February 2019 - Comp-neuro - lists.cnsorg.org

Modeller's Workshop for the Brain Dynamics Toolbox
by Stewart Heitmann 28 Feb '19

28 Feb '19

Modeller’s Workshop for the Brain Dynamics Toolbox Online Course March 1-22, 2019 https://bdtoolbox.org/p/modellers-workshop/ Learn the art of programming differential equations in Matlab using the Brain Dynamics Toolbox. This is an on-line course for modellers who wish to simulate their own dynamical systems using the graphical toolbox. Participants are taken step-by-step through the process of programming differential equations and solving them numerically. Participants learn to program custom systems of Ordinary Differential Equations, Partial Differential Equations, Delay Differential Equations and Stochastic Differential Equations. Example code is provided in all cases. Early-bird enrolments ($100) close Friday 15th March, 2019. Late enrolments ($150) close Friday 22nd March,2019.

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Doctoral position in computational neuroscience, Ruhr Uni. Bochum
by Vinita Samarasinghe 27 Feb '19

27 Feb '19

Prof. Sen Cheng, Institute for Neural Computation at the Ruhr University Bochum in Germany, invites applicants for the position of *Doctoral Fellow in Computational Neuroscience*. The work will focus on studying the interaction between neocortex and hippocampus using spiking neural network models. The position is part of the project"Theory of the interplay between sensory cortices and hippocampus in memory formation and retrieval", which is funded by the German Research Foundation as part of the collaborative research center SFB 874. The position is funded from*01.07.2019 - 30.06.2022* (TV-L E13 65%). Candidates should have an excellent university degree in neuroscience, physics, mathematics, engineering or a related field and be eligible to enroll in a relevant PhD program at the Ruhr University. Competence in mathematical modeling and excellent programming skillsare mandatory. Familiarity with computational neuroscience or computational cognitive modeling would be a further asset. The Ruhr University Bochum is home to a vibrant research community in neuroscienceand cognitive science. The Institute for Neural Computation is an independent research unit and combines different areas of expertise ranging from experimental and theoretical neuroscienceto machine learning androbotics. For further information see www.rub.de/cns <http://www.rub.de/cns>. To apply please send a statement of your motivation and research interests, academic transcripts, and a complete CV to samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de> in a single PDF file. Please, also request from at least two academic referees that they send letters of reference directly to the same email address. The *deadline for applications is 31.03.2019*. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. https://www.ini.rub.de/the_institute/jobs/doctoral_position_in_computationa… -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Universitätstr. 150 D-44801 Bochum Tel: +49 (0)234 32 27316 Email: samarasinghe(a)ini.rub.de Hours: Mon. - Fri. 8-11

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Cajal Course in Computational Neuroscience 2019
by Macke, Jakob 26 Feb '19

26 Feb '19

CAJAL COURSE IN COMPUTATIONAL NEUROSCIENCE 11 August - 31 August 2019, Champalimaud Centre for the Unknown<http://www.fchampalimaud.org/en/the-foundation/champalimaud-centre-unknown/>, Portugal http://www.cccn.pt Applications deadline: 11 March 2019 Course directors: Brent Doiron<https://www.mathematics.pitt.edu/people/brent-doiron> (University of Pittsburgh, USA) Maria Geffen<https://www.med.upenn.edu/apps/faculty/index.php/g329/p8404062> (University of Pennsylvania,USA) Jako<http://www.mackelab.org/people/>b Macke<http://www.cne.ei.tum.de> (Technical University of Munich, Germany) Joe Paton<http://neuro.fchampalimaud.org/en/person/115/> (Champalimaud Research, Portugal) Confirmed faculty: Matt Botvinick<https://www.google.com/url?q=https%3A%2F%2Fdeepmind.com%2F&sa=D&sntz=1&usg=…>, Google Deepmind, UK Claudia Clopath<http://www.google.com/url?q=http%3A%2F%2Fwww.bg.ic.ac.uk%2Fresearch%2Fc.clo…>, Imperial College London, UK Sophie Denèv<https://www.google.com/url?q=https%3A%2F%2Flnc2.dec.ens.fr%2Fen%2Fmember%2F…>e, Institut d'Etudes de la Cognition (IEC), France Julijana Gjorgjieva<http://www.google.com/url?q=http%3A%2F%2Fbrain.mpg.de%2Fresearch%2Fcomputat…>, Max Planck Institute for Brain Research, Germany Pedro J. Gonçalves<http://www.google.com/url?q=http%3A%2F%2Fppjgoncalves.github.io%2F&sa=D&snt…>, Research Center Caeser, an Associate of Max Planck Society, Bonn, Germany Ann Hermundstadt<https://www.google.com/url?q=https%3A%2F%2Fwww.janelia.org%2Flab%2Fhermunds…>, Janelia Research Campus, USA Kate Jeffery<http://www.google.com/url?q=http%3A%2F%2Fwww.ucl.ac.uk%2Fjefferylab&sa=D&sn…>, University College of London, UK Brian Lau<https://www.google.com/url?q=https%3A%2F%2Ficm-institute.org%2Fen%2Fmember%…>, Brain and Spine Institute, France Gilles Laurent<http://www.google.com/url?q=http%3A%2F%2Fbrain.mpg.de%2Fresearch%2Flaurent-…>, Max Planck Institute for Brain Research, Germany Máté Lengyel<http://www.google.com/url?q=http%3A%2F%2Fwww3.eng.cam.ac.uk%2F~ml468%2F&sa=…>, University of Cambridge, UK Jennifer Linden<http://www.google.com/url?q=http%3A%2F%2Fwww.ucl.ac.uk%2Fear%2Fresearch%2Fp…>, UCL Ear Institute, UK Christian Machens<http://www.google.com/url?q=http%3A%2F%2Fmachenslab.org%2F&sa=D&sntz=1&usg=…>, Champalimaud Research, Portugal Ken Miller<https://www.google.com/url?q=https%3A%2F%2Fctn.zuckermaninstitute.columbia.…>, Columbia University, USA Tony Movshon<http://www.google.com/url?q=http%3A%2F%2Fwww.cns.nyu.edu%2Fcorefaculty%2FMo…>, New York University, USA Mala Murthy<http://www.google.com/url?q=http%3A%2F%2Fmala-murthy.squarespace.com%2F&sa=…>, Princeton Neuroscience Institute, USA Maneesh Sahani<http://www.google.com/url?q=http%3A%2F%2Fwww.gatsby.ucl.ac.uk%2F~maneesh%2F…>, Gatsby Computational Neuroscience Unit, UCL, UK Eero Simoncelli<http://www.google.com/url?q=http%3A%2F%2Fwww.cns.nyu.edu%2F~eero%2F&sa=D&sn…>, New York University, USA Tim Vogels<https://www.google.com/url?q=https%3A%2F%2Fwww.dpag.ox.ac.uk%2Fresearch%2Fv…>, University of Oxford, UK About the course: Computational Neuroscience is a rapidly evolving field whose methods and techniques are critical for understanding and modelling the brain, and also for designing and interpreting experiments. Mathematical modeling is an essential tool to cut through the vast complexity of neurobiological systems and their many interacting elements. This three-weeks school teaches the central ideas, methods, and practice of modern computational neuroscience through a combination of lectures and hands-on project work. Each morning is devoted to lectures given by distinguished international faculty on topics across the breadth of experimental and computational neuroscience. During the rest of the day, students work on research projects in teams of 2-3 people under the close supervision of expert tutors and faculty. Research projects will be proposed by faculty before the course, and will include the modeling of neurons, neural systems, and behavior, the analysis of state-of-the-art neural data (behavioral data, multi-electrode recordings, calcium imaging data, connectomics data, etc.), and the development of theories to explain experimental observations. The course is designed for graduate students and postdoctoral fellows from a variety of disciplines, including neuroscience, physics, electrical engineering, computer science, mathematics and psychology. Students are expected to have a keen interest and basic background in neurobiology, a solid foundation in mathematics, as well as some computer experience. A four-day pre-school in mathematics and programming is offered for students that want to catch up on their math and programming skills. A maximum of 24 students will be accepted. Students of any nationality can apply. We specifically encourage applications from researchers who work in the developing world. Stipends are available. Apply here: www.fens.org/Training/CAJAL-programme/CAJAL-courses-2019/CCCN2019/<http://www.fens.org/Training/CAJAL-programme/CAJAL-courses-2019/CCCN2019/> Applications deadline: 11 March 2019 Stipends are available. CAJAL Advanced Neuroscience Training Programme is funded by FENS<http://www.fens.org/>, IBRO<http://ibro.info/> and The Gatsby Foundation<http://www.gatsby.org.uk/>. For more information on the CAJAL programme: www.cajal-training.org<http://www.cajal-training.org/> Contact address: Simone Zacarias, simone.zacarias(a)research.fchampalimaud.org<mailto:simone.zacarias@research.fchampalimaud.org> — Prof. Dr. rer. nat. Jakob Macke Technical University of Munich Department of Electrical and Computer Engineering Professorship for Computational Neuroengineering macke(a)tum.de<mailto:macke@tum.de> www.cne.ei.tum.de<http://www.cne.ei.tum.de> +49 89 289 26902 Office: Alexandra Petelski Alexandra.Petelski(a)tum.de<mailto:Alexandra.Petelski@tum.de> Tel.: +49 (0)89 - 289 26900 Fax: +49 (0)89 - 289 26901

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Masters in Neuroengineering at TU Munich
by Macke, Jakob 26 Feb '19

26 Feb '19

Dear colleagues, we are accepting applications for the Masters of Science in Neuroengineering (MSNE) at TU Munich. The ENB Elite Master of Science program in Neuroengineering (MSNE) at the Technische Universität München (TUM) is a two-year graduate program, with an optional Research Excellence Certificate, hosted by the Department of Electrical and Computer Engineering and the Center of Competence on Neuroengineering. Neuroengineering is an emerging interdisciplinary field that aims to translate findings in neuroscience to engineering applications, and to provide engineering solutions for neuroscience research. MSNE provides research-oriented, interdisciplinary and international training in this novel research field, combing experimental and theoretical neuroscience with fundamental training in engineering. Funding by the Elite Network Bavaria is making it possible to ensure small class-sizes, to provide individual mentoring to students, and to emphasize hands-on, research-oriented courses. Core courses in Systems- and Computational Neuroscience, Neural Recording and Interface-Technologies, Neuro-Inspired Engineering, Data-Analysis, Signal Processing and Machine Learning, are supplemented by mentor-approved electives, hands-on practicals, research internships (both in TUM and abroad), early-career training for independent research, and awareness of ethical aspects of Neuroengineering. Final deadline for applications is May 31, 2019. Applications will be reviewed on a ‘rolling’ basis, and we encourage interested students to apply as soon as possible. Detailed information can be found on www.msne.ei.tum.de<http://www.msne.ei.tum.de>, and enquiries should be directed to msne(a)ei.tum.de<mailto:msne@ei.tum.de>. Best regards, Jakob Macke — Prof. Dr. rer. nat. Jakob Macke Technical University of Munich Department of Electrical and Computer Engineering Professorship for Computational Neuroengineering macke(a)tum.de<mailto:macke@tum.de> www.cne.ei.tum.de<http://www.cne.ei.tum.de> +49 89 289 26902<tel:+49%2089%20289%2026902> Office: Alexandra Petelski Alexandra.Petelski(a)tum.de<mailto:Alexandra.Petelski@tum.de> Tel.: +49 (0)89 - 289 26900<tel:+49%2089%20-%20289%2026900> Fax: +49 (0)89 - 289 26901<tel:+49%2089%20-%20289%2026901>

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postdoc opportunity at MIT: Halassa and Fiete groups
by Ila Fiete 26 Feb '19

26 Feb '19

The Halassa lab, in collaboration with the Fiete lab, at MIT’s Department of Brain and Cognitive Sciences is seeking to fill one postdoctoral position at the interface of computational systems neuroscience and theoretical neuroscience. Specifically, the work will involve analyzing neural recordings and constructing neural models of prefrontal circuit operations during decision making, working memory and perceptual inference. The postdoctoral researcher will be involved in joint- and individual-lab projects. The researcher will also have the opportunity to participate in several ongoing department- and institution-wide initiatives such as the Center for Brains Minds and Machines (https://cbmm.mit.edu/), and the MIT Quest for Intelligence (https://quest.mit.edu/). The Halassa lab combines well-controlled, parametric behavioral tasks in multiple species (rodents, tree shrews and marmosets) with high-density multi-site electrophysiological recordings of neural ensembles and circuit-specific optical perturbation tools. Recent studies have revealed novel roles of subcortical structures such as the thalamus in regulating prefrontal activity, and thereby, its engagement in working memory and selective attention (e.g. Schmitt et al., 2017 Nature; Rikhye et al., 2018 Nature Neuroscience). The Fiete lab builds theories and models of neural circuit plasticity, dynamics, coding, and function, and performs quantitative analysis of neural data to test models of circuit function. This is an excellent opportunity for a theoretically inclined candidate who would like to work closely with neural data. An ideal candidate will have some familiarity with neuroscience and a background in a relevant quantitative discipline, such as theoretical or computational neuroscience, physics, engineering, or mathematics. Knowledge and experience in spike train analysis and building neural models are a plus. Please contact Mike Halassa: mhalassa(a)mit.edu<mailto:mhalassa@mit.edu> or Ila Fiete: fiete(a)mit.edu<mailto:fiete@mit.edu>. See also: halassalab.mit.edu<http://halassalab.mit.edu>, http://clm.utexas.edu/fietelab/

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PhD Studentship at Keele University
by Peter Andras 26 Feb '19

26 Feb '19

Applications are sought from candidates interested in PhD research in Computer Science. Deadline for applications: 10th March 2019. One particular area of interest is machine learning and computational intelligence. Interested applicants are encouraged to discuss project ideas first informally by email by contacting Professor Peter Andras (p.andras(a)keele.ac.uk <mailto:p.andras@keele.ac.uk> ). Possible projects include: . machine learning applied to medical imaging data (e.g. x-ray, EEG, MRI), bioinformatics data (e.g. virus evolution) or astronomy data (e.g. exoplanet discovery and analysis); . machine learning synthesis of realistic scenarios and interactions in virtual worlds; . complexity and learnability analysis of deep learning architectures; . evolutionary learning of deep networks. The full call is available at: https://www.keele.ac.uk/study/postgraduateresearch/studentships/FNSGS%202019 -04%20studentship%20form.pdf

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Postdoctoral Position in Computational Neuroscience
by Vinita Samarasinghe 26 Feb '19

26 Feb '19

Prof. Sen Cheng, Institute for Neuroinformatics at Ruhr University Bochum, invites applications for a full-time position of *Postdoctoral Scholar (TV-L E13) in Computational Neuroscience. *The position starts on 1st July 2019 and is funded for *3 years*. This project is part of the newly established DFG research unit 2812 “Constructing Scenarios of the Past: A New Framework in Episodic Memory” at the Ruhr University Bochum and the Westfälische Wilhelms University Münster. The research unit will study the cognitive and neuronal mechanisms underlying the constructed scenarios that make up episodic memory. It will employ and combine approaches from Philosophy, Psychology as well as Experimental and Computational Neuroscience. Further information about the project can be found at www.rub.de/cns <http://www.rub.de/cns>. *Job description* The successful candidate will model the function of episodic memory in inference and prediction using abstract computational models. This project strives to find answers to the questions: * Why are specific experiences stored in episodic memory helpful for predicting the future? * Why can general, or semantic, information not serve the same purpose? *Your Profile: * Candidates should hold a PhD in neuroscience, physics, mathematics, engineering, or a related field. Competence in mathematical modeling or machine learning, and excellent programming skills are mandatory. In addition, relevant research experience in neuroscience or a related field is required. Experience in the study of episodic memory and in working within a collaborative research group would be a further asset. Candidates should have excellent communication skills in English and the ability to work well in a team. The Ruhr University Bochum is home to a vibrant research community in neuroscienceand cognitive science. The Institute for Neural Computation is an independent research unit and combines different areas of expertise ranging from experimental and theoretical neuroscienceto machine learning androbotics. For further information see www.rub.de/cns <http://www.rub.de/cns>. Please send your application, including CV, transcripts and research statement electronically, as a single PDF file, to samarasinghe(a)ini.rub.de <mailto:samarasinghe@ini.rub.de>. In addition, at least two academic references may be sent independently to the above email address. The deadline for applications is 15.03.2019. The Ruhr University Bochum is committed to equal opportunity. We strongly encourage applications from qualified women and persons with disabilities. We are committed to providing a supportive work environment for female researchers, in particular those with young children. Our university provides mentoring and coaching opportunities specifically aimed at women in research. We have a strong research network with female role models and will provide opportunities to meet with them. Wherever possible, events will be scheduled during regular childcare hours. Special childcare will be arranged if events have to be scheduled outside of regular hours, in case of sickness and during school or daycare closures. Where childcare is not an option parents will be offered a home office solution. Contact person: Vinita Samarasinghe -- Vinita Samarasinghe M.Sc., M.A. Science Manager Arbeitsgruppe Computational Neuroscience Institut für Neuroinformatik Ruhr-Universität Bochum, NB 3/26 Universitätstr. 150 D-44801 Bochum Tel: +49 (0)234 32 27316 Email: samarasinghe(a)ini.rub.de Hours: Mon. - Fri. 8-11

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CfP, Special session - Hybrid Life II, ALife 2019
by Manuel Baltieri 25 Feb '19

25 Feb '19

[Apologies for cross-posting] ********** Call for Papers ********** Special session - Hybrid Life II: Approaches to integrate biological, artificial and cognitive systems https://sites.google.com/view/hybrid-life-ii/ <https://sites.google.com/view/hybrid-life-ii/> 2019 Artificial Life conference (ALife) Newcastle, UK, 29 July - 3 August 2019 - http://2019.alife.org/ <http://2019.alife.org/> --------------------------------------------------------------------------------------------- DESCRIPTION: The main focus of ALife research is the study of natural systems with the goal of understanding what life is. More concretely, ALife defines ways to investigate processes that contribute to the formation and proliferation of living organisms. In this session we focus on three common approaches to tackle this investigation, proposing ways to integrate, extend and possibly improve them. More specifically we refer to: 1) the formalisation of the necessary properties for the definition of life, 2) the implementation of artificial agents, and 3) the study of the relation between life and cognition. For this special session we propose to start from these well-established Alife methodologies, and extend them through: a unified formal language for the description and modelling of living, as well as artificial and cognitive systems, e.g. control theory, Bayesian inference, dynamical systems theory, etc., the exploration of biological creatures enhanced by artificial systems (or artificial systems augmented with organic parts) in order to investigate the boundaries between living and nonliving organisms, and the evaluation of coupled biological-artificial systems that could shed light on the importance of interactions among systems for the study of living and cognitive organisms. This special sessions aims to invite contributions from the fields of psychology, computational neuroscience, HCI, theoretical biology, artificial intelligence, robotics and cognitive science to discuss current research on the formalisation, combination and interaction of artificial/living/cognitive systems from theoretical, modelling and implementational perspectives. Potential topics include, but are not limited to: Formalisation of life and cognition (e.g. dynamical systems theory, stochastic optimal control, Bayesian inference, etc.) Cognitive robotics Autopoiesis Life-mind continuity thesis Systems biology Origins-of-life theories with relationships to artificial and cognitive systems Animal-robot interaction Bio-inspired robotics Bio-integrated robotics Human-machine interaction Augmented cognition Sensory substitution Interactive evolutionary computation Artificial perception Important Dates 8th March 2019 – Paper submission deadline 24th April 2019 – Paper acceptance notification 24th May 2019 – Camera-ready version 29th July - 3rd August 2019 – Artificial Life conference (ALife), Newcastle, UK Paper Submission Papers and abstracts submitted to this special sessions will be reviewed by a selected group of experts from the a-life community as well as from other areas key to our proposal, specifically chosen for this review process. If you are submitting to a special session you will be given the opportunity to select it during the submission process. Submissions to special sessions follow the same format, instructions and deadlines of regular ALife papers. Organizers Manuel Baltieri, University of Sussex, Brighton, UK Keisuke Suzuki, University of Sussex, Brighton, UK Hiryuki IIzuka, Hokkaido University, Sapporo, Japan Olaf Witkowski, Earth-Life Science Institute - Tokyo Institute of Technology, Tokyo, Japan Contacts For questions, enquiries and more information please check our website https://sites.google.com/view/hybrid-life-ii/ <https://sites.google.com/view/hybrid-life-ii/> or get in touch with m.baltieri(a)sussex.ac.uk <mailto:m.baltieri@sussex.ac.uk>. All the best, -- Manuel Baltieri PhD Candidate, EASy group, Sussex Neuroscience, Department of Informatics, University of Sussex, UK Twitter: @manuelbaltieri

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Post-Doctoral Fellowship in Whole Brain Modelling
by John Griffiths 25 Feb '19

25 Feb '19

Post-Doctoral Fellowship in Whole Brain Modelling The Whole Brain Modelling Group (PI Dr. John Griffiths; www.grifflab.com) at the Krembil Centre for Neuroinformatics, Toronto, is looking to hire a Post-Doctoral Fellow with a strong background in computational neuroscience and/or neuroimaging. The successful candidate shall spearhead the group's efforts in computational modelling of large-scale brain dynamics, with a particular focus on brain stimulation (TMS, TDCS), EEG, neural plasticity, and macro-connectomics. The fellow will have the opportunity to shape the details of the project based on their specific interests, as well as to contribute to other ongoing projects on a range of topics, including: neuroinformatics of whole-brain modelling, mapping and modelling anatomical connectivity and microstructure with DWI in relation to ageing and stroke, and multi-scale modelling of the thalamocortical system in relation to sleep, pharmacological neuromodulation, and neuropsychiatric disease. The successful candidate will have a PhD in neuroscience, engineering, physics, psychology, or related area, a track record for independent research, and a strong publication record. Strong programming skills and familiarity with neuroimaging data analysis (s/d/fMRI and/or M/EEG) are required; experience with computational modelling using numerical simulations (particularly modelling of neural population activity with mean-field/neural mass/neural field techniques) would be advantageous. Full details of the position and application instructions can be found at www.grifflab.com/positions/ For informal inquiries, please email Dr. John Griffiths at john.griffiths(a)camh.ca with the title “Post-Doctoral Fellowship in Whole Brain Modelling” in the subject line. -- Dr. John D. Griffiths Independent Scientist @ Krembil Centre for Neuroinformatics, CAMH, Toronto Assistant Professor @ Department of Psychiatry, University of Toronto www.grifflab.com

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PhD Available: Predicting Recovery from Stroke with Machine Learning
by Howard Bowman 25 Feb '19

25 Feb '19

PhD Available: Predicting Recovery from Stroke with Machine Learning Professor Howard Bowman (University of Kent and University of Birmingham) is looking to take on a PhD student to work on interpretable machine learning applied to data acquired from stroke patients (https://www.ucl.ac.uk/ploras/). This work will be with Professor Cathy Price (Wellcome Centre for Human Neuroimaging, UCL), whose (PLORAS) team has collected one of the largest data sets of stroke patients (greater than 1,000), including structural MRI scans, behaviour and demographics. A key focus of Cathy Price's work is to predict the recovery trajectory of stroke patients from their structural MRI scans, particularly patients with language deficits (i.e. that are aphasic). Progress has been made on this using traditional and now deep learning methods. Critical to clinical uptake of machine learning in this area is the ability to interpret the predictions it provides in a fashion that can be communicated to clinicians, patients and carers. We seek to appoint a PhD student to work on this topic, using methods such as neural-symbolic techniques. The student will be located in the School of Computing at the University of Kent, but will regularly visit and work closely with Cathy Price's team at the Wellcome Centre for Human Neuroimaging. Expertise in machine learning will be provided by Dr Thomas Hope (Wellcome Centre for Human Neuroimaging, UCL) and Dr Marek Grzes (School of Computing, University of Kent). The PhD being advertised will be one of a tranche of scholarships available in the School of Computing at the University of Kent at Canterbury. These will be competitively allocated across a range of topics. To be eligible for these scholarships, please contact Howard Bowman (H.Bowman(a)kent.ac.uk) before 31st March 2019. Relevant articles: Besold, T. R., Garcez, A. D. A., Bader, S., Bowman, H., Domingos, P., Hitzler, P., ... & de Penning, L. (2017). Neural-symbolic learning and reasoning: A survey and interpretation. arXiv preprint arXiv:1711.03902. Hope, T. M., Seghier, M. L., Leff, A. P., & Price, C. J. (2013). Predicting outcome and recovery after stroke with lesions extracted from MRI images. NeuroImage: clinical, 2, 424-433. Seghier, M. L., Patel, E., Prejawa, S., Ramsden, S., Selmer, A., Lim, L., ... & Price, C.J. (2016). The PLORAS database: a data repository for predicting language outcome and recovery after stroke. Neuroimage, 124, 1208-1212.

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