1
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Shoup AM, Porwal N, Fakharian MA, Hage P, Orozco SP, Shadmehr R. Rejuvenating silicon probes for acute neurophysiology. J Neurophysiol 2024; 132:308-315. [PMID: 38865216 PMCID: PMC11383388 DOI: 10.1152/jn.00121.2024] [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: 03/25/2024] [Revised: 06/11/2024] [Accepted: 06/11/2024] [Indexed: 06/14/2024] Open
Abstract
Neurophysiological recording with a new probe often yields better signal quality than with a used probe. Why does the signal quality degrade after only a few experiments? Here, we considered silicon probes in which the contacts are densely packed, and each contact is coated with a conductive polymer that increases its surface area. We tested 12 Cambridge Neurotech silicon probes during 61 recording sessions from the brain of three marmosets. Out of the box, each probe arrived with an electrodeposited polymer coating on 64 gold contacts and an impedance of around 50 kΩ. With repeated use, the impedance increased and there was a corresponding decrease in the number of well-isolated neurons. Imaging of the probes suggested that the reduction in signal quality was due to a gradual loss of the polymer coating. To rejuvenate the probes, we first stripped the contacts, completely removing their polymer coating, and then recoated them in a solution of 10 mM 3,4-Ethylenedioxythiophene (EDOT) monomer with 11 mM Poly(sodium 4-styrenesulfonate) (PSS) using a current density of about 3 mA/cm2 for 30 s. This recoating process not only returned probe impedance to around 50 kΩ but also yielded significantly improved signal quality during neurophysiological recordings. Thus, insertion into the brain promoted the loss of the polymer that coated the contacts of the silicon probes. This led to degradation of signal quality, but recoating rejuvenated the probes.NEW & NOTEWORTHY With repeated use, a silicon probe's ability to isolate neurons degrades. As a result, the probe is often discarded after only a handful of uses. Here, we demonstrate a major source of this problem and then produce a solution to rejuvenate the probes.
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Affiliation(s)
- Alden M Shoup
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, United States
| | - Natasha Porwal
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, United States
| | - Mohammad Amin Fakharian
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, United States
| | - Paul Hage
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, United States
| | - Simon P Orozco
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, United States
| | - Reza Shadmehr
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland, United States
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2
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Pi JS, Fakharian MA, Hage P, Sedaghat-Nejad E, Muller SZ, Shadmehr R. The olivary input to the cerebellum dissociates sensory events from movement plans. Proc Natl Acad Sci U S A 2024; 121:e2318849121. [PMID: 38630714 PMCID: PMC11047103 DOI: 10.1073/pnas.2318849121] [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: 10/27/2023] [Accepted: 03/19/2024] [Indexed: 04/19/2024] Open
Abstract
Neurons in the inferior olive are thought to anatomically organize the Purkinje cells (P-cells) of the cerebellum into computational modules, but what is computed by each module? Here, we designed a saccade task in marmosets that dissociated sensory events from motor events and then recorded the complex and simple spikes of hundreds of P-cells. We found that when a visual target was presented at a random location, the olive reported the direction of that sensory event to one group of P-cells, but not to a second group. However, just before movement onset, it reported the direction of the planned movement to both groups, even if that movement was not toward the target. At the end of the movement if the subject experienced an error but chose to withhold the corrective movement, only the first group received information about the sensory prediction error. We organized the P-cells based on the information content of their olivary input and found that in the group that received sensory information, the simple spikes were suppressed during fixation, then produced a burst before saccade onset in a direction consistent with assisting the movement. In the second group, the simple spikes were not suppressed during fixation but burst near saccade deceleration in a direction consistent with stopping the movement. Thus, the olive differentiated the P-cells based on whether they would receive sensory or motor information, and this defined their contributions to control of movements as well as holding still.
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Affiliation(s)
- Jay S. Pi
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MA21205
| | - Mohammad Amin Fakharian
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MA21205
| | - Paul Hage
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MA21205
| | - Ehsan Sedaghat-Nejad
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MA21205
| | - Salomon Z. Muller
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY10027
| | - Reza Shadmehr
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MA21205
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3
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Hur SW, Safaryan K, Yang L, Blair HT, Masmanidis SC, Mathews PJ, Aharoni D, Golshani P. Correlated signatures of social behavior in cerebellum and anterior cingulate cortex. eLife 2024; 12:RP88439. [PMID: 38345922 PMCID: PMC10942583 DOI: 10.7554/elife.88439] [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] [Indexed: 02/15/2024] Open
Abstract
The cerebellum has been implicated in the regulation of social behavior. Its influence is thought to arise from communication, via the thalamus, to forebrain regions integral in the expression of social interactions, including the anterior cingulate cortex (ACC). However, the signals encoded or the nature of the communication between the cerebellum and these brain regions is poorly understood. Here, we describe an approach that overcomes technical challenges in exploring the coordination of distant brain regions at high temporal and spatial resolution during social behavior. We developed the E-Scope, an electrophysiology-integrated miniature microscope, to synchronously measure extracellular electrical activity in the cerebellum along with calcium imaging of the ACC. This single coaxial cable device combined these data streams to provide a powerful tool to monitor the activity of distant brain regions in freely behaving animals. During social behavior, we recorded the spike timing of multiple single units in cerebellar right Crus I (RCrus I) Purkinje cells (PCs) or dentate nucleus (DN) neurons while synchronously imaging calcium transients in contralateral ACC neurons. We found that during social interactions a significant subpopulation of cerebellar PCs were robustly inhibited, while most modulated neurons in the DN were activated, and their activity was correlated with positively modulated ACC neurons. These distinctions largely disappeared when only non-social epochs were analyzed suggesting that cerebellar-cortical interactions were behaviorally specific. Our work provides new insights into the complexity of cerebellar activation and co-modulation of the ACC during social behavior and a valuable open-source tool for simultaneous, multimodal recordings in freely behaving mice.
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Affiliation(s)
- Sung Won Hur
- Department of Neurology, DGSOM, University of California Los AngelesLos AngelesUnited States
- The Lundquist Institute for Biomedical Innovation, Harbor-UCLA Medical CenterTorranceUnited States
| | - Karen Safaryan
- Department of Neurology, DGSOM, University of California Los AngelesLos AngelesUnited States
| | - Long Yang
- Department of Neurobiology, University of California Los AngelesLos AngelesUnited States
| | - Hugh T Blair
- Department of Psychology, University of California Los AngelesLos AngelesUnited States
| | - Sotiris C Masmanidis
- Department of Neurobiology, University of California Los AngelesLos AngelesUnited States
| | - Paul J Mathews
- The Lundquist Institute for Biomedical Innovation, Harbor-UCLA Medical CenterTorranceUnited States
- Department of Neurology, Harbor-UCLA Medical CenterTorranceUnited States
| | - Daniel Aharoni
- Department of Neurology, DGSOM, University of California Los AngelesLos AngelesUnited States
| | - Peyman Golshani
- Department of Neurology, DGSOM, University of California Los AngelesLos AngelesUnited States
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4
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Muller SZ, Pi JS, Hage P, Fakharian MA, Sedaghat-Nejad E, Shadmehr R. Complex spikes perturb movements and reveal the sensorimotor map of Purkinje cells. Curr Biol 2023; 33:4869-4879.e3. [PMID: 37858343 PMCID: PMC10751015 DOI: 10.1016/j.cub.2023.09.062] [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: 05/15/2023] [Revised: 07/05/2023] [Accepted: 09/25/2023] [Indexed: 10/21/2023]
Abstract
Computations that are performed by the cerebellar cortex are transmitted via simple spikes of Purkinje cells (P-cells) to downstream structures, but because P-cells are many synapses away from muscles, we do not know the relationship between modulation of simple spikes and control of behavior. Here, we recorded the spiking activities of hundreds of P-cells in the oculomotor vermis of marmosets during saccadic eye movements and found that following the presentation of a visual stimulus, the olivary input to a P-cell coarsely described the direction and amplitude of the visual stimulus as well as the upcoming movement. Occasionally, the complex spike occurred just before saccade onset, suppressing the P-cell's simple spikes and disrupting its output during that saccade. Remarkably, this brief suppression of simple spikes altered the saccade's trajectory by pulling the eyes toward the part of the visual space that was preferentially encoded by the olivary input to that P-cell. Thus, there is an alignment between the sensory space encoded by the complex spikes and the behavior conveyed by the simple spikes: a reduction in simple spikes is a signal to bias the ongoing movement toward the part of the sensory space preferentially encoded by the olivary input to that P-cell.
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Affiliation(s)
- Salomon Z Muller
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY 10027, USA.
| | - Jay S Pi
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Paul Hage
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Mohammad Amin Fakharian
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Ehsan Sedaghat-Nejad
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
| | - Reza Shadmehr
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA.
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5
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Hur SW, Safaryan K, Yang L, Blair HT, Masmanidis SC, Mathews PJ, Aharoni D, Golshani P. Correlated signatures of social behavior in cerebellum and anterior cingulate cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.05.535750. [PMID: 37066345 PMCID: PMC10104017 DOI: 10.1101/2023.04.05.535750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
The cerebellum has been implicated in the regulation of social behavior. Its influence is thought to arise from communication, via the thalamus, to forebrain regions integral in the expression of social interactions, including the anterior cingulate cortex (ACC). However, the signals encoded or the nature of the communication between the cerebellum and these brain regions is poorly understood. Here, we describe an approach that overcomes technical challenges in exploring the coordination of distant brain regions at high temporal and spatial resolution during social behavior. We developed the E-Scope, an electrophysiology-integrated miniature microscope, to synchronously measure extracellular electrical activity in the cerebellum along with calcium imaging of the ACC. This single coaxial cable device combined these data streams to provide a powerful tool to monitor the activity of distant brain regions in freely behaving animals. During social behavior, we recorded the spike timing of multiple single units in cerebellar right Crus I (RCrus I) Purkinje cells (PCs) or dentate nucleus (DN) neurons while synchronously imaging calcium transients in contralateral ACC neurons. We found that during social interactions a significant subpopulation of cerebellar PCs were robustly inhibited, while most modulated neurons in the DN were activated, and their activity was correlated with positively modulated ACC neurons. These distinctions largely disappeared when only non-social epochs were analyzed suggesting that cerebellar-cortical interactions were behaviorally specific. Our work provides new insights into the complexity of cerebellar activation and co-modulation of the ACC during social behavior and a valuable open-source tool for simultaneous, multimodal recordings in freely behaving mice.
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Affiliation(s)
- Sung Won Hur
- Department of Neurology, DGSOM, University of California Los Angeles, Los Angeles, California, USA
- The Lundquist Institute for Biomedical Innovation, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Karen Safaryan
- Department of Neurology, DGSOM, University of California Los Angeles, Los Angeles, California, USA
| | - Long Yang
- Department of Neurobiology, University of California Los Angeles, Los Angeles, California, USA
| | - Hugh T Blair
- Department of Psychology, University of California Los Angeles, Los Angeles, California, USA
| | - Sotiris C Masmanidis
- Department of Neurobiology, University of California Los Angeles, Los Angeles, California, USA
| | - Paul J Mathews
- The Lundquist Institute for Biomedical Innovation, Harbor-UCLA Medical Center, Torrance, California, USA
- Department of Neurology, Harbor-UCLA Medical Center, Torrance, California, USA
| | - Daniel Aharoni
- Department of Neurology, DGSOM, University of California Los Angeles, Los Angeles, California, USA
| | - Peyman Golshani
- Department of Neurology, DGSOM, University of California Los Angeles, Los Angeles, California, USA
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6
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Muller SZ, Pi JS, Hage P, Fakharian MA, Sedaghat-Nejad E, Shadmehr R. Complex spikes perturb movements, revealing the sensorimotor map of Purkinje cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.16.537034. [PMID: 37090615 PMCID: PMC10120735 DOI: 10.1101/2023.04.16.537034] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
The cerebellar cortex performs computations that are critical for control of our actions, and then transmits that information via simple spikes of Purkinje cells (P-cells) to downstream structures. However, because P-cells are many synapses away from muscles, we do not know how their output affects behavior. Furthermore, we do not know the level of abstraction, i.e., the coordinate system of the P-cell's output. Here, we recorded spiking activities of hundreds of P-cells in the oculomotor vermis of marmosets during saccadic eye movements and found that following the presentation of a visual stimulus, the olivary input to a P-cell encoded a probabilistic signal that coarsely described both the direction and the amplitude of that stimulus. When this input was present, the resulting complex spike briefly suppressed the P-cell's simple spikes, disrupting the P-cell's output during that saccade. Remarkably, this brief suppression altered the saccade's trajectory by pulling the eyes toward the part of the visual space that was preferentially encoded by the olivary input to that P-cell. Thus, analysis of behavior in the milliseconds following a complex spike unmasked how the P-cell's output influenced behavior: the preferred location in the coordinates of the visual system as conveyed probabilistically from the inferior olive to a P-cell defined the action in the coordinates of the motor system for which that P-cell's simple spikes directed behavior.
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Affiliation(s)
- Salomon Z. Muller
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY USA
| | - Jay S. Pi
- Laboratory for Computational Motor Control, Dept. of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland USA
| | - Paul Hage
- Laboratory for Computational Motor Control, Dept. of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland USA
| | - Mohammad Amin Fakharian
- Laboratory for Computational Motor Control, Dept. of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland USA
| | - Ehsan Sedaghat-Nejad
- Laboratory for Computational Motor Control, Dept. of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland USA
| | - Reza Shadmehr
- Laboratory for Computational Motor Control, Dept. of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland USA
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7
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How Do Spike Collisions Affect Spike Sorting Performance? eNeuro 2022; 9:ENEURO.0105-22.2022. [PMID: 36171060 PMCID: PMC9532018 DOI: 10.1523/eneuro.0105-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 06/15/2022] [Accepted: 06/23/2022] [Indexed: 12/15/2022] Open
Abstract
Recently, a new generation of devices have been developed to record neural activity simultaneously from hundreds of electrodes with a very high spatial density, both for in vitro and in vivo applications. While these advances enable to record from many more cells, they also challenge the already complicated process of spike sorting (i.e., extracting isolated single-neuron activity from extracellular signals). In this work, we used synthetic ground-truth recordings with controlled levels of correlations among neurons to quantitatively benchmark the performance of state-of-the-art spike sorters focusing specifically on spike collisions. Our results show that while modern template-matching-based algorithms are more accurate than density-based approaches, all methods, to some extent, failed to detect synchronous spike events of neurons with similar extracellular signals. Interestingly, the performance of the sorters is not largely affected by the spiking activity in the recordings, with respect to average firing rates and spike-train correlation levels. Since the performances of all modern spike sorting algorithms can be affected as function of the activity of the recorded neurons, scientific claims on correlations and synchrony should be carefully assessed based on the analysis provided in this paper.
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8
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Mahadevan A, Codadu NK, Parrish RR. Xenon LFP Analysis Platform Is a Novel Graphical User Interface for Analysis of Local Field Potential From Large-Scale MEA Recordings. Front Neurosci 2022; 16:904931. [PMID: 35844228 PMCID: PMC9285004 DOI: 10.3389/fnins.2022.904931] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 06/08/2022] [Indexed: 11/24/2022] Open
Abstract
High-density multi-electrode array (HD-MEA) has enabled neuronal measurements at high spatial resolution to record local field potentials (LFP), extracellular action potentials, and network-wide extracellular recording on an extended spatial scale. While we have advanced recording systems with over 4,000 electrodes capable of recording data at over 20 kHz, it still presents computational challenges to handle, process, extract, and view information from these large recordings. We have created a computational method, and an open-source toolkit built in Python, rendered on a web browser using Plotly’s Dash for extracting and viewing the data and creating interactive visualization. In addition to extracting and viewing entire or small chunks of data sampled at lower or higher frequencies, respectively, it provides a framework to collect user inputs, analyze channel groups, generate raster plots, view quick summary measures for LFP activity, detect and isolate noise channels, and generate plots and visualization in both time and frequency domain. Incorporated into our Graphical User Interface (GUI), we also created a novel seizure detection method, which can be used to detect the onset of seizures in all or a selected group of channels and provide the following measures of seizures: distance, duration, and propagation across the region of interest. We demonstrate the utility of this toolkit, using datasets collected from an HD-MEA device comprising of 4,096 recording electrodes. For the current analysis, we demonstrate the toolkit and methods with a low sampling frequency dataset (300 Hz) and a group of approximately 400 channels. Using this toolkit, we present novel data demonstrating increased seizure propagation speed from brain slices of Scn1aHet mice compared to littermate controls. While there have been advances in HD-MEA recording systems with high spatial and temporal resolution, limited tools are available for researchers to view and process these big datasets. We now provide a user-friendly toolkit to analyze LFP activity obtained from large-scale MEA recordings with translatable applications to EEG recordings and demonstrate the utility of this new graphic user interface with novel biological findings.
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Affiliation(s)
- Arjun Mahadevan
- Department of Cellular and Molecular Biology, Xenon Pharmaceuticals Inc., Burnaby, BC, Canada
| | - Neela K. Codadu
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, United Kingdom
| | - R. Ryley Parrish
- Department of Cellular and Molecular Biology, Xenon Pharmaceuticals Inc., Burnaby, BC, Canada
- *Correspondence: R. Ryley Parrish,
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9
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Király B, Hangya B. Navigating the Statistical Minefield of Model Selection and Clustering in Neuroscience. eNeuro 2022; 9:ENEURO.0066-22.2022. [PMID: 35835556 PMCID: PMC9282170 DOI: 10.1523/eneuro.0066-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 06/16/2022] [Accepted: 06/22/2022] [Indexed: 11/21/2022] Open
Abstract
Model selection is often implicit: when performing an ANOVA, one assumes that the normal distribution is a good model of the data; fitting a tuning curve implies that an additive and a multiplicative scaler describes the behavior of the neuron; even calculating an average implicitly assumes that the data were sampled from a distribution that has a finite first statistical moment: the mean. Model selection may be explicit, when the aim is to test whether one model provides a better description of the data than a competing one. As a special case, clustering algorithms identify groups with similar properties within the data. They are widely used from spike sorting to cell type identification to gene expression analysis. We discuss model selection and clustering techniques from a statistician's point of view, revealing the assumptions behind, and the logic that governs the various approaches. We also showcase important neuroscience applications and provide suggestions how neuroscientists could put model selection algorithms to best use as well as what mistakes should be avoided.
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Affiliation(s)
- Bálint Király
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, H-1083, Budapest, Hungary
- Department of Biological Physics, Eötvös Loránd University, H-1083, Budapest, Hungary
| | - Balázs Hangya
- Lendület Laboratory of Systems Neuroscience, Institute of Experimental Medicine, H-1083, Budapest, Hungary
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10
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Gaffield MA, Sauerbrei BA, Christie JM. Cerebellum encodes and influences the initiation, performance, and termination of discontinuous movements in mice. eLife 2022; 11:e71464. [PMID: 35451957 PMCID: PMC9075950 DOI: 10.7554/elife.71464] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Accepted: 04/21/2022] [Indexed: 11/23/2022] Open
Abstract
The cerebellum is hypothesized to represent timing information important for organizing salient motor events during periodically performed discontinuous movements. To provide functional evidence validating this idea, we measured and manipulated Purkinje cell (PC) activity in the lateral cerebellum of mice trained to volitionally perform periodic bouts of licking for regularly allocated water rewards. Overall, PC simple spiking modulated during task performance, mapping phasic tongue protrusions and retractions, as well as ramping prior to both lick-bout initiation and termination, two important motor events delimiting movement cycles. The ramping onset occurred earlier for the initiation of uncued exploratory licking that anticipated water availability relative to licking that was reactive to water allocation, suggesting that the cerebellum is engaged differently depending on the movement context. In a subpopulation of PCs, climbing-fiber-evoked responses also increased during lick-bout initiation, but not termination, highlighting differences in how cerebellar input pathways represent task-related information. Optogenetic perturbation of PC activity disrupted the behavior by degrading lick-bout rhythmicity in addition to initiating and terminating licking bouts confirming a causative role in movement organization. Together, these results substantiate that the cerebellum contributes to the initiation and timing of repeated motor actions.
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Affiliation(s)
| | | | - Jason M Christie
- Max Planck Florida Institute for NeuroscienceJupiterUnited States
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11
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Sedaghat-Nejad E, Pi JS, Hage P, Fakharian MA, Shadmehr R. Synchronous spiking of cerebellar Purkinje cells during control of movements. Proc Natl Acad Sci U S A 2022; 119:e2118954119. [PMID: 35349338 PMCID: PMC9168948 DOI: 10.1073/pnas.2118954119] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 02/13/2022] [Indexed: 11/18/2022] Open
Abstract
SignificanceThe information that one region of the brain transmits to another is usually viewed through the lens of firing rates. However, if the output neurons could vary the timing of their spikes, then, through synchronization, they would spotlight information that may be critical for control of behavior. Here we report that, in the cerebellum, Purkinje cell populations that share a preference for error convey, to the nucleus, when to decelerate the movement, by reducing their firing rates and temporally synchronizing the remaining spikes.
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Affiliation(s)
- Ehsan Sedaghat-Nejad
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205
| | - Jay S. Pi
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205
| | - Paul Hage
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205
| | - Mohammad Amin Fakharian
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences, Tehran, 1956836484, Iran
| | - Reza Shadmehr
- Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD 21205
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