Biology subjects

Herrojo Ruiz, M.

Publications and source records attributed to Herrojo Ruiz, M..

10 recordsLinked to original sources

bioRxiv2026

Cardiac Timing Biases Creative Exploration and Exploitation

Creative ideation involves a dynamic exchange between exploring new idea categories and exploiting familiar ones, reflecting optimal foraging principles. Although interoceptive signals, particularly cardiac activity, are associated with differences in attention and cognitive control, their role in explore-exploit dynamics during creative idea generation remains unknown. Recording both electroencephalography (EEG) and electrocardiography (ECG) data, we used convolution general linear models to examine cardiac-brain interactions underlying semantic exploration and exploitation during creative idea generation, in both spontaneous (self-selected) and directed (externally cued) conditions. Cardiac deceleration predicted ideation time: this relationship scaled nonlinearly during exploration (category switching), but linearly during exploitation (category persistence), in both conditions. Cardiac deceleration did not predict semantic distance (between response and cue word) or response accuracy during the directed condition, suggesting that heart rate slowing reflects cognitive effort allocation rather than ideational content. Cardiac phase systematically biased explore-exploit dynamics: spontaneous switching and accurate directed-switching were preferentially associated with diastolic phases and parieto-occipital alpha (8-12 Hz) desynchronization, whereas category persistence was associated with systolic phase timing and frontal theta (4-6 Hz) synchronization. The former activity was coupled to higher CD, as expected. However, the latter time-frequency activity was linked to responses timed to systole. These findings suggest that creative ideation unfolds through embodied cardiac-cortical coordination, whereby diastolic states are associated with flexible semantic exploration and alpha-related attentional dynamics, whereas systolic states are associated with exploitative persistence and theta-related control processes. This suggests interoceptive rhythms as temporal scaffolding that structures when and how ideas emerge, fundamentally expanding creativity neuroscience beyond purely cortical models.

neuroscience↗

bioRxiv2025

Voluntary movement initiation is associated with cardiac input in Libet's task.

The relationship between motor intention and initiation of voluntary movement remains a fundamental topic in neuroscience, originating from the B. Libet seminal framework introduced in 1983. Libets paradigm significantly influenced discussions on intentionality, motor control, and free will. However, methodological critiques continue to challenge its interpretations, specifically the accuracy and validity of the urge to move phenomenon. One understudied factor in this debate is the potential influence of interoceptive signals--particularly cardiac activity--in shaping the experience of motor intention and movement initiation. In our study, we addressed this gap by examining whether cardiac signals modulate participants experience of the urge to move, using behavioural and electrophysiological measures in 34 healthy human participants performing Libets task. Crucially, when participants were asked to report the perceived urge to move, their button press timings were predominantly aligned with the diastolic phase of the cardiac cycle, indicating cardiac modulation of motor intention perception. However, analysing heart evoked potential (HEP) amplitudes as a measure of cardiac input perception, we observed no differences in HEP amplitudes associated with changes in introspective demands during the task in both source and sensor spaces. Our results suggest that implicit perception of cardiac signals biases subjective experience of voluntary action initiation, independent from cortical interoceptive markers. These findings have implications for models of motor preparation, intentionality and the bodily basis of voluntary action, challenging conventional interpretations of motor intention and informing debates on volition and interoception. Significance StatementOur study provides evidence that implicit perception of cardiac signals influences the subjective experience of motor intention--the urge to move in Libets experiment. We demonstrate, for the first time, that when reporting urge to move, participants tended to initiate voluntary movements during the diastolic phase of the cardiac cycle. These findings challenge traditional views on factors affecting motor initiation, suggesting relevance of interoceptive processing. By highlighting the role of cardiac input in experiencing motor intention, our findings impact existing debates on volition, agency and free will, further underscoring the importance of integrating bodily signals into these theoretical frameworks.

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bioRxiv2022

Changes in oscillations in anterior cingulate and medial prefrontal cortex are associated with altered signatures of Bayesian predictive coding in trait anxiety

Recent advances in the computational understanding of decision-making processes have led to proposals that anxiety biases how individuals form beliefs and estimate uncertainty. The anxiety and decision-making circuitry broadly overlap in regions such as the medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), and orbitofrontal cortex (OFC). Changes in activity across these brain areas could help explain how misestimation of uncertainty and altered belief updating can lead to impaired learning in anxiety. To test this prediction, this study built on recent progress in rhythm-based formulations of Bayesian predictive coding to identify sources of oscillatory modulations across the ACC, mPFC, and OFC that are associated with altered learning in subclinical trait anxiety. In a magnetoencephalography (MEG) experiment, two groups of human participants pre-screened with high and low trait anxiety (HTA, LTA: 39) performed a volatile probabilistic reward-based learning task. We modelled behaviour using a hierarchical Bayesian learning model. Furthermore, we quantified the parametric effects of trial-wise estimates of unsigned precision-weighted prediction errors (pwPEs) and, separately, precision weights and surprise on source-reconstructed MEG time-frequency responses using convolution modelling. We showed that HTA interferes with overall reward-based learning performance associated with more stochastic decisions and more pronounced lose-shift tendencies. These behavioural effects were explained by an overestimation of volatility and faster belief updating in HTA when compared to LTA. On a neural level, we observed enhanced gamma responses and decreased alpha/beta activity in HTA during the encoding of unsigned pwPEs about about stimulus outcomes relative to LTA. These effects emerged primarily in the ACC and dorsomedial PFC (dmPFC), and they were accompanied by additional ACC alpha/beta modulations representing differential encoding of precision weights in each anxiety group. Our study supports the association between subclinical trait anxiety and faster updating of beliefs in a volatile environment through gamma and alpha/beta activity changes in the ACC and dmPFC.

neuroscience↗

bioRxiv2021

Characterizing the middle-age neurophysiology using EEG/MEG

Middle adulthood - the period of life between 40 and 60 years of age - is accompanied by important physical and emotional changes, as well as cognitive and neuronal ones. Nevertheless, middle age is often overlooked in neuroscience under the assumption that this is a time of relative stability, although cognitive decline, as well as changes in brain structure and function are well-established by the age of 60. Here we characterized the middle-aged brain in the context of healthy younger and older adults by assessing resting-state electrophysiological and neuromagnetic activity in two different samples (N = 179, 631). Alpha and beta oscillations - two key ageing signatures - were analyzed in terms of spectral power and burst events. While posterior alpha power and burst rate features changed linearly with age, similarly to behavioral measures, sensorimotor beta power and burst rate properties varied non-linearly, with inflection points during middle age. The findings suggest that ageing is characterized by distinct spatial and temporal brain dynamics, some critically arising in middle age.

neuroscience↗

bioRxiv2021

Introspection confidence correlates with EEG decoding of self-generated thoughts and meta-awareness

The neurophysiological bases of mind wandering (MW) - an experiential state wherein attention is disengaged from the external environment in favour of internal thoughts, and state meta-awareness are poorly understood. In parallel, the relationship between introspection confidence in experiential state judgements and neural representations remains unclear. Here, we recorded EEG whilst participants completed a listening task within which they made experiential state judgments and rated their confidence. Alpha power was reliably greater during MW episodes, with unaware MW further associated with greater delta and theta power. Multivariate pattern classification analysis revealed that MW, and meta-awareness can be decoded from the distribution of power in these three frequency bands. Critically, we show that individual decoding accuracies positively correlate with introspection confidence. Our results reaffirm the role of alpha oscillations in MW, implicate lower frequencies in meta-awareness, and are consistent with the proposal that introspection confidence indexes neurophysiological discriminability of representational states.

neuroscience↗

bioRxiv2021

State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward learning

Anxiety influences how the brain estimates and responds to uncertainty. These behavioural effects have been described within predictive coding and Bayesian inference frameworks, yet the associated neural correlates remain unclear. Recent work suggests that predictions in generative models of perception are represented in alpha (8-12 Hz) and beta oscillations (13-30 Hz). Updates to predictions are driven by prediction errors weighted by precision (inverse variance; pwPE), and are encoded in gamma oscillations (>30 Hz) and associated with suppression of beta activity. We tested whether state anxiety alters the neural oscillatory activity associated with predictions and pwPE during learning. Healthy human participants performed a probabilistic reward-learning task in a volatile environment. In our previous work, we described learning behaviour in this task using a hierarchical Bayesian model, revealing more precise (biased) beliefs about the reward tendency in state anxiety, consistent with reduced learning in this group. The model provided trajectories of predictions and pwPEs for the current study, allowing us to assess their parametric effects on the time-frequency representations of EEG data. Using convolution modelling for oscillatory responses, we found that, relative to a control group, state anxiety increased beta activity in frontal and sensorimotor regions during processing of pwPE, and in fronto-parietal regions during encoding of predictions. No effects of state anxiety on gamma modulation were found. Our findings expand prior evidence on the oscillatory representations of predictions and pwPEs into the reward-learning domain. The results suggest that state anxiety modulates beta-band oscillatory correlates of pwPE and predictions in generative models, providing insights into the neural processes associated with biased belief updating and poorer reward learning.

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.

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bioRxiv2020

Modulation of neural activity in frontopolar cortex drives reward-based motor learning

Decision-making is increasingly being recognised to play a role in learning motor skills. Understanding the neural processes regulating motor decision-making is therefore essential to identify mechanisms that contribute to motor skill learning. In decision-making tasks, the frontopolar cortex (FPC) is involved in tracking the reward of different alternative choices, as well as their reliability. Whether this FPC function extends to reward landscapes associated with a continuous movement dimension remains unknown. Here we used anodal transcranial direct current stimulation (tDCS) over the right FPC to investigate its role in reward-based motor learning. Nineteen healthy human participants completed a motor sequence learning task using trial-wise reward feedback to discover a hidden performance goal along a continuous dimension: timing. As a control condition, we modulated contralateral motor cortex (left M1) activity with tDCS, which has been shown to benefit motor skill learning but less consistently reward-based motor learning. Each active tDCS condition was contrasted to sham stimulation. Right FPC-tDCS led to faster learning primarily through a regulation of exploration, without concurrent modulation of motor noise. A Bayesian computational model revealed that following rFPC-tDCS, participants had a higher expectation of reward, consistent with their faster learning. These higher reward estimates were inferred to be less volatile, and thus participants under rFPC-tDCS deemed the mapping between movement and reward to be more stable. Relative to sham, lM1-tDCS did not significantly modulate main behavioral outcomes. The results indicate that brain regions previously linked to decision-making, such as the FPC, are relevant for motor skill learning.

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bioRxiv2019

State anxiety biases estimates of uncertainty during reward learning in volatile environments

Previous research established that clinical anxiety impairs decision making and that high trait anxiety interferes with learning rates. Less understood are the effects of temporary anxious states on learning and decision making in healthy populations. Here we follow proposals that anxious states in healthy individuals elicit a pattern of aberrant behavioural, neural, and physiological responses comparable with those found in anxiety disorders, particularly when processing uncertainty in unstable environments. In our study, both a state anxious and a control group learned probabilistic stimulus-outcome mappings in a volatile task environment while we recorded their electrophysiological (EEG) signals. By using a hierarchical Bayesian model, we assessed the effect of state anxiety on Bayesian belief updating with a focus on uncertainty estimates. State anxiety was associated with an underestimation of environmental and informational uncertainty, and an increase in uncertainty about volatility estimates. Anxious individuals deemed their beliefs about reward contingencies to be more precise and to require less updating, ultimately leading to impaired reward-based learning. We interpret this pattern as evidence that state anxious individuals are less tolerant to informational uncertainty about the contingencies governing their environment and more uncertain about the level of stability of the world itself. Further, we tracked the neural representation of belief update signals in the trial-by-trial EEG amplitudes. In control participants, both lower-level precision-weighted prediction errors (pwPEs) about the reward outcomes and higher-level volatility-pwPEs were represented in the ERP signals with an anterior distribution. A different pattern emerged under state anxiety, where a neural representation of pwPEs was only found for updates about volatility. Expanding previous computational work on trait anxiety, our findings establish that temporary anxious states in healthy individuals impair reward-based learning in volatile environments, primarily through changes in uncertainty estimates and potentially a degradation of the neuronal representation of hierarchically-related pwPEs, considered to play a central role in current Bayesian accounts of perceptual inference and learning.

neuroscience↗

bioRxiv2018

Cardiac afferent activity modulates early neural signature of error detection during skilled performance

Behavioral adaptations during performance rely on predicting and evaluating the consequences of our actions through action monitoring. Previous studies revealed that proprioceptive and exteroceptive signals contribute to error-monitoring processes, which are implemented in the posterior medial frontal cortex. Interestingly, errors trigger changes in autonomic nervous system activity such as pupil dilation or heartbeat deceleration. Yet, the contribution of implicit interoceptive signals of bodily states to error-monitoring during ongoing performance has been overlooked. This is more surprising given the evidence on the relevance of interoceptive signals for the modulation of perceptual, affective and cognitive processes.\n\nWe investigated whether cardiovascular interoceptive signals influence the neural correlates of error processing during performance, with an emphasis on the early stages of error processing. We recorded participants electroencephalography and electrocardiogram during the performance of highly-trained music pieces in musicians. Previous event-related potential (ERP) studies revealed that pitch errors during skilled musical performance are preceded by an error detection signal, the pre-error-negativity (preERN), and followed by a later error positivity (PE). In this study, by combining ERP, source localization and multivariate pattern classification analysis, we found that the error-correct ERP waveform had a larger amplitude within 40-100 ms following errors in the systolic period of the cardiac cycle. This component could be decoded from single-trials, was dissociated from the preERN and PE, and stemmed from the inferior parietal cortex, which is a region implicated in cardiac autonomic regulation. In addition, the cardiac phase influenced behavioral alterations resulting from errors, with a smaller post-error slowing and less perturbed velocity in keystrokes following pitch errors in the systole phase of the cardiac cycle. This study provides the first evidence of preconscious visceral information modulating neural and behavioral responses related to early error monitoring during skilled performance.

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