Classification of Complex Emotions Using EEG and Virtual Environment: Proof of Concept and Therapeutic Implication.

During the last decades, neurofeedback training for emotional self-regulation has received significant attention from scientific and clinical communities. Most studies have investigated emotions using functional magnetic resonance imaging (fMRI), including the real-time application in neurofeedback training. However, the electroencephalogram (EEG) is a more suitable tool for therapeutic application.

Capturing the non-stationarity of whole-brain dynamics underlying human brain states.

Brain dynamics depicts an extremely complex energy landscape that changes over time, and its characterisation is a central unsolved problem in neuroscience. We approximate the non-stationary landscape sustained by the human brain through a novel mathematical formalism that allows us characterise the attractor structure, i.e.

Loss of consciousness reduces the stability of brain hubs and the heterogeneity of brain dynamics.

Low-level states of consciousness are characterized by disruptions of brain activity that sustain arousal and awareness. Yet, how structural, dynamical, local and network brain properties interplay in the different levels of consciousness is unknown. Here, we study fMRI brain dynamics from patients that suffered brain injuries leading to a disorder of consciousness and from healthy subjects undergoing propofol-induced sedation.

Rare long-range cortical connections enhance human information processing.

What are the key topological features of connectivity critically relevant for generating the dynamics underlying efficient cortical function? A candidate feature that has recently emerged is that the connectivity of the mammalian cortex follows an exponential distance rule, which includes a small proportion of long-range high-weight anatomical exceptions to this rule. Whole-brain modeling of large-scale human neuroimaging data in 1,003 participants offers the unique opportunity to create two models, with and without long-range exceptions, and explicitly study their functional consequences. We found that rare long-range exceptions are crucial for significantly improving information processing.

Understanding neural signals of post-decisional performance monitoring: An integrative review.

Performance monitoring is a key cognitive function, allowing to detect mistakes and adapt future behavior. Post-decisional neural signals have been identified that are sensitive to decision accuracy, decision confidence and subsequent adaptation. Here, we review recent work that supports an understanding of late error/confidence signals in terms of the computational process of post-decisional evidence accumulation.

Nonequilibrium brain dynamics as a signature of consciousness.

The cognitive functions of human and nonhuman primates rely on the dynamic interplay of distributed neural assemblies. As such, it seems unlikely that cognition can be supported by macroscopic brain dynamics at the proximity of equilibrium. We confirmed this hypothesis by investigating electrocorticography data from nonhuman primates undergoing different states of unconsciousness (sleep, and anesthesia with propofol, ketamine, and ketamine plus medetomidine), and functional magnetic resonance imaging data from humans, both during deep sleep and under propofol anesthesia.

Perturbations in dynamical models of whole-brain activity dissociate between the level and stability of consciousness.

Consciousness transiently fades away during deep sleep, more stably under anesthesia, and sometimes permanently due to brain injury. The development of an index to quantify the level of consciousness across these different states is regarded as a key problem both in basic and clinical neuroscience. We argue that this problem is ill-defined since such an index would not exhaust all the relevant information about a given state of consciousness.

Statistical Properties of Color Matching Functions.

In trichromats, color vision entails the projection of an infinite-dimensional space (the one containing all possible electromagnetic power spectra) onto the three-dimensional space that modulates the activity of the three types of cones. This drastic reduction in dimensionality gives rise to metamerism, that is, the perceptual chromatic equivalence between two different light spectra. The classes of equivalence of metamerism are revealed by color-matching experiments in which observers adjust the intensity of three monochromatic light beams of three preset wavelengths (the primaries) to produce a mixture that is perceptually equal to a given monochromatic target stimulus.

Circuit mechanisms for the chemical modulation of cortex-wide network interactions and behavioral variability.

Influential theories postulate distinct roles of catecholamines and acetylcholine in cognition and behavior. However, previous physiological work reported similar effects of these neuromodulators on the response properties (specifically, the gain) of individual cortical neurons. Here, we show a double dissociation between the effects of catecholamines and acetylcholine at the level of large-scale interactions between cortical areas in humans.

Dynamical consequences of regional heterogeneity in the brain's transcriptional landscape.

Brain regions vary in their molecular and cellular composition, but how this heterogeneity shapes neuronal dynamics is unclear. Here, we investigate the dynamical consequences of regional heterogeneity using a biophysical model of whole-brain functional magnetic resonance imaging (MRI) dynamics in humans. We show that models in which transcriptional variations in excitatory and inhibitory receptor (E:I) gene expression constrain regional heterogeneity more accurately reproduce the spatiotemporal structure of empirical functional connectivity estimates than do models constrained by global gene expression profiles or MRI-derived estimates of myeloarchitecture.

Genetic influences on hub connectivity of the human connectome.

Brain network hubs are both highly connected and highly inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization are poorly understood. Using diffusion-weighted magnetic resonance imaging in twins, we identify a major role for genes, showing that they preferentially influence connectivity strength between network hubs of the human connectome.

Rapid attentional adaptations due to language (monolingual vs bilingual) context.

Does our general attentional system adapt to the language context we are in? Bilinguals switch between contexts in which only one language is present or both languages are equiprobable. Previous research by Wu and Thierry (2013) suggested that the bilingual language context can modify the workings of inhibitory control mechanisms. Here we investigate whether this can be replicated and whether other attentional mechanisms (alerting and orienting) also adjust depending on whether we are in a bilingual or a monolingual situation.

Macroscopic Quantities of Collective Brain Activity during Wakefulness and Anesthesia.

The study of states of arousal is key to understand the principles of consciousness. Yet, how different brain states emerge from the collective activity of brain regions remains unknown. Here, we studied the fMRI brain activity of monkeys during wakefulness and anesthesia-induced loss of consciousness.

Brain Connectivity Studies on Structure-Function Relationships: A Short Survey with an Emphasis on Machine Learning.

This short survey reviews the recent literature on the relationship between the brain structure and its functional dynamics. Imaging techniques such as diffusion tensor imaging (DTI) make it possible to reconstruct axonal fiber tracks and describe the structural connectivity (SC) between brain regions. By measuring fluctuations in neuronal activity, functional magnetic resonance imaging (fMRI) provides insights into the dynamics within this structural network.

Leonardo da Vinci and the search for order in neuroscience.

Finding order in disorder is a hallmark of science and art. In the time of Leonardo da Vinci, the schism between science and art had yet to arise. In fact, Leonardo freely used scientific methods for his art and vice versa; for example, when he used his observations of turbulent, whirling water to guide his artistic imagination.

Early life multiple exposures and child cognitive function: A multi-centric birth cohort study in six European countries.

Epidemiological studies mostly focus on single environmental exposures. This study aims to systematically assess associations between a wide range of prenatal and childhood environmental exposures and cognition. The study sample included data of 1298 mother-child pairs, children were 6-11 years-old, from six European birth cohorts.

Ketamine disrupts naturalistic coding of working memory in primate lateral prefrontal cortex networks.

Ketamine is a dissociative anesthetic drug, which has more recently emerged as a rapid-acting antidepressant. When acutely administered at subanesthetic doses, ketamine causes cognitive deficits like those observed in patients with schizophrenia, including impaired working memory. Although these effects have been linked to ketamine's action as an N-methyl-D-aspartate receptor antagonist, it is unclear how synaptic alterations translate into changes in brain microcircuit function that ultimately influence cognition.

Early detection of language categories in face perception.

Does language categorization influence face identification? The present study addressed this question by means of two experiments. First, to establish language categorization of faces, the memory confusion paradigm was used to create two language categories of faces, Spanish and English. Subsequently, participants underwent an oddball paradigm, in which faces that had been previously paired with one of the two languages (Spanish or English), were presented.

Foreign Language Processing Undermines Affect Labeling.

Unlabelled: Identifying emotional states and explicitly putting them into words, known as affect labeling, reduces amygdala activation. Crucially, bilinguals do not only label emotions in their native language; they sometimes do it in their foreign language as well. However, one's foreign languages are less emotional and more cognitively demanding than one's native language.

Microsaccades during high speed continuous visual search.

Here, we provide an analysis of the microsaccades that occurred during continuous visual search and targeting of small faces that we pasted either into cluttered background photos or into a simple gray background. Subjects continuously used their eyes to target singular 3-degree upright or inverted faces in changing scenes. As soon as the participant's gaze reached the target face, a new face was displayed in a different and random location.

Bridging the gap between single receptor type activity and whole-brain dynamics.

What is the effect of activating a single modulatory neuronal receptor type on entire brain network dynamics? Can such effect be isolated at all? These are important questions because characterizing elementary neuronal processes that influence network activity across the given anatomical backbone is fundamental to guide theories of brain function. Here, we introduce the concept of the cortical 'receptome' taking into account the distribution and densities of expression of different modulatory receptor types across the brain's anatomical connectivity matrix. By modelling whole-brain dynamics in silico, we suggest a bidirectional coupling between modulatory neurotransmission and neuronal connectivity hardware exemplified by the impact of single serotonergic (5-HT) receptor types on cortical dynamics.

Directed information exchange between cortical layers in macaque V1 and V4 and its modulation by selective attention.

Achieving behavioral goals requires integration of sensory and cognitive information across cortical laminae and cortical regions. How this computation is performed remains unknown. Using local field potential recordings and spectrally resolved conditional Granger causality (cGC) analysis, we mapped visual information flow, and its attentional modulation, between cortical layers within and between macaque brain areas V1 and V4.

Noise-driven multistability vs deterministic chaos in phenomenological semi-empirical models of whole-brain activity.

An outstanding open problem in neuroscience is to understand how neural systems are capable of producing and sustaining complex spatiotemporal dynamics. Computational models that combine local dynamics with in vivo measurements of anatomical and functional connectivity can be used to test potential mechanisms underlying this complexity. We compared two conceptually different mechanisms: noise-driven switching between equilibrium solutions (modeled by coupled Stuart-Landau oscillators) and deterministic chaos (modeled by coupled Rossler oscillators).

Prefrontal cortex represents heuristics that shape choice bias and its integration into future behavior.

Goal-directed behavior requires integrating sensory information with prior knowledge about the environment. Behavioral biases that arise from these priors could increase positive outcomes when the priors match the true structure of the environment, but mismatches also happen frequently and could cause unfavorable outcomes. Biases that reduce gains and fail to vanish with training indicate fundamental suboptimalities arising from ingrained heuristics of the brain.