Event-related potentials and ongoing oscillatory electroencephalogram (EEG) activity were measured while subjects performed a cued visual spatial attention task. They were instructed to shift their attention to either the left or right visual hemifield according to a cue, which could be valid or invalid. Thereafter, a peripheral target had to be evaluated. At posterior parietal brain areas early components of the event-related potential (P1 and N1) were higher when the cue had been valid compared with invalid. An anticipatory attention effect was found in EEG alpha magnitude at parieto-occipital electrode sites. Starting 200 ms before target onset alpha amplitudes were significantly stronger suppressed at sites contralateral to the attended visual hemifield than ipsilateral to it. In addition, phase coupling between prefrontal and posterior parietal electrode sites was calculated. It was found that prefrontal cortex shows stronger phase coupling with posterior sites that are contralateral to the attended hemifield than ipsilateral sites. The results suggest that a shift of attention selectively modulates excitability of the contralateral posterior parietal cortex and that this posterior modulation of alpha activity is controlled by prefrontal regions.

No abstract

In humans, some evidence suggests that there are two different types of spindles during sleep, which differ by their scalp topography and possibly some aspects of their regulation. To test for the existence of two different spindle types, we characterized the activity associated with slow (11-13 Hz) and fast (13-15 Hz) spindles, identified as discrete events during non-rapid eye movement sleep, in non-sleepdeprived human volunteers, using simultaneous electroencephalography and functional MRI. An activation pattern common to both spindle types involved the thalami, paralimbic areas (anterior cingulate and insular cortices), and superior temporal gyri. No thalamic difference was detected in the direct comparison between slow and fast spindles although some thalamic areas were preferentially activated in relation to either spindle type. Beyond the common activation pattern, the increases in cortical activity differed significantly between the two spindle types. Slow spindles were associated with increased activity in the superior frontal gyrus. In contrast, fast spindles recruited a set of cortical regions involved in sensorimotor processing, as well as the mesial frontal cortex and hippocampus. The recruitment of partially segregated cortical networks for slow and fast spindles further supports the existence of two spindle types during human non-rapid eye movement sleep, with potentially different functional significance.H uman sleep is associated with a profound modification of consciousness and the emergence of distinct sleep oscillations. In the early stages of non-rapid eye movement (NREM) sleep, electroencephalographic recordings show characteristic spindle oscillations. In humans, spindles consist of waxing-and-waning 11-to 15-Hz oscillations, lasting 0.5-3 sec. At the cellular level, spindles are associated with substantial neuronal activity. Spindles arise from cyclic inhibition of thalamo-cortical (TC) neurons by reticular thalamic neurons. Postinihibitory rebound spike bursts in TC cells entrain cortical populations in spindle oscillations (1). These neuronal mechanisms, which involve large TC populations, are thought to shape the processing of information during light NREM sleep and participate in the alteration of consciousness that characterizes this stage of sleep.Little is known on the cerebral correlates of human spindles. Early positron emission tomography studies reported a negative relationship between thalamic cerebral blood flow and the power spectrum in the spindle frequency band (2). However, the low temporal resolution of positron emission tomography did not allow for a fine-grained characterization of the cerebral correlates of human spindles. In addition, two kinds of spindles are described in humans. Slow spindles (Ͻ13 Hz) predominate over frontal, whereas fast spindles (Ͼ13 Hz) prevail over centro-parietal areas. The difference in spindle scalp topography is also reflected by profound functional differences. These two spindling activities differ by their circadian and homeostatic regul...

A growing body of evidence supports the active role of sleep for information reprocessing. Whereas past research focused mainly on the distinct rapid eye movement and slow-wave sleep, these results indicate that increased sleep stage 2 spindle activity is related to an increase in recall performance and, thus, may reflect memory consolidation.

Abstract■ Evidence from functional neuroimaging studies on resting state suggests that there are two distinct anticorrelated cortical systems that mediate conscious awareness: an "extrinsic" system that encompasses lateral fronto-parietal areas and has been linked with processes of external input (external awareness), and an "intrinsic" system which encompasses mainly medial brain areas and has been associated with internal processes (internal awareness). The aim of our study was to explore the neural correlates of resting state by providing behavioral and neuroimaging data from healthy volunteers. With no a priori assumptions, we first determined behaviorally the relationship between external and internal awareness in 31 subjects. We found a significant anticorrelation between external and internal awareness with a mean switching frequency of 0.05 Hz (range: 0.01-0.1 Hz). Interestingly, this frequency is similar to BOLD fMRI slow oscillations. We then evaluated 22 healthy volunteers in an fMRI paradigm looking for brain areas where BOLD activity correlated with "internal" and "external" scores. Activation of precuneus/posterior cingulate, anterior cingulate/mesiofrontal cortices, and parahippocampal areas ("intrinsic system") was linearly linked to intensity of internal awareness, whereas activation of lateral fronto-parietal cortices ("extrinsic system") was linearly associated with intensity of external awareness. ■

The hypothesis was tested of whether neurofeedback training (NFT)--applied in order to increase upper alpha but decrease theta power--is capable of increasing cognitive performance. A mental rotation task was performed before and after upper alpha and theta NFT. Only those subjects who were able to increase their upper alpha power (responders) performed better on mental rotations after NFT. Training success (extent of NFT-induced increase in upper alpha power) was positively correlated with the improvement in cognitive performance. Furthermore, the EEG of NFT responders showed a significant increase in reference upper alpha power (i.e. in a time interval preceding mental rotation). This is in line with studies showing that increased upper alpha power in a prestimulus (reference) interval is related to good cognitive performance.

Slow wave sleep (SWS) is associated with spontaneous brain oscillations that are thought to participate in sleep homeostasis and to support the processing of information related to the experiences of the previous awake period. At the cellular level, during SWS, a slow oscillation (<1 Hz) synchronizes firing patterns in large neuronal populations and is reflected on electroencephalography (EEG) recordings as large-amplitude, low-frequency waves. By using simultaneous EEG and event-related functional magnetic resonance imaging (fMRI), we characterized the transient changes in brain activity consistently associated with slow waves (>140 V) and delta waves (75-140 V) during SWS in 14 non-sleep-deprived normal human volunteers. Significant increases in activity were associated with these waves in several cortical areas, including the inferior frontal, medial prefrontal, precuneus, and posterior cingulate areas. Compared with baseline activity, slow waves are associated with significant activity in the parahippocampal gyrus, cerebellum, and brainstem, whereas delta waves are related to frontal responses. No decrease in activity was observed. This study demonstrates that SWS is not a state of brain quiescence, but rather is an active state during which brain activity is consistently synchronized to the slow oscillation in specific cerebral regions. The partial overlap between the response pattern related to SWS waves and the waking default mode network is consistent with the fascinating hypothesis that brain responses synchronized by the slow oscillation restore microwake-like activity patterns that facilitate neuronal interactions.fMRI ͉ neuroimaging ͉ sleep physiology ͉ slow oscillation D uring the deepest stage of nonrapid eye movement (NREM) sleep, also referred to as slow wave sleep (SWS) in humans (stage 3-4 of sleep), spontaneous brain activity is organized by specific physiological rhythms, the neural correlates of which have been described in animals (1). Unit recordings have shown that neuronal activity during SWS is characterized by a fundamental oscillation of membrane potential. This so-called ''slow oscillation'' (Ͻ1 Hz) is recorded in all major types of neocortical neurons during SWS and is composed of a depolarizing phase, associated with important neuronal firing (''up state''), followed by a hyperpolarizing phase during which cortical neurons remain silent for a few hundred milliseconds (''down state'') (2, 3). The slow oscillation occurs synchronously in large neuronal populations in such a way that it can be reflected on electroencephalography (EEG) recordings as large-amplitude, low-frequency waves (4).Delta rhythm (1-4 Hz) is another characteristic oscillation of NREM sleep. The neural underpinnings of delta rhythm remain uncertain, however. In the dorsal thalamus, a clock-like delta rhythm is generated by the interplay of two intrinsic membrane currents, although another delta rhythm survives complete thalamectomy, suggesting a cortical origin (1).In humans, a slow oscillation was identified on s...

After encoding, memory traces are initially fragile and have to be reinforced to become permanent. The initial steps of this process occur at a cellular level within minutes or hours. Besides this rapid synaptic consolidation, systems consolidation occurs within a time frame of days to years. For declarative memory, the latter is presumed to rely on an interaction between different brain regions, in particular the hippocampus and the medial prefrontal cortex (mPFC). Specifically, sleep has been proposed to provide a setting that supports such systems consolidation processes, leading to a transfer and perhaps transformation of memories. Using functional MRI, we show that postlearning sleep enhances hippocampal responses during recall of word pairs 48 h after learning, indicating intrahippocampal memory processing during sleep. At the same time, sleep induces a memory-related functional connectivity between the hippocampus and the mPFC. Six months after learning, memories activated the mPFC more strongly when they were encoded before sleep, showing that sleep leads to longlasting changes in the representation of memories on a systems level.fMRI ͉ hippocampus ͉ medial prefrontal cortex ͉ memory N ew memories must undergo a period of consolidation to become stable and immune to interference (1). Consolidation occurs in the form of molecular processes at individual synapses (2) but also in the form of systems consolidation, which is a reorganization of the memory trace within different brain systems (3)(4)(5). This is most obvious for declarative memory, where recall initially depends on the hippocampus, but after some time becomes hippocampus-independent (6-8). Instead, neocortical areas, especially the medial prefrontal cortex (mPFC), are assumed to take over its function (9,10). In a recent functional imaging study, Takashima et al. (11) showed that both regions display opposite activity over the course of 3 months; whereas the hippocampal contribution to memory recall decreases with time, the prefrontal one rises.During the last few years, an important contribution of sleep to memory consolidation has been revealed (12, 13). Sleep prevents forgetting and makes memories resistant to interference, especially when it closely follows learning (14, 15). In particular, animal research has shown that sleep provides the conditions for a hippocampal-neocortical dialogue and information transfer (16,17). Low levels of cholinergic neuromodulation disinhibit hippocampal-neocortical feedback synapses (18), and hippocampus and neocortex show synchronous activity during sleep (19). Together, these findings support the idea that sleep modifies the trace of a recently stored memory. In the present experiment, we tested this hypothesis using functional MRI (fMRI) to characterize brain activity related to free recall immediately, 48 h, and 6 months after learning a declarative memory task. The contribution of sleep to systems memory consolidation was tested by allowing subjects to sleep or by sleep depriving them during the first ...