The brain is composed of electrically excitable neuronal networks regulated by the activity of voltage-gated ion channels. Further portraying the molecular composition of the brain, however, will not reveal anything remotely reminiscent of a feeling, a sensation or a conscious experience. In classical physics, addressing the mind-brain problem is a formidable task because no physical mechanism is able to explain how the brain generates the unobservable, inner psychological world of conscious experiences and how in turn those conscious experiences steer the underlying brain processes toward desired behavior. Yet, this setback does not establish that consciousness is non-physical. Modern quantum physics affirms the interplay between two types of physical entities in Hilbert space: unobservable quantum states, which are vectors describing what exists in the physical world, and quantum observables, which are operators describing what can be observed in quantum measurements. Quantum no-go theorems further provide a framework for studying quantum brain dynamics, which has to be governed by a physically admissible Hamiltonian. Comprising consciousness of unobservable quantum information integrated in quantum brain states explains the origin of the inner privacy of conscious experiences and revisits the dynamic timescale of conscious processes to picosecond conformational transitions of neural biomolecules. The observable brain is then an objective construction created from classical bits of information, which are bound by Holevo's theorem, and obtained through the measurement of quantum brain observables. Thus, quantum information theory clarifies the distinction between the unobservable mind and the observable brain, and supports a solid physical foundation for consciousness research.
We propose a non-substance dualism theory, following Heisenberg: The world consists of both ontologically real possibilities that do not obey Aristotle's Law of the Excluded Middle, and ontologically real Actuals that do o0bey the Law of the Excluded Middle. This quantum approach solves five issues in quantum mechanics and numerous puzzles about the mind-brain relationship. It raises the possibility that some aspects of mind are non-local, and that mind plays an active role in the physical world. We present supporting evidence.
Up to now, we have been faced with an age old fundamental dilemma posed by the mind-brain interaction problem, i.e. how is it that the mind which is subjective and immaterial, can interact with the brain which is objective and material? Analysis of recent experiments appears to indicate that quantum mechanics may have a role to play in the resolution of the mind-brain interaction problem in the form of biological entanglement and nonlocality. This analysis, when coupled with ongoing and proposed experiments, may help us to simultaneously resolve related issues such as whether mental events can…
We review the dissipative quantum model of brain and present recent developments related with the rôle of entanglement, quantum noise and chaos in the model.
In contrast to the critical brain hypothesis in which the brain tunes itself to a critical point between $states$ of chaos and order, analysis of Coordination Dynamics suggests that a vast repertoire of $coexisting$ $tendencies$ exists for regions of the brain to integrate and segregate at the same time. Rather than teetering between order and randomness, the brain~mind lives in an immense sea of metastability where it can create functional information.
The brain-as-computer metaphor has anchored the professed computational nature of the mind, wresting it down from the intangible logic of Platonic philosophy to a material basis for empirical science. However, as with many long-lasting metaphors in science, the computer metaphor has been explored and stretched long enough to reveal its boundaries. These boundaries highlight widening gaps in our understanding of the brain's role in an organism's goal-directed, intelligent behaviors and thoughts. In search of a more appropriate metaphor that reflects the potentially noncomputable functions of mi…
We propose a model of processing of information in the brain which has the following distinguishing features: a). It is quantum-like (QL). The brain uses the quantum rule (given by von Neumann trace formula) for calculation of averages for psychological functions. b). Those functions are considered as self-observations of the brain. c). The QL-representation has the temporal basis. The brain is a machine transferring time into cognition. d). Any cognitive process is based on (at least) two time scales: precognitive time scale (which is very fine) and cognitive time scale (which is essentially …
Perhaps the most important question posed by brain research is: How the brain gives rise to the mind. To answer this question, we have primarily relied on the connectionist paradigm: The brain's entire knowledge and thinking skills are thought to be stored in the connections; and the mental operations are executed by network computations. I propose here an alternative paradigm: Our knowledge and skills are stored in metabotropic receptors (MRs) and the G protein-gated ion channels (GPGICs). Here, mental operations are assumed to be executed by the functions of MRs and GPGICs. As GPGICs have th…
Addressing the question of visualising human mind could help us to find regions that are associated with observed cognition and responsible for expressing the elusive mental image, leading to a better understanding of cognitive function. The traditional approach treats brain decoding as a classification problem, reading the mind through statistical analysis of brain activity. However, human thought is rich and varied, that it is often influenced by more of a combination of object features than a specific type of category. For this reason, we propose an end-to-end brain decoding framework which…
State University of New York at New Paltz（纽约州立大学新帕尔兹分校）；Northeastern University（东北大学）
Turing inspired a computer metaphor of the mind and brain that has been handy and has spawned decades of empirical investigation, but he did much more and offered behavioral and cognitive sciences another metaphor--that of the cascade. The time has come to confront Turing's cascading instability, which suggests a geometrical framework driven by power laws and can be studied using multifractal formalism and multiscale probability density function analysis. Here, we review a rapidly growing body of scientific investigations revealing signatures of cascade instability and their consequences for a…
Beijing University of Posts and Telecommunications（北京邮电大学）；Carnegie Mellon University（卡内基梅隆大学）；Tsinghua University（清华大学）
Understanding how brain functions has been an intriguing topic for years. With the recent progress on collecting massive data and developing advanced technology, people have become interested in addressing the challenge of decoding brain wave data into meaningful mind states, with many machine learning models and algorithms being revisited and developed, especially the ones that handle time series data because of the nature of brain waves. However, many of these time series models, like HMM with hidden state in discrete space or State Space Model with hidden state in continuous space, only wor…
The human brain is a complex network that supports mental function. The nascent field of network neuroscience applies tools from mathematics to neuroimaging data in the hopes of shedding light on cognitive function. A critical question arising from these empirical studies is how to modulate a human brain network to treat cognitive deficits or enhance mental abilities. While historically a number of tools have been employed to modulate mental states (such as cognitive behavioral therapy and brain stimulation), theoretical frameworks to guide these interventions - and to optimize them for clinic…
The central problem with understanding brain and mind is the neural code issue: understanding the matter of our brain as basis for the phenomena of our mind. The richness with which our mind represents our environment, the parsimony of genetic data, the tremendous efficiency with which the brain learns from scant sensory input and the creativity with which our mind constructs mental worlds all speak in favor of mind as an emergent phenomenon. This raises the further issue of how the neural code supports these processes of organization. The central point of this communication is that the neural…
The cognitive frame in which most neuropsychological research on the neural basis of behavior is conducted contains the assumption that brain mechanisms per se fully suffice to explain all psychologically described phenomena. This assumption stems from the idea that the brain is made up entirely of material particles and fields, and that all causal mechanisms must therefore be formulated solely in terms of properties of these elements. One consequence of this stance is that psychological terms having intrinsic mentalistic and/or experiential content (terms such as "feeling," "knowing," and "ef…
Introduction. Increased efforts in neuroscience try to understand mental disorders as brain disorders. In the present study we investigate how common a neuroreductionist inclination is among highly educated people. In particular, we shed light on implicit presuppositions of mental disorders little is known about in the public, exemplified here by the case of Body Integrity Dysphoria (BID) that is considered a mental disorder for the first time in ICD-11. Methods. Identically graphed, simulated data of mind-brain correlations were shown in three contexts with presumably different presumptions a…
Humboldt-University of Berlin（柏林洪堡大学）；University of Tartu（塔尔图大学）
Can deep learning (DL) guide our understanding of computations happening in biological brain? We will first briefly consider how DL has contributed to the research on visual object recognition. In the main part we will assess whether DL could also help us to clarify the computations underlying higher cognitive functions such as Theory of Mind. In addition, we will compare the objectives and learning signals of brains and machines, leading us to conclude that simply scaling up the current DL algorithms will most likely not lead to human level Theory of Mind.
IMT Lille Douai（IMT里尔杜埃）；CRIStAL UMR CNRS 9189（法国国家科学研究中心信息、自动化与信号处理实验室）；University of Mons（蒙斯大学）
Visual attention estimation is an active field of research at the crossroads of different disciplines: computer vision, artificial intelligence and medicine. One of the most common approaches to estimate a saliency map representing attention is based on the observed images. In this paper, we show that visual attention can be retrieved from EEG acquisition. The results are comparable to traditional predictions from observed images, which is of great interest. For this purpose, a set of signals has been recorded and different models have been developed to study the relationship between visual at…
Meditation practices have been claimed to have a positive effect on the regulation of mood and emotion for quite some time by practitioners, and in recent times there has been a sustained effort to provide a more precise description of the changes induced by meditation on human brain. Longitudinal studies have reported morphological changes in cortical thickness and volume in selected brain regions due to meditation practice, which is interpreted as evidence for effectiveness of it beyond the subjective self reporting. Evidence based on real time monitoring of meditating brain by functional im…
Understanding how the brain encodes external stimuli and how these stimuli can be decoded from the measured brain activities are long-standing and challenging questions in neuroscience. In this paper, we focus on reconstructing the complex image stimuli from fMRI (functional magnetic resonance imaging) signals. Unlike previous works that reconstruct images with single objects or simple shapes, our work aims to reconstruct image stimuli that are rich in semantics, closer to everyday scenes, and can reveal more perspectives. However, data scarcity of fMRI datasets is the main obstacle to applyin…
Models of the mind are based on the possibility of computing in brain microtubules. From this point of view, information processing is the fundamental issue for understanding the brain mechanisms that produce consciousness. The cytoskeleton polymers could store and process information through their dynamic coupling mediated by mechanical energy. We analyze the problem of information transfer and storage in brain microtubules, considering them as a communication channel. We discuss the implications of assuming that consciousness is generated by the subneuronal process.
Schizophrenic patients suffer from hallucination which its causality is not yet fully understood. This paper attempts to approach this mystery from the perspective of quantum mechanical theories. A novel approach has been adopted to demonstrate the hallucination as a time evolution of percepts basis states in the Hilbertian consciousness which are desynchronised from the time in real world. The method also extends his approach to predict mind and brain modulation through the correlation and coupling of consciousness and it reaches a clinically hypothetical outcome of inducing consciousness int…
Reconstructing the Mind's Eye: fMRI-to-Image with Contrastive Learning and Diffusion Priors
Princeton Neuroscience Institute（普林斯顿神经科学研究所）；Medical AI Research Center (MedARC)（医学人工智能研究中心（MedARC））；Ecole Normale Supérieure, PSL University（巴黎高等师范学院，PSL大学）；University of Toronto（多伦多大学）；Hebrew University of Jerusalem（希伯来大学）；EleutherAI；Stability AI
Mind-to-Image: Projecting Visual Mental Imagination of the Brain from fMRI
Obvious Research（奥布维研究机构）；GHU Paris Psychiatrie et Neurosciences（巴黎精神病学与神经科学大学医院集团）；Université Paris Cité（巴黎西岱大学）；Centre Imagerie du Nord（北方影像中心）；Raidium（雷迪姆公司）；FrontLab, Sorbonne Université（索邦大学前沿实验室）；Institut du Cerveau（大脑研究所）；Centre de NeuroImagerie de Recherche, Sorbonne Université（索邦大学神经影像研究中心）；Institut des Systèmes Intelligents et de la Robotique, Sorbonne Université（索邦大学智能系统与机器人研究所）
Understanding mind-brain-environment relations is one of the key topics in psychology. Kurt Lewin, inspired by theoretical physics, tried to establish topological and vector psychology analyzing patterns of interaction between the individual and her/his environment. The time is ripe to reformulate his ambitious goals, searching for ways to interpret objectively measured brain processes in terms of suitable psychological constructs. Connecting cognitive and social psychology constructs to neurophenomics, as it is done now in psychiatry, should ground them in physical reality.
An analysis has been performed of the theories and postulates advanced by von Neumann, London and Bauer, and Wigner, concerning the role that consciousness might play in the collapse of the wave function, which has become known as the measurement problem. This reveals that an error may have been made by them in the area of biology and its interface with quantum mechanics, when they called for the reduction of any superposition states in the brain through the mind or consciousness. Many years later Wigner changed his mind to reflect a simpler and more realistic objective position, expanded upon…
The feasibility of wave function collapse in the human brain has been the subject of vigorous scientific debates since the advent of quantum theory. Scientists like Von Neumann, London, Bauer and Wigner (initially) believed that wave function collapse occurs in the brain or is caused by the mind of the observer. It is a legitimate question to ask how human brain can receive subtle external visual quantum information intact when it must pass through very noisy and complex pathways from the eye to the brain? There are several approaches to investigate information processing in the brain, each of…
Today's 'theory of mind' (ToM) concept is rooted in the distinction of nineteenth century philosopher William Clifford between 'objects' that can be directly perceived, and 'ejects,' such as the mind of another person, which are inferred from one's subjective knowledge of one's own mind. A founder, with Charles Darwin, of the discipline of comparative psychology, George Romanes considered the minds of animals as ejects, an idea that could be generalized to 'society as eject' and, ultimately, 'the world as an eject' - mind in the universe. Yet, Romanes and Clifford only vaguely connected mind w…
Mapping minds not averages: a scalable subject-specific manifold learning framework for neuroimaging data
Electrical and Computer Engineering, Georgia Institute of Technology（电子与计算机工程系，佐治亚理工学院）；(TReNDS) Translational Research in Neuroimaging & Data Science center, Georgia State University, Georgia Institute of Technology, & Emory University（(TReNDS) 神经影像与数据科学转化研究中心，佐治亚州立大学，佐治亚理工学院，及埃默里大学）
Who Is in Mind Matters: Attachment Representations in Early Childhood Synchronize Child-Adult Interacting Brains
Shanghai Key Laboratory of Child Brain and Development, National Children's Medical Center, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University（上海交通大学医学院附属上海儿童医学中心国家儿童医学中心儿童脑发育上海市重点实验室）；School of Psychology, Shanghai Jiao Tong University（上海交通大学心理学院）；Center of Yuanshen Rehabilitation Institute, Shanghai Jiao Tong University School of Medicine（上海交通大学医学院元申康复研究中心）；School of Biomedical Engineering, Shanghai Jiao Tong University（上海交通大学生物医学工程学院）；Department of Child Health Care, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health（浙江大学医学院附属儿童医院儿童保健科国家儿童健康临床研究中心）；Department of Developmental and Behavioral Pediatrics and Pediatric Translational Medicine Institute and Shanghai Key Laboratory of Child Brain and Development, National Children's Medical Center, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine（上海交通大学医学院附属上海儿童医学中心国家儿童医学中心发育行为儿科与儿童转化医学研究所儿童脑发育上海市重点实验室）；Department of Computer Science, Vanderbilt University（范德堡大学计算机科学系）；Beijing No. 171 High School（北京市第一七一中学）；Global Institute of Future technology, Shanghai Jiao Tong university（上海交通大学未来技术全球化研究院）；Child Health Advocacy Institute, National Children's Medical Center, Shanghai Children's Medical Center, Affiliated to School of Medicine Shanghai Jiao Tong University（上海交通大学医学院附属上海儿童医学中心国家儿童医学中心儿童健康倡导研究所）；Shanghai Center for Brain Science and Brain-Inspired Technology（上海脑科学与类脑研究中心）
The nature of the existence, revealed through Human cognitive system, has been evolving since the development of the languages. Part of such revelations were the geometrical forms and the numbers, whose beauty and order, wondrous and mysterious, conveyed a sense of unreality beyond the physical reality normally discerned; to Plato they were indications of the other reality of which only those few glimpses had occurred. And full access for the earthlings required breaking out of their shackles of captivity; beautifully portrayed in the Masters cave allegory. The Present era sense of wonder of t…
A Theoretical Solution of the Mind-Body Problem: An Operationalized Proof that no Purely Physical System Can Exhibit all the Properties of Human Consciousness
Brain science and artificial intelligence have made great progress toward the understanding and engineering of the human mind. The progress has accelerated significantly since the turn of the century thanks to new methods for probing the brain (both structure and function), and rapid development in deep learning research. However, despite these new developments, there are still many open questions, such as how to understand the brain at the system level, and various robustness issues and limitations of deep learning. In this informal essay, I will talk about some of the concepts that are centr…
Electroencephalography (EEG) monitors ---by either intrusive or noninvasive electrodes--- time and frequency variations and spectral content of voltage fluctuations or waves, known as brain rhythms, which in some way uncover activity during both rest periods and specific events in which the subject is under stimulus. This is a useful tool to explore brain behavior, as it complements imaging techniques that have a poorer temporal resolution. We here approach the understanding of EEG data from first principles by studying a networked model of excitatory and inhibitory neurons which generates a v…
