Increased mesiotemporal delta activity characterizes virtual navigation in humans

Hippocampal theta or rhythmic slow activity (RSA) occurring during exploratory behaviors and rapid-eye-movement (REM) sleep is a characteristic and well-identifiable oscillatory rhythm in animals. In contrast, controversy surrounds the existence and electrophysiological correlates of this activity in humans. Some argue that the human hippocampal theta occurs in short and phasic bursts. On the contrary, our earlier studies provide evidence that REM-dependent mesiotemporal RSA is continuous like in animals but instead of the theta it falls in the delta frequency range. Here we used a virtual navigation task in 24 epilepsy patients implanted with foramen ovale electrodes. EEG was analyzed for 1-Hz wide frequency bins up to 10 Hz according to four conditions: resting, non-learning route-following, acquisition and recall. We found progressively increasing spectral power in frequency bins up the 4 Hz across these conditions. No spectral power increase relative to resting was revealed within the traditional theta band and above in any of the navigation conditions. Thus the affected frequency bins were below the theta band and were similar to those characterizing REM sleep in our previous studies providing further indication that it is delta rather than theta that should be regarded as a human analogue of the animal RSA

Modality effects in implicit artificial grammar learning: An EEG study

Recently, it has been proposed that sequence learning engages a combination of modality-specific operating networks and modality-independent computational principles. In the present study, we compared the behavioural and EEG outcomes of implicit artificial grammar learning in the visual vs. auditory modality. We controlled for the influence of surface characteristics of sequences (Associative Chunk Strength), thus focusing on the strictly structural aspects of sequence learning, and we adapted the paradigms to compensate for known frailties of the visual modality compared to audition (temporal presentation, fast presentation rate). The behavioural outcomes were similar across modalities. Favouring the idea of modality-specificity, ERPs in response to grammar violations differed in topography and latency (earlier and more anterior component in the visual modality), and ERPs in response to surface features emerged only in the auditory modality. In favour of modality-independence, we observed three common functional properties in the late ERPs of the two grammars: both were free of interactions between structural and surface influences, both were more extended in a grammaticality classification test than in a preference classification test, and both correlated positively and strongly with theta event-related-synchronization during baseline testing. Our findings support the idea of modality-specificity combined with modality-independence, and suggest that memory for visual vs. auditory sequences may largely contribute to cross-modal differences. (C) 2018 Elsevier B.V. All rights reserved.Max Planck Institute for Psycholinguistics; Donders Institute for Brain, Cognition and Behaviour; Fundacao para a Ciencia e Tecnologia [PTDC/PSI-PC0/110734/2009, UID/BIM/04773/2013, CBMR 1334, PEst-OE/EQB/1A0023/2013, UM/PSI/00050/2013

EEG oscillations during sleep and dream recall. State- or trait-like individual differences?

Dreaming represents a peculiar form of cognitive activity during sleep. On the basis of the well-known relationship between sleep and memory, there has been a growing interest in the predictive role of human brain activity during sleep on dream recall. Neuroimaging studies indicate that rapid eye movement (REM) sleep is characterized by limbic activation and prefrontal cortex deactivation. This pattern could explain the presence of emotional contents in dream reports. Furthermore, the morphoanatomical measures of amygdala and hippocampus predict some features of dream contents (bizarreness, vividness, and emotional load). More relevant for a general view of dreaming mechanisms, empirical data from neuropsychological and electroencephalographic (EEG) studies support the hypothesis that there is a sort of continuity between the neurophysiological mechanisms of encoding and retrieval of episodic memories across sleep and wakefulness. A notable overlap between the electrophysiological mechanisms underlying emotional memory formation and some peculiar EEG features of REM sleep has been suggested. In particular, theta (5–8 Hz) EEG oscillations on frontal regions in the pre-awakening sleep are predictive of dream recall, which parallels the predictive relation during wakefulness between theta activity and successful retrieval of episodic memory. Although some observations support an interpretation more in terms of an intraindividual than interindividual mechanism, the existing empirical evidence still precludes from definitely disentangling if this relation is explained by state- or trait-like differences

Measuring cortical connectivity in Alzheimer's disease as a brain neural network pathology: Toward clinical applications

Objectives: The objective was to review the literature on diffusion tensor imaging as well as resting-state functional magnetic resonance imaging and electroencephalography (EEG) to unveil neuroanatomical and neurophysiological substrates of Alzheimer’s disease (AD) as a brain neural network pathology affecting structural and functional cortical connectivity underlying human cognition. Methods: We reviewed papers registered in PubMed and other scientific repositories on the use of these techniques in amnesic mild cognitive impairment (MCI) and clinically mild AD dementia patients compared to cognitively intact elderly individuals (Controls). Results: Hundreds of peer-reviewed (cross-sectional and longitudinal) papers have shown in patients with MCI and mild AD compared to Controls (1) impairment of callosal (splenium), thalamic, and anterior–posterior white matter bundles; (2) reduced correlation of resting state blood oxygen level-dependent activity across several intrinsic brain circuits including default mode and attention-related networks; and (3) abnormal power and functional coupling of resting state cortical EEG rhythms. Clinical applications of these measures are still limited. Conclusions: Structural and functional (in vivo) cortical connectivity measures represent a reliable marker of cerebral reserve capacity and should be used to predict and monitor the evolution of AD and its relative impact on cognitive domains in pre-clinical, prodromal, and dementia stages of AD. (JINS, 2016, 22, 138–163

Mental sleep activity and disturbing dreams in the lifespan

Sleep significantly changes across the lifespan, and several studies underline its crucial role in cognitive functioning. Similarly, mental activity during sleep tends to covary with age. This review aims to analyze the characteristics of dreaming and disturbing dreams at dierent age brackets. On the one hand, dreams may be considered an expression of brain maturation and cognitive development, showing relations with memory and visuo-spatial abilities. Some investigations reveal that specific electrophysiological patterns, such as frontal theta oscillations, underlie dreams during sleep, as well as episodic memories in the waking state, both in young and older adults. On the other hand, considering the role of dreaming in emotional processing and regulation, the available literature suggests that mental sleep activity could have a beneficial role when stressful events occur at dierent age ranges. We highlight that nightmares and bad dreams might represent an attempt to cope the adverse events, and the degrees of cognitive-brain maturation could impact on these mechanisms across the lifespan. Future investigations are necessary to clarify these relations. Clinical protocols could be designed to improve cognitive functioning and emotional regulation by modifying the dream contents or the ability to recall/non-recall them

Functional Roles of Alpha-Band Phase Synchronization in Local and Large-Scale Cortical Networks

Alpha-frequency band (8–14 Hz) oscillations are among the most salient phenomena in human electroencephalography (EEG) recordings and yet their functional roles have remained unclear. Much of research on alpha oscillations in human EEG has focused on peri-stimulus amplitude dynamics, which phenomenologically support an idea of alpha oscillations being negatively correlated with local cortical excitability and having a role in the suppression of task-irrelevant neuronal processing. This kind of an inhibitory role for alpha oscillations is also supported by several functional magnetic resonance imaging and trans-cranial magnetic stimulation studies. Nevertheless, investigations of local and inter-areal alpha phase dynamics suggest that the alpha-frequency band rhythmicity may play a role also in active task-relevant neuronal processing. These data imply that inter-areal alpha phase synchronization could support attentional, executive, and contextual functions. In this review, we outline evidence supporting different views on the roles of alpha oscillations in cortical networks and unresolved issues that should be addressed to resolve or reconcile these apparently contrasting hypotheses

Characterizing Motor System to Improve Training Protocols Used in Brain-Machine Interfaces Based on Motor Imagery

Motor imagery (MI)-based brain-machine interface (BMI) is a technology under development that actively modifies users’ perception and cognition through mental tasks, so as to decode their intentions from their neural oscillations, and thereby bringing some kind of activation. So far, MI as control task in BMIs has been seen as a skill that must be acquired, but neither user conditions nor controlled learning conditions have been taken into account. As motor system is a complex mechanism trained along lifetime, and MI-based BMI attempts to decode motor intentions from neural oscillations in order to put a device into action, motor mechanisms should be considered when prototyping BMI systems. It is hypothesized that the best way to acquire MI skills is following the same rules humans obey to move around the world. On this basis, new training paradigms consisting of ecological environments, identification of control tasks according to the ecological environment, transparent mapping, and multisensory feedback are proposed in this chapter. These new MI training paradigms take advantages of previous knowledge of users and facilitate the generation of mental image due to the automatic development of sensory predictions and motor behavior patterns in the brain. Furthermore, the effectuation of MI as an actual movement would make users feel that their mental images are being executed, and the resulting sensory feedback may allow forward model readjusting the imaginary movement in course