What have we really learned from functional connectivity in clinical populations?

Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool for probing functional abnormalities in clinical populations due to the promise of the approach across conceptual, technical, and practical levels. With an already vast and steadily accumulating neuroimaging literature on neurodevelopmental, psychiatric, and neurological diseases and disorders in which FC is a primary measure, we aim here to provide a high-level synthesis of major concepts that have arisen from FC findings in a manner that cuts across different clinical conditions and sheds light on overarching principles. We highlight that FC has allowed us to discover the ubiquity of intrinsic functional networks across virtually all brains and clarify typical patterns of neurodevelopment over the lifespan. This understanding of typical FC maturation with age has provided important benchmarks against which to evaluate divergent maturation in early life and degeneration in late life. This in turn has led to the important insight that many clinical conditions are associated with complex, distributed, network-level changes in the brain, as opposed to solely focal abnormalities. We further emphasize the important role that FC studies have played in supporting a dimensional approach to studying transdiagnostic clinical symptoms and in enhancing the multimodal characterization and prediction of the trajectory of symptom progression across conditions. We highlight the unprecedented opportunity offered by FC to probe functional abnormalities in clinical conditions where brain function could not be easily studied otherwise, such as in disorders of consciousness. Lastly, we suggest high priority areas for future research and acknowledge critical barriers associated with the use of FC methods, particularly those related to artifact removal, data denoising and feasibility in clinical contexts.

Dynamics of Top-Down Control and Motor Networks in Parkinson's Disease.

BACKGROUND: Motor symptoms in Parkinson's disease (PD) patients might be related to high-level task-control deficits. We aimed at investigating the dynamics between sensorimotor network and top-down control networks (frontal-parietal, cingulo-opercular, and cerebellar) in PD and at determining the effects of levodopa on the dynamics of these networks. METHODS: We investigated dynamic functional connectivity (dFC), during resting state functional magnetic resonance imaging, between sensorimotor network and top-down control networks in 36 PD patients (OFF medication, PD-OFF) and 36 healthy volunteers. We further assessed the effect of medication on dFC in18 PD patients who were also scanned ON medication. RESULTS: The dFC analyses identified three discrete states: State I (35.68%) characterized by connections between the cerebellum and sensorimotor network, State II (34.17%) with connections between the sensorimotor and frontal-parietal network, and State III (30.15%) with connection between the sensorimotor and cingulo-opercular network. PD patients have significantly fewer occurrences and overall spent less time (shorter dwell time) in State II compared to healthy controls. After levodopa intake, dwell time improved toward normal. The change in dwell time before and after taking levodopa was negatively related to the respective changes in Unified Parkinson's Disease Rating Scale, Part III. PD-OFF showed significantly decreased connectivity between sensorimotor and control networks and increased connectivity within control networks. These changes were partially improved after levodopa intake. CONCLUSIONS: Dopamine depletion in PD is associated with abnormalities in temporal and spatial properties between cognitive control and sensorimotor network, possibly contributing to clinical deficits. Levodopa partially restores the network function toward the values observed in healthy volunteers. © 2021 International Parkinson and Movement Disorder Society.

The role of the inferior parietal lobule in writer's cramp.

Humans have a distinguishing ability for fine motor control that is subserved by a highly evolved cortico-motor neuronal network. The acquisition of a particular motor skill involves a long series of practice movements, trial and error, adjustment and refinement. At the cortical level, this acquisition begins in the parieto-temporal sensory regions and is subsequently consolidated and stratified in the premotor-motor cortex. Task-specific dystonia can be viewed as a corruption or loss of motor control confined to a single motor skill. Using a multimodal experimental approach combining neuroimaging and non-invasive brain stimulation, we explored interactions between the principal nodes of the fine motor control network in patients with writer's cramp and healthy matched controls. Patients and healthy volunteers underwent clinical assessment, diffusion-weighted MRI for tractography, and functional MRI during a finger tapping task. Activation maps from the task-functional MRI scans were used for target selection and neuro-navigation of the transcranial magnetic stimulation. Single- and double-pulse TMS evaluation included measurement of the input-output recruitment curve, cortical silent period, and amplitude of the motor evoked potentials conditioned by cortico-cortical interactions between premotor ventral (PMv)-motor cortex (M1), anterior inferior parietal lobule (aIPL)-M1, and dorsal inferior parietal lobule (dIPL)-M1 before and after inducing a long term depression-like plastic change to dIPL node with continuous theta-burst transcranial magnetic stimulation in a randomized, sham-controlled design. Baseline dIPL-M1 and aIPL-M1 cortico-cortical interactions were facilitatory and inhibitory, respectively, in healthy volunteers, whereas the interactions were converse and significantly different in writer's cramp. Baseline PMv-M1 interactions were inhibitory and similar between the groups. The dIPL-PMv resting state functional connectivity was increased in patients compared to controls, but no differences in structural connectivity between the nodes were observed. Cortical silent period was significantly prolonged in writer's cramp. Making a long term depression-like plastic change to dIPL node transformed the aIPL-M1 interaction to inhibitory (similar to healthy volunteers) and cancelled the PMv-M1 inhibition only in the writer's cramp group. These findings suggest that the parietal multimodal sensory association region could have an aberrant downstream influence on the fine motor control network in writer's cramp, which could be artificially restored to its normal function.

Pedunculopontine Nucleus Cholinergic Deficiency in Cervical Dystonia.

BACKGROUND: The etiology of cervical dystonia is unknown. Cholinergic abnormalities have been identified in dystonia animal models and human imaging studies. Some animal models have cholinergic neuronal loss in the striatum and increased acetylcholinesterase activity in the pedunculopontine nucleus. OBJECTIVES: The objective of this study was to determine the presence of cholinergic abnormalities in the putamen and pedunculopontine nucleus in cervical dystonia human brain donors. METHODS: Formalin-fixed brain tissues were obtained from 8 cervical dystonia and 7 age-matched control brains (controls). Pedunculopontine nucleus was available in only 6 cervical dystonia and 5 controls. Neurodegeneration was evaluated pathologically in the putamen, pedunculopontine nucleus, and other regions. Cholinergic neurons were detected using choline acetyltransferase immunohistochemistry in the putamen and pedunculopontine nucleus. Putaminal cholinergic neurons were quantified. A total of 6 cervical dystonia patients and 6 age-matched healthy controls underwent diffusion tensor imaging to determine if there were white matter microstructural abnormalities around the pedunculopontine nucleus. RESULTS: Decreased or absent choline acetyltransferase staining was identified in all 6 pedunculopontine nucleus samples in cervical dystonia. In contrast, strong choline acetyltransferase staining was present in 4 of 5 pedunculopontine nucleus controls. There were no differences in pedunculopontine nucleus diffusion tensor imaging between cervical dystonia and healthy controls. There was no difference in numbers of putaminal cholinergic neurons between cervical dystonia and controls. CONCLUSIONS: Our findings suggest that pedunculopontine nucleus choline acetyltransferase deficiency represents a functional cholinergic deficit in cervical dystonia. Structural lesions and confounding neurodegenerative processes were excluded by absence of neuronal loss, gliosis, diffusion tensor imaging abnormalities, and beta-amyloid, tau, and alpha-synuclein pathologies. © 2018 International Parkinson and Movement Disorder Society.

Tractography patterns of subthalamic nucleus deep brain stimulation.

Deep brain stimulation therapy is an effective symptomatic treatment for Parkinson's disease, yet the precise mechanisms responsible for its therapeutic effects remain unclear. Although the targets of deep brain stimulation are grey matter structures, axonal modulation is known to play an important role in deep brain stimulation's therapeutic mechanism. Several white matter structures in proximity to the subthalamic nucleus have been implicated in the clinical benefits of deep brain stimulation for Parkinson's disease. We assessed the connectivity patterns that characterize clinically beneficial electrodes in Parkinson's disease patients, after deep brain stimulation of the subthalamic nucleus. We evaluated 22 patients with Parkinson's disease (11 females, age 57 ± 9.1 years, disease duration 13.3 ± 6.3 years) who received bilateral deep brain stimulation of the subthalamic nucleus at the National Institutes of Health. During an initial electrode screening session, one month after deep brain stimulation implantation, the clinical benefits of each contact were determined. The electrode was localized by coregistering preoperative magnetic resonance imaging and postoperative computer tomography images and the volume of tissue activated was estimated from stimulation voltage and impedance. Brain connectivity for the volume of tissue activated of deep brain stimulation contacts was assessed using probabilistic tractography with diffusion-tensor data. Areas most frequently connected to clinically effective contacts included the thalamus, substantia nigra, brainstem and superior frontal gyrus. A series of discriminant analyses demonstrated that the strength of connectivity to the superior frontal gyrus and the thalamus were positively associated with clinical effectiveness. The connectivity patterns observed in our study suggest that the modulation of white matter tracts directed to the superior frontal gyrus and the thalamus is associated with favourable clinical outcomes and may contribute to the therapeutic effects of deep brain stimulation. Our method can be further developed to reliably identify effective deep brain stimulation contacts and aid in the programming process.

Meta-analysis of real-time fMRI neurofeedback studies using individual participant data: How is brain regulation mediated?

An increasing number of studies using real-time fMRI neurofeedback have demonstrated that successful regulation of neural activity is possible in various brain regions. Since these studies focused on the regulated region(s), little is known about the target-independent mechanisms associated with neurofeedback-guided control of brain activation, i.e. the regulating network. While the specificity of the activation during self-regulation is an important factor, no study has effectively determined the network involved in self-regulation in general. In an effort to detect regions that are responsible for the act of brain regulation, we performed a post-hoc analysis of data involving different target regions based on studies from different research groups. We included twelve suitable studies that examined nine different target regions amounting to a total of 175 subjects and 899 neurofeedback runs. Data analysis included a standard first- (single subject, extracting main paradigm) and second-level (single subject, all runs) general linear model (GLM) analysis of all participants taking into account the individual timing. Subsequently, at the third level, a random effects model GLM included all subjects of all studies, resulting in an overall mixed effects model. Since four of the twelve studies had a reduced field of view (FoV), we repeated the same analysis in a subsample of eight studies that had a well-overlapping FoV to obtain a more global picture of self-regulation. The GLM analysis revealed that the anterior insula as well as the basal ganglia, notably the striatum, were consistently active during the regulation of brain activation across the studies. The anterior insula has been implicated in interoceptive awareness of the body and cognitive control. Basal ganglia are involved in procedural learning, visuomotor integration and other higher cognitive processes including motivation. The larger FoV analysis yielded additional activations in the anterior cingulate cortex, the dorsolateral and ventrolateral prefrontal cortex, the temporo-parietal area and the visual association areas including the temporo-occipital junction. In conclusion, we demonstrate that several key regions, such as the anterior insula and the basal ganglia, are consistently activated during self-regulation in real-time fMRI neurofeedback independent of the targeted region-of-interest. Our results imply that if the real-time fMRI neurofeedback studies target regions of this regulation network, such as the anterior insula, care should be given whether activation changes are related to successful regulation, or related to the regulation process per se. Furthermore, future research is needed to determine how activation within this regulation network is related to neurofeedback success.

Impairment of a parieto-premotor network specialized for handwriting in writer's cramp.

Handwriting with the dominant hand is a highly skilled task singularly acquired in humans. This skill is the isolated deficit in patients with writer's cramp (WC), a form of dystonia with maladaptive plasticity, acquired through intensive and repetitive motor practice. When a skill is highly trained, a motor program is created in the brain to execute the same movement kinematics regardless of the effector used for the task. The task- and effector-specific symptoms in WC suggest that a problem particularly occurs in the brain when the writing motor program is carried out by the dominant hand. In this MRI study involving 12 WC patients (with symptoms only affecting the right dominant hand during writing) and 15 age matched unaffected controls we showed that: (1) the writing program recruited the same network regardless of the effector used to write in both groups; (2) dominant handwriting recruited a segregated parieto-premotor network only in the control group; (3) local structural alteration of the premotor area, the motor component of this network, predicted functional connectivity deficits during dominant handwriting and symptom duration in the patient group. Dysfunctions and structural abnormalities of a segregated parieto-premotor network in WC patients suggest that network specialization in focal brain areas is crucial for well-learned motor skill. Hum Brain Mapp 37:4363-4375, 2016. © 2016 Wiley Periodicals, Inc.

DBSproc: An open source process for DBS electrode localization and tractographic analysis.

Deep brain stimulation (DBS) is an effective surgical treatment for movement disorders. Although stimulation sites for movement disorders such as Parkinson's disease are established, the therapeutic mechanisms of DBS remain controversial. Recent research suggests that specific white-matter tract and circuit activation mediates symptom relief. To investigate these questions, we have developed a patient-specific open-source software pipeline called 'DBSproc' for (1) localizing DBS electrodes and contacts from postoperative CT images, (2) processing structural and diffusion MRI data, (3) registering all images to a common space, (4) estimating DBS activation volume from patient-specific voltage and impedance, and (5) understanding the DBS contact-brain connectivity through probabilistic tractography. In this paper, we explain our methodology and provide validation with anatomical and tractographic data. This method can be used to help investigate mechanisms of action of DBS, inform surgical and clinical assessments, and define new therapeutic targets.

Rhythmic alternating patterns of brain activity distinguish rapid eye movement sleep from other states of consciousness.

Rapid eye movement (REM) sleep constitutes a distinct "third state" of consciousness, during which levels of brain activity are commensurate with wakefulness, but conscious awareness is radically transformed. To characterize the temporal and spatial features of this paradoxical state, we examined functional interactions between brain regions using fMRI resting-state connectivity methods. Supporting the view that the functional integrity of the default mode network (DMN) reflects "level of consciousness," we observed functional uncoupling of the DMN during deep sleep and recoupling during REM sleep (similar to wakefulness). However, unlike either deep sleep or wakefulness, REM was characterized by a more widespread, temporally dynamic interaction between two major brain systems: unimodal sensorimotor areas and the higher-order association cortices (including the DMN), which normally regulate their activity. During REM, these two systems become anticorrelated and fluctuate rhythmically, in reciprocally alternating multisecond epochs with a frequency ranging from 0.1 to 0.01 Hz. This unique spatiotemporal pattern suggests a model for REM sleep that may be consistent with its role in dream formation and memory consolidation.

Separating slow BOLD from non-BOLD baseline drifts using multi-echo fMRI.

The functional magnetic resonance (fMRI) baseline is known to drift over the course of an experiment and is often attributed to hardware instability. These ultraslow fMRI fluctuations are inseparable from blood oxygenation level dependent (BOLD) changes in standard single echo fMRI and they are therefore typically removed before further analysis in both resting-state and task paradigms. However, some part of these fluctuations may be of neuronal origin, as neural activity can indeed fluctuate at the scale of several minutes or even longer, such as after the administration of drugs or during the ultradian rhythms. Here, we show that it is possible to separate the slow BOLD and non-BOLD drifts automatically using multi-echo fMRI and multi-echo independent components analysis (ME-ICA) denoising by demonstrating the detection of a visual signal evoked from a flickering checkerboard with slowly changing contrast.

Role of the right dorsal anterior insula in the urge to tic in Tourette syndrome.

BACKGROUND: The mid-posterior part of the insula is involved in processing bodily sensations and urges and is activated during tic generation in Tourette syndrome. The dorsal anterior part of the insula, however, integrates sensory and emotional information with cognitive valuation and is implicated in interoception. The right dorsal anterior insula also participates in urge suppression in healthy subjects. This study examined the role of the right dorsal anterior insula in the urge to tic in Tourette syndrome. METHODS: Resting-state functional magnetic resonance imaging was performed in 13 adult Tourette patients and 13 matched controls. The role of the right dorsal anterior insula within the urge-tic network was investigated using graph theory-based neural network analysis. The functional connectivity of the right dorsal anterior insula was also correlated with urge and tic severity. RESULTS: Even though the patients did not exhibit any overt tics, the right dorsal anterior insula demonstrated higher connectivity, especially with the frontostriatal nodes of the urge-tic network in patients compared with controls. The functional connectivity between the right dorsal anterior insula and bilateral supplementary motor area also correlated positively with urge severity in patients. CONCLUSIONS: These results suggest that the right dorsal anterior insula is part of the urge-tic network and could influence the urge- and tic-related cortico-striato-thalamic regions even during rest in Tourette syndrome. It might be responsible for heightened awareness of bodily sensations generating premonitory urges in Tourette syndrome.

Role of the sensorimotor cortex in Tourette syndrome using multimodal imaging.

Tourette syndrome (TS) is a neuropsychiatric disorder characterized by motor and vocal tics. Most patients describe uncomfortable premonitory sensations preceding the tics and a subjective experience of increased sensitivity to tactile stimuli. These reports indicate that a sensory processing disturbance is an important component of TS together with motor phenomena. Thus, we focused our investigation on the role of the sensorimotor cortex (SMC) in TS using multimodal neuroimaging techniques. We measured the gamma-aminobutyric acid (GABA)+/Creatine (Cre) ratio in the SMC using GABA (1) H magnetic resonance spectroscopy. We recorded the baseline beta activity in the SMC using magnetoencephalography and correlated GABA+/Cre ratio with baseline beta band power. Finally, we examined the resting state functional connectivity (FC) pattern of the SMC using functional magnetic resonance imaging (fMRI). GABA+/Cre ratio in the SMC did not differ between patients and controls. Correlation between the baseline beta band power and GABA+/Cre ratio was abnormal in patients. The anterior insula showed increased FC with the SMC in patients. These findings suggest that altered limbic input to the SMC and abnormal GABA-mediated beta oscillations in the SMC may underpin some of the sensorimotor processing disturbances in TS and contribute to tic generation.

Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome.

Post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS) is a disabling disorder, yet the clinical phenotype is poorly defined, the pathophysiology is unknown, and no disease-modifying treatments are available. We used rigorous criteria to recruit PI-ME/CFS participants with matched controls to conduct deep phenotyping. Among the many physical and cognitive complaints, one defining feature of PI-ME/CFS was an alteration of effort preference, rather than physical or central fatigue, due to dysfunction of integrative brain regions potentially associated with central catechol pathway dysregulation, with consequences on autonomic functioning and physical conditioning. Immune profiling suggested chronic antigenic stimulation with increase in naïve and decrease in switched memory B-cells. Alterations in gene expression profiles of peripheral blood mononuclear cells and metabolic pathways were consistent with cellular phenotypic studies and demonstrated differences according to sex. Together these clinical abnormalities and biomarker differences provide unique insight into the underlying pathophysiology of PI-ME/CFS, which may guide future intervention.

Sleep and the functional connectome.

Sleep and the functional connectome are research areas with considerable overlap. Neuroimaging studies of sleep based on EEG-PET and EEG-fMRI are revealing the brain networks that support sleep, as well as networks that may support the roles and processes attributed to sleep. For example, phenomena such as arousal and consciousness are substantially modulated during sleep, and one would expect this modulation to be reflected in altered network activity. In addition, recent work suggests that sleep also has a number of adaptive functions that support waking activity. Thus the study of sleep may elucidate the circuits and processes that support waking function and complement information obtained from fMRI during waking conditions. In this review, we will discuss examples of this for memory, arousal, and consciousness after providing a brief background on sleep and on studying it with fMRI.

Classification of Functional Movement Disorders with Resting-State Functional Magnetic Resonance Imaging.

Introduction: Functional movement disorder (FMD) is a type of functional neurological disorder characterized by abnormal movements that patients do not perceive as self-generated. Prior imaging studies show a complex pattern of altered activity, linking regions of the brain involved in emotional responses, motor control, and agency. This study aimed to better characterize these relationships by building a classifier using a support vector machine to accurately distinguish between 61 FMD patients and 59 healthy controls using features derived from resting-state functional magnetic resonance imaging. Materials and Methods: First, we selected 66 seed regions based on prior related studies, then we calculated the full correlation matrix between them before performing recursive feature elimination to winnow the feature set to the most predictive features and building the classifier. Results: We identified 29 features of interest that were highly predictive of the FMD condition, classifying patients and controls with 80% accuracy. Several key features included regions in the right sensorimotor cortex, left dorsolateral prefrontal cortex, left cerebellum, and left posterior insula. Conclusions: The features selected by the model highlight the importance of the interconnected relationship between areas associated with emotion, reward, and sensorimotor integration, potentially mediating communication between regions associated with motor function, attention, and executive function. Exploratory machine learning was able to identify this distinctive abnormal pattern, suggesting that alterations in functional linkages between these regions may be a consistent feature of the condition in many FMD patients. Clinical-Trials.gov ID: NCT00500994 Impact statement Our research presents novel results that further elucidate the pathophysiology of functional movement disorder (FMD) with a machine learning model that classifies FMD and healthy controls correctly 80% of the time. Herein, we demonstrate how known differences in resting-state functional magnetic resonance imaging connectivity in FMD patients can be leveraged to better understand the complex pattern of neural changes in these patients. Knowing that there are measurable predictable differences in brain activity in patients with FMD may help both clinicians and patients conceptualize and better understand the illness at the point of diagnosis and during treatment. Our methods demonstrate how an effective combination of machine learning and qualitative approaches to analyzing functional brain connectivity can enhance our understanding of abnormal patterns of brain activity in FMD patients.

Laminar VASO fMRI in focal hand dystonia patients.

Focal Hand Dystonia (FHD) is a disabling movement disorder characterized by involuntary movements, cramps and spasms. It is associated with pathological neural microcircuits in the cortical somatosensory system. While invasive preclinical modalities allow researchers to probe specific neural microcircuits of cortical layers and columns, conventional functional magnetic resonance imaging (fMRI) cannot resolve such small neural computational units. In this study, we take advantage of recent developments in ultra-high-field MRI hardware and MR-sequences to capture altered digit representations and laminar processing in FHD patients. We aim to characterize the capability and challenges of layer-specific imaging and analysis tools in resolving laminar and columnar structures in clinical research setups. We scanned N = 4 affected and N = 5 unaffected hemispheres at 7T and found consistent results of altered neural microcircuitry in FHD patients: 1) In affected hemispheres of FHD patients, we found a breakdown of ordered finger representation in the primary somatosensory cortex, as suggested from previous low-resolution fMRI. 2) In affected primary motor cortices of FHD patients, we furthermore found increased fMRI activity in superficial cortico-cortical neural input layers (II/III), compared to relatively weaker activity in the cortico-spinal output layers (Vb/VI). Overall, we show that layer-fMRI acquisition and analysis tools have the potential to address clinically-driven neuroscience research questions about altered computational mechanisms at the spatial scales that were previously only accessible in animal models. We believe that this study paves the way for easier translation of preclinical work into clinical research in focal hand dystonia and beyond.

Individuated finger control in focal hand dystonia: an fMRI study.

OBJECTIVES: To better understand deficient selective motor control in focal hand dystonia by determining changes in striatal activation and connectivity in patients performing individuated finger control. METHODS: Functional imaging with a 3-Tesla magnetic resonance scanner was performed on 18 patients and 17 controls during non-symptom producing tasks requiring right-handed individuated or coupled finger control. A global linear model and psychophysiologic interaction model compared individuated to coupled tasks for patients and controls separately, and the results were submitted to a group analysis. The sensorimotor (posterior) and associative (anterior) parts of the putamen were considered as seed regions for the connectivity analysis. RESULTS: Compared to controls, patients had significant differences in activations and connectivity during individuated compared to coupled tasks: (i) decreased activations in the bilateral postcentral gyri, right associative posterior parietal areas, right cerebellum and left posterior putamen, while activations in the left anterior putamen were not different; (ii) increased connectivity of the left posterior putamen with the left cerebellum and left sensorimotor cortex; and (iii) increased connectivity of the left anterior putamen with bilateral supplementary motor areas, the left premotor cortex, and left cerebellum. INTERPRETATION: Decreased activations in the sensorimotor putamen and cerebellum controlling the affected hand might underlie low levels of surround inhibition during individuated tasks. For identical motor performance in both groups, increased connectivity of sensorimotor and associative striato-cortical circuits in FHD suggests that both affected and unaffected territories of the striatum participate in compensatory processes.

Self-modulation of primary motor cortex activity with motor and motor imagery tasks using real-time fMRI-based neurofeedback.

Advances in fMRI data acquisition and processing have made it possible to analyze brain activity as rapidly as the images are acquired allowing this information to be fed back to subjects in the scanner. The ability of subjects to learn to volitionally control localized brain activity within motor cortex using such real-time fMRI-based neurofeedback (NF) is actively being investigated as it may have clinical implications for motor rehabilitation after central nervous system injury and brain-computer interfaces. We investigated the ability of fifteen healthy volunteers to use NF to modulate brain activity within the primary motor cortex (M1) during a finger tapping and tapping imagery task. The M1 hand area ROI (ROI(m)) was functionally localized during finger tapping and a visual representation of BOLD signal changes within the ROI(m) fed back to the subject in the scanner. Surface EMG was used to assess motor output during tapping and ensure no motor activity was present during motor imagery task. Subjects quickly learned to modulate brain activity within their ROI(m) during the finger-tapping task, which could be dissociated from the magnitude of the tapping, but did not show a significant increase within the ROI(m) during the hand motor imagery task at the group level despite strongly activating a network consistent with the performance of motor imagery. The inability of subjects to modulate M1 proper with motor imagery may reflect an inherent difficulty in activating synapses in this area, with or without NF, since such activation may lead to M1 neuronal output and obligatory muscle activity. Future real-time fMRI-based NF investigations involving motor cortex may benefit from focusing attention on cortical regions other than M1 for feedback training or alternative feedback strategies such as measures of functional connectivity within the motor system.

Neural correlates of blink suppression and the buildup of a natural bodily urge.

Neuroimaging studies have elucidated some of the underlying physiology of spontaneous and voluntary eye blinking; however, the neural networks involved in eye blink suppression remain poorly understood. Here we investigated blink suppression by analyzing fMRI data in a block design and event-related manner, and employed a novel hypothetical time-varying neural response model to detect brain activations associated with the buildup of urge. Blinks were found to activate visual cortices while our block design analysis revealed activations limited to the middle occipital gyri and deactivations in medial occipital, posterior cingulate and precuneus areas. Our model for urge, however, revealed a widespread network of activations including right greater than left insular cortex, right ventrolateral prefrontal cortex, middle cingulate cortex, and bilateral temporo-parietal cortices, primary and secondary face motor regions, and visual cortices. Subsequent inspection of BOLD time-series in an extensive ROI analysis showed that activity in the bilateral insular cortex, right ventrolateral prefrontal cortex, and bilateral STG and MTG showed strong correlations with our hypothetical model for urge suggesting these areas play a prominent role in the buildup of urge. The involvement of the insular cortex in particular, along with its function in interoceptive processing, helps support a key role for this structure in the buildup of urge during blink suppression. The right ventrolateral prefrontal cortex findings in conjunction with its known involvement in inhibitory control suggest a role for this structure in maintaining volitional suppression of an increasing sense of urge. The consistency of our urge model findings with prior studies investigating the suppression of blinking and other bodily urges, thoughts, and behaviors suggests that a similar investigative approach may have utility in fMRI studies of disorders associated with abnormal urge suppression such as Tourette syndrome and obsessive-compulsive disorder.

Decoupling of the brain's default mode network during deep sleep.

The recent discovery of a circuit of brain regions that is highly active in the absence of overt behavior has led to a quest for revealing the possible function of this so-called default-mode network (DMN). A very recent study, finding similarities in awake humans and anesthetized primates, has suggested that DMN activity might not simply reflect ongoing conscious mentation but rather a more general form of network dynamics typical of complex systems. Here, by performing functional MRI in humans, it is shown that a natural, sleep-induced reduction of consciousness is reflected in altered correlation between DMN network components, most notably a reduced involvement of frontal cortex. This suggests that DMN may play an important role in the sustenance of conscious awareness.