First week: May 22 (Mon.) May 23 (Tue.) May 24 (Wed.) May 25 (Thu.) May 26 (Fri.)
Second week: May 29 (Mon.) May 30 (Tue.) May 31 (Wed.) June 1 (Thu.) June 2 (Fri.)
- 09:30 - 10:30 Lecture 1
- 11:00 - 12:00 Lecture 2
- 13:30 - 15:00 Parallel group discussion
- 15:30 - 16:30 Presentation by each group
- 17:00 - 18:00 Follow-up discussions with the lecturer
May 22 (Mon.)
Naotsugu Tsuchiya (Monash University)
Lecture Title: The neuronal basis of consciousness: basics and current controversies
Abstract: I will briefly introduce several key concepts on the neuronal basis of consciousness that would recur during the summer school: basics of neuroscience, clinical findings, some critical neurophysiological and neuroimaging studies, relevant discussions in philosophy and psychology and the neural correlates of consciousness. Then, I will also discuss recent breakthroughs and controversies in the science of consciousness including: theories of consciousness (eg integrated information theory, global workspace theory), consciousness and associated processes (eg attention, working memory, reports), whether consciousness is in the back or in the front of the brain.
- BolyBoly et al 2012 Frontiers
- Koch 2016 Nature Review Neuro
- Deheane 2011 Neuron
- (Attention vs consciousness) Koch & Tsuchiya 2007 TICS
Opposing view Cohen et al 2016 TICS
- (No report paradigms) Tsuchiya 2016 TICS
- (Front vs back of the brain) Two conflicting views on consciousness and the prefrontal cortex.
1. Are The Neural Correlates Of Consciousness In The Front Or In The Back Of The Cerebral Cortex? Clinical And Neuroimaging Evidence Melanie Boly, Marcello Massimini, Boly, Marcello Massimini, Naotsugu Tsychiya, Bradley R Postle, Christof Koch, Giulio Tononi
2. Should A Few Null Findings Falsify Prefrontal Theories Of Conscious Perception? Brian Odegaard, Robert T Knight, Hakwan Lau
May 23 (Tue.)
Ryota Kanai (Araya, Inc.)
Lecture Title: Two problems of machine consciousness
Abstract: Many sci-fi films depict sophisticated machines that appear to have awareness of themselves and the surroundings. The spreading of AI technologies in everyday life makes lay people wonder whether intelligent machines ever become aware. However, the mechanisms of consciousness are an unsolved mystery in neuroscience. In this lecture, I discuss two kinds of problems in machine consciousness.
The first problem is how to build a conscious machine based on considerations of possible functions of consciousness. What is the functional advantage of conscious computing as opposed to the unconscious zombie mode in the brain? This problem is related to the so-called access consciousness – the objectively verifiable aspect of consciousness. Here I argue that the ability to generate counterfactual sensory representations play a role in consciousness, and endows agents with flexible intelligence.
The second problem is how to prove the presence of a vivid and direct experience of the world and of the self within a machine, namely, phenomenal consciousness. Here, I argue that we can approach this problem using axiomatic theories such as, but not limited to, the integrated information theory of consciousness. In science, progresses have been made by extrapolating known laws and theories to conditions beyond the realm where they were established. This allows theories to make predictions about things we cannot directly observe. This is applicable for theories of consciousness originally developed for human consciousness, as they will be extrapolated to machine consciousness to make an inference as to their internal phenomenal experience.
I will discuss our current projects on these two issues taking place at Araya, Inc.
Lecture Slides: ISSA2017_0523AM.pdf
May 24 (Wed.)
Larissa Albantakis (University of Wisconsin-Madison)
Lecture Title: Integrated Information Theory of Consciousness: Introduction, Tutorial, and Extrapolations
Abstract: The Integrated Information theory of consciousness (IIT) has recently attracted attention among consciousness researchers. IIT stems from thought experiments that lead to phenomenological axioms and ontological postulates (intrinsic existence, composition, information, integration, and exclusion). According to IIT, an experience is a maximally integrated cause-effect structure, which in principle can be completely characterized, both in quantity and quality, by determining to what extent a system of causal mechanisms is irreducible to its parts. Many observations concerning the neural substrate of consciousness fall naturally into place within the IIT framework. Among them are the association of consciousness with certain neural systems rather than with others; the fact that neural processes underlying consciousness can influence or be influenced by neural processes that remain unconscious; the reduction of consciousness during dreamless sleep and generalized epileptic seizures; and the distinct role of different cortical architectures in affecting the quality of experience. The lecture will i) introduce the basic notions of IIT, and provide hands-on examples in which integrated information can be computed rigorously; ii) introduce measures of integrated information that can be applied to empirical data and discuss how they can be applied to evaluate the level of consciousness in wake, sleep, anesthesia, and disorders of consciousness; iii) demonstrate how integrated information grows in animats adapting to a complex environment, thereby shedding light on the evolution of consciousness; iv) consider the explanatory, predictive, and inferential power of IIT; and v) consider potential problems and future developments.
May 25 (Thu.)
Dan Zahavi (University of Copenhagen)
Lecture Title: Phenomenology of consciousness I - II
Phenomenology of consciousness I
I will start by giving a brief introduction to the history of phenomenology, and then move straight to a question of central concern. What is the phenomenological method and how is it employed in the study of consciousness? In answering these questions, I will criticize a number of prevalent misunderstandings, and also highlight the distinct philosophical character of phenomenology.
Phenomenology of consciousness II
In the second part, I will leave the more methodological discussion behind and instead focus on some concrete findings. What kind of insights can be found in phenomenology regarding the nature and structure of consciousness? How can phenomenology contribute to contemporary scientific investigations of consciousness? What are the prospects of a naturalized phenomenology?
- Zahavi, D.: "Phenomenology of reflection." In A. Staiti (ed.): Commentary on Husserl's Ideas I. Berlin: De Gruyter, 2015, 177-193.
- Zahavi, D.: "Naturalized Phenomenology: A Desideratum or a Category Mistake?" Royal Institute of Philosophy Supplement 72, 2013, 23-42.
May 26 (Fri.)
Jun Tani (KAIST)
Lecture Title: Exploring Robotic Minds: Emergentist Account for Non-Reductive Consciousness
Abstract: This talk proposes that the mind is comprised of emergent phenomena, which appear via intricate and often conflictive interactions between top-down intentional processes involved in proactively acting on the external world and bottom-up recognition processes involved in receiving the resultant perceptual reality. This view has been tested via a series of neurorobotics experiments employing predictive coding principles implemented in “deep” recurrent neural network (RNN) models. With the direct human tutoring of robots built on this model, robots develop the skills needed to generate complex actions, the concepts necessary for representing the world, and the potential for the linguistic competency required to express such experiences. Furthermore, these experiments confirm that “compositional” yet fluid thinking and acting develop with the spontaneous formation of a functional hierarchy in neurodynamic structures once proper constraints are established. Constraints include those on processing at multiple spatio-temporal scales, as well as those informed by tutoring at the level of behavioral interaction.
The talk highlights an account of free will, how it emerges and becomes the contents of consciousness, as related to the studies by Libet (1985). Deterministic chaos self-organizes in the higher level of the aforementioned deep RNN model, and this can cause spontaneous shifts in motor movement patterns generated in the lower level. In the other direction, intention in the higher level can be modified in a postdictive manner in the course of minimizing the prediction error generated through conflict with perceived reality. One important implication here is that one becomes consciously aware of one’s own intention for generating action via postdiction, when the intention originally unconsciously generated is modified in the face of possible conflicts due to embodiment or potential openness in the environment. Thus, a holistic dynamics of the mind emerges as the circular causality between these two poles, top-down subjective mind and bottom-up objective world. These two poles turn out to be inseparable, entangled in the ongoing embodiment of enacted (as well as simulated) trial and error as fibers weave together to form threads into the prospective future, as Merleau-Ponty has speculated. Looking forward, the essential interaction between self and world providing for consciousness and free will can be further clarified through the close examination of nonstationary characteristics emerging from normal operations of this essential dynamical structure.
- Tani, J. (2016). Exploring Robotic Minds: Actions, Symbols, and Consciousness as Self-Organizing Dynamic Phenomena. Oxford University Press.
Lecture Slides: ISSA2017_0526AM.pdf
- 09:30 - 10:30 Lecture 1
- 11:00 - 12:00 Lecture 2
- Afternoon: hands-on projects in 4 tracks (Psychophysics, MRI, MEG, Robotics)
May 29 (Mon.)
Shinji Nishimoto (CiNet)
Lecture Title: Deciphering brain activity under natural vision
Abstract: In our daily lives, we receive a massive stream of sensory inputs to make sense of the world. Understanding how our brains process natural complex inputs to generate objective and subjective experiences is a fundamental goal in systems neuroscience. In this talk, I introduce some of our recent studies to build predictive models (namely, encoding and decoding models) between natural visual experiences and the brain activity. Using the quantitative modeling approach, we aim to elucidate visual and semantic representations in the human brain and how such representations could be modified under various perceptual and cognitive conditions.
- Nishimoto S, Vu AT, Naselaris T, Benjamini Y, Yu B, Gallant JL. (2011) Reconstructing visual experiences from brain activity evoked by natural movies. Current Biology, 21(19):1641-1646.
- Çukur T, Nishimoto S, Huth AG, Gallant JL. (2013) Attention during natural vision warps semantic representation across the human brain. Nature Neuroscience, 16(6):763-770.
- Nishimoto S, Huth AG, Bilenko NY, Gallant JL. (2017) Eye movement-invariant representations in the human visual system. Journal of Vision. 17(1):11
Kaoru Amano (CiNet)
Lecture Title: Toward the neural cause of human visual perception
Abstract: We have been trying to unravel the neural causes of human visual perception and behavior. One of the promising techniques for this purpose is the fMRI decoded neurofeedback (DecNef), which can non-invasively induce neural activities corresponding to specific information (e.g. color and motion). In the first study, subjects implicitly learned to induce the BOLD signal pattern in V1/V2 corresponding to red color during the presentation of an achromatic vertical grating via DecNef training. After the training, an achromatic vertical grating was perceived to be reddish, indicating the associative learning of color and orientation in V1/V2. In the second part, we present an MEG experiment showing a functional role of alpha oscillation in visual processing. When borders defined by iso-luminant color change and those defined by luminance change are placed in close proximity, the color-defined boundary is perceived to be jittering at around 10 Hz (Amano et al., 2008). Comparison between the perceived frequency of illusory jitter and the intrinsic peak alpha oscillations (PAF) measured using magnetoencephalography (MEG) revealed that the inter- and intra-participant variations of the PAF are mirrored by an illusory jitter perception. More crucially, psychophysical and MEG measurements during amplitude-modulated current stimulation showed that the PAF can be artificially manipulated, which results in a corresponding change in the perceived jitter frequency. These results suggest the causal contribution of alpha oscillations in creating temporal characteristics of visual perception.
- Learning to Associate Orientation with Color in Early Visual Areas by Associative Decoded fMRI Neurofeedback. Amano K, Shibata K, Kawato M, Sasaki Y, Watanabe T. Curr Biol. 2016 Jul 25;26(14):1861-6
- Multivoxel neurofeedback selectively modulates confidence without changing perceptual performance. Cortese A, Amano K, Koizumi A, Kawato M, Lau H. Nat Commun. 2016 Dec 15;7:13669. doi: 10.1038/ncomms13669.
- Fear reduction without fear through reinforcement of neural activity that bypasses conscious exposure. Koizumi, A., Amano, K., Cortese, A., Shibata, K., Yoshida, W., Seymour, B.,Kawato, M. & Lau, H. Nature Human Behaviour 2016; 1, Article number: 0006
- Perceptual Cycles. VanRullen R. Trends Cogn Sci. 2016 Oct;20(10):723-35.
- Motion-induced spatial conflict. Arnold DH, Johnston A. Nature. 2003 Sep 11;425(6954):181-4.
Lecture Slides: ISSA2017_0529AM-2.pdf
May 30 (Tue.)
Noriko Yamagishi (CiNet)
Lecture Title: Neural correlates of attention and readiness
Abstract: Attention and readiness are closely related to consciousness. I will introduce series of visual attention and internal readiness studies, by using MEG and psychophysical techniques. It shows that attention modifies brain activities even before stimulus onsets and affects later behavioral task performance. Human internal readiness levels are also highly related to behavioral task performance and levels of readiness related brain modifications can predict such behavioral performance. I encourage students to think relationship between attention/readiness processes and consciousness together with other lectures.
Lecture Slides: ISSA2017_0530AM-1.pdf
Kenji Doya (OIST)
Lecture Title: Neural Circuit for Mental Simulation
Abstract: The basic process of decision making can be captured by learning of action values according to the theory of reinforcement learning. In our daily life, however, we rarely rely on pure trial-and-error and utilize any prior knowledge about the world to imagine what situation will happen before taking an action. How such “mental simulation” is realized in the circuit of the brain is an exciting new topic of neuroscience. Here I report our recent works with functional MRI in humans and two-photon imaging in mice to clarify how action-dependent state transition models are learned and utilized in the brain.
- Fermin AS, Yoshida T, Yoshimoto J, Ito M, Tanaka SC, Doya K (2016) Model-based action planning involves cortico-cerebellar and basal ganglia networks. Scientific reports 6:31378.
- Funamizu A, Kuhn B, Doya K (2016) Neural substrate of dynamic Bayesian inference in the cerebral cortex. Nature neuroscience 19:1682-1689.
May 31 (Wed.)
Yukie Nagai (Osaka University)
Lecture Title: Computational models for cognitive development
Abstract: My talk will present computational models that account for human cognitive development. Although behavioral studies have revealed developmental trajectories in infants, their underlying mechanisms remain poorly understood. We have been suggesting that predictive coding of human brain provides a unified account for cognitive development and have been proposing computational neural network models to demonstrate infant-like development in robots. Our experiments showed that a robot acquired the abilities of mirror neuron systems and mental simulation through multimodal predictive learning of sensorimotor signals. Temporal and spatial properties of predictive coding enabled the robot to associate multimodal signals and thus recall imaginary signals from actual ones. Potentials of the proposed models to account for developmental disorders as well as typical development will be discussed to show our future research direction.
- http://ieeexplore.ieee.org/document/7479539/?reload=true&arnumber=7479539 arnumber=7479539
Lecture Slides: ISSA2017_0531AM-1.pdf
Hiroshi Ishiguro (Osaka University)
Lecture Title: Studies on teleoperated androids
Abstract: Geminoid is a teleoperated android of an existing person that can transfer the human presence to the distant place. And at the same time, the operator accepts the Geminoid body as own body. This is called body ownership transfer. This lecture discusses on the scientific issues and the application on the teleoperated androids.
Lecture Slides: ISSA2017_0531AM-2.pdf
June 1 (Thu.)
Mariko Osaka (CiNet)
Lecture Title: The Neural bases of Working Memory
Abstract: Working memory refers to the capacity-constrained active memory in which information is temporarily maintained and concurrently processed for the use in an ongoing goal-directed activity(Baddeley, 1986). These dual processes are crucially required for higher cognitive brain functions such as reading text or talking to each other. While reading the text, incoming information is decoded perceptually, reorganized and integrated with the contextual interpretation, and the constituent products of each of these processes are stored for a short period. At that time, working memory is important in storing the intermediate and final products of successive data, allowing the reader to integrate the contents and place the text words into context.
Using reading span test (RST), which measures the working memory capacity to memorize the last words of sentences during reading, the individual differences in working memory capacity can be measured. The estimates of RST are thought to be highly correlated with language comprehension and the contents measured by the RST are similar to the function of central executive system.
Using fMRI, neural basis of central executive system of working memory is measured and found to be located in the dorsolateral prefrontal cortex (DLPFC), the anterior cingulate cortex (ACC) and posterior parietal cortex (PPC): DLPFC plays a role in providing top-down support for attention maintenance in task-appropriate behaviors. The ACC mediates the inhibition of a preprogrammed response so as to release any conflict and PPC contribute to shifting and focusing attention. Moreover, the individual difference in working memory capacity shows that the activation differences in these regions lead their capacity differences.
- Baddeley. A. (1986). Working memory. Oxford: Oxford University Press.
- Osaka, M. (2016). Working Memory as a Basis of Consciousness H. Ishiguro, M. Osaka, T. Fujikado, M. Asada, & M. Kasaki (Eds.), Cognitive Neuroscience Robotics B. Springer, pp.39-57
- Osaka, M., & Osaka, N. (2007). Neural basis of focusing attention in working memory. An fMRI study based on individual differences. In N. Osaka, R. H. Logie, & M. D'Esposito (Eds.), The cognitive neuroscience of working memory: Behavioral and neural correlates. Oxford University Press, pp. 99-117
Lecture Slides: ISSA2017_0601AM-1.pdf
Piet Hut (Institute for Advanced Study, ELSI, YHouse)
Lecture Title: YHouse: a new research institute in New York City
Abstract: YHouse (https://yhousenyc.org/) is a initiative in Manhattan, for the start of an interdisciplinary center focused on both research and outreach, around the central theme of awareness (or consciousness, cognition, intelligence). I will describe the research structure of YHouse, which will be centered around two problems, both connected with the explosive growth of our knowledge in neuroscience and in. machine learning. The first problem is how to synthesize all this new knowledge, and the second problem, to let that integrated knowledge ripen into new forms of insight, sorely needed for our survival.
Our solution to the first problem is to take a long view, in three parts: past, present and future. We will trace awareness from its biological roots, four billion years ago; through its cultural roots, the origins of human civilization and its ongoing transformations; to its technological roots that are being forged while we watch, in the near future.
Our solution to the second problem is to reflect on this long view, on two levels. First, we will use philosophy, to compare and contrast developments in the current decade with what we have learned in the last few centuries. Second, we will throw a wider net by initiating dialogues with, and comparative studies of, the great wisdom traditions of the past.