FASST- a FMRI Artefact rejection and Sleep Scoring Toolbox
Schrouff, Jessica ; Leclercq, Yves ; Noirhomme, Quentin et al
Poster (2011, June 28)
We started writing the “fMRI artefact rejection and sleep scoring toolbox”, or “FASST”, to process our sleep EEG-fMRI data, that is, the simultaneous recording of electroencephalographic and functional ... [more ▼]
We started writing the “fMRI artefact rejection and sleep scoring toolbox”, or “FASST”, to process our sleep EEG-fMRI data, that is, the simultaneous recording of electroencephalographic and functional magnetic resonance imaging data acquired while a subject is asleep. FAST tackles three crucial issues typical of this kind of data: (1) data manipulation (viewing, comparing, chunking, etc.) of long continuous M/EEG recordings, (2) rejection of the fMRI-induced artefact in the EEG signal, and (3)manual sleep-scoring of the M/EEG recording. Currently, the toolbox can efficiently deal with these issues via a GUI, SPM8 batching system or handwritten script. The tools developed are, of course, also useful for other EEG applications, for example, involving simultaneous EEG-fMRI acquisition, continuous EEG eye-balling, and manipulation. Even though the toolbox was originally devised for EEG data, it will also gracefully handle MEG data without any problem. “FAST” is developed in Matlab as an add-on toolbox for SPM8 and, therefore, internally uses its SPM8-meeg data format. “FAST” is available for free, under the GNU-GPL. [less ▲]Detailed reference viewed: 11 (1 ULg)
Decoding Directed Brain Activity in fMRI using Support Vector Machines and Gaussian Processes
Schrouff, Jessica ; Kussé, Caroline ; Wehenkel, Louis et al
Poster (2011, June 26)
Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental ... [more ▼]
Predicting a particular cognitive state from a specific pattern of fMRI voxel values is still a methodological challenge. Decoding brain activity is usually performed in highly controlled experimental paradigms characterized by a series of distinct states induced by a temporally constrained experimental design. In more realistic conditions, the number, sequence and duration of mental states are unpredictably generated by the individual, resulting in complex and imbalanced fMRI data sets. This study tests the classification of brain activity, acquired on 16 volunteers using fMRI, during mental imagery, a condition in which the number and duration of mental events were not externally imposed but self-generated. To deal with these issues, two classification techniques were considered (Support Vector Machines, SVM, and Gaussian Processes, GP), as well as different feature extraction methods (General Linear Model, GLM and SVM). These techniques were combined in order to identify the procedures leading to the highest accuracy measures. Our results showed that 12 data sets out of 16 could be significantly modeled by either SVM or GP. Model accuracies tended to be related to the degree of imbalance between classes and to task performance of the volunteers. We also conclude that the GP technique tends to be more robust than SVM to model unbalanced data sets. [less ▲]Detailed reference viewed: 27 (5 ULg)
Modulating effect of COMT genotype on the brain regions underlying inhibition
Jaspar, Mathieu ; Grandjean, Julien ; Salmon, Eric et al
Poster (2011, June 26)
Introduction Catechol-O-methytransferase (COMT) is an important enzyme which degrades catecholamines, such dopamine, notably in the prefrontal cortex (Männistö & Kaakkola, 1999). Actually, a transition of ... [more ▼]
Introduction Catechol-O-methytransferase (COMT) is an important enzyme which degrades catecholamines, such dopamine, notably in the prefrontal cortex (Männistö & Kaakkola, 1999). Actually, a transition of guanine to adenine at codon 158 of the COMT gene results in a valine to methionine substitution (Lotta & al., 1995). This phenomenon leads to different COMT genotypes, each associated with a different COMT enzymatic activity (Weinshilboum, & al., 1999). A large number of studies reported an effect of COMT on executive functioning. However, most of them used multi-determined executive tasks (e.g., Barnett & al., 2007). We are interested here to determine the effect of COMT Val158Met genotype on the activity of frontal and parietal areas (Nee & al., 2007; Laird & al., 2005) underlying the specific executive process of inhibition. Methods Procedure In an event-related fMRI experiment, a modified form of the Stroop task was administered to 44 young adults (age range: 18-30) separated into three groups according to their COMT Val158Met genotype: 15 homozygous val/val (VV), 14 homozygous met/met (MM) and 15 heterozygotes val/met (VM) carriers. The Stroop task consisted in the presentation of color words printed in various ink colors (e.g the word blue written in red). Subjects were instructed to name of ink color as fast and accurately as possible by avoiding to read the word. In this version of the Stroop task, three different contexts were created (data not showed here): (1) a congruent context (MC) with a majority of facilitator items (IC), (2) a non-congruent context (MI) with mainly interfering items (II), (3) a neutral context (MN) with mainly neutral items (IN, series of %%% written in different colors). MRI acquisition, data analysis Functional MRI time series were acquired on a 3T head-only scanner operated with the standard transmit-receive quadrature head coil. Multislice T2*-weighted functional images were acquired with a gradient-echo echo-planar imaging sequence using axial slice orientation and covering the whole brain (32 slices, FoV = 220x220 mm², voxel size 3.4x3.4x3 mm³, 30% interslice gap, matrix size 64x64x32, TR = 2130 ms, TE = 40 ms, FA = 90°). Structural images were obtained using a high resolution T1-weighted sequence (3D MDEFT [Deichmann & al., (2004)] ; TR = 7.92 ms, TE = 2.4 ms, TI = 910 ms, FA = 15°, FoV = 256 x 224 x 176 mm³, 1 mm isotropic spatial resolution). Preprocessing and statistical analyses were performed with SPM8 (p<.001 uncorrected). Results Behavioral results indicated the presence of a general interference effect (II – IN items) for reaction time (F(1,41) = 292,44 ; p < 0,001) but no significant difference in interference between the three groups (F(2,41) = 0,27; p = 0,76). FMRI results revealed that interference effect [(MI_II-MI_IN) + (MC_II-MC_IN) + (MN_II-MN_IN)] observed in our three groups is mainly associated with cerebral activity in frontal and parietal areas. Moreover, group comparisons indicates that this effect is associated with increased medial frontal and precentral gyrus activity in VV and VM groups by comparison with MM group, but also in the superior temporal gyrus and in the thalamus in the VM by comparison to MM . Conversely, no supplementary brain area was observed for the comparison of the MM to the two other groups. Conclusions The fronto-parietal brain network associated with interference resolution observed here is consistent with prior reports (Nee & al., 2007; Laird & al., 2005). Moreover, results showed activity in different brain areas according to the COMT genotype. Indeed, a similar behavioral performance is associated to the recruitment of supplementary areas in the carriers of the val allele. This observation, paralleling with the lower COMT enzymatic activity and, thus, the higher cortical dopamine level in met/met individuals, confirms our expectation of a COMT Val158Met genotype modulation of the brain regions underlying inhibition efficiency. [less ▲]Detailed reference viewed: 41 (7 ULg)
Experience-dependent induction of hypnagogic images during daytime naps: a combined behavioral and EEG study.
Kussé, Caroline ; ; Schrouff, Jessica et al
in Association for the Scientific Study of Consciousness 15, Kyoto, Japan, 9-12 June 2011 (2011, June 09)Detailed reference viewed: 8 (1 ULg)
Reciprocal interactions between wakefulness and sleep influence global and regional brain activity
Muto, Vincenzo ; Mascetti, Laura ; et al
in Current Topics in Medicinal Chemistry (2011), 11(19), 2403-13Detailed reference viewed: 21 (11 ULg)
Brain functional integration decreases during propofol-induced loss of consciousness.
Schrouff, Jessica ; ; Boly, Mélanie et al
in NeuroImage (2011), 57(1), 198-205
Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol ... [more ▼]
Consciousness has been related to the amount of integrated information that the brain is able to generate. In this paper, we tested the hypothesis that the loss of consciousness caused by propofol anesthesia is associated with a significant reduction in the capacity of the brain to integrate information. To assess the functional structure of the whole brain, functional integration and partial correlations were computed from fMRI data acquired from 18 healthy volunteers during resting wakefulness and propofol-induced deep sedation. Total integration was significantly reduced from wakefulness to deep sedation in the whole brain as well as within and between its constituent networks (or systems). Integration was systematically reduced within each system (i.e., brain or networks), as well as between networks. However, the ventral attentional network maintained interactions with most other networks during deep sedation. Partial correlations further suggested that functional connectivity was particularly affected between parietal areas and frontal or temporal regions during deep sedation. Our findings suggest that the breakdown in brain integration is the neural correlate of the loss of consciousness induced by propofol. They stress the important role played by parietal and frontal areas in the generation of consciousness. [less ▲]Detailed reference viewed: 81 (33 ULg)
Functional neuroimaging of the reciprocal influences between sleep and wakefulness.
Jedidi, Zayd ; Rikir, Estelle ; Muto, Vincenzo et al
in Pflugers Archiv : European journal of physiology (2011), 463(1), 103-9
The activity patterns adopted by brain neuronal populations differ dramatically between wakefulness and sleep. However, these vigilance states are not independent and they reciprocally interact. Here, we ... [more ▼]
The activity patterns adopted by brain neuronal populations differ dramatically between wakefulness and sleep. However, these vigilance states are not independent and they reciprocally interact. Here, we provide evidence that in humans, regional brain activity during wakefulness is influenced by sleep regulation, namely by the interaction between sleep homeostasis and circadian signals. We also show that, by contrast, regional brain activity during sleep is influenced by the experience acquired during the preceding waking period. These data reveal the dynamic interactions by which the succession of vigilance states support normal brain function and human cognition. [less ▲]Detailed reference viewed: 50 (22 ULg)
Neural Correlates of Human NREM Sleep Oscillations
Foret, Ariane ; Shaffii, Anahita ; Muto, Vincenzo et al
in Hutt, Axel (Ed.) Sleep and Anesthesia (2011)Detailed reference viewed: 26 (13 ULg)
Abnormal Hypothalamic Response to Light in Seasonal Affective Disorder
Vandewalle, Gilles ; ; et al
in Biological Psychiatry (2011), 70(10), 954-961Detailed reference viewed: 18 (2 ULg)
Sleep contributes to the strengthening of some memories over others, depending on hippocampal activity at learning.
; Feyers, Dorothée ; et al
in Journal of Neuroscience (2011), 31(7), 2563-2568
Memory consolidation benefits from sleep. Besides strengthening some memory traces, another crucial, albeit overlooked, function of memory is also to erase irrelevant information. Directed forgetting is ... [more ▼]
Memory consolidation benefits from sleep. Besides strengthening some memory traces, another crucial, albeit overlooked, function of memory is also to erase irrelevant information. Directed forgetting is an experimental approach consisting in presenting “to be remembered” and “to be forgotten” information, that allows selectively decreasing or increasing the strength of individual memory traces according to the instruction provided at learning. This paradigm was used in combination with fMRI to determine, in Humans, what specifically triggers at encoding sleep-dependent compared to time-dependent consolidation. Our data indicate that relevant items which subjects strived to memorize are consolidated during sleep to a greater extend than items that participants did not intend to learn. This process appears to depend on a differential activation of the hippocampus at encoding, which acts as a signal for the offline reprocessing of relevant memories during post-learning sleep episodes. [less ▲]Detailed reference viewed: 47 (12 ULg)
"Relevance vector machine" consciousness classifier applied to cerebral metabolism of vegetative and locked-in patients.
Phillips, Christophe ; Bruno, Marie-Aurélie ; Maquet, Pierre 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 ▲]Detailed reference viewed: 45 (12 ULg)
Is brain activity during a Stroop inhibitory task modulated by the kind of cognitive control required?
Collette, Fabienne ; D'Ostilio, Kevin ; D'Argembeau, Arnaud et al
Performance on the Stroop task is associated to a large antero-posterior cerebral network involving notably the anterior cingulate and dorsolateral prefrontal cortex. In this study, we used a mixed-BOLD ... [more ▼]
Performance on the Stroop task is associated to a large antero-posterior cerebral network involving notably the anterior cingulate and dorsolateral prefrontal cortex. In this study, we used a mixed-BOLD-fMRI design (N=25) to determine the neural substrates of inhibitory functioning in a Stroop task according to contextual information. Consequently, two task-contexts were created: (1) congruent context with a majority of facilitator items, (2) non-congruent context with mainly interfering items. Based on the dual cognitive control model, we postulated that the non-congruent blocks will involve proactive control, which is anticipatory, sustained, and involved when a large number of interfering items are successively presented. On the contrary, congruent blocks were assumed to involve reactive control, which occurs when few interfering items are presented, and just after the presentation of these items only. On this basis, we hypothesized that the kind of cognitive control modulates cerebral activity associated to inhibitory functioning. For behavioral data, we obtained faster response times for interfering items in the non-congruent vs. congruent condition, indicating proactive control specific to the congruent condition only. Functional neuro-imaging data showed an increased transient activity for interfering vs neutral items in a fronto-parietal network more important in the congruent than in the neutral condition. A similar contrast in the non-congruent condition showed no significant brain activity at the statistical threshold used. These data indicate the existence of a modulation of the cerebral areas associated to inhibitory functioning according to the kind of cognitive control necessary to perform the task. [less ▲]Detailed reference viewed: 73 (4 ULg)
Depression alters "top-down" visual attention: a dynamic causal modeling comparison between depressed and healthy subjects.
Desseilles, Martin ; ; Dang Vu, Thien Thanh et al
in NeuroImage (2011), 54(2), 1662-8
Using functional magnetic resonance imaging (fMRI), we recently demonstrated that nonmedicated patients with a first episode of unipolar major depression (MDD) compared to matched controls exhibited an ... [more ▼]
Using functional magnetic resonance imaging (fMRI), we recently demonstrated that nonmedicated patients with a first episode of unipolar major depression (MDD) compared to matched controls exhibited an abnormal neural filtering of irrelevant visual information (Desseilles et al., 2009). During scanning, subjects performed a visual attention task imposing two different levels of attentional load at fixation (low or high), while task-irrelevant colored stimuli were presented in the periphery. In the present study, we focused on the visuo-attentional system and used "Dynamic Causal Modeling" (DCM) on the same dataset to assess how attention influences a network of three dynamically-interconnected brain regions (visual areas V1 and V4, and intraparietal sulcus (P), differentially in MDD patients and healthy controls. Bayesian model selection (BMS) and model space partitioning (MSP) were used to determine the best model in each population. The best model for the controls revealed that the increase of parietal activity by high attention load was selectively associated with a negative modulation of P on V4, consistent with high attention reducing the processing of irrelevant colored peripheral stimuli. The best model accounting for the data from the MDD patients showed that both low and high attention levels exerted modulatory effects on P. The present results document abnormal effective connectivity across visuo-attentional networks in MDD, which likely contributes to deficient attentional filtering of information. [less ▲]Detailed reference viewed: 51 (16 ULg)
Multimodal neuroimaging in patients with disorders of consciousness showing "functional hemispherectomy".
Bruno, Marie-Aurélie ; ; Lehembre, Remy et al
in Progress in Brain Research (2011), 193
Beside behavioral assessment of patients with disorders of consciousness, neuroimaging modalities may offer objective paraclinical markers important for diagnosis and prognosis. They provide information ... [more ▼]
Beside behavioral assessment of patients with disorders of consciousness, neuroimaging modalities may offer objective paraclinical markers important for diagnosis and prognosis. They provide information on the structural location and extent of brain lesions (e.g., morphometric MRI and diffusion tensor imaging (DTI-MRI) assessing structural connectivity) but also their functional impact (e.g., metabolic FDG-PET, hemodynamic fMRI, and EEG measurements obtained in "resting state" conditions). We here illustrate the role of multimodal imaging in severe brain injury, presenting a patient in unresponsive wakefulness syndrome (UWS; i.e., vegetative state, VS) and in a "fluctuating" minimally conscious state (MCS). In both cases, resting state FDG-PET, fMRI, and EEG showed a functionally preserved right hemisphere, while DTI showed underlying differences in structural connectivity highlighting the complementarities of these neuroimaging methods in the study of disorders of consciousness. [less ▲]Detailed reference viewed: 38 (4 ULg)
Interplay between spontaneous and induced brain activity during human non-rapid eye movement sleep.
Dang Vu, Thien Thanh ; ; et al
in Proceedings of the National Academy of Sciences of the United States of America (2011), 108(37), 15438-43
Humans are less responsive to the surrounding environment during sleep. However, the extent to which the human brain responds to external stimuli during sleep is uncertain. We used simultaneous EEG and ... [more ▼]
Humans are less responsive to the surrounding environment during sleep. However, the extent to which the human brain responds to external stimuli during sleep is uncertain. We used simultaneous EEG and functional MRI to characterize brain responses to tones during wakefulness and non-rapid eye movement (NREM) sleep. Sounds during wakefulness elicited responses in the thalamus and primary auditory cortex. These responses persisted in NREM sleep, except throughout spindles, during which they became less consistent. When sounds induced a K complex, activity in the auditory cortex was enhanced and responses in distant frontal areas were elicited, similar to the stereotypical pattern associated with slow oscillations. These data show that sound processing during NREM sleep is constrained by fundamental brain oscillatory modes (slow oscillations and spindles), which result in a complex interplay between spontaneous and induced brain activity. The distortion of sensory information at the thalamic level, especially during spindles, functionally isolates the cortex from the environment and might provide unique conditions favorable for off-line memory processing. [less ▲]Detailed reference viewed: 39 (12 ULg)
Neural precursors of delayed insight
Darsaud, Annabelle ; ; Balteau, Evelyne et al
in Journal of Cognitive Neuroscience (2011), 23(8), 1900-1910
The solution of a problem left unresolved in the evening can sometimes pop into mind as a sudden insight after a night of sleep in the following morning. Although favorable effects of sleep on insightful ... [more ▼]
The solution of a problem left unresolved in the evening can sometimes pop into mind as a sudden insight after a night of sleep in the following morning. Although favorable effects of sleep on insightful behavior have been experimentally confirmed, the neural mechanisms determining this delayed insight remain unknown. Here, using functional magnetic resonance imaging (fMRI), we characterize the neural precursors of delayed insight in the number reduction task (NRT), in which a hidden task structure can be learned implicitly, but can also be recognized explicitly in an insightful process, allowing immediate qualitative improvement in task performance. Normal volunteers practiced the NRT during two fMRI sessions (training and retest), taking place 12 hours apart after a night of sleep. After this delay, half of the subjects gained insight into the hidden task structure ("solvers," S), whereas the other half did not ("nonsolvers," NS). Already at training, solvers and nonsolvers differed in their cerebral responses associated with implicit learning. In future solvers, responses were observed in the superior frontal sulcus, posterior parietal cortex, and the insula, three areas mediating controlled processes and supporting early learning and novice performance. In contrast, implicit learning was related to significant responses in the hippocampus in nonsolvers. Moreover, the hippocampus was functionally coupled with the basal ganglia in nonsolvers and with the superior frontal sulcus in solvers, thus potentially biasing participants' strategy towards implicit or controlled processes of memory encoding, respectively. Furthermore, in solvers but not in nonsolvers, response patterns were further transformed overnight, with enhanced responses in ventral medial prefrontal cortex, an area previously implicated in the consolidation of declarative memory. During retest in solvers, before they gain insight into the hidden rule, significant responses were observed in the same medial prefrontal area. After insight, a distributed set of parietal and frontal areas is recruited among which information concerning the hidden rule can be shared in a so-called global workspace. [less ▲]Detailed reference viewed: 59 (8 ULg)
Functional neuroimaging in sleep, sleep deprivation, and sleep disorders.
Desseilles, Martin ; Dang Vu, Thien Thanh ; Maquet, Pierre
in Chokroverty, Sudhansu; Montagna, Pasquale (Eds.) Handbook of Clinical Neurology, Sleep Disorders, Part I (2011)Detailed reference viewed: 56 (6 ULg)
Spontaneous neural activity during human non-rapid eye movement sleep.
Mascetti, Laura ; Foret, Ariane ; Shaffii, Anahita et al
in Progress in Brain Research (2011), 193
Recent neuroimaging studies characterized the neural correlates of slow waves and spindles during human non-rapid eye movement (NREM) sleep. They showed that significant activity was consistently ... [more ▼]
Recent neuroimaging studies characterized the neural correlates of slow waves and spindles during human non-rapid eye movement (NREM) sleep. They showed that significant activity was consistently associated with slow (> 140 muV) and delta waves (75-140 muV) during NREM sleep in several cortical areas including inferior frontal, medial prefrontal, precuneus, and posterior cingulate cortices. Unexpectedly, slow waves were also associated with transient responses in the pontine tegmentum and in the cerebellum. On the other hand, spindles were associated with a transient activity in the thalami, paralimbic areas (anterior cingulate and insular cortices), and superior temporal gyri. Moreover, slow spindles (11-13 Hz) were associated with increased activity in the superior frontal gyrus. In contrast, fast spindles (13-15 Hz) recruited a set of cortical regions involved in sensorimotor processing, as well as the mesial frontal cortex and hippocampus. These findings indicate that human NREM sleep is an active state during which brain activity is temporally organized by spontaneous oscillations (spindles and slow oscillation) in a regionally specific manner. The functional significance of these NREM sleep oscillations is currently interpreted in terms of synaptic homeostasis and memory consolidation. [less ▲]Detailed reference viewed: 49 (24 ULg)