scholarly journals Active inference unifies intentional and conflict-resolution imperatives of motor control

2021 ◽  
Author(s):  
Antonella Maselli ◽  
Pablo Lanillos ◽  
Giovanni Pezzulo
Keyword(s):  
Motor Control ◽  
Conflict Resolution ◽  
Movement Control ◽  
Prediction Errors ◽  
Active Inference ◽  
Rubber Hand ◽  
Classical Studies ◽  
Online Corrections ◽  
Motor Awareness ◽  
Shed Light

The field of motor control has long focused on the achievement of external goals through action (e.g., reaching and grasping objects). However, recent studies in conditions of multisensory conflict, such as when a subject experiences the rubber hand illusion or embodies an avatar in virtual reality, reveal the presence of unconscious movements that are not goal-directed, but rather aim at resolving multisensory conflicts; for example, by aligning the position of a person’s arm with that of an embodied avatar. This second, conflict-resolution imperative of movement control did not emerge in classical studies of motor adaptation and online corrections, which did not allow movements to reduce the conflicts; and has been largely ignored so far in formal theories. Here, we propose a model of movement control grounded in the theory of active inference that integrates intentional and conflict-resolution imperatives. We present three simulations showing that the active inference model is able to characterize movements guided by the intention to achieve an external goal, by the necessity to resolve multisensory conflict, or both. Furthermore, our simulations reveal a fundamental difference between the (active) inference underlying intentional and conflict-resolution imperatives, respectively, by showing that it is driven by two different (model and sensory) kinds of prediction errors. Finally, our simulations show that when movement is only guided by conflict-resolution, the model incorrectly infers that is velocity is zero, as if it was not moving. This result suggests a novel speculative explanation for the fact that people are unaware of their subtle compensatory movements to avoid multisensory conflict. Furthermore, it can potentially help shed light on deficits of motor awareness that arise in psychopathological conditions.

Activity, Agency, and Inner Speech Pathology

2018 ◽  
Author(s):  
Lauren Swiney
Keyword(s):  
Motor Control ◽  
Sensory Input ◽  
The Other ◽  
Predictive Processing ◽  
Inner Speech ◽  
Speech Pathology ◽  
Active Inference ◽  
Comparator Hypothesis

Over the last thirty years the comparator hypothesis has emerged as a prominent account of inner speech pathology. This chapter discusses a number of cognitive accounts broadly derived from this approach, highlighting the existence of two importantly distinct notions of inner speech in the literature; one as a prediction in the absence of sensory input, the other as an act with sensory consequences that are themselves predicted. Under earlier frameworks in which inner speech is described in the context of classic models of motor control, I argue that these two notions may be compatible, providing two routes to inner speech pathology. Under more recent accounts grounded in the architecture of Bayesian predictive processing, I argue that “active inference” approaches to action generation pose serious challenges to the plausibility of the latter notion of inner speech, while providing the former notion with rich explanatory possibilities for inner speech pathology.

scholarly journals Active Inference: Applicability to Different Types of Social Organization Explained through Reference to Industrial Engineering and Quality Management

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 198
Author(s):  
Stephen Fox
Keyword(s):  
Artificial Intelligence ◽  
Quality Management ◽  
Social Organization ◽  
Generative Models ◽  
Industrial Engineering ◽  
Prediction Errors ◽  
Active Inference ◽  
For Profit ◽  
Different Types ◽  
Inference Theory

Active inference is a physics of life process theory of perception, action and learning that is applicable to natural and artificial agents. In this paper, active inference theory is related to different types of practice in social organization. Here, the term social organization is used to clarify that this paper does not encompass organization in biological systems. Rather, the paper addresses active inference in social organization that utilizes industrial engineering, quality management, and artificial intelligence alongside human intelligence. Social organization referred to in this paper can be in private companies, public institutions, other for-profit or not-for-profit organizations, and any combination of them. The relevance of active inference theory is explained in terms of variational free energy, prediction errors, generative models, and Markov blankets. Active inference theory is most relevant to the social organization of work that is highly repetitive. By contrast, there are more challenges involved in applying active inference theory for social organization of less repetitive endeavors such as one-of-a-kind projects. These challenges need to be addressed in order for active inference to provide a unifying framework for different types of social organization employing human and artificial intelligence.

Adaptive timing, attention, and movement control

1997 ◽  
Vol 20 (4) ◽  
pp. 619-619 ◽  
Author(s):  
Stephen Grossberg
Keyword(s):  
Motor Control ◽  
Movement Control ◽  
The Difference ◽  
Adaptive Timing

Examples of how LTP and LTD can control adaptively-timed learning that modulates attention and motor control are given. It is also suggested that LTP/LTD can play a role in storing memories. The distinction between match-based and mismatch-based learning may help to clarify the difference.

scholarly journals Locus Coeruleus tracking of prediction errors optimises cognitive flexibility: An Active Inference model

2019 ◽  
Vol 15 (1) ◽  
pp. e1006267 ◽  
Author(s):  
Anna C. Sales ◽  
Karl J. Friston ◽  
Matthew W. Jones ◽  
Anthony E. Pickering ◽  
Rosalyn J. Moran
Keyword(s):  
Locus Coeruleus ◽  
Cognitive Flexibility ◽  
Prediction Errors ◽  
Active Inference ◽  
Inference Model

scholarly journals T136. NEURAL CORRELATES OF ALTERED COGNITIVE FLEXIBILITY AND STABILITY FOR MOTOR CONTROL IN SCHIZOPHRENIA – JUST TWO SIDES OF THE SAME COIN?

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S282-S282
Author(s):  
Rebekka Lencer ◽  
Isabel Standke ◽  
Udo Dannlowski ◽  
Ricarda I Schubotz ◽  
Ima Trempler
Keyword(s):  
Motor Control ◽  
Cognitive Flexibility ◽  
Negative Symptoms ◽  
Region Of Interest ◽  
Brain Regions ◽  
System Level ◽  
Motor Symptoms ◽  
Prediction Errors ◽  
Cognitive Stability ◽  
Imaging Results

Abstract Background It has been suggested that patients with schizophrenia are impaired in the use of prediction error signals resulting in disturbances of motor control. Alterations in fronto-striatal dopamine transmitter systems are regarded to contribute to these deficits. It is unclear whether the use of predictive strategies for motor control may be systematically related to impaired cognitive functions in patients. In healthy subjects, cognitive flexibility has been related to medial prefrontal cortex (PFC) function, while cognitive stability was related to lateral PFC integrity with both brain regions being modulated by striatal activity. Despite these findings, the interplay of cognitive flexibility and stability needed for motor control and its associations to alterations on the brain system level have not been investigated systematically in this patient group. Methods We assessed patients with schizophrenia (N=22) and healthy controls (N=22) on first, detection of relevant unexpected events (cognitive flexibility) and second, distractor resistance to irrelevant prediction errors (cognitive stability) using a serial prediction task including the digits 1-2-3-4. We applied an event-related design in a functional magnetic resonance imaging (fMRI) environment (3T) to explore brain networks underlying cognitive flexibility and stability, respectively. In analyses, the minimum cluster extent was set to k > 20 and corrected using the false discovery rate (FDR) with p < 0.05. Since we were specifically interested in the role of the striatum, we applied small volume correction at p < 0.05 with the minimum cluster extent set to k > 5 in a region of interest analyses. Participants were also assessed on general cognitive function using the Brief Assessment of Cognition in Schizophrenia (BACS) battery and on motor symptoms using the Heidelberg Scale for Neurological Soft Signs (NSS). Results Patients detected less behaviorally relevant events (M(Pat) = 0.57 vs. M(HC) = 0.78, F(41,1) = 16.32, p < 0.001) and ignored less irrelevant events (M(Pat) = 0.87 vs. M(HC) = 0.93, F(41,1) = 11.78, p < 0.001) implying impairments of both cognitive flexibility and stability in patients. Motor symptoms (NSS) and cognitive deficits (BACS) in patients were exclusively related to cognitive flexibility, but not stability. Brain correlates of reduced flexibility in patients were found in a fronto-striato-thalamo network. More specifically, reduced striatal activation in patients was related to weaker event discrimination and reduced detection of unexpected relevant events. Additionally, exploratory follow-up analyses revealed reduced fronto-striato-temporal activation in patients associated with weaker distractor resistance during the stability task. Note, chlorpromazine equivalents as an indicator of antipsychotic dosage as well as positive and negative symptoms were unrelated to measures of cognitive flexibility and stability. Discussion Together, our findings provide evidence for distinctive neurobiological alterations underlying reduced cognitive flexibility and stability in schizophrenia with reduced flexibility being associated with general cognitive and motor impairments. Our main imaging results show reduced activation in a fronto-striato-thalamo network in response to relevant prediction errors in patients, while impaired cognitive stability may be rather related to alterations in a fronto-striato-temporal network. Reduced caudate activation during behavioral relevant events, which was associated with weaker event discrimination and detection of relevant prediction errors in patients, supports a model of striatal gating being essentially impaired in patients.

scholarly journals Variations in glenohumeral movement control when implementing an auditory feedback system: A pilot study

2019 ◽  
Vol 67 (4) ◽  
pp. 477-483
Author(s):  
Mauricio Barramuño ◽  
Pablo Valdés-Badilla ◽  
Exequiel Guevara
Keyword(s):  
Young Adults ◽  
Motor Control ◽  
Auditory Feedback ◽  
Movement Control ◽  
Feedback System ◽  
Post Exposure ◽  
System A ◽  
Randomized Intervention ◽  
Execution Speed ◽  
Human Motor

Introduction: Human motor control requires a learning process and it can be trained by means of various sensory feedback sources.Objective: To determine variations in glenohumeral movement control by learning in young adults exposed to an auditory feedback system while they perform object translation tasks classified by difficulty level.Materials and methods: The study involved 45 volunteers of both sexes (22 women), aged between 18 and 32 years. Glenohumeral movement control was measured by means of the root mean square (RMS) of the accelerometry signal, while task execution speed (TES) was measured using an accelerometer during the execution of the task according to its difficulty (easy, moderate and hard) in four stages of randomized intervention (control, pre-exposure, exposure-with auditory feedback, and post-exposure).Results: Statistically significant differences (p<0.001) were found between the pre-exposure and exposure stages and between pre-exposure and post-exposure stages. A significant increase (p <0.001) in TES was identified between the pre-exposure and exposure stages for tasks classified as easy and hard, respectively.Conclusion: The use of an auditory feedback system in young adults without pathologies enhanced learning and glenohumeral movement control without reducing TES. This effect was maintained after the feedback, so the use of this type of feedback system in healthy individuals could result in a useful strategy for the training of motor control of the shoulder.

Shared Cortical Anatomy for Motor Awareness and Motor Control

Science ◽  
2005 ◽  
Vol 309 (5733) ◽  
pp. 488-491 ◽  
Author(s):  
A. Berti
Keyword(s):  
Motor Control ◽  
Motor Awareness

scholarly journals Hemispheric Specialization for Movement Control Produces Dissociable Differences in Online Corrections after Stroke

2011 ◽  
Vol 22 (6) ◽  
pp. 1407-1419 ◽  
Author(s):  
S. Y. Schaefer ◽  
P. K. Mutha ◽  
K. Y. Haaland ◽  
R. L. Sainburg
Keyword(s):  
Hemispheric Specialization ◽  
Movement Control ◽  
Online Corrections

Active inference and cognitive-emotional interactions in the brain

2015 ◽  
Vol 38 ◽  
Author(s):  
Giovanni Pezzulo ◽  
Laura Barca ◽  
Karl J. Friston
Keyword(s):  
Prediction Errors ◽  
Active Inference ◽  
Bayesian Fusion ◽  
The Brain

AbstractAll organisms must integrate cognition, emotion, and motivation to guide action toward valuable (goal) states, as described by active inference. Within this framework, cognition, emotion, and motivation interact through the (Bayesian) fusion of exteroceptive, proprioceptive, and interoceptive signals, the precision-weighting of prediction errors, and the “affective tuning” of neuronal representations. Crucially, misregulation of these processes may have profound psychopathological consequences.

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