yearly archives: 2011

  • Silicon synapses

    By Massimiliano Versace | December 8, 2011

    I was recently interviewed by Scope, a publication established in 2005 to showcase the work undertaken by the students in the MIT Graduate Program in Science Writing. The interview was about a research project led by Chi-Sang Poon, whose MIT group has designed a chip emulating in detail the dynamics of brain synapses, the junctions between neurons. Read the rest of this entry »

  • Optic Flow-Based Navigation

    By Vincent | October 31, 2011

    This summer, I was part of the Boston University Research Internship in Science and Engineering. I worked primarily with Samuel Kim, another high school intern from Minnesota, Florian Raudies, a postdoctorate research associate in the Cognitive and Neural Systems Department, Schuyler Eldridge, an electrical engineering graduate student, and Dr. Ajay Joshi, the assistant professor in the Electrical and Computer Engineering Department. Much of the work was done in the Boston University's Neuromorphics Laboratory. Read the rest of this entry »

  • The name of the Outstein

    By Ennio Mingolla | September 29, 2011

    On Friday, September 16, 2011 Boston University chartered a vibrant new center to house research in Computational Neuroscience and Neural Technology (CompNet). In addition to some new areas of emphasis CompNet will support many aspects of the research mission of the former Department of Cognitive and Neural Systems (CNS). The closing of the CNS Department affords an opportunity to reflect on an epoch through the lens of the Outstein symbol that came to be its de facto logo. On the left, the Outstein logo. Read the rest of this entry »

  • Study Computational Neuroscience at Boston University

    By Frank Guenther | September 21, 2011

    Computational BrainThe Computational Neuroscience PhD specialization of Boston University’s Graduate Program for Neuroscience provides students with a uniquely specialized curriculum that supplements core neuroscience coursework with advanced training in a wide array of computational methods for studying the nervous system and developing neuroscience-related technologies. Topics of study include: neural network modeling, neural dynamics, sensory, motor, and cognitive modeling, statistical modeling, sensory and motor prosthesis, brain-machine interfaces, neuroinformatics, neuromorphic engineering, and robotics. Coursework is chosen from the wide array of computational and neuroscience courses offered by the many departments and programs of the main Boston University campus and the BU School of Medicine. Students pursue their research interests in laboratories across the University and have the opportunity to combine hands on experimental research with highly sophisticated computational analysis.

  • Learning to see in a virtual world

    By Massimiliano Versace | September 18, 2011

    This post is authored by Jasmin Leveille and Gennady Livitz, two Neuromorphics Lab researchers working on the development of the MoNETA brain. The goal of the MOdular Neural Exploring Traveling Agent (MoNETA; Versace and Chanlder, 2010) project is to develop an animat, or virtual agent, that can intelligently interact and learn to navigate a virtual world making decisions aimed at increasing rewards while avoiding danger. The animat is designed to be modular: a whole brain system, or artificial nervous system including many cortical and subcortical areas found in mammalian brains, is progressively refined with more complex and adaptive modules, and is tested in increasingly more challenging environment. This post discusses the development of a key component of the visual system. Read the rest of this entry »

  • SSVEP-controlled robots

    By Sean Lorenz | September 2, 2011

    Both the brain-computer interface (BCI) and bran-machine interface (BMI) fields have shown some interesting applications as of late. One interesting potential is sure to be seen in the realm of EEG-controlled robotics. A partnership between the Neural Prosthetics Lab, Neuromorphics Lab, and Speech Lab at Boston University is underway to merge adaptive robotics with BCI control. Read the rest of this entry »

  • IBM Cognizer. Really?

    By Massimiliano Versace | August 25, 2011

    One of the main goals of Neurdon, since its very beginnings, was to educate readers to tell apart fiction from reality. Nowadays, big companies are diving (or dive-bombing) in the field of neural computing with hyperbolic claims of being able to simulate biological brains, from feline to humans. One of such a claim comes, again, from IBM. This is the truth behind what IBM calls "cognitive computer". Read the rest of this entry »

  • Fuzzy logic and memristive hardware

    By Massimiliano Versace | August 9, 2011

    This brief essay, originated by the work on the Neuromorphics Lab in the DARPA SyNAPSE project, describes our early effort in the study of alternative computing schemes that will make use of massive memristive-based devices coupled with low-power CMOS processes to efficiently compute neural activation and learning in novel computing devices. The answer was to couple fuzzy inference with dense memristive memory. This combination can provide extensive power and silicon real estate savings while maintaining a high degree of accuracy in the resulting precision of the computations. Read the rest of this entry »

  • Computing in the Neocortex

    By AnnMary Mathew | July 29, 2011

    More than anything, the neocortex makes us human, so it has been said. Humans are better than any other living things at reading blog posts, scheduling daily activities, and filling out tax forms, among other things mundane and not. Much progress has been made localizing certain functions to certain areas of the brain, in the neocortex in particular. Other questions remain unanswered. These include how function arises from form: how do the individual neurons cooperate together to process and combine information? What is the role of each of the six neocortical layers in information processing? What impact does network connectivity have on the shape of dynamics? How do neuronal oscillations and rhythms help process information? How are different aspects of cognition coordinated? These questions are often difficult or impossible to answer from in-vivo measurements, not only because it is currently impossible to measure the state of all neurons in the brain, but also because knowledge of the state of each neuron would create an insurmountably large dataset that would be difficult to interpret. Read the rest of this entry »

  • Silicon brains

    By Massimiliano Versace | July 19, 2011

    This article, appeared on 7/19/2011 on AZoRobotics, discusses the main reasons why I believe that we are on the verge of a paradigm shift in the way robots are going to be programmed. is part of AZoNetwork, a leading online science, engineering and medical publisher serving over 2.5 million monthly visitor sessions across its suite of sites.... so it's a good venue to get some valuable feedback.

    Click here to read the article.