EEG-Meta-Microstates: Towards a More Objective Use of Resting-State EEG Microstate Findings Across Studies.

Over the last decade, EEG resting-state microstate analysis has evolved from a niche existence to a widely used and well-accepted methodology. The rapidly increasing body of empirical findings started to yield overarching patterns of associations of biological and psychological states and traits with specific microstate classes. However, currently, this cross-referencing among apparently similar microstate classes of different studies is typically done by "eyeballing" of printed template maps by the individual authors, lacking a systematic procedure. To improve the reliability and validity of future findings, we present a tool to systematically collect the actual data of template maps from as many published studies as possible and present them in their entirety as a matrix of spatial similarity. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps from ongoing or published studies. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps in the literature. The analysis of 40 included sets of template maps indicated that: (i) there is a high degree of similarity of template maps across studies, (ii) similar template maps were associated with converging empirical findings, and (iii) representative meta-microstates can be extracted from the individual studies. We hope that this tool will be useful in coming to a more comprehensive, objective, and overarching representation of microstate findings

A Critical Analysis on Characterizing the Meditation Experience Through the Electroencephalogram

Meditation practices, originated from ancient traditions, have increasingly received attention due to their potential benefits to mental and physical health. The scientific community invests efforts into scrutinizing and quantifying the effects of these practices, especially on the brain. There are methodological challenges in describing the neural correlates of the subjective experience of meditation. We noticed, however, that technical considerations on signal processing also don't follow standardized approaches, which may hinder generalizations. Therefore, in this article, we discuss the usage of the electroencephalogram (EEG) as a tool to study meditation experiences in healthy individuals. We describe the main EEG signal processing techniques and how they have been translated to the meditation field until April 2020. Moreover, we examine in detail the limitations/assumptions of these techniques and highlight some good practices, further discussing how technical specifications may impact the interpretation of the outcomes. By shedding light on technical features, this article contributes to more rigorous approaches to evaluate the construct of meditation

Neuronal Assemblies Evidence Distributed Interactions within a Tactile Discrimination Task in Rats

Accumulating evidence suggests that neural interactions are distributed and relate to animal behavior, but many open questions remain. The neural assembly hypothesis, formulated by Hebb, states that synchronously active single neurons may transiently organize into functional neural circuits—neuronal assemblies (NAs)—and that would constitute the fundamental unit of information processing in the brain. However, the formation, vanishing, and temporal evolution of NAs are not fully understood. In particular, characterizing NAs in multiple brain regions over the course of behavioral tasks is relevant to assess the highly distributed nature of brain processing. In the context of NA characterization, active tactile discrimination tasks with rats are elucidative because they engage several cortical areas in the processing of information that are otherwise masked in passive or anesthetized scenarios. In this work, we investigate the dynamic formation of NAs within and among four different cortical regions in long-range fronto-parieto-occipital networks (primary somatosensory, primary visual, prefrontal, and posterior parietal cortices), simultaneously recorded from seven rats engaged in an active tactile discrimination task. Our results first confirm that task-related neuronal firing rate dynamics in all four regions is significantly modulated. Notably, a support vector machine decoder reveals that neural populations contain more information about the tactile stimulus than the majority of single neurons alone. Then, over the course of the task, we identify the emergence and vanishing of NAs whose participating neurons are shown to contain more information about animal behavior than randomly chosen neurons. Taken together, our results further support the role of multiple and distributed neurons as the functional unit of information processing in the brain (NA hypothesis) and their link to active animal behavior

Code

Code for date analysis and figures presented in the manuscrip

Temporal Contrast Enhancement as a Framework for Understanding Paradoxical Heat Sensation

In this project we demonstrate contrast enhancement principles are applicable to thermosensation and offer a novel framework for understanding thermal perceptual phenomena, such as paradoxical heat. This is the repository for pre-print, code and data for the associated manuscript

Measures for brain connectivity analysis: nodes centrality and their invariant patterns

The high dynamical complexity of the brain is related to its small-world topology, which enable both segregated and integrated information processing capabilities. Several measures of connectivity estimation have already been employed to characterize functional brain networks from multivariate electrophysiological data. However, understanding the properties of each measure that lead to a better description of the real topology and capture the complex phenomena present in the brain remains challenging. In this work we compared four nonlinear connectivity measures and show that each method characterizes distinct features of brain interactions. The results suggest an invariance of global network parameters from different behavioral states and that more complete description may be reached considering local features, independently of the connectivity measure employed. Our findings also point to future perspectives in connectivity studies that combine distinct and complementary dependence measures in assembling higher dimensions manifolds

Thermal contrast enhancement predicts paradoxical heat sensation

Acknowledgements: We thank Amalie Holm Lund Sørensen, Anna Villaume Stuckert, Bianka Szöllösi, Camile Maria Costa Correa, Dora Veraszto, Dunja Paunovic, Katarina Vulic, Laura Gaini, Magnus Knudsen, Melina Vejlø, Povilas Tarailis and Sara Viuf for their help with data collection. We also thank Signe Kirk Brødbæk and Thea Rolskov Sloth for data preparation. This publication is based upon work from and supported by the COST Action CA18106 (European Cooperation in Science and Technology). A.G.M., C.S.D., J.F.E. and F.F. are supported by a European Research Council Starting Grant (ERC-2020-StG-948838). M.G.A. is supported by a Lundbeckfonden Fellowship (R272-2017-4345), and M.G.A. and A.S.C. are supported by a European Research Council Starting Grant (ERC-2020-StG-948788). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper.AbstractParadoxical Heat Sensation (PHS) is the remarkable feeling of warmth or heat pain while the skin is cooling. Despite its initial documentation over 100 years ago, a unified explanation for this perplexing experience remains elusive. Here we apply contrast enhancement principles, known for their instrumental role in understanding visual illusions, to the domain of thermosensation. Contrast enhancement describes the amplification of two contrasting visual features, such as the enhanced perception of an edge between a light and dark bar. In thermosensation, this encompasses an enhancement of the difference between sequential warming and cooling of the skin, and is defined as the normalised difference between successive temporal warm and cold temperatures. Remarkably, thermal contrast predicts the occurrence of PHS. Our findings reveal compelling evidence supporting the role of thermal contrast in the generation of PHS, shedding light on its underlying mechanism and offering a framework for broader encoding principles in thermosensation and pain.</jats:p

Microstates in complex and dynamical environments: Unraveling situational awareness in critical helicopter landing maneuvers

Understanding decision‐making in complex and dynamic environments is relevant for designing strategies targeting safety improvements and error rate reductions. However, studies evaluating brain dynamics in realistic situations are scarce in the literature. Given the evidence that specific microstates may be associated with perception and attention, in this work we explored for the first time the application of the microstate model in an ecological, dynamic and complex scenario. More specifically, we evaluated elite helicopter pilots during engine‐failure missions in the vicinity of the so called “dead man's curve,” which establishes the operational limits for a safe landing after the execution of a recovery maneuver (autorotation). Pilots from the Brazilian Air Force flew a AS‐350 helicopter in a certified aerodrome and physiological sensor data were synchronized with the aircraft's flight test instrumentation. We assessed these neural correlates during maneuver execution, by comparing their modulations and source reconstructed activity with baseline epochs before and after flights. We show that the topographies of our microstate templates with 4, 5, and 6 classes resemble the literature, and that a distinct modulation characterizes decision‐making intervals. Moreover, the source reconstruction result points to a differential activity in the medial prefrontal cortex, which is associated to emotional regulation circuits in the brain. Our results suggest that microstates are promising neural correlates to evaluate realistic situations, even in a challenging and intrinsically noisy environment. Furthermore, it strengthens their usage and expands their application for studying cognition under more realistic conditions

Microstates in complex and dynamical environments: Unraveling situational awareness in critical helicopter landing maneuvers.

Understanding decision-making in complex and dynamic environments is relevant for designing strategies targeting safety improvements and error rate reductions. However, studies evaluating brain dynamics in realistic situations are scarce in the literature. Given the evidence that specific microstates may be associated with perception and attention, in this work we explored for the first time the application of the microstate model in an ecological, dynamic and complex scenario. More specifically, we evaluated elite helicopter pilots during engine-failure missions in the vicinity of the so called "dead man's curve," which establishes the operational limits for a safe landing after the execution of a recovery maneuver (autorotation). Pilots from the Brazilian Air Force flew a AS-350 helicopter in a certified aerodrome and physiological sensor data were synchronized with the aircraft's flight test instrumentation. We assessed these neural correlates during maneuver execution, by comparing their modulations and source reconstructed activity with baseline epochs before and after flights. We show that the topographies of our microstate templates with 4, 5, and 6 classes resemble the literature, and that a distinct modulation characterizes decision-making intervals. Moreover, the source reconstruction result points to a differential activity in the medial prefrontal cortex, which is associated to emotional regulation circuits in the brain. Our results suggest that microstates are promising neural correlates to evaluate realistic situations, even in a challenging and intrinsically noisy environment. Furthermore, it strengthens their usage and expands their application for studying cognition under more realistic conditions