Biology subjects

Hohwy, J.

Publications and source records attributed to Hohwy, J..

10 recordsLinked to original sources

bioRxiv2024

When your heart isn't in it anymore: Cardiac correlates of task disengagement

Neuroscience is beginning to uncover the role of interoceptive feedback in perception, learning, and decision-making; however, the relation between spontaneous visceral and cognitive dynamics has received surprisingly little scrutiny. Here, we investigate how subjective, physiological, and behavioural indicators of arousal and attentional state vary in relation to ongoing cardiac activity and brain-heart coupling. Electroencephalogram, electrocardiogram, and pupillometric records were obtained from 65 adults during the performance of a sustained attention to response task (SART). Thought probes were intermittently administered during the SART to collect subjective reports of attentional state (i.e., on-task, mind-wandering, mind-blanking) and vigilance level (i.e., alertness vs. sleepiness). Mind-wandering and mind-blanking reports increased in frequency with time-on-task and were accompanied by decreases in alertness and pupil-linked arousal, but evinced distinct psychophysiological and behavioural profiles. While mind-wandering was associated with greater heart-rate variability and late modulation of the heartbeat-evoked potential, mind-blanking was characterised by greater decreases in heart-rate, pupil size, and brain-heart coupling. Lower heart-rate predicted decreased vigilance and pupil size, in addition to slower, less-biased responses; increased heart-rate variability predicted more impulsive behaviour and pupil dilation. Together, these findings reveal that cardiac and brain-heart connectivity measures afford complementary information about arousal states and attentional dynamics during task performance.

neuroscience↗

bioRxiv2024

Experienced meditators show greater forward travelling cortical alpha wave strengths

Mindfulness meditation involves training attention, commonly towards the current sensory experience, with an attitude of non-judgemental awareness. Theoretical perspectives suggest meditation alters the brains predictive processing mechanisms, increasing the synaptic gain and precision with which sensory information is processed, and reducing the generation or elaboration of higher-order beliefs. Recent research suggests that forwards and backwards travelling cortical alpha waves provide an indication of these predictive processing functions. Here, we used electroencephalography (EEG) to test whether the strength of forwards and backwards travelling cortical alpha waves differed between experienced meditators and a matched sample of non-meditators, both during an eyes-closed resting state (N = 97) and during a visual cognitive (Go/No-go) task (N = 126). Our results showed that meditators produced stronger forwards travelling cortical alpha waves compared to non-meditators, both while resting with their eyes closed and during task performance. Meditators also exhibited weaker backwards travelling cortical alpha wave strength while resting with their eyes closed. These results may be indicative of a neural mechanism underpinning enhanced attention associated with meditation practice, as well as a potential neural marker of the reductions in resting mind-wandering that are suggested to be associated with meditation practice. The results also support models of brain function that suggest attention modification can be achieved by mental training aimed at increased processing of sensory information, which might be indexed by greater strength of forwards travelling cortical alpha waves.

neuroscience↗

bioRxiv2024

Psilocybin increases optimistic engagement over time: computational modelling of behavior in rats

Psilocybin has shown promise as a novel pharmacological intervention for treatment of depression, where post-acute effects of psilocybin treatment have been associated with increased positive mood and decreased pessimism. Although psilocybin is proving to be effective in clinical trials for treatment of psychiatric disorders, the information processing mechanisms affected by psilocybin are not well understood. Here, we fit computational models of underlying decision-making mechanisms to behaviour in rats. The model revealed that rats treated with psilocybin achieve more rewards through increased task engagement, mediated by modification of forgetting rates and reduced loss aversion. These findings suggest that psilocybin may afford an optimism bias that arises through altered belief updating, with translational potential for clinical populations characterised by lack of optimism.

animal behavior and cognition↗

bioRxiv2022

Meditators probably show increased behaviour-monitoring related neural activity

ObjectivesMindfulness meditation is associated with better attention function. Performance monitoring and error-processing are important aspects of attention. We investigated whether experienced meditators showed different neural activity related to performance monitoring and error-processing. Previous research has produced inconsistent results. This study used more rigorous analyses and a larger sample to resolve the inconsistencies. MethodsWe used electroencephalography (EEG) to measure the error-related negativity (ERN) and error positivity (Pe) following correct and incorrect responses to a Go/Nogo task from 27 experienced meditators and 27 non-meditators. ResultsNo differences were found in the ERN (all p > 0.05). Meditators showed larger global field potentials (GFP) in the Pe after both correct responses and errors, indicating stronger neural responses (p = 0.0190, FDR-p = 0.152, np2 = 0.0951, BFincl = 2.691). This effect did not pass multiple comparison controls. However, single electrode analysis of the Pe did pass multiple comparison controls (p = 0.002, FDR-p = 0.016, np2 = 0.133, BFincl = 220.659). Meditators also showed a significantly larger Pe GFP for errors only, which would have passed multiple comparison controls, but was not a primary analysis (p = 0.0028, np2 = 0.1493, BF10 = 9.999). ConclusionsMeditation may strengthen neural responses related to performance monitoring (measured by the Pe), but not specifically to error monitoring (although measurements of the Pe after errors may be more sensitive to group differences). However, only the single electrode analysis passed multiple comparison controls, while analysis including all electrodes did not, so this conclusion remains tentative.

neuroscience↗

bioRxiv2021

Expectations boost the reconstruction of auditory features from electrophysiological responses to noisy speech

Online speech processing imposes significant computational demands on the listening brain, the underlying mechanisms of which remain poorly understood. Here, we exploit the perceptual pop-out phenomenon (i.e. the dramatic improvement of speech intelligibility after receiving information about speech content) to investigate the neurophysiological effects of prior expectations on degraded speech comprehension. We recorded electroencephalography and pupillometry from 21 adults while they rated the clarity of noise-vocoded and sine-wave synthesised sentences. Pop-out was reliably elicited following visual presentation of the corresponding written sentence, but not following incongruent or neutral text. Pop-out was associated with improved reconstruction of the acoustic stimulus envelope from low-frequency EEG activity, implying that improvements in perceptual clarity were mediated via top-down signals that enhance the quality of cortical speech representations. Spectral analysis further revealed that pop-out was accompanied by a reduction in theta-band power, consistent with predictive coding accounts of acoustic filling-in and incremental sentence processing. Moreover, delta-band power, alpha-band power, and pupil diameter were all increased following the provision of any written sentence information, irrespective of content. Together, these findings reveal distinctive profiles of neurophysiological activity that differentiate the content-specific processes associated with degraded speech comprehension from the context-specific processes invoked under adverse listening conditions.

neuroscience↗

bioRxiv2021

Differences in working memory coding of biological motion attributed to oneself and others

The question how the brain distinguishes between information about oneself and the rest of the world is of fundamental interest to both philosophy and neuroscience. This question can be approached empirically by investigating how associating stimuli with oneself leads to differences in neurocognitive processing. However, little is known about the brain network involved in forming such self-associations for, specifically, bodily stimuli. In this fMRI study, we sought to distinguish the neural substrates of representing a full-body movement as ones movement and as someone elses movement. Participants performed a delayed match-to-sample working memory task where a retained full-body movement (displayed using point-light walkers) was arbitrarily labelled as ones own movement or as performed by someone else. By using arbitrary associations we aimed to address a limitation of previous studies, namely that our own movements are more familiar to us than movements of other people. A searchlight multivariate decoding analysis was used to test where information about types of movement and about self-association was coded. Movement specific activation patterns was found in a network of regions also involved in perceptual processing of movement stimuli, however not in early sensory regions. Information about whether a memorized movement was associated with the self or with another person was found to be coded by activity in the left middle frontal gyrus (MFG), left inferior frontal gyrus (IFG), bilateral supplementary motor area, and (at reduced threshold) in the left temporoparietal junction (TPJ). These areas are frequently reported as involved in action understanding (IFG, MFG) and domain-general self/other distinction (TPJ). Finally, in univariate analysis we found that selecting a self-associated movement for retention was related to increased activity in the ventral medial prefrontal cortex.

neuroscience↗

bioRxiv2020

The Effect of Uncertainty on Prediction Error in the Action-Perception Loop

Among all their sensations, agents need to distinguish between those caused by themselves and those caused by external causes. The ability to infer agency is particularly challenging under conditions of uncertainty. Within the predictive processing framework, this should happen through active control of prediction error that closes the action-perception loop. Here we use a novel, temporally-sensitive, behavioural proxy for prediction error to show that it is minimised most quickly when variability is low, but also when volatility is high. Further, when human participants report agency, they show steeper prediction error minimisation. We demonstrate broad effects of uncertainty on accuracy of agency judgements, movement, policy selection, and hypothesis switching. Measuring autism traits, we find differences in policy selection, sensitivity to uncertainty and hypothesis switching despite no difference in overall accuracy.

neuroscience↗

bioRxiv2018

Expectation and attention increase the integration of top-down and bottom-up signals in perception through different pathways

Perception results from the integration of incoming sensory information with pre-existing information available in the brain. In this EEG (electroencephalography) study we utilised the Hierarchical Frequency Tagging method to examine how such integration is modulated by expectation and attention. Using intermodulation (IM) components as a measure of non-linear signal integration, we show in three different experiments that both expectation and attention enhance integration between top-down and bottom-up signals. Based on multispectral phase coherence, we present two direct physiological measures to demonstrate the distinct yet related mechanisms of expectation and attention. Specifically, our results link expectation to the modulation of prediction signals and the integration of top-down and bottom-up information at lower levels of the visual hierarchy. Meanwhile, they link attention to the propagation of ascending signals and the integration of information at higher levels of the visual hierarchy. These results are consistent with the predictive coding account of perception.

neuroscience↗

bioRxiv2017

Deep Brain Stimulation for Parkinson’s disease changes perception in the Rubber Hand Illusion

Parkinsons disease (PD) alters cortico-basal ganglia-thalamic circuitry and susceptibility to an illusion of bodily awareness, the Rubber Hand Illusion (RHI). Bodily awareness is thought to result from multisensory integration in a predominantly cortical network; the role of subcortical connections is unknown. We studied the effect of modulating cortico-subcortical circuitry on multisensory integration for bodily awareness in PD patients treated with subthalamic nucleus (STN) deep brain stimulation (DBS) using the RHI experiment. Typically, synchronous visuo-tactile cues induce a false perception of touch on the rubber hand as if it were the subjects hand, whereas asynchronous visuo-tactile cues do not. However, we found that in the asynchronous condition, patients in the off-stimulation state did not reject the RHI as strongly as healthy controls; switching on STN-DBS partially normalised their responses. Patients in the off-stimulation state also misjudged the position of their hand, indicating it to be closer to the rubber hand than controls. However, STN-DBS did not affect proprioceptive judgements or subsequent arm movements altered by the perceptual effects of the illusion. Our findings support the idea that the STN and subcortical connections have a key role in multisensory integration for bodily awareness. Decisionmaking in multisensory bodily illusions is discussed.

neuroscience↗

bioRxiv2016

Hierarchical Frequency Tagging reveals neural markers of predictive coding under varying uncertainty

Understanding the integration of top-down and bottom-up signals is essential for the study of perception. Current accounts of predictive coding describe this in terms of interactions between state units encoding expectations or predictions, and error units encoding prediction error. However, direct neural evidence for such interactions has not been well established. To achieve this, we combined EEG methods that preferentially tag different levels in the visual hierarchy: Steady State Visual Evoked Potential (SSVEP at 10Hz, tracking bottom-up signals) and Semantic Wavelet-Induced Frequency Tagging (SWIFT at 1.3Hz tracking top-down signals). Importantly, we examined intermodulation components (IM, e.g., 11.3Hz) as a measure of integration between these signals. To examine the influence of expectation and predictions on the nature of such integration, we constructed 50-second movie streams and modulated expectation levels for upcoming stimuli by varying the proportion of images presented across trials. We found SWIFT, SSVEP and IM signals to differ in important ways. SSVEP was strongest over occipital electrodes and was not modified by certainty. Conversely, SWIFT signals were evident over temporo- and parieto-occipital areas and decreased as a function of increasing certainty levels. Finally, IMs were evident over occipital electrodes and increased as a function of certainty. These results link SSVEP, SWIFT and IM signals to sensory evidence, predictions, prediction errors and hypothesis-testing - the core elements of predictive coding. These findings provide neural evidence for the integration of top-down and bottom-up information in perception, opening new avenues to studying such interactions in perception while constraining neuronal models of predictive coding.\n\nSIGNIFICANCE STATEMENTThere is a growing understanding that both top-down and bottom-up signals underlie perception. But how do these signals interact? And how does this process depend on the signals probabilistic properties? Predictive coding theories of perception describe this in terms how well top-down predictions fit with bottom-up sensory input. Identifying neural markers for such signal integration is therefore essential for the study of perception and predictive coding theories in particular. The novel Hierarchical Frequency Tagging method simultaneously tags top-down and bottom-up signals in EEG recordings, while obtaining a measure for the level of integration between these signals. Our results suggest that top-down predictions indeed integrate with bottom-up signals in a manner that is modulated by the predictability of the sensory input.

neuroscience↗