August 2020 - Comp-neuro - lists.cnsorg.org

NeuTouch Summer School

by Miguel Casal Santiago

The Horizon 2020 project Neutouch is glad to announce that the first summer school of the project about “Touch for prosthetics” will be held online the 21 & 28 September and 5 & 12 October 2020. The school will have talks from cutting-edge professors and students in the field of touch, including topics such as neuromorphic engineering, brain-computer interfaces, computational neuroscience and machine learning, among others. We invite you to take a look at the program together with a small description of the talks in this link <https://www.neutouch.eu/events/neuschool20>, where you can also subscribe for free. You can contact neutouchboard(a)gmail.com <mailto:neutouchboard@gmail.com> for doubts and requests Neutouch Editorial Board

Aug. 31, 2020

Postdoc positions in Aarhus University, Denmark

by Diego Vidaurre

Dear all, Funded by an ERC grant, I am opening two postdoc positions in my lab in Aarhus University in collaboration with Oxford University, to develop new methods on machine learning and Bayesian time series modelling, with application to specific problems in computational neuroscience. If someone is interested, or know of someone interested, please get in contact. More details on the topics, salary, conditions, requirements, etc. here: https://health.au.dk/en/about-health/vacant-positions/job/postdoc-in-integr… Thanks Diego Vidaurre

Aug. 30, 2020

Postdoc in computational cognitive neuroscience of speech processing at the University of Texas at Austin (USA)

by Hamilton, Liberty

The Hamilton Lab at The University of Texas at Austin seeks to hire a full-time postdoctoral fellow to study brain processing of natural speech in the presence of noise. Our approaches include computational methods (neural networks, linear/nonlinear regression models, encoding/decoding), electrophysiology (scalp EEG and intracranial EEG), and fMRI. A postdoc is sought for a one-year contract to begin a collaborative project with the Huth Lab on brain processing of natural sounds using scalp EEG and fMRI. Lab websites: https://slhs.utexas.edu/research/hamilton-lab and https://cs.utexas.edu/~huth/ Start date: Open Full time, benefits eligible, one-year contract with potential for extension based on performance/funding. Qualifications: The ideal candidate will have a strong quantitative background (time series analysis, regression models) and ability to code in python or MATLAB (though python will be used for most projects). All candidates must hold a PhD by the time of appointment. Preferred Qualifications: Previous experience in scalp EEG and/or fMRI strongly preferred, though related work in other electrophysiology methods will also be considered. A PhD in neuroscience, computer science, cognitive science, psychology, bioengineering, communication disorders, or other related fields is suggested. The Hamilton Lab is located in the Department of Speech, Language, and Hearing Sciences and is jointly affiliated with the Department of Neurology at Dell Medical School. The Huth Lab is located in the Departments of Neuroscience and Computer Science. The Hamilton and Huth labs are committed to fostering a supportive and diverse environment. We are strongly committed to mentoring our students and postdoctoral scholars to reach their goals. Our groups work as a multidisciplinary team, where each member’s contribution is valued. Our lab members come from a wide variety of fields including speech/language/hearing science, neuroscience, linguistics, music, physics, computer science, and psychology. The candidate is expected to work collaboratively with graduate students and research assistants in these fields. Apply at: https://utaustin.wd1.myworkdayjobs.com/UTstaff/job/UT-MAIN-CAMPUS/Postdocto…

Aug. 28, 2020

Professor position in Goettingen, Germany

by Rizzoli, Silvio

Dear colleagues, I hope this email finds you well. My institute at the University Medical Center Goettingen, Germany, the Institute for Neuro- and Sensory Physiology, currently has an announcement for a W2 professorship position in the field of computational modeling of synaptic physiology. Our institute produces substantial quantitative data on synapses, from fluorescence imaging to biochemistry, mass spectrometry and electron microscopy (see for example Wilhelm et al., Science, 2014). We are looking for an investigator with substantial expertise in computational aspects, who would benefit from these data, and would be able to use them for important studies. This professorship will be integrated in an excellent neuroscience campus, and will benefit strongly from our collaborative research center CRC/SFB 1286, dedicated to Quantitative Synaptology (composed of more than 20 collaborating laboratories, from many excellent institutions). Our announcement can be found at: <https://jobs.zeit.de/jobs/universitaetsprofessur-w2-modellierung-synaptisch…>https://www.academics.com/jobs/university-professorship-w2-modeling-synapti… It would be great if you could also send this announcement to colleagues in your department, who may be interested in applying for this position. Best wishes, and thank you in advance, Silvio Rizzoli Prof. Dr. Silvio O. Rizzoli UNIVERSITÄTSMEDIZIN GÖTTINGEN GEORG-AUGUST-UNIVERSITÄT Direktor des Instituts für Neuro- und Sinnesphysiologie Zentrum Physiologie und Pathophysiologie Humboldtallee 23, 37073 Göttingen Telefon: 0551-39-5911 FAX: 0551-39–66031 E-Mail: srizzol(a)gwdg.de Sprecher des Centers Biostructural Imaging of Neurodegeneration (BIN) von-Siebold-Straße 3a, 37075 Göttingen Sprecher des Sonderforschungsbereichs 1286 Quantitative Synaptologie (Collaborative Research Center 1286 Quantitative Synaptology)

Aug. 26, 2020

Professorship in computational modeling of synaptic physiology at the University Medical Center Göttingen, Germany

by Erik De Schutter

The University Medical Center Göttingen, Germany has announced a W2 professorship position in the field of computational modeling of synaptic physiology. The institute produces substantial quantitative data on synapses, from fluorescence imaging to biochemistry, mass spectrometry and electron microscopy. They are looking for an investigator with substantial expertise in computational aspects, who would benefit from these data, and would be able to use them for important studies. This professorship will be integrated in an excellent neuroscience campus, and will benefit strongly from our collaborative research center CRC/SFB 1286, dedicated to Quantitative Synaptology (composed of more than 20 collaborating laboratories, from many excellent institutions). The announcement can be found at: https://www.academics.com/jobs/university-professorship-w2-modeling-synapti…

Aug. 26, 2020

SMILES virtual workshop @ICDL 2020

by Xavier Hinaut

The SMILES (Sensorimotor Interaction, Language and Embodiment of Symbols) Workshop will take place virtually at the ICDL 2020 (International Conference on Developmental Learning). * Call for abstracts and papers: - Deadline: 25th of September 2020 - papers abstracts: 2 pages - long papers: 4-6 pages - Submissions: smiles.conf(a)gmail.com <mailto:smiles.conf@gmail.com> - Papers format: same as ICDL conference https://cis.ieee.org/publications/t-cognitive-and-developmental-systems/tcd… <https://cis.ieee.org/publications/t-cognitive-and-developmental-systems/tcd…> - Workshop dates (coming soon): the days before or after the ICDL conference (26-30 October 2020) * Workshop Short Description On the one hand, models of sensorimotor interaction are embodied in the environment and in the interaction with other agents. On the other hand, recent Deep Learning development of Natural Language Processing (NLP) models allow to capture increasing language complexity (e.g. compositional representations, word embedding, long term dependencies). However, those NLP models are disembodied in the sense that they are learned from static datasets of text or speech. How can we bridge the gap from low-level sensorimotor interaction to high-level compositional symbolic communication? The SMILES workshop will address this issue through -an interdisciplinary approach involving researchers from (but not limited to): - Sensori-motor learning, - Emergent communication in multi-agent systems, - Chunking of perceptuo-motor gestures (gestures in a general sense: motor, vocal, ...), - Sensori-motor learning, - Symbol grounding and symbol emergence, - Compositional representations for communication and action sequence, - Hierarchical representations of temporal information, - Language processing and acquisition in brains and machines, - Models of animal communication, - Understanding composition and temporal processing in neural network models, and - Enaction, active perception, perception-action loop. * More info - contact: smiles.conf(a)gmail.com <mailto:smiles.conf@gmail.com> - organizers: Xavier Hinaut, Clement Moulin-Frier, Silvia Pagliarini, Joni Zhong, Loo CHU KIONG, Michael Spranger, Tadahiro Taniguchi - invited speakers (coming soon) - workshop website (comming soon): https://sites.google.com/view/smiles-workshop/ <https://sites.google.com/view/smiles-workshop/> - ICDL conference website: https://cdstc.gitlab.io/icdl-2020/ <https://cdstc.gitlab.io/icdl-2020/> * Workshop Long Description Recently Deep Learning networks have broken many benchmarks in Natural Language Processing (NLP), e.g. [1]. Such breakthroughs are realized by a few mechanisms (e.g. continuous representations like word embedding, attention mechanism, ...). However, no equivalent finding happened towards the understanding of which mechanisms enable the brain to perform similar functions. Deep Learning does not reproduce learning mechanisms nor the dynamics of the brain. The brain needs to parse incoming stimuli and learn from them incrementally, it cannot unfold time like deep learning algorithms such as Back-propagation through time (BPTT). Thus, we still lack the key neuronal mechanisms needed to properly model the (hierarchies of) functions in language perception and production. Other models of language processing reproducing the behavior of brain dynamics (Event-Related-Potentials (ERPs) [2] or functional Magnetic Resonance Imaging (fMRI) [3]) have been developed. However, such model softens lack explanatory power demonstrating the causes of such observed dynamics: i.e. what is computed and why is it computed – for which purpose? We need more biologically plausible learning mechanisms while producing causal explanations of the experimental data modelled. There is converging evidence that language production and comprehension are not separated processes in a modular mind, they are rather interwoven, and this interweaving is what enables people to predict themselves and each other [4].Interweaving of action and perception is important because it allows a learning agent (or a baby) to learn from its own actions: for instance, by learning the perceptual consequences(e.g. the heard sounds) of its own actions (e.g. vocal productions) during babbling [5]. Thus, the agent learns in a self-supervised way instead of relying only on supervised learning, which in contrast, imply non-biological teacher signals cleverly designed by the modeler. Explicit neuronal models explaining which are the mechanisms shaping these perceptuo-motor units through development are missing. The existence of sensorimotor (i.e. mirror) neurons at abstract representation levels (often called action-perception circuits [6]), jointly with the perceptuo-motor shaping of sensorimotor gestures [5], suggest the existence of similar action-perception mechanisms implemented at different levels of hierarchy. How could we go towards such hierarchical architectures based on action-perception mechanisms? Importantly, a language processing model needs a way to acquire the semantics of the (symbolic) perceptuo-motor gestures and of the more abstract representations, otherwise it would consider only morphosyntactic and prosodic featuresof language. These symbolic gestures, i.e. signs, need to be grounded to the mental concept, i.e. signified, they are representing. Several theories and robotic experiments give examples of how symbols could be grounded or how symbols could emerge [7]. However, current neurocomputational models aiming to explain brain processes are not grounded. Robotics have an important role here for the grounding of semantics by experiencing the world through interactions with the physical world and with humans. We need mechanisms that start from raw sensory perception and raw motor commands in order to let emerge plausible representations through development, instead of arbitrary representations. Finally, computational models of emergent communication in agent populations are currently gaining interest in the machine learning community [8], [9]. These contributions show how a communication system can emerge to solve cooperative tasks in sequential environments. However, they are still relatively disconnected from the earlier theoretical and computational literature aiming at understanding how language might have emerged from a prelinguistic substance [10], [11]. We need to conceive communication as the emergent result of a collective behavior optimization process and to ground the resulting computational models into the theoretical literature from language evolution research. The SMILES workshop will aim at discussing each of the questions mentioned above, together with original approaches on how to integrate them. [1] J. Devlin et al., 2018. [2] H. Brouwer and J. C. J. Hoeks, 2013. [3] M. Garagnani et al. 2008. [4] M. J. Pickering and S. Garrod, 2013. [5] J.-L. Schwartz et al., 2012. [6] F. Pulvermüller and L. Fadiga, 2010. [7] T. Taniguchi et al., 2016. [8] S. Sukhbaatar et al.,2016. [9] I. Mordatch and P. Abbeel, 2017. [10] M. Tomasello et al., 2005. [11] P.-Y. Oudeyer and L. Smith, 2015. Xavier Hinaut Inria Researcher (CR) Mnemosyne team, Inria LaBRI, Université de Bordeaux Institut des Maladies Neurodégénératives +33 5 33 51 48 01 www.xavierhinaut.com

Aug. 21, 2020

Postdoc/PhD/RA positions at ÖAW Acoustics Research Institute, Vienna

by Robert Baumgartner

We are currently looking for enthusiastic researchers at all levels to join an exciting interdisciplinary research consortium addressing „Dynamic Auditory Predictions in Human and Non-human Primates (Dynamates)". It rests on a strong collaboration between cognitive neuroscience, cognitive biology, and computational modeling – for more information, visit our Dynamates website <https://www.kfs.oeaw.ac.at/dynamates>. The following positions are immediately available under my supervision at the Acoustics Research Institute of the Austrian Academy of Sciences: Postdoc <https://www.oeaw.ac.at/fileadmin/subsites/Jobs/ISF083PD220.pdf> focussing on computational models explaining the causal relationship between neural activity (EEG) and perception/behaviour in humans PhD Student <https://www.oeaw.ac.at/fileadmin/subsites/Jobs/ISF082DOC220.pdf> focussing on computational models for comparative behaviour Research Assistant <https://www.oeaw.ac.at/fileadmin/subsites/Jobs/ISF081STUD220.pdf> helping with (mainly EEG) data collection They are open until appropriate candidates are found. The 1st round of evaluation will start on Sept 1, 2020. Feel free to distribute! Best, Robert — Robert Baumgartner, PhD YIRG Leader | Research Associate Acoustics Research Institute Austrian Academy of Sciences Wohllebengasse 12-14, 1040 Vienna, Austria +43 1 51581-2527 Robert.Baumgartner(a)oeaw.ac.at https://www.kfs.oeaw.ac.at/baumgartner Like us on Facebook <https://www.facebook.com/SCHALLFORSCHUNG.OEAW/> Follow us on Twitter/oeaw <https://twitter.com/oeaw?lang=en> Visit us on Youtube <https://www.youtube.com/channel/UCY3rUdfN-VCjvfUWojWkayQ>

Aug. 19, 2020

Phd/Postdoc position for research on interpretable Deep Learning and brain modelling

by Wolfgang Maass

We are looking for a highly talented and motivated Phd student or Postdoc to complement our team in the Faculty for Computer Science and Biomedical Engineering of Graz University of Technology in Austria. The researcher will work on advancing Deep Learning and methods for understanding its outcomes ("interpretable AI") for applications to large data-based cortical microcircuit models, using state-of-the-art supercomputing facilities. The goals are to elucidate the organization of computing and learning in neural networks of the brain, and to develop on this basis spike-based AI methods. The research will be based on recently developed algorithms and TensorFlow software for spiking neural networks, as published for example in G. Bellec, D. Salaj, A. Subramoney, R. Legenstein, and W. Maass. Long short-term memory and learning-to-learn in networks of spiking neurons. 32nd Conference on Neural Information Processing Systems (NIPS 2018), https://igi-web.tugraz.at/PDF/243.pdf G. Bellec, F. Scherr, A. Subramoney, E. Hajek, D. Salaj, R. Legenstein, and W. Maass. A solution to the learning dilemma for recurrent networks of spiking neurons. Nature Communications, 2020. .https://www.nature.com/articles/s41467-020-17236-y.pdf F. Scherr, C. Stoeckl, and W. Maass. One-shot learning with spiking neural networks. bioRxiv, 2020. https://igi-web.tugraz.at/PDF/256.pdf This is a fully funded research position in the Human Brain Project of the EU, which offers an exciting international interdisciplinary research environment. Requirements: --strong mathematical background and analytical skills --deep interest in understanding the function of neural networks in the brain --excellent programming skills --very good knowledge in Machine Learning Please send your CV, grades, motivation letter, and links to pdf of your master thesis and other relevant preceding work to charlotte.rumpf(a)tugraz.at -- Prof. Dr. Wolfgang Maass Institut fuer Grundlagen der Informationsverarbeitung Technische Universitaet Graz Inffeldgasse 16b , A-8010 Graz, Austria Tel.: ++43/316/873-5822 Fax ++43/316/873-5805 http://www.igi.tugraz.at/maass/Welcome.html

Aug. 18, 2020

Neurodata Without Borders (NWB) User Days Workshop - September 21-23

by Ryan Ly

Neurodata Without Borders (NWB) is a data standard for neurophysiology, providing neuroscientists with a common standard to share, archive, use, and build analysis tools for neurophysiology data. NWB is designed to store a variety of neurophysiology data, including data from intracellular and extracellular electrophysiology experiments, data from optical physiology experiments, behavioral data, and stimulus data. The NWB Team will be hosting the 9th NWB User Days Workshop remotely on September 21-23. The workshop schedule will be centered on Central European Time (UTC+2) and will focus primarily on user training, including lessons for complete beginners to NWB. Come learn how to get your data into the NWB data standard and use state-of-the-art data analysis, visualization, and management tools with NWB, e.g., Brainstorm, CaImAn, calciumImagingAnalysis, DANDI, DataJoint, MIES, NWB Explorer, NWB Widgets, SpikeInterface, and suite2p. Event page: https://neurodatawithoutborders.github.io/nwb_hackathons/HCK09_2020_Remote/ Register here: https://bit.ly/2PHbE34 (it's free) Learn more about NWB at our website: https://www.nwb.org/ Best, The NWB Team -- Ryan Ly Scientific Data Engineer Lawrence Berkeley National Laboratory 1 Cyclotron Road Mail Stop 59R4104 Berkeley, CA 94720 Email: rly(a)lbl.gov Pronouns: he/him

Aug. 17, 2020

Neural Data Analysis Online Course

by Maryam

You are invited to “Neural Data Analysis Online Course” Dear Sir, Madam; ScienceBeam, which is a forefront technology provider of neuroscience applications, would like to take the opportunity to invite you for 10-session “Neural Data Analysis Online Course” that is going to start on September 7, 2020. During this course you will learn: ( Programming fundamentals: Variables, plots, loops ( How to compare ERPs in a statistical way: confidence intervals and bootstrapping ( EEG spectrum and spectrogram: from time to frequency and time-frequency ( More on spectrum: windowing and zero padding ( Analysis of coupled rhythms: covariance and coherence ( Filtering, filtering, and filtering! ( Cross-frequency coupling and Hilbert transform ( Brain states in sleep and Hidden Markov Model Hamed Yeganegi, PhD researcher in systems neuroscience, Technical University of Munich, Germany, is the instructor of this course. He is also a member of German Neuroscience Society (NWG) and Member of Federation of European Neuroscience Societies (FENS). Registration is open until September 4th. You won’t want to miss this! Don’t hesitate and register from the link below: Register NOW ! If you needed more information please contact us via Whatsapp or Mail: Whatsapp number: +86 133 8078 1282 Email: workshop(a)sciencebeam.com www.sciencebeam.com

Aug. 17, 2020