Pierre Bellec

Contributions of the basal ganglia and functionally related brain structures to motor learning

This review discusses the cerebral plasticity, and the role of the cortico-striatal system in particular, observed as one is learning or planning to execute a newly learned motor behavior up to when the skill is consolidated or has become highly automatized. A special emphasis is given to imaging work describing the neural substrate mediating motor sequence learning and motor adaptation paradigms. These results are then put into a plausible neurobiological model of motor skill learning, which proposes an integrated view of the brain plasticity mediating this form of memory at different stages of the acquisition process.

A Convergent Functional Architecture of the Insula Emerges Across Imaging Modalities

Empirical evidence increasingly supports the hypothesis that patterns of intrinsic functional connectivity (iFC) are sculpted by a history of evoked coactivation within distinct neuronal networks. This, together with evidence of strong correspondence among the networks defined by iFC and those delineated using a variety of other neuroimaging techniques, suggests a fundamental brain architecture detectable across multiple functional and structural imaging modalities. Here, we leverage this insight to examine the functional organization of the human insula. We parcellated the insula on the basis of three distinct neuroimaging modalities - task-evoked coactivation, intrinsic (i.e., task-independent) functional connectivity, and gray matter structural covariance. Clustering of these three different covariance-based measures revealed a convergent elemental organization of the insula that likely reflects a fundamental brain architecture governing both brain structure and function at multiple spatial scales. While not constrained to be hierarchical, our parcellation revealed a pseudo-hierarchical, multiscale organization that was consistent with previous clustering and meta-analytic studies of the insula. Finally, meta-analytic examination of the cognitive and behavioral domains associated with each of the insular clusters obtained elucidated the broad functional dissociations likely underlying the topography observed. To facilitate future investigations of insula function across healthy and pathological states, the insular parcels have been made freely available for download via http://fcon_1000.projects.nitrc.org, along with the analytic scripts used to perform the parcellations.

Multi-level bootstrap analysis of stable clusters in resting-state fMRI

A variety of methods have been developed to identify brain networks with spontaneous, coherent activity in resting-state functional magnetic resonance imaging (fMRI). We propose here a generic statistical framework to quantify the stability of such resting-state networks (RSNs), which was implemented with k-means clustering. The core of the method consists in bootstrapping the available datasets to replicate the clustering process a large number of times and quantify the stable features across all replications. This bootstrap analysis of stable clusters (BASC) has several benefits: (1) it can be implemented in a multi-level fashion to investigate stable RSNs at the level of individual subjects and at the level of a group; (2) it provides a principled measure of RSN stability; and (3) the maximization of the stability measure can be used as a natural criterion to select the number of RSNs. A simulation study validated the good performance of the multi-level BASC on purely synthetic data. Stable networks were also derived from a real resting-state study for 43 subjects. At the group level, seven RSNs were identified which exhibited a good agreement with the previous findings from the literature. The comparison between the individual and group-level stability maps demonstrated the capacity of BASC to establish successful correspondences between these two levels of analysis and at the same time retain some interesting subject-specific characteristics, e.g. the specific involvement of subcortical regions in the visual and fronto-parietal networks for some subjects.

Brain plasticity related to the consolidation of motor sequence learning and motor adaptation

This study aimed to investigate, through functional MRI (fMRI), the neuronal substrates associated with the consolidation process of two motor skills: motor sequence learning (MSL) and motor adaptation (MA). Four groups of young healthy individuals were assigned to either (i) a night/sleep condition, in which they were scanned while practicing a finger sequence learning task or an eight-target adaptation pointing task in the evening (test) and were scanned again 12 h later in the morning (retest) or (ii) a day/awake condition, in which they were scanned on the MSL or the MA tasks in the morning and were rescanned 12 h later in the evening. As expected and consistent with the behavioral results, the functional data revealed increased test–retest changes of activity in the striatum for the night/sleep group compared with the day/awake group in the MSL task. By contrast, the results of the MA task did not show any difference in test–retest activity between the night/sleep and day/awake groups. When the two MA task groups were combined, however, increased test–retest activity was found in lobule VI of the cerebellar cortex. Together, these findings highlight the presence of both functional and structural dissociations reflecting the off-line consolidation processes of MSL and MA. They suggest that MSL consolidation is sleep dependent and reflected by a differential increase of neural activity within the corticostriatal system, whereas MA consolidation necessitates either a period of daytime or sleep and is associated with increased neuronal activity within the corticocerebellar system.

An open science resource for establishing reliability and reproducibility in functional connectomics.

Efforts to identify meaningful functional imaging-based biomarkers are limited by the ability to reliably characterize inter-individual differences in human brain function. Although a growing number of connectomics-based measures are reported to have moderate to high test-retest reliability, the variability in data acquisition, experimental designs, and analytic methods precludes the ability to generalize results. The Consortium for Reliability and Reproducibility (CoRR) is working to address this challenge and establish test-retest reliability as a minimum standard for methods development in functional connectomics. Specifically, CoRR has aggregated 1,629 typical individuals’ resting state fMRI (rfMRI) data (5,093 rfMRI scans) from 18 international sites, and is openly sharing them via the International Data-sharing Neuroimaging Initiative (INDI). To allow researchers to generate various estimates of reliability and reproducibility, a variety of data acquisition procedures and experimental designs are included. Similarly, to enable users to assess the impact of commonly encountered artifacts (for example, motion) on characterizations of inter-individual variation, datasets of varying quality are included.

Functional connectivity in patients with idiopathic generalized epilepsy

Purpose:  Idiopathic generalized epilepsy (IGE) is characterized by electroencephalography (EEG) recordings with generalized spike wave discharges (GSWDs) arising from normal background activity. Although GSWDs are the result of highly synchronized activity in the thalamocortical network, EEG without GSWDs is believed to represent normal brain activity. The aim of this study was to investigate whether thalamocortical interactions are altered even during GSWD‐free EEG periods in patients with IGE.

Regions, systems, and the brain: Hierarchical measures of functional integration in fMRI

In neuroscience, the notion has emerged that the brain abides by two principles: segregation and integration. Segregation into functionally specialized systems and integration of information flow across systems are basic principles that are thought to shape the functional architecture of the brain. A measure called integration, originating from information theory and derived from mutual information, has been proposed to characterize the global integrative state of a network. In this paper, we show that integration can be applied in a hierarchical fashion to quantify functional interactions between compound systems, each system being composed of several regions. We apply this method to fMRI datasets from patients with low-grade glioma and show how it can efficiently extract information related to both intra- and interhemispheric reorganization induced by lesional brain plasticity.

Age-related differences in test-retest reliability in resting-state brain functional connectivity.

Resting-state functional MRI (rs-fMRI) has emerged as a powerful tool for investigating brain functional connectivity (FC). Research in recent years has focused on assessing the reliability of FC across younger subjects within and between scan-sessions. Test-retest reliability in resting-state functional connectivity (RSFC) has not yet been examined in older adults. In this study, we investigated age-related differences in reliability and stability of RSFC across scans. In addition, we examined how global signal regression (GSR) affects RSFC reliability and stability. Three separate resting-state scans from 29 younger adults (18–35 yrs) and 26 older adults (55–85 yrs) were obtained from the International Consortium for Brain Mapping (ICBM) dataset made publically available as part of the 1000 Functional Connectomes project www.nitrc.org/projects/fcon_1000. 92 regions of interest (ROIs) with 5 cubic mm radius, derived from the default, cingulo-opercular, fronto-parietal and sensorimotor networks, were previously defined based on a recent study. Mean time series were extracted from each of the 92 ROIs from each scan and three matrices of z-transformed correlation coefficients were created for each subject, which were then used for evaluation of multi-scan reliability and stability. The young group showed higher reliability of RSFC than the old group with GSR (p-value = 0.028) and without GSR (p-value <0.001). Both groups showed a high degree of multi-scan stability of RSFC and no significant differences were found between groups. By comparing the test-retest reliability of RSFC with and without GSR across scans, we found significantly higher proportion of reliable connections in both groups without GSR, but decreased stability. Our results suggest that aging is associated with reduced reliability of RSFC which itself is highly stable within-subject across scans for both groups, and that GSR reduces the overall reliability but increases the stability in both age groups and could potentially alter group differences of RSFC.

The pipeline system for Octave and Matlab (PSOM): a lightweight scripting framework and execution engine for scientific workflows

The analysis of neuroimaging databases typically involves a large number of inter-connected steps called a pipeline. The pipeline system for Octave and Matlab (PSOM) is a flexible framework for the implementation of pipelines in the form of Octave or Matlab scripts. PSOM does not introduce new language constructs to specify the steps and structure of the workflow. All steps of analysis are instead described by a regular Matlab data structure, documenting their associated command and options, as well as their input, output, and cleaned-up files. The PSOM execution engine provides a number of automated services: (1) it executes jobs in parallel on a local computing facility as long as the dependencies between jobs allow for it and sufficient resources are available; (2) it generates a comprehensive record of the pipeline stages and the history of execution, which is detailed enough to fully reproduce the analysis; (3) if an analysis is started multiple times, it executes only the parts of the pipeline that need to be reprocessed. PSOM is distributed under an open-source MIT license and can be used without restriction for academic or commercial projects. The package has no external dependencies besides Matlab or Octave, is straightforward to install and supports of variety of operating systems (Linux, Windows, Mac). We ran several benchmark experiments on a public database including 200 subjects, using a pipeline for the preprocessing of functional magnetic resonance images (fMRI). The benchmark results showed that PSOM is a powerful solution for the analysis of large databases using local or distributed computing resources.

Age dependence of hemodynamic response characteristics in human functional magnetic resonance imaging

Functional magnetic resonance imaging (fMRI) studies of cognitive aging have generally compared the amplitude and extent of blood oxygen level-dependent (BOLD) signal increases evoked by a task in older and younger groups. BOLD is thus used as a direct index of neuronal activation and it is assumed that the relationship between neuronal activity and the hemodynamic response is unchanged across the lifespan. However, even in healthy aging, differences in vascular and metabolic function have been observed that could affect the coupling between neuronal activity and the BOLD signal. Here we use a calibrated fMRI method to explore vascular and metabolic changes that might bias such BOLD comparisons. Though BOLD signal changes evoked by a cognitive task were found to be similar between a group of younger and older adults (e.g., 0.50 ± 0.04% vs. 0.50 ± 0.05% in right frontal areas), comparison of BOLD and arterial spin labelling (ASL) responses elicited in the same set of structures by a controlled global hypercapnic manipulation revealed significant differences between the 2 groups. Older adults were found to have lower responses in BOLD and flow responses to hypercapnia (e.g., 1.48 ± 0.07% vs. 1.01 ± 0.06% over gray matter for BOLD and 24.92 ± 1.37% vs. 20.67 ± 2.58% for blood flow), and a generally lower maximal BOLD response M (5.76 ± 0.2% vs. 5.00 ± 0.3%). This suggests that a given BOLD response in the elderly might represent a larger change in neuronal activity than the same BOLD response in a younger cohort. The results of this study highlight the importance of ancillary measures such as ASL for the correct interpretation of BOLD responses when fMRI responses are compared across populations who might exhibit differences in vascular physiology.