Rosa M. Salas’s research while affiliated with University of Seville and other places

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Publications (16)


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

February 1999

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38 Reads

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79 Citations

Neuropsychobiology

José Luis Cantero

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Rosa M. Salas

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

February 1999

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64 Reads

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75 Citations

Brain Topography

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.



PROPIEDADES ELECTROFISIOLOGICAS DE LASVARIANTES NORMALES DE ACTIVIDAD ALFA EN ELCONTINUO VIGILIA-SUEÑO

2 Reads

The study of cerebral rhythms ispossible by analyzing its electrophysiological features with quantitative EEG techniques. In the cases in which the same activity appears spontaneously in different brain states, the study of its electrophysiological features would help to establish functional differences associated to each of these states. The present work reviews those studies that determined the electrophysiological features of the different normal variants of alpha activity appearing in the wake-sleep continuous, more specifically, during relaxed wakefulness, drowsiness and REM sleep. The results indicate that each normal variant of alpha activity, in spite of showing a similar topographical distribution in each of the brain states, shows differentfeatures in relation to its spectral composition, functional relationships among cortical regions, and underlying brain micro-states. According to these experimental findings, each alpha variant would playa different brain function. Thus, the wakefulness alpha rhythm seems to reflect a maximum neuronal synchronization due to the absence of visual processing, whereas alpha activity during the drowsiness period would be associated with the brain processing of hypnagogic imagery happening at sleep onset. However, spontaneous alpha bursts ofREM sleep would reflect the contact between the.sleeping brain and the environment. Thiselectrophysiological characterization has its most direct applied field in the design of algorithms to stage sleep automatically, as well as in the diagnosis and evaluation of clinical entities in which the brain generator mechanisms ofthis activity could be affected through the wake-sleep continuous.


Figura 3. Perceptron multicapa.  
Figura 4. Gráfico de líneas para evaluar el ajuste a la serie empírica.  
Hojas de cálculo para la simulación de redes de neuronas artificiales (RNA)
  • Article
  • Full-text available

923 Reads

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4 Citations

Antonio Ramón García

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José Luis Cantero

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La utilización de Redes de Neuronas Artificiales (RNA) en problemas de predicción de series de tiempo, clasificación y reconocimiento de patrones ha aumentado considerablemente en los últimos años. Programas informáticos de matemáticas de propósito general tales como MATLAB, MATHCAD y aplicaciones estadísticas como SPSS y S-PLUS incorporan herramientas que permiten implementar RNAs. A esta oferta de software hay que añadir programas específicos como NeuralWare, EasyNN o Neuron. Desde un punto de vista educativo, el acceso de los estudiantes a estos programas puede ser difícil dado que no están pensados como herramientas didácticas. Por otro lado, las hojas de cálculo como Excel y Gnumeric incorporan utilidades que permiten implementar RNAs y son de fácil acceso para los estudiantes. El objetivo de este trabajo es proporcionar un pequeño tutorial sobre la utilización de Excel para implementar una RNA que nos permita ajustar los valores de una serie de tiempo correspondiente a actividad cerebral alfa y que permita al alumno entender el funcionamiento de estos dispositivos de cálculo

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Efecto del estado de activación cerebral sobre la memoria sensorial auditiva

30 Reads

En: Cognitiva Madrid 2000, v. 12, n. 1 ; p. 7-35 Se pretende, en primer lugar, examinar las características definitorias de la memoria sensorial así como las funciones que dicha forma de memoria puede desempeñar en el procesamiento cognitivo. En segundo lugar, se ofrece una revisión crítica de aquellos trabajos que han abordado el estudio de la memoria sensorial auditiva durante otros estados de activación cerebral diferentes al de vigilia con el fin de analizar la influencia que ejercer estados como el sueño sobre los resultados de las operaciones subyacentes a dicha forma de memoria. Todo ello se expone, primero, desde un nivel de análisis conductual, basándose muy especialmente en el modelo de procesamiento de la información propuesto por Cowan (1988), para posteriormente adentrarse en un nivel electrofisiológico, desde el cual se presentan los datos más relevantes acerca de la representación neural de la memoria sensorial de acuerdo con el modelo neurocognitivo de Näätänen (1990)


Citations (11)


... Local gamma oscillations are higher during REM sleep compared to NREM sleep [21][22][23]25]. On the other hand, the extent of interactions between different cortices at the gamma frequency band can be explored through a mathematical function called 'coherence', which reflects the 'strength' of functional interactions between cortical areas [26][27][28]. Gamma coherence between distant areas has been proposed as a neural correlate of conscious perception and self-awareness [29][30][31][32][33]. In this regard, coherence in the gamma frequency band is lost during anesthesiainduced unconsciousness [34][35][36], and is severely altered in psychiatric disorders [37,38]. ...

Reference:

Absence of EEG gamma coherence in a local activated cortical state: a conserved trait of REM sleep
Valor clínico de la coherencia EEG como índice electrofisiológico de conectividad córtico­cortical durante el sueño
  • Citing Article
  • January 2000

Revista de Neurología

... NNS was used to identify how the different water variables linked to Chl-a concentration produce changes. The construction of NNS was made following García (2002) using Microsoft Excel® software. The NNS was set up with input of seven variables (Fig. 2, Table 2), a hidden layer of 10 neurons, and one exit neuron. ...

Hojas de cálculo para la simulación de redes de neuronas artificiales (RNA)

... Furthermore, abnormalities in α oscillations in the frontal cortex during WAKE and NREM sleep may result from abnormal transmission of neural signals within corticobasal ganglia circuits. 49 However, the mechanism of power changes in different frequency bands of cortical neurons remains unclear. It is anticipated that applying novel imaging techniques and multichannel EEG recordings will provide a better understanding of the intricate interplay between typical oscillatory and synchronized activities within the cortico-basal ganglia motor circuit and muscle. ...

Spectral Structure and Brain Mapping of Human Alpha Activities in Different Arousal States
  • Citing Article
  • February 1999

Neuropsychobiology

... Microstate analysis has been used in a wide range of studies, including resting state of the brain (Schiller et al., 2020), neuropsychiatric diseases (Nishida et al., 2013), sleepiness (Cantero et al., 1999), gender differences (Tomescu et al., 2018), and tasksbased brain activities (Seitzman et al., 2017;Hu et al., 2023). ...

Brain Spatial Microstates of Human Spontaneous Alpha Activity in Relaxed Wakefulness, Drowsiness Period, and REM Sleep
  • Citing Article
  • February 1999

Brain Topography

... In keeping with this, significant negative correlations between the visual activity index (defined by performing a quantitative analysis of dream content, also see [42]) and occipital alpha power have been demonstrated during REM's dream mentation in congenitally blind subjects [43]. This is largely in line with reduced or blocked alpha power over the occipital cortex, commonly associated with visual imagery in normally sighted people [44][45][46]. Strikingly, some congenitally blind subjects have also been able to represent the visual content of their dreams in accurate drawings, if somewhat less detailed and slightly more symbolic and archetypal, similar to those of sighted controls [42]. ...

Alpha power modulation during periods with rapid oculomotor activity in human REM sleep
  • Citing Article
  • July 1999

Neuroreport

... Based on EEG recordings, we estimated three classes of measures: (1) measures estimating spectral powerraw and normalized power spectra, median spectral frequency (MSF), spectral edge 90 (SEF90), and spectral edge 95 (SEF95), (2) measures estimating information content-spectral entropy, Kolmogorov-Chaitin complexity (K) and permutation entropy, and (3) measures estimating functional connectivity-symbolic mutualiInformation (SMI) and weighted symbolic mutual information (wSMI). Power spectrum density (PSD) was computed over the delta (1-4 Hz), theta (4-8 Hz) alpha (8-12 Hz), beta (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), gamma (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45) spectral bands, using the Welch spectrum approximation (segments = 512 ms, overlap = 400ms). Segment rejections were windowed using a Hanning window and zero-padded to 4096 samples. ...

Alpha EEG coherence in different brain states: An electrophysiological index of the arousal level in human subjects
  • Citing Article
  • September 1999

Neuroscience Letters

... According to research reports, significant differences in EEG features in different sleep stages, such as power spectrum features, nonlinear dynamics features, and functional connections (37)(38)(39). Cantero et al. pointed out that alpha wave power is an important feature of human REM sleep (40). Miskovic et al. found that in the whole sleep cycle, the change of entropy strongly depends on the time scale, and slow-wave sleep is characterized by the decrease of entropy in the short time scale and the increase of entropy in the long time scale (41). ...

Spectral Features of EEG Alpha Activity in Human REM Sleep: Two Variants with Different Functional Roles?
  • Citing Article
  • October 2000

Sleep

... Pineda (2005) suggested that the common base frequency range for both the motor (mu rhythm) and visual (alpha rhythm) cortex can provide communication between these areas of the cortex during complex perception tasks. Studies of other neural processes have revealed evidence of the functional connection of independent alpha networks (for example, during sleep: Cantero et al. 2000), but the features and sensitivity of the occipital alpha and central mu rhythms during observation of actions have yet to be studied. ...

State-modulation of cortico-cortical connections underlying normal EEG alpha variants
  • Citing Article
  • October 2000

Physiology & Behavior

... There is another type of less-known neurons that contribute to the accumulation and release of sleep pressure, and balance the homeostasis of waking and sleeping (Donlea et al. 2014). It has been presumed that environmental factors such as light, sound, and temperature can regulate sleep via these two mechanisms, but the details of these processes are not clear (Busza et al. 2007;Cantero et al. 2002;Dubruille and Emery 2008). ...

Effects of waking-auditory stimulation on human sleep architecture
  • Citing Article
  • February 2002

Behavioural Brain Research

... Although the alpha frequency band has been extensively studied in the literature, particularly in relation to physiological phenomena such as sleep, wakefulness, and various cognitive processes such as attention and memory (Cantero et al., 2002;Stipacek et al., 2003), few studies to date have examined its relationship with emotional regulation and processing. While lower alpha is involved in internalized attention (Aftanas and Golocheikine, 2001), upper alpha is involved in specific cognitive tasks and memory processes (Klimesch et al., 1997). ...

Human alpha oscillations in wakefulness, drowsiness period, and REM sleep: Different electroencephalographic phenomena within the alpha band
  • Citing Article
  • February 2002

Neurophysiologie Clinique