A Neuromorphic Digital Circuit for Neuronal Information Encoding Using Astrocytic Calcium Oscillations

Abstract

Neurophysiological observations are clarifying how astrocytes can actively participate in information processing and how they can encode information through frequency and amplitude modulation of intracellular Ca2+ signals. Consequently, hardware realization of astrocytes is important for developing the next generation of bio-inspired computing systems. In this paper, astrocytic calcium oscillations and neuronal firing dynamics are presented by De Pittà and IF (Integrated & Fire) models, respectively. Considering highly nonlinear equations of the astrocyte model, linear approximation and single constant multiplication (SCM) techniques are employed for efficient hardware execution while maintaining the dynamic of the original models. This low-cost hardware architecture for the astrocyte model is able to show the essential features of different types of Ca2+ modulation such as amplitude modulation (AM), frequency modulation (FM), or both modes (AFM). To show good agreement between the results of original models simulated in MATLAB and the proposed digital circuits executed on FPGA, quantitative, and qualitative analyses including phase plane are done. This new neuromorphic circuit of astrocyte is able to successfully demonstrate AM/FM/AFM calcium signaling in its real operation on FPGA and has applications in self-repairing systems. It also can be employed as a subsystem for linking biological cells to artificial neuronal networks using astrocytic calcium oscillations in future research.

A Digital Realization of Neuroglial Interaction Model and Its Network Structure

“…The hardware analysis of the proposed astrocyte model in desynchronizing the hypersynchronous coupled neurons and regulating the synaptic transmission between presynaptic and postsynaptic neurons has the same performance of the original model. The comparison results of the hardware realization in terms of the number of resources and maximum speed have been performed between the modified models and the previous proposed tripartite synapse models in [17], [27], [43], [50]- [52]. These results are reported in Table . IV.…”

“…Furthermore, the frequency of the design in [51] is reported 139MHz. A neuromorphic digital design for neuroglial interaction model by employing the linear approximation method is realized in [52]. Based on their research work, 5 multipliers are reported in the high-level utilization table.…”

Emulation of Astrocyte Induced Neural Phase Synchrony in Spin-Orbit Torque Oscillator Neurons

“…Recently, there has been extensive literature reporting astrocyte computational models and their impact on synaptic learning (De Pittà et al, 2012 ; Manninen et al, 2018 ). Continuing these fundamental investigations to decode neuro-glia interaction, there have been recent neuromorphic implementations of astrocyte functionality in analog and digital Complementary Metal Oxide Semiconductor (CMOS) hardware (Möller et al, 2007 ; Irizarry-Valle and Parker, 2015 ; Naeem et al, 2015 ; Ranjbar and Amiri, 2017 ; Karimi et al, 2018 ; Faramarzi et al, 2019 ). For instance, analog CMOS circuits capturing the neural-glial transmitter behavior have been demonstrated (Joshi et al, 2011 ; Irizarry-Valle et al, 2013 ; Irizarry-Valle and Parker, 2015 ; Lee and Parker, 2016 ).…”

“…For instance, analog CMOS circuits capturing the neural-glial transmitter behavior have been demonstrated (Joshi et al, 2011 ; Irizarry-Valle et al, 2013 ; Irizarry-Valle and Parker, 2015 ; Lee and Parker, 2016 ). There is also increasing interest in low-complexity FPGA implementation of the astrocyte computation models (Nazari et al, 2015 ; Ranjbar and Amiri, 2016 , 2017 ; Karimi et al, 2018 ; Faramarzi et al, 2019 ). However, the primary focus has been on a brain-emulation perspective, i.e., implementing astrocyte computational models with high degree of detail in the underlying hardware.…”

Emulation of Astrocyte Induced Neural Phase Synchrony in Spin-Orbit Torque Oscillator Neurons

“…Recently, there has been extensive literature reporting astrocyte computational models and their impact on synaptic learning [8,9]. Continuing these fundamental investigations to decode neuro-glia interaction, there have been recent neuromorphic implementations of astrocyte functionality in analog and digital Complementary Metal Oxide Semiconductor (CMOS) hardware [3,[10][11][12][13][14]. While there has been extensive work on exploring post-CMOS technologies for mimicking bio-realistic computations due to the prospects of low-power and compact hardware design, they have been only studied from standalone neuron/synapse perspective.…”