- Comp-neuro - lists.cnsorg.org

Origins of Order in Behaviour Workshop: Deadline extended till Feb 15h
by Mateusz Kostecki 12 Feb '24

12 Feb '24

Dear Colleagues, we have extended the deadline for our Workshop of Ideas in Neuroscience: Origins of Order in Behaviour till Feb 15th! Come to Warsaw, to beautiful wooden house in the middle of the greenest part of the city, to discuss the concept of instinct and innate behaviour, the role of genes, environmental and organismal factors in the development of behaviour and behavioural evolution together with our fantastic guest: Kevin Mitchell, Gregory Kohn, Joanna Rączaszek Leonardi and Daniel Czegel. The workshop will be based on extensive talks and discussions in an informal atmosphere - more info can be found here - https://nenckiopenlab.org/origins_of_order/ Best, Mat -- --- Mateusz Kostecki PhD Student Knapska Laboratory Nencki Institute 02-093 Warsaw, Pasteura 3, Poland https://twitter.com/mtkostecki https://evolvingbehavior.blog/

1 0

position: data scientist / data analyst researcher at NIMH
by Francisco Pereira 11 Feb '24

11 Feb '24

(reposting for a colleague, please follow contact instructions at the end if interested; apologies for repeated postings!) ### HIRING: Data Analyst / Data Scientist Position at the CDN Lab The Unit on Computational Decision Neuroscience (CDN, https://www.nimh.nih.gov/research/research-conducted-at-nimh/research-areas… ) at the National Institute of Mental Health is seeking a full-time Data Scientist/Data Analyst. The lab is focused on understanding the neural and computational bases of adaptive and maladaptive decision-making and their relationship to mental health. Current studies investigate how internal states lead to biases in decision-making and how this is exacerbated in mental health disorders. Our approach involves a combination of computational model-based tasks, questionnaires, biosensor data, fMRI, and intracranial recordings. The main models of interest come from neuroeconomics, reinforcement learning, Bayesian inference, signal detection, and information theory. The main tasks for this position include but are not restricted to computational modeling of behavioral data from decision-making and other cognitive tasks, statistical analysis of task-based, clinical, physiological and neuroimaging data, as well as data visualization for the purposes of scientific presentations, public communication, and academic manuscripts. The candidate is expected to demonstrate experience with best practices for the development of well-documented, reproducible programming pipelines for data analysis, that facilitate sharing and collaboration, and live up to our open-science philosophy, as well as to our data management and sharing commitments at NIH. No prior experience with psychiatry research is needed but a familiarity with the constructs and models of interest in the lab (value-based learning and decision-making, metacognition, belief updating, emotion regulation, and/or effort-cost estimation) is desirable, as these are universally important for understanding adaptive healthy functioning and psychiatric disease. This is an exciting opportunity for a candidate with established programming and analytic skills to work at the cutting edge of psychiatry research and computational cognitive neuroscience. You can find more about our work and recent publications at https://www.nimh.nih.gov/research/research-conducted-at-nimh/research-areas… ## Job Requirements: - Assisting with setting up and managing analysis pipelines - Conducting advanced analysis of behavioral, physiological, and imaging data, including but not limited to computational modeling and machine learning - Integrating complex datasets across multiple modalities, including fMRI, electrophysiology, biosensor data neuroendocrinology, behavior, and self-report - Assisting in data visualization for manuscripts and presentation of results at scientific meetings - Supporting/co-mentoring junior members of the lab on data analysis practices ## Qualifications: - A PhD in neuroscience, cognitive science, psychology, computer science, data science, statistics, engineering, or a related field - Strong programming skills (ideally in Python, and/or MATLAB, R) - Experience working within Linux environment and cloud computing - An ability to work well in multidisciplinary and highly collaborative teams - An interest in translational research - A track record or potential for scholarly productivity - Effective independent problem-solving and task prioritization ## Experience with any of the following is not required, but preferred: - Computational modeling (mathematical optimization, reinforcement learning, Bayesian inference, neuroeconomics or other types of modeling of human/animal learning and decision-making) - statistical inference (e.g. generalized linear models, mixed effect models, state space models, survival analysis) - Dynamic analysis of longitudinal or time series data (e.g. neuroimaging, MEG, EEG, or neural recordings) - Advanced statistical methods and machine learning The data analyst will work under the supervision of Dr. Silvia Lopez-Guzman on projects that aim to understand (1) the process of adaptively evaluating options and committing to a choice; (2) how changes in internal and motivational states may abnormally shape decisions in individuals with and without psychopathology; and (3) how cognitive and metacognitive resources support these adaptive or maladaptive decision-making processes. The CDN lab leverages the rich clinical resources and computational expertise across the NIH, and collaborates actively with labs that specialize on addiction, depression, anxiety, and pain. The lab is an active part of a growing community of expert labs on learning and decision-making who work together to improve our understanding from the circuits and behavioral neuroscience level to the human cognitive and clinical levels, making this a unique opportunity for any scientist with an interest in decision science and computational psychiatry. ## How to Apply: To apply, please send your CV and a cover letter to Dr. Silvia Lopez-Guzman (silvia.lopezguzman(a)nih.gov ) with the subject “CDN Lab Data Analyst App”. Inquiries about any aspect of the position are very welcome!

1 0

Grenoble Neurotech School 2024 (Aussois, France, April 2-5): Preregistration opened
by Blaise Yvert 09 Feb '24

09 Feb '24

Dear Colleagues, We are pleased to announce the upcoming school on Neurotechnologies organized by the Grenoble-Neurotech IDEX project from the University Grenoble Alpes The school will be held at the CNRS Paul Langevin center in Aussois on April 2-5, 2024 It is intended for PhD students, postdocs, young scientists and anyone interested by neurotechnologies. For this first edition, the number of selected applications will be limited to 40 We will provide certificates of attendance for PhD students in case they would like to make this school validated by their doctoral school Here are 3 links for details: Descriptive flyer: https://framaforms.org/sites/default/files/forms/files/grenoble_neurotech_s… Program: https://framaforms.org/sites/default/files/forms/files/grenoble_neurotech_s… Free pre-registration: https://framaforms.org/grenoble-neurotech-school-2024-1698319763 Selected applicants will then be asked to register and make payment by the end of February Kind regards, Blaise Yvert, for the organizing committee.

1 0

ICANN 2024 - First Call for Papers
by Sebastian Otte 09 Feb '24

09 Feb '24

ICANN 2024 - FIRST CALL FOR PAPERS ======================================================================= The International Conference on Artificial Neural Networks (ICANN) is the annual flagship conference of the European Neural Network Society (ENNS). In 2024, the ICANN will take place in Lugano, Switzerland. Conference Dates: September 17 to September 20, 2024 Conference Venue: Campus of the University of Southern Switzerland and the University of Applied Sciences and Arts of Southern Switzerland, Via la Santa 1, 6962 Lugano-Viganello, Switzerland. Conference Webpage: https://icann2024.org The ICANN 2024 features three conference tracks, namely AI and Machine Learning, Bio-Inspired Computing, and the Applications Track, making it a unique forum to bring together researchers across a wide range of disciplines related to Artificial Intelligence and Neural Networks. ======================================================================= We invite prospective authors to submit original and innovative papers in the following areas: AI and Machine Learning: Theory and Foundations of Neural Networks, Novel Neural Network Architectures, Topics in Neural Networks, Large Language Models, Explainable AI, Graph Methods, Graph Neural Networks, and Clustering, Reinforcement Learning, Topics in Artificial Intelligence and Machine Learning Bio-Inspired Computing: Brain-Inspired Computing, Cognitive and Theoretical/Computational Neuroscience Applications: Human-Computer Interaction, Biosignal Processing, Medicine and Physiology, Speech and Language Processing, Computer Vision, Robotics, Climate and Environment, General Applications of Machine Learning Workshops: - AI in Drug Discovery - Deep Learning for Neuro-heuristic Brain Analysis - Reservoir Computing Special Sessions: - Spiking Neural Networks and Neuromorphic Computing - Accuracy, Stability, and Robustness in Deep Neural Networks - Antifragile dynamical systems: beyond robustness, resilience, and adaptiveness - Neurorobotics For details and updates, as well as for the final list of workshops and special sessions, consider the current version of the list at: https://e-nns.org/icann2024/conference-programme/conference-topics The ICANN 2024 will be an in-person conference. We expect that at least one co-author of each paper will be physically present in Lugano to give his or her presentation. We will also enforce a no-show rule, in order to encourage an optimal quality of the scientific discussion here in Lugano. Papers must be written in English language and must conform to the format defined in the Author’s Kit, available on the conference webpage at: https://e-nns.org/icann2024/submission Both short papers (6-11 pages) and full papers (12-15 pages) can be submitted. Papers shorter than 6 pages will not be accepted to the main conference, please check special submission rules for the conference workshops on the webpage of the respective workshop if you plan to submit there. Papers will undergo rigorous peer review; the Program Committee will make the final decision which papers will be included in the conference program. For papers with conflicting reviews, or which are on the borderline between acceptance and rejection, a short rebuttal phase is foreseen. Full papers will usually be assigned to oral sessions (15 minutes presentation + 5 minutes questions), short papers may be assigned to oral or poster sessions, depending on the quantity of submissions; this assignment does in no way incur a judgment on paper quality. Note that presentation rules for workshops and special sessions may differ. All accepted papers will be published in the Springer LNCS series. KEYNOTE SPEAKERS Jürgen Schmidhuber, IDSIA USI-SUPSI, Switzerland, and KAUST AI Initiative, Saudi Arabia Tanja Schultz, University of Bremen, Germany Walter Senn, University of Bern, Switzerland Henry Markram, École polytechnique fédérale de Lausanne, Switzerland CONFERENCE COMMITTEE General Chairs Jürgen Schmidhuber, IDSIA USI-SUPSI, Switzerland, and KAUST AI Initiative, Saudi Arabia Igor Tetko, HGMU Munich, Germany Program Chairs Michael Wand, IDSIA USI-SUPSI, Switzerland Kristína Malinovská, Comenius University, Bratislava, Slovakia Honorary Chair Stefan Wermter, University of Hamburg, Germany Full list of the organization committee: https://e-nns.org/icann2024/organization/organising-committee IMPORTANT DATES - Opening of submission portal: Feb 15 2024 - Deadline for full paper submission: March 15 2024 - Notification of Acceptance or Rebuttal: May 15 2024 - Deadline for rebuttal: May 31 2024 - Final notification of Acceptance or Rejection after Rebuttal: June 10 2024 - Camera-ready paper upload and author registration: June 30 2024 Contact: For questions, please contact program-committee(a)icann2024.org. Link to this call: https://e-nns.org/icann2024/call-for-papers

1 0

Available Ph.D. Position in Health Care and Machine Learning
by Amir Aly 08 Feb '24

08 Feb '24

Dear All, *Apologies for cross-posting* We are pleased to announce an opportunity for a funded PhD studentship (*BioMarkML: Machine Learning-Driven Bio-Sensing for Early Diagnosis of Alzheimer’s Disease*) at Plymouth University, UK. The closing date for applications is *12 noon on **15th March 2024* *(The difference in tuition fees between national and international students will be waived for excellent international candidates)*. More details *about the topic *and *how to apply* are available at: https://www.jobs.ac.uk/job/DFL216/phd-studentship-biomarkml-machine-learnin… If you have any questions, please don't hesitate to contact me, Regards ---------------- *Dr. Amir Aly* Lecturer in Artificial Intelligence and Robotics / AI Consultant Programme Manager of Artificial Intelligence Center for Robotics and Neural Systems (CRNS) School of Engineering, Computing, and Mathematics Room A307 Portland Square, Drake Circus, PL4 8AA University of Plymouth, UK ------------------------------ <http://www.plymouth.ac.uk/worldclass>

1 0

Seventh Groningen Spring School on Cognitive Modeling
by Jelmer Borst 07 Feb '24

07 Feb '24

– ACT-R, Nengo, PRIMs – Date: 8-12 April 2024 Location: Groningen, the Netherlands Fee: € 305 (late fee after March 7 will be € 355) More information and registration: http://www.ai.rug.nl/springschool/ – – – – – – – – – – – – – – – – – – – – Dear colleagues and students, This is a reminder that the early registration deadline for the seventh Spring School on Cognitive Modeling in Groningen (8-12 April 2024) ends on March 7th! As announced earlier, the Spring School will cover three different modeling paradigms: ACT-R, Nengo, and PRIMs. Each of these topics consists of a series of lectures, as well as a number of hands-on exercises (tutorials). Past years have shown that students get most out of the spring school if they really immerse themselves into one modeling paradigm. We therefore recommend you choose one topic for which you will attend both the lectures as well as the tutorials. In addition, you can select a second paradigm, for which you attend the lectures only. To give students a broader picture, there will be multiple guest lectures throughout the week. These lectures will give an introduction to other modeling paradigms, as well as practical research examples to show you what can be done with the modeling paradigms presented! Everyone is encouraged to attend those lectures. To round off the program, there will be a poster session, where students present themselves and their research, as well as a city tour, and our (in)famous spring school dinner. Registration closes on March 31. The early registration deadline ends March 7. Please feel free to forward the information to anyone who might be interested in the Spring School, and let us know if you have any questions! We are looking forward to welcoming you (again) in Groningen, The Spring School team springschool(a)rug.nl <mailto:springschool@rug.nl> – – – – – – – – – – – – – – – – – – – – ACT-R Teachers: Jelmer Borst & Stephen Jones (University of Groningen) Website: http://act-r.psy.cmu.edu <http://act-r.psy.cmu.edu/> ACT-R is a high-level cognitive theory and simulation system for developing cognitive models for tasks that vary from simple reaction time experiments to driving a car, learning algebra, and air traffic control. ACT-R can be used to develop process models of a task at a symbolic level. Participants will follow a compressed five-day version of the traditional summer school curriculum. We will also cover the connection between ACT-R and fMRI. Nengo Teacher: Terry Stewart (University of Waterloo) Website: http://www.nengo.ca <http://www.nengo.ca/> Nengo is a toolkit for converting high-level cognitive theories into low-level spiking neuron implementations. In this way, aspects of model performance such as response accuracy and reaction times emerge as a consequence of neural parameters such as the neurotransmitter time constants. It has been used to model adaptive motor control, visual attention, serial list memory, reinforcement learning, Tower of Hanoi, and fluid intelligence. Participants will learn to construct these kinds of models, starting with generic tasks like representing values and positions, and ending with full production-like systems. There will also be special emphasis on extracting various forms of data out of a model, such that it can be compared to experimental data. PRIMs Teacher: Niels Taatgen (University of Groningen) Website: https://www.ai.rug.nl/~niels/prims/index.html How do people handle and prioritize multiple tasks? How can we learn something in the context of one task, and partially benefit from it in another task? The goal of PRIMs is to cross the artificial boundary that most cognitive architectures have imposed on themselves by studying single tasks. It has mechanisms to model transfer of cognitive skills, and the competition between multiple goals. In the tutorial we will look at how PRIMs can model phenomena of cognitive transfer and cognitive training, and how multiple goals compete for priority in models of distraction. – – – – – – – – – – – – – – – – – – – – _______________________________________________ ACT-R-users mailing list ACT-R-users(a)act-r.psy.cmu.edu https://mailman.srv.cs.cmu.edu/mailman/listinfo/act-r-users -- Jelmer Borst Associate Professor – Computational Cognitive Neuroscience University of Groningen, Bernoulli Institute, dept. of Artificial Intelligence http://www.jelmerborst.nl/

1 0

Postdoctoral Researcher in Computational Neuroscience: Effects of Neuromodulation on Learning in SRNNs
by Fleur Zeldenrust 05 Feb '24

05 Feb '24

*The 'Biophysics of Neural Computation' group in Nijmegen (PI: dr. Fleur Zeldenrust) is looking for a postdoctoral researcher (26 months) to study the effects of neuromodulators in biologically realistic networks and learning tasks in the Vidi project 'Top-down neuromodulation and bottom-up network computation, a computational study'. You will use cellular and behavioural data gathered by our department over the previous five years on dopamine, acetylcholine and serotonin in mouse barrel cortex, to bridge the gap between single cell, network and behavioural effects.* The aim of this project is to explain the effects of neuromodulation on task performance in biologically realistic spiking recurrent neural networks (SRNNs). You will use biologically realistic learning frameworks, such as force learning, to study how network structure influences task performance. You will use existing open source data to train a SRNN on a pole detection task <https://linkinghub.elsevier.com/retrieve/pii/S0896627315002512> (for rodents using their whiskers) and incorporate realistic network properties of the (barrel) cortex based on our *lab's measurements <https://link.springer.com/article/10.1007/s12021-022-09576-5>*. Next, you will incorporate the cellular effects of dopamine, acetylcholine and serotonin that we have measured (see *this paper <https://doi.org/10.1093/gigascience/giy147>* and *this preprint <https://www.biorxiv.org/content/10.1101/2022.01.12.476007v1>*) into the network, and investigate their effects on task performance. In particular, you will research the effects of biologically realistic network properties (balance between excitation and inhibition and the resulting chaotic activity, non-linear neuronal input-output relations, patterns in connectivity, Dale's law) and incorporate known neuron and network effects. You will build on the single cell data, network models and analysis methods available in our group, and your results will be incorporated into our group's further research to develop and validate efficient coding models of (somatosensory) perception. We are therefore looking for a team player who can collaborate well with the other group members, and is willing to both learn from them and share their knowledge. *Your profile:* Profile - You hold a PhD in computational neuroscience, mathematics, physics, computer science, AI or a similar computational field. - You have experience in working with machine learning models in (computational) neuroscience and are able to perform network simulations, analytical derivations and advanced data analysis. - You are a highly motivated, independent, critical and creative researcher who wants to bridge the gap between real data and abstract theoretical models. - You are a team player, ready to collaborate in a diverse multidisciplinary research group. - You have an excellent command of spoken and written English. - You have experience in coding (Python and/or Matlab). We are *Our profile:* You will be appointed at the *Biophysics of Neural Computation <https://www.ru.nl/donders/research/theme-4-neural-computation-neurotechnolo…>* group, *Donders Centre for Neuroscience <https://www.ru.nl/science/dcn/>*, *Donders Institute for Brain, Cognition and Behaviour <https://www.ru.nl/donders/>*. <https://www.ru.nl/donders/> This vibrant and multidisciplinary institute studies the organisation and function of neural circuits across scales and techniques, from genes and proteins to behaviour and from in vitro and in vivo experiments to computational modelling. It is an open and international environment, where young scientists from different backgrounds share a fascination for the interaction between brain structure and function. Postdoctoral researchers enjoy a *lively community <https://www.ru.nl/donders/talent-education/postdoctoral-researchers/>* and specialised support. *We offer:* We offer - It concerns an employment for 0.8 - 1.0 FTE. - The gross monthly salary amounts to a minimum of €3,226 and a maximum of €5,090 based on a 38-hour working week, depending on previous education and number of years of relevant work experience (*salary scale 10 <https://www.ru.nl/en/staff/services/salary-and-selection-model/salary/amoun…>* ). - You will receive 8% holiday allowance and 8.3% end-of-year bonus. - You will be employed on the basis of a temporary contract for 26 months. - You will be able to use our *Dual Career and Family Care Services <https://www.ru.nl/en/staff/services/living-working-and-studying-netherlands…>*. Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen. - Working for us means getting extra days off. In case of full-time employment, you can choose *between 30 or 41 <https://www.ru.nl/en/staff/services/employment-conditions/working-time/flex…>* <https://www.ru.nl/en/staff/services/employment-conditions/working-time/flex…>days of annual leave instead of the legally allotted 20. *Please, apply via the website before February 11th: * https://www.ru.nl/en/working-at/job-opportunities/postdoctoral-researcher-i… Profil -- Fleur Zeldenrust Associate Professor Donders Institute for Brain, Cognition and Behaviour Donders Centre for Neuroscience Faculty of Science, Radboud University Heyendaalseweg 135, room HG 00.111 6525 AJ Nijmegen, the Netherlands tel +31 24 36 53195 fleurzeldenrust.nl *Due to my own family/work balance, you may receive emails from me outside of normal working hours. I do not expect a response from you outside of your own working pattern, nor do I expect an immediate response when you are working.*

1 1

Two months until submission deadline for From Animals to Animats: 17th International Conference on the Simulation of Adaptive Behavior (SAB 2024)
by Jeffrey L Krichmar 04 Feb '24

04 Feb '24

Dear Colleagues, The deadline for SAB24 paper submissions is less than two months away! The Simulation of Adaptive Behavior (SAB) interdisciplinary conference brings together researchers in artificial intelligence, artificial life, computer science, cybernetics, ethology, evolutionary biology, neuroscience, robotics, and many other fields, to further our understanding of the behaviors and underlying mechanisms that allow natural animals and artificial agents to adapt and survive in complex, dynamic and uncertain environments. Animats denote the connection between animals and synthetic agents. The conference focuses on models and experiments designed to help characterize and compare various organizational principles and architectures underlying adaptive behavior in real animals and in animats. SAB 2024 solicits contributions dealing with any aspect of adaptive behavior. We especially invite submissions from researchers who connect biology and natural behavior to synthetic agents. Conference papers are peer-reviewed and accepted papers will be published in “From Animals to Animats 17. SAB 2024.” Lecture Notes in Artificial Intelligence, Springer Nature. Website: https://sites.uci.edu/sab2024/ Venue -------- CalIT2 Auditorium University of California, Irvine Irvine, CA 92697 USA CALL FOR PAPERS - SAB 2024 (April 1, 2024 Deadline) ————————————————————— More details can be found at: https://sab2024.socsci.uci.edu/call-for-papers Important Dates ---------------------- April 1, 2024: Deadline for paper submission April 15, 2024: Deadline for Workshop and tutorial proposals June15, 2024: Notice of acceptance June 30, 2024: Camera-ready papers September 9-12: Conference dates More details can be found at: https://sab2024.socsci.uci.edu/call-for-papers Jeff Krichmar Department of Cognitive Sciences 2328 Social & Behavioral Sciences Gateway University of California, Irvine Irvine, CA 92697-5100 jkrichma(a)uci.edu http://www.socsci.uci.edu/~jkrichma https://sites.uci.edu/sab2024/

1 0

Available Ph.D. Position in Cognitive Robotics / Human-Robot Interaction
by Amir Aly 03 Feb '24

03 Feb '24

Dear All, *Apologies for cross-posting* We are pleased to announce an opportunity for a funded PhD studentship (*Cross-Modal Language Learning with Large Language Models through Human-Robot Interaction*) at the Center for Robotics and Neural Systems (CRNS) at Plymouth University, UK. The closing date for applications is *12 noon on **15th March 2024* *(The difference in tuition fees between national and international students will be waived for international candidates)*. This exciting project aims to create a robot learning framework that integrates the wide linguistic capabilities of *Large Language Models *(LLMs) with robot perceptual information (e.g., visual and/or haptic perception) for language learning covering *word grounding* and bottom-up *sentence formation*, which can make robots develop language and understand human communication across contexts (*more details and research questions are available in the link below*). More details *about the topic *and *how to apply* are available at: https://www.jobs.ac.uk/job/DFL347/phd-studentship-cross-modal-language-lear… <https://www.jobs.ac.uk/job/DFL347/phd-studentship-cross-modal-language-lear…> PhD Studentship - Cross-Modal Language Learning with Large Language Models through Human-Robot Interaction at University of Plymouth <https://www.jobs.ac.uk/job/DFL347/phd-studentship-cross-modal-language-lear…> Find a PhD Studentship - Cross-Modal Language Learning with Large Language Models through Human-Robot Interaction on jobs.ac.uk, the top job board in higher education. Click to view more! www.jobs.ac.uk If you have any questions, please don't hesitate to contact me, Regards ---------------- *Dr. Amir Aly* Lecturer in Artificial Intelligence and Robotics / AI Consultant Programme Manager of Artificial Intelligence Center for Robotics and Neural Systems (CRNS) School of Engineering, Computing, and Mathematics Room A307 Portland Square, Drake Circus, PL4 8AA University of Plymouth, UK ------------------------------ <http://www.plymouth.ac.uk/worldclass>

1 0

NEXTEN Conference registration now open
by Goodhill, Geoffrey 03 Feb '24

03 Feb '24

NEXTEN: Envisaging Theoretical and Computational Neuroscience for the next 10 years May 16-17, 2024, Washington University in St Louis Registration and abstract submission for this event is now open (deadline Feb 28). For more details see nexten.wustl.edu Theoretical/Computational Neuroscience is currently undergoing a phase of unprecedented growth. Dramatic advances in the ease with which large-scale datasets of behavior, neural activity, connectomic and gene expression information can be collected have coincided with a revolution in the capabilities of Artificial Intelligence-based algorithms to interrogate such datasets. Concurrently, these new datasets are inspiring exciting new developments in mathematical tools for extracting their underlying structure and relationships. What is the current state of the art in our theoretical/computational understanding of the brain, and what does the future hold? You are invited to join an exciting line-up of leaders in the field to address these questions. Confirmed speakers include Adam Kepecs (WashU) Mackenzie Mathis (EPFL) Terry Sejnowski (Salk Institute) Andreas Tolias (Baylor College of Medicine) Richard Zemel (Columbia University) Abstract submissions for posters presenting current research in the field are encouraged, and some of these will be selected for short talks. Some travel awards will be available for qualified trainees. The conference is sponsored by the Center for Theoretical and Computational Neuroscience at Washington University in St Louis (ctcn.wustl.edu) It will be held in the new 600,000 sq ft Neuroscience Research Building on the WashU Medical School campus, into which ~100 neuroscience labs have recently moved (https://medicine.wustl.edu/news/newly-opened-jeffrey-t-fort-neuroscience-re…) The deadline for registration and abstract submission is Wednesday, February 28, 2024 (for those external to WashU). However, due to the size of the auditorium total registrations are limited to 150, and so registration may close earlier than Feb 28 if this limit is reached. Please direct any questions to ctcn(a)wustl.edu Professor Geoffrey J Goodhill Departments of Developmental Biology and Neuroscience Director, Center for Theoretical and Computational Neuroscience (ctcn.wustl.edu) Washington University School of Medicine 660 S. Euclid Avenue St. Louis, MO 63110 g.goodhill(a)wustl.edu https://neuroscience.wustl.edu/people/geoffrey-goodhill-phd

1 0