus, right hippocampus and periaqueductal gray.

Conclusions:

Central pain processing is altered in children with PTH. Pre-existing headaches help to drive this process.

Trial registration:

The PlayGame Trial was registered in ClinicalTrials.gov database ( ClinicalTrials.gov Identifier: NCT01874847).

BVAR-Connect: A Variational Bayes Approach to Multi-Subject Vector Autoregressive Models for Inference on Brain Connectivity Networks

In this paper we propose BVAR-connect, a variational inference approach to a Bayesian multi-subject vector autoregressive (VAR) model for inference on effective brain connectivity based on resting-state functional MRI data. The modeling framework uses a Bayesian variable selection approach that flexibly integrates multi-modal data, in particular structural diffusion tensor imaging (DTI) data, into the prior construction. The variational inference approach we develop allows scalability of the methods and results in the ability to estimate subject- and group-level brain connectivity networks over whole-brain parcellations of the data. We provide a brief description of a user-friendly MATLAB GUI released for public use. We assess performance on simulated data, where we show that the proposed inference method can achieve comparable accuracy to the sampling-based Markov Chain Monte Carlo approach but at a much lower computational cost. We also address the case of subject groups with imbalanced sample sizes. Finally, we illustrate the methods on resting-state functional MRI and structural DTI data on children with a history of traumatic injury.

Altered hippocampal-prefrontal functional network integrity in adult macaque monkeys with neonatal hippocampal lesions

The dorsolateral prefrontal cortex (DLPFC) and ventral lateral prefrontal cortex (VLPFC) play critical but different roles in working memory (WM) processes. Resting-state functional MRI (rs-fMRI) was employed to investigate the effects of neonatal hippocampal lesions on the functional connectivity (FC) between the hippocampus (H) and the DLPFC and VLPFC and its relation to WM performance in adult monkeys. Adult rhesus monkeys with neonatal H lesions (Neo-H, n = 5) and age- and gender-matched sham-operated monkeys (Neo-C, n = 5) were scanned around 10 years of age. The FC of H-DLPFC and H-VLPFC in Neo-H monkeys was significantly altered as compared to controls, but also switched from being positive in the Neo-C to negative in the Neo-H. In addition, the altered magnitude of FC between right H and bilateral DLPFC was significantly associated with the extent of the hippocampal lesions. In particular, the effects of neonatal hippocampal lesion on FC appeared to be selective to the left hemisphere of the brain (i.e. asymmetric in the two hemispheres). Finally, FC between H and DLPFC correlated with WM task performance on the SU-DNMS and the Obj-SO tasks for the control animals, but only with the H-VLPFC and SU-DNMS task for the Neo-H animals. In conclusion, the present rsfMRI study revealed that the neonatal hippocampal lesions significantly but differently altered the integrity in the functional connectivity of H-DLPFC and H-VLPFC. The similarities between the behavioral, cognitive and neural alterations in Neo-H monkeys and Schizophrenia (SZ) patients provide a strong translational model to develop new therapeutic tools for SZ.

Brain Connectivity Changes after Osteopathic Manipulative Treatment: A Randomized Manual Placebo-Controlled Trial

The effects of osteopathic manipulative treatment (OMT) on functional brain connectivity in healthy adults is missing in the literature. To make up for this lack, we applied advanced network analysis methods to analyze resting state functional magnetic resonance imaging (fMRI) data, after OMT and Placebo treatment (P) in 30 healthy asymptomatic young participants randomized into OMT and placebo groups (OMTg; Pg). fMRI brain activity measures, performed before (T0), immediately after (T1) and three days after (T2) OMT or P were used for inferring treatment effects on brain circuit functional organization. Repeated measures ANOVA and post-hoc analysis demonstrated that Right Precentral Gyrus (F (2, 32) = 5.995, p < 0.005) was more influential over the information flow immediately after the OMT, while decreased betweenness centrality in Left Caudate (F (2, 32) = 6.496, p < 0.005) was observable three days after. Clustering coefficient showed a distinct time-point and group effect. At T1, reduced neighborhood connectivity was observed after OMT in the Left Amygdala (L-Amyg) (F (2, 32) = 7.269, p < 0.005) and Left Middle Temporal Gyrus (F (2, 32) = 6.452, p < 0.005), whereas at T2 the L-Amyg and Vermis-III (F (2, 32) = 6.772, p < 0.005) increased functional interactions. Data demonstrated functional connectivity re-arrangement after OMT.

Sense of external agency is sustained by multisensory functional integration in the somatosensory cortex

"Sense of agency" (SoA), the feeling of control for events caused by one's own actions, is deceived by visuomotor incongruence. Sensorimotor networks are implicated in SoA, however little evidence exists on brain functionality during agency processing. Concurrently, it has been suggested that the brain's intrinsic resting-state (rs) activity has a preliminary influence on processing of agency cues. Here, we investigated the relation between performance in an agency attribution task and functional interactions among brain regions as derived by network analysis of rs functional magnetic resonance imaging. The action-effect delay was adaptively increased (range 90-1,620 ms) and behavioral measures correlated to indices of cognitive processes and appraised self-concepts. They were then regressed on local metrics of rs brain functional connectivity as to isolate the core areas enabling self-agency. Across subjects, the time window for self-agency was 90-625 ms, while the action-effect integration was impacted by self-evaluated personality traits. Neurally, the brain intrinsic organization sustaining consistency in self-agency attribution was characterized by high connectiveness in the secondary visual cortex, and regional segregation in the primary somatosensory area. Decreased connectiveness in the secondary visual area, regional segregation in the superior parietal lobule, and information control within a primary visual cortex-frontal eye fields network sustained self-agency over long-delayed effects. We thus demonstrate that self-agency is grounded on the intrinsic mode of brain function designed to organize information for visuomotor integration. Our observation is relevant for current models of psychopathology in clinical conditions in which both rs activity and sense of agency are altered.

One season of head-to-ball impact exposure alters functional connectivity in a central autonomic network

Repetitive head impacts represent a risk factor for neurological impairment in team-sport athletes. In the absence of symptoms, a physiological basis for acute injury has not been elucidated. A basic brain function that is disrupted after mild traumatic brain injury is the regulation of homeostasis, instantiated by activity across a specific set of brain regions that comprise a central autonomic network. We sought to relate head-to-ball impact exposure to changes in functional connectivity in a core set of central autonomic regions and then to determine the relation between changes in brain and changes in behavior, specifically cognitive control. Thirteen collegiate men's soccer players and eleven control athletes (golf, cross-country) underwent resting-state fMRI and behavioral testing before and after the season, and a core group of cortical, subcortical, and brainstem regions was selected to represent the central autonomic network. Head-to-ball impacts were recorded for each soccer player. Cognitive control was assessed using a Dot Probe Expectancy task. We observed that head-to-ball impact exposure was associated with diffuse increases in functional connectivity across a core CAN subnetwork. Increased functional connectivity between the left insula and left medial orbitofrontal cortex was associated with diminished proactive cognitive control after the season in those sustaining the greatest number of head-to-ball impacts. These findings encourage measures of autonomic physiology to monitor brain health in contact and collision sport athletes.

Disentangling brain functional network remodeling in corticobasal syndrome - A multimodal MRI study

OBJECTIVE

The clinical diagnosis of corticobasal syndrome (CBS) represents a challenge for physicians and reliable diagnostic imaging biomarkers would support the diagnostic work-up. We aimed to investigate the neural signatures of CBS using multimodal T1-weighted and resting-state functional magnetic resonance imaging (MRI).

METHODS

Nineteen patients with CBS (age 67.0 ± 6.0 years; mean±SD) and 19 matched controls (66.5 ± 6.0) were enrolled from the German Frontotemporal Lobar Degeneration Consortium. Changes in functional connectivity and structure were respectively assessed with eigenvector centrality mapping complemented by seed-based analysis and with voxel-based morphometry. In addition to mass-univariate statistics, multivariate support vector machine (SVM) classification tested the potential of multimodal MRI to differentiate patients and controls. External validity of SVM was assessed on independent CBS data from the 4RTNI database.

RESULTS

A decrease in brain interconnectedness was observed in the right central operculum, middle temporal gyrus and posterior insula, while widespread connectivity increases were found in the anterior cingulum, medial superior-frontal gyrus and in the bilateral caudate nuclei. Severe and diffuse gray matter volume reduction, especially in the bilateral insula, putamen and thalamus, characterized CBS. SVM classification revealed that both connectivity (area under the curve 0.81) and structural abnormalities (0.80) distinguished CBS from controls, while their combination led to statistically non-significant improvement in discrimination power, questioning the additional value of functional connectivity over atrophy. SVM analyses based on structural MRI generalized moderately well to new data, which was decisively improved when guided by meta-analytically derived disease-specific regions-of-interest.

CONCLUSIONS

Our data-driven results show impairment of functional connectivity and brain structure in CBS and explore their potential as imaging biomarkers.

Bidirectional signal exchanges and their mechanisms during joint attention interaction - A hyperscanning fMRI study

Social interactions are essential to our daily life. We tested the hypothesis that social interactions during joint attention (JA) require bidirectional communication, each with a different mechanism. We used a novel multivariate functional connectivity analysis, which enables obtaining directed pathways between four regions at each time-frequency point, with hyper-scanning MRI data of real-time JA interaction. Constructing multiple "4-regional directed pathways" and counting the number of times, regions engaged in feedforward or feedback processes in the 'sender' or the 'receiver brains, we obtained the following. (1) There were more regions in feedforward than in feedback processes (125 versus 99). (2) The right hemisphere was more involved in feedforward (74 versus 33), while the left hemisphere in feedback (66 versus 51). (3) The dmPFC was more engaged in feedforward (73 versus 44) while the TPJ in both (49 versus 45). (4) The dmPFC was more involved in the sending processes (i.e. initiation of feedforward and feedback) while the TPJ in the receiving processes. (5) JA interaction was involved with high MRI frequencies (0.04-0.1 Hz), while continues interactions by low MRI frequencies (0.01-0.04 Hz). (6) Initiation and responding to JA (i.e. IJA and RJA) evolved with composite neural systems: similar systems for pathways that included the dmPFC, vmPFC and the STS, and different systems for pathways that included the TPJ, vmPFC, PCC and the STS. These findings have important consequences in the basic understanding of social interaction and could help in diagnose and follow-up of social impairments.

Brain networks construction using Bayes FDR and average power function

Brain functional connectivity is a widely investigated topic in neuroscience. In recent years, the study of brain connectivity has been largely aided by graph theory. The link between time series recorded at multiple locations in the brain and the construction of a graph is usually an adjacency matrix. The latter converts a measure of the connectivity between two time series, typically a correlation coefficient, into a binary choice on whether the two brain locations are functionally connected or not. As a result, the choice of a threshold τ over the correlation coefficient is key. In the present work, we propose a multiple testing approach to the choice of τ that uses the Bayes false discovery rate and a new estimator of the statistical power called average power function to balance the two types of statistical error. We show that the proposed average power function estimator behaves well both in case of independence and weak dependence of the tests and it is reliable under several simulated dependence conditions. Moreover, we propose a robust method for the choice of τ using the 5% and 95% percentiles of the average power function and False Discovery Rate bootstrap distributions, respectively, to improve stability. We applied our approach to functional magnetic resonance imaging and high density electroencephalogram data.

Dynamic Changes of Functional Neuronal Activities Between the Auditory Pathway and Limbic Systems Contribute to Noise-Induced Tinnitus with a Normal Audiogram

Tinnitus is thought to be triggered by aberrant neural activity in the central auditory pathway and is often accompanied by comorbidities of emotional distress and anxiety, which imply maladaptive functional connectivity to limbic structures, such as the amygdala and hippocampus. Tinnitus patients with normal audiograms can also have accompanying anxiety and depression, clinically. To test the role of functional connectivity between the central auditory pathway and limbic structures in patients with tinnitus with normal audiograms, we developed a murine noise-induced tinnitus model with a temporary threshold shift (TTS). Tinnitus mice exhibited reduced auditory brainstem response wave I amplitude, and an enhanced wave IV amplitude and wave IV/I amplitude ratio, as compared with control and non-tinnitus mice. Resting-state functional magnetic resonance imaging (fMRI) was used to identify abnormal connectivity of the amygdala and hippocampus and to determine the relationship with tinnitus characteristics. We found increased fMRI responses with amplitude of low-frequency fluctuation (ALFF) in the auditory cortex and decreased ALFF in the amygdala and hippocampus at day 1, but decreased ALFF in the auditory cortex and increased ALFF in the amygdala at day 28 post-noise exposure in tinnitus mice. Decreased functional connectivity between auditory brain regions and limbic structures was demonstrated at day 28 in tinnitus mice. Therefore, aberrant neural activities in tinnitus mice with TTS involved not only the central auditory pathway, but also limbic structures, and there was maladaptive functional connectivity between the central auditory pathway and limbic structures, such as the amygdala and hippocampus.

Enhanced Central Neural Gain Compensates Acoustic Trauma-induced Cochlear Impairment, but Unlikely Correlates with Tinnitus and Hyperacusis

For successful future therapeutic strategies for tinnitus and hyperacusis, a subcategorization of both conditions on the basis of differentiated neural correlates would be of invaluable advantage. In the present study, we used our refined operant conditioning animal model to divide equally noise-exposed rats into groups with either tinnitus or hyperacusis, with neither condition, or with both conditions co-occurring simultaneously. Using click stimulus and noise burst-evoked Auditory Brainstem Responses (ABR) and Distortion Product Otoacoustic Emissions, no hearing threshold difference was observed between any of the groups. However, animals with neither tinnitus nor hyperacusis responded to noise trauma with shortened ABR wave I and IV latencies and elevated central neuronal gain (increased ABR wave IV/I amplitude ratio), which was previously assumed in most of the literature to be a neural correlate for tinnitus. In contrast, animals with tinnitus had reduced neural response gain and delayed ABR wave I and IV latencies, while animals with hyperacusis showed none of these changes. Preliminary studies, aimed at establishing comparable non-invasive objective tools for identifying tinnitus in humans and animals, confirmed reduced central gain and delayed response latency in human and animals. Moreover, the first ever resting state functional Magnetic Resonance Imaging (rs-fMRI) analyses comparing humans and rats with and without tinnitus showed reduced rs-fMRI activities in the auditory cortex in both patients and animals with tinnitus. These findings encourage further efforts to establish non-invasive diagnostic tools that can be used in humans and animals alike and give hope for differentiated classification of tinnitus and hyperacusis.

From eyes-closed to eyes-open: Role of cholinergic projections in EC-to-EO alpha reactivity revealed by combining EEG and MRI

Alpha rhythm (8 to 12 Hz) observed in EEG over human posterior cortex is prominent during eyes-closed (EC) resting and attenuates during eyes-open (EO) resting. Research shows that the degree of EC-to-EO alpha blocking or alpha desynchronization, termed alpha reactivity here, is a neural marker of cognitive health. We tested the role of acetylcholine in EC-to-EO alpha reactivity by applying a multimodal neuroimaging approach to a cohort of young adults and a cohort of older adults. In the young cohort, simultaneous EEG-fMRI was recorded from twenty-one young adults during both EO and EC resting. In the older cohort, functional MRI was recorded from forty older adults during EO and EC resting, along with FLAIR and diffusion MRI. For a subset of twenty older adults, EEG was recorded during EO and EC resting in a separate session. In both young and older adults, functional connectivity between the basal nucleus of Meynert (BNM), the major source of cortical acetylcholine, and the visual cortex increased from EC to EO, and this connectivity increase was positively associated with alpha reactivity; namely, the stronger the BNM-visual cortex functional connectivity increase from EC to EO, the larger the EC-to-EO alpha desynchronization. In older adults, lesions of the fiber tracts linking BNM and visual cortex quantified by leukoaraiosis volume, associated with reduced alpha reactivity. These findings support a role of acetylcholine and particularly cholinergic pathways in mediating EC-to-EO alpha reactivity and suggest that impaired alpha reactivity could serve as a marker of the integrity of the cholinergic system.

Reduced sound-evoked and resting-state BOLD fMRI connectivity in tinnitus

The exact neurophysiological basis of chronic tinnitus, which affects 10-15% of the population, remains unknown and is controversial at many levels. It is an open question whether phantom sound perception results from increased central neural gain or not, a crucial question for any future therapeutic intervention strategies for tinnitus. We performed a comprehensive study of mild hearing-impaired participants with and without tinnitus, excluding participants with co-occurrences of hyperacusis. A right-hemisphere correlation between tinnitus loudness and auditory perceptual difficulty was observed in the tinnitus group, independent of differences in hearing thresholds. This correlation was linked to reduced and delayed sound-induced suprathreshold auditory brain responses (ABR wave V) in the tinnitus group, suggesting subsided rather than exaggerated central neural responsiveness. When anatomically predefined auditory regions of interest were analysed for altered sound-evoked BOLD fMRI activity, it became evident that subcortical and cortical auditory regions and regions involved in sound detection (posterior insula, hippocampus), responded with reduced BOLD activity in the tinnitus group, emphasizing reduced, rather than increased, central neural gain. Regarding previous findings of evoked BOLD activity being linked to positive connectivities at rest, we additionally analysed r-fcMRI responses in anatomically predefined auditory regions and regions associated with sound detection. A profound reduction in positive interhemispheric connections of homologous auditory brain regions and a decline in the positive connectivities between lower auditory brainstem regions and regions involved in sound detection (hippocampus, posterior insula) were observed in the tinnitus group. The finding went hand-in-hand with the emotional (amygdala, anterior insula) and temporofrontal/stress-regulating regions (prefrontal cortex, inferior frontal gyrus) that were no longer positively connected with auditory cortex regions in the tinnitus group but were instead positively connected to lower-level auditory brainstem regions. Delayed sound processing, reduced sound-evoked BOLD fMRI activity and altered r-fcMRI in the auditory midbrain correlated in the tinnitus group and showed right hemisphere dominance as did tinnitus loudness and perceptual difficulty. The findings suggest that reduced central neural gain in the auditory stream may lead to phantom perception through a failure to energize attentional/stress-regulating networks for contextualization of auditory-specific information. Reduced auditory-specific information flow in tinnitus has until now escaped detection in humans, as low-level auditory brain regions were previously omitted from neuroimaging studies.

TRIAL REGISTRATION

German Clinical Trials Register DRKS0006332.

Positive Connectivity Predicts the Dynamic Intrinsic Topology of the Human Brain Network

Functional connectivity MRI (fcMRI) has become instrumental in facilitating research of human brain network organization in terms of coincident interactions between positive and negative synchronizations of large-scale neuronal systems. Although there is a common agreement concerning the interpretation of positive couplings between brain areas, a major debate has been made in disentangling the nature of negative connectivity patterns in terms of its emergence in several methodological approaches and its significance/meaning in specific neuropsychiatric diseases. It is still not clear what information the functional negative correlations or connectivity provides or how they relate to the positive connectivity. Through implementing stepwise functional connectivity (SFC) analysis and studying the causality of functional topological patterns, this study aims to shed light on the relationship between positive and negative connectivity in the human brain functional connectome. We found that the strength of negative correlations between voxel-pairs relates to their positive connectivity path-length. More importantly, our study describes how the spatio-temporal patterns of positive connectivity explain the evolving changes of negative connectivity over time, but not the other way around. This finding suggests that positive and negative connectivity do not display equivalent forces but shows that the positive connectivity has a dominant role in the overall human brain functional connectome. This phenomenon provides novel insights about the nature of positive and negative correlations in fcMRI and will potentially help new developments for neuroimaging biomarkers.

Organization and hierarchy of the human functional brain network lead to a chain-like core

The brain is a paradigmatic example of a complex system: its functionality emerges as a global property of local mesoscopic and microscopic interactions. Complex network theory allows to elicit the functional architecture of the brain in terms of links (correlations) between nodes (grey matter regions) and to extract information out of the noise. Here we present the analysis of functional magnetic resonance imaging data from forty healthy humans at rest for the investigation of the basal scaffold of the functional brain network organization. We show how brain regions tend to coordinate by forming a highly hierarchical chain-like structure of homogeneously clustered anatomical areas. A maximum spanning tree approach revealed the centrality of the occipital cortex and the peculiar aggregation of cerebellar regions to form a closed core. We also report the hierarchy of network segregation and the level of clusters integration as a function of the connectivity strength between brain regions.

Alterations in the expression of a neurodevelopmental gene exert long-lasting effects on cognitive-emotional phenotypes and functional brain networks: translational evidence from the stress-resilient Ahi1 knockout mouse

Many psychiatric disorders are highly heritable and may represent the clinical outcome of early aberrations in the formation of neural networks. The placement of brain connectivity as an 'intermediate phenotype' renders it an attractive target for exploring its interaction with genomics and behavior. Given the complexity of genetic make up and phenotypic heterogeneity in humans, translational studies are indicated. Recently, we demonstrated that a mouse model with heterozygous knockout of the key neurodevelopmental gene Ahi1 displays a consistent stress-resilient phenotype. Extending these data, the current research describes our multi-faceted effort to link early variations in Ahi1 expression with long-term consequences for functional brain networks and cognitive-emotional phenotypes. By combining behavioral paradigms with graph-based analysis of whole-brain functional networks, and then cross-validating the data with robust neuroinformatic data sets, our research suggests that physiological variation in gene expression during neurodevelopment is eventually translated into a continuum of global network metrics that serve as intermediate phenotypes. Within this framework, we suggest that organization of functional brain networks may result, in part, from an adaptive trade-off between efficiency and resilience, ultimately culminating in a phenotypic diversity that encompasses dimensions such as emotional regulation and cognitive function.

Modafinil-Induced Changes in Functional Connectivity in the Cortex and Cerebellum of Healthy Elderly Subjects

In the past few years, cognitive enhancing drugs (CEDs) have gained growing interest and the focus of investigations aimed at exploring their use to potentiate the cognitive performances of healthy individuals. Most of this exploratory CED-related research has been performed on young adults. However, CEDs may also help to maintain optimal brain functioning or compensate for subtle and or subclinical deficits associated with brain aging or early-stage dementia. In this study, we assessed effects on resting state brain activity in a group of healthy elderly subjects undergoing acute administration of modafinil, a wakefulness-promoting agent. To that aim, participants (n = 24) were investigated with resting state functional Magnetic Resonance Imaging (rs-fMRI) before and after the administration of a single dose (100 mg) of modafinil. Effects were compared to age and size-matched placebo group. Rs-fMRI effects were assessed, employing a graph-based approach and Eigenvector Centrality (EC) analysis, by taking in account topological changes occurring in functional brain networks. The main finding of the study is that modafinil promotes enhanced centrality, a measure of the importance of nodes within functional networks, of the bilateral primary visual (V1) cortex. EC analysis also revealed that modafinil-treated subjects show increased functional connectivity between the V1 and specific cerebellar (Crus I, Crus II, VIIIa lobule) and frontal (right inferior frontal sulcus and left middle frontal gyrus) regions. Present findings provide functional data supporting the hypothesis that modafinil can modulate the cortico-cerebellar connectivity of the aging brain.

Frequency-phase analysis of resting-state functional MRI

We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience.

High-order resting-state functional connectivity network for MCI classification

Brain functional connectivity (FC) network, estimated with resting-state functional magnetic resonance imaging (RS-fMRI) technique, has emerged as a promising approach for accurate diagnosis of neurodegenerative diseases. However, the conventional FC network is essentially low-order in the sense that only the correlations among brain regions (in terms of RS-fMRI time series) are taken into account. The features derived from this type of brain network may fail to serve as an effective disease biomarker. To overcome this drawback, we propose extraction of novel high-order FC correlations that characterize how the low-order correlations between different pairs of brain regions interact with each other. Specifically, for each brain region, a sliding window approach is first performed over the entire RS-fMRI time series to generate multiple short overlapping segments. For each segment, a low-order FC network is constructed, measuring the short-term correlation between brain regions. These low-order networks (obtained from all segments) describe the dynamics of short-term FC along the time, thus also forming the correlation time series for every pair of brain regions. To overcome the curse of dimensionality, we further group the correlation time series into a small number of different clusters according to their intrinsic common patterns. Then, the correlation between the respective mean correlation time series of different clusters is calculated to represent the high-order correlation among different pairs of brain regions. Finally, we design a pattern classifier, by combining features of both low-order and high-order FC networks. Experimental results verify the effectiveness of the high-order FC network on disease diagnosis. Hum Brain Mapp 37:3282-3296, 2016. © 2016 Wiley Periodicals, Inc.

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package “DensParcorr” can be downloaded from CRAN for implementing the proposed statistical methods.