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Brain Dynamics Toolbox for Matlab
by Stewart Heitmann March 23, 2018

March 23, 2018

Dear all, The Brain Dynamics Toolbox (http://www.bdtoolbox.org <http://www.bdtoolbox.org/>) is open-source software for simulating dynamical systems in neuroscience. It is for researchers and students who wish to explore mathematical models of brain function using Matlab. It includes a graphical tool for simulating dynamical systems in real-time as well as command-line tools for scripting large-scale simulations. Custom systems of differential equations can typically be defined in less than 100 lines of standard matlab code. The graphical interface is designed to be used as both a research tool and a teaching tool. Its hub-and-spoke architecture allows new combinations of numerical solvers and interactive plots (time plots, phase plots, bifurcation diagrams, space-time plots, etc) to be applied to any model with no additional programming effort. Version 2018a of the Brain Dynamics Toolbox has just been released and is available from http://www.bdtoolbox.org <http://www.bdtoolbox.org/> The Handbook for the Brain Dynamics Toolbox is available from https://www.amazon.com/dp/198057250X <https://www.amazon.com/dp/198057250X> The toolbox will be featured at the at the Australian Connectomics School (ACS-2018) in Melbourne, 30 May to 1 June 2018. Best Regards Stewart Heitmann & Michael Breakspear QIMR Berghofer Medical Research Institute Systems Neuroscience Group

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Now hiring: The Krembil Centre for Neuroinformatics, CAMH - Toronto, Canada
by Sean Hill March 22, 2018

March 22, 2018

The Krembil Centre for Neuroinformatics (www.krembilneuroinformatics.ca<http://www.krembilneuroinformatics.ca>) based at CAMH (www.camh.ca<http://www.camh.ca>), and fully affiliated with the University of Toronto, Canada, is hiring world-leading specialists to transform our understanding of mental health by organizing, integrating, analyzing, visualizing and modelling data across all levels of the brain —from genes to circuits to behaviour. This multimodal data is gathered across the clinical environment including genetic, epigenetic, MRI, DTI, fMRI, hd-EEG, actigraphy and electronic medical record data. Teams will employ state-of-the-art techniques including topological data analysis, machine learning and multiscale computational modeling to accelerate identification and treatment of mental health disorders. Research is performed in an open, team science environment, with an emphasis on reproducible data-driven research and a patient-centric approach. A focus on global collaboration is key to transforming our understanding of mental health and its treatment. The centre will operate as an incubator for medical technologies to identify, manage and treat mental illness, while shaping policy at national and global levels. The centre is expanding with the following openings (see http://krembilneuroinformatics.ca/apply for full details and to apply): *Independent Scientist for Computational Genomics The Independent Scientist for Computational Genomics will build and lead a team of talented bioinformatics researchers, computational biologists, and computer scientists who employ and develop state-of-the-art genetic, epigenetic and transcriptomic analyses and predictive models to provide new insights into mental health and brain disorders in a data driven way, making outcome predictors and identifying optimal intervention opportunities. *Independent Scientist for Brain Circuit Modelling The Independent Scientist for Brain Circuit Modelling will build and lead a team responsible for the development, simulation and analysis of dynamic and perturbable computational models of biophysically detailed brain circuitry (for both preclinical and human brains), integrating genetic, epigenetic and transcriptomic data, and ion channel, cellular and synaptic biophysics. The team will work in close collaboration with other groups involved in detailed biophysical modeling, e.g. the Blue Brain Project and Allen Institute for Brain Science. The team will also be responsible for curating and maintaining data, literature and models to enable data-driven modeling of brain circuitry in health and disease, in addition to the concurrent construction of atlases, development of analysis approaches and identification of biomarkers to define mental health and brain disorders in a data driven way, such as aberrant dynamical processes. *Independent Scientist for Whole Brain Modelling The Independent Scientist for Whole Brain Modelling will build and lead a team responsible for the development of dynamic and perturbable causal models of the human brain, in health and in the context of mental illness, incorporating multi-modal neuroimaging and expression data including, but not limited to, structural, functional, diffusion and spectrometry MRI, PET/CT and EEG. The team will also be responsible for the concurrent construction of atlases, development of analysis approaches and identification of biomarkers to define mental health and brain disorders in a data driven manner. *Independent Scientist for Whole Person Modelling The Independent Scientist for Whole Person Modeling will build and lead a team responsible for the development and application of predictive modeling approaches for individual citizen, patient and population trajectories and outcomes. This includes tools, pipelines and approaches for the exploration, visualization and analysis of complex high-dimensional data, with the aim of the data-driven definition of mental health and brain disorders, and the establishment of outcome predictors and identification of optimal intervention opportunities. *Independent Scientist for Brain and Health Knowledge Management The Independent Scientist for Brain and Health Knowledge Management will build and lead a team responsible for organizing and disseminating data, models and literature related to the definition and treatment of mental health disorders to support both researchers and clinicians. This team will maintain and curate ontologies of brain disorders and link to data, analyses, visualizations, literature and models supporting their definition. This clinical support platform will support reasoning and inference across definitions and datasets to bridge psychiatric and neurological disorders. *Knowledge Engineering Lead The Krembil Centre for Neuroinformatics is launching a knowledge engineering initiative to structure and map vast quantities of clinical and research data into a unified schema and develop a knowledge graph. This initiative will lay the technical foundation to support supervised and unsupervised content discovery, enable data mining, and facilitate interactive modes of engagement with our data corpus. A new Knowledge Engineering team is being established to spearhead the implementation of this initiative. This is a unique opportunity to partner with world-class researchers in the creation of unprecedented knowledge discovery tools. *Brain Imaging Data Engineer The Brain Imaging Data Engineer role will be accountable for managing and enhancing the solution for collecting, storing, curating and integrating brain imaging data sets across the organization, including, but not limited to the following modalities: MRI, PET and EEG. You will work closely with the senior architects on the technology team as well as collaborating with scientific leads. You will be accountable to evolve the technology solution to keep up with industry changes to ensure the solution remains optimal. *Molecular Data Engineer The Molecular Data Engineer role will be accountable for managing and enhancing the solution for collecting, storing, curating and integrating molecular data sets across the organization. You will work closely with the senior architects on the technology team as well as collaborating with scientific leads. You will be accountable to evolve the technology solution to keep up with industry changes to ensure the solution remains optimal. *Senior Project Manager – BrainHealth Databank The Senior Project Manager will work with multiple stakeholders both internal and external to CAMH and be responsible for the hands-on leadership and oversight for the development and execution of work plans, accountabilities, and timelines associated with the BrainHealth Databank initiative. The BrainHealth Databank platform will be specifically designed to support multidimensional phenotyping studies that combine digital phenotyping and laboratory-based data across existing and future clinical studies at CAMH. All data will be organized within the knowledge graph of the BrainHealth Databank. The platform will support configuration of studies that integrate common data elements and CRFs, wearable and mobile devices, voice samples, electronic medical record (EMR) extracts, outcome assessments and health care system usage. CONFIDENTIALITY NOTICE: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. AVIS DE CONFIDENTIALITÉ : Ce message électronique, ainsi que tout fichier qui y est joint, est reserve à l'usage exclusif du destinataire visé et peut contenir des renseignements confidentiels et privilégiés. Toute lecture, utilisation, divulgation ou distribution non autorisée est interdite. Si vous n'êtes pas le destinataire visé, veuillez en aviser l'expéditeur par retour de courriel et détruire toutes les copies du message original.

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CFP, Special session - Hybrid Life: Approaches to integrate biological, artificial and cognitive systems, ALife 2018
by Manuel Baltieri March 21, 2018

March 21, 2018

[Apologies for cross-posting] ********** Call for Papers ********** Special session - Hybrid Life: Approaches to integrate biological, artificial and cognitive systems https://sites.google.com/view/hybrid-life/ <https://sites.google.com/view/hybrid-life/> 2018 Artificial Life conference (ALife) Tokyo, JAPAN, 23-27 July 2018 - http://2018.alife.org/ <http://2018.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 19th March 2018 – Paper submission deadline 23rd April 2018 – Paper acceptance notification 21st May 2018 – Camera-ready version 23-27th July 2018 – Artificial Life conference (ALife), Tokyo, Japan 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. m.baltieri(a)sussex.ac.uk <mailto:m.baltieri@sussex.ac.uk> Keisuke Suzuki, University of Sussex, Brighton, UK. k.suzuki(a)sussex.ac.uk <mailto:filippo.m.bianchi@uit.no> Hiryuki IIzuka, Hokkaido University, Sapporo, Japan hiroyukiiizuka(a)gmail.com <mailto:hiroyukiiizuka@gmail.com> Contacts For questions, enquiries and more information please check our website https://sites.google.com/view/hybrid-life/ <https://sites.google.com/view/hybrid-life/> or get in touch with m.baltieri(a)sussex.ac.uk <mailto:m.baltieri@sussex.ac.uk>. All the best, -- Manuel Baltieri, EASy group Department of Informatics, University of Sussex, UK Twitter: @manuelbaltieri

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Abstract submission for Neuroinformatics 2018 in Montréal, Canada is open!
by congress March 21, 2018

March 21, 2018

Dear all, Abstract submission for Neuroinformatics 2018 in Montréal, Canada on August 9-10 is now open! The annual INCF Congress provides a meeting place for researchers in all fields related to neuroinformatics. Join us for keynotes from top neuroscientists, community sessions and poster- and demo sessions. Neuroinformatics 2018 will be a great opportunity to introduce new participants to the field of neuroinformatics and highlight new and innovative tools and approaches. Providing a forum for infrastructure providers and developers of tools, standards, and best practices to help define the capabilities of the global network, receive training on how to participate in the Open, FAIR and Citable global network and learn how to provide better services to their constituents. *Abstract submission deadline is April 30: **neuroinformatics2018.org/abstracts <http://neuroinformatics2018.org/abstracts>* Registration will open shortly. More information: *neuroinformatics2018.org <http://www.neuroinformatics2018.org>* Please spread this information to anyone you feel would be interested in attending. *The International Neuroinformatics Coordinating Facility (INCF) is an international non-profit organization devoted to advancing the field of neuroinformatics and global collaborative brain research. Learn more about INCF www.incf.org <http://www.incf.org/>* *We look forward to seeing you in Montréal!* Best Regards The INCF Secretariat <http://www.neuroinformatics2018.org> <http://www.neuroinformatics2018.org>

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DynaSim: A MATLAB/GNU Octave Toolbox for Neural Modeling and Simulation
by Jason Sherfey March 20, 2018

March 20, 2018

Dear Colleagues, We are happy to announce the release of DynaSim, an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It was designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments; it is the first, comprehensive neural modeling and simulation platform developed in MATLAB. It provides C compilation, optimized vector calculations, multi-core processing, and support for compute clusters to overcome the traditionally slow simulation speeds of MATLAB. It is also available for high performance computing via the Neuroscience Gateway web portal. A paper introducing DynaSim was recently published in Frontiers in Neuroinformatics: https://www.frontiersin.org/articles/10.3389/fninf.2018.00010/full. Documentation is available online at http://dynasimtoolbox.org. We hope this tool reduces barriers for investigating dynamics in neural models, facilitates collaborative modeling, and complements other tools being developed in the neuroinformatics community. Most of all, we hope you find this toolbox useful! Please direct questions to the lead developer, Jason Sherfey < sherfey(a)mit.edu> or the user mailing list: https://groups.google.com/forum/#!forum/dynasim-users. Best regards, Jason Dr. Jason Sherfey Postdoctoral Research Fellow Psychological & Brain Sciences, Boston University Massachusetts Institute of Technology The Picower Institute for Learning & Memory http://JasonSherfey.com

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PhD/postdoc in Sensory and Behavioral Neuroscience, Gjorgjieva and Grunwald Kadow Labs in Frankfurt/Munich
by Gjorgjieva, Julijana March 20, 2018

March 20, 2018

Reminder and deadline extension: The labs of Julijana Gjorgjieva (Max Planck Institute for Brain Research, Frankfurt, Germany) and Ilona Grunwald Kadow at the TUM School of Life Sciences, Technical University of Munich, Germany invite applications for a fully-funded position (Postdoc or PhD student). We are looking for highly-motivated individuals with a strong quantitative background (in mathematics, physics, engineering, computer science, or related fields), experience in programming and data analysis, and a desire to develop cutting-edge experimental techniques. Previous background in neuroscience, imaging or behavioral analysis is a plus! The project will examine the neural basis of need and effort-based decision-making in a collaboration between the Gjorgjieva lab, which develops theoretical models of neural circuit processing, and the Grunwald Kadow lab, which studies neural circuits underlying sensory processing and decision making in animal models. The project aims to uncover circuit principles and behavioral readouts of motivation, persistence, and value perception as a function of internal state or experience (e.g. hunger). In particular, the Grunwald Kadow lab is collecting rich data sets of behavioral trajectories of single Drosophila flies as well as functional imaging data (i.e. multiphoton and light-sheet) of neuronal populations (e.g. modulatory neurons). The project will aim to develop advanced analysis techniques that extract key statistical features of the behavioral trajectories and imaging data, and build mathematical models that reproduce the data and make new predictions to be further tested experimentally. By combining behaviour, genetics and imaging, we will also develop neural circuit models that involve several brain areas, including sensory brain areas and higher cognitive regions of the fly brain (i.e. mushroom body). References: S. Sayin J. Gjorgjieva, I. C. Grunwald Kadow (2018). A neural circuit arbitrates between perseverance and reward in hungry Drosophila. BioRxiv doi.org/10.1101/259119<http://doi.org/10.1101/259119> J. Gjorgjieva, G. Drion and E. Marder (2016). Computational implications of biophysical diversity and multiple timescales in neurons and synapses for circuit performance. Curr Opin Neurobiol 37:44-52. Lewis L, Siju KP, Aso Y, Friedrich AB, Bulteel AJB, Rubin GM, Grunwald Kadow IC (2015). A higher brain circuit for immediate integration of conflicting sensory information in Drosophila. Current Biology PMID: 26299514, doi: 10.1016/j.cub.2015.07.015 Application: The position will be based at the Technical University of Munich, with frequent visits to the Max Planck Institute for Brain Research in Frankfurt, two of the most exciting and international cities in Germany. The application deadline has been extended to: April 15, 2018. Applicants will be considered until the position is filled. For further information please visit: http://www.cns.wzw.tum.de and http://www.neuro.wzw.tum.de or email gjorgjieva(a)brain.mpg.de and ilona.grunwald(a)tum.de. To apply, please email the following to: neuro(a)wzw.tum.de (ref. GGK application) 1. A curriculum vitae 2. A letter of motivation explaining your scientific interests, your strengths when working on a problem, why us etc. 3. Contact details for 2 referees 4. A written sample of scientific research, e.g. a manuscript, thesis, or code etc. ----------------------------------------- Julijana Gjorgjieva, PhD Research Group Leader Max Planck Institute for Brain Research Max-von-Laue-Str. 4, Frankfurt Assistant Professor of Computational Neuroscience Technical University of Munich, WZW Freising office: +49 69 850033 3600 http://cns.wzw.tum.de

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Cajal Course in Computational Neuroscience -- Deadline April 2
by Jakob Macke March 20, 2018

March 20, 2018

Dear colleagues, final reminder and line-up for the Cajal Computational Neuroscience Course in Lisbon this summer. We extended the deadline to April 2, so there is still time to apply! Best, Jakob Macke CAJAL COURSE IN COMPUTATIONAL NEUROSCIENCE 12 August - 1 September 2018, Champalimaud Centre for the Unknown, Lisbon, Portugal http://www.cccn.pt Applications deadline: 2 April 2018 (midnight, CET time) DIRECTORS • Joe Paton (Champalimaud Centre for the Unknown, Portugal) • Jakob Macke (TU Darmstadt & Research Center Caesar Bonn, Germany) • Christian Machens (Champalimaud Centre for the Unknown, Portugal) 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. More information on the course website, http://www.cccn.pt Apply here: http://www.fens.org/Training/CAJAL-programme/CAJAL-courses-2018/CCCN-2018/A… Contact address: Simone Zacarias, simone.zacarias(a)research.fchampalimaud.org Confirmed faculty: Matthias Bethge, University of Tübingen Kevin Briggman, Research Center Caesar, Bonn, Germany Megan Carey, Champalimaud Centre for the Unknown, Portugal Claudia Clopath, Imperial College London, UK Sophie Deneve, ENS Paris, France Rainer Engelken, Columbia University, US Julijana Gjorgjieva, Max Planck Institute for Brain Research, Germany Pedro Goncalves, Research Center Caesar, Bonn, Germany Michael Häusser, Wolfson Institute for Biomedical Research, University College London, UK Andreas Herz, Bernstein Center for Computational Neuroscience Munich, Germany Simon Laughlin, University of Cambridge, UK Gilles Laurent, Max Planck Institute for Brain Research, Germany Máté Lengyel, University of Cambridge, UK Jennifer Linden, UCL Ear Institute, UK Elliot Ludvig, Warwick University, UK Anthony Movshon, New York University, USA Maneesh Sahani, Gatsby Computational Neuroscience Unit, UCL, UK Cristina Savin, New York University, USA Jeffrey Taube, Dartmouth College, USA Eero Simoncelli, New York University, USA Tim Vogels, Oxford University, UK Byron Yu, Carnegie Mellon University, USA Jakob Macke www.mackelab.org

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postdoctoral positions in theoretical neuroscience at the Kavli Institute in Trondheim
by Yasser Roudi March 19, 2018

March 19, 2018

Postdoctoral positions in theoretical/computational neuroscience are available at the Kavli Institute for Systems Neuroscience/Centre for Neural Computation in Trondheim, Norway. The position(s) is a part of the Kavli Institute for Systems Neuroscience. The Centre for Neural Computation is a recently established centre of excellence funded for 10 years by the Norwegian Research Council. We offer an international and multidisciplinary environment in which creativity and scientific discourse is valued and stimulated. Through our widespread network of international collaborations, unique career possibilities are offered. See http://www.ntnu.no/cbm/ for detailed information. The position will be part of the group headed by Professor Yasser Roudi. The position/s will be for 2 years. The successful applicant will take part in mainly independent research in theoretical neuroscience and statistical inference within the Roudi group. The specifics of the projects are up to agreement and discussion and new and novel ideas are highly welcome. Developing models of grid cells and their interactions with hippocampus as well as analysis of neural data from these areas will be one possible directions of research that can be taken during the tenure of the position. For more Information and details about how to apply please see https://www.jobbnorge.no/ledige-stillinger/stilling/149615/post-doc-kavli-i…

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FENS Satellite Meeting on "Receptive Fields: Analysis, Models and Applications": 6 July 2018 - applications open
by Anthony Burkitt March 18, 2018

March 18, 2018

Dear Colleagues, I would like to draw your attention to the FENS Satellite Meeting on "Receptive Fields: Analysis, Models and Applications", to be held on 6th July 2018. Applications are open at the Workshop website: fenscibf2018.eventbrite.com.au<http://fenscibf2018.eventbrite.com.au> RECEPTIVE FIELDS: ANALYSIS, MODELS AND APPLICATIONS At this FENS satellite meeting, eight world-leading researchers will discuss the latest advances on the formation and analysis of visual receptive fields and place maps, bringing together insights and discoveries from around the world. Topics will include state-of-the-art experimental and computational approaches to receptive field analysis, visual pathways, place maps and adaptation to the statistics of the visual environment. KEYNOTE SPEAKERS: • Tatyana Sharpee SALK Institute, USA • Michael Ibbotson National Vision Research Institute, Australia • Yves Fragnac CNRS, France • Jose-Manuel Alonso State University of New York, USA • TR Vidyasagar University of Melbourne, Australia • Dirk Jancke Ruhr University, Germany • Elizabeth Zavitz Monash University, Australia • Simon Schultz Imperial College, UK MEETING DETAILS DATE: Friday, 6 July 2018 TIME: 9am – 5pm CEST / Germany (Berlin) Time VENUE: Hotel NH Collection Berlin Friedrichstraße, Friedrichstraße 96, 10117 Berlin, Germany COST: Early bird fee by 6 April 2018 - €30 ; Standard fee by 22 June 2018 - €50 ; Registration includes refreshments, lunch and snacks. REGISTER HERE URL: fenscibf2018.eventbrite.com.au<http://fenscibf2018.eventbrite.com.au> CONTACT Email: Tenille Ryan (tryan(a)aco.org.au<mailto:tryan@aco.org.au>)

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Failures of adaptively timed hippocampal learning during memory consolidation and Fragile X syndrome
by Grossberg, Stephen March 17, 2018

March 17, 2018

The following two articles model how failures of adaptively timed learning and incentive motivational support by hippocampus (i.e., failure of “time cells”) can cause clinical problems in memory consolidation and Fragile X syndrome: ***************** Franklin, D. J., and Grossberg, S. (2017). A neural model of normal and abnormal learning and memory consolidation: Adaptively timed conditioning, hippocampus, amnesia, neurotrophins, and consciousness. Cognitive, Affective, and Behavioral Neuroscience, 17, 24-76. http://link.springer.com/article/10.3758/s13415-016-0463-y This article explains and simulates the kinds of data that many cognitive neuroscientists have reported after the famous case of the amnesic patient HM; namely, how, after some learning occurs, early vs. late lesions of amygdala, hippocampus, or orbitofrontal cortex can cause very different memory consolidation problems. ***************** Grossberg, S., and Kishnan, D. (2018). Neural dynamics of autistic repetitive behaviors and Fragile X syndrome: Basal ganglia movement gating and mGluR-modulated adaptively timed learning. Frontiers in Psychology, Psychopathology. https://doi.org/10.3389/fpsyg.2018.00269. This article explains how Fragile X syndrome can be caused when mGluR-mediated adaptively timed hippocampal learning and support of motivated attention fail.

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