Functional and effective connectivity of visuomotor control systems demonstrated using generalized partial least squares and structural equation modeling

Seizure Frequency Is Associated with Effective Connectivity of the Hippocampal-Diencephalic-Cingulate in Epilepsy with Unilateral Mesial Temporal Sclerosis

Background: Temporal lobe epilepsy (TLE) with mesial temporal sclerosis (MTS) is a common intractable epilepsy. To seek neural correlates of seizure recurrence, this study investigated aberrant intrinsic effective connectivity (iEC) in TLE with unilateral MTS and their associations with seizure frequency. Methods: Thirty patients with unilateral MTS (left/right MTS = 14/16) and 37 age-matched healthy controls underwent resting-state functional magnetic resonance imaging (rsfMRI) on a 3-Tesla magnetic resonance imaging (MRI) system. The structural equation modeling was employed to estimate the iEC of the three candidate epilepsy models, including the Papez circuit, hippocampal-diencephalic-cingulate (HDC) model, and simplified HDC model. After comparing the performance of model fitting, the best model was selected to compare iEC among the study groups. The linear regression analysis was performed to associate abnormal iEC with seizure frequency. Results: The simplified HDC model was the best model to estimate iEC across the three study groups (p < 0.05), and it composed of the 26 interconnected pathway between the mesial temporal lobe, thalamus, and cingulate cortices. The linear regression analysis revealed a significant relationship between the shared iEC alterations in both patient groups and seizure frequency (adjusted-R² = 0.350; p = 0.037), including the three paths of mammillary body (MB) → bilateral anterior thalamic nuclei (left: standardized β-value = 0.580, p = 0.013; right: standardized β-value = -0.711, p = 0.006) and right hippocampus → MB (standardized β-value = 0.541, p = 0.045). Conclusions: Our findings provide new insights into neurophysiological significance relevant to seizure recurrence. Aberrant iEC on the neural paths connected to the MB can be a potential imaging marker, aiding the therapeutic management in TLE with unilateral MTS. Impact statement Within the simplified hippocampal-diencephalic-cingulate model, we identified that altered intrinsic effective connectivity (iEC) on the three paths connecting to the mammillary body was common in temporal lobe epilepsy (TLE) with left and right mesial temporal sclerosis (MTS) and was associated with seizure frequency. Therefore, these common iEC alterations could be a potential imaging marker, aiding the therapeutic management in patients with TLE with unilateral MTS.

Fronto-cerebellar connectivity mediating cognitive processing speed

Processing speed is an important construct in understanding cognition. This study was aimed to control task specificity for understanding the neural mechanisms underlying cognitive processing speed. Forty young adult subjects performed attention tasks of two modalities (auditory and visual) and two levels of task rules (compatible and incompatible). Block-design fMRI captured BOLD signals during the tasks. Thirteen regions of interest were defined with reference to publicly available activation maps for processing speed tasks. Cognitive speed was derived from task reaction times, which yielded six sets of connectivity measures. Mixed-effect LASSO regression revealed six significant paths suggestive of a cerebello-frontal network predicting the cognitive speed. Among them, three are long range (two fronto-cerebellar, one cerebello-frontal), and three are short range (fronto-frontal, cerebello-cerebellar, and cerebello-thalamic). The long-range connections are likely to relate to cognitive control, and the short-range connections relate to rule-based stimulus-response processes. The revealed neural network suggests that automaticity, acting on the task rules and interplaying with effortful top-down attentional control, accounts for cognitive speed.

Activations in gray and white matter are modulated by uni-manual responses during within and inter-hemispheric transfer: effects of response hand and right-handedness

Because the visual cortices are contra-laterally organized, inter-hemispheric transfer tasks have been used to behaviorally probe how information briefly presented to one hemisphere of the visual cortex is integrated with responses resulting from the ipsi- or contra-lateral motor cortex. By forcing rapid information exchange across diverse regions, these tasks robustly activate not only gray matter regions, but also white matter tracts. It is likely that the response hand itself (dominant or non-dominant) modulates gray and white matter activations during within and inter-hemispheric transfer. Yet the role of uni-manual responses and/or right hand dominance in modulating brain activations during such basic tasks is unclear. Here we investigated how uni-manual responses with either hand modulated activations during a basic visuo-motor task (the established Poffenberger paradigm) alternating between inter- and within-hemispheric transfer conditions. In a large sample of strongly right-handed adults (n = 49), we used a factorial combination of transfer condition [Inter vs. Within] and response hand [Dominant(Right) vs. Non-Dominant (Left)] to discover fMRI-based activations in gray matter, and in narrowly defined white matter tracts. These tracts were identified using a priori probabilistic white matter atlases. Uni-manual responses with the right hand strongly modulated activations in gray matter, and notably in white matter. Furthermore, when responding with the left hand, activations during inter-hemispheric transfer were strongly predicted by the degree of right-hand dominance, with increased right-handedness predicting decreased fMRI activation. Finally, increasing age within the middle-aged sample was associated with a decrease in activations. These results provide novel evidence of complex relationships between uni-manual responses in right-handed subjects, and activations during within- and inter-hemispheric transfer suggest that the organization of the motor system exerts sophisticated functional effects. Moreover, our evidence of activation in white matter tracts is consistent with prior studies, confirming fMRI-detectable white matter activations which are systematically modulated by experimental condition.

Exoskeleton-Robot Assisted Therapy in Stroke Patients: A Lesion Mapping Study

Background: Technology-supported rehabilitation is emerging as a solution to support therapists in providing a high-intensity, repetitive and task-specific treatment, aimed at improving stroke recovery. End-effector robotic devices are known to positively affect the recovery of arm functions, however there is a lack of evidence regarding exoskeletons. This paper evaluates the impact of cerebral lesion load on the response to a validated robotic-assisted rehabilitation protocol.

Methods: Fourteen hemiparetic patients were assessed in a within-subject design (age 66.9 ± 11.3 years; 10 men and 4 women). Patients, in post-acute phase, underwent 7 weeks of bilateral arm training assisted by an exoskeleton robot combined with a conventional treatment (consisting of simple physical activity together with occupational therapy). Clinical and neuroimaging evaluations were performed immediately before and after rehabilitation treatments. Fugl-Meyer (FM) and Motricity Index (MI) were selected to measure primary outcomes, i.e., motor function and strength. Functional independance measure (FIM) and Barthel Index were selected to measure secondary outcomes, i.e., daily living activities. Voxel-based lesion symptom mapping (VLSM) was used to determine the degree of cerebral lesions associated with motor recovery.

Results: Robot-assisted rehabilitation was effective in improving upper limb motor function recovery, considering both primary and secondary outcomes. VLSM detected that lesion load in the superior region of the corona radiata, internal capsule and putamen were significantly associated with recovery of the upper limb as defined by the FM scores (p-level < 0.01).

Conclusions: The probability of functional recovery from stroke by means of exoskeleton robotic rehabilitation relies on the integrity of specific subcortical regions involved in the primary motor pathway. This is consistent with previous evidence obtained with conventional neurorehabilitation approaches.

Parietal operculum and motor cortex activities predict motor recovery in moderate to severe stroke

While motor recovery following mild stroke has been extensively studied with neuroimaging, mechanisms of recovery after moderate to severe strokes of the types that are often the focus for novel restorative therapies remain obscure. We used fMRI to: 1) characterize reorganization occurring after moderate to severe subacute stroke, 2) identify brain regions associated with motor recovery and 3) to test whether brain activity associated with passive movement measured in the subacute period could predict motor outcome six months later.

Because many patients with large strokes involving sensorimotor regions cannot engage in voluntary movement, we used passive flexion-extension of the paretic wrist to compare 21 patients with subacute ischemic stroke to 24 healthy controls one month after stroke. Clinical motor outcome was assessed with Fugl-Meyer motor scores (motor-FMS) six months later. Multiple regression, with predictors including baseline (one-month) motor-FMS and sensorimotor network regional activity (ROI) measures, was used to determine optimal variable selection for motor outcome prediction. Sensorimotor network ROIs were derived from a meta-analysis of arm voluntary movement tasks. Bootstrapping with 1000 replications was used for internal model validation.

During passive movement, both control and patient groups exhibited activity increases in multiple bilateral sensorimotor network regions, including the primary motor (MI), premotor and supplementary motor areas (SMA), cerebellar cortex, putamen, thalamus, insula, Brodmann area (BA) 44 and parietal operculum (OP1-OP4). Compared to controls, patients showed: 1) lower task-related activity in ipsilesional MI, SMA and contralesional cerebellum (lobules V-VI) and 2) higher activity in contralesional MI, superior temporal gyrus and OP1-OP4. Using multiple regression, we found that the combination of baseline motor-FMS, activity in ipsilesional MI (BA4a), putamen and ipsilesional OP1 predicted motor outcome measured 6 months later (adjusted-R² = 0.85; bootstrap p < 0.001). Baseline motor-FMS alone predicted only 54% of the variance. When baseline motor-FMS was removed, the combination of increased activity in ipsilesional MI-BA4a, ipsilesional thalamus, contralesional mid-cingulum, contralesional OP4 and decreased activity in ipsilesional OP1, predicted better motor outcome (djusted-R² = 0.96; bootstrap p < 0.001).

In subacute stroke, fMRI brain activity related to passive movement measured in a sensorimotor network defined by activity during voluntary movement predicted motor recovery better than baseline motor-FMS alone. Furthermore, fMRI sensorimotor network activity measures considered alone allowed excellent clinical recovery prediction and may provide reliable biomarkers for assessing new therapies in clinical trial contexts. Our findings suggest that neural reorganization related to motor recovery from moderate to severe stroke results from balanced changes in ipsilesional MI (BA4a) and a set of phylogenetically more archaic sensorimotor regions in the ventral sensorimotor trend, in which OP1 and OP4 processes may complement the ipsilesional dorsal motor cortex in achieving compensatory sensorimotor recovery.

•

Motor recovery after stroke can be robustly predicted using a passive task fMRI paradigm.

•

Sensorimotor network activity is decreased in moderate to severe stroke patients relative to healthy controls

•

Compensatory mechanisms in severe stroke involve both the dorsal (MI BA4a), and the ventral (OP1 and OP4) sensorimotor stream

Performance monitoring and behavioral adaptation during task switching: an fMRI study

Despite significant advances, the neural correlates and neurochemical mechanisms involved in performance monitoring and behavioral adaptation are still a matter for debate. Here, we used a modified Eriksen-Flanker task in a magnetic resonance imaging (MRI) study that required the participants to derive the correct stimulus-response association based on a feedback given after each flanker stimulus. Participants had to continuously monitor and adapt their performance as the stimulus-response association switched after a jittered time interval without notice. After every switch an increase of reaction times was observed. At the neural level, the feedback indicating the need to switch was associated with activation of the precuneus, the cingulate cortex, the insula and a brainstem region tentatively identified as the locus coeruleus. This brainstem system appears to interact with this cortical network and seems to be essential for performance monitoring and behavioral adaptation. In contrast, the cerebellum crus and prefrontal areas are activated during error feedback processing. Furthermore we found activations of the hippocampus and parahippocampal gyrus bilaterally after a correct feedback in learnable stimulus-response associations. These results highlight the contribution of brainstem nuclei to performance adaptation.

Network dynamics engaged in the modulation of motor behavior in healthy subjects

Motor skills are mediated by a dynamic and finely regulated interplay of the primary motor cortex (M1) with various cortical and subcortical regions engaged in movement preparation and execution. To date, data elucidating the dynamics in the motor network that enable movements at different levels of behavioral performance remain scarce. We here used functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to investigate effective connectivity of key motor areas at different movement frequencies performed by right-handed subjects (n=36) with the left or right hand. The network of interest consisted of motor regions in both hemispheres including M1, supplementary motor area (SMA), ventral premotor cortex (PMv), motor putamen, and motor cerebellum. The connectivity analysis showed that performing hand movements at higher frequencies was associated with a linear increase in neural coupling strength from premotor areas (SMA, PMv) contralateral to the moving hand and ipsilateral cerebellum towards contralateral, active M1. In addition, we found hemispheric differences in the amount by which the coupling of premotor areas and M1 was modulated, depending on which hand was moved. Other connections were not modulated by changes in motor performance. The results suggest that a stronger coupling, especially between contralateral premotor areas and M1, enables increased motor performance of simple unilateral hand movements.

Physiological interference in effective connectivity of action network

The effect of temporal interference of physiological signals on time-lag effective connectivity, derived from a functional network connectivity tool box (FNC), was examined by a blood-oxygen-level-dependent functional MRI study of action. The known effect of physiological signals on time-lag FNC was verified by (a) comparison of time-lag FNC analyses without and with retrospective image-based correction (RETROICOR) and (b) the other time-lag FNC analysis including the ventricular component related to the cerebrospinal fluid with dominant physiological effects. Twenty-five right-handed normal individuals performed motor task with motor response by the right middle/index fingers. Behavioral data of the reaction time (RT) and physiological signals (electrocardiogram, respiration, and pulsation) were recorded during neuroimaging studies of a 2-s repetition time at 3T. After standard image preprocessing, RETROICOR of the physiological effects and group independent component analysis (ICA), five action-related components were selected from 59 ICA components according to spatial extension involving known functional correlates of visuomotor tasks. Time-lag FNC was constructed by calculating the maximal correlation coefficients among five selected components. Attenuation of the physiological effect at 0.02-0.25 Hz was an average of 0.63 dB after RETROICOR (P<0.0005). Results of FNC analyses without and with RETROICOR were compatible with the action networks using the right hand. On the basis of the time-lag FNC after RETROICOR, the connectivity among the ventricular component and other components of action network attenuated. The FNC map with RETROICOR was more explicable with known action networks, for example interhemispheric inhibition. The effects of physiological signals significantly misled the interpretation of time-lag FNC in terms of direction and connectivity strength.

Ultrafast inverse imaging techniques for fMRI

Inverse imaging (InI) supercharges the sampling rate of traditional functional MRI 10-100 fold at a cost of a moderate reduction in spatial resolution. The technique is inspired by similarities between multi-sensor magnetoencephalography (MEG) and highly parallel radio-frequency (RF) MRI detector arrays. Using presently available 32-channel head coils at 3T, InI can be sampled at 10 Hz and provides about 5-mm cortical spatial resolution with whole-brain coverage. Here we discuss the present applications of InI, as well as potential future challenges and opportunities in further improving its spatiotemporal resolution and sensitivity. InI may become a helpful tool for clinicians and neuroscientists for revealing the complex dynamics of brain functions during task-related and resting states.

Functional neuroimaging studies of sexual arousal and orgasm in healthy men and women: a review and meta-analysis

In the last fifteen years, functional neuroimaging techniques have been used to investigate the neuroanatomical correlates of sexual arousal in healthy human subjects. In most studies, subjects have been requested to watch visual sexual stimuli and control stimuli. Our review and meta-analysis found that in heterosexual men, sites of cortical activation consistently reported across studies are the lateral occipitotemporal, inferotemporal, parietal, orbitofrontal, medial prefrontal, insular, anterior cingulate, and frontal premotor cortices as well as, for subcortical regions, the amygdalas, claustrum, hypothalamus, caudate nucleus, thalami, cerebellum, and substantia nigra. Heterosexual and gay men show a similar pattern of activation. Visual sexual stimuli activate the amygdalas and thalami more in men than in women. Ejaculation is associated with decreased activation throughout the prefrontal cortex. We present a neurophenomenological model to understand how these multiple regional brain responses could account for the varied facets of the subjective experience of sexual arousal. Further research should shift from passive to active paradigms, focus on functional connectivity and use subliminal presentation of stimuli.

A cerebellar thalamic cortical circuit for error-related cognitive control

Error detection and behavioral adjustment are core components of cognitive control. Numerous studies have focused on the anterior cingulate cortex (ACC) as a critical locus of this executive function. Our previous work showed greater activation in the dorsal ACC and subcortical structures during error detection, and activation in the ventrolateral prefrontal cortex (VLPFC) during post-error slowing (PES) in a stop signal task (SST). However, the extent of error-related cortical or subcortical activation across subjects was not correlated with VLPFC activity during PES. So then, what causes VLPFC activation during PES? To address this question, we employed Granger causality mapping (GCM) and identified regions that Granger caused VLPFC activation in 54 adults performing the SST during fMRI. These brain regions, including the supplementary motor area (SMA), cerebellum, a pontine region, and medial thalamus, represent potential targets responding to errors in a way that could influence VLPFC activation. In confirmation of this hypothesis, the error-related activity of these regions correlated with VLPFC activation during PES, with the cerebellum showing the strongest association. The finding that cerebellar activation Granger causes prefrontal activity during behavioral adjustment supports a cerebellar function in cognitive control. Furthermore, multivariate GCA described the "flow of information" across these brain regions. Through connectivity with the thalamus and SMA, the cerebellum mediates error and post-error processing in accord with known anatomical projections. Taken together, these new findings highlight the role of the cerebello-thalamo-cortical pathway in an executive function that has heretofore largely been ascribed to the anterior cingulate-prefrontal cortical circuit.