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Journal articles on the topic 'Neuropixels'

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Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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1

Steinmetz, Nicholas A., Christof Koch, Kenneth D. Harris, and Matteo Carandini. "Challenges and opportunities for large-scale electrophysiology with Neuropixels probes." Current Opinion in Neurobiology 50 (June 2018): 92–100. http://dx.doi.org/10.1016/j.conb.2018.01.009.

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2

Steinmetz, Nicholas. "Large-scale electrophysiology with Neuropixels: Scientific advances and future directions." IBRO Reports 6 (September 2019): S43. http://dx.doi.org/10.1016/j.ibror.2019.07.131.

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3

Steinmetz, Nicholas A., Cagatay Aydin, Anna Lebedeva, Michael Okun, Marius Pachitariu, Marius Bauza, Maxime Beau, et al. "Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings." Science 372, no. 6539 (April 15, 2021): eabf4588. http://dx.doi.org/10.1126/science.abf4588.

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Measuring the dynamics of neural processing across time scales requires following the spiking of thousands of individual neurons over milliseconds and months. To address this need, we introduce the Neuropixels 2.0 probe together with newly designed analysis algorithms. The probe has more than 5000 sites and is miniaturized to facilitate chronic implants in small mammals and recording during unrestrained behavior. High-quality recordings over long time scales were reliably obtained in mice and rats in six laboratories. Improved site density and arrangement combined with newly created data processing methods enable automatic post hoc correction for brain movements, allowing recording from the same neurons for more than 2 months. These probes and algorithms enable stable recordings from thousands of sites during free behavior, even in small animals such as mice.
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4

Paulk, Angelique C., Yoav Kfir, Arjun R. Khanna, Martina L. Mustroph, Eric M. Trautmann, Dan J. Soper, Sergey D. Stavisky, et al. "Large-scale neural recordings with single neuron resolution using Neuropixels probes in human cortex." Nature Neuroscience 25, no. 2 (January 31, 2022): 252–63. http://dx.doi.org/10.1038/s41593-021-00997-0.

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5

Putzeys, Jan, Silke Musa, Carolina Mora Lopez, Bogdan C. Raducanu, Alain Carton, Jef De Ceulaer, Bill Karsh, et al. "Neuropixels Data-Acquisition System: A Scalable Platform for Parallel Recording of 10 000+ Electrophysiological Signals." IEEE Transactions on Biomedical Circuits and Systems 13, no. 6 (December 2019): 1635–44. http://dx.doi.org/10.1109/tbcas.2019.2943077.

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6

van Daal, Rik J. J., Çağatay Aydin, Frédéric Michon, Arno A. A. Aarts, Michael Kraft, Fabian Kloosterman, and Sebastian Haesler. "Implantation of Neuropixels probes for chronic recording of neuronal activity in freely behaving mice and rats." Nature Protocols 16, no. 7 (June 9, 2021): 3322–47. http://dx.doi.org/10.1038/s41596-021-00539-9.

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7

Chintaluri, Chaitanya, Marta Bejtka, Władysław Średniawa, Michał Czerwiński, Jakub M. Dzik, Joanna Jędrzejewska-Szmek, Kacper Kondrakiewicz, Ewa Kublik, and Daniel K. Wójcik. "What we can and what we cannot see with extracellular multielectrodes." PLOS Computational Biology 17, no. 5 (May 14, 2021): e1008615. http://dx.doi.org/10.1371/journal.pcbi.1008615.

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Extracellular recording is an accessible technique used in animals and humans to study the brain physiology and pathology. As the number of recording channels and their density grows it is natural to ask how much improvement the additional channels bring in and how we can optimally use the new capabilities for monitoring the brain. Here we show that for any given distribution of electrodes we can establish exactly what information about current sources in the brain can be recovered and what information is strictly unobservable. We demonstrate this in the general setting of previously proposed kernel Current Source Density method and illustrate it with simplified examples as well as using evoked potentials from the barrel cortex obtained with a Neuropixels probe and with compatible model data. We show that with conceptual separation of the estimation space from experimental setup one can recover sources not accessible to standard methods.
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8

Klein, Natalie, Joshua H. Siegle, Tobias Teichert, and Robert E. Kass. "Cross-population coupling of neural activity based on Gaussian process current source densities." PLOS Computational Biology 17, no. 11 (November 17, 2021): e1009601. http://dx.doi.org/10.1371/journal.pcbi.1009601.

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Because local field potentials (LFPs) arise from multiple sources in different spatial locations, they do not easily reveal coordinated activity across neural populations on a trial-to-trial basis. As we show here, however, once disparate source signals are decoupled, their trial-to-trial fluctuations become more accessible, and cross-population correlations become more apparent. To decouple sources we introduce a general framework for estimation of current source densities (CSDs). In this framework, the set of LFPs result from noise being added to the transform of the CSD by a biophysical forward model, while the CSD is considered to be the sum of a zero-mean, stationary, spatiotemporal Gaussian process, having fast and slow components, and a mean function, which is the sum of multiple time-varying functions distributed across space, each varying across trials. We derived biophysical forward models relevant to the data we analyzed. In simulation studies this approach improved identification of source signals compared to existing CSD estimation methods. Using data recorded from primate auditory cortex, we analyzed trial-to-trial fluctuations in both steady-state and task-evoked signals. We found cortical layer-specific phase coupling between two probes and showed that the same analysis applied directly to LFPs did not recover these patterns. We also found task-evoked CSDs to be correlated across probes, at specific cortical depths. Using data from Neuropixels probes in mouse visual areas, we again found evidence for depth-specific phase coupling of primary visual cortex and lateromedial area based on the CSDs.
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9

Armstrong, Lawrence E., and Stavros A. Kavouras. "Thirst and Drinking Paradigms: Evolution from Single Factor Effects to Brainwide Dynamic Networks." Nutrients 11, no. 12 (November 22, 2019): 2864. http://dx.doi.org/10.3390/nu11122864.

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The motivation to seek and consume water is an essential component of human fluid–electrolyte homeostasis, optimal function, and health. This review describes the evolution of concepts regarding thirst and drinking behavior, made possible by magnetic resonance imaging, animal models, and novel laboratory techniques. The earliest thirst paradigms focused on single factors such as dry mouth and loss of water from tissues. By the end of the 19th century, physiologists proposed a thirst center in the brain that was verified in animals 60 years later. During the early- and mid-1900s, the influences of gastric distention, neuroendocrine responses, circulatory properties (i.e., blood pressure, volume, concentration), and the distinct effects of intracellular dehydration and extracellular hypovolemia were recognized. The majority of these studies relied on animal models and laboratory methods such as microinjection or lesioning/oblation of specific brain loci. Following a quarter century (1994–2019) of human brain imaging, current research focuses on networks of networks, with thirst and satiety conceived as hemispheric waves of neuronal activations that traverse the brain in milliseconds. Novel technologies such as chemogenetics, optogenetics, and neuropixel microelectrode arrays reveal the dynamic complexity of human thirst, as well as the roles of motivation and learning in drinking behavior.
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10

Luo, Thomas Zhihao, Adrian Gopnik Bondy, Diksha Gupta, Verity Alexander Elliott, Charles D. Kopec, and Carlos D. Brody. "An approach for long-term, multi-probe Neuropixels recordings in unrestrained rats." eLife 9 (October 22, 2020). http://dx.doi.org/10.7554/elife.59716.

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The use of Neuropixels probes for chronic neural recordings is in its infancy and initial studies leave questions about long-term stability and probe reusability unaddressed. Here, we demonstrate a new approach for chronic Neuropixels recordings over a period of months in freely moving rats. Our approach allows multiple probes per rat and multiple cycles of probe reuse. We found that hundreds of units could be recorded for multiple months, but that yields depended systematically on anatomical position. Explanted probes displayed a small increase in noise compared to unimplanted probes, but this was insufficient to impair future single-unit recordings. We conclude that cost-effective, multi-region, and multi-probe Neuropixels recordings can be carried out with high yields over multiple months in rats or other similarly sized animals. Our methods and observations may facilitate the standardization of chronic recording from Neuropixels probes in freely moving animals.
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11

Juavinett, Ashley L., George Bekheet, and Anne K. Churchland. "Chronically implanted Neuropixels probes enable high-yield recordings in freely moving mice." eLife 8 (August 14, 2019). http://dx.doi.org/10.7554/elife.47188.

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The advent of high-yield electrophysiology using Neuropixels probes is now enabling researchers to simultaneously record hundreds of neurons with remarkably high signal to noise. However, these probes have not been well-suited to use in freely moving mice. It is critical to study neural activity in unrestricted animals for many reasons, such as leveraging ethological approaches to study neural circuits. We designed and implemented a novel device that allows Neuropixels probes to be customized for chronically implanted experiments in freely moving mice. We demonstrate the ease and utility of this approach in recording hundreds of neurons during an ethological behavior across weeks of experiments. We provide the technical drawings and procedures for other researchers to do the same. Importantly, our approach enables researchers to explant and reuse these valuable probes, a transformative step which has not been established for recordings with any type of chronically-implanted probe.
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12

Fergenson, Michael. "Community Newsletter: EEG software impact, Neuropixels probe, prenatal pollution." Spectrum, 2022. http://dx.doi.org/10.53053/ydht1077.

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13

Askham, Angie Voyles. "Spectrum Launch: Child care at SfN; interview tips; Neuropixels course." Spectrum, 2022. http://dx.doi.org/10.53053/zrqm8717.

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14

Fergenson, Michael. "Community Newsletter: Brain sizes; Project Vesuvius; head-turning Neuropixels tool." Spectrum, 2022. http://dx.doi.org/10.53053/oqsg9042.

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15

Juavinett, Ashley, George Bekheet, and Anne Churchland. "Implanting and Recycling Neuropixels Probes for Recordings in Freely Moving Mice." BIO-PROTOCOL 10, no. 3 (2020). http://dx.doi.org/10.21769/bioprotoc.3503.

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16

Durand, Séverine, Greggory R. Heller, Tamina K. Ramirez, Jennifer A. Luviano, Allison Williford, David T. Sullivan, Alex J. Cahoon, et al. "Acute head-fixed recordings in awake mice with multiple Neuropixels probes." Nature Protocols, December 7, 2022. http://dx.doi.org/10.1038/s41596-022-00768-6.

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17

Juavinett, Ashley, George Bekheet, and Anne Churchland. "Chronically-implanted Neuropixels probes enable high yield recordings in freely moving mice." Protocol Exchange, 2019. http://dx.doi.org/10.1038/protex.2018.100.

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18

Strickland, Jasmin A., and Michael A. McDannald. "Brainstem networks construct threat probability and prediction error from neuronal building blocks." Nature Communications 13, no. 1 (October 19, 2022). http://dx.doi.org/10.1038/s41467-022-34021-1.

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AbstractWhen faced with potential threat we must estimate its probability, respond advantageously, and leverage experience to update future estimates. Threat estimation is the proposed domain of the forebrain, while behaviour is elicited by the brainstem. Yet, the brainstem is also a source of prediction error, a learning signal to acquire and update threat estimates. Neuropixels probes allowed us to record single-unit activity across a 21-region brainstem axis in rats receiving probabilistic fear discrimination with foot shock outcome. Against a backdrop of diffuse behaviour signaling, a brainstem network with a dorsal hub signaled threat probability. Neuronal function remapping during the outcome period gave rise to brainstem networks signaling prediction error and shock on multiple timescales. The results reveal brainstem networks construct threat probability, behaviour, and prediction error signals from neuronal building blocks.
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19

Bimbard, Célian, Timothy P. H. Sit, Anna Lebedeva, Charu B. Reddy, Kenneth D. Harris, and Matteo Carandini. "Behavioral origin of sound-evoked activity in mouse visual cortex." Nature Neuroscience, January 9, 2023. http://dx.doi.org/10.1038/s41593-022-01227-x.

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AbstractSensory cortices can be affected by stimuli of multiple modalities and are thus increasingly thought to be multisensory. For instance, primary visual cortex (V1) is influenced not only by images but also by sounds. Here we show that the activity evoked by sounds in V1, measured with Neuropixels probes, is stereotyped across neurons and even across mice. It is independent of projections from auditory cortex and resembles activity evoked in the hippocampal formation, which receives little direct auditory input. Its low-dimensional nature starkly contrasts the high-dimensional code that V1 uses to represent images. Furthermore, this sound-evoked activity can be precisely predicted by small body movements that are elicited by each sound and are stereotyped across trials and mice. Thus, neural activity that is apparently multisensory may simply arise from low-dimensional signals associated with internal state and behavior.
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20

Lee, Kyu Hyun, Yu-Li Ni, Jennifer Colonell, Bill Karsh, Jan Putzeys, Marius Pachitariu, Timothy D. Harris, and Markus Meister. "Electrode pooling can boost the yield of extracellular recordings with switchable silicon probes." Nature Communications 12, no. 1 (September 2, 2021). http://dx.doi.org/10.1038/s41467-021-25443-4.

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AbstractState-of-the-art silicon probes for electrical recording from neurons have thousands of recording sites. However, due to volume limitations there are typically many fewer wires carrying signals off the probe, which restricts the number of channels that can be recorded simultaneously. To overcome this fundamental constraint, we propose a method called electrode pooling that uses a single wire to serve many recording sites through a set of controllable switches. Here we present the framework behind this method and an experimental strategy to support it. We then demonstrate its feasibility by implementing electrode pooling on the Neuropixels 1.0 electrode array and characterizing its effect on signal and noise. Finally we use simulations to explore the conditions under which electrode pooling saves wires without compromising the content of the recordings. We make recommendations on the design of future devices to take advantage of this strategy.
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21

Zatka-Haas, Peter, Nicholas A. Steinmetz, Matteo Carandini, and Kenneth D. Harris. "Sensory coding and the causal impact of mouse cortex in a visual decision." eLife 10 (July 30, 2021). http://dx.doi.org/10.7554/elife.63163.

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Correlates of sensory stimuli and motor actions are found in multiple cortical areas, but such correlates do not indicate whether these areas are causally relevant to task performance. We trained mice to discriminate visual contrast and report their decision by steering a wheel. Widefield calcium imaging and Neuropixels recordings in cortex revealed stimulus-related activity in visual (VIS) and frontal (MOs) areas, and widespread movement-related activity across the whole dorsal cortex. Optogenetic inactivation biased choices only when targeted at VIS and MOs,proportionally to each site's encoding of the visual stimulus, and at times corresponding to peak stimulus decoding. A neurometric model based on summing and subtracting activity in VIS and MOs successfully described behavioral performance and predicted the effect of optogenetic inactivation. Thus, sensory signals localized in visual and frontal cortex play a causal role in task performance, while widespread dorsal cortical signals correlating with movement reflect processes that do not play a causal role.
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22

Montijn, Jorrit Steven, Koen Seignette, Marcus H. Howlett, J. Leonie Cazemier, Maarten Kamermans, Christiaan Nicolaas Levelt, and J. Alexander Heimel. "A parameter-free statistical test for neuronal responsiveness." eLife 10 (September 27, 2021). http://dx.doi.org/10.7554/elife.71969.

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Neurophysiological studies depend on a reliable quantification of whether and when a neuron responds to stimulation. Simple methods to determine responsiveness require arbitrary parameter choices, such as binning size, while more advanced model-based methods require fitting and hyperparameter tuning. These parameter choices can change the results, which invites bad statistical practice and reduces the replicability. New recording techniques that yield increasingly large numbers of cells would benefit from a test for cell-inclusion that requires no manual curation. Here, we present the parameter-free ZETA-test, which outperforms t-tests, ANOVAs, and renewal-process-based methods by including more cells at a similar false-positive rate. We show that our procedure works across brain regions and recording techniques, including calcium imaging and Neuropixels data. Furthermore, in illustration of the method, we show in mouse visual cortex that 1) visuomotor-mismatch and spatial location are encoded by different neuronal subpopulations; and 2) optogenetic stimulation of VIP cells leads to early inhibition and subsequent disinhibition.
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23

Buccino, Alessio Paolo, Samuel Garcia, and Pierre Yger. "Spike sorting: new trends and challenges of the era of high-density probes." Progress in Biomedical Engineering, April 29, 2022. http://dx.doi.org/10.1088/2516-1091/ac6b96.

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Abstract Recording from a large neuronal population of neurons is a crucial challenge to unravel how information is processed by the brain. In this review, we highlight the recent advances made in the field of “spike sorting”, which is arguably a very essential processing step to extract neuronal activity from extracellular recordings. We more specifically target the challenges faced by newly manufactured high-density multielectrode array devices (HD-MEA), e.g. Neuropixels probes. Among them, we cover in depth the prominent problem of drifts (movements of the neurons with respect to the recording devices) and the current solutions to circumscribe it. In addition, we also review recent contributions making use of deep learning approaches for spike sorting, highlighting their advantages and disadvantages. Next, we highlight efforts and advances in unifying, validating, and benchmarking spike sorting tools. Finally, we discuss the spike sorting field in terms of its open and unsolved challenges, specifically regarding scalability and reproducibility. We conclude by providing our personal view on how the future of spike sorting, calling for a community-based development and validation of spike sorting algorithms and fully automated, cloud-based spike sorting solutions for the neuroscience community.
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24

Trepka, Ethan B., Shude Zhu, Ruobing Xia, Xiaomo Chen, and Tirin Moore. "Functional interactions among neurons within single columns of macaque V1." eLife 11 (November 2, 2022). http://dx.doi.org/10.7554/elife.79322.

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Recent developments in high-density neurophysiological tools now make it possible to record from hundreds of single neurons within local, highly interconnected neural networks. Among the many advantages of such recordings is that they dramatically increase the quantity of identifiable, functional interactions between neurons thereby providing an unprecedented view of local circuits. Using high-density, Neuropixels recordings from single neocortical columns of primary visual cortex in nonhuman primates, we identified 1000s of functionally interacting neuronal pairs using established crosscorrelation approaches. Our results reveal clear and systematic variations in the synchrony and strength of functional interactions within single cortical columns. Despite neurons residing within the same column, both measures of interactions depended heavily on the vertical distance separating neuronal pairs, as well as on the similarity of stimulus tuning. In addition, we leveraged the statistical power afforded by the large numbers of functionally interacting pairs to categorize interactions between neurons based on their crosscorrelation functions. These analyses identified distinct, putative classes of functional interactions within the full population. These classes of functional interactions were corroborated by their unique distributions across defined laminar compartments and were consistent with known properties of V1 cortical circuitry, such as the lead-lag relationship between simple and complex cells. Our results provide a clear proof-of-principle for the use of high-density neurophysiological recordings to assess circuit-level interactions within local neuronal networks.
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25

Fuglstad, Jingyi Guo, Pearl Saldanha, Jacopo Paglia, and Jonathan R. Whitlock. "Histological E-data registration in rodent brain spaces." eLife 12 (January 13, 2023). http://dx.doi.org/10.7554/elife.83496.

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Recording technologies for rodents have seen huge advances in the last decade, allowing users to sample thousands of neurons simultaneously from multiple brain regions. This has prompted the need for digital tool kits to aid in curating anatomical data, however, existing tools either provide limited functionalities or require users to be proficient in coding to use them. To address this we created HERBS (Histological E-data Registration in rodent Brain Spaces), a comprehensive new tool for rodent users that offers a broad range of functionalities through a user-friendly graphical user interface. Prior to experiments, HERBS can be used to plan coordinates for implanting electrodes, targeting viral injections or tracers. After experiments, users can register recording electrode locations (e.g. Neuropixels, tetrodes), viral expression or other anatomical features, and visualize the results in 2D or 3D. Additionally, HERBS can delineate labeling from multiple injections across tissue sections and obtain individual cell counts.Regional delineations in HERBS are based either on annotated 3D volumes from the Waxholm Space Atlas of the Sprague Dawley Rat Brain or the Allen Mouse Brain Atlas, though HERBS can work with compatible volume atlases from any species users wish to install. HERBS allows users to scroll through the digital brain atlases and provides custom-angle slice cuts through the volumes, and supports free-transformation of tissue sections to atlas slices. Furthermore, HERBS allows users to reconstruct a 3D brain mesh with tissue from individual animals. HERBS is a multi-platform open-source Python package that is available on PyPI and GitHub, and is compatible with Windows, macOS and Linux operating systems.
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26

Town, Stephen M., Katarina C. Poole, Katherine C. Wood, and Jennifer K. Bizley. "Reversible inactivation of ferret auditory cortex impairs spatial and non-spatial hearing." Journal of Neuroscience, January 5, 2023, JN—RM—1426–22. http://dx.doi.org/10.1523/jneurosci.1426-22.2022.

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A key question in auditory neuroscience is to what extent are brain regions functionally specialized for processing specific sound features such as location and identity. In auditory cortex, correlations between neural activity and sounds support both the specialization of distinct cortical subfields, and encoding of multiple sound features within individual cortical areas. However, few studies have tested the contribution of auditory cortex to hearing in multiple contexts. Here we determined the role of ferret primary auditory cortex in both spatial and non-spatial hearing by reversibly inactivating the middle ectosylvian gyrus during behavior using cooling (n=2 females) or optogenetics (n=1 female). Optogenetic experiments utilized the mDLx promoter to express Channelrhodopsin2 in GABAergic interneurons and we confirmed both viral expression (n=2 females) and light-driven suppression of spiking activity in auditory cortex, recorded using Neuropixels under anesthesia (n=465 units from 2 additional untrained female ferrets). Cortical inactivation via cooling or optogenetics impaired vowel discrimination in co-located noise. Ferrets implanted with cooling loops were tested in additional conditions that revealed no deficits for identifying vowels in clean conditions, or when the temporally coincident vowel and noise were spatially separated by 180 degrees. These animals did however show impaired sound localization when inactivating the same auditory cortical region implicated in vowel discrimination in noise. Our results demonstrate that, as a brain region showing mixed selectivity for spatial and non-spatial features of sound, primary auditory cortex contributes to multiple forms of hearing.SIGNIFICANCE STATEMENT:Neurons in primary auditory cortex are often sensitive to the location and identity of sounds. Here we inactivated auditory cortex during spatial and non- spatial listening tasks using cooling, or optogenetics. Auditory cortical inactivation impaired multiple behaviors, demonstrating a role in both the analysis of sound location and identity and confirming a functional contribution of mixed selectivity observed in neural activity. Parallel optogenetic experiments in two additional untrained ferrets linked behavior to physiology by demonstrating that expression of Channelrhodopsin 2 permitted rapid light-driven suppression of auditory cortical activity recorded under anesthesia.
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