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1st EBRAINS National Node Germany Workshop ***26.09.2023 in Berlin, Germany***
by Frings, Maren 10 Aug '23

10 Aug '23

Dear Colleagues, We would like to kindly invite you to participate the 1st EBRAINS National Node Germany Workshop which will take place on September 26, 2023 in Berlin from 09:00-13:30 CET. Guest Speakers: Dr. Seán Froudist-Walsh, University of Bristol Prof. Dr. Thomas Wachtler, Ludwig-Maximilians-University Munich Prof. Dr. Lena Oden, FernUni Hagen & FZ Jülich Prof. Dr. Bryan Strange, Technical University Madrid Dr. Andreas Rowald, Friedrich Alexander University Erlangen-Nürnberg Prof. Dr. Petra Ritter, Charité Universitätsmedizin Berlin Prof. Dr. Thanos Manos, Cergy Paris University For further details and for registration please browse to our <https://flagship.kip.uni-heidelberg.de/jss/HBPm?m=SgD&mI=254> event website. The EBRAINS National Node Germany (NNG) invites to the 1st EBRAINS NNG Workshop as a back-to-back event of the Bernstein Conference 2023 in Berlin, Germany. You will hear about the EBRAINS RI, its usage, an Expert Discussion on Digital tools to bridge the gap between experimental and computational neuroscience and will have the opportunity to network during our NNG lunch. <https://ebrains.eu> EBRAINS is a unique digital Research Infrastructure (RI), created by the EU-funded Human Brain Project. It is an open platform providing an extensive range of data and tools to enhance brain-related research. EBRAINS is a pan-European distributed network of services, that will in the future be organized through National Nodes. The <https://www.ebrains.eu/national-nodes/germany> EBRAINS NNG currently encompasses about 40 universities and research institutions across Germany joining forces to develop a common scientific and technical strategy, addressing the major scientific challenges of our time. The EBRAINS NNG partners offer unique services, including science liaison activities, for basic neuroscience, medical applications, and industry in the fields of: * High-Performance Computing * Neuromorphic Computing * Artificial Intelligence * Simulation * Robotics * Information privacy and security Programme Committee: Nicola Palomero-Gallagher, Petra Ritter, Fabrice Morin, Francesca Cavallaro, Björn Kindler, Sandra Diaz, Maren Frings In case of further questions please dont hesitate to contact ebrains-nng(a)fz-juelich.de <mailto:ebrains-nng@fz-juelich.de> Kind regards Maren Frings on behalf of the Programme Committee Dr. Maren Frings Project Manager, EBRAINS National Node Germany Jülich Supercomputing Centre Institute for Advanced Simulation Tel +49 2461 61-6431 Fax +49 2461 61-6656 <http://www.fz-juelich.de/ias/jsc> www.fz-juelich.de/ias/jsc ------------------------------------------------------------------- Forschungszentrum Jülich GmbH 52425 Jülich Sitz der Gesellschaft: Jülich Eingetragen im Handelsregister des Amtsgerichts Düren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Stefan Müller Geschäftsführung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Dr. Ir. Pieter Jansens, Prof. Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior -------------------------------------------------------------------

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Integrative Biophysics Group Opportunities
by Ahmed Elhady 06 Aug '23

06 Aug '23

The Integrative Biophysics group (https://twitter.com/IntBioPhysics ) headed by Dr. Ahmed Elhady at the Cluster for Advanced study of collective behavior in the university of Konstanz , focuses on understanding theoretical foundations of biophysical phenomena from excitability up to social foraging. The group is part of the Cluster for Advanced Study of Collective behavior. We are a *Cluster of Excellence* within the Excellence Strategy of the German Federal and State Governments. Being a cooperation between the University of Konstanz and the Max Planck Institute of Animal Behavior, we use the extensive expertise in the region to create an interdisciplinary environment for the study of collective behaviour that is unique worldwide. "The Centre for the Advanced Study of Collective Behaviour" is dedicated to the study of collective behaviour across a variety of species and across different organizational levels. For more information on the Cluster of Excellence, please visit: Collective Behaviour | exc.uni-konstanz.de <https://www.exc.uni-konstanz.de/collective-behaviour/>. There are several opportunities to do research with us at the Integrative Biophysics group : 1. Postdoctoral position focused on theoretical analysis of social foraging involving theoretical modeling and advanced data analysis ( deadline: September 15th) . For more details , please check this : https://stellen.uni-konstanz.de/jobposting/4418ec7f80f7b2371d7a0e963fab434a… 2. Postdoctoral fellowships: we are very happy to discuss potential fellowship proposals relating to theoretical biophysics of collectives ( from cells to animals) that we can host in our group. Get in touch to discuss your ideas ! 3. University of Konstanz offers this unique independent postdoctoral fellowship ( deadline: October 10th), check it out here: https://www.uni-konstanz.de/zukunftskolleg/fellowships/postdoctoral-fellows… . If you are granted this fellowship, you can have a collaboration with us at the Integrative biophysics group. To get in touch and discuss ideas and potential projects, please email Dr. Ahmed elhady at : ahmed.el-hady(a)uni-konstanz.de All the best regards, Ahmed Elhady Dr. Ahmed El Hady Research Group Leader Cluster for Advanced Study of Collective Behavior Max Planck Institute of Animal Behavior Universitätsstraße 10, 78464 Konstanz Room ZT 907 Postbox 687 Tel.: +49 7531 88-4742

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Re: ChatSOME: A neural model of how children learn language meanings
by Grossberg, Stephen 05 Aug '23

05 Aug '23

Dear Comp-Neuro colleagues, I am writing to call your attention to an article that I just published Open Access which is relevant to many current themes in neural modeling: Grossberg, S. (2023). How children learn to understand language meanings: A neural model of adult–child multimodal interactions in real-time. Frontiers in Psychology, August 2, 2023. Section on Cognitive Science, Volume 14. https://doi.org/10.3389/fpsyg.2023.1216479 Here is its Abstract: ++++++++++++++++++++++ This article describes a biological neural network model that can be used to explain how children learn to understand language meanings about the perceptual and affective events that they consciously experience. This kind of learning often occurs when a child interacts with an adult teacher to learn language meanings about events that they experience together. Multiple types of self-organizing brain processes are involved in learning language meanings, including processes that control conscious visual perception, joint attention, object learning and conscious recognition, cognitive working memory, cognitive planning, emotion, cognitive-emotional interactions, volition, and goal-oriented actions. The article shows how all of these brain processes interact to enable learning of language meanings to occur. The article also contrasts these human capabilities with AI models like ChatGPT. The current model is called the ChatSOME model, where SOME abbreviates Self-Organizing Meaning. +++++++++++++++++++++++++++++++++ These contributions build upon results that are described in my recently published Magnum Opus: Conscious Mind, Resonant Brain: How Each Brain Makes a Mind https://www.amazon.com/Conscious-Mind-Resonant-Brain-Makes/dp/0190070552 that I wrote to be self-contained and non-technical in a conversational style for the general public. Best, Steve Stephen Grossberg Wang Professor of Cognitive and Neural Systems Director, Center for Adaptive Systems Emeritus Professor of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering Boston University sites.bu.edu/steveg/ steve(a)bu.edu<mailto:steve@bu.edu> http://en.wikipedia.org/wiki/Stephen_Grossberg http://scholar.google.com/citations?user=3BIV70wAAAAJ&hl=en https://sites.bu.edu/steveg/files/2021/08/Grossberg-CV-8-14-21.pdf https://youtu.be/9n5AnvFur7I https://www.youtube.com/watch?v=_hBye6JQCh4

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ESI SyNC 2023: September 14 - 15
by El Mahmoudi, Nada 04 Aug '23

04 Aug '23

[https://www.esi-frankfurt.de/img/esisync/esisync2023_header.jpg] Linking hypotheses: where neuroscience, computation, and cognition meet Dear Neuroscientists, We are happy to announce that the Ernst Strüngmann Institute Systems Neuroscience Conference (ESI SyNC) 2023 will take place in-person and online this year, on September 14 and 15 at the Ernst Strüngmann Institute in Frankfurt, Germany. This year’s topic is: Linking hypotheses: where neuroscience, computation, and cognition meet. Eleven speakers will discuss their research and views on the intersection of systems, behavioral, and computational neuroscience from a wide array of viewpoints: from basic network interactions in the brain probed at the electrophysiological and mechanistic levels, to complex animal behavior and cognition. This year’s conference is an outstanding platform bringing together sub-fields in the neurosciences that find themselves, regrettably often, treated in isolation. Young researchers will have the opportunity to exchange ideas and raise questions in formal and informal discussions. There will also be a poster session in person for which we welcome submissions. This conference is free for online participants and researchers in Frankfurt am Main. Registration Link: https://survey.academiccloud.de/index.php/763913?lang=en List of speakers: https://www.esi-frankfurt.de/newevent/ Best Regards, ESI-Sync Organizing Committee

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Postdoc position in computational systems neuroscience, Voigts Lab, Janelia
by Voigts, Jakob 03 Aug '23

03 Aug '23

The Voigts Lab at HHMI Janelia Research Campus is recruiting postdocs to work on how neocortex learns and applies models of the world to enable complex cognitive abilities. We will study flexible cognition by examining naturalistic behaviors that require animals to perform sequential computations, yet are learned quickly. We'll be able to throw whatever technology is needed at the problem of combining sufficient measurements with complex naturalistic behavior in mice, e.g. large-scale electrophysiology or calcium imaging, unrestrained behavior in large complex environments, closed-loop manipulations, circuit reconstruction, etc., but more importantly we'll work on the challenge of modeling, analyzing, and ultimately learning from data when there are no strictly repeated trials to average over. The postdoc position could focus on experimental and/or computational approaches to these questions, depending on the interests and experience of the candidate. We're part of the new Mechanistic Cognitive Neuroscience research area at Janelia. Postdocs will have access to an unusual amount of resources and support, allowing us to make rapid progress on these challenging questions. We'll also work closely with experimental, theoretical, methods, and machine learning researchers in- and outside of Janelia to make this research program possible, collaborative, and fun. Our lab website is https://www.voigtslab.org<https://www.voigtslab.org/>. To apply, please send a brief statement of research interests and CV to voigtsj(a)janelia.hhmi.org<mailto:voigtsj@janelia.hhmi.org>

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Two postdoc positions in neuroAI
by Rui Ponte Costa 02 Aug '23

02 Aug '23

Dear all, We are seeking to appoint two Postdoctoral Research Scientists to join the Neural and Machine Learning Group part of the world-class Oxford Neuroscience and the Oxford Neurotheory initiative. You will carry out research at the intersection between computational neuroscience and machine learning, closely informed by experimental observations. More details here: shorturl.at/hkwG3<https://t.co/d7ugbOLFDV> and of our group: neuralml.github.io<https://neuralml.github.io/> Best wishes, Rui Ponte Costa Group Leader, Neural and Machine Learning group<https://neuralml.github.io/> Centre for Neural Circuits and Behaviour | Oxford Neurotheory Department of Physiology, Anatomy and Genetics Department of Experimental Psychology (honorary member) University of Oxford, UK

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[Job][PhD] at Inria Bordeaux, FR: From Reservoir Transformers to BrainGPT
by Xavier Hinaut 02 Aug '23

02 Aug '23

PhD position available at Inria, Bordeaux, France: "From Reservoir Transformers to BrainGPT" # Keywords Transformers; Reservoir Computing; Computational Neuroscience # Duration & start date 3 years starting 1st October 2023 (estimated) # Contact & Application Informal contact/questions and application: email to xavier dot hinaut at inria dot fr Application & More info: https://recrutement.inria.fr/public/classic/en/offres/2023-06611 All positions available: https://github.com/neuronalX/phd-and-postdoc-positions Deadline: Applications will be considered on a rolling basis. A candidate will be selected as soon as a suitable profile is found. # Context This PhD thesis is part of the BrainGPT "Inria Exploratory Action" project. In the wake of the emergence of large-scale language models such as ChatGPT, the BrainGPT project is at the forefront of research in Artificial Intelligence and Computational Neuroscience. These models, although remarkably powerful, do not reflect the way in which our brains process and learn language. BrainGPT is rising to the challenge by focusing on the development of models that are more faithful to human cognitive functioning, inspired by data on brain activity during listening or reading. The ambition is to create more efficient models that are less dependent on intensive calculations and massive volumes of data. BrainGPT will open up new perspectives on our understanding of language and cognition. # Project and Work description The rapid rise in performance of language models, as demonstrated by the recent appeal of ChatGPT, is undeniable. However, the computational cost and environmental impact associated with such models are often overlooked [1]. These models rely on Transformers [2], which facilitate unsupervised learning on a large volume of data. These same models are used to predict brain activity from functional magnetic resonance imaging (fMRI) or magnetoencephalography (MEG), an application our team also exploits [3]. The main ambition of the BrainGPT project is to combine the explainability of mechanistic models with the predictive power of Transformers to analyze brain imaging data. Today, on the one hand we have explanatory but less predictive mechanistic models, such as those based on Reservoir Computing, and on the other hand, high-performance predictive models, but not explanatory, like Transformers. Our goal is to combine the best of these two approaches, to develop more efficient ("sample efficient") models inspired by Transformers, which more faithfully reflect the how the brain works, while improving the predictive power of mechanistic models. Towards this ambition, the BrainGPT project seeks to identify the key mechanisms that allow Transformers to predict brain activity. Furthermore, our project strives to build models that are more biologically plausible than Transformers, incorporating the most relevant components for predicting brain activity, while integrating constraints derived from human cognition studies. The long-term objectives of the BrainGPT project are as follows: - Making Transformers more biologically plausible, which could improve the prediction of brain activity by imaging (fMRI, MEG, etc.). - Proposing new perspectives and computing paradigms that do not rely exclusively on gradient backpropagation, given its high computational and energy cost. - Reducing the energy footprint of Transformers by minimizing the computational costs associated with their learning. In summary, the thesis will mainly consist of developing new bio-inspired models inspired by the mechanisms, learning methods, and emerging behaviors of Large Language Models (LLMs) and Transformers. Subsequently, in collaboration with our collaborators, these models will be tested to assess their ability to predict brain activity from imaging data. [1] Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021, March). On the dangers of stochastic parrots: Can language models be too big?🦜. In Proc. of the 2021 ACM conference on fairness, accountability, and transparency (pp. 610-623). [2] Vaswani, A. et al. (2017) Attention is all you need. In Proc. of Advances in neural information processing systems. [3] Oota, S. R., Trouvain, N., Alexandre, F., & Hinaut, X. (2023, August). MEG Encoding using Word Context Semantics in Listening Stories. In Proc. of INTERSPEECH 2023. # Skills Ideal Candidate Profile: - Holds an engineering or scientific degree and/or a PhD in digital sciences (computer science, automation, signal processing). - Has a first professional experience (6 months of internship or more) in Machine Learning and Python development. Especially in one or more of the following: Recurrent Neural Networks (in particular Reservoir Computing), Transformers, Large Language Models. - Possesses strong expertise in the scientific Python software and scientific stack (numpy/scipy). - Demonstrates a solid grasp of linear algebra concepts. - Proficiency in technical English is crucial, as it enables efficient collaboration with our international partners and effective presentations at conferences. - Has proven experience with version management, familiarity with Git, and proficiency in using the GitHub platform. # Advisor & Location Xavier Hinaut Inria Bordeaux & Institute for Neurodegenerative diseases (Pellegrin Hospital Campus, Bordeaux). Best regards, Xavier Hinaut Inria Research Scientist www.xavierhinaut.com -- +33 5 33 51 48 01 Mnemosyne team, Inria, Bordeaux, France -- https://team.inria.fr/mnemosyne & LaBRI, Bordeaux University -- https://www4.labri.fr/en/formal-methods-and-models & IMN (Neurodegeneratives Diseases Institute) -- http://www.imn-bordeaux.org/en --- Our Reservoir Computing library: https://github.com/reservoirpy/reservoirpy

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[JOBS] Tenure Track Assistant Professor Intelligent Systems @ Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence at the University of Groningen, the Netherlands.
by Kerstin Bunte 02 Aug '23

02 Aug '23

Tenure Track Assistant Professor Intelligent Systems https://www.rug.nl/about-ug/work-with-us/job-opportunities/?details=00347-0… Closing date = 17-9-2023 We offer a Tenure Track Assistant Professor position with a research profile in Intelligent Systems within the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence at the University of Groningen, The Netherlands. Intelligent Systems aim to give computers and cyber-physical systems the abilities to perceive, analyze and learn from data, make decisions, and enhance human capabilities. The research area has experienced tremendous growth in recent years, especially due to the increase in incorporation of intelligent systems into nearly every aspect of our lives. The societal relevance of sustainability, efficiency, robustness, understanding and guarantees of algorithms is gaining more and more importance, not only in software but also in combination with cyber-physical systems. Relevant aspects are: the theory of machine learning, artificial intelligence and the mathematics of computing (ACM Computing Classification System, 2012 Revision). For this position, possible research directions include (but are not limited to) the theory and application of novel machine learning and artificial intelligence methods with an emphasis on solving pressing open questions, such as efficiency, transparency and interpretability, fairness, the integration of multi-modal and complex heterogeneous data, causal inference, continuous machine learning, generative and dynamic systems. Complex problems demand an increasing amount of interdisciplinary and cross-domain knowledge. Therefore, backgrounds in information theory, probabilistic representations, causality and computational geometry are also welcome to apply. As Assistant Professor with a focus on research, you will: - set up and develop your own research line and research group - supervise PhD students - acquire external funding - promote the societal relevance of your research - teach in and contribute to the development of the degree programs of the School of Science and Engineering, especially courses with computing science content - contribute to the organization of the faculty, for example by participating in working groups and committees, in the domains of teaching, research and management. The position will be embedded in the Intelligent Systems research unit. Our research areas include biologically inspired computational modeling, the theory of machine learning and algorithmic development, as well as image processing with mathematical morphology, machine learning and AI. National and international research collaborations span a multitude of application domains, including medical sciences and health care, natural sciences (astronomy, bioinformatics), remote sensing, computer vision, robotics, smart industry and engineering. About the University of Groningen Since its foundation in 1614, the University of Groningen has enjoyed an international reputation as a dynamic and innovative center of higher education offering high-quality teaching and research. Balanced study and career paths in a wide variety of disciplines encourage currently more than 37,000 students and researchers to develop their own individual talents. Belonging to the best research universities in Europe and the top 100 universities in the world, the University of Groningen is truly an international place of knowledge. More information can be found at: https://www.rug.nl/about-ug/work-with-us/job-opportunities/?details=00347-0… Kind regards, Kerstin -- Kerstin Bunte, Associate Professor | Rosalind Franklin Fellow Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence Faculty of Science and Engineering University of Groningen P.O. Box 407, 9700 AK Groningen The Netherlands Email: k.bunte(a)rug.nl web: http://www.cs.rug.nl/~kbunte/

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Advanced Electrophysiology Post-doc Position Available - Interventional Psychiatry Program, Minneapolis, MN, USA
by Hiba Sheheitli 01 Aug '23

01 Aug '23

*About the Job* Dr. Ziad Nahas (Interventional Psychiatry Lab) in the University of Minnesota Department of Psychiatry and Behavioral Sciences is seeking an outstanding candidate for a postdoctoral position to conduct and analyze the effects of neuromodulation on brain activity in mood disorders. Candidates should be passionate about advancing knowledge in the area of translational research of depressive disorders and other mental health conditions with a focus on invasive and non-invasive brain stimulation treatments. The position is available June 1, 2023, and funding is available for at least two years. *Qualifications* Required Qualifications: ●PhD in relevant field (neuroscience, psychology, cognitive science) ●Strong programming and/or data analysis skills. MATLAB or Python is essential. C/C++ (and derivatives), LabVIEW, and scripting languages could be useful. Prior experience with data acquisition hardware including behavioral as well as EEG would be helpful. Proficiency with Microsoft Office software ●Experience with neurophysiology (human or animal), psychophysics and/or brain stimulation is ideal. ●Excellent verbal and written communication skills, with specific documentation of those skills through published work and oral scientific presentations. ●Demonstrated ability to work independently and to independently overcome complex technical challenges. ●Interpersonal skills appropriate for collaboration in a very multidisciplinary and highly diverse environment. Preferred Qualifications: •Previous experience with psychiatric patient populations, the biological mechanisms of mental illness, and/or medical device development. •Signal processing and/or computer science background. •Previous experience with human functional imaging or electrophysiology. *About the Department* Dr. Ziad Nahas’s Lab is located primarily at the Interventional Psychiatry Program’s St. Louis Park clinic, with additional study activity at UMN and M Health Fairview sites on the UMN campus. Our work focuses on advancing translational research of mood dysregulation and depressive disorders. Specific interests and areas of expertise include: ● Improving patient care of treatment resistant disorders using neuromodulation techniques. ● Functional neuroimaging (fMRI), electroencephalography (EEG) and brain stimulation modalities: Transcranial magnetic stimulation (TMS), transcranial alternating current stimulation (tACS), vagus nerve stimulation (VNS), prefrontal cortical stimulation (PCS), deep brain stimulation (DBS), electroconvulsive therapy (ECT) and focal electrically administered seizure therapy (FEAST). ● Increasing equitable access to neuromodulation interventions for patient care. To learn more about Dr Ziad Nahas and the Department of Psychiatry & Behavioral Sciences, please visit: https://med.umn.edu/bio/psychiatry/ziad-nahas *Apply here: * https://hr.umn.edu/Jobs/Find-Job <https://hr.umn.edu/Jobs/Find-Job> (Click on External Candidates and search for 355003 to find the Job Posting)

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NeurIPS Workshop "Information-Theoretic Principles in Cognitive Systems"
by Rava A. da Silveira 30 Jul '23

30 Jul '23

NeurIPS Workshop: "Information-Theoretic Principles in Cognitive Systems" CALL FOR PAPERS Website (with submission information): https://sites.google.com/view/infocog-neurips-2023/call-for-papers Contact: infocog.neurips2023(a)gmail.com Important Dates: * Paper submission deadline: September 20, 2023 * Author notification: October 27, 2023 * Camera ready deadline: November 27, 2023 The second InfoCog@NeurIPS workshop aims to further the understanding of information flow in cognitive processes and neural networks models of cognition by bringing together researchers from multiple disciplines, including machine learning, cognitive science, neuroscience, and information theory. This is the second workshop of this kind in NeurIPS. This year the workshop will continue last year’s community-building momentum and will additionally focus on advancing two main goals: First, providing a fruitful platform for discussing formulations of storage and processing of information in human and artificial cognitive systems, via information-theoretic measures. Specifically, we aim to further integrate information theory researchers in such discussions, deepening the mathematical knowledge and tools shared across disciplines. [NZ1] Second, facilitating research on addressing the challenges of computing information theoretic quantities, specifically for the needs of cognitive science and machine learning. We invite short submissions (up to 4 pages – NeurIPS format) that present original work related to information theory and cognitive systems, and particularly encourage submissions of collaborative interdisciplinary work. Examples of specific topics of interest include but are not limited to: * Novel information-theoretic approaches to cognitive functions (e.g., perception, decision making, language, social reasoning, etc.) * Method and approaches for the validation of information theoretic formalisms in human and artificial cognition * Novel methods and approaches for the computation and/or estimation of information theoretic quantities and their applications to human and artificial cognition * Challenges and limitations of the use of information theory in studying cognitive systems * Application of information theory to training human-aligned artificial agents, i.e., agents that can better communicate and cooperate with humans All accepted papers will be presented in a poster session during the workshop, and a number of papers will also be selected for an oral presentation. We expect to have limited resources to offer financial aid to selected participants. More details will follow upon acceptance.

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