116 research outputs found

    A dynamic link between respiration and arousal

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    Viewing brain function through the lense of other physiological processes has critically added to our understanding of human cognition. Further advances though may need a closer look at the interactions between these physiological processes themselves. Here we characterise the interplay of the highly periodic, and metabolically vital respiratory process and fluctuations in arousal neuromodulation, a process classically seen as non-periodic. In data of three experiments (N = 56 / 27 / 25) we tested for covariations in tidal volume (respiration) and pupil size (arousal). After substantiating a robust coupling in the largest dataset, we further show that coupling strength decreases during task performance compared with rest, and that it mirrors a decreased respiratory rate when participants take deeper breaths. Taken together, these findings suggest a stronger link between respiratory and arousal processes than previously thought. Moreover, these links imply a stronger coupling during periods of rest, and the effect of respiratory rate on the coupling suggests a driving role. As a consequence, studying the role of neuromodulatory arousal on cortical function may also need to consider respiratory influences.<br/

    Respiration modulates oscillatory neural network activity at rest

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    Despite recent advances in understanding how respiration affects neural signalling to influence perception, cognition, and behaviour, it is yet unclear to what extent breathing modulates brain oscillations at rest. We acquired respiration and resting state magnetoencephalography (MEG) data from human participants to investigate if, where, and how respiration cyclically modulates oscillatory amplitudes (2 to 150 Hz). Using measures of phase–amplitude coupling, we show respiration-modulated brain oscillations (RMBOs) across all major frequency bands. Sources of these modulations spanned a widespread network of cortical and subcortical brain areas with distinct spectrotemporal modulation profiles. Globally, delta and gamma band modulations varied with distance to the head centre, with stronger modulations at distal (versus central) cortical sites. Overall, we provide the first comprehensive mapping of RMBOs across the entire brain, highlighting respiration–brain coupling as a fundamental mechanism to shape neural processing within canonical resting state and respiratory control networks (RCNs)

    Coupling of pupil- and neuronal population dynamics reveals diverse influences of arousal on cortical processing

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    Fluctuations in arousal, controlled by subcortical neuromodulatory systems, continuously shape cortical state, with profound consequences for information processing. Yet, how arousal signals influence cortical population activity in detail has so far only been characterized for a few selected brain regions. Traditional accounts conceptualize arousal as a homogeneous modulator of neural population activity across the cerebral cortex. Recent insights, however, point to a higher specificity of arousal effects on different components of neural activity and across cortical regions. Here, we provide a comprehensive account of the relationships between fluctuations in arousal and neuronal population activity across the human brain. Exploiting the established link between pupil size and central arousal systems, we performed concurrent magnetoencephalographic (MEG) and pupillographic recordings in a large number of participants, pooled across three laboratories. We found a cascade of effects relative to the peak timing of spontaneous pupil dilations: Decreases in low-frequency (2-8 Hz) activity in temporal and lateral frontal cortex, followed by increased high-frequency (>64 Hz) activity in mid-frontal regions, followed by monotonic and inverted U relationships with intermediate frequency-range activity (8-32 Hz) in occipito-parietal regions. Pupil-linked arousal also coincided with widespread changes in the structure of the aperiodic component of cortical population activity, indicative of changes in the excitation-inhibition balance in underlying microcircuits. Our results provide a novel basis for studying the arousal modulation of cognitive computations in cortical circuits

    Surmising synchrony of sound and sight:Factors explaining variance of audiovisual integration in hurdling, tap dancing and drumming

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    Auditory and visual percepts are integrated even when they are not perfectly temporally aligned with each other, especially when the visual signal precedes the auditory signal. This window of temporal integration for asynchronous audiovisual stimuli is relatively well examined in the case of speech, while other natural action-induced sounds have been widely neglected. Here, we studied the detection of audiovisual asynchrony in three different whole-body actions with natural action-induced sounds–hurdling, tap dancing and drumming. In Study 1, we examined whether audiovisual asynchrony detection, assessed by a simultaneity judgment task, differs as a function of sound production intentionality. Based on previous findings, we expected that auditory and visual signals should be integrated over a wider temporal window for actions creating sounds intentionally (tap dancing), compared to actions creating sounds incidentally (hurdling). While percentages of perceived synchrony differed in the expected way, we identified two further factors, namely high event density and low rhythmicity, to induce higher synchrony ratings as well. Therefore, we systematically varied event density and rhythmicity in Study 2, this time using drumming stimuli to exert full control over these variables, and the same simultaneity judgment tasks. Results suggest that high event density leads to a bias to integrate rather than segregate auditory and visual signals, even at relatively large asynchronies. Rhythmicity had a similar, albeit weaker effect, when event density was low. Our findings demonstrate that shorter asynchronies and visual-first asynchronies lead to higher synchrony ratings of whole-body action, pointing to clear parallels with audiovisual integration in speech perception. Overconfidence in the naturally expected, that is, synchrony of sound and sight, was stronger for intentional (vs. incidental) sound production and for movements with high (vs. low) rhythmicity, presumably because both encourage predictive processes. In contrast, high event density appears to increase synchronicity judgments simply because it makes the detection of audiovisual asynchrony more difficult. More studies using real-life audiovisual stimuli with varying event densities and rhythmicities are needed to fully uncover the general mechanisms of audiovisual integration

    Comparison of undirected frequency-domain connectivity measures for cerebro-peripheral analysis

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    Analyses of cerebro-peripheral connectivity aim to quantify ongoing coupling between brain activity (measured by MEG/EEG) and peripheral signals such as muscle activity, continuous speech, or physiological rhythms (such as pupil dilation or respiration). Due to the distinct rhythmicity of these signals, undirected connectivity is typically assessed in the frequency domain. This leaves the investigator with two critical choices, namely a) the appropriate measure for spectral estimation (i.e., the transformation into the frequency domain) and b) the actual connectivity measure. As there is no consensus regarding best practice, a wide variety of methods has been applied. Here we systematically compare combinations of six standard spectral estimation methods (comprising fast Fourier and continuous wavelet transformation, bandpass filtering, and short-time Fourier transformation) and six connectivity measures (phase-locking value, Gaussian-Copula mutual information, Rayleigh test, weighted pairwise phase consistency, magnitude squared coherence, and entropy). We provide performance measures of each combination for simulated data (with precise control over true connectivity), a single-subject set of real MEG data, and a full group analysis of real MEG data. Our results show that, overall, WPPC and GCMI tend to outperform other connectivity measures, while entropy was the only measure sensitive to bimodal deviations from a uniform phase distribution. For group analysis, choosing the appropriate spectral estimation method appears to be more critical than the connectivity measure. We discuss practical implications (sampling rate, SNR, computation time, and data length) and aim to provide recommendations tailored to particular research questions

    Non-Equilibrium Large N Yukawa Dynamics: marching through the Landau pole

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    The non-equilibrium dynamics of a Yukawa theory with N fermions coupled to a scalar field is studied in the large N limit with the goal of comparing the dynamics predicted from the renormalization group improved effective potential to that obtained including the fermionic backreaction. The effective potential is of the Coleman-Weinberg type. Its renormalization group improvement is unbounded from below and features a Landau pole. When viewed self-consistently, the initial time singularity does not arise. The different regimes of the dynamics of the fully renormalized theory are studied both analytically and numerically. Despite the existence of a Landau pole in the model, the dynamics of the mean field is smooth as it passes the location of the pole. This is a consequence of a remarkable cancellation between the effective potential and the dynamical chiral condensate. The asymptotic evolution is effectively described by a quartic upright effective potential. In all regimes, profuse particle production results in the formation of a dense fermionic plasma with occupation numbers nearly saturated up to a scale of the order of the mean field. This can be interpreted as a chemical potential. We discuss the implications of these results for cosmological preheating.Comment: 36 pages, 14 figures, LaTeX, submitted to Physical Review

    Anomalous Pseudoscalar-Photon Vertex In and Out of Equilibrium

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    The anomalous pseudoscalar-photon vertex is studied in real time in and out of equilibrium in a constituent quark model. The goal is to understand the in-medium modifications of this vertex, exploring the possibility of enhanced isospin breaking by electromagnetic effects as well as the formation of neutral pion condensates in a rapid chiral phase transition in peripheral, ultrarelativistic heavy-ion collisions. In equilibrium the effective vertex is afflicted by infrared and collinear singularities that require hard thermal loop (HTL) and width corrections of the quark propagator. The resummed effective equilibrium vertex vanishes near the chiral transition in the chiral limit. In a strongly out of equilibrium chiral phase transition we find that the chiral condensate drastically modifies the quark propagators and the effective vertex. The ensuing dynamics for the neutral pion results in a potential enhancement of isospin breaking and the formation of π0\pi^0 condensates. While the anomaly equation and the axial Ward identity are not modified by the medium in or out of equilibrium, the effective real-time pseudoscalar-photon vertex is sensitive to low energy physics.Comment: Revised version to appear in Phys. Rev. D. 42 pages, 4 figures, uses Revte

    Autologous humanized PDX modeling for immuno-oncology recapitulates features of the human tumor microenvironment.

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    BACKGROUND: Interactions between immune and tumor cells are critical to determining cancer progression and response. In addition, preclinical prediction of immune-related drug efficacy is limited by interspecies differences between human and mouse, as well as inter-person germline and somatic variation. To address these gaps, we developed an autologous system that models the tumor microenvironment (TME) from individual patients with solid tumors. METHOD: With patient-derived bone marrow hematopoietic stem and progenitor cells (HSPCs), we engrafted a patient\u27s hematopoietic system in MISTRG6 mice, followed by transfer of patient-derived xenograft (PDX) tissue, providing a fully genetically matched model to recapitulate the individual\u27s TME. We used this system to prospectively study tumor-immune interactions in patients with solid tumor. RESULTS: Autologous PDX mice generated innate and adaptive immune populations; these cells populated the TME; and tumors from autologously engrafted mice grew larger than tumors from non-engrafted littermate controls. Single-cell transcriptomics revealed a prominent vascular endothelial growth factor A (VEGFA) signature in TME myeloid cells, and inhibition of human VEGF-A abrogated enhanced growth. CONCLUSIONS: Humanization of the interleukin 6 locus in MISTRG6 mice enhances HSPC engraftment, making it feasible to model tumor-immune interactions in an autologous manner from a bedside bone marrow aspirate. The TME from these autologous tumors display hallmarks of the human TME including innate and adaptive immune activation and provide a platform for preclinical drug testing
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