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Real-Time Detection of Acute Pain Signals Based on Spikes/LFP

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Handbook of Neuroengineering

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Abstract

Acute pain is triggered by noxious stimuli that induce changes in neural responses of specific neural circuits at both single neuron and population levels. Detecting acute pain signals may provide a closed-loop feedback signal for neuromodulation to achieve pain relief. Human neuroimaging studies have identified circuit changes in pain states, and brain regions identified by such methods include the primary somatosensory cortex (S1) and anterior cingulate cortex (ACC), which are thought to provide key information on sensory and affective components of pain, respectively. In animal and human studies, methods for detecting acute pain signals in real time have been developed based on invasive or noninvasive neural recordings. This chapter provides an overview of several statistical machine learning and signal processing approaches for detecting acute pain signals based on spikes and/or local field potentials (LFPs) recorded from freely behaving rats. To facilitate closed-loop neuroscience experiments or brain-machine interface (BMI), real-time computational consideration is emphasized. We present various detection strategies and illustrations using the in vivo electrophysiological recordings from the rat ACC and/or S1 and discuss important issues related to robust detection and closed-loop neuromodulation in future practice.

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Acknowledgements

The author likes to thank all coauthors who had contributed to previous publications. The work was supported by the NIH grant R01-NS100065 and NSF-CBET grant #1835000.

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Authors and Affiliations

  1. Department of Psychiatry, Department of Neuroscience and Physiology, Neuroscience Institute, School of Medicine, New York University, New York, NY, USA

    Zhe Sage Chen

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  1. Zhe Sage Chen
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Correspondence to Zhe Sage Chen .

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Editors and Affiliations

  1. Singapore Institute for Neurotechnology, National University of Singapore, Singapore, Singapore

    Nitish V. Thakor

Section Editor information

  1. N.1. Institute for Health, National University of Singapore, Singapore, Singapore

    Andrei Dragomir

  2. Department of Biomedical Engineering, University of Houston, Houston, USA

    Andrei Dragomir

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Chen, Z.S. (2022). Real-Time Detection of Acute Pain Signals Based on Spikes/LFP. In: Thakor, N.V. (eds) Handbook of Neuroengineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-2848-4_72-2

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  • DOI: https://doi.org/10.1007/978-981-15-2848-4_72-2

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