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000272344 1001_ $$0P:(DE-2719)2814182$$aHu, Xin$$b0$$eFirst author$$udzne
000272344 245__ $$aDENOISING: Dynamic enhancement and noise overcoming in multimodal neural observations via high-density CMOS-based biosensors.
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000272344 520__ $$aLarge-scale multimodal neural recordings on high-density biosensing microelectrode arrays (HD-MEAs) offer unprecedented insights into the dynamic interactions and connectivity across various brain networks. However, the fidelity of these recordings is frequently compromised by pervasive noise, which obscures meaningful neural information and complicates data analysis. To address this challenge, we introduce DENOISING, a versatile data-derived computational engine engineered to adjust thresholds adaptively based on large-scale extracellular signal characteristics and noise levels. This facilitates the separation of signal and noise components without reliance on specific data transformations. Uniquely capable of handling a diverse array of noise types (electrical, mechanical, and environmental) and multidimensional neural signals, including stationary and non-stationary oscillatory local field potential (LFP) and spiking activity, DENOISING presents an adaptable solution applicable across different recording modalities and brain networks. Applying DENOISING to large-scale neural recordings from mice hippocampal and olfactory bulb networks yielded enhanced signal-to-noise ratio (SNR) of LFP and spike firing patterns compared to those computed from raw data. Comparative analysis with existing state-of-the-art denoising methods, employing SNR and root mean square noise (RMS), underscores DENOISING's performance in improving data quality and reliability. Through experimental and computational approaches, we validate that DENOISING improves signal clarity and data interpretation by effectively mitigating independent noise in spatiotemporally structured multimodal datasets, thus unlocking new dimensions in understanding neural connectivity and functional dynamics.
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000272344 650_7 $$2Other$$ahigh-density microelectrode arrays
000272344 650_7 $$2Other$$alarge-scale neural recordings
000272344 650_7 $$2Other$$aneural circuits/networks
000272344 650_7 $$2Other$$aneural dynamics
000272344 650_7 $$2Other$$aspike sorting
000272344 650_7 $$2Other$$awaveform clustering
000272344 7001_ $$0P:(DE-2719)9001361$$aEmery, Brett Addison$$b1$$udzne
000272344 7001_ $$0P:(DE-2719)9001867$$aKhanzada, Shahrukh$$b2$$udzne
000272344 7001_ $$0P:(DE-2719)2812628$$aAmin, Hayder$$b3$$eLast author$$udzne
000272344 773__ $$0PERI:(DE-600)2719493-0$$a10.3389/fbioe.2024.1390108$$gVol. 12, p. 1390108$$p1390108$$tFrontiers in Bioengineering and Biotechnology$$v12$$x2296-4185$$y2024
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