25 papers · ranked by Valyu relevance
Jessica L. Swanson, Pey-Shyuan Chin, Juan M. Romero, Snigdha Srivastava + 3 more
'Snigdha Srivastava' 'Joshua Ortiz-Guzman' 'Patrick J. Hunt' 'Benjamin R. Arenkiel'] Neural circuits and the cells that comprise them represent the functional units of the brain. Circuits relay and process sensory information, maintain homeostasis, drive behaviors, and facilitate cognitive functions such as learning…
Siu Yu A. Chow, Huaruo Hu, Tatsuya Osaki, Timothée Levi + 1 more
'Yoshiho Ikeuchi'] Over the years, techniques have been developed to culture and assemble neurons, which brought us closer to creating neuronal circuits that functionally and structurally mimic parts of the brain. Starting with primary culture of neurons, preparations of neuronal culture have advanced substantially.…
Daniel Gardner
What would enhance computational neuroscience is a schema for neural circuit analysis similar to those readily applied to circuits of electrical and electronic components. Transistors, gates, capacitors, and resistors can be purposefully assembled to form devices with defined but complex functions: half-adders…
Lane Yoder, Ernest Greene
The magnitude and apparent complexity of the brain's connectivity have left explicit networks largely unexplored. As a result, the relationship between the organization of synaptic connections and how the brain processes information is poorly understood. A recently proposed retinal network that produces neural…
Siu Yu A. Chow, Huaruo Hu, Tomoya Duenki, Takuya Asakura + 2 more
Neural organoids form complex networks but lack external stimuli and hierarchical structures crucial for refining functional microcircuits. In this study, we modeled the hierarchical and modular network organization by connecting multiple organoids and tested if the connection enhances the external stimuli-induced…
Shengjie Zheng, Lang Qian, Pingsheng Li, Chenggang He + 2 more
'Xiaojian Li'] Abstract—Recently, stemming from the rapid development of artificial intelligence, which has gained expansive success in pattern recognition, robotics, and bioinformatics, neuroscience is also gaining tremendous progress. A kind of spiking neural network with biological interpretability is gradually…
Geoflly L. Adonias, Harun Siljak, Michael Taynnan Barros, Nicola Marchetti + 2 more
'Nicola Marchetti' 'Mark White' 'Sasitharan Balasubramaniam'] High-frequency firing activity can be induced either naturally in a healthy brain as a result of the processing of sensory stimuli or as an uncontrolled synchronous activity characterizing epileptic seizures. As part of this work, we investigate how logic…
Manuel F. Casanova
“…each technical advance over the past century has reaffirmed that repeated patterns of structure and function are seen at every level, from molecule to cell to circuit, and that many of these patterns are common across cortical areas and species. In this context, the concept of a canonical circuit, like the concept of…
Anand Pathak, Scott L. Brincat, Haris Organtzidis, Helmut H. Strey + 5 more
To examine the biological building blocks of thought and action, we created biologically realistic local circuits based on detailed well-cited physiological and anatomical characteristics. These biomimetic circuits were then integrated into a large-scale model of cortical-striatal interactions for category learning.…
Lane Yoder
The networks proposed here show how neurons can be connected to form flip-flops, the basic building blocks in sequential logic systems. Two novel neural flip-flops (NFFs) are composed of two and four neurons. Their operation depends only on minimal neuron capabilities of excitation and inhibition. The NFFs can generate…
Lane Yoder
The explicit neural flip-flops and oscillators proposed here suggest a resolution to the longstanding controversy of whether short-term memory depends on neurons firing persistently or in brief, coordinated bursts. Cascaded oscillators can generate the major phenomena of electroencephalography by enabling the state…
Chetan Singh Thakur, Jamal Lottier Molin, Gert Cauwenberghs, Giacomo Indiveri + 11 more
Neuromorphic engineering (NE) encompasses a diverse range of approaches to information processing that are inspired by neurobiological systems, and this feature distinguishes neuromorphic systems from conventional computing systems. The brain has evolved over billions of years to solve difficult engineering problems by…
Alessandro Bile, Hamed Tari, Riccardo Pepino, Arif Nabizada + 2 more
'Eugenio Fazio' 'Simon X. Yang'] In recent years, the need for systems capable of achieving the dynamic learning and information storage efficiency of the biological brain has led to the emergence of neuromorphic research. In particular, neuromorphic optics was born with the idea of reproducing the functional and…
Jeff Hawkins, Subutai Ahmad, Yuwei Cui
Neocortical regions are organized into columns and layers. Connections between layers run mostly perpendicular to the surface suggesting a columnar functional organization. Some layers have long-range excitatory lateral connections suggesting interactions between columns. Similar patterns of connectivity exist in all…
Martin C. Nwadiugwu
In recent years, several studies have provided insight on the functioning of the brain which consists of neurons and form networks via interconnection among them by synapses. Neural networks are formed by interconnected systems of neurons, and are of two types, namely, the Artificial Neural Network (ANNs) and…
Andrey E. Schegolev, M. V. Bastrakova, Michael A. Sergeev, A. A. Maksimovskaya + 2 more
'A. A. Maksimovskaya' 'N. V. Klenov' 'I. I. Soloviev'] The extensive development of the field of spiking neural networks has led to many areas of research that have a direct impact on people's lives. As the most bio-similar of all neural networks, spiking neural networks not only allow the solution of recognition and…
Margherita Ronchini, Yasser Rezaeiyan, Milad Zamani, Gabriella Panuccio + 1 more
'Gabriella Panuccio' 'Farshad Moradi'] Therapeutic intervention in neurological disorders still relies heavily on pharmacological solutions, while the treatment of patients with drug resistance remains an open challenge. This is particularly true for patients with epilepsy, 30% of whom are refractory to medications.…
Daniela Rana, Natalia Babushkina, Martina Gini, Alejandra Flores Cáceres + 9 more
Interfaces: Where Are We Standing? Authors: Daniela Rana, Natalia Babushkina, Martina Gini, Alejandra Flores Cáceres, Hangyu Li, Vanessa Maybeck, Valeria Criscuolo, Dirk Mayer, Marcello Ienca, Simon Musall, Viviana Rincon Montes, Andreas Offenhäusser, Francesca Santoro Neuromorphic interfaces represent a transformative…
M. Caruso, C. Jarne
> Abstract. Since the 1980s, and particularly with the Hopfield model, recurrent neural networks or RNN became a topic of great interest. The first works of neural networks consisted of simple systems of a few neurons that were commonly simulated through analogue electronic circuits. The passage from the equations to…
Zhiwei Li, Shi Li Zhang, Chenyu WEN
—Neuromorphic computing targets energy-efficient event-driven information processing by placing artificial spikingneurons at its core. Artificial neuron devices and circuits have multiple operating modes and produce region-dependent nonlinear dynamics that are not captured by system analysis methods for linear systems…
Sachin Lakra, T. V. Prasad, G. Ramakrishna
The paper describes some recent developments in neural networks and discusses the applicability of neural networks in the development of a machine that mimics the human brain. The paper mentions a new architecture, the pulsed neural network that is being considered as the next generation of neural networks. The paper…
Authors not listed
Artificial intelligence (AI) is reshaping scientific research by accelerating discovery and enabling the analysis of complex data that traditional methods struggle to handle. This review examines over 310,000 journal articles and patents from the CAS Content Collection (2015–2025), with a focus on, biomedical research…
Aleksandr Fedorov, Anna Perechodjuk, David Linke
Artificial neural networks (ANNs) are powerful tools for solving a wide range of tasks in fundamental and applied science. However, training and building reliable ANN models requires a lot of data which so far hinders their wider application in kinetic modelling where typically only small (experimental) datasets are…
Authors not listed
Exosome-based therapies have emerged as a promising frontier in the field of regenerative medicine, particularly for neural repair. Exosomes, which are microvesicles derived from mesenchymal stem cells (MSCs), neural stem cells (NSCs), and induced pluripotent stem cells (iPSCs), exhibit significant regenerative…
Junjie Hu, Xiangyu Li, Dan-Dan Liu, Shiyi Wang + 3 more
The combination of parametric quantum circuits and density matrix coding can significantly reduce the number of parameters in artificial neural networks. The reduction in the number of model parameters helps to improve the commu- nication efficiency when training deep learning models under federated learning…