Deciphering neuronal population codes for acute thermal pain

Abstract

Objective Pain is defined as an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage. Current pain research mostly focuses on molecular and synaptic changes at the spinal and peripheral levels. However, a complete understanding of pain mechanisms requires the physiological study of the neocortex. Our goal is to apply a neural decoding approach to read out the onset of acute thermal pain signals, which can be used for brain–machine interface. Approach We used micro wire arrays to record ensemble neuronal activities from the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC) in freely behaving rats. We further investigated neural codes for acute thermal pain at both single-cell and population levels. To detect the onset of acute thermal pain signals, we developed a novel latent state-space framework to decipher the sorted or unsorted S1 and ACC ensemble spike activities, which reveal information about the onset of pain signals. Main results The state space analysis allows us to uncover a latent state process that drives the observed ensemble spike activity, and to further detect the ‘neuronal threshold’ for acute thermal pain on a single-trial basis. Our method achieved good detection performance in sensitivity and specificity. In addition, our results suggested that an optimal strategy for detecting the onset of acute thermal pain signals may be based on combined evidence from S1 and ACC population codes. Significance Our study is the first to detect the onset of acute pain signals based on neuronal ensemble spike activity. It is important from a mechanistic viewpoint as it relates to the significance of S1 and ACC activities in the regulation of the acute pain onset.

Ketamine reduces aversion in rodent pain models by suppressing hyperactivity of the anterior cingulate cortex

“…Stereotrodes were constructed from two twisted 12.7 µm polyimide-coated microwires (Sandvik) and mounted in a VersaDrive8 (Neuralynx) 8 , 67 . Electrode tips were plated with gold to reduce electrode impedances to 100–500 kΩ.…”

Closed-Loop Deep Brain Stimulation for Refractory Chronic Pain

“…sensory stimulation, arousal state, etc.). Single action potentials from S1 and ACC were used in a rodent model of acute thermal pain to decode a pain state defined through use of a Hidden Markov Model (Chen et al, 2017 ). In this experiment, signals from the population of single neurons used to computed baseline and pain states were not stable over even a few trials, making the chronic computation of a pain state untenable.…”

“…Animal studies also help to identify brain regions and candidate signals that may serve as affective biomarkers of pain perception. In a study recording single spikes from S1 and ACC of rats, a state space model was used to identify neuronal codes underlying acute painful thermal stimuli that produce a paw withdrawal reflex (Chen et al, 2017 ). One key insight from this study was that population spiking activity from S1 provides better sensitivity for acute pain prediction, while activity from ACC provides better specificity suggesting that a subset of neurons in ACC encode pain information.…”

Closed-Loop Deep Brain Stimulation for Refractory Chronic Pain

“…sensory stimulation, arousal state, etc.). Single action potentials from S1 and ACC were used in a rodent model of acute thermal pain to decode a pain state defined through use of a Hidden Markov Model (Chen et al, 2017). In this experiment, signals from the population of single neurons used to computed baseline and pain states were not stable over even a few trials, making the chronic computation of a pain state untenable.…”

“…Animal studies also help to identify brain regions and candidate signals that may serve as affective biomarkers of pain perception. In a study recording single spikes from S1 and ACC of rats, a state space model was used to identify neuronal codes underlying acute painful thermal stimuli that produce a paw withdrawal reflex (Chen et al, 2017). One key insight from this study was that population spiking activity from S1 provides better sensitivity for acute pain prediction, while activity from ACC provides better specificity suggesting that a subset of neurons in ACC encode pain information.…”