Memory reactivation during rapid eye movement sleep promotes its generalization and integration in cortical stores.

STUDY OBJECTIVES: Memory reactivation appears to be a fundamental process in memory consolidation. In this study we tested the influence of memory reactivation during rapid eye movement (REM) sleep on memory performance and brain responses at retrieval in healthy human participants. PARTICIPANTS: Fifty-six healthy subjects (28 women and 28 men, age [mean ± standard deviation]: 21.6 ± 2.2 y) participated in this functional magnetic resonance imaging (fMRI) study. METHODS AND RESULTS: Auditory cues were associated with pictures of faces during their encoding. These memory cues delivered during REM sleep enhanced subsequent accurate recollections but also false recognitions. These results suggest that reactivated memories interacted with semantically related representations, and induced new creative associations, which subsequently reduced the distinction between new and previously encoded exemplars. Cues had no effect if presented during stage 2 sleep, or if they were not associated with faces during encoding. Functional magnetic resonance imaging revealed that following exposure to conditioned cues during REM sleep, responses to faces during retrieval were enhanced both in a visual area and in a cortical region of multisensory (auditory-visual) convergence. CONCLUSIONS: These results show that reactivating memories during REM sleep enhances cortical responses during retrieval, suggesting the integration of recent memories within cortical circuits, favoring the generalization and schematization of the information.

The impact of visual perceptual learning on sleep and local slow-wave initiation.

During non-rapid eye movement (NREM) sleep, a global decrease in synaptic strength associated with slow waves (SWs) would enhance signal-to-noise ratio of neural responses during subsequent wakefulness. To test this prediction, 32 human volunteers were trained to a coarse orientation discrimination task, in either the morning or evening. They were retested after 8 h of wakefulness or sleep, respectively. Performance was enhanced only after a night of sleep, in the absence of any change in the abundance of NREM SWs but in proportion to the number of SWs "initiated" in lateral occipital areas during posttraining NREM sleep. The sources of these waves overlapped with the lateral occipital complex, in which responses to the learned stimulus, as assessed by fMRI, were selectively increased the next morning. This response enhancement was proportional to rapid eye movement (REM) sleep duration. These results provide an example of local sleep in which local initiation of SWs during NREM sleep predicts later skill improvement and foreshadows locally enhanced neural signals the next day. In addition, REM sleep also promotes local learning-dependent activity, possibly by promoting synaptic plasticity.

Resting-state EEG study of comatose patients: a connectivity and frequency analysis to find differences between vegetative and minimally conscious states.

The aim of this study was to look for differences in the power spectra and in EEG connectivity measures between patients in the vegetative state (VS/UWS) and patients in the minimally conscious state (MCS). The EEG of 31 patients was recorded and analyzed. Power spectra were obtained using modern multitaper methods. Three connectivity measures (coherence, the imaginary part of coherency and the phase lag index) were computed. Of the 31 patients, 21 were diagnosed as MCS and 10 as VS/UWS using the Coma Recovery Scale-Revised (CRS-R). EEG power spectra revealed differences between the two conditions. The VS/UWS patients showed increased delta power but decreased alpha power compared with the MCS patients. Connectivity measures were correlated with the CRS-R diagnosis; patients in the VS/UWS had significantly lower connectivity than MCS patients in the theta and alpha bands. Standard EEG recorded in clinical conditions could be used as a tool to help the clinician in the diagnosis of disorders of consciousness.

Circadian preference modulates the neural substrate of conflict processing across the day.

Human morning and evening chronotypes differ in their preferred timing for sleep and wakefulness, as well as in optimal daytime periods to cope with cognitive challenges. Recent evidence suggests that these preferences are not a simple by-product of socio-professional timing constraints, but can be driven by inter-individual differences in the expression of circadian and homeostatic sleep-wake promoting signals. Chronotypes thus constitute a unique tool to access the interplay between those processes under normally entrained day-night conditions, and to investigate how they impinge onto higher cognitive control processes. Using functional magnetic resonance imaging (fMRI), we assessed the influence of chronotype and time-of-day on conflict processing-related cerebral activity throughout a normal waking day. Sixteen morning and 15 evening types were recorded at two individually adapted time points (1.5 versus 10.5 hours spent awake) while performing the Stroop paradigm. Results show that interference-related hemodynamic responses are maintained or even increased in evening types from the subjective morning to the subjective evening in a set of brain areas playing a pivotal role in successful inhibitory functioning, whereas they decreased in morning types under the same conditions. Furthermore, during the evening hours, activity in a posterior hypothalamic region putatively involved in sleep-wake regulation correlated in a chronotype-specific manner with slow wave activity at the beginning of the night, an index of accumulated homeostatic sleep pressure. These results shed light into the cerebral mechanisms underlying inter-individual differences of higher-order cognitive state maintenance under normally entrained day-night conditions.

fMRI artefact rejection and sleep scoring toolbox.

We started writing the "fMRI artefact rejection and sleep scoring toolbox", or "FAST", 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 hand-written 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

Homeostatic sleep pressure and responses to sustained attention in the suprachiasmatic area.

Throughout the day, cognitive performance is under the combined influence of circadian processes and homeostatic sleep pressure. Some people perform best in the morning, whereas others are more alert in the evening. These chronotypes provide a unique way to study the effects of sleep-wake regulation on the cerebral mechanisms supporting cognition. Using functional magnetic resonance imaging in extreme chronotypes, we found that maintaining attention in the evening was associated with higher activity in evening than morning chronotypes in a region of the locus coeruleus and in a suprachiasmatic area (SCA) including the circadian master clock. Activity in the SCA decreased with increasing homeostatic sleep pressure. This result shows the direct influence of the homeostatic and circadian interaction on the neural activity underpinning human behavior.

Rejection of pulse related artefact (PRA) from continuous electroencephalographic (EEG) time series recorded during functional magnetic resonance imaging (fMRI) using constraint independent component analysis (cICA).

Rejection of the pulse related artefact (PRA) from electroencephalographic (EEG) time series recorded simultaneously with fMRI data is difficult, particularly during NREM sleep because of the similarities between sleep slow waves and PRA, in both temporal and frequency domains and the need to work with non-averaged data. Here we introduce an algorithm based on constrained independent component analysis (cICA) for PRA removal. This method has several advantages: (1) automatic detection of the components corresponding to the PRA; (2) stability of the solution and (3) computational treatability. Using multichannel EEG recordings obtained in a 3 T MR scanner, with and without concomitant fMRI acquisition, we provide evidence for the sensitivity and specificity of the method in rejecting PRA in various sleep and waking conditions.