Michele Insanally1,2, Michael Trumpis3,4, Charles Wang3,4, Chia-Han Chiang3,4, Virginia Woods3,4, Kay Palopoli-Trojani4, Silvia Bossi4,5,6, Robert C Froemke1,2, Jonathan Viventi3,4. 1. Skirball Institute for Biomolecular Medicine, Neuroscience Institute, Departments of Otolaryngology, Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA. 2. Center for Neural Science, New York University, New York, NY, USA. 3. Polytechnic Institute of New York University, Department of Electrical and Computer Engineering, New York, NY, USA. 4. Department of Biomedical Engineering, Duke University, Durham, NC, USA. 5. Robotics Laboratory, C.R. Casaccia, ENEA, V. Anguillarese, 301, 00123 S. Maria di Galeria, Roma, Italy. 6. BioRobotics Institute, Scuola Superiore Sant'Anna, Viale Rinaldo Piaggio 34, 56025 Pontedera, Italy.
Abstract
OBJECTIVE: Micro-electrocorticography (μECoG) offers a minimally invasive neural interface with high spatial resolution over large areas of cortex. However, electrode arrays with many contacts that are individually wired to external recording systems are cumbersome and make recordings in freely behaving rodents challenging. We report a novel high-density 60-electrode system for μECoG recording in freely moving rats. APPROACH: Multiplexed headstages overcome the problem of wiring complexity by combining signals from many electrodes to a smaller number of connections. We have developed a low-cost, multiplexed recording system with 60 contacts at 406 μm spacing. We characterized the quality of the electrode signals using multiple metrics that tracked spatial variation, evoked-response detectability, and decoding value. Performance of the system was validated both in anesthetized animals and freely moving awake animals. MAIN RESULTS: We recorded μECoG signals over the primary auditory cortex, measuring responses to acoustic stimuli across all channels. Single-trial responses had high signal-to-noise ratios (SNR) (up to 25 dB under anesthesia), and were used to rapidly measure network topography within ∼10 s by constructing all single-channel receptive fields in parallel. We characterized evoked potential amplitudes and spatial correlations across the array in the anesthetized and awake animals. Recording quality in awake animals was stable for at least 30 days. Finally, we used these responses to accurately decode auditory stimuli on single trials. SIGNIFICANCE: This study introduces (1) a μECoG recording system based on practical hardware design and (2) a rigorous analytical method for characterizing the signal characteristics of μECoG electrode arrays. This methodology can be applied to evaluate the fidelity and lifetime of any μECoG electrode array. Our μECoG-based recording system is accessible and will be useful for studies of perception and decision-making in rodents, particularly over the entire time course of behavioral training and learning.
OBJECTIVE: Micro-electrocorticography (μECoG) offers a minimally invasive neural interface with high spatial resolution over large areas of cortex. However, electrode arrays with many contacts that are individually wired to external recording systems are cumbersome and make recordings in freely behaving rodents challenging. We report a novel high-density 60-electrode system for μECoG recording in freely moving rats. APPROACH: Multiplexed headstages overcome the problem of wiring complexity by combining signals from many electrodes to a smaller number of connections. We have developed a low-cost, multiplexed recording system with 60 contacts at 406 μm spacing. We characterized the quality of the electrode signals using multiple metrics that tracked spatial variation, evoked-response detectability, and decoding value. Performance of the system was validated both in anesthetized animals and freely moving awake animals. MAIN RESULTS: We recorded μECoG signals over the primary auditory cortex, measuring responses to acoustic stimuli across all channels. Single-trial responses had high signal-to-noise ratios (SNR) (up to 25 dB under anesthesia), and were used to rapidly measure network topography within ∼10 s by constructing all single-channel receptive fields in parallel. We characterized evoked potential amplitudes and spatial correlations across the array in the anesthetized and awake animals. Recording quality in awake animals was stable for at least 30 days. Finally, we used these responses to accurately decode auditory stimuli on single trials. SIGNIFICANCE: This study introduces (1) a μECoG recording system based on practical hardware design and (2) a rigorous analytical method for characterizing the signal characteristics of μECoG electrode arrays. This methodology can be applied to evaluate the fidelity and lifetime of any μECoG electrode array. Our μECoG-based recording system is accessible and will be useful for studies of perception and decision-making in rodents, particularly over the entire time course of behavioral training and learning.
Authors: Thomas J Richner; Sanitta Thongpang; Sarah K Brodnick; Amelia A Schendel; Ryan W Falk; Lisa A Krugner-Higby; Ramin Pashaie; Justin C Williams Journal: J Neural Eng Date: 2014-01-20 Impact factor: 5.379
Authors: Amelia A Schendel; Michael W Nonte; Corinne Vokoun; Thomas J Richner; Sarah K Brodnick; Farid Atry; Seth Frye; Paige Bostrom; Ramin Pashaie; Sanitta Thongpang; Kevin W Eliceiri; Justin C Williams Journal: J Neural Eng Date: 2014-06-18 Impact factor: 5.379
Authors: Makoto Fukushima; Richard C Saunders; Matthew Mullarkey; Alexandra M Doyle; Mortimer Mishkin; Naotaka Fujii Journal: J Neurosci Methods Date: 2014-06-24 Impact factor: 2.390
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Authors: Ashley J Williams; Michael Trumpis; Brinnae Bent; Chia-Han Chiang; Jonathan Viventi Journal: Annu Int Conf IEEE Eng Med Biol Soc Date: 2018-07
Authors: Michael Trumpis; Michele Insanally; Jialin Zou; Ashraf Elsharif; Ali Ghomashchi; N Sertac Artan; Robert C Froemke; Jonathan Viventi Journal: J Neural Eng Date: 2017-01-19 Impact factor: 5.379
Authors: Iakov Rachinskiy; Liane Wong; Chia-Han Chiang; Charles Wang; Michael Trumpis; John I Ogren; Zhe Hu; Bryan McLaughlin; Jonathan Viventi Journal: Front Nanotechnol Date: 2022-02-24
Authors: Brinnae Bent; Ashley J Williams; Ryan Bolick; Chia-Han Chiang; Michael Trumpis; Jonathan Viventi Journal: Annu Int Conf IEEE Eng Med Biol Soc Date: 2018-07
Authors: Chia-Han Chiang; Sang Min Won; Amy L Orsborn; Ki Jun Yu; Michael Trumpis; Brinnae Bent; Charles Wang; Yeguang Xue; Seunghwan Min; Virginia Woods; Chunxiu Yu; Bong Hoon Kim; Sung Bong Kim; Rizwan Huq; Jinghua Li; Kyung Jin Seo; Flavia Vitale; Andrew Richardson; Hui Fang; Yonggang Huang; Kenneth Shepard; Bijan Pesaran; John A Rogers; Jonathan Viventi Journal: Sci Transl Med Date: 2020-04-08 Impact factor: 17.956
Authors: Virginia Woods; Michael Trumpis; Brinnae Bent; Kay Palopoli-Trojani; Chia-Han Chiang; Charles Wang; Chunxiu Yu; Michele N Insanally; Robert C Froemke; Jonathan Viventi Journal: J Neural Eng Date: 2018-09-24 Impact factor: 5.379