Mindfulness-based cognitive therapy neurobiology in treatment-resistant obsessive-compulsive disorder: A domain-related resting-state networks approach.

Mindfulness-based cognitive therapy (MBCT) stands out as a promising augmentation psychological therapy for patients with obsessive-compulsive disorder (OCD). To identify potential predictive and response biomarkers, this study examines the relationship between clinical domains and resting-state network connectivity in OCD patients undergoing a 3-month MBCT programme. Twelve OCD patients underwent two resting-state functional magnetic resonance imaging sessions at baseline and after the MBCT programme. We assessed four clinical domains: positive affect, negative affect, anxiety sensitivity, and rumination. Independent component analysis characterised resting-state networks (RSNs), and multiple regression analyses evaluated brain-clinical associations. At baseline, distinct network connectivity patterns were found for each clinical domain: parietal-subcortical, lateral prefrontal, medial prefrontal, and frontal-occipital. Predictive and response biomarkers revealed significant brain-clinical associations within two main RSNs: the ventral default mode network (vDMN) and the frontostriatal network (FSN). Key brain nodes -the precuneus and the frontopolar cortex- were identified within these networks. MBCT may modulate vDMN and FSN connectivity in OCD patients, possibly reducing symptoms across clinical domains. Each clinical domain had a unique baseline brain connectivity pattern, suggesting potential symptom-based biomarkers. Using these RSNs as predictors could enable personalised treatments and the identification of patients who would benefit most from MBCT.

Musical memories in newborns: A resting-state functional connectivity study.

Music is known to induce emotions and activate associated memories, including musical memories. In adults, it is well known that music activates both working memory and limbic networks. We have recently discovered that as early as during the newborn period, familiar music is processed differently from unfamiliar music. The present study evaluates music listening effects at the brain level in newborns, by exploring the impact of familiar or first-time music listening on the subsequent resting-state functional connectivity in the brain. Using a connectome-based framework, we describe resting-state functional connectivity (RS-FC) modulation after music listening in three groups of newborn infants, in preterm infants exposed to music during their neonatal-intensive-care-unit (NICU) stay, in control preterm, and full-term infants. We observed modulation of the RS-FC between brain regions known to be implicated in music and emotions processing, immediately following music listening in all newborn infants. In the music exposed group, we found increased RS-FC between brain regions known to be implicated in familiar and emotionally arousing music and multisensory processing, and therefore implying memory retrieval and associative memory. We demonstrate a positive correlation between the occurrence of the prior music exposure and increased RS-FC in brain regions implicated in multisensory and emotional processing, indicating strong engagement of musical memories; and a negative correlation with the Default Mode Network, indicating disengagement due to the aforementioned cognitive processing. Our results describe the modulatory effect of music listening on brain RS-FC that can be linked to brain correlates of musical memory engrams in preterm infants.

Mapping the subcortical connectivity of the human default mode network.

The default mode network (DMN) mediates self-awareness and introspection, core components of human consciousness. Therapies to restore consciousness in patients with severe brain injuries have historically targeted subcortical sites in the brainstem, thalamus, hypothalamus, basal forebrain, and basal ganglia, with the goal of reactivating cortical DMN nodes. However, the subcortical connectivity of the DMN has not been fully mapped, and optimal subcortical targets for therapeutic neuromodulation of consciousness have not been identified. In this work, we created a comprehensive map of DMN subcortical connectivity by combining high-resolution functional and structural datasets with advanced signal processing methods. We analyzed 7 Tesla resting-state functional MRI (rs-fMRI) data from 168 healthy volunteers acquired in the Human Connectome Project. The rs-fMRI blood-oxygen-level-dependent (BOLD) data were temporally synchronized across subjects using the BrainSync algorithm. Cortical and subcortical DMN nodes were jointly analyzed and identified at the group level by applying a novel Nadam-Accelerated SCAlable and Robust (NASCAR) tensor decomposition method to the synchronized dataset. The subcortical connectivity map was then overlaid on a 7 Tesla 100 µm ex vivo MRI dataset for neuroanatomic analysis using automated segmentation of nuclei within the brainstem, thalamus, hypothalamus, basal forebrain, and basal ganglia. We further compared the NASCAR subcortical connectivity map with its counterpart generated from canonical seed-based correlation analyses. The NASCAR method revealed that BOLD signal in the central lateral nucleus of the thalamus and ventral tegmental area of the midbrain is strongly correlated with that of the DMN. In an exploratory analysis, additional subcortical sites in the median and dorsal raphe, lateral hypothalamus, and caudate nuclei were correlated with the cortical DMN. We also found that the putamen and globus pallidus are negatively correlated (i.e., anti-correlated) with the DMN, providing rs-fMRI evidence for the mesocircuit hypothesis of human consciousness, whereby a striatopallidal feedback system modulates anterior forebrain function via disinhibition of the central thalamus. Seed-based analyses yielded similar subcortical DMN connectivity, but the NASCAR result showed stronger contrast and better spatial alignment with dopamine immunostaining data. The DMN subcortical connectivity map identified here advances understanding of the subcortical regions that contribute to human consciousness and can be used to inform the selection of therapeutic targets in clinical trials for patients with disorders of consciousness.

Pretreatment intranetwork connectivity can predict the outcomes in idiopathic tinnitus patients treated with sound therapy.

Previous studies demonstrated that brain morphological differences and distinct patterns of neural activation exist in tinnitus patients with different prognoses after sound therapy. This study aimed to explore possible differences in intrinsic network-level functional connectivity (FC) in patients with different outcomes after sound therapy (narrow band noise). We examined intrinsic FC using resting-state functional magnetic resonance imaging in 78 idiopathic tinnitus patients (including 35 effectively treated and 43 ineffectively treated) and 52 healthy controls (HCs) via independent component analysis. We also investigated the associations between the differences in FC and clinical variables. Analyses revealed significantly altered intranetwork connectivity in the auditory network (AUN) and some nonauditory-related networks in the EG/IG patients compared to HCs; compared with EG patients, IG patients showed decreased intranetwork connectivity in the anterior default mode network (aDMN) and AUN. Meanwhile, robust differences were also evident in internetwork connectivity between some nonauditory-related networks (salience network and executive control network; posterior default mode network and dorsal attention network) in the EG relative to IG patients. We combined intranetwork connectivity in the aDMN and AUN as an imaging indicator to evaluate patient outcomes and screen patients before treatment; this approach reached a sensitivity of 94.3% and a specificity of 76.7%. Our study suggests that tinnitus patients with different outcomes show distinct network-level functional reorganization patterns. Intranetwork connectivity in the aDMN and AUN may be indicators that can be used to predict prognoses in patients with idiopathic tinnitus and screen patients before sound therapy.

Selective vulnerability to atrophy in sporadic Creutzfeldt-Jakob disease.

OBJECTIVE: Identification of brain regions susceptible to quantifiable atrophy in sporadic Creutzfeldt-Jakob disease (sCJD) should allow for improved understanding of disease pathophysiology and development of structural biomarkers that might be useful in future treatment trials. Although brain atrophy is not usually present by visual assessment of MRIs in sCJD, we assessed whether using voxel-based morphometry (VBM) can detect group-wise brain atrophy in sCJD. METHODS: 3T brain MRI data were analyzed with VBM in 22 sCJD participants and 26 age-matched controls. Analyses included relationships of regional brain volumes with major clinical variables and dichotomization of the cohort according to expected disease duration based on prion molecular classification (i.e., short-duration/Fast-progressors (MM1, MV1, and VV2) vs. long-duration/Slow-progressors (MV2, VV1, and MM2)). Structural equation modeling (SEM) was used to assess network-level interactions of atrophy between specific brain regions. RESULTS: sCJD showed selective atrophy in cortical and subcortical regions overlapping with all but one region of the default mode network (DMN) and the insulae, thalami, and right occipital lobe. SEM showed that the effective connectivity model fit in sCJD but not controls. The presence of visual hallucinations correlated with right fusiform, bilateral thalami, and medial orbitofrontal atrophy. Interestingly, brain atrophy was present in both Fast- and Slow-progressors. Worse cognition was associated with bilateral mesial frontal, insular, temporal pole, thalamus, and cerebellum atrophy. INTERPRETATION: Brain atrophy in sCJD preferentially affects specific cortical and subcortical regions, with an effective connectivity model showing strength and directionality between regions. Brain atrophy is present in Fast- and Slow-progressors, correlates with clinical findings, and is a potential biomarker in sCJD.

Taking the body off the mind: Decreased functional connectivity between somatomotor and default-mode networks following Floatation-REST.

Floatation-Reduced Environmental Stimulation Therapy (REST) is a procedure that reduces stimulation of the human nervous system by minimizing sensory signals from visual, auditory, olfactory, gustatory, thermal, tactile, vestibular, gravitational, and proprioceptive channels, in addition to minimizing musculoskeletal movement and speech. Initial research has found that Floatation-REST can elicit short-term reductions in anxiety, depression, and pain, yet little is known about the brain networks impacted by the intervention. This study represents the first functional neuroimaging investigation of Floatation-REST, and we utilized a data-driven exploratory analysis to determine whether the intervention leads to altered patterns of resting-state functional connectivity (rsFC). Healthy participants underwent functional magnetic resonance imaging (fMRI) before and after 90 min of Floatation-REST or a control condition that entailed resting supine in a zero-gravity chair for an equivalent amount of time. Multivariate Distance Matrix Regression (MDMR), a statistically-stringent whole-brain searchlight approach, guided subsequent seed-based connectivity analyses of the resting-state fMRI data. MDMR identified peak clusters of rsFC change between the pre- and post-float fMRI, revealing significant decreases in rsFC both within and between posterior hubs of the default-mode network (DMN) and a large swath of cortical tissue encompassing the primary and secondary somatomotor cortices extending into the posterior insula. The control condition, an active form of REST, showed a similar pattern of reduced rsFC. Thus, reduced stimulation of the nervous system appears to be reflected by reduced rsFC within the brain networks most responsible for creating and mapping our sense of self.

Psilocybin exerts distinct effects on resting state networks associated with serotonin and dopamine in mice.

Hallucinogenic agents have been proposed as potent antidepressants; this includes the serotonin (5-HT) receptor 2A agonist psilocybin. In human subjects, psilocybin alters functional connectivity (FC) within the default-mode network (DMN), a constellation of inter-connected regions that displays altered FC in depressive disorders. In this study, we investigated the effects of psilocybin on FC across the entire brain with a view to investigate underlying mechanisms. Psilocybin effects were investigated in lightly-anaesthetized mice using resting-state fMRI. Dual-regression analysis identified reduced FC within the ventral striatum in psilocybin- relative to vehicle-treated mice. Refinement of the analysis using spatial references derived from both gene expression maps and viral tracer projection fields revealed two distinct effects of psilocybin: it increased FC between 5-HT-associated networks and cortical areas, including elements of the murine DMN, thalamus, and midbrain; it decreased FC within dopamine (DA)-associated striatal networks. These results suggest that interactions between 5-HT- and DA-regulated neural networks contribute to the neural and therefore psychological effects of psilocybin. Furthermore, they highlight how information on molecular expression patterns and structural connectivity can assist in the interpretation of pharmaco-fMRI findings.

Interrelations between dopamine and serotonin producing sites and regions of the default mode network.

Recent functional magnetic resonance imaging (fMRI) studies showed that blood oxygenation level-dependent (BOLD) signal fluctuations in the default mode network (DMN) are functionally tightly connected to those in monoaminergic nuclei, producing dopamine (DA), and serotonin (5-HT) transmitters, in the midbrain/brainstem. We combined accelerated fMRI acquisition with spectral Granger causality and coherence analysis to investigate causal relationships between these areas. Both methods independently lead to similar results and confirm the existence of a top-down information flow in the resting-state condition, where activity in core DMN areas influences activity in the neuromodulatory centers producing DA/5-HT. We found that latencies range from milliseconds to seconds with high inter-subject variability, likely attributable to the resting condition. Our novel findings provide new insights into the functional organization of the human brain.

The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample.

Brain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static, perspective, but its validity for cognitive sciences remains under debate. Here, we analyzed brain activity recorded with functional Magnetic Resonance Imaging from 71 healthy participants evaluated for depressive symptoms after a relationship breakup based on the conventional Major Depression Inventory (MDI). We compared both static and dynamic FC patterns between participants reporting high and low depressive symptoms. Between-group differences in static FC were estimated using a standard pipeline for network-based statistic (NBS). Additionally, FC was analyzed from a dynamic perspective by characterizing the occupancy, lifetime, and transition profiles of recurrent FC patterns. Recurrent FC patterns were defined by clustering the BOLD phase-locking patterns obtained using leading eigenvector dynamics analysis (LEiDA). NBS analysis revealed a brain subsystem exhibiting significantly lower within-subsystem correlation values in more depressed participants (high MDI). This subsystem predominantly comprised connections between regions of the default mode network (i.e., precuneus) and regions outside this network. On the other hand, LEiDA results showed that high MDI participants engaged more in a state connecting regions of the default mode, memory retrieval, and frontoparietal network (p-FDR = 0.012); and less in a state connecting mostly the visual and dorsal attention systems (p-FDR = 0.004). Although both our analyses on static and dynamic FC implicate the role of the precuneus in depressive symptoms, only including the temporal evolution of BOLD FC helped to disentangle over time the distinct configurations in which this region plays a role. This finding further indicates that a holistic understanding of brain function can only be gleaned if the temporal dynamics of FC is included.

Vocal music enhances memory and language recovery after stroke: pooled results from two RCTs.

OBJECTIVE: Previous studies suggest that daily music listening can aid stroke recovery, but little is known about the stimulus-dependent and neural mechanisms driving this effect. Building on neuroimaging evidence that vocal music engages extensive and bilateral networks in the brain, we sought to determine if it would be more effective for enhancing cognitive and language recovery and neuroplasticity than instrumental music or speech after stroke. METHODS: Using data pooled from two single-blind randomized controlled trials in stroke patients (N = 83), we compared the effects of daily listening to self-selected vocal music, instrumental music, and audiobooks during the first 3 poststroke months. Outcome measures comprised neuropsychological tests of verbal memory (primary outcome), language, and attention and a mood questionnaire performed at acute, 3-month, and 6-month stages and structural and functional MRI at acute and 6-month stages. RESULTS: Listening to vocal music enhanced verbal memory recovery more than instrumental music or audiobooks and language recovery more than audiobooks, especially in aphasic patients. Voxel-based morphometry and resting-state and task-based fMRI results showed that vocal music listening selectively increased gray matter volume in left temporal areas and functional connectivity in the default mode network. INTERPRETATION: Vocal music listening is an effective and easily applicable tool to support cognitive recovery after stroke as well as to enhance early language recovery in aphasia. The rehabilitative effects of vocal music are driven by both structural and functional plasticity changes in temporoparietal networks crucial for emotional processing, language, and memory.

Mindfulness training preserves sustained attention and resting state anticorrelation between default-mode network and dorsolateral prefrontal cortex: A randomized controlled trial.

Mindfulness training can enhance cognitive control, but the neural mechanisms underlying such enhancement in children are unknown. Here, we conducted a randomized controlled trial (RCT) with sixth graders (mean age 11.76 years) to examine the impact of 8 weeks of school-based mindfulness training, relative to coding training as an active control, on sustained attention and associated resting-state functional brain connectivity. At baseline, better performance on a sustained-attention task correlated with greater anticorrelation between the default mode network (DMN) and right dorsolateral prefrontal cortex (DLPFC), a key node of the central executive network. Following the interventions, children in the mindfulness group preserved their sustained-attention performance (i.e., fewer lapses of attention) and preserved DMN-DLPFC anticorrelation compared to children in the active control group, who exhibited declines in both sustained attention and DMN-DLPFC anticorrelation. Further, change in sustained-attention performance correlated with change in DMN-DLPFC anticorrelation only within the mindfulness group. These findings provide the first causal link between mindfulness training and both sustained attention and associated neural plasticity. Administered as a part of sixth graders' school schedule, this RCT supports the beneficial effects of school-based mindfulness training on cognitive control.

Network-based fMRI-neurofeedback training of sustained attention.

The brain regions supporting sustained attention (sustained attention network; SAN) and mind-wandering (default-mode network; DMN) have been extensively studied. Nevertheless, this knowledge has not yet been translated into advanced brain-based attention training protocols. Here, we used network-based real-time functional magnetic resonance imaging (fMRI) to provide healthy individuals with information about current activity levels in SAN and DMN. Specifically, 15 participants trained to control the difference between SAN and DMN hemodynamic activity and completed behavioral attention tests before and after neurofeedback training. Through training, participants improved controlling the differential SAN-DMN feedback signal, which was accomplished mainly through deactivating DMN. After training, participants were able to apply learned self-regulation of the differential feedback signal even when feedback was no longer available (i.e., during transfer runs). The neurofeedback group improved in sustained attention after training, although this improvement was temporally limited and rarely exceeded mere practice effects that were controlled by a test-retest behavioral control group. The learned self-regulation and the behavioral outcomes suggest that neurofeedback training of differential SAN and DMN activity has the potential to become a non-invasive and non-pharmacological tool to enhance attention and mitigate specific attention deficits.

Functional differentiation in the human ventromedial frontal lobe: A data-driven parcellation.

Ventromedial regions of the frontal lobe (vmFL) are thought to play a key role in decision-making and emotional regulation. However, aspects of this area's functional organization, including the presence of a multiple subregions, their functional and anatomical connectivity, and the cross-species homologies of these subregions with those of other species, remain poorly understood. To address this uncertainty, we employed a two-stage parcellation of the region to identify six distinct structures within the region on the basis of data-driven classification of functional connectivity patterns obtained using the meta-analytic connectivity modeling (MACM) approach. From anterior to posterior, the derived subregions included two lateralized posterior regions, an intermediate posterior region, a dorsal and ventral central region, and a single anterior region. The regions were characterized further by functional connectivity derived using resting-state fMRI and functional decoding using the Brain Map database. In general, the regions could be differentiated on the basis of different patterns of functional connectivity with canonical "default mode network" regions and/or subcortical regions such as the striatum. Together, the findings suggest the presence of functionally distinct neural structures within vmFL, consistent with data from experimental animals as well prior demonstrations of anatomical differences within the region. Detailed correspondence with the anterior cingulate, medial orbitofrontal cortex, and rostroventral prefrontal cortex, as well as specific animal homologs are discussed. The findings may suggest future directions for resolving potential functional and structural correspondence of subregions within the frontal lobe across behavioral contexts, and across mammalian species.

Common and specific dimensions of internalizing disorders are characterized by unique patterns of brain activity on a task of emotional cognitive control.

Alterations in neural systems underlying cognitive control are well-documented across individuals with various internalizing disorders. The current study examined how individual differences in underlying traits related to internalizing disorders influence brain activation, as assessed by fMRI, when cognitive control must be exerted to make a decision about the emotional valence (positive, negative) of a task-relevant word displayed concurrently with a task-irrelevant emotional face. Taking a bi-factor model approach, fifty-five middle-aged female participants were characterized on symptom level on a common internalizing latent factor representing shared symptoms across anxiety and depression, as well as on specific factors remaining after taking the common internalizing factor into account: low positive affect, anxious arousal, and anxious apprehension. Contrasting activation on trials requiring higher vs. lower control revealed that higher levels of the Common Internalizing factor are associated with less deactivation of regions of the default mode network. Higher levels of the Low Positive Affect-specific factor are associated with less differentiation in engagement of portions of the fronto-parietal control network, while higher levels of the Anxious Arousal-specific factor are associated with less of a differentiation in activation of the thalamus. No effects were observed for level of the Anxious Apprehension-specific factor. These results suggest that prior findings of alterations in default mode activity associated with depression may not be specific to depressive symptoms per se but may characterize internalizing symptoms more generally. In addition, they suggest that reduced engagement of cognitive control regions may be more associated with low positive affect than depressive symptoms more generally.

The Endogenous Analgesia Signature in the Resting Brain of Healthy Adults and Migraineurs.

Altered pain modulation and resting state functional connectivity (rsFC) were found to be related to migraine pathology and clinical manifestation. We examined how pain modulation psychophysical measures are related to resting-state networks and rsFC between bottom-up and top-down pain modulation areas. Thirty-two episodic migraineurs and 23 age-matched healthy individuals underwent temporal summation of pain (TSOP) and conditioned pain modulation (CPM) tests, followed by a resting-state imaging scan. No differences in temporal summation of pain and CPM were found between groups. However, in healthy individuals, more efficient CPM was correlated with 1) stronger rsFCs of the posterior cingulate cortex, with the ventromedial prefrontal cortex and with the pregenual anterior cingulate cortex; 2) weaker rsFC of the anterior insula with the angular gyrus. Conversely, in migraineurs, the association between CPM and rsFC was altered. Our results suggest that the functional connectivity within the default mode network (DMN) components and the functional coupling between the DMN and pain inhibitory brain areas is linked with pain inhibition efficiency. In migraineurs, this interplay is changed, yet enables normal pain inhibition. Our findings shed light on potential functional adaptation of the DMN and its role in pain inhibition in health and migraine. PERSPECTIVE: This article establishes evidence for the relationship between the resting-state brain and individual responses in psychophysical pain modulation tests, in both migraine and healthy individuals. The results emphasize the significant role of the default mode network in maintaining pain inhibition efficiency in health and in the presence of chronic pain.

Self-regulation of ventromedial prefrontal cortex activation using real-time fMRI neurofeedback-Influence of default mode network.

The ventromedial prefrontal cortex (vmPFC) is involved in regulation of negative emotion and decision-making, emotional and behavioral control, and active resilient coping. This pilot study examined the feasibility of training healthy subjects (n = 27) to self-regulate the vmPFC activity using a real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf). Participants in the experimental group (EG, n = 18) were provided with an ongoing vmPFC hemodynamic activity (rtfMRI-nf signal represented as variable-height bar). Individuals were instructed to raise the bar by self-relevant value-based thinking. Participants in the control group (CG, n = 9) performed the same task; however, they were provided with computer-generated sham neurofeedback signal. Results demonstrate that (a) both the CG and the EG show a higher vmPFC fMRI signal at the baseline than during neurofeedback training; (b) no significant positive training effect was seen in the vmPFC across neurofeedback runs; however, the medial prefrontal cortex, middle temporal gyri, inferior frontal gyri, and precuneus showed significant decreasing trends across the training runs only for the EG; (c) the vmPFC rtfMRI-nf signal associated with the fMRI signal across the default mode network (DMN). These findings suggest that it may be difficult to modulate a single DMN region without affecting other DMN regions. Observed decreased vmPFC activity during the neurofeedback task could be due to interference from the fMRI signal within other DMN network regions, as well as interaction with task-positive networks. Even though participants in the EG did not show significant positive increase in the vmPFC activity among neurofeedback runs, they were able to learn to accommodate the demand of self-regulation task to maintain the vmPFC activity with the help of a neurofeedback signal.

Motor and Limbic System Contribution to Emotional Laughter across the Lifespan.

Laughter is a universal human behavior generated by the cooperation of different systems toward the construction of an expressive vocal pattern. Given the sensitivity of neuroimaging techniques to movements, the neural mechanisms underlying laughter expression remain unclear. Herein, we characterized the neural correlates of emotional laughter using the onsets and the duration of laughter bursts to inform functional magnetic resonance imaging. Laughter-related blood oxygen level-dependent (BOLD) increases involved both the motor (motor cortex, supplementary motor area, frontal operculum) and the emotional/limbic (anterior cingulate cortex, amygdala, n. accumbens, hippocampus) systems, as well as modulatory circuitries encompassing the basal ganglia, thalamus, and cerebellum. BOLD changes related to the 2 s preceding the laughter outbreak were selectively observed at the temporo-occipital junction and the periaqueductal gray matter, supporting the role of the former in the detection of incongruity and the gating role of the latter in the initiation of spontaneous laughter. Moreover, developmental changes were identified in laughter processing, consisting in a greater engagement of the reward circuitry in younger subjects; conversely, the default mode network appears more activated in older participants. Our findings contribute valuable information about the processing of real-life humorous materials and suggest a close link between laughter-related motor, affective, and cognitive elements, confirming its complex and multi-faceted nature.