Goal-free sensory encoding and learning DOI Open Access
Sophie Smit, Genevieve L. Quek, Manuel Varlet

et al.

Published: June 4, 2024

Investigating how goals impact the way we explore, represent, and interact with world is vital for understanding human cognition. In their insightful review, Molinaro & Collins (2023) redefine conventional role of in computational theories learning decision-making, arguing that reinforcement frameworks, traditionally ‘fixed’ elements (e.g., states, actions, rewards) are fact intricately linked to influenced by an agent’s current goals. support claim dynamic actively shape information processing altering state, they draw on fMRI work showing neural representations prefrontal cortex vary systematically when participants imagine using same object achieve different (Castegnetti et al., 2021). These other findings suggest do not only influence high-level cognitive processes, but can also modulate encoding sensory information, including early areas (Schaffner 2023). Here provide nuance this perspective highlighting obligatory largely automatic nature processing, wherein evoked responses complex stimuli faces, objects) encode visual input a manner independent goal state. This caveat arises out time-resolved decoding literature suggests while observer’s task undoubtedly guides attention its stages comparatively subtle.

Language: Английский

Curiosity and the dynamics of optimal exploration DOI Creative Commons
Francesco Poli, Jill X. O’Reilly, Rogier B. Mars

et al.

Trends in Cognitive Sciences, Journal Year: 2024, Volume and Issue: 28(5), P. 441 - 453

Published: Feb. 26, 2024

What drives our curiosity remains an elusive and hotly debated issue, with multiple hypotheses proposed but a cohesive account yet to be established. This review discusses traditional emergent theories that frame as desire know drive learn, respectively. We adopt model-based approach maps the temporal dynamics of various factors underlying curiosity-based exploration, such uncertainty, information gain, learning progress. In so doing, we identify limitations past posit integrated harnesses their strengths in describing tool for optimal environmental exploration. unified account, serves 'common currency' which must balanced other safety hunger achieve efficient action.

Language: Английский

Citations

22

Goal commitment is supported by vmPFC through selective attention DOI Creative Commons
Eleanor Holton, Jan Grohn, Harry Ward

et al.

Nature Human Behaviour, Journal Year: 2024, Volume and Issue: unknown

Published: April 17, 2024

When striking a balance between commitment to goal and flexibility in the face of better options, people often demonstrate strong perseveration. Here, using functional MRI (n = 30) lesion patient 26) studies, we argue that ventromedial prefrontal cortex (vmPFC) drives linked changes goal-directed selective attention. Participants performed an incremental pursuit task involving sequential decisions persisting with versus abandoning progress for alternative options. Individuals stronger perseveration showed higher attention interleaved task. Increasing also affected abandonment decisions: while pursuing goal, lost their sensitivity valuable goals remaining more sensitive current goal. In healthy population, individual differences both biases goal-oriented were predicted by baseline goal-related activity vmPFC. Among patients, vmPFC damage reduced commitment, leading performance benefit.

Language: Английский

Citations

9

Fundamental processes in sensorimotor learning: Reasoning, refinement, and retrieval DOI Creative Commons
Jonathan S. Tsay, Hyosub E. Kim, Samuel D. McDougle

et al.

eLife, Journal Year: 2024, Volume and Issue: 13

Published: Aug. 1, 2024

Motor learning is often viewed as a unitary process that operates outside of conscious awareness. This perspective has led to the development sophisticated models designed elucidate mechanisms implicit sensorimotor learning. In this review, we argue for broader perspective, emphasizing contribution explicit strategies tasks. Furthermore, propose theoretical framework motor consists three fundamental processes: reasoning, understanding action–outcome relationships; refinement, optimizing and cognitive parameters achieve goals; retrieval, inferring context recalling control policy. We anticipate ‘3R’ how complex movements are learned will open exciting avenues future research at intersection between cognition action.

Language: Английский

Citations

9

Fundamental processes in sensorimotor learning: Reasoning, Refinement, and Retrieval DOI Open Access
Jonathan S. Tsay, Hyosub E. Kim, Samuel D. McDougle

et al.

Published: Aug. 2, 2023

[Now published in eLife: https://elifesciences.org/articles/91839] Motor learning is often viewed as a unitary process that operates outside of conscious awareness. This perspective has led to the development sophisticated models designed elucidate mechanisms implicit sensorimotor learning. In this review we argue for broader perspective, emphasizing contribution explicit strategies tasks. Furthermore, propose theoretical framework motor consists three fundamental processes: Reasoning, understanding action-outcome relationships; Refinement, optimizing and cognitive parameters achieve goals; Retrieval, inferring context recalling control policy. We anticipate “3R” how complex movements are learned will open exciting avenues future research at intersection between cognition action.

Language: Английский

Citations

15

The affective gradient hypothesis: an affect-centered account of motivated behavior DOI
Amitai Shenhav

Trends in Cognitive Sciences, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 1, 2024

Language: Английский

Citations

6

From tripping and falling to ruminating and worrying: a meta-control account of repetitive negative thinking DOI Creative Commons

Peter F Hitchcock,

Michael J. Frank

Current Opinion in Behavioral Sciences, Journal Year: 2024, Volume and Issue: 56, P. 101356 - 101356

Published: Feb. 16, 2024

Language: Английский

Citations

4

Neurocomputational model of compulsivity: deviating from an uncertain goal-directed system DOI Creative Commons
Taekwan Kim, Sang Wan Lee, Silvia Kyungjin Lho

et al.

Brain, Journal Year: 2024, Volume and Issue: 147(6), P. 2230 - 2244

Published: April 8, 2024

Despite a theory that an imbalance in goal-directed versus habitual systems serve as building blocks of compulsions, research has yet to delineate how this occurs during arbitration between the two obsessive-compulsive disorder. Inspired by brain model which inferior frontal cortex selectively gates putamen guide or actions, study aimed examine whether disruptions process via fronto-striatal circuit would underlie imbalanced decision-making and compulsions patients. Thirty patients with disorder [mean (standard deviation) age = 26.93 (6.23) years, 12 females (40%)] 30 healthy controls 24.97 (4.72) 17 (57%)] underwent functional MRI scans while performing two-step Markov decision task, was designed dissociate behaviour from behaviour. We employed neurocomputational account for uncertainty-based process, prefrontal arbitrator (i.e. gyrus) allocates behavioural control more reliable strategy gating putamen. analysed group differences neural estimates uncertainty each strategy. also compared psychophysiological interaction effects system preference (goal-directed habitual) on coupling groups. examined correlation compulsivity score activity connectivity involved process. The computational captured subjects' preferences strategies. Compared controls, had stronger (t -2.88, P 0.006), attributed uncertain 2.72, 0.009). Before allocation exhibited hypoactivity gyrus when region tracked inverse reliability) (P 0.001, family-wise error rate corrected). When reorienting behaviours reach specific goals, weaker right ipsilateral ventrolateral prefronto-putamen than This hypoconnectivity correlated severe (r -0.57, 0.002). Our findings suggest attenuated top-down underlies Enhancing may be potential neurotherapeutic approach adaptive decision-making.

Language: Английский

Citations

4

Motivational context determines the impact of aversive outcomes on mental effort allocation DOI
Mahalia Prater Fahey, Debbie Yee, Xiamin Leng

et al.

Cognition, Journal Year: 2024, Volume and Issue: 254, P. 105973 - 105973

Published: Oct. 15, 2024

Language: Английский

Citations

4

Beyond Preferences in AI Alignment DOI Creative Commons
Tan Zhi‐Xuan, Micah Carroll, Matija Franklin

et al.

Philosophical Studies, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 9, 2024

Abstract The dominant practice of AI alignment assumes (1) that preferences are an adequate representation human values, (2) rationality can be understood in terms maximizing the satisfaction preferences, and (3) systems should aligned with one or more humans to ensure they behave safely accordance our values. Whether implicitly followed explicitly endorsed, these commitments constitute what we term a preferentist approach alignment. In this paper, characterize challenge approach, describing conceptual technical alternatives ripe for further research. We first survey limits rational choice theory as descriptive model, explaining how fail capture thick semantic content utility representations neglect possible incommensurability those then critique normativity expected (EUT) AI, drawing upon arguments showing agents need not comply EUT, while highlighting EUT is silent on which normatively acceptable. Finally, argue limitations motivate reframing targets alignment: Instead user, developer, humanity-writ-large, normative standards appropriate their social roles, such role general-purpose assistant. Furthermore, negotiated agreed by all relevant stakeholders. On alternative conception alignment, multiplicity will able serve diverse ends, promote mutual benefit limit harm despite plural divergent

Language: Английский

Citations

3

Goals as reward-producing programs DOI
Guy Davidson, Graham Todd,

Julian Togelius

et al.

Nature Machine Intelligence, Journal Year: 2025, Volume and Issue: 7(2), P. 205 - 220

Published: Feb. 21, 2025

Language: Английский

Citations

0