Predicting Solvation Free Energies from the Minnesota Solvation Database Using Classical Density Functional Theory Based on the PC-SAFT Equation of State

We critically assess the capabilities of classical density functional theory (DFT) based on the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state to predict the solvation free energies of small molecules in various hydrocarbon solvents. We compare DFT results with experimental data from the Minnesota solvation database and utilize statistical methods to analyze the accuracy of our approach, as well as its weaknesses. The mean absolute error of the solvation free energies is 3.7 kJ mol-1 for n-alkane solvents, ranging from pentane to hexadecane, with 473 solute-solvent systems. For solvents consisting of cyclic hydrocarbons (cyclohexane, benzene, toluene, and ethylbenzene) with 245 solute-solvent systems, we report a slightly larger mean absolute error of 4.2 kJ mol-1. We identify three possible sources of errors: (i) the neglect of solute-solvent and solvent-solvent Coulomb interactions, which limits the applicability of PC-SAFT DFT to nonpolar and weakly polar molecules; (ii) the solute's Lennard-Jones parameters supplied by the general AMBER force field, which are not parametrized toward solvation free energies; and (iii) the application of the Lorentz-Berthelot combining rules to the dispersive interactions between a segment of the PC-SAFT solvent and a Lennard-Jones interaction site of the solute. The approach is more accurate than standard implementations of phenomenological models in common chemistry software packages, which exhibit mean absolute errors larger than 9.12 kJ mol-1, even though newer phenomenological models achieve a mean absolute error of about 2 kJ mol-1. PC-SAFT DFT is more computationally efficient than state of the art explicit molecular simulations in combination with free energy perturbation methods. It is predictive with respect to solvation free energies, i.e., the input for the model is the (element-specific) molecular force field, the solute configuration from molecular dynamics simulations, and the (substance-specific) PC-SAFT parameters. The PC-SAFT parametrization uses pure-component data and does not require experimental solvation free energies. The PC-SAFT equation of state, without applying a DFT formalism, can also be used to calculate solvation free energies, provided that the PC-SAFT parameters for the solute are available. A large number of substances was recently parametrized by members of our group (Esper, T.; Bauer, G.; Rehner, P.; Gross, J. Ind. Eng. Chem. Res. 2023, 62), which enables a comparison to the DFT approach for 103 substances. Accurate results are obtained from the PC-SAFT equation of state with an MAE below 2.51 kJ mol-1. The DFT approach does not require PC-SAFT parameters for the solute and can be applied to all solutes that can be represented by the molecular force field.

A Systematic Evaluation of Machine Learning-Based Biomarkers for Major Depressive Disorder

Importance

Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative biomarkers have been identified.

Objective

To evaluate whether machine learning (ML) can identify a multivariate biomarker for MDD.

Design, Setting, and Participants

This study used data from the Marburg-Münster Affective Disorders Cohort Study, a case-control clinical neuroimaging study. Patients with acute or lifetime MDD and healthy controls aged 18 to 65 years were recruited from primary care and the general population in Münster and Marburg, Germany, from September 11, 2014, to September 26, 2018. The Münster Neuroimaging Cohort (MNC) was used as an independent partial replication sample. Data were analyzed from April 2022 to June 2023.

Exposure

Patients with MDD and healthy controls.

Main Outcome and Measure

Diagnostic classification accuracy was quantified on an individual level using an extensive ML-based multivariate approach across a comprehensive range of neuroimaging modalities, including structural and functional magnetic resonance imaging and diffusion tensor imaging as well as a polygenic risk score for depression.

Results

Of 1801 included participants, 1162 (64.5%) were female, and the mean (SD) age was 36.1 (13.1) years. There were a total of 856 patients with MDD (47.5%) and 945 healthy controls (52.5%). The MNC replication sample included 1198 individuals (362 with MDD [30.1%] and 836 healthy controls [69.9%]). Training and testing a total of 4 million ML models, mean (SD) accuracies for diagnostic classification ranged between 48.1% (3.6%) and 62.0% (4.8%). Integrating neuroimaging modalities and stratifying individuals based on age, sex, treatment, or remission status does not enhance model performance. Findings were replicated within study sites and also observed in structural magnetic resonance imaging within MNC. Under simulated conditions of perfect reliability, performance did not significantly improve. Analyzing model errors suggests that symptom severity could be a potential focus for identifying MDD subgroups.

Conclusion and Relevance

Despite the improved predictive capability of multivariate compared with univariate neuroimaging markers, no informative individual-level MDD biomarker-even under extensive ML optimization in a large sample of diagnosed patients-could be identified.

IL-10 dependent adaptation allows macrophages to adjust inflammatory responses to TLR4 stimulation history

During an infection, innate immune cells must adjust nature and strength of their responses to changing pathogen abundances. To determine how stimulation of the pathogen sensing TLR4 shapes subsequent macrophage responses, we systematically varied priming and restimulation concentrations of its ligand KLA. We find that different priming strengths have very distinct effects at multiple stages of the signaling response, including receptor internalization, MAPK activation, cytokine and chemokine production, and nuclear translocation and chromatin association of NFκB and IκB members. In particular, restimulation-induced TNF-α production required KLA doses equal to or greater than those used for prior exposure, indicating that macrophages can detect and adaptively respond to changing TLR4 stimuli. Interestingly, while such adaptation was dependent on the anti-inflammatory cytokine IL-10, exogenous concentrations of IL-10 corresponding to those secreted after strong priming did not exert suppressive effects on TNF-α without such prior priming, confirming the critical role of TLR4 stimulation history.

Comparing the performance of beamformer algorithms in estimating orientations of neural sources

The efficacy of transcranial electric stimulation (tES) to effectively modulate neuronal activity depends critically on the spatial orientation of the targeted neuronal population. Therefore, precise estimation of target orientation is of utmost importance. Different beamforming algorithms provide orientation estimates; however, a systematic analysis of their performance is still lacking. For fixed brain locations, EEG and MEG data from sources with randomized orientations were simulated. The orientation was then estimated (1) with an EEG and (2) with a combined EEG-MEG approach. Three commonly used beamformer algorithms were evaluated with respect to their abilities to estimate the correct orientation: Unit-Gain (UG), Unit-Noise-Gain (UNG), and Array-Gain (AG) beamformer. Performance depends on the signal-to-noise ratios for the modalities and on the chosen beamformer. Overall, the UNG and AG beamformers appear as the most reliable. With increasing noise, the UG estimate converges to a vector determined by the leadfield, thus leading to insufficient orientation estimates.

Intact Mismatch Negativity Responses in Clinical High Risk for Psychosis and First-Episode Psychosis: Evidence From Source-Reconstructed Event-Related Fields and Time-Frequency Data

BACKGROUND

This study examined whether mismatch negativity (MMN) responses are impaired in participants at clinical high risk for psychosis (CHR-P) and patients with first-episode psychosis (FEP) and whether MMN deficits predict clinical outcomes in CHR-Ps.

METHODS

Magnetoencephalography data were collected during a duration-deviant MMN paradigm for a group of 116 CHR-P participants, 33 FEP patients (15 antipsychotic-naïve), clinical high risk negative group (n = 38) with substance abuse and affective disorder, and 49 healthy control participants. Analysis of group differences of source-reconstructed event-related fields as well as time-frequency and intertrial phase coherence focused on the bilateral Heschl's gyri and bilateral superior temporal gyri.

RESULTS

Significant magnetic MMN responses were found across participants in the bilateral Heschl's gyri and bilateral superior temporal gyri. However, MMN amplitude as well as time-frequency and intertrial phase coherence responses were intact in CHR-P participants and FEP patients compared with healthy control participants. Furthermore, MMN deficits were not related to persistent attenuated psychotic symptoms or transitions to psychosis in CHR-P participants.

CONCLUSIONS

Our data suggest that magnetic MMN responses in magnetoencephalography data are not impaired in early-stage psychosis and may not predict clinical outcomes in CHR-P participants.

Normative tDCS over V5 and FEF reveals practice-induced modulation of extraretinal smooth pursuit mechanisms, but no specific stimulation effect

The neural networks subserving smooth pursuit eye movements (SPEM) provide an ideal model for investigating the interaction of sensory processing and motor control during ongoing movements. To better understand core plasticity aspects of sensorimotor processing for SPEM, normative sham, anodal or cathodal transcranial direct current stimulation (tDCS) was applied over visual area V5 and frontal eye fields (FEF) in sixty healthy participants. The identical within-subject paradigm was used to assess SPEM modulations by practice. While no specific tDCS effects were revealed, within- and between-session practice effects indicate plasticity of top-down extraretinal mechanisms that mainly affect SPEM in the absence of visual input and during SPEM initiation. To explore the potential of tDCS effects, individual electric field simulations were computed based on calibrated finite element head models and individual functional localization of V5 and FEF location (using functional MRI) and orientation (using combined EEG/MEG) was conducted. Simulations revealed only limited electric field target intensities induced by the applied normative tDCS montages but indicate the potential efficacy of personalized tDCS for the modulation of SPEM. In sum, results indicate the potential susceptibility of extraretinal SPEM control to targeted external neuromodulation (e.g., personalized tDCS) and intrinsic learning protocols.

Patterns of Failure in Pediatric and Young Adult Rhabdomyosarcoma

PURPOSE/OBJECTIVE(S)

To characterize patterns of failure in pediatric and young adult patients with rhabdomyosarcoma (RMS) from a single institution with over 20 years of experience.

MATERIALS/METHODS

Patients diagnosed with RMS from 2000 to 2022 were identified retrospectively. Time to failure was calculated from diagnosis. Local only failure was defined as first failure at the primary site without distant failure. Distant failure was defined as first failure outside of the primary site with or without local failure. Cumulative incidence (CI) of failure was calculated using death as a competing risk. Fine-Gray regression was used to evaluate impact of prognostic factors.

RESULTS

Ninety-five patients were eligible. Median age was 7.28 years (range 0 - 35 years), 41% of patients were >10 years old. Median follow up was 33.3 months. Approximately half (n = 47, 49.5%) of the tumors demonstrated alveolar histology. FOXO1 fusion status was available in 76 (80%) patients, of which 7 out of 37 alveolar tumors (18.9%) were FOXO1 fusion negative. The majority of tumors presented with unfavorable primary site (n = 72, 75.8%) and advanced stage (Stage III and IV, n = 72, 75.8%). The 5-yr CI of local only failure and distant failure for the entire cohort was 19.0% (95% CI 11.3, 28.3) and 34.6% (24.0, 45.5%), respectively. The predominant pattern of failure by Group was: Groups 1&2: Local only (5yr CI 14.8%), Group 3: Distant (5yr CI: 25.9%), Group 4: Distant (5yr CI: 67.6%). CI of distant failure by primary site was higher in perianal/gluteal (n = 2/5, 5yr CI 60.0%) and extremity (n = 8/19, 5yr CI 45.9%) sites. Of the 28 distant failures, 10 (36%) also had a local failure component. CI of local only failure by primary site was higher in parameningeal head and neck (n = 6/25, 5yr CI 30%) and bladder/prostate (n = 2/12, 5yr CI 23%) sites. The following were associated with an increased CI of distant failures: increasing age (HR 1.08, p<0.01), alveolar vs. embryonal histology (HR 3.01, p = 0.0095), FOXO1 fusion positive vs. negative (HR 2.8, p = 0.02) and Group IV vs. Groups I/II (HR 7.7, p = 0.0007). FOXO1 fusion and alveolar histology were associated with older age and Group IV, both of which were independently associated with increased distant failure on multivariate analysis.

CONCLUSION

Failures were predominantly distant in older patients and patients with Group IV RMS, both of which were associated with FOXO1 fusion and alveolar histology, highlighting the need to improve therapies in this population. Local only failures were highest in parameningeal head and neck and bladder/prostate primaries, highlighting the need to improve local control strategies at these sites.

Neural responses to natural and enhanced speech edges in children with and without dyslexia

Sensory-neural studies indicate that children with developmental dyslexia show impairments in processing acoustic speech envelope information. Prior studies suggest that this arises in part from reduced sensory sensitivity to amplitude rise times (ARTs or speech "edges") in the envelope, accompanied by less accurate neural encoding of low-frequency envelope information. Accordingly, enhancing these characteristics of the speech envelope may enhance neural speech processing in children with dyslexia. Here we applied an envelope modulation enhancement (EME) algorithm to a 10-min story read in child-directed speech (CDS), enhancing ARTs and also enhancing low-frequency envelope information. We compared neural speech processing (as measured using MEG) for the EME story with the same story read in natural CDS for 9-year-old children with and without dyslexia. The EME story affected neural processing in the power domain for children with dyslexia, particularly in the delta band (0.5-4 Hz) in the superior temporal gyrus. This may suggest that prolonged experience with EME speech could ameliorate some of the impairments shown in natural speech processing by children with dyslexia.

DISCOVER-EEG: an open, fully automated EEG pipeline for biomarker discovery in clinical neuroscience

Biomarker discovery in neurological and psychiatric disorders critically depends on reproducible and transparent methods applied to large-scale datasets. Electroencephalography (EEG) is a promising tool for identifying biomarkers. However, recording, preprocessing, and analysis of EEG data is time-consuming and researcher-dependent. Therefore, we developed DISCOVER-EEG, an open and fully automated pipeline that enables easy and fast preprocessing, analysis, and visualization of resting state EEG data. Data in the Brain Imaging Data Structure (BIDS) standard are automatically preprocessed, and physiologically meaningful features of brain function (including oscillatory power, connectivity, and network characteristics) are extracted and visualized using two open-source and widely used Matlab toolboxes (EEGLAB and FieldTrip). We tested the pipeline in two large, openly available datasets containing EEG recordings of healthy participants and patients with a psychiatric condition. Additionally, we performed an exploratory analysis that could inspire the development of biomarkers for healthy aging. Thus, the DISCOVER-EEG pipeline facilitates the aggregation, reuse, and analysis of large EEG datasets, promoting open and reproducible research on brain function.

Breathing in waves: Understanding respiratory-brain coupling as a gradient of predictive oscillations

Breathing plays a crucial role in shaping perceptual and cognitive processes by regulating the strength and synchronisation of neural oscillations. Numerous studies have demonstrated that respiratory rhythms govern a wide range of behavioural effects across cognitive, affective, and perceptual domains. Additionally, respiratory-modulated brain oscillations have been observed in various mammalian models and across diverse frequency spectra. However, a comprehensive framework to elucidate these disparate phenomena remains elusive. In this review, we synthesise existing findings to propose a neural gradient of respiratory-modulated brain oscillations and examine recent computational models of neural oscillations to map this gradient onto a hierarchical cascade of precision-weighted prediction errors. By deciphering the computational mechanisms underlying respiratory control of these processes, we can potentially uncover new pathways for understanding the link between respiratory-brain coupling and psychiatric disorders.

CutFEM forward modeling for EEG source analysis

Introduction

Source analysis of Electroencephalography (EEG) data requires the computation of the scalp potential induced by current sources in the brain. This so-called EEG forward problem is based on an accurate estimation of the volume conduction effects in the human head, represented by a partial differential equation which can be solved using the finite element method (FEM). FEM offers flexibility when modeling anisotropic tissue conductivities but requires a volumetric discretization, a mesh, of the head domain. Structured hexahedral meshes are easy to create in an automatic fashion, while tetrahedral meshes are better suited to model curved geometries. Tetrahedral meshes, thus, offer better accuracy but are more difficult to create.

Methods

We introduce CutFEM for EEG forward simulations to integrate the strengths of hexahedra and tetrahedra. It belongs to the family of unfitted finite element methods, decoupling mesh and geometry representation. Following a description of the method, we will employ CutFEM in both controlled spherical scenarios and the reconstruction of somatosensory-evoked potentials.

Results

CutFEM outperforms competing FEM approaches with regard to numerical accuracy, memory consumption, and computational speed while being able to mesh arbitrarily touching compartments.

Discussion

CutFEM balances numerical accuracy, computational efficiency, and a smooth approximation of complex geometries that has previously not been available in FEM-based EEG forward modeling.

Predictive coordination of breathing during intra-personal speaking and listening

It has long been known that human breathing is altered during listening and speaking compared to rest: during speaking, inhalation depth is adjusted to the air volume required for the upcoming utterance. During listening, inhalation is temporally aligned to inhalation of the speaker. While evidence for the former is relatively strong, it is virtually absent for the latter. We address both phenomena using recordings of speech envelope and respiration in 30 participants during 14 min of speaking and listening to one's own speech. First, we show that inhalation depth is positively correlated with the total power of the speech envelope in the following utterance. Second, we provide evidence that inhalation during listening to one's own speech is significantly more likely at time points of inhalation during speaking. These findings are compatible with models that postulate alignment of internal forward models of interlocutors with the aim to facilitate communication.

Modulatory dynamics of periodic and aperiodic activity in respiration-brain coupling

Bodily rhythms such as respiration are increasingly acknowledged to modulate neural oscillations underlying human action, perception, and cognition. Conversely, the link between respiration and aperiodic brain activity - a non-oscillatory reflection of excitation-inhibition (E:I) balance - has remained unstudied. Aiming to disentangle potential respiration-related dynamics of periodic and aperiodic activity, we applied recently developed algorithms of time-resolved parameter estimation to resting-state MEG and EEG data from two labs (total N = 78 participants). We provide evidence that fluctuations of aperiodic brain activity (1/f slope) are phase-locked to the respiratory cycle, which suggests that spontaneous state shifts of excitation-inhibition balance are at least partly influenced by peripheral bodily signals. Moreover, differential temporal dynamics in their coupling to non-oscillatory and oscillatory activity raise the possibility of a functional distinction in the way each component is related to respiration. Our findings highlight the role of respiration as a physiological influence on brain signalling.

Spatiotemporal dynamics characterise spectral connectivity profiles of continuous speaking and listening

Speech production and perception are fundamental processes of human cognition that both rely on intricate processing mechanisms that are still poorly understood. Here, we study these processes by using magnetoencephalography (MEG) to comprehensively map connectivity of regional brain activity within the brain and to the speech envelope during continuous speaking and listening. Our results reveal not only a partly shared neural substrate for both processes but also a dissociation in space, delay, and frequency. Neural activity in motor and frontal areas is coupled to succeeding speech in delta band (1 to 3 Hz), whereas coupling in the theta range follows speech in temporal areas during speaking. Neural connectivity results showed a separation of bottom-up and top-down signalling in distinct frequency bands during speaking. Here, we show that frequency-specific connectivity channels for bottom-up and top-down signalling support continuous speaking and listening. These findings further shed light on the complex interplay between different brain regions involved in speech production and perception.

Thalamo-cortical circuits during sensory attenuation in emerging psychosis: a combined magnetoencephalography and dynamic causal modelling study

Evidence suggests that schizophrenia (ScZ) involves impairments in sensory attenuation. It is currently unclear, however, whether such deficits are present during early-stage psychosis as well as the underlying network and the potential as a biomarker. To address these questions, Magnetoencephalography (MEG) was used in combination with computational modeling to examine M100 responses that involved a "passive" condition during which tones were binaurally presented, while in an "active" condition participants were asked to generate a tone via a button press. MEG data were obtained from 109 clinical high-risk for psychosis (CHR-P) participants, 23 people with a first-episode psychosis (FEP), and 48 healthy controls (HC). M100 responses at sensor and source level in the left and right thalamus (THA), Heschl's gyrus (HES), superior temporal gyrus (STG) and right inferior parietal cortex (IPL) were examined and dynamic causal modeling (DCM) was performed. Furthermore, the relationship between sensory attenuation and persistence of attenuated psychotic symptoms (APS) and transition to psychosis was investigated in CHR-P participants. Sensory attenuation was impaired in left HES, left STG and left THA in FEP patients, while in the CHR-P group deficits were observed only in right HES. DCM results revealed that CHR-P participants showed reduced top-down modulation from the right IPL to the right HES. Importantly, deficits in sensory attenuation did not predict clinical outcomes in the CHR-P group. Our results show that early-stage psychosis involves impaired sensory attenuation in auditory and thalamic regions but may not predict clinical outcomes in CHR-P participants.

Physically based equation of state for Mie ν-6 fluids

We develop a physically based equation of state that describes Mie ν-6 fluids with an accuracy comparable to that of state-of-the-art empirical models. The equation of state is developed within the framework of the uv-theory [T. van Westen and J. Gross, J. Chem. Phys. 155, 244501 (2021)], which is modified by incorporating the third virial coefficient B3 in the low-density description of the model. The new model interpolates between a first-order Weeks-Chandler-Andersen (WCA) perturbation theory at high densities and a modified first-order WCA theory that recovers the virial expansion up to B3 at low densities. A new algebraic equation for the third virial coefficient of Mie ν-6 fluids is developed-other inputs are taken from previous work. Predicted thermodynamic properties and phase equilibria are compared to a comprehensive database of molecular simulation results from the literature, including Mie fluids of repulsive exponents 9 ≤ ν ≤ 48. The new equation of state is applicable to states with densities up to ρ*(T*)⪅1.1+0.12T* and temperatures T* > 0.3. For the Lennard-Jones fluid (ν = 12), the performance of the model is comparable to that of the best empirical equations of state available. As compared to empirical models, the physical basis of the new model provides several advantages, however: (1) the new model is applicable to Mie fluids of repulsive exponents 9 ≤ ν ≤ 48 instead of only ν = 12, (2) the model leads to a better description of the meta-stable and unstable region (which is important for describing interfacial properties by classical density functional theory), and (3) being a first-order perturbation theory, the new model (potentially) allows an easier and more rigorous extension to non-spherical (chain) fluids and mixtures.

Local brain oscillations and interregional connectivity differentially serve sensory and expectation effects on pain

Pain emerges from the integration of sensory information about threats and contextual information such as an individual's expectations. However, how sensory and contextual effects on pain are served by the brain is not fully understood so far. To address this question, we applied brief painful stimuli to 40 healthy human participants and independently varied stimulus intensity and expectations. Concurrently, we recorded electroencephalography. We assessed local oscillatory brain activity and interregional functional connectivity in a network of six brain regions playing key roles in the processing of pain. We found that sensory information predominantly influenced local brain oscillations. In contrast, expectations exclusively influenced interregional connectivity. Specifically, expectations altered connectivity at alpha (8 to 12 hertz) frequencies from prefrontal to somatosensory cortex. Moreover, discrepancies between sensory information and expectations, i.e., prediction errors, influenced connectivity at gamma (60 to 100 hertz) frequencies. These findings reveal how fundamentally different brain mechanisms serve sensory and contextual effects on pain.

Classical density functional theory for interfacial properties of hydrogen, helium, deuterium, neon, and their mixtures

We present a classical density functional theory (DFT) for fluid mixtures that is based on a third-order thermodynamic perturbation theory of Feynman-Hibbs-corrected Mie potentials. The DFT is developed to study the interfacial properties of hydrogen, helium, neon, deuterium, and their mixtures, i.e., fluids that are strongly influenced by quantum effects at low temperatures. White Bear fundamental measure theory is used for the hard-sphere contribution of the Helmholtz energy functional, and a weighted density approximation is used for the dispersion contribution. For mixtures, a contribution is included to account for non-additivity in the Lorentz-Berthelot combination rule. Predictions of the radial distribution function from DFT are in excellent agreement with results from molecular simulations, both for pure components and mixtures. Above the normal boiling point and 5% below the critical temperature, the DFT yields surface tensions of neon, hydrogen, and deuterium with average deviations from experiments of 7.5%, 4.4%, and 1.8%, respectively. The surface tensions of hydrogen/deuterium, para-hydrogen/helium, deuterium/helium, and hydrogen/neon mixtures are reproduced with a mean absolute error of 5.4%, 8.1%, 1.3%, and 7.5%, respectively. The surface tensions are predicted with an excellent accuracy at temperatures above 20 K. The poor accuracy below 20 K is due to the inability of Feynman-Hibbs-corrected Mie potentials to represent the real fluid behavior at these conditions, motivating the development of new intermolecular potentials. This DFT can be leveraged in the future to study confined fluids and assess the performance of porous materials for hydrogen storage and transport.

The timing of cortical activation in associator grapheme-colour synaesthetes using MEG

Grapheme-colour synaesthetes experience an anomalous form of perception in which graphemes systematically induce specific colour concurrents in their mind's eye ("associator" type). Although grapheme-colour synaesthesia has been well characterised behaviourally, its neural mechanisms remain largely unresolved. There are currently several competing models, which can primarily be distinguished according to the anatomical and temporal predictions of synaesthesia-inducing neural activity. The first main model (Cross-Activation/Cascaded Cross-Tuning and its variants) posits early recruitment of occipital colour areas in the initial feed-forward sweep of brain activity. The second (Disinhibited Feedback) posits: (i) later involvement of a multisensory convergence zone (for example, in parietal cortices) after graphemes have been processed in their entirety; and (ii) subsequent feedback to early visual areas (i.e., occipital colour areas). In this study, we examine both the timing and anatomical correlates of associator grapheme-colour synaesthetes (n = 6) using MEG. Using innovative and unbiased analysis methods with little a priori assumptions, we applied Independent Component Analysis (ICA) on a single-subject level to identify the dominant patterns of activity corresponding to the induced, synaesthetic percept. We observed evoked activity that significantly dissociates between synaesthesia-inducing and non-inducing graphemes at approximately 190 ms following grapheme presentation. This effect is present in grapheme-colour synaesthetes, but not in matched controls, and exhibits an occipito-parietal topology localised consistently within individuals to extrastriate visual cortices and superior parietal lobes. Due to the observed timing of this evoked activity and its localization, our results support a model predicting relatively late synaesthesia-inducing activity, more akin to the Disinhibited Feedback model.

Investigating temporal and prosodic markers in clinical high-risk for psychosis participants using automated acoustic analysis

AIM

Language disturbances are a candidate biomarker for the early detection of psychosis. Temporal and prosodic abnormalities have been observed in schizophrenia patients, while there is conflicting evidence whether such deficits are present in participants meeting clinical high-risk for psychosis (CHR-P) criteria.

METHODS

Clinical interviews from CHR-P participants (n = 50) were examined for temporal and prosodic metrics and compared against a group of healthy controls (n = 17) and participants with affective disorders and substance abuse (n = 23).

RESULTS

There were no deficits in acoustic variables in the CHR-P group, while participants with affective disorders/substance abuse were characterized by slower speech rate, longer pauses and higher unvoiced frames percentage.

CONCLUSION

Our finding suggests that temporal and prosodic aspects of speech are not impaired in early-stage psychosis. Further studies are required to clarify whether such abnormalities are present in sub-groups of CHR-P participants with elevated psychosis-risk.

Bioelectromagnetism in Human Brain Research: New Applications, New Questions

Bioelectromagnetism has contributed some of the most commonly used techniques to human neuroscience such as magnetoencephalography (MEG), electroencephalography (EEG), transcranial magnetic stimulation (TMS), and transcranial electric stimulation (TES). The considerable differences in their technical design and practical use give rise to the impression that these are quite different techniques altogether. Here, we review, discuss and illustrate the fundamental principle of Helmholtz reciprocity that provides a common ground for all four techniques. We show that, more than 150 years after its discovery by Helmholtz in 1853, reciprocity is important to appreciate the strengths and limitations of these four classical tools in neuroscience. We build this case by explaining the concept of Helmholtz reciprocity, presenting a methodological account of this principle for all four methods and, finally, by illustrating its application in practical clinical studies.

Towards a network control theory of electroconvulsive therapy response

Electroconvulsive Therapy (ECT) is arguably the most effective intervention for treatment-resistant depression. While large interindividual variability exists, a theory capable of explaining individual response to ECT remains elusive. To address this, we posit a quantitative, mechanistic framework of ECT response based on Network Control Theory (NCT). Then, we empirically test our approach and employ it to predict ECT treatment response. To this end, we derive a formal association between Postictal Suppression Index (PSI)-an ECT seizure quality index-and whole-brain modal and average controllability, NCT metrics based on white-matter brain network architecture, respectively. Exploiting the known association of ECT response and PSI, we then hypothesized an association between our controllability metrics and ECT response mediated by PSI. We formally tested this conjecture in N = 50 depressive patients undergoing ECT. We show that whole-brain controllability metrics based on pre-ECT structural connectome data predict ECT response in accordance with our hypotheses. In addition, we show the expected mediation effects via PSI. Importantly, our theoretically motivated metrics are at least on par with extensive machine learning models based on pre-ECT connectome data. In summary, we derived and tested a control-theoretic framework capable of predicting ECT response based on individual brain network architecture. It makes testable, quantitative predictions regarding individual therapeutic response, which are corroborated by strong empirical evidence. Our work might constitute a starting point for a comprehensive, quantitative theory of personalized ECT interventions rooted in control theory.

Speech onsets and sustained speech contribute differentially to delta and theta speech tracking in auditory cortex

When we attentively listen to an individual's speech, our brain activity dynamically aligns to the incoming acoustic input at multiple timescales. Although this systematic alignment between ongoing brain activity and speech in auditory brain areas is well established, the acoustic events that drive this phase-locking are not fully understood. Here, we use magnetoencephalographic recordings of 24 human participants (12 females) while they were listening to a 1 h story. We show that whereas speech-brain coupling is associated with sustained acoustic fluctuations in the speech envelope in the theta-frequency range (4-7 Hz), speech tracking in the low-frequency delta (below 1 Hz) was strongest around onsets of speech, like the beginning of a sentence. Crucially, delta tracking in bilateral auditory areas was not sustained after onsets, proposing a delta tracking during continuous speech perception that is driven by speech onsets. We conclude that both onsets and sustained components of speech contribute differentially to speech tracking in delta- and theta-frequency bands, orchestrating sampling of continuous speech. Thus, our results suggest a temporal dissociation of acoustically driven oscillatory activity in auditory areas during speech tracking, providing valuable implications for orchestration of speech tracking at multiple time scales.

Clinical determinants and neural correlates of presbyphagia in community-dwelling older adults

Background

“Presbyphagia” refers to characteristic age-related changes in the complex neuromuscular swallowing mechanism. It has been hypothesized that cumulative impairments in multiple domains affect functional reserve of swallowing with age, but the multifactorial etiology and postulated compensatory strategies of the brain are incompletely understood. This study investigates presbyphagia and its neural correlates, focusing on the clinical determinants associated with adaptive neuroplasticity.

Materials and methods

64 subjects over 70 years of age free of typical diseases explaining dysphagia received comprehensive workup including flexible endoscopic evaluation of swallowing (FEES), magnetoencephalography (MEG) during swallowing and pharyngeal stimulation, volumetry of swallowing muscles, laboratory analyzes, and assessment of hand-grip-strength, nutritional status, frailty, olfaction, cognition and mental health. Neural MEG activation was compared between participants with and without presbyphagia in FEES, and associated clinical influencing factors were analyzed. Presbyphagia was defined as the presence of oropharyngeal swallowing alterations e.g., penetration, aspiration, pharyngeal residue pooling or premature bolus spillage into the piriform sinus and/or laryngeal vestibule.

Results

32 of 64 participants showed swallowing alterations, mainly characterized by pharyngeal residue, whereas the airway was rarely compromised. In the MEG analysis, participants with presbyphagia activated an increased cortical sensorimotor network during swallowing. As major clinical determinant, participants with swallowing alterations exhibited reduced pharyngeal sensation. Presbyphagia was an independent predictor of a reduced nutritional status in a linear regression model.

Conclusions

Swallowing alterations frequently occur in otherwise healthy older adults and are associated with decreased nutritional status. Increased sensorimotor cortical activation may constitute a compensation attempt to uphold swallowing function due to sensory decline. Further studies are needed to clarify whether the swallowing alterations observed can be considered physiological per se or whether the concept of presbyphagia may need to be extended to a theory with a continuous transition between presbyphagia and dysphagia.

Multivariate analysis of speech envelope tracking reveals coupling beyond auditory cortex

The systematic alignment of low-frequency brain oscillations with the acoustic speech envelope signal is well established and has been proposed to be crucial for actively perceiving speech. Previous studies investigating speech-brain coupling in source space are restricted to univariate pairwise approaches between brain and speech signals, and therefore speech tracking information in frequency-specific communication channels might be lacking. To address this, we propose a novel multivariate framework for estimating speech-brain coupling where neural variability from source-derived activity is taken into account along with the rate of envelope's amplitude change (derivative). We applied it in magnetoencephalographic (MEG) recordings while human participants (male and female) listened to one hour of continuous naturalistic speech, showing that a multivariate approach outperforms the corresponding univariate method in low- and high frequencies across frontal, motor, and temporal areas. Systematic comparisons revealed that the gain in low frequencies (0.6 - 0.8 Hz) was related to the envelope's rate of change whereas in higher frequencies (from 0.8 to 10 Hz) it was mostly related to the increased neural variability from source-derived cortical areas. Furthermore, following a non-negative matrix factorization approach we found distinct speech-brain components across time and cortical space related to speech processing. We confirm that speech envelope tracking operates mainly in two timescales (δ and θ frequency bands) and we extend those findings showing shorter coupling delays in auditory-related components and longer delays in higher-association frontal and motor components, indicating temporal differences of speech tracking and providing implications for hierarchical stimulus-driven speech processing.

The natural frequencies of the resting human brain: An MEG-based atlas

Brain oscillations are considered to play a pivotal role in neural communication. However, detailed information regarding the typical oscillatory patterns of individual brain regions is surprisingly scarce. In this study we applied a multivariate data-driven approach to create an atlas of the natural frequencies of the resting human brain on a voxel-by-voxel basis. We analysed resting-state magnetoencephalography (MEG) data from 128 healthy adult volunteers obtained from the Open MEG Archive (OMEGA). Spectral power was computed in source space in 500 ms steps for 82 frequency bins logarithmically spaced from 1.7 to 99.5 Hz. We then applied k-means clustering to detect characteristic spectral profiles and to eventually identify the natural frequency of each voxel. Our results provided empirical confirmation of the canonical frequency bands and revealed a region-specific organisation of intrinsic oscillatory activity, following both a medial-to-lateral and a posterior-to-anterior gradient of increasing frequency. In particular, medial fronto-temporal regions were characterised by slow rhythms (delta/theta). Posterior regions presented natural frequencies in the alpha band, although with differentiated generators in the precuneus and in sensory-specific cortices (i.e., visual and auditory). Somatomotor regions were distinguished by the mu rhythm, while the lateral prefrontal cortex was characterised by oscillations in the high beta range (>20 Hz). Importantly, the brain map of natural frequencies was highly replicable in two independent subsamples of individuals. To the best of our knowledge, this is the most comprehensive atlas of ongoing oscillatory activity performed to date. Critically, the identification of natural frequencies is a fundamental step towards a better understanding of the functional architecture of the human brain.

POS0993 RADIOLOGICAL CERVICAL INVOLVMENT IN ANKYLOSING SPONDYLITIS

Background

Cervical involvement in ankylosing spondylitis (AS) is particularly disabling and has been poorly studied yet. Actual radiologic scoring design to assess disease progression does not provide a comprehensive picture of the cervical involvement in AS. [1] Association with clinical features such as psoriasis are discussed.

Objectives

We aimed to assess radiographic features of cervical involvement in AS and clinico-biological parameters associated with this specific radiographic location.

Methods

Cross-sectional study based on radiographic analysis of a subgroup of patients included in the French BambooSpine cohort, originally designed to study the genetic risk factors of AS structural severity. The analysis was based on patients included in Parisian hospitals to have access to images of the entire spine on the Picture Archiving and Communication System (PACS) shared by all University Hospitals in Paris. A double reading of the images was performed by a rheumatologist/radiologist pair until consensus was reached, to identify syndesmophytes, zygapophyseal joint (ZJ) involvement and posterior ligament structures (PLS) at each cervical level, syndesmophytes in the thoracic region, and ZJ and PLS involvement in the lumbar region.

Results

Of the 113 assessed patients, 101 were men, mean age 53 years (+/- 11 years) with 27 years (+/- 13 years) of disease duration (Table 1). Of those whose HLA B27 status was known, 85% (70/82) were carriers. Among 86 patients with radiological cervical involvement, 83% had syndesmophytes, 86% had ZJ involvement and 24% had PLS involvement. In the cervical region, 13 patients (15%) had zygapophyseal fusion without syndesmophytes. 26/113 patients were completely free of any cervical involvement while 30/113 had a maximal cervical involvement (anterior and posterior). In univariate analyses, HLA-B27 was significantly associated with ZJ involvement at the cervical and lumbar level (p=0.016). Cervical involvement of any type was not associated with psoriasis. Low educational level (not beyond secondary school) was significantly associated with syndesmophytic involvement (p=0.035). There was a non-significant trend for an association between arthritis and ZJ involvement.

Table 1.

Clinical features

Men (n,%)101/11389,4%Age at diagnosis (mean, SD)31,211,68Duration of evolution (mean, SD)27,013,0Smoking ever (n,%)65/11258,0 %Chronic Back Pain (for > 3 months) (n,%)109/11396,5%Chest pain45/11040,9%Buttock pain78/10971,6%Arthritis36/11132,4%Enthesitis38/11233,9%Dactylitis6/1115,4%HLA B2770/8285,4%CRP87/10384,5%X ray sacro-iliitis112/112100%Personnal history -Uveitis41/11336,3% -Inflammatory bowel disease13/11311,5% -Reactive arthritis2/1121,8% -Psoriasis19/11117,1%

Conclusion

Cervical involvement was very frequent (76% of this severe AS population) but not associated with psoriasis, as usually thought. Zygapophyseal involvement was present in 86 % of cases and exclusive in 15 % of cases. This latter radiological form of the disease, i.e. without syndesmophytes, is usually more difficult to diagnose, and should be systematically assessed among AS patients with cervical pain and/or patients with reduced cervical mobility.

References

[1]Wanders AJB, Landewé RBM, Spoorenberg A, et al. What is the most appropriate radiologic scoring method for ankylosing spondylitis? Arthritis & Rheumatism 2004

Disclosure of Interests

None declared

Characterising cognitive heterogeneity in individuals at clinical high-risk for psychosis: a cluster analysis with clinical and functional outcome prediction

Schizophrenia is characterised by cognitive impairments that are already present during early stages, including in the clinical high-risk for psychosis (CHR-P) state and first-episode psychosis (FEP). Moreover, data suggest the presence of distinct cognitive subtypes during early-stage psychosis, with evidence for spared vs. impaired cognitive profiles that may be differentially associated with symptomatic and functional outcomes. Using cluster analysis, we sought to determine whether cognitive subgroups were associated with clinical and functional outcomes in CHR-P individuals. Data were available for 146 CHR-P participants of whom 122 completed a 6- and/or 12-month follow-up; 15 FEP participants; 47 participants not fulfilling CHR-P criteria (CHR-Ns); and 53 healthy controls (HCs). We performed hierarchical cluster analysis on principal components derived from neurocognitive and social cognitive measures. Within the CHR-P group, clusters were compared on clinical and functional variables and examined for associations with global functioning, persistent attenuated psychotic symptoms and transition to psychosis. Two discrete cognitive subgroups emerged across all participants: 45.9% of CHR-P individuals were cognitively impaired compared to 93.3% of FEP, 29.8% of CHR-N and 30.2% of HC participants. Cognitively impaired CHR-P participants also had significantly poorer functioning at baseline and follow-up than their cognitively spared counterparts. Specifically, cluster membership predicted functional but not clinical outcome. Our findings support the existence of distinct cognitive subgroups in CHR-P individuals that are associated with functional outcomes, with implications for early intervention and the understanding of underlying developmental processes.

Perturbation theories for fluids with short-ranged attractive forces: A case study of the Lennard-Jones spline fluid

It is generally not straightforward to apply molecular-thermodynamic theories to fluids with short-ranged attractive forces between their constituent molecules (or particles). This especially applies to perturbation theories, which, for short-ranged attractive fluids, typically must be extended to high order or may not converge at all. Here, we show that a recent first-order perturbation theory, the uv-theory, holds promise for describing such fluids. As a case study, we apply the uv-theory to a fluid with pair interactions defined by the Lennard-Jones spline potential, which is a short-ranged version of the LJ potential that is known to provide a challenge for equation-of-state development. The results of the uv-theory are compared to those of third-order Barker–Henderson and fourth-order Weeks–Chandler–Andersen perturbation theories, which are implemented using Monte Carlo simulation results for the respective perturbation terms. Theoretical predictions are compared to an extensive dataset of molecular simulation results from this (and previous) work, including vapor–liquid equilibria, first- and second-order derivative properties, the critical region, and metastable states. The uv-theory proves superior for all properties examined. An especially accurate description of metastable vapor and liquid states is obtained, which might prove valuable for future applications of the equation-of-state model to inhomogeneous phases or nucleation processes. Although the uv-theory is analytic, it accurately describes molecular simulation results for both the critical point and the binodal up to at least 99% of the critical temperature. This suggests that the difficulties typically encountered in describing the vapor–liquid critical region are only to a small extent caused by non-analyticity.

Neural sampling of the speech signal at different timescales by children with dyslexia

Phonological difficulties characterize individuals with dyslexia across languages. Currently debated is whether these difficulties arise from atypical neural sampling of (or entrainment to) auditory information in speech at slow rates (<10 Hz, related to speech rhythm), faster rates, or neither. MEG studies with adults suggest that atypical sampling in dyslexia affects faster modulations in the neurophysiological gamma band, related to phoneme-level representation. However, dyslexic adults have had years of reduced experience in converting graphemes to phonemes, which could itself cause atypical gamma-band activity. The present study was designed to identify specific linguistic timescales at which English children with dyslexia may show atypical entrainment. Adopting a developmental focus, we hypothesized that children with dyslexia would show atypical entrainment to the prosodic and syllable-level information that is exaggerated in infant-directed speech and carried primarily by amplitude modulations <10 Hz. MEG was recorded in a naturalistic story-listening paradigm. The modulation bands related to different types of linguistic information were derived directly from the speech materials, and lagged coherence at multiple temporal rates spanning 0.9-40 Hz was computed. Group differences in lagged speech-brain coherence between children with dyslexia and control children were most marked in neurophysiological bands corresponding to stress and syllable-level information (<5 Hz in our materials), and phoneme-level information (12-40 Hz). Functional connectivity analyses showed network differences between groups in both hemispheres, with dyslexic children showing significantly reduced global network efficiency. Global network efficiency correlated with dyslexic children's oral language development and with control children's reading development. These developmental data suggest that dyslexia is characterized by atypical neural sampling of auditory information at slower rates. They also throw new light on the nature of the gamma band temporal sampling differences reported in MEG dyslexia studies with adults.

Equation of state and Helmholtz energy functional for fused heterosegmented hard chains

Modern equations of state for real nonspherical molecules are often based on Wertheim's first-order thermodynamic perturbation theory (TPT1). A major drawback of TPT1 is that it assumes tangentially bonded spheres. In this work, we develop a Helmholtz energy functional for systems comprising hard heterosegmented chains with arbitrary bond lengths. This is achieved by using hard-sphere fragments (i.e., hard spheres with spherical caps removed at the intersection to their neighbors) as monomers as opposed to full hard spheres. The model is written as a Helmholtz energy functional for inhomogeneous systems and the equation of state for a homogeneous system is determined as a special case. We thereby obtain an equation of state that can be used as a reference to develop statistical associating fluid theory models that more accurately describe the thermodynamic properties of nonspherical molecules. The model is validated against molecular simulation results of bulk pressures and density profiles in slit pores. For the bulk pressures, we show that the equation of state is in excellent agreement with results from molecular simulation for dimers, trimers, and chains of up to 20 segments. The density profiles of individual segments of the chains are regarded in slit pores. Some deviations of the theory from results of molecular simulations are observed for strongly fused chains. Overall, however, good agreement is found for inhomogeneous systems.

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

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.

Hippocampal structural alterations in early-stage psychosis: Specificity and relationship to clinical outcomes

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Individuals with early-stage psychosis show reduced hippocampal volumes.

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FEP show bilateral and widespread changes, while left hemisphere is affected in CHR-P.

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However, hippocampal changes do not show a relationship with clinical outcomes.

Hippocampal dysfunctions are a core feature of schizophrenia, but conflicting evidence exists whether volumetric and morphological changes are present in early-stage psychosis and to what extent these deficits are related to clinical trajectories. In this study, we recruited individuals at clinical high risk for psychosis (CHR-P) (n = 108), patients with a first episode of psychosis (FEP) (n = 37), healthy controls (HC) (n = 70) as well as a psychiatric control group with substance abuse and affective disorders (CHR-N: n = 38). MRI-data at baseline were obtained and volumetric as well as vertex analyses of the hippocampus were carried out. Moreover, volumetric changes were examined in the amygdala, caudate, nucleus accumbens, pallidum, putamen and thalamus. In addition, we obtained follow-up functional and symptomatic assessments in CHR-P individuals to examine the question whether anatomical deficits at baseline predicted clinical trajectories. Our results show that the hippocampus is the only structure showing significant volumetric decrease in early-stage psychosis, with FEPs showing significantly smaller hippocampal volumes bilaterally alongside widespread shape changes in the vertex analysis. For the CHR-P group, volumetric decreases were confined to the left hippocampus. However, hippocampal alterations in the CHR-P group were not robustly associated with clinical outcomes, including the persistence of attenuated psychotic symptoms and functional trajectories. Accordingly, our findings highlight that dysfunctions in hippocampal anatomy are an important feature of early-stage psychosis which may, however, not be related to clinical outcomes in CHR-P participants.

MR-Spectroscopy of GABA and Glutamate/Glutamine Concentrations in Auditory Cortex in Clinical High-Risk for Psychosis Individuals

Psychosis involves changes in GABAergic and glutamatergic neurotransmission in auditory cortex that could be important for understanding sensory deficits and symptoms of psychosis. However, it is currently unclear whether such deficits are present in participants at clinical high-risk for psychosis (CHR-P) and whether they are associated with clinical outcomes. Magnetic Resonance Spectroscopy (MEGAPRESS, 1H-MRS at 3 Tesla) was used to estimate GABA, glutamate, and glutamate-plus-glutamine (Glx) levels in auditory cortex in a large sample of CHR-P (n = 99), CHR-N (clinical high-risk negative, n = 32), and 45 healthy controls. Examined were group differences in metabolite concentrations as well as relationships with clinical symptoms, general cognition, and 1-year follow-up clinical and general functioning in the CHR-P group. Results showed a marginal (p = 0.039) main group effect only for Glx, but not for GABA and glutamate concentrations, and only in left, not right, auditory cortex. This effect did not survive multiple comparison correction, however. Exploratory post-hoc tests revealed that there were significantly lower Glx levels (p = 0.029, uncorrected) in the CHR-P compared to the CHR-N group, but not relative to healthy controls (p = 0.058, uncorrected). Glx levels correlated with the severity of perceptual abnormalities and disorganized speech scores. However, in the CHR-P group, Glx levels did not predict clinical or functional outcomes. Accordingly, the findings from the present study suggest that MRS-measured GABA, glutamate and Glx levels in auditory cortex of CHR-P individuals are largely intact.

Accurate thermodynamics of simple fluids and chain fluids based on first-order perturbation theory and second virial coefficients: uv-theory

We develop a simplification of our recently proposed uf-theory for describing the thermodynamics of simple fluids and fluids comprising short chain molecules. In its original form, the uf-theory interpolates the Helmholtz energy between a first-order f-expansion and first-order u-expansion as (effective) lower and upper bounds. We here replace the f-bound by a new, tighter (effective) lower bound. The resulting equation of state interpolates between a first-order u-expansion at high densities and another first-order u-expansion that is modified to recover the exact second virial coefficient at low densities. The theory merely requires the Helmholtz energy of the reference fluid, the first-order u-perturbation term, and the total perturbation contribution to the second virial coefficient as input. The revised theory-referred to as uv-theory-is thus simpler than the uf-theory but leads to similar accuracy, as we show for fluids with intermolecular pair interactions governed by a Mie potential. The uv-theory is thereby easier to extend to fluid mixtures and provides more flexibility in extending the model to non-spherical or chain-like molecules. The usefulness of the uv-theory for developing equation-of-state models of non-spherical molecules is here exemplified by developing an equation of state for Lennard-Jones dimers.

Respiration aligns perception with neural excitability

Recent studies from the field of interoception have highlighted the link between bodily and neural rhythms during action, perception, and cognition. The mechanisms underlying functional body-brain coupling, however, are poorly understood, as are the ways in which they modulate behavior. We acquired respiration and human magnetoencephalography data from a near-threshold spatial detection task to investigate the trivariate relationship between respiration, neural excitability, and performance. Respiration was found to significantly modulate perceptual sensitivity as well as posterior alpha power (8-13 Hz), a well-established proxy of cortical excitability. In turn, alpha suppression prior to detected versus undetected targets underscored the behavioral benefits of heightened excitability. Notably, respiration-locked excitability changes were maximized at a respiration phase lag of around -30° and thus temporally preceded performance changes. In line with interoceptive inference accounts, these results suggest that respiration actively aligns sampling of sensory information with transient cycles of heightened excitability to facilitate performance.

Respiration modulates oscillatory neural network activity at rest

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).

MR Imaging Differences in the Circle of Willis between Healthy Children and Adults

BACKGROUND AND PURPOSE

Asymmetries in the circle of Willis have been associated with several conditions, including migraines and stroke, but they may also be age-dependent. This study examined the impact of age and age-dependent changes in cerebral perfusion on circle of Willis anatomy in healthy children and adults.

MATERIALS AND METHODS

We performed an observational, cross-sectional study of bright and black-blood imaging of the proximal cerebral vasculature using TOF-MRA and T2 sampling perfection with application-optimized contrasts by using different flip angle evolution (T2-SPACE) imaging at the level of the circle of Willis in 23 healthy children and 43 healthy adults (4-74 years of age). We compared arterial diameters measured manually and cerebral perfusion via pseudocontinuous arterial spin-labeling between children and adults.

RESULTS

We found that the summed cross-sectional area of the circle of Willis is larger in children than in adults, though the effect size was smaller with T2-SPACE-based measurements than with TOF-MRA. The circle of Willis is also more symmetric in children, and nonvisualized segments occur more frequently in adults than in children. Moreover, the size and symmetry of the circle of Willis correlate with cerebral perfusion.

CONCLUSIONS

Our results demonstrate that the circle of Willis is different in size and symmetry in healthy children compared with adults, likely associated with developmental changes in cerebral perfusion. Further work is needed to understand why asymmetric vasculature develops in some but not all adults.

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

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.