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Grandmother cells a failed concept? Or is Barlow right that grandmother cells exist and “can now be recorded from and studied reliably?"

by Asim Roy

Ann-Sophie Barwich recently published an article in Frontiers in Neuroscience titled “The Value of Failure in Science: The Story of Grandmother Cells in Neuroscience” (https://www.frontiersin.org/articles/10.3389/fnins.2019.01121/full) where she argues for the need for failure analysis in science and, in the context of neuroscience, analyzed the grandmother cell concept as a failed one. Although I was one of the reviewers who endorsed the article for publication (publication of alternative viewpoints is essential in science), I felt that Barwich’s arguments against grandmother cells were deeply flawed. I point out these flaws in a Commentary in Frontiers in Neuroscience: “Commentary: The Value of Failure in Science: The Story of Grandmother Cells in Neuroscience:” https://www.frontiersin.org/articles/10.3389/fnins.2020.00059/full I think Reddy and Thorpe’s 2014 article clears the confusion about concept cells. With Reddy and Thorpe’s characterization of concept cells, one would find no difference between concept cells and grandmother cells. And that’s essentially what I have done in the Commentary – show that concept cells and grandmother cells have identical properties. I also point out in the Commentary that it’s a false claim by Barwich (and in other prior articles that Barwich references) that concept cells can be part of a sparse population coding scheme. Given that concept cells have “meaning” on a stand-alone basis, they can’t be part of any population coding scheme. And it’s also a false claim in Barwich that grandmother cells do not use associative learning, because grandmother cells have always been characterized as “multimodal” going all the way back to Gross (2002). In addition, the neurophysiological evidence on multisensory neurons clearly point to a single-cell based abstract cognitive system in the brain, as claimed by Roy (2017). Overall, concept cell findings confirm the prediction of Barlow (2009)<https://www.frontiersin.org/articles/10.3389/fnins.2020.00059/full#B1> that grandmother cells exist and “can now be recorded from and studied reliably.” YOU CAN EMAIL ME IF YOU WANT TO JOIN A DISCUSSION GROUP ON THIS TOPIC. Barlow, H. B. (2009). “Grandmother cells, symmetry, and invariance: how the term arose and what the facts suggest,” in The Cognitive Neurosciences, 4th Edn., ed M. Gazzaniga (Cambridge, MA: MIT Press), 309–320. Reddy, L., and Thorpe, S. J. (2014). Concept cells through associative learning of high-level representations. Neuron 84, 248–251. doi: 10.1016/j.neuron.2014.10.004 Roy, A. (2017). The theory of localist representation and of a purely abstract cognitive system: the evidence from cortical columns, category cells, and multisensory neurons. Front. Psychol. 8:186. doi: 10.3389/fpsyg.2017.00186

Feb. 16, 2020

job post: machine learning research scientist at NIMH

by Francisco Pereira

*** HIRING: machine learning research scientist The Machine Learning Team at the National Institute of Mental Health (NIMH) in Bethesda, MD, has an open position for a machine learning research scientist. The NIMH is the lead federal agency for research on mental disorders and neuroscience, and part of the National Institutes of Health (NIH). *** About the NIMH Machine Learning Team Our mission is to help NIMH scientists use machine learning methods to address a diverse set of research problems in clinical and cognitive psychology and neuroscience. These range from identifying biomarkers for aiding diagnoses to creating and testing models of mental processes in healthy subjects. We work with many different data types, including very large brain imaging datasets from various imaging modalities, behavioral data, and picture and text corpora. We have excellent computational resources, both of our own (tens of GPUs for deep learning) and shared within the NIH (a cluster with hundreds of thousands of CPUs, and hundreds of GPUs). As a machine learning research group, we develop new methods and publish in the main machine learning conferences (e.g. NeurIPS and ICLR), as well as in psychology and neuroscience journals. Many of our problems require devising research approaches that combine imaging and non-imaging data, and leveraging structured knowledge resources (databases, scientific literature, etc) to generate explanations and hypotheses. You can find more about our work and publications at https://cmn.nimh.nih.gov/mlt *** About the position We are seeking candidates who are capable of combining machine learning, statistical, and domain-specific computational tools to solve practical data analysis challenges (e.g. designing experiments, generating and testing statistical hypotheses, training and interpreting predictive models, and developing novel models and methods). Additionally, candidates should be capable of visualizing and communicating findings to a broad scientific audience, as well as explaining the details of relevant methods to researchers in a variety of domains. Desirable experience that is not required, but will be considered very favorably: - neuroimaging data processing and analysis (any MRI modality, as well as MEG/EEG) - Bayesian statistical modelling - natural language processing / structured data such as EHR or questionnaires Finally, you should have demonstrable experience coding in languages currently used in data-intensive, scientific computing, such as Python, MATLAB or R. This is an ideal position for someone who wants to establish a research career in method development and applications driven by scientific and clinical needs. Given our access to a variety of collaborators and large or unique datasets, there is ample opportunity to match research interests with novel research problems. We also maintain collaborations outside of the NIH, driven by our own research interests. If you would like to be considered for this position, please send francisco.pereira(a)nih.gov a CV, with your email serving as cover letter. If you already have a research statement, please feel free to send that as well. There is no need for reference letters at this stage. Other inquiries are also welcome. Thank you for your attention and interest!

Feb. 15, 2020

Call for Applications: EADM Summer School on Learning and Decision Making

by Hrvoje Stojic

APPLICATIONS ARE NOW OPEN (until 15 March 2020)! Dates: 8-15 July, 2020 Location: Universitat Pompeu Fabra, Barcelona, Spain Topic: Learning and Decision Making Eligibility to Apply: Early career researchers Further details available at: https://ldmss.org APPLICATION INSTRUCTIONS: https://ldmss.org#apply The 5th EADM Learning and Decision Making summer school will take place from the 8th to the 15th of July in Barcelona, Spain. It will cover a wide range of topics related to learning and decision making, including reinforcement learning, sampling biases, decisions from experience, function learning, category learning and social learning. Participants will receive advanced training and hands-on tutoring on various computational modeling approaches in learning and decision making from experts in the field and will get feedback on their latest research ideas in poster sessions. The program will also include social and group activities in the beautiful city of Barcelona. Confirmed faculty include: Mirta Galesic (Santa Fe Institute) Maarten Speekenbrink (University College London) Johannes Müller-Trede (IESE Business School) Henrik Olsson (Santa Fe Institute) G. Elliot Wimmer (University College London) Mehdi Keramati (City University) Jörg Rieskamp (University of Basel) Elizaveta Konovalova (Max Planck Institute for Human Development) Cecília Nunes (Universitat Pompeu Fabra) More coming soon! The organization team: Gael Le Mens (Universitat Pompeu Fabra) Emmanouil Konstantinidis (University of Warwick) Hrvoje Stojic (University College London) Pantelis P. Analytis (University of Southern Denmark) Mikhail Spektor (Universitat Pompeu Fabra) Feel free to send us any questions at: ldmss(a)protonmail.com or on Twitter @ldmsschool. ----------------------------- Hrvoje Stojic, PhD Postdoctoral researcher University College London Website: [https://hstojic.re/](http://hstojic.re/)

Feb. 15, 2020

[ICDL-2020] Call for Tutorials

by Miguel Solís

Apologies if you receive multiple copies of this call due to cross-posting, please help to distribute among possible interested contributors. CALL FOR TUTORIALS: 10th IEEE International Conference on Development and Learning (ICDL) 7th-10th September 2020, Valparaiso, Chile Web page: https://cdstc.gitlab.io/icdl-2020/ An IEEE Computational Society-sponsored conference ==== Important Dates ==== Tutorial Proposals Open: 15th February 2020 Tutorial Proposals Deadline: 30h April 2020 Tutorial Proposals Notification: 15th May 2020 ==== Overview ==== We invite experts in different areas to organize a tutorial. The goal of tutorials is to provide insights into specific topics through hands-on training and interactive experiences or in-depth state of the art review. Tutorial organizers have several responsibilities, including activities scheduling, publicizing and providing the content on time. ICDL will support the organization with rooms, audio-visual equipment and coffee breaks. ==== Scope and Topics ==== The main list of topics of interest includes, but not limited to: - principles and theories of development and learning; - development of skills in biological systems and robots; - nature vs nurture, developmental stages; - models on the contributions of interaction to learning; - verbal, non-verbal and multi-modal interaction; - models on active learning; - architectures for lifelong learning; - emergence of body and affordance perception; - analysis and modelling of human motion and state; - models for prediction, planning and problem solving; - models of human-human and human-robot interaction; - emergence of verbal and non-verbal communication; - epistemological foundations and philosophical issues; - robot prototyping of human and animal skills; - ethics and trust in computational intelligence and robotics; - social learning in humans, animals, and robots. ==== Submission format ==== Proposals should be maximum of two pages long following the standard IEEE conference style. Proposals should be submitted in PDF format by email to icdl2020(a)ac3e.cl with subject “[Tutorials]”. Proposals should specify the following: Title Organizers Duration (half-day or full-day) A brief description of the topics to be covered Tentative program Target audience and interested groups Website Any logistic requirements such as poster stands, computers, projector, etc. For more information about the conference, travel grants, social events, etc. visit the conference webpage under https://cdstc.gitlab.io/icdl-2020/ ==== Organizing committee ==== General Chairs: Giulio Sandini, and Javier Ruiz-del-Solar Program and Finance Chairs: Nicolás Navarro-Guerrero, and María-José Escobar Bridge Chairs: Minoru Asada, Frédéric Alexandre, and Linda Smith Publicity Chairs: Carmelo Bastos, Maya Cakmak, Angelo Cangelosi, Yukie Nagai, and Emre Ugur Publication Chairs: Pablo Barros, and Haian Wu Tutorials and Workshops Chair: Miguel Solis Travel and Registration Awards Chair: Francisco Cruz Local chairs: Mauricio Araya Webpage Chairs: Cristóbal Nettle, and Patricio Castillo Graphics: Camila Angel Alfaro Best regards from the organizing committee,

Feb. 14, 2020

Postdoctoral fellow for an international collaboration

by Lucia Melloni

Dear all, There is an exciting opportunity for a 2-3 years senior post-doctoral research position to work with Michael Pitts at Reed College, Portland Oregon, USA (https://www.reed.edu/psychology/scalp/) and Liad Mudrik at Tel Aviv University, Tel Aviv, Israel (http://www.mudriklab.tau.ac.il) (location flexible in one of the two labs). Project: International adversarial collaboration <https://science.sciencemag.org/content/366/6463/293?utm_campaign=toc_sci-ma…> on the neural basis of visual consciousness, aimed at testing key predictions of integrated information theory and global neuronal workspace theory. Collaborators include: Lucia Melloni, Stanislas Dehaene, Giulio Tononi, Christof Koch, David Chalmers, Hal Blumenfeld, Floris de Lange, Ole Jensen, Gabriel Kreiman, Huan Luo, Francis Fallon, and others. Required skills: • expertise in advanced data analysis for as many of the following techniques as possible:EEG/MEG, fMRI, ECoG • experience and interest in managing large datasets • experience and interest in cloud-based or local-cluster-based computing • interest and ability to work on team-based projects Start date: Flexible between June and October 2020 To apply: send an email including your CV, research statement, and cover letter to mudrikli(a)tauex.tau.ac.il and mpitts(a)reed.edu by March 30th, 2020

Feb. 14, 2020

PhD Position in Computational Neuroscience, University of Edinburgh

by Chadwick, Angus

Applications are invited for a fully-funded PhD studentship in Computational Neuroscience with Dr. Angus Chadwick at the Institute for Adaptive and Neural Computation in the School of Informatics, University of Edinburgh, commencing September 2020 or later. Exceptional applicants interested in a September 2021 start may also apply. Students should hold, or be close to completion of, an undergraduate or masters degree in physics, mathematics, computer science, engineering, or similar, and be interested in applying their analytical skills to tackle problems in neuroscience. Highly motivated students with other backgrounds may also be considered. The newly-formed Chadwick group focuses on the dynamics of neural populations underlying visual perception and spatial navigation. We use a combination of approaches, including 1) top-down modelling of neural circuit function guided by machine learning and artificial intelligence solutions 2) bottom-up analysis and simulation of neuronal network dynamics, and 3) statistical modelling of large-scale neural recordings. Our long-term goal is to develop a unified theory of the neural circuit computations supporting visual and spatial processing which spans these levels of analysis. We collaborate closely with a number of experimental neuroscience laboratories both in Edinburgh and further afield. Edinburgh is a vibrant and international city with a large student population, and has been voted as “best place to live in Britain”. The School of Informatics maintains an internationally-leading research environment in Computational Neuroscience, Machine Learning and Robotics, with close links to the Centre for Discovery Brain Sciences and the School of Philosophy, Psychology and Language Sciences. Applicants should email Dr. Angus Chadwick directly at angus.chadwick(a)ucl.ac.uk with their CV and a brief statement of interest, or for informal enquiries and discussion. Applications will be considered until the position is filled.

Feb. 12, 2020

International Brain Lab now hiring data scientists!

by Hannah M Bayer

The International Brain Laboratory (https://www.internationalbrainlab.com/) is seeking 3 data scientists, who will play key roles in a large-scale international collaboration in brain research. The International Brain Lab combines the efforts of approximately 50 scientists in 20 laboratories toward understanding the brain-wide basis of a complex behavior. The project will involve recording the activity of millions of neurons in the working brain and building mathematical models of the resulting data. The data sets this project will produce are vast and complex, including physiological recordings, behavioural measurements, and video, all of which must be standardized into common formats, integrated into a single database, and subjected to quality control. These core positions will support both experimental and theoretical work through the entire lifecycle of data, including acquisition, analysis, modeling and dissemination. For more details about the positions, please check out: https://bit.ly/2OLwWwq or https://www.internationalbrainlab.com/opportunities Please address all inquiries about these positions to info+careers(a)internationalbrainlab.org

Feb. 11, 2020

Vacancy project assistent

by Pieter Roelfsema

We have an exciting opportunity for a Project assistant (0,5 fte) for the INTENSE consortium. The consortium develops new implantable devices for the nervous system to increase the quality of life of people that are blind, deaf, paralyzed or suffer from epilepsy. The consortium consists of neuroscientists, technologists, medical doctors, patient societies and companies. The project will not only lead to new fundamental insights and solutions for unmet patient needs, but also to new products and entrepreneurship. Job description You will coordinate all INTENSE related activities. You will interact with the chairman of the consortium (Pieter Roelfsema) on a daily basis to discuss managerial and administrative issues. Besides the daily management and the planning of meetings, you will organize meetings of committees within the consortium and ensure timely reporting of the subprojects. Furthermore, you will establish and maintain relationships with stakeholders including patient groups and industry partners. We expect from you: We will consider highly motivated, self-driven candidates with a degree in neuroscience, (neuro)psychology, biomedical sciences, natural sciences, material science, mathematics, physics, etc. A high level of written and spoken English is required. The ideal candidate will have managerial experience, an understanding of neuroscience and entrepreneurship. You should expect from us: • An exciting research project • Mentoring, supervision and training • Flexible working hours • A stimulating international research environment Environment The partners of INTENSE include the country’s leading fundamental neuroscience research institutes and technical universities. You will be based at the Netherlands Institute for Neuroscience (http://www.nin.nl) in Amsterdam where English is the working language. Appointment We offer an exciting job at a dynamic research institute and an attractive package of fringe benefits. The first appointment is for one year with an extension pending on an evaluation. Salary The salary will be commensurate with experience and institutional guidelines based on the Collective Labour Agreement for Dutch Universities; CAO NU, scale 7-9). The starting salary depends on experience and ranges from € 2.452,- to € 4.274,- before taxes. A 8% holiday allowance and 8.3% year-end bonus are excluded. We offer travel expenses, paid parental leave, flexible working hours and 30 days paid leave per year by fulltime employment. Starting date The starting date is between May and September 2020. To apply Please, send your application to l.van.der.vecht(a)nin.knaw.nl including: 1. A Curriculum Vitae 2. An application letter 3. Two reference letters Applications should be submitted before March 7th 2020. All qualified applicants will receive consideration for employment without regard to race, religion, sexual orientation, nationality, disability, etc. Any acquisition further to this advertisement will not be appreciated.

Feb. 11, 2020

[Call for Participation] First Latin American Summer School on Cognitive Robotics

by Nicolás Navarro-Guerrero

https://www.lacoro.org We are excited to announce our first Latin American Summer School on Cognitive Robotics (LACORO), which aims at making cutting-edge knowledge on Artificial Intelligence for Robotics Applications accessible to everyone, especially in the Southern Hemisphere. Our aims are: - to build a sustainable community of students and researchers in the area of Artificial Intelligence for Robotics, particularly Cognitive Inspired Aspects of AI. - to make cutting-edge scientific topics accessible to everyone. - to overcome the complexity of a multi-cultural and interdisciplinary learning context. **Applications period is now open** Format: We will organize the Summer School in Latin America biennially. LACORO will include cutting-edge lectures and tutorials on Artificial Intelligence and Robotics but also aspects of Human Cognition. Moreover, we will host a hackathon where attendees can acquire hands-on experience on some of the topics of the Summer School. Date and Location: September 3rd to September 5th, 2020 at the Universidad Técnica Federico Santa María, Valparaíso, Chile. Applications: Please visit our website, where you can find more information regarding costs, travel, lodging, along with an application form. Pre-registration is required because there will be a limited number of participants. If you have any questions about the school or the application process, please contact the organizing committee: lacoro(a)innovacionyrobotica.com Best regards from the organizing committee, -- Nicolás Navarro-Guerrero Assistant Professor Department of Engineering, and School of Culture and Society Aarhus University, Denmark E-mail: nng(a)eng.au.dk https://nicolas-navarro-guerrero.github.io/ Aarhus University Finlandsgade 22, building 5125 8200 Aarhus N Denmark Tel.: +45 8715 0000 eng(a)au.dk www.eng.au.dk/en/

Feb. 11, 2020

NSF Neuronex Big Brain Imaging Workshop @ Boston University - April 15-16, 2020

by Chen, Jerry

We are proud to announce the 2020 Big Brain Imaging Workshop hosted jointly by the NSF NeuroNex Nemonic Hub as well as the Boston University Neurophotonics Center! This two-day workshop will take place on Wednesday, April 15th and continue on Thursday, April 16th, 2020 at the Boston University Photonics Center, 8 Saint Mary's Street, Room 906, Boston, MA 02215. The 2020 Big Brain Imaging Workshop is an opportunity to join in the discussion on optical approaches for cellular resolution imaging of neuronal populations that have been highly instrumental for uncovering the principles of neural circuit function. To date, the microscope technology development for imaging the nervous system has largely been focused on applications on a subset of model species with smaller, optically accessible brains (ex. c. elegans, zebrafish, mice). The ability to translate these technologies to species with brains that are both physically larger and less optically accessible remains a challenge. The topic of the workshop is focused on advancing cellular resolution brain imaging techniques in "larger" brains of mammalian species (ex. rats, cats, ferrets, marmosets, macaques). The goal is to bring neuroscientists and optical engineers together to discuss challenges and come up with potential solutions that will pave the way for the next generation of microscopes that can be applied to a greater number of model organisms. Invited Speakers Daniel Aharoni - University of California, Los Angeles Michele Basso - University of California, Los Angeles Adam Charles - Johns Hopkins University Anna Devor - Boston University David Fitzpatrick - Max Planck Institute Florida Emily Gibson - University of Colorado Anschutz Prakash Kara - University of Minnesota Jerome Mertz - Boston University Kristina Nielsen - Johns Hopkins University Anitha Pasupathy - University of Washington Bijan Perasan - New York University Eyal Seidemann - University of Texas, Austin Lei Tian - Boston University Alipasha Vaziri - Rockefeller University Chris Xu - Cornell University In addition to the invited speakers, spots are available for short talks by visiting the registration page and submitting a brief abstract: For more information and free registration, visit: https://nemonic.ece.ucsb.edu/index.php/Big_Brain Jerry Chen, PhD Assistant Professor Department of Biology Boston University www.chen-lab.org<http://www.chen-lab.org> jerry(a)chen-lab.org

Feb. 10, 2020