Toru Aonishi

The University of Tokyo | Todai · Department of Complexity Science and Engineering

In recent years, quantum Ising machines have drawn a lot of attention, but due to physical implementation constraints, it has been difficult to achieve dense coupling, such as full coupling with sufficient spins to handle practical large-scale applications. Consequently, classically computable equations have been derived from quantum master equatio...

Coherent Ising Machine (CIM) is a network of optical parametric oscillators that solves combinatorial optimization problems by finding the ground state of an Ising Hamiltonian. As a practical application of CIM, Aonishi et al. proposed a quantum-classical hybrid system to solve optimization problems of L0-regularization-based compressed sensing (L0...

To solve large-scale real-world problems, attempts have been made to realize high-speed simulations of quantum Ising machines using field-programmable gate arrays (FPGAs) and to virtually realize networks with a large number of fully coupled spins, which are difficult to achieve in physical systems. We developed an FPGA-implemented cyber coherent I...

Coherent Ising Machine (CIM) is a network of optical parametric oscillators that solve combinatorial optimization problems by finding the ground state of an Ising Hamiltonian. In CIMs, a problem arises when attempting to realize the Zeeman term because of the mismatch in size between interaction and Zeeman terms due to the variable amplitude of the...

Coherent Ising machine (CIM) is a network of optical parametric oscillators that can solve large-scale combinatorial optimisation problems by finding the ground state of an Ising Hamiltonian. As a practical application of CIM, Aonishi et al., proposed a quantum-classical hybrid system to solve optimisation problems of l0\documentclass[12pt]{minimal...

Coherent Ising Machine (CIM) is a network of optical parametric oscillators that solves combinatorial optimization problems by finding the ground state of an Ising Hamiltonian. In CIMs, a problem arises when attempting to realize the Zeeman term because of the mismatch in size between interaction and Zeeman terms due to the variable amplitude of th...

We attempt to estimate the spatial distribution of heterogeneous physical parameters involved in the formation of magnetic domain patterns of polycrystalline thin films by using convolutional neural networks. We propose a method to obtain a spatial map of physical parameters by estimating the parameters from patterns within a small subregion window...

Coherent Ising Machine (CIM) is a network of optical parametric oscillators that can solve large-scale combinatorial optimisation problems by finding the ground state of an Ising Hamiltonian. As a practical application of CIM, Aonishi et al., proposed a quantum-classical hybrid system to solve optimisation problems of l0-regularisation-based compre...

Prepulse inhibition (PPI) is a behavioural phenomenon in which a preceding weaker stimulus suppresses the startle response to a subsequent stimulus. The effect of PPI has been found to be reduced in psychiatric patients and is a promising neurophysiological indicator of psychiatric disorders. Because the neural circuit of the startle response has b...

There is increasing evidence that dopamine (DA) functions as a negative regulator of glucose-stimulated insulin secretion (GSIS); however, the underlying molecular mechanism remains unknown. Using total internal reflection fluorescence microscopy, we monitored insulin granule exocytosis in primary islet cells to dissect the effect of DA. We found t...

A coherent Ising machine (CIM) is an open-dissipative Ising solver using optical pulses generated from a degenerate optical parametric oscillator as analog magnetizations. When solving real-world optimization problems with CIM, this solver has two difficulties: mutual coupling induced amplitude inhomogeneity and absence of natural way to implement...

L0-regularization-based compressed sensing (L0-RBCS) has the potential to outperform L1-regularization-based compressed sensing (L1-RBCS), but the optimization in L0-RBCS is difficult because it is a combinatorial optimization problem. To perform optimization in L0-RBCS, we propose a quantum-classical hybrid system consisting of a quantum machine a...

The rapid progress of calcium imaging techniques has reached a point where the activity of thousands to tens of thousands of cells can be recorded simultaneously with single-cell resolution in a field-of-view (FOV) of about ten mm². Consequently, there is a pressing need for developing automatic cell detection methods for large-scale image data. Se...

The rapid progress of imaging devices such as two-photon microscopes has made it possible to measure the activity of thousands to tens of thousands of cells at single-cell resolution in a wide field of view (FOV) data. However, it is not possible to manually identify thousands of cells in such wide FOV data. Several research groups have developed m...

Growing demand for high-speed Ising-computing-specific hardware has prompted a need for determining how the accuracy depends on a hardware implementation with physically limited resources. For instance, in digital hardware such as field-programmable gate arrays, as the number of bits representing the coupling strength is reduced, the density of int...

Fast and wide field-of-view imaging with single-cell resolution, high signal-to-noise ratio, and no optical aberrations have the potential to inspire new avenues of investigations in biology. However, such imaging is challenging because of the inevitable tradeoffs among these parameters. Here, we overcome these tradeoffs by combining a resonant sca...

Markov Random Field (MRF) models have become increasingly necessary especially in data-driven science. There are two kinds of MRF model applicable to image segmentation: edge-based and region-based. The region-based model is more easily implemented and is more robust to noise than the edge-based model. However, the region-based model often becomes...

L0-regularization-based compressed sensing (L0-RBCS) has the potential to outperform L1-regularization-based compressed sensing (L1-RBCS), but the optimization in L0-RBCS is difficult because it is a combinatorial optimization problem. To perform optimization in L0-RBCS, we propose a quantum-classical hybrid system consisting of a quantum machine a...

The question of how to understand the underlying mechanisms of complicated spatiotemporal patterns formed in various physical, chemical, and biological systems is still and open issue. Here, we give a successful example using the machine learning methods of a convolutional neural network (CNN) and a kernel ridge regression (KRR). By using these met...

Lithium-ion secondary batteries have been used in a wide variety of purposes, such as for powering mobile devices and electric vehicles, but their performance should be improved. One of the factors that limits their performance is the non-uniformity of the chemical reaction in the process of charging and discharging. Many attempts have been made to...

Fast and wide imaging with single-cell resolution, high signal-to-noise ratio and no optical aberration has the potential to open up new avenues of investigation in biology. However, this imaging is challenging because of the inevitable tradeoffs among those parameters. Here, we overcome the tradeoffs by combining a resonant scanning system, a larg...

Growing demand for high-speed Ising-computing-specific hardware has prompted a need for determining how the accuracy depends on a hardware implementation with physically limited resources. For instance, in digital hardware such as field-programmable gate arrays, as the number of bits representing the coupling strength is reduced, the density of int...

Neurons in the central nervous systems are exposed to endogenous oscillating electric fields and their activities are likely to be modified by those fields. We had previously investigated the effects of AC electric field by using a newly developed method to monitor local Ca transients in the dendrites of a neuronal population in acute rat hippocamp...

The scalability and computational ability of the coherent Ising machine (CIM) have made it attract attention as one of the most effective Ising computing architectures for solving large-scale optimization problems. However, the theory and techniques of equilibrium classical thermodynamics cannot be directly applied to the CIM because it is an open-...

The rapid progress of calcium imaging has reached a point where the activity of tens of thousands of cells can be recorded simultaneously. However, the huge amount of data in such records makes manual analysis difficult. Consequently, there is a pressing need for automatic analysis for large-scale image data. Some automatic cell detection methods u...

The coherent Ising machine (CIM) has attracted attention as one of the most effective Ising comput-ing architectures for solving large-scale optimization problems because of its scalability and high-speed computational ability. The CIM is a non-equilibrium open-dissipative system, so the theoriesand techniques of classical equilibrium thermodynamic...

To improve the spatial resolution of two-dimensional elemental images in solid organic and inorganic materials, a novel numerical correction method was developed for laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). Diffusion and dilution of LA aerosol particles in the carrier gas during transportation from the LA cell to the...

The motion detection mechanism of insects has been attracted attention of many researchers. Several motion-detection models have been proposed on the basis of insect visual system studies. Here, we examine two models, the Hassenstein-Reichardt (HR) model and the two-detector (2D) model. We analytically obtain the mean and variance of the stationary...

Several motion-detection models have been proposed based on insect visual system studies. We specifically examine two models, the Hassenstein-Reichardt (HR) model and the two-detector (2D) model, before selecting model the more efficient motion encoders. We analytically obtained the mean and variance of stationary responses of the HR and the 2D mod...

The coherent Ising machine (CIM) has attracted attention as one of the most effective Ising computing architectures for solving large scale optimization problems because of its scalability and high-speed computational ability. However, it is difficult to implement the Ising computation in the CIM because the theories and techniques of classical the...

We propose a cell detection algorithm using non-negative matrix factorization (NMF) on Ca$^{2+}$ imaging data. To apply NMF to Ca$^{2+}$ imaging data, we use the bleaching line of the background fluorescence intensity as an a priori background constraint to make the NMF uniquely dissociate the background component from the image data. This constrai...

Appropriate and robust behavioral control in a noisy environment is important for the survival of most organisms. Understanding such robust behavioral control has been an attractive subject in neuroscience research. Here, we investigated the processing of wide-field motion with random dot noise at both the behavioral and neuronal level in Drosophil...

Neurons might interact via electric fields and this notion has been referred to as ephaptic interaction. It has been shown that various types of ion channels are distributed along the dendrites and are capable of supporting generation of dendritic spikes. We hypothesized that generation of dendritic spikes play important roles in the ephaptic inter...

The phase response curve (PRC) is an important measure representing the interaction between oscillatory elements. To understand synchrony in biological systems, many research groups have sought to measure PRCs directly from biological cells including neurons. Ermentrout et al. and Ota et al. showed that PRCs can be identified through measurement of...

Animals collect and integrate information from their environment, and select an appropriate strategy to elicit a behavioral response. Here, we investigate the behavioral strategy employed by Drosophila larvae during chemotaxis toward a food source functioning as an attractive odor source. In larvae, sharp turns have been identified as the main stra...

We propose a cell detection algorithm using non-negative matrix factorization (NMF) on Ca(2+) imaging data. To apply NMF to Ca(2+) imaging data, we use the bleaching line of the background fluorescence intensity as an a priori background constraint to make the NMF uniquely dissociate the background component from the image data. This constraint hel...

How is binocular motion information integrated in the bilateral network of wide-field motion-sensitive neurons, called lobula plate tangential cells (LPTCs), in the visual system of flies? It is possible to construct an accurate model of this network because a complete picture of synaptic interactions has been experimentally identified. We investig...

Many associative memory models with synaptic decay such as the forgetting model and the zero-order decay model have been proposed and studied so far. The previous studies showed the relation between the storage capacity C and the synaptic decay coefficient a in each synaptic decay model. However, with the exceptions of a few studies, they did not c...

We verify whether the optimal pairs of coupling functions and spike-timing-dependent plasticity (STDP) window functions for executing the auto-associative memory algorithm derived from the viewpoint of hardware implementation are identical to those derived from the computational viewpoint by Lengyel et al. (2005). With a zero noise limit, we obtain...

Recently reported experimental findings suggest that the hippocampal CA1 network stores spatio-temporal spike patterns and retrieves temporally reversed and spread-out patterns. In this paper, we explore the idea that the properties of the neural interactions and the synaptic plasticity rule in the CA1 network enable it to function as a hetero-asso...

Recently reported experimental findings suggest that the hippocampal CA1 network stores spatio-temporal spike patterns and retrieves temporally reversed and spread-out patterns. In this paper, we explore the idea that the properties of the neural interactions and the synaptic plasticity rule in the CA1 network enable it to function as a hetero-asso...

Recently reported experimental findings suggest that the hippocampal CA1 network stores spatio-temporal spike patterns and retrieves temporally reversed [1] and spread-out [2] patterns. In this paper, we explore the idea that the properties of the neural interactions and the synaptic plasticity rule in the CA1 network enable it to function as a het...

Experience in early life can affect the development of the nervous system. There is now evidence that experience-dependent plasticity exists in adult insects. To uncover the molecular basis of plasticity, an invertebrate model, such as Drosophila melanogaster, is a powerful tool, as many established genetic and molecular methods can be applied. To...

We propose a statistical method for estimating the spatial distribution of membrane properties that are non-uniformly distributed over dendrites from partially observable noisy data. We used the Bayesian statistical approach to extract the hidden but substantial information about the distribution of membrane properties over the dendrites. Simulated...

The dielectric properties of brain tissue are important for understanding how neural activity is related to local field potentials and electroencephalograms. It is known that the permittivity of brain tissue exhibits strong frequency dependence (dispersion) and that the permittivity is very large in the low-frequency region. However, little is know...

For the purpose of elucidating the neural coding process based on the neural excitability mechanism, researchers have recently investigated the relationship between neural dynamics and the spike triggered stimulus ensemble (STE). Ermentrout et al. analytically derived the relational equation between the phase response curve (PRC) and the spike trig...

In this paper, we investigate the effect of synaptogenesis on memories in the brain, using the abstract-associative memory model, Hopfield model with the zero-order synaptic decay. Using the numerical simulation, we demonstrate the possibility that synaptogenesis plays a role in maintaining recent memories embedded in the network while avoiding ove...

This article provides a theoretical basis for relating macroscopic electrical signals recorded from biological tissue, such as electroencephalogram (EEG) and local field potential (LFP), to the electrophysiological processes at the cellular level in a manner consistent with Maxwell's equations. Concepts of the apparent extracellular current density...

We investigate a sparsely encoded Hopfield model with unit replacement by using a statistical mechanical method called self-consistent signal-to-noise analysis. We theoretically obtain a relation between the storage capacity and the number of replacement units for each sparseness a. Moreover, we compare the unit replacement model with the forgettin...

Many research groups have sought to measure phase response curves (PRCs) from real neurons. In contrast to the numerical calculations of the PRCs for the mathematical neuron models, electrophysiological experiments on real neurons face serious problems whereby PRCs have to be retrieved from noisy data. However, methods for estimating PRCs from nois...

With developments in optical imaging over the past decade, statistical methods for estimating dendritic membrane resistance from observed noisy signals have been proposed. In most of previous studies, membrane resistance over a dendritic tree was assumed to be constant, or membrane resistance at a point rather than that over a dendrite was investig...

One of the more useful tools for better understanding population dynamics is the phase response curve (PRC). Recent physiological experiments on the PRCs using real neurons showed that different shapes of the PRCs are generated depending on the perturbation, which has a finite amplitude. In order to clarify the origin of the nonlinear response of t...

We sought to measure infinitesimal phase response curves (iPRCs) from rat hippocampal CA1 pyramidal neurons. It is difficult to measure iPRCs from noisy neurons because of the dilemma that either the linearity or the signal-to-noise ratio of responses to external perturbations must be sacrificed. To overcome this difficulty, we used an iPRC measure...

A calcium imaging method has superior ability in recording of spatial temporal variations in ion concentration. However, it has two major problems. First, the imaging signals are very noisy. Second, the observation data are only the fluorescence intensities of Ca2+ indicator dyes that provide indirect information about the Ca2+ concentration. We de...

The Hopfield model has a storage capacity: the maximum number of memory patterns that can be stably stored. The memory state of this network model disappears if the number of embedded memory patterns is larger than 0.138N, where N is the system size. Recently, it has been shown in numerical simulations that the Hopfield model with a unit replacemen...

Under physiological and artificial conditions, the dendrites of neurons can be exposed to electric fields. Recent experimental studies suggested that the membrane resistivity of the distal apical dendrites of cortical and hippocampal pyramidal neurons may be significantly lower than that of the proximal dendrites and the soma. To understand the beh...

Spike-triggered analysis is a statistical method used to elucidate encoding properties in neural systems by estimating the statistical structure of input stimulus preceding spikes. A recent numerical study suggested that the profile of the spike-triggered average (STA) changes depending on whether the mean input stimuli are subthreshold or suprathr...

Calcium imaging method has superior ability in recording of spatial-temporal variations of ion concentrations. However, it has two major problems. First, the imaging signals are too noisy. Second, the observation data are the fluorescent intensities of Ca2+ indicator dyes that are only indirect information about the Ca2+ concentration. We made a no...