Information-Theoretic Approaches in EEG Correlates of Auditory Perceptual Awareness under Informational Masking.

In informational masking paradigms, the successful segregation between the target and masker creates auditory perceptual awareness. The dynamics of the build-up of auditory perception is based on a set of interactions between bottom-up and top-down processes that generate neuronal modifications within the brain network activity. These neural changes are studied here using event-related potentials (ERPs), entropy, and integrated information, leading to several measures applied to electroencephalogram signals. The main findings show that the auditory perceptual awareness stimulated functional activation in the fronto-temporo-parietal brain network through (i) negative temporal and positive centro-parietal ERP components; (ii) an enhanced processing of multi-information in the temporal cortex; and (iii) an increase in informational content in the fronto-central cortex. These different results provide information-based experimental evidence about the functional activation of the fronto-temporo-parietal brain network during auditory perceptual awareness.

Investigating the influence of masker and target properties on the dynamics of perceptual awareness under informational masking.

Informational masking has been investigated using the detection of an auditory target embedded in a random multi-tone masker. The build-up of the target percept is influenced by the masker and target properties. Most studies dealing with discrimination performance neglect the dynamics of perceptual awareness. This study aims at investigating the dynamics of perceptual awareness using multi-level survival models in an informational masking paradigm by manipulating masker uncertainty, masker-target similarity and target repetition rate. Consistent with previous studies, it shows that high target repetition rates, low masker-target similarity and low masker uncertainty facilitate target detection. In the context of evidence accumulation models, these results can be interpreted by changes in the accumulation parameters. The probabilistic description of perceptual awareness provides a benchmark for the choice of target and masker parameters in order to examine the underlying cognitive and neural dynamics of perceptual awareness.

How do maternal emotional regulation difficulties modulate the mother-infant behavioral synchrony?

Mother-infant synchrony is one of the most important processes in the development of socio-affective competencies in children. While maternal abilities and psychopathology are related to maladaptive mother-infant synchrony, it is as yet unclear how maternal emotion regulation difficulties contribute to it. Based on a panel of behavioral indicators (i.e., gaze, vocal, and motor), the present study examined mother-infant synchrony at 6 months of age in a modified version of Ainsworth's Strange Situation (n = 72 dyads). Mother-infant interaction sequences were characterized by indicators of complexity (LZ complexity of joint behavioral sequences) and of synchronization quality (cross-recurrence plot quantification). Results showed that mothers' touch was greater in the reunion condition than in the initial condition. Mothers' motor behaviors were associated with the global levels of infants' behavioral involvement in the reunion condition, unlike the symmetrical influence observed between mothers and infants in the initial condition. Results show that maternal anxiety mediates the relationships between mothers' emotion regulation difficulties and gaze, vocal, and motor synchrony between mothers and infants in the initial and reunion conditions. This study emphasizes the central role of maternal emotion regulation difficulties in the establishment of maladaptive synchrony and in the adjustments of maternal physical contacts with infants.

The influence of attachment styles on autonomic correlates of perspective-taking.

This study examined the effects of attachment styles on physiological responses during a perspective-taking task. Sixty-eight participants were selected according to attachment styles. Physiological responses were assessed using skin conductance responses (SCRs) in the three attachment groups (secure, insecure-anxious and insecure-avoidant) during the presentation of attachment-based pictures (distress, comfort or neutral) in two different perspective-taking conditions: self perspective-taking (i.e. imagine how you would feel in the given situation) or other perspective-taking (i.e. imagine how that person could feel in this situation). In the self perspective-taking condition, insecure-anxious individuals displayed higher SCRs than secure individuals for distress pictures. In the other perspective-taking condition, insecure-anxious individuals showed higher SCRs than secure individuals for comfort pictures. The results also showed a strong negative association between self-reported perspective-taking tendencies and SCRs in secure individuals. The findings suggest that perspective-taking plays an important role in the modulation of physiological responses in reaction to attachment-related pictures, which varies according to attachment styles.

Using centrality measures to extract core pattern of brain dynamics during the resting state.

The patterns of brain dynamics were studied during resting state on a macroscopic scale for control subjects and multiple sclerosis patients. Macroscopic brain dynamics is defined after successive coarse-grainings and selection of significant patterns and transitions based on Markov representation of brain activity. The resulting networks show that control dynamics is merely organized according to a single principal pattern whereas patients dynamics depict more variable patterns. Centrality measures are used to extract core dynamical pattern in brain dynamics and classification technique allow to define MS dynamics with relevant error rate.

Two is better than one: The effects of strategic cooperation on intra- and inter-brain connectivity by fNIRS.

Inter-brain synchronization during joint actions is a core question in social neuroscience, and the differential contribution of intra- and inter-brain functional connectivity has yet to be clarified along with the role of psychological variables such as perceived self-efficacy. The cognitive performance and the neural activation underlying the execution of joint actions were recorded by functional Near-Infrared imaging during a synchronicity game. An 8-channel array of optodes was positioned over the frontal and prefrontal regions. During the task, the dyads received reinforcing feedback that was experimentally manipulated to induce adoption of common strategies. Intra- and inter-brain connectivity indices were computed along with an inter-brain/intra-brain connectivity index (ConIndex). Finally, correlation analyses were run to assess the relationship between behavioral and physiological levels. The results showed that the external feedback could modulate participant responses in both behavioral and neural components. After the reinforcing manipulation, there were faster response times and increased inter-brain connectivity, and ConIndex emerged primarily over the dorsolateral prefrontal cortex. Additionally, the presence of significant correlations between response times and inter-brain connectivity revealed that only the "two-players connection" may guarantee an efficient performance. The present study provides a significant contribution to the identification of intra- and inter-brain functional connectivity when social reinforcement is provided.

A Case of Acoustic Shock with Post-trauma Trigeminal-Autonomic Activation.

This study reports the case of an acoustic shock injury (ASI), which did not result in a significant hearing loss, but was followed by manifold chronic symptoms both within (tinnitus, otalgia, tingling in the ear, tension in the ear, and red tympanum) and outside the ears (blocked nose, pain in the neck/temporal region). We suggest that these symptoms may result from a loop involving injury to middle ear muscles, peripheral inflammatory processes, activation and sensitization of the trigeminal nerve, the autonomic nervous system, and central feedbacks. The pathophysiology of this ASI is reminiscent of that observed in post-traumatic trigeminal-autonomic cephalalgia. This framework opens new and promising perspectives on the understanding and medical management of ASI.

Acute granulocyte macrophage-colony stimulating factor treatment modulates neuroinflammatory processes and promotes tactile recovery after spinal cord injury.

Neuroinflammation is known to play a key role in the prognosis of functional recovery after spinal cord injury (SCI). The involvement of microglial and mast cells in early and late stages of inflammation has been receiving increasing attention. This study was aimed at determining the influence of a pro-inflammatory cytokine, the granulocyte macrophage-colony stimulating factor (GM-CSF), on microglia and mast cell activation, glial scar formation and functional recovery following SCI. Rats were randomly injected with saline or GM-CSF one hour after a C4-C5 medio-lateral hemisection. To assess functional impairment and recovery, the rats were subjected to sensorimotor tasks for one month. Then, responses evoked by forepaw stimulation in the primary somatosensory cortex were recorded. We also quantified the changes in GM-CSF, IL-1ß, IL-6 and BDNF levels, the gliosis and lesion volume as well as microglial and mast cell density, and mast cell surface. Our findings show that GM-CSF promotes cortical reactivation and recovery of tactile abilities, whereas it does not influence motor performances. A transient decrease in pro-inflammatory cytokines after GM-CSF treatment was also observed, whereas the endogenous GM-CSF level was unchanged. While the beneficial role of GM-CSF in reducing glial scar is confirmed, our findings reveal that neuroinflammatory events mediated by microglial and mast cells as well as the alteration of IL-1ß and IL-6 levels are paralleled with an improvement in tactile recovery. These mechanisms could limit the duration and intensity of homeostatic imbalance and promote the plasticity of spared tissues.

Quantifying the dynamics of emotional expressions in family therapy of patients with anorexia nervosa.

Emotional interactions have been considered dynamical processes involved in the affective life of humans and their disturbances may induce mental disorders. Most studies of emotional interactions have focused on dyadic behaviors or self-reports of emotional states but neglected the dynamical processes involved in family therapy. The main objective of this study is to quantify the dynamics of emotional expressions and their changes using the family therapy of patients with anorexia nervosa as an example. Nonlinear methods characterize the variability of the dynamics at the level of the whole therapeutic system and reciprocal influence between the participants during family therapy. Results show that the variability of the dynamics is higher at the end of the therapy than at the beginning. The reciprocal influences between therapist and each member of the family and between mother and patient decrease with the course of family therapy. Our results support the development of new interpersonal strategies of emotion regulation during family therapy. The quantification of emotional dynamics can help understanding the emotional processes underlying psychopathology and evaluating quantitatively the changes achieved by the therapeutic intervention.

Correspondences between the binding characteristics of a non-natural peptide, Lei-Dab7, and the distribution of SK subunits in the rat central nervous system.

Small-conductance calcium-activated potassium channels (SK1-SK3 channels) are responsible for long-lasting hyperpolarization following action potential and contribute to the neuronal firing and integration signal. Two peptide toxins: apamin and Leiurotoxin 1, block this SK channels with high affinities. We generated a modified Leiurotoxin 1 (Lei-Dab7) that inhibits SK2 channels with a high selectivity. Competitive binding of radio-iodinated apamin to different rat brain structures, in the presence of native apamin and Lei-Dab7, has shown that dissociation constants differ by a factor of 1000 and thus demonstrated that ligand affinity is as important as ligand selectivity for a specific receptor. However, the lack of ligands discriminating between SK channel subunits is impeding the understanding of the role of each heteromeric SK channel type in different tissues. Our study aims to better understand the molecular combinations of SK channels and their association with specific functional implications. On this purpose, a clustering technique allows us to identify five groups of brain structures reflecting singular profiles of affinity and selectivity of Lei-Dab7 in comparison with apamin. The analysis of correspondences between Lei-Dab7 binding and distribution of SK subunits in these groups of brain structures suggests that functional heteromeric SK channels are involved in specific information processes.

Integrating neuroinformatics tools in TheVirtualBrain.

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the convergence of clinical, systems, and theoretical neuroscience in the analysis, visualization and modeling of neural and neuroimaging dynamics. TVB is composed of a flexible simulator for neural dynamics measured across scales from local populations to large-scale dynamics measured by electroencephalography (EEG), magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI), and core analytic and visualization functions, all accessible through a web browser user interface. A datatype system modeling neuroscientific data ties together these pieces with persistent data storage, based on a combination of SQL and HDF5. These datatypes combine with adapters allowing TVB to integrate other algorithms or computational systems. TVB provides infrastructure for multiple projects and multiple users, possibly participating under multiple roles. For example, a clinician might import patient data to identify several potential lesion points in the patient's connectome. A modeler, working on the same project, tests these points for viability through whole brain simulation, based on the patient's connectome, and subsequent analysis of dynamical features. TVB also drives research forward: the simulator itself represents the culmination of several simulation frameworks in the modeling literature. The availability of the numerical methods, set of neural mass models and forward solutions allows for the construction of a wide range of brain-scale simulation scenarios. This paper briefly outlines the history and motivation for TVB, describing the framework and simulator, giving usage examples in the web UI and Python scripting.

Affiliative behaviour and conflictual communication during brief family therapy of patients with anorexia nervosa.

OBJECTIVE: Although patients with anorexia nervosa (AN) present positive responses to family therapy, the key features of therapeutic changes still require identification. This study explores the role of conflictual communication and affiliative nonverbal behaviour in therapeutic change in brief strategic family therapy (BSFT) for AN patients. METHODS: Ten female AN patients and their parents were included in the sample and took part in a 6-month follow-up of BSFT. The durations of conflictual communication and of affiliative nonverbal behaviour estimated by eye contact were compared between the first and the last sessions of family-based treatment using nonparametric statistical tests. RESULTS: An increase of the Body Mass Index associated with an increase in the conflictual communication expressed during BSFT sessions were observed. Moreover, affiliative nonverbal behaviour expressed by the father and the patient decrease, after a BSFT follow-up, in conflictual situations only. By contrast, no significant difference was observed in affiliative nonverbal behaviour expressed by the mother. CONCLUSION: The present study demonstrates that the impact of the BSFT differs between members of a family: the AN patient and the father have established a new form of emotional functioning with a decrease in emotional involvement. The study of the combination between verbal and nonverbal communication can represent an important step in the understanding of the mechanisms of therapeutic change.

Mapping the dynamic repertoire of the resting brain.

The resting state dynamics of the brain shows robust features of spatiotemporal pattern formation but the actual nature of its time evolution remains unclear. Computational models propose specific state space organization which defines the dynamic repertoire of the resting brain. Nevertheless, methods devoted to the characterization of the organization of brain state space from empirical data still lack and thus preclude comparison of the hypothetical dynamical repertoire of the brain with the actual one. We propose here an algorithm based on set oriented approach of dynamical system to extract a coarse-grained organization of brain state space on the basis of EEG signals. We use it for comparing the organization of the state space of large-scale simulation of brain dynamics with actual brain dynamics of resting activity in healthy subjects. The dynamical skeleton obtained for both simulated brain dynamics and EEG data depicts similar structures. The skeleton comprised chains of macro-states that are compatible with current interpretations of brain functioning as series of metastable states. Moreover, macro-scale dynamics depicts correlation features that differentiate them from random dynamics. We here propose a procedure for the extraction and characterization of brain dynamics at a macro-scale level. It allows for the comparison between models of brain dynamics and empirical measurements and leads to the definition of an effective coarse-grained dynamical skeleton of spatiotemporal brain dynamics.

Decrease of mutual information in brain electrical activity of patients with relapsing-remitting multiple sclerosis.

The disturbance of cortical communication has been hypothesized as an important factor in the appearance of cognitive impairment in (MS). Cortical communication is quantified here in control subjects and patients with relapsing-remitting multiple sclerosis (RRMS) on the basis of mean coherence in the δ, θ, α, ß and γ bands and using mutual information computed between pairs of bipolar EEG signals recorded during resting condition. Each patient received also a cognitive assessment using a battery of neuropsychological tests specific to cognitive deficits in MS. No difference was observed for the coherence indices whereas inter-hemispheric and right hemisphere mutual information is significantly lower in patients with MS than in control subjects. Moreover, inter-hemispheric mutual information decrease significantly with illness duration and right mutual information differentiate cognitively deficient and non-deficient patients. Mutual information allows to quantify the cortical communication in patients with RRMS and is related to clinical characteristics. Cortical communication quantified in a resting state might be a potential marker for the neurological damage induced by RRMS.

Delay independence of mutual-information rate of two symbolic sequences.

Introduced by Shannon as a "rate of actual transmission," mutual information rate (MIR) is an extension of mutual information to a pair of dynamical processes. We show a delay-independence theorem, according to which MIR is not sensitive to a time shift between the two processes. Numerical studies of several benchmark situations confirm that this theoretical asymptotic property remains valid for realistic finite sequences. Estimations based on block entropies and a causal state machine algorithm perform better than an estimation based on a Lempel-Ziv compression algorithm provided that block length and maximum history length, respectively, can be chosen larger than the delay. MIR is thus a relevant index for measuring nonlinear correlations between two experimental or simulated sequences when the transmission delay (in input-output devices) or dephasing (in coupled systems) is variable or unknown.

Entropy estimation of very short symbolic sequences.

While entropy per unit time is a meaningful index to quantify the dynamic features of experimental time series, its estimation is often hampered in practice by the finite length of the data. We here investigate the performance of entropy estimation procedures, relying either on block entropies or Lempel-Ziv complexity, when only very short symbolic sequences are available. Heuristic analytical arguments point at the influence of temporal correlations on the bias and statistical fluctuations, and put forward a reduced effective sequence length suitable for error estimation. Numerical studies are conducted using, as benchmarks, the wealth of different dynamic regimes generated by the family of logistic maps and stochastic evolutions generated by a Markov chain of tunable correlation time. Practical guidelines and validity criteria are proposed. For instance, block entropy leads to a dramatic overestimation for sequences of low entropy, whereas it outperforms Lempel-Ziv complexity at high entropy. As a general result, the quality of entropy estimation is sensitive to the sequence temporal correlation hence self-consistently depends on the entropy value itself, thus promoting a two-step procedure. Lempel-Ziv complexity is to be preferred in the first step and remains the best estimator for highly correlated sequences.

Assessment of bursting activity and interspike intervals variability: a case study for methodological comparison.

The detection and characterization of bursting activity remains a topic where no consensual definition has been reached so far. We compare here three different approaches of spike trains variability: statistical characterization (average frequency, coefficient of variation), burst detection (Poisson and rank surprise) and multi-scale analysis (detrended fluctuations analysis). Using both real and simulated data, we show that Poisson surprise provides information closely related to the coefficient of variation and that rank surprise detects significant bursts which are associated with long-range correlations. Since these long-range correlations are only adequately characterized with multi-scale analysis, this study emphasizes the complementarity of these approaches for the complete characterization of spike trains.

Cellular automata approach of transmembrane ionic currents.

Ionic currents across neuron and glial cells membranes lie at the origin of the entire brain electrophysiology. They are the common root of functional brain dynamics and mesoscopic or macroscopic phenomena such as extracellular fields. In particular, they provide the relevant basis to relate cellular electrophysiology and macroscopic dipole models. In order to derive robust features and to envision the multi-scale approaches required to connect the different levels of observation, an essential prerequisite is to have minimal model of elementary ionic motions. In this paper, we propose a general cellular automata framework allowing to investigate the distribution of ionic currents in heterogeneous media interspersed with membranes, from which follows the local electromagnetic field.

Dynamics of emotional expression in autobiographic speech of patients with anorexia nervosa.

Emotional disturbances in persons with anorexia nervosa have mainly been documented using static descriptions. This study presents the temporal organisation of emotional expression in autobiographical speech of anorexic patients and thereby provides a first attempt to quantify the dynamics of emotions in patients' speech. The temporal pattern of emotional expression for persons with anorexia nervosa was studied after transforming the autobiographical narratives of 14 patients and 13 matched controls into symbolic sequences of positive, negative, and neutral emotional expressions. These symbolic sequences of emotional states and silences were analyzed using static and dynamic indices. Static indices showed that patients with anorexia nervosa expressed more negative emotions and fewer neutral states than control participants. Dynamic indices showed in patients' speech a cycle of negative emotions and silence. These results showed specific dynamics of emotional expression in persons with anorexia nervosa characterised by the presence of negative emotional perseveration. The possible clinical implications of these findings are discussed.

Distinct patterns of striatal medium spiny neuron activity during the natural sleep-wake cycle.

Striatal medium-sized spiny neurons (MSNs) integrate and convey information from the cerebral cortex to the output nuclei of the basal ganglia. Intracellular recordings from anesthetized animals show that MSNs undergo spontaneous transitions between hyperpolarized and depolarized states. State transitions, regarded as necessary for eliciting action potential firing in MSNs, are thought to control basal ganglia function by shaping striatal output. Here, we use an anesthetic-free rat preparation to show that the intracellular activity of MSNs is not stereotyped and depends critically on vigilance state. During slow-wave sleep, much as during anesthesia, MSNs displayed rhythmic step-like membrane potential shifts, correlated with cortical field potentials. However, wakefulness was associated with a completely different pattern of temporally disorganized depolarizing synaptic events of variable amplitude. Transitions from slow-wave sleep to wakefulness converted striatal discharge from a cyclic brisk firing to an irregular pattern of action potentials. These findings illuminate different capabilities of information processing in basal ganglia networks, suggesting in particular that a novel style of striatal computation is associated with the waking state.