The role of arousal in predictive coding

2016 ◽  
Vol 39 ◽  
Author(s):  
Fernando Ferreira-Santos
Keyword(s):  
Predictive Models ◽  
Predictive Coding ◽  
Prediction Errors

AbstractWithin a predictive coding approach, the arousal/norepinephrine effects described by the GANE (glutamate amplifies noradrenergic effects) model seem to modulate the precision attributed to prediction errors, favoring the selective updating of predictive models with larger prediction errors. However, to explain how arousal effects are triggered, it is likely that different kinds of prediction errors (including interoceptive/affective) need to be considered.

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 Interlimb Coordination of Rhythm and Beat Performance

2021 ◽  
Author(s):  
Signe Hagner ◽  
Cecilie Møller ◽  
Peter Vuust
Keyword(s):  
Prediction Models ◽  
Predictive Coding ◽  
Interlimb Coordination ◽  
Prediction Errors ◽  
Left Hand ◽  
Music Making ◽  
Hands And Feet ◽  
Action Coupling ◽  
Perception Action

Abstract Interlimb coordination is critical to the successful performance of simple activities in everyday life and it depends on precisely timed perception-action coupling. This is particularly true in music-making, where performers often use body-movements to keep the beat while playing more complex rhythmic patterns. In the current study, we used a musical rhythmic paradigm of simultaneous rhythm/beat performance to examine how interlimb coordination between voice, hands and feet is influenced by the inherent hierarchical relationship between rhythm and beat. Sixty right-handed participants—musicians, amateur-musicians and non-musicians—performed three short rhythmic patterns while keeping the underlying beat, using 12 different combinations of voice, hands and feet. Results revealed a bodily hierarchy with five levels 1) left foot, 2) right foot, 3) left hand, 4) right hand, 5) voice, implying a more precise task execution when the rhythm was performed with a limb occupying a higher level in the hierarchy than the limb keeping the beat. The notion of a bodily hierarchy implies that the role assigned to the different limbs is key to successful interlimb coordination: the performance level of a specific limb combination differs considerably, depending on which limb holds the supporting role of the beat and which limb holds the conducting role of the rhythm. Although performance generally increased with expertise, the evidence of the hierarchy was consistent in all three expertise groups. The effects of expertise further highlight how perception influences action: Embracing a predictive coding view, we discuss the possibility that musicians’ more robust metrical prediction models make it easier for musicians to attenuate prediction errors than non-musicians. Overall, the study suggests a comprehensive bodily hierarchy, showing how interlimb coordination is influenced by hierarchical principles in both perception and action.

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 Precision weighting of cortical unsigned prediction errors is mediated by dopamine and benefits learning

2018 ◽  
Author(s):  
J. Haarsma ◽  
P.C. Fletcher ◽  
H. Ziauddeen ◽  
T.J. Spencer ◽  
K.M.J. Diederen ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Predictive Coding ◽  
Learning Task ◽  
Anterior Cingulate ◽  
Dopamine Antagonist ◽  
Prediction Errors ◽  
Data Set ◽  
Health And Illness ◽  
Hierarchical Bayesian Inference

AbstractThe predictive coding framework construes the brain as performing a specific form of hierarchical Bayesian inference. In this framework the precision of cortical unsigned prediction error (surprise) signals is proposed to play a key role in learning and decision-making, and to be controlled by dopamine. To test this hypothesis, we re-analysed an existing data-set from healthy individuals who received a dopamine agonist, antagonist or placebo and who performed an associative learning task under different levels of outcome precision. Computational reinforcement-learning modelling of behaviour provided support for precision-weighting of unsigned prediction errors. Functional MRI revealed coding of unsigned prediction errors relative to their precision in bilateral superior frontal gyri and dorsal anterior cingulate. Cortical precision-weighting was (i) perturbed by the dopamine antagonist sulpiride, and (ii) associated with task performance. These findings have important implications for understanding the role of dopamine in reinforcement learning and predictive coding in health and illness.

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.

Reward Prediction Errors Drive Declarative Learning Irrespective of Agency

2020 ◽  
Author(s):  
Kate Ergo ◽  
Luna De Vilder ◽  
Esther De Loof ◽  
Tom Verguts
Keyword(s):  
Learning Theory ◽  
Learning Effect ◽  
Steady Increase ◽  
Prediction Errors ◽  
Experimental Paradigm ◽  
Reward Prediction ◽  
Declarative Learning

Recent years have witnessed a steady increase in the number of studies investigating the role of reward prediction errors (RPEs) in declarative learning. Specifically, in several experimental paradigms RPEs drive declarative learning; with larger and more positive RPEs enhancing declarative learning. However, it is unknown whether this RPE must derive from the participant’s own response, or whether instead any RPE is sufficient to obtain the learning effect. To test this, we generated RPEs in the same experimental paradigm where we combined an agency and a non-agency condition. We observed no interaction between RPE and agency, suggesting that any RPE (irrespective of its source) can drive declarative learning. This result holds implications for declarative learning theory.

scholarly journals A continuum hypothesis of psychotomimetic rapid antidepressants

2021 ◽  
Vol 5 ◽  
pp. 239821282110077
Author(s):  
Joost Haarsma ◽  
Catherine J Harmer ◽  
Sandra Tamm
Keyword(s):  
Continuum Hypothesis ◽  
Sense Of Self ◽  
Predictive Coding ◽  
Common Mechanism ◽  
Symptoms Of Depression ◽  
Research Areas ◽  
Sensory Evidence ◽  
Perceptual Distortions ◽  
Psychotomimetic Effects

Ketamine, classical psychedelics and sleep deprivation are associated with rapid effects on depression. Interestingly, these interventions also have common psychotomimetic actions, mirroring aspects of psychosis such as an altered sense of self, perceptual distortions and distorted thinking. This raises the question whether these interventions might be acute antidepressants through the same mechanisms that underlie some of their psychotomimetic effects. That is, perhaps some symptoms of depression can be understood as occupying the opposite end of a spectrum where elements of psychosis can be found on the other side. This review aims at reviewing the evidence underlying a proposed continuum hypothesis of psychotomimetic rapid antidepressants, suggesting that a range of psychotomimetic interventions are also acute antidepressants as well as trying to explain these common features in a hierarchical predictive coding framework, where we hypothesise that these interventions share a common mechanism by increasing the flexibility of prior expectations. Neurobiological mechanisms at play and the role of different neuromodulatory systems affected by these interventions and their role in controlling the precision of prior expectations and new sensory evidence will be reviewed. The proposed hypothesis will also be discussed in relation to other existing theories of antidepressants. We also suggest a number of novel experiments to test the hypothesis and highlight research areas that could provide further insights, in the hope to better understand the acute antidepressant properties of these interventions.

The Role of Machine Learning in Centralized Authorization Process of Nanomedicines in European Union

2021 ◽  
Vol 21 ◽  
Author(s):  
Ricardo Santana ◽  
Enrique Onieva ◽  
Robin Zuluaga ◽  
Aliuska Duardo-Sánchez ◽  
Piedad Gañán
Keyword(s):  
Machine Learning ◽  
European Union ◽  
Scientific Knowledge ◽  
Predictive Models ◽  
Physicochemical Characteristics ◽  
Success Rates ◽  
European Regulation ◽  
European Public ◽  
European Public Assessment Report

Background: Machine Learning (ML) has experienced an increasing use given the possibilities to expand the scientific knowledge of different disciplines, such as nanotechnology. This has allowed the creation of Cheminformatic models, capable of predicting biological activity and physicochemical characteristics of new components with high success rates in training and test partitions. Given the current gaps of scientific knowledge and the need of efficient application of medicines products law, this paper analyzes the position of regulators for marketing medicinal nanoproducts in European Union and the role of ML in the authorization process. Methods: In terms of methodology, a dogmatic study of the European regulation and the guidances of the European Medicine Agency on the use of predictive models for nanomaterials was carried out. The study has, as the framework of reference, the European Regulation 726/2004 and has focused on the analysis of how ML processes are contemplated in the regulations. Results: As result, we present a discussion of the information that must be provided for every case for simulation methods. The results show a favorable and flexible position for the development of the use of predictive models to complement the applicant's information. Conclusion: It is concluded that Machine Learning has the capacity to help to improve the application of nanotechnology medicine products regulation. Future regulations should promote this kind of information given the advanced state of art in terms of algorithms that are able to build accurate predictive models. This especially applies to methods such as Perturbation Theory Machine Learning (PTML), given that it is aligned with principles promoted by the standards of Organization for Economic Co-operation and Development (OECD), European Union regulations and European Authority Medicine. To our best knowledge this is the first study focused on nanotechnology medicine products and machine learning use to support technical European public assessment report (EPAR) for complementary information.

The Embodiment of Concepts

2018 ◽  
pp. 640-660
Author(s):  
Michiel Van Elk ◽  
Harold Bekkering
Keyword(s):  
Prediction Error ◽  
Predictive Processing ◽  
Prediction Errors ◽  
Conceptual Representation ◽  
Recurrent Processing ◽  
Different Dimensions ◽  
Prior Models ◽  
Processing Framework

We characterize theories of conceptual representation as embodied, disembodied, or hybrid according to their stance on a number of different dimensions: the nature of concepts, the relation between language and concepts, the function of concepts, the acquisition of concepts, the representation of concepts, and the role of context. We propose to extend an embodied view of concepts, by taking into account the importance of multimodal associations and predictive processing. We argue that concepts are dynamically acquired and updated, based on recurrent processing of prediction error signals in a hierarchically structured network. Concepts are thus used as prior models to generate multimodal expectations, thereby reducing surprise and enabling greater precision in the perception of exemplars. This view places embodied theories of concepts in a novel predictive processing framework, by highlighting the importance of concepts for prediction, learning and shaping categories on the basis of prediction errors.

scholarly journals Neuropsychological assessment and virtual reality training of social prediction in patients with cerebellar malformation

2021 ◽  
Author(s):  
Cosimo Urgesi ◽  
Niccolò Butti ◽  
Alessandra Finisguerra ◽  
Emilia Biffi ◽  
Enza Maria Valente ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Social Cognition ◽  
Contextual Information ◽  
Predictive Coding ◽  
Predictive Processing ◽  
Cerebellar Malformation ◽  
Use Context ◽  
Predictive Role ◽  
Social Prediction

AbstractIt has been proposed that impairments of the predictive function exerted by the cerebellum may account for social cognition deficits. Here, we integrated cerebellar functions in a predictive coding framework to elucidate how cerebellar alterations could affect the predictive processing of others’ behavior. Experiment 1 demonstrated that cerebellar patients were impaired in relying on contextual information during action prediction, and this impairment was significantly associated with social cognition abilities. Experiment 2 indicated that patients with cerebellar malformation showed a domain-general deficit in using contextual information to predict both social and physical events. Experiment 3 provided first evidence that a social-prediction training in virtual reality could boost the ability to use context-based predictions to understand others’ intentions. These findings shed new light on the predictive role of the cerebellum and its contribution to social cognition, paving the way for new approaches to the rehabilitation of the Cerebellar Cognitive Affective Syndrome.

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