- Comp-neuro - lists.cnsorg.org

Open Source Brain workshop 9-11 Sept 2019 & new publication

by Gleeson, Padraig

[Apologies if you receive multiple copies of this due to cross-posting] The 2019 Open Source Brain workshop will be held in Alghero, Sardinia on 9-11th September 2019. Full details: http://www.opensourcebrain.org/docs/Help/Meetings#OSB_2019 Open Source Brain (http://www.opensourcebrain.org) is a platform for sharing and collaboratively developing models in computational neuroscience. Models of cells and circuits in standardised formats can be visualised, analysed and simulated through a standard web browser. A key driver for the development of this technology is to improve accessibility, scientific scrutiny, reproducibility and reuse of models of brain function. The platform is described in a recent paper in Neuron: https://www.cell.com/neuron/fulltext/S0896-6273(19)30444-1 The 2019 OSB Workshop will highlight the latest features of OSB and engage current and future users of the platform through invited talks, posters, hands on demonstrations, and user presentations. Since we are substantially expanding the functionality of Open Source Brain to enable sharing of standardized experimental data used to build and test the models of neurons and circuits, this year’s meeting will have two key themes: 1) Accessible sharing of cellular neuroscience data Through support for the Neurodata Without Borders (NWB) format, OSB will facilitate sharing of multiple types of experimental data used to constrain computational models, including electrophysiological recordings, Ca2+ fluorescence imaging, 2D, 3D and 4D imaging and behavioural data. Challenges, requirements and solutions to data standardization will be discussed. 2) Modelling cortical structures across scales Cortical networks are modelled at many scales from abstract representations of interacting populations (neural masses) to networks of biophysically and morphologically detailed cell models. NeuroML is being expanded to cover a greater range of these models, which will allow them to be shared and simulated on OSB, facilitating comparison of models and ideas between researchers. This ongoing work is taking place as part of the SIG on Standardised Representations of Network Structures<https://www.incf.org/activities/standards-and-best-practices/incf-special-i…>. Registration The registration fee for the meeting for 3 days will be £130. This will help cover organisation and speaker costs, meeting room hire, lunch, tea and coffee for 3 days and one workshop dinner. Please register here<https://onlinestore.ucl.ac.uk/conferences-and-events/faculty-of-life-scienc…>. Registration closes on 1st September 2019. Confirmed speakers Yazan Billeh (Allen Institute, USA) Matteo Cantarelli (MetaCell Ltd) Alex Cayco Gajic (UCL, UK & École Normale Supérieure, France) Sharon Crook (Arizona State University, USA) Jeffrey S. Diamond (NINDS, USA) Matt Earnshaw (University College London, UK) Jan Fousek (Aix Marseille Université, France) Padraig Gleeson (University College London, UK) Boris Marin (Universidade Federal do ABC, Brazil) Diego Restrepo (University of Colorado, USA) Simon Schultz (Imperial College, UK) Angus Silver (University College London, UK) Sacha van Albada (Jülich Research Centre, Germany) For more details please see: http://www.opensourcebrain.org/docs/Help/Meetings#OSB_2019 The OSB 2019 organising committee Padraig Gleeson Matt Earnshaw Angus Silver

July 2, 2019

Academic Fellowship positions Computational Neuroscience, Nottingham

by Mark van Rossum

The University of Nottingham is a research intensive university ranked in the top 10 in the UK and in the top 30 of Europe. It has a strong tradition in Cognition, Perception, Mathematical Biology, and structural and functional Imaging research. To support further development across these areas, and stimulate new research opportunities, the University has recently made a major investment in Computational Neuroscience. As part of this investment we are inviting applications for two independent fellowships. The positions are for 3 years, after which the fellows are expected to be competitive candidates for permanent positions at the University. The positions are ideal for researchers with a strong vision that are planning to develop their own research group in a supportive, interdisciplinary environment with outstanding research facilities. We are interested in candidates working across a broad spectrum of research topics areas in Computational Neuroscience, including functional neuroimaging, neural networks, and models of cognition. Research methodologies could include numerical simulation, machine learning, theoretical neuroscience, and innovative data analysis. The Fellows will be based in the School of Psychology and/or Mathematical Sciences. For more info and the online application form see http://jobs.nottingham.ac.uk/SCI215819 For informal inquiries contact Mark van Rossum, mark.vanrossum(a)nottingham.ac.uk, +44-115-7486851 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.

June 30, 2019

【2019ICCBC】International Collegiate Competition for Brain-inspired Computing

by 郑浩

Dear Collegiates, International Collegiate Competition for Brain-inspired Computing [2019 ICCBC] is an annual academic activity hosted by Tsinghua University to provide a platform for international communication and collaboration on issues of integrating neuroscience and computer science to build intelligent machines and solve real-world issues. This contest is organized by the center for brain-inspired computing research [CBICR] at Tsinghua University. We look forward to talents who have insights into these issues. Final will be held in Oct in Tsinghua University. Prize is BIG! Airfare can be partly covered for finalists! More information can be found bellow and on official website: https://contest.cbicr.org/en/ ICCBC 2019 International Collegiate Competition for Brain-inspired Computing What is contest about？ How computation emerges from the human brain is a fundamental and unsolved mystery for general intelligence and behavior. The combination of neuroscience and computer science is considered as the most promising approach to the development of artificial general intelligence (AGI) - one of the most exciting blueprints of this century. How the computational principles in the brain promote artificial intelligence strategies and how to implement silicon-based brain-inspired systems are the key research topics in brain-inspired computing. In this annual contest, we gather global talents who have unique insights into these issues, or who have creative ideas on applications to solve real-world problems. This contest provides a unique platform for the participants to share their knowledge, discuss the state-of-the-art and examine the future challenges of brain-inspired computing. In addition, participants have the opportunity to win decent prizes. What is the expectation? In this year’s contest, we generalize brain-inspired computing to a broader extent, reflecting the integration of neuroscience and computer science on issues related to general intelligence. Themes include Perception, Cognition, Computation and Decision making. Embodiment can be theories, algorithms, hardware, software, application, etc. Two special topics are setup this year. The Education topic aims to promote a better education system based on our knowledge of brain development and AI strategies. The “Hybrid topic” aims to inspire ideas on hybrid computing models. Since heterogeneity is a common feature of neural system, it is of great importance to intelligent behavior but its implementation is not trivial. Hybrid models that integrate AI and spiking neurons are possible approaches. For more details, please go to https://contest.cbicr.org/en/ Organization and partner Host: Tsinghua University Organizer: Office of Scientific R&D, Tsinghua University Center for Brain-Inspired Computing Research Co-organizers: Tsinghua Holdings, Co., Ltd CETHIK Group Corporation Lynxi Technologies Co., Ltd. Awards | Total award amount | RMB 1,000,000 | | Grand prize | RMB 300,000 for one team | | First prize | RMB 100,000 for two teams | | Second prize | RMB 60,000 for three teams | | Third prize | RMB 30,000 for four teams | | Excellence prize | RMB 20,000 for six teams | | Second prize for the preliminary round | RMB 5,000 for 16 teams | Evaluation In accordance with the principles of fairness, impartiality, and openness, all entries will be evaluated based on the following criteria and weightings: Novelty (25%) Technical advancement and difficulty (20%) Completeness and reproducibility (20%) Live presentation and demonstration (15%) Application value and significance (10%) Formality of document reporting (10%) Time Table | Events | Deadline | Comments | | Online application | 28 July 2019 | Login to the official website https://contest.cbicr.org/ and fill in the registration information. | | Entry submission | 15 Sept. 2019 | Document requirements: slide presentation, technical documentation, source code, videos, application executables, etc. | | Finals | 19-20 October 2019 | 16 teams will advance to the finals. Invited Talks and Poster Session on first day Slide Presentation and Awarding on second day | Past review The contest has cumulatively received applications of 444 teams from 131 different universities. The entries covered a large range of aspects including algorithm, software and hardware. In 2018, the team from the Institute of Automation, Chinese Academy of Sciences won the special award and was awarded 300 thousand RMB in cash. For more details, please refer to the official web “Past review”: https://contest.cbicr.org/en/index.php?id=27 Contact Official website: https://contest.cbicr.org/en/ for more details Tel: (+86) 010-62787245 Email: contest(a)cbicr.org Info about Organizer The Center for Brain Inspired Computing Research (CBICR) was established in September 2014 at Tsinghua University. It is the first research center in China to advance brain-inspired intelligence, covering neural functional, computing theory, neural coding, machine learning algorithms, operational systems, programming software, system integration, architecture design, chip processing, material science and nanotechnology. The center consists of 35 affiliated faculties from seven departments at Tsinghua University, including neuroscience science, electronic engineering, microelectronics, computer science, automation, material science and precision instrument, with the goal of innovations on interdisciplinary research. The center focuses on the development of brain-inspired computing by integrating neuroscience and computer science. -- ICCBC Team

June 30, 2019

[DEADLINE EXTENSION]: The 2nd International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2019): ENTERING THE ERA OF BIG DATA VIA TRANSFER LEARNING AND DATA HARMONIZATION

by MLCN Workshop

Dear Colleagues,The submission deadline for MLCN 2019 workshop as a satellite event of the MICCAI 2019 conference has been extended to 14/07/2019. For more information, please visit https://mlcnws.com/call-for-papers/ . Call for Papers Recent advances in neuroimaging and machine learning provide an exceptional opportunity for investigators and physicians to discover complex relationships between brain, behaviors, and mental and neurological disorders. The MLCN 2019 workshop (https://mlcnws.com) as a satellite event of MICCAI 2019 (https://www.miccai2019.org) aims to bring together researchers in both theory and application from various fields in domains such as *e.g.* machine learning, neuroimaging, predictive clinical neuroscience, *etc.* Topics of interests include, but are not limited to: - Transfer learning in clinical neuroimaging - Model stability in transfer learning - Data prerequisites for successful transfer learning - Domain adaptation in neuroimaging - Data harmonization across sites - Data pooling – practical issues - Cross-domain learning in neuroimaging - Interpretability for transfer learning - Unsupervised methods for domain adaptation - Multi-site data analysis, from preprocessing to modeling - Big data in clinical neuroimaging - Scalable machine learning methods - Benefits, problems, and solutions of working with very large datasets SUBMISSION PROCESS: The workshop seeks high quality, original, and unpublished work on algorithms, theory, and applications of machine learning in clinical neuroimaging related to big data, transfer learning, and data harmonization. Papers should be submitted electronically in Springer Lecture Notes in Computer Science (LCNS) style ( https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…) with up to 8-pages and using the CMT system at https://cmt3.research.microsoft.com/MLCN2019. The MLCN workshop uses a double-blind review process in the evaluation phase, thus authors must ensure anonymous submissions. Accepted papers will be published in a joint proceeding with the MICCAI 2019 conference. IMPORTANT DATES: - Paper submission deadline: July 14, 2019 (23:59 PST) - Notification of Acceptance: August 5, 2019 - Camera-ready Submission: August 12, 2019 - Workshop Date: October 13, 2019 Best regards, MLCN 2019 Organizing Committee <https://mlcnws.com/organization/>, Email: mlcnworkshop(a)gmail.com Website: https://mlcnws.com/ twitter: @MLCNworkshop <https://twitter.com/MLCNworkshop>

June 30, 2019

Neuronal Oscillations Workshop at CNS-2019 - July 17, 2019 - Barcelona + Data Blitz

by Horacio G. Rotstein

Dear All, We would like to call your attention to the CNS-2019 ( https://www.cnsorg.org/cns-2019) workshop on "Neuronal Oscillations: mechanisms, computational properties, and functionality" on July 17, 2019. Please check the information here <http://www.vassiliscutsuridis.org/workshops/CNS2019/CNS2019web.htm> http://www.vassiliscutsuridis.org/workshops/CNS2019/CNS2019web.htm The CNS workshops originated as a spontaneous gathering of CNS participants interested in discussing a specific topic. In order to revive this tradition and give the opportunity to the community to interact, this year we are including a *data blitz* session. CNS participants interested in briefly presenting their work are encouraged to do so. It will be helpful if you contact us in advance to be able to plan. Looking forward to seeing you in Barcelona Horacio -- Horacio, NY/NJ area. Horacio G. Rotstein, PhD (he/him/his) Professor Mathematical Biology & Computational Neuroscience BioDatanamics Lab Federated Department of Biological Sciences Rutgers University / New Jersey Institute of Technology Newark, NJ, 07102, USA. Graduate Faculty Behavioral Neurosciences Program Rutgers University (NWK) tel: (1-973) 596-8460 e-mail: horacio(a)njit.edu horacior(a)andromeda.rutgers.edu <horacio(a)njit.edu> http://web.njit.edu/~horacio

June 29, 2019

Fw: Research Associate Position in Early detection of Alzheimer's

by Dr. Krishna Miyapuram

Applications are invited from interested and motivated candidates for the post of Research Associate in a time-bound research project funded by India-Trento Programme for Advanced Research for a temporary period purely on contractual basis. Principal Investigator Dr. Krishna Prasad Miyapuram. Project Title Early detection of Alzheimer’s using Individualized Brain Atlases and Machine Learning. Name of the Post Research Associate. Salary Rs. 36000/- + HRA (subject to revision as per DST norms). Essential Qualification PhD in Psychology, Cognitive Science, Neuroscience, Computer Science, Electrical Engineering, Biomedical Engineering, or any other related field. Desirable Qualification Previous knowledge of structural and functional MRI, Brain Imaging Techniques, Programming experience in Matlab, Brain connectivity Analysis, Familiarity with Machine Learning techniques. Tenure The appointment will be for One Year duration. How to Apply Interested candidates should apply by sending a CV by e-mail to the PI Dr Krishna Prasad Miyapuram Assistant Professor (HSS & CSE) Indian Institute of Technology – Gandhinagar (email: kprasad(a)iitgn.ac.in) preferably before July 5th, 2019. The applications will remain open until the Position is filled. Selection will be based on the interview (by telephone for outstation candidates). Shortlisted candidates will be intimated well in advance the date and time of the interview. Contact E-mail: kprasad(a)iitgn.ac.in.

June 28, 2019

Two related articles on Efficient Coding in the Brain

by Jeff Krichmar

Dear Colleagues, I don’t usually like to post papers to these lists. But, I thought it was more than just a coincidence that two papers from our group on how the brain efficiently represents information came out today. Hope you enjoy. Feedback is most welcome. "Neural correlates of sparse coding and dimensionality reduction” M Beyeler, EL Rounds, KD Carlson, N Dutt, and JL Krichmar PLoS Computational Biology https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006… "Making BREAD: Biomimetic Strategies for Artificial Intelligence Now and in the Future” JL Krichmar, W Severa, MS Khan, JL Olds Frontiers in Neuroscience - Neuromorphic Engineering Section https://www.frontiersin.org/articles/10.3389/fnins.2019.00666/full 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

June 28, 2019

Modeller's Workshop for the Brain Dynamics Toolbox, 1-19 July 2019.

by Stewart Heitmann

Modeller’s Workshop for the Brain Dynamics Toolbox Online Course July 1-19, 2019 The Brain Dynamics Toolbox is an open toolbox for simulating dynamical systems in neuroscience. This on-line course is for researchers, students and instructors who wish to use the toolbox to build their own dynamical models. Participants learn the art of programming differential equations in Matlab and how to use the toolbox to solve those equations interactively. Topics include programming Ordinary Differential Equations, Partial Differential Equations, Delay Differential Equations, Stochastic Differential Equations, Auxiliary Plot Functions and command-line tools. Example code is provided in all cases. https://bdtoolbox.org/p/modellers-workshop/ Important Dates Early-bird enrolments ($100) close Friday 7th July, 2019. Late enrolments ($150) close Friday 19th July, 2019. Lifetime Access This is a self-paced on-line course. After enrolling, students have unlimited lifetime access to the course materials. Stewart Heitmann | Computational Scientist Victor Chang Cardiac Research Institute | Lowy Packer Building | 405 Liverpool St, Darlinghurst NSW 2010 Australia E: s.heitmann(a)victorchang.edu.au | @VictorChangInst ______________________________________________________________________ The Victor Chang Cardiac Research Institute's Email is scanned by the MessageLabs Email Security System.

June 27, 2019

Postdoctoral position at the University of Pittsburgh

by Anna Manelis

*Postdoctoral Position opening at the University of Pittsburgh in neuroimaging of mood disorders* Candidates are being considered for a post-doctoral associate position in the Anticipation, Cognition and Emotion lab ( www.ace.pitt.edu ) at the University of Pittsburgh (http://www.pitt.edu) to work with Dr. Anna Manelis and her team. A successful candidate will work on the NIMH funded research project that uses multimodal neuroimaging (fMRI, MRI, DTI and fNIRS) to understand the contribution of anticipatory processing to cognitive and emotional dysfunction in individuals with mood disorders. Pittsburgh is a vibrant community which promotes diversity and collaboration within its university and medical systems. Our lab works in conjunction with the University of Pittsburgh Medical Center to perform neuroimaging studies which will help us to better understand mood disorders, including major depressive disorder and bipolar disorders. *Required Qualification*s: we are seeking a highly motivated candidate with a PhD degree (or anticipated PhD degree) in psychology, cognitive neuroscience, computational neuroscience or a related discipline. A strong research background in the analysis and interpretation of neuroimaging data is required. A successful candidate will have excellent writing and communication skills. Candidates with a strong computational background are encouraged to apply. Experience with FSL, Freesurfer and E-prime is preferred. The ability to program in Shell, Matlab, Python and/or R is preferred. Experience with fNIRS, graph modeling and pattern classification analyses is a plus. While prior experience with clinical populations is not necessary, we expect candidates to be interested in neuroimaging research of working and episodic memory and/or anticipatory and emotional processing in individuals with mood disorders. *Responsibilities*: · Help to run fMRI/fNIRS experiments · Analyze fMRI, MRI, DTI and fNIRS neuroimaging data · Write manuscripts · Present findings from studies at conferences This is a full-time position that can be extended to 3 years. We are looking for someone to join our lab in Fall 2019 (with some flexibility). This position is funded by the NIMH and salary will vary based on experience. If you are interested in this position, please send a CV, research statement, preprints/reprints of papers, and the names and contact information for two references to *Anna Manelis (manelisa(a)upmc.edu <manelisa(a)upmc.edu>).*

June 27, 2019

Paper: Forward propagation closed loop learning

by Bernd Porr

Dear all, we have a new paper out where we have propagated errors forwards (and not backwards): "For an autonomous agent, the inputs are the sensory data that inform the agent of the state of the world, and the outputs are their actions, which act on the world and consequently produce new sensory inputs. The agent only knows of its own actions via their effect on future inputs; therefore desired states, and error signals, are most naturally defined in terms of the inputs. Most machine learning algorithms, however, operate in terms of desired outputs. For example, backpropagation takes target output values and propagates the corresponding error backwards through the network in order to change the weights. In closed loop settings, it is far more obvious how to define desired sensory inputs than desired actions, however. To train a deep network using errors defined in the input space would call for an algorithm that can propagate those errors forwards through the network, from input layer to output layer, in much the same way that activations are propagated. In this article, we present a novel learning algorithm which performs such ‘forward-propagation’ of errors. We demonstrate its performance, first in a simple line follower and then in a 1st person shooter game." https://journals.sagepub.com/doi/10.1177/1059712319851070 The PDF of the accepted submission version can be found on my personal homepage: https://www.berndporr.me.uk/Porr_Miller_FCL_2019_Adaptive_Behaviour.pdf https://www.berndporr.me.uk/publications.php The code is available here: https://github.com/glasgowneuro/feedforward_closedloop_learning A video clip of the learning behaviour of a simple FPS agent is here: https://www.youtube.com/watch?v=QLVDBdlAQLY Best, /Bernd Porr & Paul Miller -- www: http://www.tinnitustailor.tech http://www.attys.tech http://www.glasgowneuro.tech http://www.berndporr.me.uk Mobile: +44 (0)7840 340069

June 27, 2019