Toru Aonishi

811 total citations
52 papers, 436 citations indexed

About

Toru Aonishi is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Cellular and Molecular Neuroscience. According to data from OpenAlex, Toru Aonishi has authored 52 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Cognitive Neuroscience, 19 papers in Artificial Intelligence and 14 papers in Cellular and Molecular Neuroscience. Recurrent topics in Toru Aonishi's work include Neural dynamics and brain function (21 papers), stochastic dynamics and bifurcation (10 papers) and Quantum Computing Algorithms and Architecture (9 papers). Toru Aonishi is often cited by papers focused on Neural dynamics and brain function (21 papers), stochastic dynamics and bifurcation (10 papers) and Quantum Computing Algorithms and Architecture (9 papers). Toru Aonishi collaborates with scholars based in Japan and United States. Toru Aonishi's co-authors include Masato Okada, Hiroyoshi Miyakawa, Masashi Inoue, Toshiaki Omori, Keisuke Ota, Ichiro Kato, Y. Yamamoto, Masato Okada, Yoshitaka Inui and Satoshi Kako and has published in prestigious journals such as Physical Review Letters, PLoS ONE and Journal of Applied Physics.

In The Last Decade

Toru Aonishi

49 papers receiving 428 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Toru Aonishi Japan 12 201 129 118 83 71 52 436
Valentin Zhigulin United States 7 241 1.2× 57 0.4× 111 0.9× 109 1.3× 118 1.7× 10 451
Kamiar Rahnama Rad United States 10 169 0.8× 87 0.7× 73 0.6× 64 0.8× 66 0.9× 20 349
Chad Giusti United States 9 293 1.5× 50 0.4× 50 0.4× 65 0.8× 164 2.3× 15 681
László Orzó Hungary 11 70 0.3× 81 0.6× 66 0.6× 108 1.3× 22 0.3× 37 320
Eyal Hulata Israel 8 350 1.7× 65 0.5× 245 2.1× 45 0.5× 104 1.5× 12 550
Michael Denker Germany 14 449 2.2× 49 0.4× 321 2.7× 55 0.7× 63 0.9× 38 630
Martina Scolamiero Sweden 5 135 0.7× 29 0.2× 48 0.4× 44 0.5× 105 1.5× 8 485
Diek W. Wheeler United States 15 438 2.2× 93 0.7× 376 3.2× 170 2.0× 166 2.3× 33 753
Douglas Zhou China 15 344 1.7× 51 0.4× 181 1.5× 65 0.8× 200 2.8× 56 570
Michael Reimann Switzerland 11 510 2.5× 25 0.2× 297 2.5× 51 0.6× 84 1.2× 45 762

Countries citing papers authored by Toru Aonishi

Since Specialization
Citations

This map shows the geographic impact of Toru Aonishi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Toru Aonishi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Toru Aonishi more than expected).

Fields of papers citing papers by Toru Aonishi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Toru Aonishi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Toru Aonishi. The network helps show where Toru Aonishi may publish in the future.

Co-authorship network of co-authors of Toru Aonishi

This figure shows the co-authorship network connecting the top 25 collaborators of Toru Aonishi. A scholar is included among the top collaborators of Toru Aonishi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Toru Aonishi. Toru Aonishi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Aonishi, Toru, et al.. (2024). Highly Versatile FPGA-Implemented Cyber Coherent Ising Machine. IEEE Access. 12. 175843–175865. 1 indexed citations
2.
Sasaki, R, et al.. (2023). Effect of Coupling Discretization on Coherent-Ising-Machine-Implemented Hopfield Model. Journal of the Physical Society of Japan. 92(4). 2 indexed citations
3.
Kako, Satoshi, et al.. (2023). Effective implementation of $$\text{L}{0}$$-regularised compressed sensing with chaotic-amplitude-controlled coherent Ising machines. Scientific Reports. 13(1). 16140–16140. 5 indexed citations
4.
Inui, Yoshitaka, et al.. (2023). Mean-field coherent Ising machines with artificial Zeeman terms. Journal of Applied Physics. 134(23). 6 indexed citations
5.
Aonishi, Toru, Tetsuya Kitaguchi, Harumi Takahashi, et al.. (2022). Dopamine Negatively Regulates Insulin Secretion Through Activation of D1-D2 Receptor Heteromer. Diabetes. 71(9). 1946–1961. 13 indexed citations
6.
Ishibashi, Masayuki, et al.. (2022). Computational model predicts the neural mechanisms of prepulse inhibition in Drosophila larvae. Scientific Reports. 12(1). 15211–15211.
7.
Ota, Keisuke, Yasuhiro Oisi, Chie Matsubara, et al.. (2022). Low computational-cost cell detection method for calcium imaging data. Neuroscience Research. 179. 39–50. 4 indexed citations
8.
9.
Aonishi, Toru, et al.. (2018). A numerical inversion method for improving the spatial resolution of elemental imaging by laser ablation-inductively coupled plasma-mass spectrometry. Journal of Analytical Atomic Spectrometry. 33(12). 2210–2218. 6 indexed citations
10.
Morimoto, Takako, et al.. (2014). A novel behavioral strategy, continuous biased running, during chemotaxis in Drosophila larvae. Neuroscience Letters. 570. 10–15. 12 indexed citations
11.
Suzuki, Yoshinori, Takako Morimoto, Hiroyoshi Miyakawa, & Toru Aonishi. (2014). Cooperative Integration and Representation Underlying Bilateral Network of Fly Motion-Sensitive Neurons. PLoS ONE. 9(1). e85790–e85790. 1 indexed citations
12.
Ota, Keisuke, et al.. (2013). Optimal Design for Hetero-Associative Memory: Hippocampal CA1 Phase Response Curve and Spike-Timing-Dependent Plasticity. PLoS ONE. 8(10). e77395–e77395. 4 indexed citations
13.
Aonishi, Toru, et al.. (2011). Detection of cells from calcium imaging data using non-negative matrix factorization. IEICE Technical Report; IEICE Tech. Rep.. 111(96). 3–8. 1 indexed citations
14.
Ota, Keisuke, et al.. (2011). Measurement of infinitesimal phase response curves from noisy real neurons. Physical Review E. 84(4). 41902–41902. 18 indexed citations
15.
Monai, Hiromu, Toshiaki Omori, Masato Okada, et al.. (2010). An Analytic Solution of the Cable Equation Predicts Frequency Preference of a Passive Shunt-End Cylindrical Cable in Response to Extracellular Oscillating Electric Fields. Biophysical Journal. 98(4). 524–533. 12 indexed citations
16.
Omori, Toshiaki, Toru Aonishi, & Masato Okada. (2010). Switch of encoding characteristics in single neurons by subthreshold and suprathreshold stimuli. Physical Review E. 81(2). 21901–21901. 3 indexed citations
17.
Omori, Toshiaki, Toru Aonishi, Hiroyoshi Miyakawa, Masashi Inoue, & Masato Okada. (2009). Steep decrease in the specific membrane resistance in the apical dendrites of hippocampal CA1 pyramidal neurons. Neuroscience Research. 64(1). 83–95. 9 indexed citations
18.
Ota, Keisuke, Toshiaki Omori, & Toru Aonishi. (2008). MAP estimation algorithm for phase response curves based on analysis of the observation process. Journal of Computational Neuroscience. 26(2). 185–202. 17 indexed citations
19.
Omori, Toshiaki, Toru Aonishi, Hiroyoshi Miyakawa, Masashi Inoue, & Masato Okada. (2006). Estimated distribution of specific membrane resistance in hippocampal CA1 pyramidal neuron. Brain Research. 1125(1). 199–208. 12 indexed citations
20.
Aonishi, Toru & Masato Okada. (2003). Dynamically Coupled Oscillators: Cooperative Behavior via Dynamical Interaction. Journal of the Physical Society of Japan. 72(6). 1334–1337.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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