Article Figures & Data
Figures
- Figure 1.
The ToneBox system for automated auditory operant conditioning in the mouse home cage. a, ToneControl software runs from the Matlab environment on a desktop computer. A Wi-Fi router is used to connect the computer to each Wi-Fi ToneBox. b, The ToneBox CCU. Bottom, A 3D model of the CCU case. Inside each CCU is a Raspberry Pi 3+ (middle) that is connected to a custom shield (top) with two capacitive touch sensors used to monitor behavioral responses. A USB sound card (middle) is used for audio input and output. c, The ToneBox BI: 3.5 mm audio cables connect the CCU to the BI within each home cage. An overhead speaker in the BI presents sounds. Pure tones of 1-45 kHz were calibrated to <1 dB magnitude variability. The waterspout at the base of the BI is connected to the CCU capacitive touch sensor to detect licks. d, The CCU, BI, and home cage are placed within an actively ventilated enclosure. The BI is mounted on the side of the cage. The BI is designed to place the waterspout inside the cage, while keeping the speaker outside to avoid damage from exploratory behavior by the mice. Water tubing enters through the back of the enclosure, connecting a flow regulator to the waterspout. e, Twelve enclosures with clear doors are shown stacked together on a mobile rack, with water supplies.
- Figure 2.
Auditory detection task performance in mice trained using ToneBoxes. a, Example of behavioral data collected over 9 consecutive days in a single box of two mice. Response rates were calculated using a 25-trial sliding window. b, Task engagement was defined as the average number of trials with at least one lick per trial. The solid and dotted lines show the dark and light cycles, respectively. The Shading shows ±2 SEM. c, Hit and early response rates for each of the 12 tested boxes, color coded as in a. d, Hit and early response rates for three individual mice that were initially trained in pairs, then isolated and trained alone (left three panels), and a box of four mice initially trained together (right). Data color coded as in a. e, Pure-tone detection with roving tone frequency and level. Hot and cool colors indicate high and low hit rates, respectively.
- Figure 3.
Statistical distributions of tone detection behavioral response rates across 12 ToneBoxes. a, Behavioral response rate histograms across time in a trial for hits during the dark cycle (dark blue) and light cycle (light blue), and for early responses also during the dark cycle (dark green) and light cycle (light green). Shading shows ±2 SEMs. b, Response rate-based task performance accuracy box plots. The star indicates that the dark cycle hit rate was significantly above the light cycle hit rate (p = 0.019, KS test; n = 12 cages). Data color coded as in a. The + marks indicate data points outside of the 25th and 75th percentiles. c, Hit and early rates shown for each hour of the day. The bin for each hour begins at tick marks. The dark cycle is shown in the shaded region. The thick black line shows when the hit rate was significantly above the early rate (p < 0.01, KS test; n = 12 cages). Shading shows ±2 SEMs.
- Figure 4.
Pure-tone detection behavioral response latencies (i.e., the delay from trial onset until the first lick of the waterspout in each trial). a, Latency histograms for each cage. The black bar shows when the 1 s tone was presented. b, Average response latency distributions across 12 ToneBoxes. c, Latency-based task performance accuracy box plots. Performance accuracy was defined here by the AULH (a) for hit and early responses. Shading shows ±2 SEMs. Data color coded as in b. d, Hit and early latency-based task performance accuracy shown for each hour of the day. The dark cycle is shown in the shaded region. Shading shows ±2 SEMs. Data color coded as in b.
- Figure 5.
Pure-tone frequency discrimination task performance. a, Example of behavioral data collected over 19 consecutive days in a single ToneBox of two mice. b, Hit, early, and false alarm response rate histograms across time in a trial, color coded as in a. c, Hit, early, and false alarm latency histograms across time in a trial, color coded as in a.
- Figure 6.
Statistical distributions of tone discrimination response rates across two ToneBoxes. a, Response rate-based task performance accuracy box plots for hits during the dark cycle (dark blue) and light cycle (light blue), false alarms during the dark cycle (dark red) and light cycle (light red), and for early responses also during the dark cycle (dark green) and light cycle (light green). b, Hit, false alarm, and early rates shown for each hour of the day. The dark cycle is shown in the shaded region. Data color coded as in a. Shading shows 2 SEMs. c, Response rate-based d´ values for each hour of the day. Shading shows ±2 SEMs.
- Figure 7.
Statistical distributions of tone discrimination response latencies across two ToneBoxes. a, Latency-based task performance accuracy box plots. Performance accuracy was defined here by the AULH for hit and early responses. b, Response latency-based task performance accuracy shown for each hour of the day, and for hit, false alarm, and early responses. The dark cycle is shown in the shaded region. Shading shows ±2 SEMs. Data color coded as in a. c, Response latency-based d´ values for each hour of the day. Shading shows ±2 SEMs.
Extended Data
Extended Data 1
ToneBox.zip contains a manual with parts lists and comprehensive step-by-step instructions for assembly and operation of the ToneBox system. We also provide models for 3D printing and PCB manufacturing, as well as software for system operation and data analysis. Download Extended Data 1, ZIP file.
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