A positively tuned voltage indicator for extended electrical recordings in the brain.

Plasmid Construction. For transfection into HEK293-Kir2.1 Cells for electrical screening, the parent ASAP2f L146G S147T R414Q was subcloned into pcDNA3.1 with a CMV enhancer and promoter and bGH poly(A) signal. All plasmids were made by standard molecular biology techniques with all cloned fragments confirmed by sequencing (Sequetech). PCR reactions were carried out to generate PCR product libraries using standard PCR techniques, which were used to directly transfect HEK293-Kir2.1 cells with the linear product using lipofectamine 3000 (Thermo Fisher Scientific). For patch clamp characterization in HEK293A cells, all voltage indicators were subcloned into a pcDNA3.1/Puro- CAG vector between NheI and HindIII sites 20 . For in vitro characterization in cultured neurons, acute hippocampal slice and in vivo hippocampal imaging, ASAP variants were subcloned into pAAV.hSyn.WPRE. These were then midi-prepped and packaged into adeno-associated virus 8 (AAV8) by the Neuroscience Gene Vector and Virus Core of Stanford University. For somatic targeting in acute slice and in vivo, the C-terminus of ASAP4 variants was attached to the C-terminal cytoplasmic segment of the Kv2.1 potassium channel 27 , that we previously used to restrict ASAP3 to the soma, axon and proximal dendrites 6 . For EF1α-driven ASAP expression, viral constructs were generated by modifying published methods 39 using GateWay recombination and Gibson assembly, and produced in-house as previously described 6 , 40 . These were then packaged into AAV8 capsids by the Neuroscience Gene Vector and Virus Core at Stanford University. For quantification of membrane trafficking, ASAP variants (ASAP3 or ASAP4b or ASAP4e), internal ribosome-entry site (IRES), and Crimson-CAAX 26 were assembled into Lenti-DIO-EF1α backbone vector (Addgene #170327) between AscI and NheI sites using HiFi DNA Assembly Master Mix (New England Biolabs). All constructs were confirmed by whole plasmid sequencing (Primordium labs). Cultured Cell Lines. All cell lines were maintained in a humidified incubator at 37°C with 5% CO 2 . For electrical screening the previously described HEK293-Kir2.1 cell line 41 was maintained in high-glucose DMEM (Thermo Fisher Scientific), 5% fetal-bovine serum (FBS; Gemini bio), 2 mM L-glutamine (Gemini bio), and 500 μg/mL geneticin (Thermo Fisher Scientific). For patch-clamp recordings to measure ASAP responsivity and kinetics, HEK293A cells were cultured in high-glucose DMEM with 5% FBS and 2 mM L-glutamine. Cultured Neurons. Hippocampal neurons were isolated from embryonic day 18 Sprague Dawley rat embryos of both sexes. Procedures were carried out in compliance with the rules of the Stanford University Administrative Panel on Laboratory Animal Care. Viruses. AAV9-CamKII-Cre was obtained from the Penn Vector Core. AAV1-Syn-NES-jRGECO1a, ≥1x10 11 vg/mL, Addgene #100854, and AAV1-syn-NES-jRGECO1b-WPRE-SV40, AddGene #100857, were ordered from Addgene. All ASAP viruses were produced by the Stanford Neuroscience Gene Vector and Virus Core facility, and by the lab of Sui Wang at Stanford University. For the acute slice brightness comparisons, viruses were diluted in phosphate-buffered saline (PBS) until the following titers were reached: AAV9-CamKII-cre at a titer of 5.6x10 9 vg/mL, and all three ASAP viruses at a titer of 3.45x10 11 vg/mL. For the two-photon imaging while patch clamping evoked spikes in hippocampal slice work, AAV8-syn-ASAP3/4b-Kv was injected at a titer between 1.21x10 12 and 5x10 12 vg/mL, and AAV1-syn-jrGECO1b was injected at a titer between 1.3x10 12 and 5x10 12 vg/mL, but we were not able to image the jRGECO1b well, so it was excluded from the analysis. For the one-photon imaging of patch clamping in hippocampal slice and evoking spikes, AAV8-syn-ASAP4b-Kv and AAV8-syn-ASAP3-Kv were injected at titers approximately between 1x10 12 and 1x10 13 vg/mL. For the in vivo two-photon imaging of ASAP4e and jRGECO1a in V1, AAV8-Syn-ASAP4e-Kv at a titer of 4.66x10 11 vg/mL was co-injected with AAV1-Syn-NES-jRGECO1a at a titer of approximately 1x10 11 vg/mL. For the in vivo one-photon imaging of hippocampus during running, either AAV8-ef1α -DiO-ASAP3-Kv at a titer of 2.35x10 12 vg/mL, AAV8-ef1α -DiO-ASAP4b-Kv at a titer of 2.36x10 12 vg/mL, or AAV8-ef1α -DiO-ASAP4e-Kv at a titer of 3.45x10 11 vg/mL was injected. For the in vivo two-photon imaging of the hippocampus during a spatial navigation task, AAV8-syn-ASAP4b-Kv at a titer of 1.17×10 12 vg/mL was co-injected with AAV1-syn-NES-jRGECO1b-WPRE-SV40 at a titer of 1.3x10 13 . Lentiviruses were produced for the membrane trafficking quantification experiment by a previously described method 42 . Briefly, low-passage-number HEK293T cells (ATCC CRL-3216) were plated onto 15-cm dishes (Corning TCA-430599) in DMEM (Gibco 31-053-036) supplemented with 10% FBS, 2 mM L-Glutamine and 1% Penicillin/Streptomycin (DMEM10). When HEK293T cells reached 80% confluency, the medium was exchanged to a serum-free DMEM. After 1h, the cells were transfected using polyethylenimine (PEI; Polysciences 23966) with 15.5 μg of the vector plasmid (pLenti-DIO-EF1α-ASAPx-IRES-Crimson-CAAX), 10 μg of the second-generation packaging plasmid psPAX2 (Addgene #12260), and 4.5 μg of viral entry protein VSV-G plasmid pMD2.G (Addgene #12259). The three plasmid DNAs were mixed into 1.35 mL of serum-free DMEM and 40 μL of 1 mg/mL PEI was added at the end. The mixture was incubated at room temperature for 10 min and added dropwise to the culture. After 4 h, the medium was exchanged back to 18 mL of DMEM10. The supernatant was harvested at 36 h post-transfection and kept at 4 °C. Then, 18 ml of DMEM10 was added to the cells and incubated for another 24 h. At 60 h post-transfection, the supernatant was harvested again and combined with the first batch of supernatant, centrifuged for 5 min at 1500 g, and filtered through a 0.45-μm syringe filter (EMD Millipore SLHVR33RB). Next, 12 mL Lenti-X concentrator (Takara Bio #631232) was added to the supernatant and incubated in 4 °C for 1 h. Viruses were centrifuged for 45 min at 1500 g and dissolved in PBS. Titer of the lentiviruses were measured with Lenti-X GoStix (Clontech #631244) kit after 1:100 dilution. The viral particles were aliquoted, and stored at −80 °C for neuronal transduction. Animals. For the one-photon acute slice brightness comparisons, two-photon acute slice patch clamping experiments and in two-photon in vivo imaging experiments, adult male and female wild-type C57BL/6 were used. All mice were housed in standard conditions (up to five animals per cage, 12-hour light/dark cycles with the light on at 7 a.m., with water and food ad libitum). Day-18 Sprague Dawley rat embryos were used for hippocampal tissue for neuronal culture. All protocols were approved by the Stanford Institutional Animal Use and Care Committee. For the in vivo fly imaging, ASAP4b was cloned into the pJFRC7-20XUAS vector 43 using standard molecular cloning methods (GenScript Biotech), and then inserted into the attP40 phiC31 landing site by injection of fertilized embryos (BestGene). We used the cell type-specific driver 21D-GAL4 44 to express ASAP2f and ASAP4b in L2 cells. We imaged the axon terminals of L2 cells in its medulla layer M2 arbors. The genotypes of the imaged flies in Extended Data Fig. 6 were: L2>>ASAP2f: +; UAS-ASAP2f/+; 21D-Gal4/+. L2>>ASAP4b: yw/+; UAS-ASAP4b/+; 21D-GAL4/+. In vivo one-photon imaging experiments were conducted at the University of California at Los Angeles (UCLA), where adult (11–23 week old) SST-IRES-cre knock-in adult male and female mice were used for all experiments. All animals were group housed (2–5 per cage) on a 12 h light/dark cycle. All experimental protocols were approved by the Chancellor’s Animal Research Committee of UCLA in accordance with NIH guidelines. Animals used in acute slice one-photon patch clamping experiments were male and female wild-type mice aged 20–40 days. All mice used were maintained on a 12-h light/dark cycle, with food and water available ad libitum and in accordance with the Institutional Animal Care and Use Committee of Columbia University. For the co-imaging of ASAP4e and jRGECO1a in V1, all animal experiments were conducted according to the National Institutes of Health guidelines for animal research. Procedures and protocols on mice were approved by the Animal Care and Use Committee at the University of California, Berkeley. Cell screening. HEK293-Kir2.1 cells were plated in 384-well plates (Grace Bio-Labs) on conductive glass slides (Sigma-Aldrich). Cells were transfected with PCR-generated libraries in 384-well plates with Lipofectamine 3000 (~100 ng DNA, 0.4 μL p3000 reagent, 0.4 μL Lipofectamine) followed by a media change 4–5 hours later, with imaging done 2 days post-transfection in Hank’s Balanced Salt solution (HBSS; Cytiva) buffered with 10 mM HEPES (Thermo Fisher Scientific). Cells were imaged at room temperature on an IX81 inverted microscope fitted with a 20× 0.75-numerical aperture (NA) objective (Olympus). A 120-W Mercury vapor short arc lamp (X-Cite 120PC, Exfo) served as the excitation light source. The filter cube set consisted of a 480/40-nm excitation filter and a 503-nm long pass emission filter. ASAP libraries were screened at room temperature with the operator locating the best field of view and focusing on the cells. A single field of view was imaged for a total of 5 s, with a 10-μs 150-V electroporating square pulse applied near the 3-s mark as previously described 6 . Fluorescence was recorded at 100 Hz (10-ms exposure per frame) by an ORCA Flash4.0 V2 CMOS camera (Hamamatsu C11440 –22CA) with pixel binning set to 4×4. Mutants were screened at least three times. Whole cell patch clamping and imaging of HEK293A cells. Patch-clamp experiments were mainly done as previously described 6 . Cells were transfected with pcDNA3.1/Puro-CAG-based plasmids expressing each GEVI using Lipofectamine 3000 (400 ng DNA, 0.8 μL P3000 reagent, 0.8 μL Lipofectamine) per manufacturer’s recommended instructions. After plating the cells on 12 mm glass coverslips (Carolina Biological), the cells were patch clamped 24 hours after transfection. Signals were recorded in voltage-clamp mode with a Multiclamp 700B amplifier and using pClamp software (Molecular Devices). Fluorophores were illuminated at ~4.3 mW/mm 2 power density at the sample plane with a blue LED (Prizmatix UHP-Mic-LED-460) passed through a 484/15-nm excitation filter and focused on the sample through a 40× 1.3-NA oil-immersion objective (Zeiss). Emitted fluorescence passed through a 525/50-nm emission filter and was captured by an iXon 860 electron-multiplied charge-coupled device camera (Oxford Instruments) cooled to −80 °C. For all experiments fluorescence traces were corrected for photobleaching by dividing the recorded signal by a mono-exponential fit to the data. To characterize steady-state fluorescence responses, cells were voltage-clamped at a holding potential of −70 mV, then voltage steps of 1 s duration were imposed at −120, −100, −80, −60, −40, −20, 0, 30, 50, 70, 90, and 120mV. To obtain complete fluorescence–voltage (F–V) curves, the above steps plus additional ones at −200, −180, −160, −140, and 120mV were imposed. When voltage-clamp could not be imposed on some cells at the highest potentials, that step was excluded from data analysis. A scaled action potential waveform (FWHM 3.5 ms, −70mV to +30mV) recorded from a cultured hippocampal neuron was included before each step to estimate the fluorescence change of the indicators to action potential waveform. To estimate per-molecule brightness, we assume the chromophore with the cpGFP domain of each ASAP variant has similar molar brightness in its deprotonated 490 nm-absorbing state. This assumption is based on the observation GCaMP GECIs, which have the same chromophore, show similar per-molecule brightness to EGFP upon 490-nm excitation when fully calcium-saturated and deprotonated 34 , despite the cpGFP domain of GcaMPs presenting a different environment around the group ring than the EGFP domain. That is, the identical chromophores in cpGFP and EGFP exhibit similar brightness when deprotonated, despite different chromophore environments near the phenotpye group, and thus we assume the deprotonated states of ASAP variants will be similarly bright to each other. A relative measure of population brightness at rest for equivalent numbers of molecules expressed ( mF 0 ) is then given by F −70 / F max , the brightness at −70mV relative to maximum fluorescence across all voltages. We obtained F-V readings across a wide-enough V range to obtain asymptotic maximum F values. To characterize kinetics of ASAP indicators at both room temperature and 37 °C, images were acquired at 2.5 kHz from an area cropped down to 64×64 pixels and further binned to comprise only 8×8 pixels. Fluorescence was quantified by averaging pixels with signal change in the corresponding cell shape after subtracting by the background pixels. Command voltage steps were applied for 1 s, and a double exponential or single exponential fit was applied to a 60-ms interval from the starting point of the onset and offset of voltage steps using MATLAB software (MathWorks). To characterize GEVIs on simulated AP burst waveforms (2 and 4 ms at FWHM) at room temperature, images were acquired at 1000 Hz from a 64×64-pixel FOV, then binned using 4×4 pixel binning. To characterize ASAP variants on square pulses (1, 2, and 4 ms, −70mV to +30mV) and AP burst waveforms (FWHM 1.0 ms) at 37 °C, images were acquired at 2500 Hz from a 64×64-pixel FOV, then 8×8 binning was applied. One-photon excitation and emission spectra measurements. HEK293-Kir2.1 cells were cultured as described above until 70–80% confluency, then transfected using Lipofectamine 3000 (Thermo Fisher) with pCAG-ASAP4.2-F413S construct. Two days post-transfection, approximately 1×10 5 cells were replated in a 96-well plate in PBS. The excitation spectra from 300 to 530 nm, upon emission at 550 nm with a bandwidth of 10 nm, and the emission spectra from 500 to 850 nm, upon excitation at 480 nm with a bandwidth of 10 nm were obtained in an Infinite M1000 Pro microplate reader (Tecan). Spectra were averaged over 4 wells and normalized to its peak value. Primary neuronal culture and transfection. Hippocampal neurons were isolated from embryonic day 18 (E18) Sprague Dawley (SD) rat embryos by dissociating them in RPMI medium containing 5 units/mL papain (Worthington Biochemical) and 0.005% DNase I at 37 °C and 5% CO2 in air. Neurons were plated on washed 12-mm No.1 glass coverslips pre-coated overnight with > 300-kDa poly-D-lysine hydrobromide (Sigma-Aldrich). Cells were plated for several hours in Neurobasal media with 10% FBS (Gemini bio), 2 mM GlutaMAX (Thermo Fisher Scientific), and B27 supplement (Thermo Fisher Scientific), then the media was replaced with Neurobasal with 1% FBS, 2 mM GlutaMAX, and B27. Half of the media was replaced every 3–4 days with fresh media without FBS. 5-Fluoro-2’-deoxyuridine (Sigma-Aldrich) was typically added at a final concentration of 16 μM at 7–9 DIV to limit glial growth. Hippocampal neurons were transfected at 9–11 DIV with 500 ng total DNA including 100–300 ng of indicator DNA and 1 μL Lipofectamine 2000 (Thermo Fisher Scientific) in 200 μL Neurobasal with 2 mM GlutaMax. Cortical neurons from E18 rat embryos were dissected as previously described 6 . Briefly, 1×10 5 dissociated rat cortical neurons were plated in each well of 24-well glass bottom plates (Cellvis; P24-1.5H-N) that was coated with >300-kDa poly-D-lysine hydrobromide (Sigma-Aldrich #P1024). The cells were incubated for 1-day in Neurobasal media with 10% FBS, 2 mM GlutaMAX, and B27 supplement (Thermo Fisher Scientific), then the media were replaced with the same media but with 1% FBS. A half of the media was then replaced every 3 days with fresh Neurobasal media without FBS. 5-Fluoro-2’-deoxyuridine (Sigma-Aldrich #F0503) was typically added at a final concentration of 16 mM at DIV 4 to limit excessive non-neuronal cell growth. On DIV 7, the cortical neurons were infected with Lenti-DIO-EF1α-ASAPx-IRES-Crimson-CAAX virus, and then transfected with pCAG-iCre (Addgene #89573) plasmid on DIV 8, using Lipofectamine 2000 (Thermo Fisher Scientific). High resolution cultured hippocampal neuron imaging. Cultured hippocampal neurons were transfected at 9–11 DIV via Lipofectamine 3000 (Thermo Fisher Scientific) with pAAV-hSyn-ASAPx-WPRE and pAAV-hSyn-Ace2-D92N-E199V-mNeon-ST-WPRE (upward Ace2N-mNeon) variants. Cells were imaged at 12–20 DIV on an inverted confocal microscope (Zeiss Axiovert 200M) with a 40× 1.2-NA objective (Zeiss). ASAPs and upward Ace2N-mNeon were excited by a 120-W Mercury vapor short arc lamp (X-Cite 120PC, Exfo) set to 12% maximum output and passed through a 488/30-nm filters, and fluorescence was collected via 531/40-nm filters. Images were taken using an ORCA Flash4.0 V2 C11440-22CA CMOS camera (Hamamatsu) with Micro-manager software. Exposure time was 1 s per frame, with frames collected as 2048×2048 16-bit images. One-photon photobleaching in HEK293-Kir2.1 cells. HEK293-Kir2.1 cells were plated and cultured on a 60-mm culture dish (CellTreat) by using the same culture condition described above. At approximately 80% confluency, the cells in each dish were transfected with 4 μg of plasmid expressing ASAP3, ASAP4b, ASAP4e, or ncpASAP4b from a CMV promoter, and Lipofectamine 3000 per manufacturer protocols (8 μL of P3000 and 8 μL Lipofectamine in OptiMEM, all from Thermo Fisher Scientific). One day after transfection, cells were dissociated with 0.25% trypsin 0.53 mM EDTA solution (Gemini Bio) and replated onto 29mm-diameter glass-bottom dishes with a 20 mm-diameter #1.5 cover glass (CellVis). The next day, the media was replaced to HBSS containing 10 mM HEPES (Thermo Fisher Scientific). The transfected cells were then imaged under an Axiovert 200M microscope (Zeiss) using a 40× 1.2-NA water-immersion objective (Zeiss C-Apochromat). Illumination was provided with a 453-nm LED via a liquid light guide (Prizmatix UHP-F-3-455 and LLG-3) and filtered through a green fluorescence filter set (Zeiss BP 450-490, FT 510, BP 515-565). By controlling the LED’s current level and by using a neutral density filter with optical density of 1 (10% transmittance), five different excitation power levels could be used for the photobleaching experiments. Emission was then acquired with a Flash 4.0LT+ CMOS camera (Hamamatsu C11440 ) at a framerate of 5 fps for 5 min of continuous illumination. The camera was controlled by μManager 45 and images saved as TIFF stacks. The TIFF stacks were analyzed in NIH Fiji 46 by manually selecting cellular ROIs as well as a dark background ROI for each FOV and measuring mean intensities. Background-substrated intensities were calculated and normalized to the initial value in Excel (Microsoft). Two-photon photobleaching and excitation spectra measurements in HEK293-Kir2.1 cells. HEK293-Kir2.1 cells were cultured as described above and then plated on 12-mm diameter coverslips (0.13–0.17 mm thickness, Carolina Biological) coated with poly-D-lysine (MP Biomedicals). The cells were transiently transfected at 60–80% confluency with 200–300 ng of expression plasmid expressing GEVIs from a CMV promoter and Lipofectamine 3000 per manufacturer protocols (0.8 μL of P3000 and 0.8 μL Lipofectamine in OptiMEM). The transfected cells were imaged 1–3 days post-transfection. During imaging, cells were bathed in HBSS supplemented with 10 mM HEPES. For experiments without recovery, cells were imaged using resonant galvonometer scanning (8-kHz line scan rate) on a Bruker Ultima system with a 20× 1.0 NA water immersion objective (Leica). The excitation laser (Spectra-Physics) was tuned to 920 nm, and signals were collected by a GaAsP-type photomultiplier tubes after a 525/50-nm filter, with a frame rate of 75 Hz. The resolution was 800×200 pixels with 0.65 μm spacing. For experiments with recovery, custom-built two-photon microscope system using a tunable two-photon laser (Spectra-Physics InSight X3) was modulated with a Pockel’s cell (Conoptics 350-80). The laser was directed with a 12.0-kHz resonant scanner 47 and focused through a 40× 0.8-NA objective (Nikon). Cells were imaged under 930-nm light for ASAP4b and ASAP4e, or 940-nm light for ASAP3 and ncpASAP4b. Data were collected by a photomultiplier tube (Hamamatsu H10770PA-40), after being filtered for green light (Chroma ET525/50M). Membrane trafficking quantification in cultured rat neurons. Cortical neurons transduced with relevant Lentivirus as described above were imaged at DIV 15 (7 days after iCre transfection) in imaging solution (HBSS with 2 mM GlutaMAX, 1 mM sodium pyruvate, and 10 mM HEPES pH 7.4). As a membrane-localized reference channel, Crimson RFP 26 with a C-terminal farnesylation motif (CAAX) for membrane targeting was co-expressed with an ASAP variant via IRES. The epifluorescence from the cells were imaged on an Axiovert 200M inverted microscope with a 40x 1.2-NA water-immersion objective (Zeiss) and an X-Cite 120 metal-halide lamp (Exfo) as the excitation light source. For ASAP, excitation and emission filters were BP450-490 and BP515-565 (Zeiss). For Crimson, excitation and emission filters were HQ535/50m and HQ625/60m (Chroma). For each cell, 15 focal planes spaced 1 μm apart were captured by a Flash4.0LT+ camera using μManager. To quantify membrane localization, a custom-written MATLAB (MathWorks) code was used. Membrane masks of the neurons were generated by applying the graythresh function on Sobel-filtered red channel images. The soma masks were manually selected using the roipoly function on red channel images. Then the two masks were applied to background-subtracted green channel images to obtain the membrane fluorescence and the soma fluorescence of the ASAP reporter. The total fluorescence is the sum of the two. Two-photon in vivo imaging of Drosophila . Flies were mounted, dissected to expose the brain, perfused with a saline-sugar solution, and imaged for up to 1 h, as previously described 12 , 48 . Neurons were excited at 920 nm with 5–15 mW of total power, and photons were collected with a 525/50-nm filter. Data was collected at 82.4 frames per s with 200×20-pixel frames using a 15× digital zoom, using bidirectional scanning. We used a Leica TCS SP5 II two-photon microscope with a Leica HCX APO 20× 1.0-NA water immersion objective (Leica) and a pre-compensated Chameleon Vision II femtosecond laser (Coherent, Inc.). Visual stimuli were generated with custom-written software using MATLAB (MathWorks) and presented using the blue LED of a DLP Lightcrafter 4500 (Texas Instruments) projector in Pattern Sequence mode. The stimulus was refreshed at 300 Hz and utilized 6 bits/pixel, allowing for 64 distinct luminance values. The stimulus was projected onto a 9×9-cm rear-projection screen positioned approximately 8 cm anterior to the fly that spanned approximately 70° of the fly’s visual field horizontally and 40° vertically. A small square was also simultaneously projected onto a photodiode (Thorlabs, SM05PD1A) configured in a reversed-biased circuit. The stimulus was filtered with a 482/18-nm bandpass filter so that it could not be detected by the microscope PMTs. The radiance at 482 nm was approximately 78 mW sr −1 m −2 . The Imaging and the visual stimulus presentation were synchronized using triggering functions provided by the LAS AF Live Data Mode software (Leica) as well as the signal from the photodiode directly capturing projector output. A Data Acquisition Device (NI DAQ USB-6211, National Instruments) connected to the computer used for stimulus generation was used to acquire the photodiode signal, generate a trigger signal at the beginning of stimulus presentation, and acquire the trigger produced by the LAS software at the start of each imaging frame. This allowed the imaging and the stimulus presentation to initialize in a coordinated manner and ensured that stimulus presentation details were saved together with imaging frame timings (in MATLAB .mat files) to be used in subsequent processing. Data was acquired on the DAQ at 5000 Hz. The visual stimuli used were 300-ms search stimuli: alternating full contrast light and dark flashes, each 300 ms in duration, were presented at the center of the otherwise dark screen. The stimulus was such that from the perspective of the fly, the flashing region was 8° from each edge of the screen. In subsequent analysis, the responses to this stimulus were used to select ROIs with receptive fields located at the center of the screen instead of at the edges. This stimulus was presented for 5000 imaging frames (61 s) per field of view. Single 20-ms light and dark flashes, with 500-ms of gray between the flashes, were presented over the entire screen. The light and dark flashes were randomly chosen at each presentation. The Weber contrast of the flashes relative to the gray was 1. This stimulus was presented for 10,000 imaging frames (122 s) per field of view. The acquired time series was saved as .lif files and read into MATLAB using Bio-Formats (Open Microscopy Environment). Each time series was aligned in x and y coordinates by maximizing the cross-correlation in Fourier space of each image with a reference image (the average of the first 30 images in the time series). For each time series, ROIs around individual arbors were selected by thresholding the series-averaged image with a value that generates appropriate ROIs, and then splitting any thresholded ROIs consisting of merged cells and/or adding ROIs that were missed by the thresholding. The fluorescence response for each time series was calculated after subtracting the background intensity and correcting for bleaching as previously described 12 , 48 . Time series with uncorrected movement, which was apparent as irregular spikes or steps in the Δ F / F traces that were coordinated across ROIs, were discarded. The stimulus-locked average response was computed for each ROI by reassigning the timing of each imaging frame to be relative to the stimulus transitions (gray to light or gray to dark) and then computing a simple moving average. The averaging window was 8.33 ms and the shift was 8.33 ms, which effectively resampled our data from 82.4 to 120 fps. As the screen on which the stimulus was presented did not span the fly’s entire visual field, only a subset of imaged ROIs experienced the stimulus across approximately the entire extent of their spatial receptive fields. These ROIs were identified based on having a response of the appropriate sign to the 300-ms search stimulus. ROIs lacking a response to these stimuli or having one of the opposite sign were not considered further. The peak response to each flash (peak Δ F / F ) was the Δ F / F value farthest from zero in the expected direction of the initial response (depolarization or hyperpolarization). The time to peak (t peak ) was the time at which this peak response occurred, relative to the start of the light or dark flash. Pairwise Student’s t-tests were performed. Acute slice brightness comparisons. Viruses were diluted with PBS until the following titers were reached: 3.5×10 11 genome copies (GC) per mL for AAV8-EF1α-fLex-ASAP3/4.4/4.5 and 5.6 ×10 9 GC/mL for AAV9-CamkII-cre, which was obtained from the uPenn viral core (Addgene plasmid #105558). Mice were injected at postnatal ages 40–56 days. Each mouse was injected with 950–1000 nL at a flow rate of 200 nL/min. Acute slices were obtained 28–36 days post-injection. Injections were performed at the following coordinates relative to Bregma: AP: +1.2 mm; ML: −2 mm; DV: −3.2 to −2 mm, placing them into the dorsal striatum. Light was delivered to and received from the samples via a GFP filter cube (Chroma U- N41017 EN), through a 40x water immersion objective (Olympus LUMPlanFL 40×). To control for fluctuations in illumination intensity, videos of 50 frames were recorded at 33 Hz with a 30-ms exposure time, and the average taken. Imaging was done with the Orca Flash4.0 LT camera. ROIs for the cells were drawn in NIH Fiji, taking the mean pixel value within the ROI. Background was determined as the tissue near the cell without any cell debris present, and the mean was taken and subtracted out to give the final brightness value for a cell. Simultaneous one-photon imaging and electrophysiology in hippocampal slice. Mice aged 20–40 days were injected with AAV expressing ASAP3-Kv or ASAP4b-Kv. 4–7 days post-injection, animals were anesthetized with 5% isoflurane and acute coronal slices were prepared as previously described 49 . After achieving whole-cell recording configuration, APS were evoked in current clamp mode using 1-ms injections of 1 nA. Images were simultaneously recorded at ~1000 frames per second using a blue LED light source (coolLED pe300) and a photometrics prime-95B camera (Teledyne Photometrics) with a 40×W 0.8-NA objective (Olympus LUMPLFLN). Simultaneous two-photon imaging and electrophysiology in hippocampal slice. Mice of 28–60 days postnatal age were anesthetized with either ketamine/xylazine or isofluorane, then injected with a 1-μL mixture of AAV8-syn-ASAP3/b-Kv-WPRE and AAV1-syn-jRGECO1b-WPRE into the right hippocampus. Final concentrations were between 1.21×10 12 and 5×10 12 GC/mL for AAV8-syn-ASAP3/b-Kv-WPRE and between 1.3×10 12 and 5×10 12 GC/mL for AAV1-syn-jRGECO1b-WPRE. The mixture was injected via a glass micropipette (VWR) pulled with a long narrow tip (size ~10–20 μm) by a micropipette puller (Sutter Instrument) at a rate of 100 nL/min at the following coordinates from bregma: AP: −1.5 mm. ML: −1.5mm. DV: −1.5 to −1.3mm. The pipette was gently withdrawn 5 min after the end of infusion and the scalp was sutured. Coronal brain slices (300 μm) containing the dorsal striatum were obtained 4–8 weeks after AAV injection using standard techniques 50 . Briefly, animals were anesthetized with isoflurane and decapitated. The brain was exposed and chilled with ice-cold artificial cerebrospinal fluid (ACSF) containing 125 mM NaCl, 2.5 mM KCl, 2 mM CaCl 2 , 1.25 mM NaH 2 PO 4 , 1 mM MgCl 2 , 25 mM NaHCO 3 , and 15 mM D-glucose (300–305 mOsm). Brain slices were prepared with a vibrating microtome (Leica VT1200 S, Germany) and left to recover in ACSF at 34 °C for 30 min followed by room temperature (20–22 °C) incubation for at least additional 30 min before transfer to a recording chamber. The slices were recorded within 5 hours after recovery. All solutions were saturated with 95% O 2 and 5% CO 2 (Carbogen) in ACSF, which was pumped out of the recording chamber using a Masterflex HV-77122-24 pump. Hippocampal CA1 layer pyramidal neurons were visualized with infrared differential interference contrast (DIC) illumination and ASAP3/4b-Kv-expressing neurons were identified with epifluorescence illumination on a BX-51 microscope equipped with a 60× 1.0-NA water-immersion objective and DIC optics (Olympus) and a Lambda XL arc lamp (Sutter Instrument). Whole-cell current-clamp recording was performed with borosilicate glass microelectrodes (3–5 MΩ) filled with a K + based internal solution (135 mM KCH 3 SO 3 , 8.1 mM KCl, 10 mM HEPES, 8 mM Na 2 phosphocreatine, 0.3 mM Na 2 GTP, 4 mM MgATP, 0.1 mM CaCl 2 , 1 mM EGTA, pH 7.2–7.3, 285–290 mOsm). Access resistance was compensated by applying bridge balance. To induce firing, 1-ms pulses of 2-nA current were injected to induce spiking at 10, 20, or 50 Hz, or constant currents were injected starting at 100 pA and increasing by 50–100 pA until spiking was elicited, and then continued until spikes began to attenuate due to the depolarization blockade. Recordings were obtained with a Multiclamp 700B amplifier (Molecular Devices) using the WinWCP software (University of Strathclyde, UK). Signals were filtered with a Bessel filter at 2 kHz to eliminate high frequency noise, digitized at 10 kHz (NI PCIe-6259, National Instruments). Two-photon imaging was performed with a custom built two-photon laser-scanning microscope as described previously 51 , equipped with a mode-locked tunable (690–1040 nm) Mai Tai eHP DS Ti:sapphire laser (Spectra-Physics) tuned to 940 nm. The jRGECO signal in the red channel was ultimately not included because this setup was not able to obtain jRGECO signals at 940 nm, and did not have enough power at higher wavelengths to obtain a good signal in the red channel. ASAP signals were acquired by a 1-kHz line scan across the membrane region of a cell at powers of 130–150 mW. Signals recorded along each line were integrated to produce a fluorescence trace over time, and a region of the line scan corresponding to the background beyond the cell membrane was chosen as the background value, and subtracted from the integrated membrane region. All traces were then normalized to 1.0 by either dividing by a monoexponential, or dividing by the first 0.5 s of data where no activity was present, if there was no photobleaching present and the exponential fit was not working well. For the SNR calculation, the formula △ F / F 0 divided by the standard deviation (SD) of F 0 was used. F 0 was determined by using the value of the monoexponential or linear fit right before the spike occurred in the raw data. To calculate SD, the 50 points immediately preceding the detected spike peak in the raw data were used. Δ F is the maximum value attained by each spike after the trace was normalized to 1 by dividing by a monoexponential fit to the trace. The data points ± 2 ms of the peak of the average fluorescence waveform were searched to find the peak of single spikes, in order to account for timing jitter in the recordings. For the current steps, spikes were included in the SNR comparisons and average waveforms if the corresponding electrophysiological waveform crossed 20 mV in height at its peak. This excluded attenuated spikes from the analysis. Once detected in the data, spikes were aligned to where the electrophysiology trace crossed the 20mV threshold. Spike onset times for current step spikes were also determined by where the electrophysiology trace first crosses 20mV. The fluorescence traces were aligned to this threshold crossing, and the difference between the peak of the mean fluorescence trace and this threshold crossing in the electrophysiological trace taken to be the average delay time. The standard deviation was determined by finding the peak in the individual fluorescence responses within a 3ms window of time from when the average peak occurred for that respective protein, giving each trace an average time delay value +/− a standard deviation. For the ISI histograms, the time between spikes during current step application were sorted into 20 histogram bins in 10-ms increments, from ISIs of 10 to 200 ms. Anything larger than 200 ms was added to the 200-ms bin, giving a slight bump at the 200ms bin.” In vivo two-photon imaging of ASAP4e and jRGECO1a in the visual cortex. Wild-type C57Bl/6 mice (Jackson Laboratories #000664) were used for simultaneous calcium and voltage imaging. A cranial window was implanted as described previously 52 . In brief, a 3-month-old mouse was administered 1–2% isoflurane in O 2 by inhalation for anesthesia and bunprenorphine for analgesia, then head-fixed in a stereotax. A craniotomy was made over the left V1 region, followed by injection at 300 μm below the exposed brain surface of 200 nL of a 3:1 mixture of AAV8-Syn-ASAP4e-Kv (from 6.21×10 11 GC/mL stock) and AAV1-Syn-NES-jRGECO1a (from ≥ 1×10 11 GC/mL stock, Addgene #100854). A glass window was embedded and sealed in the craniotomy. A stainless-steel head-bar was firmly attached to the skull with dental acrylic. The implanted mouse was provided with the post-operative analgesic Meloxicam for 2 days and allowed to recover for 2 weeks prior to imaging. Imaging was performed on awake head-fixed mice. A modified, commercially available two-photon microscope was used 28 . A titanium-sapphire laser (Chameleon Ultra II, Coherent Inc.) was used as the two-photon excitation source, and a wavelength of 1000 nm was chosen to excite both ASAP4e-Kv and jRGECO1a fluorescent proteins. Post-objective powers of 18–31 mW were used for imaging of depths 140–185 μm below brain surface. Fields of view from 32×32 μm to 240×240 μm were imaged at a pixel size of 0.25×0.25 μm/pixel, resulting in frame rates varying from 15-99Hz. Images from two fluorescence emission channels (green: ASAP4e-Kv, red: jRGECO1a) were collected simultaneously. Image time stacks were first registered with rigid motion correction (NoRMCorre, MATLAB), then single neuron time traces were extracted by averaging the signal within hand-drawn ROIs using Fiji (ImageJ). In vivo one-photon imaging of hippocampus during running. Adult (11–23 weeks old) SST-IRES-Cre mice (2 male, 5 female) were injected with 500 nL of either AAV8-EF1α-DiO-ASAP3-Kv at a titer of 2.4×10 12 GC/mL (2 mice), AAV8-eEFα-DiO-ASAP4b-Kv at a titer of 2.4×10 12 GC/mL (2 mice), or AAV8-EF1α-DiO-ASAP4e-Kv at a titer of 3.45×10 11 GC/mL (4 mice), in the right dorsal CA1 area at 60 nL/min. 455-nm light was used as it has been shown to increase photostability over 470 nm in ASAP family GEVIs 53 . We kept maximum LED power at 5 mW total and 250 mW/mm 2 or less, as we found, and it has been previously shown, that sustained power levels above this resulted in tissue damage 54 . Data was acquired at 1000 fps while the mice ran on a wheel, in 11-s behavioral intervals. In between each 11-s recording bout was an 8.1-s pause. All surgical procedures, injection site, postoperative and training protocols are as previously described 55 . Animals were imaged using a custom-built, high-speed single-photon epi-fluorescent microscope. Photoexcitation was provided via a fiber-coupled LED (Thorlabs, M455F3) with a center wavelength of 455nm 53 . Excitation light is collimated after a 2-m long, 400-μm core multi-mode fiber optic patch cord (Thorlabs, M28L02) and expanded using a Keplerian telescope. The expanded beam is passed through a spectral excitation filter (Thorlabs, MF455-45), and reflected off of a long-pass dichroic mirror (Thorlabs, MD480) before teaching a 16× 0.8-NA water-immersion objective (Nikon, CFI75 LWD 16×W). The expander is used to generate a localized excitatory spot ~165 μm in diameter, at the focal plane. Emitted fluorescence is collected and transmitted through the dichroic mirror and an emission filter (Thorlabs, MF530-43) before reaching a 100-mm tube lens (Thorlabs, AC300-100-A) to form an image on a fast scientific CMOS camera (Hamamatsu Photonics, ORCA-Lightning C12120-20P) capable of kilohertz framerates. HCImage (Hamamatsu) was used for image acquisition. Excitatory power (mW) was measured on a power meter (Thorlabs PM100D, S130C sensor) before each experiment and converted to irradiance (mW/mm 2 ) within the excitatory spot area for direct comparisons between datasets. Time series data was extracted by first motion correcting the videos using NoRMCorre (MATLAB). ROIs were then drawn by hand in Fiji and mean fluorescence measured across time. Mean intensity from a background ROI was subtracted at each timepoint, then traces were time-binned to 500 fps and intensities normalized to the earliest stable baseline. For examples of spiking activity before and after photobleaching, 500-fps traces were exhibited without filtering or flattening. For measurements of photostability in neurons, traces were time-binned to 1 fps to reduce the contribution of shot noise to the variance between neurons. For spike statistics, traces were flattened by dividing it by a lowpass filtered version of itself using a 0.5- to 2-Hz lowpass second-order butterworth filter. This had the desired effect of capturing small changes due to movement and eliminating them, something a monoexponential fit did not do well. The data was then put through our spike detection algorithm, choosing a minimum of 10 spike templates per cell. To obtain the theta phase, we bandpass filtered the fluorescence traces between 6 and 11 Hz using a first-order Butterworth filter, giving us the theta frequency band. We then applied the Hilbert transform, giving us the instantaneous amplitude and phase of the bandpass filtered signal. We were able to detect a very consistent relationship between theta phase and spiking across all mice and all indicators, with spike likelihood peaking at 0 radians ( Fig. 4E ). Note that the ASAP3-Kv plot was flipped; as ASAP3 is a negatively tuned indicator, it would produce theta rhythms with peaks at pi radians off from the positive indicators if its response were not flipped. To generate images of ASAP-expressing neurons for display, images were spatially upsampled by 4× in each dimension and then aligned using the Fiji Template Matching plugin, and a maximum intensity projection of the new time series was made. This mimicked a long time exposure while minimizing blurring caused by motion. In vivo one-photon voltage imaging from mouse motor cortex during running. Stereotaxic viral injection and cranial window surgery were conducted in 6-week-old wild-type C57BL/6J male mouse (Jackson Laboratories #000664) as previously described 56 . Briefly, two viruses were mixed in saline (AAV-EF1α-Flex-ASAP4e-Kv (2.9×10 12 GC/mL), and AAV-hSyn-Cre (2.0×10 13 GC/mL)) prior to injection, but the latter was diluted at 1/1000 in volume which resulted in ~100× less Cre-recombinase virus in titer relative to the ASAP4e-Kv virus to achieve sparse labeling. The mouse was anesthetized using 1.5–2.0% isoflurane and then 500 nL of the viral mixture was injected in the left hemisphere at 1.0 mm AP, −1.5 mm ML, and 1.5 mm DV. After four weeks of recovery, a 3×3 mm cranial window (#1 glass coverslip) was implanted over the injection site using dental cement (Parkell C&B Metabond). A titanium headplate was attached to the skull to immobilize the mouse head during subsequent imaging on the running wheel. Four weeks after the cranial window surgery, mice were placed on a custom-made running wheel to acquire spontaneous brain activity from primary motor cortex layer 1. A BX-51 microscope (Olympus) equipped with a long-working distance (2.0 mm) 20× 1.0-NA objective (Olympus XLUMPlanFLN), a 470-nm LED (SOLIS-470C, Thorlabs), and a FITC-5050A filter set (Semrock) were used for excitation. The field aperture diaphragm was closed to the minimum size to improve signal-to-background ratio as previously described 57 . High-speed images were acquired by a Flash4.0 V2 CMOS camera (Hamamatsu C11440 –22CA) controlled by HCImage Live software (Hamamatsu). Spatial binning (4×4), and cropping (512×128 pixels) were used to achieve a framerate of 384 fps. Images were saved in DCIMG file format, then converted to TIFF files in MATLAB (Mathworks) with a manufacturer-provided DCIMG reader for subsequent image analyses. The acquired TIFF stack image was further cropped using NIH Fiji to retain only the field of illumination. We then used a custom-written motion correction algorithm based on pyStackReg to register rigid motions in the stack. Cellular and background ROIs were manually selected, then background-subtracted signals were normalized to initial values. To generate the image of ASAP4e-Kv-expressing neuron for display, the original TIFF stack file was spatially up-sampled, and then re-registered as described above, and intensities summed through the stack. In vivo two-photon imaging of hippocampus during spatial navigation. Prior to surgery, imaging cannula implants were prepared using similar methods to those previously published 58 . Imaging cannulas consisted of a 1.3-mm-long stainless steel cannula (3-mm outer diameter, McMaster) glued to a circular cover glass (Warner Instruments, #0 cover glass 3-mm diameter; Norland Optics #81 adhesive). Excess glass overhanging the edge of the cannula was shaved off using a diamond tip file. C57BL/6J mice (Jackson Laboratory stock #000664) were first anaesthetized by an intra-peritoneal injection of a ketamine/xylazine mixture. Before the start of the surgery, animals were also subcutaneously administered 0.08 mg Dexamethasone, 0.2 mg Carprofen, and 0.2 mg Mannitol. After one hour, animals were maintained under anesthesia via inhalation of a mixture of oxygen and 0.5–1% isoflurane. Then, 500 nL of a virus mixture (AAV8-syn-ASAP4b-Kv-WPRE at 1.17×10 12 GC/mL final; AAV1-syn-NES-jRGECO1b-WPRE-SV40 at 1.3×10 13 GC/mL final, Addgene #100857) was injected into the left hippocampus (500 nL injected at −1.8 mm AP, −1.1 mm ML, 1.4 mm DV) using a 36-gauge Hamilton syringe (World Precisions Instruments). The needle was left in place for 15 min to allow for virus diffusion. The needle was then retracted and the imaging cannula implant was performed. A 3-mm-diameter craniotomy was performed over the left posterior cortex (centered at −2 mm AP, −1.8 mm ML). The dura was then gently removed and the overlying cortex was aspirated using a blunt aspiration needle under constant irrigation with sterile artificial cerebrospinal fluid (ACSF). Excessive bleeding was controlled using gel foam that had been torn into small pieces and soaked in sterile ACSF. Aspiration ceased when the fibers of the external capsule were clearly visible. Once bleeding had stopped, the imaging cannula was lowered into the craniotomy until the cover glass made light contact with the fibers of the external capsule. In order to make maximal contact with the hippocampus while minimizing distortion of the structure, the cannula was placed at approximately a 10° roll angle relative to the animal’s skull. The cannula was then held in place with cyanoacrylate adhesive. A thin layer of adhesive was also applied to the exposed skull. A number-11 scalpel was used to score the surface of the skull prior to the craniotomy so that the adhesive had a rougher surface on which to bind. A headplate with a left-offset 7-mm diameter beveled window was placed over the secured imaging cannula at a matching 10-degree angle, and cemented in place with Met-a-bond dental acrylic that had been dyed black using India ink to prevent VR light from coming into the objective. At the end of the procedure, animals were administered 1 mL of saline and 0.2 mg of Baytril and placed on a warming blanket to recover. Animals were typically active within 20 min and were allowed to recover for several hours before being placed back in their home cage. Mice were monitored for the next several days and given additional Carprofen and Baytril if they showed signs of discomfort or infection. Mice were allowed to recover for at least 10 days before beginning water restriction and VR training. All virtual reality environments were designed and implemented using the Unity game engine ( https://unity.com/ ). Virtual environments were displayed on three 24-in LCD monitors that surrounded the mouse and were placed at 90° angles relative to each other. A dedicated PC was used to control the virtual environments and behavioral data was synchronized with calcium imaging acquisition using transistor-transistor logic (TTL) pulses sent to the scanning computer on every VR frame. Mice ran on a fixed-axis foam cylinder, and running activity was monitored using a high precision rotary encoder (Yumo). Separate Arduino Unos were used to monitor the rotary encoder and control the reward delivery system. In order to incentivize mice to run, the animals’ water intake was restricted. Water restriction was not implemented until 10–14 days after the imaging cannula implant procedure. Animals were given 0.8–1.0 mL of 5% sugar water each day until they reached ~85% of their baseline weight and given enough water to maintain this weight. Mice were handled for 3 days during initial water restriction and watered through a syringe by hand to acclimate them to the experimenter. On the fourth day, we began acclimating animals to head fixation (day 4: ~30 min, day 5: ~1 h). After mice showed signs of being comfortable on the treadmill (walking forward and pausing to groom), we began to teach them to receive water from a “lickport”. The lickport consisted of a feeding tube (Kent Scientific) connected to a gravity fed water line with an in-line solenoid valve (Cole Palmer). The solenoid valve was controlled using a transistor circuit and an Arduino Uno. A wire was soldered to the feeding tube and capacitance of the feeding tube was sensed using an RC circuit and the Arduino capacitive sensing library. The metal headplate holder was grounded to the same capacitive-sensing circuit to improve signal-to-noise, and the capacitive sensor was calibrated to detect single licks. The water delivery system was calibrated to deliver ~4 μL of liquid per drop. After mice were comfortable on the ball, we trained them to progressively run further distances on a VR training track in order to receive sugar water rewards. The training track was 450 cm long with black and white checkered walls. A pair of movable towers indicated the next reward location. At the beginning of training, this set of towers were placed 30 cm from the start of the track. If the mouse licked within 25 cm of the towers, it would receive a liquid reward. If the animal passed by the towers without licking, it would receive an automatic reward. After the reward was dispensed the towers would move forward. If the mouse covered the distance from the start of the track (or the previous reward) to the current reward in under 20 seconds, the inter-reward distance would increase by 10 cm. If it took the animal longer than 30 seconds to cover the distance from the previous reward, the inter-reward distance would decrease by 10 cm. The minimum reward distance was set to 30 cm and the maximal reward distance was 450 cm. Once animals consistently ran 450 cm to get a reward within 20 s, the automatic reward was removed and mice had to lick within 25 cm of the reward towers in order to receive the reward. After the animals consistently requested rewards with licking, we began training on tracks used for imaging. Two visually distinct VR tracks were used for imaging. Each track was 200 cm in length with a 50-cm hidden reward zone. In the first VR track, the 50-cm reward zone was the last 50 cm of the track, and in the second VR track, the 50-cm reward zone began 75 cm down the VR track so that it was in the middle of the track. Mice had to lick within the reward zone in order to receive liquid rewards. At the end of each trial, the animal was teleported to a dark hallway for a randomly determined timeout period of 5–10 s, chosen with equal probability for each possible timout length. During this timeout period, the laser power was reduced to 0 mW in order to reduce excessive photobleaching. After the timeout period finished, the laser power was increased and the mouse self initiated the beginning of the next trial by running forward. Data from both VR tracks was included in all analyses. To image the calcium and voltage activity of populations of neurons in CA1, we used a resonant galvonometer-scanning two-photon microscope (Neurolabware). All data was collected using a 25× 1.0-NA objective (Leica HC IRAPO). Neurolabware microscope firmware was modified to allow continuous bidirectional scanning at 989 Hz without digitizer buffer overload (16×796 pixels, 0.02×0.64-mm field of view). 940-nm light (Coherent Discovery laser) was used for excitation of both jRGECO1b and ASAP4b-Kv in all cases. Laser power was controlled using a pockels cell (Conoptics). Laser power was set on each session to obtain satisfactory SNR with the least amount of power possible. For ASAP4b-Kv imaging, the power ranged from 366 to 645 mW/mm 2 . Light was collected using photomultiplier tubes (Hamamatsu H10770B-40 and H11706-40 MOD for green and red channels respectively). Data was motion-corrected using the motion correction pipeline from the Suite2P software package 36 . Putative CA1 cell membrane segments were circled by hand using the motion corrected average ASAP4b-Kv image from each session in ImageJ ( imagej.nih.gov ). Given the dense labeling of cells as well as the dense cell packing of the CA1 pyramidal cell layer, some of the membrane segments likely contain signals mixed from several cells. Based on the numerical aperture of the objective and our approximate axial resolution, we estimate that each ROI contains signal from (~1–3) cells. Pixel-averaged timeseries were extracted from both the red and green channels for each ROI. For each ROI, we calculated Δ F / F independently for the green and red channels. Since laser power was set to 0 mW between each trial, signal baseline was calculated independently on each trial as well. Due to the small FOV and the fact that animals were running at high speeds (~40 cm/s) some frames were not able to be accurately motion corrected. We attempted to remove the effect of these high-motion frames from our analyses by using Suite2P’s motion estimates to calculate which frames were corrupted by motion. Any frame within 20 frames of one of these high motion frames was replaced with a “NaN” value. Motion estimates from Suite2P rigid motion correction were then used as nuisance regressors for the remaining timepoints, with the following design matrix: X = [ x ( t ) , y ( t ) , x 2 ( t ) , y 2 ( t ) , x ( t ) x ( t ) ] . The residual timeseries from this regression were used for the remaining analyses. For baseline calculation, NaNs were linearly interpolated from the surrounding frames. These motion-imputed timeseries were then low pass filtered to calculate a baseline timeseries (green channel: 0.5 Hz 8 th order Butterworth low pass filter, red channel: 0.25 Hz 8 th order Butterworth low pass filter). Residual ROI timeseries (NaNs included) were divided by this baseline to get Δ F / F . For place cell identification and visualization, Δ F / F was convolved with a 5-frame Gaussian. Place cells were identified using a previously published spatial information (SI) metric 36 , S I = ∑ j P j λ j λ j λ , where λ j is the average activity rate of a cell in position bin j , λ is the position-averaged activity rate of the cell, and p j is the fractional occupancy of bin j . The track was divided into 10 cm bins, giving a total of 20 bins. To determine the significance of the SI value for a given cell, we created a null distribution for each cell independently using a shuffling procedure. On each shuffling iteration, we circularly permuted the cell’s time series relative to the position trace within each trial and recalculated the SI for the shuffled data. Shuffling was performed 100 times for each cell, and only cells that exceeded all 95% of permutations were determined to be significant “place cells”. To further ensure the reliability of the place cells, we implemented split-halves cross-validation. Taking only the odd-numbered trials, we computed the average firing rate map to identify the position of peak activity. Each cell’s activity was “z-scored” based on the mean and standard deviation across spatial bins on odd-numbered trials. Cells were sorted by this position and then the average activity on even-numbered trials was plotted. This gives a visual impression of the reliability of the place cells. For visualization, single trial activity rate maps were smoothed with a 20-cm (2 spatial bins) Gaussian kernel. Gaussian log-likelihood-based signal detection. Our spike detection framework builds on a previously published log likelihood ratio based framework by Wilt et al 30 . To implement the equations in that study on real-world empirical data, we changed the assumed dominant noise structure from Poisson-distributed shot noise to Gaussian distributions. We found noise in our measurements was primarily Gaussian in nature, likely because electronic sources dominated over photon shot noise. Spike templates were chosen for each imaging session, and were chosen to be the largest spiking events from the beginning of the session, with a minimum of 10 chosen each time. Naturally, as photobleaching occurred across trials and spikes become noisier, fewer were detected since the template spikes were taken from the initial imaging period and were thus much larger. While taking only the largest events to use as the template results in very conservative detection, with smaller, noisier events remaining undetected, we wanted to be confident in the events we did detect, and felt that this was a safer approach. The red line represents the significance threshold, which was chosen such that after breaking the data vector into pieces with lengths equal to the length of the spike template, there was a 1/(20 × number of pieces) chance of getting a false positive in any given piece of data. This was done to correct for multiple comparisons. Once the event templates were chosen, the equations and procedures described below allow the data to be converted into a probability vector. The probability vector quantifies the probability that the data came from the distribution defined by the templates. N is the length of the templates in samples (time bins), and the data is taken in N samples at a time and compared to it. The background also has a template of length N, but since our data was normalized to 1, we set the background to a vector of ones of length N. See the section below on Background Noise Estimation for how we estimated the standard deviation of the background template. Our new gaussian equations for calculating the log likelihood probability that the observed data came from the distribution defined by the template events are as follows: For time bins where the k ’th mean template value is less than the k ’th value of the background, where k only counts the time bins where this condition is true: U is the total number of time bins where the mean of the templates are less than the mean of the background. f k is the k ’th sample of the new data being analyzed. C h a n c e N o i s e U n d e r k = ∏ k = 1 U ∫ − ∞ f k N ( μ B k , σ B k ) μ B k is the mean of the mean of the background template at the k ’th data point. For our purposes this was the number 1 for all k since we normalized the data, but it does not have to be. σ B k is the standard deviation of the background at the k ’th point. See the “ Background noise estimation ” for how this was estimated. C h a n c e S i g n a l U n d e r k = ∏ k = 1 U ∫ f k ∞ N ( μ S k , σ S k ) μ S k is the mean of the templates the user selected at the k ’th point. Note that this allows for the shape of the event to be taken into account when calculating probabilities. σ S k is the standard deviation of the k ’th time bin for the templates chosen. This means that each time bin of the event template has its own mean and standard deviation, creating N gaussian distributions, which are needed to take the gaussian integrals at each time bin. N is the length of the templates in time bins. Below, for time bins when the j ’th mean template value is greater than the j’ th value of the background, where j only counts the time bins where this condition is true: O is the total number of time bins where the mean of the templates are greater than the mean of the background. f j is the j ’th sample of the new data being analyzed. C h a n c e N o i s e O v e r j = ∏ j = 1 O ∫ f j ∞ N ( μ B j , σ B j ) C h a n c e S i g n a l O v e r j = ∏ j = 1 O ∫ − ∞ f j N ( μ S j , σ S j ) This is the same as above, only for time bins where μ B j < μ S j , so the limits of integration change. These probabilities are multiplied together, the log of the ratio of them obtained, and ultimately a single number for the i’ th sample of the data vector is returned, where i runs from 1 to the length of the data vector. L i = l n ( ∏ k = 1 U C h a n c e S i g n a l U n d e r k ∗ ∏ j = 1 O C h a n c e S i g n a l O v e r j ∏ k = 1 U C h a n c e N o i s e U n d e r k ∗ ∏ j = 1 O C h a n c e N o i s e O v e r j ) Note that since N is the length of the template in samples, N = U + O . This is repeated, each time shifting over by a single time bin in the data, until the entire data vector has been analyzed and converted into a probability vector. The very end of the data vector is chopped as we did not find an objective way to pad the end of data vector such that it would not impact the probabilities calculated for when the template distribution reaches the end. Fortunately, our templates were typically very short in length, so this resulted in a very negligible loss of data at the very end of each data set (a few tens of milliseconds). While taking the log of the ratio here is not strictly necessary for the purposes of signal detection, it helped to keep the ratio from becoming too positive or too negative to visualize effectively when making plots. We next find all of the events that cross the probability threshold we set. Every segment above threshold is considered a single template matching event, for as long as it stays above threshold in the log likelihood probability vector. Since it does this, it is important to set the filter parameters such that you pull out the events you care about. For example, if the user wanted to detect single spikes riding on top of depolarizing calcium waves, as well as the depolarizing waves themselves, you would first set a very low frequency lowpass filter as the baseline calculation, and choose the entire duration of the burst as a template. Once you have the detected bursts pulled out, you would then set the passband of the lowpass filtered calculation of the baseline higher than what was used previously to pull out the entire burst, in order to flatten out the calcium portion of the event, while maintaining the faster spikes for detection. This enables the user to sequentially detect bursts, followed by spikes within bursts. For onset timing, the time point where the log likelihood ratio first crosses the threshold is considered the start of the event. For the event detection performed on the one-photon in vivo imaging dataset of somatostatin-positive (SST+) interneurons, we first highpass filtered both the spike templates and raw data with a 20-Hz second-order Butterworth filter. Background noise estimation. The standard deviation (SD) of the background template in this case is assumed to be constant across the background template. It is recalculated for each new batch of data that is fed into the program, and involves 3 successive attempts, if the previous attempt fails. Attempt 1: The program fits a gaussian mixed model (GMM) to the entire data vector, with the assumption that there are two gaussians present. One is the signal, one is the noise. This tends to work well for traces where lots of activity is present, giving the histogram of the data vector a tail to one side; otherwise it tends to only find a single gaussian. The standard deviation of the noise is set to be the std. of the gaussian on the left if the indicator is upward going, or the gaussian on the right if it is downward going, which the program detects from the peak of the average templates. This prevents overestimating the noise, which would result in more false negatives than desired (but fewer false positives as well). Attempt 2 : If the SD of the GMM fit is greater than the SD of the whole data vector, then the fit is considered invalid. The program then reverts to an “asymmetric distribution technique”: If the data contains signals, the distribution of the data will be skewed to one side. To the right if the indicator is upward going, and to the left if it is downward going. The side of the distribution away from the direction the indicator moves in must be pure noise, with no contamination from the signal we are looking for. That half of the distribution is then flipped about the mean to replace the half that is a mix of noise and signals, giving a good estimation of how the distribution of the data would look if there were no signals present in it. The SD of this “flipped” distribution is then taken to be the standard deviation of the noise. Attempt 3 : Occasionally, attempt 2 also fails, possibly due to movement or lots of hyperpolarizing activity, and the standard deviation of the flipped distribution is greater than the standard deviation of the data itself, which again does not make sense. This happens very rarely, but in this case the standard deviation of the background is simply assigned the value of the standard deviation of the entire data vector. This will have the effect of giving too many false negatives, but it has the advantage of giving fewer false positives as well, so represents a conservative estimate of spike probability. Note that how the background noise is chosen affects the numbers in the log-likelihood vector. Less background noise will result in larger log likelihood values, and vice versa. This is because that as the noise distribution gets narrower via a smaller SD, the probability that the same data point came from the noise distribution shrinks. If there are more than 9 templates, the SD of the templates themselves are taken, as described previously, to be the SD of the templates at each time bin in the template vector. If there are less than 10 templates, the SD of the templates is assumed to be the same as the noise, and only the mean changes (the mean template trace is still taken, but each time bin just has the same SD which is the same as the noise).

Supplementary Material Supplementary Video 1 Supplementary Video 1. In Vivo Imaging of ASAP4e-kv and jRGECO1a in Mouse V1. Neurons co-expressing ASAP4e-Kv and jRECO1a were recorded by two-photon scanning at 99 frames per second with a single 1000-nm excitation wavelength, with green (ASAP4e-Kv) and red (jRECO1a) emissions directed to separate detectors by a beam-splitter. Above, raw image data. The white arrow points to the quantified cell. Below, plots of ΔF/F0 in green and red channels. Traces are corrected for photobleaching for display purposes but unfiltered. The same traces uncorrected for photobleaching can be seen in Fig. 3 . ASAP4e-Kv fluorescence changes of ΔF/F0 > 3 standard deviations from the baseline are marked visually by ticks above the trace and aurally by a click sound. 2