Introduction to the special issue on physics of mind
Introduction
In past decades, brain science has made tremendous progresses in its attempt to understand the organizational principles of information processing. From the hierarchical mechanisms of perception and cognition, to the role of emotions in the organization of neural assemblies, and the study of bounds on cognition and problem-solving: at nearly all levels of analysis, a wide range of experimental data offers a clearer understanding of the thinking brain and its living body. Despite tremendous progress, our understanding of basic functions such as learning, intelligence and consciousness rest upon vague concepts, which remain difficult to operationalize with precision. With the special issue, we aim to offer a step toward working collaboratively on these problems by providing a common language built upon stable definitions abstracted from reproducible experiments. With the advent of ubiquitous computing, artificial intelligence and their deployment in civil society, new questions concerning the very nature of natural intelligence come into the scope of empirical analysis [11], [12]. The explosion in demographics and our increasing dependence on technology, are causing possibilities for human conflict to explode exponentially at a global scale. We need an in-depth understanding of human behavior that is coherent across disciplines, and new models for the principles underlying brain communication, interaction and self-control, these very same principles that allow life and knowledge to flourish and expand through culture.
In this editorial, we propose to outline eight fundamental problems, which remain unsolved and, in our opinion, demand pressing scientific attention. We divided these problems into two categories, easy and hard. Easy problems are essentially problems at the descriptive level of analysis. They are concerned with identifying invariant patterns in human behavior and explaining away the deviations observable in the case of psychiatric disorders and the differences observable in the large-scale societal organization of knowledge and cognition. Hard problems concern the rigorous measurement of concepts (e.g., emotions, interoception, consciousness) and the development of the appropriate technology for doing so. We present these problems in a gradual order of difficulty, and discuss eventual means toward their solutions. Finally, we conclude this article with some remarks concerning the mechanisms underlying brain growth, and the evolution of cognitive and cultural systems in the wild.
An emphasis has been placed on cultural processes and their underlying affective life, as culture is perhaps the domain of research where neuroscience meets its most interesting frontiers, and where applications hold the greatest transformative potential. This list is not meant to be exhaustive, but rather present the scope and the field of analysis of what has been referred to in recent years as the physics of mind. Physics is often regarded as the most successful area of science. It has even been argued that the methods of physics are the sole means for obtaining truth about the known universe, in the form of general laws that can be applied at all scales and sizes. In its current form, the span of physics covers a wide range of different areas: Newtonian mechanics describe celestial bodies, electrodynamics describe interactions at a small scale, astrophysics describes the nature of stars and interstellar medium, condensed matter physics teaches us the properties of matter, thermodynamics describes heat and help us build heat engines, biophysics enlighten our understanding of life and death and their origins on our planet. One peculiar object in the universe still pervades the scope of physics: the human mind, which generates physics. This begs the following question, is it possible to develop a physics of mind modeling accurately human cognition? Can science, and the scientists producing science, perceive perception, understand language, think cognition, and model that which models? Physics of mind differs from other attempts to understand the brain in its aims and methodology. This methodology is organized in three stages:
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Define few fundamental laws approximating a broad physical area, and propose their mathematical or diagrammatic formulations.
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Based on these fundamental laws build a theory for this area of knowledge, which does not contradict any known fact and predicts new nontrivial and experimentally verifiable phenomena.
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Conduct experiments to prove or disprove the theory.
In past decades and due to large funding programs, such as the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) initiative and the Human Brain Project, a manifold of mental phenomena has been explored, including brain functions such as perception, attention, memory, learning, emotion, and language. Successful technological applications such as brain-computer interfaces and other neurotechnologies have been devised [5]. These advances have been paralleled by trends in the biomedical and clinical sciences, concerned with designing a more reliable psychiatry. For example, the Research Domain Criteria by the NIMH is a research framework for new approaches to investigate mental disorders [19]. In order to explore the basic dimensions of functioning that span the full range of human behavior from normal to abnormal, this framework integrates many levels of information (from genomics and circuits to behavior and self-reports). The goal is to understand the nature of mental health and illness in terms of varying degrees of dysfunctions in general cognitive systems. However, these frameworks lack unifying principles and deep models for general cognitive systems. Physics of mind can bring fundamentally new insights to these endeavor by providing simple models for basic cognitive functions and offering predictions explaining away signs and symptoms, paving the way for new technological applications and treatments avoiding the severe side effects associated to the existing chemical and electrical treatments. After two years of curation, we hope that the special issue can contribute to these collective endeavors by providing parsimonious explanations to make sense of large amount of experimental data and pave the way toward truly transcultural brain and behavioral sciences.
Section snippets
Easy problems: invariant patterns in human behavior
We start by listing some easy problems for cognitive neuroscience. These easy problems essentially depend on descriptive studies to identify invariance in human behavior at a global scale. One of the major drawbacks in this regard is the lack of heterogeneity in psychological data and the issue of reliability of the existing data, meaning the problem of reproducibility. To address these issues, collaborative projects founded on principles of open science such as Neurosynth from Tal Yarkoni,
Hard problems: testing fundamental theories
Hard problems depend on the development of precise technology to measure basic mind mechanisms such as learning or emotions, in order to test fundamental theories and derive meaningful definitions for terms such as consciousness, attention, and interoception. The most difficult problems in our opinion are those at the interface between science and philosophy, where truth meets meaning. These problems concern the nature of human semantics and their relevance not only for (linguistic)
Conclusion
The history of brain and cognitive sciences lead to several fundamental principles for behavior, which have been verified across life, such as the Weber laws [6], which quantifies the perception of differences between stimuli and has been demonstrated to hold even in lower animals [13]. A complete review of such psychophysical laws is presented in this volume by Ihor Lubashevsky [6]. More recent theories, such as homeostatic reward learning or cognitive dissonance have been mathematically
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