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: 12 (2 ULg)
Locus-coeruleus activation in patients with major depression and suicidal ideations. Abstract book of the conference
Desseilles, Martin ; Phillips, Christophe ; et al
Conference (2011, June)Detailed reference viewed: 10 (0 ULg)
Effects of stress induction on functional brain connectivity in obsessive-compulsive disorder assessed by wavelet-based correlations. Abstract book of the conference
; Desseilles, Martin ; Maquet, Pierre et al
Conference (2011, April)Detailed reference viewed: 10 (1 ULg)
Functional connectivity of the resting brain in obsessive compulsive disorder. Abstract Book of the conference
; Desseilles, Martin ; Maquet, Pierre et al
Conference (2011, March 26)Detailed reference viewed: 12 (0 ULg)
Functional connectivity of the resting brain in obsessive compulsive disorder. Abstract Book of the conference.
; Desseilles, Martin ; Maquet, Pierre et al
Conference (2011, February)Detailed reference viewed: 8 (0 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: 46 (12 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: 60 (26 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: 27 (13 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: 110 (35 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: 32 (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: 35 (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: 66 (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: 92 (15 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: 113 (5 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: 118 (18 ULg)