Linking Sleep Slow Oscillations with consciousness theories: new vistas on Slow Wave Sleep unconsciousness.

We review current models of consciousness in the context of wakefulness and sleep. We show that recent results on Slow Wave Sleep, including our own works, naturally fit within consciousness models. In particular, Sleep Slow Oscillations, namely low-frequency (<1Hz) oscillations, contain electrophysiological properties (up and down states) able to elicit and quench neural integration during Slow Wave Sleep. The physiological unconsciousness related to the Sleep Slow Oscillation derives from the interplay between spontaneous or evoked wake-like activities (up states) and half-a-second's electrical silences (down states). Sleep Slow Oscillation induces unconsciousness via the formation of parallel and segregated neural activities.

Disentangling different functional roles of evoked K-complex components: Mapping the sleeping brain while quenching sensory processing.

During non-REM sleep the largest EEG response evoked by sensory stimulation is the K-complex (eKC), composed of an initial positive bump (P200) followed by a bistable cortical response: a giant negative deflection (N550) and a large positive one (P900), respectively reflecting down states and up states of < 1 Hz oscillations.Sensory-modality-independent topology of N550 and P900, with maximal detection rate on fronto-central areas, has been consistently reported, suggesting that sensory inputs arise to the cortex avoiding specific primary sensory areas. However, these studies neglected latencies of all KC components as a function of electrode sites.Our aim is to identify, component by component, which topological/dynamical properties of eKCs depend on stimulus modality and which are mainly related to local cortical properties. We measured temporal and morphological features of acoustic, tactile and visual eKCs to disentangle specific sensory excitatory activities from aspecific responses due to local proneness to bistability, measured by means of the N550 descending steepness (synchronization in falling into down state).While confirming the sensory-modality independence of N550 and P900 topology with maximal detection rate in fronto-central areas, four main original results emerge from this study: (i) the topology of P200 latency depends on the sensory modality with earliest waves in the stimulation-related primary sensory areas; (ii) P200 rapidly travels as a cortical excitation; (iii) P200-like excitations when KCs are not evoked are detected over the scalp with significantly smaller amplitudes in fronto-central areas, compared to eKC P200s; and (iv) N550 latency mirrors its mean local steepness which is a function of topological proneness to bistability.From these results we can describe the emergence N550/P900 complex as the interplay between a waxing P200 cortical travel and higher fronto-central proneness to bistability.In conclusion, eKCs exhibit a physiological dichotomy: P200 acts as a traveling cortical excitation whose function is to induce the bistable cortical response (N550/P900), which in turn is crucial for maintaining sleep and unconsciousness.

Nonlinear indices of heart rate variability in chronic heart failure patients: redundancy and comparative clinical value.

AIMS: We aimed to assess the mutual interrelationships and to compare the prognostic value of a comprehensive set of nonlinear indices of heart rate variability (HRV) in a population of chronic heart failure (CHF) patients. METHODS AND RESULTS: Twenty nonlinear HRV indices, representative of symbolic dynamics, entropy, fractality-multifractality, predictability, empirical mode decomposition, and Poincaré plot families, were computed from 24-hour Holter recordings in 200 stable CHF patients in sinus rhythm (median age [interquartile range]: 54 [47-58] years, LVEF: 23 [19-28]%, NYHA class II-III: 88%). End point for survival analysis (Cox model) was cardiac death or urgent transplantation. Homogeneous variables were grouped by cluster analysis, and in each cluster redundant variables were discarded. A prognostic model including only known clinical and functional risk factors was built and the ability of each selected HRV variable to add prognostic information to this model assessed. Bootstrap resampling was used to test the models stability. Four nonlinear variables showed a correlation >0.90 with classical linear ones and were discarded. Correlations >0.80 were found between several nonlinear variables. Twelve clusters were obtained and from each cluster a candidate predictor was selected. Only two variables (from empirical mode decomposition and symbolic dynamics families) added prognostic information to the clinical model. CONCLUSION: This exploratory study provides evidence that, despite some redundancies in the informative content of nonlinear indices and strong differences in their prognostic power, quantification of nonlinear properties of HRV provides independent information in risk stratification of CHF patients.

Renewal, modulation, and superstatistics in times series.

We consider two different approaches, to which we refer to as renewal and modulation, to generate time series with a nonexponential distribution of waiting times. We show that different time series with the same waiting time distribution are not necessarily statistically equivalent, and might generate different physical properties. Renewal generates aging and anomalous scaling, while modulation yields no significant aging and either ordinary or anomalous diffusion, according to the dynamic prescription adopted. We show, in fact, that the physical realization of modulation generates two classes of events. The events of the first class are determined by the persistent use of the same exponential time scale for an extended lapse of time, and consequently are numerous; the events of the second class are identified with the abrupt changes from one to another exponential prescription, and consequently are rare. The events of the second class, although rare, determine the scaling of the diffusion process, and for this reason we term them as crucial events. According to the prescription adopted to produce modulation, the distribution density of the time distances between two consecutive crucial events might have, or not, a diverging second moment. In the former case the resulting diffusion process, although going through a transition regime very extended in time, will eventually become anomalous. In conclusion, modulation rather than ruling out the action of renewal events, produces crucial events hidden by clouds of exponential events, thereby setting the challenge for their identification.

Correlation function and generalized master equation of arbitrary age.

We study a two-state statistical process with a non-Poisson distribution of sojourn times. In accordance with earlier work, we find that this process is characterized by aging and we study three different ways to define the correlation function of arbitrary age of the corresponding dichotomous fluctuation. These three methods yield exact expressions, thus coinciding with the recent result by Godrèche and Luck [J. Stat. Phys. 104, 489 (2001)]. Actually, non-Poisson statistics yields infinite memory at the probability level, thereby breaking any form of Markovian approximation, including the one adopted herein, to find an approximated analytical formula. For this reason, we check the accuracy of this approximated formula by comparing it with the numerical treatment of the second of the three exact expressions. We find that, although not exact, a simple analytical expression for the correlation function of arbitrary age is very accurate. We establish a connection between the correlation function and a generalized master equation of the same age. Thus this formalism, related to models used in glassy materials, allows us to illustrate an approach to the statistical treatment of blinking quantum dots, bypassing the limitations of the conventional Liouville treatment.

A renewal model for the emergence of anomalous solute crowding in liposomes.

A fundamental evolutionary step in the onset of living cells is thought to be the spontaneous formation of lipid vesicles (liposomes) in the pre-biotic mixture. Even though it is well known that hydrophobic forces drive spontaneous liposome formation in aqueous solutions, how the components of the earliest biochemical pathways were trapped and concentrated in the forming vesicles is an issue that still needs to be clarified. In recent years, some authors carried out a set of experiments where a unexpectedly high amount of solutes were found in a small number of liposomes, spontaneously formed in aqueous solution. A great number of empty liposomes were found in the same experiments and the global observed behavior was that of a distribution of solute particles into liposomes in agreement with a inverse power-law function rather than with the expected Poisson distribution. The chemical and physical mechanisms leading to the observed "anomalous solute crowding" are still unclear, but the non-Poisson power-law behavior is associated with some cooperative behavior with strong non-linear interactions in the biochemical processes occurring in the solution. For tackling this issue we propose a model grounding on the Cox's theory of renewal point processes, which many authors consider to play a central role in the description of complex cooperative systems. Starting from two very basic hypotheses and the renewal assumption, we derive a model reproducing the behavior outlined above. In particular, we show that the assumption of a "cooperative" interaction between the solute molecules and the forming liposomes is sufficient for the emergence of the observed power-law behavior. Even though our approach does not provide experimental evidences of the chemical and physical bases of the solute crowding, it suggests promising directions for experimental research and it also provide a first theoretical prediction that could possibly be tested in future experimental investigations.

Self-organized dynamical complexity in human wakefulness and sleep: different critical brain-activity feedback for conscious and unconscious states.

Criticality reportedly describes brain dynamics. The main critical feature is the presence of scale-free neural avalanches, whose auto-organization is determined by a critical branching ratio of neural-excitation spreading. Other features, directly associated to second-order phase transitions, are: (i) scale-free-network topology of functional connectivity, stemming from suprathreshold pairwise correlations, superimposable, in waking brain activity, with that of ferromagnets at Curie temperature; (ii) temporal long-range memory associated to renewal intermittency driven by abrupt fluctuations in the order parameters, detectable in human brain via spatially distributed phase or amplitude changes in EEG activity. Herein we study intermittent events, extracted from 29 night EEG recordings, including presleep wakefulness and all phases of sleep, where different levels of mentation and consciousness are present. We show that while critical avalanching is unchanged, at least qualitatively, intermittency and functional connectivity, present during conscious phases (wakefulness and REM sleep), break down during both shallow and deep non-REM sleep. We provide a theory for fragmentation-induced intermittency breakdown and suggest that the main difference between conscious and unconscious states resides in the backwards causation, namely on the constraints that the emerging properties at large scale induce to the lower scales. In particular, while in conscious states this backwards causation induces a critical slowing down, preserving spatiotemporal correlations, in dreamless sleep we see a self-organized maintenance of moduli working in parallel. Critical avalanches are still present, and establish transient auto-organization, whose enhanced fluctuations are able to trigger sleep-protecting mechanisms that reinstate parallel activity. The plausible role of critical avalanches in dreamless sleep is to provide a rapid recovery of consciousness, if stimuli are highly arousing.

Pattern recognition with adaptive-thresholds for sleep spindle in high density EEG signals.

Medicine and Surgery, University of Pisa, via Savi 10, 56126, Pisa, Italy Sleep spindles are electroencephalographic oscillations peculiar of non-REM sleep, related to neuronal mechanisms underlying sleep restoration and learning consolidation. Based on their very singular morphology, sleep spindles can be visually recognized and detected, even though this approach can lead to significant mis-detections. For this reason, many efforts have been put in developing a reliable algorithm for spindle automatic detection, and a number of methods, based on different techniques, have been tested via visual validation. This work aims at improving current pattern recognition procedures for sleep spindles detection by taking into account their physiological sources of variability. We provide a method as a synthesis of the current state of art that, improving dynamic threshold adaptation, is able to follow modification of spindle characteristics as a function of sleep depth and inter-subjects variability. The algorithm has been applied to physiological data recorded by a high density EEG in order to perform a validation based on visual inspection and on evaluation of expected results from normal night sleep in healthy subjects.

Looking for a precursor of spontaneous Sleep Slow Oscillations in human sleep: The role of the sigma activity.

Sleep Slow Oscillations (SSOs), paradigmatic EEG markers of cortical bistability (alternation between cellular downstates and upstates), and sleep spindles, paradigmatic EEG markers of thalamic rhythm, are two hallmarks of sleeping brain. Selective thalamic lesions are reportedly associated to reductions of spindle activity and its spectrum ~14 Hz (sigma), and to alterations of SSO features. This apparent, parallel behavior suggests that thalamo-cortical entrainment favors cortical bistability. Here we investigate temporally-causal associations between thalamic sigma activity and shape, topology, and dynamics of SSOs. We recorded sleep EEG and studied whether spatio-temporal variability of SSO amplitude, negative slope (synchronization in downstate falling) and detection rate are driven by cortical-sigma-activity expression (12-18Hz), in 3 consecutive 1s-EEG-epochs preceding each SSO event (Baselines). We analyzed: (i) spatial variability, comparing maps of baseline sigma power and of SSO features, averaged over the first sleep cycle; (ii) event-by-event shape variability, computing for each electrode correlations between baseline sigma power and amplitude/slope of related SSOs; (iii) event-by-event spreading variability, comparing baseline sigma power in electrodes showing an SSO event with the homologous ones, spared by the event. The scalp distribution of baseline sigma power mirrored those of SSO amplitude and slope; event-by-event variability in baseline sigma power was associated with that in SSO amplitude in fronto-central areas; within each SSO event, electrodes involved in cortical bistability presented higher baseline sigma activity than those free of SSO. In conclusion, spatio-temporal variability of thalamocortical entrainment, measured by background sigma activity, is a reliable estimate of the cortical proneness to bistability.

Psycho-physiological tele-monitoring of human operators in commercial diving: The Life Support System in the SUONO project.

Sea-diving operations for monitoring or intervention are carried out by highly-specialized divers called Certified Commercial Divers (CCD). CCDs operate under highly demanding working conditions in extreme and hazardous environments. Every day consists of an 8 hours' shift. To avoid decompression problems the remaining 16 hours are spent in a hyperbaric environment located aboard the surface vessel or on the platform. These operating conditions require the design of a technologically-advanced device for tele-monitoring, to maximize CCDs' safety. Here we describe a proposal for monitoring and supporting CCDs during operations. We design a dedicated Life Support System (LSS), that captures real-time, vital (heart rate, respiratory rate, accelerometry, etc) and stress-related (heart-rate variability) signals from operators to transmit them to dedicated servers via telematic protocols. LSS is equipped with protocols for tele-medicine/tele-consultation. Our system is being developed within the research project SUONO (Safe Underwater OperatioNs in Oceans).

Generalized master equation via aging continuous-time random walks.

We discuss the problem of the equivalence between continuous-time random walk (CTRW) and generalized master equation (GME). The walker, making instantaneous jumps from one site of the lattice to another, resides in each site for extended times. The sojourn times have a distribution density psi(t) that is assumed to be an inverse power law with the power index micro. We assume that the Onsager principle is fulfilled, and we use this assumption to establish a complete equivalence between GME and the Montroll-Weiss CTRW. We prove that this equivalence is confined to the case where psi(t) is an exponential. We argue that is so because the Montroll-Weiss CTRW, as recently proved by Barkai [E. Barkai, Phys. Rev. Lett. 90, 104101 (2003)], is nonstationary, thereby implying aging, while the Onsager principle is valid only in the case of fully aged systems. The case of a Poisson distribution of sojourn times is the only one with no aging associated to it, and consequently with no need to establish special initial conditions to fulfill the Onsager principle. We consider the case of a dichotomous fluctuation, and we prove that the Onsager principle is fulfilled for any form of regression to equilibrium provided that the stationary condition holds true. We set the stationary condition on both the CTRW and the GME, thereby creating a condition of total equivalence, regardless of the nature of the waiting-time distribution. As a consequence of this procedure we create a GME that is a bona fide master equation, in spite of being non-Markov. We note that the memory kernel of the GME affords information on the interaction between system of interest and its bath. The Poisson case yields a bath with infinitely fast fluctuations. We argue that departing from the Poisson form has the effect of creating a condition of infinite memory and that these results might be useful to shed light on the problem of how to unravel non-Markov quantum master equations.

How stressful are 105 days of isolation? Sleep EEG patterns and tonic cortisol in healthy volunteers simulating manned flight to Mars.

Spaceflights "environment" negatively affects sleep and its functions. Among the different causes promoting sleep alterations, such as circadian rhythms disruption and microgravity, stress is of great interest also for earth-based sleep medicine. This study aims to evaluate the relationships between stress related to social/environmental confinement and sleep in six healthy volunteers involved in the simulation of human flight to Mars (MARS500). Volunteers were sealed in a spaceship simulator for 105 days and studied at 5 specific time-points of the simulation period. Sleep EEG, urinary cortisol (24 h preceding sleep EEG recording) and subjectively perceived stress levels were collected. Cognitive abilities and emotional state were evaluated before and after the simulation. Sleep EEG parameters in the time (latency, duration) and frequency (power and hemispheric lateralization) domains were evaluated. Neither cognitive and emotional functions alterations nor abnormal stress levels were found. Higher cortisol levels were associated to: (i) decrease of sleep duration, increase of arousals, and shortening of REM latency; (ii) reduction of delta power and enhancement of sigma and beta in NREM N3; and (iii) left lateralization of delta activity (NREM and REM) and right lateralization of beta activity (NREM). Stressful conditions, even with cortisol fluctuations in the normal range, alter sleep structure and sleep EEG spectral content, mirroring pathological conditions such as primary insomnia or insomnia associated to depression. Correlations between cortisol fluctuations and sleep changes suggest a covert risk for developing allostatic load, and thus the need to develop ad-hoc countermeasures for preventing sleep alterations in long lasting manned space missions.

Fragments of wake-like activity frame down-states of sleep slow oscillations in humans: new vistas for studying homeostatic processes during sleep.

During NREM sleep cortical activity corresponding to EEG fast rhythms (FRs>10 Hz) is interrupted by fragments of neural stillness (down-states), responsible for the negative peak within sleep slow oscillation (SSO). Researchers still debate whether the down-states spontaneously occur or need an initial overshoot in fluctuating activity. Herein, we studied temporally-isolated SSO in healthy subjects in order to identify two distinct EEG markers defining a putative initial up-state: i) a significant positive deflection and ii) an associated FR increase, before the negative peak. We found a positive bump preceding the down-state, which is detectable already at the cortical SSO origin site, both during N2 and N3. This early positive deflection, concurrent with a broadband activation, is characterized by an increase of sigma activity (12-18 Hz) from N2 to N3, while an opposite trend was observed for sigma activity crowning the up-state following the negative peak. Also, we found: (i) FR activations during up-states up to high gamma frequencies; (ii) depressed sigma activity in after-spindle recovery phase; and (iii) tightly coordinated activities between distinct bands (12-36 Hz, ~70 Hz, ~85 Hz and 105-125 Hz). The correlation between different bands suggested a common mechanism for sigma and gamma, and the pre-down-state activation associated with the initial bump suggested an activity ignition for down-state, whose intensity is dependent on sleep stage. In conclusion, we hypothesize that FR accompanying SSO could mark i) sleep homeostatic processes, such as the regulation/stabilization of sleep, counterbalancing the detrimental effects of continuous inputs from peripheries, and ii) neural mechanisms favoring the storage of information acquired during wakefulness.

Dominant Lyapunov exponent and approximate entropy in heart rate variability during emotional visual elicitation.

In this work we characterized the non-linear complexity of Heart Rate Variability (HRV) in short time series. The complexity of HRV signal was evaluated during emotional visual elicitation by using Dominant Lyapunov Exponents (DLEs) and Approximate Entropy (ApEn). We adopted a simplified model of emotion derived from the Circumplex Model of Affects (CMAs), in which emotional mechanisms are conceptualized in two dimensions by the terms of valence and arousal. Following CMA model, a set of standardized visual stimuli in terms of arousal and valence gathered from the International Affective Picture System (IAPS) was administered to a group of 35 healthy volunteers. Experimental session consisted of eight sessions alternating neutral images with high arousal content images. Several works can be found in the literature showing a chaotic dynamics of HRV during rest or relax conditions. The outcomes of this work showed a clear switching mechanism between regular and chaotic dynamics when switching from neutral to arousal elicitation. Accordingly, the mean ApEn decreased with statistical significance during arousal elicitation and the DLE became negative. Results showed a clear distinction between the neutral and the arousal elicitation and could be profitably exploited to improve the accuracy of emotion recognition systems based on HRV time series analysis.

From self-organized to extended criticality.

We address the issue of criticality that is attracting the attention of an increasing number of neurophysiologists. Our main purpose is to establish the specific nature of some dynamical processes that although physically different, are usually termed as "critical," and we focus on those characterized by the cooperative interaction of many units. We notice that the term "criticality" has been adopted to denote both noise-induced phase transitions and Self-Organized Criticality (SOC) with no clear connection with the traditional phase transitions, namely the transformation of a thermodynamic system from one state of matter to another. We notice the recent attractive proposal of extended criticality advocated by Bailly and Longo, which is realized through a wide set of critical points rather than emerging as a singularity from a unique value of the control parameter. We study a set of cooperatively firing neurons and we show that for an extended set of interaction couplings the system exhibits a form of temporal complexity similar to that emerging at criticality from ordinary phase transitions. This extended criticality regime is characterized by three main properties: (i) In the ideal limiting case of infinitely large time period, temporal complexity corresponds to Mittag-Leffler complexity; (ii) For large values of the interaction coupling the periodic nature of the process becomes predominant while maintaining to some extent, in the intermediate time asymptotic region, the signature of complexity; (iii) Focusing our attention on firing neuron avalanches, we find two of the popular SOC properties, namely the power indexes 2 and 1.5 respectively for time length and for the intensity of the avalanches. We derive the main conclusion that SOC emerges from extended criticality, thereby explaining the experimental observation of Plenz and Beggs: avalanches occur in time with surprisingly regularity, in apparent conflict with the temporal complexity of physical critical points.

Cooperation-induced topological complexity: a promising road to fault tolerance and hebbian learning.

According to an increasing number of researchers intelligence emerges from criticality as a consequence of locality breakdown and long-range correlation, well known properties of phase transition processes. We study a model of interacting units, as an idealization of real cooperative systems such as the brain or a flock of birds, for the purpose of discussing the emergence of long-range correlation from the coupling of any unit with its nearest neighbors. We focus on the critical condition that has been recently shown to maximize information transport and we study the topological structure of the network of dynamically linked nodes. Although the topology of this network depends on the arbitrary choice of correlation threshold, namely the correlation intensity selected to establish a link between two nodes; the numerical calculations of this paper afford some important indications on the dynamically induced topology. The first important property is the emergence of a perception length as large as the flock size, thanks to some nodes with a large number of links, thus playing the leadership role. All the units are equivalent and leadership moves in time from one to another set of nodes, thereby insuring fault tolerance. Then we focus on the correlation threshold generating a scale-free topology with power index ν ≈ 1 and we find that if this topological structure is selected to establish consensus through the linked nodes, the control parameter necessary to generate criticality is close to the critical value corresponding to the all-to-all coupling condition. We find that criticality in this case generates also a third state, corresponding to a total lack of consensus. However, we make a numerical analysis of the dynamically induced network, and we find that it consists of two almost independent structures, each of which is equivalent to a network in the all-to-all coupling condition. This observation confirms that cooperation makes the system evolve toward favoring consensus topological structures. We argue that these results are compatible with both Hebbian learning and fault tolerance.

Thalamic contribution to Sleep Slow Oscillation features in humans: a single case cross sectional EEG study in Fatal Familial Insomnia.

OBJECTIVE: Studying the thalamic role in the cortical expression of the Sleep Slow Oscillation (SSO) in humans by comparing SSO features in a case of Fatal Familial Insomnia (FFI) and a group of controls. METHODS: We characterize SSOs in a 51-year-old male with FFI carrying the D178N mutation and the methionine/methionine homozygosity at the polymorphic 129 codon of the PRNP gene and in eight gender and age-matched healthy controls. Polysomnographic (21 EEG electrodes, two consecutive nights) and volumetric- (Diffusion tensor imaging Magnetic Resonance Imaging DTI MRI) evaluations were carried out for the patient in the middle course of the disease (five months after the onset of insomnia; disease duration: 10 months). We measured a set of features describing each SSO event: the wave shape, the event-origin location, the number and the location of all waves belonging to the event, and the grouping of spindle activity as a function of the SSO phase. RESULTS: We found that the FFI individual showed a marked reduction of SSO event rate and wave morphological alterations as well as a significant reduction in grouping spindle activity, especially in frontal areas. These alterations paralleled DTI changes in the thalamus and the cingulate cortex. CONCLUSIONS: This work gives a quantitative picture of spontaneous SSO activity during the NREM sleep of a FFI individual. The results suggest that a thalamic neurodegeneration specifically alters the cortical expression of the SSO. This characterization also provides indications about cortico-thalamic interplays in SSO activity in humans.

Mind-body relationships in elite apnea divers during breath holding: a study of autonomic responses to acute hypoxemia.

The mental control of ventilation with all associated phenomena, from relaxation to modulation of emotions, from cardiovascular to metabolic adaptations, constitutes a psychophysiological condition characterizing voluntary breath-holding (BH). BH induces several autonomic responses, involving both autonomic cardiovascular and cutaneous pathways, whose characterization is the main aim of this study. Electrocardiogram and skin conductance (SC) recordings were collected from 14 elite divers during three conditions: free breathing (FB), normoxic phase of BH (NPBH) and hypoxic phase of BH (HPBH). Thus, we compared a set of features describing signal dynamics between the three experimental conditions: from heart rate variability (HRV) features (in time and frequency-domains and by using nonlinear methods) to rate and shape of spontaneous SC responses (SCRs). The main result of the study rises by applying a Factor Analysis to the subset of features significantly changed in the two BH phases. Indeed, the Factor Analysis allowed to uncover the structure of latent factors which modeled the autonomic response: a factor describing the autonomic balance (AB), one the information increase rate (IIR), and a latter the central nervous system driver (CNSD). The BH did not disrupt the FB factorial structure, and only few features moved among factors. Factor Analysis indicates that during BH (1) only the SC described the emotional output, (2) the sympathetic tone on heart did not change, (3) the dynamics of interbeats intervals showed an increase of long-range correlation that anticipates the HPBH, followed by a drop to a random behavior. In conclusion, data show that the autonomic control on heart rate and SC are differentially modulated during BH, which could be related to a more pronounced effect on emotional control induced by the mental training to BH.

Fractal complexity in spontaneous EEG metastable-state transitions: new vistas on integrated neural dynamics.

Resting-state EEG signals undergo rapid transition processes (RTPs) that glue otherwise stationary epochs. We study the fractal properties of RTPs in space and time, supporting the hypothesis that the brain works at a critical state. We discuss how the global intermittent dynamics of collective excitations is linked to mentation, namely non-constrained non-task-oriented mental activity.

Complex intermittency blurred by noise: theory and application to neural dynamics.

We propose a model for the passage between metastable states of mind dynamics. As changing points we use the rapid transition processes simultaneously detectable in EEG signals related to different cortical areas. Our model consists of a non-Poissonian intermittent process, which signals that the brain is in a condition of complexity, upon which a Poisson process is superimposed. We provide an analytical solution for the waiting-time distribution for the model, which is well obeyed by physiological data. Although the role of the Poisson process remains unexplained, the model is able to reproduce many behaviors reported in literature, although they seem contradictory.