scholarly journals The Energy Homeostasis Principle: A Naturalistic Approach to Explain the Emergence of Behavior

2022 ◽  
Vol 15 ◽  
Author(s):  
Sergio Vicencio-Jimenez ◽  
Mario Villalobos ◽  
Pedro E. Maldonado ◽  
Rodrigo C. Vergara
Keyword(s):  
Energy Homeostasis ◽  
Mental States ◽  
Energy Principle ◽  
Current Form ◽  
Information Theoretic ◽  
Deterministic Systems ◽  
Alternative Approach ◽  
Learning Scenarios ◽  
Goal Oriented Behavior

It is still elusive to explain the emergence of behavior and understanding based on its neural mechanisms. One renowned proposal is the Free Energy Principle (FEP), which uses an information-theoretic framework derived from thermodynamic considerations to describe how behavior and understanding emerge. FEP starts from a whole-organism approach, based on mental states and phenomena, mapping them into the neuronal substrate. An alternative approach, the Energy Homeostasis Principle (EHP), initiates a similar explanatory effort but starts from single-neuron phenomena and builds up to whole-organism behavior and understanding. In this work, we further develop the EHP as a distinct but complementary vision to FEP and try to explain how behavior and understanding would emerge from the local requirements of the neurons. Based on EHP and a strict naturalist approach that sees living beings as physical and deterministic systems, we explain scenarios where learning would emerge without the need for volition or goals. Given these starting points, we state several considerations of how we see the nervous system, particularly the role of the function, purpose, and conception of goal-oriented behavior. We problematize these conceptions, giving an alternative teleology-free framework in which behavior and, ultimately, understanding would still emerge. We reinterpret neural processing by explaining basic learning scenarios up to simple anticipatory behavior. Finally, we end the article with an evolutionary perspective of how this non-goal-oriented behavior appeared. We acknowledge that our proposal, in its current form, is still far from explaining the emergence of understanding. Nonetheless, we set the ground for an alternative neuron-based framework to ultimately explain understanding.

scholarly journals Energy Homeostasis Principle: A Naturalistic Approach to Explain the Emergence of Behavior

2021 ◽  
Author(s):  
Sergio Vicencio ◽  
Mario Villalobos ◽  
Pedro Maldonado ◽  
Rodrigo Vergara
Keyword(s):  
Energy Homeostasis ◽  
Mental States ◽  
Energy Principle ◽  
Current Form ◽  
Information Theoretic ◽  
Deterministic Systems ◽  
Neuronal Mechanisms ◽  
Alternative Approach ◽  
Basic Learning

Explaining the emergence of behavior and understanding on the basis of neuronal mechanisms is still elusive. One renowned proposal is the Free Energy Principle (FEP), which uses an information-theoretic framework derived from thermodynamic considerations to describe how behavior and understanding would emerge. FEP starts from a whole organism approach, based on mental states and phenomena, mapping them into the neuronal substrate. An alternative approach, the Energy Homeostasis Principle (EHP), initiates a similar explanatory effort, but starting from single neuron phenomena and building up to the whole organism’s behavior and understanding. In this work, we develop the EHP as an alternative but complementary vision to FEP and try to explain how behavior and understanding would emerge from the local requirements of the neurons. Based on EHP and a strict naturalist approach that sees living beings as physical and deterministic systems, we explain scenarios where learning would emerge without the need for volition or goals. Given these starting points, we state several considerations of how we see the nervous system, particularly the role of function, purpose, and the conception of goal-oriented behaviors. We problematize these conceptions, giving an alternative teleology-free framework in which behavior and, ultimately, understanding would still emerge. We reinterpret neural processing explaining basic learning situations up to simple anticipatory behavior. Finally, we end the work with an evolutionary perspective of how this non-goal-oriented behavior appears. We acknowledge that in the current form of our proposal, we are still far from explaining the emergence of understanding. Still, we set the ground for an alternative neuron-based framework to ultimately explain understanding.

scholarly journals tomsup: An implementation of computational Theory of Mind in Python

2020 ◽  
Author(s):  
Kenneth C. Enevoldsen ◽  
Peter Thestrup Waade
Keyword(s):  
Theory Of Mind ◽  
Model Simulation ◽  
Mental States ◽  
Future Research ◽  
Model Parameters ◽  
Computational Theory Of Mind ◽  
Agent Based Models ◽  
Energy Principle ◽  
Current Form ◽  
Agent Based

Computational implementations of Theory of Mind (ToM), the ability to attribute mental states to others, has been used to investigate a variety of issues. This includes the effect of framing effects on, or inter-species differences in, ability to do ToM (Devaine et al., 2014a, 2017), ToM in autists (d’Arc et al., 2018), or providing an explanation for the apparent limits on human ability to do ToM recursively (Devaine et al., 2014b). It has been implemented in the VBA package for Matlab (Daunizeau et al., 2014), but not in any free and open-source software. Therefore this thesis presents the Theory of Mind simulation using Python (tomsup) package.The tomsup package provides accessible tools for running agent-based models in a game theory context, and allows the implementation of a computational model of ToM, either in agent-based models or in interaction with a human player. The implementation of the ToM model was originally proposed by Yoshida et al. (2008), and was developed by drawing on the Free Energy Principle (Friston, 2010) to its current form as it is in Devaine et al. (2017), where it is generalized to any 2-player game which can be operationalized as a 2-by-2 payoff matrix. Importantly, the ToM implementation introduces a sophistication level k, which determines how many recursive simulations of its opponent it can perform, hereby assuming bounded rationality (Kahneman, 2003). An agent using the ToM model, denoted as k-ToM, uses a variational Bayes Laplace approximation (Daunizeau, 2017b) on a turn-by-turn basis to infer its opponent’s model parameters and sophistication level, based on which it predicts the opponent’s choice and acts accordingly.An agent-based model simulation using the competitive matching pennies game was done to perform a prelim- inary investigation of the behaviour of the k-ToM model. Most importantly, it was found that k-ToM’s prior beliefs about its opponent have a notable effect on its performance, even over many trials, warranting further research into how its priors should be formed. Various ways are suggested in which the tomsup package and the k-ToM model could be applied and developed further, as well as a discussion on how to make it broadly available, so as to scaffold future research using computational ToM models.

Aboutness

2014 ◽  
Author(s):  
Stephen Yablo
Keyword(s):  
Subject Matter ◽  
Philosophy Of Language ◽  
Mental States ◽  
Library Science ◽  
Philosophical Methodology ◽  
Major Advance ◽  
Truth Conditions ◽  
Ways Of Being ◽  
Made In

Aboutness has been studied from any number of angles. Brentano made it the defining feature of the mental. Phenomenologists try to pin down the aboutness features of particular mental states. Materialists sometimes claim to have grounded aboutness in natural regularities. Attempts have even been made, in library science and information theory, to operationalize the notion. However, it has played no real role in philosophical semantics, which is surprising. This is the first book to examine through a philosophical lens the role of subject matter in meaning. A long-standing tradition sees meaning as truth conditions, to be specified by listing the scenarios in which a sentence is true. Nothing is said about the principle of selection—about what in a scenario gets it onto the list. Subject matter is the missing link here. A sentence is true because of how matters stand where its subject matter is concerned. This book maintains that this is not just a feature of subject matter, but its essence. One indicates what a sentence is about by mapping out logical space according to its changing ways of being true or false. The notion of content that results—directed content—is brought to bear on a range of philosophical topics, including ontology, verisimilitude, knowledge, loose talk, assertive content, and philosophical methodology. The book represents a major advance in semantics and the philosophy of language.

The role and relationship of mindreading and social attunement in HRI – position statements of interdisciplinary researchers. Workshop HRI'20

2020 ◽  
Author(s):  
Agnieszka Wykowska ◽  
Jairo Pérez-Osorio ◽  
Stefan Kopp
Keyword(s):  
Mental States ◽  
Human Robot Interaction ◽  
Human Interaction ◽  
Artificial Agents ◽  
The Novel ◽  
Robot Interaction ◽  
Novel Coronavirus ◽  
Relationship Of ◽  
The Relationship

This booklet is a collection of the position statements accepted for the HRI’20 conference workshop “Social Cognition for HRI: Exploring the relationship between mindreading and social attunement in human-robot interaction” (Wykowska, Perez-Osorio & Kopp, 2020). Unfortunately, due to the rapid unfolding of the novel coronavirus at the beginning of the present year, the conference and consequently our workshop, were canceled. On the light of these events, we decided to put together the positions statements accepted for the workshop. The contributions collected in these pages highlight the role of attribution of mental states to artificial agents in human-robot interaction, and precisely the quality and presence of social attunement mechanisms that are known to make human interaction smooth, efficient, and robust. These papers also accentuate the importance of the multidisciplinary approach to advance the understanding of the factors and the consequences of social interactions with artificial agents.

Minimal Event-Causal Libertarianism

2018 ◽  
Author(s):  
Christopher Evan Franklin
Keyword(s):  
Free Action ◽  
Mental States ◽  
Human Action

This chapter explains the differences between agency reductionism and nonreductionism, explains the varieties of libertarianism, and sets out the main contours of minimal event-causal libertarianism, highlighting just how minimal this theory is. Crucial to understanding how minimal event-causal libertarianism differs from other event-causal libertarian theories is understanding the location and role of indeterminism in human action, the kinds of mental states essential to causing free action, the nature of nondeterministic causation, and how the theory is constructed from compatibilist accounts. The chapter argues that libertarians must face up to both the problem of luck and the problem of enhanced control when determining the best theoretical location of indeterminism.

Parentheticalism and (Ir)rational Agency

2018 ◽  
Author(s):  
Tim Henning
Keyword(s):  
Mental States ◽  
Rational Agency ◽  
Willingness To Use

This chapter considers various cases of irrationality (such as akrasia, weakness in executive commitments, doxastic incontinence, etc.), all of which involve a break between an agent’s considered judgment and her effective mental states. It is shown that parentheticalism can solve puzzles that these phenomena typically raise. The discussion leads into a deeper grasp of the rationale behind parenthetical and non-parenthetical uses of verbs like “believe” and “want”: They are associated with aspects of rational agency that normally coincide but can come apart. In the latter cases, our willingness to use verbs like “believe” and “want” is conflicted in a way that confirms parentheticalism. Finally, I suggest that parentheticalism can help us understand the role of the agent in rational agency and solve the Missing Agent Problem.

Conceptualizing and Measuring Affective and Cognitive Empathy

2020 ◽  
pp. 8-30
Author(s):  
Ross Buck ◽  
Zhan Xu
Keyword(s):  
Mental States ◽  
Cognitive Empathy ◽  
Emotional Empathy ◽  
Symbolic Communication ◽  
Current State ◽  
Communication Processes ◽  
Neuroscience Research ◽  
Emotion Displays ◽  
Central Nervous Systems

Individual differences in the ability to recognize emotion displays relate strongly to emotional intelligence, and emotional and social competence. However, there is a difference between the ability to judge the emotions of another person (i.e., emotional empathy) and the ability to take the perspective of another person, including making accurate appraisals, attributions, and inferences about the mental states of others (i.e., cognitive empathy). In this chapter, we review the concept of emotional empathy and the current state of the field, including emerging and converging evidence from neuroscience research that emotional and cognitive empathy involve doubly dissociable brain systems. We also discuss emerging literature on the physiological mechanisms underlying empathy in the peripheral and central nervous systems. We then distinguish spontaneous and symbolic communication processes to show how cognitive empathy emerges from emotional empathy during development. Development starts with the prelinguistic mutual contingent responsiveness of infant and caregiver yielding “raw” primary intersubjectivity, then secondary and tertiary intersubjectivity advances with increasing social experience, and finally cognitive empathic abilities expand in perspective taking and Theory of Mind (ToM) skills. We then present an Affect-Reason-Involvement (ARI) model to guide the conceptualization and measurement of emotional and cognitive empathy. We consider emotion correlation scores as a flexible and valid approach to empathy measurement, with implications for understanding the role of discrete emotions in decision making. Finally, we apply this reasoning to recent studies of the role of emotion and empathy in bullying.

scholarly journals Robust Universal Inference

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 773
Author(s):  
Amichai Painsky ◽  
Meir Feder
Keyword(s):  
Robust Estimation ◽  
Minimax Estimator ◽  
Worst Case ◽  
Capacity Theory ◽  
Alternative Approach ◽  
True Model ◽  
Finite Set ◽  
Universal Prediction ◽  
Estimation Scheme

Learning and making inference from a finite set of samples are among the fundamental problems in science. In most popular applications, the paradigmatic approach is to seek a model that best explains the data. This approach has many desirable properties when the number of samples is large. However, in many practical setups, data acquisition is costly and only a limited number of samples is available. In this work, we study an alternative approach for this challenging setup. Our framework suggests that the role of the train-set is not to provide a single estimated model, which may be inaccurate due to the limited number of samples. Instead, we define a class of “reasonable” models. Then, the worst-case performance in the class is controlled by a minimax estimator with respect to it. Further, we introduce a robust estimation scheme that provides minimax guarantees, also for the case where the true model is not a member of the model class. Our results draw important connections to universal prediction, the redundancy-capacity theorem, and channel capacity theory. We demonstrate our suggested scheme in different setups, showing a significant improvement in worst-case performance over currently known alternatives.

scholarly journals Chemical and Biological Molecules Involved in Differentiation, Maturation, and Survival of Dopaminergic Neurons in Health and Parkinson’s Disease: Physiological Aspects and Clinical Implications

Biomedicines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 754
Author(s):  
Giulia Gaggi ◽  
Andrea Di Credico ◽  
Pascal Izzicupo ◽  
Giovanni Iannetti ◽  
Angela Di Baldassarre ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Dopaminergic Neurons ◽  
Potential Role ◽  
High Efficiency ◽  
Biological Molecules ◽  
Alternative Approach ◽  
Non Coding Rnas ◽  
Set Up

Parkinson’s disease (PD) is one of the most common neurodegenerative disease characterized by a specific and progressive loss of dopaminergic (DA) neurons and dopamine, causing motor dysfunctions and impaired movements. Unfortunately, available therapies can partially treat the motor symptoms, but they have no effect on non-motor features. In addition, the therapeutic effect reduces gradually, and the prolonged use of drugs leads to a significative increase in the number of adverse events. For these reasons, an alternative approach that allows the replacement or the improved survival of DA neurons is very appealing for the treatment of PD patients and recently the first human clinical trials for DA neurons replacement have been set up. Here, we review the role of chemical and biological molecules that are involved in the development, survival and differentiation of DA neurons. In particular, we review the chemical small molecules used to differentiate different type of stem cells into DA neurons with high efficiency; the role of microRNAs and long non-coding RNAs both in DA neurons development/survival as far as in the pathogenesis of PD; and, finally, we dissect the potential role of exosomes carrying biological molecules as treatment of PD.

The Role of Tanycytes in the Hypothalamus-Pituitary-Thyroid Axis and the Possibilities for Their Genetic Manipulation

2019 ◽  
Vol 128 (06/07) ◽  
pp. 388-394
Author(s):  
Helge Müller-Fielitz ◽  
Markus Schwaninger
Keyword(s):  
Energy Homeostasis ◽  
Genetic Manipulation ◽  
Heart Function ◽  
Feedback Regulation ◽  
Target Organs ◽  
Pituitary Thyroid Axis ◽  
Thyroid Axis ◽  
Hpt Axis ◽  
The Brain

AbstractThyroid hormone (TH) regulation is important for development, energy homeostasis, heart function, and bone formation. To control the effects of TH in target organs, the hypothalamus-pituitary-thyroid (HPT) axis and the tissue-specific availability of TH are highly regulated by negative feedback. To exert a central feedback, TH must enter the brain via specific transport mechanisms and cross the blood-brain barrier. Here, tanycytes, which are located in the ventral walls of the 3rd ventricle in the mediobasal hypothalamus (MBH), function as gatekeepers. Tanycytes are able to transport, sense, and modify the release of hormones of the HPT axis and are involved in feedback regulation. In this review, we focus on the relevance of tanycytes in thyrotropin-releasing hormone (TRH) release and review available genetic tools to investigate the physiological functions of these cells.

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