A new automated device for quantifying mechanical nociceptive responses

Accepted Manuscript Title: A new automated device for quantifying mechanical nociceptive responses Authors: Jahrane Dale, Haocheng Zhou, Qiaosheng Zhang, Amrita Singh, Jing Wang PII: DOI: Reference:

S0165-0270(18)30393-5 https://doi.org/10.1016/j.jneumeth.2018.12.001 NSM 8201

To appear in:

Journal of Neuroscience Methods

Received date: Revised date: Accepted date:

13 September 2018 1 December 2018 1 December 2018

Please cite this article as: Dale J, Zhou H, Zhang Q, Singh A, Wang J, A new automated device for quantifying mechanical nociceptive responses, Journal of Neuroscience Methods (2018), https://doi.org/10.1016/j.jneumeth.2018.12.001 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

A new automated device for quantifying mechanical nociceptive responses Jahrane Dale1, Haocheng Zhou1,2, Qiaosheng Zhang1, Amrita Singh1, & Jing Wang1,3,4*

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Department of Anesthesiology, Perioperative Care and Pain Medicine, New York University

School of Medicine, New York, NY, USA. 2

Department of Pain Medicine, The Third Xiangya Hospital and Institute of Pain Medicine, Central

South University, Changsha, Hunan Province, China. 3

Department of Neuroscience and Physiology, New York University School of Medicine, New

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York, NY, USA. 4

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Lead contact

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*Correspondence: [email protected]

HIGHLIGHTS

Development of an automated system to quantify nociceptive withdrawal responses in rats

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Demonstration that this automated system can distinguish different nociceptive intensities

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The temporal sensitivity for this assay system allows behavioral correlation for

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neurophysiological studies

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ABSTRACT

Background: Traditional methods to assess pain in rodents depend on measures of nociceptive responses, most commonly from the hind paws. While these measures can quantify nociceptive responses to allow pharmacologic testing, they typically have high inter-experimenter variability

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and are not time-sensitive enough to correct with neural processes that occur on millisecond scales. New Method: We have invented a pain detection device that uses changes in skin conductance to measure nocifensive withdrawal responses. This device automatically records how long it takes

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for a rodent to withdraw its paw from the onset of peripheral noxious stimulation. Results: with this pain device, we can record accurate timing (on the millisecond scale) for nociceptive responses, with high accuracy and consistency. Furthermore, we demonstrate that this device can allow us to distinguish the nociceptive response to mechanical noxious stimuli of different intensities. Finally, we demonstrate that this device can be digitally integrated to correlate behavior

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with neural activities in real-time. Conclusions: This study demonstrates a new automated,

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temporally specific method for quantifying nociceptive responses to facilitate rodent pain studies.

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Keywords: pain, touch circuit, nociceptive, withdrawal, automated

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INTRODUCTION

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Pain can be viewed as a behavioral and emotional response to a highly salient sensory (noxious)

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input. In order to study pain, we need to quantify this behavioral response. In humans, we can assess pain by verbal reports of the emotional response. However, verbal reports are not always

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reliable, leading to under- and over-reporting of pain intensity1-3. In animal studies, particularly studies in rodents, pain is assessed by behavioral, rather than verbal reports4-6. Current methods to

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record pain in rodents rely on conditioned or unconditioned nociceptive responses7-9.

Conditioned responses in rodents can be measured by assays such as conditioned place preference and conditioned place aversion10-14. These tests are relatively sensitive and specific for pain.

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However, they are time and labor intensive, and they do not provide real-time readouts. Thus, they are less useful as direct behavioral correlates for neurophysiological recordings. Meanwhile, unconditioned nociceptive responses are typically measured as nocifensive withdrawal

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behaviors5,7,8,15. Withdrawal behaviors can be elicited by either a thermal or mechanical stimulus. A classic method for testing withdrawal behavior in response to thermal stimulus is the Hargreaves’ test, also known as the Plantar Test, which assesses the time it takes for a rodent to withdraw its foot in response to an infra-red thermal stimulus5. While Hargreaves’ test has high inter-subject and intra-subject reproducibility, it is not highly time-sensitive, as withdrawal times

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are recorded on the scale of seconds. Meanwhile, nociceptive response to mechanical stimulus is

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typically measured as the force required to elicit withdrawal to a stimulus, either in naïve rodents

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or rodents with chronic pain7,8,14,16,17. Such measurements are labor intensive and are dependent

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on the experience of the experimenter, and hence can result in inter-experimenter variability. Furthermore, most of these tests cannot assay nociceptive response in rodents on highly sensitive

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time scales.

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Recently, there has been an explosion of new techniques for measuring neural activities in vivo, such as single unit or field recordings using invasive or surface electrodes, or single or two-photon

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calcium imaging. In order to successfully incorporate these techniques in the investigation of pain mechanisms, it will be important to reliably correlate nociceptive behavior with neural activities,

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on precise time scales.

Here, we present a pain detection device, based on a touch electrical circuit, which allows automated measures of paw withdrawal time in response to a noxious mechanical stimulus. We

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show that this method has high intra- and inter-subject reproducibility. This method also allows the assessment of nociceptive responses on millisecond scales, appropriate for in vivo

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electrophysiological studies in rodents.

EXPERIMENTAL PROCEDURE

Device Construction

This prototype pain detection device is consisted of an input interface, a circuit PCB, the batteries,

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an output interface, and an outer case (enclosure) (Figure 1). The key component of the device is

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the circuit PCB which was designed using DipTrace (Novarm Ltd.). Its function is detecting a

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touch input signal and generating a digital output. The input signal is pre-amplified, then put

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through a bridge rectifier, a smoothing capacitor, an amplifier and finally a comparator in order to convert the analog input signal into a digital output signal indicating contact or non-contact with

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the touch interface of the device (Figure 2).

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The bare PCB was printed using the ProtoMat D104 (LPKF Laser and Electronics). This circuit uses multiple surface mounted device (SMD) resistors with values of 100 Ω and 1 kΩ (RK73G2B

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series, KOA Speer Electronics, Inc.) and a single 22 µF SMD capacitor (F93 series, AVX). Additionally, a bridge rectifier integrated circuit (DB103, Rectron Semiconductor) was used, and

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amplifiers used in the circuit are instrumentation amplifiers (AD620ANZ, Analog Devices).

Assembly and soldering were done by hand. A 1/8” drill chuck shank (CML Supply) was electrically connected to the input of the circuit to allow for easy loading of needles (or any

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alternative metal piece) into the collet for touch sensing. The output of the device was electrically connected to a female BNC connector for simple connection to sensing or recording equipments. The device enclosure was designed in Blender (Blender Foundation) and 3D printed using a Form

the printed circuit board, two 9V batteries, and a BNC port.

Circuit Probing

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2 3D printer (Formlabs) with clear resin and .05 mm thickness. The enclosure encases the collet,

The Circuit was probed using a TBS1000B series Digital Storage Oscilloscope (Tektronix). To

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prevent damage and loading effects to the circuit while probing, a voltage follower circuit was

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used to act as a buffer between the device circuit and the probe. This buffer prevents any

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interference in sensing the true behavior of the circuit.

Animal

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All animal care and experimental procedures of this study were approved by the New York

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University School of Medicine (NYUSOM) Institutional Animal Care and Use Committee

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(IACUC) as consistent with the National Institute of Health (NIH) Guide for the Care and Use of Laboratory Animals to ensure minimal animal use and discomfort. Male Sprague-Dawley rats

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were purchased from Taconic Farms, Albany, NY and kept at Mispro Biotech Services Facility in the Alexandria Center for Life Science, with controlled humidity, temperature, and 12 hr (6:30

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AM to 6:30 PM) light-dark cycle. Food and water were available ad libitum. Animals arrived to the animal facility at 250 to 300 grams and were given about 14 days to adjust to the new environment prior to any experiment.

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Complete Freund’s Adjuvant (CFA) administration To induce chronic inflammatory pain, 0.1 ml of CFA (mycobacterium tuberculosis, SigmaAldrich) was suspended in an oil-saline (1:1) emulsion and injected subcutaneously into the plantar

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aspect of the hind paw18. Behavioral testing occurred 14 days after CFA injection.

Noxious stimulation and detection

A freely moving animal was placed over a mesh table. A needle (of varying gauge) was placed in the touch-circuit device, and an experimenter used the device to prick the hind paw of the animal

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through openings in the mesh table. With each gauge of needle, the experiment was repeated 10-

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15 trials, with inter-trial interval of at least 1 minute to avoid sensitization. The response of that

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animal to each stimulus was calculated based on the average withdrawal latency of all the trials.

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For neural recordings, at least 30 trials were delivered in a similar fashion for each recording

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session.

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Electrode implant and surgery

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Tetrodes were constructed from four twisted 12.7 µm polyimide-coated microwires (Sandvik) and mounted in an eight tetrode VersaDrive (Neuralynx)19-21. Electrode tips were plated with gold to

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reduce electrode impedances to 100–500 kΩ at 1 kHz. Rats were anesthetized with isoflurane (1.5– 2%). The skull was exposed and a 3-mm-diameter hole was drilled above the target region. A

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durotomy was performed before tetrodes were slowly lowered unilaterally into the S1 with the stereotaxic apparatus. Coordinates for S1 tetrode implants were: AP -1.5 mm, ML +3.0 mm, and DV -1.5 mm. The drive was secured to the skull screws with dental cement.

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In vivo electrophysiological recordings As described previously19,20, before stimulation, animals with chronic tetrode implants were given 30 min to habituate to a recording chamber over a mesh table. Noxious stimulation was delivered

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by needles mounted on the pain detection device. Stimulation was applied to the plantar surface of the hind paw contralateral to the brain recording site in freely moving rats. Noxious stimulation was terminated by paw withdrawals. All recording sessions consisted of approximately 30 trials with variable inter-trial intervals. A video camera (HC-V550, Panasonic) was used to record the experiment. Both the video camera and touch circuit were used to record the timestamp of each

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needle prick stimulus. For video recording, two flash led lights were used to synchronize the video

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camera and neural recording devices. The touch circuit board output the touch and withdrawal

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timestamps automatically to a neural recording digital input channel through TTL pulse. Long

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inter-trial intervals between trials (~45-60s) and 3-4 hour breaks between sessions were used to

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avoid sensitization. No behavioral sensitization or physical damage to the paw was observed.

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Neural data collection and preprocessing

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Tetrodes were lowered in steps of 60 µm before each day of recording. The neuronal activity and the onset of pin prick stimulation were simultaneously recorded with acquisition equipment (Open

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Ephys) via an RHD2132 amplifier board (Intan Technologies). Signals were monitored and recorded from 32 low-noise amplifier channels at 30 kHz, band-passed filtered (0.3 to 7.5 kHz).

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To get spike activity, the raw data were high-pass filtered at 300 Hz with subsequent thresholding and offline sorting by commercial software (Offline Sorter, Plexon). The threshold was lower than the 3-Sigma peak heights line and optimized manually based on the signal to noise ratio. The features of three valley electrodes were used for spike sorting. Trials were aligned to the initiation

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of the peripheral stimulus to compute the PSTH for each single unit using MATLAB (Mathworks). A total of 39 neurons were recorded from one rat.

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Statistical Analysis For behavioral analysis, Welch’s t test was used to compare the withdrawal latencies to different stimuli. The results of behavioral experiments were given as means ± SEMs. For neuronal spike analysis, we calculated peri-stimulus time histograms (PSTH), using a 5 s range before and after peripheral stimulus and a bin size of 100 ms. The number of spikes in each stimulus-aligned bin

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was averaged across all trials to create the PSTH. We then calculated basal spontaneous firing rate

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for each neuron to be the average of the PSTH bins before stimulus onset, and peak pain-evoked

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firing rate to be the maximum value of the PSTH after stimulus onset (within 5 s from the

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stimulus).

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To define a neuron that altered its firing rate in response to a peripheral stimulus, we used the

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method described previously20-22. The baseline mean is calculated by the average of the PSTH bins before stimulus onset, with standard deviation of the PSTH bins before stimulus onset. To calculate

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the Z scored firing rate, we used the following equation: Z = (FR − mean of FRb)/standard deviation of FRb, where FR indicates the firing rate for each bin and FRb indicates the baseline firing rate

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before stimulus onset. To define a pain-responsive neuron, we used the following criteria: (1) the

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absolute value of the Z scored firing rate of least one time bin after stimulation must be ≥2.5, and (2) if the first criterion is passed, at least the next two bins must be >1.645. These criteria must be fulfilled within 3 s after the peripheral stimulus.

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RESULTS

We developed a new electronic touch circuit device to automatically and precisely detect the onset

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and offset of the paw withdrawal response to a mechanical stimulus. The signal input to the touch detection circuit is in contact with the conductive touch interface loaded into the device (e.g. a 27 G needle). Any conductive material such as a metal rod will activate the circuit when in physical contact with the conductive touch interface of the device (animal tissues such as skin), but non-

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conductive materials (e.g. plastic, rubber, etc.) will not.

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The touch input signal was pre-amplified. The pre-amplified signal of the red trace showed that

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when the contact between the needle and the rodent paw was detected using a 27 G needle, the

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signal demonstrated a consistent oscillating profile. The proceeding stages of the circuit must convert this signal oscillation to a consistent digital signal shown in the blue trace (the output)

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where the height of the signal indicated the contact (Figure 3A). The bridge rectifier and smoothing

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capacitor can dramatically attenuate these oscillations (Figure 3B). Those smoothed ripples were

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then removed by the 2nd stage amplifier and the signal quickly reached saturation. The discharge seen at the end of the red trace was due to the discharging of the same capacitor that smoothed the

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signal. The slower the capacitor discharges, the smaller the ripples, but also the longer the duration of the final discharge. Smaller ripples allow the analog to digital conversion to be more resistant

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to signal noise, but it could also prolong the latency to detect the loss of contact (Figure 3C). Due to the smoothing capacitor, a compromise must be met with accurate touch detection and removal of the dramatic oscillations for reliable outputs. The capacitor charges very quickly, providing almost instant detection of the touch onset. The time difference between the beginning of

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oscillations at the preamplifier stage indicating contact in the red trace and the final output seen in blue was less than the sampling rate of the oscilloscope (i.e. 0.4 ms) (Figure 3D). This difference was larger when the capacitor discharged (Figure 3E), with the difference in offset of touch

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between the preamplifier stage in red and the final output varying based on the comparator threshold setting, capacitor and resistor settings, etc. The offset delays are respectively 0.116 s, 0.120 s, 0.120 s, and 0.121 s (Figure 3A and 3E). The mean and standard deviation of these observations is 0.119 ± .002 s. The observed offset values are tightly clustered around the mean and agree with the theoretical value within 5 ms, suggesting the error is systematic. Because these

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errors are systematic rather than random, accurate timestamps for onset and offset can be acquired

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by subtracting these differences from the final output onset and offset times.

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A collet in this prototype was allowed for the replacement of different gauge needles. A lower gauge needle, with a larger puncture area, when applied to the hind paw of rats, could cause higher

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intensity pain, as reflected by a shorter withdraw latency. Our results showed that this touch device

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could detect withdrawal latency that correlated with different needle gauges (Figure 4). Two

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different experimenters independently measured withdrawal latency using different gauge needles. Data collected by Experimenter 1 (Figure 4A) showed statistically significant differences between

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30 G and 27 G needles (n= 4-7 rats; p = 0.0011, t = 5.517, df = 6.561, Welch’s t test), between 27 G and 23 G needles (n= 4-7; p = 0.0003, t = 7.428, df = 5.868, Welch’s t test), and between 23G

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and 18G needles (n= 4-7; p = 0.0025, t = 4.325, df = 7.989, Welch’s t test). Data collected by Experimenter 2 (Figure 4B) also showed statistically significant differences between 30 G and 27 G needles (n= 4 rats; p = 0.0156, t = 3.34, df = 6, Welch’s t test), between 27 G and 23 G needles (n= 4; p = 0.0010, t = 5.955, df =6, Welch’s t test), and between 23G and 18G needles (n= 4; p =

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0.0246, t = 2.98, df = 6, Welch’s t test). A two-way ANOVA was used to compare withdrawal latencies for different gauge needles between the two independent experimenters. While needle gauge was a significant source of variation in the data (p<0.0001), identity of the experimenter

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was not a significant source of variation (p = 0.549), demonstrating reproducibility of results characteristic of the use of this device. Data are represented as mean ± SEM. In addition, the introduction of chronic pain through CFA injection induced a measurable difference in the withdrawal latency. The difference in the withdrawal latency when applying 27 G needles was also statistically significantly different between naïve rats and rats with chronic pain, suggesting

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that this device can be used to quantify chronic pain as well (Figure 5; n= 4 rats, 8; p < 0.0001, t =

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7.606, df = 10, unpaired t test). Data are represented as mean ± SEM.

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Finally, we show that this pain detection device can be used to provide accurate time stamps for in vivo electrophysiological recordings (Figure 6). A total of 39 neurons were recorded. We

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compared the analysis of the same recordings based on our pain detection device vs. video camera.

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The upper PSTH is derived using noxious (27 G needle) stimulus onset times from a video

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analysis. As can be seen, there is a time lag in the PSTH constructed based on video analysis. The mean lag of the device compared with video analysis across all trials is -0.1942± 0.0723 s. In fact,

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the analysis of this PSTH indicates a non-responsive neuron by the response criteria (see Methods for a description of pain-responsive neurons.)20. The lower PSTH was constructed using noxious

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stimulus onset times from the pain detection device, and indicated a negatively responding neuron. This discrepancy is due to the decrease in neuronal activity immediately before the onset time, which was inaccurately determined by video analysis. Additionally, the variation in the firing rates (FR) is noticeably smaller in the PSTH derived from our pain detection device compared with the

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video analysis, especially within 3 seconds after the stimulus onset. The time stamp provided by our device is more accurate than the time stamp provided by the camera recording for the onset and offset of the stimulus. In addition, unlike the video recording, which requires manual review, system

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neurophysiological recordings.

DISCUSSION

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The goal of our study is to develop an automated method to assay nociceptive responses in rodents.

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Our results show that our novel pain detection device can achieve this goal. This device allows for

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the measurement of peripheral withdrawal response to a mechanical noxious stimulus with

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millisecond time resolution, and the performance is highly reproducible. In addition, we show that this device can be used not only to quantitate nociceptive responses, but can also be used to provide

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time stamps for in vivo electrophysiological recordings.

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There are two major advances in our methodology. First, our pain detection device provides automated measures for nociception. Previous studies of nociceptive responses, particularly in

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response to mechanical pain, are highly dependent on the skills of the experimenter and can lead to inter-experimental variability23-26. For example, the classic up-down method frequently used to

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assess the withdrawal threshold for mechanical pain, requires training to target the same areas of the paw8,27. A current automated device to measure mechanical nociceptive responses is the electric von Frey device. While both automated von Frey and our touch circuit device can provide readouts for pain response, there are significant differences. von Frey filaments are not by

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themselves noxious, and thus they can be used to index hypersensitivity to non-noxious stimulation, such as hyperalgesia or allodynia in animals with chronic pain. These filaments cannot be used to assess acute pain response in naïve or healthy animals. Our device, however, can be

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used with both non-noxious (blunt tip needles) or noxious stimuli (sharp needles). Thus, in addition to providing information on hyperalgesia or allodynia, our device can uniquely provide information on acute mechanical nociception. Furthermore, our device is easy to apply even in highly mobile animals, as its performance requires less than a second of immobility of the animal, whereas von Frey assays require the animals to stay immobile for a longer period of time. In

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addition, our device dramatically decreases the amount of time involved in a mechanical

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nociceptive assay, and its ability to input data directly to the computer further reduces the

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experimental burden. A second important innovation in our study is the precise timing achieved

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with our pain detection device. In our study, we are able to record the withdrawal response with millisecond time resolution, which cannot be accomplished with any currently available pain

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delivery and measurement devices. Such time resolution is critical for in vivo neurophysiological

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studies. Thus, our device can provide the accurate time of onset of noxious stimulus as well as the

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time of offset of such stimulus or withdrawal time. By providing these two accurate time stamps, we can better understand pain perception and response, in both the peripheral or central nervous

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system.

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A limitation of our study is that the device we invented can only be used for mechanical stimulus. Thermal pain can be measured by Hargreaves’ test, but not with the same time resolution. Thus, additional innovations are needed to provide temporally precise measures of behavioral responses to thermal stimuli. Another limitation of our method is that this is a measure of peripheral

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nociceptive response, not central pain response. Pain is far more complex than the peripheralspinal reflex can indicate. Thus, future studies are needed to develop more accurate and precise

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central readouts for pain in rodents.

It should be noted that the actual force of experimental delivery ultimately translates to the amount of noxious input an animal would experience, which is in turn is reported as the latency to withdrawal. Thus, it is possible that an experimenter who pushes the needle more forcefully may generate a greater noxious input with a 27 G needle than another experimenter more gently pushing

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the same needle. The data in Figure 4 and 5 are produced by two independent experimenters in our

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lab who pushed with similar forces, and these figures are used to demonstrate the quantitative

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reporting capability of our device for nociceptive responses. However, these are not absolute

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values. Future improvements on this device may include a mechanical spring to ensure that our device can deliver similar forces each time. It should also be noted that even with equal amounts

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of externally applied force, the peripheral nociceptive experience of the experimental animal may

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still be different, due to variations in skin thickness, proximity of nerve endings to the site of

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stimulation, and the condition of the supporting table (wetness, etc). Nevertheless, our device, through its electrical touch circuit, can be used to ultimately detect the amount of noxious input an

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animal would experience.

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While we have tried this device on rodents in the current study, our system may be used to assess peripheral nociceptive responses in non-human primates as well as human subjects. In humans, pain can often be assessed by higher order cognitive feedback such as verbal reports or gestures. However, it may be interesting in future studies to correlate central cognitive feedback with

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peripheral reflex to understand fully the relationship between nociception and pain, or between peripheral and central pain responses. Furthermore, this device or related devices which accurately measure peripheral nociceptive responses may be helpful in cases where subjects are unable to

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report pain, such as patients with limited mental capacity or dementia1-3.

In conclusion, in this study we have invented an automated method to measure peripheral nociceptive responses. This method provides accurate measures for nociceptive intensity, and it also provides precise time stamps for on- and offsets of noxious stimulations to allow behavioral

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correlation for neurophysiological studies.

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ACKNOWLEDGEMENTS

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The work was supported by NIH grants GM115384 (J.W.) and NS100016 (J.W.), National Natural Science Foundation of China (8177041362 H.Z.) and China Scholarship Council (201606370208,

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H.Z.).

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AUTHOR CONTRIBUTIONS

JD and JW designed the pain detection device and the experiments. JD and QZ constructed the

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pain detection device. JD, HZ, AS, and QZ performed electrophysiological recording and behavior

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experiments. JD and AS performed the statistical analysis. JW wrote the manuscript.

DECLARATION OF INTERESTS A patent has been filed, under the title “NYU OIL ID WAN02-06: Provisional Application 62/725,744 : Mechanical pain detection device.”

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REFERENCES

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FIGURE LEGENDS

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Fig. 1. Block diagram and complete assembly of the prototype pain detection device. (A) The input

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from the skin contact is converted to a digital signal indicating contact or non-contact and sent to

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a computer for digital acquisition. (B) Internal components for the pain detection device. A collet holds a needle, and allows for the use of different needle gauges, replacement of dull or used

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needles, and the use of any conductor to be used as the touch interface. A BNC connector is used

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for the output signal to allow easy connection with peripheral data acquisition equipment. (C)

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Complete assembly of the prototype device in the 3D printed enclosure.

Fig. 2. Circuit diagram for the pain detection device. It is consisted of a pre-amplifier, bridge rectifier, smoothing ripple wave, second stage amplifier, and comparator. The signal input to the touch detection circuit is contact with the conductive touch interface loaded into the device (e.g. 27G needle). Any conductive material such as a figure or metal rod will activate the circuit when 17

in physical contact with the conductive touch interface of the device, but non-conductive materials (e.g. plastic, rubber, etc.) will not. The input signal is pre-amplified, then put through a bridge rectifier, smoothing capacitor, amplifier and finally a comparator in order to convert the analog

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input signal into a digital output signal indicating contact or non-contact with the touch interface of the device.

Fig. 3. Input-output relationship of the touch device. All blue traces show the final digital output of the device. A 27 G needle was used to detect contact with the animal’s skin. (A) The red

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oscillation trace represents the output of the pre-amplifier. (B) The output of the smoothing

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capacitor is shown in the red trace. (C) The red trace is the output of the 2nd stage amplifier. (D)

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Details of the rising phase of the preamplifier output (red trace) and final output trace (blue trace).

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(E) The time difference in the offset between the preamplifier stage in red and the final digital

D

output signal in blue.

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Fig. 4. The paw withdrawal latency can be measured accurately by the pain detection device. (A)

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Data collected by Experimenter 1 had statistically significant differences in withdrawal latency determined using the touch device between 30 G and 27 G needles (n= 4-7 rats; p = 0.0011, t =

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5.517, df = 6.561, Welch’s t test), between 27 G and 23 G needles (n= 4-7; p = 0.0003, t = 7.428, df = 5.868, Welch’s t test), and between 23G and 18G needles (n= 4-7; p = 0.0025, t = 4.325, df =

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7.989, Welch’s t test). (B) Data collected by Experimenter 2 (Figure 4B) also had statistically significant differences between 30 G and 27 G needles (n= 4 rats; p = 0.0156, t = 3.34, df = 6, Welch’s t test), between 27 G and 23 G needles (n= 4; p = 0.0010, t = 5.955, df =6, Welch’s t test), and between 23G and 18G needles (n= 4; p = 0.0246, t = 2.98, df = 6, Welch’s t test). (C) A two-

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way ANOVA was used to compare withdrawal latencies for different gauge needles between the two independent experimenters. Data are represented as mean ± SEM.

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Fig. 5. The introduction of chronic pain through CFA injection induced a measurable difference in the withdrawal latency (n= 4 rats, 8; p < 0.0001, t = 7.606, df = 10, unpaired t test). The withdrawal latency as measured by the pain detection device can be used to distinguish naïve rats from rats with chronic pain. Data are represented as mean ± SEM.

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Fig. 6. Comparisons of peri-stimulus timed histograms (PSTHs) constructed using the onset times

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derived through video analysis and touch device. Time 0 indicates the onset (i.e. application) of

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noxious stimulation from a 27 G needle. FR: firing rates in spikes per seconds. The upper PSTH

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is derived using noxious stimulus onset times from video analysis, and indicates a non-responsive neuron by the response criteria (see Methods for a description of pain-responsive neurons). The

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lower PSTH constructed using noxious stimulus onset times from the touch device indicates a

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CC

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from one rat.

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negatively responding neuron. These PSTHs were selected from a total of 39 neurons recorded

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Spring-loaded needle (or acutator)

Touch Circuit

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A

A

A

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PT

B

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Digital Acquisition

Pre-amplifier

Bridge Rectifier

+

Smoothing Amplifier Comparator Ripple Wave

Output

Touch

_

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8 7

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4 3

-3

-2

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1 1

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Voltage (V)

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1 0 -1.5

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Voltage (V)

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0 -0.5 -0.4 -0.3 -0.2 -0.1

0

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300 250 200 150

30 G

27 G

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Withrawal Latency (ms)

Withrawal Latency (ms)

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Withrawal Latency (ms)

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300 250 200

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30 G

27 G

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350 Experimenter 1 Experimenter 2

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Withrawal Latency (ms)

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+ CFA - CFA

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Video

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FR

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0

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Touch Circuit

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FR

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time (s)

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-1

time (s)