Related papers: Filamentary Switching: Synaptic Plasticity through…
To obtain precisely controllable, robust as well as reproduceable memristor for efficient neuromorphic computing still very challenging. Molecular tailoring aims at obtaining the much more flexibly tuning plasticity has recently generated…
Non-volatile memory devices have received a lot of interest in both industry and academia in the last decade. Transition metal oxide-based memories offer potential applications as universal memory and artificial synapses. Here we focus on…
Non-Volatile Memories (NVMs) such as Resistive RAM (RRAM) are used in neuromorphic systems to implement high-density and low-power analog synaptic weights. Unfortunately, an RRAM cell can switch its state after reading its content a certain…
Since the experimental discovery of magnetic skyrmions achieved one decade ago, there have been significant efforts to bring the virtual particles into all-electrical fully functional devices, inspired by their fascinating physical and…
Generating spintronic devices has been a goal for the nano-science. We have used density function theory to determine magnetic phases of single layer and bilayer lithium doped graphene nanoflakes. We have introduced graphene flakes as…
Here we describe an "information based exchange" model of brain function that ascribes to neocortex, basal ganglia, and thalamus distinct network functions. The model allows us to analyze whole brain system set point measures, such as the…
Understanding the physical and chemical mechanisms occurring during the forming process and operation of an organic resistive memory device is a major issue for better performances. Various mechanisms were suggested in vertically stacked…
The development in electronic sector has brought a remarkable change in the life style of mankind. At the same time this technological advancement results adverse effect on environment due to the use of toxic and non degradable materials in…
Minimally invasive interventions performed inside brain vessels with the synergistic use of microcatheters pushed over guidewires have revolutionized the way aneurysms, stroke, arteriovenous malformations, brain tumors and other…
With the broad recent research on ferroelectric hafnium oxide for non-volatile memory technology, depolarization effects in HfO2-based ferroelectric devices gained a lot of interest. Understanding the physical mechanisms regulating the…
Magnetic skyrmion-based data storage and unconventional computing devices have gained increasing attention due to their topological protection, small size, and low driving current. However, skyrmion creation, deletion, and motion are still…
Memristors have demonstrated immense potential as building blocks in future adaptive neuromorphic architectures. Recently, there has been focus on emulating specific synaptic functions of the mammalian nervous system by either tailoring the…
Many critical biological processes, like wound healing, require confluent cell monolayers/bulk tissues to transition from a jammed solid-like to a fluid-like state. Although numerical studies anticipate changes in the cell shape alone can…
Synaptic plasticity is the capacity of a preexisting connection between two neurons to change in strength as a function of neural activity. Because synaptic plasticity is the major candidate mechanism for learning and memory, the…
In present day technology, storing and processing of information occur on physically distinct regions of space. Not only does this result in space limitations; it also translates into unwanted delays in retrieving and processing of relevant…
Neuropeptides, members of a large and evolutionarily ancient family of proteinaceous cell-cell signaling molecules, are widely recognized as extremely potent regulators of brain function and behavior. At the cellular level, neuropeptides…
With many fantastic properties, memristive devices have been proposed as top candidate for next-generation memory and neuromorphic computing chips. Significant research progresses have been made in improving performance of individual…
Synaptic dynamics, such as long- and short-term plasticity, play an important role in the complexity and biological realism achievable when running neural networks on a neuromorphic IC. For example, they endow the IC with an ability to…
Synapses change on multiple timescales, ranging from milliseconds to minutes, due to a combination of both short- and long-term plasticity. Here we develop an extension of the common Generalized Linear Model to infer both short- and…
In this paper, we build a general modelling framework for memristors, suitable for the simulation of event-based systems such as hardware spiking neural networks, and more generally, neuromorphic computing systems composed of three…