Jose L. Cantero

Reduction of Basal Forebrain Cholinergic System Parallels Cognitive Impairment in Patients at High Risk of Developing Alzheimer's Disease

Neuropathological studies suggest that the basal forebrain cholinergic system (BFCS) is affected in Alzheimers disease (AD), but there is no in vivo evidence of early damage to this system in subjects at high risk of developing AD. Here, we found that mild cognitive impairment (MCI) patients exhibited significant volume reduction of the nucleus basalis of Meynert (NbM) using recently developed probabilistic maps of the BFCS space. In addition, volumes of different magnocellular compartments varied significantly with regional gray matter atrophy in regions known to be affected by AD and were found to correlate with cognitive decline in MCI patients. Bilateral reductions of the horizontal nucleus of the diagonal band of Broca (Ch3) and frontal lobe (medial frontal, orbital, subcallosal gyrus, anterior cingulate, and middle frontal gyrus) were significantly associated with a global decline in cognitive status, whereas volume reduction of the posterior compartment of Ch4 (NbM) and temporal lobe (including hippocampus, entorhinal cortex, and amygdala) were associated with impaired delayed recall in MCI patients. These findings establish, for the first time, a link between degeneration of specific cholinergic compartments of the BFCS and cognitive-related deficits in subjects at high risk of developing AD.

Measuring directional coupling between EEG sources

Directional connectivity in the brain has been typically computed between scalp electroencephalographic (EEG) signals, neglecting the fact that correlations between scalp measurements are partly caused by electrical conduction through the head volume. Although recently proposed techniques are able to identify causality relationships between EEG sources rather than between recording sites, most of them need a priori assumptions about the cerebral regions involved in the EEG generation. We present a novel methodology based on multivariate autoregressive (MVAR) modeling and Independent Component Analysis (ICA) able to determine the temporal activation of the intracerebral EEG sources as well as their approximate locations. The direction of synaptic flow between these EEG sources is then estimated using the directed transfer function (DTF), and the significance of directional coupling strength evaluated with surrogated data. The reliability of this approach was assessed with simulations manipulating the number of data samples, the depth and orientation of the equivalent source dipoles, the presence of different noise sources, and the violation of the non-Gaussianity assumption inherent to the proposed technique. The simulations showed the superior accuracy of the proposed approach over other traditional techniques in most tested scenarios. Its validity was also evaluated analyzing the generation mechanisms of the EEG-alpha rhythm recorded from 20 volunteers under resting conditions. Results suggested that the major generation mechanism underlying EEG-alpha oscillations consists of a strong bidirectional feedback between thalamus and cuneus. The precuneus also seemed to actively participate in the generation of the alpha rhythm although it did not exert a significant causal influence neither on the thalamus nor on the cuneus. All together, these results suggest that the proposed methodology is a promising non-invasive approach for studying directional coupling between mutually interconnected neural populations.

Gamma EEG dynamics in neocortex and hippocampus during human wakefulness and sleep

Little is known about the neurophysiological mechanisms underlying the human sleep-wake cycle. Using intracranial electrodes in humans, we investigated changes in topographic distribution of gamma power and local- and long-range gamma EEG coherence in neocortex and hippocampus during different cerebral states. We report significantly greater variability in gamma power across cortical regions during wakefulness than during either slow wave or rapid eye movement (REM) sleep. In addition, local (within cortical regions) and long-range (between cortical regions) gamma coherence was significantly higher during wakefulness than during sleep, and functional gamma-range coupling between the neocortex and hippocampus was seen during wakefulness, but not during sleep. These findings demonstrate a functional link between different stages of conscious awareness and the level of coupling of gamma-band oscillations in the human brain.

Complex sound processing during human REM sleep by recovering information from long-term memory as revealed by the mismatch negativity (MMN)

Perceptual learning is thought to be the result of neural changes that take place over a period of several hours or days, allowing information to be transferred to long-term memory. Evidence suggests that contents of long-term memory may improve attentive and pre-attentive sensory processing. Therefore, it is plausible to hypothesize that learning-induced neural changes that develop during wakefulness could improve automatic information processing during human REM sleep. The MMN, an objective measure of the automatic change detection in auditory cortex, was used to evaluate long-term learning effects on pre-attentive processing during wakefulness and REM sleep. When subjects learned to discriminate two complex auditory patterns in wakefulness, an increase in the MMN was obtained in both wake and REM states. The automatic detection of the infrequent complex auditory pattern may therefore be improved in both brain states by reactivating information from long-term memory. These findings suggest that long-term learning-related neural changes are accessible during REM sleep as well.

Auditory information processing during human sleep as revealed by event-related brain potentials

The main goal of this review is to elucidate up to what extent pre-attentive auditory information processing is affected during human sleep. Evidence from event-related brain potential (ERP) studies indicates that auditory information processing is selectively affected, even at early phases, across the different stages of sleep-wakefulness continuum. According to these studies, 3 main conclusions are drawn: (1) the sleeping brain is able to automatically detect stimulus occurrence and trigger an orienting response towards that stimulus if its degree of novelty is large; (2) auditory stimuli are represented in the auditory system and maintained for a period of time in sensory memory, making the automatic-change detection during sleep possible; and (3) there are specific brain mechanisms (sleep-specific ERP components associated with the presence of vertex waves and K-complexes) by which information processing can be improved during non-rapid eye movement sleep. However, the remarkably affected amplitude and latency of the waking-ERPs during the different stages of sleep suggests deficits in the building and maintenance of a neural representation of the stimulus as well as in the process by which neural events lead to an orienting response toward such a stimulus. The deactivation of areas in the dorsolateral pre-frontal cortex during sleep contributing to the generation of these ERP components is hypothesized to be one of the main causes for the attenuated amplitude of these ERPs during human sleep.

Muscle Artifact Removal from Human Sleep EEG by Using Independent Component Analysis

Muscle artifacts are typically associated with sleep arousals and awakenings in normal and pathological sleep, contaminating EEG recordings and distorting quantitative EEG results. Most EEG correction techniques focus on ocular artifacts but little research has been done on removing muscle activity from sleep EEG recordings. The present study was aimed at assessing the performance of four independent component analysis (ICA) algorithms (AMUSE, SOBI, Infomax, and JADE) to separate myogenic activity from EEG during sleep, in order to determine the optimal method. AMUSE, Infomax, and SOBI performed significantly better than JADE at eliminating muscle artifacts over temporal regions, but AMUSE was independent of the signal-to-noise ratio over non-temporal regions and markedly faster than the remaining algorithms. AMUSE was further successful at separating muscle artifacts from spontaneous EEG arousals when applied on a real case during different sleep stages. The low computational cost of AMUSE, and its excellent performance with EEG arousals from different sleep stages supports this ICA algorithm as a valid choice to minimize the influence of muscle artifacts on human sleep EEG recordings.

The Cholinergic System in Mild Cognitive Impairment and Alzheimer's Disease: An In Vivo MRI and DTI study

Few studies have investigated in vivo changes of the cholinergic basal forebrain in Alzheimers disease (AD) and amnestic mild cognitive impairment (MCI), an at risk stage of AD. Even less is known about alterations of cortical projecting fiber tracts associated with basal forebrain atrophy. In this study, we determined regional atrophy within the basal forebrain in 21 patients with AD and 16 subjects with MCI compared to 20 healthy elderly subjects using deformation‐based morphometry of MRI scans. We assessed effects of basal forebrain atrophy on fiber tracts derived from high‐resolution diffusion tensor imaging (DTI) using tract‐based spatial statistics. We localized significant effects relative to a map of cholinergic nuclei in MRI standard space as determined from a postmortem brain. Patients with AD and MCI subjects showed reduced volumes in basal forebrain areas corresponding to anterior medial and lateral, intermediate and posterior nuclei of the Nucleus basalis of Meynert (NbM) as well as in the diagonal band of Broca nuclei (P < 0.01). Effects in MCI subjects were spatially more restricted than in AD, but occurred at similar locations. The volume of the right antero‐lateral NbM nucleus was correlated with intracortical projecting fiber tract integrity such as the corpus callosum, cingulate, and the superior longitudinal, inferior longitudinal, inferior fronto‐occipital, and uncinate fasciculus (P < 0.05, corrected for multiple comparisons). Our findings suggest that a multimodal MRI‐DTI approach is supportive to determine atrophy of cholinergic nuclei and its effect on intracortical projecting fiber tracts in AD. Hum Brain Mapp, 2010.

The mismatch negativity component reveals the sensory memory during REM sleep in humans

Auditory evoked potentials (AEPs) were recorded during presentation of stimuli of 1000 Hz (standard) and 2000 Hz (deviant) in trains of 10 tone bursts (one deviant per train) in the wake and rapid eye movement (REM) sleep states. The constant inter-stimulus interval (ISI) was 600 ms and the trains were separated by 3 s of silence. The deviant tone occurring at the train start elicited a mismatch negativity component (MMN) in both arousal states, displaying a peak latency between 100 and 150 ms post-stimulation at fronto-central areas. These results suggest the existence of an auditory memory trace (sensory memory) surviving for at least 3 s during REM sleep.

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.