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Virtual dissection of white matter (WM) using diffusion MRI tractography is confounded by its poor reproducibility. Despite the increased adoption of advanced reconstruction models, early region-of-interest driven protocols based on diffusion tensor imaging (DTI) remain the dominant reference for virtual dissection protocols. Here we bridge this gap by providing a comprehensive description of typical WM anatomy reconstructed using a reproducible automated subject-specific parcellation-based approach based on probabilistic constrained-spherical deconvolution (CSD) tractography. We complement this with a WM template in MNI space comprising 68 bundles, including all associated anatomical tract selection labels and associated automated workflows. Additionally, we demonstrate bundle inter- and intra-subject variability using 40 (20 test-retest) datasets from the human connectome project (HCP) and 5 sessions with varying b-values and number of b-shells from the single-subject Multiple Acquisitions for Standardization of Structural Imaging Validation and Evaluation (MASSIVE) dataset. The most reliably reconstructed bundles were the whole pyramidal tracts, primary corticospinal tracts, whole superior longitudinal fasciculi, frontal, parietal and occipital segments of the corpus callosum and middle cerebellar peduncles. More variability was found in less dense bundles, e.g., the fornix, dentato-rubro-thalamic tract (DRTT), and premotor pyramidal tract. Using the DRTT as an example, we show that this variability can be reduced by using a higher number of seeding attempts. Overall inter-session similarity was high for HCP test-retest data (median weighted-dice = 0.963, stdev = 0.201 and IQR = 0.099). Compared to the HCP-template bundles there was a high level of agreement for the HCP test-retest data (median weighted-dice = 0.747, stdev = 0.220 and IQR = 0.277) and for the MASSIVE data (median weighted-dice = 0.767, stdev = 0.255 and IQR = 0.338). In summary, this WM atlas provides an overview of the capabilities and limitations of automated subject-specific probabilistic CSD tractography for mapping white matter fasciculi in healthy adults. It will be most useful in applications requiring a reproducible parcellation-based dissection protocol, and as an educational resource for applied neuroimaging and clinical professionals., Competing Interests: Declaration of Competing Interest Maxime Descoteaux is a founder and co-owner of Imeka Solutions Inc. No conflicts related to the current work., (Copyright © 2022. Published by Elsevier Inc.)

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process., (Copyright © 2021. Published by Elsevier Inc.)

Brain atlases and templates are at the heart of neuroimaging analyses, for which they facilitate multimodal registration, enable group comparisons and provide anatomical reference. However, as atlas-based approaches rely on correspondence mapping between images they perform poorly in the presence of structural pathology. Whilst several strategies exist to overcome this problem, their performance is often dependent on the type, size and homogeneity of any lesions present. We therefore propose a new solution, referred to as Virtual Brain Grafting (VBG), which is a fully-automated, open-source workflow to reliably parcellate magnetic resonance imaging (MRI) datasets in the presence of a broad spectrum of focal brain pathologies, including large, bilateral, intra- and extra-axial, heterogeneous lesions with and without mass effect. The core of the VBG approach is the generation of a lesion-free T1-weighted image, which enables further image processing operations that would otherwise fail. Here we validated our solution based on Freesurfer recon-all parcellation in a group of 10 patients with heterogeneous gliomatous lesions, and a realistic synthetic cohort of glioma patients (n = 100) derived from healthy control data and patient data. We demonstrate that VBG outperforms a non-VBG approach assessed qualitatively by expert neuroradiologists and Mann-Whitney U tests to compare corresponding parcellations (real patients U(6,6) = 33, z = 2.738, P < .010, synthetic-patients U(48,48) = 2076, z = 7.336, P < .001). Results were also quantitatively evaluated by comparing mean dice scores from the synthetic-patients using one-way ANOVA (unilateral VBG = 0.894, bilateral VBG = 0.903, and non-VBG = 0.617, P < .001). Additionally, we used linear regression to show the influence of lesion volume, lesion overlap with, and distance from the Freesurfer volumes of interest, on labeling accuracy. VBG may benefit the neuroimaging community by enabling automated state-of-the-art MRI analyses in clinical populations using methods such as FreeSurfer, CAT12, SPM, Connectome Workbench, as well as structural and functional connectomics. To fully maximize its availability, VBG is provided as open software under a Mozilla 2.0 license (https://github.com/KUL-Radneuron/KUL&#95;VBG)., (Copyright © 2021. Published by Elsevier Inc.)

Establishing the associations between magnetic resonance spectroscopy (MRS)-assessed gamma-aminobutyric acid (GABA) levels and transcranial magnetic stimulation (TMS)-derived 'task-related' modulations in GABA A receptor-mediated inhibition and how these associations change with advancing age is a topic of interest in the field of human neuroscience. In this study, we identified the relationship between GABA levels and task-related modulations in GABA A receptor-mediated inhibition in the dominant (left) and non-dominant (right) sensorimotor (SM) cortices. GABA levels were measured using edited MRS and task-related GABA A receptor-mediated inhibition was measured using a short-interval intracortical inhibition (SICI) TMS protocol during the preparation and premotor period of a choice reaction time (CRT) task in 25 young (aged 18-33 years) and 25 older (aged 60-74 years) adults. Our results demonstrated that GABA levels in both SM voxels were lower in older adults as compared to younger adults; and higher SM GABA levels in the dominant as compared to the non-dominant SM voxel pointed to a lateralization effect, irrespective of age group. Furthermore, older adults showed decreased GABA A receptor-mediated inhibition in the preparation phase of the CRT task within the dominant primary motor cortex (M1), as compared to young adults. Finally, results from an exploratory correlation analysis pointed towards positive relationships between MRS-assessed GABA levels and TMS-derived task-related SICI measures. However, after correction for multiple comparisons none of the correlations remained significant., (Copyright © 2019. Published by Elsevier Inc.)

Aging is associated with gradual alterations in the neurochemical characteristics of the brain, which can be assessed in-vivo with proton-magnetic resonance spectroscopy ( 1 H-MRS). However, the impact of these age-related neurochemical changes on functional motor behavior is still poorly understood. Here, we address this knowledge gap and specifically focus on the neurochemical integrity of the left sensorimotor cortex (SM1) and the occipital lobe (OCC), as both regions are main nodes of the visuomotor network underlying bimanual control. 1 H-MRS data and performance on a set of bimanual tasks were collected from a lifespan (20-75 years) sample of 86 healthy adults. Results indicated that aging was accompanied by decreased levels of N-acetylaspartate (NAA), glutamate-glutamine (Glx), creatine ​+ ​phosphocreatine (Cr) and myo-inositol (mI) in both regions, and decreased Choline (Cho) in the OCC region. Lower NAA and Glx levels in the SM1 and lower NAA levels in the OCC were related to poorer performance on a visuomotor bimanual coordination task, suggesting that NAA could serve as a potential biomarker for the integrity of the motor system supporting bimanual control. In addition, lower NAA, Glx, and mI levels in the SM1 were found to be correlates of poorer dexterous performance on a bimanual dexterity task. These findings highlight the role for 1 H-MRS to study neurochemical correlates of motor performance across the adult lifespan., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Diffusion-weighted imaging (DWI) facilitates probing neural tissue structure non-invasively by measuring its hindrance to water diffusion. Analysis of DWI is typically based on generative signal models for given tissue geometry and microstructural properties. In this work, we generalize multi-tissue spherical deconvolution to a blind source separation problem under convexity and nonnegativity constraints. This spherical factorization approach decomposes multi-shell DWI data, represented in the basis of spherical harmonics, into tissue-specific orientation distribution functions and corresponding response functions, without assuming the latter as known thus fully unsupervised. In healthy human brain data, the resulting components are associated with white matter fibres, grey matter, and cerebrospinal fluid. The factorization results are on par with state-of-the-art supervised methods, as demonstrated also in Monte-Carlo simulations evaluating accuracy and precision of the estimated response functions and orientation distribution functions of each component. In animal data and in the presence of oedema, the proposed factorization is able to recover unseen tissue structure, solely relying on DWI. As such, our method broadens the applicability of spherical deconvolution techniques to exploratory analysis of tissue structure in data where priors are uncertain or hard to define., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Diffusion-weighted imaging and tractography provide a unique, non-invasive technique to study the macroscopic structure and connectivity of brain white matter in vivo. Global tractography methods aim at reconstructing the full-brain fiber configuration that best explains the measured data, based on a generative signal model. In this work, we incorporate a multi-shell multi-tissue model based on spherical convolution, into a global tractography framework, which allows to deal with partial volume effects. The required tissue response functions can be estimated from and hence calibrated to the data. The resulting track reconstruction is quantitatively related to the apparent fiber density in the data. In addition, the fiber orientation distribution for white matter and the volume fractions of gray matter and cerebrospinal fluid are produced as ancillary results. Validation results on simulated data demonstrate that this data-driven approach improves over state-of-the-art streamline and global tracking methods, particularly in the valid connection rate. Results in human brain data correspond to known white matter anatomy and show improved modeling of partial voluming. This work is an important step toward detecting and quantifying white matter changes and connectivity in healthy subjects and patients., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Ever since the introduction of the concept of fiber tractography, methods to generate better and more plausible tractograms have become available. Many modern methods can handle complex fiber architecture and take on a probabilistic approach to account for different sources of uncertainty. The resulting tractogram from any such method typically represents a finite random sample from a complex distribution of possible tracks. Generating a higher amount of tracks allows for a more accurate depiction of the underlying distribution. The recently proposed method of track-density imaging (TDI) allows to capture the spatial distribution of a tractogram. In this work, we propose an extension of TDI towards the 5D spatio-angular domain, which we name track orientation density imaging (TODI). The proposed method aims to capture the full track orientation distribution (TOD). Just as the TDI map, the TOD is amenable to spatial super-resolution (or even sub-resolution), but in addition also to angular super-resolution. Through experiments on in vivo human subject data, an in silico numerical phantom and a challenging tractography phantom, we found that the TOD presents an increased amount of regional spatio-angular consistency, as compared to the fiber orientation distribution (FOD) from constrained spherical deconvolution (CSD). Furthermore, we explain how the amplitude of the TOD of a short-tracks distribution (i.e. where the track length is limited) can be interpreted as a measure of track-like local support (TLS). This in turn motivated us to explore the idea of TOD-based fiber tractography. In such a setting, the short-tracks TOD is able to guide a track along directions that are more likely to correspond to continuous structure over a longer distance. This powerful concept is shown to greatly robustify targeted as well as whole-brain tractography. We conclude that the TOD is a versatile tool that can be cast in many different roles and scenarios in the expanding domain of fiber tractography based methods and their applications., (Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.)

To study the dynamics of contour integration in the human brain, we simultaneously acquired EEG and fMRI data while participants were engaged in a passive viewing task. The stimuli were Gabor arrays with some Gabor elements positioned on the contour of an embedded shape, in three conditions: with local and global structure (perfect contour alignment), with global structure only (orthogonal orientations interrupting the alignment), or without contour. By applying JointICA to the EEG and fMRI responses of the subjects, new insights could be obtained that cannot be derived from unimodal recordings. In particular, only in the global structure condition, an ERP peak around 300ms was identified that involved a loop from LOC to the early visual areas. This component can be interpreted as being related to the verification of the consistency of the different local elements with the globally defined shape, which is necessary when perfect local-to-global alignment is absent. By modifying JointICA, a quantitative comparison of brain regions and the time-course of their interplay were obtained between different conditions. More generally, we provide additional support for the presence of feedback loops from higher areas to lower level sensory regions., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Purpose: Linear least squares estimators are widely used in diffusion MRI for the estimation of diffusion parameters. Although adding proper weights is necessary to increase the precision of these linear estimators, there is no consensus on how to practically define them. In this study, the impact of the commonly used weighting strategies on the accuracy and precision of linear diffusion parameter estimators is evaluated and compared with the nonlinear least squares estimation approach., Methods: Simulation and real data experiments were done to study the performance of the weighted linear least squares estimators with weights defined by (a) the squares of the respective noisy diffusion-weighted signals; and (b) the squares of the predicted signals, which are reconstructed from a previous estimate of the diffusion model parameters., Results: The negative effect of weighting strategy (a) on the accuracy of the estimator was surprisingly high. Multi-step weighting strategies yield better performance and, in some cases, even outperformed the nonlinear least squares estimator., Conclusion: If proper weighting strategies are applied, the weighted linear least squares approach shows high performance characteristics in terms of accuracy/precision and may even be preferred over nonlinear estimation methods., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Since several years, neuroscience research started to focus on multimodal approaches. One such multimodal approach is the combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). However, no standard integration procedure has been established so far. One promising data-driven approach consists of a joint decomposition of event-related potentials (ERPs) and fMRI maps derived from the response to a particular stimulus. Such an algorithm (joint independent component analysis or JointICA) has recently been proposed by Calhoun et al. (2006). This method provides sources with both a fine spatial and temporal resolution, and has shown to provide meaningful results. However, the algorithm's performance has not been fully characterized yet, and no procedure has been proposed to assess the quality of the decomposition. In this paper, we therefore try to answer why and how JointICA works. We show the performance of the algorithm on data obtained in a visual detection task, and compare the performance for EEG recorded simultaneously with fMRI data and for EEG recorded in a separate session (outside the scanner room). We perform several analyses in order to set the necessary conditions that lead to a sound decomposition, and to give additional insights for exploration in future studies. In that respect, we show how the algorithm behaves when different EEG electrodes are used and we test the robustness with respect to the number of subjects in the study. The performance of the algorithm in all the experiments is validated based on results from previous studies., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Diffusion tensor imaging (DTI) is increasingly being used to study white matter (WM) degeneration in patients with psychiatric and neurological disorders. In order to compare diffusion measures across subjects in an automated way, voxel-based analysis (VBA) methods were introduced. In VBA, all DTI data are transformed to a template, after which the diffusion measures of control subjects and patients are compared quantitatively in each voxel. Although VBA has many advantages compared to other post-processing approaches, such as region of interest analysis or tractography, VBA results need to be interpreted cautiously, since it has been demonstrated that they depend on the different parameter settings that are applied in the VBA processing pipeline. In this paper, we examine the effect of the template selection on the VBA results of DTI data. We hypothesized that the choice of template to which all data are transformed would also affect the VBA results. To this end, simulated DTI data sets as well as DTI data from control subjects and multiple sclerosis patients were aligned to (i) a population-specific DTI template, (ii) a subject-based DTI atlas in MNI space, and (iii) the ICBM-81 DTI atlas. Our results suggest that the highest sensitivity and specificity to detect WM abnormalities in a VBA setting was achieved using the population-specific DTI atlas, presumably due to the better spatial image alignment to this template., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Simultaneous EEG-fMRI measurements can combine the high spatial resolution of fMRI with the high temporal resolution of EEG. Therefore, we applied this approach to the study of peripheral vision. More specifically, we presented visual field quadrant fragments of checkerboards and a full central checkerboard in a simple detection task. A technique called "integration-by-prediction" was used to integrate EEG and fMRI data. In particular, we used vectors of single-trial ERP amplitude differences between left and right occipital electrodes as regressors in an ERP-informed fMRI analysis. The amplitude differences for the regressors were measured at the latencies of the visual P1 and N1 components. Our results indicated that the traditional event-related fMRI analysis revealed mostly activations in the vicinity of the primary visual cortex and in the ventral visual stream, while both P1 and N1 regressors revealed activation of areas in the temporo-parietal junction. We conclude that simultaneous EEG-fMRI in a spatial detection task can separate visual processing at 100-200 ms from stimulus onset from the rest of the information processing in the brain., (Copyright © 2010 Elsevier Inc. All rights reserved.)

The large variety of tasks that humans can perform is governed by a small number of key frontal-insular regions that are commonly active during task performance. Little is known about how this network distinguishes different tasks. We report on fMRI data in twelve participants while they performed four cognitive tasks. Of 20 commonly active frontal-insular regions in each hemisphere, five showed a BOLD response increase with increased task demands, regardless of the task. Although active in all tasks, each task invoked a unique response pattern across the voxels in each area that proved reliable in split-half multi-voxel correlation analysis. Consequently, voxels differed in their preference for one or more of the tasks. Voxel-based functional connectivity analyses revealed that same preference voxels distributed across all areas of the network constituted functional sub-networks that characterized the task being executed., (Copyright 2010 Elsevier Inc. All rights reserved.)

Multimodal approaches are of growing interest in the study of neural processes. To this end much attention has been paid to the integration of electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data because of their complementary properties. However, the simultaneous acquisition of both types of data causes serious artifacts in the EEG, with amplitudes that may be much larger than those of EEG signals themselves. The most challenging of these artifacts is the ballistocardiogram (BCG) artifact, caused by pulse-related electrode movements inside the magnetic field. Despite numerous efforts to find a suitable approach to remove this artifact, still a considerable discrepancy exists between current EEG-fMRI studies. This paper attempts to clarify several methodological issues regarding the different approaches with an extensive validation based on event-related potentials (ERPs). More specifically, Optimal Basis Set (OBS) and Independent Component Analysis (ICA) based methods were investigated. Their validation was not only performed with measures known from previous studies on the average ERPs, but most attention was focused on task-related measures, including their use on trial-to-trial information. These more detailed validation criteria enabled us to find a clearer distinction between the most widely used cleaning methods. Both OBS and ICA proved to be able to yield equally good results. However, ICA methods needed more parameter tuning, thereby making OBS more robust and easy to use. Moreover, applying OBS prior to ICA can optimize the data quality even more, but caution is recommended since the effect of the additional ICA step may be strongly subject-dependent., (Copyright 2010 Elsevier Inc. All rights reserved.)

Functional magnetic resonance imaging was used to reveal the shared neural resources between movements performed with effectors of the left versus right body side. Prior to scanning, subjects extensively practiced a complex coordination pattern involving cyclical motions of the ipsilateral hand and foot according to a 90 degrees out-of-phase coordination mode. Brain activity associated with this (nonpreferred) coordination pattern was contrasted with pre-existing isodirectional (preferred) coordination to extract the learning-related brain networks. To identify the principal candidates for effector-independent movement encoding, the conjunction of training-related activity for left and right limb coordination was determined. A dominantly left-lateralized parietal-to-(pre)motor activation network was identified, with activation in inferior and superior parietal cortex extending into intraparietal sulcus and activation in the premotor areas, including inferior frontal gyrus (pars opercularis). Similar areas were previously identified during observation of complex coordination skills by expert performers. These parietal-premotor areas are principal candidates for abstract (effector-independent) movement encoding, promoting motor equivalence, and they form the highest level in the action representation hierarchy., (Copyright (c) 2009 Elsevier Inc. All rights reserved.)

Objective: Aim of present study was to evaluate changes in diffusion tensor imaging (DTI) parameters in the whole brain of 28 patients with amyotrophic lateral sclerosis (ALS) compared to 26 healthy controls., Methods: In both fibertracking and voxel-based analysis, quantitative comparisons of the diffusion parameters between ALS patients and controls were performed. Correlation analyses of diffusion parameters and disease duration and disease severity were performed. A second DTI examination was acquired, allowing the evaluation of the effect of disease progression on the diffusion parameters., Results: Fibertracking analysis revealed that especially the precentral part of the corticospinal tract (CST) was impaired. In the voxel-based analysis, it was shown that changes of diffusion parameters occurred throughout the brain, including frontal, temporal and parietal lobes. Disease severity was inversely correlated with the fractional anisotropy (FA). In the follow-up examination, a further decline of FA over time could be demonstrated in the CST as well as in the whole brain white matter., Interpretation: This study provides support for the view of ALS as being a multisystem degenerative disease, in which abnormalities of extra-motor areas play an important role in the in vivo physiopathology.

Studies of unilateral finger movement in right-handed subjects have shown asymmetrical patterns of activation in primary motor cortex and subcortical regions. In order to investigate the existence of an analogous pattern during lower limb joints movements, functional magnetic resonance imaging (fMRI) was used. Eighteen healthy, right leg dominant volunteers participated in a motor block design study, performing unilateral right and left repetitive knee, ankle and toes flexion/extension movements. Aiming to relate lower limb joints activation to the well-described patterns of finger movement, serial finger-to-thumb opposition was also assessed. All movements were auditory paced at 72 beats/min (1.2 Hz). Brain activation during movement of the nondominant joints was more bilateral than during the same movement performed with the dominant joints. Finger movement had a stronger lateralized pattern of activation in comparison with lower limb joints, implying a different functional specialization. Differences were also evident between the joints of the lower limb. Ankle and toes movements elicited the same extend of MR signal change in the majority of the examined brain regions, whereas knee joint movement was associated with a different pattern. Finally, lateralization index in primary sensorimotor cortex and basal ganglia was significantly affected by the main effect of dominance, whereas the lateralization index in cerebellum was significantly affected by the joint main effect, demonstrating a lateralization index increase from proximal to distal joints.

It is a fundamental insight of neuroscience that the cerebral cortex is divided into spatially separated and functionally distinct areas. In this study, we tried to map a large number of visual areas in individual subjects passively viewing a simple stimulus sequence during functional magnetic resonance imaging (fMRI) at 1.5 T. The blocked stimulus sequence contrasted static object photographs with video takes of movement through natural indoor and outdoor scenes, alternated with a control fixation task. Two runs of the 5-min sequence sufficed to invoke 29 distinguishable activations, 16 (13 bilateral) of which were observed in all 10 participants. At the ventral side, object responsive activations were organized along the lateral occipital-temporal surface and near the collateral and occipital-temporal sulci. The latter activations, corresponding to the lateral occipital complex, showed a different activation profile from those near the collateral sulcus, most likely corresponding to the color constancy areas V4/V8-V4alpha. A potentially new fusiform object area was seen in 6 subjects, even more anterior than the parahippocampal place area. At the dorsal side, consistent activations were mainly related to motion stimuli and included the well-known areas V3a, VIPS, POIPS, hV5+, STS and the cingulate sulcus. There was consistent activation in the parietal-occipital sulcus, containing the areas V6a and V6. In addition, all subjects showed activation in the superior-anterior precuneus. Thus, the short stimulus sequence robustly invoked multiple visual areas and can be used to map the organization of the visual system in normal and brain-damaged individuals.

Somatosensory discrimination of unseen objects relies on processing of proprioceptive and tactile information to detect spatial features, such as shape or length, as acquired by exploratory finger movements. This ability can be impaired after stroke, because of somatosensory-motor deficits. Passive somatosensory discrimination tasks are therefore used in therapy to improve motor function. Whereas the neural correlates of active discrimination have been addressed repeatedly, little is known about the neural networks activated during passive discrimination of somatosensory information. In the present study, we applied functional magnetic resonance imaging (fMRI) while the right index finger of ten healthy subjects was passively moved along various shapes and lengths by an fMRI compatible robot. Comparing discriminating versus non-discriminating passive movements, we identified a bilateral parieto-frontal network, including the precuneus, superior parietal gyrus, rostral intraparietal sulcus, and supramarginal gyrus as well as the supplementary motor area (SMA), dorsal premotor (PMd), and ventral premotor (PMv) areas. Additionally, we compared the discrimination of different spatial features, i.e., discrimination of length versus familiar (rectangles or triangles) and unfamiliar geometric shapes (arbitrary quadrilaterals). Length discrimination activated mainly medially located superior parietal and PMd circuits whereas discrimination of familiar geometric shapes activated more laterally located inferior parietal and PMv regions. These differential parieto-frontal circuits provide new insights into the neural basis of extracting spatial features from somatosensory input and suggest that different passive discrimination tasks could be used for lesion-specific training following stroke.

In the present functional magnetic resonance imaging (fMRI) study, we assessed the neural network governing bimanual coordination during manipulations of spatiotemporal complexity and cycling frequency. A parametric analysis was applied to determine the effects of each of both factors as well as their interaction. Subjects performed four different cyclical movement tasks of increasing spatiotemporal complexity (i.e., unimanual left-right hand movements, bimanual in-phase movements, bimanual anti-phase movements, and bimanual 90 degrees out-of-phase movements) across four frequency levels (0.9, 1.2, 1.5, and 1.8 Hz). Results showed that, within the network involved in bimanual coordination, functional subcircuits could be distinguished: Activation in the supplementary motor area, superior parietal cortex (SPS), and thalamic VPL Nc was mainly correlated with increasing spatiotemporal complexity of the limb movements, suggesting that these areas are involved in higher-order movement control. By contrast, activation within the primary motor cortex, cingulate motor cortex (CMC), globus pallidus, and thalamic VLo Nc correlated mainly with movement frequency, indicating that these areas play an important role during movement execution. Interestingly, the cerebellum and the dorsal premotor cortex were identified as the principal regions responding to manipulation of both parameters and exhibiting clear interaction effects. Therefore, it is concluded that both areas represent critical sites for the control of bimanual coordination.

We investigated the contribution of the human cerebellum to cerebral function during visual discrimination using PET and fMRI. The cognitive task was a successive discrimination of shades of brown with a parametric variation of the stimulus presentation rate and a constant task difficulty. The successive color discrimination task was contrasted to a dimming detection control task, with identical retinal input but with double the number of motor responses. Three sets of activated cerebellar and cerebral regions were observed: rate-dependent and rate-independent color discrimination networks and a motor-and-detection network. The rate-dependent color discrimination network included both an anterior and a posterior activation site in lobule-VI of the two lateral cerebellar hemispheres, whereas the rate-independent network involved a bilateral activation site in lateral Crus-I. Cerebellar sites of the motor-and-detection network were located in medial lobule-V bilaterally, in the vermis, and in posterior left Crus-I and right Crus-II. An additional fMRI study was performed to control for differences in motor output and response timing between the tasks. In this control study, the cerebellar activation sites of the rate-dependent and rate-independent color discrimination networks remained unaltered. The motor-and-detection network included cerebellar activations in posterior left Crus-I and right Crus-II, but none in lobule-V or the vermis. Thus, cerebellar activation sites of the motor-and-detection network could be subdivided into those related to a motor network and those belonging to a dimming detection network. We conclude that successive color discrimination activates multiple, functionally distinct cerebellar regions.

It is commonly agreed that a functional dissociation with respect to the internal vs external control of movements exists for several brain regions. This has, however, only been tested in relation to the timing and preparation of motor responses, but not to ongoing movement control. Using functional magnetic resonance imaging (fMRI), the present study addressed the neuroanatomical substrate of the internal-external control hypothesis by comparing regional brain activation for cyclical bimanual movements performed in the presence or absence of augmented visual feedback. Subjects performed a bimanual movement pattern, either with the help of on-line visual feedback of the movements (externally guided coordination) or with the eyes closed on the basis of an internal representation of the movement pattern (internally generated coordination). Visual control and baseline rest conditions were also added. Results showed a clear functional dissociation within the network involved in movement coordination. The hMT/V5+, the superior parietal cortex, the premotor cortex, the thalamus, and cerebellar lobule VI showed higher activation levels when movements were guided by visual feedback. Conversely, the basal ganglia, the supplementary motor area, cingulate motor cortex, the inferior parietal, frontal operculum, and cerebellar lobule IV-V/dentate nucleus showed higher involvement when movements were internally generated. Consequently, the present findings suggest the existence of distinct cortico-cortical and subcortico-cortical neural pathways for externally (augmented feedback) and internally guided cyclical bimanual movements. This provides a neurophysiological account for the beneficial effect of providing augmented visual feedback to optimize movements in normal and motor disordered patients.

Whereas behavioral studies have made significant contributions toward the identification of the principles governing the coordination of limb movements, little is known about the role of higher brain areas that are involved in interlimb coordination. Functional magnetic resonance imaging (fMRI) was used to reveal the brain areas activated during the cyclical coordination of ipsilateral wrist and foot movements. Six normal subjects performed five different tasks that were presented in a random order, i.e., isolated flexion-extension movements of the right wrist (WRIST) and right foot (FOOT), cyclical coordination of wrist and foot according to the isodirectional (ISODIR) and nonisodirectional (NON-ISODIR) mode, and rest (REST). All movements were auditory paced at 66 beats/min. During the coordination of both limb segments, a distributed network was identified showing activation levels in the supplementary motor area (SMA), cingulate motor cortex (CMC), premotor cortex (PMC), primary sensorimotor cortex (M1/S1), and cerebellum that exceeded the sum of the activations observed during the isolated limb movements. In addition, coordination of the limb movements in different directions was associated with extra activation of the SMA as compared to movements in the same direction. It is therefore concluded that the SMA is substantially involved in the coordination of the nonhomologous limbs as part of a distributed motor network. Accordingly, the long-standing exclusive association that has been made between this medial frontal area and bimanual (homologous) coordination needs to be abandoned and extended towards other forms of interlimb coordination (nonhomologous)., (Copyright 2001 Academic Press.)

To investigate the role of human fusiform gyrus in shape processing, we determined the effect of shape degradation on BOLD contrast in this region with fMRI during three tasks requiring subjects to determine either whether two successively presented nonsense shapes had the same global orientation (OR task); whether two successively presented meaningful objects belonged to the same basic level category (CAT task); or whether two successively presented objects represented the same exemplar of a category (EX task). On the behavioral level, shape degradation by locally shifting the pixels constituting the lines of stimuli had no effect on performance in the OR task, while it was detrimental to performance in the CAT and EX tasks. In comparison to the OR task, both the CAT and EX tasks were associated with activations in the occipitotemporal and parietal cortex. When shape degradation was applied, activation in the middle fusiform gyrus was reduced in all tasks. The occurrence of this effect in the OR task indicates that it is independent of memory representations. The persistence of the effect in both tasks that showed a behavioral effect of degradation suggests that it does not reflect the amount of shape processing performed on the stimuli, but rather the specificity of the final perceptual representation that can be built from the shape information that is available. Other studies have shown effects of stimulus familiarity and task requirements in the fusiform gyrus, suggesting that there is no need to assume different modules for perceptual representation and representation in memory., (Copyright 2000 Academic Press.)

We studied the functional neuroanatomy of attention to speed of motion using functional magnetic resonance imaging in eight healthy subjects, who performed a speed discrimination (SID) task using a random textured pattern moving at a reference speed of 6 deg/s. During the control condition (DIM), with retinal stimulation identical to that during SID, subjects detected the dimming of the central fixation point. Attention to speed (SID compared to DIM) activated mainly ventral V3 and V4, dorsal V3 and V3A. Compared to a fixation control condition, speed discrimination recruited a large visuomotor network, including hMT/V5+. However, hMT/V5+ was only marginally more active during speed discrimination than during dimming detection. Thus hMT/V5+ is involved in speed discrimination, in line with the speed discrimination impairments following hMT/V5+ lesions, but our results suggest that this activity simply reflects the processing of motion rather than attention to speed. Manipulating the difficulty of the speed discrimination task over a large range of the psychometric curve revealed that increasing difficulty linearly increases activity in right frontal regions, as well as in lateral occipital and dorsal parietal regions. A weak effect of difficulty was also observed in dorsal V3., (Copyright 2000 Academic Press.)

Brain activation patterns associated with three motor tasks, differing in the mode of movement selection, were studied in seven right-handed subjects, using functional magnetic resonance imaging (fMRI). The tasks consisted of sequences of finger movements in which the next finger was selected (i) according to a fixed sequence (FIX), (ii) in response to an external sensory cue (RAND), or (iii) on the basis of free, internal selection (SELF). Periods of hand relaxation (REST) alternating with the tasks served as a control. Functional maps resulting from comparison of the motor tasks with REST reveal activation in primary sensorimotor cortex, medial and lateral premotor areas, cingulate cortex, and parietal cortex. The task activation level, defined as the percentage MR signal increase for each task relative to REST, and the differential activation, defined as the percentage MR signal increase for RAND and SELF relative to FIX, were calculated in each area. All areas showed a higher activation level for RAND and SELF than for FIX. A significant difference in activation level or differential activation between SELF and RAND was found in the posterior part of the superior frontal sulcus, in a part of the premotor cortex on the lateral brain surface, in the anterior cingulate motor cortex, and in the posterior part of the superior parietal cortex. The high-resolution and single-subject approach, provided by fMRI, allowed the distinguishing of multiple foci in medial frontal areas, premotor cortex, and parietal cortex, reflecting the functional heterogeneity of these areas suggested by previous studies., (Copyright 1997 Academic Press.)