The dorsal mesial frontal cortex contains the supplementary motor area (SMA) and the pre-supplementary motor area (pre-SMA), which play an important role in action and cognition. Evidence from cytoarchitectonic, stimulation, and functional studies suggests structural and functional divergence between the two subregions. However, a microstructural map of these areas obtained in a representative sample of brains in a stereotaxic reference space is still lacking. In the present study we show that the dorsal mesial frontal motor cortex comprises two microstructurally different brain regions: area SMA and area pre-SMA. Area-specific cytoarchitectonic patterns were studied in serial histological sections stained for cell bodies of ten human postmortem brains. Borders of the two cortical areas were identified using image analysis and statistical features. The 3D reconstructed areas were transferred to a common reference space, and probabilistic maps were calculated by superimposing the individual maps. A coordinate-based meta-analysis of functional imaging data was subsequently performed using the two probabilistic maps as microstructurally defined seed regions. It revealed that areas SMA and pre-SMA were strongly co-activated with areas in precentral, supramarginal and superior frontal gyri, Rolandic operculum, thalamus, putamen and cerebellum. Both areas were related to motor functions, but area pre-SMA was involved in more complex processes such as learning, cognitive processes and perception. The here described subsequent analyses led to converging evidence supporting the microstructural, and functional segregation of areas SMA and pre-SMA, and maps will be made available to the scientific community to further elucidate the microstructural substrates of motor and cognitive control.
The aim of this study was to provide a computational system model of effective connectivity in the human brain underlying overt speech production. Meta-analysis of neuroimaging studies and functional magnetic resonance imaging data acquired during a verbal fluency task revealed a core network consisting of Brodmann's area (BA) 44 in Broca's region, anterior insula, basal ganglia, cerebellum, premotor cortex (PMC, BA 6) and primary motor cortex (M1, areas 4a/4p). Dynamic causal modelling (DCM) indicated the highest evidence for a system architecture featuring the insula in a serial position between BA 44 and two parallel nodes (cerebellum/basal ganglia), from which information converges onto the PMC and finally M1. Parameter inference revealed that effective connectivity from the insular relay into the cerebellum/basal ganglia is primarily task driven (preparation) while the output into the cortical motor system strongly depends on the actual word production rate (execution). DCM hence allowed not only a quantitative characterization of the human speech production network, but also the distinction of a preparatory and an executive subsystem within it. The proposed model of physiological integration during speech production may now serve as a reference for investigations into the neurobiology of pathological states such as dysarthria and apraxia of speech.
Over 90 percent of patients with Parkinson's disease experience speech-motor impairment, namely, hypokinetic dysarthria characterized by reduced pitch and loudness. Resting-state functional connectivity analysis of blood oxygen level-dependent functional magnetic resonance imaging is a useful measure of intrinsic neural functioning. We utilized resting-state functional connectivity modeling to analyze the intrinsic connectivity in patients with Parkinson's disease within a vocalization network defined by a previous meta-analysis of speech (Brown et al., 2009). Functional connectivity of this network was assessed in 56 patients with Parkinson's disease and 56 gender-, age-, and movement-matched healthy controls. We also had item 5 and 18 of the UPDRS, and the PDQ-39 Communication subscale available for correlation with the voice network connectivity strength in patients. The within-group analyses of connectivity patterns demonstrated a lack of subcortical-cortical connectivity in patients with Parkinson's disease. At the cortical level, we found robust (homotopic) interhemispheric connectivity but only inconsistent evidence for many intrahemispheric connections. When directly contrasted to the control group, we found a significant reduction of connections between the left thalamus and putamen, and cortical motor areas, as well as reduced right superior temporal gyrus connectivity. Furthermore, most symptom measures correlated with right putamen, left cerebellum, left superior temporal gyrus, right premotor, and left Rolandic operculum connectivity in the voice network. The results reflect the importance of (right) subcortical nodes and the superior temporal gyrus in Parkinson's disease, enhancing our understanding of the neurobiological underpinnings of vocalization impairment in Parkinson's disease.
A typical feature of Parkinson's disease (PD) is pathological activity in the subthalamic nucleus (STN). Here, we tested whether in patients with PD under dopaminergic treatment functional connectivity of the STN differs from healthy controls (HC) and whether some brain regions show (anti-) correlations between functional connectivity with STN and motor symptoms. We used functional magnetic resonance imaging to investigate whole-brain resting-state functional connectivity with STN in 54 patients with PD and 55 HC matched for age, gender, and within-scanner motion. Compared to HC, we found attenuated negative STN-coupling with Crus I of the right cerebellum and with right ventromedial prefrontal regions in patients with PD. Furthermore, we observed enhanced negative STN-coupling with bilateral intraparietal sulcus/superior parietal cortex, right sensorimotor, right premotor, and left visual cortex compared to HC. Finally, we found a decline in positive STN-coupling with the left insula related to severity of motor symptoms and a decline of inter-hemispheric functional connectivity between left and right STN with progression of PD-related motor symptoms. Motor symptom related uncoupling of the insula, a key region in the saliency network and for executive function, from the STN might be associated with well-known executive dysfunction in PD. Moreover, uncoupling between insula and STN might also induce an insufficient setting of thresholds for the discrimination between relevant and irrelevant salient environmental stimuli, explaining observations of disturbed response control in PD. In sum, motor symptoms in PD are associated with a reduced coupling between STN and a key region for executive function.
Several neurobiological factors have been found to correlate with functional recovery after brain lesions. However, predicting the individual potential of recovery remains difficult. Here we used multivariate support vector machine (SVM) classification to explore the prognostic value of functional magnetic resonance imaging (fMRI) to predict individual motor outcome at 4-6 months post-stroke. To this end, 21 first-ever stroke patients with hand motor deficits participated in an fMRI hand motor task in the first few days post-stroke. Motor impairment was quantified assessing grip force and the Action Research Arm Test. Linear SVM classifiers were trained to predict good versus poor motor outcome of unseen new patients. We found that fMRI activity acquired in the first week post-stroke correctly predicted the outcome for 86% of all patients. In contrast, the concurrent assessment of motor function provided 76% accuracy with low sensitivity (<60%). Furthermore, the outcome of patients with initially moderate impairment and high outcome variability could not be predicted based on motor tests. In contrast, fMRI provided 87.5% prediction accuracy in these patients. Classifications were driven by activity in ipsilesional motor areas and contralesional cerebellum. The accuracy of subacute fMRI data (two weeks post-stroke), age, time post-stroke, lesion volume, and location were at 50%-chance-level. In conclusion, multivariate decoding of fMRI data with SVM early after stroke enables a robust prediction of motor recovery. The potential for recovery is influenced by the initial dysfunction of the active motor system, particularly in those patients whose outcome cannot be predicted by behavioral tests.
The cerebellum historically has been thought to mediate motor and sensory signals between the body and cerebral cortex, yet cerebellar lesions are also associated with altered cognitive behavioral performance. Neuroimaging evidence indicates that the cerebellum contributes to a wide range of cognitive, perceptual, and motor functions. Here, we used the BrainMap database to investigate whole-brainco-activation patterns between cerebellar structures and regions of the cerebral cortex, as well as associations with behavioral tasks. Hierarchical clustering was performed to meta-analytically identify cerebellar structures with similar cortical co-activation, and independently, with similar correlations to specific behavioral tasks. Strong correspondences were observed in these separate but parallel analyses of meta-analytic connectivity and behavioral metadata. We recovered differential zones of cerebellar co-activation that are reflected across the literature. Furthermore, the behaviors and tasks associated with the different cerebellar zones provide insight into the specialized function of the cerebellum, relating to high-order cognition, emotion, perception, interoception, and action. Taken together, these task-basedmeta-analytic results implicate distinct zones of the cerebellum as critically involved in the monitoring and mediation of psychological responses to internal and external stimuli.
Swallowing consists of a hierarchical sequence of primary motor and somatosensory processes. The temporal interplay of different phases is complex and clinical disturbances frequent. Of interest was the temporal interaction of the swallowing network. Time resolution optimized functional magnetic resonance imaging was used to describe the temporal sequence of representation sites of swallowing and their functional connectivity. Sixteen young healthy volunteers were investigated who swallowed 2 ml of water 20 times per run with a repetition time for functional imaging of 514 ms. After applying the general linear model approach to identify activation magnitude in preselected regions of interest repeated measures analysis of variance (rmANOVA) was used to detect relevant effects on lateralization, time, and onset. Furthermore, dynamic causal modeling (DCM) was applied to uncover where the input enters the model and the way in which the cortical regions are connected. The temporal analysis revealed a successive activation starting at the premotor cortex, supplementary motor area (SMA), and bilateral thalamus, followed by the primary sensorimotor cortex, the posterior insula, and cerebellum and culminating with activation in the pons shortly before subsiding. The rmANOVA revealed that activation was lateralized initially to the left hemisphere and gradually moved to the right hemisphere over time. The group random effects DCM analysis resulted in a most likely model that consisted of inputs to SMA and M1S1, bidirectionally connected, and a one-way connection from M1S1 to the posterior insula.
Handedness denotes the individual predisposition to consistently use the left or right hand for most types of skilled movements. A putative neurobiological mechanism for handedness consists in hemisphere-specific differences in network dynamics that govern unimanual movements. We, therefore, used functional magnetic resonance imaging and dynamic causal modeling to investigate effective connectivity between key motor areas during fist closures of the dominant or non-dominant hand performed by 18 right- and 18 left-handers. Handedness was assessed employing the Edinburgh-Handedness-Inventory (EHI). The network of interest consisted of key motor regions in both hemispheres including the primary motor cortex (M1), supplementary motor area (SMA), ventral premotor cortex (PMv), motor putamen (Put) and motor cerebellum (Cb). The connectivity analysis revealed that in right-handed subjects movements of the dominant hand were associated with significantly stronger coupling of contralateral (left, i.e., dominant) SMA with ipsilateral SMA, ipsilateral PMv, contralateral motor putamen and contralateral M1 compared to equivalent connections in left-handers. The degree of handedness as indexed by the individual EHI scores also correlated with coupling parameters of these connections. In contrast, we found no differences between right- and left-handers when testing for the effect of movement speed on effective connectivity. In conclusion, the data show that handedness is associated with differences in effective connectivity within the human motor network with a prominent role of SMA in right-handers. Left-handers featured less asymmetry in effective connectivity implying different hemispheric mechanisms underlying hand motor control compared to right-handers.
Changes in fiber tract architecture have gained attention as a potentially important aspect of schizophrenia neuropathology. Although the exact pathogenesis of these abnormalities yet remains to be elucidated, a genetic component is highly likely. Neuregulin-1 (NRG1) is one of the best-validated schizophrenia susceptibility genes. We here report the impact of the Neuregulin-1 rs35753505 variant on white matter structure in healthy young individuals with no family history of psychosis. We compared fractional anisotropy in 54 subjects that were either homozygous for the risk C allele carriers (n = 31) for rs35753505 or homozygous for the T allele (n = 23) using diffusion tensor imaging with 3T. Tract-Based Spatial Statistics (TBSS), a method especially developed for diffusion data analysis, was used to improve white matter registration and to focus the statistical analysis to major fiber tracts. Statistical analysis showed that homozygous risk C allele carriers featured elevated fractional anisotropy (FA) in the right perihippocampal region and the white matter proximate to the left area 4p as well as the right hemisphere of the cerebellum. We found three clusters of reduced FA values in homozygous C allele carriers: in the left superior parietal region, the right prefrontal white matter and in the deep white matter of the left frontal lobe. Our results highlight the importance of Neuregulin-1 for structural connectivity of the right medial temporal lobe. This finding is in line with well known neuropathological findings in this region in patients with schizophrenia.
Parkinson's disease (PD) is characterized by typical extrapyramidal motor features and increasingly recognized non-motor symptoms such as working memory (WM) deficits. Using functional magnetic resonance imaging (fMRI), we investigated differences in neuronal activation during a motor WM task in 23 non-demented PD patients and 23 age- and gender-matched healthy controls. Participants had to memorize and retype variably long visuo-spatial stimulus sequences after short or long delays (immediate or delayed serial recall). PD patients showed deficient WM performance compared to controls, which was accompanied by reduced encoding-related activation in WM-related regions. Mirroring slower motor initiation and execution, reduced activation in motor structures such as the basal ganglia and superior parietal cortex was detected for both immediate and delayed recall. Increased activation in limbic, parietal and cerebellar regions was found during delayed recall only. Increased load-related activation for delayed recall was found in the posterior midline and the cerebellum. Overall, our results demonstrate that impairment of WM in PD is primarily associated with a widespread reduction of task-relevant activation, whereas additional parietal, limbic and cerebellar regions become more activated relative to matched controls. While the reduced WM-related activity mirrors the deficient WM performance, the additional recruitment may point to either dysfunctional compensatory strategies or detrimental crosstalk from "default-mode" regions, contributing to the observed impairment.
Auditory verbal hallucinations (AVH) are a hallmark of psychotic experience. Various mechanisms including misattribution of inner speech and imbalance between bottom-up and top-down factors in auditory perception potentially due to aberrant connectivity between frontal and temporo-parietal areas have been suggested to underlie AVH. Experimental evidence for disturbed connectivity of networks sustaining auditory-verbal processing is, however, sparse. We compared functional resting-state connectivity in 49 psychotic patients with frequent AVH and 49 matched controls. The analysis was seeded from the left middle temporal gyrus (MTG), thalamus, angular gyrus (AG) and inferior frontal gyrus (IFG) as these regions are implicated in extracting meaning from impoverished speech-like sounds. Aberrant connectivity was found for all seeds. Decreased connectivity was observed between the left MTG and its right homotope, between the left AG and the surrounding inferior parietal cortex (IPC) and the left inferior temporal gyrus, between the left thalamus and the right cerebellum, as well as between the left IFG and left IPC, and dorsolateral and ventrolateral prefrontal cortex (DLPFC/VLPFC). Increased connectivity was observed between the left IFG and the supplementary motor area (SMA) and the left insula and between the left thalamus and the left fusiform gyrus/hippocampus. The predisposition to experience AVH might result from decoupling between the speech production system (IFG, insula and SMA) and the self-monitoring system (DLPFC, VLPFC, IPC) leading to misattribution of inner speech. Furthermore, decreased connectivity between nodes involved in speech processing (AG, MTG) and other regions implicated in auditory processing might reflect aberrant top-down influences in AVH.
The rostral cingulate cortex has been associated with a multitude of cognitive control functions. Recent neuroimaging data suggest that the anterior midcingulate cortex (aMCC) has a key role for cognitive aspects of movement generation, i.e., intentional motor control. We here tested the functional connectivity of this area using two complementary approaches: (1) resting-state connectivity of the aMCC based on fMRI scans obtained in 100 subjects, and (2) functional connectivity in the context of explicit task conditions using meta-analytic connectivity modeling (MACM) over 656 imaging experiment. Both approaches revealed a convergent functional network architecture of the aMCC with prefrontal, premotor and parietal cortices as well as anterior insula, area 44/45, cerebellum and dorsal striatum. To specifically test the role of the aMCC's task-based functional connectivity in cognitive motor control, separate MACM analyses were conducted over "cognitive" and "action" related experimental paradigms. Both analyses confirmed the same task-based connectivity pattern of the aMCC. While the "cognition" domain showed higher convergence of activity in supramodal association areas in prefrontal cortex and anterior insula, "action" related experiments yielded higher convergence in somatosensory and premotor areas. Secondly, to probe the functional specificity of the aMCC's convergent functional connectivity, it was compared with a neural network of intentional movement initiation. This exemplary comparison confirmed the involvement of the state independent FC network of the aMCC in the intentional generation of movements. In summary, the different experiments of the present study suggest that the aMCC constitute a key region in the network realizing intentional motor control.
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.
Theories positing that the cerebellum contributes to cognitive as well as motor control are driven by two sources of information: (1) studies highlighting connections between the cerebellum and both prefrontal and motor territories, (2) functional neuroimaging studies demonstrating cerebellar activations evoked during the performance of both cognitive and motor tasks. However, almost no studies to date have combined these two sources of information and investigated cortico-cerebellar connectivity during task performance. Through the use of a novel neuroimaging tool (Meta-Analytic Connectivity Modelling) we demonstrate for the first time that cortico-cerebellar connectivity patterns seen in anatomical studies and resting fMRI are also present during task performance. Consistent with human and nonhuman primate anatomical studies cerebellar lobules Crus I and II were significantly coactivated with prefrontal and parietal cortices during task performance, whilst lobules HV, HVI, HVIIb, and HVIII were significantly coactivated with the pre- and postcentral gyrus. An analysis of the behavioral domains showed that these circuits were driven by distinct tasks. Prefrontal-parietal-cerebellar circuits were more active during cognitive and emotion tasks whilst motor-cerebellar circuits were more active during action execution tasks. These results highlight the separation of prefrontal and motor cortico-cerebellar loops during task performance, and further demonstrate that activity within these circuits relates to distinct functions.
Bidirectional integration between sensory stimuli and contextual framing is fundamental to action control. Stimuli may entail context-dependent actions, while temporal or spatial characteristics of a stimulus train may establish a contextual framework for upcoming stimuli. Here we aimed at identifying core areas for stimulus-context integration and delineated their functional connectivity (FC) using meta-analytic connectivity modeling (MACM) and analysis of resting-state networks. In a multi-study conjunction, consistently increased activity under higher demands on stimulus-context integration was predominantly found in the right temporo-parietal junction (TPJ), which represented the largest cluster of overlap and was thus used as the seed for the FC analyses. The conjunction between task-dependent (MACM) and task-free (resting state) FC of the right TPJ revealed a shared network comprising bilaterally inferior parietal and frontal cortices, anterior insula, premotor cortex, putamen and cerebellum, i.e., a 'ventral' action/attention network. Stronger task-dependent (vs. task-free) connectivity was observed with the pre-SMA, dorsal premotor cortex, intraparietal sulcus, basal ganglia and primary sensori motor cortex, while stronger resting-state (vs. task-dependent) connectivity was found with the dorsolateral prefrontal and medial parietal cortex. Our data provide strong evidence that the right TPJ may represent a key region for the integration of sensory stimuli and contextual frames in action control. Task-dependent associations with regions related to stimulus processing and motor responses indicate that the right TPJ may integrate 'collaterals' of sensory processing and apply (ensuing) contextual frames, most likely via modulation of preparatory loops. Given the pattern of resting-state connectivity, internal states and goal representations may provide the substrates for the contextual integration within the TPJ in the absence of a specific task.
The ability to generate intentional behavior is undeniably at the core of what makes us acting subjects. Intentional actions consist of at least 2 components (Brass M, Haggard P. 2008. The what, when, whether model of intentional action. Neuroscientist. 14:319-325.): choosing an appropriate behavior (what) and selecting the moment of execution (when). The aim of this study was to identify differing and overlapping neural networks underlying the "what" and "when" of intentional movement initiation. While scanned with functional magnetic resonance imaging, 35 healthy subjects performed self-initiated and reactive, that is, internally and externally triggered movements of the right or left index finger in 3 experimental conditions: 1) "Free Choice" (free timing: when/choice of hand: what), 2) "Timed Choice" (external timing/choice of hand: what), and 3) "No Choice" (external timing/cued hand). The what-component specifically employed the presupplementary motor area (SMA) and dorsal premotor cortex bilaterally. The when-network consisted of superior SMA together with insula and Area 44 bilaterally as well as bilateral anterior putamen, globus pallidus, and left cerebellum subcortically. These 2 components recruited different networks, pointing to a partially distinct neuronal realization of the relating functions. Finally, the more intentional components were involved, the higher was activity in the anterior midcingulate cortex, which highlighted its role in intentional initiation of behavior.
Neuroimaging studies have improved our understanding of which brain structures are involved in motor learning. Despite this, questions remain regarding the areas that contribute consistently across paradigms with different task demands. For instance, sensorimotor tasks focus on learning novel movement kinematics and dynamics, while serial response time task (SRTT) variants focus on sequence learning. These differing task demands are likely to elicit quantifiably different patterns of neural activity on top of a potentially consistent core network. The current study identified consistent activations across 70 motor learning experiments using activation likelihood estimation (ALE) meta-analysis. A global analysis of all tasks revealed a bilateral cortical-subcortical network consistently underlying motor learning across tasks. Converging activations were revealed in the dorsal premotor cortex, supplementary motor cortex, primary motor cortex, primary somatosensory cortex, superior parietal lobule, thalamus, putamen and cerebellum. These activations were broadly consistent across task specific analyses that separated sensorimotor tasks and SRTT variants. Contrast analysis indicated that activity in the basal ganglia and cerebellum was significantly stronger for sensorimotor tasks, while activity in cortical structures and the thalamus was significantly stronger for SRTT variants. Additional conjunction analyses then indicated that the left dorsal premotor cortex was activated across all analyses considered, even when controlling for potential motor confounds. The highly consistent activation of the left dorsal premotor cortex suggests it is a critical node in the motor learning network.
Spinocerebellar ataxia type 17 (SCA17) is a rare autosomal dominant neurodegenerative disorder characterized by progressive cerebellar ataxia but also a broad spectrum of other neuropsychiatric signs. As anatomical and structural studies have shown severe cerebellar atrophy in SCA17 and a differentiation of the human cerebellum into an anterior sensorimotor and posterior cognitive/emotional partition has been implicated, we aimed at investigating functional connectivity patterns of two cerebellar clusters of atrophy revealed by a morphometric analysis in SCA17 patients. In particular, voxel-based morphometry (VBM) revealed a large cluster of atrophy in SCA17 in the bilateral anterior cerebellum (lobule V) and another one in the left posterior cerebellum (lobules IX, VIIb, VIIIA, VIIIB). These two cerebellar clusters were used as seeds for functional connectivity analyses using task-based meta-analytic connectivity modeling (MACM) and task-free resting state connectivity analysis. Results demonstrated first consistent functional connectivity throughout the cerebellum itself; the anterior cerebellar seed showed stronger connectivity to lobules V, VI and to some extent I-IV, and the posterior cerebellar seed to the posterior lobules VI-IX. Importantly, the cerebellar anterior seed also showed consistently stronger functional connectivity than the posterior one with pre- and motor areas as well as the primary somatosensory cortex. In turn, task-based task-independent functional connectivity analyses revealed that the cerebellar posterior seed was linked with fronto-temporo-parietal areas as well as partly the insula and the thalamus, i.e., brain regions implicated in cognitive and affective processes. Functional characterization of experiments activating either cerebellar seed further corroborated this notion, revealing mainly motor-related functions for the anterior cluster and predominantly cognitive functions were associated for the posterior one. The differential functional connectivity of the cerebellar anterior and posterior cluster highlights the manifold connections and dichotomy of the human cerebellum, providing additional valuable information about probably disrupted cerebellar-cerebral connections and reflecting the brunt of motor but also the broad spectrum of neuropsychiatric deficits in SCA17.
Sustained responsiveness to external stimulation is fundamental to many time-critical interactions with the outside world. We used functional magnetic resonance imaging during speeded stimulus detection to identify convergent and divergent neural correlates of maintaining the readiness to respond to auditory, tactile, and visual stimuli. In addition, using a multimodal condition, we investigated the effect of making stimulus modality unpredictable. Relative to sensorimotor control tasks, all three unimodal detection tasks elicited stronger activity in the right temporo-parietal junction, inferior frontal cortex, anterior insula, dorsal premotor cortex, and anterior cingulate cortex as well as bilateral mid-cingulum, midbrain, brainstem, and medial cerebellum. The multimodal detection condition additionally activated left dorsal premotor cortex and bilateral precuneus. Modality-specific modulations were confined to respective sensory areas: we found activity increases in relevant, and decreases in irrelevant sensory cortices. Our findings corroborate the modality independence of a predominantly right-lateralized core network for maintaining an alert (i.e., highly responsive) state and extend previous results to the somatosensory modality. Monitoring multiple sensory channels appears to induce additional processing, possibly related to stimulus-driven shifts of intermodal attention. The results further suggest that directing attention to a given sensory modality selectively enhances and suppresses sensory processing-even in simple detection tasks, which do not require inter- or intra-modal selection.
Over the past two decades, several functional neuroimaging experiments demonstrated changes in neural activity in stroke patients with motor deficits. Conclusions from single experiments are usually constrained by small sample sizes and high variability across studies. Here, we used coordinate-based activation likelihood estimation meta-analyses to provide a quantitative synthesis of the current literature on motor-related neural activity after stroke. Of over 1000 PubMed search results through January 2011, 36 studies reported standardized whole-brain group coordinates. Meta-analyses were performed on 54 experimental contrasts for movements of the paretic upper limb (472 patients, 452 activation foci) and on 20 experiments comparing activation between patients and healthy controls (177 patients, 113 activation foci). We computed voxelwise correlations between activation likelihood and motor impairment, time post-stroke, and task difficulty across samples. Patients showed higher activation likelihood in contralesional primary motor cortex (M1), bilateral ventral premotor cortex and supplementary motor area (SMA) relative to healthy subjects. Activity in contralesional areas was more likely found for active than for passive tasks. Better motor performance was associated with greater activation likelihood in ipsilesional M1, pre-SMA, contralesional premotor cortex and cerebellum. Over time post-stroke, activation likelihood in bilateral premotor areas and medial M1 hand knob decreased. This meta-analysis shows that increased activation in contralesional M1 and bilateral premotor areas is a highly consistent finding after stroke despite high inter-study variance resulting from different fMRI tasks and motor impairment levels. However, a good functional outcome relies on the recruitment of the original functional network rather than on contralesional activity.
The startle reflex provides a unique tool for the investigation of sensorimotor gating and information processing. Simultaneous EMG-fMRI acquisition (i.e., online stimulation and recording in the MR environment) allows for the quantitative assessment of the neuronal correlates of the startle reflex and its modulations on a single trial level. This serves as the backbone for a startle response informed fMRI analysis, which is fed by data acquired in the same brain at the same time. We here present the first MR study using a single trial approach with simultaneous acquired EMG and fMRI data on the human startle response in 15 healthy young men. It investigates the neural correlates for isolated air puff startle pulses (PA), prepulse-pulse inhibition (PPI), and prepulse facilitation (PPF). We identified a common core network engaged by all three conditions (PA, PPI, and PPF), consisting of bilateral primary and secondary somatosensory cortices, right insula, right thalamus, right temporal pole, middle cingulate cortex, and cerebellum. The cerebellar vermis exhibits distinct activation patterns between the startle modifications. It is differentially activated with the highest amplitude for PPF, a lower activation for PA, and lowest for PPI. The orbital frontal cortex exhibits a differential activation pattern, not for the type of startle response but for the amplitude modification. For pulse alone it is close to zero; for PPI it is activated. This is in contrast to PPF where it shows deactivation. In addition, the thalamus, the cerebellum, and the anterior cingulate cortex add to the modulation of the startle reflex.
Childhood is a critical period for the development of cognitive planning. There is a lack of knowledge on its neural mechanisms in children. This study aimed to examine cerebello-cortical and cortico-cortical functional connectivity in association with planning skills in 6-year-olds (n = 76). We identified the cerebello-cortical and cortico-cortical functional networks related to cognitive planning using activation likelihood estimation (ALE) meta-analysis on existing functional imaging studies on spatial planning, and data-driven independent component analysis (ICA) of children's resting-state functional MRI (rs-fMRI). We investigated associations of cerebello-cortical and cortico-cortical functional connectivity with planning ability in 6-year-olds, as assessed using the Stockings of Cambridge task. Long-range functional connectivity of two cerebellar networks (lobules VI and lateral VIIa) with the prefrontal and premotor cortex were greater in children with poorer planning ability. In contrast, cortico-cortical association networks were not associated with the performance of planning in children. These results highlighted the key contribution of the lateral cerebello-frontal functional connectivity, but not cortico-cortical association functional connectivity, for planning ability in 6-year-olds. Our results suggested that brain adaptation to the acquisition of planning ability during childhood is partially achieved through the engagement of the cerebello-cortical functional connectivity.