Timing in cognition and EEG brain dynamics: discreteness versus continuity

Abnormal Spatial and Temporal Overlap of Time-Varying Brain Functional Networks in Patients with Schizophrenia

Schizophrenia (SZ) is a complex psychiatric disorder with unclear etiology and pathological features. Neuroscientists are increasingly proposing that schizophrenia is an abnormality in the dynamic organization of brain networks. Previous studies have found that the dynamic brain networks of people with SZ are abnormal in both space and time. However, little is known about the interactions and overlaps between hubs of the brain underlying spatiotemporal dynamics. In this study, we aimed to investigate different patterns of spatial and temporal overlap of hubs between SZ patients and healthy individuals. Specifically, we obtained resting-state functional magnetic resonance imaging data from the public dataset for 43 SZ patients and 49 healthy individuals. We derived a representation of time-varying functional connectivity using the Jackknife Correlation (JC) method. We employed the Betweenness Centrality (BC) method to identify the hubs of the brain's functional connectivity network. We then applied measures of temporal overlap, spatial overlap, and hierarchical clustering to investigate differences in the organization of brain hubs between SZ patients and healthy controls. Our findings suggest significant differences between SZ patients and healthy controls at the whole-brain and subnetwork levels. Furthermore, spatial overlap and hierarchical clustering analysis showed that quasi-periodic patterns were disrupted in SZ patients. Analyses of temporal overlap revealed abnormal pairwise engagement preferences in the hubs of SZ patients. These results provide new insights into the dynamic characteristics of the network organization of the SZ brain.

The applied principles of EEG analysis methods in neuroscience and clinical neurology

Electroencephalography (EEG) is a non-invasive measurement method for brain activity. Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural signals, EEG has aroused much interest in scientific research and medical fields. This article reviews the types of EEG signals, multiple EEG signal analysis methods, and the application of relevant methods in the neuroscience field and for diagnosing neurological diseases. First, three types of EEG signals, including time-invariant EEG, accurate event-related EEG, and random event-related EEG, are introduced. Second, five main directions for the methods of EEG analysis, including power spectrum analysis, time-frequency analysis, connectivity analysis, source localization methods, and machine learning methods, are described in the main section, along with different sub-methods and effect evaluations for solving the same problem. Finally, the application scenarios of different EEG analysis methods are emphasized, and the advantages and disadvantages of similar methods are distinguished. This article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives, provide references for subsequent research, and summarize current issues and prospects for the future.

Procedure for extracting temporal structure embedded within psychophysical data

The idea that mental events unfold over time with an intrinsically paced regularity has a long history within experimental psychology, and it has gained traction from the actual measurement of brain rhythms evident in EEG signals recorded from the human brain and from direct recordings of action potentials and local field potentials within the nervous systems of nonhumans. The weak link in this idea, however, is the challenge of extracting signatures of this temporal structure from behavioral measures. Because there is nothing in the seamless stream of conscious awareness that belies rhythmic modulations in sensitivity or mental acuity, one must deploy inferential strategies for extracting evidence for the existence of temporal regularities in neural activity. We have devised a parametric procedure for analysis of temporal structure embedded in behaviorally measured data comprising durations. We confirm that this procedure, dubbed PATS, achieves comparable results to those obtained using spectral analysis, and that it outperforms conventional spectral analysis when analyzing human response time data containing just a few hundred data points per condition. PATS offers an efficient, sensitive means for bridging the gap between oscillations identified neurophysiologically and estimates of rhythmicity embedded within durations measured behaviorally.

Holistic temporal order judgment of tones requires top-down disentanglement

How temporal sequence gets organized is a central topic in cognitive processing. In a high-frequency time window of tens of milliseconds, the temporal order is reconstructed rather than mirroring the sequence of events objectively in physical time. Two separate phases or strategies, a holistic coding phase that groups successively presented events as a gestalt and a disentanglement phase that decodes the temporal order of discrete events from the gestalt representation, may presumably be involved in the perception of temporal order across different modalities. With a temporal order adaptation protocol of pure tones using glide adaptors, the present study demonstrated a dissociation between constant discriminability and shifted subjective simultaneity across different adaptor directions. While discriminability of temporal order was not adapted by glides, revealing a constant coding sensitivity of different asynchronies, the shift of subjective simultaneity indicated the recalibration of a top-down disentanglement of the holistic processing under the influence of glide adaptors. The results suggest a dual-phase holistic processing in temporal order perception, supporting two separate cognitive strategies for event timing on the sub-second level.

Auditory Processing in Musicians, a Cross-Sectional Study, as a Basis for Auditory Training Optimization

Μusicians are reported to have enhanced auditory processing. This study aimed to assess auditory perception in Greek musicians with respect to their musical specialization and to compare their auditory processing with that of non-musicians. Auditory processing elements evaluated were speech recognition in babble, rhythmic advantage in speech recognition, short-term working memory, temporal resolution, and frequency discrimination threshold detection. All groups were of 12 participants. Three distinct experimental groups tested included western classical musicians, Byzantine chanters, and percussionists. The control group consisted of 12 non-musicians. The results revealed: (i) a rhythmic advantage for word recognition in noise for classical musicians (M = 12.42) compared to Byzantine musicians (M = 9.83), as well as for musicians compared to non-musicians (U = 120.50, p = 0.019), (ii) better frequency discrimination threshold of Byzantine musicians (M = 3.17, p = 0.002) compared to the other two musicians' group for the 2000 Hz region, (iii) statistically significant better working memory for musicians (U = 123.00, p = 0.025) compared to non-musicians. Musical training enhances elements of auditory processing and may be used as an additional rehabilitation approach during auditory training, focusing on specific types of music for specific auditory processing deficits.

Patients with Disorders of Consciousness: Are They Nonconscious, Unconscious, or Subconscious? Expanding the Discussion

Unprecedented advancements in the diagnosis and treatment of patients with disorders of consciousness (DoC) have given rise to ethical questions about how to recognize and respect autonomy and a sense of agency of the personhood when those capacities are themselves disordered, as they typically are in patients with DoC. At the intersection of these questions rests the distinction between consciousness and unconsciousness. Indeed, evaluations of consciousness levels and capacity for recovery have a significant impact on decisions regarding whether to discontinue or prolong life-sustaining therapy for DoC patients. However, in the unconsciousness domain, there is the confusing array of terms that are regularly used interchangeably, making it quite challenging to comprehend what unconsciousness is and how it might be empirically grounded. In this opinion paper, we will provide a brief overview of the state of the field of unconsciousness and show how a rapidly evolving electroencephalogram (EEG) neuroimaging technique may offer empirical, theoretical, and practical tools to approach unconsciousness and to improve our ability to distinguish consciousness from unconsciousness and also nonconsciousness with greater precision, particularly in cases that are borderline (as is typical in patients with DoC). Furthermore, we will provide a clear description of three distant notions of (un)consciousness (unconsciousness, nonconsciousness, and subconsciousness) and discuss how they relate to the experiential selfhood which is essential for comprehending the moral significance of what makes life worth living.

The temporal dynamics of Large-Scale brain network changes in disorders of consciousness: A Microstate-Based study

BACKGROUND AND OBJECTIVES

The resting-state brain is composed of several discrete networks, which remain stable for 10-100 ms. These functional microstates are considered the building blocks of spontaneous consciousness. Electroencephalography (EEG) microstate analysis may provide insight into the altered brain dynamics underlying consciousness recovery in patients with disorders of consciousness (DOC). We aimed to analyze microstates in the resting-state EEG source space in patients with DOC, the relationship between state-specific features and consciousness levels, and the corresponding patterns of microstates and functional networks.

METHODS

We obtained resting-state EEG data from 84 patients with DOC (27 in a minimally conscious state [MCS] and 57 in a vegetative state [VS] or with unresponsive wakefulness syndrome). We conducted a microstate analysis of the resting-state (EEG) source space and developed a state-transition analysis protocol for patients with DOC.

RESULTS

We identified seven microstates with distinct spatial distributions of cortical activation. Multivariate pattern analyses revealed that different functional connectivity patterns were associated with source-level microstates. There were significant differences in the microstate properties, including spatial activation patterns, temporal dynamics, state shifts, and connectivity construction, between the MCS and VS groups.

DISCUSSION

Our findings suggest that consciousness depends on complex dynamics within the brain and may originate from the anterior cortex.

Evolutionary Advantages of Stimulus-Driven EEG Phase Transitions in the Upper Cortical Layers

Spatio-temporal brain activity monitored by EEG recordings in humans and other mammals has identified beta/gamma oscillations (20-80 Hz), which are self-organized into spatio-temporal structures recurring at theta/alpha rates (4-12 Hz). These structures have statistically significant correlations with sensory stimuli and reinforcement contingencies perceived by the subject. The repeated collapse of self-organized structures at theta/alpha rates generates laterally propagating phase gradients (phase cones), ignited at some specific location of the cortical sheet. Phase cones have been interpreted as neural signatures of transient perceptual experiences according to the cinematic theory of brain dynamics. The rapid expansion of essentially isotropic phase cones is consistent with the propagation of perceptual broadcasts postulated by Global Workspace Theory (GWT). What is the evolutionary advantage of brains operating with repeatedly collapsing dynamics? This question is answered using thermodynamic concepts. According to neuropercolation theory, waking brains are described as non-equilibrium thermodynamic systems operating at the edge of criticality, undergoing repeated phase transitions. This work analyzes the role of long-range axonal connections and metabolic processes in the regulation of critical brain dynamics. Historically, the near 10 Hz domain has been associated with conscious sensory integration, cortical "ignitions" linked to conscious visual perception, and conscious experiences. We can therefore combine a very large body of experimental evidence and theory, including graph theory, neuropercolation, and GWT. This cortical operating style may optimize a tradeoff between rapid adaptation to novelty vs. stable and widespread self-organization, therefore resulting in significant Darwinian benefits.

Functional Complex Networks Based on Operational Architectonics: Application on Electroencephalography-Brain-computer Interface for Imagined Speech

A new method for analyzing brain complex dynamics and states is presented. This method constructs functional brain graphs and is comprised of two pylons: (a) Operational architectonics (OA) concept of brain and mind functioning. (b) Network neuroscience. In particular, the algorithm utilizes OA framework for a non-parametric segmentation of EEGs, which leads to the identification of change points, namely abrupt jumps in EEG amplitude, called Rapid Transition Processes (RTPs). Subsequently, the time coordinates of RTPs are used for the generation of undirected weighted complex networks fulfilling a scale-free topology criterion, from which various network metrics of brain connectivity are estimated. These metrics form feature vectors, which can be used in machine learning algorithms for classification and/or prediction. The method is tested in classification problems on an EEG-based BCI data set, acquired from individuals during imagery pronunciation tasks of various words/vowels. The classification results, based on a Naïve Bayes classifier, show that the overall accuracies were found to be above chance level in all tested cases. This method was also compared with other state-of-the-art computational approaches commonly used for functional network generation, exhibiting competitive performance. The method can be useful to neuroscientists wishing to enhance their repository of brain research algorithms.

Time and time again: a multi-scale hierarchical framework for time-consciousness and timing of cognition

Temporality and the feeling of ‘now’ is a fundamental property of consciousness. Different conceptualizations of time-consciousness have argued that both the content of our experiences and the representations of those experiences evolve in time, or neither have temporal extension, or only content does. Accounting for these different positions, we propose a nested hierarchical model of multiple timescales that accounts for findings on timing of cognition and phenomenology of temporal experience. This framework hierarchically combines the three major philosophical positions on time-consciousness (i.e. cinematic, extensional and retentional) and presents a common basis for temporal experience. We detail the properties of these hierarchical levels and speculate how they could coexist mechanistically. We also place several findings on timing and temporal experience at different levels in this hierarchy and show how they can be brought together. Finally, the framework is used to derive novel predictions for both timing of our experiences and time perception. The theoretical framework offers a novel dynamic space that can bring together sub-fields of cognitive science like perception, attention, action and consciousness research in understanding and describing our experiences both in and of time.

A guideline for linking brain wave findings to the various aspects of discrete perception

Brain waves, determined by electrical and magnetic brain recordings (e.g., EEG and MEG), and fluctuating behavioral responses, determined by response time or accuracy measures, are frequently taken to support discrete perception. For example, it has been proposed that humans experience only one conscious percept per brain wave (e.g., during one alpha cycle). However, the proposed link between brain waves and discrete perception is typically rather vague. More importantly, there are many models and aspects of discrete perception and it is often not apparent in what theoretical framework brain wave findings are interpreted and to what specific aspects of discrete perception they relate. Here, we review different approaches to discrete perception and highlight issues with particular interpretations. We then discuss how certain findings on brain waves may relate to certain aspects of discrete perception. The main purpose of this meta‐contribution is to give a short overview of discrete models of perception and to illustrate the need to make explicit what aspects of discrete theories are addressed by what aspects of brain wave findings.

Temporal twilight zone and beyond: Timing mechanisms in consciously delayed actions

Precise timing is essential for many kinds of human behavior. When a fastest response is not required, movements are initiated at the appropriate time requiring an anticipatory temporal component. Temporal mechanisms for movements with such an anticipatory component are not yet sufficiently understood; in particular, it is not known whether on the operational level for delayed movements distinct time windows are used or whether anticipatory control is characterized by continuous temporal processing. With a modified reaction-time paradigm, we asked participants to act with predefined time delays between 400 and 5000 ms; after each individual trial, a numerical feedback was provided which allowed correction of the response time for each next trial. Visual stimuli (Experiment 1) and auditory stimuli (Experiment 2) were used. In the statistical analyses, piecewise linear models and exponential decay models for the response variability of different delay times were compared. These analyses favored piecewise linear models; a decreasing variability with increasing delay of voluntary controlled actions was observed up to ~1 s, followed by close to constant variability beyond this delay. We suggest that precise temporal control of voluntary delayed movements is reached only after a "temporal twilight zone" of ~1 s, which apparently marks a temporal border between two different timing mechanisms.

On the Hierarchical Organization of Oscillatory Assemblies: Layered Superimposition and a Global Bioelectric Framework

Bioelectric oscillations occur throughout the nervous system of nearly all animals, revealed to play an important role in various aspects of cognitive activity such as information processing and feature binding. Modern research into this dynamic and intrinsic bioelectric activity of neural cells continues to raise questions regarding their role in consciousness and cognition. In this theoretical article, we assert a novel interpretation of the hierarchical nature of "brain waves" by identifying that the superposition of multiple oscillations varying in frequency corresponds to the superimposing of the contents of consciousness and cognition. In order to describe this isomorphism, we present a layered model of the global functional oscillations of various frequencies which act as a part of a unified metastable continuum described by the Operational Architectonics theory and suggested to be responsible for the emergence of the phenomenal mind. We detail the purposes, functions, and origins of each layer while proposing our main theory that the superimposition of these oscillatory layers mirrors the superimposition of the components of the integrated phenomenal experience as well as of cognition. In contrast to the traditional view that localizations of high and low-frequency activity are spatially distinct, many authors have suggested a hierarchical nature to oscillations. Our theoretical interpretation is founded in four layers which correlate not only in frequency but in evolutionary development. As other authors have done, we explore how these layers correlate to the phenomenology of human experience. Special importance is placed on the most basal layer of slow oscillations in coordinating and grouping all of the other layers. By detailing the isomorphism between the phenomenal and physiologic aspects of how lower frequency layers provide a foundation for higher frequency layers to be organized upon, we provide a further means to elucidate physiological and cognitive mechanisms of mind and for the well-researched outcomes of certain voluntary breathing patterns and meditative practices which modulate the mind and have therapeutic effects for psychiatric and other disorders.

Connective Core Structures in Cognitive Networks: the Role of Hubs

Complex network analysis applied to the resting brain has shown that sets of highly interconnected networks with coherent activity may support a default mode of brain function within a global workspace. Perceptual processing of environmental stimuli induces architectural changes in network topology with higher specialized modules. Evidence shows that, during cognitive tasks, network topology is reconfigured and information is broadcast from modular processors to a connective core, promoting efficient information integration. In this study, we explored how the brain adapts its effective connectivity within the connective core and across behavioral states. We used complex network metrics to identify hubs and proposed a method of classification based on the effective connectivity patterns of information flow. Finally, we interpreted the role of the connective core and each type of hub on the network effectiveness. We also calculated the complexity of electroencephalography microstate sequences across different tasks. We observed that divergent hubs contribute significantly to the network effectiveness and that part of this contribution persists across behavioral states, forming an invariant structure. Moreover, we found that a large quantity of multiple types of hubs may be associated with transitions of functional networks.

Scale-free behaviour and metastable brain-state switching driven by human cognition, an empirical approach

We developed a framework to study brain dynamics under cognition. In particular, we investigated the spatiotemporal properties of brain state switches under cognition. The lack of electroencephalography stationarity is exploited as one of the signatures of the metastability of brain states. We correlated power law exponents in the variables that we proposed to describe brain states, and dynamical properties of non-stationarities with cognitive conditions. This framework was successfully tested with three different datasets: a working memory dataset, an Alzheimer disease dataset, and an emotions dataset. We discuss the temporal organization of switches between states, providing evidence suggesting the need to reconsider the piecewise model, in which switches appear at discrete times. Instead, we propose a more dynamically rich view, in which besides the seemingly discrete switches, switches between neighbouring states occur all the time. These micro switches are not (physical) noise, as their properties are also affected by cognition.

Bridging Waves and Crucial Events in the Dynamics of the Brain

Earlier research work on the dynamics of the brain, disclosing the existence of crucial events, is revisited for the purpose of making the action of crucial events, responsible for the 1/f −noise in the brain, compatible with the wave-like nature of the brain processes. We review the relevant neurophysiological literature to make clear that crucial events are generated by criticality. We also show that although criticality generates a strong deviation from the regular wave-like behavior, under the form of Rapid Transition Processes, the brain dynamics also host crucial events in regions of nearly coherent oscillations, thereby making many crucial events virtually invisible. Furthermore, the anomalous scaling generated by the crucial events can be established with high accuracy by means of direct analysis of raw data, suggested by a theoretical perspective not requiring the crucial events to yield a visible physical effect. The latter follows from the fact that periodicity, waves and crucial events are the consequences of a spontaneous process of self-organization. We obtain three main results: (a) the important role of crucial events is confirmed and established with greater accuracy than previously; (b) we demonstrate the theoretical tools necessary to understand the joint action of crucial events and periodicity; (c) we argue that the results of this paper can be used to shed light on the nature of this important process of self-organization, thereby contributing to the understanding of cognition.

Metastable States of Multiscale Brain Networks Are Keys to Crack the Timing Problem

The dynamics of the environment where we live in and the interaction with it, predicting events, provided strong evolutionary pressures for the brain functioning to process temporal information and generate timed responses. As a result, the human brain is able to process temporal information and generate temporal patterns. Despite the clear importance of temporal processing to cognition, learning, communication and sensory, motor and emotional processing, the basal mechanisms of how animals differentiate simple intervals or provide timed responses are still under debate. The lesson we learned from the last decade of research in neuroscience is that functional and structural brain connectivity matter. Specifically, it has been accepted that the organization of the brain in interacting segregated networks enables its function. In this paper we delineate the route to a promising approach for investigating timing mechanisms. We illustrate how novel insight into timing mechanisms can come by investigating brain functioning as a multi-layer dynamical network whose clustered dynamics is bound to report the presence of metastable states. We anticipate that metastable dynamics underlie the real-time coordination necessary for the brain's dynamic functioning associated to time perception. This new point of view will help further clarifying mechanisms of neuropsychiatric disorders.

Mutual Information-Based Brain Network Analysis in Post-stroke Patients With Different Levels of Depression

Post-stroke depression (PSD) is the most common stroke-related emotional disorder, and it severely affects the recovery process. However, more than half cases are not correctly diagnosed. This study was designed to develop a new method to assess PSD using EEG signal to analyze the specificity of PSD patients' brain network. We have 107 subjects attended in this study (72 stabilized stroke survivors and 35 non-depressed healthy subjects). A Hamilton Depression Rating Scale (HDRS) score was determined for all subjects before EEG data collection. According to HDRS score, the 72 patients were divided into 3 groups: post-stroke non-depression (PSND), post-stroke mild depression (PSMD) and post-stroke depression (PSD). Mutual information (MI)-based graph theory was used to analyze brain network connectivity. Statistical analysis of brain network characteristics was made with a threshold of 10-30% of the strongest MIs. The results showed significant weakened interhemispheric connections and lower clustering coefficient in post-stroke depressed patients compared to those in healthy controls. Stroke patients showed a decreasing trend in the connection between the parietal-occipital and the frontal area as the severity of the depression increased. PSD subjects showed abnormal brain network connectivity and network features based on EEG, suggesting that MI-based brain network may have the potential to assess the severity of depression post stroke.

Transcranial alternating current stimulation modulates auditory temporal resolution in elderly people

Recent research provides evidence for a functional role of brain oscillations for perception. For example, auditory temporal resolution seems to be linked to individual gamma frequency of auditory cortex. Individual gamma frequency not only correlates with performance in between-channel gap detection tasks but can be modulated via auditory transcranial alternating current stimulation. Modulation of individual gamma frequency is accompanied by an improvement in gap detection performance. Aging changes electrophysiological frequency components and sensory processing mechanisms. Therefore, we conducted a study to investigate the link between individual gamma frequency and gap detection performance in elderly people using auditory transcranial alternating current stimulation. In a within-subject design, twelve participants were electrically stimulated with two individualized transcranial alternating current stimulation frequencies: 3 Hz above their individual gamma frequency (experimental condition) and 4 Hz below their individual gamma frequency (control condition), while they were performing a between-channel gap detection task. As expected, individual gamma frequencies correlated significantly with gap detection performance at baseline and in the experimental condition, transcranial alternating current stimulation modulated gap detection performance. In the control condition, stimulation did not modulate gap detection performance. In addition, in elderly, the effect of transcranial alternating current stimulation on auditory temporal resolution seems to be dependent on endogenous frequencies in auditory cortex: Elderlies with slower individual gamma frequencies and lower auditory temporal resolution profit from auditory transcranial alternating current stimulation and show increased gap detection performance during stimulation. Our results strongly suggest individualized transcranial alternating current stimulation protocols for successful modulation of performance.

Consciousness: a unique way of processing information

In this article, I argue that consciousness is a unique way of processing information, in that: it produces information, rather than purely transmitting it; the information it produces is meaningful for us; the meaning it has is always individuated. This uniqueness allows us to process information on the basis of our personal needs and ever-changing interactions with the environment, and consequently to act autonomously. Three main basic cognitive processes contribute to realize this unique way of information processing: the self, attention and working memory. The self, which is primarily expressed via the central and peripheral nervous systems, maps our body, the environment, and our relations with the environment. It is the primary means by which the complexity inherent to our composite structure is reduced into the "single voice" of a unique individual. It provides a reference system that (albeit evolving) is sufficiently stable to define the variations that will be used as the raw material for the construction of conscious information. Attention allows for the selection of those variations in the state of the self that are most relevant in the given situation. Attention originates and is deployed from a single locus inside our body, which represents the center of the self, around which all our conscious experiences are organized. Whatever is focused by attention appears in our consciousness as possessing a spatial quality defined by this center and the direction toward which attention is focused. In addition, attention determines two other features of conscious experience: periodicity and phenomenal quality. Self and attention are necessary but not sufficient for conscious information to be produced. Complex forms of conscious experiences, such as the various modes of givenness of conscious experience and the stream of consciousness, need a working memory mechanism to assemble the basic pieces of information selected by attention.

Cortical sources of resting state electroencephalographic rhythms probe brain function in naïve HIV individuals

OBJECTIVE

Here we evaluated the hypothesis that resting state electroencephalographic (EEG) cortical sources correlated with cognitive functions and discriminated asymptomatic treatment-naïve HIV subjects (no AIDS).

METHODS

EEG, clinical, and neuropsychological data were collected in 103 treatment-naïve HIV subjects (88 males; mean age 39.8 years ± 1.1 standard error of the mean, SE). An age-matched group of 70 cognitively normal and HIV-negative (Healthy; 56 males; 39.0 years ± 2.0 SE) subjects, selected from a local university archive, was used for control purposes. LORETA freeware was used for EEG source estimation in fronto-central, temporal, and parieto-occipital regions of interest.

RESULTS

Widespread sources of delta (<4 Hz) and alpha (8-12 Hz) rhythms were abnormal in the treatment-naïve HIV group. Fronto-central delta source activity showed a slight but significant (p < 0.05, corrected) negative correlation with verbal and semantic test scores. So did parieto-occipital delta/alpha source ratio with memory and composite cognitive scores. These sources allowed a moderate classification accuracy between HIV and control individuals (area under the ROC curves of 70-75%).

CONCLUSIONS

Regional EEG abnormalities in quiet wakefulness characterized treatment-naïve HIV subjects at the individual level.

SIGNIFICANCE

This EEG approach may contribute to the management of treatment-naïve HIV subjects at risk of cognitive deficits.

EEG microstates as a tool for studying the temporal dynamics of whole-brain neuronal networks: A review

The present review discusses a well-established method for characterizing resting-state activity of the human brain using multichannel electroencephalography (EEG). This method involves the examination of electrical microstates in the brain, which are defined as successive short time periods during which the configuration of the scalp potential field remains semi-stable, suggesting quasi-simultaneity of activity among the nodes of large-scale networks. A few prototypic microstates, which occur in a repetitive sequence across time, can be reliably identified across participants. Researchers have proposed that these microstates represent the basic building blocks of the chain of spontaneous conscious mental processes, and that their occurrence and temporal dynamics determine the quality of mentation. Several studies have further demonstrated that disturbances of mental processes associated with neurological and psychiatric conditions manifest as changes in the temporal dynamics of specific microstates. Combined EEG-fMRI studies and EEG source imaging studies have indicated that EEG microstates are closely associated with resting-state networks as identified using fMRI. The scale-free properties of the time series of EEG microstates explain why similar networks can be observed at such different time scales. The present review will provide an overview of these EEG microstates, available methods for analysis, the functional interpretations of findings regarding these microstates, and their behavioral and clinical correlates.

Optimized auditory transcranial alternating current stimulation improves individual auditory temporal resolution

BACKGROUND

Temporal resolution of cortical, auditory processing mechanisms is suggested to be linked to peak frequency of neuronal gamma oscillations in auditory cortex areas (individual gamma frequency, IGF): Individuals with higher IGF tend to have better temporal resolution.

HYPOTHESIS

Modulating ongoing gamma activity with transcranial alternating current stimulation (tACS) is expected to improve performance in gap detection (GD) tasks (shorter GD thresholds) if the frequency is higher and to decrease GD performance (longer GD thresholds) if the frequency is lower than IGF.

METHODS

For 26 healthy participants the IGF and temporal resolution were identified using an auditory steady state response (ASSR) paradigm and a between-channel GD task. Finite element modelling was used to generate an optimized tACS electrode montage (one channel per hemisphere: FC5-TP7/P7 and FC6-TP8/P8). Afterwards, GD thresholds were examined during tACS (tACS frequency group A: above IGF, tACS frequency group B: below IGF). Relative changes of GD thresholds were compared between groups. Additionally, effects of tACS on oscillatory activity were investigated comparing relative changes of ASSR amplitudes before and after stimulation.

RESULTS

Performance of group-A-participants improved significantly during tACS in comparison to performance of group-B-participants. Significant relative changes of ASSR amplitudes were found in both groups.

CONCLUSION

The possibility to improve gap detection with individualized stimulation protocols for tACS further supports the link between oscillatory activity and temporal resolution, whereby the improvement of temporal resolution is particularly relevant for the clinical aspect of auditory tACS.

Topodynamics of metastable brains

The brain displays both the anatomical features of a vast amount of interconnected topological mappings as well as the functional features of a nonlinear, metastable system at the edge of chaos, equipped with a phase space where mental random walks tend towards lower energetic basins. Nevertheless, with the exception of some advanced neuro-anatomic descriptions and present-day connectomic research, very few studies have been addressing the topological path of a brain embedded or embodied in its external and internal environment. Herein, by using new formal tools derived from algebraic topology, we provide an account of the metastable brain, based on the neuro-scientific model of Operational Architectonics of brain-mind functioning. We introduce a "topodynamic" description that shows how the relationships among the countless intertwined spatio-temporal levels of brain functioning can be assessed in terms of projections and mappings that take place on abstract structures, equipped with different dimensions, curvatures and energetic constraints. Such a topodynamical approach, apart from providing a biologically plausible model of brain function that can be operationalized, is also able to tackle the issue of a long-standing dichotomy: it throws indeed a bridge between the subjective, immediate datum of the naïve complex of sensations and mentations and the objective, quantitative, data extracted from experimental neuro-scientific procedures. Importantly, it opens the door to a series of new predictions and future directions of advancement for neuroscientific research.

How far can we go in chronic disorders of consciousness differential diagnosis? The use of neuromodulation in detecting internal and external awareness

Awareness generation and modulation may depend on a balanced information integration and differentiation across default mode network (DMN) and external awareness networks (EAN). Neuromodulation approaches, capable of shaping information processing, may highlight residual network activities supporting awareness, which are not detectable through active paradigms, thus allowing to differentiate chronic disorders of consciousness (DoC). We studied aftereffects of repetitive transcranial magnetic stimulation (rTMS) by applying graph theory within canonical frequency bands to compare the markers of these networks in the electroencephalographic data from 20 patients with DoC. We found that patients' high-frequency networks suffered from a large-scale connectivity breakdown, paralleled by a local hyperconnectivity, whereas low-frequency networks showed a preserved but dysfunctional large-scale connectivity. There was a correlation between metrics and the behavioral awareness. Interestingly, two persons with UWS showed a residual rTMS-induced modulation of the functional correlations between the DMN and the EAN, as observed in patients with MCS. Hence, we may hypothesize that the patients with UWS who demonstrate evidence of residual DMN-EAN functional correlation may be misdiagnosed, given that such residual network correlations could support covert consciousness.

Brain and cognitive functions in two groups of naïve HIV patients selected for a different plan of antiretroviral therapy: A qEEG study

OBJECTIVE

Cortical sources of electroencephalographic (EEG) rhythms were investigated in two sub-populations of naïve HIV subjects, grouped based on clinical criteria to receive different combination anti-retroviral therapies (cARTs). These EEG sources were hypothesized to reflect beneficial effects of both regimes.

METHODS

Eyes-closed resting state EEG data were collected in 19 (Group A) and 39 (Group B) naïve HIV subjects at baseline (i.e. pre-treatment; T0) and after 5months of cART (T5). Compared with the Group A, the Group B was characterized by slightly worse serological parameters and higher cardiovascular risk. At T0, mean viral load (VL) and CD4 count were 87,694copies/ml and 435cells/μl in the Group A and 187,370copies/ml and 331cells/μl in the Group B. The EEG data were also collected in 50 matched control HIV-negative subjects. Cortical EEG sources were assessed by LORETA software.

RESULTS

Compared to the Control Group, the HIV Groups showed lower alpha (8-12Hz) source activity at T0 while the Group B also exhibited higher delta source activity. The treatment partially normalized alpha and delta source activity in the Group A and B, respectively, in association with improved VL, CD4, and cognitive functions.

CONCLUSIONS

Different cART regimens induced diverse beneficial effects in delta or alpha source activity in the two naïve HIV Groups.

SIGNIFICANCE

These sources might unveil different neurophysiological effects of diverse cART on brain function in naïve HIV Groups as a function of clinical status and/or therapeutic compounds.

Novel Modeling of Task vs. Rest Brain State Predictability Using a Dynamic Time Warping Spectrum: Comparisons and Contrasts with Other Standard Measures of Brain Dynamics

Dynamic time warping, or DTW, is a powerful and domain-general sequence alignment method for computing a similarity measure. Such dynamic programming-based techniques like DTW are now the backbone and driver of most bioinformatics methods and discoveries. In neuroscience it has had far less use, though this has begun to change. We wanted to explore new ways of applying DTW, not simply as a measure with which to cluster or compare similarity between features but in a conceptually different way. We have used DTW to provide a more interpretable spectral description of the data, compared to standard approaches such as the Fourier and related transforms. The DTW approach and standard discrete Fourier transform (DFT) are assessed against benchmark measures of neural dynamics. These include EEG microstates, EEG avalanches, and the sum squared error (SSE) from a multilayer perceptron (MLP) prediction of the EEG time series, and simultaneously acquired FMRI BOLD signal. We explored the relationships between these variables of interest in an EEG-FMRI dataset acquired during a standard cognitive task, which allowed us to explore how DTW differentially performs in different task settings. We found that despite strong correlations between DTW and DFT-spectra, DTW was a better predictor for almost every measure of brain dynamics. Using these DTW measures, we show that predictability is almost always higher in task than in rest states, which is consistent to other theoretical and empirical findings, providing additional evidence for the utility of the DTW approach.

Abnormal cortical sources of resting state electroencephalographic rhythms in single treatment-naïve HIV individuals: A statistical z-score index

OBJECTIVE

This study tested a simple statistical procedure to recognize single treatment-naïve HIV individuals having abnormal cortical sources of resting state delta (<4 Hz) and alpha (8-13 Hz) electroencephalographic (EEG) rhythms with reference to a control group of sex-, age-, and education-matched healthy individuals. Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values were expected to show worse cognitive status.

METHODS

Resting state eyes-closed EEG data were recorded in 82 treatment-naïve HIV (39.8 ys.±1.2 standard error mean, SE) and 59 age-matched cognitively healthy subjects (39 ys.±2.2 SE). Low-resolution brain electromagnetic tomography (LORETA) estimated delta and alpha sources in frontal, central, temporal, parietal, and occipital cortical regions.

RESULTS

Ratio of the activity of parietal delta and high-frequency alpha sources (EEG marker) showed the maximum difference between the healthy and the treatment-naïve HIV group. Z-score of the EEG marker was statistically abnormal in 47.6% of treatment-naïve HIV individuals with reference to the healthy group (p<0.05). Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values exhibited lower mini mental state evaluation (MMSE) score, higher CD4 count, and lower viral load (p<0.05).

CONCLUSIONS

This statistical procedure permitted for the first time to identify single treatment-naïve HIV individuals having abnormal EEG activity.

SIGNIFICANCE

This procedure might enrich the detection and monitoring of effects of HIV on brain function in single treatment-naïve HIV individuals.

Auditory temporal resolution is linked to resonance frequency of the auditory cortex

A brief silent gap embedded in an otherwise continuous sound is missed by a human listener when it falls below a certain threshold: the gap detection threshold. This can be interpreted as an indicator that auditory perception is a non-continuous process, during which acoustic input is fragmented into a discrete chain of events. Current research provides evidence for a covariation between rhythmic properties of speech and ongoing rhythmic activity in the brain. Therefore, the discretization of acoustic input is thought to facilitate speech processing. Ongoing oscillations in the auditory cortex are suggested to represent a neuronal mechanism which implements the discretization process and leads to a limited auditory temporal resolution. Since gap detection thresholds seem to vary considerably between individuals, the present study addresses the question of whether individual differences in the frequency of underlying ongoing oscillatory mechanisms can be associated with auditory temporal resolution. To address this question we determined an individual gap detection threshold and a preferred oscillatory frequency for each participant. The preferred frequency of the auditory cortex was identified using an auditory steady state response (ASSR) paradigm: amplitude-modulated sounds with modulation frequencies in the gamma range were presented binaurally; the frequency which elicited the largest spectral amplitude was considered the preferred oscillatory frequency. Our results show that individuals with higher preferred auditory frequencies perform significantly better in the gap detection task. Moreover, this correlation between oscillation frequency and gap detection was supported by high test-retest reliabilities for gap detection thresholds as well as preferred frequencies.

Luria revisited: cognitive research in schizophrenia, past implications and future challenges

Contemporary psychiatry is becoming more biologically oriented in the attempt to elicit a biological rationale of mental diseases. Although mental disorders comprise mostly functional abnormalities, there is a substantial overlap between neurology and psychiatry in addressing cognitive disturbances. In schizophrenia, the presence of cognitive impairment prior to the onset of psychosis and early after its manifestation suggests that some neurocognitive abnormalities precede the onset of psychosis and may represent a trait marker. These cognitive alterations may arise from functional disconnectivity, as no significant brain damage has been found. In this review we aim to revise A.R. Luria's systematic approach used in the neuropsychological evaluation of cognitive functions, which was primarily applied in patients with neurological disorders and in the cognitive evaluation in schizophrenia and other related disorders. As proposed by Luria, cognitive processes, associated with higher cortical functions, may represent functional systems that are not localized in narrow, circumscribed areas of the brain, but occur among groups of concertedly working brain structures, each of which makes its own particular contribution to the organization of the functional system. Current developments in neuroscience provide evidence of functional connectivity in the brain. Therefore, Luria's approach may serve as a frame of reference for the analysis and interpretation of cognitive functions in general and their abnormalities in schizophrenia in particular. Having said that, modern technology, as well as experimental evidence, may help us to understand the brain better and lead us towards creating a new classification of cognitive functions. In schizophrenia research, multidisciplinary approaches must be utilized to address specific cognitive alterations. The relationships among the components of cognitive functions derived from the functional connectivity of the brain may provide an insight into cognitive machinery.

Comparison of two tests of auditory temporal resolution in children with central auditory processing disorder, adults with psychosis, and adult professional musicians

OBJECTIVE

Evaluate auditory temporal resolution threshold outcomes across three different populations.

DESIGN

Two commercially available tests of auditory gap detection (Random gap detection (RGDT) test, and Gaps-in-noise (GIN) test) were administered to all participants.

STUDY SAMPLE

Adult professional musicians (APM) (N = 11, age range 28-61 years); children with central auditory processing disorder (CAPD) (N = 22, age range 7.5-17 years); and first episode psychosis patients (FEP) (N = 17, age range 18-48 years).

RESULTS

It was not possible to calculate a threshold for the RGDT for 13 of 22 children with CAPD and for 7 of 17 adults with FEP due to response inconsistency. Analysis of variance (ANOVA) excluding cases that produced inconsistent RGDT results showed that only RGDT thresholds differed across groups (F = 8.73, p = 0.001). Three t-tests comparing test means within group revealed statistically significant differences between the gap detection thresholds obtained with the RGDT vs. the GIN for each group. No significant correlations were seen between RGDT and GIN.

CONCLUSION

Lower/better gap detection thresholds and smaller standard deviations were obtained using the GIN in all three groups. Lack of correlation between the two tests suggests that they may measure different processes.

Chunking dynamics: heteroclinics in mind

Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components—brain modes—participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles—metastable states—connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics.

EEG oscillatory states: universality, uniqueness and specificity across healthy-normal, altered and pathological brain conditions

For the first time the dynamic repertoires and oscillatory types of local EEG states in 13 diverse conditions (examined over 9 studies) that covered healthy-normal, altered and pathological brain states were quantified within the same methodological and conceptual framework. EEG oscillatory states were assessed by the probability-classification analysis of short-term EEG spectral patterns. The results demonstrated that brain activity consists of a limited repertoire of local EEG states in any of the examined conditions. The size of the state repertoires was associated with changes in cognition and vigilance or neuropsychopathologic conditions. Additionally universal, optional and unique EEG states across 13 diverse conditions were observed. It was demonstrated also that EEG oscillations which constituted EEG states were characteristic for different groups of conditions in accordance to oscillations' functional significance. The results suggested that (a) there is a limit in the number of local states available to the cortex and many ways in which these local states can rearrange themselves and still produce the same global state and (b) EEG individuality is determined by varying proportions of universal, optional and unique oscillatory states. The results enriched our understanding about dynamic microstructure of EEG-signal.

EEG oscillatory states: universality, uniqueness and specificity across healthy-normal, altered and pathological brain conditions

For the first time the dynamic repertoires and oscillatory types of local EEG states in 13 diverse conditions (examined over 9 studies) that covered healthy-normal, altered and pathological brain states were quantified within the same methodological and conceptual framework. EEG oscillatory states were assessed by the probability-classification analysis of short-term EEG spectral patterns. The results demonstrated that brain activity consists of a limited repertoire of local EEG states in any of the examined conditions. The size of the state repertoires was associated with changes in cognition and vigilance or neuropsychopathologic conditions. Additionally universal, optional and unique EEG states across 13 diverse conditions were observed. It was demonstrated also that EEG oscillations which constituted EEG states were characteristic for different groups of conditions in accordance to oscillations' functional significance. The results suggested that (a) there is a limit in the number of local states available to the cortex and many ways in which these local states can rearrange themselves and still produce the same global state and (b) EEG individuality is determined by varying proportions of universal, optional and unique oscillatory states. The results enriched our understanding about dynamic microstructure of EEG-signal.

Alterations in the sense of time, space, and body in the mindfulness-trained brain: a neurophenomenologically-guided MEG study

Meditation practice can lead to what have been referred to as “altered states of consciousness.”One of the phenomenological characteristics of these states is a joint alteration in the sense of time, space, and body. Here, we set out to study the unique experiences of alteration in the sense of time and space by collaborating with a select group of 12 long-term mindfulness meditation (MM) practitioners in a neurophenomenological setup, utilizing first-person data to guide the neural analyses. We hypothesized that the underlying neural activity accompanying alterations in the sense of time and space would be related to alterations in bodily processing. The participants were asked to volitionally bring about distinct states of “Timelessness” (outside time) and “Spacelessness” (outside space) while their brain activity was recorded by MEG. In order to rule out the involvement of attention, memory, or imagination, we used control states of “Then” (past) and “There” (another place). MEG sensors evidencing alterations in power values were identified, and the brain regions underlying these changes were estimated via spatial filtering (beamforming). Particularly, we searched for similar neural activity hypothesized to underlie both the state of “Timelessness” and “Spacelessness.” The results were mostly confined to the theta band, and showed that: (1) the “Then”/“There” overlap yielded activity in regions related to autobiographic memory and imagery (right posterior parietal lobule (PPL), right precentral/middle frontal gyrus (MFG), bilateral precuneus); (2) “Timelessness”/“Spacelessness” conditions overlapped in a different network, related to alterations in the sense of the body (posterior cingulate, right temporoparietal junction (TPJ), cerebellum); and (3) phenomenologically-guided neural analyses enabled us to dissociate different levels of alterations in the sense of the body. This study illustrates the utility of employing experienced contemplative practitioners within a neurophenomenological setup for scientifically characterizing a self-induced altered sense of time, space and body, as well as the importance of theta activity in relation with these altered states.

Temporal order perception of auditory stimuli is selectively modified by tonal and non-tonal language environments

The close relationship between temporal perception and speech processing is well established. The present study focused on the specific question whether the speech environment could influence temporal order perception in subjects whose language backgrounds are distinctively different, i.e., Chinese (tonal language) vs. Polish (non-tonal language). Temporal order thresholds were measured for both monaurally presented clicks and binaurally presented tone pairs. Whereas the click experiment showed similar order thresholds for the two language groups, the experiment with tone pairs resulted in different observations: while Chinese demonstrated better performance in discriminating the temporal order of two "close frequency" tone pairs (600 Hz and 1200 Hz), Polish subjects showed a reversed pattern, i.e., better performance for "distant frequency" tone pairs (400 Hz and 3000 Hz). These results indicate on the one hand a common temporal mechanism for perceiving the order of two monaurally presented stimuli, and on the other hand neuronal plasticity for perceiving the order of frequency-related auditory stimuli. We conclude that the auditory brain is modified with respect to temporal processing by long-term exposure to a tonal or a non-tonal language. As a consequence of such an exposure different cognitive modes of operation (analytic vs. holistic) are selected: the analytic mode is adopted for "distant frequency" tone pairs in Chinese and for "close frequency" tone pairs in Polish subjects, whereas the holistic mode is selected for "close frequency" tone pairs in Chinese and for "distant frequency" tone pairs in Polish subjects, reflecting a double dissociation of function.

Dissociation of vegetative and minimally conscious patients based on brain operational architectonics: factor of etiology

Discrimination between patients in vegetative (VS) and minimally conscious state (MCS) is currently based upon the behavioral gold standard. Behavioral assessment remains equivocal and difficult to interpret as evidence for the presence or absence of consciousness, resulting in possible clinical misdiagnosis in such patients. Application of an operational architectonics (OA) strategy to electroencephalogram (EEG) analysis reveals that absence of consciousness in patients in VS is paralleled by significant impairment in overall EEG operational architecture compared to patients in MCS: neuronal assemblies become smaller, their life span shortened, and they became highly unstable and functionally disconnected (desynchronized). However, in a previous study, patients with different brain damage etiologies were intermixed. Therefore, the goal of the present study was to investigate whether the application of OA methodology to EEG could reliably dissociate patients in VS and MCS independent of brain damage etiology. We conclude that the observed EEG OA structure impairment in patients in VS and partial preservation in patients in MCS is a marker of consciousness/unconsciousness rather than physiological damage. Results of this study may have neuroscientific, clinical, and ethical implications.

Dynamic systems approaches and levels of analysis in the nervous system

Various analyses are applied to physiological signals. While epistemological diversity is necessary to address effects at different levels, there is often a sense of competition between analyses rather than integration. This is evidenced by the differences in the criteria needed to claim understanding in different approaches. In the nervous system, neuronal analyses that attempt to explain network outputs in cellular and synaptic terms are rightly criticized as being insufficient to explain global effects, emergent or otherwise, while higher-level statistical and mathematical analyses can provide quantitative descriptions of outputs but can only hypothesize on their underlying mechanisms. The major gap in neuroscience is arguably our inability to translate what should be seen as complementary effects between levels. We thus ultimately need approaches that allow us to bridge between different spatial and temporal levels. Analytical approaches derived from critical phenomena in the physical sciences are increasingly being applied to physiological systems, including the nervous system, and claim to provide novel insight into physiological mechanisms and opportunities for their control. Analyses of criticality have suggested several important insights that should be considered in cellular analyses. However, there is a mismatch between lower-level neurophysiological approaches and statistical phenomenological analyses that assume that lower-level effects can be abstracted away, which means that these effects are unknown or inaccessible to experimentalists. As a result experimental designs often generate data that is insufficient for analyses of criticality. This review considers the relevance of insights from analyses of criticality to neuronal network analyses, and highlights that to move the analyses forward and close the gap between the theoretical and neurobiological levels, it is necessary to consider that effects at each level are complementary rather than in competition.