Bio


Boahen's research interests include mixed-mode multichip VLSI models of biological sensory and perceptual systems, their epigenetic development, and asynchronous digital communication for reconfigurable connectivity.

Academic Appointments


Honors & Awards


  • NIH Director's Pioneer Award, National Institute of Health (2006)
  • Young Investigator Program, Office of Naval Research (2002-present)
  • Faculty Early Career Program, National Science Foundation (2001-present)
  • Fellowships in Science and Engineering, Packard Foundation (1999-2004)

Professional Education


  • PhD, Caltech (1997)

Current Research and Scholarly Interests


Large-scale models of sensory, perceptual and motor systems

2015-16 Courses


All Publications


  • Synchrony in silicon: The gamma rhythm IEEE TRANSACTIONS ON NEURAL NETWORKS Arthur, J. V., Boahen, K. A. 2007; 18 (6): 1815-1825

    Abstract

    In this paper, we present a network of silicon interneurons that synchronize in the gamma frequency range (20-80 Hz). The gamma rhythm strongly influences neuronal spike timing within many brain regions, potentially playing a crucial role in computation. Yet it has largely been ignored in neuromorphic systems, which use mixed analog and digital circuits to model neurobiology in silicon. Our neurons synchronize by using shunting inhibition (conductance based) with a synaptic rise time. Synaptic rise time promotes synchrony by delaying the effect of inhibition, providing an opportune period for interneurons to spike together. Shunting inhibition, through its voltage dependence, inhibits interneurons that spike out of phase more strongly (delaying the spike further), pushing them into phase (in the next cycle). We characterize the interneuron, which consists of soma (cell body) and synapse circuits, fabricated in a 0.25-microm complementary metal-oxide-semiconductor (CMOS). Further, we show that synchronized interneurons (population of 256) spike with a period that is proportional to the synaptic rise time. We use these interneurons to entrain model excitatory principal neurons and to implement a form of object binding.

    View details for DOI 10.1109/TNN.2007.900238

    View details for Web of Science ID 000250789100019

    View details for PubMedID 18051195