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Recent paper on using Machine Learning to classify autism from schizophrenia
by Stephen Jose Hanson April 7, 2018

April 7, 2018

Please find new Machine learning/Neuroimaging research. ?Neuroimage:Clinical Differences in atypical resting-state effective connectivity distinguish autism from schizophrenia Dana Mastrovito, Catherine Hanson, Stephen Jose Hanson Abstract Autism and schizophrenia share overlapping genetic etiology, common changes in brain structure and common cognitive deficits. A number of studies using resting state fMRI have shown that machine learning algorithms can distinguish between healthy controls and individuals diagnosed with either autism spectrum disorder or schizophrenia. However, it has not yet been determined whether machine learning algorithms can be used to distinguish between the two disorders. Using a linear support vector machine, we identify features that are most diagnostic for each disorder and successfully use them to classify an independent cohort of subjects. We find both common and divergent connectivity differences largely in the default mode network as well as in salience, and motor networks. Using divergent connectivity differences, we are able to distinguish autistic subjects from those with schizophrenia. Understanding the common and divergent connectivity changes associated with these disorders may provide a framework for understanding their shared cognitive deficits https://www.sciencedirect.com/science/article/pii/S2213158218300147?via%3Di… Stephen José Hanson Professor & Director Rutgers Brain Imaging Center (RUBIC) Cognitive Science Center (NB) Rutgers University

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PRNI 2018: THE SUBMISSION DEADLINE HAS BEEN EXTENDED TO 18th APRIL, 2018
by Justin Dauwels (Assoc Prof) April 7, 2018

April 7, 2018

PRNI 2018: THE SUBMISSION DEADLINE HAS BEEN EXTENDED TO 18th APRIL, 2018 ******* please accept our apologies for cross-posting ******* -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- CALL FOR PAPERS AND TUTORIALS PRNI 2018: 8th International Workshop on Pattern Recognition in Neuroimaging to be held 12-14 June 2018 at the National University of Singapore, Singapore www.prni.org<http://www.prni.org/> - @PRNIworkshop - www.facebook.com/PRNIworkshop/<http://www.facebook.com/PRNIworkshop/> ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- The 8th International Workshop on Pattern Recognition in Neuroimaging (PRNI) will be held at the Centre for Life Sciences Auditorium, National University of Singapore, Singapore on June 12-14, 2018.Pattern recognition techniques are an important tool for neuroimaging data analysis. These techniques are helping to elucidate normal and abnormal brain function, cognition and perception, anatomical and functional brain architecture, biomarkers for diagnosis and personalized medicine, and as a scientific tool to decipher neural mechanisms underlying human cognition. The International Workshop on Pattern Recognition in Neuroimaging (PRNI) aims to: (1) foster dialogue between developers and users of cutting-edge analysis techniques in order to find matches between analysis techniques and neuroscientific questions; (2) showcase recent methodological advances in pattern recognition algorithms for neuroimaging analysis; and (3) identify challenging neuroscientific questions in need of new analysis approaches. Authors should prepare full papers with a maximum length of 4 pages (two column IEEE style) for double-blind review. The PAPER submission deadline has been extended until WEDNESDAY, 18th APRIL 2018, 11:59 pm SGT. Accepted manuscripts will be assigned either to an oral or poster sessions. All accepted manuscripts will be included in the IEEE Xplore digital library. Similarly to previous years, in addition to full length papers PRNI will also accept short abstracts (word count not including the title, author list, tables, captions, or references) for poster presentation. Closing date: 04-MAY-2018 Open call for tutorial proposals: Finally, this year PRNI has an open call for tutorial proposals. A tutorial can take a form of 2h, 4h or whole day event aimed at demonstrating a computational technique, software tool, or specific concept. Tutorial proposals featuring hands on demonstrations and promoting diversity (e.g. gender, background, institution) will be preferred. PRNI will cover conference registration fees for up to two tutors per accepted program. The TUTORIAL submission deadline has been extended until WEDNESDAY, 18th APRIL 2018, 11:59 pm SGT Please see www.prni.org<http://www.prni.org/> and follow @PRNIworkshop and www.facebook.com/PRNIworkshop/<http://www.facebook.com/PRNIworkshop/> for news and details. [http://www3.ntu.edu.sg/cits2/CITS_web_resources/signature/img/ntulogo2.jpg] Assoc Prof Justin DAUWELS Associate Professor Deputy Director, ST Engineering - NTU Corporate Laboratory<http://ste-ntulab.ntu.edu.sg/> School of Electrical & Electronic Engineering 50 Nanyang Avenue, S2.2-B2-15, Singapore 639798 T 65-6790-5410 F 65-6790-9313 jdauwels(a)ntu.edu.sg<mailto:jdauwels@ntu.edu.sg> www.ntu.edu.sg<http://www.ntu.edu.sg/> ________________________________ CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents. Towards a sustainable earth: Print only when necessary. Thank you.

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CFP: The first International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2018)
by Mostafa Kia April 6, 2018

April 6, 2018

*Dear Colleagues,We are delighted to invite you to join us for the MLCN 2018 <https://mlcn2018.com/> workshop as a satellite event of MICCAI 2018 conference, Granada, Spain. Call for PapersRecent advances in neuroimaging and statistical machine learning provide an exceptional opportunity for investigators and physicians to discover complex relationships between brain, behaviors, and mental and neurological disorders. MLCN 2018 <https://mlcn2018.com/> workshop, as a satellite event of MICCAI 2018 <http://www.miccai2018.org/en/>, aims to bring together researchers in both theory and application from various fields in domains of spatial statistics, pattern recognition in neuroimaging, and predictive clinical neuroscience. Topics of interests include but are not limited to: - Applications of spatio-temporal modeling in predictive clinical neuroscience- Spatial regularization in decoding clinical neuroimaging data- Spatial statistics in neuroimaging- Learning with structured inputs and outputs in clinical neuroscience- Multi-task learning in analyzing structured neuroimaging data- Deep learning in analyzing structured neuroimaging data- Model stability and interpretability in clinical neuroscienceCONFIRMED SPEAKERS: - Christos Davatzikos (University of Pennsylvania)- Gaël Varoquaux (Parietal team, INRIA)- Jian Kang (University of Michigan)SUBMISSION PROCESS:The workshop seeks high quality, original, and unpublished work on algorithms, theory, and applications of machine learning in clinical neuroimaging and spatially structured data analysis. Papers should be submitted electronically in Springer Lecture Notes in Computer Science (LCNS) style <https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…> of up to 8-pages papers using the CMT system at https://cmt3.research.microsoft.com/MLCN2018 <https://mail.ru.nl/owa/redir.aspx?C=cF_JmZM8kIynrj31nweTMkQwN3oMG8T7g2yKH7j…>. This workshop uses a double-blind review process in the evaluation phase, thus authors must ensure anonymous submissions. Accepted papers will be published in a joint proceeding with the MICCAI conference.IMPORTANT DATES: - Paper submission deadline: June 11, 2018- Notification of Acceptance: July 16, 2018- Camera-ready Submission: July 23, 2018- Workshop Date: September 20, 2018Best regards,MLCN 2018 Organizing Committee,Email: mlcnworkshop(a)gmail.com <mlcnworkshop(a)gmail.com>Website: https://mlcn2018.com/ <https://mlcn2018.com/>twitter: @MLCN2018*

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Open Research Associate Position in the Dept. of Psychiatry, Baylor College of Medicine
by Lopez, Camila April 6, 2018

April 6, 2018

The Papageorgiou/Investigational Targeted Brain Neurotherapeutics Laboratory is seeking a highly motivated Research Associate to manage innovative research with a focus on neuromodulation and neurorehabilitative approaches using imaging-based neurofeedback. Our Laboratory focuses on the following areas: (i) to elucidate the mechanisms that guide plasticity following insult to the brain, by using structural, and functional measures; (ii) induce functional plasticity/reorganization of the brain by applying neurofeedback methods, such as real-time fMRI and EEG; (iii) develop optimization neurofeedback approaches via computational modelling; (iv) develop MR-compatible instruments that will assist in examining plasticity for our longitudinal studies. Our goal is to elucidate the mechanisms involved in cortical blindness, motor impairment, and chronic pain using highly quantitative methods, such as population receptive field, multivariate and univariate analyses. Equally important, our studies focus on a variety of innovative approaches, including neurofeedback in targeted and individualized regions of interest based on the patient's location and spatial extent of the lesion, optimization of rt-fMRI nFb methods with the long-term goal of central and peripheral nervous system injury neuro-rehabilitation. Required Qualifications: Ph.D. in Neuroscience, or Psychology or a related field. Masters degree in Neuroscience, or Psychology with 5 years of experience performing human study experiments will substitute for a PhD degree. The Research Associate is expected: • Manage clinical and basic science - fMRI and EEG studies. • Screen and schedule research volunteers. • Perform psychophysics, and behavioral assessments. • Complete study source documents and maintain study files. • Enter all data from research forms. • Perform statistical analysis and image processing. • Maintain compliance with HIPAA and IRB regulations and assist with IRB submissions. •Train undergraduate, and graduate students to run lab studies • Opportunities to contribute and write up scientific publications, including statistical analyses and graphical representation of data and writing. This position requires interfacing with patients: (i) during the recruitment phase; (ii) the experimental, MR scanning phase; and (iii) following up with patients as our studies are longitudinal. The candidate will have excellent interpersonal skills by focusing on solving conflict, maintain confidentiality, listen to others without interrupting, keep emotions under control, remain open to others' ideas in the team. The applicant MUST have the passion and motivation to manage these innovative scientific research studies. Apply: Please send a pdf or word CV, 3-4 references, and cover letter to Dr. Dorina Papageorgiou at papageor(a)bcm.edu<mailto:papageor@bcm.edu> Compensation commensurate with experience up to $50K. Baylor College of Medicine is an Equal Opportunity /Affirmative Action/Equal Access Employer.

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PhD position at Bernstein Center Berlin available
by Benjamin Lindner April 6, 2018

April 6, 2018

*Benefits of noise in the transmission and processing of time-dependent stimuli by populations of sensory neurons** * We are looking for a PhD candidate to work on signal processing in recurrent neural networks, especially information filtering of sensory signals and the functional role of intrinsic fluctuations and cell heterogeneity. These aspects of neural information processing will be explored by means of analytical calculations, numerical simulations of network models, and the comparison to experimental data (collaboration with Jan Benda, University Tubingen, Germany). In order to get an idea about similar approaches pursued in the past, have a look at our recent paper in PNAS [Grewe, Kruscha, Lindner, and Benda PNAS 114 E1977 (2017)]. The successful candidate should have a degree in physics, mathematics or computational neuroscience (a background in neurobiology is desirable but not obligatory), programming skills (C++, Python, LaTeX, Linux), an excellent command of the English language, good communication skills and team spirit. Funding is provided for three years, starting within the next six months. For details on the doctoral examination process at the Physics Department of Humboldt University Berlin, see https://fakultaeten.hu-berlin.de/en/mnf/wisskar/promotionen/index_html?set_…. Applications, including a letter of motivation, a CV, and a list of three potential referees should be sent by email to   me benjamin.lindner(a)physik.hu-berlin.de  (cc to nikola.schrenk(a)bccn-berlin.de)  The deadline for applications is April 18th 2018, however, later applications might also be considered. Kind regards, -------------------------------------------------------------------------------------------------------------------- Benjamin Lindner Professor for Theory of Complex Systems and Neurophysics Bernstein Center for Computational Neuroscience Berlin Philippstr. 13, Haus 2, 10115 Berlin Room: 1.17, phone: 0049(0)302093 6336 Department of Physics Humboldt University Berlin Newtonstr. 15 12489 Berlin Room: 3.408, phone: 0049(0)302093 7934 http://people.physik.hu-berlin.de/~lindner/index.html --------------------------------------------------------------------------------------------------------------------

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postdoctoral position
by Obermayer, Klaus, Prof. Dr. April 6, 2018

April 6, 2018

Dear Moderator, can you please post this job announcement on the list? Thank you very much! Best regards Klaus Obermayer ----------------------------------------------------------------------------------------------------------------------------------------------------------- Postdoctoral Position in Computational Neuroscience Neural Information Processing Group, Fakultät IV, Technische Universität Berlin and Bernstein Center for Computational Neuroscience, Berlin, Germany Salary grade E13 (TV-L Berliner Hochschulen) Duration: max. 5 years Starting date: immediate Working field: The successful candidate is expected to join collaborative research projects at the interface of computational neuroscience and machine learning (decision making and reward based learning or neural dynamics). The position is also affiliated with the Bernstein Center for Computational Neuroscience Berlin (https://www.bccn-berlin.de/) and the candidate is welcome to participate in its scientific and training activities. Teaching responsibilities include the supervision of two tutorials per week during the semester associated with the courses taught by the Neural Information Processing Group. For more information about our current research projects see: http://www.ni.tu-berlin.de/. Requirements: Successfully completed university degree (Master, Diplom or equivalent) and doctoral degree in Computational Neuroscience, Computer Science or another MINT subject; very good knowledge of machine learning and Computational Neuroscience; experience in teaching (supervision of tutorials) is desirable; good command of the German and English language. How to apply: Please send your written application with the reference number (IV-178/18) and the usual documents to Technische Universität Berlin - Der Präsident - Fakultät IV, Institut für Softwaretechnik und Theoretische Informatik, FG Neuronale Informationsverarbeitung, Prof. Dr. Obermayer, Sekr. MAR 5-6, Marchstr. 23, 10587 Berlin or - preferably - by e-mail to klaus.obermayer(a)tu-berlin.de. Closing date: May 4th, 2018 To ensure equal opportunities between women and men, applications by women with the required qualifications are explicitly desired. Qualified individuals with disabilities will be favored. The TU Berlin values the diversity of its members and is committed to the goals of equal opportunities. Please send copies only. Original documents will not be returned.

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Conference: “Missing links in neuroscience: Bridging scales in theory and experiment”, June 5/6 2018, Bonn
by Jakob Macke April 6, 2018

April 6, 2018

Dear colleagues, We are happy to announce the 7th international caesar conference: “Missing links in neuroscience: Bridging scales in theory and experiment” / June 5th – 6th, 2018, at caesar Bonn. In addition to invited talks, the program will also include a poster-session and contributed talks which will be selected from submitted abstracts— deadline for submissions is May 1st. We especially encourage junior scientists to apply for contributed talks We will provide free childcare at the conference (subject to capacity limitations). Enquires about childcare should be addressed to Bettina.Bosse(a)caesar.de<mailto:Bettina.Bosse@caesar.de> Info and registration: www.caesarconference.com<http://www.caesarconference.com> Topic: Unraveling the principles by which neural circuits process information and guide behavior is one of the central problems of neuroscience. One of the main challenges is that neural information processing takes place on multiple temporal and spatial scales, ranging from subcellular processes in neurons and synapses up to the level of the behaving animal. Bridging these scales requires both experimental techniques which can monitor and probe the system at multiple levels of organization, as well as mathematical frameworks for interpreting experimental results and formulating testable theories. The caesar conference brings together scientists from experimental and theoretical neuroscience to discuss how observations and models of the nervous system at a multiple spatial and/or temporal scales can be integrated. We aim to foster discussions about how to bridge not only the relevant scales, but also how to link experimental data, numerical simulations and conceptual models. Invited speakers: Johann Bollmann Carlos Brody Andrea Bugalossi Eugenia Chiappe Mark Ellisman Rainer Friedrich Surya Ganguli Vivek Jayaraman Peter Jonas Judit Makara Hannah Monyer Eilif Muller Timothy O’Leary Manuela Schmidt Haim Sompolinsky Staci Sorensen Tim Vogels Claire Wyart Research center caesar (www.caesar.de<http://www.caesar.de>) is a center for neuroethology research operated by the caesar foundation, and is associated with the Max Planck Society. The organizing committee can be contacted via Bettina Bosse (bettina.bosse(a)caesar.de<mailto:bettina.bosse@caesar.de>). With best regards, Jakob Macke, Marcel Oberlaender, Bettina Schnell, Johannes Seelig Jakob Macke, TU Darmstadt and caesar Bonn www.mackelab.org<http://www.mackelab.org>

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PhD position in Mathematical Neuroscience at Inria Sophia Antipolis (France)
by Mathieu Desroches April 5, 2018

April 5, 2018

Dear all, We invite candidatures for a PhD position in the Inria MathNeuro Team <http://team.inria.fr/mathneuro> (Sophia Antipolis, France) on Multi-scale modeling of cortical spreading depression. We are looking for candidates with some notions of dynamical systems and neuronal modeling. The project will involve detailed biophysical modeling as well as model reduction and a mathematical analysis of reduced models (in particular their bifurcation and slow-fast structure). Familiarity with programming will be a strong point for the selection process of candidates. The project will be pursued in collaboration with the experimental lab of Massimo Mantegazza at the Molecular and Cellular Pharmacology Institute (IPMC, Sophia Antipolis, France). The deadline is April 15th, 2018. Applications are done online via the following webpage: https://jobs.inria.fr/public/classic/fr/offres/2018-00525 <https://jobs.inria.fr/public/classic/fr/offres/2018-00525>. For more informations on the project, feel free to email me. Best Regards, Mathieu Desroches. --------------------------------------------------------------------- Dr. Mathieu Desroches Research Scientist (Chargé de Recherche) MathNeuro Team <https://team.inria.fr/mathneuro/>Inria Sophia Antipolis - Méditerranée, France http://www-sop.inria.fr/members/Mathieu.Desroches/ <http://www-sop.inria.fr/members/Mathieu.Desroches/>

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6th Baltic-Nordic School on Neuroinformatics (BNNI 2018)
by Marja-Leena Linne April 3, 2018

April 3, 2018

6th Baltic-Nordic School on Neuroinformatics BNNI 2018 Understanding the Brain: from Neuroscience to Deep Learning Don't miss the extended application deadline: 12 April 2018: Application deadline (extended) 15 April 2018: Acceptance notification 11-13 June 2018: School See more information and applications at: web.lsmuni.lt/bnni2018/en<http://web.lsmuni.lt/bnni2018/en> Place: Ventspils University of Applied Sciences Inženieru 101, Ventspils Latvia Time: 11-13 June 2018 We invite advanced master students, doctoral students, and postdoctoral researchers to participate in the BNNI 2018 to be held at the Ventspils University of Applied Sciences, Ventspils, Latvia in June 2018. The course is interdisciplinary and covers modeling at different levels of organization of the brain. Additionally this year's training course is planned more diverse and will include also EEG/SEEG signal processing techniques, forward and inverse modeling of the brain and various aspects of deep learning algorithms. This school is the sixth in the series of the Baltic-Nordic Courses on Neuroinformatics (BNNI 2013 in Kaunas, Lithuania; BNNI 2014 in Tampere, Finland; BNNI 2015 in Tartu, Estonia; BNNI 2016 in Warsaw, Poland, BNNI 2017 in Kaunas, Lithuania). The target audience of the course will be advanced master students, doctoral students and postdoctoral researchers in biomedical and technology sciences, from medicine, biology, psychology, to mathematics, informatics, information technology, physics, chemistry, who would like to get an introduction to neuroinformatics and computational neuroscience. Some experience with programming and quantitative reasoning as well as strong interest in computational and mathematical modeling of the brain will be desirable but not necessary to benefit from the school. Last year we had participants from 14 countries all over the world! Faculty includes: Marja-Leena Linne, Tampere University of Technology, Finland; The Human Brain Project Bruce Graham, University of Stirling, UK Daniel Wojcik, Nencki Institute of Experimental Biology, Warsaw, Poland Arnd Roth, University College London, UK Peter Jedlicka, NeuroScience Center, Goethe-University, Frankfurt, Germany Gaute Einevoll, UiO Department of Physics The Faculty of Mathematics and Natural Sciences, Norway Ausra Saudargiene, Neuroscience Institute, Lithuanian University of Health Sciences, Kaunas, Lithuania Radu Ranta, CRAN, University of Lorraine, France Louis Maillard, CHRU Hôpital central - Nancy, CRAN, University of Lorraine, France Janis Hofmanis, Smart Technology Research Center, Ventspils University of Applied Sciences, Ventspils, Latvia and others. Venue The lectures will be held at the Ventspils University of Applied Sciences, Inženieru 101, Ventspils, Latvia. Practical arrangements There is a small tuition fee of 50 euros. The organizers will provide teaching materials, meals and coffee during the course. The participants are expected to cover their travel and health insurance expenses as well as lodging. Although Student accommodation will be available at a reduced cost. Ventspils University of Applied Sciences can provide a student dormitory rooms - 2 students per room, 2 rooms per block. One block costs 51 EUR (12,75 EUR for one person per night). We are looking forward to welcome you at the BNNI 2018 in Ventspils, Latvia!

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[journals] CfP: Topical Issue on Deep Learning and Neural Systems in Robotics
by Di Nuovo, Alessandro April 3, 2018

April 3, 2018

CALL FOR PAPERS Deep Learning and Neural Systems in Robotics Topical issue in PALADYN. Journal of Behavioural Robotics DESCRIPTION Deep Learning can equip robots with a new level of skill by utilizing insights from neuroscience. These new developments have impact on various types of robots, from companion robots to driver assistance in semi-autonomous vehicles. Deep Learning can enable unprecedented quality of results in tasks such as object detection, localization, communication and behavior learning. Training deep neural networks typically requires GPU workstations or high-performance computing servers. It may require huge amounts of data or innovative training schemes. These issues indicate only some of the special challenges when utilizing deep networks in robotics. Within this context the topics of this special issue include, but are not limited to: - Applications of deep learning - Software and hardware systems - Data acquisition for deep learning - Neural information processing systems - Deep learning training schemes and paradigms - GPU computing for deep learning - Software engineering for deep learning - Neural networks on low powered devices - Human robot interaction and communication - Cognitive, developmental and evolutionary robotics IMPORTANT DATES The deadlines for the submission are as follows: 15 June 2018 (publication in 2018) 15 December 2018 (publication in 2019) Notification of acceptance will be communicated as we progress with the review process. Individual papers will be reviewed and published online on an ongoing basis. HOW TO SUBMIT Authors are requested to submit their full version of papers to the Topical Issue complying also the general scope of the journal. The submitted papers will undergo the standard peer-review process before they can be accepted. All submissions to the Topical Issue must be made electronically via the journal online submission system Editorial Manager (http://www.editorialmanager.com/paladyn/) When entering your submission via online submission system please choose the option "TI on Deep Learning and Neural Systems in Robotics". All manuscripts will undergo the standard peer-review process (single blind, at least two independent reviewers). Submissions for the Topical Issue are now open. Contributors to the Topical Issue will benefit from: NO submission and publication FEES Free language assistance for authors from non-English speaking regions Fast online publication of articles (continuous publication model) Open Access to your article for all interested readers Indexation in SCOPUS Long-time preservation (articles archived in Portico) Extensive post-publication promotion GUEST EDITORS Stephan K. Chalup, University of Newcastle, Australia Alessandro Di Nuovo, Sheffield Hallam University, UK Alan D. Blair, University of New South Wales, Australia Aydan M. Erkmen, Middle East Technical University, Ankara, Turkey Neil Vaughan, Royal Academy of Engineering / University of Chester, UK We are looking forward to your submission. If you have any question, please contact us at Stephan.Chalup(a)newcastle.edu.au or Justyna.Zuk(a)degruyteropen.com.

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