September 2021 - Comp-neuro - lists.cnsorg.org

Call for Visiting Scholars in Theoretical Sciences at OIST (Application by August 15)
by Kenji Doya Oct. 21, 2023

Oct. 21, 2023

We are pleased to announce Visiting Scholars in Theoretical Sciences at OIST for a flexible term of 1 to 12 months as below. ***** As part of an initiative to develop a vibrant program in theoretical sciences, OIST invites applications for Visiting Scholars in the Theoretical Sciences. The Okinawa Institute of Science and Technology (OIST) is a research institution with a Ph.D. program. Outstanding graduate students and faculty are being attracted internationally. OIST is beautifully situated on the tropical island of Okinawa, Japan. Applicants should have a Ph.D. in a relevant field and be independent researchers, i.e., should have an academic standing equivalent to senior postdoc, junior group leader, or faculty member at a research-intensive institution. The position has a flexible term of 1 to 12 months taken continuously starting between October 2021 and March 2022 with a preference for longer-term visitors. The appointment may be taken while on leave or sabbatical from another university and comes with housing, research funds, and moving allowance. Successful candidates will be eligible to apply for support with salary, where this is necessary to facilitate the visit. No teaching duties come with the position. OIST is an institution with no departments, aiming to eliminate barriers between people working in different fields. It provides a family-friendly working environment including the multilingual Child Development Center and has proactive policies designed to promote a culture of diversity. OIST is an equal opportunity, affirmative action educator, and employer. Further details can be found at https://www.oist.jp/. Applicants should submit a CV including a list of publications, a brief description of their research to date and proposed research while visiting OIST, and the desired period of visit. All visits are subject to the availability of funding. Applications received by August 15, 2021, are guaranteed full consideration. If you have any questions, please send inquiries to: tsvp(a)oist.jp To apply, please go to our Interfolio page, http://apply.interfolio.com/88541 ---- Kenji Doya <doya(a)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

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Up to 6 PhD fellowships in Cognitive Neuroscience at SISSA, Trieste, Italy, to start Oct, 2020
by Alessandro Treves Oct. 12, 2022

Oct. 12, 2022

SISSA is an elite postgraduate research institution located in Trieste, Italy, and focused on Maths, Physics and Neuroscience. It operates in English: many among its students and faculty are not Italian. The Cognitive Neuroscience Department hosts 6 research labs that study the neuronal bases of time and magnitude processing, visual perception, motivation and intelligence, language and reading, tactile perception and learning, and neural computation. The Department is very inter–disciplinary; our approaches include behavioural, psychophysics, and neurophysiological experiments with humans and animals, as well as computational and mathematical models. Students with diverse backgrounds (physics, math, medicine, psychology, biology) are most welcome to apply. The Department has an exceptional track record with highly competitive funds (recent funding includes 4 ERC and 3 Human Frontiers grants) and publication in top journals (Nature, Science, PNAS, Current Biology). Recent placements after PhD include Harvard, MIT, Columbia and Princeton in the US; the NTNU, Manchester and Radboud in Europe; and Sydney University, Australia. Our alumni have been awarded 4 ERC grants, the 2015 Kandel Young Neuroscientist Prize and the 2017 ICTP Prize. More information about the Department is available at our website https://phdcns.sissa.it. The selection procedure is now open; to learn how to apply, please visit https://phdcns.sissa.it/admission-procedure. Please contact the PhD Coordinator (davide.crepaldi(a)sissa.it) and/or your prospective supervisor for more information and informal enquiries. -- Alessandro Treves SISSA, Cognitive Neuroscience, http://people.sissa.it/~ale/limbo.html if in, rm 241, via Bonomea 265, 34136 Trieste, Italy: +39-040-3787623

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Postdoc in neural data analysis
by Mark Humphries June 26, 2022

June 26, 2022

A 3 year postdoc post is available in the lab of Prof Mark Humphries, at the University of Nottingham (UK) In this project, our aim is to test the overarching hypothesis that movement transitions are encoded by the same neural population reconfiguring its joint activity, for both rhythmic and discrete movements. We will tackle this question using newly-available population recordings during rhythmic movement transitions in Aplysia and discrete arm movement transitions in monkeys, The Humphries’ group researches fundamental insights into how the joint activity of neurons encodes information about and actions in the world. For more see: https://www.humphries-lab.org Queries: mark.humphries(a)nottingham.ac.uk Deadline: 5th September Full details, and to apply: https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2 [http://jobs.nottingham.ac.uk/org/images/socialmedia.png]<https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2> Job Vacancy at the University of Nottingham: Research Associate/Fellow (Fixed term)<https://jobs.nottingham.ac.uk/Vacancy.aspx?id=27005&forced=2> Applications are invited for a postdoctoral research fellow to join the Humphries’ group on the MRC-funded project “Uncovering the neural basis of movement transitions”. The Humphries’ group researches fundamental... jobs.nottingham.ac.uk Professor Mark Humphries | MRC Senior non-Clinical Fellow | Chair in Computational Neuroscience Lab: humphries-lab.org<https://www.humphries-lab.org/> Twitter: @markdhumphries Public blog: https://medium.com/the-spike This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.

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Explainable AI: Overcoming problems of Deep Learning problems with Adaptive Resonance
by Grossberg, Stephen April 9, 2022

April 9, 2022

Dear Colleagues, There's currently a lot of interest in AI, notably Deep Learning, and in achieving autonomous adaptive intelligence. The following new article summarizes foundational problems of reliability and trustworthiness of Deep Learning, explains how Adaptive Resonance overcomes them, and outlines a blueprint for achieving autonomous adaptive intelligence: Grossberg, S. (2020). A path towards Explainable AI and autonomous adaptive intelligence: Deep Learning, Adaptive Resonance, and models of perception, emotion, and action. Frontiers in Neurobotics, June 25, 2020. https://doi.org/10.3389/fnbot.2020.00036 Best, Steve Grossberg

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Postdoc at the University of Leicester to work on human single cell recordings
by Quian Quiroga, Rodrigo (Prof.) Nov. 23, 2021

Nov. 23, 2021

The Centre for Systems Neuroscience at the University of Leicester, UK, offers a 3-years postdoc position to study single cell recordings in humans – performed in epileptic patients for curative surgery. The project will investigate concept cells (a.k.a. Jennifer Aniston neurons) – that means, neurons in the hippocampus and surrounding areas that selectively fire to specific concepts, like different pictures and the written or spoken name of a particular person (e.g. Quian Quiroga et al, Nature 2005; Quian Quiroga Nature Reviews Neuroscience 2012), which are involved in declarative memory functions. For more details see: www.le.ac.uk/csn The successful candidate will contribute to performing recordings with patients in collaborating hospitals and the analysis of the data to investigate the role of these neurons in memory. He/She should have very good quantitative skills (data processing, and programing e.g. in Matlab) and a strong background or interest in neuroscience. He/She should be able to work both independently and as part of a research team within the Centre for System Neuroscience at Leicester and with our external collaborators. Informal enquiries are welcome and should be made to Paula Warrington, Research Centre Manager, csn(a)le.ac.uk or 0116 252 3249. To apply, please use this link: https://jobs.le.ac.uk/vacancies/1393/research-associate.html The applications should include a curriculum vitae and a brief description of their scientific interests The closing date for the applications is 21st October 2019. Cheers, Rodrigo Rodrigo Quian Quiroga Centre for Systems Neuroscience University of Leicester www.le.ac.uk/csn

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Post doc in Cognitive-Computational Neuroscience at University College London (discrete and continuous human action control under threat)
by Dominik R. Bach Oct. 21, 2021

Oct. 21, 2021

*Post doc in Cognitive-Computational Neuroscience at University College London: discrete and continuous human action control under threat* We are looking for a research fellow in an ERC-funded research project "Action selection under threat - the complex control of human defence" led by Dr Dominik Bach (http://bachlab.org <http://bachlab.org>) and based at University College London, Max-Planck UCL Centre for Computational Psychiatry (https://www.mps-ucl-centre.mpg.de/en <https://www.mps-ucl-centre.mpg.de/en>) and Wellcome Centre for Human Neuroimaging (http://www.fil.ion.ucl.ac.uk/ <http://www.fil.ion.ucl.ac.uk/>). The overarching goal of the project is to understand the cognitive-computational control of human motor behaviour under acute, immediate threat. We investigate this in an immersive virtual reality (VR) environment, in which people can move to avoid a large number of different threats. As part of this project, the candidate will build and test explicit computational models of discrete and continuous action control and action updating under constraints of time pressure and unaffordable costs. We seek applicants with established cognitive-computational modelling skills and a PhD in computational neuroscience, robotics with focus on action planning, computer science/mathematics/physics with a focus on decision science, or in a related area. We are looking for an individual who is strongly motivated to pursue an academic career and is excited by the opportunities for personal and career development this position can provide. The post is available from October 2021 and funded for up to 3 years with initial appointment for 1 year. Starting salary is on UCL grade 7, ranging from £36,028 to £43,533 per annum, inclusive of London Allowance, superannuable. More information and access to the UCL online application portal: https://is.gd/VwTJCA <https://is.gd/VwTJCA> Please contact d.bach(a)ucl.ac.uk <mailto:d.bach@ucl.ac.uk> for any queries about the project or role. *Closing date: 16 July 2021* Interviews will be held remotely in July. Apologies for cross-posting. -- ----------------------- Dominik R Bach MBBS PhD Principal Research Fellow Max Planck UCL Centre for Computational Psychiatry and Ageing Research Wellcome Centre for Human Neuroimaging, University College London http://bachlab.org | @bachlab_cog

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New Job Posting | Scientific Software Engineer (Max Planck)
by Tanya Brown Sept. 30, 2021

Sept. 30, 2021

The *Max Planck Institute for Empirical Aesthetics* in Frankfurt am Main, Germany, investigates the attentional, cognitive, and affective mechanisms of aesthetic perception and evaluation. The *Department of Neuroscience *invites applications for a *Scientific Software Engineer (m/f/x)* As part of an external funded project in collaboration with Dan Marcus, Wash. U; Sean Hill, CAMH; and members of the Cogitate Consortium, we are searching for a Scientific Data Engineer to contribute to the development of generic, cross-domain metadata management framework to foster the reuse of open datasets as well as reproducibility of cognitive neuroscience datasets i.e., metadata describing the experimental context of studies employing fMRI, MEEG, and ECoG. The successful candidate will also heavily contribute to the development of data infrastructure including storage, streaming and analysis tools for reproducible science based on the BIDS standard. Efforts will be devoted to develop tools for an efficient organization and exploration of raw and processed datasets. The position is ideal for networking in the open science community as it includes interaction with the open (neuro)science community; and is a unique opportunity for someone keen to contribute to the development of open-science and large-scale collaborations and aiming to contribute to community efforts and dissemination. *Your tasks in interdisciplinary research projects focus on:* · Review of existing approaches and tools, Requirement specification, Conceptual design, blueprint of implementation, Proof-of-concept application to Cognitive Neuroscience · Presentation and publication of the results · Exchange and networking within national (NFDI, MPDL) and international (RDA, EOSC) initiatives · Developing, testing and implementing scientific software i.e., standardized neuroscience data acquisition, reproducible analysis pipelines and data storage for open science building on the BIDS standard · Providing training and support for students and postdocs at varied levels of competence in modern, high quality, open science/source coding practices · Providing support and training for data management · Being the lab’s interface with the Institute’s core IT team *Your Profile:* · Completed university degree in natural sciences, engineering or a similar field (e.g., Mathematics, Statistics, Computer Science, Physics, Informatics, Neuroscience) · Solid programming skills preferably in Python and/or C++ · Experience with Python libraries (e.g., NumPy, SciPy, Matplotlib, and pandas) is beneficial · Experience with software development (e.g., version control with Git) and data organization (e.g., data bases with SQL and MySQL) is preferable · Knowledge of relevant metadata standards and semantic techniques are beneficial (including W3C, schema.org, RDF, JSON-LD, etc) · Interest in interdisciplinary projects and cognitive and systems neuroscience · Familiarity or experience with scientific research methods · High degree of self-organization and independent work · Team spirit, reliability, and sense of responsibility · Complete spoken and written fluency in English; knowledge of German is a plus · Preference will be given to candidates with prior experience in any of these domains: BIDS standards, Open science tools, neuroimaging techniques and data analysis (especially fMRI and MEG/EEG) and/or XNAT We offer an exciting interdisciplinary field of engagement in an international scientific environment. The Institute is located in an attractive location with excellent infrastructure in Frankfurt’s Westend neighbourhood. You can expect a modern equipped workplace with flexible working hours (some remote working is possible) and the Opportunity to participate in (international) conferences and project meetings. Further development of your personal strengths, e.g. through direct interactions with the group of Dan Marcus and Sean Hill, as well as researchers forming part of the Cogitate Consortium (e.g., Christof Koch, Gabriel Kreiman, Ole Jensen, Sylvain Baillet among many others) is possible. The position *will begin earliest on December 1, 2021* and is initially limited to two years, with the possibility of an extension pending funding approval. Salary is paid in accordance with the collective agreement for the public sector (TVöD Bund), according to your qualifications and experience. The Max Planck Society strives for gender equality and diversity. We are also committed to increasing the number of individuals with disabilities in our workforce. Therefore, applicants of all backgrounds are welcome. Your application should include: your detailed CV (including details of your educational background and skills); a cover letter that explains why this position interests you and how your skills and abilities are suitable; copies of relevant degrees and/or certificates. Please send these materials all together in a single PDF file, *before November 1, 2021*, by e-mail to job(a)ae.mpg.de using the code *“TWCF Engineer”* in the subject. Please feel free to contact job(a)ae.mpg.de or Tanya Brown < tanya.brown(a)ae.mpg.de <tanya.brown(a)ae.mpg.de?subject=TWCF%20Engineer>> if you have any questions about the position.

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PhD position in Numerical and Computational Analysis for Mathematical Neuroscience
by Avitabile, D. Sept. 27, 2021

Sept. 27, 2021

Below you can find the details of a PhD position at Radboud University (The Netherlands) on Numerical and Computational Analysis for Mathematical Neuroscience, under the supervision of Prof. Gabriel Lord. The deadline for applications is the 29th of October 2021. https://www.ru.nl/english/working-at/vacature/details-vacature/?recid=11705… Daniele Avitabile Associate Professor in Applied Mathematics Vrije Universiteit Amsterdam www.danieleavitabile.com

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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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