Article
Nanoscience & Nanotechnology
Ruofei Hu, Xinyi Li, Jianshi Tang, Yijun Li, Xiaojian Zheng, Bin Gao, He Qian, Huaqiang Wu
Summary: This paper investigates two distinct types of resistive switching in Ti/TiOx/Pd-based RRAM devices: filamentary resistive switching and dynamic resistive switching. Filamentary resistive switching is caused by spikes in the bottom Pd electrode, while dynamic resistive switching occurs when the bottom electrode is flat without spikes, resulting in dynamic changes in device resistance over time.
ADVANCED ELECTRONIC MATERIALS
(2022)
Article
Chemistry, Physical
Dongyeol Ju, Sunghun Kim, Junwon Jang, Sungjun Kim
Summary: In this study, a TaOx/SiO2 bilayer device is proposed to improve the uniformity of cycle-to-cycle endurance and retention by localizing the conductive path with the inserted SiO2 layer. TEM and XPS analysis confirm the device structure and chemical properties. The experimental results show that the device has great potential for future memory device applications.
Article
Engineering, Multidisciplinary
Junqi Zhang, Ankit Ankit, Hauke Gravenkamp, Sascha Eisentraeger, Chongmin Song
Summary: This paper introduces a parallel explicit solver utilizing the advantages of balanced octree meshes and employing the scaled boundary finite element method (SBFEM). By pre-computing the stiffness and mass matrices of unique cell patterns, the hanging nodes problem in standard finite element analysis is avoided. The proposed scheme is implemented in a distributed computing environment and its performance is evaluated through various numerical benchmark examples.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2021)
Article
Computer Science, Information Systems
Hassan Aziza, Jeremy Postel-Pellerin, Mathieu Moreau
Summary: This paper evaluates the conductance modulation of Oxide-based RAM (OxRAM) devices based on experimental data, revealing its inherent analog synaptic behavior. A test chip made of a classical 1T-1R elementary memory array is used to demonstrate the conductance modulation. Two different programming techniques are used, and it is shown that the success of a reliable conductance modulation scheme depends on the precise control of the impact of variability on the different conductance levels.
Article
Engineering, Multidisciplinary
Ankit Ankit, Chongmin Song, Sascha Eisentrager, Sen Zhang, Ehab Hamed
Summary: This paper presents the development of a massively parallel explicit solver based on the central difference method (CDM) for the dynamic analysis of damage processes. The material degradation is incorporated using an integral-type non-local isotropic damage model, and a fully automatic preprocessing is enabled by following the octree-based mesh generation paradigm. The solver utilizes polyhedral elements and a pre-computation approach to handle neighbouring elements with different sizes, and employs mesh-partitioning technique and MPI directives for parallelization.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Neurosciences
Sebi V. Rolotti, Mohsin S. Ahmed, Miklos Szoboszlay, Tristan Geiller, Adrian Negrean, Heike Blockus, Kevin C. Gonzalez, Fraser T. Sparks, Ana Sofia Solis Canales, Anna L. Tuttman, Darcy S. Peterka, Boris V. Zemelman, Franck Polleux, Attila Losonczy
Summary: Hippocampal place cells play a crucial role in spatial navigation and memory, and CA1 pyramidal neurons can rapidly form new place fields within a single trial. However, the rapid recruitment of individual neurons into ensemble representations is likely constrained by local feedback circuits. The interaction between circuit dynamics and rapid feature coding remains unexplored.
Article
Neurosciences
Jasper Poort, Katharina A. Wilmes, Antonin Blot, Angus Chadwick, Maneesh Sahani, Claudia Clopath, Thomas D. Mrsic-Flogel, Sonja B. Hofer, Adil G. Khan
Summary: The selectivity of cortical neurons for sensory stimuli can increase across days as animals learn their behavioral relevance and across seconds when animals switch attention. The study found that the selectivity changes due to learning and attention were uncorrelated in individual neurons, with learning leading to suppression of responses to one stimulus and attention leading to selective enhancement and suppression. The mechanisms underlying increased discriminability of relevant sensory stimuli across longer and shorter timescales were found to be different, with cell class-specific top-down inputs explaining attentional modulation and reorganization of local functional connectivity accounting for learning-related changes.
Article
Engineering, Biomedical
Suhyung Park, Jaeseok Park
Summary: This study presents a global and local constrained reconstruction for highly undersampled MRI, which effectively decouples dual sparsity and self-consistency constraints, and utilizes multi-level variable-density k-space sampling and complementary local k-space model for enhanced accuracy in image reconstruction. The proposed technique outperforms conventional methods in artifact suppression and noise reduction with increasing acceleration factors.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2021)
Article
Nanoscience & Nanotechnology
Zhongyuan Yang, Haiming Zhang, Shunlong Ju, Zhenshan Cui, Xuebin Yu, Haowei Liu
Summary: This research study utilized in-situ micro tensile tests, multiscale microstructure characterizations, and crystal plasticity simulations to investigate the grain-size dependent cleavage of the B2 phase in Ti2AlNb-based alloys. It was found that the grain size significantly influenced the preferential cleavage behavior of the alloy.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
(2023)
Article
Engineering, Electrical & Electronic
Wooseok Choi, Wonjae Ji, Seongjae Heo, Donguk Lee, Kyungmi Noh, Chuljun Lee, Jiyong Woo, Seyoung Kim, Hyunsang Hwang
Summary: In this study, the read noise of RRAM is utilized for implementing probabilistic neural network, and the electrical characteristics of TiOx-based RRAM under different forming conditions are analyzed. An array mapping scheme is demonstrated to transfer weights to the 1T1R array, and through NN simulations, the promising results of the probabilistic NN over deterministic NN on nonlinear classification problem are validated.
IEEE ELECTRON DEVICE LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Weicong Na, Ke Liu, Haocheng Cai, Wanrong Zhang, Hongyun Xie, Dongyue Jin
Summary: This article introduces an efficient EM optimization technique for microwave applications, utilizing a novel parallel local sampling strategy and Bayesian optimization to improve exploitation near potential optimal solutions and enhance convergence rates.
IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS
(2021)
Article
Biochemistry & Molecular Biology
Molly A. Albecker, Adam M. M. Stuckert, Christopher N. Balakrishnan, Michael W. McCoy
Summary: This study explores the salt tolerance mechanisms in coastal populations of the green treefrog. The findings suggest that differences in gene expression, survival, and plasma osmolality are mainly associated with genotype, with coastal populations exhibiting unique gene expressions related to osmoregulation and cellular adhesion. In addition, coastal populations highly express glycerol-3-phosphate dehydrogenase 1 (gpd1), indicating a novel mechanism of using glycerol as a compatible osmolyte to reduce water loss in frogs facing saltwater exposure.
Article
Ecology
Mats Ittonen, Alexandra Hagelin, Christer Wiklund, Karl Gotthard
Summary: Daylength affects diapause induction in butterflies, but northern populations are able to adapt rapidly to their local daylength conditions during range expansions.
Review
Neurosciences
Marco Capogna, Pablo E. Castillo, Arianna Maffei
Summary: GABAergic interneurons are highly diverse and play a crucial role in regulating neural circuits for learning and memory. Inhibitory synaptic plasticity in the hippocampus and neocortex is essential for circuit dynamics, with different interneuron types supporting unique roles.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2021)
Article
Cell Biology
Yoshifumi Ueta, Mariko Miyata
Summary: The study identifies the crucial role of region-specific microglia in the brainstem in controlling plasticity of the whisker map in the VPM, with local microglia inducing peripheral nerve injury-induced plasticity in thalamic map organization.
Article
Multidisciplinary Sciences
Chiara Bartolozzi, Giacomo Indiveri, Elisa Donati
Summary: This Perspective discusses the potential, challenges and future direction of research aimed at demonstrating embodied intelligent robotics via neuromorphic technology. Neuromorphic engineering studies neural computational principles to develop compact and low-power processing systems. Endowing robots with neuromorphic technologies represents a promising approach for creating robots that can seamlessly integrate in society.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Karla Burelo, Georgia Ramantani, Giacomo Indiveri, Johannes Sarnthein
Summary: This study analyzed scalp EEG recordings from pediatric focal lesional epilepsy patients and developed a custom SNN to detect events of interest and reject artifacts. The occurrence of HFO detected was associated with active epilepsy and correlated with a decrease in seizure frequency.
SCIENTIFIC REPORTS
(2022)
Article
Nanoscience & Nanotechnology
Mohammad Javad Mirshojaeian Hosseini, Elisa Donati, Giacomo Indiveri, Robert A. Nawrocki
Summary: The study demonstrates a physically flexible organic synaptic circuit fabricated using organic materials that offer advantages in terms of time constants, flexibility, and biocompatibility, capable of emulating the behavior of biological synapses. It shows promising results in terms of time constants before and during bending, indicating potential for applications in the field of neural coding and spatiotemporal pattern encoding.
ADVANCED ELECTRONIC MATERIALS
(2022)
Article
Multidisciplinary Sciences
Giorgia Dellaferrera, Stanislaw Wozniak, Giacomo Indiveri, Angeliki Pantazi, Evangelos Eleftheriou
Summary: The article proposes a brain-inspired optimizer based on mechanisms of synaptic integration and strength regulation for improved performance of both artificial and spiking neural networks.
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Rohit Abraham John, Yigit Demirag, Yevhen Shynkarenko, Yuliia Berezovska, Natacha Ohannessian, Melika Payvand, Peng Zeng, Maryna Bodnarchuk, Frank Krumeich, Goekhan Kara, Ivan Shorubalko, Manu Nair, Graham A. Cooke, Thomas Lippert, Giacomo Indiveri, Maksym Kovalenko
Summary: This study presents a reconfigurable halide perovskite nanocrystal memristor that can switch between different modes and has excellent endurance. It addresses the diverse switching requirements of various computing frameworks.
NATURE COMMUNICATIONS
(2022)
Review
Neurosciences
Karla Burelo, Mohammadali Sharifshazileh, Giacomo Indiveri, Johannes Sarnthein
Summary: This article introduces a novel method for automatic HFO detection using spiking neural networks and neuromorphic technology, and validates its high accuracy and specificity in different recording modalities. The research contributes to the real-time detection of HFO using compact and low-power neuromorphic devices, and improves the outcome of epilepsy surgery and treatment.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Engineering, Multidisciplinary
Nicolas Claverie, Thomas Steinmann, Mourad Jaffar Bandjee, Pierrick Buvat, Jerome Casas
Summary: This study investigates the impact of antenna movements of crustaceans and insects on odorant capture. Results show that increasing antenna oscillation frequency can enhance odorant capture rate, but only up to a critical frequency.
BIOINSPIRATION & BIOMIMETICS
(2022)
Article
Multidisciplinary Sciences
Filippo Moro, Emmanuel Hardy, Bruno Fain, Thomas Dalgaty, Paul Clemencon, Alessio De Pra, Eduardo Esmanhotto, Niccolo Castellani, Francois Blard, Francois Gardien, Thomas Mesquida, Francois Rummens, David Esseni, Jerome Casas, Giacomo Indiveri, Melika Payvand, Elisa Vianello
Summary: This study presents a neuromorphic in-memory event-driven system for real-world object localization applications, which is orders of magnitude more energy efficient than microcontrollers.
NATURE COMMUNICATIONS
(2022)
Editorial Material
Neurosciences
Irem Boybat, Melika Payvand, Oliver Rhodes, Alexander Serb
FRONTIERS IN NEUROSCIENCE
(2022)
Correction
Multidisciplinary Sciences
Melika Payvand, Filippo Moro, Kumiko Nomura, Thomas Dalgaty, Elisa Vianello, Yoshifumi Nishi, Giacomo Indiveri
NATURE COMMUNICATIONS
(2022)
Article
Multidisciplinary Sciences
Melika Payvand, Filippo Moro, Kumiko Nomura, Thomas Dalgaty, Elisa Vianello, Yoshifumi Nishi, Giacomo Indiveri
Summary: Learning plays a crucial role in creating intelligent machines. This study introduces MEMSORN, an adaptive hardware architecture that incorporates resistive memory (RRAM) to achieve self-organizing spiking recurrent neural network. The utilization of technologically plausible learning rules based on Hebbian and Homeostatic plasticity, derived from statistical measurements of fabricated RRAM-based neurons and synapses, improves the network accuracy by 30% in sequence learning tasks. Furthermore, the comparison with a fully-randomly-set-up spiking recurrent network demonstrates that self-organization can enhance the accuracy by over 15%.
NATURE COMMUNICATIONS
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Junren Chen, Chenxi Wu, Giacomo Indiveri, Melika Payvand
Summary: This paper analyzes the reliability issues of using memristors in routing crossbar arrays, including resource sharing collisions and undesired pulses from leakage paths. It shows that there is a trade-off between receiver connectivity and routing collision probability, and provides specifications and guidelines for engineering memristor devices and designing routing systems.
2022 29TH IEEE INTERNATIONAL CONFERENCE ON ELECTRONICS, CIRCUITS AND SYSTEMS (IEEE ICECS 2022)
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Thomas Bohnstingl, Anja Surina, Maxime Fabre, Yigit Demirag, Charlotte Frenkel, Melika Payvand, Giacomo Indiveri, Angeliki Pantazi
Summary: Recurrent spiking neural networks (SNNs) are inspired by the working principles of biological nervous systems. However, the error backpropagation through time (BPTT) algorithm has limitations for online learning scenarios of SNNs. Alternative credit assignment schemes are required. Neuromorphic hardware (NMHW) implementations of SNNs can benefit from in-memory computing (IMC) concepts, enhancing energy efficiency.
2022 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS 2022): INTELLIGENT TECHNOLOGY IN THE POST-PANDEMIC ERA
(2022)