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Opening: Postdoctoral Researcher in Computational Neuroscience to study network dynamics, brain function, and psychedelics
by Joern Davidsen June 16, 2021

June 16, 2021

Dear all: We are recruiting a talented postdoctoral researcher to participate in a cutting-edge International Network for Brain-Inspired Computation<https://www.nsf.gov/awardsearch/showAward?AWD_ID=2019976&HistoricalAwards=f…> that includes nodes in Montreal, Paris, and the Pacific Northwest of the US and Canada (e.g. University of Washington, Allen Brain Institute). The project is at the intersection of mathematics, physics, and neuroscience in the general area of complex network dynamics and emergent activity patterns and representations that drive biological computation. The specific objective is to understand cognitive brain function and the effects of psychedelics by analyzing large-scale ensemble neural data collected in our labs, in conjunction with computational and/or analytical work to identify key mathematical principles and develop theories of core function. The ideal candidate will have a quantitative background (e.g. PhD in mathematics, physics, computer science) along with experience in applying this background to neuroscience. This postdoctoral position is partially funded by the Pacific Institute for Mathematical Sciences<https://www.pims.math.ca/> and is aimed to strengthen the link between the Campus Alberta computational neuroscience community at the University of Calgary (Complexity Science Group<https://www.ucalgary.ca/complexity/>, Hotchkiss Brain Institute<https://hbi.ucalgary.ca/>) and the University of Lethbridge (Canadian Center for Behavioural Neuroscience<https://www.uleth.ca/artsci/neuroscience/about>) with the other network members including the Computational Neuroscience Center<https://cneuro-web01.s.uw.edu/> at the University of Washington. The position is open immediately with primary locations in either Calgary or Lethbridge. The specific start date has to be within five years of being awarded a PhD degree. The position is funded for at least two years and includes an annual stipend in the range of CAD$42,000 – $50,000 plus benefits. Opportunities for brief residences in partner nodes (Montreal, Seattle, or Paris) are also available. Interested candidates should submit their application package including a cover letter, their CV with a list of publications, brief statement of research interests and their possible start dates in PDF format to Dr. Jörn Davidsen (davidsen(a)phas.ucalgary.ca<mailto:davidsen@phas.ucalgary.ca>) and Dr. Aaron Gruber (aaron.gruber(a)uleth.ca<mailto:aaron.gruber@uleth.ca>). Applicants should arrange for at least two letters of reference to be sent as well. Review of applications will begin July 31st, 2021, and continue until the position is filled. For additional information and informal inquiries, please contact Dr. Davidsen or Dr. Gruber. We strive for a diverse and inclusive environment, and encourage applications from members of any identity. --- Dr. Jörn Davidsen Professor of Physics & Humboldt Research Fellow University of Calgary www.ucalgary.ca/davidsen<http://www.ucalgary.ca/davidsen>

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PostDoc position in Neuroinformatics, Nijmegen, The Netherlands
by Rembrandt Bakker June 16, 2021

June 16, 2021

(apologies for any cross-postings) The FLAG-ERA project NeuronsReunited is looking for a postdoctoral research associate (Neuroinformatics/Computational Neuroscience) for a 2 year position at 0.9 fte. Each mental event or voluntary motor act involves the coordinated activity of neurons in areas of the brain far apart. Thin, branched and extremely long cellular processes called axons provide the physical substrate of these interactions. Since a few years it is possible to fully trace these long- range axons one at a time. The goal of the FlagERA research project "NeuronsReunited" (https://www.flagera.eu/wp-content/uploads/2020/06/FLAG-ERA_JTC2019_HBP_Neur…) is to create tools for speeding up the conversion of experimental data into digital axons, and to precisely place neurons into a digital reference brain to reveal their context. The tools are applied to existing and new data in mouse, and the resulting insights are incorporated into new models for brain function. The project is a collaboration between five international partners, two experimental partners (Prof. Francisco Clasca, Madrid; Prof. Egidio d'Angelo, Pavia) and three computational/theoretical partners (Prof. Paul Tiesinga, Dr. Rembrandt Bakker, Nijmegen; Prof. Michele Giugliano, Trieste; Prof. Sacha Van Albada, Jülich). As a postdoctoral research associate you will design strategies to get axonal arbors precisely registered in a brain atlas. The brain atlas consists of high-resolution 3d dataset that represents the average mouse brain anatomy, while the neuron consists of a vector representation of its morphology that can be extended with images of selected tissue sections. Depending on your field of expertise, further steps can focus on automating the process to trace neurons from stained tissue sections or to integrate the resulting database of precisely registered neurons with other data modalities to generate new knowledge. You will be part of a team that deals with atlasing and data integration (Nijmegen) and model building (Jülich, Padova, Trieste). A key deliverable will be the creation of a gold standard online catalog of precisely placed neurons that future generations of neuroscientists can contribute to and compare data to. The tools make use of an existing body of work that consists of web-based applications: HBP Morphology Viewer (https://neuroinformatics.nl/HBP/morphology-viewer) Scalable Brain Atlas (https://scalablebrainatlas.incf.org/) and interactive notebooks (Python). Besides being a member of the project team, you will also be part of the European Human Brain Project and have access to the expertise of the large neuroscience community at the Donders Institute for Brain, Cognition and Behavior. We ask: • A PhD degree in a quantitative field (engineering, physics, computational neuroscience, etc). • Expertise in neuroscience or interest in acquiring it. • Excellent programming skills, preferably in JavaScript applications or Python-based pipelines. • Experience with neuroinformatics, visualization/3d-graphics, image processing, and/or machine learning. • Demonstrated ability to work in a multidisciplinary environment at the forefront of science. • Excellent communication skills in spoken and written English. We are: The Donders Institute for Brain, Cognition and Behaviour, home to more than 600 researchers from 35 countries, is a world-class research centre devoted to understanding the mechanistic underpinnings of human cognition and behaviour in health and disease. The institute's mission includes conducting excellent interdisciplinary research at the unique interface between genetic, molecular and cellular processes at one end and computational, system-level neuroscience with cognitive and behavioural analysis at the other end. Within this playing field, the Neuroinformatics department plays an essential role in developing new approaches for both computational modeling and data processing, all with the aim to turn raw data into highly valuable and well-integrated resources from which neuro-scientific insights can be extracted. Radboud University We want to get the best out of science, others and ourselves. Why? Because this is what the world around us desperately needs. Leading research and education make an indispensable contribution to a healthy, free world with equal opportunities for all. This is what unites the more than 22,000 students and 5,000 employees at Radboud University. And this requires even more talent, collaboration and lifelong learning. You have a part to play! We offer: • Employment: 0.9 FTE. • A maximum gross monthly salary of € 4,402 based on a 38-hour working week (salary scale 10). • The exact salary depends on the candidate's qualifications and amount of relevant professional experience. • In addition to the salary: an 8% holiday allowance and an 8.3% end-of-year bonus. • Duration of the contract: 25 months. • The intended start date is 1 September 2021. • You will be able to use our Dual Career and Family Care Services. Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen. • Have a look at our excellent employment conditions. They include a good work-life balance (among other things because of the excellent leave arrangements), opportunities for development and a great pension scheme. Apply directly Please use this link to apply: https://www.ru.nl/english/working-at/vacature/online-solliciteren/?tk=uk&re…. Address your application to Paul Tiesinga and submit it no later than 1 July 2021. Your application should include the following attachments: • Letter of motivation. • CV including contact details of two references. • Your research statement. The first round of interviews will take place on 6th July 2021. The second round of interviews will take place on 13th July 2021. For more information about this vacancy, please contact: Paul Tiesinga, Full Professor Tel.: +31 24 365 22 32 Email: p.tiesinga(a)science.ru.nl<mailto:p.tiesinga@science.ru.nl> Rembrandt Bakker, Postdoctoral Researcher Tel.: +31 24 365 26 33 Email: r.bakker(a)donders.ru.nl<mailto:r.bakker@donders.ru.nl> ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Volker Rieke Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Dr. Astrid Lambrecht, Prof. Dr. Frauke Melchior ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------

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Postdoctoral position - Pinto Lab @ Northwestern University
by Lucas Pinto June 15, 2021

June 15, 2021

Dear colleagues, The Pinto Lab<http://www.pintolab.org> is seeking a postdoc who is excited about studying how neural circuits across many brain areas interact to support decision making, at the interface between experimental and computational neuroscience. In particular, the lab is interested in understanding the circuit mechanisms the control how these interactions are flexibly reconfigured when animals make decisions that use different underlying computations. To answer these questions, the candidate will use a combination high-throughput behavior in virtual reality, optical and genetic tools to measure and/or manipulate the dynamics of single neurons and neuronal populations, and computational approaches to understand both the behavior and its relationship to neural activity. We are a brand new lab that started in January 2021 at the Feinberg School of Medicine<https://www.feinberg.northwestern.edu/> at Northwestern University<http://www.northwestern.edu>, located in the heart of Chicago. Come join a vibrant neuroscience community<https://www.nuin.northwestern.edu/> in a world-class and highly livable city, working with a young PI committed to mentoring. Please visit our website<http://www.pintolab.org> for more details. Applicants should be nearing completion or already hold a PhD in neuroscience, biology, engineering, computer science, psychology or other related fields. Coding and/or experimental skills are preferred, but the applicant will have the opportunity to be trained in these techniques. We strongly encourage candidates from underrepresented groups to apply. Please send a CV, a one-page statement of research interests and skills, and contact information for 2-3 references to Lucas Pinto at lucas.pinto(a)northwestern.edu<mailto:lucas.pinto@northwestern.edu>. Best, Lucas - - - - - - - - - - - - - - - - - - - - - - - - - - - Lucas Pinto, M.D., Ph.D. Assistant Professor Department of Physiology Feinberg School of Medicine Northwestern University lucas.pinto(a)northwestern.edu<mailto:lucas.pinto@northwestern.edu> www.pintolab.org

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NEST Conference 2021 — Registration Deadline 21 June
by Hans Ekkehard Plesser June 15, 2021

June 15, 2021

Dear all, Just a little reminder that the registration deadline for the NEST Conference 2021 is on Monday next week, June 21. More information on the programme and how to register can be found on the conference website https://nest-simulator.org/conference This year's conference will again take place as a virtual conference on Monday/Tuesday 28/29 June 2021 followed by a virtual NEST User Hackathon until Friday 2 July. The NEST Conference provides an opportunity for the NEST Community to meet, exchange success stories, swap advice, learn about current developments in and around NEST spiking network simulation and its application. We are looking forward to seeing you all! Hans Ekkehard Plesser & many more -- Prof. Dr. Hans Ekkehard Plesser Head, Department of Data Science Faculty of Science and Technology Norwegian University of Life Sciences PO Box 5003, 1432 Aas, Norway Phone +47 6723 1560 Email hans.ekkehard.plesser(a)nmbu.no<mailto:hans.ekkehard.plesser@nmbu.no> Home http://arken.nmbu.no/~plesser

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INCF/OCNS Software WG Dev session on SciUnit/NeuronUnit (June 21, 1600 UTC)
by Ankur Sinha June 14, 2021

June 14, 2021

Dear all, Apologies for the cross posts. The INCF/OCNS Software WG[1] is happy to announce the next Dev Session where members of the developer teams of commonly used neuroscience software introduce their software and then discuss their *development* pipelines. ---- In the next Dev Session, Rick Gerkin will introduce the SciUnit framework and discuss its development: https://ocns.github.io/SoftwareWG/2021/06/04/dev-session-rick-gerkin-sciuni… The session will be held at June 21, 2021, 1600 UTC over Zoom: https://ucl.zoom.us/j/91246735902?pwd=WVdVK3I5SGdlaDFZdllDQ0w2djVBdz09 Click here to see the event in your local time: https://www.timeanddate.com/worldclock/fixedtime.html?msg=Dev+session%3A+Ri… SciUnit is a discipline-agnostic framework for model validation, handling all of the testing workflow by using a implementation-independent interface to models. SciUnit also contains code for visualization of model results, and command line tools for incorporating testing into continuous integration workflows. SciUnit is used in model validation in neuroscience via NeuronUnit, which implements an interface to several simulators and model description languages, handles test calculations according to domain standards, and enables automated construction of tests based on data from several major public data repositories. ------- The aim of these sessions is to stimulate discussion of the development practices and tools used by different teams to improve the software we use while also improving our knowledge of these practices and tools. We also hope to encourage more users of these tools to contribute to their development to ensure their longevity. If you develop software for neuroscience, we would love to hear about your development pipeline. Please get in touch with the Software WG on our communication channels[2]. The WG is a community based group that is open to everyone at all levels of their careers (academic or otherwise). Please introduce yourself to the community on our channels to get involved. [1] https://ocns.github.io/SoftwareWG/ [2] https://ocns.github.io/SoftwareWG/pages/contact.html On behalf of the Software WG, -- Thanks, Regards, Ankur Sinha (He / Him / His) Research Fellow at the Silver Lab | http://silverlab.org/ Department of Neuroscience, Physiology, & Pharmacology University College London, London, UK Time zone: Europe/London

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Postdoc on Alzheimer's Disease modeling (Inria, UCL, BCAM)
by desroche June 14, 2021

June 14, 2021

Dear all, This is an invitation to join a multidisciplinary research on Alzheimer’s Disease (AD) for a 24-month postdoc. The project aims at combining mathematics and novel experiments to better understand the causes of the progressive symptoms of memory impairment in persons living with AD. Despite progress, AD research has hit a bottleneck and to date there are no effective treatments to prevent AD. It is now recognised that this is partially due to limitations in AD mice models that do not recapitulate human AD, to conflicting results and research focus on molecular mechanisms. We aim to overcome these limitations by exploring a gab in our understading of abnormal synaptic process (including neural-glia, inflammatory processes) and neural tissue dynamics that lead to AD. To this end, we will combine state-of-the-art experiments based on human brain tissue data, recent mice model that recapitulate human AD, mathematics and computations, which in tandem will address the multi-factorial nature of the disease for future successful drug development. The project is part of a long-standing collaboration between Mathieu Desroches (MathNeuro Project-Team, Inria Sophia Antipolis, France), Serafim Rodrigues (MCEN research group, Basque Center for Applied Mathematics, Bilbao, Spain) and Afia B Ali (School of Pharmacology, University College London, UK) on neurotransmission and its possible disruptions (see here <https://www.pnas.org/content/113/8/E1108.short>). The postdoc will strongly interact with these three researchers. Regarding profiles that we are seeking, familiarity of the candidate with mathematical modeling in Neuroscience. Experience with multiple-timescale systems is wishable but not mandatory. Ability and willingness to do programming, as well as analyse experimental data, will also be a strong point to select candidates. Please apply online via the following page: https://recrutement.inria.fr/public/classic/fr/offres/2021-03775 <https://recrutement.inria.fr/public/classic/fr/offres/2021-03775> For informal enquiries, please contact me: mathieu.desroches(a)inria.fr <mailto:mathieu.desroches@inria.fr> --------------------------------------------------------------------- Dr. Mathieu Desroches Research Scientist (Chargé de Recherche) MathNeuro Project Team Leader <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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CFP Workshop on Spatio-temporal Aspects of Embodied Predictive Processing @ ICDL2021
by Stefan Heinrich June 14, 2021

June 14, 2021

Call For Contributions - Workshop on Spatio-temporal Aspects of Embodied Predictive Processing @ IEEE ICDL2021 Aims and Scope: Understanding human intelligence and building strong AI systems is a key challenge for our generation. A particularly puzzling aspect is that the human brain seems to cope very well with the highly variable and uncertain nature of perception and action, regarding both their signal characteristic and how they extend over time. Furthermore, it seems apparent that the information processing in the brain always involves previous bodily experiences and all our senses, thus is embodied and crossmodal. For explaining these characteristics, there are strong accounts that the brain is constantly predicting sensory input and feedback while minimising free energy in the prediction and is hierarchically abstracting the perception as well as hierarchically composing action. Furthermore, it is also hypothesised that mechanistic priors in the brain’s information processing induce a failure of hierarchical inference in the brain, accounting for atypical perception and action of psychiatric disorders. For example, some brains might have developed to focus too strongly on current sensory input while others might focus too strongly on memorised previous experience. A typically developed brain, in contrast, would show a fine balance compared to these two extreme priors. The big open mystery is: how is the brain developing this on a mechanistic level and thus how can this get learned within an AI system? Thus, to lift this mystery, we further need to bring together research from computational neuroscience, cognitive psychology, and artificial intelligence. With this workshop, we particularly want to wrap up different recent hypotheses, models, and experiments and discuss in-depth how to shape future imaging, behavioural, and developmental robotics studies as a complement to computational modelling and bio-inspired artificial intelligent algorithms. As a guiding theme, we aim to approach the following central questions: - How does the brain learn spatio-temporal stochasticity in perception and action? - What is the role of priors in learning spatio-temporal adaptive prediction? - How can developmental robotics help us to study spatio-temporal stochasticity as an analogy to infant learning? We examine these questions with the insight from invited key speakers from complementary fields as well as original contributions in breakout sessions in order to conclude the next steps within in a panel discussion. All information online: https://sites.google.com/view/stepp21/home Keynotes/Panellists: - Jun Tani, Cognitive Neurorobotics, Okinawa Institute of Science and Technology (OIST) - Marcel van Gerven, Artificial Cognitive Systems, Donders Institute, Radboud University - Takuya Isomura, Brain Intelligence Theory, RIKEN Center for Brain Science - Takamitsu Watanabe, Brain Network Dynamics, International Research Center for Neurointelligence (IRCN), The University of Tokyo Contributions: We invite submissions of extended abstracts on ongoing research that focuses on one or several of our guiding questions as contributions. In addition to the live presentation and discussion during the workshop, the contributions will be made public in workshop proceedings. - Extended abstract submission deadline: 11.07.2021 - Decision & Notification: 25.07.2021 - Camera-ready version due: 08.08.2021 - Workshop online: 22.08.2021 Submission website: https://sites.google.com/view/stepp21/ => Contribute Organisers: Stefan Heinrich, IRCN, The University of Tokyo, Japan Shingo Murata, Dept. Electronics and Electrical Engineering, Keio University, Japan Yukie Nagai, IRCN & Institute for AI and Beyond, The University of Tokyo, Japan Yuichi Yamashita, National Center of Neurology and Psychiatry, Japan -- ************************************************************* Dr. Stefan Heinrich Postdoctoral Project Researcher Cognitive Developmental Robotics Lab The University of Tokyo, Institutes for Advanced Studies, International Research Center for Neurointelligence Email: heinrich.stefan(a)ircn.jp https://developmental-robotics.jp/en/members/stefan_heinrich/ https://ircn.jp/en/ https://stefanheinrich.net/ *************************************************************

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Multiple postdoctoral openings in reinforcement learning in multi-scale brain networks at Washington University in St. Louis
by Ching, ShiNung June 14, 2021

June 14, 2021

Multiple postdoctoral openings in modeling reinforcement learning in multi-scale brain networks at Washington University in St. Louis Multiple postdoctoral openings are available for a new and large, multi-PI project to study the circuit underpinnings of reinforcement learning and decision-making. A key focus is on understanding multiple time-scales of information processing in neural circuits and involvement of neuron-astrocyte interactions. Experiment- and theory-forward positions are available. Applicants should have prior experience in neuroscience (computational or otherwise), modeling of large-scale systems, optimization, machine learning or related areas. Positions will be cross-appointed between Engineering and Neuroscience. Washington University in St. Louis is an independent, Research 1 university in St. Louis, MO, USA, with nearly 60 of the university's graduate and undergraduate programs ranked in the top 25 by US News & World Report. www.wustl.edu Interested applicants are invited to send a CV and brief description of interests to ShiNung Ching: shinung(a)wustl.edu

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EITN Seminar: Paul Miller (Brandeis U, Waltham MA, USA) - Friday 18 June 16:00
by Zélie Tournoud June 14, 2021

June 14, 2021

Dear colleagues, We are pleased to welcome *Paul Miller* from Brandeis University (Waltham MA, USA) for an online seminar this week. It will take place on Zoom on *Friday 18 June at 16:00* CEST (Paris time). *Title**: **Information processing in neural circuits with multiple quasi-stable attractor states* *Abstract: *Circuits containing clusters of neurons with strong within-cluster excitatory connections and random between-cluster connections can possess multiple activity states, with each state defined by the set of clusters with stably high versus low neural firing rates. Noise or adaptive processes can render the states quasi-stable such that in the presence of constant input, or following successive identical inputs, the network can progress through a sequence of different activity states. Here we study the properties of such models, including the role of finite size effects in producing multistability in networks with Gaussian random cross-coupling, and we assess the extent to which such state sequences might subserve information processing and behavior in a range of cognitive tasks. Join on the day on the event at: > Topic: EITN seminar: Paul Miller (Brandeis University) > Time: 18 June 2021 04:00 PM Paris (CEST) > Join Zoom meeting: > https://zoom.us/j/99754103845?pwd=UGlHSjgySTBXeUtvSW5SVUVMRnFiZz09 > <https://zoom.us/j/99754103845?pwd=UGlHSjgySTBXeUtvSW5SVUVMRnFiZz09> > Meeting ID: 997 5410 3845 > Password: 634477 We look forwards to see you at the seminar. Kind regards, The EITN Team

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Adaptive Machines: Leveraging Neuroscience for Lifelong Learning Systems
by Andrea Soltoggio June 14, 2021

June 14, 2021

Dear Connectionists, I’d like to bring your attention to the Research Topic “Adaptive Machines: Leveraging Neuroscience for Lifelong Learning Systems” to be co-hosted by Frontiers in Neuroscience, Robotics and AI, Big Data, Artificial Intelligence, Neurorobotics and Computational Neuroscience. The article submission deadline is the 30th of September. Link: https://www.frontiersin.org/research-topics/20053/adaptive-machines-leverag… Description: Artificial intelligence has always sought inspiration in the brain. Artificial neural networks (ANNs), in particular, were modeled after their biological counterparts (biological neural networks, BNNs). However, state-of-the-art deep networks are drastically different from BNNs. Their architectures (at both the single-neuron and macro levels), learning algorithms, and failure conditions share little in common with brain circuit dynamics. In particular, state-of-the-art deep learning is optimized for single, well-defined, static tasks. Deep networks struggle to learn multiple or evolving tasks over time (i.e., continual learning) or to adjust their processing based on environmental conditions. They are also less modular than BNNs, and thus less energy efficient, and utilize little-to-no feedback signals. We believe that deep networks suffer from these limitations because their modeling of brain dynamics is too superficial. Modeling more sophisticated neural mechanisms is therefore key for deep networks to achieve continual or lifelong learning and to cope with open-ended, dynamic environments. The goal of this Research Topic is to publish novel models and/or algorithms that expand the capabilities of deep learning (e.g., achieve better continual learning) by incorporating additional properties of BNNs. We are also interested in neuroscience research that elucidates mechanisms that can be leveraged by the AI community. Neuroscience has uncovered a wide range of learning and regulatory mechanisms, at scales ranging from single molecules to the entire nervous system, that help the brain learn, remember, and adapt. These include replay (systems-level consolidation), neuromodulation, neurogenesis, neuroevolution, attention, homeostatic plasticity, and synaptic consolidation. There exist some deep learning techniques motivated by these mechanisms (e.g., experience replay or attention networks), but they have rarely been used for lifelong learning. As such, our focus will be on approaches that leverage brain-like principles---ideally biologically well-grounded---to solve problems currently beyond the capabilities of the state of the art. We will also welcome neuroscience research that helps to elucidate the brain’s mechanisms, in the hope that they can be used by the next generation of machine learning models. The scope of this Research Topic covers: (1) biologically inspired techniques in deep learning (2) neuroscience research on how the brain facilitates learning and adapts to different contexts We seek to address continual or lifelong learning, transfer learning, and other ML scenarios that go beyond the traditional, train-then-test learning paradigm. Since machine learning is an experimental field, a paper must include experimental results to be accepted; however, we encourage authors to include theoretical analyses of their methods. We aim to collect the following types of manuscripts: Original Research and Brief Research Reports. Since the goal of this Research Topic is to publish highly novel, experimentally grounded work, we are not interested in Reviews (Systematic, Policy and Practice, etc.), General Commentaries, or Opinions. In addition, since the editorial board does not include medical experts, we cannot accept Clinical Trials or Study Protocols. The Research Topic will be edited by Rolando Jose Estrada, Georgia State University, USA Andrea Soltoggio, Loughborough University, UK Praveen K. Pilly, HRL Laboratories, USA Vincenzo Lomonaco, University of Pisa, Italy, Davide Maltoni, University of Bologna, Italy. Please consider submitting your original research to this Research Topic. Do not hesitate to get in touch if you wish to discuss your contribution. Best wishes, Andrea -- Dr. Andrea Soltoggio (he/him or they/them) Senior Lecturer (Associate Professor) in Artificial Intelligence Department of Computer Science, School of Science & Intelligent Automation Centre https://www.intelligent-automation.org.uk/about-us/centre-staff & Centre for Information Management https://www.lboro.ac.uk/departments/sbe/cim/ Haslegrave Building, N.2.03 Loughborough University LE11 3TU, UK Email: a.soltoggio(a)lboro.ac.uk<mailto:a.soltoggio@lboro.ac.uk> Web: http://www.lboro.ac.uk/departments/compsci/staff/dr-andrea-soltoggio.html

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