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- 7414 messages
CFP (Deadline, 1 Feb 2015): IEEE Computational Intelligence Magazine (CIM) Special Issue: “Computational Intelligence for Changing Environments"
by Dr Amir Hussain
CALL FOR PAPERS (Deadline: 1 Feb 2015) - With advance apologies for any
cross postings!
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE (CIM)
(http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=10207)
SPECIAL ISSUE (Nov 2015) ON "Computational Intelligence for Changing
Environments"
(http://www.cs.stir.ac.uk/~ahu/IEEE-CIM-CICE2015.pdf)
AIMS AND SCOPE:
Over the past decade or so, computational intelligence techniques have
been highly successful for solving big data challenges in changing
environments. In particular, there has been growing interest in so
called biologically inspired learning (BIL), which refers to a wide
range of learning techniques, motivated by biology, that try to mimic
specific biological functions or behaviors. Examples include the
hierarchy of the brain neocortex and neural circuits, which have
resulted in biologically-inspired features for encoding, deep neural
networks for classification, and spiking neural networks for general
modelling.
To ensure that these models are generalizable to unseen data, it is
common to assume that the training and test data are independently
sampled from an identical distribution, known as the sample i.i.d.
assumption. In dynamic and non- stationary environments, the
distribution of data changes over time, resulting in the phenomenon of
‘concept drift’ (also known as population drift or concept shift),
which is a generalization of covariance shift in statistics. Over the
last five years, transfer learning and multitask learning have been
used to tackle this problem. Fundamental analyses using probably
approximately correct (PAC) and Rademacher complexity frameworks have
explained why appropriate incorporation of context and concept drift
can improve generalizability in changing environments. It is possible
to use human-level processing power to tackle concept drift in
changing environments. Concept drift is a real-world problem, usually
associated with online and concept learning, where the relationships
between input data and target variables dynamically change over time.
Traditional learning schemes do not adequately address this issue,
either because they are offline or because they avoid dynamic
learning. However, BIL seems to possess properties that would be
helpful for solving concept drift problems in changing environments.
Intuitively, the human capacity to deal with concept drift is innate
to cognitive processes, and the learning problems susceptible to
concept drift seem to share some of the dynamic demands placed on
plastic neural areas in the brain. Using improved biological models in
neural networks can provide insight into cognitive computational
phenomena. However, a main outstanding issue in using computational
intelligence for changing environments and domain adaptation is how to
build complex networks, or how networks should be connected to the
features, samples, and distribution drifts. Manual design and building
of these networks are beyond current human capabilities. Recently,
computational intelligence methods has been used to address concept
drift in changing environments, with promising results. A Hebbian
learning model has been used to handle random, as well as correlated,
concept drift. Neural networks have been used for concept drift
detection, and the influence of latent variables on concept drift in a
neural network has been studied. In another study, a timing-dependent
synapse model has been applied to concept drift. These works mainly
apply biologically-plausible computational models to concept drift
problems. Although these results are still in their infancy, they open
up new possibilities to achieve brain-like intelligence for solving
concept drift problems in changing environments.
Taking the current state of research in computational intelligence for
changing environments into account, the objective of this special
issue is to collate this research to help unify the concepts and
terminology of computational intelligence in changing environments,
and to survey state-of-the-art computational intelligence
methodologies and the key techniques investigated to date. Therefore,
this special issue invites submissions on the most recent developments
in computational intelligence for changing environments, algorithms
and architectures, theoretical foundations, and representations, &
their application to real-world problems. We also welcome timely
surveys & review papers.
TOPICS OF INTEREST include (but are not limited to):
• Computational intelligence methodologies and implementation for
changing environments
•Transfer learning, Multitask learning, Domain adaption
•Incremental Learning architectures, Unsupervised and semi-supervised
learning architectures
•Incremental Knowledge augmentation, Representation learning and
disentangling
•Incremental Adaptive Neuro-fuzzy systems
•Incremental and single-pass data mining
•Incremental Neural Clustering & Regression
•Incremental Adaptive decision systems
•Incremental Feature selection and reduction
•Incremental Constructive Learning
•Novelty detection in Incremental learning
SUBMISSION PROCESS
The maximum length for the manuscript is typically 25 pages in single
column format with double-spacing, including figures and references.
Authors should specify in the first page of their manuscripts the
corresponding author’s contact and up to 5 keywords. Submission should
be made via: https://easychair.org/conferences/?conf=ieeecimcdbil2015
IMPORTANT (REVISED) DATES (for November 2015 Issue)
1st Feb, 2015: Submission of Manuscripts
15th April, 2015: Notification of Review Results
15th May, 2015: Submission of Revised Manuscripts
15th June, 2015: Submission of Final Manuscripts
GUEST EDITORS
Professor Amir Hussain,
University of Stirling, Stirling FK9 4LA, Scotland, UK
Email: ahu(a)cs.stir.ac.uk
http://cs.stir.ac.uk/~ahu/
Professor Dacheng Tao,
University of Technology, Sydney, 235 Jones Street, Ultimo, NSW 2007,
Australia
Email: dacheng.tao(a)uts.edu.au
Professor Jonathan Wu
University of Windsor, 401 Sunset Avenue, Windsor, ON, Canada
Email: jwu(a)uwindsor.ca
Professor Dongbin Zhao
Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
E-mail: dongbin.zhao(a)gmail.com
-----
A PDF copy of the CFP is attached with this email for forwarding to
interested colleagues. It is also available for download from:
http://www.cs.stir.ac.uk/~ahu/IEEE-CIM-CICE2015.pdf
For more information on the IEEE CIM, see:
http://cis.ieee.org/ieee-computational-intelligence-magazine.html
--
The University of Stirling has been ranked in the top 12 of UK universities for graduate employment*.
94% of our 2012 graduates were in work and/or further study within six months of graduation.
*The Telegraph
The University of Stirling is a charity registered in Scotland, number SC 011159.
Jan. 6, 2015
MBL Methods in Computational Neuroscience Course 2015: applications due March 5
by Mark Goldman
Applications are open for the Methods in Computational Neuroscience
course at the Marine Biology Laboratory in Woods Hole, MA. The course
will run from July 29 to August 26, 2014, and the online application
form can be found at:
http://ws2.mbl.edu/studentapp/studentapp.asp?CourseID=MCN. The course
application deadline is March 5.
The course covers a range of topics in computational neuroscience
including neuronal biophysics, neural coding & information processing,
circuit dynamics, learning & memory, motor control, and cognitive
processing & disease. In addition, numerous tutorials and problem sets
will cover a broad range of computational and mathematical modeling
methods. The course strongly emphasizes the collaboration between
theory and experiment in solving neuroscience problems, and lectures
will be given by a mixture of theorists and experimentalists. The final
weeks of the course are primarily reserved for development and work on
projects that students design in collaboration with the resident
faculty. Further information can be found on the MCN website:
http://www.mbl.edu/mcn/
2015 Course Directors:
Michale Fee, MIT
Mark Goldman, UC Davis
2015 Confirmed Faculty:
Larry Abbott, Columbia University
Steve Baccus, Stanford University
William Bialek, Princeton University
Dmitri Chklovskii, HHMI Janelia Farm
Peter Dayan, University College London
Bard Ermentrout, University of Pittsburgh
Adrienne Fairhall, University of Washington
Ila Fiete, UT Austin
Loren Frank, UCSF
Michael Frank, Brown University
Surya Ganguli, Stanford University
John Huguenard, Stanford University
David Kleinfeld, UC San Diego
Nancy Kopell, Boston University
John Lisman, Brandeis University
Eve Marder, Brandeis University
Bartlett Mel, University of Southern California
Jonathan Pillow, Princeton University
Terry Sejnowski, Salk Institute
Michael Shadlen, Columbia University
Josh Shaevitz, Princeton University
Sara Solla, Northwestern University
Haim Sompolinsky, Hebrew University
David Tank, Princeton University
Josh Tenenbaum, MIT
Xiao-Jing Wang, NYU
Daniel Wolpert, Cambridge University
Ryohei Yasuda, Duke University
Jan. 6, 2015
CNS*2015 Call for Workshop Proposals - Deadline Approaching
by Farzan Nadim
CNS 2015 Prague July 1823, 2015: Call for Workshops DEADLINE APPROACHING
We are requesting proposals for workshops from the international community
of computational neuroscientists. Proposals from all levels of faculty as
well as advanced postdoctoral fellows are welcome. This is a great
opportunity to organize a small meeting with just a few of the headaches
of actually organizing it.
Workshop proposal submission instructions for CNS 2015
The last two days (July 22-23) of the 24th annual CNS meeting will be
devoted to workshops, in which computationally related neuroscience topics
can be presented and discussed. Workshops can be anywhere between one half
to two days in duration. Usually several speakers are invited to introduce
a unifying theme, but ample time for discussion should also be planned.
Submit workshop proposals to: workshops(a)cnsorg.org. The Past Meetings page
gives access to archives of workshops held at previous CNS meetings.
The proposal should be submitted as a Word or pdf file and MUST include
the following sections:
1. Workshop Title
2. Organizers (list primary organizer first; include affiliations and emails)
3. One or two days (2 sessions per day)
4. Number of expected speakers
5. Brief Description (~150 words; if possible, say why this is significant
or timely)
6. Speakers (mark expected or confirmed)
Also please note the following rules which were approved by the OCNS Board
on July 15, 2013:
Each individual can be the organizer or co-organizer on only one workshop.
The number of confirmed speakers is a criterion for accepting the proposal.
Overlapping proposals may be asked to be combined. If the organizers do
not wish to combine the proposals, only one of the proposals may be
accepted.
Workshops submitted before January 15, 2015 will be given priority in
acceptance. Workshop proposals arriving after January 15, 2015 will be
evaluated based on remaining space for additional workshops. No further
workshop acceptances will be anticipated after May 15, 2015.
Registration: Workshop registration will occur through the OCNS
registration web site for CNS 2015. All workshop participants, including
speakers must register. Each workshop is eligible to receive registration
waivers for 2 speakers.
Travel awards: a limited number of Travel Awards will be available for
postdoctoral researchers to lead and be included as speakers.
Exceptionally starting assistant professors may also be given
consideration. These Travel Awards will be variable depending on distance
traveled. Please indicate which speakers you would like to be considered
for this mechanism but take into account that there will be less travel
awards than workshops.
Springer Computational Neuroscience Book Series: Some of the workshops may
be published by the Springer Series in Computational Neuroscience.
Workshop organizers interested in this mechanism should submit a book
proposal to Simina Calin (Simina.calin(a)springer.com) and indicate in the
workshop proposal their interest in publishing a book.
Logistics: Rooms, AV equipment, snacks and beverages during breaks will be
provided by OCNS to the workshop organizers.
Jan. 5, 2015
[publication and call for dialog] IEEE CIS Newsletter on Autonomous Mental Development, Fall 2014
by Pierre-Yves Oudeyer
Dear colleagues,
For this new year, I am happy to announce the release of the Fall 2014 issue of the IEEE CIS Newsletter on Autonomous Mental Development.
This is the biannual newsletter of the computational developmental sciences and developmental robotics community, studying mechanisms of lifelong learning and development in machines and humans.
It is available at:
http://www.cse.msu.edu/amdtc/amdnl/AMDNL-V11-N2.pdf
Featuring:
=== “Trained on everything"
=== Dialog Initiated by Katharina Rohlfing, Britta Wrede and Gerhard Sagerer, with responses from Giulio Sandino and David Vernon, Franck Ramus and Thérèse Collins, Maha Salem, Juyang Weng, Thomas Schultz, and Christina Bergmann:
In the years to come, one very important challenge in developmental sciences is education. Taking an integrated and interdisciplinary approach requires to handle with dexterity concepts and methods from diverse scientific fields ranging from psychology, neuroscience, biology, robotics, computer science or mathematics. How can we grow a community of young researchers mastering the latest advances? How can we teach them to establish cross-disciplinary collaboration and impact?
=== "Will social robots need to be consciously aware?”
=== New dialog initiated by Janet Wiles
A large research community is today working towards the objective of building robots capable of believable, relevant and useful social interaction with humans. We are far from understanding what “consciousness” is, but intuition tells us that it would be very difficult for an “unconscious” human to enter into a social interaction. So what about robots? At least can we identify levels of awareness (of the self, of others) which constitute a necessary basis on which to build social competence? Those of you interested in reacting to this dialog initiation are welcome to submit a response by March 30th, 2015. The length of each response must be between 600 and 800 words including references (contact pierre- yves.oudeyer(a)inria.fr)
Let me remind you that previous issues of the newsletter are all open-access and available at: http://www.cse.msu.edu/amdtc/amdnl/
I wish you a stimulating reading!
Best regards,
Pierre-Yves Oudeyer,
Editor of the IEEE CIS Newsletter on Autonomous Mental Development
Research director, Inria
Head of Flower project-team
Inria and Ensta ParisTech, France
http://www.pyoudeyer.com
https://flowers.inria.fr
Jan. 5, 2015
Postdoc Opportunity at Stanford in the Modulation of Neural Circuitry for Cognitive and Emotional Control
by Wei Wu
The Laboratory of Amit Etkin, MD PhD at Stanford Universityis currently accepting applications for a postdoctoral research fellowship focused on understanding and modulating the neural systems underlying cognitive and emotional control in both healthy individuals and patients with a range of psychiatric conditions. Special emphasis is put on use of causal circuit manipulation tools (eg TMS and concurrent TMS and fMRI) as well as a range of cognitive neuroscience paradigms at the behavioral, physiological and neural levels.
The successful applicant will have a PhD in Cognitive Neuroscience, Neurophysiology, Psychology, Computer Science, Statistics or related fields. Experience with analysis of fMRI data and/or TMS is required. Additional experience with psychophysiology or programming is a plus. A US Citizenship is also required. Duties will also include manuscript preparation, presentation of findings at conferences, management of research assistants and contribution to the preparation of grants. Laboratory and Stanford resources include research-dedicated 3T and 7T MRI scanners, concurrent TMS/fMRI setups and concurrent TMS/EEG setups. Salary commensurate with experience. More information about our ongoing studies can be found at: http://etkinlab.stanford.edu.
To apply, please send a curriculum vitae, a statement describing research interests and relevant background and three letters of recommendations, as well as relevant reprints/preprints of research articles to:
Amit Etkin, MD, PhD
Department of Psychiatry and Behavioral Sciences
Stanford University
amitetkin(a)stanford.edu
Jan. 5, 2015
Last Mile: BIOTECHNO 2015 and BIOCOMPUTATION 2015 || May 24 - 29, 2015 - Rome, Italy
by Cristina Pascual
INVITATION:
=================
Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and publish original scientific results to:
- BIOTECHNO 2015, The Seventh International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies
- BIOCOMPUTATION 2015, The International Symposium on Big Data and BioComputation
The submission deadline is extended to January 23, 2015.
Authors of selected papers will be invited to submit extended article versions to one of the IARIA Journals: http://www.iariajournals.org
=================
============== BIOTECHNO 2015 | BIOCOMPUTATION 2015 | Call for Papers ===============
CALL FOR PAPERS, TUTORIALS, PANELS
BIOTECHNO 2015, The Seventh International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies
General page: http://www.iaria.org/conferences2015/BIOTECHNO15.html
Submission page: http://www.iaria.org/conferences2015/SubmitBIOTECHNO15.html
BIOCOMPUTATION 2015, The International Symposium on Big Data and BioComputation
General page: http://www.iaria.org/conferences2015/BIOCOMPUTATION.html
Submission page: http://www.iaria.org/conferences2015/BIOCOMPUTATION.html#SubmitAPaper
Events schedule: May 24 - 29, 2015 - Rome, Italy
Contributions:
- regular papers [in the proceedings, digital library]
- short papers (work in progress) [in the proceedings, digital library]
- ideas: two pages [in the proceedings, digital library]
- extended abstracts: two pages [in the proceedings, digital library]
- posters: two pages [in the proceedings, digital library]
- posters: slide only [slide-deck posted at www.iaria.org]
- presentations: slide only [slide-deck posted at www.iaria.org]
- demos: two pages [posted at www.iaria.org]
- doctoral forum submissions: [in the proceedings, digital library]
Proposals for:
- mini symposia: see http://www.iaria.org/symposium.html
- workshops: see http://www.iaria.org/workshop.html
- tutorials: [slide-deck posed on www.iaria.org]
- panels: [slide-deck posed on www.iaria.org]
Submission deadline: January 23, 2015
Sponsored by IARIA, www.iaria.org
Extended versions of selected papers will be published in IARIA Journals: http://www.iariajournals.org
Print proceedings will be available via Curran Associates, Inc.: http://www.proceedings.com/9769.html
Articles will be archived in the free access ThinkMind Digital Library: http://www.thinkmind.org
The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas.
All tracks are open to both research and industry contributions, in terms of Regular papers, Posters, Work in progress, Technical/marketing/business presentations, Demos, Tutorials, and Panels.
Before submission, please check and comply with the editorial rules: http://www.iaria.org/editorialrules.html
BIOTECHNO 2015 Topics (for topics and submission details: see CfP on the site)
Call for Papers: http://www.iaria.org/conferences2015/CfPBIOTECHNO15.html
============================================================
A. Bioinformatics, chemoinformatics, neuroinformatics and applications
Bioinformatics (Bioinformatics modeling; Bioinformatics databases; Epidemic models; Informatics and statistics in bio-pharmaceutical research; Machine learning and artificial intelligence in molecular design; Systems biology and metabolic networks; Medical informatics; Genomics informatics; Biostatistics; Structural and functional genomics; Identifying molecular sequence and structure databases; Mechanisms for specifying molecular interactions and structure predictions; Formalisms for gene regulation and expression databases; Algorithms for gene identification and pattern discovery; Techniques for gene expression analysis; Modeling and simulation of biomarkers)
Advanced biocomputation technologies (Stochastic modeling; Computational drug discovery; Graph theory and bioinformatics; Biological databases and information retrieval; Experimental studies and results; Application of computational intelligence in medicine and biological sciences (artificial neural networks, fuzzy logic, evolutionary computing, and simulated annealing); High-performance computing as applied to natural and medical sciences; Hardware computing accelerators; Computer-based medical systems (automation in medicine, etc.); Other aspects and applications relating to technological advancements in medicine and biological sciences; Novel applications)
Chemoinformatics (Computer-aided drug design; Concepts, methods, and tools for drug discovery; Virtual screening of chemical libraries; ADMET - absorption, distribution, metabolism, excretion, and toxicity; QSAR - quantitative structure-activity relationships; Protein-ligand docking and scoring functions; Chemical similarity and diversity; Chemogenomics in drug discovery; QSPR - quantitative structure-property relationships; Theoretical models in chemical reactivity; Mathematical chemistry and chemical graphs; In silico environmental toxicology; Computer-assisted chemical engineering; Combinatorial chemistry; Graph theory in chemistry; Prediction of drug toxicity; Property prediction; Molecular mechanics and quantum chemical calculations; Modeling and measurements of solid-liquid and vapor-liquid equilibria; Blood-brain barrier penetration; Comparison of the similarity(diversity of chemo-data libraries; Chemoinformatics applications)
Bioimaging ( Image processing in medicine and biological sciences; Measurements techniques; Mass spectrometry; Numerical(mathematical approaches; Biological data integration and visualization)
Neuroinformatics (Neurosciences; Neurocomputing)
B. Computational systems (genetics, biology, and microbiology)
Bio-ontologies and semantics (Software environments for bio-computation, bio-informatics, and biomedical applications; Medical informatics; Epidemic models; Biological data mining; Biomedical knowledge discovery; Pattern classification and recognition; Mathematical biology; Graph theory and bio-informatics; Stochastic modeling; Biological databases and information retrieval; Processing mutation information; Archiving of mutation specific information)
Biocomputing (Computational biology; Bioengineering; Biomedical image computing and informatics; Biomedical automation and control; Image-based diagnosis and therapy; Modeling and simulation of systems biology; Applications of large-scale bio-systems)
Genetics (Gene regulation; Gene expression databases; Gene pattern discovery and identification; Genetic network modeling and inference; Gene expression analysis; RNA and DNA structure and sequencing; Evolution of regulatory genomic sequences; Biological data mining and knowledge discovery; Bio-pattern classification and recognition; Bio-sequence analysis and alignment; Comparative genomics; Structural and functional genomics; Amino acid sequencing)
Molecular and Cellular Biology (Protein modeling; Molecular interactions; Metabolic modeling and pathways; Evolution and phylogenetics; Macromolecular structure prediction; Proteomics; Protein folding and fold recognition; Molecular sequence and structure databases; Molecular dynamics and simulation; Molecular sequence classification, alignment and assembly)
Microbiology (Bio-nanotechnologies; Self-assembly and self-replication; Global regulatory networks and mechanisms; Microbial propagation and immunity; Microbial therapies; Microbial life under extreme energy limitation; Cellular microbiology and contact systems; Phylogenetics; Genome dynamics; Transmission dynamics and evolution of emerging diseases; Metagenomics and drug resistance; Microbes and alternative energies)
C. Biotechnologies and biomanufacturing
Fundamentals in biotechnologies (Bioengineering; Bioelectronics; Biomaterials; Bio-films in ecology and medicine; Biometric screening techniques; Biorobotics)
Biodevices (Biosensors; Biomechanical devices; Biochips; Biocomputing; Biometrics devices; Specialized biodevices; Nanotechnology for biosystems)
Biomedical technologies (Biomedical engineering; Biomedical instrumentation; Biomedical metrology and certification; Biomedical sensors; Biomedical monitoring devices; Biomedical devices with embedded computers; Biomedical integrated systems)
Biological technologies (Biological data integration; Image processing in medicine and biological sciences; Biological data visualization; Synthetic biological systems)
Biomanufacturing (Manufacturing platforms; Biopharmaceutical industry; Generic biopharmaceuticals; Bioprocess management; Clinical trials; Disposables and product changeover; Upstream and downstream bioprocessing; Technology benchmarks; International regulations)
BIOCOMPUTATION 2015 Topics (for topics and submission details: see CfP on the site)
CfP: http://www.iaria.org/conferences2015/BIOCOMPUTATION.html#CallForPapers
==========================
Big Data and Context-sensitive Computation
Big Data and Cloud Technology and Services in BioComputation
Big Data, Cloud computing and GPU (Graphical Process Units) for BioComputation
Scale-up and high-performance techniques for data-centric BioComputation
Big Data and Prediction Computational Models
Big Data Computation Applications
Big Data and Evolution Models
Big Data and BioStatistics
Big Data and Personalized Healthcare Computation
Big Data in Genome Analytics
Big Data and Computation on Illness Patterns/Variations (cancer, diabetes, etc.)
Big Data and Donor Information
Big Data and Drugs-related Computation
Big Data and Health/eHealth/Telemedicine Computation
Big Data and Computation in Clinical Context
Big Data and BioImage Computation
Big Data and Molecular Modeling
Big Data and Computational Physics
Big Data and Biological Systems
Big Data and Scalability of BioComputation Tools
Big Data and Trusted Bio-Datasets
Big Data BioComputation and Regulator Borders
------------------------
BIOTECHNO 2015 Committee: http://www.iaria.org/conferences2015/ComBIOTECHNO15.html
BIOCOMPUTATION 2015 Committee: http://www.iaria.org/conferences2015/BIOCOMPUTATION.html#Committees
===============
Jan. 5, 2015
Okinawa/OIST Computational Neuroscience Course 2015: applications open
by Erik De Schutter
OKINAWA/OIST COMPUTATIONAL NEUROSCIENCE COURSE 2015
Methods, Neurons, Networks and Behaviors
June 8 - June 25, 2015
Okinawa Institute of Science and Technology Graduate University, Japan
https://groups.oist.jp/ocnc
The aim of the Okinawa/OIST Computational Neuroscience Course is to
provide opportunities for young researchers with theoretical backgrounds
to learn the latest advances in neuroscience, and for those with experimental
backgrounds to have hands-on experience in computational modeling.
We invite graduate students and postgraduate researchers to participate
in the course, held from June 8th through June 25th, 2015 at an oceanfront
seminar house of the Okinawa Institute of Science and Technology Graduate
University. Applications are through the course web page
(https://groups.oist.jp/ocnc) only; they will close February 8th, 2015.
Applicants will receive confirmation of acceptance in March.
The course has a strong hands-on component based on student proposed
modeling or data analysis projects, which are further refined with the help
of a dedicated tutor. Applicants are required to propose their project at the
time of application.
Like in preceding years, OCNC will be a comprehensive three-week course
covering single neurons, networks, and behaviors with ample time for
student projects. The first week will focus exclusively on methods with
hands-on tutorials during the afternoons, while the second and third weeks
will have lectures by international experts. We invite those who are interested
in integrating experimental and computational approaches at each level, as
well as in bridging different levels of complexity.
There is no tuition fee. The sponsor will provide lodging and meals during
the course and may support travel for those without funding. We hope that
this course will be a good opportunity for theoretical and experimental
neuroscientists to meet each other and to explore the attractive nature and
culture of Okinawa, the southernmost island prefecture of Japan.
Invited faculty:
• Gordon Arbuthnott (OIST)
• Axel Borst (MPI, Münich, Germany)
• Erik De Schutter (OIST)
• Kenji Doya (OIST)
• Eugene Izihikevich (Brain Corporation, USA)
• Bernd Kuhn (OIST)
• Peter Latham (Gatsby Unit, UCL, UK)
• Miguel Nicolelis (Duke University, USA)
• Steve Prescott (University of Toronto, Canada)
• John Rinzel (New York University, USA)
• Jackie Schiller (Technion, Israel)
• Greg Stephens (OIST)
• Jeff Wickens (OIST)
• Taro Toyoizumi (RIKEN BSI, Japan)
• Xiao-Jing Wang (New York University, USA)
• Wako Yoshida (ATR, Japan)
Jan. 5, 2015
Neural-Inspired Computational Elements workshop and student competition
by Aimone, James Bradley
The 3rd Neural-Inspired Computational Elements (NICE) workshop will be held in Bernalillo, New Mexico between February 23rd and February 25th. This year's meeting will focus on the value proposition of neural inspired computing, with speakers discussing topics in neuroscience, neural-inspired algorithms, neural-inspired hardware, and application drivers. NICE is organized by scientists at Sandia National Laboratories and is co-sponsored by the Department of Energy Office of Science, DAPRA, and IARPA.
For an updated speaker list and registration info, please go to http://nice.sandia.gov.
STUDENT COMPETITION
For this first time this year, we are having a student competition. Go to Student Thesis Competition<https://nm.kip.uni-heidelberg.de/jss/ApplyForThesisAward> (https://nm.kip.uni-heidelberg.de/jss/ApplyForThesisAward) to submit a student thesis abstract and advisor recommendation on a Neuro-inspired Computation related topic. Submissions must be in by January 16th, winners will be announced by January 30th. Three selected students will receive travel support to attend the workshop and have the opportunity to present a 10 minute 'snap overview'. Runner-up notable submissions will be considered for poster presentations during the workshop.
Jan. 4, 2015
postdoctoral position: olfactory coding and holographic optogentics
by Rinberg, Dmitry
Postdoctoral position in the Rinberg (NYU) – Shoham (Technion) labs to study
olfactory coding using holographic optogenetics
We are seeking a talented postdoctoral researcher for our collaborative BRAIN Initiative project to study behavioral readouts of spatiotemporal codes using holographic optogenetics. The project will advance and apply a new technology for spatiotemporal patterned control of multiple neurons in the peripheral olfactory system and use behavioral responses to test how these patterns are being read.
An ideal candidate should have a background in neuroscience, physics and math. Knowledge and experience in computer-generated holography, mutliphoton imaging and/or nonlinear optics are a big plus.
The work will be carried out at the NYU Neuroscience Institute with possible visits to the Technion; the candidate will gain both from NYU’s thriving neuroscience community and from the Technion’s excellence in advanced technology development. Interested applicants should send a cover letter, curriculum vitae, and arrange for reference letters to be sent to Dr. Dmitry Rinberg (rinberg(a)nyu.edu<mailto:rinberg@nyu.edu>).
Jan. 4, 2015
CFP: Special Issue on Neurobiologically Inspired Robotics: Enhanced Autonomy Through Neuromorphic Cognition
by Jeff Krichmar
Dear Computational Neuroscientists,
I hope some of you will consider submitting to this special issue of Neural Networks (http://www.journals.elsevier.com/neural-networks/call-for-papers/special-is…)
Neurobiologically inspired robotics goes by many names: brain-based devices, cognitive robots, neurorobots, and neuromorphic robots, to name a few. The field has grown into an exciting area of research and engineering.
The common goal is twofold: Firstly, developing a system that demonstrates some level of cognitive ability can lead to a better understanding of the neural machinery that realizes cognitive function. The often used phrase, “understanding through building”, implies that one can get a deep understanding of a system by constructing physical artifacts that can operate in the real-world. In building and studying neurobiologically inspired robots, scientists must address theories of neuroscience that couple brain, body, and behavior. Secondly, the deep theoretical understanding of cognition, neurobiology and behavior obtained by constructing physical systems, could lead to a system that demonstrates capabilities commonly found in the animal kingdom, but rarely found in artificial systems, most notably their adaptive and flexible autonomous behavior. There have already been some successes that meet these goals. For example, navigation models based on the hippocampus are now deploy!
ed on robots that autonomously explore their environment. Machine image processing systems based on visual cortex have been used in a number of unsupervised recognition and perception applications. Robots designed to address impairments due to disorders such as Alzheimer’s disease, autism spectrum disorder, and attentional deficit disorders, are being used as therapeutic and diagnostic tools without the need for constant caretaker supervision.
Despite these successes, the field is still in its infancy and basic research is needed. In particular, we are interested in papers that describe: 1) How models of cognitive functions, such as attention, decision-making, learning and memory, perception, and social cognition can be constructed on physical robots. 2) How the neuromorphic devices, which are designed to run neural algorithms with low-power, can advance the construction of autonomous robotics. 3) How the theoretical and engineering lessons learned from constructing neurobiologically inspired robots can transfer to autonomous robots carrying out practical applications.
This Special Issue invites papers that address the three broad topics described above.
Topics of interest
• Adaptive behavior
• Active sensing
• Artificial empathy
• Cortical computing
• Developmental robotics
• Embodied Cognition
• Neuromorphic Engineering
• On-line learning and memory systems
• Prediction and planning
• Socially assistive robotics
Guest Editors
Jeffrey Krichmar, University of California, Irvine
Minoru Asada, Osaka University
Jorg Conradt, Technische Universitat München
Important Dates
Submission due: 1 Feb 2015
Acceptance notification: 1 Aug 2015
Expected publication: 1 Nov 2015
Submission instructions
Each paper for submission should be formatted according to the style and length limit of Neural Networks. Please refer complete Author Guidelines at http://www.elsevier.com/journals/neural-networks/0893-6080/guide-for-authors. Note that published papers and those currently under review by other journals or conferences are prohibited. A separate cover letter should be submitted that includes the paper title, the list of all authors and their affiliations, and information of the contact author. Each paper will be reviewed rigorously, and possibly in two rounds, i.e., minor/major revisions will undergo another round of review. Prospective authors are invited to submit their papers directly via the online submission system at http://ees.elsevier.com/neunet/. To ensure that all manuscripts are correctly included into the special issue described, it is important that all authors select “SI: Neurobiological Robotics” when they reach the "Article Type" step in the submission process.
Jeff Krichmar
Department of Cognitive Sciences
2328 Social & Behavioral Sciences Gateway
University of California, Irvine
Irvine, CA 92697-5100
jkrichma(a)uci.edu
http://www.socsci.uci.edu/~jkrichma
Jan. 2, 2015