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• W3110842501 abstract "•CaMPARI2 can permanently label neurons based on their in vivo firing rate set point•Total E/I ratio is not correlated with firing rate set point of L4 pyramidal neurons•High set point neurons have greater intrinsic excitability than low set point neurons•High set point neurons have stronger local excitatory inputs, but outputs don’t differ Neocortical pyramidal neurons regulate firing around a stable mean firing rate (FR) that can differ by orders of magnitude between neurons, but the factors that determine where individual neurons sit within this broad FR distribution are not understood. To access low- and high-FR neurons for ex vivo analysis, we used Ca2+- and UV-dependent photoconversion of CaMPARI2 in vivo to permanently label neurons according to mean FR. CaMPARI2 photoconversion was correlated with immediate early gene expression and higher FRs ex vivo and tracked the drop and rebound in ensemble mean FR induced by prolonged monocular deprivation. High-activity L4 pyramidal neurons had greater intrinsic excitability and recurrent excitatory synaptic strength, while E/I ratio, local output strength, and local connection probability were not different. Thus, in L4 pyramidal neurons (considered a single transcriptional cell type), a broad mean FR distribution is achieved through graded differences in both intrinsic and synaptic properties. Neocortical pyramidal neurons regulate firing around a stable mean firing rate (FR) that can differ by orders of magnitude between neurons, but the factors that determine where individual neurons sit within this broad FR distribution are not understood. To access low- and high-FR neurons for ex vivo analysis, we used Ca2+- and UV-dependent photoconversion of CaMPARI2 in vivo to permanently label neurons according to mean FR. CaMPARI2 photoconversion was correlated with immediate early gene expression and higher FRs ex vivo and tracked the drop and rebound in ensemble mean FR induced by prolonged monocular deprivation. High-activity L4 pyramidal neurons had greater intrinsic excitability and recurrent excitatory synaptic strength, while E/I ratio, local output strength, and local connection probability were not different. Thus, in L4 pyramidal neurons (considered a single transcriptional cell type), a broad mean FR distribution is achieved through graded differences in both intrinsic and synaptic properties. Decades of research have convincingly demonstrated that the activity of neuronal circuits is tightly controlled, despite many forces that dynamically perturb circuit excitability (Davis, 2013Davis G.W. Homeostatic Signaling and the Stabilization of Neural Function.Neuron. 2013; 80: 718-728Abstract Full Text Full Text PDF PubMed Scopus (174) Google Scholar; Marder, 2011Marder E. Variability, compensation, and modulation in neurons and circuits.Proc. Natl. Acad. Sci. USA. 2011; 108: 15542-15548Crossref PubMed Scopus (216) Google Scholar; Turrigiano, 2008Turrigiano G.G. The Self-Tuning Neuron: Synaptic Scaling of Excitatory Synapses.Cell. 2008; 135: 422-435Abstract Full Text Full Text PDF PubMed Scopus (980) Google Scholar). To enable this stability, rodent neocortical pyramidal neurons actively maintain their mean firing rates within a target range, termed their firing rate set point (FRSP) (Dhawale et al., 2017Dhawale A.K. Poddar R. Wolff S.B. Normand V.A. Kopelowitz E. Ölveczky B.P. Automated long-term recording and analysis of neural activity in behaving animals.eLife. 2017; 6: e27702Crossref PubMed Scopus (61) Google Scholar; Hengen et al., 2016Hengen K.B. Torrado Pacheco A. McGregor J.N. Van Hooser S.D. Turrigiano G.G. Neuronal Firing Rate Homeostasis Is Inhibited by Sleep and Promoted by Wake.Cell. 2016; 165: 180-191Abstract Full Text Full Text PDF PubMed Scopus (151) Google Scholar; Keck et al., 2013Keck T. Keller G.B. Jacobsen R.I. Eysel U.T. Bonhoeffer T. Hübener M. Synaptic Scaling and Homeostatic Plasticity in the Mouse Visual Cortex In Vivo.Neuron. 2013; 80: 327-334Abstract Full Text Full Text PDF PubMed Scopus (181) Google Scholar; Torrado Pacheco et al., 2019Torrado Pacheco A. Tilden E.I. Grutzner S.M. Lane B.J. Wu Y. Hengen K.B. Gjorgjieva J. Turrigiano G.G. Rapid and active stabilization of visual cortical firing rates across light-dark transitions.Proc. Natl. Acad. Sci. USA. 2019; 116: 18068-18077Crossref PubMed Scopus (9) Google Scholar, Torrado Pacheco et al., 2020Torrado Pacheco A. Bottorff J. Gao Y. Turrigiano G.G. Sleep promotes downward firing rate homeostasis.Neuron. 2020; (Published online November 23, 2020)https://doi.org/10.1016/j.neuron.2020.11.001Abstract Full Text Full Text PDF Scopus (22) Google Scholar). Remarkably, while FRSPs of pyramidal neurons can span several orders of magnitude (Buzsáki and Mizuseki, 2014Buzsáki G. Mizuseki K. The log-dynamic brain: how skewed distributions affect network operations.Nat. Rev. Neurosci. 2014; 15: 264-278Crossref PubMed Scopus (464) Google Scholar), individual neurons reliably return to their own specific FRSP following activity perturbations, indicating that these individual set points are actively maintained (Hengen et al., 2016Hengen K.B. Torrado Pacheco A. McGregor J.N. Van Hooser S.D. Turrigiano G.G. Neuronal Firing Rate Homeostasis Is Inhibited by Sleep and Promoted by Wake.Cell. 2016; 165: 180-191Abstract Full Text Full Text PDF PubMed Scopus (151) Google Scholar; Torrado Pacheco et al., 2020Torrado Pacheco A. Bottorff J. Gao Y. Turrigiano G.G. Sleep promotes downward firing rate homeostasis.Neuron. 2020; (Published online November 23, 2020)https://doi.org/10.1016/j.neuron.2020.11.001Abstract Full Text Full Text PDF Scopus (22) Google Scholar). The factors that generate this broad distribution of FRSPs in vivo are poorly understood, so we developed an approach for permanently labeling pyramidal neurons according to their in vivo mean firing rates that permits subsequent ex vivo analysis of their synaptic and intrinsic properties. This broad distribution of mean FRs is a ubiquitous feature of cortical circuits that likely contributes to the information carrying capacity of these networks (Buzsáki and Mizuseki, 2014Buzsáki G. Mizuseki K. The log-dynamic brain: how skewed distributions affect network operations.Nat. Rev. Neurosci. 2014; 15: 264-278Crossref PubMed Scopus (464) Google Scholar). Disruptions in the homeostatic regulation of network activity have been proposed to contribute to a wide range of neurological disorders, including Alzheimer’s disease, epilepsy, and autism spectrum disorders (Ebert and Greenberg, 2013Ebert D.H. Greenberg M.E. Activity-dependent neuronal signalling and autism spectrum disorder.Nature. 2013; 493: 327-337Crossref PubMed Scopus (406) Google Scholar; Nelson and Valakh, 2015Nelson S.B. Valakh V. Excitatory/Inhibitory Balance and Circuit Homeostasis in Autism Spectrum Disorders.Neuron. 2015; 87: 684-698Abstract Full Text Full Text PDF PubMed Scopus (532) Google Scholar; Styr and Slutsky, 2018Styr B. Slutsky I. Imbalance between firing homeostasis and synaptic plasticity drives early-phase Alzheimer’s disease.Nat. Neurosci. 2018; 21: 1-11Crossref Scopus (112) Google Scholar), supporting the central importance of network stability in proper circuit function. High- and low-FR neurons in rodent frontal cortex and hippocampus are differentially modulated by sleep states, suggesting that they are functionally distinct and may play unique roles in information storage and transmission (Miyawaki and Diba, 2016Miyawaki H. Diba K. Regulation of Hippocampal Firing by Network Oscillations during Sleep.Curr. Biol. 2016; 26: 893-902Abstract Full Text Full Text PDF PubMed Scopus (67) Google Scholar; Miyawaki et al., 2019Miyawaki H. Watson B.O. Diba K. Neuronal firing rates diverge during REM and homogenize during non-REM.Sci. Rep. 2019; 9: 689Crossref PubMed Scopus (17) Google Scholar; Watson et al., 2016Watson B.O. Levenstein D. Greene J.P. Gelinas J.N. Buzsáki G. Network Homeostasis and State Dynamics of Neocortical Sleep.Neuron. 2016; 90: 1-15Abstract Full Text Full Text PDF PubMed Scopus (151) Google Scholar). The restoration of individual mean FR following perturbations can be driven by homeostatic changes in synaptic strength, intrinsic excitability, or both (Gainey and Feldman, 2017Gainey M.A. Feldman D.E. Multiple shared mechanisms for homeostatic plasticity in rodent somatosensory and visual cortex.Philos. Trans. R Soc. Lond. B Biol. Sci. 2017; 372: 20160157Crossref PubMed Scopus (43) Google Scholar; Hengen et al., 2013Hengen K.B. Lambo M.E. Hooser S.D.V. Katz D.B. Turrigiano G.G. Firing Rate Homeostasis in Visual Cortex of Freely Behaving Rodents.Neuron. 2013; 80: 335-342Abstract Full Text Full Text PDF PubMed Scopus (183) Google Scholar; Lambo and Turrigiano, 2013Lambo M.E. Turrigiano G.G. Synaptic and Intrinsic Homeostatic Mechanisms Cooperate to Increase L2/3 Pyramidal Neuron Excitability during a Late Phase of Critical Period Plasticity.J. Neurosci. 2013; 33: 8810-8819Crossref PubMed Scopus (90) Google Scholar; Maffei et al., 2004Maffei A. Nelson S.B. Turrigiano G.G. Selective reconfiguration of layer 4 visual cortical circuitry by visual deprivation.Nat. Neurosci. 2004; 7: 1353-1359Crossref PubMed Scopus (312) Google Scholar; Nataraj and Turrigiano, 2011Nataraj K. Turrigiano G.G. Regional and Temporal Specificity of Intrinsic Plasticity Mechanisms in Rodent Primary Visual Cortex.J. Neurosci. 2011; 31: 17932-17940Crossref PubMed Scopus (18) Google Scholar, Torrado Pacheco et al., 2020Torrado Pacheco A. Bottorff J. Gao Y. Turrigiano G.G. Sleep promotes downward firing rate homeostasis.Neuron. 2020; (Published online November 23, 2020)https://doi.org/10.1016/j.neuron.2020.11.001Abstract Full Text Full Text PDF Scopus (22) Google Scholar), and in vitro data suggest that excitatory synaptic strengths and intrinsic excitability are jointly regulated as a means of maintaining different FRSPs (Joseph and Turrigiano, 2017Joseph A. Turrigiano G.G. All for one but not one for all: Excitatory synaptic scaling and intrinsic excitability are coregulated by CaMKIV, while inhibitory synaptic scaling is under independent control.J. Neurosci. 2017; 37: 6778-6785Crossref PubMed Scopus (47) Google Scholar). The overall balance between excitation and inhibition (E/I) has also been proposed to play an important role in differentiating high- from low-activity neurons (Yassin et al., 2010Yassin L. Benedetti B.L. Jouhanneau J.-S. Wen J.A. Poulet J.F.A. Barth A.L. An Embedded Subnetwork of Highly Active Neurons in the Neocortex.Neuron. 2010; 68: 1043-1050Abstract Full Text Full Text PDF PubMed Scopus (156) Google Scholar), and in the homeostatic stabilization of network activity (Keck et al., 2017Keck T. Hübener M. Bonhoeffer T. Interactions between synaptic homeostatic mechanisms: an attempt to reconcile BCM theory, synaptic scaling, and changing excitation/inhibition balance.Curr. Opin. Neurobiol. 2017; 43: 87-93Crossref PubMed Scopus (38) Google Scholar). Despite this progress, it is currently unknown how intrinsic excitability, excitatory synaptic strength, and E/I balance contribute to the broad distribution of FRSPs seen even within single cell types in vivo, in part because of the difficulty of identifying individual neurons ex vivo after recording their activity in vivo. Targeted approaches for labeling individual neurons based on their in vivo responses are low throughput and prone to sampling bias (Gilbert and Wiesel, 1979Gilbert C.D. Wiesel T.N. Morphology and intracortical projections of functionally characterised neurones in the cat visual cortex.Nature. 1979; 280: 280120a0Crossref Scopus (723) Google Scholar; Lien and Scanziani, 2011Lien A.D. Scanziani M. In vivo Labeling of Constellations of Functionally Identified Neurons for Targeted in vitro Recordings.Front. Neural Circuits. 2011; 5: 16Crossref PubMed Scopus (11) Google Scholar; Pinault, 1996Pinault D. A novel single-cell staining procedure performed in vivo under electrophysiological control: morpho-functional features of juxtacellularly labeled thalamic cells and other central neurons with biocytin or Neurobiotin.J. Neurosci. Methods. 1996; 65: 113-136Crossref PubMed Scopus (566) Google Scholar). Reconstruction of serial sections following in vivo Ca2+ imaging is possible but requires unambiguous realignment of acute slices with in vivo images (Ko et al., 2011Ko H. Hofer S.B. Pichler B. Buchanan K.A. Sjöström P.J. Mrsic-Flogel T.D. Functional specificity of local synaptic connections in neocortical networks.Nature. 2011; 473: 87-91Crossref PubMed Scopus (497) Google Scholar). Labeling neurons based on immediate early gene (IEG) expression can identify active subsets of cells (Yassin et al., 2010Yassin L. Benedetti B.L. Jouhanneau J.-S. Wen J.A. Poulet J.F.A. Barth A.L. An Embedded Subnetwork of Highly Active Neurons in the Neocortex.Neuron. 2010; 68: 1043-1050Abstract Full Text Full Text PDF PubMed Scopus (156) Google Scholar), but the relationship between IEG expression and firing rate is not linear (Tyssowski and Gray, 2019Tyssowski K.M. Gray J.M. The neuronal stimulation-transcription coupling map.Curr. Opin. Neurobiol. 2019; 59: 87-94Crossref PubMed Scopus (11) Google Scholar). Therefore, to permanently label neurons in monocular visual cortex (V1m) of freely behaving mice in vivo based on their mean firing rate, we developed an approach that uses the permanent green-to-red Ca2+- and UV-dependent photoconversion of CaMPARI2 as a proxy for mean neuronal activity (Fosque et al., 2015Fosque B.F. Sun Y. Dana H. Yang C.-T. Ohyama T. Tadross M.R. Patel R. Zlatic M. Kim D.S. Ahrens M.B. et al.Neural circuits. Labeling of active neural circuits in vivo with designed calcium integrators.Science. 2015; 347: 755-760Crossref PubMed Scopus (239) Google Scholar; Moeyaert et al., 2018Moeyaert B. Holt G. Madangopal R. Perez-Alvarez A. Fearey B.C. Trojanowski N.F. Ledderose J. Zolnik T.A. Das A. Patel D. et al.Improved methods for marking active neuron populations.Nat. Commun. 2018; 9: 1-12Crossref PubMed Scopus (51) Google Scholar; Zolnik et al., 2016Zolnik T.A. Sha F. Johenning F.W. Schreiter E.R. Looger L.L. Larkum M.E. Sachdev R.N.S. All-optical functional synaptic connectivity mapping in acute brain slices using the calcium integrator CaMPARI.J. Physiol. 2016; 595: 1465-1477Crossref PubMed Scopus (21) Google Scholar). Following a paradigm that transiently increases neuronal activity, we found a correlation between cFos expression and in vivo CaMPARI2 photoconversion. The red/green ratio of individual neurons was lognormally distributed, similar to the distribution of firing rates. Neurons with greater in vivo photoconversion had higher firing rates ex vivo, and during ex vivo photoconversion, neurons with higher firing rates underwent a greater change in CaMPARI2 red/green ratio. Prolonged monocular deprivation (MD), a manipulation known to first induce a drop and then a restoration of ensemble firing rates (Hengen et al., 2016Hengen K.B. Torrado Pacheco A. McGregor J.N. Van Hooser S.D. Turrigiano G.G. Neuronal Firing Rate Homeostasis Is Inhibited by Sleep and Promoted by Wake.Cell. 2016; 165: 180-191Abstract Full Text Full Text PDF PubMed Scopus (151) Google Scholar), caused first a decrease and then a restoration in ensemble CaMPARI2 red/green ratios. Taken together, these data indicate that CaMPARI2 labeling is sensitive enough to detect differences in mean firing rates, and thus to differentiate between neurons with low and high FRSPs. We went on to characterize the properties that differentiate high- from low-FR neurons and found that high-activity layer 4 (L4) pyramidal neurons had greater intrinsic excitability and received stronger inputs from other L4 pyramidal neurons, although there were no consistent differences in total E/I ratio between these neurons. These data demonstrate that CaMPARI2 can be used to permanently label cells based on their in vivo mean firing rates and suggest that intrinsic excitability and intralaminar excitatory synaptic strength are important contributors to the broad range of FRSPs observed within single cell types in vivo. The Ca2+ dependence, titratability, and irreversibility of CaMPARI2 photoconversion makes it an attractive candidate for activity-dependent labeling of neurons in freely behaving animals in vivo. While CaMPARI2 has previously been used to identify neurons that transiently respond to specific sensory stimuli (Moeyaert et al., 2018Moeyaert B. Holt G. Madangopal R. Perez-Alvarez A. Fearey B.C. Trojanowski N.F. Ledderose J. Zolnik T.A. Das A. Patel D. et al.Improved methods for marking active neuron populations.Nat. Commun. 2018; 9: 1-12Crossref PubMed Scopus (51) Google Scholar), its usefulness as a permanent marker of average activity in vivo over longer time windows (~30 min) has not been assessed. To this end, we injected an adeno-associated virus (AAV) that expresses CaMPARI2 into the monocular portion of primary visual cortex (V1m) of mice at postnatal day 15 (P15) and 1 week later implanted a fiberoptic probe in the same craniotomy hole used for virus injection. One to 2 weeks after cannula implantation, freely behaving mice were subjected to in vivo photoconversion. We found that, with low UV light power (~0.20 mW), 30 min of UV illumination was sufficient to cause robust photoconversion. Due to the light-scattering properties of brain tissue, light intensity attenuates with increasing distance from the source, especially at shorter wavelengths (Al-Juboori et al., 2013Al-Juboori S.I. Dondzillo A. Stubblefield E.A. Felsen G. Lei T.C. Klug A. Light Scattering Properties Vary across Different Regions of the Adult Mouse Brain.Plos One. 2013; 8: e676269Crossref Scopus (83) Google Scholar). We found that the average red/green CaMPARI2 photoconversion ratio was quite constant within approximately 200 μm of the center of the exposed section of the fiberoptic probe (Figures 1A and S1), so all subsequent experiments were performed on neurons within this distance. To further control for differences in light intensity, all recordings following in vivo photoconversion were performed from pairs of nearby neurons, and statistical comparisons were made within these pairs. To verify that neurons with a higher red/green CaMPARI2 ratio after in vivo photoconversion represent neurons with greater average activity, we wanted to compare this ratio to an established in vivo marker of neuronal activity. Labeling with IEGs such as cFos is a common approach for identifying neurons that have recently undergone activity-dependent gene transcription (Barth et al., 2004Barth A.L. Gerkin R.C. Dean K.L. Alteration of neuronal firing properties after in vivo experience in a FosGFP transgenic mouse.J. Neurosci. 2004; 24: 6466-6475Crossref PubMed Scopus (173) Google Scholar; Sagar et al., 1988Sagar S.M. Sharp F.R. Curran T. Expression of c-fos protein in brain: metabolic mapping at the cellular level.Science. 1988; 240: 1328-1331Crossref PubMed Scopus (1753) Google Scholar; Yap and Greenberg, 2018Yap E.-L. Greenberg M.E. Activity-Regulated Transcription: Bridging the Gap between Neural Activity and Behavior.Neuron. 2018; 100: 330-348Abstract Full Text Full Text PDF PubMed Scopus (183) Google Scholar), although the precise relationship between neuronal activity and cFos expression is often nonlinear (Tyssowski and Gray, 2019Tyssowski K.M. Gray J.M. The neuronal stimulation-transcription coupling map.Curr. Opin. Neurobiol. 2019; 59: 87-94Crossref PubMed Scopus (11) Google Scholar). Recent work in rodent V1 revealed that 60 h of dark exposure followed by 1 h of light re-exposure drives an elevation in firing and robust expression of cFos (Torrado Pacheco et al., 2019Torrado Pacheco A. Tilden E.I. Grutzner S.M. Lane B.J. Wu Y. Hengen K.B. Gjorgjieva J. Turrigiano G.G. Rapid and active stabilization of visual cortical firing rates across light-dark transitions.Proc. Natl. Acad. Sci. USA. 2019; 116: 18068-18077Crossref PubMed Scopus (9) Google Scholar). Therefore, we subjected mice to this protocol while photoconverting CaMPARI2 during the first 30 min of light re-exposure, when firing is elevated (Torrado Pacheco et al., 2019Torrado Pacheco A. Tilden E.I. Grutzner S.M. Lane B.J. Wu Y. Hengen K.B. Gjorgjieva J. Turrigiano G.G. Rapid and active stabilization of visual cortical firing rates across light-dark transitions.Proc. Natl. Acad. Sci. USA. 2019; 116: 18068-18077Crossref PubMed Scopus (9) Google Scholar). In mice housed on a normal 12/12 light/dark cycle, we saw only a weak correlation between cFos protein levels and CaMPARI2 photoconversion (r = 0.23, Figure 1B), but after light re-exposure the correlation between these two activity markers was robust (r = 0.65, Figures 1C and 1D). Our primary motivation for using CaMPARI2 to label neurons based on their in vivo activity was to be able to subsequently interrogate electrophysiological differences between high- and low-activity neurons. Therefore, it was essential to determine whether neurons with different firing rates in vivo retained these properties in acute slices. To this end, we photoconverted CaMPARI2 in vivo as above and then prepared acute slices from V1m and obtained cell-attached recordings from pyramidal neurons across all layers in active artifical cerebrospinal fluid (ACSF) (Maffei et al., 2004Maffei A. Nelson S.B. Turrigiano G.G. Selective reconfiguration of layer 4 visual cortical circuitry by visual deprivation.Nat. Neurosci. 2004; 7: 1353-1359Crossref PubMed Scopus (312) Google Scholar) to measure spontaneous firing rates (Figures 2A–2C). We found that the distribution of firing rates ex vivo was lognormal and very similar to the distribution observed from chronic in vivo recordings that spanned all layers (Figure 2D, data from Hengen et al., 2016Hengen K.B. Torrado Pacheco A. McGregor J.N. Van Hooser S.D. Turrigiano G.G. Neuronal Firing Rate Homeostasis Is Inhibited by Sleep and Promoted by Wake.Cell. 2016; 165: 180-191Abstract Full Text Full Text PDF PubMed Scopus (151) Google Scholar were used to generate the in vivo plot). The distribution of red/green ratios was also lognormal, though over a narrower range than the firing rate distribution (Figure 2E). To verify that neurons with high in vivo photoconversion have higher firing rates ex vivo than low photoconversion neurons, we recorded from pairs of nearby neurons with different red/green ratios; in almost all cases, the higher red/green ratio neuron (indicating greater in vivo activity) had a higher ex vivo firing rate (Figures 2F and S2A). Conversely, when neurons within each pair were sorted by ex vivo firing rate, higher firing rate neurons had a higher red/green ratio (Figures S2B and S2C). Further, the magnitude of differences in firing rate and red/green ratio within each pair were positively correlated (Figure 2G). Thus, many of the factors that cause a neuron to have a high or low firing rate in vivo are preserved in the active acute slice preparation. We next sought to directly confirm that CaMPARI2 photoconversion rate is well correlated with firing rate. To test this, we devised an ex vivo photoconversion protocol in active acute slices (Figures 3A and 3B ; see STAR methods for details). This approach has the advantage that illumination is uniform in the X-Y plane, so we are not limited to comparing pairs of nearby neurons and thus can directly compare several neurons from a given slice. As above, we used cell-attached recordings to record the spontaneous firing of individual or pairs of neurons during photoconversion and measured the red/green ratio of these neurons every 5 min. We found that over a 30-min period, the number of action potentials was well correlated with the change in red/green ratio (Figure 3C), demonstrating that CaMPARI2 red/green ratio can be used to differentiate neurons based on their mean activity over the long timescales needed to estimate mean firing rate. To determine if differences in CaMPARI2 expression levels influence neuronal firing rates (through calcium buffering or other mechanisms) or photoconversion ratios, we examined the relationship between total CaMPARI2 fluorescence and spontaneous firing or photoconversion. We found no correlation between CaMPARI2 expression and firing rate (Figure S2D) or between CaMPARI2 expression and photoconversion (Figures S2E and S3A). Notably, Fano factor, a measurement of variability in spike timing and therefore “burstiness” (Eden and Kramer, 2010Eden U.T. Kramer M.A. Drawing inferences from Fano factor calculations.J. Neurosci. Methods. 2010; 190: 149-152Crossref PubMed Scopus (45) Google Scholar; Shadlen and Newsome, 1998Shadlen M.N. Newsome W.T. The variable discharge of cortical neurons: implications for connectivity, computation, and information coding.J. Neurosci. 1998; 18: 3870-3896Crossref PubMed Google Scholar), was not correlated with the change in red/green ratio, suggesting that the pattern of firing is a less important for photoconversion than the number of spikes (Figure S3B). Thirty minutes of UV exposure at levels sufficient for photoconversion did not influence mean spontaneous neuronal activity rates (Figure S3C), suggesting this paradigm does not cause significant photodamage. As a final confirmation that greater photoconversion is correlated with higher firing rates, we compared the activity of pairs of simultaneously recorded neurons during ex vivo photoconversion for 10 min. In each case, the neuron with a higher red/green ratio was the one with a greater mean firing rate in the previous 10 min (Figure 3D). The converse was true as well, as neurons with a greater mean firing rate always had a higher red/green ratio (Figure S3D). As with the 30-min photoconversion experiments described above, we found that neurons with high and low red/green ratios did not have different Fano factors (Figure 3E), and that mean firing rate was not significantly affected by CaMPARI2 expression levels (Figure S3E). Together, these data demonstrate that CaMPARI2 red/green ratio can be used to reliably differentiate neurons with different mean activity levels. It is well established that brief (3 day) monocular deprivation (MD) via monocular lid suture during the classic visual system critical period (roughly postnatal days 21–33) induces a drop in activity in the monocular portion of primary visual cortex relative to the unmanipulated hemisphere (Gordon and Stryker, 1996Gordon J.A. Stryker M.P. Experience-dependent plasticity of binocular responses in the primary visual cortex of the mouse.J. Neurosci. 1996; 16: 3274-3286Crossref PubMed Google Scholar; Mrsic-Flogel et al., 2007Mrsic-Flogel T.D. Hofer S.B. Ohki K. Reid R.C. Bonhoeffer T. Hübener M. Homeostatic Regulation of Eye-Specific Responses in Visual Cortex during Ocular Dominance Plasticity.Neuron. 2007; 54: 961-972Abstract Full Text Full Text PDF PubMed Scopus (247) Google Scholar). Further, activity is gradually homeostatically restored if MD is continued, so that by 6 days of MD activity in the deprived and control hemispheres are indistinguishable (Hengen et al., 2013Hengen K.B. Lambo M.E. Hooser S.D.V. Katz D.B. Turrigiano G.G. Firing Rate Homeostasis in Visual Cortex of Freely Behaving Rodents.Neuron. 2013; 80: 335-342Abstract Full Text Full Text PDF PubMed Scopus (183) Google Scholar, Hengen et al., 2016Hengen K.B. Torrado Pacheco A. McGregor J.N. Van Hooser S.D. Turrigiano G.G. Neuronal Firing Rate Homeostasis Is Inhibited by Sleep and Promoted by Wake.Cell. 2016; 165: 180-191Abstract Full Text Full Text PDF PubMed Scopus (151) Google Scholar; Tatavarty et al., 2020Tatavarty V. Torrado Pacheco A. Kuhnle C.G. Lin H. Koundinya P. Miska N.J. Hengen K.B. Wagner F.F. Hooser S.D.V. Turrigiano G.G. Autism-Associated Shank3 Is Essential for Homeostatic Compensation in Rodent V1.Neuron. 2020; 106: 769-777Abstract Full Text Full Text PDF PubMed Scopus (38) Google Scholar). To determine whether CaMPARI2 is sensitive enough to detect this drop and restoration of activity, we labeled L4 pyramidal neurons using a Cre-dependent pan-neuronal CaMPARI2 virus in Scnn1a-Cre mice, in which Cre expression is restricted to L4 excitatory neurons (Madisen et al., 2010Madisen L. Zwingman T.A. Sunkin S.M. Oh S.W. Zariwala H.A. Gu H. Ng L.L. Palmiter R.D. Hawrylycz M.J. Jones A.R. et al.A robust and high-throughput Cre reporting and characterization system for the whole mouse brain.Nat. Neurosci. 2010; 13: 133-140Crossref PubMed Scopus (3579) Google Scholar; Miska et al., 2018Miska N.J. Richter L.M. Cary B.A. Gjorgjieva J. Turrigiano G.G. Sensory experience inversely regulates feedforward and feedback excitation-inhibition ratio in rodent visual cortex.eLife. 2018; 7: 39Crossref Scopus (28) Google Scholar). We chose to restrict this analysis to L4 pyramidal neurons because they are considered a single transcriptional cell type (Tasic et al., 2018Tasic B. Yao Z. Graybuck L.T. Smith K.A. Nguyen T.N. Bertagnolli D. Goldy J. Garren E. Economo M.N. Viswanathan S. et al.Shared and distinct transcriptomic cell types across neocortical areas.Nature. 2018; 563: 1-41Crossref Scopus (562) Google Scholar), and below we characterize this cell type in more detail. Following 3 or 6 days of MD, we used our ex vivo photoconversion paradigm to permanently label neurons from both hemispheres of monocular V1 based on their activity and then quantified the red/green ratio (Figure 4A); we normalized the red/green ratio to the total fluorescence for each cell to minimize any effect of different expression levels between hemispheres. With this approach, we were able to sample a large number of identified neurons (>480) in each condition. After 3 days of MD, there was a significant reduction in the red/green ratio in the deprived population relative to the control population (Figures 4B and 4C). The magnitude of the drop (median deprived value was 72% of control) was similar" @default.
• W3110842501 created "2020-12-21" @default.
• W3110842501 creator A5013330823 @default.
• W3110842501 creator A5063639195 @default.
• W3110842501 creator A5072749446 @default.
• W3110842501 date "2021-02-01" @default.
• W3110842501 modified "2023-10-15" @default.
• W3110842501 title "Activity labeling in vivo using CaMPARI2 reveals intrinsic and synaptic differences between neurons with high and low firing rate set points" @default.
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