January 7 (Wed) to 9 (Fri), 2015
|Rusutsu Resort Hotel , Hokkaido, Japan|
Registration fee : 2,000 yen ( Student : free )
|"Integration of mind"|
|18:10-19:00||György Buzsáki（New York Univ)|
|19:10-20:00||Giulio Tononi（Univ of Wisconsin）|
|20:10-21:00||Etienne Koechlin（École normale supérieure）|
|15:30-16:20||Naotsugu Tsuchiya(Monash University)|
|17:30-18:20||Hiroaki Mizuhara（Kyoto University)|
|January 8||Tutorial : Integrated Information Theory of Consciousness|
|20:00-22:00||Giulio Tononi (Univ of Wisconsin)|
|9:00-9:50||Shin’ya Nishida（NTT Communication Science Laboratories）|
|10:00-10:50||Yousuke Morishima（University of Bern）|
|11:00-11:50||Makoto Higuchi(National Institute of Radiological Sciences)|
Abstracts and References：
1. BUZSAKI LAB Latest Publications
2. Rhythms of the Brain
The science of consciousness has made great strides by focusing on the behavioral and neuronal correlates of experience. However, correlates are not enough if we are to understand even basic facts, for example, why the cerebral cortex gives rise to consciousness but the cerebellum does not, though it has even more neurons and appears to be just as complicated. Moreover, correlates are of little help in many instances where we would like to know if consciousness is present: patients with a few islands of functioning cortex, pre-term infants, non-mammalian species, and machines that are rapidly outperforming people at driving, recognizing faces and objects, and answering difficult questions. To address these issues, we need not only more data, but also a theory of consciousness – one that says what experience is and what type of physical systems can have it. Integrated Information Theory (IIT) does so by starting from experience itself via five phenomenological axioms of existence, composition, information, integration, and exclusion. From these it derives five postulates about the properties required of physical mechanisms, such as neurons and their connections, to support consciousness. The theory provides a principled account of both the quantity and the quality of an individual experience, and a calculus to evaluate whether or not a particular system of mechanisms is conscious and of what. Moreover, IIT can explain a range of clinical and laboratory findings, makes a number of testable predictions, and extrapolates to a number of unusual conditions.
From the phenomenology to the mechanisms of consciousness: Integrated Information Theory 3.0.
I will present recent works from our lab combining computational modeling, experimental psychology and functional magnetic resonance imaging describing how the prefrontal cortex subserves reasoning in the service of decision-making and adaptive behavior. I will show how the ventromedial, dorsomedial, lateral and polar prefrontal regions along with the striatum form an unified system combining inferential and creative abilities for efficient behavior in uncertain, variable and open-ended environments.
The Integrated information theory (IIT) aims to explain how our conscious experience is supported by the mechanisms in the brain. The IIT predicts that a pattern of integrated information generated by some parts of the brain corresponds to the contents of consciousness. Here, we set out to test the prediction by measuring a pattern of the integrated information, or phi*, based on field potentials recorded with electrodes in awake epilepsy patients, who performed several visual psychophysical tasks. We found a structure of phi*, constructed from the face selective areas in the temporal lobe, without any supervised learning, classified subjective visual experience of faces, rather than properties of physical visual input of faces. We ruled out a possibility that high dimensionality of the phi*-pattern was sufficient for such categorization by analysing high-dimensional pattern derived by other quantities as well as phi* structure derived from other areas that are not selective to faces: both poorly reflected subjective experience compared to phi* structure derived from the face selective areas. In sum, without any training or decoding, high-dimensional phi* structure naturally mirrored subjective experience of faces, promising the IIT as a possible solution to the enigma of consciousness.
Sense of selfhood is the core of our subjective experiences. The property seemed so private that scientists could hardly access or evaluate it quantitatively. However, recent studies have begun to give some clues to the issues. As one example, I will first introduce our studies on confidence. Confidence is regarded as a consequence of self-assessment on the certain or uncertain status of one’s own performances or cognitions. Using a modified wagering task, we estimated the monkey’s graded confidence levels and found evidences from correlation to causation that the pulvinar, a higher order nucleus of visual thalamus, attaches a subject’s confidence to visual categorization. Second, we performed the human psychophysics with subjective reports of confidence. We found that human’s confidence scores as a function of stimulus ambiguity and behavioral outcome showed same patterns as the modulation of monkey’s pulvinar activities. These data indicate the common computation for confidence in monkeys and humans, thereby potentially relating the animal data to humans’ subjectivity. Finally I would like to discuss the relationships between the neurobiology of selfhood, and other cognitive functions as well as clinical disorders.
Responses of pulvinar neurons reflect a subject's confidence in visual categorization
Neurons in distributed cortices must dynamically communicate with each other for an appropriate processing depending on situation. The timing of the neural activities in the distributed cortices would be entrained by the synchrony of neural oscillations for the temporal binding of appropriate cortical activities. In human EEG studies, the neural synchrony can be observed as the hierarchical coupling between the amplitude of fast oscillation and phase of slow oscillation. I will introduce our recent studies on the human neural synchrony, where the fast oscillations simultaneously appeared at the frontal and occipital scalp sites at even intervals of the slow oscillation for successful working memory retention. Our simultaneous fMRI-EEG also revealed that the fast and slow oscillations accompanied with cortical activities in the visual image related areas, and in the mnemonic circuit, respectively. The theoretical framework on the neural synchrony can be extended to explain the underlying mechanism of inter-personal
1. Human cortical circuits for central executive function emerge by theta phase synchronization.
2. Neuronal ensemble for visual working memory via interplay of slow and fast oscillations.
Human has an excellent perceptual ability to readily recognise what kind of material properties an object has, and what kind of material category the object belongs to. Despite being an essential sensory function of brain and mind for proper interactions with the environment, material perception has been largely ignored in sensory science until recently, leaving many questions unsolved. In this talk, I will explain our general strategy in material perception research, and then review our recent research about a few specific topics, including how to perceive liquid and its viscosity from visual motion information, how to perceive hair fineness below spatial resolution limit of the visual system, and how to integrate material information across multiple sensory modalities.
1. Seeing liquids from visual motion
2. Combining colour and temperature: A blue object is more likely to be judged as warm than a red object
3. Audiovisual integration in the human perception of materials
Optimal adjustment of brain networks allows the biased processing of information in response to the demand of environments and is therefore prerequisite for adaptive behaviour. It is widely shown that a biased state of networks is associated with a particular cognitive process. However, those associations were identified by backward categorization of trials and cannot provide a causal association with cognitive processes. This problem still remains a big obstacle to advance the state of our field in particular human cognitive neuroscience. In my talk, I will present two approaches to address the causal relationships between brain network interactions and behaviour. Firstly, we combined connectivity analysis of fMRI data and a machine leaning method to predict inter-individual differences of behaviour and responsiveness to environmental demands. The connectivity-based classification approach outperforms local activation-based classification analysis, suggesting that interactions in brain networks carry information of instantaneous cognitive processes. Secondly, we have recently established a brand new method combining transcranial alternating current stimulation (tACS), transcranial magnetic stimulation (TMS), and EEG. We use the method to measure signal transmission between brain areas while introducing extrinsic oscillatory brain activity and to study causal association between oscillatory activity and behaviour. We show that phase-matched oscillatory activity creates the phase-dependent modulation of signal transmission between brain areas, while phase-shifted oscillatory activity blunts the phase-dependent modulation. The results suggest that phase coherence between brain areas plays a cardinal role in signal transmission in the brain networks. In sum, I argue that causal approaches will provide more concreate backbones to cognitive neuroscience.
Aging is intimately associated with deposition of abnormal proteins in the brain exemplified by amyloid-beta and tau, and excess accumulation of these aggregates eventually leads to the onset and progression of Alzheimer’s disease and other neurodegenerative dementias. Molecular links between protein deposition and neuronal deteriorations are yet to be clarified, while a consensus hypothetical view is that protein aggregation triggers chain reactions of key pathological processes including neuroinflammation and aberrant neurotransmissions, resulting in synaptic dysfunction and neuronal death. This pathogenetic signal cascade has been visualized in living human and animal brains using positron emission tomography (PET) and radiotracers targeting essential components in the key processes. By near-simultaneous observations of multiple key processes with PET, it has been recently revealed that downstream processes also mechanistically regulate upstream processes, implying a ‘backflow’ of the cascade. Indeed, causal relations could be found between any two of the key processes, thereby rationalizing a network concept rather than cascade-like one-way signaling. Hence, molecular and cellular etiology of age-related brain diseases could be analyzed as emergence of pathological but ordered network of key processes in the brain, instead of disruption of physiological and homeostatic orders.
1. In-vivo visualization of key molecular processes involved in Alzheimer’s disease pathogenesis: insights from neuroimaging research in humans and rodent models.
2. Imaging of tau pathology in a tauopathy mouse model and in Alzheimer patients compared to normal controls.