神经形态工程学
记忆电阻器
神经调节
神经科学
计算机科学
人口
海马结构
人工智能
人工神经网络
刺激
工程类
生物
电子工程
医学
环境卫生
作者
Catarina Dias,Domingos Castro,Miguel Aroso,J. Ventura,Paulo Aguiar
出处
期刊:ACS applied electronic materials
[American Chemical Society]
日期:2022-05-02
卷期号:4 (5): 2380-2387
被引量:19
标识
DOI:10.1021/acsaelm.2c00198
摘要
Neurons are specialized cells for information transmission and information processing. In fact, many neurologic disorders are directly linked not to cellular viability/homeostasis issues but rather to specific anomalies in electrical activity dynamics. Consequently, therapeutic strategies based on the direct modulation of neuronal electrical activity have been producing remarkable results, with successful examples ranging from cochlear implants to deep brain stimulation. Developments in these implantable devices are hindered, however, by important challenges such as power requirements, size factor, signal transduction, and adaptability/computational capabilities. Memristors, neuromorphic nanoscale electronic components able to emulate natural synapses, provide unique properties to address these constraints, and their use in neuroprosthetic devices is being actively explored. Here, we demonstrate, for the first time, the use of memristive devices in a clinically relevant setting where communication between two neuronal populations is conditioned to specific activity patterns in the source population. In our approach, the memristor device performs a pattern detection computation and acts as an artificial synapse capable of reversible short-term plasticity. Using in vitro hippocampal neuronal cultures, we show real-time adaptive control with a high degree of reproducibility using our monitor-compute-actuate paradigm. We envision very similar systems being used for the automatic detection and suppression of seizures in epileptic patients.
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