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See detailThe heterogeneity of the left dorsal premotor cortex evidenced by multimodal connectivity-based parcellation and functional characterization
Genon, Sarah ULg; Reid, Andrew; Li, Hai et al

in NeuroImage (in press)

Despite the common conception of the dorsal premotor cortex (PMd) as a single brain region, its diverse connectivity profiles and behavioral heterogeneity argue for a differentiated organization of the ... [more ▼]

Despite the common conception of the dorsal premotor cortex (PMd) as a single brain region, its diverse connectivity profiles and behavioral heterogeneity argue for a differentiated organization of the PMd. A previous study revealed that the right PMd is characterized by a rostro-caudal and a ventro-dorsal distinction dividing it into five subregions: rostral, central, caudal, ventral and dorsal. The present study assessed whether a similar organization is present in the left hemisphere, by capitalizing on a multimodal data-driven approach combining connectivity-based parcellation (CBP) based on meta-analytic modeling, resting- state functional connectivity, and probabilistic diffusion tractography. The resulting PMd modules were then characterized based on multimodal functional connectivity and a quantitative analysis of associated behavioral functions. Analyzing the clusters consistent across all modalities revealed an organization of the left PMd that mirrored its right counterpart to a large degree. Again, caudal, central and rostral modules reflected a cognitive- motor gradient and a premotor eye-field was found in the ventral part of the left PMd. In addition, a distinct module linked to abstract cognitive functions was observed in the rostro- ventral left PMd across all CBP modalities, implying greater differentiation of higher cognitive functions for the left than the right PMd. [less ▲]

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See detailExploring sex differences in the adult zebra finch brain: in vivo diffusion tensor imaging and ex vivo super-resolution track density imaging
Hamaide, J.; De Groof, G.; Van Steenkiste, G. et al

in NeuroImage (2017)

Zebra finches are an excellent model to study the process of vocal learning, a complex socially-learned tool of communication that forms the basis of spoken human language. So far, structural ... [more ▼]

Zebra finches are an excellent model to study the process of vocal learning, a complex socially-learned tool of communication that forms the basis of spoken human language. So far, structural investigation of the zebra finch brain has been performed ex vivo using invasive methods such as histology. These methods are highly specific, however, they strongly interfere with performing whole-brain analyses and exclude longitudinal studies aimed at establishing causal correlations between neuroplastic events and specific behavioral performances. Therefore, the aim of the current study was to implement an in vivo Diffusion Tensor Imaging (DTI) protocol sensitive enough to detect structural sex differences in the adult zebra finch brain. Voxel-wise comparison of male and female DTI parameter maps shows clear differences in several components of the song control system (i.e. Area X surroundings, the high vocal center (HVC) and the lateral magnocellular nucleus of the anterior nidopallium (LMAN)), which corroborate previous findings and are in line with the clear behavioral difference as only males sing. Furthermore, to obtain additional insights into the 3-dimensional organization of the zebra finch brain and clarify findings obtained by the in vivo study, ex vivo DTI data of the male and female brain were acquired as well, using a recently established super-resolution reconstruction (SRR) imaging strategy. Interestingly, the SRR-DTI approach led to a marked reduction in acquisition time without interfering with the (spatial and angular) resolution and SNR which enabled to acquire a data set characterized by a 78μm isotropic resolution including 90 diffusion gradient directions within 44h of scanning time. Based on the reconstructed SRR-DTI maps, whole brain probabilistic Track Density Imaging (TDI) was performed for the purpose of super resolved track density imaging, further pushing the resolution up to 40μm isotropic. The DTI and TDI maps realized atlas-quality anatomical maps that enable a clear delineation of most components of the song control and auditory systems. In conclusion, this study paves the way for longitudinal in vivo and high-resolution ex vivo experiments aimed at disentangling [less ▲]

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See detailANIMA: A data-sharing initiative for neuroimaging meta-analyses
Reid, Andrew T.; Bzdok, Danilo; Genon, Sarah ULg et al

in NeuroImage (2016), 124(B), 1245-1253

Meta-analytic techniques allow cognitive neuroscientists to pool large amounts of data across many individual task-based functional neuroimaging experiments. These methods have been aided by the ... [more ▼]

Meta-analytic techniques allow cognitive neuroscientists to pool large amounts of data across many individual task-based functional neuroimaging experiments. These methods have been aided by the introduction of online databases such as Brainmap.org or Neurosynth.org, which collate peak activation coordinates obtained from thousands of published studies. Findings from meta-analytic studies typically include brain regions which are consistently activated across studies for specific contrasts, investigating cognitive or clinical hypotheses. These regions can be subsequently used as the basis for seed-based connectivity analysis, or formally compared to neuroimaging data in order to help interpret new findings. To facilitate such approaches, we have developed a new online repository of meta-analytic neuroimaging results, named the Archive of Neuroimaging Meta-analyses (ANIMA). The ANIMA platform consists of an intuitive online interface for querying, downloading, and contributing data from published meta-analytic studies. Additionally, to aid the process of organizing, visualizing, and working with these data, we present an open-source desktop application called Volume Viewer. Volume Viewer allows users to easily arrange imaging data into composite stacks, and save these sessions as individual files, which can also be uploaded to the ANIMA database. The application also allows users to perform basic functions, such as computing conjunctions between images, or extracting regions-of-interest or peak coordinates for further analysis. The introduction of this new resource will enhance the ability of researchers to both share their findings and incorporate existing meta-analytic results into their own research. [less ▲]

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See detailNeural correlates of event clusters in past and future thoughts: How the brain integrates specific episodes with autobiographical knowledge
Demblon, Julie ULg; Bahri, Mohamed Ali ULg; D'Argembeau, Arnaud ULg

in NeuroImage (2016), 127

When remembering the past or envisioning the future, events often come to mind in organized sequences or stories rather than in isolation from one another. The aim of the present fMRI study was to ... [more ▼]

When remembering the past or envisioning the future, events often come to mind in organized sequences or stories rather than in isolation from one another. The aim of the present fMRI study was to investigate the neural correlates of such event clusters. Participants were asked to consider pairs of specific past or future events: in one condition, the two events were part of the same event cluster (i.e., they were thematically and/or causally related to each other), whereas in another condition the two events only shared a surface feature (i.e., their location); a third condition was also included, in which the two events were unrelated to each other. The results showed that the processing of past and future events that were part of a same cluster was associated with higher activation in the medial prefrontal cortex (PFC), rostrolateral PFC, and left lateral temporal and parietal regions, compared to the two other conditions. Furthermore, functional connectivity analyses revealed an increased coupling between these cortical regions. These findings suggest that largely similar processes are involved in organizing events in clusters for the past and the future. The medial and rostrolateral PFC might play a pivotal role in mediating the integration of specific events with conceptual autobiographical knowledge ‘stored’ in more posterior regions. Through this integrative process, this set of brain regions might contribute to the attribution of an overarching meaning to representations of specific past and future events, by contextualizing them with respect to personal goals and general knowledge about one's life story. [less ▲]

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See detailA finite-element reciprocity solution for EEG forward modeling with realistic individual head models
Ziegler, Erik ULg; Chellappa, Sarah Laxhmi ULg; Gaggioni, Giulia ULg et al

in NeuroImage (2014), 103

Highlights • Creates EEG forward models suitable for high-resolution source localization. • Automatic T1-based whole-head finite element meshing and leadfield computation. • Pipelines can incorporate ... [more ▼]

Highlights • Creates EEG forward models suitable for high-resolution source localization. • Automatic T1-based whole-head finite element meshing and leadfield computation. • Pipelines can incorporate conductivity tensors from diffusion-weighted images. • Open-source toolbox shared under a permissive software license. • Accuracy comparable to SimBio FEM and superior to OpenMEEG BEM solutions. [less ▲]

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See detailMapping track density changes in nigrostriatal and extranigral pathways in Parkinson's disease
Ziegler, Erik ULg; Rouillard, Maud; André, Elodie et al

in NeuroImage (2014), 99

Highlights First whole-brain probabilistic tractography study in Parkinson's disease High quality diffusion-weighted images (120 gradient directions, b = 2500 s/mm2) Voxel-based group analysis comparing ... [more ▼]

Highlights First whole-brain probabilistic tractography study in Parkinson's disease High quality diffusion-weighted images (120 gradient directions, b = 2500 s/mm2) Voxel-based group analysis comparing early-stage patients and controls Abnormal reconstructed track density in the nigrostriatal pathway and brainstem Track density also increased in limbic and cognitive circuits. [less ▲]

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See detailFast and accurate modelling of longitudinal and repeated measures neuroimaging data.
Guillaume, Bryan ULg; Hua, Xue; Thompson, Paul et al

in NeuroImage (2014), 94

Despite the growing importance of longitudinal data in neuroimaging, the standard analysis methods make restrictive or unrealistic assumptions (e.g., assumption of Compound Symmetry--the state of all ... [more ▼]

Despite the growing importance of longitudinal data in neuroimaging, the standard analysis methods make restrictive or unrealistic assumptions (e.g., assumption of Compound Symmetry--the state of all equal variances and equal correlations--or spatially homogeneous longitudinal correlations). While some new methods have been proposed to more accurately account for such data, these methods are based on iterative algorithms that are slow and failure-prone. In this article, we propose the use of the Sandwich Estimator method which first estimates the parameters of interest with a simple Ordinary Least Square model and second estimates variances/covariances with the "so-called" Sandwich Estimator (SwE) which accounts for the within-subject correlation existing in longitudinal data. Here, we introduce the SwE method in its classic form, and we review and propose several adjustments to improve its behaviour, specifically in small samples. We use intensive Monte Carlo simulations to compare all considered adjustments and isolate the best combination for neuroimaging data. We also compare the SwE method to other popular methods and demonstrate its strengths and weaknesses. Finally, we analyse a highly unbalanced longitudinal dataset from the Alzheimer's Disease Neuroimaging Initiative and demonstrate the flexibility of the SwE method to fit within- and between-subject effects in a single model. Software implementing this SwE method has been made freely available at http://warwick.ac.uk/tenichols/SwE. [less ▲]

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See detailSleep sharpens sensory stimulus coding in human visual cortex after fear conditioning.
Sterpenich, Virginie; Piguet, Camille; Desseilles, Martin ULg et al

in NeuroImage (2014), 100

Efficient perceptual identification of emotionally-relevant stimuli requires optimized neural coding. Because sleep contributes to neural plasticity mechanisms, we asked whether the perceptual ... [more ▼]

Efficient perceptual identification of emotionally-relevant stimuli requires optimized neural coding. Because sleep contributes to neural plasticity mechanisms, we asked whether the perceptual representation of emotionally-relevant stimuli within sensory cortices is modified after a period of sleep. We show combined effects of sleep and aversive conditioning on subsequent discrimination of face identity information, with parallel plasticity in the amygdala and visual cortex. After one night of sleep (but neither immediately nor after an equal waking interval), a fear-conditioned face was better detected when morphed with another identity. This behavioral change was accompanied by increased selectivity of the amygdala and face-responsive fusiform regions. Overnight neural changes can thus sharpen the representation of threat-related stimuli in cortical sensory areas, in order to improve detection in impoverished or ambiguous situations. These findings reveal an important role of sleep in shaping cortical selectivity to emotionally-relevant cues and thus promoting adaptive responses to new dangers. [less ▲]

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See detailSimultaneous EEG-fMRI acquisition at low, high and ultra-high magnetic fields up to 9.4 T: perspectives and challenges.
Neuner, Irene; Arrubla Martinez, Jorge Andres ULg; Felder, Jorg et al

in NeuroImage (2014), 102 Pt 1

In this perspectives article we highlight the advantages of simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). As MRI moves towards using ultra-high ... [more ▼]

In this perspectives article we highlight the advantages of simultaneous acquisition of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). As MRI moves towards using ultra-high magnetic fields in the quest for increased signal-to-noise, the question arises whether combined EEG-fMRI measurements are feasible at magnetic fields of 7 T and higher. We describe the challenges of MRI-EEG at 1.5, 3, 7 and 9.4 T and review the proposed solutions. In an outlook, we discuss further developments such as simultaneous trimodal imaging using MR, positron emission tomography (PET) and EEG under the same physiological conditions in the same subject. [less ▲]

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See detailSpatiotemporal properties of auditory intensity processing in multisensor MEG.
Wyss, C.; Boers, F.; Kawohl, W. et al

in NeuroImage (2014), 102 Pt 2

Loudness dependence of auditory evoked potentials (LDAEP) evaluates loudness processing in the human auditory system and is often altered in patients with psychiatric disorders. Previous research has ... [more ▼]

Loudness dependence of auditory evoked potentials (LDAEP) evaluates loudness processing in the human auditory system and is often altered in patients with psychiatric disorders. Previous research has suggested that this measure may be used as an indicator of the central serotonergic system through the highly serotonergic innervation of the auditory cortex. However, differences among the commonly used analysis approaches (such as source analysis and single electrode estimation) may lead to different results. Putatively due to discrepancies of the underlying structures being measured. Therefore, it is important to learn more about how and where in the brain loudness variation is processed. We conducted a detailed investigation of the LDAEP generators and their temporal dynamics by means of multichannel magnetoencephalography (MEG). Evoked responses to brief tones of five different intensities were recorded from 19 healthy participants. We used magnetic field tomography in order to appropriately localize superficial as well as deep source generators of which we conducted a time series analysis. The results showed that apart from the auditory cortex other cortical sources exhibited activation during the N1/P2 time window. Analysis of time courses in the regions of interest revealed a sequential cortical activation from primary sensory areas, particularly the auditory and somatosensory cortex to posterior cingulate cortex (PCC) and to premotor cortex (PMC). The additional activation within the PCC and PMC has implications on the analysis approaches used in LDAEP research. [less ▲]

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See detailEEG acquisition in ultra-high static magnetic fields up to 9.4 T.
Neuner, Irene; Warbrick, Tracy; Arrubla Martinez, Jorge Andres ULg et al

in NeuroImage (2013), 68

The simultaneous acquisition of electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data has gained momentum in recent years due to the synergistic effects of the two modalities ... [more ▼]

The simultaneous acquisition of electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) data has gained momentum in recent years due to the synergistic effects of the two modalities with regard to temporal and spatial resolution. Currently, only EEG-data recorded in fields of up to 7 T have been reported. We investigated the feasibility of recording EEG inside a 9.4 T static magnetic field, specifically to determine whether meaningful EEG information could be recovered from the data after removal of the cardiac-related artefact. EEG-data were recorded reliably and reproducibly at 9.4 T and the cardiac-related artefact increased in amplitude with increasing B0, as expected. Furthermore, we were able to correct for the cardiac-related artefact and identify auditory event related responses at 9.4 T in 75% of subjects using independent component analysis (ICA). Also by means of ICA we detected event related spectral perturbations (ERSP) in subjects at 9.4 T in response to opening/closing the eyes comparable with the response at 0 T. Overall our results suggest that it is possible to record meaningful EEG data at ultra-high magnetic fields. The simultaneous EEG-fMRI approach at ultra-high-fields opens up the horizon for investigating brain dynamics at a superb spatial resolution and a temporal resolution in the millisecond domain. [less ▲]

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See detailRelationships between brain metabolism decrease in normal aging and changes in structural and functional connectivity
Chételat, Gael; Landeau, Brigitte; Salmon, Eric ULg et al

in NeuroImage (2013), 76

Normal aging is characterized by brain glucose metabolism decline predominantly in the prefrontal cortex. The goal of the present study was to assess whether this change was associated with age-related ... [more ▼]

Normal aging is characterized by brain glucose metabolism decline predominantly in the prefrontal cortex. The goal of the present study was to assess whether this change was associated with age-related alteration of white matter (WM) structural integrity and/or functional connectivity. FDG-PET data from 40 young and 57 elderly healthy participants from two research centres (n=49/48 in Centre 1/2) were analyzed. WM volume from T1-weighted MRI (Centre 1), fractional anisotropy from diffusion-tensor imaging (Centre 2), and resting-state fMRI data (Centre 1) were also obtained. Group comparisons were performed within each imaging modality. Then, positive correlations were assessed, within the elderly, between metabolism in the most affected region and the other neuroimaging modalities. Metabolism decline in the elderly predominated in the left inferior frontal junction (LIFJ). LIFJ hypometabolism was significantly associated with macrostructural and microstructural WM disturbances in long association fronto-temporo-occipital fibers, while no relationship was found with functional connectivity. The findings offer new perspectives to understand normal aging processes and open avenues for future studies to explore causality between age-related metabolism and connectivity changes. [less ▲]

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See detailMetabolic and structural connectivity within the default mode network relates to working memory performance in young healthy adults
Yakushev, Igor; Chételat, Gael; Fischer F.U. et al

in NeuroImage (2013), 79

Studies of functional connectivity suggest that the default mode network (DMN) might be relevant for cognitive functions. Here, we examined metabolic and structural connectivity between major DMN nodes ... [more ▼]

Studies of functional connectivity suggest that the default mode network (DMN) might be relevant for cognitive functions. Here, we examined metabolic and structural connectivity between major DMN nodes, the posterior cingulate (PCC) and medial prefrontal cortex (MPFC), in relation to normal working memory (WM). DMN was captured using independent component analysis of [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) data from 35 young healthy adults (27.1±5.1 years). Metabolic connectivity, a correlation between FDG uptake in PCC and MPFC, was examined in groups of subjects with (relative to median) low (n=18) and high (n=17) performance on digit span backward test as an index of verbal WM. In addition, fiber tractography based on PCC and MPFC nodes as way points was performed in a subset of subjects. FDG uptake in the DMN nodes did not differ between high and low performers. However, significantly (p=0.01) lower metabolic connectivity was found in the group of low performers. Furthermore, as compared to high performers, low performers showed lower density of the left superior cingulate bundle. Verbal WM performance is related to metabolic and structural connectivity within the DMN in young healthy adults. Metabolic connectivity as quantified with FDG-PET might be a sensitive marker of the normal variability in some cognitive functions. [less ▲]

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See detailBinary classification of (1)(8)F-flutemetamol PET using machine learning: comparison with visual reads and structural MRI
Vandenberghe, R.; Nelissen, N.; Salmon, Eric ULg et al

in NeuroImage (2013), 64

(18)F-flutemetamol is a positron emission tomography (PET) tracer for in vivo amyloid imaging. The ability to classify amyloid scans in a binary manner as 'normal' versus 'Alzheimer-like', is of high ... [more ▼]

(18)F-flutemetamol is a positron emission tomography (PET) tracer for in vivo amyloid imaging. The ability to classify amyloid scans in a binary manner as 'normal' versus 'Alzheimer-like', is of high clinical relevance. We evaluated whether a supervised machine learning technique, support vector machines (SVM), can replicate the assignments made by visual readers blind to the clinical diagnosis, which image components have highest diagnostic value according to SVM and how (18)F-flutemetamol-based classification using SVM relates to structural MRI-based classification using SVM within the same subjects. By means of SVM with a linear kernel, we analyzed (18)F-flutemetamol scans and volumetric MRI scans from 72 cases from the (18)F-flutemetamol phase 2 study (27 clinically probable Alzheimer's disease (AD), 20 amnestic mild cognitive impairment (MCI), 25 controls). In a leave-one-out approach, we trained the (18)F-flutemetamol based classifier by means of the visual reads and tested whether the classifier was able to reproduce the assignment based on visual reads and which voxels had the highest feature weights. The (18)F-flutemetamol based classifier was able to replicate the assignments obtained by visual reads with 100% accuracy. The voxels with highest feature weights were in the striatum, precuneus, cingulate and middle frontal gyrus. Second, to determine concordance between the gray matter volume- and the (18)F-flutemetamol-based classification, we trained the classifier with the clinical diagnosis as gold standard. Overall sensitivity of the (18)F-flutemetamol- and the gray matter volume-based classifiers were identical (85.2%), albeit with discordant classification in three cases. Specificity of the (18)F-flutemetamol based classifier was 92% compared to 68% for MRI. In the MCI group, the (18)F-flutemetamol based classifier distinguished more reliably between converters and non-converters than the gray matter-based classifier. The visual read-based binary classification of (18)F-flutemetamol scans can be replicated using SVM. In this sample the specificity of (18)F-flutemetamol based SVM for distinguishing AD from controls is higher than that of gray matter volume-based SVM. [less ▲]

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See detailNeural substrates of cognitive switching and inhibition in a face processing task.
Piguet, Camille; Sterpenich, Virginie; Desseilles, Martin ULg et al

in NeuroImage (2013), 82

We frequently need to change our current occupation, an operation requiring additional effortful cognitive demands. Switching from one task to another may involve two distinct processes: inhibition of the ... [more ▼]

We frequently need to change our current occupation, an operation requiring additional effortful cognitive demands. Switching from one task to another may involve two distinct processes: inhibition of the previously relevant task-set, and initiation of a new one. Here we tested whether these two processes are underpinned by separate neural substrates, and whether they differ depending on the nature of the task and the emotional content of stimuli. We used functional magnetic resonance imaging in healthy human volunteers who categorize emotional faces according to three different judgment rules (color, gender, or emotional expression). Our paradigm allowed us to separate neural activity associated with inhibition and switching based on the sequence of the tasks required on successive trials. We found that the bilateral medial superior parietal lobule and left intraparietal sulcus showed consistent activation during switching regardless of the task. On the other hand, no common region was activated (or suppressed) as a consequence of inhibition across all tasks. Rather, task-specific effects were observed in brain regions that were more activated when switching to a particular task but less activated after inhibition of the same task. In addition, compared to other conditions, the emotional task elicited a similar switching cost but lower inhibition cost, accompanied by selective decrease in the anterior cingulate cortex when returning to this task shortly after inhibiting it. These results demonstrate that switching relies on domain-general processes mediated by postero-medial parietal areas, engaged across all tasks, but also provide novel evidence that task inhibition produces domain-specific decreases as a function of particular task demands, with only the latter inhibition component being modulated by emotional information. [less ▲]

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See detailNeural Correlates of Performance Variabilty during Motor Sequence Acquisition
Albouy, Geneviève ULg; Sterpenich, V.; Vandewalle, Gilles ULg et al

in NeuroImage (2012), 60(1), 324-331

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See detailComa and consciousness: Paradigms (re)framed by neuroimaging.
Laureys, Steven ULg; Schiff, N.

in NeuroImage (2012)

The past 15years has provided an unprecedented collection of discoveries that bear upon our scientific understanding of recovery of consciousness in the human brain following severe brain damage ... [more ▼]

The past 15years has provided an unprecedented collection of discoveries that bear upon our scientific understanding of recovery of consciousness in the human brain following severe brain damage. Highlighted among these discoveries are unique demonstrations that patients with little or no behavioral evidence of conscious awareness may retain critical cognitive capacities and the first scientific demonstrations that some patients, with severely injured brains and very longstanding conditions of limited behavioral responsiveness, may nonetheless harbor latent capacities for significant recovery. Included among such capacities are particularly human functions of language and higher-level cognition that either spontaneously or through direct interventions may reemerge even at long time intervals or remain unrecognized. Collectively, these observations have reframed scientific inquiry and further led to important new insights into mechanisms underlying consciousness in the human brain. These studies support a model of consciousness as the emergent property of the collective behavior of widespread frontoparietal network connectivity modulated by specific forebrain circuit mechanisms. We here review these advances in measurement and the scientific and broader implications of this rapidly progressing field of research. [less ▲]

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See detailCognitive reserve impacts on inter-individual variability in resting-state cerebral metabolism in normal aging
Bastin, Christine ULg; Yakushev, Igor; Bahri, Mohamed Ali ULg et al

in NeuroImage (2012), 63

There is a great deal of heterogeneity in the impact of aging on cognition and cerebral functioning. One potential factor contributing to individual differences among the elders is the cognitive reserve ... [more ▼]

There is a great deal of heterogeneity in the impact of aging on cognition and cerebral functioning. One potential factor contributing to individual differences among the elders is the cognitive reserve, which designates the partial protection from the deleterious effects of aging that lifetime experience provides. Neuroimaging studies examining task-related activation in elderly people suggested that cognitive reserve takes the form of more efficient use of brain networks and/or greater ability to recruit alternative networks to compensate for age-related cerebral changes. In this multi-centre study, we examined the relationships between cognitive reserve, as measured by education and verbal intelligence, and cerebral metabolism at rest (FDG-PET) in a sample of 74 healthy older participants. Higher degree of education and verbal intelligence was associated with less metabolic activity in the right posterior temporoparietal cortex and the left anterior intraparietal sulcus. Functional connectivity analyses of resting-state fMRI images in a subset of 41 participants indicated that these regions belong to the default mode network and the dorsal attention network respectively. Lower metabolism in the temporoparietal cortex was also associated with better memory abilities. The findings provide evidence for an inverse relationship between cognitive reserve and resting-state activity in key regions of two functional networks respectively involved in internal mentation and goal-directed attention. [less ▲]

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See detail"Relevance vector machine" consciousness classifier applied to cerebral metabolism of vegetative and locked-in patients.
Phillips, Christophe ULg; Bruno, Marie-Aurélie ULg; Maquet, Pierre ULg et al

in NeuroImage (2011), 56(2), 797808

The vegetative state is a devastating condition where patients awaken from their coma (i.e., open their eyes) but fail to show any behavioural sign of conscious awareness. Locked-in syndrome patients also ... [more ▼]

The vegetative state is a devastating condition where patients awaken from their coma (i.e., open their eyes) but fail to show any behavioural sign of conscious awareness. Locked-in syndrome patients also awaken from their coma and are unable to show any motor response to command (except for small eye movements or blinks) but recover full conscious awareness of self and environment. Bedside evaluation of residual cognitive function in coma survivors often is difficult because motor responses may be very limited or inconsistent. We here aimed to disentangle vegetative from "locked-in" patients by an automatic procedure based on machine learning using fluorodeoxyglucose PET data obtained in 37 healthy controls and in 13 patients in a vegetative state. Next, the trained machine was tested on brain scans obtained in 8 patients with locked-in syndrome. We used a sparse probabilistic Bayesian learning framework called "relevance vector machine" (RVM) to classify the scans. The trained RVM classifier, applied on an input scan, returns a probability value (p-value) of being in one class or the other, here being "conscious" or not. Training on the control and vegetative state groups was assessed with a leave-one-out cross-validation procedure, leading to 100% classification accuracy. When applied on the locked-in patients, all scans were classified as "conscious" with a mean p-value of .95 (min .85). In conclusion, even with this relatively limited data set, we could train a classifier distinguishing between normal consciousness (i.e., wakeful conscious awareness) and the vegetative state (i.e., wakeful unawareness). Cross-validation also indicated that the clinical classification and the one predicted by the automatic RVM classifier were in accordance. Moreover, when applied on a third group of "locked-in" consciously aware patients, they all had a strong probability of being similar to the normal controls, as expected. Therefore, RVM classification of cerebral metabolic images obtained in coma survivors could become a useful tool for the automated PET-based diagnosis of altered states of consciousness. [less ▲]

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