• Neuromorphic Engineering Overview

    Neuromorphic engineering, also known as neuromorphic computing, is a concept developed by Carver Mead, in the late 1980s, describing the use of very-large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures present in the nervous system.

    In recent times the term neuromorphic has been used to describe analog, digital, and mixed-mode analog/digital VLSI and software systems that implement models of neural systems (for perception, motor control, or multisensory integration).

  • Big Neuron – Towards Big Data in Neuroscience

    This year Hanchuan Peng (Allen Institute for Brain Science) began the next phase of the effort called Big Neuron. However, rather than a competition, this time the project would be a collaboration.

    The key idea is to create a single platform on which all algorithms can be run, compared, and their results combined to form reconstructions better than any one could achieve alone.

  • Todd Gillette

    Ph.D. in Neuroscience
    Research Assistant in the Center for Neural Informatics, Neural Structures, and Neural Plasticity (CN3)
    Curator of the Neuroscience Knowledge Network (NKN)

  • Neurotechnology Panel at Potomac Policy Institute

    A SEMINAR ON “NEUROTECHNOLOGY: ENHANCING THE HUMAN BRAIN AND RESHAPING SOCIETY”

    From the Potomac Institute for Policy Studies:

    The …

  • ‘Mental Floss’ Project Brings Artists and Scientists Together

    Mason faculty and students create an interpretive 3-D sculpture called “Mental Floss.” The sculpture depicts 13 different neurons that are located in the hippocampus, the region of the brain responsible for processing autobiographical memories.

    “Our goal for this project was to provoke viewers to ponder not only how intricate and complex the inner fabric of the brain appears, but also how beautiful and awe-inspiring it can be, providing a bridge between rational thought and emotions,” says Ascoli.

  • Neuromorphic Engineering Overview

    Neuromorphic engineering, also known as neuromorphic computing, is a concept developed by Carver Mead, in the late 1980s, describing the use of very-large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures present in the nervous system.

    In recent times the term neuromorphic has been used to describe analog, digital, and mixed-mode analog/digital VLSI and software systems that implement models of neural systems (for perception, motor control, or multisensory integration).

  • Big Neuron – Towards Big Data in Neuroscience

    This year Hanchuan Peng (Allen Institute for Brain Science) began the next phase of the effort called Big Neuron. However, rather than a competition, this time the project would be a collaboration.

    The key idea is to create a single platform on which all algorithms can be run, compared, and their results combined to form reconstructions better than any one could achieve alone.

  • Todd Gillette

    Ph.D. in Neuroscience
    Research Assistant in the Center for Neural Informatics, Neural Structures, and Neural Plasticity (CN3)
    Curator of the Neuroscience Knowledge Network (NKN)

  • Doctoral Dissertation Globally aligning tree sequences

    My dissertation, entitled “Comparative topological analysis of neuronal arbors via sequence representation and alignment”, is focused on applying bioinformatic approaches to neuronal morphology to enable new discoveries and increase understanding about how morphology and neuron function interrelate.

  • Alignment and cluster analysis of neuronal tree sequences Multiple Sequence Alignment

    Alignment of neurons represented as sequences of branching points can be used to detect clusters of similar neurons which can then be investigated for their stereotypical branching patterns. We use a modified sequence alignment procedure to produce pairwise similarity values between two neuronal sequences and then, after embedding the neurites (axons, dendrites, or apical dendrites) into a consistent abstract space, we found clusters in the space. By overlaying those clusters with known cell classes we found significant associations. There were strong associations by cell type, brain region, and species, indicating that neuronal branching patterns are indicative of neuronal type and function.

  • IBM’s TrueNorth – The first neuromorphic chip

    IBM has recently released details of a neuromorphic chip named TrueNorth via their website, the press, and a research report in the journal Science. The research team, headed by Dharmendra Modha as part of the DARPA SyNAPSE Program, developed a chip containing a million “programmable spiking neurons” and 256 million synapses. The chips use 5.4 billion transistors on 4096 “neurosynaptic cores” which each has its memory (in the form of connection routing and timing delays) close to its “neuronal” processing units.

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