Anatomical congruence of metabolic and electromagnetic activation signals during a self-paced motor task: a combined PET-MEG study

Beta oscillation is an indicator for two patterns of sensorimotor synchronization

Previous study indicates that there are two distinct behavioral patterns in the sensory-motor synchronization task with short stimulus onset asynchrony (SOA; 2-3 s) or long SOA (beyond 4 s). However, the underlying neural indicators and mechanisms have not been elucidated. The present study applied magnetoencephalography (MEG) technology to examine the functional role of several oscillations (beta, gamma, and mu) in sensorimotor synchronization with different SOAs to identify a reliable neural indicator. During MEG recording, participants underwent a listening task without motor response, a sound-motor synchronization task, and a motor-only continuation task. These tasks were used to explore whether and how the activity of oscillations changes across different behavioral patterns with different tempos. Results showed that during both the listening and the synchronization task, the beta oscillation changes with the tempo. Moreover, the event-related synchronization of beta oscillations was significantly correlated with motor timing during synchronization. In contrast, mu activity only changes with the tempo in the synchronization task, while the gamma activity remains unchanged. In summary, the current study indicates that beta oscillation could be an indicator of behavioral patterns between fast tempo and slow tempo in sensorimotor synchronization. Also, it is likely to be the potential mechanism of maintaining rhythmic continuous movements with short SOA, which is embedded within the 3 s time window.

Rhythmic motor behavior explains individual differences in grammar skills in adults

A growing body of literature has reported the relationship between music and language, particularly between individual differences in perceptual rhythm skill and grammar competency in children. Here, we investigated whether motoric aspects of rhythm processing-as measured by rhythmic finger tapping tasks-also explain the rhythm-grammar connection in 150 healthy young adults. We found that all expressive rhythm skills (spontaneous, synchronized, and continued tapping) along with rhythm discrimination skill significantly predicted receptive grammar skills on either auditory sentence comprehension or grammaticality well-formedness judgment (e.g., singular/plural, past/present), even after controlling for verbal working memory and music experience. Among these, synchronized tapping and rhythm discrimination explained unique variance of sentence comprehension and grammaticality judgment, respectively, indicating differential associations between different rhythm and grammar skills. Together, we demonstrate that even simple and repetitive motor behavior can account for seemingly high-order grammar skills in the adult population, suggesting that the sensorimotor system continue to support syntactic operations.

The neural basis of audiomotor entrainment: an ALE meta-analysis

Synchronization of body movement to an acoustic rhythm is a major form of entrainment, such as occurs in dance. This is exemplified in experimental studies of finger tapping. Entrainment to a beat is contrasted with movement that is internally driven and is therefore self-paced. In order to examine brain areas important for entrainment to an acoustic beat, we meta-analyzed the functional neuroimaging literature on finger tapping (43 studies) using activation likelihood estimation (ALE) meta-analysis with a focus on the contrast between externally-paced and self-paced tapping. The results demonstrated a dissociation between two subcortical systems involved in timing, namely the cerebellum and the basal ganglia. Externally-paced tapping highlighted the importance of the spinocerebellum, most especially the vermis, which was not activated at all by self-paced tapping. In contrast, the basal ganglia, including the putamen and globus pallidus, were active during both types of tapping, but preferentially during self-paced tapping. These results suggest a central role for the spinocerebellum in audiomotor entrainment. We conclude with a theoretical discussion about the various forms of entrainment in humans and other animals.

Remember the future II: meta-analyses and functional overlap of working memory and delay discounting

Previously we showed that working memory training decreased the discounting of future rewards in stimulant addicts without affecting a go/no-go task. While a relationship between delay discounting and working memory is consistent with other studies, the unique brain regions of plausible causality between these two abilities have yet to be determined. Activation likelihood estimation meta-analyses were performed on foci from studies of delay discounting (DD = 449), working memory (WM = 452), finger tapping (finger tapping = 450), and response inhibition (RI = 450). Activity maps from relatively less (finger tapping) and more (RI) demanding executive tasks were contrasted with maps of DD and WM. Overlap analysis identified unique functional coincidence between DD and WM. The anterior cingulate cortex was engaged by all tasks. Finger tapping largely engaged motor-related brain areas. In addition to motor-related areas, RI engaged frontal brain regions. The right lateral prefrontal cortex was engaged by RI, DD, and WM and was contrasted out of overlap maps. A functional cluster in the posterior portion of the left lateral prefrontal cortex emerged as the largest location of unique overlap between DD and WM. A portion of the left lateral prefrontal cortex is a unique location where delay discounting and working memory processes overlap in the brain. This area, therefore, represents a therapeutic target for improving behaviors that rely on the integration of the recent past with the foreseeable future.

In vivo assessment of human brain oscillations during application of transcranial electric currents

Brain oscillations reflect pattern formation of cell assemblies’ activity, which is often disturbed in neurological and psychiatric diseases like depression, schizophrenia and stroke. In the neurobiological analysis and treatment of these conditions, transcranial electric currents applied to the brain proved beneficial. However, the direct effects of these currents on brain oscillations have remained an enigma because of the inability to record them simultaneously. Here we report a novel strategy that resolves this problem. We describe accurate reconstructed localization of dipolar sources and changes of brain oscillatory activity associated with motor actions in primary cortical brain regions undergoing transcranial electric stimulation. This new method allows for the first time direct measurement of the effects of non-invasive electrical brain stimulation on brain oscillatory activity and behavior.

Sulcal depth-position profile is a genetically mediated neuroscientific trait: description and characterization in the central sulcus

Genetic and environmental influences on brain morphology were assessed in an extended-pedigree design by extracting depth-position profiles (DPP) of the central sulcus (CS). T1-weighted magnetic resonance images were used to measure CS length and depth in 467 human subjects from 35 extended families. Three primary forms of DPPs were observed. The most prevalent form, present in 70% of subjects, was bimodal, with peaks near hand and mouth regions. Trimodal and unimodal configurations accounted for 15 and 8%, respectively. Genetic control accounted for 56 and 66% of between-subject variance in average CS depth and length, respectively, and was not significantly influenced by environmental factors. Genetic control over CS depth ranged from 1 to 50% across the DPP. Areas of peak heritability occurred at locations corresponding to hand and mouth areas. Left and right analogous CS depth measurements were strongly pleiotropic. Shared genetic influence lessened as the distance between depth measurements was increased. We argue that DPPs are powerful phenotypes that should inform genetic influence of more complex brain regions and contribute to gene discovery efforts.

Reduced representations of heterogeneous mixed neural networks with synaptic coupling

In the human brain, large-scale neural networks are considered to instantiate the integrative mechanisms underlying higher cognitive, motor, and sensory functions. Computational models of such large-scale networks typically lump thousands of neurons into a functional unit, which serves as the "atom" for the network integration. These atoms display a low dimensional dynamics corresponding to the only type of behavior available for the neurons within the unit, namely, the synchronized regime. Other dynamical features are not part of the unit's repertoire. With this limitation in mind, here we have studied the dynamical behavior of a neural network comprising "all-to-all" synaptically connected excitatory and inhibitory nonidentical neurons. We found that the network exhibits various dynamical characteristics, synchronization being only a particular case. Then we construct a low-dimensional representation of the network dynamics, and we show that this reduced system captures well the main dynamical features of the entire population. Our approach provides an alternate model for a neurocomputational unit of a large-scale network that can account for rich dynamical features of the network at low computational costs.

Neural population modes capture biologically realistic large scale network dynamics

Large scale brain networks are understood nowadays to underlie the emergence of cognitive functions, though the detailed mechanisms are hitherto unknown. The challenges in the study of large scale brain networks are amongst others their high dimensionality requiring significant computational efforts, the complex connectivity across brain areas and the associated transmission delays, as well as the stochastic nature of neuronal processes. To decrease the computational effort, neurons are clustered into neural masses, which then are approximated by reduced descriptions of population dynamics. Here, we implement a neural population mode approach (Assisi et al. in Phys. Rev. Lett. 94(1):018106, 2005; Stefanescu and Jirsa in PLoS Comput. Biol. 4(11):e1000219, 2008), which parsimoniously captures various types of population behavior. We numerically demonstrate that the reduced population mode system favorably captures the high-dimensional dynamics of neuron networks with an architecture involving homogeneous local connectivity and a large-scale, fiber-like connection with time delay.

Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: a random-effects approach based on empirical estimates of spatial uncertainty

A widely used technique for coordinate-based meta-analyses of neuroimaging data is activation likelihood estimation (ALE). ALE assesses the overlap between foci based on modeling them as probability distributions centered at the respective coordinates. In this Human Brain Project/Neuroinformatics research, the authors present a revised ALE algorithm addressing drawbacks associated with former implementations. The first change pertains to the size of the probability distributions, which had to be specified by the used. To provide a more principled solution, the authors analyzed fMRI data of 21 subjects, each normalized into MNI space using nine different approaches. This analysis provided quantitative estimates of between-subject and between-template variability for 16 functionally defined regions, which were then used to explicitly model the spatial uncertainty associated with each reported coordinate. Secondly, instead of testing for an above-chance clustering between foci, the revised algorithm assesses above-chance clustering between experiments. The spatial relationship between foci in a given experiment is now assumed to be fixed and ALE results are assessed against a null-distribution of random spatial association between experiments. Critically, this modification entails a change from fixed- to random-effects inference in ALE analysis allowing generalization of the results to the entire population of studies analyzed. By comparative analysis of real and simulated data, the authors showed that the revised ALE-algorithm overcomes conceptual problems of former meta-analyses and increases the specificity of the ensuing results without loosing the sensitivity of the original approach. It may thus provide a methodologically improved tool for coordinate-based meta-analyses on functional imaging data.

Mutual-information-based approach for neural connectivity during self-paced finger lifting task

Frequency-dependent modulation between neuronal assemblies may provide insightful mechanisms of functional organization in the context of neural connectivity. We present a conjoined time-frequency cross mutual information (TFCMI) method to explore the subtle brain neural connectivity by magnetoencephalography (MEG) during a self-paced finger lifting task. Surface electromyogram (sEMG) was obtained from the extensor digitorum communis. Both within-modality (MEG-MEG) and between-modality studies (sEMG-MEG) were conducted. The TFCMI method measures both the linear and nonlinear dependencies of the temporal dynamics of signal power within a pre-specified frequency band. Each single trial of MEG across channels and sEMG signals was transformed into time-frequency domain with use of the Morlet wavelet to obtain better temporal spectral (power) information. As compared to coherence approach (linear dependency only) in broadband analysis, the TFCMI method demonstrated advantages in encompassing detection for the mesial frontocentral cortex and bilateral primary sensorimotor areas, clear demarcation of event- and non-event-related regions, and robustness for sEMG - MEG between-modality study, i.e., corticomuscular communication. We conclude that this novel TFCMI method promises a possibility to better unravel the intricate functional organizations of brain in the context of oscillation-coded communication.

Functional neuroimaging correlates of finger-tapping task variations: an ALE meta-analysis

Finger-tapping tasks are one of the most common paradigms used to study the human motor system in functional neuroimaging studies. These tasks can vary both in the presence or absence of a pacing stimulus as well as in the complexity of the tapping task. A voxel-wise, coordinate-based meta-analysis was performed on 685 sets of activation foci in Talairach space gathered from 38 published studies employing finger-tapping tasks. Clusters of concordance were identified within the primary sensorimotor cortices, supplementary motor area, premotor cortex, inferior parietal cortices, basal ganglia, and anterior cerebellum. Subsequent analyses performed on subsets of the primary set of foci demonstrated that the use of a pacing stimulus resulted in a larger, more diverse network of concordance clusters, in comparison to varying the complexity of the tapping task. The majority of the additional concordance clusters occurred in regions involved in the temporal aspects of the tapping task, rather than its execution. Tapping tasks employing a visual pacing stimulus recruited a set of nodes distinct from the results observed in those tasks employing either an auditory or no pacing stimulus, suggesting differing cognitive networks when integrating visual or auditory pacing stimuli into simple motor tasks. The relatively uniform network of concordance clusters observed across the more complex finger-tapping tasks suggests that further complexity, beyond the use of multi-finger sequences or bimanual tasks, may be required to fully reveal those brain regions necessary to execute truly complex movements.

Modeling motor connectivity using TMS/PET and structural equation modeling

Structural equation modeling (SEM) was applied to positron emission tomographic (PET) images acquired during transcranial magnetic stimulation (TMS) of the primary motor cortex (M1(hand)). TMS was applied across a range of intensities, and responses both at the stimulation site and remotely connected brain regions covaried with stimulus intensity. Regions of interest (ROIs) were identified through an activation likelihood estimation (ALE) meta-analysis of TMS studies. That these ROIs represented the network engaged by motor planning and execution was confirmed by an ALE meta-analysis of finger movement studies. Rather than postulate connections in the form of an a priori model (confirmatory approach), effective connectivity models were developed using a model-generating strategy based on improving tentatively specified models. This strategy exploited the experimentally imposed causal relations: (1) that response variations were caused by stimulation variations, (2) that stimulation was unidirectionally applied to the M1(hand) region, and (3) that remote effects must be caused, either directly or indirectly, by the M1(hand) excitation. The path model thus derived exhibited an exceptional level of goodness (chi(2)=22.150, df=38, P=0.981, TLI=1.0). The regions and connections derived were in good agreement with the known anatomy of the human and primate motor system. The model-generating SEM strategy thus proved highly effective and successfully identified a complex set of causal relationships of motor connectivity.

Temporal information processing in ADHD: Findings to date and new methods

The ability to perceive and represent time is a fundamental but complex cognitive skill that allows us to perceive and organize sequences of events and actions, and to anticipate or predict when future events will occur. It is a multidimensional construct, and a variety of methods have been used to understand timing performance in ADHD samples, which makes it difficult to integrate findings across studies. While further replication is needed, growing evidence links ADHD to problems in several aspects of temporal information processing, including duration discrimination, duration reproduction, and finger tapping. Neuroimaging studies of ADHD have also implicated cerebellar, basal ganglia, and prefrontal regions of the brain, which are believed to subserve temporal information processing. This line of research implicates more basic cognitive mechanisms than previously linked with ADHD and challenges researchers to develop and utilize innovative, multidisciplinary, scientific methods to dissect the various components of temporal information processing. Recent advances in neuroimaging, such as magnetoencephalography in collaboration with structural magnetic resonance imaging, can discriminate temporal processing at the level of a millisecond. This approach can lay the groundwork to provide a more precise understanding of neural network activity during different aspects and stages of temporal information processing in ADHD.

Functional-anatomical validation and individual variation of diffusion tractography-based segmentation of the human thalamus

Parcellation of the human thalamus based on cortical connectivity information inferred from non-invasive diffusion-weighted images identifies sub-regions that we have proposed correspond to nuclei. Here we test the functional and anatomical validity of this proposal by comparing data from diffusion tractography, cytoarchitecture and functional imaging. We acquired diffusion imaging data in eleven healthy subjects and performed probabilistic tractography from voxels within the thalamus. Cortical connectivity information was used to divide the thalamus into sub-regions with highest probability of connectivity to distinct cortical areas. The relative volumes of these connectivity-defined sub-regions correlate well with volumetric predictions based on a histological atlas. Previously reported centres of functional activation within the thalamus during motor or executive tasks co-localize within atlas regions showing high probabilities of connection to motor or prefrontal cortices, respectively. This work provides a powerful validation of quantitative grey matter segmentation using diffusion tractography in humans. Co-registering thalamic sub-regions from 11 healthy individuals characterizes inter-individual variation in segmentation and results in a population-based atlas of the human thalamus that can be used to assign likely anatomical labels to thalamic locations in standard brain space. This provides a tool for specific localization of functional activations or lesions to putative thalamic nuclei.

Noninvasive identification of human central sulcus: a comparison of gyral morphology, functional MRI, dipole localization, and direct cortical mapping

The locations of the human primary hand cortical somatosensory and motor areas were estimated using structural and functional MRI, scalp-recorded somatosensory-evoked potential dipole localization, expert judgments based on cortical anatomy, and direct cortical stimulation and recording studies. The within-subject reliability of localization (across 3 separate days) was studied for eight normal subjects. Intraoperative validation was obtained from five neurosurgical patients. The mean discrepancy between the different noninvasive functional imaging methods ranged from 6 to 26 mm. Quantitative comparison of the noninvasive methods with direct intraoperative stimulation and recording studies did not reveal a significant mean difference in accuracy. However, the expert judgments of the location of the sensory hand areas were significantly more variable (maximum error, 39 mm) than the dipole or functional MRI techniques. It is concluded that because expert judgments are less reliable for identifying the cortical hand area, consideration of the findings of noninvasive functional MRI and dipole localization studies is desirable for preoperative surgical planning.

Cortical neuromagnetic fields evoked by voluntary and passive hand movements in healthy adults

Neuromagnetic fields were recorded from the left cerebral hemisphere of six healthy right-handed subjects under three different conditions: (1) externally triggered rapid voluntary extension and flexion of the right hand, (2) passive extension and flexion of the right hand, and (3) stimulation of the skin of the right index finger by means of air pressure. Location analysis using the current density analysis did not reveal any differences between motor evoked field I (MEF I) in active and passive movements, and met the maximum of cerebral activation in the contralateral precentral region. In contrast, the sensory evoked field was located clearly in the contralateral postcentral region. Additionally, a significantly shorter latency of MEF I (with respect to movement onset) was observed in flexion compared with extension in both passive and active movements. These results support the assumption that MEF I is generated by cortical activation resulting from proprioceptive, probably muscle spindle, input. The current density analysis has proved to be an appropriate method for investigating movement-related fields. Furthermore, the described method seems to be appropriate for evaluating the processes of cortical reorganization and the influence of neurorehabilitation within longitudinal studies in patients with lesions in motor centers of the brain.

Early onset of post-movement beta electroencephalogram synchronization in the supplementary motor area during self-paced finger movement in man

A voluntary finger movement is accompanied by an event-related desynchronization followed by a short burst of beta oscillations or event-related synchronization. These beta bursts are dominant over the contralateral hand representation area, but also appear over the midcentral area overlaying the supplementary motor area (SMA) and the foot representation area. We show that the induced midcentral beta oscillations following movement-offset display not only slightly higher frequency components, but have also a significantly earlier onset. These beta oscillations arise likely from the SMA. Assuming that the short-lasting beta synchronizations at frequencies below 35 Hz after termination of a movement reflect a state of localized cortical inhibition, we propose that the induced midcentral oscillations reflect the inhibition of networks within the SMA. This assumed resetting or inhibitory process within the SMA precedes that of the networks within the primary motor hand area.

GABA-ergic modulation of prefrontal spatio-temporal activation pattern during emotional processing: a combined fMRI/MEG study with placebo and lorazepam

Various prefrontal cortical regions have been shown to be activated during emotional stimulation, whereas neurochemical mechanisms underlying emotional processing in the prefrontal cortex remain unclear. We therefore investigated the influence of the GABA-A potentiator lorazepam on prefrontal cortical emotional-motor spatio-temporal activation pattern in a combined functional magnetic resonance imaging/magnetoencephalography study. Lorazepam led to the reversal in orbito-frontal activation pattern, a shift of the early magnetic field dipole from the orbito-frontal to medial prefrontal cortex, and alterations in premotor/motor cortical function during negative and positive emotional stimulation. It is concluded that negative emotional processing in the orbito-frontal cortex may be modulated either directly or indirectly by GABA-A receptors. Such a modulation of orbito-frontal cortical emotional function by lorazepam has to be distinguished from its effects on cortical motor function as being independent from the kind of processing either emotional or nonemotional.

New approach to localize speech relevant brain areas and hemispheric dominance using spatially filtered magnetoencephalography

We used a current localization by spatial filtering-technique to determine primary language areas with magnetoencephalography (MEG) using a silent reading and a silent naming task. In all cases we could localize the sensory speech area (Wernicke) in the posterior part of the left superior temporal gyrus (Brodmann area 22) and the motor speech area (Broca) in the left inferior frontal gyrus (Brodmann area 44). Left hemispheric speech dominance was determined in all cases by a laterality index comparing the current source strength of the activated left side speech areas to their right side homologous. In 12 cases we found early Wernicke and later Broca activation corresponding to the Wernicke-Geschwind model. In three cases, however, we also found early Broca activation indicating that speech-related brain areas need not necessarily be activated sequentially but can also be activated simultaneously. Magnetoencephalography can be a potent tool for functional mapping of speech-related brain areas in individuals, investigating the time-course of brain activation, and identifying the speech dominant hemisphere. This may have implications for presurgical planning in epilepsy and brain tumor patients.

Statistical probability mapping reveals high-frequency magnetoencephalographic activity in supplementary motor area during self-paced finger movements

Investigations of both haemodynamic and electroencephalographic measures of brain activity have demonstrated supplementary motor area (SMA) involvement in self-paced finger movements. In contrast, analysis of magnetoencephalographic (MEG) signals in the time domain has usually failed to detect SMA activity in healthy individuals. We investigated oscillatory MEG activity in 12 normal adults during (a) a self-paced, complex sequence of finger movements and (b) a simple finger opposition task paced externally by tactile stimuli presented to the contralateral thumb. Statistical probability mapping revealed enhanced non-phase-locked spectral amplitudes in the 22-28 Hz range over bilateral frontal cortex during self-paced as compared to externally cued finger movements. This activity may reflect recruitment of cell assemblies in SMA during self-paced, complex movements.

FMRI and PET of self-paced finger movement: comparison of intersubject stereotaxic averaged data

We compared the intersubject-averaged functional anatomy of self-paced right index finger movement as revealed by (15)O water positron emission tomography (PET) and blood oxygen level-dependent functional magnetic resonance imaging (FMRI) at 1.5 T. Image data sets were acquired with both techniques on a group of eight subjects, spatially normalized in the stereotaxic space and subsequently processed in order to get identical smoothness and degrees of freedom. Intersubject-averaged PET and FMRI activation maps were found congruent in the left primary sensorimotor area (PSM), bilateral supplementary motor area, bilateral supra marginalis gyri, left operculum, left inferior parietal lobule, right middle frontal gyrus, and right cerebellum. In those regions the mean distance between PET and FMRI local maxima was 7.4 mm. FMRI detected additional activations in the right precentral gyrus, right rolandic operculum, right inferior parietal lobule, and bilateral insula, whereas PET demonstrated a higher detection sensitivity at the deep nuclei level. PET and FMRI percentage signal variations were found linearly related by a factor around 10, both within the PSM and across a set of distributed local extrema. However, in most cases, FMRI was more sensitive than PET, as assessed by t values. Finally the pattern of deactivations was markedly dissimilar between the two techniques, possibly due to differences in the "Rest" control task.