Rosa M. Salas

Alpha EEG coherence in different brain states: an electrophysiological index of the arousal level in human subjects

The functional relationships between the brain areas supposedly involved in the generation of the alpha activity were quantified by means of INTRA- and INTER-hemispheric coherences during different arousal states (relaxed wakefulness, drowsiness at sleep onset, and rapid eye movement sleep) where such an activity can be clearly detectable in the human EEG. A significant decrease in the fronto-occipital as well as in the inter-frontal coherence values in the alpha range was observed with the falling of the vigilance level, which suggests that the brain mechanisms underlying these coherences are state dependent. Making fronto-frontal coherence values in the alpha frequency band useful indexes to discern between brain functional states characterized by a different arousal level.

Spectral Structure and Brain Mapping of Human Alpha Activities in Different Arousal States

In a study with 10 young, healthy subjects, alpha activities were studied in three different arousal states: eyes closed in relaxed wakefulness (EC), drowsiness (DR), and REM sleep. The alpha band was divided into three subdivisions (slow, middle, and fast) which were analyzed separately for each state. The results showed a different spectral composition of alpha band according to the physiological state of the subject. Slow alpha seemed to be independent of the arousal state, whereas middle alpha showed a difference between REM and the other states. The fast-alpha subdivision appears mainly as a waking EEG component because of the increased power displayed only in wakefulness and lower and highly stable values for DR and REM. Scalp distribution of alpha activity was slightly different in each state: from occipital to central regions in EC, this topography was extended to fronto-polar areas in DR, with a contribution from occipital to frontal regions in REM sleep. These results provide evidence for an alpha power modulation and a different scalp distribution according to the cerebral arousal state.

Brain spatial microstates of human spontaneous alpha activity in relaxed wakefulness, drowsiness period, and REM sleep.

Spontaneous alpha activity clearly present in relaxed wakefulness with closed eyes, drowsiness period at sleep onset, and REM sleep was studied with spatial segmentation methods in order to determine if the brain activation state would be modulating the alpha spatial microstates composition and duration. These methods of spatial segmentation show some advantages: i) they extract topographic descriptors independent of the chosen reference (reference-free methods), and ii) they achieve spatial data reduction that are more data-driven than dipole source analysis. The results obtained with this study revealed that alpha activity presented a different spatio-temporal pattern of brain electric fields in each arousal state used in this study. These differences were reflected in a) the mean duration of alpha microstates (longer in relaxed wakefulness than in drowsy period and REM sleep), b) the number of brain microstates contained in one second (drowsiness showed more different microstates than did relaxed wakefulness and REM state), and c) the number of different classes (more abundant in drowsiness than in the rest of brain states). If we assume that longer segments of stable brain activity imply a lesser amount of different information to process (as reflected by a higher stability of the brain generator), whereas shorter segments imply a higher number of brain microstates caused by more different steps of information processing, it is possible that the alpha activity appearing in the sleep onset period could be indexing the hypnagogic imagery self-generated by the sleeping brain, and a phasic event in the case of REM sleep. Probably, REM-alpha bursts are associated with a brain microstate change (such as sleep spindles), as demonstrated by its phasic intrusion in a desynchronized background of brain activity. On the other hand, alpha rhythm could be the “baseline” of brain activity when the sensory inputs are minimum and the state is relaxed wakefulness.

Alpha power modulation during periods with rapid oculomotor activity in human REM sleep

Alpha activity attenuation (blocking) over occipital regions is an electrophysiological index of cortical activation associated with visual attention and waking mental imagery. The present work focused on exploring whether the human REM background alpha activity was modulated, attending to tonic- (without rapid oculomotor activity) and phasic-REM periods (with a prominent burst of REMs). The obtained results revealed that the background alpha activity showed a decreased spectral power over occipital brain regions during phasic-REM in comparison with tonic-REM periods. This result suggests an active visual processing caused by the complex mental imagery generated during periods of oculomotor activity in human REM sleep.

State-modulation of cortico-cortical connections underlying normal EEG alpha variants

Normal electroencephalographic (EEG) alpha variants appear during relaxed wakefulness with closed eyes, drowsiness period at sleep onset, and rapid eye movement (REM) sleep in bursts without arousal signals. Previous results revealed that fronto-occipital and fronto-frontal alpha coherences became weaker from wakefulness to drowsiness, and finally to REM sleep. The present work was aimed at determining whether a generalized or a unidirectional deactivation of the long fronto-occipital fasciculi, previously proposed to be involved in the alpha rhythm generation, could explain the above-mentioned results. Polynomial regression analyses, applied to the change of alpha coherence with distance along the antero-posterior axis, suggested that the anterior and posterior local circuits show a similar level of activation in all brain states. Bivariate partial correlation analyses between local alpha coherences revealed that such local circuits maintain a reciprocal dependency during wakefulness, but unidirectional during drowsiness (anterior-to-posterior, A-P) and REM sleep (posterior-to-anterior, P-A). From these findings, both anterior and posterior cortical structures are suggested as being involved in the generation of the three alpha variants. If the implication of a double cortical generation source (anterior and posterior) of alpha variants is assumed, these two generators seem to maintain a mutual inter-dependency during wakefulness, whereas during the transition to human sleep, the anterior areas work quite independently of the posterior regions. Finally, the occipital structures may be the driving force for the REM-alpha bursts generation, since involvement of frontal regions demonstrated a high dependence on the posterior neural circuits in the genesis of this sleep event.

Effects of waking-auditory stimulation on human sleep architecture

Evidence suggests that sleep architecture is affected by endogenous homeostatic mechanisms as well as by behavioral and sensory demands during the prior wakefulness. Regarding the auditory system, sensory deprivation has shown to drastically modify the sleep structure, stressing the relevance of such sensory system for sleep organization. Changes in sleep architecture following prolonged auditory stimulation during prior wakefulness would provide additional support to this hypothesis. In the present study, auditory stimulation was administered over a 6 h period prior to sleep. Sleep parameters obtained from visual scoring were quantified across the total sleep period, for each sleep cycle, and for the two halves of the night, separately. Results showed that 6 h of waking-auditory stimulation were followed by an increase in the duration of slow wave sleep, a shortening of the latency between slow wave sleep periods, and a longer sleep onset latency as compared with the baseline night. In contrast, REM sleep parameters were unaffected by the pre-sleep auditory stimulation. These results indicate that sleep architecture depends on auditory demands during the prior wakefulness, suggesting that the local neural activation underlying auditory stimulation may trigger brain control mechanisms selectively involved in both the slow wave sleep maintenance and organization.

Efecto del estado de activación cerebral sobre la memoria sensorial auditiva

espanolDesde el marco de la psicologia del procesamiento de la informacion el presente trabajo pretende, en primer lugar, examinar las caracteristicas definitorias de la memoria sensorial asi como las funciones que dicha forma de memoria puede desempenar en el procesamiento cognitivo. En segundo lugar, este texto ofrecera una revision critica de aquellos trabajos que han abordado el estudio de la memoria sensorial auditiva durante otros estados de activacion cerebral diferentes al de vigilia con el fin de analizar la influencia que ejercen estados como el sueno sobre los resultados de las operaciones subyacentes a dicha forma de memoria. Todo ello sera expuesto, primero, desde un nivel de analisis conductual, basandonos muy especialmente en el modelo de procesamiento de la informacion propuesto por Cowan (1988), para posteriormente adentrarnos en un nivel electrofisiologico. desde el cual se presentaran los datos mas relevantes acerca de la representacion neural de la memoria sensorial de acuerdo con el modelo neurocognitivo de Naadanen (1990). EnglishThe main goal of the present work within the framework of information processing psychology is, in the first place, to examine distinguishing features of sensory memory as well as the ways in which it could be used in cognitive processing. In the second place, this text is a critical review of the studies dealing with the sensory memory during other arousal states different from waking in order to analyse the influence exerted by brain states such as sleep on the results of processes underlying sensory memory. All of this will be expounded, first, from a behavioural analysis level, based especially on the information processing model proposed by Cowan (1988), and second, from an electrophysiological level, from which we will offer the most relevant data on the neural representation of sensory memory according to the neurocognitive model of Naatanen (1990).