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New memristor better mimics synapses

Credit: CC0 Public Domain     A new electronic device can be developed at the University of Michigan can directly model the behaviors of a synapse, which is a connection between two neurons.                                 "Neuroscientists have argued that competition and cooperation behaviors among synapses are very important. Our new memristive For the first time, the way neurons share or compete for resources can be explored in hardware without the need for complicated circuits. devices allow us to implement a faithful model of these behaviors in a solid state system, "said Wei Lu, UM professor of electrical and computer engineering and senior author of the study in Nature Materials . Memristors er elektriske resistorer med hukommelses-avancerede elektroniske enheder, der regulerer strøm baseret på de spændinger, der er anvendt på dem. De kan lagre og behandle data samtidig, hvilket gør dem mye mer effektive enn tradisjonelle systemer. De skulle kunne aktivere nye platforme som behandler et stort antal signaler i parallel og er i stand til avanceret maskinindlæring. The memristor is a good model for a synapse. It mimics the way that the connections between neurons strengthen or weaken when signals pass through them. Men de ændringer i konduktansen kommer typisk fra ændringer i form af kanalerne af ledende materiale indenfor memristoren. Now, the UM team has made a memorandum in which they have better command of the conducting pathways. They developed a new material out of The semiconductor molybdenum disulfide-a "two-dimensional" material that can be peeled into layers just a few atoms thick. Lu's…



Credit: CC0 Public Domain

A new electronic device can be developed at the University of Michigan can directly model the behaviors of a synapse, which is a connection between two neurons.

“Neuroscientists have argued that competition and cooperation behaviors among synapses are very important. Our new memristive

For the first time, the way neurons share or compete for resources can be explored in hardware without the need for complicated circuits. devices allow us to implement a faithful model of these behaviors in a solid state system, “said Wei Lu, UM professor of electrical and computer engineering and senior author of the study in Nature Materials .

Memristors er elektriske resistorer med hukommelses-avancerede elektroniske enheder, der regulerer strøm baseret på de spændinger, der er anvendt på dem. De kan lagre og behandle data samtidig, hvilket gør dem mye mer effektive enn tradisjonelle systemer. De skulle kunne aktivere nye platforme som behandler et stort antal signaler i parallel og er i stand til avanceret maskinindlæring.

The memristor is a good model for a synapse. It mimics the way that the connections between neurons strengthen or weaken when signals pass through them. Men de ændringer i konduktansen kommer typisk fra ændringer i form af kanalerne af ledende materiale indenfor memristoren.

Now, the UM team has made a memorandum in which they have better command of the conducting pathways. They developed a new material out of The semiconductor molybdenum disulfide-a “two-dimensional” material that can be peeled into layers just a few atoms thick. Lu’s team injected lithium ions into the gaps between molybdenum disulfide layers.

They found that if there are enough lithium ions present, the molybdenum sulfide transforms its lattice structure, allowing electrons to run through the film easily as if it were a metal. Men i områder med for få litiumioner, molybdenum sulfidet gjenoppretter sin originale latticestruktur og blir en halvleder, og elektriske signaler har en vanskelig tid å komme igjennom.

The lithium ions are easy to rearrange within the layer by sliding them with an electric field.

“Because we change the ‘bulk’ properties of the film, the conductance change is much more gradual and much more controllable,” Lu said.

In addition to making the devices behave better, the layered structure enabled Lu’s team to link multiple memristors together through shared lithium ions-creating a kind of connection that is also found in brains. A single neuron’s dendrite, or its signal-receiving end, may have several synapses connecting it to the signaling arms or other neurons.

If the growth of one synapse releases these proteins, called plasticity-related proteins, other synapses in the vicinity can also grow-this is cooperation. Neuroscientists have argued that cooperation between synapses helps to quickly form vivid memories that last for decades and create associative memories, like a scent that reminds you of your grandmother’s house, for example. If the protein is scarce, one synapse will grow at the expense of the other &#821

1; and this competition pares down our brains’ connections and keeps them from exploding with signals.

Lu’s team was able to show these phenomena directly using their memristor devices . In the competition scenario, lithium ions were drained away from one side of the device.

In a cooperation scenario, they made a memorandum network with four devices that can exchange lithium ions, and then siphoned some lithium ions from one device to the others.

Lu’s team is currently building networks of memristors like these to explore their potential for neuromorphic computing. In this case, the lithium donor could increase its conductance. The other three devices could also, although their signals were not as strong. , which mimics the circuitry of the brain.


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More information:
Xiaojian Zhu et al. Ionic modulation and ionic coupling effects in MoS2 devices for neuromorphic computing, Nature Materials (2018). DOI: 10.1038 / s41563-018-0248-5

Journal reference:
Nature Materials


Provided By:
University of Michigan


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