- Comp-neuro - lists.cnsorg.org

Postdoc position on speech BCI (Univ Grenoble, France)

by Blaise Yvert

Dear Colleagues, I would be very grateful if you could forward this announcement for a postdoc position currently available in my group at the University of Grenoble (France) on the development of a speech BCI (ECoG and Intracortical). More information is available at the following link: https://sites.google.com/view/blaise-yvert/available-positions/postdoc-deco… Thank you very much Kind regards, Blaise. -- Blaise Yvert, PhD. Inserm Research Director Team Neurotechnology and Network Dynamics BrainTech Laboratory U1205 Inserm and Univ Grenoble Alpes UFR Chimie Biologie Bâtiment Biologie B 3e étage 2280 rue de la piscine 38400 Saint Martin d'Hères France Tel (admin). +33 4 56 52 03 73 Tel (direct). +33 4 56 52 03 74 Tel (lab). +33 4 56 52 03 81 Tel (mobile). +33 6 32 88 75 90 https://sites.google.com/view/blaise-yvert/accueil http://www.braincom-project.eu/

Nov. 19, 2019

Modellers Workshop for the Brain Dynamics Toolbox, Final Call.

by Stewart Heitmann

Modeller’s Workshop for the Brain Dynamics Toolbox Online Course Nov 1-22, 2019 Final Announcement. Enrolments close Friday. The Brain Dynamics Toolbox is an open toolbox for simulating dynamical systems in neuroscience. The Modeller’s Workshop is an on-line course is for those 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. Course Website https://bdtoolbox.org/p/modellers-workshop/ Important Dates Enrolments open Friday 1st Nov, 2019. Enrolments close Friday 22nd Nov, 2019. This course will not be offered again until March 2020. ______________________________________________________________________ The Victor Chang Cardiac Research Institute's Email is scanned by the MessageLabs Email Security System.

Nov. 19, 2019

Postdoctoral Position in Systems/Computational Neuroscience, Drexel University

by Liang,Hualou

A postdoctoral fellowship is available to conduct research with Drs. Hualou Liang and Vikas Bhandawat at Drexel University. The position is for a computational neuroscientist. Experience/Interest in performing experiments is a plus but not essential. The research project is aimed at understanding neural control of movement – how descending neurons and thoracic (equivalent to spinal cord) motor circuits, and sensory feedback control the coordination of a fly’s leg and coordination between legs. Because each leg has many degrees of freedom, and there are 6 legs, the movement space is large. We will employ concepts from dynamical systems, statistical methods as well as machine learning/deep learning to discover latent structure from high-dimensional data, to extract movement states, and to understand how these states are regulated by interactions between behavioral demands (carried by descending inputs), current body configuration (computed by thoracic circuits based on past limb positions), and on-going sensory feedback (through proprioceptors and load feedback). The successful candidate will have received a Ph.D. in a relevant discipline with substantial experience in Computational Neuroscience. The position will be largely computational, but there is an opportunity to perform a wide variety of experiments, including, in vivo whole-cell patch clamp, in vivo functional imaging, tethered/free behavioral assays in the Bhandawat lab. The Liang Lab works on problems at the intersection of machine learning and neuroscience, with particular interest in using the tools of artificial intelligence to study brain function and other complex processes. The major thrust of the lab is computational. Our current research uses data science to advance a broad range of topics that include understanding brain function, discovering causal structure from observations, and using deep learning and natural language processing to ease the burden of generic drug review. For current projects, please visit https://liang-lab.org/research/. The Bhandawat lab studies how animal behavior emerges from the complex interaction amongst the animal's nervous systems, their muscle-body dynamics, and their environment. We use fruit flies (Drosophila melanogaster) as our model organism because they perform many complex behaviors with a relatively simple brain, and because of the many genetic tools that are available in the flies. We employ a multi-pronged approach which includes in vivo whole-cell patch clamp recordings, imaging, and quantitative measurement of behavior, biomechanics and computation. For more information on research conducted in the Bhandawat lab, please check our website at http://biomed.drexel.edu/labs/bhandawat/ To be considered for this position please send a CV and a letter describing research interest to Hualou Liang (hualou.liang(a)drexel.edu) and Vikas Bhandawat (vikas.bhandawat(a)drexel.edu) Start date: Immediately Funding mechanism: funded by a NIH grant. Hualou Liang, PhD Professor School of Biomedical Engineering Drexel University 3141 Chestnut Street Philadelphia, PA 19104 Tel: (215) 571-3706 Fax: (215) 895-4983 hualou.liang(a)drexel.edu<mailto:hualou.liang@drexel.edu> https://liang-lab.org/ Mailing address: Monell Building 3508 Market Street Suite 100 Philadelphia, PA 19104

Nov. 18, 2019

postdoc opportunity at NIMH (machine learning approaches in anxiety and depression)

by Francisco Pereira

Dear list, We have a postdoc opportunity in the Section on Development and Affective Neuroscience at NIMH, working with Daniel Pine, David Jangraw, and the NIMH Machine Learning Team. Please see below for full details. Francisco Pereira ## Who we are: Drs. Daniel Pine (https://www.nimh.nih.gov/research/research-conducted-at-nimh/research-areas…) and David Jangraw (https://davidjangraw.wordpress.com) are seeking applicants for a Post-Doctoral Fellowship position that would develop new machine learning-based approaches for the diagnosis and treatment of mental illnesses. Our aims are to better understand the causes and mechanisms of certain psychiatric disorders, improve their definition and classification, and ensure the best treatment can be offered to psychiatric patients. We do this by identifying neuroscience-based phenotypes that map onto clinical phenotypes, and which can be targeted with novel treatments. The position is co-advised by the NIMH Machine Learning Team (https://cmn.nimh.nih.gov/mlt) led by Dr. Francisco Pereira, whose mission is to solve the scientific problems of NIMH researchers by developing new machine learning methods, or developing new analysis approaches relying on existing methods. ## What you will do: One line of research will focus on refining and testing latent constructs derived from multiple brain imaging and behavioral markers of inhibitory control. Inhibitory control deficits are common to many psychiatric disorders, and if the latent construct shows good reliability, it may serve as a target for novel treatments. Another line of research will hinge on extracting characteristics of psychotherapy session data, such as therapist speech and facial expressions, that can predict patient clinical outcomes. While the work will concentrate on anxiety and mood disorders in young people, the approaches will be applicable to any mental disorder. The fellow will work with multi-modal imaging datasets that include MRI (functional, structural), EEG, MEG, and associated behavioral and clinical data, all of which may be used as input to machine learning methods. Data sets are already available, and the fellow will devote most of their time to analyzing these data or developing new methods. The fellow will also have access to excellent computational resources within NIH (e.g., top-100 supercomputer with hundreds of thousands of CPUs and hundreds of GPUs). ## Who you are: Candidates with a strong computational background (e.g., PhD in Engineering, Physics, Computer Science, Mathematics, Statistics, Computational Neuroscience, and related areas) who are interested in brain development and psychopathology are particularly encouraged to apply. Requirements for this position include: - Programming experience in data-intensive computation tasks, in Python (preferably) or in R/Matlab - Practical machine learning experience (e.g., training of classification/regression models, statistical testing of results, interpretation and visualization of models), especially using open source machine learning platforms such as scikit-learn - Excellent interpersonal and written (English) communication skills Experience in psychiatry or knowledge of software for processing neuroimaging data are not required. However, the candidate will be expected to learn some of these topics as part of their role in our research group. ## How to apply: The successful candidate will work jointly with Drs. Daniel Pine, David Jangraw, and Francisco Pereira. Please write to them (pined(a)mail.nih.gov, david.jangraw(a)nih.gov, francisco.pereira(a)nih.gov) with your CV, using the email as the cover letter. Other enquiries are also very welcome. The National Institutes of Health is an equal opportunity employer.

Nov. 17, 2019

PhD grant on spiking networks at Barcelona

by Xavier Otazu

The Neurocomputation and Biological Vision Team (NeuroBiT) (http://www.cvc.uab.es/neurobit) offer a PhD scholarship to work in a highly multidisciplinary project which includes computational modelling of primary visual cortex and psychophysical experimentation of colour perception and its relationship to visual migraines. The Research will take place at the Computer Vision Centre (http://www.cvc.uab.es) of the Univ. Autònoma de Barcelona, which is consistently ranked among the top Spanish Universities (https://www.uab.cat/web/about-the-uab/the-uab/the-uab-in-the-rankings-13456…) The centre is located in a campus outside the vibrant city of Barcelona and has a strong tradition of multidisciplinary research in computational colour vision with their own psychophysical laboratory, living labs facilities and several computer clusters. The candidate will be part of the NeuroComputation and Biological Vision Team (NeuroBiT), a recently-formed multidisciplinary research group which combines perceptual and computational approaches with visual neuroscience. We offer regular meetings with other PhD students, international contacts and the possibility of internship/cooperation with other experimental/theoretical labs. The successful candidate is likely to obtain several high-impact publications. The PhD student research topic will be the development of recurrent multilayer spiking networks to reproduce the biological architecture of the primary visual cortex and several of its physiological properties, aiming at reproducing the results of psychophysical studies in colour perception and clinical studies on migraines. The duration of the position is 3 years (36 months). We expect the position to start before July 1st 2020 (i.e. eventual visa issues should be solved beforehand!). The total annual stipend of the grant is around 15.000 euros gross, which include the cost of registration fees for the official doctorate program. Conditions: The candidate must -hold a European Higher Education Area (EHEA) qualification of at least 300 ECTS credits or a university-awarded Master degree or equivalent in the natural sciences/engineering at the time of signing the contract. - have experience in programming with Python and/or Matlab (C, C++, Unix environment and computer cluster experience are also valued) - have knowledge of / interest in the human visual system, visual perception and statistics - proficiency in English and (desired in) Spanish or Catalan - have excellent skills in analytical thinking, perceptiveness, commitment, self-organization, teamwork, and communication. Any previous experience in the subject of computational modelling will also be a bonus. How to apply: Please send your CV and a short statement (500 words) connecting your previous work with the topics of this grant to xotazu(a)cvc.uab.es and a copy of the official academic transcript (including GPA) before november 25th. We encourage candidates with strong skills in programming who are interested to work in a highly multidisciplinary project and environment (computer science, neuroscience, psychophysics), to apply. Candidates should have a degree in a related subject (Neuroscience, Computer Science, Mathematics, Physics, Biology, etc.). Xavier Otazu Senior Researcher at Computer Vision Center Professor at Computer Science Department, Univ Autonoma de Barcelona

Nov. 16, 2019

PhD Position in Psychology at Ghent University

by Clay Holroyd

PhD Position in Psychology at Ghent University The Learning and Cognitive Control Lab is recruiting a highly motivated PhD student for a 4-year position at the Department of Experimental Psychology, Ghent University (Belgium). The position is funded by a European Research Council Advanced Grant, “Cracking the Anterior Cingulate Cortex Code: Toward a Unified Theory of ACC Function” ( https://cordis.europa.eu/project/rcn/216511/factsheet/en ). Our department provides a vibrant and collaborative research environment that include several groups investigating the cognitive neuroscience of cognitive control and decision making. The available facilities include a research-dedicated 3T Siemens Magnetom Trio MRI scanner, EEG, TMS, eye-tracking, and an MR-compatible EEG system. Our seminar programs enable staff and students to engage with leading researchers from across the world. The successful candidate will conduct functional magnetic resonance imaging experiments following a model-based cognitive neuroscience approach (for an example of our approach, see doi 10.1073/pnas.1803650115 ). There are also opportunities in the department to conduct EEG, pupillometry and TMS experiments. Candidates are expected to have a Master’s degree in psychology, cognitive neuroscience, or a closely related discipline at the time of the starting date. Candidates with prior fMRI training as well as good programming skills (Python, Matlab) would be excellent for this position. The position can start any time between February 1st 2020 and July 1st 2020. The call closes on January 5th 2020. Interested candidates should email their CV, a statement of research interests, and have three letters of reference forwarded to Clay Holroyd at clay.holroyd(a)ugent.be. Inquiries may be directed to him at this email address.

Nov. 16, 2019

MindCORE at the University of Pennsylvania: Postdoctoral Fellowship Opening - Jan 3 deadline

by Calvert, Heather J

MindCORE Postdoctoral Research Fellowship at Penn MindCORE, an interdisciplinary effort to understand human intelligence and behavior at the University of Pennsylvania, seeks to recruit outstanding postdoctoral researchers for our MindCORE Fellowship. Designed for individuals who have recently obtained a PhD degree in psychology, linguistics, neuroscience, philosophy or other cognitive science discipline, the MindCORE Fellowship is a springboard for young researchers as they establish their own research program. The fellowship covers salary and a modest research budget. The most exciting applications often come from candidates who are interested in working collaboratively with multiple faculty members. Applications for 2020 are due January 3rd: https://mindcore.sas.upenn.edu/post-doctoral-research-fellowship/ Heather J. Calvert (she / her) Executive Director, MindCORE Penn's hub for the integrative study of the mind. 112 Leidy Labs, 3740 Hamilton Walk, University of Pennsylvania 215-573-1111 ~ hcalvert(a)sas.upenn.edu https://web.sas.upenn.edu/mindcore/ Follow MindCORE on Twitter & Facebook @PennMindCORE

Nov. 14, 2019

Call for papers for Vision Research special issue on "Calibrating the visual system"

by Ruben Coen-Cagli

**Apologies for cross-posting ** Calibrating the visual system Vision Research seeks contributions for a special issue entitled ‘Calibrating the visual system’. Visual systems evolved according to consistent characteristics of the environment and task demands of the species, but also to be malleable in order to adapt to specific perturbations in the stimulus and the observer. The special issue aims to integrate work on the calibration of visual processes in relation to the stable properties of natural scenes or to variations in the sensory stimulus or the individual’s sensory apparatus, in different visual domains and over different time scales. Of particular interest are processes of short, medium and long-term adaptation, and processes to maintain perceptual constancy, as well as processes that occur during visual development. We are also seeking papers concerned with the benefits, costs, and limitations of these adaptations for optimal encoding of visual information, and for learning and representing relevant stimuli in the environment. We are seeking both original research articles and reviews on this subject, covering diverse methods including psychophysics, physiology, neuroimaging, and computational modelling Guest Editors: Jenny Bosten, University of Sussex Ruben Coen Cagli, Albert Einstein College of Medicine Anna Franklin, University of Sussex Samuel Solomon, UCL Michael Webster, University of Nevada, Reno Submission Deadline: March 2020 Manuscripts are submitted through the Special Issue portal of the submission system and go through peer review as usual. Each article in the special issue is assigned a unique identifier and once the article is accepted will be published in a regular journal issue as soon as available. The unique identifier allows us to simultaneously add the article to the special issue on ScienceDirect which is gradually built up as individual articles are published online. We do provide Shared Link of the final published version to the corresponding authors with 50 days free access so that they can share it. Submission Instructions https://ees.elsevier.com/vr/<https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fees.elsev…> Authors to select “VSI: Calibrating vision” as article type when submitting their special issue paper in EES. Guide for Authors for more details <https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.elsev…>https://www.elsevier.com/journals/vision-research/0042-6989/guide-for-autho…<https://nam02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.elsev…>https://www.elsevier.com/journals/vision-research/0042-6989/guide-for-autho…

Nov. 14, 2019

Postdoctoral fellow in AI, and real time signal processing for Brain Computer Interface clinical application at CEA, Grenoble and Paris-Saclay, France

by Tetiana AKSENOVA 218551

Postdoctoral fellow in AI, and real time signal processing for Brain Computer Interface clinical application The post-doctoral fellowship will be carried out within the frame of the multidisciplinary project "Brain Computer Interface" (BCI) at CEA-LETI-CLINATEC, Grenoble, France, in collaboration with the Data Intelligence Service from CEA-LIST (Paris-Saclay), France. The goal of the BCI project is the proof of concept that it is possible to control complex effectors thanks to brain activity decoding. Motor BCI raises the hope that limb mobility may be restored for severely motor-impaired patients to regain autonomy, providing them with control over orthosis or prostheses. The project is based on the recording of neuronal activity at the level of cerebral motor cortex (ElectroCorticoGrams, ECoG) with innovative wireless WIMAGINE® implant dedicated to the long term clinical use. A clinical research protocol « BCI and Tetraplegia » at CLINATEC® includes several tetraplegic subjects and is in progress. In this general frame, the project of partners CEA-LETI-CLINATEC and CEA-LIST "Enabling out-of-laboratory neuroprosthetics for severely motor-impaired patients using artificial intelligence", is supported by Programme Transversal de Compétences « Simulation Numérique » of CEA. The particular objective of the project is moving toward neuroprosthetics out-of-the-lab applications. This goal entails solving major challenges: increase number of Degrees of Freedom (DoF), improving accuracy and robustness of neural signal decoding to ensure usability of neuroprosthetics for real life tasks from one side, and providing a BCI system for constrained execution environments offered by portable devices from another side. One direction to improve decoding performances is to use recent advances in artificial neural networks. To ensure that the decoding algorithm is compatible with constrained environments, including the restrained CPU and memory costs such that real-time signal processing and decoding remains feasible, various strategies could be investigated. Missions of post-doctoral fellow will include: The experiment design and set up for real life tasks of using of neuroprosthesis by tetraplegic subject; Design of innovative ANN decoding algorithms, the test and the comparison to conventional methods; Optimization and implementation for real time application, integration to the Clinatec BCI platform; A unique clinical trial ECoG database supports the project. Initial contract duration is 12 months with possible prolongation (24 months at max), initial 12 months in CEA / DRT / LETI / CLINATEC, Grenoble and the next ones in CEA / DRT / List / DM2I / SID / LI3A, Saclay. Profile of candidate: PhD or equivalent with strong knowledge in Machine learning, Deep learning, real time Signal processing (high dimensional data flow), with strong skills in Python, matlab. Application: The candidates should send a CV, the names of 2 referees, and a cover letter to Dr. Tetiana AKSENOVA, tetiana.aksenova(a)cea.fr<mailto:tetiana.aksenova@cea.fr>, Dr. Cedric GOUY-PAILLER, cedric.gouy-pailler(a)cea.fr, and Dr. Pierre BLANCHART, pierre.blanchart(a)cea.fr. The selected candidates will be interviewed for an expected start in March 2019.

Nov. 14, 2019

Call for Paper: [Computers]: Special Issue "Simulation, Imaging and Modelling for Biomedical Systems" (Scopus, ESCI, 50% discount, Deadline Approaching)

by Blink Yu

[Apologies if you receive multiple copies of this message] ==================================== Special Issue "Simulation, Imaging and Modelling for Biomedical Systems" Deadline for manuscript submissions: 15 December 2019 Guest Editor: Dr. Elena Casiraghi and Dr. Barbara Barricelli Department of Computer Science; Università degli Studi di Milano, Italy Website: https://www.mdpi.com/journal/computers/special_issues/SIM_BS ===================================== Dear Colleagues, Over the past decades, a continuous increase in computational power, together with substantial advances in the digital image processing and pattern recognition fields, has motivated the development of computer-aided diagnostic (CAD) systems, augmented and virtual reality applications for surgical planning and simulation, and digital-twin applications for healthcare. Thanks to their effective, precise, and repeatable results, validated CAD systems are nowadays exploited as a valid aid during diagnostic procedures. Surgical simulation applications have become an essential part of surgical procedures as well as training, while research on the development of digital-twin applications in healthcare is continuously increasing, to deliver significant societal and health benefits. Similar important advances in the field of microscopy image analysis have been motivated by the advent of digital microscopes producing high-resolution digital images. Indeed, in the past thirty years the development of computerized systems that have helped pathologists in their analysis of images obtained by fluorescence, histochemical, and immunohistochemical labeling has become a main research focus for computer scientists and clinicians. State-of-the-art automatic microscopy image analysis systems automatically identify biological structures of interest and then try to reproduce the evaluation and quantification performed by expert pathologists and clinicians. These tools are much appreciated in the field for their potential to minimize the inherent subjectivity of manual analysis and to largely reduce the workload of clinicians via high-throughput analysis. This Special Issue intends to provide a comprehensive overview of recent, theoretical, and/or practical advances and new trends in biomedical/microscopy image enhancement and analysis, vision modelling, and general physiological models applied to biomedical/microscopy image processing and advanced visualization methods and devices, and to discuss their applications in the biological and medical fields. Keywords: BioMedical/microscopy image enhancement Biomedical/microscopy image quality assessment Biomedical/microscopy image analysis Computational approaches for citology and histology Computer-aided diagnosis Neuro imaging BioMedical/microscopy image databases Machine learning and artificial intelligence Image segmentation, registration, and fusion Interventional imaging systems Image-guided interventions and surgery Surgical and interventional simulation systems Interventional tracking and navigation Surgical planning and simulation Surgical visualization and mixed, augmented and virtual reality Digital twins and end-user development in biomedicine Interventional software and user interfaces Physiological models Dr. Elena Casiraghi Dr. Barbara Barricelli Guest Editors -- Mr. Blink Yu Managing Editor E-Mail: blink.yu(a)mdpi.com Skype: live:c91693ac8277e1f0 -- MDPI Wuhan Office No.6 Jingan Road, 430064 Wuhan, China MDPI Postfach, CH-4020 Basel, Switzerland http://www.mdpi.com -- Disclaimer: MDPI recognizes the importance of data privacy and protection. We treat personal data in line with the General Data Protection Regulation (GDPR) and with what the community expects of us. The information contained in this message is confidential and intended solely for the use of the individual or entity to whom they are addressed. If you have received this message in error, please notify me and delete this message from your system. You may not copy this message in its entirety or in part, or disclose its contents to anyone.

Nov. 14, 2019