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Online Workshop: 30/09 - 01/10/2021 "Towards multipurpose neural network models II: Model testing and model fitting"
by Zélie Tournoud Sept. 27, 2021

Sept. 27, 2021

Dear colleagues, The European Institute for Theroretical Neurosience (EITN) is happy to invite you all to its next online workshop taking place online this week from Wednesday to Friday. It is open to everyone upon registration. You will find all the information at the end of this email. Kind regards, Zélie, for the EITN team *_____* **** * * *Workshop on "Towards multipurpose neural network models II: Model testing and model fitting"* /Organized by Anton Arkhipov (Allen Institute, Seattle), Gaute Einevoll (NMBU/University of Oslo)/ *_Dates:_*Wednesday 29 September – Friday October 1st *_Time:_*5PM – 9.15PM (CET) <https://www.eitn.org/images/events/TMNNM-II-MTaMF_Flyer.pdf> Online workshop. Free to attend, but registration is mandatory. *REGISTER HERE.* <https://cnrs.zoom.us/webinar/register/WN_saMXfg31Roe4tqHbWtTdFg> *https://cnrs.zoom.us/webinar/register/WN_saMXfg31Roe4tqHbWtTdFg* *_Abstract:_* Starting with the work of Hodgkin, Huxley, Cole, Rall, Katz, Eccles and others in the 1950s and 1960s, we have a reasonably good understanding of the biophysical principles by which single neurons operate. For neural circuits the understanding is much more limited. Most network studies have considered stylized models with a few populations of identical neurons and focused on explaining a particular experimental phenomenon. However, real neural networks consist of a variety of neuron types and have structured synaptic connections. Furthermore, real networks typically perform multiple functions and can be characterized by a variety of readouts from various measurement modalities, including spiking activity, local field potentials, and others. How can we move towards multipurpose models that incorporate the true biological complexity of neural circuits and faithfully reproduce multiple observables in many different situations? The first workshop on the topic was arranged in August 2020 (see https://alleninstitute.org/what-we-do/brain-science/events-training/allen-i… <https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Falleninst…> for program and videos of talks). In this second (also virtual) workshop in the series we will focus on two key aspects of the overall endeavor: model testing and model fitting. Multipurpose network models mimicking real neural circuits will contain numerous model parameters that must be optimized. Efficient methods for fitting of model parameters to experimental data are thus needed. Further, the candidate models must be systematically tested against a variety of experimental data, requiring development of commonly accepted benchmarks and test suites. In the workshop these methodological challenges will be addressed from a variety of angles. *_Confirmed speakers:_*__ Anton Arkhipov (Allen Institute) Marcus Covert (Stanford) Sharon Crook (Arizona State U.) James DiCarlo (MIT) Gaute Einevoll (NMBU/U. Oslo) Julijana Gjorgjeva (Max Planck Institute and TUM) Peder Jedlicka (U. Giessen) Szabolcs Kali (Institute of Experimental Medicine, Budapest, Hungary) Arvind Kumar (KTH Stockholm) Jacob Macke (U. Tübingen) Stefan Mihalas (Allen Institute) Aaron Milstein (Rutgers U.) Kanaka Rajan (Mount Sinai) Atle Rimehaug (U. Oslo) Frances Skinner (Krembil Brain Institute, University Health Network, and U. Toronto) Carsen Stringer (Janelia) Kristin Tøndel (NMBU) * * *Wednesday, September 29, 2021* *Time (PDT)* *Time (CEST)* *Speaker* *Affiliation* *Title* 8:00 am – 8:15 am 5:00 pm – 5:15 pm Gaute Einevoll NMBU/U. Oslo Introduction 8:15 am – 8:55 am 5:15 pm – 5:55 pm Jacob Macke U. Tübingen *Keynote* Simulation-based inference: Bridging the gap between mechanistic models and machine learning. 8:55 am – 9:25 am 5:55 pm – 6:25 pm Aaron Milstein Rutgers U. Nested parallel simulation and multi-objective optimization of neuronal cell and circuit models 9:25 am – 9:40 am 6:25 pm – 6:40 pm Break 9:40 am – 10:10 am 6:40 pm – 7:10 pm Atle Rimehaug U. Oslo Enhancing model constraints by utilizing current source densities 10:10 am – 10:40 am 7:10 pm – 7:40 pm Kristin Tøndel NMBU Facilitating optimization using metamodelling 10:40 am – 10:50 am 7:40 pm – 7:50 pm Break 10:50 am – 11:20 am 7:50 pm – 8:20 pm Frances Skinner Krembil Brain Institute, University Health Network, and University of Toronto Clarity in model development and goals leads to model linkages and biological insights 11:20 am – 12:10 pm 8:20 pm – 9:10 pm _Panel debate – All participants of the day._ *Thursday, September 30, 2021* *Time (PDT)* *Time (CEST)* *Speaker* *Affiliation* *Title* 8:00 am – 8:15 am 5:00 pm – 5:15 pm Anton Arkhipov Allen Institute Introduction 8:15 am – 8:55 am 5:15 pm – 5:55 pm James DiCarlo MIT *Keynote* Reverse Engineering Visual Intelligence 8:55 am – 9:25 am 5:55 pm – 6:25 pm Sharon Crook Arizona State U. Testing the Data-driven Model 9:25 am – 9:40 am 6:25 pm – 6:40 pm Break 9:40 am – 10:10 am 6:40 pm – 7:10 pm Szabolcs Kali Institute of Experimental Medicine, Budapest, Hungary Systematic construction and evaluation of models of rodent hippocampal neurons 10:10 am – 10:40 am 7:10 pm – 7:40 pm Peter Jedlicka U. Giessen Building consistent and robust models of hippocampal granule cells and CA1 pyramidal cells 10:40 am – 10:50 am 7:40 pm – 7:50 pm Break 10:50 am – 11:20 am 7:50 pm – 8:20 pm Stefan Mihalas Allen Institute Computing with a mess: How nonstationary, heterogeneous and noisy components help the brain’s computational power 11:20 am – 12:10 pm 8:20 pm – 9:10 pm _Panel debate – All participants of the day._ *Friday, October 1, 2021* *Time (PDT)* *Time (CEST)* *Speaker* *Affiliation* *Title* 8:00 am – 8:40 am 5:00 pm – 5:40 pm Markus Covert Stanford *Special lecture* Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation 8:40 am – 9:20 am 5:40 pm – 6:20 pm Kanaka Rajan Mount Sinai *Keynote* Data-constrained neural network models of adaptive learning in the brain 9:20 am – 9:40 am 6:20 pm – 6:40 pm Break 9:40 am – 10:10 am 6:40 pm – 7:10 pm Julijana Gjorgjeva Max Planck Institute and TUM Biologically plausible learning in developing networks 10:10 am – 10:40 am 7:10 pm – 7:40 pm Carsen Stringer Janelia Rastermap: Extracting structure from high-dimensional neural data 10:40 am – 10:50 am 7:40 pm – 7:50 pm Break 10:50 am – 11:20 am 7:50 pm – 8:20 pm Arvind Kumar KTH Stockholm Structure and activity dynamics relationship in biological neuronal networks: Measurements and models 11:20 am – 12:10 pm 8:20 pm – 9:10 pm _Panel debate – All participants of the day._

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Brain Mechanisms: Linking Cognitive Phenomena to Neuron Activity
by Andrew Coward Sept. 23, 2021

Sept. 23, 2021

Dear colleagues, I would like to bring to your attention a book that has just been published. The book, Brain Mechanisms: Linking Cognitive Phenomena to Neuron Activity, describes how to understand higher cognition in terms of anatomical, physiological and chemical processes in the brain using techniques based on how we understand the operation of complex electronic systems. A brain has absolutely no resemblance to an electronic system. Nevertheless, how we go about understanding complex electronic systems has some important lessons for how to go about understanding the brain. Brains have huge numbers of neurons, and understanding obviously cannot be based on simultaneously imagining the ongoing activity of all these neurons. Some way must be found to organize all this information in a way humans can handle. A complex computing system can have hundreds of billions of components like transistors. Engineers could not design such systems by simultaneously imagining the activity of all the components that could be involved. Rather, the design information is organized in such a way that all design tasks are within the mental bandwidth of a human designer. The techniques to achieve this involve hierarchies of description, carefully managed use of approximation, and the ubiquitous use of just two types of information process: instructions and data read/writes. Natural selection pressures have resulted in brain architectures to which analogous techniques for organizing information can be applied. The pressures have resulted in the ubiquitous presence of two types of information processes in the brain, condition definition/detections and behavioural recommendation definition/integrations. These information processes are completely different from those in computing systems, but they allow creation of analogous hierarchies of description. Such hierarchies of description make it possible to achieve an intuitively satisfying understanding of human memory, consciousness and self-awareness in terms of the activity of the billions of neurons. A blog touches on some of these ideas. The book is available at Amazon.comDownload a sample chapterVideo of recent lecture at Florida State University Andrew CowardAustralian National UniversityCanberrahttps://researchers.anu.edu.au/researchers/coward-a

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PhD's and Postdoc positions at UVa
by Mario Negrello Sept. 22, 2021

Sept. 22, 2021

Posting on behalf of Jorge Mejias: Dear all, I hope things are going well for all of you. I’m writing you because I’m looking for candidates with a strong quantitative background for a PhD position and a postdoc position at my lab, both for working on computational models of large-scale brain networks. If you know of anybody in your surroundings who might be interested, would you mind sharing this information with them? I think it’s especially important for the postdoctoral position, as the deadline is approaching (Sept 30) and we still don’t have a lot of candidates. The PhD position is focused on studying multisensory integration under noisy or uncertain conditions. The researcher will design and study computational models of large-scale brain networks of the mouse for this purpose, constraining the models with anatomical data and comparing the predictions with electrophysiological recordings from local colleagues at the Cognitive and Systems Neuroscience group at the UvA. The models will later inform other colleagues, also involved in the project, to build neuro-inspired algorithms for sensor fusion in self-driving vehicles and drones. More information and application procedure (with deadline October 15) can be found here: https://www.uva.nl/en/content/vacancies/2021/09/21-734-phd-position-in-comp… <https://www.uva.nl/en/content/vacancies/2021/09/21-734-phd-position-in-comp…> The postdoc position aims to uncover the mechanisms behind compulsive behavior. The researcher will build computational models of large-scale brain networks of mouse and human, using anatomical and electrophysiological data to constrain and test the models. This is a collaboration with Ingo Willuhn at the NIN, who will provide mouse electrophysiological and human clinical data to test the models for healthy and OCD subjects. The final goal is to use the model to investigate translational biomarkers for compulsive disorders. More information and application procedure (deadline September 30) can be found in this link: https://www.uva.nl/shared-content/uva/en/vacancies/2021/09/21699-postdoctor… <https://www.uva.nl/shared-content/uva/en/vacancies/2021/09/21699-postdoctor…> Thanks a lot for the help with spreading this around! Best, Jorge

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Call for Teaching Assistants for the Cape Town Imbizo, August 11th to September 4th 2022. Apply by October 11
by Tim Vogels Sept. 22, 2021

Sept. 22, 2021

Dear Colleagues, We are looking for teaching assistants for the IBRO-Simons Computational Neuroscience Imbizo (#isiCNI), a computational neuroscience summer school held in Cape Town, South Africa. We are looking for post-doctoral or advanced PhD researchers to join our team as Teaching Assistants (TAs) for the #isiCNI2022 in August 2022. Please send your application to to isicn.imbizo(a)gmail.com <mailto:isicn.imbizo@gmail.com>. Include 1) CV and a 2) cover letter with a short motivational statement for why you would be a good fit, and what your favourite topics would be for teaching tutorials and supervising student projects. Additionally, 3) please provide the email address of one reference. We will start assessing applications on 11 October 2021. About the Imbizo: The school hosts 31 students for an amazing 25 days of lectures, tutorials, projects and parties. All this takes place on Noordhoek beach, between the mountain and the ocean. It's a spectacular location. The dates for the isiCNI2022 are August 11th to September 4th 2022. The Imbizo is a special experience, with students being totally immersed in academic, social, touristic and cultural activities, and has resulted in student and TA groups from previous schools becoming very close, personally and scientifically. This is fantastic, as a major goal of the isiCNI project is to help young African researchers grow their academic peer and friend group. About being a TA: Each TA runs one afternoon tutorial in the first week of the school, which they design themselves. Each TA will teach a different topic, which the TA's choose among themselves, to provide students with a broad exposure to problems and methods in computational neuroscience. Each TA is also assigned 5 students to supervise for project work during the last 2 weeks of the school. TAs will be asked to help processing student applications. TAs are integral in helping run the school. In addition to academic support, they foster good social interactions and academic discussions among students, and they help 'shy' students meet faculty. They also act as 'social glue’, helping to notice and support students who may be feeling ill, not fitting in socially, or generally having difficulties. To fulfil these roles, TAs need to be at all school meals and activities. What we provide: We cover a direct as possible, economy class ticket to Cape Town, as well as all board and lodging during the school. In addition, TAs will receive a cash budget for 'hosting purposes' during the school (e.g. for buying some beverages/ice-creams for students, train tickets, etc.). We also provide you with life-long memories of one of the most beautiful places on earth. I'm interested, how do I apply: If you think you would like to join us for this amazing experience, please send us a brief CV (2 or 3 pages is fine) to isicn.imbizo(a)gmail.com <mailto:isicn.imbizo@gmail.com>. Please include (as a cover letter or in your email) a short motivational statement for why you would be a good fit, and what your favourite topics would be for teaching tutorials and supervising student projects. We will start assessing applications on 11 October 2021. A call for student application will follow soon. We hope to hear from you soon! Let us know if you have any questions. Thanks and regards Demba Ba, Peter E. Latham, Joseph Raimondo, Emma Vaughan, and Tim Vogels IBRO-Simons Computational Neuroscience Imbizo Committee 2022 #isicni2022 Twitter: @isicni

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"Brains Through Time" reading club
by Paul Cisek Sept. 20, 2021

Sept. 20, 2021

Dear all, I would like to bring to your attention the Brains Through Time Reading Club I am co-organizing with people from the Instituto de Neurociencias de Alicante. As the name implies, the idea is to review the book Brains Through Time<https://oxford.universitypressscholarship.com/view/10.1093/oso/978019512568…>, by Georg Striedter<https://www.faculty.uci.edu/profile.cfm?faculty_id=3006> and Glenn Northcutt<https://en.wikipedia.org/wiki/Glenn_Northcutt>. It is a masterful synthesis of much what is known about brain evolution, and I believe it offers great insights to anyone interested in a broad understanding of how the brain produces behavior. We will dedicate a ~90 minute session to each of the 7 chapters. The first session will be on the 6th of October (6pm CEST / 12 EST) and will include the participation of Georg Striedter<https://www.faculty.uci.edu/profile.cfm?faculty_id=3006> (one of the authors), Luis Puelles<https://scholar.google.com/citations?user=nIoLKVAAAAAJ&hl=en> and Paul Cisek<https://cisek.org/pavel/>. If you are interested, please visit our web site<https://sites.google.com/view/bbtreadingclub/home> for more information and to register! Paul Cisek, PhD Département de neurosciences Université de Montréal Physical: 2960 chemin de la tour, local 4117 Montréal, QC H3T 1J4 CANADA Mailing: CP 6128 Succursale centre-ville, Montréal, QC H3C 3J7 CANADA e-mail: paul.cisek(a)gmail.com<mailto:paul.cisek@gmail.com> Web: www.cisek.org/pavel<http://www.cisek.org/pavel>

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[CFP] MDPI Molecules (IF: 4.411, ISSN: 1420-3049) - Special Issue "Practical Aspects of Molecular Communications"
by Murat Kuşcu Sept. 20, 2021

Sept. 20, 2021

MDPI Molecules (IF: 4.411, ISSN: 1420-3049) Special Issue on Practical Aspects of Molecular Communications https://www.mdpi.com/journal/molecules/special_issues/molecular_communicati… --------------------------- CALL FOR PAPERS The Internet of Bio-Nano Things (IoBNT) is an emerging technology that aims to extend our connectivity to nanoscale and biological environments with collaborative nanonetworks of artificial nanomachines and biological entities integrated into the Internet infrastructure. To enable the IoBNT and its groundbreaking applications, such as continuous intrabody health monitoring, it is imperative to devise low-complexity nanoscale communication techniques suitable for the envisioned nanomachines of simple architectures. The most promising communication technology for realizing the IoBNT is Molecular Communications (MC), as it ubiquitously manifests itself in many complex biological systems in the Universe, and thus, stands as one of the most common communication modalities, optimized from many aspects as a result of billions of years of evolutionary advancement. Making use of this naturally existing technology requires understanding its foundations through our existing modeling and analysis tools. This quest, which started almost 15 years ago, has received increasing attention from ICT researchers, which have been overly inspired by conventional electromagnetic communication technologies in their approach to this radically different paradigm. These theoretical approaches, however, have not always come with sufficient physical relevance. Currently, this emerging field has come to a critical turning point, as many researchers have started to report on initial MC experiments following different approaches and using different materials, while consistently pointing out a discrepancy between the obtained experimental results and the past theoretical work. This reveals the need to rethink the previous efforts and come up with new interdisciplinary strategies, thus building practical MC techniques and developing feasible MC system components, experimental testbeds, and prototypes in order to close the gap between theory and practice, and expedite the transfer of this emerging technology to the market. Among the challenges stated above, this Special Issue is particularly focused on the practical aspects of MC. Therefore, we are calling for technical papers that report on new research with the potential to move this field forward towards its practical applications, as well as surveys/tutorials focusing on the practical challenges of MC research. Hence, its scope encompasses a wide range of interdisciplinary research topics, with some examples listed as follows: ** The physical design, modeling, and implementation of MC system components (e.g., transmitter, receiver, channel); ** The design and implementation of MC testbeds; ** Practical and low-complexity MC methods (e.g., modulation, detection, channel estimation, synchronization, coding methods); ** The testing and validation of MC transceiver/channel models and MC methods; ** Applications of microfluidics, biosensors, and nanomaterials for MC system design; ** Bio-cyber interfaces between MC networks and conventional macroscale networks; ** Synthetic biology-based MC transceiver architectures; ** Optimization of ligand-receptor interactions for MC; ** Biocompatibility and co-existence challenges; ** Energy harvesting and power transfer techniques for MC networks; ** The design and demonstration of MC applications (e.g., those in healthcare, agriculture, biocomputing). --------------------------- Deadline for manuscript submissions: 15 December 2021 --------------------------- Guest Editors Murat Kuscu, Koc University, Turkey (mkuscu(a)ku.edu.tr) Sasitharan Balasubramaniam, TSSG/Walton Institute, Waterford Institute of Technology (sasi.bala(a)waltoninstitute.ie) Kerstin Lenk, Graz University of Technology, Austria (kerstin.lenk(a)tugraz.at ) Ergin Dinc, University of Cambridge, UK (ed502(a)cam.ac.uk) Michael Barros, University of Essex, UK (m.barros(a)essex.ac.uk) Bige D. Unluturk, Michigan State University, USA (unluturk(a)msu.edu) --------------------------- Paper submission Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions. --------------------------- Additional information: Please visit the MDPI Molecules Special Issue webpage at: https://www.mdpi.com/journal/molecules/special_issues/molecular_communicati… Inquiries can be addressed to Ms. Emity Wang at: emity.wang(a)mdpi.com, molecules(a)mdpi.com

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New "Developing Minds" global online lecture series; September 30: Pierre-Yves Oudeyer
by Jochen Triesch Sept. 19, 2021

Sept. 19, 2021

What: New bi-monthly "Developing Minds" global online lecture series; inaugural lecture by Pierre-Yves Oudeyer, INRIA, Bordeaux Sud-Ouest, France on "Developmental AI: machines that learn like children and help children learn better" When: Thursday, September 30, 13:00 UTC Where: online via zoom; please register at: https://sites.google.com/view/developing-minds-series Background: In 1950, Alan Turing asked "Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's?" Today, over 70 years later, constructing a computer program that can learn like a child and that develops a human-like general intelligence is still considered a grand, if not the ultimate, challenge for artificial intelligence (AI). An interdisciplinary community of scientists from AI, Cognitive Science, Psychology, Engineering, and Neuroscience are tackling this grand challenge. In the Developing Minds global lecture series we showcase the progress being made. It is organized by the IEEE Technical Committee on Cognitive and Developmental Systems of the IEEE Computational Intelligence Society. The inaugural lecture by Pierre-Yves Oudeyer is entitled: "Developmental AI: machines that learn like children and help children learn better" Abstract: Current approaches to AI and machine learning are still fundamentally limited in comparison with the amazing learning capabilities of children. What is remarkable is not that some children become world champions in certains games or specialties: it is rather their autonomy, open-endedness, flexibility and efficiency at learning many everyday skills under strongly limited resources of time, computation and energy. And they do not need the intervention of an engineer for each new task (e.g. they do not need someone to provide a new task specific reward function or representation). I will present a research program, which I call Developmental AI, that studies models of open-ended development and learning. These models are used as tools to help us understand better how children learn, as well as to build machines that learn like children with applications in educational technologies, automated discovery, robotics and human-computer interaction. I will ground this research program into several fundamental ideas proposed by developmental psychologists: 1) the child is autotelic, setting its own goals and spontaneously exploring the world like a curious little scientist (e.g. Piaget, Berlyne); 2) intelligence develops in a social context, where language and culture are internalized to become cognitive tools (e.g. Vygostky and Bruner); 3) intelligence is embodied and develops through self-organization of the dynamical system formed by the brain-body-environment interactions (e.g. Thelen and Smith). I will show how, together with many colleagues and students, we have worked on operationalizing these ideas in computer and robotic models, and explain how this has enabled to advance child development understanding, open new possibilities for AI systems (including for recent language-guided intrinsically motivated Deep RL systems and for training more classical Deep RL systems to foster generalization), and led to applications now used by thousands of children in the world to help them learn (educational technologies). Speaker Bio: Dr. Pierre-Yves Oudeyer has been Research Director at Inria, France, and head of the Flowers lab (Inria, Univ. Bordeaux, Ensta ParisTech). Before, he has been a permanent researcher in Sony Computer Science Laboratory for 8 years (1999-2007). He studies models of open-ended development and learning, at the frontiers of AI and cognitive sciences. These models are used as tools to help us understand better how children learn, as well as to build machines that learn like children within the field of developmental artificial intelligence. He has been developing models of intrinsically motivated learning, pioneering curiosity-driven learning algorithms working in real world robots, and developed theoretical frameworks to understand better human curiosity and autonomous learning. He also studied mechanisms enabling machines and humans to discover, invent, learn and evolve language. He is also working on applications in educational technologies, automated discovery, video games, robotics and human-computer interaction. He received several prizes for his work in developmental AI and on the origins of language. In particular, he is laureate of the Inria-National Academy of Science young researcher prize in computer sciences, and of an ERC Starting Grant EXPLORERS. Finally, he is also working actively for the diffusion of science towards the general public, through the writing of popular science articles and participation to radio and TV programs as well as science exhibitions. Web: http://www.pyoudeyer.com and http://flowers.inria.fr Upcoming speakers: Linda B. Smith, Indiana University Joshua B. Tenenbaum, MIT Please visit https://sites.google.com/view/developing-minds-series/home for up-to-date information. -- Prof. Dr. Jochen Triesch Johanna Quandt Research Professor Frankfurt Institute for Advanced Studies http://fias.uni-frankfurt.de/~triesch/ Tel: +49 (0)69 798-47531 Fax: +49 (0)69 798-47611

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CFP - Annual Conference of Cognitive Science (ACCS8) - Jan 20--22, 2022, India
by Shyam Diwakar Sept. 18, 2021

Sept. 18, 2021

Dear All, As the local organizer, it is our pleasure to invite you to participate at ACCS8. Here's more details. ACCS8: Call for contributions 8th Annual Conference of Cognitive Science (ACCS8) Amrita University, India – 20 – 22 January 2022 https://www.amrita.edu/accs8 The 8th edition of ACCS, to be hosted by Amrita Vishwa Vidyapeetham (Amrita University), Kollam, India will be held virtually. List of our invited speakers, TPC and other info will soon be made available at https://www.amrita.edu/event/accs8 CONFERENCE TOPICS Like in our previous years, the ACCS8 conference is open to all topics with Cognitive Science as a discipline, and in various areas of study, including Neuroscience, Artificial Intelligence, Linguistics, Skilling, Medicine, Anthropology, Psychology, Philosophy, and Education. SUBMISSION GUIDELINES We welcome submissions from all areas of cognitive science and from anyone worldwide. For the 2022 online event, we are accepting only abstracts containing the salient details of your study. Please copy and paste the title and abstract into the submission form. Contribution size limit for the abstract is 1000 words. We are not accepting any paper-length submissions this year, so do include all relevant details in the abstract itself. A small number of abstracts will be selected for oral presentations/talks. Submission link: https://easychair.org/conferences/?conf=accs8 For CFP: https://easychair.org/cfp/accs8 IMPORTANT DATES Abstract registration deadline November 25, 2021 Submission deadline November 25, 2021 BEST PAPER AWARDS We are planning some best poster and oral presentations. Please stay tuned. CONTACT All questions about submissions should be emailed to accs8conference(a)gmail.com<mailto:accs8conference@gmail.com> Previous ACCS events - https://www.amrita.edu/event/accs8/about With best regards, Shyam Diwakar -- Prof. Shyam Diwakar, Ph.D. Director - Amrita Mind Brain Center Faculty Fellow - Amrita Center for International Programs Amrita Vishwa Vidyapeetham (Amrita University) Amritapuri, Clappana P.O. Kollam, India. Pin: 690525 Ph:+91-476-2803116 Fax:+91-476-2899722 http://amrita.edu/mindbrain [https://docs.google.com/uc?export=download&id=1_nOxaCXob6wVcuQyYI5KVk1PhMgi…] [https://intranet.cb.amrita.edu/sig/RankingLogo.png] Disclaimer : The information transmitted in this email, including attachments, is intended only for the person(s) or entity to which it is addressed and may contain confidential and/or privileged material. Any review, retransmission, dissemination or other use of, or taking of any action in reliance upon this information by persons or entities other than the intended recipient is prohibited. Any views expressed in any message are those of the individual sender and may not necessarily reflect the views of Amrita Vishwa Vidyapeetham. If you received this in error, please contact the sender and destroy any copies of this information.

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(Call for papers) Adaptive Machines: Leveraging Neuroscience for Lifelong Learning Systems
by Andrea Soltoggio Sept. 17, 2021

Sept. 17, 2021

Dear All, This is a reminder of the upcoming deadline (30th of September) to submit to the Research Topic “Adaptive Machines: Leveraging Neuroscience for Lifelong Learning Systems”, co-hosted by Frontiers in Neuroscience, Robotics and AI, Big Data, Artificial Intelligence, Neurorobotics and Computational Neuroscience. Link: https://www.frontiersin.org/research-topics/20053/adaptive-machines-leverag… Description: Artificial intelligence has always sought inspiration in the brain. Artificial neural networks (ANNs), in particular, were modeled after their biological counterparts (biological neural networks, BNNs). However, state-of-the-art deep networks are drastically different from BNNs. Their architectures (at both the single-neuron and macro levels), learning algorithms, and failure conditions share little in common with brain circuit dynamics. In particular, state-of-the-art deep learning is optimized for single, well-defined, static tasks. Deep networks struggle to learn multiple or evolving tasks over time (i.e., continual learning) or to adjust their processing based on environmental conditions. They are also less modular than BNNs, and thus less energy efficient, and utilize little-to-no feedback signals. We believe that deep networks suffer from these limitations because their modeling of brain dynamics is too superficial. Modeling more sophisticated neural mechanisms is therefore key for deep networks to achieve continual or lifelong learning and to cope with open-ended, dynamic environments. The goal of this Research Topic is to publish novel models and/or algorithms that expand the capabilities of deep learning (e.g., achieve better continual learning) by incorporating additional properties of BNNs. We are also interested in neuroscience research that elucidates mechanisms that can be leveraged by the AI community. Neuroscience has uncovered a wide range of learning and regulatory mechanisms, at scales ranging from single molecules to the entire nervous system, that help the brain learn, remember, and adapt. These include replay (systems-level consolidation), neuromodulation, neurogenesis, neuroevolution, attention, homeostatic plasticity, and synaptic consolidation. There exist some deep learning techniques motivated by these mechanisms (e.g., experience replay or attention networks), but they have rarely been used for lifelong learning. As such, our focus will be on approaches that leverage brain-like principles---ideally biologically well-grounded---to solve problems currently beyond the capabilities of the state of the art. We will also welcome neuroscience research that helps to elucidate the brain’s mechanisms, in the hope that they can be used by the next generation of machine learning models. The scope of this Research Topic covers: (1) biologically inspired techniques in deep learning (2) neuroscience research on how the brain facilitates learning and adapts to different contexts We seek to address continual or lifelong learning, transfer learning, and other ML scenarios that go beyond the traditional, train-then-test learning paradigm. Since machine learning is an experimental field, a paper must include experimental results to be accepted; however, we encourage authors to include theoretical analyses of their methods. We aim to collect the following types of manuscripts: Original Research and Brief Research Reports. Since the goal of this Research Topic is to publish highly novel, experimentally grounded work, we are not interested in Reviews (Systematic, Policy and Practice, etc.), General Commentaries, or Opinions. In addition, since the editorial board does not include medical experts, we cannot accept Clinical Trials or Study Protocols. The Research Topic is edited by Rolando Jose Estrada, Georgia State University, USA Andrea Soltoggio, Loughborough University, UK Praveen K. Pilly, HRL Laboratories, USA Vincenzo Lomonaco, University of Pisa, Italy, Davide Maltoni, University of Bologna, Italy. Please consider submitting your original research to this Research Topic. Do not hesitate to get in touch if you wish to discuss your contribution. Best wishes, Andrea -- Dr. Andrea Soltoggio (he/him or they/them) Senior Lecturer (Associate Professor) in Artificial Intelligence Department of Computer Science, School of Science & Intelligent Automation Centre https://www.intelligent-automation.org.uk/about-us/centre-staff & Centre for Information Management https://www.lboro.ac.uk/departments/sbe/cim/ Haslegrave Building, N.2.03 Loughborough University LE11 3TU, UK Email: a.soltoggio(a)lboro.ac.uk<mailto:a.soltoggio@lboro.ac.uk> Web: http://www.lboro.ac.uk/departments/compsci/staff/dr-andrea-soltoggio.html

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ISRC Computational Neuroscience, Neurotechnology and Neuro-inspired AI Autumn School (ISRC-CN3)
by Wong-Lin, Kongfatt Sept. 17, 2021

Sept. 17, 2021

Dear All, We are excited to announce that our ISRC Computational Neuroscience, Neurotechnology and Neuro-inspired AI Autumn School (ISRC-CN3) is now live and open for registration at the following link: https://store.ulster.ac.uk/product-catalogue/faculty-of-computing-engineeri… This Autumn School (from 25th October to 29th October), which will be conducted in a hybrid format, is organised by our Intelligent Systems Research Centre (ISRC) at Ulster University, Magee campus. More details can be found at the website: https://sites.google.com/view/isrc-cn3/home<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fsites.goo…> If you have any further queries about this event, please contact Dr. KongFatt Wong-Lin (k.wong-lin(a)ulster.ac.uk) This email and any attachments are confidential and intended solely for the use of the addressee and may contain information which is covered by legal, professional or other privilege. If you have received this email in error please notify the system manager at postmaster(a)ulster.ac.uk and delete this email immediately. Any views or opinions expressed are solely those of the author and do not necessarily represent those of Ulster University. The University's computer systems may be monitored and communications carried out on them may be recorded to secure the effective operation of the system and for other lawful purposes. Ulster University does not guarantee that this email or any attachments are free from viruses or 100% secure. Unless expressly stated in the body of a separate attachment, the text of email is not intended to form a binding contract. Correspondence to and from the University may be subject to requests for disclosure by 3rd parties under relevant legislation. The Ulster University was founded by Royal Charter in 1984 and is registered with company number RC000726 and VAT registered number GB672390524.The primary contact address for Ulster University in Northern Ireland is Cromore Road, Coleraine, Co. Londonderry BT52 1SA

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Postdoctoral Associate in Neural Circuits of Learning and Memory
by Yuri Dabaghian Sept. 17, 2021

Sept. 17, 2021

NIH-funded postdoctoral position is immediately available in the group of Dr. Yuri Dabaghian in the Department of Neurology at McGovern Medical School of the University of Texas, Houston. We are looking for scientists with research interests at the intersection of mathematics, physics, and neuroscience, in the general area of emergent phenomena and representations, network dynamics, topological data analyses. Some projects aim to explain electrophysiological data patterns, some are theoretically motivated. Specifically, we are interested in circuit mechanisms of learning and memory and their involvement in neurological disorders, notably Alzheimer's Disease. Successful candidates will develop data-driven hippocampal neuronal network models explaining spatial learning dynamics, develop and creatively apply tools for the data analysis including novel methods of brain waves (EEG) analyses, Topological Data Analysis of spiking data, etc. The Position requires strong background in quantitative disciplines (PhD and ongoing interest in computational or theoretical neuroscience, physics, mathematics, or related), plus willingness to do programming and to analyze experimental data. Previous experiences in data analyses are preferred but not required. All Appointments are initially for one year and are renewable for at least three years given satisfactory performance. The salary is competitive. The postdoc will be integrated into the large, vibrant neuroscience community of the Texas Medical Center and have the opportunity to participate in collaborations with groups at Baylor College of Medicine and Rice University. To apply, please send application materials including a detailed CV, a brief statement of research interests, and contact information of 3 references to Dr. Yuri Dabaghian at [Yuri.A.Dabaghian [at] uth.tmc.edu) The position is available immediately, until filled. For Additional information and informal inquiries, please contact Dr. Dabaghian. We Strive for a diverse and inclusive environment, and encourage applications from members of any identity.

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COSYNE 2022: Meeting announcement
by Tomas Hromadka Sept. 16, 2021

Sept. 16, 2021

==================================================== Computational and Systems Neuroscience 2022 (Cosyne) MAIN MEETING 17 - 20 March 2022 Lisbon, Portugal WORKSHOPS 21 - 22 March 2022 Cascais, Portugal www.cosyne.org ==================================================== ---------------------------------------------------- MEETING ANNOUNCEMENT ---------------------------------------------------- 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. All abstract submissions will be reviewed double blind. The deadline for Abstract submission will be 20 November 2021. 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. IMPORTANT DATES Abstract submission opens: 15 October 2021 Travel grant submission opens: 01 November 2021 Abstract submission deadline: 20 November 2021 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. ORGANIZING COMMITTEE General Chairs: Anne-Marie Oswald (U Pittsburgh) and Srdjan Ostojic (Ecole Normale Superieure Paris) Program Chairs: Laura Busse (LMU Munich) and Tim Vogels (IST Austria) Workshop Chairs: Anna Schapiro (U Penn) and Blake Richards (McGill) Tutorial Chair: Kanaka Rajan (Mount Sinai) DEIA Committee: Bianca Jones Martin (Columbia), Gabrielle Gutierrez (Columbia), and Stefano Recanatesi (U Washington) Undergraduate Travel Chairs: Angela Langdon (Princeton) and Bob Wilson (U Arizona) Fundraising Chair: Michael Long (NYU) Social Media Chair: Grace Lindsay (Columbia) Poster Design: Maja Bialon PROGRAM COMMITTEE Laura Busse (U Munich) Tim Vogels (IST Austria) Athena Akrami (UCL) Omri Barak (Technion) Brice Bathellier (Paris) Bing Brunton (U Washington) Yoram Burak (Hebrew University) SueYeon Chung (Columbia) Christine Constantinople (NYU) Victor de Lafuente (UNAM Mexico) Jan Drugowitsch (Harvard) Alexander Ecker (Göttingen) Tatiana Engel (Cold Spring Harbor) Annegret Falkner (Princeton) Kevin Franks (Duke) Jens Kremkow (Berlin) Andrew Leifer (Princeton) Sukbin Lim (Shanghai) Scott Linderman (Stanford) Emilie Mace (MPI Neurobiology) Mackenzie Mathis (EPFL Lausanne) Ida Momennejad (Microsoft) Jill O'Reilly (Oxford) Il Memming Park (Stony Brook) Adrien Peyrache (McGill Montréal) Yiota Porazi (FORCE) Nathalie Rochefort (Edinburgh) Christina Savin (NYU) Daniela Vallentin (MPI Ornithology) Brad Wyble (U Penn) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) 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 -> Mailing lists for details.

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Online workshop "Towards multipurpose neural network models II: Model testing and model fitting"
by Anton Arkhipov Sept. 14, 2021

Sept. 14, 2021

Dear Colleagues, Registration is now open for the online workshop "Towards multipurpose neural network models II: Model testing and model fitting" organized by Gaute Einevoll (NMBU/University of Oslo) and Anton Arkhipov (Allen Institute, Seattle) and supported by the European Institute for Theoretical Neuroscience (EITN). Please join us for three days of talks about cutting-edge science by fantastic speakers, as well as panel discussions. Dates: September 29 – October 1, 2021 Time: 8AM – 12:15PM US Pacific time / 5PM – 9:15PM Central European Time Daily. Registration: https://cnrs.zoom.us/webinar/register/WN_saMXfg31Roe4tqHbWtTdFg Please see the agenda below and more details at this web page: https://www.eitn.org/index.php/calendar-event/eventdetail/750/-/workshop-on… We hope to see you there! Wednesday, September 29, 2021 Gaute Einevoll (NMBU/U. Oslo) Introduction Jacob Macke (U. Tübingen) Keynote. Simulation-based inference: Bridging the gap between mechanistic models and machine learning. Aaron Milstein (Rutgers U.) Nested parallel simulation and multi-objective optimization of neuronal cell and circuit models Atle Rimehaug (U. Oslo) Enhancing model constraints by utilizing current source densities Kristin Tøndel (NMBU) Facilitating optimization using metamodelling Frances Skinner (Krembil Brain Institute, University Health Network, and University of Toronto) Clarity in model development and goals leads to model linkages and biological insights Panel debate – All participants of the day. Thursday, September 30, 2021 Anton Arkhipov (Allen Institute) Introduction James DiCarlo (MIT) Keynote. Reverse Engineering Visual Intelligence Sharon Crook (Arizona State U.) Testing the Data-driven Model Szabolcs Kali (Institute of Experimental Medicine, Budapest, Hungary) Systematic construction and evaluation of models of rodent hippocampal neurons Peter Jedlicka (U. Giessen) Building consistent and robust models of hippocampal granule cells and CA1 pyramidal cells Stefan Mihalas (Allen Institute) Computing with a mess: How nonstationary, heterogeneous and noisy components help the brain’s computational power Panel debate – All participants of the day. Friday, October 1, 2021 Markus Covert (Stanford) Special lecture. Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation Kanaka Rajan (Mount Sinai) Keynote. Data-constrained neural network models of adaptive learning in the brain Julijana Gjorgjeva (Max Planck Institute and TUM) Biologically plausible learning in developing networks Carsen Stringer (Janelia) Rastermap: Extracting structure from high-dimensional neural data Arvind Kumar (KTH Stockholm) Structure and activity dynamics relationship in biological neuronal networks: Measurements and models Panel debate – All participants of the day.

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PhD position in computational neuroscience/machine learning at UC Santa Barbara
by Michael Beyeler Sept. 14, 2021

Sept. 14, 2021

The Bionic Vision Lab lab at the University of California, Santa Barbara (UCSB) invites applications for a fully funded PhD position to develop computational models of neural activity in mice navigating through real-world and virtual environments. The successful candidate will have a strong quantitative background that includes machine learning, programming experience, and a thorough interest in neuroscience. This is an opportunity to work on an impactful real-world problem within a highly interdisciplinary and collaborative environment. Interested applicants should send a CV and transcript (unofficial is fine) to Michael Beyeler (mbeyeler(a)ucsb.edu) Official applications will have to be submitted through UCSB Grad Admissions before the application deadline indicated below. All genders welcome. Application deadline: December 1, 2021 Start date: Fall 2022 UCSB is a dynamic research institution, particularly in physical sciences and engineering, and was recently rated one of the Top 5 public schools in the United States (US News & World Report). Neuroscience research is well established here, featuring >35 faculty members whose research interests span the range from molecular to theoretical neuroscience.

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Call for community feedback on the endorsement of Neurolucida XML as a standard
by Malin Sandström Sept. 14, 2021

Sept. 14, 2021

Dear all, INCF is seeking community feedback and comments on the review of the MBF neuromorphological file format v 4.0, a format for digital reconstruction & modeling structure for microscopic anatomies, also known as “Neurolucida XML”, which has been submitted to INCF for endorsement as a community standard. If you have experience of using Neurolucida XML, we ask you to read the review report and comment based on your experiences, especially if you share or reuse data in the format, or work on models or tools that use the format. Link to the review: https://f1000research.com/documents/10-712 *Why endorse community standards? * INCF (incf.org) has implemented a formal procedure for evaluating and endorsing community standards and best practices in support of the FAIR principles. Our mission is to make neuroscience more open and FAIR, to ensure that research funds and efforts are well invested, and that neuroscientific findings are robust and replicable. Open community review is a very important step in the process. Quality community standards are necessary to make FAIR resources and processes work, but too many neuroscience communities lack robust standards or have competing incompatible standards. The rapid development of new techniques also means that there is a continuous need for new and updated standards, and that old standards need an active developer and user community keeping them up to date. By endorsing standards, INCF wants to make it easy to find the best, most reliable standard appropriate for your research, and ensure recognition for community members investing their time and effort in standards. The review criteria (https://incf.org/incf-standards-review-criteria-v20) include Openness; FAIRness; Design, Testing and Implementation; Governance; Adoption and use; Stability and support; Extensibility; Comparison (similarity to other standards). -- Malin Sandström, PhD Community Engagement Officer malin.sandstrom(a)incf.org ORCID: 0000-0002-8464-2494 International Neuroinformatics Coordinating Facility Karolinska Institutet Nobels väg 15 A SE-171 77 Stockholm Sweden http://www.incf.org

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workshop on Brain Criticality: The Past, the Present and the Future
by Claudius Gros Sept. 14, 2021

Sept. 14, 2021

You are invited to attend the upcoming Bernstein workshop on Brain Criticality: The Past, the Present and the Future https://www.bernstein-network.de/en/bernstein-conference/2021-online/satell… Tuesday, September 21, 2021, 2pm CEST It is free, but you need to register with the Bernstein conference (see link above). Claudius Gros ### ### Prof. Dr. Claudius Gros ### http://itp.uni-frankfurt.de/~gros ### ### Complex and Adaptive Dynamical Systems, A Primer ### A graduate-level textbook, Springer (2008/10/13/15) ### ### Life for barren exoplanets: The Genesis project ### https://link.springer.com/article/10.1007/s10509-016-2911-0 ###

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Bernstein Conference 2021 - abstracts are published
by Anja Dorrn Sept. 13, 2021

Sept. 13, 2021

Each year the Bernstein Network invites the international computational neuroscience community to the annual Bernstein Conference for intensive scientific exchange. It has established itself as one of the most renown conferences worldwide in this field, attracting students, postdocs and PIs from around the world to meet and discuss new scientific discoveries. Due to the ongoing pandemic the Bernstein Conference will be held online. www.bernstein-conference.de ____ IMPORTANT DATES & NEWS * Bernstein Conference: September 21-23, 2021 * Abstracts are published * Registration is open and free of charge * PhD Symposium on September 24, 2021 ____ ABSTRACTS All accepted abstracts are now published online and are citable via Digital Object Identifiers (DOI). Please find them here: https://abstracts.g-node.org/conference/BC21/abstracts#/ ____ REGISTRATION The participation at the online Bernstein Conference 2021 will be free of charge for all participants. Thus the Bernstein Network contributes to keep the scientific exchange alive in the ongoing challenges during the pandemic. Please register here: https://hopin.com/events/bernstein-conference-2021 ____ PHD SYMPOSIUM The Bernstein PhD Symposium on September 24, 2021 is an opportunity for junior researchers to meet their peers, share their experience and make new connections. This year's topic is Gaming meets neuroscience. Please register here: https://hopin.com/events/bernstein-phd-symposium-2021 ____ INVITED SPEAKERS Keynote Timothy Behrens (University of Oxford, UK) Invited Talks Athena Akrami (University College London, UK) Nadine Gogolla (Max Planck Institute for Neurobiology, Martinsried, Germany) Guillaume Hennequin (University of Cambridge, UK) Jennifer Li & Drew Robson (Max Planck Institute for Biological Cybernetics, Tübingen, Germany) Scott Lindermann (Stanford University, USA) Ashok Litwin-Kumar (Columbia University, New York City, USA) Ida Momennejad (Microsoft Research, New York City, USA) Cristina Savin (New York University, USA) Marion Silies (Johannes Gutenberg University, Mainz, Germany) Daniela Vallentin (Max Planck Institute for Ornithology, Seewiesen, Germany) ____ CONFERENCE COMMITTEE Christian Leibold (Conference Chair) Julijana Gjiorgjieva (Program Chair) Christian Machens (Program Vice Chair) Marion Silies (Workshop Chair) Moritz Helias (Workshop Vice Chair) & Matthew Botvinick, Megan Carey, Peter Dayan, Brent Doiron, Rainer Friedrich, Ann Hermundstad, Srdjan Ostojic, Nathalie Rochefort, Nicole Rust, Gasper Tkacik ____ For any further questions, please contact: bernstein.conference(a)fz-juelich.de -- Dr. Anja Dorrn Scientific Coordinator Bernstein Network Computational Neuroscience | Bernstein Coordination Site (BCOS) Branch Office of the Forschungszentrum Jülich at the University of Freiburg Hansastr. 9A | 79104 Freiburg, Germany phone: (+49) 0761 203 9589 web: www.bernstein-network.de<http://www.bernstein-network.de> ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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Biologically plausible models of path planning in humans and rodents
by Jeffrey Krichmar Sept. 10, 2021

Sept. 10, 2021

Dear Colleagues, We recently published two papers on biologically plausible models of path planning that simulate and analyze navigation strategies in rodents and humans. Some of the ideas presented in these papers may be applicable to autonomous systems. If you are interested, please see: Krichmar, J.L., and He, C. (2021). Importance of Path Planning Variability: A Simulation Study. Topics in Cognitive Science. https://onlinelibrary.wiley.com/doi/10.1111/tops.12568 Individuals vary in the way they navigate through space. Some take novel shortcuts, while others rely on known routes to find their way around. We wondered how and why there is so much variation in the population. To address this, we first compared the trajectories of 368 human subjects navigating a virtual maze with simulated trajectories. The simulated trajectories were generated by strategy-based path planning algorithms from robotics. Based on the similarities between human trajectories and different strategy-based simulated trajectories, we found that there is a variation in the type of strategy individuals apply to navigate space, as well as variation within individuals on a trial-by-trial basis. Moreover, we observed variation within a trial when subjects occasionally switched the navigation strategies halfway through a trajectory. In these cases, subjects started with a route strategy, in which they followed a familiar path, and then switched to a survey strategy, in which they took shortcuts by considering the layout of the environment. Then we simulated a second set of trajectories using five different but comparable artificial maps. These trajectories produced the similar pattern of strategy variation within and between trials. Furthermore, we varied the relative cost, that is, the assumed mental effort or required timesteps to choose a learned route over alternative paths. When the learned route was relatively costly, the simulated agents tended to take shortcuts. Conversely, when the learned route was less costly, the simulated agents showed preference toward a route strategy. We suggest that cost or assumed mental effort may be the reason why in previous studies, subjects used survey knowledge when instructed to take the shortest path. We suggest that this variation we observe in humans may be beneficial for robotic swarms or collections of autonomous agents during information gathering. Krichmar, J.L., Ketz, N.A., Pilly, P.K., and Soltoggio, A. (2021). Flexible Path Planning through Vicarious Trial and Error. bioRxiv, 2021.2009.2008.459317. https://www.biorxiv.org/node/2148912.abstract Flexible planning is necessary for reaching goals and adapting when conditions change. We introduce a biologically plausible path planning model that learns its environment, rapidly adapts to change, and plans efficient routes to goals. Unlike prior models of hippocamapl replay, our model addresses the decision-making process when faced with uncertainty. We tested the model in simulations of human and rodent navigation in mazes. Like the human and rat, the model was able to generate novel shortcuts, and take detours when familiar routes were blocked. Similar to rodent hippocampus recordings, the neural activity of the model resembles neural correlates of Vicarious Trial and Error (VTE) during early learning or during uncertain conditions. Similar to rodent studies, after learning, the neural activity resembles forward replay or preplay predicting a future route, and VTE activity decreases. We suggest that VTE, in addition to weighing possible outcomes, is a way in which an organism may gather information for future use. Best regards, 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

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Postdoctoral position available
by Sara A. Solla Sept. 10, 2021

Sept. 10, 2021

*Integrating Human and Machine Learning for Enabling Co-Adaptive * *Body-Machine Interfaces* * Sandro Mussa-Ivaldi and Sara A. Solla PI’s * *Northwestern University* We are seeking postdoctoral applicants with interests and experience in computational methods, machine learning, and human-machine interactions to participate in an NSF-funded project. The goal of the project is customizing human-machine interfaces through a collaborative interaction between human and machine learning. This has relevance to the recovery of function after injury to the spinal cord. The same goals apply also to non-clinical domains. Common to the different domains is the necessity to learn novel movement skills. The project will consider how this challenge is met through the interaction with an adaptive interface, the body-machine interface, that maps body motions onto commands to external devices. The working hypotheses are H1) that through a dynamical process of learning the human operators form an internal model of the interface and connected device, and H2) that the human machine interface can be adapted to its users by an update rule that tracks the learning process of the human operator. The success of the research project will lead to a new family of intelligent human machine interfaces capable of customizing themselves to the evolving ability of their users. Applications, including a brief statement, a bio sketch, and the names of two references, should be sent to bomiproject2021(a)gmail.com

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Postdoc position on neural mechanisms of flexible behavior
by Luca Mazzucato Sept. 5, 2021

Sept. 5, 2021

Dear colleagues, We are looking for a computational neuroscience postdoc to lead a project on the neural mechanisms of flexible behavior. The theory position will be co-supervised by Luca Mazzucato and David McCormick and funded by the NIH BRAIN Initiative collaboration between the McCormick, Niell, Jaramillo and Mazzucato labs at University of Oregon. The project aims at elucidating the whole-brain dynamics enabling flexible modality switching in an audiovisual decision-making task. A successful candidate will use state-space models and multi-area recurrent network models to elucidate the activity and functional connectivity of cortical circuits from large datasets in behaving mice (2-photon mesoscope with ~10k neurons; multiple neuropixel probes). Experience with deep learning is recommended for integrating behavioral analyses with task performance and neural activity. The postdoc will be part of the vibrant neuroscience and machine learning community at the University of Oregon including the Institute of Neuroscience <https://ion.uoregon.edu/> and the Knight Campus <https://accelerate.uoregon.edu/> for Accelerating Science. The University is located in beautiful Eugene, the country's leader in the "20-minute friendly <https://tinyurl.com/y8jd8pmr>" bike commute movement, at close range between the Cascades ski areas and the Pacific Ocean. Successful candidates will have a PhD in Physics, Neuroscience, Mathematics, Computer Science, Statistics or a related discipline and, preferably, experience in theoretical neuroscience and statistical analysis of large neuroscience datasets. For inquiries please contact Luca Mazzucato or David McCormick.

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8th Baltic-Nordic Summer School on Neuroscience and Neuroinformatics (BNNI 2021)
by Pawel Herman Sept. 5, 2021

Sept. 5, 2021

Dear Fellow Neuroscientists and Students We would like to invite you to the 8th Baltic-Nordic Summer School on Neuroscience and Neuroinformatics, which will be organised as a virtual event on 21-25 September, 2021. The 8th Baltic-Nordic Summer School on Neuroscience and Neuroinformatics 2021 “Learning in the Brain and NeuroRobots – from Molecules to Behaviour” offers interdisciplinary course and covers modelling at different levels of organization of the brain, from single neurons to microcircuits, neural networks and neurorobotics. The course offers lectures on the latest achievements in understanding learning, neural and network dynamics and function in health and disease, neurorobotic theory and applications, and hands-on tutorials on the EBRAINS services and tools. The summer school targets advanced master students, doctoral students and postdoctoral researchers in biomedical and technology sciences, ranging from medicine, biology, psychology, to mathematics, informatics, information technology, physics and chemistry, who would like to get an introduction to neuroinformatics and computational neuroscience and especially the EBRAINS Infrastructure<http://ebrains.eu/> (ebrains.eu<http://ebrains.eu>). Further information and registration: https://www.humanbrainproject.eu/en/education/BNNI2021/ Best regards Pawel Herman on behalf of the organising committee ------------------------------------ Paweł Herman Associate Professor, PhD, Docent KTH Royal Institute of Technology School of Electrical Engineering and Computer Science (EECS) Division of Computational Science and Technology (CST) Lindstedtsvägen 5 114 28 Stockholm, Sweden room 4442 (4th floor, D-building) tel. +46 8 790 6513

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DEADLINE EXTENDED: Summer School on Network and Control Sciences for Psychiatry
by Jasper Bischofberger Sept. 2, 2021

Sept. 2, 2021

Dear all, We are happy to announce a Summer School on “Current and Future Applications of Network and Control Sciences for Psychiatry” Host Institution: *University of Tübingen, Germany* Location: *Online event* Dates: *September 29th – October 1st 2021* Abstract deadline: *September 10th, 2021* Registration fees: *free* *Focus* This Summer School gives an opportunity to students and young researchers to get acquainted with and exchange within a range of current topics in network and control sciences and its applications in Psychiatry. ____ *Keynotes* Danielle S. Bassett (University of Pennsylvania, USA) Peter Dayan (MPI Tübingen, Germany) John Medaglia (Drexel University, USA) For the full list of speakers visit: https://www.medizin.uni-tuebingen.de/de/summer-school-controlpsychiatry/spe… ____ *Registration* The summer school is free of charge for all participants, but to get all important information please register online via: https://www.medizin.uni-tuebingen.de/de/summer-school-controlpsychiatry ____ *Poster Submission* Participants can present their latest research results as a poster. Some of the most relevant submissions will have the possibility to present their work in a dedicated oral session and receive an official certificate. Please submit your abstract (limited to 250 words) latest by September 10th to: controlpsychiatry(a)med.uni-tuebingen.de ____ Questions? Please contact: controlpsychiatry(a)med.uni-tuebingen.de We are excited to see you soon! Best wishes, The organizing committee

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Faculty Position in Computational Neuroscience at Bristol University.
by Conor Houghton Aug. 31, 2021

Aug. 31, 2021

In the Department of Computer Science at the University of Bristol we are seeking to appoint a faculty member in Computational Neuroscience at Lecturer or Senior Lecturer level, comparable to Assistant or Associate Professorship level. https://www.bristol.ac.uk/jobs/find/details/?jobId=252155 Candidates are sought with expertise in computational neuroscience or computational cognitive science; any area of our broad subject will be considered. The University of Bristol is a significant centre for both computational neuroscience and machine learning and a leader in experimental, clinical and cognitive neuroscience. There is a robust tradition of collaboration between experimental and computational neuroscientists. Bristol itself is a friendly green coastal city with a rich and lively cultural scene and is regarded one of the best places to live in the UK. You are welcome to contact one of us (conor.houghton||laurence.aitchison||n.lepora||rui.costa)(a)bristol.ac.uk, or our head of department Chris Allen, c.b.allen(a)bristol.ac.uk, to discuss the post informally. The closing date for applications is 3 October. We value diversity and are committed to equality of opportunity. All the best Conor Houghton Laurence Aitchison Nathan Lepora Rui Ponte Costa https://bristolcnu.github.io/ http://www.bristol.ac.uk/neuroscience/

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PhD position at the Goethe University Frankfurt, Germany
by Claudius Gros Aug. 30, 2021

Aug. 30, 2021

Applications are invited for a fully funded PhD position at the Institute for Theoretical Physics, Goethe University Frankfurt, Germany Fields: theoretical neurosciences, complex systems theory, Covid-19 modeling Application deadline: Oct 15, 2021 Supervisor: Prof. Dr. Claudius Gros We are developing new models and generative principles for the societies of interacting agents using a range of toolsets from dynamical systems theory and game theory. Examples are Covid-19 modeling and the influence of envy on the structure of human societies. We are also developing operating principles for reference robot systems, and for neuroscience applications. It is expected that applicants study the publication list available on the website of the lab, as given below. Several subjects are available for the announced PhD thesis, depending on the background of the successful candidate. The work will include analytical investigations and numerical simulations. The candidates should have a Diploma/Master's in physics with an excellent academic track record and good computational skills. Experience or strong interest in the fields of complex systems, dynamical systems theory, game theory, and/or artificial or biological cognitive systems is expected. The degree of scientific research experience is expected to be on the level of a German Diploma/Master. The appointment will start early 2022, for three years. Interested applicants should submit a curriculum vitae and a list of publications, and arrange for letters of reference to be sent to the address below. Prof. Claudius Gros Institute for Theoretical Physics Goethe University Frankfurt Max-von-Laue-Str. 1 60438 Frankfurt am Main, Germany cgr(a)itp.uni-frankfurt.de http://www.itp.uni-frankfurt.de/~gros General information on the University of Frankfurt and its employment policy: With its around 46,000 students and 4,600 employees, the Goethe University in Frankfurt is the largest university in the state of Hessen and an internationally renowned, important regional employer. Numerous quality and performance oriented internal reforms have been initiated in the recent years. The reorganized campuses for natural sciences and humanities offer an ideal environment for research and education. Since 2008, the Goethe University is a foundation under public law and enjoys full administrative autonomy.  The fixed-term employment of the academic staff is subject to the provisions of the Temporary Science Employment Law and the Hessian Higher Education Act. The University advocates gender equality and therefore strongly encourages women to apply. People with disabilities are given preference if equally qualified. -- ### ### Prof. Dr. Claudius Gros ### http://itp.uni-frankfurt.de/~gros ### ### Complex and Adaptive Dynamical Systems, A Primer ### A graduate-level textbook, Springer (2008/10/13/15) ### ### Life for barren exoplanets: The Genesis project ### https://link.springer.com/article/10.1007/s10509-016-2911-0 ###

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Ph.D. student / Postdoc position in machine learning with spiking neurons at University of Bremen, Germany
by David Rotermund Aug. 30, 2021

Aug. 30, 2021

tl;dr: You looked at our paper Back-Propagation Learning in Deep Spike-By-Spike Networks ( https://www.frontiersin.org/articles/10.3389/fncom.2019.00055/full ) and thought "Interesting idea but I can improve that!" then you may want to tell us your idea... You could end up working on it as a Ph.D. student / Postdoc for the next three years in Bremen, Germany. ------------- The Computational Neuroscience group of Klaus Pawelzik invites applications for an open Ph.D. student / Postdoc position (E13 TV-L 100% for 3 years; all genders welcome) in the project "Efficient Implementation of Spike-by-Spike Neural Networks using Stochastic and Approximative Techniques". We are looking for a person with a strong background in mathematics, programming, and machine learning as well as an intense interest in neuroscience. Someone who is not afraid of cooperating with engineers, since this is a joint project with a focus on hardware development. The overarching goal of our project is to improve the efficiency of spiking artificial neural networks using hardware and algorithmic approximation techniques. Specifically, the project focuses on Spike-by-Spike networks since they offer a balance between computational requirements and biological-realism which keeps the advantages of the biological networks while enabling a compact technical realization. To fully take advantage of the unique features of SbS in terms of robustness and sparseness, dedicated hardware architectures are required. You would join in with numerical simulations, theoretical analyses, as well as through the development of new ideas and approaches for boosting the performance and capabilities of the Spike-By-Spike model. Furthermore, you would also work on combining Spike-By-Spike networks with non spiking deep neuronal networks into hybrid models. The details can be found at http://www.neuro.uni-bremen.de/content/open-position-sbs

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