November 2018 - Comp-neuro - lists.cnsorg.org

Researcher in NLP with focus on "identification of early signs of cognitive abnormalities in language"

by Dimitrios Kokkinakis

*Type of employment:* Fixed-term employment, research position (12 months) *Extent*: 100 % *Location*: Department of Swedish, Gothenburg, Sweden *First day of employment: *2019-01-01 or as agreed. *Apply by*: 2018-12-13 *The position focus*:* identification of early signs of cognitive abnormalities in language* *Details of the post and instructions on how to apply are available from this link*: < *https://www.gu.se/english/about_the_university/job-opportunities/vacancies-details/?id=3417* <https://www.gu.se/english/about_the_university/job-opportunities/vacancies-…> *>* *Qualifications*: Ph.D. in Natural Language Processing (NLP), preferably in computer science with a strong focus on NLP and/or automatic speech processing (ASP), and *preferably *with a specialization in prior work related to mental and neurological impairments The Swedish Language Bank (SB) is a research unit at the Department of Swedish, University of Gothenburg. SB is the coordinating partner of the research project: “*Linguistic and extra-linguistic parameters for early detection of cognitive impairment*”. The successful applicant will conduct research in this project and particularly in the area in NLP and/or ASP in order to develop, adapt, analyze, and implement methods for processing *available* spoken and transcribed data samples acquired from people with mild and subjective forms of cognitive impairment as well as healthy controls (i.e. differentiating the different groups and/or identifying early cognitive abnormalities such as atypical language production, that precede the onset of dementia, especially Alzheimer’s). In particular, you will be using machine learning and other related techniques (deep learning) and develop, evaluate and deploy classification models and tools for experimenting with the data. Inquiries can be made to Dimitrios Kokkinakis ( dimitrios.kokkinakis(a)svenska.gu.se)

Nov. 30, 2018

'la Caixa' INPhINIT PhD opportunity at MCEN/BCAM and UChicago on neuron-glial connectomics

by Maurizio De Pitta

Dear colleagues, please share with whoever could be interested and forward to your department mailing lists. PhD project : Structure and function of the glial connectome. Lab / Host institution : Group of Mathematical, Computational and Experimental Neuroscience (MCEN) at the Basque Center of Applied Mathematics (BCAM). Supervisors : Maurizio De Pittà (BCAM), SerafimRodrigues (BCAM), Narayanan Kasthuri (The University of Chicago, and Argonne National Labs). Location : Bilbao, The Basque Country, Spain. Duration : 3 years. Stipend : 30k+ EUR/year + mobility allowance. Starting date : May—Oct 2019 (negotiable). Award type: Preselection + competitive call. Categories: Incoming (for international students not living in Spain at the time of the call) and Retaining (for Spanish students) Preselection deadline: January 13th, 2019 (incoming); February 9th, 2019 (retaining). Application deadlines: February 6th, 2019 (incoming); February 27th, 2019 (retaining) (more details: https://goo.gl/HZCPxp) Scientific background : Neurons of the brain form complex circuits, connecting each other by means of synapses. The structure of these circuits is believed to closely relate with their function. Accordingly, mapping the architecture of neural circuits of the brain, otherwise known as the brain’s neuronal connectome, is a prominent area of investigation of modern neuroscience. In parallel, there is growing awareness that glial cells such as astrocytes, could modulate the physical structure of the neuronal connectome. Astrocytes indeed form barriers to neuronal connectivity and regulate synapse formation and deletion, but they could also modulate neuronal signal transmission in the extracellular space, along with structure and dynamics of synapses. In addition, astrocytes contact hundreds of thousand synapses, and are also connected in complex networks. This suggests that understanding the neuronal connectome should also include neuron-astrocyte interactions and thus mapping of the associated glial connectome in terms of synapse-astrocyte and astrocyte-astrocyte connections. Workplan : The candidate will be part of an international team of researchers within the framework of the Open Connectome Project (https://neurodata.io/) She/He will deploy mathematical tools borrowed from graph theory, statistical analysis, machine learning and algebraic topology to analyze big data sets from 3D electron microscopy of cortical tissue of rodent’s brain to seek the first map of astrocytic connections with synapses at subcellular spatial resolution. In parallel the candidate will develop expertise in modeling of complex heterogeneous cell networks of neurons and astrocytes, to explore potential functional relevance of specific synapse-astrocyte circuits and motifs in neuron-glial networks. Working environment : The candidate will be based in Bilbao (Spain) where she/he will work under the supervision of Drs. Maurizio De Pittà and Serafim Rodrigues at the Group of Mathematical, Computational and Experimental Neuroscience at the Basque Center of Applied Mathematics (BCAM). In addition, the candidate will also collaborate with and be supervised by Dr. Narayanan “Bobby” Kasthuri at the University of Chicago and Argonne National Labs (USA), where she/he will spend regular periods of time during her/his graduate training. Dr. De Pittà is a leading expert on computational modeling of neuron-glia interactions, with an experience in computational neuroscience of 10+ years who recently joined the MCEN group at BCAM as « Junior Leader » fellow with a start-up grant supported by la Caixa Banking Foundation. The MCEN group is a rapidly growing team led by Ikerbasque Professor Serafim Rodrigues, that was established in 2016 as part of the strategic research portfolio enacted by the Basque Country to foster interdisciplinary research in Neuroscience. Dr. Kasthuri is one of the leading experts in modern connectomics, who has pioneered large volume automated electron microscopy for mapping neuronal connections and synchrotron source X-ray microscopy to map the cellular composition of entire brains. BCAM is one of the Severo Ochoa’s excellence centers for scientific research in Spain and it provides an exeptionally fertile international environment for professional development and enriching scientific collaborations. Bilbao, as the capital of the Basque Country in Spain, is a vibrant, friendly city with one of the highest standards of life quality in Spain. Requirements : -- Master’s degree (or equivalent) in Physics, Mathematics, Engineering, or related fields. -- Excellent English skills (oral and written). – Experience in machine learning and/or statistical analysis and/or topology or algebraic topology. -- Programming skills in Matlab, Python and C/C++. -- High motivation for interdisciplinary research with strong interests for biological details and an analytic mindset. – Capacity to meet deadlines and outstanding propensity to work in an international dynamic environment. -- Essential knowledge of neuroscience and graph theory is preferred but not required. Additional notes : This is a cutting-edge project that ideally matches with outstanding and creative candidates, with a strong motivation for international collaborations, mobility, and independence. The candidate will work on the project full-time and no part-time agreements will be taken into consideration. Application process : The INPhINIT PhD Fellowship Program by la Caixa Banking Foundation is the most prestigious PhD fellowship program running in Spain. The program is highly competitive and offers unequalled training an financial support to its fellow. The ideal successful candidate should have an outstanding educational background and rank among the 5% best of his/her class. Candidates who are interested in the advertised PhD project, must first send a CV with letter of motivation (max 2 pages) to Drs. De Pittà (mdepitta(a)bcamath.org) and Kasthuri (bobbykasthuri(a)uchicago.edu) for review and preselection. Preselections are open now till January 13, 2019 (for incoming candidates) and February 3rd, 2019 (for retaining candidates). Specify as mail object: “INPhINIT PhD Project Application”. Relevant References: De Pittà et al., Astrocytes: orchestrating synaptic plasticity?, Neuroscience, 2015, 323:43. Katshuri et al., Saturated reconstruction of a volume of neocortex, Cell, 2015, 162 :648 Relevant links: Official call by BCAM: https://goo.gl/Vq8mto INPhINIT: https://goo.gl/d761sP BCAM homepage: https://goo.gl/ENSBAo Maurizio De Pittà: https://goo.gl/pJXEYJ Narayanan “Bobby” Kasthuri: https://goo.gl/pYmv2w Open Connectome Project: https://neurodata.io/ ----- Maurizio De Pitta' Research Fellow MCEN -- Group of Mathematical, Computational and Experimental Neuroscience BCAM -- Basque Center of Applied Mathematics https://sites.google.com/site/mauriziodepitta/home

Nov. 29, 2018

CFP Frontiers Research Topic: Closing the Loop: From Human Behavior to Multisensory Robots

by Pablo Barros

Call For Papers - Frontiers Research Topic: Closing the Loop: From Human Behavior to Multisensory Robots I. Aim and Scope The ability to efficiently process crossmodal information is a key feature of the human brain that provides a robust perceptual experience and behavioral responses. Consequently, the processing and integration of multisensory information streams such as vision, audio, haptics, and proprioception play a crucial role in the development of autonomous agents and cognitive robots, yielding an efficient interaction with the environment also under conditions of sensory uncertainty. This Research Topic invites authors to submit new findings, theories, systems, and trends in multisensory learning for intelligent agents and robots with the aim to foster the development of novel and impactful research which will contribute to the understanding of human behavior and the development of artificial systems operating in real-world environments. II. Potential Topics Topics include, but are not limited to: - New methods and applications for crossmodal processing and multisensory integration (e.g. vision, audio, haptics, proprioception) - Machine learning and neural networks for multisensory robot perception - Computational models of crossmodal attention and perception - Bio-inspired approaches for crossmodal learning - Multisensory conflict resolution and executive control - Sensorimotor learning for autonomous agents and robots - Crossmodal learning for embodied and cognitive robots III. Submission - Abstract - 18th January 2019 - Paper Submission - 12th May 2019 More information: https://www.frontiersin.org/research-topics/9321/closing-the-loop-from-huma… IV. Guest Editors Pablo Barros, University of Hamburg, Germany Doreen Jirak, Hamburg University, Germany German I. Parisi, Apprente, Inc., USA Jun Tani, Okinawa Institute of Science and Technology, Japan -- Dr. Pablo Barros Postdoctoral Research Associate - Crossmodal Learning Project (CML) Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.dehttp://www.pablobarros.nethttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.htmlhttps://www.inf.uni-hamburg.de/en/inst/ab/wtm/

Nov. 29, 2018

Faculty position in Computational Neuroscience and AI at the University of Edinburgh

by Matthias Hennig

The Institute for Adaptive and Neural Computation at the University of Edinburgh is inviting applications for a Lecturer/Senior Lecturer/Reader (Assistant/Associate professor) position in Computational Neuroscience and Artificial Intelligence. This position is part of an expansion of research and teaching in cognition, neuroscience, and AI. Candidates should have inter-disciplinary research interests, combining computational and machine learning based methods and cognitive science, and be able to teach undergraduate and master’s level courses in areas such as AI and machine learning, in addition to teaching in cognitive science. The closing date is 15. Jan 2019. For further details and to apply, go to: https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobs… Edinburgh is also recruiting faculty in Computational Cognitive Science: https://www.vacancies.ed.ac.uk/pls/corehrrecruit/erq_jobspec_version_4.jobs… -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

Nov. 28, 2018

Cognitive, Computational, and Systems Neuroscience Training Program at University of Oregon

by Luca Mazzucato

The Institute of Neuroscience (ION) at the University of Oregon is welcoming applications for graduate training in neuroscience (deadline December 1st 2018). The training program in Cognitive, Computational, and Systems Neuroscience ( CCSN <http://ion.uoregon.edu/content/cognitive-computational-and-systems-neurosci…>) is sponsored by the University of Oregon Institute of Neuroscience, the nation's first research institute of its kind. In keeping with the innovative origins of the Institute, the CCSN program provides a rare opportunity for graduate students to forge experimental and theoretical links between systems and cognitive neuroscience while becoming experts in their field of choice. We believe that such interdisciplinary training positions our graduates to become leaders in the growing field of integrative and behavioral neuroscience. The Computational Neuroscience core of the CCSN includes Yashar Ahmadian's and Luca Mazzucato's labs, in close collaboration with all other ION labs (Chris Doe, Santiago Jaramillo, Bryce Kuhl, Shawn Lockery, David McCormick, Cris Niell, Matt Smear, Mike Wehr, and many others). The heart of our program is thesis research. Twenty eight faculty members drawn from the departments of Biology, Psychology, and Mathematics serve as research mentors and instructors. These researchers use a wide range of approaches including molecular biology, genetics, electrophysiology, optogenetics, functional brain imaging, and computational neuroscience to tackle fundamental questions in the neuronal basis of perception, behavior, memory, and cognition. CCSN faculty study not only humans but a wide range of model organisms including C. elegans, Drosophila, zebrafish, and rodents. As a result, students enrolled in our PhD program come away with the broad conceptual and technical skills necessary to run an independent neuroscience research lab or pursue many other related career paths. Our state-of-the-art facilities and excellent support staff allow ION members to progress rapidly by making exploratory or pilot experiments accessible. When not "at the bench," trainees follow a customizable course of study that leads from a year-long graduate core course to a variety of elective courses that allow students to go deeper into their specialty. In addition to course work, trainees learn in a variety of interactive settings including lab meetings, journal clubs, seminars, bi-monthly research-in-progress meetings, and institute retreats. These activities, together with a culture of openness and engagement among CCSN faculty members, create a degree of cohesiveness that sets CCSN apart from programs at other universities. We're passionate about creating an inclusive environment that promotes and values diversity. Research institutions that are diverse in gender, gender identity, race, sexual orientation, ethnicity, age, and perspective are proven to foster greater creativity and promote synergistic, collaborative innovation and interactions. Our application deadline is December 1, 2018. If interested in applying, please contact David McCormick (davidmc(a)uoregon.edu) David A. McCormick Director, Institute of Neuroscience davidmc(a)uoregon.edu

Nov. 27, 2018

2 openings in vision rehabilitation and multi-modal data modelling: 1 PhD and 1 RA/postdoc

by Paul Matusz

Institute of Information Systems at HES-SO in Valais and Foundation for the Blind in Lausanne (Switzerland) are looking for 1 PhD student and 1 RA/postdoc (open rank) interested in links between (eye) health, neuroscience and modelling links between sensory/ perceptual - brain - cognitive processes. Our project aims to asssess the potential of virtual reality games in the rehabilitation of the most common pediatric vision disorder - amblyopia ("lazy eye"). The recovery potential is assessed at the level of both the usual, basic vision skills (visual acuity or 3D vision) and functional "visual" skills like age-appropriate literacy skills. The project likewise aims to establish the role therein of different selective attention systems (visual, multisensory), as studied with rigorous experimental paradigms combined with the advantages of EEG and multi-variate EEG/ERP analyses (eg. Murray et al. 2008 BTOP; Tivadar & Murray 2018 ORM tinyurl.com/y8uxonnf ). The project is well-suited for students interested in modelling multi-modal clinical pediatric data and clinical change in the areas of medicine, neuroscience and/or cognition. More details here: https://drive.google.com/file/d/1VpzIFBz1wzrqHQNqEsD3CnktbD2axGgv/view Paul (Pawel) Matusz, Ph.D. Junior Group Leader Institute of Information Systems, HES-SO – Radiology, University Hospital Centre & University of Lausanne, Sierre – Lausanne, Switzerland Adjunct Assistant Professor Hearing & Speech Sciences, Vanderbilt University, Nashville, TN, USA https://groupforrealworldneuroscience.wordpress.com/ https://twitter.com/paweljmatusz +41 213141547

Nov. 27, 2018

Graduate Program in Computational Neuroscience at Tübingen - Deadline Jan 15th

by Philipp Berens

The Master program "Neural Information Processing - Computational Neuroscience" covers theoretical and computational aspects of neuroscience. Faculty include: Peter Dayan, Matthias Bethge, Zhaoping Li, Martin Giese, Alexander Ecker, Philipp Berens, Fabian Sinz, Anna Levina and many more! Students obtain extensive training in computational modeling of neural systems, machine learning data analysis and neuroscience. While the first year is dedicated to course work at the graduate level, the second year provides hands-on research experience in leading labs in lab rotations and during thesis work. After finishing the Master program, students can smoothly transition to our PhD program and continue their research. The program provides research-oriented training in a wide spectrum of basic computational neuroscience topics with different options: machine learning for neuroscience and neural data analysis models of neural dynamics and coding motor control, rehabilitation robotics and brain-computer interfaces systems neuroscience and neurophysiology data science, bioinformatics and programming behaviour and cognition The deadline for applications is January, 15th (written documents must be in Tübingen). For more information please visit: https://www.bccn-tuebingen.de/education/master-of-science-neural-informatio… Please forward to interested students at the BSc level. -- Prof. Dr. Philipp Berens University of Tübingen Institute for Ophthalmic Research http://www.berenslab.org phone: +49-7071-2988833

Nov. 27, 2018

Three Postdocs in Epilepsy and Brain-Computer Interfaces, Melbourne, Australia

by David Grayden

Three Postdocs in Epilepsy and Brain-Computer Interfaces ARC Training Centre in Cognitive Computing for Medical Technologies The University of Melbourne and IBM Research - Australia http://jobs.unimelb.edu.au/caw/en/job/898108/research-fellows-in-epilepsy-3… We have created a new research training centre dedicated to Cognitive Computing for Medical Technologies and are now looking for outstanding Research Fellows to join on us on three-year appointments. This is an exciting joint venture between the Department of Biomedical Engineering and the School of Computing and Information Systems in collaboration with our research partners IBM Research Australia, University of South Australia, Western Sydney University, RMIT University, and CSIRO. Our focus is to create a workforce that is expert in developing, applying, and integrating artificial intelligence technologies in data-intensive medical contexts by facilitating the next generation of data-driven and machine learning-based medical technologies. The Three Roles: 1. Epileptic Seizure Prediction - in this project, you will work to develop and apply state-of-the-art machine learning approaches for epileptic seizure prediction as well as assessing the efficacy of epilepsy medication. 2. Epilepsy Modelling - in this project, you will help understand the causes and behaviours of epileptic seizures and develop high fidelity models for seizure prediction. This will be done by bringing together neural models of the brain with machine learning. 3. Brain-Computer Interfaces - in this project, you will work to develop a neural network-based brain-computer interface that can be used to control augmentative devices for people with speech, vision or motor disorders. We are interested in applications from those whose expertise aligns with and reflects strengths in Biomedical Engineering, Electrical Engineering, Mathematics and Computer Science. We are also interested in specific experience in programming skills, machine learning, signal processing and computational neuroscience. Applications close: 07 Jan 2019 11:55 PM AUS Eastern Daylight Time Details: http://jobs.unimelb.edu.au/caw/en/job/898108/research-fellows-in-epilepsy-3… Regards, David Professor David B. Grayden Head of Department Dept of Biomedical Engineering Melbourne School of Engineering The University of Melbourne, Victoria 3010 Australia http://www.bme.unimelb.edu.au | https://www.linkedin.com/in/dgrayden

Nov. 27, 2018

open rank faculty position in Human Movement Science at Northeastern, Boston, MA

by Marta Russo

The Department of Biology at College of Science and the Department of Physical Therapy, Movement and Rehabilitation Science at the Bouve College of Health Sciences invites nominations and applications for a tenure track faculty position (open rank, from the Assistant to the Full Professor rank). Applicants are encouraged to submit their application by November 29, 2018 to receive full considerations, but review of applications will continue until the position is filled. More info can be found below or here <https://neu.peopleadmin.com/postings/57607.>. Informal inquiries can be addressed to: Dr. Dagmar Sternad, Chair of the Search Committee (d.sternad(a)northeastern.edu) Apologies for multiple posting. -- Marta Russo, PhD Postdoctoral Research Associate Action Lab Office: 503 Richards Hall Mail: 134 Mugar Life Sciences Building Northeastern University 360 Huntington Avenue Boston, MA 02115 m.russo(a)northeastern.edu *Faculty Position in Human Movement Science* *Northeastern University, Boston, MA* *Assistant, Associate, or Full Professor* *A tenure-track position is open in Human Movement Sciences in the Department of Biology, College of Science and the Department of Physical Therapy, Movement and Rehabilitation Science, Bouve College of Health Sciences, at Northeastern University.* The position is open for applicants from the Assistant to the Full Professor rank. The candidate’s research can be in the areas of experimental, computational, or clinical human movement, with a possible bridge to prosthetics and robotics. This position is part of a growing university-wide cluster in the science of human movement, spanning research strengths from basic experimental and computational research to rehabilitation science, robotics, and neuroengineering. Priority will be placed on research strengths that complement existing strengths in computational human movement science, rehabilitation science, neurophysiology, neuroimaging, and control theory, although excellence is of top-most priority. Depending on the research profile, an affiliated appointment with Bioengineering or Electrical and Mechanical Engineering is possible. The anticipated start date is Fall Semester, 2019. Responsibilities will include conducting an independent, externally funded research program, teaching undergraduate and graduate courses, and participating in departmental, college and university service. Qualified candidates should have experience in, or be able to demonstrate a commitment to, working with diverse student populations and/or in a culturally diverse work and educational environment. The Department of Biology is strongly interdisciplinary, with 20 tenured and tenure-track faculty in Biology and an additional 9 faculty with joint appointments in other departments. The department administers programs in the College of Science at Northeastern University for 1,200 undergraduates, and 100 students in Ph.D., Masters, and Professional Masters programs. The Department of Physical Therapy, Movement and Rehabilitation Sciences, located within Bouvé College of Health Sciences, is comprised of 10 tenured and tenure track faculty and 20 clinical faculty. The Department offers a Ph.D. program in Human Movement and Rehabilitation Sciences, as well as one of the oldest and largest Doctorate in Physical Therapy (DPT) programs in the country. Grounded in its signature co-op program, Northeastern provides unprecedented global experiential learning opportunities. Northeastern University occupies a vibrant 67-acre campus in the heart of Boston, surrounded by other leading educational, health care, technological, and research institutions, as well as world-renowned venues for art and music. Applicants must have a PhD in the life sciences, including physical medicine and physical therapy, neuroscience, neurophysiology, bioengineering, electrical or mechanical engineering, kinesiology, rehabilitation sciences, or other related disciplines. All applicants should have a strong record of scholarly accomplishment that demonstrate research productivity and the ability to perform cutting edge research. Candidates seeking appointment at the associate or full professor level should have substantial research productivity and a history of grant support and academic service. *Please submit a curriculum vitae, cover letter, a two-page description of research accomplishments and plans, a statement on teaching, and the name and contact information for three references through the application portal* https://neu.peopleadmin.com/postings/57607 <https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Furldefense…> . Review of applications will begin immediately and will continue until the position is filled. Applications should be submitted by November 29, 2018 to receive full considerations. Informal inquiries can be addressed to: Dr. Dagmar Sternad, Chair of the Search Committee (d.sternad(a)northeastern.edu) -- <http://www.hsantalucia.it/5x1000-sostieni-la-nostra-ricerca> *Rispetta l'ambiente: se non ti è necessario, non stampare questo messaggio - **Please consider the environment before printing this email.*

Nov. 26, 2018

Using spike train distances to identify the most discriminative neuronal subpopulation

by Thomas Kreuz

Dear all, may I kindly draw your attention to our most recent paper which contains several new algorithms to address neuronal population coding using spike train distances: Satuvuori E, Mulansky M, Daffertshofer A, Kreuz T: Using spike train distances to identify the most discriminative neuronal subpopulation <https://www.sciencedirect.com/science/article/pii/S0165027018302747> JNeurosci Methods, 308, 354 [PDF <https://www.sciencedirect.com/science/article/pii/S0165027018302747>] and arXiv [PDF <https://arxiv.org/pdf/1805.10892.pdf>] (2018). For the abstract see below. This paper is part of the dissertation "Spike train distances and neuronal coding <http://dare.ubvu.vu.nl/bitstream/handle/1871/55855/abstract%20english.pdf?s…>" of my PhD student Eero Satuvuori whose full thesis can now be found here <http://dare.ubvu.vu.nl/bitstream/handle/1871/55855/abstract%20english.pdf?s…>. Besides some original parts and the paper cited above it also contains these recent works: Satuvuori E, Kreuz T: Which spike train distance is most suitable for distinguishing rate and temporal coding? JNeurosci Methods 299, 22 [PDF <https://ac.els-cdn.com/S0165027018300372/1-s2.0-S0165027018300372-main.pdf?…>] and arXiv [PDF <https://arxiv.org/pdf/1708.07508.pdf>] (2018). Kreuz T, Satuvuori E, Pofahl M, Mulansky M: Leaders and followers: Quantifying consistency in spatio-temporal propagation patterns New J. Phys., 19, 043028 [PDF <https://doi.org/10.1088/1367-2630/aa68c3>] and arXiv [PDF <https://arxiv.org/pdf/1610.07986v4.pdf>] (2017). Satuvuori E, Mulansky M, Bozanic N, Malvestio I, Zeldenrust F, Lenk K, Kreuz T: Measures of spike train synchrony for data with multiple time-scales JNeurosci Methods 287, 25 [PDF <https://doi.org/10.1016/j.jneumeth.2017.05.028>] and arXiv [PDF <https://arxiv.org/pdf/1702.05394.pdf>] (2017). All the best, Thomas Kreuz PS: Satuvuori E, Mulansky M, Daffertshofer A, Kreuz T: Using spike train distances to identify the most discriminative neuronal subpopulation <https://www.sciencedirect.com/science/article/pii/S0165027018302747> JNeurosci Methods, 308, 354 [PDF <https://www.sciencedirect.com/science/article/pii/S0165027018302747>] and arXiv [PDF <https://arxiv.org/pdf/1805.10892.pdf>] (2018). Abstract: Background Spike trains of multiple neurons can be analyzed following the summed population (SP) or the labeled line (LL) hypothesis. Responses to external stimuli are generated by a neuronal population as a whole or the individual neurons have encoding capacities of their own. The SPIKE-distance estimated either for a single, pooled spike train over a population or for each neuron separately can serve to quantify these responses. New method For the SP case we compare three algorithms that search for the most discriminative subpopulation over all stimulus pairs. For the LL case we introduce a new algorithm that combines neurons that individually separate different pairs of stimuli best. Results The best approach for SP is a brute force search over all possible subpopulations. However, it is only feasible for small populations. For more realistic settings, simulated annealing clearly outperforms gradient algorithms with only a limited increase in computational load. Our novel LL approach can handle very involved coding scenarios despite its computational ease. Comparison with existing methods Spike train distances have been extended to the analysis of neural populations interpolating between SP and LL coding. This includes parametrizing the importance of distinguishing spikes being fired in different neurons. Yet, these approaches only consider the population as a whole. The explicit focus on subpopulations render our algorithms complimentary. Conclusions The spectrum of encoding possibilities in neural populations is broad. The SP and LL cases are two extremes for which our algorithms provide correct identification results. -- Institute for complex systems, CNR Via Madonna del Piano 10 50119 Sesto Fiorentino (Italy) Tel: +39-349-0748506 Email: thomas.kreuz(a)cnr.it Webpage: http://www.fi.isc.cnr.it/users/thomas.kreuz/

Nov. 26, 2018