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8 protocols using led driver

1

Optogenetic Stimulation of Cerebellar Cortex

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LED photostimulation (λ = 470 nm) driven by a Thorlabs LED driver (225 μW) was given through an optic fiber (400 μm in diameter, Thorlabs, Newton, NJ, USA). The optic fiber rested on the dura mater above the midline between crus 1, crus 2, approximately 1 mm lateral from the vermis, via the craniotomy. During experiments with optogenetic stimulation, trials without stimulation, with 100 ms and with 200 ms optogenetic stimulation were randomly intermingled.
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2

Wide-Field Calcium Imaging of Mouse Cortex

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Wide-field 1-photon and two-photon calcium imaging was performed using the Bergamo II Scope (Thorlabs) with blue LED illumination using an LED driver (Thorlabs). GCaMP6s fluorescence signal from the cortical surface was acquired at about 15 Hz (640 × 540 pixels, field of view (FOV) ranges from 3×3 to 5×5 mm2) using a Zyla 5.5 sCMOS camera (Andor) controlled by μManager2. Average excitation power at the exit of the air objective (2x or 4x, UPlanFl, Olympus) ranged from 0.2 to 0.8 mW. Individual sessions were initially registered prior to recording using a blood vessel template recorded on the first chronic session. More accurate registration was performed offline using custom scripts based on pixel correlation. Single-condition response maps were expressed as ΔFF=FstimFoFo where Fstim is the trial and time-averaged response across stimulus frames, and Fo is the trial and time-averaged response during the 1 second prior to stimulus onset.
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3

Optogenetic Activation of TRPV1+ Nociceptors

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To activate TRPV1+ nociceptors by blue light (473 nm; power 4.7 mW; frequency 3 Hz; 20% duty cycle, pulse width 67ms), a LED driver (Thor Labs, Newton, New Jersey) was connected to a blue LED source (Thor Labs). Parameters previously shown to demonstrate hypersensitivity in the paw for up to 24 h were used (Daou et al. 2013 (link)). The power from the LED was measured using a power meter with the LED positioned at the same 1 cm distance from the sensor at the start and end of the experiment. The power measured from these settings at both points was 4.7mW and the pulse width was 67ms. The LED was positioned over the right hind paw at 1 cm distance from the skin (Fig. 1A). TRPV1-Cre/ChR2 mice or C57Bl6 mice were stimulated with blue light on the hind paw for 15 min. Immediately following optogenetic stimulation, mice were injected with 3 mg/kg of KLH subcutaneously in 20 µL into the same paw. Blood was collected weekly, and serum antibody titers tested.
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4

Optogenetic Stimulation of EPSPs

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Electrophysiology recording with optogenetics stimulation were performed with the same set up detailed above with a ×40/1.0 NA water immersion objective. Dissection and electrophysiological recordings were performed in the same modified HL-3 saline described above. To stimulate EPSP events, 0.5 ms light pulses of 470 nm were delivered from an LED driver (Thorlabs) at 0.5 Hz, triggered by a TTL pulse driven from a Digidata 1440 DAC programmed using pClamp 10.5 software (Molecular Devices). Light intensity was controlled by the LED driver to avoid multiple EPSP events. The power range were calibrated between 5 and 20 mW/cm2 under the objective.
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5

Threshold Light Sensitivity in Somatostatin Mice

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To measure the ‘threshold’ light intensity at which somatostatin mice began responding to stimulation, mice were placed in individual tubes with cannulae attached and allowed to first habituate for 30 minutes. Following habituation, each mouse was sequentially screened for approximate current driving a Thorlabs LED driver at which they flinched. Once an approximate current was established, testing began 30–40 mA below that threshold. A stopwatch was used to measure the latency until mice attended the stimulus (which was a lick response in all cases). A cutoff value of 20 s was chosen (i.e. stimulus did not continue more than 20 seconds). At 5 minute intervals, LED intensity was increased by 10 mA. Once the time to attendance dropped below 1 second, tests were halted. The current value at which the mouse response time first dropped below 20 s was chosen as the ‘threshold’ value, and was used in future experiments with that specific mouse. These current values were then normalized to ‘threshold’, and plotted against threshold plus or minus a delta (10 mA steps).
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6

Fiber Photometry System for Neural Activity Monitoring

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The fiber photometry system used two light-emitting diodes (490 nm and 405 nm; Thorlabs) controlled by an LED driver (Thorlabs). The 490 nm light source was filtered with a 470 nm (the excitation peak of dLight1.1) bandpass filter and the 405nm light source was used as an isosbestic control.48 (link) Light was passed through an optical fiber (400 μm, .48 NA; Doric) that was coupled to a chronically implanted fiber optic cannula in each mouse. LEDs were controlled via a real-time signal processor (RZ5P; Tucker-Davis Technologies) and emission signals from each LED were determined by multiplexing. Synapse software (Tucker-Davis Technologies) was used to control the timing and intensity of the LEDs and to record the emitted fluorescent signals upon detection by a photoreceiver (Newport Visible Femtowatt Photoreceiver Module; Doric). LED power (125 μW) was measured daily and maintained across trials and experiments. For each event of interest (e.g., cue presentation, footshock), transistor-transistor logic (TTL) signals were used to timestamp onset times from Med-PC V software (Med Associates Inc.) and were detected via the RZ5P in the Synapse software (see below). A built-in low-pass filter on the Synapse software was set to 10 Hz to eliminate noise in the fiber photometry raw data.
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7

Optogenetic Silencing of V1 in Mice

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An optical fiber (1 mm) coupled to a blue LED (470 nm; Doric Lenses) was placed over V1 above the intact skull covered with a thin layer of Krazy glue. The fiber was placed at approximately the retinotopic location corresponding to the stimulus during the initial 350 ms in the task: ~2.3 mm from midline and ~1.3 mm from lambdoid suture. To find these coordinates, we recorded multiunit activity in V1 with the monitor in the same position as during optogenetic silencing (monitor was moved <15 degrees to center the spatial receptive field of the multiunit activity). We used these same approximate coordinates for all of our recordings.
For each animal, the total power was increased until the performance was at chance level when the LED illumination started before the stimulus appeared (3.3–20 mW across animals; p>0.05; Wilcoxon ranksum test on stimulus centering times in the reward zone). To turn the LED on at specific delays after stimulus onset, the photodiode signal detecting the onset of the stimulus was sent to an amplifier (Newark; TWLUX - TW-MF2CAB) and then to an external microprocessor (Mega 1280; Arduino). The microprocessor waited for the amplified photodiode signal to cross a threshold before sending out a digital trigger to the LED driver (Thorlabs). The jitter (s.d.) of the LED onset was 4 ms.
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8

Fiber Photometry for Calcium Imaging

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Calcium imaging was performed using a custom-built fiber photometry rig based on the design of the Deisseroth (Lerner et al. 2015 (link)) and Woodward labs (Braunscheidel et al. 2019 (link)). An LED driver (Thorlabs, Newton, New Jersey) provided both 405 nm and 490 nm illumination which were combined in a fluorescence mini-cube (Doric Lenses, Québec, QC, Canada). A custom made 400 μm diameter patch cord terminating in a ceramic sleeve was used to connect the mini-cube to the animal’s fiber optic implant. Synapse software was used to control a digital processor that received input from a photodetector that collected emission signals at both 405 and 490 nm (Tucker-Davis Technologies, Alachua, FL). Integrated TTL signals were used to time-lock neuronal recordings to the start of each fear conditioning session and signaled the start of each tone throughout the session. Custom-written MatLab codes were used to analyze these data (The MathWorks Inc.). Signals from the 405 and 490 nm channels were subtracted from each other to calculate ΔF/F, and data for each testing day was then z-normalized to a combined baseline of all signaling across the whole session for that day.
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