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Neurons as autonomous agents: A biologically inspired framework for cognitive architectures in artificial intelligence

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COGNITIVE SYSTEMS RESEARCH 2025年 90卷

作者： Luczak, Artur Univ Lethbridge Canadian Ctr Behav Neurosci Lethbridge AB Canada

Despite impressive recent advances in artificial intelligence (AI), current deep neural networks still lack the adaptability and energy efficiency inherent to biological systems. Here we suggest that this problem may be overcome by taking inspiration from the brain where neurons operate as autonomous agents, each capable of adjusting its synaptic connections and internal states based on local information. Currently, typical artificial neurons are static nodes, which is in striking contrast to the rich, dynamic computations performed by biological neurons. In this review, we propose redesigning artificial neurons as self-regulating, agent-like units, making actions to maximize future energy/reward. Similarly, as single-celled organisms which can autonomously navigate in complex environments in search for food, neurons can also be viewed as autonomous decisionmakers, seeking to maximize their own energy resources. Thus, neurons could be operating similarly like reinforcement learning (RL) agents, which make actions to obtain maximum future reward. Here first we review literature illustrating that biological neurons perform complex computations and employ local, predictive learning rules to anticipate future activity to maximize metabolic energy. Next, we provide examples of recent biologically inspired learning algorithms where artificial neurons are empowered with computational flexibility, similarly to autonomous agents. Networks with neurons using such local learning rules can in some examples outperform current AI algorithms. We also discuss how this can improve scalability of current multi-agent systems (MAS) and energy efficiency. Therefore, designing neurons as autonomous agents may provide an important step toward building human-like cognition.

关键词： Biologically inspired AI predictive coding Local learning rules Neuromorphic computing Single-cell intelligence Neuronal plasticity

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Somatosensory false feedback biases emotional ratings through interoceptive embodiment

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SCIENTIFIC REPORTS 2025年第1期15卷 1-17页

作者： Patchitt, Joel Garfinkel, Sarah Strawson, William H. Miller, Mark Tsakiris, Manos Clark, Andy Critchley, Hugo D. Univ Sussex Sussex Ctr Consciousness Sci Brighton BN1 9QJ England Univ Sussex Brighton & Sussex Med Sch Dept Clin Neurosci Brighton BN1 9RY England UCL Inst Cognit Neurosci London WC1N 3AZ England Monash Univ Monash Ctr Consciousness & Contemplat Studies Melbourne Vic 3168 Australia Univ Toronto Psychol Dept Toronto ON M5S 2E5 Canada Royal Holloway Univ London Dept Psychol Egham TW20 0EX England Univ Sussex Sch Media Arts & Humanities Brighton BN1 9RG England Univ Sussex Sch Engn & Informat Brighton BN1 9QG England

Mismatches between perceived and veridical physiological signals during false feedback (FFB) can bias emotional judgements. Paradigms using auditory FFB suggest perceived changes in heart rate (HR) increase ratings of emotional intensity irrespective of feedback type (increased or decreased HR), implicating right anterior insula as a mismatch comparator between exteroceptive and interoceptive information. However, few paradigms have examined effects of somatosensory FFB. Participants rated the emotional intensity of randomized facial expressions while they received 20 s blocks of pulsatile somatosensory stimulation at rates higher than HR, lower than HR, equivalent to HR, or no stimulation during a functional magnetic resonance neuroimaging scan. FFB exerted a bidirectional effect on reported intensity ratings of the emotional faces, increasing over the course of each 20 s stimulation block. Neuroimaging showed FFB engaging regions indicative of affective touch processing, embodiment, and reflex suppression. Contrasting higher vs. lower HR FFB revealed engagement of right insula and centres supporting socio-emotional processing. Results indicate that exposure to pulsatile somatosensory stimulation can influence emotional judgements though its progressive embodiment as a perceived interoceptive arousal state, biasing how affective salience is ascribed to external stimuli. Results are consistent with multimodal integration of priors and prediction-error signalling in shaping perceptual judgments.

关键词： Interoception False physiological feedback Insula Emotion recognition Perception predictive coding

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Large-scale interactions in predictive processing: oscillatory versus transient dynamics

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TRENDS IN COGNITIVE SCIENCES 2025年第2期29卷 133-148页

作者： Vinck, Martin Uran, Cem Dowdall, Jarrod R. Rummell, Brian Canales-Johnson, Andres Max Planck Gesell Ernst Strungmann Inst ESI Neurosci D-60528 Frankfurt Germany Radboud Univ Nijmegen Donders Ctr Neurosci Dept Neurophys NL-6525 Nijmegen Netherlands Western Univ Robarts Res Inst London ON Canada Univ Catolica Maule Fac Ciencias Salud Talca 3480122 Chile Univ Cambridge Dept Psychol Cambridge CB2 3EB England

How do the two main types of neural dynamics, aperiodic transients and oscillations, contribute to the interactions between feedforward (FF) and feedback (FB) pathways in sensory inference and predictive processing? We discuss three theoretical perspectives. First, we critically evaluate the theory that gamma and alpha/beta rhythms play a role in classic hierarchical predictive coding (HPC) by mediating FF and FB communication, respectively. Second, we outline an alternative functional model in which rapid sensory inference is mediated by aperiodic transients, whereas oscillations contribute to the stabilization of neural representations over time and plasticity processes. Third, we propose that the strong dependence of oscillations on predictability can be explained based on a biologically plausible alternative to classic HPC, namely dendritic HPC.

关键词： predictive processing predictive coding classical hierarchical predictive coding dendritic hierarchical predictive coding rhythms oscillations synchronization dynamics gamma alpha beta feedforward feedback hierarchy efficient coding plasticity

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Top-down prediction signals from the medial prefrontal cortex govern auditory cortex prediction errors

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CELL REPORTS 2025年第4期44卷 115538页

作者： Hockley, Adam Bohorquez, Laura H. Malmierca, Manuel S. Inst Neurosci Castilla & Leon INCYL Cognit & Auditory Neurosci Lab Salamanca Spain Salamanca Inst Biomed Res IBSAL Salamanca Spain Univ Salamanca Fac Med Dept Cell Biol & Pathol Salamanca Spain

Under the predictive coding framework, the brain generates a model of the environment based on previous experiences. Incoming sensory information is compared to this model, such that if predictions do not match sensory inputs, a prediction error is generated. Predictions are passed top-down, and prediction errors emerge when bottom-up information does not match the predictions. Prediction errors occur sequentially in the primary auditory cortex (A1) and then the medial prefrontal cortex (mPFC). Here, we test the hypothesis that the mPFC sends predictions that contribute to the generation of prediction errors. We used optogenetics to block top-down signals from the mPFC while recording neuronal prediction errors in the A1 under the classical "oddball"paradigm. Blocking top-down signals reduces prediction errors in the A1 in response to rare sounds, while it does not affect responses to predictable or random sounds. Our results provide empirical evidence for top-down prediction signals from the mPFC that enhance A1 responses to unpredicted stimuli.

关键词： predictive coding top-down processing auditory cortex prefrontal cortex optogenetic silencing neural synchrony cingulate cortex prediction errors

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Theory of morphodynamic information processing: Linking sensing to behaviour

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VISION RESEARCH 2025年 227卷 108537页

作者： Juusola, Mikko Takalo, Jouni Kemppainen, Joni Haghighi, Keivan Razban Scales, Ben Mcmanus, James Bridges, Alice Maboudi, Hadi Chittka, Lars Univ Sheffield Sch Biosci Sheffield S10 2TN England Queen Mary Univ London Ctr Brain & Behav Sch Biol & Behav Sci London E1 4NS England

The traditional understanding of brain function has predominantly focused on chemical and electrical processes. However, new research in fruit fly ( Drosophila ) binocular vision reveals ultrafast photomechanical photoreceptor movements significantly enhance information processing, thereby impacting a fly's perception of its environment and behaviour. The coding advantages resulting from these mechanical processes suggest that similar physical motion-based coding strategies may affect neural communication ubiquitously. The theory of neural morphodynamics proposes that rapid biomechanical movements and microstructural changes at the level of neurons and synapses enhance the speed and efficiency of sensory information processing, intrinsic thoughts, and actions by regulating neural information in a phasic manner. We propose that morphodynamic information processing evolved to drive predictive coding, synchronising cognitive processes across neural networks to match the behavioural demands at hand effectively.

关键词： Vision Information theory Stochastic sampling Synaptic transmission Cognition predictive coding Neural synchronisation

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Operationalisation of interoceptive expectations: A novel paradigm to measure detection and Adjustment to Interoceptive Discrepancy

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BIOLOGICAL PSYCHOLOGY 2025年 195卷 109001页

作者： Adamic, Emily Croy, Ilona Geisler, Maria Laureate Inst Brain Res Tulsa OK USA Univ Tulsa Oxley Coll Hlth & Nat Sci Tulsa OK USA Friedrich Schiller Univ Inst Psychol Jena Thuringia Germany German Ctr Mental Hlth Jena Germany Tech Univ Dresden Med Fac Dept Psychotherapy & Psychosomat Med Dresden Germany Univ Hosp Jena Dept Psychosomat Med & Psychotherapy Jena Germany

Interoception is a bidirectional process, with both descending predictions and ascending sensation playing a role in the regulation and perception of homeostatic states. Mistuning of both streams has been associated with psychopathology in mental disorders, including hyperprecise prior beliefs and altered sensory representations. However, empirical research has typically focused on associations between self-report scales and objective physiology during rest or bodily perturbations, without manipulating or measuring descending. Therefore, we developed the novel Adjustment to Interoceptive Discrepancy (AID) paradigm, that builds and then violates interoceptive beliefs to measure expectations and adjustment of expectations over subsequent trials following an unexpected stimulus. We validated this paradigm in the nociceptive domain in a total of 57 university-aged participants. The AID paradigm successfully induced interoceptive discrepancy (i.e., a difference between expectation and perception ratings) that was resolved as participants adjusted expectations appropriately across subsequent trials. This adjustment was more rapid for stimuli that were perceived as more versus less intense than expected. Notably, there were individual differences in the pattern of this adjustment, revealing different strategies in how individuals adjust to unexpected interoceptive sensations, although these were unrelated to interoceptive sensibility scores. Overall, the AID paradigm provides a useful method to assess interoception across expected versus unexpected stimuli, to probe interindividual differences of interoceptive predictions, and ultimately to enable research on the bidirectional processing of internal stimuli in mental health.

关键词： Interoception Interoceptive awareness predictive coding Hyperprecise priors Prediction error

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Expertise advantage of automatic prediction in visual motion representation is domain-general: A meta-analysis

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PSYCHOLOGY OF SPORT AND EXERCISE 2025年 76卷 102776页

作者： Song, Tao Ye, Mingzhu Teng, Gesi Zhang, Weikun Chen, Antao Shanghai Univ Sport Res Ctr Exercise & Brain Sci Sch Psychol Shanghai Peoples R China

The expertise advantage denotes the superior perceptual-cognitive skills exhibited by experts. Nevertheless, the extent to which the expertise advantage influences automatic prediction in visual motion representation remains unclear. This meta-analysis aims to consolidate findings from various studies on the expertise advantage of automatic prediction in visual motion representation. We identified empirical research literature that measured expertise advantage of automatic prediction from the Web of Science (Core Collection), APA PsycInfo, PubMed, and Cochrane Library databases. We identified 16 studies contributing 23 effect sizes from a pool of 1110 records. The standardized mean difference (Hedges' g) was computed for the expertise advantage. The meta- analysis results reveal that, in comparison to novices, experts demonstrate superior automatic prediction in visual motion representation (Hedges' g = 0.73, 95% CI [0.54, 0.92]). Moderator analyses suggest that, when measuring the expertise advantage of automatic prediction, the effect size of the recall task is significantly larger than that of the recognition task. Other moderating variables did not exhibit significant moderating effects. These results suggest that the expertise advantage extends to automatic prediction in visual motion representation, and that this advantage is general, stable, and widespread.

关键词： Expertise advantage predictive coding Representational momentum Pattern recall Cognitive penetrability

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Do autistic individuals show atypical performance in probabilistic learning? A comparison of cue-number, predictive strength, and prediction error

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MOLECULAR AUTISM 2025年第1期16卷 1-12页

作者： Ong, Jia Hoong Zhang, Lei Liu, Fang Nottingham Trent Univ Sch Social Sci Dept Psychol Nottingham England Univ Birmingham Ctr Human Brain Hlth Sch Psychol Birmingham England Univ Birmingham Inst Mental Hlth Sch Psychol Birmingham England Univ Birmingham Ctr Dev Sci Sch Psychol Birmingham England Univ Reading Sch Psychol & Clin Language Sci Reading England

BackgroundAccording to recent models of autism, autistic individuals may find learning probabilistic cue-outcome associations more challenging than deterministic learning, though empirical evidence for this is mixed. Here we examined the mechanism of probabilistic learning more closely by comparing autistic and non-autistic adults on inferring a target cue from multiple cues or integrating multiple target cues and learning from associations with various predictive ***52 autistic and 52 non-autistic participants completed three tasks: (i) single-cue probabilistic learning, in which they had to infer a single target cue from multiple cues to learn cue-outcome associations;(ii) multi-cue probabilistic learning, in which they had to learn associations of various predictive strengths via integration of multiple cues;and (iii) reinforcement learning, which required learning the contingencies of two stimuli with a probabilistic reinforcement schedule. Accuracy on the two probabilistic learning tasks was modelled separately using a binomial mixed effects model whereas computational modelling was performed on the reinforcement learning data to obtain a model parameter on prediction error integration (i.e., learning rate).ResultsNo group differences were found in the single-cue probabilistic learning task. Group differences were evident for the multi-cue probabilistic learning task for associations that are weakly predictive (between 40 and 60%) but not when they are strongly predictive (10-20% or 80-90%). Computational modelling on the reinforcement learning task revealed that, as a group, autistic individuals had a higher learning rate than non-autistic *** to the online nature of the study, we could not confirm the diagnosis of our autistic sample. The autistic participants were likely to have typical intelligence, and so our findings may not be generalisable to the entire autistic population. The learning tasks are constrained by a rel

关键词： Probabilistic learning Associative learning Prediction errors Bayesian predictive coding Reinforcement learning

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Bayesian brain theory: Computational neuroscience of belief

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NEUROSCIENCE 2025年 566卷 198-204页

作者： Bottemanne, Hugo Univ Paris Saclay Fac Med Paris Saclay CESP Ctr Rech Epidemiol & Sante Populat MOODS TeamINSERM 1018 Le Kremlin Bicetre France Paris Saclay Univ Bicetre Hosp Assistance Publ Hop Paris AP HP Mood Ctr Paris SaclayDept PsychiatDMU Neurosci Le Kremlin Bicetre France Inst Natl Sante & Rech Med INSERM U1127 Paris Brain Inst Inst Cerveau Paris France

Bayesian brain theory, a computational framework grounded in the principles of predictive Processing (PP), proposes a mechanistic account of how beliefs are formed and updated. This theory assumes that the brain encodes a generative model of its environment, made up of probabilistic beliefs organized in networks, from which it generates predictions about future sensory inputs. The difference between predictions and sensory signals produces prediction errors, which are used to update belief networks. In this article, we introduce the fundamental principles of Bayesian brain theory, and show how the brain dynamics of prediction are associated with the generation and evolution of beliefs.

关键词： Belief Computational neuroscience predictive processing predictive coding Bayesian brain

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What Do Mismatch Negativity (MMN) Responses Tell Us About Tinnitus?

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JARO-JOURNAL OF THE ASSOCIATION FOR RESEARCH IN OTOLARYNGOLOGY 2025年第1期26卷 33-47页

作者： Yukhnovich, Ekaterina A. Alter, Kai Sedley, William Newcastle Univ Biosci Inst Med Sch Newcastle Upon Tyne NE2 4HH England Univ Cambridge Fac Modern & Medieval Languages Cambridge England Univ Cambridge Languages Sci Interdisciplinary Res Ctr Cambridge England

Due to the heterogeneous causes, symptoms and associated comorbidities with tinnitus, there remains an unmet need for a clear biomarker of tinnitus presence. Previous research has suggested a "final pathway" of tinnitus presence, which occurs regardless of the specific mechanisms that resulted in alterations of auditory predictions and, eventually, tinnitus perception. predictive inference mechanisms have been proposed as the possible basis for this final unifying pathway. A commonly used measure of prediction violation is mismatch negativity (MMN), an electrical potential generated in response to most stimuli that violate an established regularity. This narrative review discusses 16 studies comparing MMN between tinnitus and non-tinnitus groups. Methods varied considerably, including type of deviant, type of paradigm and carrier frequency. A minority of studies matched groups for age, sex and hearing, with few measuring hyperacusis. Frequency deviants were the most widely studied;at frequencies remote from tinnitus, MMN was consistently smaller in tinnitus groups, though hyperacusis or altered distress or attention could not be ruled out as explanatory factors. Few studies have used tinnitus-related frequencies;these showed larger MMN to upward frequency deviants above the tinnitus frequency, and larger MMN to upward intensity deviants at or close to the tinnitus frequency. However, the latter appears a correlate of hyperacusis rather than tinnitus, and tinnitus groups without hyperacusis instead show larger MMN to downward intensity deviants than controls. Other factors that affect MMN amplitudes included age, attention, and the specific characteristics of the range of stimuli across a particular experiment paradigm. As such, MMN cannot presently be considered a specific biomarker of tinnitus, but showed potential to objectively characterise a number of auditory processing traits relevant to tinnitus and hyperacusis.

关键词： Tinnitus Mismatch negativity predictive coding Biomarker MMN Review Tinnitus mechanisms

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