- Comp-neuro - lists.cnsorg.org

A YouTube playlist of 15 short videos for "A quick introduction to what is known about biological vision experimentally"

by Li Zhaoping

Dear colleagues, I have made this playlist "A quick introduction to what is known about biological vision experimentally" of 15 short video clips, each about 10 minutes long, see http://lizhaoping.org/zhaoping/QuickIntro_BiologicalVision_Playlist.html <https://t.co/Tfpa7epGAE> this is part of my effort for teaching materials for "Understanding vision: theory, models, and data" <http://www.lizhaoping.org/zhaoping/VideoLectures_ForBook.html>. Feedback most welcome, thank you! best Li Zhaoping -- Li Zhaoping, Ph.D. Prof. of Cognitive Science, University of Tuebingen Head of Department of Sensory and Sensorimotor Systems, Max Planck Institute for Biological Cybernetics Author of "Understanding vision: theory, models, and data", Oxford University Press, 2014 www.lizhaoping.org

May 27, 2022

PostDoc position at UCL: MEG and big data smartphone analysis

by Hauser, Tobias

PostDoc position at Max Planck UCL Centre for Computational Psychiatry with Dr Tobias Hauser We are looking for a PostDoc to work on exciting projects analysing already collected MEG and smartphone app data. We are looking for someone with experience in data analysis with behavioural and/or electrophysiological (MEG) data. The postdoc will be working on a MEG dataset of a novel task including a big patient sample. In addition, they will have the opportunity to analyse a large dataset of behavioural and questionnaire data from a smartphone app (www.brainexplorer.net<http://www.brainexplorer.net>). We are looking for someone with computational modelling, machine learning, or advanced neuroimaging data analysis expertise. The person will be based at the Max Planck UCL Centre for Computational Psychiatry and Ageing Research and the Wellcome Centre for Human Neuroimaging, located in Central London. If you have further questions, please contact Tobias Hauser (t.hauser(a)ucl.ac.uk<mailto:t.hauser@ucl.ac.uk>). To read more about the research group, please see https://devcompsy.org/ Job advert here: https://atsv7.wcn.co.uk/search_engine/jobs.cgi?amNvZGU9MTg4NDY5NiZ2dF90ZW1w… Best Tobias -- Play smartphone games and help us understand the brain: www.brainexplorer.net<http://www.brainexplorer.net> Dr Tobias U. Hauser Sir Henry Dale Fellow, Principal Research Fellow Developmental Computational Psychiatry lab Max Planck UCL Centre for Computational Psychiatry & Ageing Research Wellcome Centre for Human Neuroimaging University College London 10-12 Russell Square London WC1B 5EH +44 207 679 5264 (internal: 45264) t.hauser(a)ucl.ac.uk<mailto:t.hauser@ucl.ac.uk> www.tobiasuhauser.com<http://www.tobiasuhauser.com/> www.devcompsy.org<http://www.devcompsy.org/>

May 26, 2022

PhD position offer: Neuro-inspired macroscale model of tCS-induced changes on epileptic networks

by Elif Köksal

*Title*: Neuro-inspired macroscale model of tCS-induced changes on epileptic networks *Context*. Epilepsy refers to a neurological disorder that affects about 1% of the general population. Recent findings indicate that non-invasive brain transcranial current stimulation (tCS) is safe and of therapeutic promise in epilepsy. However, it is not yet indicated as a standard treatment due to major scientific limitations: unknown mechanisms of action, insufficient account for patient-specific factors, poor understanding of short- and long-term effects. The ambition of the GALVANI Project (ERC-SyG 2019; 2020-26) is to transform the care of a large fraction of patients living with drug-resistant epilepsies by solving a fundamental problem: to efficiently target and control large-scale epileptic brain networks with tCS-induced neuromodulatory weak electric fields. *Rationale. *Electrical stimulation (supra-threshold) and neuromodulation (sub-threshold) are two different methods that can be used to alter brain plasticity in order to lower hyperexcitability and subsequently decrease the occurrence of epileptiform events. These events are generated large-scale brain networks involving interconnected distant brain regions characterized by an increase of excitability. In this context, computational models are an efficient way to understand features of epileptiform events recorded in patients, either intracerebrally or from electrodes located on the scalp. In addition, it is an efficient tool to analyze the impact of tCS on the brain and optimize its therapeutic effect. *Objective. *This research focuses on neuromodulation induced by transcranial current stimulation (tCS). The objective of the proposed PhD position is to design a neuro-inspired macroscale model of the brain that will simulate electroencephalographic (EEG) signals under 2 conditions: spontaneous activity and tCS. The model will be able to simulate the activity of epileptogenic networks generating epileptic spikes during interictal periods. It will account for immediate (acute) and lasting (short- or long-term) effects of neuromodulatory weak electric fields, which remain elusive. Simulations will help the design of tCS-based neuromodulation strategies aimed at lowering interictal epileptic spikes. *Methods. *The model will start from previous results of the team (Merlet et al. PlosOne 2013, Bensaid et al. Frontiers in Neuroscience 2019). It will consist of a macroscale network of interconnected (edges) neural populations (nodes) located in the neocortex. Neurophysiological activity of each node will be generated by a neural mass model. The whole model will allow for simulation of normal and epileptic EEG activity (interictal spikes, ictal activity) under 2 conditions: spontaneous and tCS. Simulated signals will be compared to EEG signals recorded in patients under similar conditions. The model will be embedded into an existing software named COALIA developed in Python. tCS induced E-fields will be simulated using SimNibs (to start with) and with tools developed at Neuroelectrics. Optimal parameters reducing epileptic activity will be determined. *Scientific environment. *GALVANI involves three partners: LTSI-Inserm (Rennes), AMU-APHM (Marseille) and Neuroelectrics (Barcelona). It is intended to develop the next generation of brain stimulation solutions. GALVANI can be viewed as a distributed lab (Rennes-Barcelona-Marseille) working under a common policy to ensure coherence of research and intense collaboration and cross-fertilization. Fellows will be co-supervised in a unique, shared environment with exposure to science, technology and clinical experience. *Candidate profile.* The research project is at the interface between biomathematics (neuro-inspired models), biophysics (electric field models), and neuroscience/neurology (epilepsy). The candidate will preferably have some background in dynamical systems, computational neuroscience/systems biology or in electrical engineering, with experience in bio-signal processing and biophysics. Knowledge in electrophysiology and/or EEG analysis would be an asset. The PhD fellow will join a multidisciplinary team including research scientists in biomedical engineering, neurophysiological modeling, bio-physics, signal processing, electrophysiology, neurology. - *Contract*. The position will start on 01/10/2022. The contract is for 3 years with possible extension (3 months). The salary will be defined according to Inserm rules regarding doctoral student remuneration. Deadline for application. 15/07/2022 Contact. Applicants must send a CV and a cover letter to: Fabrice Wendling (DR Inserm, LTSI, France) Email: fabrice.wendling(a)inserm.fr Isabelle Merlet (CR Inserm, LTSI, France) Email: isabelle.merlet(a)inserm.fr Elif Koksal (Post-doc fellow, LTSI, France) Email: elif.koksal-ersoz(a)inserm.fr Pascal Benquet (Prof. Univ-Rennes1) Email: Pascal.Benquet(a)univ-rennes1.fr

May 26, 2022

Postdoc positions in NeuroAI

by Rui Ponte Costa

We are looking for two postdocs to work on deep learning-inspired computational neuroscience at the University of Bristol, United Kingdom. There are a number of exciting topics that you could contribute to: 1. Neuromodulated cortex-wide credit assignment 2. Subcortical facilitation of cortical learning 3. Theories of self-supervised learning in cortical circuits There are also opportunities to collaborate closely with leading cellular, systems and cellular neuroscientists, but also deep learning researchers. Successful candidates should have: - a strong quantitative background - keen interest in neuroscience - obtained (or be close to) a PhD in computational neuroscience, machine learning, physics, mathematics, computer science or similar. - ability to work in a strongly collaborative and interdisciplinary field Please express your interest by sending your cv and a brief statement of research interests to rui.costa(a)bristol.ac.uk<mailto:rui.costa@bristol.ac.uk> More info about our group at: neuralml.github.io<https://neuralml.github.io/> Best wishes, Rui Ponte Costa Lecturer (Assistant Professor) in Computational Neuroscience & Machine Learning Neural and Machine Learning group<https://neuralml.github.io/> Bristol Computational Neuroscience Unit<http://bristolcnu.github.io/>, Intelligent Systems Labs<https://www.bristol.ac.uk/engineering/research/intelligent-systems/> Faculty of Engineering & Bristol Neuroscience, University of Bristol<https://bristol.ac.uk/>, UK

May 26, 2022

Postdoctoral opportunity UTSA-AFRL

by Fidel Santamaria

We are looking for a postdoctoral fellow to computationally and theoretically study the effects of thermal gradients in synaptic plasticity. This is an area of research with potential translational and engineering applications. This is also a unique opportunity for those that want to explore working along the lines of interest of the Air Force Research Laboratories (AFRL). Furthermore, the funds and benefits dedicated for the training of the selected candidate are way better than what you can get in a traditional postdoctoral position. This research is part of a collaboration between the University of Texas at San Antonio, an R1 institution, and the AFRL. To apply please follow the link or look it up https://www.zintellect.com/Opportunity/Details/AFRL-711HPW-2022-0005 more information here https://orise.orau.gov/internships-fellowships/postdocs.html Please note that this position is only open to US citizens. You can also contact Dr Santamaria for more information: fidel.santamaria(a)utsa.edu<mailto:fidel.santamaria@utsa.edu> _______________________________________________________________________________ Fidel Santamaria, PhD Professor Department of Neuroscience, Development, and Regenerative Biology University of Texas at San Antonio www.utsa.edu/SantamariaLab<http://www.utsa.edu/SantamariaLab> Office: BSB 1.03.30 Tel +1(210) 458 6910

May 25, 2022

International Symposium on AI and Brain Science 2022: Call for poster abstracts and registration

by Kenji Doya

We are pleased to announce the International Symposium on AI and Brain Science 2022 on July 4th and 5th at Okinawa Institute of Science and Technology http://www.brain-ai.jp/symposium2022/ as a satellite event for Neuro2022 at Okinawa Convention Center from June 30th to July 3rd. https://neuro2022.jnss.org/en/ The symposium is on-site/online hybrid and we are calling for on-site poster presentations by June 1st. Please note that all foreign nationals currently need a visa to enter Japan and if you need a visa application support, please submit your abstract by May 25th, i.e. immediately. Attendance is free, but registration is required by June 15th from the web site: http://www.brain-ai.jp/symposium2022/registration/ Tentative Program: time in JST=GMT+9 <Monday July 4th> 9:00 Registration 9:40 Opening: Kenji Doya 10:00-12:00 Session 1: AI for Brain Science Maneesh Sahani, Angela Langdon, Xiao-Jing Wang, Terrence Sejnowski 12:00-14:00 Lunch and Poster Session 14:00-16:00 Session 2: Biological and robotic motor control Tetsuya Ogata, Tom Macpherson, Jun Izawa, Rieko Osu 16:30-18:30 Session 3: Brain-inspired AI Masashi Sugiyama, Matthew Botvinick, Yutaka Matsuo <Tuesday July 5th> 10:00-12:00 Session 4: AI, Brain, and Society Patricia Churchland, Yoshua Bengio, Ryota Kanai, Ai Koizumi 12:00-13:00 Lunch and Poster Session 13:00-15:00 Session 5: Natural and artificial consciousness Hideaki Shimazaki, Keisuke Suzuki, Makiko Yamada, Tadahiro Taniguchi 15:30-17:30 Session 6: Bayesian Brain and Computational Psychiatry Jun Tani, Karl Friston, Yuichi Yamashita, Misako Komatsu 17:30-18:00 General Discussion - Closing Hope to see many of you in Okinawa, or online. Co-organizers: Kenji Doya (Okinawa Institute of Science and Technology) Karl Friston (University College London) Hiroaki Gomi (NTT Communication Science Laboratories) Takao Hensch (The University of Tokyo International Research Center for Neurointelligence) Maneesh Sahani (Gatsby Computational Neuroscience Unit) Masashi Sugiyama (RIKEN Center for Advanced Intelligence Project) Tadahiro Taniguchi (Ritsumeikan University) Naotsugu Tsuchiya (Monash University) ---- Kenji Doya <doya(a)oist.jp<mailto:doya@oist.jp>> Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University 1919-1 Tancha, Onna, Okinawa 904-0495, Japan Phone: +81-98-966-8594; Fax: +81-98-966-2891 https://groups.oist.jp/ncu

May 24, 2022

CFP: Frontiers research topic on Neural Dynamics and Behavior in Freely Moving Animals (DL:2022.10.30)

by Panagiotis Symvoulidis

Dear Colleagues, We are organizing the Frontiers Research Topic below, aiming to create a collection of articles across the whole field of neuroscience studies of freely moving animals. Please *consider submitting* your related work and *sharing the call* with potentially interested colleagues. Apologies for the cross-post. *The Brain in Action: Neural Dynamics and Behavior in Freely Moving Animals* *Link*: https://www.frontiersin.org/research-topics/20697/the-brain-in-action-neura… *Details: *Understanding the neural basis of complex behaviors is a primary aim of neuroscience. However, until recently, the field lacked an appropriate set of techniques for simultaneously measuring neural activity and behavior in freely moving animals, forcing investigators to use immobilized animals performing simplistic behavioral tasks. Synergistic technological breakthroughs in fluorescent brain imaging and behavioral tracking approaches have paved the way to a new type of neuroscience that enables tracking behavior in setups compatible with brain imaging and manipulation, even at the single-cell level, using optical electrophysiology techniques. A diversity of such neurobehavioral imaging systems have been recently invented, spanning the range of conventional model organisms including C. Elegans, Flies, Zebrafish, and Rodents. Each species and approach showcases unique technical challenges, achievements, and opportunities. Our aim with this Research Topic is to provide an overview of this new field. We will present not only the technological advances but also discuss the novel type of experiments and insights that they promise. To achieve that, we welcome articles that span the following categories: i) Algorithms and imaging systems for tracking and quantifying complex behaviors of freely moving animals; ii) Molecular tools and microscopes, enabling capturing or manipulating neuronal dynamics. Such systems could include tracking or large field of view microscopes in small animals, head-mounted mini scopes and fiber-based systems for mammalian models, -or non-optical methods; iii) Neuroscience studies, using such tools to generate neurobehavioral datasets (ideally shareable with the community) and new biological findings; iv) Perspective articles on the future possibilities of such systems are also welcome -including ones that discuss alternatives approaches; v) Analysis pipelines and computational neuroscience frameworks exploiting the produced datasets, along with ways to integrate them with existing ( or future) knowledge and techniques. *Keywords*: Brain Imaging, Behavioral Tracking, Quantitative Behavior, Neuronal Dynamics, Freely Moving *Participating Journals:*Frontiers in Neuroscience Frontiers in Neuroimaging *Guest Editors Team:* Prof. Gershow, Prof. Venkatachalam, Dr. Marshall, and Dr. Symvoulidis *Deadline:*30 October 20202 Best, Panos

May 23, 2022

New 4-years PostDoc position in "Explainable Machine / Deep Learning in Translational Psychiatry" at Charité - Universitätsmedizin Berlin, Germany

by Kerstin Ritter

Dear all, John-Dylan Haynes and I offer a new PostDoc position in the field of "Explainable Machine Learning / Deep Learning in Clinical Neuroimaging and Translational Psychiatry" at Charité - Universitätsmedizin Berlin, Germany (see advertisement below) - please feel free to forward the advertisement to people who may be interested! Thanks a lot! Best wishes, Kerstin Ritter ______________________________________________________________ Explainable Machine Learning / Deep Learning in Clinical Neuroimaging and Translational Psychiatry PostDoc position (starting date: July/August 2022, up to 4 years; 100 %) at Charité - Universitätsmedizin (Berlin, Germany) At Charité - Universitätsmedizin Berlin and the Bernstein Center for Computational Neuroscience, we are looking for a motivated and highly qualified PostDoc for methods development at the intersection of explainable machine learning / deep learning and clinical neuroimaging / translational psychiatry. The position will be located in the research groups of Ass. Prof. Kerstin Ritter and Prof. John-Dylan Haynes at Charité Berlin. The main task will be to predict response to cognitive-behavioral psychotherapy in retrospective data and a prospective cohort of patients with internalizing disorders including depression and anxiety from a complex, multimodal data set comprising tabular data as well as imaging data (e.g., clinical data, smartphone data, EEG, structural and functional MRI data). An additional task will be to contribute to the organization and maintenance of the prospective cohort. This study will be one of several projects in the newly established Research Unit 5187 "Precision Psychotherapy" (headed by Prof. Ulrike Lüken). Please see also the job advertisement: https://www.charite.de/service/stellenangebot/angebot/detailinfo/dm11822b_r… Requirements for the Postdoc: - Excellent degree in relevant field (e.g. computer science, mathematics, physics, psychology, computational neuroscience or related). - Excellent methodological skills (esp. machine learning, deep learning, explainable AI, medical image analysis) - Excellent programming skills in python - Excellent writing and communication skills (in English) - Strong interest in neuroscientific and psychiatric research Please send your application (motivation+CV+references) in one pdf-file (in English or German) asap to: Ass. Prof. Dr. rer. nat. Kerstin Ritter Charité - Universitätsmedizin Berlin Department of Psychiatry and Psychotherapy Bernstein Center for Computational Neuroscience Sauerbruchweg 4, Charitéplatz 1, 10117 Berlin E-Mail: kerstin.ritter(a)charite.de Webpage: https://psychiatrie-psychotherapie.charite.de/en/research/translation_and_n… ______________________________________________________________

May 19, 2022

Junior Chair position in Computational Neuroscience, Marseille, France

by Sylvain Takerkart

Aix-Marseille Université (AMU) is opening a Junior Chair in Computational Neuroscience, a new tenured-track path at French Universities. The position is open at Junior Professor level (level of experience 3-10 years after PhD) and is supported with a start-up package of 470K€, including the salary for the Junior Professor. After 3-5 years, depending upon the scientific achievements, the Chair should lead to a permanent Faculty position at the Professor level (PR2). * Starting date: Sept-Dec 2022 (not flexible) * teaching is about 60h/year (negotiable) in Computational neurosciences * deadline of application June 8th * Inquiries and further information can be sent directly to both Dr Guillaume Masson (Director INT:guillaume.masson@univ-amu.fr <mailto:guillaume.masson@univ-amu.fr>) and Dr Viktor Jirsa (Director INS:viktor.jirsa@univ-amu.fr <mailto:viktor.jirsa@univ-amu.fr>) More info (in French, then in English) at https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/ListesPostesPub… <https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/ListesPostesPub…> Please circulate! -- Sylvain Takerkart Institut des Neurosciences de la Timone (INT) UMR 7289 CNRS-AMU Marseille, France tél: +33 (0)4 91 324 007 http://www.int.univ-amu.fr/_TAKERKART-Sylvain_?lang=en

May 19, 2022

Call for papers for the 5th international workshop on machine learning in clinical neuroimaging

by MLCN Workshop

Dear Colleagues, Please find below the call for papers for the International Workshop of Machine Learning in Clinical Neuroimaging (MLCN) which is held on *the 18th of September 2022 at MICCAI 2022, Singapore*. We welcome contributions to novel machine learning methods and their applications to clinical neuroimaging data. The submission deadline is *25 June 2022*, and all MLCN accepted papers will be eligible for the best paper award of 500 USD. Top accepted papers will be invited to submit an extended version to the MELBA journal. For more information, please visit https://mlcnws.com/call-for-papers/*.* Best wishes, The MLCN 2022 steering and organizing committees Christos Davatzikos, Andre Marquand, Jonas Richiardi, Emma Robinson Ahmed Abdulkadir, Nicha C. Dvornek, Mohamad Habes, Seyed Mostafa Kia, Vinod Kumar, Thomas Wolfers *Call for Papers* The International Workshop of Machine Learning in Clinical Neuroimaging (MLCN 2022 <https://mlcnws.com/>), a satellite event of MICCAI (MICCAI 2022 <https://conferences.miccai.org/2022/en/>), calls for original papers in the field of clinical neuroimaging data analysis with machine learning. The two tracks of the workshop include methodological innovations as well as clinical applications. This highly interdisciplinary topic provides an excellent platform to connect researchers of varying disciplines and to collectively advance the field in multiple directions. In the *machine learning* track, we seek novel contributions that address current methodological gaps in analyzing high-dimensional, longitudinal, and heterogeneous clinical neuroscientific data using stable, scalable, and interpretable machine learning models. Topics of interest include but are not limited to: · Big data · Spatio-temporal brain data analysis · Structural data analysis · Graph theory and complex network analysis · Longitudinal data analysis · Model stability and interpretability · Model scalability in large neuroimaging datasets · Multi-source data integration and multi-view learning · Multi-site data analysis, from preprocessing to modeling · Domain adaptation, data harmonization, and transfer learning in neuroimaging · Unsupervised methods for stratifying brain disorders · Deep learning in clinical neuroimaging · Model uncertainty in clinical predictions · … In the *clinical neuroimaging *track*,* the applications of existing machine learning algorithms are evaluated to move towards precision medicine for complex brain disorders. The discovery of biological markers in medicine is an important challenge across different fields and various experimental procedures and designs are used to detect biological signatures that can be utilized for improvement in diagnostic, treatment, or for other beneficial ends. However, for most complex brain disorders, we do not have reliable biomarkers today. The application of advanced machine learning methods may help to reach this goal. Therefore, we invite the community to submit conference contributions on machine learning approaches with the goal to improve our understanding of complex brain disorders, moving the field closer to precision medicine. Topics of interest include but are not limited to: · Biomarker discovery · Refinement of nosology and diagnostics · Biological validation of clinical syndromes · Treatment outcome prediction · Course prediction · Analysis of wearable sensors · Neurogenetics and brain imaging genetics · Mechanistic modeling · Brain aging · The presentation of clinical neuroimaging databases to stimulate developments in machine learning · … ------------------------------ *Submission Process:* The workshop seeks high-quality, original, and unpublished work that addresses one or more challenges described above. Papers should be submitted electronically in Springer Lecture Notes in Computer Science (LCNS) style (see this link <https://conferences.miccai.org/2022/en/PAPER-SUBMISSION-AND-REBUTTAL-GUIDEL…> for detailed author guidelines) using the CMT system here <https://cmt3.research.microsoft.com/MLCN2022>. The page limit is 8-pages (text, figures, and tables) plus up to 2-pages of references. We review the submissions in a double-blind process. Please make sure that your submission is anonymous. Accepted papers will be published in a joint proceeding with the MICCAI 2022 conference. ------------------------------ *MLCN Special Issue at the MELBA journal:* We will invite the top accepted papers to submit an extended version of their contribution to the MLCN special issue at the Journal of Machine Learning for Biomedical Imaging (MELBA) <https://www.melba-journal.org/>. The invited papers will go through an independent review process by the journal. *Error! Filename not specified.* <https://www.melba-journal.org/> ------------------------------ *Donders Best Paper Award:* The MLCN’s best paper award is sponsored by Donders Institute <https://www.ru.nl/donders/>. All MLCN accepted papers will be eligible for the best paper award. The recipient of the award will be chosen by the MLCN scientific committee based on the scientific quality, novelty, and clarity of contributions. The winner will be announced at the end of the workshop and will receive a 500 USD honorarium. ------------------------------ *Important Dates:* · Paper submission deadline: June 25, 2022 · Notification of Acceptance: July 23, 2022 · Camera-ready Submission: Aug 6, 2022 · Workshop Date: September 18, 2022

May 18, 2022