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An informal reconstruction of the free-energy framework, examining the conceptual problems that arise. Neuropsychologia 2022; 173:108281. [PMID: 35662551 DOI: 10.1016/j.neuropsychologia.2022.108281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 05/19/2022] [Accepted: 05/26/2022] [Indexed: 11/22/2022]
Abstract
Recent decades have seen increasing attention given to the free-energy framework. This proposes that many of the phenomena we associate with life, intelligence and adaptation can be explained in terms of a single, mathematical precept: the free-energy principle. This is claimed to apply to the adaptive behavior of primitive organisms as much as it does to the physiological structures of human brains. The proposal is potentially of interest to theorists from multiple disciplines. But as presentations often make intensive use of mathematical notation, it can be hard to understand, even for experts. The present article presents an informal reconstruction, using schematic illustrations. Mathematical notation is largely avoided, while detail and precision are retained as far as possible. The specifically conceptual problems that come to notice in the reconstruction are highlighted and discussed.
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Santos-Pata D, Amil AF, Raikov IG, Rennó-Costa C, Mura A, Soltesz I, Verschure PFMJ. Epistemic Autonomy: Self-supervised Learning in the Mammalian Hippocampus. Trends Cogn Sci 2021; 25:582-595. [PMID: 33906817 PMCID: PMC10631471 DOI: 10.1016/j.tics.2021.03.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 03/23/2021] [Accepted: 03/26/2021] [Indexed: 01/05/2023]
Abstract
Biological cognition is based on the ability to autonomously acquire knowledge, or epistemic autonomy. Such self-supervision is largely absent in artificial neural networks (ANN) because they depend on externally set learning criteria. Yet training ANN using error backpropagation has created the current revolution in artificial intelligence, raising the question of whether the epistemic autonomy displayed in biological cognition can be achieved with error backpropagation-based learning. We present evidence suggesting that the entorhinal-hippocampal complex combines epistemic autonomy with error backpropagation. Specifically, we propose that the hippocampus minimizes the error between its input and output signals through a modulatory counter-current inhibitory network. We further discuss the computational emulation of this principle and analyze it in the context of autonomous cognitive systems.
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Affiliation(s)
- Diogo Santos-Pata
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain
| | - Adrián F Amil
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | | | - César Rennó-Costa
- Digital Metropolis Institute, Federal University of Rio Grande do Norte, Natal, Rio Grande do Norte, Brazil
| | - Anna Mura
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain
| | - Ivan Soltesz
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Paul F M J Verschure
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Institute for Bioengineering of Catalonia (IBEC), Barcelona, Spain; Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain.
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Maffei G, Herreros I, Sanchez-Fibla M, Friston KJ, Verschure PFMJ. The perceptual shaping of anticipatory actions. Proc Biol Sci 2017; 284:20171780. [PMID: 29263282 PMCID: PMC5745402 DOI: 10.1098/rspb.2017.1780] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2017] [Accepted: 11/22/2017] [Indexed: 02/06/2023] Open
Abstract
Humans display anticipatory motor responses to minimize the adverse effects of predictable perturbations. A widely accepted explanation for this behaviour relies on the notion of an inverse model that, learning from motor errors, anticipates corrective responses. Here, we propose and validate the alternative hypothesis that anticipatory control can be realized through a cascade of purely sensory predictions that drive the motor system, reflecting the causal sequence of the perceptual events preceding the error. We compare both hypotheses in a simulated anticipatory postural adjustment task. We observe that adaptation in the sensory domain, but not in the motor one, supports the robust and generalizable anticipatory control characteristic of biological systems. Our proposal unites the neurobiology of the cerebellum with the theory of active inference and provides a concrete implementation of its core tenets with great relevance both to our understanding of biological control systems and, possibly, to their emulation in complex artefacts.
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Affiliation(s)
- Giovanni Maffei
- Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Ivan Herreros
- Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Imaging Neuroscience and Theoretical Neurobiology, Wellcome Trust Centre for Neuroimaging, University College of London (UCL), London, UK
| | - Marti Sanchez-Fibla
- Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Karl J Friston
- Imaging Neuroscience and Theoretical Neurobiology, Wellcome Trust Centre for Neuroimaging, University College of London (UCL), London, UK
| | - Paul F M J Verschure
- Institute for Bioengineering of Catalonia (IBEC), Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
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Verschure PFMJ. Synthetic consciousness: the distributed adaptive control perspective. Philos Trans R Soc Lond B Biol Sci 2016; 371:20150448. [PMID: 27431526 PMCID: PMC4958942 DOI: 10.1098/rstb.2015.0448] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/18/2016] [Indexed: 02/06/2023] Open
Abstract
Understanding the nature of consciousness is one of the grand outstanding scientific challenges. The fundamental methodological problem is how phenomenal first person experience can be accounted for in a third person verifiable form, while the conceptual challenge is to both define its function and physical realization. The distributed adaptive control theory of consciousness (DACtoc) proposes answers to these three challenges. The methodological challenge is answered relative to the hard problem and DACtoc proposes that it can be addressed using a convergent synthetic methodology using the analysis of synthetic biologically grounded agents, or quale parsing. DACtoc hypothesizes that consciousness in both its primary and secondary forms serves the ability to deal with the hidden states of the world and emerged during the Cambrian period, affording stable multi-agent environments to emerge. The process of consciousness is an autonomous virtualization memory, which serializes and unifies the parallel and subconscious simulations of the hidden states of the world that are largely due to other agents and the self with the objective to extract norms. These norms are in turn projected as value onto the parallel simulation and control systems that are driving action. This functional hypothesis is mapped onto the brainstem, midbrain and the thalamo-cortical and cortico-cortical systems and analysed with respect to our understanding of deficits of consciousness. Subsequently, some of the implications and predictions of DACtoc are outlined, in particular, the prediction that normative bootstrapping of conscious agents is predicated on an intentionality prior. In the view advanced here, human consciousness constitutes the ultimate evolutionary transition by allowing agents to become autonomous with respect to their evolutionary priors leading to a post-biological Anthropocene.This article is part of the themed issue 'The major synthetic evolutionary transitions'.
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Affiliation(s)
- Paul F M J Verschure
- Laboratory of Synthetic Perceptive, Emotive and Cognitive Systems, Center of Autonomous Systems and Neurorobotics, Universitat Pompeu Fabra, Barcelona, Spain ICREA-Institució Catalana de Recerca i Estudis Avançats, 08018 Barcelona, Spain
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Maffei G, Santos-Pata D, Marcos E, Sánchez-Fibla M, Verschure PFMJ. An embodied biologically constrained model of foraging: from classical and operant conditioning to adaptive real-world behavior in DAC-X. Neural Netw 2015; 72:88-108. [PMID: 26585942 DOI: 10.1016/j.neunet.2015.10.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2015] [Revised: 10/08/2015] [Accepted: 10/08/2015] [Indexed: 01/08/2023]
Abstract
Animals successfully forage within new environments by learning, simulating and adapting to their surroundings. The functions behind such goal-oriented behavior can be decomposed into 5 top-level objectives: 'how', 'why', 'what', 'where', 'when' (H4W). The paradigms of classical and operant conditioning describe some of the behavioral aspects found in foraging. However, it remains unclear how the organization of their underlying neural principles account for these complex behaviors. We address this problem from the perspective of the Distributed Adaptive Control theory of mind and brain (DAC) that interprets these two paradigms as expressing properties of core functional subsystems of a layered architecture. In particular, we propose DAC-X, a novel cognitive architecture that unifies the theoretical principles of DAC with biologically constrained computational models of several areas of the mammalian brain. DAC-X supports complex foraging strategies through the progressive acquisition, retention and expression of task-dependent information and associated shaping of action, from exploration to goal-oriented deliberation. We benchmark DAC-X using a robot-based hoarding task including the main perceptual and cognitive aspects of animal foraging. We show that efficient goal-oriented behavior results from the interaction of parallel learning mechanisms accounting for motor adaptation, spatial encoding and decision-making. Together, our results suggest that the H4W problem can be solved by DAC-X building on the insights from the study of classical and operant conditioning. Finally, we discuss the advantages and limitations of the proposed biologically constrained and embodied approach towards the study of cognition and the relation of DAC-X to other cognitive architectures.
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Affiliation(s)
- Giovanni Maffei
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Center of Autonomous Systems and Neurorobotics, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Diogo Santos-Pata
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Center of Autonomous Systems and Neurorobotics, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Encarni Marcos
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Center of Autonomous Systems and Neurorobotics, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Marti Sánchez-Fibla
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Center of Autonomous Systems and Neurorobotics, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Paul F M J Verschure
- Laboratory of Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS), Center of Autonomous Systems and Neurorobotics, Universitat Pompeu Fabra (UPF), Barcelona, Spain; Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
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