Biology subjects

Azanova, M.

Publications and source records attributed to Azanova, M..

4 recordsLinked to original sources

bioRxiv2026

Individual heartbeats track distinct prediction processes during human probabilistic learning

Heart rate continuously adjusts to accommodate perception and action, and these shifts are frequently explained through predictive processes. Yet direct evidence that interbeat intervals exhibit graded scaling with prediction remains limited. Here we investigate millisecond-resolved physiological signatures of prediction processing using a mechanistically constrained analysis of beat-to-beat cardiac dynamics. We analysed trial-by-trial electrocardiogram and electroencephalogram recordings from 34 participants performing a probabilistic learning task. We quantified stimulus-locked cardiac responses as changes between consecutive interbeat intervals and accounted for cardiac phase at feedback. This single-beat approach separated anticipatory slowing, stimulus-locked parasympathetic brake, and subsequent acceleration. Anticipatory deceleration and rebound acceleration scaled with model-derived expectations, whereas the second heartbeat after feedback tracked signed prediction errors and outcome valence, particularly when feedback occurred early in the cardiac cycle. Peak stimulus-locked cardiac deceleration covaried with parietal P3b rather than prediction features. Thus, individual cardiac cycles carry separable signatures of anticipation, orienting, and feedback-based updating. These findings demonstrate how predictive processing propagates into human autonomic physiology on a beat-to-beat timescale and provide an interpretable, mechanistically grounded framework for quantifying brain-body co-modulation during adaptive behaviour.

neuroscience↗

bioRxiv2026

Canonical Correlation Analysis and Multi-Channel Cardiography Improve Artefact Cleaning in Heartbeat-Locked Analyses

Cardiac artefacts are problematic for neurophysiological analyses, especially for heartbeat-locked brain responses where neural activity and artefacts co-occur in time. Traditional approaches using single-channel electrocardiography for artefact removal do not fully capture the multidimensional spread of cardiac fields. Moreover, even if several channels are recorded, no established methods exists for integrating them for artefact removal. Here, we propose a multivariate approach based on Canonical Correlation for cardiac artefact removal and report its effectiveness in electroencephalography recorded simultaneously with a custom 15-channel electrocardiography in 14 participants. We quantify cleaning quality via residual R-peak artefact and neural signal preservation via alpha power. Canonical Correlation systematically outperforms the traditional Independent Component Analysis in both reducing R-peak artefacts and preserving alpha power. By analysing all possible channel combinations, we found that neck or supraclavicular electrodes improve cleaning when only a few channels are available. With four or five channels, precordial electrodes in combination with limb or supraclavicular locations provide a performance comparable to the 15-channel setup. While these findings require validation in other datasets, we outline clear decision criteria for cleaning efficiency and show that canonical correlation is a reliable approach for multi-channel cardiac artefact removal.

neuroscience↗

bioRxiv2025

Heartbeat-evoked responses in M/EEG: A systematic review of methods with suggestions for analysis and reporting

Heartbeat-evoked responses (HER), as measured by electroencephalography (EEG) or magnetoencephalography (MEG), represent neural activity time-locked to heartbeats and are widely used as a marker of cardiac interoception in the study of brain-body interactions. However, HER studies report largely variable findings, at least partially due to methodological variability. To achieve consensus on HER processing and improve the reproducibility of findings, the field urgently requires a structured summary of the methods employed so far. To this end, we conducted a systematic review of 132 HER studies using non-invasive M/EEG recordings in humans. Our results reveal substantial heterogeneity across most steps of HER analysis, ranging from data acquisition and preprocessing to HER estimation and statistical approaches. The large diversity in the processing choices is accompanied by considerable proportions of unreported methodological information across reviewed studies, reaching up to 80% for key processing steps. In addition, less than 33% of studies had enough statistical power to reliably detect meta-level HER effects, while their reported spatiotemporal locations varied substantially. We provide a comprehensive reporting and quality control checklist to aid in the development of more standardized procedures, highlighting critical steps for robust HER investigations. Additionally, we share the full extracted dataset, including an interactive version, to support other researchers in answering additional specific questions they may have. We hope that these resources will improve the robustness, reproducibility, and transparency of research in the growing HER field.

neuroscience↗

bioRxiv2021

Resting-state theta oscillations and reward sensitivity in risk taking

Females demonstrate greater risk aversion than males on a variety of tasks, but the underlying neurobiological basis is still unclear. We studied how theta (4-7 Hz) oscillations at rest related to three different measures of risk taking. Thirty-five participants (15 females) completed the Bomb Risk Elicitation Task (BRET), which allowed us to measure risk taking during an economic game. The Domain-Specific Risk-Taking Scale (DOSPERT) was used to measure self-assessed risk attitudes as well as reward and punishment sensitivities. In addition, the Barratt Impulsiveness Scale (BIS11) was included to quantify impulsiveness. To obtain measures of frontal theta asymmetry and frontal theta power, we used magnetoencephalography (MEG) acquired prior to task completion, while participants were at rest. Frontal theta asymmetry correlated with average risk taking during the game but only in the female sample. By contrast, frontal theta power correlated with risk taking as well as with measures of reward and punishment sensitivity in the joint sample. Importantly, we showed that reward sensitivity mediated a correlation between risk taking and the power of theta oscillations localized to the anterior cingulate cortex. In addition, we observed significant sex differences in source- and sensor-space theta power, risk taking during the game, and reward sensitivity. Our findings suggest that sensitivity to rewards, associated with resting-state theta oscillations in the anterior cingulate cortex, is a trait that potentially contributes to sex differences in risk taking.

neuroscience↗