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Re: Some scientific history that I experienced relevant to the recent Nobel Prizes to Hopfield and Hinton

by Sara A. Solla

Stephen, You have been complaining about not getting enough credit since I first met you in the mid 1980s. You refer to publishing before Hopfield's 1984 paper. You deliberately ignore his 1982 paper, which received 27946 citations: Neural networks and physical systems with emergent collective computational abilities, JJ Hopfield PNAS, April 15, 1982, 79 (8) 2554-2558 In contrast, the 1971 student paper you mentioned received 118 citations. Your 1983 paper with Michael Cohen in IEEE Transaction of Man, Systems, and Cybernetics was received on August 1, 1982, several months after the 1982 paper by Hopfeld had appeared in print. You did get a good number of citations on this paper, 3344, but not as good as 27946. You mention a 1982 paper with Michael Cohen; I have not been able to find it. I have never heard anybody referring to you as 'the father of AI'. What I do remember is a visit to your group at BU many, many years ago - in the late 80s or early 90s. I was amazed at finding out that you closely supervised every word in every slide that anybody in your group was allowed to show when invited to give a talk. Everybody was under a lot of pressure to 'stay on message', where the 'message' was your view on things. I had never encountered a scientific group run as a cult. It made an impression, but not a positive one. So much for training over 100 people - by teaching them not to think by themselves. As for back-propagation, this is not what Hinton is cited for in the Nobel Prize citation. It is for the Boltzmann machine. Finally, I always wondered: If ART solves all problems, why are there ML/AI problems that remain to be solved? On Mon, Oct 21, 2024 at 7:49 AM Grossberg, Stephen via Comp-neuro < comp-neuro(a)lists.cnsorg.org> wrote: > Dear Comp-neuro colleagues, > > > > Here are some short summaries of the history of neural network > discoveries, as I experienced it, that are relevant to the recent Nobel > Prizes to Hopfield and Hinton: > > ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++THETHE THE NOBEL > PRIZES IN PHYSICS TO HOPFIELD AND HINTON > FOR MODELS THEY DID NOT DISCOVER: THE CASE OF HOPFIELD > > Here I summarize my concerns about the Hopfield award. > > I published articles in 1967 – 1972 in the Proceedings of the National > Academy of Sciences that introduced the Additive Model that Hopfield used > in 1984. My articles proved global theorems about the limits and > oscillations of my Generalized Additive Models. See sites.bu.edu/steveg for > these articles. > > For example: > > Grossberg, S. (1971). Pavlovian pattern learning by nonlinear neural > networks. Proceedings of the National Academy of Sciences, 68, 828-831. > https://lnkd.in/emzwx4Tw > > This article illustrates that my mathematical results were part of a > research program to develop biological neural networks that provide > principled mechanistic explanations of psychological and neurobiological > data. > > Later, Michael Cohen and I published a Liapunov function that included the > Additive Model and generalizations thereof in 1982 and 1983 before Hopfield > (1984) appeared. > > For example, > > Cohen, M.A. and Grossberg, S. (1983). Absolute stability of global pattern > formation and parallel memory storage by competitive neural networks. IEEE > Transactions on Systems, Man, and Cybernetics, SMC-13, 815-826. > https://lnkd.in/eAFAdvbu > > I was told that Hopfield knew about my work before he published his 1984 > article, without citation. > > Recall that I started my neural networks research in 1957 as a Freshman at > Dartmouth College. > > That year, I introduced the biological neural network paradigm, as well as > the short-term memory (STM), medium-term memory (MTM), and long-term memory > (LTM) laws that are used to this day, including in the Additive Model, to > explain data about how brains make minds. > > See the review in https://lnkd.in/gJZJtP_W . > > When I started in 1957, I knew no one else who was doing neural networks. > That is why my colleagues call me the Father of AI. > > I then worked hard to create a neural networks community, notably a > research center, academic department, the International Neural Network > Society, the journal Neural Networks, multiple international conferences on > neural networks, and Boston-area research centers, while training over 100 > gifted PhD students, postdocs, and faculty to do neural network research. > See the Wikipedia page. > > That is why I did not have time or strength to fight for priority of my > models. > > Recently, I was able to provide a self-contained and non-technical > overview and synthesis of some of my scientific discoveries since 1957, as > well as explanations of the work of many other scientists, in my 2021 > Magnum Opus > > Conscious Mind, Resonant Brain: How Each Brain Makes a Mind > > https://lnkd.in/eiJh4Ti > > ++++++++++++++++++++++++++++++++++++++++++++++++++++ > > THE NOBEL PRIZES IN PHYSICS TO HOPFIELD AND HINTON > FOR MODELS THEY DID NOT DISCOVER: THE CASE OF HINTON > > Here I summarize my concerns about the Hinton award. > > Many authors developed Back Propagation (BP) before Hinton; e.g., Amari > (1967), Werbos (1974), Parker (1982), all before Rumelhart, Hinton, & > Williams (1986). > > BP has serious computational weaknesses: > > It is UNTRUSTWORTHY (because it is UNEXPLAINABLE). > > It is UNRELIABLE (because it can experience CATASTROPHIC FORGETTING. > > It should thus never be used in financial or medical applications. > > BP learning is also SLOW and uses non-biological NONLOCAL WEIGHT TRANSPORT. > > See Figure, right column, top. > > In 1988, I published 17 computational problems of BP: > https://lnkd.in/erKJvXFA > > BP gradually grew out of favor because other models were better. > > Later, huge online databases and supercomputers enabled Deep Learning to > use BP to learn. > > My 1988 article contrasted BP with Adaptive Resonance Theory (ART) which I > first published in 1976: > https://lnkd.in/evkfq22G > > See Figure, right column, bottom. > > ART never had BP’s problems. > > ART is now the most advanced cognitive and neural theory that explains HOW > HUMANS LEARN TO ATTEND, RECOGNIZE, and PREDICT events in a changing world. > > > ART also explains and simulates data from hundreds of psychological and > neurobiological experiments. > > In 1980, I derived ART from a THOUGHT EXPERIMENT about how ANY system can > AUTONOMOUSLY learn to correct predictive errors in a changing world: > https://lnkd.in/eGWE8kJg > > The thought experiment derives ART from a few facts of life that do not > mention mind or brain. > > ART is thus a UNIVERSAL solution of the problem of autonomous error > correction in a changing world. > > That is why ART models can be used in designs for AUTONOMOUS ADAPTIVE > INTELLIGENCE in engineering, technology, and AI. > > ART also proposes a solution of the classical MIND-BODY PROBLEM: > > HOW, WHERE in our brains, and WHY from a deep computational perspective, > we CONSCIOUSLY SEE, HEAR, FEEL, and KNOW about the world, and use our > conscious states to PLAN and ACT to realize VALUED GOALS. > > For details, see > > Conscious Mind, Resonant Brain: How Each Brain Makes a Mind > > https://lnkd.in/eiJh4Ti > > > +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ > > > _______________________________________________ > Comp-neuro mailing list -- comp-neuro(a)lists.cnsorg.org > Mailing list webpage (to subscribe or view archives): > https://www.cnsorg.org/comp-neuro-mailing-list > > To contact admin/moderators, send an email to: > comp-neuro-owner(a)lists.cnsorg.org > To unsubscribe, send an email to comp-neuro-leave(a)lists.cnsorg.org >

Oct. 21, 2024

[Jobs] Postdoc Available in Theoretical Neuroscience

by Michael Furlong

Job Ad – Postdoctoral Researcher in Theoretical Neuroscience Prof Chris Eliasmith, who holds the Canada Research Chair in Theoretical Neuroscience and heads the Computational Neuroscience Research Group (CNRG) in the Centre for Theoretical Neuroscience (CTN) at the University of Waterloo, is seeking a postdoctoral researcher in Theoretical Neuroscience for a fixed-term appointment. Description: The postdoctoral position will be hosted in the CNRG, with a principal focus on neural modeling to build the next version of the Spaun brain model, the world’s largest functional brain model. The project integrates spiking deep neural networks, motor control, probabilistic inference, navigation, perception and cognition to develop a state-of-the-art, large-scale, spiking, whole-brain model. Applicants should have a PhD, with demonstrated skills in at least one of those areas and a willingness to learn about the others. This project leverages the CNRG’s existing expertise in using neural networks for large-scale brain modeling, originally demonstrated in 2012 with the first version of Spaun. A subsequent version in 2018 significantly extended performance. The latest version currently being built by the CNRG will again break new barriers in the scale and sophistication of whole brain models. Unlike past models, it will be embedded in a sophisticated 3D environment, yet retain the ability to perform a wide variety of tasks, from simple perceptual and motor tasks to challenging intelligence tests. Overall, the long-term goal of the project is to advance the state-of-the-art in large-scale brain models. Additional Information: The successful applicant will be housed in the vibrant Centre for Theoretical Neuroscience (CTN), which includes 7 core and 7 affiliated labs focussed on neural modeling and improving our basic understanding of neural computation. The CTN hosts monthly seminars, a yearly ‘Brain Day’ event, a summer school, and regular social activities. The position is for a fixed term of one year, eight months, with extensions contingent on performance and securing additional funding. Salary is $45,000 - 65,000 CAD per year. To apply, please send a full CV, 3 references and cover letter explaining your background and fit for the job to: Dr. Chris Eliasmith at celiasmith(a)uwaterloo.ca.

Oct. 21, 2024

Re: "Experienced" history of Neural Networks

by James Bower

argg I am sorry, typing too fast Could you change: Any equally interesting conflict I witnessed first hand (with no horse in the race), which even at that time was full of similar claims of precedence. I could tell that story too, but instead, I will simply say that Stephen's recent posting made me a bit nostalgic for the days when you were either were in the “email from Stephen claiming prescience club” or not - I thankfully never was. To An equally interesting conflict I witnessed first hand (with no horse in the race), which even at that time was full of similar claims of precedence. I could tell that story too, but instead, I will simply say that Stephen's recent posting made me a bit nostalgic for the days when you were either in the “email from Stephen claiming prescience club” or not - I thankfully never was. Or I can resubmit Sorry for the extra work Jim Dr. James M. Bower Ph.D. 541-499-7502 Simulating a 17th century landed gentry scientist. Also: Affiliate Professor of Biology Southern Oregon University Visiting Professor of Computational Neuroscience Biocomputation Research Group School of Physics, Engineering and Computer Science University of Hertfordshire, UK Linked in <https://www.linkedin.com/in/james-m-bower-130163/> Wikipedia <https://en.wikipedia.org/wiki/James_M._Bower> > On Oct 21, 2024, at 11:15 AM, James Bower <bowerj(a)sou.edu> wrote: > > Any equally interesting conflict I witnessed first hand (with no horse in the race), which even at that time was full of similar claims of precedence. > > I could tell that story too, but instead, I will simply say that Stephen's recent posting made me a bit nostalgic for the days when you were either were in the “email from Stephen claiming prescience club” or not - I thankfully never was.

Oct. 21, 2024

Re: "Experienced" history of Neural Networks

by James Bower

opps, Here is the post with a spelling error corrected. Thank you Jim Being historical myself, I thought I might be appropriate for me to respond briefly to Stephen Grossberg’s recent personal recounting and retelling of history. To Witt, I sometimes, for fun, refer to myself as the pet neurobiologist in the early days of the neural network movement. Here is a recent semi-autobiographical (and thus of course certainly somewhat biased) account of those early days I was recently asked to write, which includes how the CNS meeting (as well as this mailing list) emerged from those days. https://www.researchgate.net/publication/365925517_NIPS_NeurIPS_and_Neurosc… (PDF) (NIPS) NeurIPS and Neuroscience: A personal historical perspective researchgate.net https://www.researchgate.net/publication/365925517_NIPS_NeurIPS_and_Neurosc… Not included in that account where the other abundant political circumstances surrounding the re-emergence of neural networks, including for example, the revelry between the NIPS meeting and the “International Neural Network Society” and their annual meeting referred to in Stephen Grossberg’s recent post. Any equally interesting conflict I witnessed first hand (with no horse in the race), which even at that time was full of similar claims of precedence. I could tell that story too, but instead, I will simply say that Stephen's recent posting made me a bit nostalgic for the days when you were either were in the “email from Stephen claiming prescience club” or not - I thankfully never was. Anyway, for those interested, from my understanding I think this is a pretty good and balanced history of neural networks. https://en.wikipedia.org/wiki/History_of_artificial_neural_networks https://en.wikipedia.org/wiki/History_of_artificial_neural_networks What should be clear from that history, and as also mentioned by Stephen, much of the algorithmic basis for ‘machine learning’ today are based on work done many years ago and therefore that most of the recent innovation in the field is not algorithmic but implementation, given faster and faster computers, cheaper and cheaper memory, and massive amounts of data. Given that, very tricky to assign ‘father or’ or for that matter ‘godfather of’ either. :-) In that light however, one other thing to say, which I could say a lot more about - as will almost certainly be clear in John Hopfield’s Nobel lecture, John was never much interested in the AI implications of his work. From the time I meet him through the rest of his career, he was focused on using the tools he had as a condensed matter physicist to explore questions in biology. In my experience at the time, John was almost uniquely committed to actually understanding the biology, rather than simply imposing his will upon it. That said, there is no question and as I witnessed it myself, publication of “The Hopfield Network” in 1981, re-ignited interest in an approach to AI that had been strongly resisted by the dons of the field at that time, precisely because it was not “explainable” in the then desired sense. Put another way, the role of the engineer in self-learning networks was not to impose their own predisposed assumptions about how to solve a particular problem (sometimes then, unfortunately extended to claims about how the nervous system works), but instead to construct a system that found a solution to the problem. Because of its success machine learning has now become the dominant paradigm in real world AI. But, it is now also increasingly being used as a tool to understand the brain. Too long a discussion for that here, but I have serious concerns about those efforts. In fact, I am giving at talk this week at the University of Oregon on a recent example in the neurobiology of olfaction. It is being webcast, so if anyone is interested, email me and I can send you the URL. In summary then, there is no question in my mind that John Hopfield’s contribution was unique and deserving of the acclaim he is now receiving - but I have to say I feel even better about his award because he never sought it, or expected it, or campaigned to get it, and in fact, is being rewarded for a consequence of his work that was never the real focus of his efforts. Good for you John. Respectfully, Jim Bower Dr. James M. Bower Ph.D. 541-499-7502 Simulating a 17th century landed gentry scientist. Also: Affiliate Professor of Biology Southern Oregon University Visiting Professor of Computational Neuroscience Biocomputation Research Group School of Physics, Engineering and Computer Science University of Hertfordshire, UK Linked in <https://www.linkedin.com/in/james-m-bower-130163/> Wikipedia <https://en.wikipedia.org/wiki/James_M._Bower> > On Oct 21, 2024, at 11:10 AM, James Bower <bowerj(a)sou.edu> wrote: > > Being historical myself, I thought I might be appropriate for me to respond briefly to Stephen Grossberg’s recent personal recounting and retelling of history. > > To Witt, I sometimes, for fun, refer to myself as the pet neurobiologist in the early days of the neural network movement. > > Here is a recent semi-autobiographical (and thus of course cretainly somewhat biased) account of those early days I was recently asked to write, which includes how the CNS meeting (as well as this mailing list) emerged from those days. > > https://www.researchgate.net/publication/365925517_NIPS_NeurIPS_and_Neurosc… > > Not included in that account where the other abundant political circumstances surrounding the re-emergence of neural networks, including for example, the revelry between the NIPS meeting and the “International Neural Network Society” and their annual meeting referred to in Stephen Grossberg’s recent post. > > Any equally interesting conflict I witnessed first hand (with no horse in the race), which even at that time was full of similar claims of precedence. > > I could tell that story too, but instead, I will simply say that Stephen's recent posting made me a bit nostalgic for the days when you were either were in the “email from Stephen claiming prescience club” or not - I thankfully never was. > > Anyway, for those interested, from my understanding I think this is a pretty good and balanced history of neural networks. > > https://en.wikipedia.org/wiki/History_of_artificial_neural_networks > > What should be clear from that history, and as also mentioned by Stephen, much of the algorithmic basis for ‘machine learning’ today are based on work done many years ago and therefore that most of the recent innovation in the field is not algorithmic but implementation, given faster and faster computers, cheaper and cheaper memory, and massive amounts of data. Given that, very tricky to assign ‘father or’ or for that matter ‘godfather of’ either. :-) > > In that light however, one other thing to say, which I could say a lot more about - as will almost certainly be clear in John Hopfield’s Nobel lecture, John was never much interested in the AI implications of his work. From the time I meet him through the rest of his career, he was focused on using the tools he had as a condensed matter physicist to explore questions in biology. In my experience at the time, John was almost uniquely committed to actually understanding the biology, rather than simply imposing his will upon it. > > That said, there is no question and as I witnessed it myself, publication of “The Hopfield Network” in 1981, re-ignited interest in an approach to AI that had been strongly resisted by the dons of the field at that time, precisely because it was not “explainable” in the then desired sense. Put another way, the role of the engineer in self-learning networks was not to impose their own predisposed assumptions about how to solve a particular problem (sometimes then, unfortunately extended to claims about how the nervous system works), but instead to construct a system that found a solution to the problem. > > Because of its success machine learning has now become the dominant paradigm in real world AI. But, it is now also increasingly being used as a tool to understand the brain. Too long a discussion for that here, but I have serious concerns about those efforts. In fact, I am giving at talk this week at the university of oregon on a recent example in the neurobiology of olfaction. > > It is being webcast, so if anyone is interested, email me and I can send you the URL. > > In summary then, there is no question in my mind that John Hopfield’s contribution was unique and deserving of the acclaim he is now receiving - but I have to say I feel even better about his award because he never sought it, or expected it, or campaigned to get it, and in fact, is being rewarded for a consequence of his work that was never the real focus of his efforts. > > Good for you John. > > > Respectfully, > > Jim Bower > > > > > > Dr. James M. Bower Ph.D. > > 541-499-7502 > > Simulating a 17th century landed gentry scientist. > > Also: > > Affiliate Professor of Biology > Southern Oregon University > > Visiting Professor of > Computational Neuroscience > Biocomputation Research Group > School of Physics, Engineering and Computer Science > University of Hertfordshire, UK > > Linked in <https://www.linkedin.com/in/james-m-bower-130163/> > > Wikipedia <https://en.wikipedia.org/wiki/James_M._Bower> > > > > >

Oct. 21, 2024

Re: Some scientific history that I experienced relevant to the recent Nobel Prizes to Hopfield and Hinton

by Grossberg, Stephen

Dear Comp-neuro colleagues, Here are some short summaries of the history of neural network discoveries, as I experienced it, that are relevant to the recent Nobel Prizes to Hopfield and Hinton: ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++THETHE THE NOBEL PRIZES IN PHYSICS TO HOPFIELD AND HINTON FOR MODELS THEY DID NOT DISCOVER: THE CASE OF HOPFIELD Here I summarize my concerns about the Hopfield award. I published articles in 1967 – 1972 in the Proceedings of the National Academy of Sciences that introduced the Additive Model that Hopfield used in 1984. My articles proved global theorems about the limits and oscillations of my Generalized Additive Models. See sites.bu.edu/steveg<http://sites.bu.edu/steveg> for these articles. For example: Grossberg, S. (1971). Pavlovian pattern learning by nonlinear neural networks. Proceedings of the National Academy of Sciences, 68, 828-831. https://lnkd.in/emzwx4Tw This article illustrates that my mathematical results were part of a research program to develop biological neural networks that provide principled mechanistic explanations of psychological and neurobiological data. Later, Michael Cohen and I published a Liapunov function that included the Additive Model and generalizations thereof in 1982 and 1983 before Hopfield (1984) appeared. For example, Cohen, M.A. and Grossberg, S. (1983). Absolute stability of global pattern formation and parallel memory storage by competitive neural networks. IEEE Transactions on Systems, Man, and Cybernetics, SMC-13, 815-826. https://lnkd.in/eAFAdvbu I was told that Hopfield knew about my work before he published his 1984 article, without citation. Recall that I started my neural networks research in 1957 as a Freshman at Dartmouth College. That year, I introduced the biological neural network paradigm, as well as the short-term memory (STM), medium-term memory (MTM), and long-term memory (LTM) laws that are used to this day, including in the Additive Model, to explain data about how brains make minds. See the review in https://lnkd.in/gJZJtP_W . When I started in 1957, I knew no one else who was doing neural networks. That is why my colleagues call me the Father of AI. I then worked hard to create a neural networks community, notably a research center, academic department, the International Neural Network Society, the journal Neural Networks, multiple international conferences on neural networks, and Boston-area research centers, while training over 100 gifted PhD students, postdocs, and faculty to do neural network research. See the Wikipedia page. That is why I did not have time or strength to fight for priority of my models. Recently, I was able to provide a self-contained and non-technical overview and synthesis of some of my scientific discoveries since 1957, as well as explanations of the work of many other scientists, in my 2021 Magnum Opus Conscious Mind, Resonant Brain: How Each Brain Makes a Mind https://lnkd.in/eiJh4Ti ++++++++++++++++++++++++++++++++++++++++++++++++++++ THE NOBEL PRIZES IN PHYSICS TO HOPFIELD AND HINTON FOR MODELS THEY DID NOT DISCOVER: THE CASE OF HINTON Here I summarize my concerns about the Hinton award. Many authors developed Back Propagation (BP) before Hinton; e.g., Amari (1967), Werbos (1974), Parker (1982), all before Rumelhart, Hinton, & Williams (1986). BP has serious computational weaknesses: It is UNTRUSTWORTHY (because it is UNEXPLAINABLE). It is UNRELIABLE (because it can experience CATASTROPHIC FORGETTING. It should thus never be used in financial or medical applications. BP learning is also SLOW and uses non-biological NONLOCAL WEIGHT TRANSPORT. See Figure, right column, top. In 1988, I published 17 computational problems of BP: https://lnkd.in/erKJvXFA BP gradually grew out of favor because other models were better. Later, huge online databases and supercomputers enabled Deep Learning to use BP to learn. My 1988 article contrasted BP with Adaptive Resonance Theory (ART) which I first published in 1976: https://lnkd.in/evkfq22G See Figure, right column, bottom. ART never had BP’s problems. ART is now the most advanced cognitive and neural theory that explains HOW HUMANS LEARN TO ATTEND, RECOGNIZE, and PREDICT events in a changing world. ART also explains and simulates data from hundreds of psychological and neurobiological experiments. In 1980, I derived ART from a THOUGHT EXPERIMENT about how ANY system can AUTONOMOUSLY learn to correct predictive errors in a changing world: https://lnkd.in/eGWE8kJg The thought experiment derives ART from a few facts of life that do not mention mind or brain. ART is thus a UNIVERSAL solution of the problem of autonomous error correction in a changing world. That is why ART models can be used in designs for AUTONOMOUS ADAPTIVE INTELLIGENCE in engineering, technology, and AI. ART also proposes a solution of the classical MIND-BODY PROBLEM: HOW, WHERE in our brains, and WHY from a deep computational perspective, we CONSCIOUSLY SEE, HEAR, FEEL, and KNOW about the world, and use our conscious states to PLAN and ACT to realize VALUED GOALS. For details, see Conscious Mind, Resonant Brain: How Each Brain Makes a Mind https://lnkd.in/eiJh4Ti +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

Oct. 21, 2024

Arduino for Neuroscience Workshop, Brighton, Nov 20-22th

by Mateusz Kostecki

Hello! We are happy to announce the first Cambridge Open Lab Workshop, organised in collaboration with the Open Research Technologies Hub. Learn how to apply Arduino in your research! Arduino is a powerful device that you can use to build and program thousands of devices – from weather stations, through smart house applications to drones and robots. It has also recently became a powerful tool used in laboratory – you can use it to control lasers, build automated mazes or stimulus delivery systems for behavioural experiments – and much more. It is easy to learn and doesn’t require previous experience with programming. During our workshop, you will learn everything you need to start building your own devices. We will guide you through the topics ranging from basic electronics, diodes, trough motors and servos to sensors of all types. You will learn how to use Arduino to control different research devices and synchronize them! After the workshop, you will be able to write complex Arduino programs and have a knowledge of electronics that will allow you to design devices used in your lab. Topics: - Basic electronics – from electrons to laws - Controlling devices with Arduino – diodes, motors, servos - Writing code to control lasers in optogenetic experiments - Synchronizing devices with Arduino - Sensing environment – light, temperature, and distance sensors - Wireless communication - Writing complex code in Arduino The workshop will take place at University of Sussex Library, Brighton, Nov 20-22 2024 from 9 AM to 6 PM. The cost of the workshop is GBP 150. Registration form can be found here - https://nenckiopenlab.org/arduino-cam/. The deadline for registration is Oct 30th. Best, Mateusz Kostecki -- --- Mateusz Kostecki PhD Student Knapska Laboratory Nencki Institute 02-093 Warsaw, Pasteura 3, Poland https://twitter.com/mtkostecki https://evolvingbehavior.blog/

Oct. 21, 2024

COSYNE 2025: Abstract submission closes soon; Cosyne DEIA Committee

by Tomas Hromadka

==================================================== Computational and Systems Neuroscience 2025 (Cosyne) MAIN MEETING 27 March - 30 March 2025 Montreal, Canada WORKSHOPS 31 March - 01 April 2025 Mont-Tremblant, Canada www.cosyne.org ==================================================== IMPORTANT DATES Abstract submission is now open. Abstract submission deadline: 23 October 2024 11:59pm PST ---------------------------------------------------- COSYNE MEETING & WORKSHOPS ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks is selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. Cosyne topics include but are not limited to: neural basis of behavior, sensory and motor systems, circuitry, learning, neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, neuromodulation, and computation with spiking networks. We would like to foster increased participation from experimental groups as well as computational ones. Please circulate widely and encourage your students and postdocs to apply. When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. ---------------------------------------------------- COSYNE DEIA COMMITTEE ---------------------------------------------------- Join our 2025 DEIA Committee for @CosyneMeeting!!! The Cosyne DEIA Committee is dedicated to fostering inclusivity. We’re seeking 4 new members to contribute to the planning of the 2025 conference and drive inclusive practices. All career stages are encouraged to join (e.g., faculty, postdocs, and graduate students). For questions, contact the committee co-chairs, Luke Sjulson (@lukesjulson, luke [at] sjulsonlab.org) or Denise Cai (@denisejcai, denisecai [at] gmail.com) The application deadline is 15 November 2024. Join us and make a lasting impact—apply today! https://forms.gle/gqSNuZj2Cb68UevN9 ----------------------------------------------------- COSYNE 2025 COMMITTEES ----------------------------------------------------- ORGANIZING COMMITTEE General Chairs: Bing Brunton (U Washington) and Chandramouli Chandrasekaran (Boston U) Program Chairs: Tatiana Engel (CSHL) and Kevin Franks (Duke) Workshop Chairs: SueYeon Chung (NYU) and Guillaume Lajoie (MILA/U Montreal) Tutorial Chair: Talmo Pereira (Salk) DEIA Committee: Denise Cai (Mount Sinai) and Luke Sjulson (Albert Einstein) Undergraduate Travel Chairs: Kimberly Stachenfeld (DeepMind) and Marcelo Mattar (NYU) Fundraising Chair: Michael Long (NYU) Social Media Chair: Sabera Talukder (Caltech) Audio-Video Media Chair: Carlos Stein Brito (Chamaplimaud) Poster Design: Maja Bialon PROGRAM COMMITTEE Tatiana Engel (CSHL) Co-chair Kevin Franks (Duke) Co-chair Mikio Aoi (UCSD) Arkarup Banerjee (CSHL) Marcus Benna (UCSD) Adrian Bondy (Princeton) Timothy Buschman (Princeton) Celine Cammarata (Duke) Alex Cayco Gajic (Ecole Normale Superieure) Hannah Choi (Gatech) Benjamin Cowley (CSHL) Carina Curto (Brown) Brian DePasquale (Boston U) Sridhar Devarajan (Indian Inst Sci) Laura Driscoll (Stanford) Ann Duan (UCL) Lea Duncker (Stanford) Annegret Falkner (Princeton) Arseny Finkelstein (Tel Aviv U) Rainer Friedrich (Friedrich Miescher Institute) Juan Gallego (Imperial) Matthew Golub (U Washington) Bilal Haider (Georgia Tech) Kiah Hardcastle (Harvard) Ann Hermundstad (Janelia) Michele Insanally (U Pitt) Monika Jadi (Yale) Jonathan Kao (UCLA) Kohitij Kar (York U) Ann Kennedy (Northwestern) Guillaume Lajoie (MILA) Anna Levina (U Tubingen) Laura Lewis (MIT) Camilo Libedinsky (National U Singapore) Ashok Litwin-Kumar (Columbia) Laureline Logiaco (MIT) Emily Mace (Max Planck) Francesca Mastrogiuseppe (Champalimaud) Luca Mazzucato (U Oregon) Jorge Mejias (U Amsterdam) Jonathan Michaels (York U) Eilif Muller (U Montreal) James Murray (U Oregon) Hendrikje Nienborg (NIH) Gouki Okazawa (Chinese Acad Sci) Marino Pagan (U Edinburgh) Hannah Payne (Columbia) Talmo Pereira (Salk) Erin Rich (Mount Sinai) Ben Scott (Boston U) Nicholas Steinmetz (U Washington) Carsen Stringer (HHMI) Marie Suver (Vanderbilt) Tatjana Tchumatchenko (U Bonn) John Tuthill (U Washington) Ali Weber (Bryn Mawr) Brady Weissbourd (MIT) Alex Williams (NYU) Klaus Wimmer (CRM) Brad Wyble (Penn State) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Anne-Marie Oswald (U Pittsburgh) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT meeting [at] cosyne.org ----------------------------------------------------- COSYNE MAILING LISTS ----------------------------------------------------- Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> About-> Mailing lists for details.

Oct. 20, 2024

Post-doctoral Fellow Position available in National University of Singapore

by sc.phua＠nus.edu.sg

Postdoctoral Fellow Position in the Neuron Signaling Laboratory, NUS, Singapore We are actively seeking a Postdoctoral Fellow to join us in the following project (This position will be co-supervised with a PI from the Biomedical Engineering Department): Investigating a transcriptional role of primary cilia in striatal neural computation mediating cognitive flexibility Qualifications: The candidate should hold or is going to obtain a PhD in one of the disciplines below: - Biomedical engineering, systems neuroscience, computational neuroscience or related fields. - At least one first-author research publication in a peer-reviewed journal Skills: - Strong motivation and leadership in pursuing challenging scientific questions - An ability to work well with interdisciplinary colleagues - Experience in mentoring and training junior researchers - Excellent written and interpersonal communication skills - Good time and resource management skills Experience: - High proficiency in Python/Matlab (essential requirement) •⁠ ⁠⁠Preferably experience working with neural data (spikes, calcium imaging) at scale •⁠ ⁠⁠Some background in machine learning with strong grounding in statistical methods •⁠ ⁠⁠Familiarity with techniques for dimensionality reduction - Expertise in in vivo brain recording techniques, e.g. microendoscopy, electrophysiology, fiber photometry - Expertise in rodent stereotaxic surgeries Candidates should email (i) a description of research interests, (ii) a CV and (iii) the names of 3 references to Dr. Phua at sc.phua(a)nus.edu.sg . The position is available immediately but we will wait for the candidate with the ideal combination of skills and interests.

Oct. 19, 2024

Two Tenure-Track faculty positions in Applied Mathematics, UW Seattle

by Eric Shea-Brown

Hello comp neuro colleagues! Sharing news of two tenure-track assistant professor positions in at UW Applied Mathematics, in Seattle. Please apply by 10/31! Details here: https://www.mathjobs.org/jobs/list/25055 Yours, Eric ________________ Eric Shea-Brown (he/him) Professor, Applied Mathematics + Physiology and Biophysics, ECE Co-director, Computational Neuroscience Center University of Washington

Oct. 18, 2024

One week left: Research Summit on Open Problems for AI (Euston, London, Oct 23-24th)

by Battleday, Ruairidh

AE Autumn Summit on Open Problems for AI. Friends House, Euston, London, Oct 23-24. What are the next set of challenges for AI algorithms? What are the open problems in application? Join the UK’s leading AI researchers, policy makers, and entrepreneurs in this global summit. One week left until the Summit! Some tickets sold out, others still available! www.algopreneurship.org Day 1 (Oct 23rd) - Algorithms We’ll be hearing from Professor Karl Friston <https://en.wikipedia.org/wiki/Karl_J._Friston> (UCL & Verses.ai <http://verses.ai/>), Professor Claudia Clopath <https://profiles.imperial.ac.uk/c.clopath> (Imperial), Dr Katja Hofman <https://www.microsoft.com/en-us/research/people/kahofman/>n (Microsoft), Dr Martin Riedmiller <https://sites.google.com/view/riedmiller/home> (Google DeepMind), Professor Tim Rocktäschel <https://rockt.github.io/> (Google DeepMind & UCL) Panels on Fundamental AI research challenges (University of Oxford, DeepMind, Meta <https://ai.meta.com/research/fair-paris/>, XTX Markets <https://xtxmarkets.com/>); New Kinds of AI Research Institution (Kings AI Institute <https://www.kcl.ac.uk/ai>, <https://www.aria.org.uk/>Alan Turing Institute <https://www.turing.ac.uk/>, Advanced Research and Invention Agency <https://www.aria.org.uk/>, Ellison Institute <https://eit.org/>, <https://www.airstreet.com/>Cambridge Consultants <https://www.cambridgeconsultants.com/>) Day 2 (Oct 24th) - Applications Professor Sana Khareghani <https://rai.ac.uk/team/professor-sana-khareghani-2/> (RAI <https://rai.ac.uk/> & KCL), James Donovan <https://www.linkedin.com/in/james-donovan-111a7a122/> (OpenAI), Professor Mounia Lalmas <https://research.atspotify.com/2020/09/mounia-lalmas-roelleke/> (Spotify), Dr Olvier Vince <https://theorg.com/org/basecamp-research/org-chart/oliver-vince> (Basecamp Research <https://basecamp-research.com/>), Professor Eiman Kanjo <https://profiles.imperial.ac.uk/e.kanjo> (tinyML/Imperial/Nottingham Trent), Danny Gray <https://jaaq.org/creator/35911> (Just Ask A Question <https://jaaq.org/home>), Tarig Hilal <https://www.linkedin.com/in/tarighilal/> (Akord AI <https://cdi.akord.org/>), Ashley Ramrachia <https://www.linkedin.com/in/ashley-ramrachia-0988675/> ( Academy <https://academy.tech/>), Dr Chanuki Illushka Seresinhe <https://www.linkedin.com/in/chanukiseresinhe/> (Boon/beautifulplaces.ai) Future Leaders Breakout Rooms (UKRI, Future Leaders Development Network <https://www.flfdevnet.com/>, No, 10 Downing Street Data Team, Tony Blair Institute <https://www.institute.global/>, Zeki <https://www.thezeki.com/>, Octopus ventures <https://octopusventures.com/>, Entrepreneur First <https://www.joinef.com/>, Financial Times), Panels on AI and Education Panel (Raspberry Pi <https://www.raspberrypi.org/>, Inversity <https://inversity.co/welcome>, micro:bit <https://microbit.org/>, memrise <https://www.memrise.com/en-us/>, Five Arrows <https://www.rothschildandco.com/en/five-arrows/>); Challenges for AI in Biomedicine Panel (KCL, QMU, Alan Turing Institute, Sonus AI <https://decorte.co.uk/>, Basecamp Research <https://www.basecamp-research.com/>, RedAlpine <https://www.redalpine.com/> ) Student tickets: £10 General: £30 This should be an exciting and productive event, and we expect an audience of 1000 of the UK best AI researchers, policy makers, and entrepreneurs, at student, early stage, and full career levels. -- Dr Ruairidh McLennan Battleday BMBCh (Oxon) PhD President Thinking About Thinking, Inc <https://thinkingaboutthinking.org> Postdoctoral Research Fellow Center for Brain Science, Harvard University Center for Brains, Minds, and Machines, MIT

Oct. 17, 2024

School on the Origins of Life, Behavior and Cognition

by Ahmed El Hady

*School on the Origins of Life, Behavior and Cognition* *March 10-21, 2025* *ICTP-SAIFR, São Paulo, Brazil* */Application Deadline:/ December 28, 2024* School on Origins is an interdisciplinary school that tackles the foundational questions concerning the origins of biophysical systems which include but are not limited to : molecular, cellular, neural and behavioral systems. We aim to find principles shared across systems using tools from statistical physics, mathematical analysis and numerical simulations to explore these questions. We have invited researchers that work both on the experimental and theoretical side to cover a variety of biophysical systems and theoretical approaches. The school is aimed at graduate students either at the master’s or PhD level who have a strong quantitative background and a keen interest to pursue interdisciplinary research. We invite students pursuing degrees in physics, computer science, engineering, or mathematics. Those pursuing degrees in biology need to provide evidence of strong and extensive quantitative background in topics such as calculus, dynamical systems and numerical programming. /There is no registration fee and limited funds are available for travel and local expenses./ *Organizers:* * *Ahmed El Hady* (Cluster of Excellence Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Germany.) * *Antonio C. Roque* (USP Ribeirão Preto, Brazil) * *Daniel Y. Takahashi* (UFRN, Brazil) *Lecturers:* * *Suzanne Still* (University of Hawaii at Mānoa, USA) * *Randall Beer* (Indiana University Bloomington, USA) * *Asif Ghazanfar* (Princeton University, USA) * *Don Katz* (Brandeis University, USA) * *Gandhimohan M. Viswanathan* (Universidade Federal do Rio Grande do Norte – UFRN, Brazil) * *Bruno Mota* (Federal University of Rio de Janeiro, Brazil) * *Ana Amador* (University of Buenos Aires, Argentina ) All details and application procedure can be found here: https://www.ictp-saifr.org/solbc2025/ All the best, Ahmed El Hady Dr. Ahmed El Hady Research Group Leader Cluster for Advanced Study of Collective Behavior University of Konstanz / Max Planck Institute of Animal Behavior Universitätsstraße 10, 78464 Konstanz Room ZT 907 Postbox 687 Tel.: +49 7531 88-4742

Oct. 17, 2024

PhD/postdoc positions in NeuroAI

by Adam Gosztolai

Dear Comp-neuro community, I would like to inform you about PhD and postdoc opportunities in my lab in Vienna. We are the Dynamics of Neural Systems Lab, currently generously supported by an ERC Starting grant. We have several exciting projects at the interface of neuro, mathematical modelling (geometry and dynamical systems) and ML. All have broad impact in fundamental ML theory and neuroscience and translational impact in neuroprosthetic interfaces. I also have an open project for someone with strong mathematical and programming skills, e.g., to develop a project like MARBLE (https://arxiv.org/html/2304.03376v3) at the interface of dynamical systems, probabilistic modelling and deep learning. More details on the projects can be found here: https://www.gosztolai-lab.org/news/2024/09/15/Hiring.html Would you be so kind to circulate this among colleagues and interested students? They can contact me directly with questions. All the best, Adam ————— Adam Gosztolai Group leader AI Institute Medical University of Vienna Research Affiliate McGovern Institute for Brain Research MIT gosztolai-lab.org

Oct. 17, 2024

Open PhD Position at El-Boustani Lab - University of Geneva (Switzerland)

by sami El-Boustani

The El-Boustani Lab at the University of Geneva is looking for a highly motivated PhD student to research the plasticity mechanisms underlying the learning of goal-directed sensorimotor associations in mice. This project involves whole-brain mappings, two-photon calcium imaging of neuronal populations, as well as dendritic spine imaging in mice during the acquisition of perceptual decision-making tasks. Genetically encoded tools will be used to dissect the circuits that contribute to the learning of these tasks, and state-of-the-art behavioral modeling will help infer the timescales of synaptic plasticity. Successful applicant will contribute to a collaborative research program focused on understanding how changes in specific sensorimotor synapses underpin the acquisition of new associations. We welcome applicants with diverse quantitative backgrounds, including but not limited to neuroscience, mathematics, physics, and engineering. We are especially interested in applicants with excellent programming skills (e.g., MATLAB, Python), and experience with mouse behavior and/or imaging techniques through cranial windows. Switzerland offers a vibrant neuroscience community with outstanding research conditions and attractive salaries. Candidates should send their CV, at least two references and a brief cover letter describing their previous work and future goals to Sami El-Boustani: <mailto:sami.el-boustani@unige.ch> sami.el-boustani(a)unige.ch<mailto:sami.el-boustani@unige.ch>. Please visit http://elboustani-lab.org/ for more details.

Oct. 16, 2024

2-year postdoc at Neurospin/INM, Paris: Deep phenotyping of learning and decision-making 7T MRI, MEG & computational modeling

by Alexander Paunov

2-YEAR POSTDOCTORAL POSITION AVAILABLE AT NEUROSPIN/INM (PARIS, FRANCE) https://florentmeyniel.weebly.com/uploads/5/9/7/2/59727215/ad_recruitment_p… Project Deep phenotyping of learning and decision-making 7T MRI, MEG & computational modeling Supervisor and contact Dr Florent MEYNIEL https://www.unicog.org/lab/the-computational-brain/ Duration and Dates * Initial duration: two years * Extension possible * Full-time post * Preferred starting date: January 2025 Project description Learning and decision making are intertwined processes in many everyday situations. One example is when you decide where to have lunch: should you go to the nearby coffee shop or to the university cafeteria? Learning depends on choice, because you can learn which option you prefer by trying each option repeatedly, and decision making depends on learning, because you eventually want to select the option you have learned you like best. Uncertainty plays a key role in both learning1–4 and decision making5, especially when the environment is not stationary (e.g., a new brand now runs the nearby coffee shop and you like it less). In the CEA-funded EXPLORE+ collaborative project, we are interested in characterizing the neural representation of uncertainty6–8 and value that emerge from learning and guide decisions. Our approach follows a deep phenotyping approach, attempting to characterize each subject with a large multimodal dataset. We collected data from 16 participants who participated in one behavioral session, two 7T fMRI sessions, and two MEG sessions. The large number of trials allows us to estimate and test different computational models of the decision and learning processes. The 7T MRI and MEG data provide access to the topographical organization of neural representations and their dynamics, respectively, to better understand learning and decision making. One postdoc is currently working on the fMRI data, and we are looking for another postdoc for the MEG dataset. Both postdocs will work together to perform analyses informed by both modalities. The EXPLORE+ project will continue with another previously funded project called BrainSync, which will collect data from 11.7 fMRI and intracranial recordings using the same task, providing an opportunity to extend the current work. Profile Ph.D. in neuroscience, machine learning or psychology, with good programming skills (ideally Python). Previous experience with ideally MEG, EEG or alternatively fMRI, computational modeling. You will be responsible for data analysis (mainly MEG, also fMRI-MEG in collaboration with Alexander Paunov, postdoc working on the fMRI part) and dissemination of results in internal seminars, international conferences and journal articles. The working language of the lab is English. French is not required. Workplace and environment Dr Florent MEYNIEL leads the Computational Brain team (more info here), which is located in two places. * Institute of NeuroModulation (INM), Sainte Anne Hospital, Paris, France. The INM is part of the GHU Paris, Psychiatry & Neurosciences. The INM combines clinical activities and innovative clinical research in psychiatry with basic research in computational neuroscience. Team members spend most of their days here. * NeuroSpin, Paris-Saclay Campus, France. NeuroSpin is part of the CEA (Commissariat à l'Energie Atomique). Directed by Prof. Stanislas DEHAENE, NeuroSpin is a world-class brain imaging center equipped with a MEG system (Elekta, Neuromag) and several human MRI scanners (3T Prisma, 7T and 11.7T), all for research purposes only. The community at NeuroSpin is very stimulating, combining MRI physicists, machine learning experts, and cognitive neuroscientists. Team members go there to collect data and collaborate with their colleagues in the Cognitive NeuroImaging Unit. Application procedure Please send an email to Florent Meyniel (florent.meyniel(a)cea.fr) and Alexander Paunov (alexander.paunov(a)gmail.com) * Your CV * a research statement (what you like and want to do) * the contact details of two referees Applications will be considered on a rolling basis (positions will remain open until filled). Salary According to CEA standards. According to experience. References 1. Meyniel, F., Schlunegger, D. & Dehaene, S. The Sense of Confidence during Probabilistic Learning: A Normative Account. PLoS Comput Biol 11, e1004305 (2015). 2. Meyniel, F., Sigman, M. & Mainen, Z. F. Confidence as Bayesian Probability: From Neural Origins to Behavior. Neuron 88, 78–92 (2015). 3. Foucault, C. & Meyniel, F. Two Determinants of Dynamic Adaptive Learning for Magnitudes and Probabilities. Open Mind 8, 615–638 (2024). 4. Meyniel, F. Brain dynamics for confidence-weighted learning. PLOS Comput. Biol. 16, e1007935 (2020). 5. Paunov, A. et al. Multiple and subject-specific roles of uncertainty in reward-guided decision-making. 2024.03.27.587016 Preprint at https://doi.org/10.1101/2024.03.27.587016 (2024). 6. Walker, E. Y. et al. Studying the neural representations of uncertainty. Nat. Neurosci. 1–11 (2023) doi:10.1038/s41593-023-01444-y. 7. Bounmy, T., Eger, E. & Meyniel, F. A characterization of the neural representation of confidence during probabilistic learning. NeuroImage 268, 119849 (2023). 8. Meyniel, F. & Dehaene, S. Brain networks for confidence weighting and hierarchical inference during probabilistic learning. Proc. Natl. Acad. Sci. 201615773 (2017) doi:10.1073/pnas.1615773114.

Oct. 15, 2024

Call for Workshop Proposals on Complex Systems at FRCCS 2025

by Hocine Cherifi

The organizing committee of *Fr*ance’s International *C*onference on *C* omplex *S*ystems (FRCCS 2025 <https://iutdijon.u-bourgogne.fr/ccs-france/>) invites proposals for full- or half-day workshops on current or emerging topics in Complex Systems. Workshops provide an interactive platform for in-depth exploration of novel issues or application domains, fostering collaboration across disciplines. We especially welcome multidisciplinary workshops that engage both researchers and practitioners. *Workshop Date:* May 21-23, 2025 *Proposal Deadline:* January 12, 2024 *Workshop Format & Duration* We encourage diverse formats beyond traditional paper presentations, including: - *Discussions*, *demos*, *panels*, and *challenge sessions*. - *Full-day workshops*: 7 hours, including two 30-minute breaks. - *Half-day workshops*: 4 hours, including one 30-minute break. *Organizer Responsibilities* Workshop organizers are responsible for managing their sessions independently, which includes drafting and disseminating the Call for Papers (CFP) for their workshops, reviewing submitted papers, and coordinating with participants. *Proposal Guidelines (2-4 pages in PDF)* Proposals should include the following details: 1. *Title* 2. *Overview*: Key issues, relevance, and associated research areas. 3. *Organizers*: Names, affiliations, and contact information (with one primary contact). 4. *Workshop Format*: Planned structure (talks, panels, etc.). 5. *Duration*: Half-day or full-day. 6. *Call for Submissions* (optional draft). 7. *Expected Submissions and Participants* 8. *Speakers*: Confirmed or pre-contacted (if applicable). 9. *Logistics Needs* (e.g., poster stands, AV equipment). *Incentives* Workshops with more than ten registered contributions will receive a waived registration fee for one organizer or invited speaker. *Important Dates* - *Proposal Submission Deadline* : January 12, 2024 - *Acceptance Notification* : January 26, 2024 - *Workshop Paper Submission Deadline*: March 20, 2024 - *Author Notification* : April 17, 2024 *Submission Link* Submit your proposal via: https://cmt3.research.microsoft.com/FRCCS2025/. Choose the "Workshop Proposal" track. *Publication* Workshop contributions will be included in the FRCCS 2025 conference companion book (with ISBN). Selected submissions may be invited for publication in partner journals. *Why Organize a Workshop?* By organizing a workshop, you will: - Shape discussions on cutting-edge topics in Complex Systems. - Build networks with leading researchers and practitioners. - Promote interdisciplinary collaboration and share your expertise with an engaged audience. *We look forward to receiving your innovative and exciting workshop proposals!* For more details, visit: https://iutdijon.u-bourgogne.fr/ccs-france/workshops-proposals/ Or contact the workshop chair Maria Malek maria.malek(a)cyu.fr Join us at COMPLEX NETWORKS 2024 <https://www.complexnetworks.org/> *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comté Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Editor in Chief Plos Complex Systems <https://plos.org/complex-systems-research-journal/#:~:text=PLOS%20Complex%2….> Founding & Adisory Editor Applied Network Science <https://appliednetsci.springeropen.com/> Editorial Board member PLOS One <https://journals.plos.org/plosone/>, IEEE ACCESS <https://ieeeaccess.ieee.org/?http%3A%2F%2Fieeeaccess_ieee_org%2F>, Scientific Reports <https://www.nature.com/srep/>, Journal of Imaging <https://www.mdpi.com/journal/jimaging>, Quality and Quantity <https://www.springer.com/journal/11135/>, Computational Social Networks <https://computationalsocialnetworks.springeropen.com/>, Complex Systems <https://www.complex-systems.com/>

Oct. 15, 2024

Brains in Space - A virtual colloquium on spatial navigation

by Vinita Samarasinghe

On behalf of Sen Cheng, Sandhiya Vijayabaskaran and Laurenz Wiskott from the Institute of Neural Computation, Faculty for Computer Science, Ruhr University Bochum, I invite you to attend a colloquium series "*Brains in Space: An Interdisciplinary Research Colloquium on Spatial Navigation*". In this colloquium, speakers will present their research in various areas of spatial navigation, including behavioral, neuroscientific, and theoretical approaches. The goal is to foster interdisciplinary discussions along the lines of the review article "A Map of Spatial Navigation for Neuroscience" (Parra-Barrero et al., 2023) that proposes a taxonomy of spatial navigation processes in mammals. The talks will cover a diverse range of topics, from the neural underpinnings of navigation to complex navigation behaviors. Attendees will gain a better understanding of how the mammalian brain represents and navigates through space, as well as learn about several cognitive processes such as learning and memory through the lens of spatial navigation. The colloquium takes place virtually on Tuesday's from 16:00 to 17:30 (CET) and the complete schedule can be found at https://www.ini.rub.de/teaching/courses/colloquium_brains_in_space_an_inter… . The first talk is on October 29th 2024.* * *Confirmed speakers include:* Arne Ekstrom, Klaus Gramann, Michael Hornberger, Russell Epstein, Ed Manley and Behnam Ghazinouri. This colloquium is open to the public. Please feel free to forward this information to any of your colleagues who may be interested. Zoom link: https://ruhr-uni-bochum.zoom-x.de/j/67839364827?pwd=RfcIgK8OUfjkwWTNCf80ARX… [Meeting ID: 678 3936 4827; Passcode: 841644] October 29th: *Klaus Gramann* - TU Berlin *Title:* Mobile Brain/Body Imaging in Actively Navigating Humans *Abstract:* The human brain is embodied, intertwined with our physical form, leveraging this embodiment to enhance perception in complex and dynamically changing environments. Traditional brain imaging techniques have largely ignored these aspects of embodied cognition. However, recent years have witnessed a significant paradigm shift, with established brain imaging technologies being employed outside conventional experimental frameworks to record brain dynamics in actively behaving individuals. This evolution in research methodologies introduces new challenges in both hardware and analytical approaches but allows for unprecedented insights into human brain activity underlying natural cognition. In this presentation, I will provide an overview of research in the Berlin Mobile Brain/Body Imaging Labs that focus on the neural dynamics underlying human navigation using mobile EEG technologies. Utilizing Mobile Brain/Body Imaging (MoBI), I will present findings from experiments that examine multisensory integration during navigation, both within classical laboratory protocols and in scenarios that permit full-body movement in virtual and real-world settings. The results reveal substantial changes in brain dynamics in actively behaving participants compared to traditional brain imaging configurations, highlighting important implications for future research directions. We look forward to seeing you. Kind regards, Vinita -- Vinita Samarasinghe Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/73 Postfachnummer 110 Universitätstr. 150 D-44801 Bochum Tel: +49 (0)234 32 27996 Email:samarasinghe@ini.rub.de

Oct. 15, 2024

Faculty position in Mathematical Biology

by Alla R Borisyuk

The Department of Mathematics at the University of Utah has an OPEN RANK FACULTY POSITION search in Mathematical Biology (including Computational Neuroscience). Please help us spread the word by forwarding this announcement to anyone who might be interested. For the official job announcement please see www.mathjobs.org/jobs/UofUtah/TTMATHBIO and please let us know if you have any questions. Alla Borisyuk Professor Department of Mathematics University of Utah

Oct. 14, 2024

Creating an inclusive and anti-racist academia – Online Panel Discussion and Q&A – 28th October, 1pm GMT / 2pm CET

by Sidarus, Nura

Creating an inclusive and anti-racist academia Online Panel Discussion with Q&A Monday, October 28 1-2pm GMT / 2-3pm CET Details & registration: https://www.eventbrite.com/e/1027101356807 Despite ongoing efforts to promote anti-racism and equity, diversity, and inclusion (EDI), systemic inequalities persist and academic work often remains limited to Western perspectives, neglecting the rich diversity of global knowledge systems. Women in Cognitive Science-Europe<https://www.womenincogsci.org/wics-europe> is organising this discussion on occasion of the United Kingdom’s Black History Month, making time to recognise the contribution of Black scholars and thought, and foster conversations that challenge the cultural narratives and practices that marginalise people of colour. We believe we all need to work together to fight against all types of discrimination and marginalisation. Panelists will provide evidence and showcase ongoing initiatives to promote a more inclusive and anti-racist academia. Attendees will gain insights into these issues and be inspired to take action in their own contexts. Panelists: * Prof. Felix Ameka, Leiden University, The Netherlands * Prof. Narender Ramnani, Royal Holloway, University of London, UK * Dr. Nura Sidarus, Royal Holloway, University of London, UK Join us and help us spread the word about this event. Everyone is welcome! Details & registration: https://www.eventbrite.com/e/1027101356807 __________________________________________________________ Dr Nura Sidarus (she/her) Lecturer | Chair of Equity, Diversity & Inclusion Team Department of Psychology | Office: Wolfson 248 Royal Holloway University of London | Egham | TW20 0EX Affiliate Member | Institute of Cognitive Neuroscience, UCL Computations in Agency and Metacognition Lab<https://www.compagencymeta.com/> nura.sidarus(a)rhul.ac.uk<mailto:%20nura.sidarus@rhul.ac.uk> | Personal Website<http://www.nurasidarus.com/> __________________________________________________________ This email, its contents and any attachments are intended solely for the addressee and may contain confidential information. In certain circumstances, it may also be subject to legal privilege. Any unauthorised use, disclosure, or copying is not permitted. If you have received this email in error, please notify us and immediately and permanently delete it. Any views or opinions expressed in personal emails are solely those of the author and do not necessarily represent those of Royal Holloway, University of London. It is your responsibility to ensure that this email and any attachments are virus free.

Oct. 14, 2024

Apply to the Bertalanffy Doctoral Student Award @ FRCCS 2025

by Hocine Cherifi

*DOCTORAL STUDENT AWARD* <https://iutdijon.u-bourgogne.fr/ccs-france/doctoral-student-award/> *@ **FRCCS 2025* <https://iutdijon.u-bourgogne.fr/ccs-france/> The Bertalanffy Doctoral Student Award is part of CSS FRANCE's <https://www.cssfrance.org/> global initiative to support early career researchers in their quest to advance the frontiers of science across a broad range of disciplines. It is in place to recognize early career contributions and leadership in research in Complex Systems related fields. It is awarded to young researchers enrolled in a Ph.D. program. This competition consists of presenting your research in simple terms in a five-minute video to a lay audience. Your presentation should be clear, concise, and convincing. *Eligibility* - Eligible candidates must: - Be under 30. - Be enrolled in a Ph.D. program in whatever discipline Complex Systems covers. - Commit to presenting their work at France's International Conference on Complex Systems <https://iutdijon.u-bourgogne.fr/ccs-france/> ( FRCCS 2025) <https://iutdijon.u-bourgogne.fr/ccs-france/> if awarded - Accept and authorize the use and distribution of videos and photos related to the competition, including on social networks - Have informed their thesis supervisor of their participation in the competition - Present a sufficiently advanced state of the doctoral research project - Individuals may only be candidates for this award once in their lifetime. *Important dates* · Application deadline: *March 11, 2025* · Notification to applicants: *April 02, 2025* *Application Instruction* The application package must contain the following: - A CV of the candidate (maximum two pages) - A summary (maximum two pages) presenting the research work, its context, main contribution, and scientific impact. - A 5-minute video presentation. *Application Process* Applications are made via a Google form on the online portal. <https://forms.gle/CEGYgJFV8MoiSQS36> *Note that Google Forms requires you to be signed in to a Google account to upload files and submit your responses. * *Selection Process* FRCCS Award Committee will evaluate all qualified candidates and propose the winner to the Advisory Board of CSS FRANCE, which will make the final decision. *Award Procedure* · The awardee will be recognized and present their work at FRCCS 2025 <https://iutdijon.u-bourgogne.fr/ccs-france/>. · The awardee will receive a 500-euro prize. · If the awardee is not an author at FRCCS 2025 <https://iutdijon.u-bourgogne.fr/ccs-france/>, the prize will include an additional coverage of their registration fee. · If the awardee has an accepted submission to FRCCS 2025 <https://iutdijon.u-bourgogne.fr/ccs-france/>,, they need to pay the registration fee for their contribution. For more information, contact: hocine.cherifi(a)gmail.com Join us at COMPLEX NETWORKS 2024 <https://www.complexnetworks.org/> *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comté Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Editor in Chief Plos Complex Systems <https://plos.org/complex-systems-research-journal/#:~:text=PLOS%20Complex%2….> Founding & Adisory Editor Applied Network Science <https://appliednetsci.springeropen.com/> Editorial Board member PLOS One <https://journals.plos.org/plosone/>, IEEE ACCESS <https://ieeeaccess.ieee.org/?http%3A%2F%2Fieeeaccess_ieee_org%2F>, Scientific Reports <https://www.nature.com/srep/>, Journal of Imaging <https://www.mdpi.com/journal/jimaging>, Quality and Quantity <https://www.springer.com/journal/11135/>, Computational Social Networks <https://computationalsocialnetworks.springeropen.com/>, Complex Systems <https://www.complex-systems.com/>

Oct. 14, 2024

CFP FRCCS 2025 Bordeaux, France May 21 – 23, 2025

by Hocine Cherifi

Fifth France’s International* C*onference on* C*omplex* S*ystems May 21 – 23, 2025 Bordeaux, France *FRCCS 2025* <https://iutdijon.u-bourgogne.fr/ccs-france/> The fifth edition of France’s International Conference on Complex Systems (FRCCS 2025) will be held in Bordeaux, France. This single-track international conference serves as a platform to foster interdisciplinary exchanges among researchers from various scientific disciplines and diverse backgrounds, including sociology, economics, history, management, archaeology, geography, linguistics, statistics, mathematics, and computer science. FRCCS 2025 allows participants to meet yearly in France, exchange and promote ideas, and facilitate the cross-fertilization of recent research work, industrial advancements, and original applications. Moreover, the conference emphasizes research topics with a high societal impact, showcasing the significance of complexity science in addressing complex societal challenges. You are cordially invited to submit your contribution by *February 21, 2025.* Finalized work (published or unpublished) and work in progress are welcome. Three types of contributions are accepted: · *Long Papers* about *original research* (up to 12 pages) · *Short Papers *about* original research* (up to 8 pages) · *Extended Abstract* about *published or unpublished* research (3 to 4 pages). *Keynote Speakers* · Elsa Arcaute, <https://www.ucl.ac.uk/bartlett/casa> University College London, UK · Ulrik Brandes <https://sn.ethz.ch/> ETH Zürich Switzerland · Mikko Kivelä, <http://www.mkivela.com/> Aalto University, Finland · Caterina La Porta, <https://www.oncolab.unimi.it/about-caterina/> University of Milan, Italy · *More TBA…* *Publication* o *Papers *will be included in the conference *proceedings edited by Springer* o *Extended abstracts* will be included in the book of abstracts (With ISBN) o *Selected submissions of unpublished work will be invited for publication in special issues (fast track procedure) **of the journals:* o Applied Network Science, <https://appliednetsci.springeropen.com/> edited by Springer o Frontiers in Big Data <https://www.frontiersin.org/journals/big-data> edited by Frontiers *Submission * · Submit on CMT Microsoft at: https://cmt3.research.microsoft.com/FRCCS2025/ <https://cmt3.research.microsoft.com/FRCCS2025/> · *Select the Track: FRCCS2025* *Topics include, but are not limited to: * · *Foundations of complex systems * - Self-organization, non-linear dynamics, statistical physics, mathematical modeling and simulation, conceptual frameworks, ways of thinking, methodologies and methods, philosophy of complexity, knowledge systems, Complexity and information, Dynamics and self-organization, structure and dynamics at several scales, self-similarity, fractals - *Complex Networks * - Structure & Dynamics, Multilayer and Multiplex Networks, Adaptive Networks, Temporal Networks, Centrality, Patterns, Cliques, Communities, Epidemics, Rumors, Control, Synchronization, Reputation, Influence, Viral Marketing, Link Prediction, Network Visualization, Network Digging, Network Embedding & Learning. - *Neuroscience, **Linguistics* - Evolution of language, social consensus, artificial intelligence, cognitive processes & education, Narrative complexity - *Economics & Finance* - Game Theory, Stock Markets and Crises, Financial Systems, Risk Management, Globalization, Economics and Markets, Blockchain, Bitcoins, Markets and Employment - *Infrastructure, planning, and environment * - critical infrastructure, urban planning, mobility, transport and energy, smart cities, urban development, urban sciences - *Biological and (bio)medical complexity * - biological networks, systems biology, evolution, natural sciences, medicine and physiology, dynamics of biological coordination, aging - *Social complexity* o social networks, computational social sciences, socio-ecological systems, social groups, processes of change, social evolution, self-organization and democracy, socio-technical systems, collective intelligence, corporate and social structures and dynamics, organizational behavior and management, military and defense systems, social unrest, political networks, interactions between human and natural systems, diffusion/circulation of knowledge, diffusion of innovation - *Socio-Ecological Systems* - Global environmental change, green growth, sustainability & resilience, and culture - *Organisms and populations * - Population biology, collective behavior of animals, ecosystems, ecology, ecological networks, microbiome, speciation, evolution - *Engineering systems and systems of systems* - bioengineering, modified and hybrid biological organisms, multi-agent systems, artificial life, artificial intelligence, robots, communication networks, Internet, traffic systems, distributed control, resilience, artificial resilient systems, complex systems engineering, biologically inspired engineering, synthetic biology - *Complexity in physics and chemistry* - quantum computing, quantum synchronization, quantum chaos, random matrix theory - *Machine learning and AI in the context of Complex Systems* *GENERAL CHAIRS* Jean Loup Guillaume La Rochelle University, France Bruno Pinaud University of Bordeaux, France *PROGRAM CHAIRS* Hocine Cherifi University of Burgundy, France Guy Melançon University of Bordeaux, France Join us at COMPLEX NETWORKS 2024 <https://www.complexnetworks.org/> *-------------------------* Hocine CHERIFI University of Burgundy Franche-Comté Laboratoire* I*nterdisciplinaire *C*arnot de *B*ourgogne - ICB UMR 6303 CNRS Editor in Chief Plos Complex Systems <https://plos.org/complex-systems-research-journal/#:~:text=PLOS%20Complex%2….> Founding & Adisory Editor Applied Network Science <https://appliednetsci.springeropen.com/> Editorial Board member PLOS One <https://journals.plos.org/plosone/>, IEEE ACCESS <https://ieeeaccess.ieee.org/?http%3A%2F%2Fieeeaccess_ieee_org%2F>, Scientific Reports <https://www.nature.com/srep/>, Journal of Imaging <https://www.mdpi.com/journal/jimaging>, Quality and Quantity <https://www.springer.com/journal/11135/>, Computational Social Networks <https://computationalsocialnetworks.springeropen.com/>, Complex Systems <https://www.complex-systems.com/>

Oct. 14, 2024

Faculty position in Theoretical/Computational Neuroscience

by Goodhill, Geoffrey

The Department of Neuroscience at Washington University School of Medicine is seeking a tenure-track investigator at the level of Assistant Professor to develop an innovative research program in Theoretical/Computational Neuroscience. Applicants should have a demonstrated commitment to neuroscience and a strong background in mathematics, physics, engineering, computer science, or a related field and hold a PhD. Areas of interest include (but are not limited to) research on fundamental molecular/cellular/circuit/systems mechanisms of brain architecture/development/function, machine learning methods for neuroscientific data, neuro-AI, and computational cognition/behavior/psychiatry. We seek talented, creative, and ambitious candidates from the entire span of computational neuroscience, and we are especially interested in candidates interested in building collaborations with experimental groups. The successful candidate will join a thriving theoretical/computational neuroscience community at Washington University, including the new Center for Theoretical and Computational Neuroscience. In addition, the Department also has world-class research strengths in systems, circuits and behavior, cellular and molecular neuroscience using a variety of animal models including worms, flies, zebrafish, rodents and non-human primates. The Department’s focus on fundamental neuroscience, outstanding research support facilities, and the depth, breadth and collegiality of our culture provide an exceptional environment to launch your independent research program. To apply, submit an application packet including a cover letter describing your interest in our Department, curriculum vitae, a research statement (of no more than 3 pages) to the Faculty Opportunities Portal and arrange for three confidential letters of recommendation to be sent to neurosearch(a)wustl.edu c/o Professor Timothy E. Holy, Vice Chair for Research, Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110. The review of applications will begin on November 4, 2024. Washington University is an Equal Opportunity Employer, and broadening opportunity is core mission of the institution. Our department highly values all our researchers, staff and trainees, and we provide an inclusive environment for people from diverse backgrounds and experiences. For more information about the Department, Washington University, and life in St. Louis, visit: https://neuroscience.wustl.edu/assistant-professor-theoretical-computationa… Professor Geoffrey J Goodhill Departments of Developmental Biology and Neuroscience Director, Center for Theoretical and Computational Neuroscience (ctcn.wustl.edu) Affiliate appointments: Physics, Biomedical Engineering, Computer Science and Engineering, and Electrical and Systems Engineering Washington University School of Medicine 4370 Duncan Ave. St Louis, MO 63110 g.goodhill(a)wustl.edu https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd

Oct. 12, 2024

Cluster Hiring of UT System Research Excellence Regents' Professorships at UTSA

by Dhireesha Kudithipudi

The University of Texas at San Antonio (UTSA), MATRIX AI Consortium, invites applications for the position of Full Professor / Associate Professor, to be appointed as a University of Texas System (UT System) Research Excellence Regents' Professor. Successful candidates will be part of a strategic Clustered & Connected Hiring Program (CCP) <https://www.utsa.edu/strategicplan/initiatives/research/strategic-hiring/cc…> focused on Artificial Intelligence, with an anticipated start date in the Fall of the 2025-26 academic year. The University of Texas System recently approved the creation of the Regents’ Research Excellence Program across its four Emerging Research Universities (ERUs), including UTSA. UT System has allocated $55 million across all four ERUs to fund the recruitment of research-active faculty to dramatically grow its national research prominence and federal funding opportunities. The 5 positions open are in areas: 1. *Trustworthy AI/ML Algorithms (eg: neuro-inspired algorithms)* 2. *Neuromorphic AI Accelerators/Chips* 3. *Human-Centered AI* 4. *AI Ethics* 5. *Quantum Encryption for AI Confidentiality* The Regents Professors will be core members of the MATRIX Consortium, which is a central hub for 87 AI scientists, facilitating transdisciplinary research, fostering high-impact collaborations, and offering thought leadership and domain expertise to address the most challenging and complex problems in AI. Areas of interest include Trustworthy AI/ML Algorithms, Neuromorphic AI Accelerators, Human-centered AI, AI Ethics, all of which advance the research thrusts in the MATRIX. MATRIX strives for scientific excellence in developing holistic solutions for human well-being. The team has a successful track record in securing large collaborative grants that generated multiple centers, such as the NSF AI Partner Institute, two NSF EFRI BRAIDs, AFOSR COE in neuro-inspired AI, along with large collaborative projects in AI for healthcare. Apply here: https://zahr-prd-candidate-ada.utshare.utsystem.edu/psc/ZAHRPRDADA/EMPLOYEE… Best Regards, Dhireesha Kudithipudi Founding Director| MATRIX <https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fai.utsa.e…> AI Consortium & NUAI <https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nuail…> Research Lab Professor| McDermott Endowed Chair| ECE/CS| UTSA

Oct. 11, 2024

Postdoc positions at U Oregon

by James Murray

Postdoc positions are available at the University of Oregon’s NeuroAI Center (ion.uoregon.edu/neuroai<https://urldefense.com/v3/__https://ion.uoregon.edu/neuroai__;!!K-Hz7m0Vt54…>) in the Murray and Mazzucato labs. In our research, we seek to uncover the principles of how the brain performs computations related to sensory perception, decision making, and motor control. While previous experience in computational neuroscience and machine learning are desirable, applicants from other quantitative fields (e.g. math, physics, statistics, computer science) who are eager to learn about neuroscience are highly encouraged to apply as well. Some of the scientific questions that motivate our work are * How do different regions of the brain interact to learn new motor skills? * What are the neural mechanisms underlying optimal performance in complex cognitive tasks? * What are the principles that enable brains and artificial agents to learn efficiently from experience while minimizing forgetting? * How can neural circuits generate the complex dynamics enabling naturalistic animal behavior? Our labs aim at building mechanistic models of brain function grounded in a combination of theoretical approaches, neural network-based simulations, and statistical analysis of experimental data. The candidate will have the opportunity to collaborate with a large network of experimental collaborators at University of Oregon and at other institutions with expertise in sensory processing (visual, auditory, and olfactory), motor control, naturalistic behavior, neural engineering, and brain-computer interfaces. The Oregon NeuroAI Center is part of the Institute of Neuroscience at the University of Oregon (ion.uoregon.edu<https://urldefense.com/v3/__http://https.ion.uoregon.edu__;!!K-Hz7m0Vt54!jj…>), a major hub for systems and theoretical neuroscience research. The successful candidate will also join our International Network for Bio-Inspired Computing (in-bic.org<https://urldefense.com/v3/__http://www.in-bic.org__;!!K-Hz7m0Vt54!jjW_DXqAj…>), a worldwide consortium of NeuroAI groups that provides trainees with an extended network for collaboration, including trainee exchanges, workshops, and schools. The University of Oregon is located in Eugene, Oregon, a vibrant college town in the Pacific Northwest with ample cultural offerings and phenomenal access to outdoor recreation. We offer a competitive salary commensurate with the candidate’s experience, and remote work arrangements may be considered. Our Institute strongly advocates for inclusivity in science, and we encourage applications from underrepresented groups. Required Qualifications Successful candidates will have a PhD in a quantitative field, including physics, neuroscience, mathematics, statistics, computer science, or related fields. Applicants should have a strong quantitative background including at least some coding experience. Application The application can be found here: https://academicjobsonline.org/ajo/jobs/28843. Application reviews will start on December 1st and will continue until the position is filled. Inquiries can be sent to James Murray (jmurray9 at uoregon dot edu) or Luca Mazzucato (lmazzuca at uoregon dot edu). -- James M Murray Assistant Professor Depts. of Biology and Mathematics and Institute of Neuroscience University of Oregon murraylab.uoregon.edu<https://urldefense.com/v3/__https://murraylab.uoregon.edu__;!!K-Hz7m0Vt54!j…>

Oct. 11, 2024

1st CFP ESANN 25: Special Session on ML and applied AI in COGNITIVE SCIENCES and PSYCHOLOGY

by Alfredo Vellido

> > > > > * apologies for cross-posting* > > > > **Special Session on ML and applied AI in COGNITIVE SCIENCES and PSYCHOLOGY** > > > > **ESANN 2025**: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning > > 23 to Friday 25 April 2025 > > > > https://www.esann.org/ESANN2025specialsessions#psycho > > > > *************************************************** > > On the wake of the finalisation of the European flagship Human Brain Project and similar initiatives around the world, it has become clear that Cognitive Science has become a data-centric endeavour. Cognitive Science is an interdisciplinary research field comprising neuroscience, psychology, linguistics, artificial intelligence, and philosophy. In particular, mental health is an important topic both for Cognitive Science and Healthcare. Data-based approaches stemming from Artificial Intelligence and particularly from Machine Learning are important tools in the pursuit of personalized medicine goals as means for improvement in diagnosis, prognosis and treatment. In the medical domain in general, both the trustworthiness of models and the explainability of methods are relevant for the adoption of such machine learning-based approaches in clinical diagnosis and treatment. This session will consider developments in the field of applied Artificial Intelligence for Cognitive Science, with a focus on medical applications. Topics of interest are, among others: > > - Neuroscience > > - Psychology and Psychiatry > > - Neurodegenerative diseases > > - Linguistics > > - Philosophy > > - Artificial Intelligence applications for diagnosis, prognosis and treatment of cognitive impairments and pathologies. > > - Patient cohort analysis. > > - Interpretable and explainable artificial intelligence methods in Cognitive Science. > > - Personalized medicine. > > - Artificial Intelligence–based medical devices regulation. > > > > **IMPORTANT DATES** > > Deadline for submissions: 20 November 2024 > > Notification of decisions: 24 January 2025 > > > > We are looking forward to seeing you in Bruges! > > **Organizing Committee**: Caroline König and Alfredo Vellido (UPC Barcelona Tech, Spain), Steffen Moritz (University Medical Center Hamburg-Eppendorf, Germany), Susana Ochoa (Parc Sanitari Sant Joan de Déu, Spain) > > >

Oct. 11, 2024

Postdoc Position in Computational Neuroscience and Neuroimaging at UNC-Chapel Hill

by Li, Guoshi

Dear Colleagues, A postdoctoral research associate position is available in the Department of Radiology, at UNC-Chapel Hill (https://guoshi.web.unc.edu/recruit/) The postdoctoral researcher will carry out research on computational neuroimaging and neuroscience using functional/diffusion MRI and PET data. Potential research projects include, but are not limited to, mechanistic identification of excitation-inhibition imbalance in Alzheimer's disease using fMRI/DTI and amyloid and tau PET, large-scale mapping of disrupted circuit interactions in major depressive disorders, and accurate localization of seizure onset zone via multiscale neural model inversion of resting-state fMRI. Initial appointment is for one year, with the possibility of renewal up to 3 years based on mutual agreement. A preferred start date of the position is November/December 2024, although it can be flexible. Candidates should have a strong background in computational neuronal modeling and neuroimaging analysis. Interested candidates are encouraged to contact Dr. Guoshi Li (guoshi_li(a)med.unc.edu<mailto:guoshi_li@med.unc.edu>) with a CV and a brief description of research interest. Thank you for your attention! Best regards, Guoshi Li https://guoshi.web.unc.edu/

Oct. 10, 2024