iGluSnFR wide-field imaging responses to 2-72 Hz flicker
Data files
Sep 04, 2024 version files 131.04 GB
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README.md
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Spatiotemporal_resonance_DATA_Flicker.zip
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Spatiotemporal_resonance_DATA_Pulse.zip
Abstract
Human primary visual cortex (V1) responds more strongly, or resonates, when exposed to ~10, ~15-20, ~40-50 Hz rhythmic flickering light. Full-field flicker also evokes perception of hallucinatory geometric patterns, which mathematical models explain as standing-wave formations emerging from periodic forcing at resonant frequencies of the simulated neural network. However, empirical evidence for such flicker-induced standing waves in the visual cortex was missing. We recorded cortical responses to flicker in awake mice using high spatial resolution widefield imaging in combination with high temporal resolution glutamate-sensing fluorescent reporter (iGluSnFR). The temporal frequency tuning curves in the mouse V1 were similar to those observed in humans, showing a banded structure with multiple resonance peaks (8 Hz, 15 Hz, 33 Hz). Spatially, all flicker frequencies evoked responses in V1 corresponding to retinotopic stimulus location, but some evoked additional peaks. These flicker-induced cortical patterns displayed standing wave characteristics and matched linear wave equation solutions in an area restricted to the visual cortex. Taken together, the interaction of periodic traveling waves with cortical area boundaries leads to spatiotemporal activity patterns that may affect perception.
README: iGluSnFR wide-field imaging responses to 2-72 Hz flicker
https://doi.org/10.5061/dryad.vdncjsz42
Description of the data and file structure
There are two ZIP files containing widefield imaging DATA from two visual stimulation protocols used in the experiment: (1) sine-wave modulated luminance changes (flicker; Spatiotemporal_resonance_DATA_Flicker.zip) and (2) pulse stimulation (Spatiotemporal_resonance_DATA_Pulse.zip). Data is organized in folders. Each folder contains single-animal data, e.g. Glu1, Glu2 etc.
Organization of the folders:
(1) Spatiotemporal_resonance_DATA_Flicker.zip
In each animal's data folder you will find a subfolder named "Ready4preprocessing" with the following file types:
- datafiles (.raw); scripts to load this datafile type can be found in Spatiotemporal_resonance_CODE.zip, file named *imreadallraw.m, for an example how to use it, see 1_Preprocessing_singleTrial_SSVER.m line 154
- stimulus onset/offset timestamp files (.abf); scripts to load this datafile type can be found in Spatiotemporal_resonance_CODE.zip file named *abfload.m, for an example how to use it, see 1_Preprocessing_singleTrial_SSVER.m line 78
stimulus files (Rec.mat); variable *frex contains flicker frequency on each trial (Hz), variable trialDuration indicates trial duration (10 sec), flickeringLEDsAmplitude variable indicates light intensity setting of a custom-built LED stimulation device (arbitrary units) and it corresponds to maximum luminance of 215 cd/m2
transformation matrix used to align across recordings (adjusted.mat); generated using *0_Coregistration_across_recordings.m scrip
matrix marking pixels containing the brain data (Mask*.tif; brain pixels = 1; non-brain = 0)
Recordings are organized by day in alphabetic order, such that a1 and a2 are the files for recording day 1; b1 and b2 are for recording day 2, etc.
File naming. Both *.raw and *.abf files contain information about the recording (e.g. a1_06_20180412_ssvep_92000fr_150Hz_intensity_15_2_74Hz_animal_1):
- recording: e.g. a1
- file-order during data acquisition: e.g. 06
- recording date: e.g. 20180412
- number of camera frames in the recording: e.g. 92000fr
- sampling rate: e.g. 150Hz
- stimulation intensity (LED stimulation device): e.g. 15
- range of frequencies used in the experiment: e.g. 2-74Hz
- which animal: animal 1
Each animal's data folder also contains vasculature images from each recording. These images were used to align data across recordings. Use the code 0_Coregistration_across_recordings.m if you want to redo the realignment, or use the *adjusted.mat files instead.
(2) Spatiotemporal_resonance_DATA_Pulse.zip
In each animal's data folder you will find the following file types:
datafiles (.raw); scripts to load this datafile type can be found in Spatiotemporal_resonance_CODE.zip, file named *imreadallraw.m, for an example how to use it, see 1_Preprocessing_singleTrial_Pulse.m line 154
stimulus onset/offset timestamp files (.abf); scripts to load this datafile type can be found in Spatiotemporal_resonance_CODE.zip file named abfload.m, for an example how to use it, see *1_Preprocessing_singleTrial_SSVER.m line 79
transformation matrix used to align across recordings (adjusted.mat; obtained using *0_Coregistration_across_recordings.m script);
matrix marking pixels containing the brain data (Mask*.tif; brain pixels = 1; non-brain = 0)
Code
The main scripts are 1_Preprocessing_singleTrial_PULSE.m and 1_Preprocessing_singleTrial_SSVER.m (preprocessing is done separately for two stimulation paradigms). The other scripts will be called by this main script.
The scripts in the folder allow to preprocess the data and prepare it for the analysis. The full analysis scripts are provided on: https://osf.io/u37ar/
Requirements: MATLAB Image Processing Toolbox and Signal Processing Toolbox. The code was run on MATLAB 2019b.
Methods
In vivo glutamate imaging was performed in awake head-fixed animals using a charge-coupled device (CCD) camera. To capture the fast glutamate sensor iGluSnFR kinetics, images of iGluSnFR activity were captured at 150 Hz sampling rate. The glutamate fluorescent indicator was excited using blue LED light (Luxeon K2, 470 nm), which was band-pass filtered using an optical filter (Chroma Technology Corp, 467-499 nm). Light emitted from excited fluorescent indicators was passed through a band-pass optical filter (Chroma, 510 to 550 nm; Semrock, New York, NY) and a macroscope composed of front-to-front optical lenses. The focal length of the lenses was adjusted such that the field of view was 8.6 × 8.6 mm (128 × 128 pixels, with 67 μm per pixel). To minimize the effect of hemodynamic signal originating from large cortical blood vessels, we focused the optical lens at ~1 mm depth.
Steady-state visual evoked potentials. We used a custom-built setup of white light-emitting diodes (LEDs; luminous intensity 6900 mcd, color temperature 9000K, Model C513A-WSN, Cree Inc.) to deliver visual stimulation (the setup previously used in Gulbinaite et al. 2019 NeuroImage). The LED array was placed in a cardboard box, with a circular aperture subtending 35° of visual angle covered by a sheet of tracing paper (6 cm away from LED array). The visual stimulation box was placed on the left side of the animal, 8 cm from the left eye, at a 50° angle to the animal’s body axis. Flicker was implemented as a sine-wave modulation of the power supply to the LEDs (luminance changes from 0 to 215 cd/m2). On each trial, the animals were exposed to 10 s of flicker followed by 10 s inter-trial interval of complete darkness (Figure 1B). Mice were exposed to flicker frequencies that ranged from 2 to 72 Hz (logarithmically spaced 30 different frequencies). For all frequencies, the stimulation started and ended with maximal luminance (215 cd/m2, π/2 phase of the sine-wave cycle). Each imaging session lasted up to 30 minutes, during which each flicker frequency was presented twice in pseudo-random order. Each animal underwent 5 experimental sessions (i.e. 5 recordings on separate days). Thus in total, each flicker frequency was presented 10 times.
Visual evoked-potentials. In addition to sine-wave stimulation, we recorded responses to single light pulses (20 ms) using 1500 cd/m2 luminance stimuli to characterize spatiotemporal dynamics in response to single stimuli and on/off responses.