Synchrony in Silicon: The Gamma Rhythm

• Published in: IEEE transactions on neural networks Vol. 18; no. 6; pp. 1815 - 1825
• Main Authors: Arthur, J.V., Boahen, K.A.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2007; Institute of Electrical and Electronics Engineers
• Subjects: Action Potentials - physiology; Animals; Applied sciences; Artificial intelligence; Binding; Cerebral Cortex - physiology; Computer science; control theory; systems; Computer Simulation; conductance-based neuron circuit; Connectionism. Neural networks; Cortical Synchronization; Delay effects; delay model of synchrony; Dendrites - physiology; Digital circuits; Electric potential; Electronics, Medical - instrumentation; Electronics, Medical - methods; Electrophysiology - instrumentation; Electrophysiology - methods; Exact sciences and technology; Excitatory Postsynaptic Potentials - physiology; Frequency synchronization; Humans; Inhibition; inhibitory interneuron; Interneurons - physiology; Models, Neurological; Neural Inhibition - physiology; Neural networks; Neural Networks (Computer); Neural Pathways - physiology; neuromorphic engineering; Neuromorphics; Neuronal Plasticity - physiology; Neurons; Procainamide; Pyramidal Cells - physiology; Rhythm; Semiconductor device modeling; shunting inhibition; Silicon; Spikes; Synapses - physiology; synaptic rise time; Timing; Voltage; Binding; neuromorphic engineering; synaptic rise time; shunting inhibition; delay model of synchrony; conductance-based neuron circuit; inhibitory interneuron; Analog circuit; Human; Brain; Role playing; Central nervous system; Neural network; Modeling; Timed system; Delay; Encephalon; Interneuron; Neurophysiology; Biomimetics; Digital circuit
• ISSN: 1045-9227; 1941-0093
• DOI: 10.1109/TNN.2007.900238

In this paper, we present a network of silicon in-terneurons 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 interneu-rons 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- mum 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.