scholarly journals Focus of attention modulates the heartbeat evoked potential

2018 ◽  
Author(s):  
Frederike H. Petzschner ◽  
Lilian A. Weber ◽  
Katharina V. Wellstein ◽  
Gina Paolini ◽  
Cao Tri Do ◽  
...  
Keyword(s):  
Evoked Potential ◽  
Time Window ◽  
Predictive Coding ◽  
Sensory Information ◽  
Attentional Focus ◽  
The Body ◽  
Self Report ◽  
Prediction Errors ◽  
Theoretical Frameworks ◽  
Heartbeat Evoked Potential

AbstractTheoretical frameworks such as predictive coding suggest that the perception of the body and world – interoception and exteroception – involve intertwined processes of inference, learning, and prediction. In this framework, attention is thought to gate the influence of sensory information on perception. In contrast to exteroception, there is limited evidence for purely attentional effects on interoception. Here, we empirically tested if attentional focus modulates cortical processing of single heartbeats, using a newly-developed experimental paradigm to probe purely attentional differences between exteroceptive and interoceptive conditions in the heartbeat evoked potential (HEP). We found that the HEP is significantly higher during interoceptive compared to exteroceptive attention, in a time window of 520-580ms after the R-peak. Furthermore, this effect predicted self-report measures of autonomic system reactivity. This study thus provides direct evidence that the HEP is modulated by attention and supports recent interpretations of the HEP as a neural correlate of interoceptive prediction errors.

scholarly journals Skipping a Beat: Heartbeat-Evoked Potentials Reflect Predictions during Interoceptive-Exteroceptive Integration

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Leah Banellis ◽  
Damian Cruse
Keyword(s):  
Predictive Coding ◽  
Auditory Stimuli ◽  
Prediction Errors ◽  
Self Awareness ◽  
Early Effect ◽  
Temporal Cues ◽  
Heartbeat Evoked Potential ◽  
External Signals ◽  
Potential Tool

Abstract Several theories propose that emotions and self-awareness arise from the integration of internal and external signals and their respective precision-weighted expectations. Supporting these mechanisms, research indicates that the brain uses temporal cues from cardiac signals to predict auditory stimuli and that these predictions and their prediction errors can be observed in the scalp heartbeat-evoked potential (HEP). We investigated the effect of precision modulations on these cross-modal predictive mechanisms, via attention and interoceptive ability. We presented auditory sequences at short (perceived synchronous) or long (perceived asynchronous) cardio-audio delays, with half of the trials including an omission. Participants attended to the cardio-audio synchronicity of the tones (internal attention) or the auditory stimuli alone (external attention). Comparing HEPs during omissions allowed for the observation of pure predictive signals, without contaminating auditory input. We observed an early effect of cardio-audio delay, reflecting a difference in heartbeat-driven expectations. We also observed a larger positivity to the omissions of sounds perceived as synchronous than to the omissions of sounds perceived as asynchronous when attending internally only, consistent with the role of attentional precision for enhancing predictions. These results provide support for attentionally modulated cross-modal predictive coding and suggest a potential tool for investigating its role in emotion and self-awareness.

scholarly journals Attention Promotes the Neural Encoding of Prediction Errors

2019 ◽  
Author(s):  
Cooper A. Smout ◽  
Matthew F. Tang ◽  
Marta I. Garrido ◽  
Jason B. Mattingley
Keyword(s):  
Information Processing ◽  
Coding Theory ◽  
Predictive Coding ◽  
Sensory Information ◽  
Neural Response ◽  
Prediction Errors ◽  
Feature Information ◽  
The Difference ◽  
Stimulus Features ◽  
The Brain

AbstractThe human brain is thought to optimise the encoding of incoming sensory information through two principal mechanisms: prediction uses stored information to guide the interpretation of forthcoming sensory events, and attention prioritizes these events according to their behavioural relevance. Despite the ubiquitous contributions of attention and prediction to various aspects of perception and cognition, it remains unknown how they interact to modulate information processing in the brain. A recent extension of predictive coding theory suggests that attention optimises the expected precision of predictions by modulating the synaptic gain of prediction error units. Since prediction errors code for the difference between predictions and sensory signals, this model would suggest that attention increases the selectivity for mismatch information in the neural response to a surprising stimulus. Alternative predictive coding models proposes that attention increases the activity of prediction (or ‘representation’) neurons, and would therefore suggest that attention and prediction synergistically modulate selectivity for feature information in the brain. Here we applied multivariate forward encoding techniques to neural activity recorded via electroencephalography (EEG) as human observers performed a simple visual task, to test for the effect of attention on both mismatch and feature information in the neural response to surprising stimuli. Participants attended or ignored a periodic stream of gratings, the orientations of which could be either predictable, surprising, or unpredictable. We found that surprising stimuli evoked neural responses that were encoded according to the difference between predicted and observed stimulus features, and that attention facilitated the encoding of this type of information in the brain. These findings advance our understanding of how attention and prediction modulate information processing in the brain, and support the theory that attention optimises precision expectations during hierarchical inference by increasing the gain of prediction errors.

scholarly journals Heart–brain interactions shape somatosensory perception and evoked potentials

2020 ◽  
Vol 117 (19) ◽  
pp. 10575-10584 ◽  
Author(s):  
Esra Al ◽  
Fivos Iliopoulos ◽  
Norman Forschack ◽  
Till Nierhaus ◽  
Martin Grund ◽  
...  
Keyword(s):  
Evoked Potential ◽  
Cardiac Cycle ◽  
Predictive Coding ◽  
Conscious Perception ◽  
Somatosensory Processing ◽  
Attentional Resources ◽  
Sensory Effects ◽  
Stimulus Timing ◽  
Timing Effects ◽  
Heartbeat Evoked Potential

Even though humans are mostly not aware of their heartbeats, several heartbeat-related effects have been reported to influence conscious perception. It is not clear whether these effects are distinct or related phenomena, or whether they are early sensory effects or late decisional processes. Combining electroencephalography and electrocardiography, along with signal detection theory analyses, we identify two distinct heartbeat-related influences on conscious perception differentially related to early vs. late somatosensory processing. First, an effect on early sensory processing was found for the heartbeat-evoked potential (HEP), a marker of cardiac interoception. The amplitude of the prestimulus HEP negatively correlated with localization and detection of somatosensory stimuli, reflecting a more conservative detection bias (criterion). Importantly, higher HEP amplitudes were followed by decreases in early (P50) as well as late (N140, P300) somatosensory-evoked potential (SEP) amplitudes. Second, stimulus timing along the cardiac cycle also affected perception. During systole, stimuli were detected and correctly localized less frequently, relating to a shift in perceptual sensitivity. This perceptual attenuation was accompanied by the suppression of only late SEP components (P300) and was stronger for individuals with a more stable heart rate. Both heart-related effects were independent of alpha oscillations’ influence on somatosensory processing. We explain cardiac cycle timing effects in a predictive coding account and suggest that HEP-related effects might reflect spontaneous shifts between interoception and exteroception or modulations of general attentional resources. Thus, our results provide a general conceptual framework to explain how internal signals can be integrated into our conscious perception of the world.

scholarly journals Systematic review and meta-analysis of the relationship between the heartbeat-evoked potential and interoception.

2020 ◽  
Author(s):  
Michel-Pierre Coll ◽  
Hannah Hobson ◽  
Jennifer Murphy
Keyword(s):  
Systematic Review ◽  
Empirical Evidence ◽  
Evoked Potential ◽  
Meta Analysis ◽  
Clinical Status ◽  
The Body ◽  
Indirect Measures ◽  
Heartbeat Evoked Potential ◽  
Meta Analyses ◽  
The Relationship

The Heartbeat Evoked Potential (HEP) has been proposed as a neurophysiological marker of interoceptive processing. Despite its use to validate interoceptive measures and to assess interoceptive functioning in clinical groups, the empirical evidence for a relationship between HEP amplitude and interoceptive processing, including measures of such processing, is scattered across several studies with varied designs. The aim of this systematic review and meta-analysis was to examine the body of HEP-interoception research, and consider the associations the HEP shows with various direct and indirect measures of interoception, and how it is affected by manipulations of interoceptive processing. Specifically, we assessed the effect on HEP amplitude of manipulating attention to the heartbeat; manipulating participants’ arousal; the association between the HEP and behavioural measures of cardiac interoception; and comparisons between healthy and clinical groups. Following database searches and screening, 45 studies were included in the systematic review and 42 in the meta-analyses. We noted variations in the ways individual studies have attempted to address key confounds, particularly the cardiac field artefact. Meta-analytic summaries indicated there were moderate to large effects of attention, arousal, and clinical status on the HEP, and a moderate association between HEP amplitude and behavioural measures of interoception. Problematically, the reliability of the meta-analytic effects documented here remain unknown, given the lack of standardised protocols for measuring the HEP. Thus, it is possible effects are driven by confounds such as cardiac factors or somatosensory effects.

scholarly journals The predictive brain in action: Involuntary actions reduce body prediction errors

2020 ◽  
Author(s):  
Pablo Lanillos ◽  
Sae Franklin ◽  
David W. Franklin
Keyword(s):  
Prediction Error ◽  
Sensory Information ◽  
The Body ◽  
Predictive Processing ◽  
Body Ownership ◽  
Prediction Errors ◽  
Uncertain Information ◽  
Energy Principle ◽  
Virtual Hand ◽  
The Brain

AbstractThe perception of our body in space is flexible and manipulable. The predictive brain hypothesis explains this malleability as a consequence of the interplay between incoming sensory information and our body expectations. However, given the interaction between perception and action, we might also expect that actions would arise due to prediction errors, especially in conflicting situations. Here we describe a computational model, based on the free-energy principle, that forecasts involuntary movements in sensorimotor conflicts. We experimentally confirm those predictions in humans by means of a virtual reality rubber-hand illusion. Participants generated movements (forces) towards the virtual hand, regardless of its location with respect to the real arm, with little to no forces produced when the virtual hand overlaid their physical hand. The congruency of our model predictions and human observations shows that the brain-body is generating actions to reduce the prediction error between the expected arm location and the new visual arm. This observed unconscious mechanism is an empirical validation of the perception-action duality in body adaptation to uncertain situations and evidence of the active component of predictive processing.Author SummaryHumans’ capacity to perceive and control their body in space is central in awareness, adaptation and safe interaction. From low-level body perception to body-ownership, discovering how the brain represents the body and generates actions is of major importance for cognitive science and also for robotics and artificial intelligence. The present study shows that humans move their body to match the expected location according to other (visual) sensory input, which corresponds to reducing the prediction error. This means that the brain adapts to conflicting or uncertain information from the senses by unconsciously acting in the world.

scholarly journals Atypical visual-auditory predictive coding in autism spectrum disorder: Electrophysiological evidence from stimulus omissions

Autism ◽  
2020 ◽  
Vol 24 (7) ◽  
pp. 1849-1859
Author(s):  
Thijs van Laarhoven ◽  
Jeroen J Stekelenburg ◽  
Mart LJM Eussen ◽  
Jean Vroomen
Keyword(s):  
Autism Spectrum Disorder ◽  
Brain Activity ◽  
Predictive Coding ◽  
Sensory Information ◽  
Sensory Stimulation ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Prediction Errors ◽  
Typical Development ◽  
Autism Spectrum Disorder Group

Autism spectrum disorder is a pervasive neurodevelopmental disorder that has been linked to a range of perceptual processing alterations, including hypo- and hyperresponsiveness to sensory stimulation. A recently proposed theory that attempts to account for these symptoms, states that autistic individuals have a decreased ability to anticipate upcoming sensory stimulation due to overly precise internal prediction models. Here, we tested this hypothesis by comparing the electrophysiological markers of prediction errors in auditory prediction by vision between a group of autistic individuals and a group of age-matched individuals with typical development. Between-group differences in prediction error signaling were assessed by comparing event-related potentials evoked by unexpected auditory omissions in a sequence of audiovisual recordings of a handclap in which the visual motion reliably predicted the onset and content of the sound. Unexpected auditory omissions induced an increased early negative omission response in the autism spectrum disorder group, indicating that violations of the prediction model produced larger prediction errors in the autism spectrum disorder group compared to the typical development group. The current results show that autistic individuals have alterations in visual-auditory predictive coding, and support the notion of impaired predictive coding as a core deficit underlying atypical sensory perception in autism spectrum disorder. Lay abstract Many autistic individuals experience difficulties in processing sensory information (e.g. increased sensitivity to sound). Here we show that these difficulties may be related to an inability to process unexpected sensory stimulation. In this study, 29 older adolescents and young adults with autism and 29 age-matched individuals with typical development participated in an electroencephalography study. The electroencephalography study measured the participants’ brain activity during unexpected silences in a sequence of videos of a handclap. The results showed that the brain activity of autistic individuals during these silences was increased compared to individuals with typical development. This increased activity indicates that autistic individuals may have difficulties in processing unexpected incoming sensory information, and might explain why autistic individuals are often overwhelmed by sensory stimulation. Our findings contribute to a better understanding of the neural mechanisms underlying the different sensory perception experienced by autistic individuals.

scholarly journals Skipping a beat: heartbeat-evoked potentials reflect predictions during interoceptive-exteroceptive integration

2020 ◽  
Author(s):  
Leah Banellis ◽  
Damian Cruse
Keyword(s):  
Predictive Coding ◽  
Auditory Stimuli ◽  
Prediction Errors ◽  
Self Awareness ◽  
Early Effect ◽  
Temporal Cues ◽  
Heartbeat Evoked Potential ◽  
External Signals ◽  
Potential Tool

AbstractSeveral theories propose that emotions and self-awareness arise from the integration of internal and external signals and their respective precision-weighted expectations. Supporting these mechanisms, research indicates that the brain uses temporal cues from cardiac signals to predict auditory stimuli, and that these predictions and their prediction errors can be observed in the scalp heartbeat-evoked potential (HEP). We investigated the effect of precision modulations on these cross-modal predictive mechanisms, via attention and interoceptive ability. We presented auditory sequences at short (perceived synchronous) or long (perceived asynchronous) cardio-audio delays, with half of the trials including an omission. Participants attended to the cardio-audio synchronicity of the tones (internal attention) or the auditory stimuli alone (external attention). Comparing HEPs during omissions allowed for the observation of pure predictive signals, without contaminating auditory input. We observed an early effect of cardio-audio delay, reflecting a difference in heartbeat-driven expectations. We also observed a larger positivity to omissions of sounds perceived as synchronous than to omissions of sounds perceived as asynchronous when attending internally only, consistent with the role of attentional precision for enhancing predictions. These results provide support for attentionally-modulated cross-modal predictive coding, and suggest a potential tool for investigating its role in emotion and self-awareness.

scholarly journals A Computational Theory of Mindfulness Based Cognitive Therapy from the “Bayesian Brain” Perspective

2019 ◽  
Author(s):  
Zina-Mary Manjaly ◽  
Sandra Iglesias
Keyword(s):  
Cognitive Therapy ◽  
Theoretical Perspective ◽  
Predictive Coding ◽  
Computational Modelling ◽  
Behavioural Therapy ◽  
The Body ◽  
Prediction Errors ◽  
Recurrent Depression ◽  
Bayesian Brain ◽  
Core Concepts

Mindfulness Based Cognitive Therapy (MBCT) was developed to combine methods from cognitive behavioural therapy and meditative techniques, with the specific goal of preventing relapse in recurrent depression. While supported by empirical evidence from multiple clinical trials, the cognitive mechanisms behind the effectiveness of MBCT are not well understood in computational (information processing) or biological terms.This article introduces a testable theory about the computational mechanisms behind MBCT that is grounded in “Bayesian brain” concepts of perception from cognitive neuroscience, such as predictive coding. These concepts regard the brain as embodying a model of its environment (including the external world and the body) which predicts future sensory inputs and is updated by prediction errors, depending on how precise these error signals are.This article offers a concrete proposal how core concepts of MBCT – the being mode, decentring, and reactivity – could be understood in terms of perceptual and metacognitive processes that draw on specific computational mechanisms of the “Bayesian brain”. Importantly, the proposed theory can be tested experimentally, using a combination of behavioural paradigms, computational modelling, and neuroimaging. The novel theoretical perspective on MBCT described in this paper may offer opportunities for finessing the conceptual and practical aspects of MBCT.

scholarly journals Looking forward does not mean forgetting about the past: ERP evidence for the interplay of predictive coding and interference during language processing

2019 ◽  
Author(s):  
Pia Schoknecht ◽  
Dietmar Roehm ◽  
Matthias Schlesewsky ◽  
Ina Bornkessel-Schlesewsky
Keyword(s):  
Language Processing ◽  
Model Updating ◽  
Time Window ◽  
Critical Word ◽  
Predictive Coding ◽  
Prediction Errors ◽  
Interference Effects ◽  
Neuronal Mechanisms ◽  
Mechanisms Of Memory ◽  
Retrieval Interference

AbstractInterference and prediction have independently been identified as crucial influencing factors during language processing. However, their interaction remains severely underinvestigated. Furthermore, the neurobiological basis of cue-based retrieval and retrieval interference during language processing remains insufficiently understood. Here, we present an ERP experiment that systematically examined the interaction of interference and prediction during language processing. We used the neurobiologically well-established predictive coding framework and insights regarding the neuronal mechanisms of memory for the theoretical framing of our study. German sentence pairs were presented word-by-word, with an article in the second sentence constituting the critical word. We analyzed mean single trial EEG activity in the N400 time window and found an interaction between interference and prediction (measured by cloze probability). Under high predictability, no interference effects were observable. Under the predictive coding account, highly predictable input is totally explained by top-down activity. Therefore the input induces no retrieval operations which could be influenced by interference. In contrast, under low predictability, conditions with high interference or with a close, low-interference distractor showed a broadly distributed negativity compared to conditions with a distant, low-interference distractor. We interpret this result as showing that when unpredicted input induces model updating, this may elicit memory retrieval including the evaluation of distractor items, thus leading to interference effects. We conclude that interference should be included in predictive coding-based accounts of language because prediction errors can trigger retrieval operations and, therefore, induce interference.

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time

2016 ◽  
Vol 63 (6) ◽  
pp. 333-342
Author(s):  
Roberto Limongi ◽  
Angélica M. Silva
Keyword(s):  
Response Time ◽  
Short Term Memory ◽  
Estimation Error ◽  
Predictive Coding ◽  
Time Estimation ◽  
Prediction Errors ◽  
Memory Scanning ◽  
Short Term ◽  
Term Memory ◽  
Temporal Prediction

Abstract. The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production – where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

Sign in / Sign up

Export Citation Format

Share Document