Sora Ahn

Analytic Model of Spin-Torque Oscillators (STO) for Circuit-Level Simulation

Spin-torque oscillators (STO) is a new device that can be used as a tunable microwave source in various wireless devices. Spin-transfer torque effect in magnetic multilayered nanostructure can induce precession of magnetization when bias current and external magnetic field are properly applied, and a microwave signal is generated from that precession. We proposed a semi-empirical circuit-level model of an STO in previous work. In this paper, we present a refined STO model which gives more accuracy by considering physical phenomena in the calculation of effective field. Characteristics of the STO are expressed as functions of external magnetic field and bias current in Verilog-A HDL such that they can be simulated with circuit-level simulators such as Hspice. The simulation results are in good agreement with the experimental data.

Advanced Circuit-Level Model of Magnetic Tunnel Junction-based Spin-Torque Oscillator with Perpendicular Anisotropy Field

Interest in spin-torque oscillators (STOs) has been increasing due to their potential use in communication devices. In particular the magnetic tunnel junction-based STO (MTJ-STO) with high perpendicular anisotropy is gaining attention since it can generate high output power. In this paper, a circuit-level model for an in-plane magnetized MTJSTO with partial perpendicular anisotropy is proposed. The model includes the perpendicular torque and the shift field for more accurate modeling. The bias voltage dependence of perpendicular torque is represented as quadratic. The model is written in Verilog-A, and simulated using HSPICE simulator with a current-mirror circuit and a multi-stage wideband amplifier. The simulation results show the proposed model can accurately replicate the experimental data such that the power increases and the frequency decreases as the value of the perpendicular anisotropy gets close to the value of the demagnetizing field.

A New Circuit Model for Spin-Torque Oscillator Including Perpendicular Torque of Magnetic Tunnel Junction

Spin-torque oscillator (STO) is a promising new technology for the future RF oscillators, which is based on the spin-transfer torque (STT) effect in magnetic multilayered nanostructure. It is expected to provide a larger tunability, smaller size, lower power consumption, and higher level of integration than the semiconductor-based oscillators. In our previous work, a circuit-level model of the giant magnetoresistance (GMR) STO was proposed. In this paper, we present a physics-based circuit-level model of the magnetic tunnel junction (MTJ)-based STO. MTJ-STO model includes the effect of perpendicular torque that has been ignored in the GMR-STO model. The variations of three major characteristics, generation frequency, mean oscillation power, and generation linewidth of an MTJ-STO with respect to the amount of perpendicular torque, are investigated, and the results are applied to our model. The operation of the model was verified by HSPICE simulation, and the results show an excellent agreement with the experimental data. The results also prove that a full circuit-level simulation with MJT-STO devices can be made with our proposed model.

Computational modeling of epileptiform activities in medial temporal lobe epilepsy combined with in vitro experiments

In this paper, we propose a comprehensive computational model that is able to reproduce three epileptiform activities. The model targets a hippocampal formation that is known to be an important lesion in medial temporal lobe epilepsy. It consists of four sub-networks consisting of excitatory and inhibitory neurons and well-known signal pathways, with consideration of propagation delay. The three epileptiform activities involve fast and slow interictal discharge and ictal discharge, and those activities can be induced in vitro by application of 4-Aminopyridine in entorhinal cortex combined hippocampal slices. We model the three epileptiform activities upon previously reported biological mechanisms and verify the simulation results by comparing them with in vitro experimental data obtained using a microelectrode array. We use the results of Granger causality analysis of recorded data to set input gains of signal pathways in the model, so that the compatibility between the computational and experimental models can be improved. The proposed model can be expanded to evaluate the suppression effect of epileptiform activities due to new treatment methods.

Study on the mechanisms of seizure-like events suppression effect by electrical stimulation using a microelectrode array

In this paper, we studied the mechanisms underlying the suppression of seizure-like events (SLEs) by electrical stimulation. We conducted an in-vitro experiment using entorhinal cortex combined hippocampal slices and two convulsant drugs, bicuculline and 4-aminopyridine, to induce spontaneous SLEs. We used a microelectrode array to observe network dynamics over the entire hippocampal area simultaneously, including regions far from the stimulation site. We stimulated the entorhinal cortex region, which has been determined to be a focus of SLEs by Granger causality analysis of multichannel time series data, by an external electrode. In bicuculline application, electrical stimulation showed a marked suppression effect, even though the sizes of the effective region differed. In 4-aminopyridine application, however, stimulation under the same conditions did not suppress the activities in ∼80% of SLEs. The suppression effect was more remarkable in the areas surrounding the stimulation site in both cases. Our experimental results could support the neuronal depolarization blockade mechanism by accumulation of extracellular potassium ions, which is one of the most convincing mechanisms to understand seizure suppression phenomena because of electrical stimulation. Computer simulation using a neuronal network model also confirmed the mechanism.

Physics-Based SPICE Model of Spin-Torque Oscillators

The spin-torque oscillator (STO) is a new compact device operating as a tunable RF oscillator in the tens of gigahertz range whose characteristics are determined by the applied current and magnetic field. In this paper, we present a physics-based empirical circuit-level model of an STO that is compatible with circuit-level simulators such as SPICE. The characteristics of an STO are modeled as physics-based analytic functions of the applied current and external magnetic field. The validity of our model was verified by the HSPICE simulation of a current mirror circuit that contains an STO element. The simulation results are in good agreement with the experimental data in the normal operation range. High-order nonlinear effects at large currents are not included in our model because there is no theoretical equation available yet that can precisely explain these effects.

Prediction of the Seizure Suppression Effect by Electrical Stimulation via a Computational Modeling Approach

In this paper, we identified factors that can affect seizure suppression via electrical stimulation by an integrative study based on experimental and computational approach. Preferentially, we analyzed the characteristics of seizure-like events (SLEs) using our previous in vitro experimental data. The results were analyzed in two groups classified according to the size of the effective region, in which the SLE was able to be completely suppressed by local stimulation. However, no significant differences were found between these two groups in terms of signal features or propagation characteristics (i.e., propagation delays, frequency spectrum, and phase synchrony). Thus, we further investigated important factors using a computational model that was capable of evaluating specific influences on effective region size. In the proposed model, signal transmission between neurons was based on two different mechanisms: synaptic transmission and the electrical field effect. We were able to induce SLEs having similar characteristics with differentially weighted adjustments for the two transmission methods in various noise environments. Although the SLEs had similar characteristics, their suppression effects differed. First of all, the suppression effect occurred only locally where directly received the stimulation effect in the high noise environment, but it occurred in the entire network in the low noise environment. Interestingly, in the same noise environment, the suppression effect was different depending on SLE propagation mechanism; only a local suppression effect was observed when the influence of the electrical field transmission was very weak, whereas a global effect was observed with a stronger electrical field effect. These results indicate that neuronal activities synchronized by a strong electrical field effect respond more sensitively to partial changes in the entire network. In addition, the proposed model was able to predict that stimulation of a seizure focus region is more effective for suppression. In conclusion, we confirmed the possibility of a computational model as a simulation tool to analyze the efficacy of deep brain stimulation (DBS) and investigated the key factors that determine the size of an effective region in seizure suppression via electrical stimulation.

Computational model of medial temporal lobe epilepsy

Temporal lobe epilepsy represents a high proportion of whole epilepsy patients. Medial temporal lobe epilepsy (MTLE) is generated from internal structures like hippocampus, and patients with MTLE are poorly controlled by antiepileptic drugs [1]. Recently, deep brain stimulation (DBS) that is to control seizure activity by stimulating epileptic zone is receiving attention as a new treatment of epilepsy. However, the exact mechanisms are still unclear and the current method is being developed relying on clinical experiences. Consequently, researches for etiology of disease along with seizure suppress mechanisms by electrical stimulation are very significant. These studies would be best progressed with complementary cooperation between in-vitro and in-vivo experiments, and computer simulations using a computational model. In this paper, we propose a hippocampal network model which portrays seizure-like events (SLEs) recorded in in-vitro experiments. The model is composed of excitatory and inhibitory neurons interconnected following the well-known synaptic pathway to form a small world network [2]. Each neuron is descripted by Izhikevichs model [3] and synaptic current is calculated based on conductance of a receptor. Short-term and long-term plasticity are also applied to every synapse [4]. SLEs induced by 4-AP are divided into three regions according to time-frequency features. The first region is transition to ictal region by excitatory GABAergic drive [5], the second region is tonic firing region by synchronization due to recurrent excitation between principle neurons [6], and the last region is clonic bursting and termination region by GABA-mediated inhibitory mechanisms [1]. Proposed model faithfully reproduces these phenomena by controlling synaptic input gain. The effectiveness of the model is confirmed by comparing the simulation results with experimental data which were recorded in rat hippocampal slice in 4-AP bath application using micro-electrode array (MEA). Below Figure ​Figure11 are time domain signals generated from computer model and recorded in in-vitro measurement, respectively. Figure 1 Recording data (left) and simulation result (right) of seizure-like events in entorhinal cortex.

Circuit-Level Model of Phase-Locked Spin-Torque Oscillators

Spin-torque oscillators (STOs) are new oscillating devices based on spintronics technology with many advantageous features, i.e., nanoscale size, high tunability, and compatibility with standard silicon processing. Recent research has shown that two electrically connected STOs may operate as a single device when specific conditions are met. To overcome the limitation of the small output power of STOs, the phase-locking behavior of multiple STOs is hereby extensively investigated. In this paper, we present a circuit-level model of two coupled STOs considering the interaction between them such that it can represent the phase-locking behavior of multiple STOs. In our model, the characteristics of each STO are defined first as functions of applied DC current and external magnetic field. Then, the phase-locking condition is examined to determine the properties of the two coupled STOs on the basis of a theoretical model. The analytic model of two coupled STOs is written in Verilog-A hardware description language. The behavior of the proposed model is verified by circuit-level simulation using HSPICE with CMOS circuits including a current-mirror circuit and differential amplifiers. Simulation results with various CMOS circuits have confirmed the effectiveness of our model.

Circuit Level Model of Phase-Locked Spin Torque Oscillators

Spin-torque oscillators (STOs) are new oscillating devices based on spintronics technology with many advantageous features, i.e., nanoscale size, high tunability, and compatibility with standard silicon processing. Recent research has shown that two electrically connected STOs may operate as a single device when specific conditions are met. To overcome the limitation of the small output power of STOs, the phase-locking behavior of multiple STOs is hereby extensively investigated. In this paper, we present a circuit-level model of two coupled STOs considering the interaction between them such that it can represent the phase-locking behavior of multiple STOs. In our model, the characteristics of each STO are defined first as functions of applied DC current and external magnetic field. Then, the phase-locking condition is examined to determine the properties of the two coupled STOs on the basis of a theoretical model. The analytic model of two coupled STOs is written in Verilog-A hardware description language. The behavior of the proposed model is verified by circuit-level simulation using HSPICE with CMOS circuits including a current-mirror circuit and differential amplifiers. Simulation results with various CMOS circuits have confirmed the effectiveness of our model. # 2013 The Japan Society of Applied Physics