TVB-EduPack: An interactive learning and scripting platform for The Virtual Brain

The Virtual Brain (TVB; thevirtualbrain.org) is a neuroinformatics platform for full brain network simulation based on individual anatomical connectivity data. The framework addresses clinical and neuroscientific questions by simulating multi-scale neural dynamics that range from local population activity to large-scale brain function and related macroscopic signals like electroencephalography and functional magnetic resonance imaging. TVB is equipped with a graphical and a command-line interface to create models that capture the characteristic biological variability to predict the brain activity of individual subjects. To enable researchers from various backgrounds a quick start into TVB and brain network modeling in general, we developed an educational module: TVB-EduPack. EduPack offers two educational functionalities that seamlessly integrate into TVB's graphical user interface (GUI): (i) interactive tutorials introduce GUI elements, guide through the basic mechanics of software usage and develop complex use-case scenarios; animations, videos and textual descriptions transport essential principles of computational neuroscience and brain modeling; (ii) an automatic script generator records model parameters and produces input files for TVB's Python programming interface; thereby, simulation configurations can be exported as scripts that allow flexible customization of the modeling process and self-defined batch- and post-processing applications while benefitting from the full power of the Python language and its toolboxes. This article covers the implementation of TVB-EduPack and its integration into TVB architecture. Like TVB, EduPack is an open source community project that lives from the participation and contribution of its users. TVB-EduPack can be obtained as part of TVB from thevirtualbrain.org

Early astrocytic atrophy in the entorhinal cortex of a triple transgenic animal model of Alzheimer's disease

The EC (entorhinal cortex) is fundamental for cognitive and mnesic functions. Thus damage to this area appears as a key element in the progression of AD (Alzheimer's disease), resulting in memory deficits arising from neuronal and synaptic alterations as well as glial malfunction. In this paper, we have performed an in-depth analysis of astroglial morphology in the EC by measuring the surface and volume of the GFAP (glial fibrillary acidic protein) profiles in a triple transgenic mouse model of AD [3xTg-AD (triple transgenic mice of AD)]. We found significant reduction in both the surface and volume of GFAP-labelled profiles in 3xTg-AD animals from very early ages (1 month) when compared with non-Tg (non-transgenic) controls (48 and 54%, reduction respectively), which was sustained for up to 12 months (33 and 45% reduction respectively). The appearance of Aβ (amyloid β-peptide) depositions at 12 months of age did not trigger astroglial hypertrophy; nor did it result in the close association of astrocytes with senile plaques. Our results suggest that the AD progressive cognitive deterioration can be associated with an early reduction of astrocytic arborization and shrinkage of the astroglial domain, which may affect synaptic connectivity within the EC and between the EC and other brain regions. In addition, the EC seems to be particularly vulnerable to AD pathology because of the absence of evident astrogliosis in response to Aβ accumulation. Thus we can consider that targeting astroglial atrophy may represent a therapeutic strategy which might slow down the progression of AD

Accurate path integration in continuous attractor network models of grid cells

Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of ~10–100 meters and ~1–10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other

Parallel Alterations of Functional Connectivity during Execution and Imagination after Motor Imagery Learning

BACKGROUND: Neural substrates underlying motor learning have been widely investigated with neuroimaging technologies. Investigations have illustrated the critical regions of motor learning and further revealed parallel alterations of functional activation during imagination and execution after learning. However, little is known about the functional connectivity associated with motor learning, especially motor imagery learning, although benefits from functional connectivity analysis attract more attention to the related explorations. We explored whether motor imagery (MI) and motor execution (ME) shared parallel alterations of functional connectivity after MI learning. METHODOLOGY/PRINCIPAL FINDINGS: Graph theory analysis, which is widely used in functional connectivity exploration, was performed on the functional magnetic resonance imaging (fMRI) data of MI and ME tasks before and after 14 days of consecutive MI learning. The control group had no learning. Two measures, connectivity degree and interregional connectivity, were calculated and further assessed at a statistical level. Two interesting results were obtained: (1) The connectivity degree of the right posterior parietal lobe decreased in both MI and ME tasks after MI learning in the experimental group; (2) The parallel alterations of interregional connectivity related to the right posterior parietal lobe occurred in the supplementary motor area for both tasks. CONCLUSIONS/SIGNIFICANCE: These computational results may provide the following insights: (1) The establishment of motor schema through MI learning may induce the significant decrease of connectivity degree in the posterior parietal lobe; (2) The decreased interregional connectivity between the supplementary motor area and the right posterior parietal lobe in post-test implicates the dissociation between motor learning and task performing. These findings and explanations further revealed the neural substrates underpinning MI learning and supported that the potential value of MI learning in motor function rehabilitation and motor skill learning deserves more attention and further investigation

Testing the potential of a virtual reality neurorehabilitation system during performance of observation, imagery and imitation of motor actions recorded by wireless functional near-infrared spectroscopy (fNIRS)

Background Several neurorehabilitation strategies have been introduced over the last decade based on the so-called simulation hypothesis. This hypothesis states that a neural network located in primary and secondary motor areas is activated not only during overt motor execution, but also during observation or imagery of the same motor action. Based on this hypothesis, we investigated the combination of a virtual reality (VR) based neurorehabilitation system together with a wireless functional near infrared spectroscopy (fNIRS) instrument. This combination is particularly appealing from a rehabilitation perspective as it may allow minimally constrained monitoring during neurorehabilitative training. Methods fNIRS was applied over F3 of healthy subjects during task performance in a virtual reality (VR) environment: 1) 'unilateral' group (N = 15), contralateral recording during observation, motor imagery, observation & motor imagery, and imitation of a grasping task performed by a virtual limb (first-person perspective view) using the right hand; 2) 'bilateral' group (N = 8), bilateral recording during observation and imitation of the same task using the right and left hand alternately. Results In the unilateral group, significant within-condition oxy-hemoglobin concentration Δ[O2Hb] changes (mean ± SD μmol/l) were found for motor imagery (0.0868 ± 0.5201 μmol/l) and imitation (0.1715 ± 0.4567 μmol/l). In addition, the bilateral group showed a significant within-condition Δ[O2Hb] change for observation (0.0924 ± 0.3369 μmol/l) as well as between-conditions with lower Δ[O2Hb] amplitudes during observation compared to imitation, especially in the ipsilateral hemisphere (p < 0.001). Further, in the bilateral group, imitation using the non-dominant (left) hand resulted in larger Δ[O2Hb] changes in both the ipsi- and contralateral hemispheres as compared to using the dominant (right) hand. Conclusions This study shows that our combined VR-fNIRS based neurorehabilitation system can activate the action-observation system as described by the simulation hypothesis during performance of observation, motor imagery and imitation of hand actions elicited by a VR environment. Further, in accordance with previous studies, the findings of this study revealed that both inter-subject variability and handedness need to be taken into account when recording in untrained subjects. These findings are of relevance for demonstrating the potential of the VR-fNIRS instrument in neurofeedback applications

Cerebellar Asymmetry and Cortical Connectivity in Monozygotic Twins with Discordant Handedness

Handedness differentiates patterns of neural asymmetry and interhemispheric connectivity in cortical systems that underpin manual and language functions. Contemporary models of cerebellar function incorporate complex motor behaviour and higher-order cognition, expanding upon earlier, traditional associations between the cerebellum and motor control. Structural MRI defined cerebellar volume asymmetries and correlations with corpus callosum (CC) size were compared in 19 pairs of adult female monozygotic twins strongly discordant for handedness (MZHd). Volume and asymmetry of cerebellar lobules were obtained using automated parcellation.CC area and regional widths were obtained from midsagittal planimetric measurements. Within the cerebellum and CC, neurofunctional distinctions were drawn between motor and higher-order cognitive systems. Relationships amongst regional cerebellar asymmetry and cortical connectivity (as indicated by CC widths) were investigated. Interactions between hemisphere and handedness in the anterior cerebellum were due to a larger right-greater-than-left hemispheric asymmetry in right-handed (RH) compared to left-handed (LH) twins. In LH twins only, anterior cerebellar lobule volumes (IV, V) for motor control were associated with CC size, particularly in callosal regions associated with motor cortex connectivity. Superior posterior cerebellar lobule volumes (VI, Crus I, Crus II, VIIb) showed no correlation with CC size in either handedness group. These novel results reflected distinct patterns of cerebellar-cortical relationships delineated by specific CC regions and an anterior-posterior cerebellar topographical mapping. Hence, anterior cerebellar asymmetry may contribute to the greater degree of bilateral cortical organisation of frontal motor function in LH individuals

A Common Anterior Insula Representation of Disgust Observation, Experience and Imagination Shows Divergent Functional Connectivity Pathways

Similar brain regions are involved when we imagine, observe and execute an action. Is the same true for emotions? Here, the same subjects were scanned while they (a) experience, (b) view someone else experiencing and (c) imagine experiencing gustatory emotions (through script-driven imagery). Capitalizing on the fact that disgust is repeatedly inducible within the scanner environment, we scanned the same participants while they (a) view actors taste the content of a cup and look disgusted (b) tasted unpleasant bitter liquids to induce disgust, and (c) read and imagine scenarios involving disgust and their neutral counterparts. To reduce habituation, we inter-mixed trials of positive emotions in all three scanning experiments. We found voxels in the anterior Insula and adjacent frontal operculum to be involved in all three modalities of disgust, suggesting that simulation in the context of social perception and mental imagery of disgust share a common neural substrates. Using effective connectivity, this shared region however was found to be embedded in distinct functional circuits during the three modalities, suggesting why observing, imagining and experiencing an emotion feels so different

Consensus Paper: Radiological Biomarkers of Cerebellar Diseases

Hereditary and sporadic cerebellar ataxias represent a vast and still growing group of diseases whose diagnosis and differentiation cannot only rely on clinical evaluation. Brain imaging including magnetic resonance (MR) and nuclear medicine techniques allows for characterization of structural and functional abnormalities underlying symptomatic ataxias. These methods thus constitute a potential source of radiological biomarkers, which could be used to identify these diseases and differentiate subgroups of them, and to assess their severity and their evolution. Such biomarkers mainly comprise qualitative and quantitative data obtained from MR including proton spectroscopy, diffusion imaging, tractography, voxel-based morphometry, functional imaging during task execution or in a resting state, and from SPETC and PET with several radiotracers. In the current article, we aim to illustrate briefly some applications of these neuroimaging tools to evaluation of cerebellar disorders such as inherited cerebellar ataxia, fetal developmental malformations, and immune-mediated cerebellar diseases and of neurodegenerative or early-developing diseases, such as dementia and autism in which cerebellar involvement is an emerging feature. Although these radiological biomarkers appear promising and helpful to better understand ataxia-related anatomical and physiological impairments, to date, very few of them have turned out to be specific for a given ataxia with atrophy of the cerebellar system being the main and the most usual alteration being observed. Consequently, much remains to be done to establish sensitivity, specificity, and reproducibility of available MR and nuclear medicine features as diagnostic, progression and surrogate biomarkers in clinical routine

Somatosensory System Deficits in Schizophrenia Revealed by MEG during a Median-Nerve Oddball Task

Although impairments related to somatosensory perception are common in schizophrenia, they have rarely been examined in functional imaging studies. In the present study, magnetoencephalography (MEG) was used to identify neural networks that support attention to somatosensory stimuli in healthy adults and abnormalities in these networks in patient with schizophrenia. A median-nerve oddball task was used to probe attention to somatosensory stimuli, and an advanced, high-resolution MEG source-imaging method was applied to assess activity throughout the brain. In nineteen healthy subjects, attention-related activation was seen in a sensorimotor network involving primary somatosensory (S1), secondary somatosensory (S2), primary motor (M1), pre-motor (PMA), and paracentral lobule (PCL) areas. A frontal–parietal–temporal “attention network”, containing dorsal- and ventral–lateral prefrontal cortex (DLPFC and VLPFC), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), superior parietal lobule (SPL), inferior parietal lobule (IPL)/supramarginal gyrus (SMG), and temporal lobe areas, was also activated. Seventeen individuals with schizophrenia showed early attention-related hyperactivations in S1 and M1 but hypo-activation in S1, S2, M1, and PMA at later latency in the sensorimotor network. Within this attention network, hypoactivation was found in SPL, DLPFC, orbitofrontal cortex, and the dorsal aspect of ACC. Hyperactivation was seen in SMG/IPL, frontal pole, and the ventral aspect of ACC in patients. These findings link attention-related somatosensory deficits to dysfunction in both sensorimotor and frontal–parietal–temporal networks in schizophrenia