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CfP: Call for Paper Frontiers in Neuroscience: Special Issue "Graph Learning for Brain Imaging"
by Feng Liu 25 Aug '21

25 Aug '21

Dear Colleagues, We are writing to you know that we are organizing a special issue "Graph Learning for Brain Imaging" in Frontiers in Neuroscience (impact factor 4.7). We believe this is a timely special issue to showcase the new developments using graph representation, deep learning on graph-structured data to address important brain imaging and computational neuroscience problems. *Link*: https://www.frontiersin.org/research-topics/23683/graph-learning -for-brain-imaging *Keywords*: Brain Networks, Graph Neural Networks, Brain Imaging, Graph Embedding, Multi-Modal Imaging. *Topics*: We are looking for original, high-quality submissions on innovative research and developments in the analysis of brain imaging using graph learning techniques. Topics of interest include (but are not limited to): • Graph neural networks (GNN) for network neuroscience applications • Graph neural network for brain mapping and data integration • Graph convolution network (GCN) for brain disorder classification • (Dynamic) Functional brain networks • Brain networks development trajectories • Graphical model for brain imaging data analysis • Spatial-temporal brain network modeling • Graph embedding and graph representation learning • Information fusion for brain networks from multiple modalities or scales (fMRI, M/EEG, DTI, PET, genetics) • Generative graph models in brain imaging • Brain network inference: scalable, online, and from non-linear relationships • Machine learning over graphs: kernel-based techniques, clustering methods, scalable algorithms for brain imaging • A few-shot learning for learning from limited brain data • Graph federated learning for brain imaging *Important Dates*: Abstract: 30-Sep-2021 Full paper: 30-Dec-2021 *Background:* Unprecedented collections of large-scale brain imaging data, such as MRI, PET, fMRI, M/EEG, DTI, etc. provide a unique opportunity to deepen our understanding of the brain working mechanisms, improve prognostic predictions for mental disorders, and tailor personalized treatment plans for brain diseases. Recent advances in machine learning and large-scale brain imaging data collection, storage, and sharing lead to a series of novel interdisciplinary approaches among the fields of computational neuroscience, signal processing, deep learning, brain imaging, cognitive science, and computational psychiatry, among which graph learning provides a valuable means to address important questions in brain imaging. Graph learning refers to designing effective machine learning and deep learning methods extracting important information from graphs or exploiting the graph structure in the data to guide the knowledge discovery. Given the complex data structure in different imaging modalities as well as the networked organizational structure of the human brain, novel learning methods based on graphs inferred from imaging data, graph regularizations for the data, and graph embedding of the recorded data, have shown great promise in modeling the interactions of multiple brain regions, information fusion among networks derived from different brain imaging modalities, latent space modeling of the high dimensional brain networks, and quantifying topological neurobiomarkers. The goal of this Research Topic is to synergize the start-of-the-art discoveries in terms of new computational brain imaging models and insights of brain mechanisms through the lens of brain networks and graph learning. --On Behalf of all the Guest Editors Feng Liu, Stevens Institute of Technology, Hoboken, NJ, USA Yu Zhang, Lehigh University, Bethlehem, PA, USA Jordi Solé-Casals, Universitat de Vic - Universitat Central de Catalunya, Barcelona, SpainIslem Rekik, Istanbul Technical University, Istanbul, TurkeyYehia Massoud, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia Best regards Feng Liu

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WWNeuRise series on predictive processing (Sept-Oct 2021)
by William Podlaski 24 Aug '21

24 Aug '21

WorldWideNeuRise will host several online talks throughout September-October on the topic of predictive processing from the following speakers (titles TBA): Wednesday, 8 September, 5pm CET Caroline Jahn (Buschman Lab, Princeton University) Ramon Bartolo (Averbeck Lab, National Institute of Mental Health) Wednesday, 22 September, 5pm CET Nick Audette (Schneider Lab, New York University) Colleen J. Gillon (Richards Lab, Mila & McGill University) Wednesday, 6 October, 5pm CET Nuttida Rungratsameetaweemana (Sejnowski Lab, UCSD & Salk Institute) Oded Bein (Niv Lab, Princeton University) Wednesday, 20 October, 5pm CET Selina Solomon (Growth Intelligence) Tomaso Muzzu (Saleem Lab, University College London) For more information, please visit our website (https://neurise.github.io/) find us on WorldWideNeuro (https://www.world-wide.org/Neuro/WWNeuRise/) or follow us on Twitter (https://twitter.com/WWNeuRise) We are actively searching for PhD students and postdocs to give talks in our upcoming seminar blocks. On our website (https://neurise.github.io/) you can find an application form to directly apply, as well as a recommendation form, where you can suggest individuals from your lab, institute, or otherwise who you think might have an interesting story to tell! We are looking forward to seeing you at our upcoming seminars! The organising committee, Ellen Boven (Apps lab, University of Bristol) Christina Buetfering (Häusser lab, University College London) Lucie Descamps (Kentros lab, Norwegian University of Science and Technology) Gily Ginosar (Ulanovsky lab, Weizmann Institute) Loreen Hertäg (Clopath lab, Imperial College London) Joram Keijser (Sprekeler lab, TU Berlin) Bill Podlaski (Machens lab, Champalimaud Research)

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Reminder (one week left): Call for papers: Symposium on Mathematics of Neuroscience
by Ruairidh McLennan Battleday 23 Aug '21

23 Aug '21

Two decades into the 21st century, can we claim to be any closer to a unified model of the brain? In this exploratory symposium, we invite submissions for short talks and posters presenting general mathematical models of brain function. We give priority to those models that account for brain or behavioural data, or provide simulations to that effect. The symposium will be held at the applied mathematics conference ICNAAM 2021, to be held virtually and in person on the island of Rhodes, Greece from the 20-26th of September 2021. Submission is by 250-word abstract before the 30th August, sent to the organizers Prof Dan V. Nicolau Jr ( dan.nicolau(a)qut.edu.au) and Dr Ruairidh M. Battleday ( battleday(a)princeton.edu) We already have a great lineup (www.neuromonster.org) and with one week left until the deadline for the abstract submission encourage any remaining interested parties to apply. Ruairidh and Dan -- Dr. Ruairidh McLennan Battleday, BMBCh (Oxon) MA PhD Candidate and Cognitive Science Fellow Computational Cognitive Science Lab, Department of Computer Science Princeton University Department of Statistics St John's College University of Oxford

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[meetings] 2nd SMILES workshop, Aug 31st: Sensorimotor Interaction, Language and Embodiment of Symbols
by Xavier Hinaut 21 Aug '21

21 Aug '21

* WHAT The SMILES workshop is about Sensorimotor Interaction, Language and Embodiment of Symbols (SMILES). It is a satellite event from the ICDL 2020 (International Conference on Developmental Learning). * WHEN Tuesday 31st of August 2021. Planned schedule (it might change): 9am - 8.30pm CEST (UTC+2). * WHERE Online event on Zoom. (Link sent to registered people the day before, see LINKS section) * WHO 8 Invited speakers from multiple fields: neurolinguistics, speech communication, language evolution, developmental science, social robotics, computational neuroscience, language acquisition. - Morten Christiansen, Cornell University, NY, USA & Aarhus University, Denmark - Kaya de Barbaro, University of CaliforniaSan Diego, USA - Cynthia Matuszek, University of Maryland, Baltimore County, USA - Yair Lakretz, NeuroSpin Center, Gif sur Yvette, France - Harm Brouwer, Saarland University, Germany - Jean-Luc Schwartz, Gipsa lab, Grenoble-Alpes University, France - Daniel Dor, Tel Aviv University, Israel - Lauren Emberson, University of British Columbia, Canada * LINKS - ** Website **: https://sites.google.com/view/smiles-workshop/home <https://sites.google.com/view/smiles-workshop/home> - ** Registration is free but mandatory **: https://forms.gle/tyvMdbb8UJFyXZky8 <https://forms.gle/tyvMdbb8UJFyXZky8> - Contact: smiles.conf(a)gmail.com <mailto:smiles.conf@gmail.com> - ICDL conference website: https://icdl-2021.org/ <https://icdl-2021.org/> * WHAT+ (Short Description) On the one hand, models of sensorimotor interaction are embodied in the environment and in the interaction with other agents. On the other hand, recent Deep Learning development of Natural Language Processing (NLP) models allow to capture increasing language complexity (e.g. compositional representations, word embedding, long term dependencies). However, those NLP models are disembodied in the sense that they are learned from static datasets of text or speech. How can we bridge the gap from low-level sensorimotor interaction to high-level compositional symbolic communication? The SMILES workshop will address this issue through an interdisciplinary approach involving researchers from (but not limited to): - Sensori-motor learning, - Emergent communication in multi-agent systems, - Chunking of perceptuo-motor gestures (gestures in a general sense: motor, vocal, ...), - Sensori-motor learning, - Symbol grounding and symbol emergence, - Compositional representations for communication and action sequence, - Hierarchical representations of temporal information, - Language processing and acquisition in brains and machines, - Models of animal communication, - Language evolution, - Understanding composition and temporal processing in neural network models, and - Enaction, active perception, perception-action loop. SMILES workshop organisers - Xavier Hinaut, Inria, Bordeaux, France - Clément Moulin-Frier, Inria and Ensta ParisTech, Bordeaux, France - Silvia Pagliarini, Inria, Bordeaux, France - Michael Spranger, Sony AI and Sony CSL, Tokyo, Japan - Tadahiro Taniguchi, Ritsumeikan University, Kyoto, Japan - Anne S. Warlaumont, University of California, Los Angeles, America - Junpei Zhong, Nottingham Trent University, Nottingham, United Kingdom Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Université de Bordeaux Institut des Maladies Neurodégénératives www.xavierhinaut.com <http://www.xavierhinaut.com/>

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Postdoc and PhD Positions in Computational Cognitive Neuroscience at UKE - Hamburg
by Stefano Panzeri 20 Aug '21

20 Aug '21

The Panzeri and Donner laboratories at the University Medical Center Hamburg-Eppendorf (UKE) aim to fill joint postdoc and PhD positions starting at any time. The vacant positions are for collaborative projects in computational cognitive neuroscience, and funding is available for several years. Applications will be reviewed when they are received until positions are filled. Both labs aim to understand how higher brain functions such as sensation, perception, decision-making, and memory, emerge from the interactions between brain areas and/or populations of neurons within these areas. These topics are studied in the healthy brain and in neuropsychiatric disorders, and they are addressed through a tight interplay between theoretical and experimental approaches. Joint ongoing work focuses on how feedforward and feedback communication across the cortical hierarchy, excitation-inhibition balance, and neuromodulatory processes, shape decision-making. The Panzeri Lab, newly established at UKE Hamburg, is a theoretical lab which develops advanced mathematical tools for brain data analysis, applies these methods to real data to produce new results on neural information processing, and develops biophysically plausible neural network models of how information is processed in the brain. The Donner lab is an experimental lab that combines pharmacological intervention, psychophysics, eye-tracking, and neuroimaging (MEG and fMRI) in human subjects with advanced data analysis and computational modeling tools to uncover signatures and mechanisms of cognitive computation. The new lab members will join existing teams with extensive expertise in both computational and experimental neuroscience. The new lab members will also benefit from both labs’ extensive international collaborations including Harvard Medical School, Italian Institute of Technology, Baylor College of Medicine, Cornell University, École Normale Supérieure, New York University, Pompeu Fabra University, University of Pennsylvania, SISSA and others. We seek applications from qualified individuals from all demographics, genders, and backgrounds. Both labs are committed to diversity, highly international, and operate in English. Hamburg is a vibrant, international, family-friendly, and green city. It hosts one of the world’s largest harbours, an internationally acclaimed concert hall, a large lake, and dozens of canals, lots of beautiful parks, and many other nice places for leisure time. The UKE also has excellent family-friendly facilities. Candidates should have a solid background in numerate sciences and a keen interest in applying advanced mathematical concepts to reveal the function of the brain. Experience in quantitative or computational neuroscience is a major plus. The main criterion, however, is a commitment to scientific excellence. Applications (full CV, statement of research interest and name and contact of 2 referees) should be sent to t.donner(a)uke.de , stefano.panzeri(a)gmail.com Further information on both labs can be found here: http://www.tobiasdonner.net https://www.uke.de/english/departments-institutes/institutes/department-of-… Recent relevant publications of the labs include: Pfeffer, T. et al (2021), Circuit mechanisms for the chemical modulation of cortex-wide network interactions and behavioral variability*. *Science Advances 7: eabf5620 Valente, M., et al (2021), Correlations enhance the behavioral readout of neural population activity in association cortex. Nature Neuroscience, 24, 975–986 Murphy P., et al (2021), Adaptive circuit dynamics across human cortex during evidence accumulation in changing environments. Nature Neuroscience 7: 987-997. Wilming N., et al (2020), Large-scale dynamics of decision information across human cortex. Nature Communications 11: 5109. Chong, E. et al (2020) Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception. Science 368, 1329. Runyan C. A., et al (2017) Distinct timescales of population coding across cortex, Nature: 548: 92-96. Stefano Panzeri, Professor of Neural Information Processing Tobias H. Donner, Professor of Integrative Neuroscience University Medical Center Hamburg-Eppendorf

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Faculty research fellowships ('tenure-track') available at the University of Nottingham
by Marcus Kaiser 19 Aug '21

19 Aug '21

Dear all, New recruitment round launched for Nottingham Research and Anne McLaren Fellowship schemes! Join a cohort of ambitious and exceptional early-career researchers. Generous funding, research expenses, childcare costs, leadership mentoring + more. We have two schemes, each offering the same package of support: - *Anne McLaren Fellowships* are aimed at outstanding female postdoctoral researchers in science, technology, engineering and medicine, who are at the early stage of their academic careers and wish to establish a research career in the UK - *Nottingham Research Fellowships* are aimed at outstanding postdoctoral researchers who are at the early stage of their academic careers from all academic disciplines represented at the university We offer: - three years’ independent research funding, covering salary costs at c. £40,000-49,000 - *the link to a permanent academic post, subject to performance* - additional funding for research expenses totalling £75,000 - childcare costs of up to £15,000 - access to mentoring, career development and networking with the wider fellowship community Find out more at: https://www.nottingham.ac.uk/research/researchwithus/fellowships/nottingham… Nottingham “the home of MRI” offers an excellent environment for imaging ( https://www.nottingham.ac.uk/research/beacons-of-excellence/precision-imagi… and https://www.nottingham.ac.uk/research/groups/spmic/index.aspx ), is pioneering the use of neurotechnology for brain disorders ( http://mindtech.org.uk/ ), hosts the Institute of Mental Health ( https://www.institutemh.org.uk ), and has a large group of faculty members including four full professors (Stephen Coombes, Mark van Rossum, Mark Humphries, Marcus Kaiser) in the area of computational/mathematical neuroscience. Please contact me if you want to find out more about how your research might fit in with our priorities of connectomics, brain stimulation, neurotechnology, neuroimaging, and computational/mathematical neuroscience. Best, Marcus -- *Marcus Kaiser, Ph.D. FRSB* @ConnectomeLab <https://twitter.com/ConnectomeLab> *Professor of Neuroinformatics* *Precision Imaging Beacon, School of Medicine, University of Nottingham* Guanci Visiting Professor Rui Jin Hospital, Shanghai Jiao Tong University, China Book: Changing Connectomes https://mitpress.mit.edu/books/changing-connectomes Lab website: http://www.dynamic-connectome.org/ Neuroinformatics UK: http://www.neuroinformatics.org.uk/

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PhD position: Molecular basis of synaptic plasticity and consolidation
by Fauth, Michael 18 Aug '21

18 Aug '21

Apologies for cross-postings. The Institute of Biophysics at the Georg-August-Universität Göttingen is looking to fill a Ph.D. position (German Salary Scale TV-L E13, 66% of 39.8 weekly hours) for 3 years to work on theoretical models of the molecular underpinnings of (structural) synaptic plasticity and consolidation. This post is designed to foster young researchers and give the successful applicant the opportunity to pursue a doctoral degree. The position should be filled by September 15th 2021 or soon thereafter. Suitable candidates should hold a Master in Physics, Mathematics, Computer Science or comparable subjects, preferably with some additional experiences in Computational Neuroscience, Geometrical Modeling and Stochastic Processes. We expect excellent mathematical and coding skills (e.g., Python, Matlab, C++) as well as skills in scientific communication (including proficiency in English). The candidate should be curious, highly motivated, self-organized, and show a keen interest to work in a lively research team, collaborate with experimental research labs and to perform leading-edge research. The positions will be affiliated with the groups of Dr. Michael Fauth and Prof Florentin Wörgötter, who are investigating the emergence of stable behavior like memory and computation in the presence of a continuously changing biological substrate (see, e.g., Fauth & van Rossum, eLife, 2019; Bonilla-Quintana et al., Scientific Reports 2021). The aim of the research project is to model the dynamics of the synaptic scaffolding protein actin as well as its influence on synapse geometry during and after synaptic plasticity, exploring a possible molecular mechanism for the consolidation of synaptic changes. The project is embedded in and funded through the Collaborative Research Center 1286 “Quantitative Synaptology” (German Science Foundation). Consequently, the successful candidate will also be involved and pursue an active collaboration with experimental partners within the CRC. The Göttingen Campus is a leading center of neuroscience in Europe hosting numerous internationally renowned research institutions, including the University and its Medical Center, the three life science Max Planck Institutes, the European Neuroscience Institute, the German Primate Center, and the Bernstein Center for Computational Neuroscience (BCCN) Göttingen. For more information, consult the official announcement at https://www.uni-goettingen.de/de/2794.html?cid=15701

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Call for papers: Symposium on Mathematics of Neuroscience
by Ruairidh McLennan Battleday 17 Aug '21

17 Aug '21

Symposium on the Mathematics of Neuroscience. ICNAAM, Rhodes, 20-26th September 2021. Two decades into the 21st century, can we claim to be any closer to a unified model of the brain? In this exploratory symposium, we invite submissions for short talks and posters presenting general mathematical models of brain function. We give priority to those models that account for brain or behavioural data, or provide simulations to that effect. The symposium will be held at the applied mathematics conference ICNAAM 2021, to be held virtually and in person on the island of Rhodes, Greece from the 20-26th of September 2021 (www.neuromonster.org) Submission is by 250-word abstract before the 30th August, sent to the organizers Prof Dan V. Nicolau Jr (dan.nicolau(a)qut.edu.au) and Dr Ruairidh M. Battleday ( battleday(a)princeton.edu) -- Dr. Ruairidh McLennan Battleday, BMBCh (Oxon) MA Cognitive Science Fellow Computational Cognitive Science Lab, Department of Computer Science Princeton University Department of Statistics St John's College University of Oxford

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Assistant Professor in Cognitive Neuroscience of Aging at UC Riverside
by Aaron Seitz 16 Aug '21

16 Aug '21

Cognitive Neuroscience of Aging in the UCR Psychology Department Tenure-Track Assistant Professor The Department of Psychology at the University of California, Riverside invites applications for a tenure-track assistant professor position with a focus on Cognitive Neuroscience of Aging beginning July 1, 2022. We seek applicants who investigate individual differences, as well as diverse populations, in cognitive and neural mechanisms of aging. We are particularly interested in candidates whose research will benefit from the social, ethnic, and linguistic diversity of Southern California’s aging population. Specific topics of research can address any area of cognitive psychology that will add to or complement our existing research specializations in perception, action, learning, memory, language, and experience-driven change. We are further interested in candidates whose research includes quantitative methods such as computational neuroscience; uses neuroimaging methodologies; makes connections between human, animal, and computational perspectives of cognition; and/or makes connections with the Developmental, Social/Personality, and/or Behavioral Neuroscience areas of the Department. Applicants should be committed to excellence in undergraduate and graduate education, and interest in teaching courses related to cognitive neuroscience, aging, cognition, and quantitative methods is desirable. Review of applications will begin on 11/15/2021 and will continue until the position is filled. Candidates who apply by this date will be given full consideration. The University of California, Riverside is a world-class research university with an exceptionally diverse undergraduate and graduate student body (http://diversity.ucr.edu/)<http://diversity.ucr.edu/>. Its mission is explicitly linked to providing routes to educational success for underrepresented and first-generation college students. A commitment to this mission is a preferred qualification. The department is particularly interested in candidates who have experience working with students from diverse backgrounds and a demonstrated commitment to improving access to higher education for underrepresented students. The campus is surrounded by mountain ranges and is only an hour away from ski slopes, surfing, and hiking in mountain and desert environments. It boasts a fully-accredited child care facility and maintains a commitment to “family friendly” policies and programs. A Ph.D. in psychology, neuroscience or a related discipline is required at the time of appointment, and relevant postdoctoral experience and significant publications are expected. Salary level will be competitive and commensurate with qualifications and experience. Advancement through the faculty ranks at the University of California is through a series of structured, merit-based evaluations, occurring every 2-3 years, each of which includes substantial peer input. Applications must include a cover letter, curriculum vita, statements of research and teaching interests, reprints and preprints, a statement of contributions to diversity, and three letters of recommendation. All application materials must be submitted through AP Recruit at: https://aprecruit.ucr.edu/apply/JPF01442. For more information about the position, please contact the Search Committee Chair, Dr. Aaron Seitz, Department of Psychology, at aseitz(a)ucr.edu<mailto:aseitz@ucr.edu>. UCR is a world-class research university with an exceptionally diverse undergraduate student body. Its mission is explicitly linked to providing routes to educational success for underrepresented and first-generation college students. A commitment to this mission is a preferred qualification. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified candidates will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic protected by law. -Aaron ************************************************** Aaron Seitz, Ph.D. Professor of Psychology Director of UCR Brain Game Center Director of UCR Aging Initiative Campbell Endowed Term Chair for Research Excellence and Undergraduate Research Mentoring University of California, Riverside 900 University Ave. Riverside, CA 92521 Ph: (951) 827-6422 Fax: (951) 827-3985 Email: aseitz(a)ucr.edu<mailto:aseitz@ucr.edu> Web: http://faculty.ucr.edu/~aseitz/ BGC: http://braingamecenter.ucr.edu<http://braingamecenter.ucr.edu/> **************************************************

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Call For Participation - Workshop on Spatio-temporal Aspects of Embodied Predictive Processing - StEPP @ ICDL2021 - 22.08.2021
by Stefan Heinrich 15 Aug '21

15 Aug '21

Call For Participation - Workshop on Spatio-temporal Aspects of Embodied Predictive Processing - StEPP @ IEEE ICDL2021 Schedule and Venue Date: 22. August 2021, 13:30-18:00h (GMT+8) Location: Online (Details will be announced on the website) All details and full schedule: https://sites.google.com/view/stepp21 Aims and Scope: Understanding human intelligence and building strong AI systems is a key challenge for our generation. A particularly puzzling aspect is that the human brain seems to cope very well with the highly variable and uncertain nature of perception and action, regarding both their signal characteristic and how they extend over time. Furthermore, it seems apparent that the information processing in the brain always involves previous bodily experiences and all our senses, thus is embodied and crossmodal. For explaining these characteristics, there are strong accounts that the brain is constantly predicting sensory input and feedback while minimising free energy in the prediction and is hierarchically abstracting the perception as well as hierarchically composing action. Furthermore, it is also hypothesised that mechanistic priors in the brain’s information processing induce a failure of hierarchical inference in the brain, accounting for atypical perception and action of psychiatric disorders. For example, some brains might have developed to focus too strongly on current sensory input while others might focus too strongly on memorised previous experience. A typically developed brain, in contrast, would show a fine balance compared to these two extreme priors. The big open mystery is: how is the brain developing this on a mechanistic level and thus how can this get learned within an AI system? Thus, to lift this mystery, we further need to bring together research from computational neuroscience, cognitive psychology, and artificial intelligence. With this workshop, we particularly want to wrap up different recent hypotheses, models, and experiments and discuss in-depth how to shape future imaging, behavioural, and developmental robotics studies as a complement to computational modelling and bio-inspired artificial intelligent algorithms. As a guiding theme, we aim to approach the following central questions: - How does the brain learn spatio-temporal stochasticity in perception and action? - What is the role of priors in learning spatio-temporal adaptive prediction? - How can developmental robotics help us to study spatio-temporal stochasticity as an analogy to infant learning? We examine these questions with the insight from invited key speakers from complementary fields as well as original contributions in breakout sessions in order to conclude the next steps within a panel discussion. Keynotes/Panellists and topics: - Jun Tani, Cognitive Neurorobotics, Okinawa Institute of Science and Technology (OIST) An analysis of meta-level cognitive processes of a variational recurrent neural network model when acting with the environment. - Marcel van Gerven, Artificial Cognitive Systems, Donders Institute, Radboud University How can the brain match the unreasonable effectiveness of backpropagation? - Takuya Isomura, Brain Intelligence Theory, RIKEN Center for Brain Science Reverse engineering Bayesian aspect of canonical neural networks. - Takamitsu Watanabe, Brain Network Dynamics, International Research Center for Neurointelligence (IRCN), The University of Tokyo Global and local brain dynamics underlying typical and atypical human intelligence. Organisers: Stefan Heinrich, IRCN, The University of Tokyo, Japan Shingo Murata, Dept. Electronics and Electrical Engineering, Keio University, Japan Yukie Nagai, IRCN & Institute for AI and Beyond, The University of Tokyo, Japan Yuichi Yamashita, National Center of Neurology and Psychiatry, Japan -- ************************************************************* Dr. Stefan Heinrich Postdoctoral Project Researcher Cognitive Developmental Robotics Lab The University of Tokyo, Institutes for Advanced Studies, International Research Center for Neurointelligence Email: heinrich.stefan(a)ircn.jp https://developmental-robotics.jp/en/members/stefan_heinrich/ https://ircn.jp/en/ https://stefanheinrich.net/ *************************************************************

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