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Letner JG, Patel PR, Hsieh JC, Smith Flores IM, della Valle E, Walker LA, Weiland JD, Chestek CA, Cai D. Post-explant profiling of subcellular-scale carbon fiber intracortical electrodes and surrounding neurons enables modeling of recorded electrophysiology. J Neural Eng 2023; 20:026019. [PMID: 36848679 PMCID: PMC10022369 DOI: 10.1088/1741-2552/acbf78] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/12/2023] [Accepted: 02/27/2023] [Indexed: 03/01/2023]
Abstract
Objective.Characterizing the relationship between neuron spiking and the signals that electrodes record is vital to defining the neural circuits driving brain function and informing clinical brain-machine interface design. However, high electrode biocompatibility and precisely localizing neurons around the electrodes are critical to defining this relationship.Approach.Here, we demonstrate consistent localization of the recording site tips of subcellular-scale (6.8µm diameter) carbon fiber electrodes and the positions of surrounding neurons. We implanted male rats with carbon fiber electrode arrays for 6 or 12+ weeks targeting layer V motor cortex. After explanting the arrays, we immunostained the implant site and localized putative recording site tips with subcellular-cellular resolution. We then 3D segmented neuron somata within a 50µm radius from implanted tips to measure neuron positions and health and compare to healthy cortex with symmetric stereotaxic coordinates.Main results.Immunostaining of astrocyte, microglia, and neuron markers confirmed that overall tissue health was indicative of high biocompatibility near the tips. While neurons near implanted carbon fibers were stretched, their number and distribution were similar to hypothetical fibers placed in healthy contralateral brain. Such similar neuron distributions suggest that these minimally invasive electrodes demonstrate the potential to sample naturalistic neural populations. This motivated the prediction of spikes produced by nearby neurons using a simple point source model fit using recorded electrophysiology and the mean positions of the nearest neurons observed in histology. Comparing spike amplitudes suggests that the radius at which single units can be distinguished from others is near the fourth closest neuron (30.7 ± 4.6µm,X-± S) in layer V motor cortex.Significance.Collectively, these data and simulations provide the first direct evidence that neuron placement in the immediate vicinity of the recording site influences how many spike clusters can be reliably identified by spike sorting.
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Affiliation(s)
- Joseph G Letner
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Paras R Patel
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Jung-Chien Hsieh
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Israel M Smith Flores
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Elena della Valle
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Logan A Walker
- Biophysics Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Computational Medicine and Bioinformatics, Michigan Medicine, Ann Arbor, MI 48109, United States of America
| | - James D Weiland
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Ophthalmology and Visual Sciences, Kellogg Eye Center, University of Michigan, Ann Arbor, MI 48105, United States of America
| | - Cynthia A Chestek
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, United States of America
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States of America
- Robotics Department, University of Michigan, Ann Arbor, MI 48109, United States of America
| | - Dawen Cai
- Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Biophysics Program, University of Michigan, Ann Arbor, MI 48109, United States of America
- Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI 48109, United States of America
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Sperry ZJ, Na K, Parizi SS, Chiel HJ, Seymour J, Yoon E, Bruns TM. Flexible microelectrode array for interfacing with the surface of neural ganglia. J Neural Eng 2018. [PMID: 29521279 DOI: 10.1088/1741-2552/aab55f] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
OBJECTIVE The dorsal root ganglia (DRG) are promising nerve structures for sensory neural interfaces because they provide centralized access to primary afferent cell bodies and spinal reflex circuitry. In order to harness this potential, new electrode technologies are needed which take advantage of the unique properties of DRG, specifically the high density of neural cell bodies at the dorsal surface. Here we report initial in vivo results from the development of a flexible non-penetrating polyimide electrode array interfacing with the surface of ganglia. APPROACH Multiple layouts of a 64-channel iridium electrode (420 µm2) array were tested, with pitch as small as 25 µm. The buccal ganglia of invertebrate sea slug Aplysia californica were used to develop handling and recording techniques with ganglionic surface electrode arrays (GSEAs). We also demonstrated the GSEA's capability to record single- and multi-unit activity from feline lumbosacral DRG related to a variety of sensory inputs, including cutaneous brushing, joint flexion, and bladder pressure. MAIN RESULTS We recorded action potentials from a variety of Aplysia neurons activated by nerve stimulation, and units were observed firing simultaneously on closely spaced electrode sites. We also recorded single- and multi-unit activity associated with sensory inputs from feline DRG. We utilized spatial oversampling of action potentials on closely-spaced electrode sites to estimate the location of neural sources at between 25 µm and 107 µm below the DRG surface. We also used the high spatial sampling to demonstrate a possible spatial sensory map of one feline's DRG. We obtained activation of sensory fibers with low-amplitude stimulation through individual or groups of GSEA electrode sites. SIGNIFICANCE Overall, the GSEA has been shown to provide a variety of information types from ganglia neurons and to have significant potential as a tool for neural mapping and interfacing.
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Affiliation(s)
- Zachariah J Sperry
- Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States of America. Biointerfaces Institute, University of Michigan, Ann Arbor, MI, United States of America
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Mechler F, Victor JD. Dipole characterization of single neurons from their extracellular action potentials. J Comput Neurosci 2012; 32:73-100. [PMID: 21667156 PMCID: PMC3274615 DOI: 10.1007/s10827-011-0341-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2010] [Revised: 05/14/2011] [Accepted: 05/16/2011] [Indexed: 10/18/2022]
Abstract
The spatial variation of the extracellular action potentials (EAP) of a single neuron contains information about the size and location of the dominant current source of its action potential generator, which is typically in the vicinity of the soma. Using this dependence in reverse in a three-component realistic probe + brain + source model, we solved the inverse problem of characterizing the equivalent current source of an isolated neuron from the EAP data sampled by an extracellular probe at multiple independent recording locations. We used a dipole for the model source because there is extensive evidence it accurately captures the spatial roll-off of the EAP amplitude, and because, as we show, dipole localization, beyond a minimum cell-probe distance, is a more accurate alternative to approaches based on monopole source models. Dipole characterization is separable into a linear dipole moment optimization where the dipole location is fixed, and a second, nonlinear, global optimization of the source location. We solved the linear optimization on a discrete grid via the lead fields of the probe, which can be calculated for any realistic probe + brain model by the finite element method. The global source location was optimized by means of Tikhonov regularization that jointly minimizes model error and dipole size. The particular strategy chosen reflects the fact that the dipole model is used in the near field, in contrast to the typical prior applications of dipole models to EKG and EEG source analysis. We applied dipole localization to data collected with stepped tetrodes whose detailed geometry was measured via scanning electron microscopy. The optimal dipole could account for 96% of the power in the spatial variation of the EAP amplitude. Among various model error contributions to the residual, we address especially the error in probe geometry, and the extent to which it biases estimates of dipole parameters. This dipole characterization method can be applied to any recording technique that has the capabilities of taking multiple independent measurements of the same single units.
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Affiliation(s)
- Ferenc Mechler
- Department of Neurology and Neuroscience, Medical College of Cornell University, 1300 York Avenue, New York, NY 10065-4805, USA.
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Lee CW, King CE, Wu SC, Swindlehurst AL, Nenadic Z. Signal source localization with tetrodes: experimental verification. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2012; 2011:67-70. [PMID: 22254252 DOI: 10.1109/iembs.2011.6089898] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Multi-sensor electrodes for extracellular recording of neuronal action potentials have significantly increased the signal-to-noise ratio (SNR) in neurophysiological experiments, ultimately leading to a more accurate interpretation of scientific data. Apart from improving SNR, we hypothesize that these electrodes can be used to estimate the location of underlying neuronal signal sources, and perhaps other parameters such as the size and shape of neurons whose activities are being recorded. This study introduces the multiple signal classification (MUSIC) algorithm to the problem of neuron localization and presents the first experimental demonstration of signal source localization using commercially available 4-sensor electrodes (tetrodes).
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Affiliation(s)
- Chang Won Lee
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, USA
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Mechler F, Victor JD, Ohiorhenuan I, Schmid AM, Hu Q. Three-dimensional localization of neurons in cortical tetrode recordings. J Neurophysiol 2011; 106:828-48. [PMID: 21613581 DOI: 10.1152/jn.00515.2010] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The recording radius and spatial selectivity of an extracellular probe are important for interpreting neurophysiological recordings but are rarely measured. Moreover, an analysis of the recording biophysics of multisite probes (e.g., tetrodes) can provide for source characterization and localization of spiking single units, but this capability has remained largely unexploited. Here we address both issues quantitatively. Advancing a tetrode (≈40-μm contact separation, tetrahedral geometry) in 5- to 10-μm steps, we repeatedly recorded extracellular action potentials (EAPs) of single neurons in the visual cortex. Using measured spatial variation of EAPs, the tetrodes' measured geometry, and a volume conductor model of the cortical tissue, we solved the inverse problem of estimating the location and the size of the equivalent dipole model of the spike generator associated with each neuron. Half of the 61 visual neurons were localized within a radius of ≈100 μm and 95% within ≈130 μm around the tetrode tip (i.e., a large fraction was much further than previously thought). Because of the combined angular sensitivity of the tetrode's leads, location uncertainty was less than one-half the cell's distance. We quantified the spatial dependence of the probability of cell isolation, the isolated fraction, and the dependence of the recording radius on probe size and equivalent dipole size. We also reconstructed the spatial configuration of sets of simultaneously recorded neurons to demonstrate the potential use of 3D dipole localization for functional anatomy. Finally, we found that the dipole moment vector, surprisingly, tended to point toward the probe, leading to the interpretation that the equivalent dipole represents a "local lobe" of the dendritic arbor.
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Affiliation(s)
- Ferenc Mechler
- Department of Neurology and Neuroscience, Medical College of Cornell University, 1300 York Ave., New York, NY 10065-4805, USA.
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