- Comp-neuro - lists.cnsorg.org

Biomag 2016 Brain Connectivity Analysis Competition
by Stefan Haufe June 17, 2016

June 17, 2016

Dear colleagues, we have just launched a data analysis competition on brain connectivity analysis using EEG and MEG. Detailed information on the challenge and the data to be analyzed can be found at http://bbci.de/supplementary/EEGconnectivity/BBCB.html . At this website, we also offer a basic Matlab-based software framework for generating EEG/MEG data in a realistic head model, plotting results, etc. You and your colleagues are warmly invited to participate in the challenge. Please feel free to pass on this link to anyone else who might be interested. Besides active participation we would also be very happy to just hear your general opinion on the design of the challenge, and about any suggestions for extension (in the future). Our challenge is on of three official data analysis competitions of this year's BIOMAG conference. The invitation to participate in all three challenges is pasted below for your convenience. With best wishes, Stefan Haufe and Arne Ewald -------- Forwarded Message -------- Subject: [megcommunity] Biomag 2016 Data Analysis Competition Date: Mon, 30 May 2016 16:56:31 +0200 From: Ole Jensen <ole.jensen(a)DONDERS.RU.NL> Reply-To: Ole Jensen <ole.jensen(a)DONDERS.RU.NL> To: MEGCOMMUNITY(a)JISCMAIL.AC.UK Dear all, We are happy to announce three challenges for the 'Data Analysis Competition' at Biomag 2016. Please see details at http://www.biomag2016.org/data_analysis_competition.php The aim of the competitions is to promote the development and application of new analysis techniques. The challenges will help to elucidate pros and cons of different techniques and attract experts from outside the MEG field. The winners of the competition will be given the opportunity to present their proposal at the Biomag meeting in Seoul (Oct 1-6) in order to spark discussions on analysis. Please encourage colleagues to participate! Best regards, Ole Jensen -- Prof. dr. Ole Jensen http://www.neuosc.com

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FW: 2nd Call for Papers: IEEE Transactions on Cognitive and Developmental Systems Special Issue on Neuromorphic Computing and Cognitive Systems
by Arindam Basu June 17, 2016

June 17, 2016

Dear all， You are invited to submit your work to IEEE Transactions on Cognitive and Developmental Systems Special Issue on Neuromorphic Computing and Cognitive Systems. The submission deadline has been extended to June 30, 2016. Thanks for your contributions! (And apologies for cross-posting if any) IEEE Transactions on Cognitive and Developmental Systems Special Issue on Neuromorphic Computing and Cognitive Systems AIM AND SCOPE In recent years neuromorphic computing has become an important emerging research area. There has been rapid progress in computational theory, learning algorithms, signal processing and circuit design and implementation, which have shown appealing computational advantages over conventional solutions. The low size, weight, and power of these hardware architectures shows great potential for embedded cognitive systems. Starting from emulating the computational principles and architecture found in neural systems, neuromorphic computing aims to integrate sensory coding, synaptic computing (e.g., STDP), learning and memory, and attempts to develop neuromorphic sensors and chips, and cognitive behaving systems such as robots. Neuromorphic hardware has provided a fundamentally different technique for data representation and learning, e.g., asynchronous events rather than regularly sampled frames of images. Various hardware systems leveraging on neural spikes based computing have been reported to achieve good performance with much lower power consumption. Therefore, neuromorphic computing can inform cognitive systems because the algorithms that run on this hardware must be neurobiologically inspired. A huge potential exists for applying this emerging computing framework to the next generation of cognitive systems and robotics, neuro-inspired sensors and processors, etc. THEMES This special issue aims to report state-of-the-art approaches and recent advances on (a) learning algorithms constrained by limits of biology and neuromorphic hardware (b) neuromorphic hardware for cognitive systems and (c) applications of neuromorphic architecture or hardware to cognitive robotics. Topics relevant to this special issue include, but are not limited to • Neuromorphic cognitive systems • Cognitive robotics • Brain-inspired data representation models • STDP, Spike-based sensing and learning algorithms • Spike based processing and methods for configuring spike-based processors SUBMISSION Manuscripts should be prepared according to the “Information for Authors” of the journal found at http://cis.ieee.org/publications.html and submissions should be done through the IEEE TCDS Manuscript center: https://mc.manuscriptcentral.com/tcds-ieee <https://mc.manuscriptcentral.com/tcds-ieee> and please select the category “SI: Neuromorphic Computing”. IMPORTANT DATES 15 June 2016-Extended to 30 June 2016: Deadline for manuscript submission 15 Sep 2016: Notification of authors 15 Oct 2016: Deadline for revised manuscripts 15 Nov 2016：Final version GUEST EDITORS Huajin Tang, Sichuan University, China. （htang(a)scu.edu.cn<mailto:htang@scu.edu.cn>） Tiejun Huang, Peking University, China. （tjhuang(a)pku.edu.cn<mailto:tjhuang@pku.edu.cn>） Garrick Orchard，National University of Singapore (garrickorchard(a)nus.edu.sg<mailto:garrickorchard@nus.edu.sg>） Arindam Basu，Nanyang Technological University, Singapore (arindam.basu(a)ntu.edu.sg<mailto:arindam.basu@ntu.edu.sg>） Jeffrey L. Krichmar，University of California, Irvine, US （jkrichma(a)uci.edu<mailto:jkrichma@uci.edu>） Best regards, Arindam ________________________________ CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents. Towards a sustainable earth: Print only when necessary. Thank you.

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Fwd: Faculty Position in Neural Data and Imaging Sciences, Sabanci Univ., Istanbul
by Mujdat Cetin June 16, 2016

June 16, 2016

*Faculty Position in Neural Data and Imaging Sciences at Sabancı University* http://ee.sabanciuniv.edu/en/full-time-faculty-position-neural-data-and-ima… The Faculty of Engineering and Natural Sciences (FENS) at Sabancı University, İstanbul, Turkey invites applications for a full-time faculty position in the area of Neural Data and Imaging Sciences with a targeted start date of Fall 2016. The ideal candidate for this position would have a Ph.D. degree in electrical engineering, computer science, biomedical engineering, computational neuroscience, or a related field, as well as a strong research and publication record in the area of information extraction from challenging neural data. Particular research areas of interest include but are not limited to neuroinformatics, big neural sensor data analytics, biomedical imaging, brain informatics, signal processing of neural activity, computational neuroimaging, neural image analysis, machine learning for understanding the brain, and connectomics. Sensing/imaging modalities of interest include but are not necessarily limited to MRI, fMRI, DTI, PET, EEG, MEG, ECoG, and several forms of microscopy. Application areas of interest include, but are not limited to healthcare, neurotechnology, brain-computer interfaces, neurorehabilitation, and neurorobotics. The faculty member will have a primary affiliation with the Electronics Engineering program but will be expected to conduct collaborative research with other programs in FENS as well. Applications from candidates at all ranks are encouraged. For candidates at the Assistant Professor level, post-doctoral research experience is a plus. Successful candidates are expected to develop externally-funded internationally-recognized research programs; teach undergraduate and graduate courses; advise and mentor graduate and undergraduate students; and undertake service responsibilities. Successful candidates will have the opportunity to benefit from the state-of-the-art infrastructure of the brand-new Nanotechnology Research and Application Center (SUNUM), as well as to be involved in the Professional Master’s Program in Data Analytics. Sabancı University, a privately funded premier academic institution, established in 1996 in its state-of-the-art campus located in suburban İstanbul. The university offers 13 undergraduate programs and 38 graduate programs in three faculties (Faculty of Engineering and Natural Sciences, Faculty of Arts and Social Sciences, School of Management). The University aims to establish a high standard of academic excellence and a research-oriented atmosphere for its international faculty and students, while nurturing productive relationships particularly with the industries in the region which constitute the industrial heartland of Turkey. The medium of instruction is English. In 2015, Sabancı University ranked 13th globally in the Times Higher Education (THE) ranking of the top 100 universities under 50 years old, and 21st in the THE Asia university rankings. In the recently announced THE ranking of the world’s best small universities in 2016, Sabancı University ranked 10th globally. It ranked first among all universities in Turkey in the University Entrepreneurship and Innovation Index of the Ministry of Science, Industry, and Technology in 2015. Detailed information about the Electronics Engineering Program at Sabancı University can be found at http://ee.sabanciuniv.edu/ Applicants should submit their applications online through https://crm.sabanciuniv.edu/acadcv/application.php and provide a cover letter, curriculum vitae, statement of research interests, statement of teaching interests, and at least three professional references. Review of applications will begin on July 1, 2016 and will continue until the position is filled. -- Mujdat Cetin Technical Program Co-chair, IVMSP 2016 -- http://ivmsp2016.org Technical Co-chair, FUSION 2016 -- http://fusion2016.org Faculty Member Faculty of Engineering and Natural Sciences Sabanci University Orhanli, Tuzla 34956, Istanbul, Turkey Phone : +90 (216) 483-9594 Fax : +90 (216) 483-9550 E-mail : mcetin(a)sabanciuniv.edu Web : http://spis.sabanciuniv.edu

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Scientist II opening in Computational Neuroscience at the Allen Institute for Brain Science (Seattle, USA)
by Costas Anastassiou June 16, 2016

June 16, 2016

Scientist II opening in Computational Neuroscience Lab headed by Dr. Costas Anastassiou Allen Institute of Brain Science Do you want to make a difference in our understanding of brain disorders? Do you have a solid background in computational neuroscience/scientific computing/simulation-based research and curious about how the brain works? Are you able to meet aggressive timelines and deliverables in a collaborative environment? The laboratory headed by Dr. Costas Anastassiou at the Allen Institute is currently looking for a talented Scientist II to work on large-scale, biophysically detailed brain circuit simulations to explore the pathophysiology of epilepsy. Our mission at the Allen Institute for Brain Science is to accelerate the understanding of how the human brain works in health and disease. By implementing a team science approach on a large scale we strive to generate useful public resources, drive technological innovations and discover fundamental brain properties through integration of experiments, modeling and theory. Position summary: We are seeking to fill a position at the level of Scientist II (SciII) to work on an exciting new translational neuroscience pilot project at the Institute. The goal of this project is to investigate cellular and circuit mechanisms of epileptogenesis in human hippocampus. To address these questions, we seek to develop a faithful computational model of the human epileptogenetic hippocampus consisting of a multitude of reconstructed, interconnected and biophysically faithful neurons emulating anatomical and dynamical characteristics of the pathological brain tissue. For examples of biophysically realistic network models as pursued in this work see [Schomburg, Anastassiou et al, J Neurosci, 2012; Reimann, Anastassiou et al, Neuron, 2013; Taxidis, Anastassiou et al, Neuron, 2015]. The aim of the computational model is to (i) understand how synaptic, cellular and connectivity properties of pathological brain tissue give rise to pathophysiological network dynamics, (ii) understand how pathophysiological dynamics are reflected on signals such as depth-, ECoG- and EEG-recordings, and (iii) identify intervention targets to abort or suppress pathological activity. Importantly, the computational effort will occur in parallel with novel in vitro experiments in brain slices derived from patients undergoing surgery for treatment refractory mesial temporal lobe epilepsy that will provide the data on which the computational modeling will be based. The project will be pursued in collaboration with in-house experimental colleagues as well as neurologists and neurosurgeons and has a guaranteed duration initially of 18 months beginning in the summer of 2016. Responsibilities: · Construct detailed biophysical models using cable theory and NEURON-software. · Design, implement and analyze large-scale network simulations. · Publish/present findings in peer-reviewed journals/scientific conferences. · Prepare written and oral reports on a regular basis. · Publish scientific findings in peer-reviewed journals and relevant conferences. · Maintain clear and accurate communication with supervisor and team members. Qualifications: · PhD degree in computational neuroscience, physics, biology, bioengineering or related fields. · Strong background in scientific computing; experience in computational neuroscience is preferred, but other strong applicants will be considered (with background in computational physics, biophysics, and related disciplines). Experience with parallel computing is a plus as well as familiarity with high-level programming languages such as python. · Ability to meet aggressive timelines and deliverables in a collaborative environment. · Strong publication record. · Experience in pursuing research projects in collaborative fashion. · Proven independent thinking and flexibility. · Familiarity with in vitro and in vivoelectrophysiological monitoring techniques and data analyses. · Strong written and verbal communication skills. How to apply: Visit the Allen Institute for Brain Science Careers website and fill out your information for the Scientist II-position under “2200-Modeling, Analysis and Theory”.

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Programmer wanted for Neuroscience and Neuroprosthetics Lab
by Sliman Bensmaia June 16, 2016

June 16, 2016

Lab at the cutting edge of neuroscience and neurotechnology looking for a programmer to keep us at the cutting edge! The lab has two general pursuits: discover the neural basis of touch and proprioception – how do patterns of activation in the nerve and in the brain mediate our ability to feel objects by touch and sense the position and movements of our limbs in space? – and to develop a somatosensory neuroprosthesis – How can we recreate the sense of touch by stimulating the nerve or the brain. See http://bensmaialab.org for additional information regarding the lab and the exciting work we are doing. Ideally, looking for a motivated, intelligent individual who works well with people, someone who might be able to make a long term commitment to the lab and help us build something special. Job Summary Responsible for interfacing the various machines in the lab (robots, sensors, data acquisition systems, etc.) with computers and with each other to run neurophysiological and behavioral experiments with human and non-human primates. Education Bachelor's degree in computer science or a related field of engineering required. Experience One year of relevant programming experience required. Experience developing, implementing, debugging and maintaining applications required. Two years of professional programming experience preferred. Experience developing applications using C++, Matlab, Python, Java, MySQL, Visual Basic, and/or any other object oriented programming language preferred. Experience building and debugging electronic systems preferred but not required. Knowledge of electromechanical systems preferred but not required. Interest in and/or knowledge of neurophysiology preferred but not required. -- Sliman Bensmaia Associate Professor Department of Organismal Biology and Anatomy University of Chicago 773.834.5203 -- Sliman Bensmaia Associate Professor Department of Organismal Biology and Anatomy University of Chicago 773.834.5203

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Postdoctoral positions available in Dr. Suzanne Haber's lab
by Sarah Heilbronner June 16, 2016

June 16, 2016

2 Postdoctoral positions are available in Dr. Suzanne Haber’s lab at the University of Rochester. The studies use nonhuman primate anatomical connectivity studies in combination with MRI in nonhuman and human primates to investigate: 1. Reward pathways and their interface with cognitive and motor control circuits; and 2. Circuitry underlying obsessive-compulsive disorder (OCD). The first project is designed to delineate connectional hubs within cortex and basal ganglia structures that receive convergent inputs from reward and cognitive control regions. Specific focus is on dorsolateral, ventrolateral, ventromedial, orbital, and anterior cingulate cortices and the striatum and amygdala. The approach is to use traditional anatomical tract-tracing circuitry techniques in combination with state of the art imaging methods such as diffusion and functional MRI to explore the location of these hubs in both animal and human brains and their relationship to disease. The second project is designed to characterize the organizational principles that govern white matter organization and trajectories connecting frontal areas with particular emphasis on the connectional hubs. These data will form the basis for segmenting white matter with respect to function in order to identify and evaluate diffusion MRI changes associated with OCD and its treatments. These studies are part of a Silvio O. Conte Center grant involving several Institutions and multiple techniques investigating the neurocircuitry of OCD and effects of neurostimulation. The ideal applicants would have background in systems neuroscience and/or neuroimaging. These positions will give opportunities to interact with pioneering scientists through the Conte Center grant and will provide unique training at the forefront of anatomy, neuroimaging, and translational neuroscience. Applicants should submit a summary of research interests, a curriculum vitae and names of three references to: Dr. Suzanne Haber, Department of Pharmacology and Physiology: Email: Suzanne_Haber(a)URMC.Rochester.edu. (AA/EOE).

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Extended Deadline for Goettingen's Advanced Computational Neuroscience Summer School
by Agostina Palmigiano June 16, 2016

June 16, 2016

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Extended deadline for applications for the Advanced COMPUTATIONAL NEUROSCIENCE Summer School in Göttingen, Germany September 06th - 16th, 2016 DEADLINE *June 24, 2016* %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% The aCNS School is a 10-day intensive course in mathematical and computational neuroscience. It offers students working in computational neuroscience and already familiar with its interdisciplinary nature, an intensive pedagogy of advanced mathematical and computational tools, designed to qualify young researchers to push the frontiers of the field. The course counts with and introductory day + 4 two-day theoretical blocks + 4 evening lectures in charge of the following researchers: * Vijay Balasubramanian <http://www.sas.upenn.edu/%7Evbalasub/public-html/Home.html>, University of Pennsylvania, Philadelphia, USA * Jason Kerr <http://www.caesar.de/bbo.html>, Center of Advanced European Studies and Research, Bonn, Germany * Gilles Laurent <http://brain.mpg.de/research/laurent-department.html>, MPI for Brain research, Frankfurt, Germany * Tobias Moser <http://www.innerearlab.uni-goettingen.de/>, University Medical Center, Göttingen Germany * Erwin Neher <http://www.nobelprize.org/nobel_prizes/medicine/laureates/1991/neher-bio.ht…>, Max Planck Institute for Biophysical Chemistry, Göttingen, Germany * Magnus Richardson <https://www2.warwick.ac.uk/fac/sci/systemsbiology/staff/richardson/>, University of Warwick, Conventry, England * Wolf Singer <http://www.esi-frankfurt.de/research/singer-lab/>, Ernst Strüngmann Institute for Neuroscience, Frankfurt, Germany * Misha Tsodyks <http://www.weizmann.ac.il/neurobiology/labs/tsodyks/>, Weizmann Institute of Science, Rehovot, Israel The consecutive two day thematic blocks are dedicated to mathematical approaches to circuit dynamics. Each lecturer will give a self-contained introduction to a particular set of theoretical tools in a block of two morning lectures. In the afternoon, participants will work on problem sets designed to develop proficiency in both the mathematical and computational tools learned earlier that day. An additional set of evening ‘easy’ lectures will give the opportunity to discuss significant advances in the field. The course takes place at the Department of Nonlinear Dynamics of the Max-Planck Institute for Dynamics and Self-Organization, Göttingen. Registration fee is 200 euros. Course language is English. Housing is provided by the school. Travel grants can be provided upon request. Only 15 participants will accepted. We invite applicants to apply by filling out the application form at: http://www.bccn-goettingen.de/events/cns-course <http://www.bccn-goettingen.de/events/cns-course> by *June 24, 2016*. Organizers: Rainer Engelken, Joscha Liedtke, Agostina Palmigiano, Manuel Schottdorf, Jens Wilting Best wishes and looking forward to seeing you in Göttingen, Agostina Palmigiano ___________________________ Agostina Palmigiano Max Planck Institute for Dynamics and Self-Organization Am Fassber 17, 37077 Goettingen +49 551 5176 421 office +49 163 882 6689 mobile http://www.nld.ds.mpg.de/ <http://www.nld.ds.mpg.de/> ___________________________

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Postdoctoral Position in Computational Neuroscience at Georgia State University
by Yaroslav Molkov June 16, 2016

June 16, 2016

A postdoctoral/research associate position in computational neuroscience for the initial duration of one year is immediately available in the externally funded project focusing on multi-scale computational modeling of motor control mechanisms, involving interactions between basal ganglia, thalamus, cerebellum, cortex, and spinal cord in connection with realistic simulation of pathological changes in motor control during Huntington’s disease. This collaborative project is performed jointly by the groups of Drs. Ilya Rybak (Dept. of Neurobiology and Anatomy, Drexel University, Philadelphia, PA) and Yaroslav Molkov (Dept. of Mathematics, Georgia State University, Atlanta, GA). Applicants must have a PhD degree in Neuroscience, Applied Mathematics, Physics, or a related discipline, a strong research record, and excellent C++ programming skills. Previous experience in computational neuronal modeling is a plus. Georgia State University is an urban public research university. Georgia State students and employees can take advantage of the university’s easy access to Atlanta’s rich creative environment, diversity of cultures and lifestyles, and wide variety of indoor and outdoor activities. The world’s busiest airport is just minutes from campus. Atlanta provides Georgia State’s faculty and students with an urban laboratory, enabling them to draw creative inspiration. Interested candidates are encouraged to contact Dr. Molkov (ymolkov(a)gsu.edu) by email. To apply, please send an email along with (1) curriculum vitae; (2) a cover letter describing previous research experience and interests; (3) the names and contact information of three references. Dr. Molkov will be available to answer questions about this position during Organization for Computational Neuroscience Annual meeting, July 2-7, 2016, Jeju, Korea. ================================= Yaroslav Molkov, Ph.D. Associate Professor Georgia State University Department of Mathematics and Statistics 30 Pryor St SW, 750-COE, Atlanta, GA 30303 Office: 722-COE Phone/fax: (404) 413-6422 Email: ymolkov(a)gsu.edu

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Final Call for Papers: Extracellular Space
by Reinoud Maex June 16, 2016

June 16, 2016

JOURNAL OF INTEGRATIVE NEUROSCIENCE http://www.worldscinet.com/jin Call for Papers! Special Issue on Extracellular Space In experimental neuroscience, most electric signals are picked up from the electrolytic (or colloidal) solution that constitutes extracellular (interneuronal) space, yet the origin of these potentials is incompletely understood. Even more, theoreticians have recently argued about the physical principles underlying these phenomena. The present special issue invites experimental and theoretical work that can shed light on electric phenomena in extracellular space, with an emphasis on extracellular potentials and endogenous electric field interactions. The contributions solicited are original research papers and comprehensive reviews on methodological aspects. Submission deadline: 30 September 2016 Contact: Dr. Reinoud Maex reinoud.maex(a)ens.fr Questions that may be addressed are (but are not limited to): 1. The nature of extracellular potentials - What is nature of the electric currents, and what is the velocity (distribution) of the ions involved? Since membrane currents underlie the extracellular currents, what are the relative contributions of synaptic versus voltage-gated channels, excitatory versus inhibitory synapses, capacitive currents? How important are Lorenz forces between currents (due to the generated magnetic fields) and is there a contribution of polarization currents? - Is extracellular space purely resistive, or is a capacitive component involved, and what factors (such as ionic concentration, Debye shielding, etc.) contribute to its resistivity? 2. Modeling of extracellular potentials and electric field interactions - What level of detail is needed to model extracellular electrical phenomena, and which formalism can be employed? How valid is the cable equation, or need slow concentration changes of the major ionic components involved be modeled explicitly? How can LFP calculations be incorporated in simulation software? - Can volume transmission be simulated adequately as volume conductors? Are ephaptic coupling effects adequately simulated in one dimension? 3. Neuronal inference from measured extracellular potentials - What is the importance of the electrode characteristics for the proper interpretation of the measured signals? - What are the underlying assumptions, and limitations, of current-source-density analysis? How valid is the dipole approximation? Why are recent experiments being interpreted in terms of monopoles, and can single-compartmental model neurons generate local field potentials at all? - What can be learned from the power density distribution of signal frequencies? 4. Neurostimulation - What is the effect on neurons of an externally applied current or potential, and what mechanism (or rationale) underlies deep brain stimulation? 5. Physiological roles of extracellular potentials and endogenous electrical fields - Do extracellular potentials contribute to neuron-neuron and neuron-glia communication? Can there be a role for extracellular potentials in the homeostasis, clearance, and volume regulation of extracellular space, and in the control of blood flow and of the blood-brain-barrier. - What is the integrative role of endogenous electrical fields in brain function?

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Papers on networks of neurons with nonlinear dendrites and Binary Synapses trained by structural plasticity
by Arindam Basu June 16, 2016

June 16, 2016

Dear all Let me draw your attention to some work done by our group over the past few years in developing networks of neurons with lumped dendritic nonlinearity and binary synapses. The connections on each dendritic branch is sparse and the neurons learn to classify patterns when trained using different structural plasticity rules. Thus learning happens by modiying network connection matrix and not by weight change. These networks have advantage for hardware implementations--reduced memory and resistance to mismatch due to binary synapses. We have demonstrated supervised and unsupervised spike time based learning rules and have used these networks as readout of liquid state machines, to improve the reservoir in a liquid state machine, to classify spike latency patterns like tempotron or to classify MNIST images. I summarize the papers below and also include arxiv links for your reading pleasure. 1. S. Hussain, S. C. Liu and A. Basu, "Biologically plausible, Hardware-friendly Structural Learning for Spike-based pattern classification using a simple model of Active Dendrites," Neural Computation , vol. 27, no. 4, pp. 845-897, April 2015 link: http://arxiv.org/pdf/1411.5881.pdf ** Margin based learning, spike time based supervised learning, results on UCI dataset 2. S. Roy, A. Banerjee and A. Basu, "Liquid State Machine with Dendritically Enhanced Readout for Low-power, Neuromorphic VLSI Implementations," IEEE Trans. on Biomedical Circuits & Systems , vol. 8, no. 5, pp. 681-695, 2014. link:http://arxiv.org/pdf/1411.5458.pdf ** Readout of LSM, 30X less binary synapses compared to parallel perceptron 3. S. Roy, P. P. San, S. Hussain, Lee Wang Wei and A. Basu, "Learning Spike Time Codes through Morphological Learning with Binary Synapses," IEEE Trans. on Neural Networks & Learning Systems , vol. 27, no. 7, July 2016. link: http://arxiv.org/pdf/1506.05212.pdf ** Classifying spike time latency patterns, comparison with tempotron 4. S. Hussain and A. Basu, "Multi-class Classification by Adaptive Network of Dendritic Neurons with Binary Synapses using Structural Plasticity," Frontiers in Neuroscience , Mar, 2016. doi: 10.3389/fnins.2016.00113 link: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4814530/ ** Ensemble learning, adaptive allocation of dendrites, performance on MNIST, hardware savings analysis 5. S. Roy and A. Basu, "An Online Unsupervised Structural Plasticity Algorithm for Spiking Neural Networks," IEEE Trans. on Neural Networks and Learning Systems , accepted, 2016. link: http://arxiv.org/pdf/1512.01314.pdf ** unsupervised spike time based learning, sequence learning 6.S. Roy and A. Basu, "An online structural plasticity rule for generating better reservoirs," Neural Computation , accepted, 2016. link: http://arxiv.org/pdf/1604.05459.pdf ** Improving separation property of reservoirs in LSM Thanks Arindam Basu Assistant Professor School of EEE Nanyang Technological University http://www3.ntu.edu.sg/home/arindam.basu/ Regards, Arindam ________________________________ CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents. Towards a sustainable earth: Print only when necessary. Thank you.

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