Altered evoked low-frequency connectivity from SI to ACC following nerve injury in rats

Inhibitory gamma-aminobutyric acidergic neurons in the anterior cingulate cortex participate in the comorbidity of pain and emotion

Pain is often comorbid with emotional disorders such as anxiety and depression. Hyperexcitability of the anterior cingulate cortex has been implicated in pain and pain-related negative emotions that arise from impairments in inhibitory gamma-aminobutyric acid neurotransmission. This review primarily aims to outline the main circuitry (including the input and output connectivity) of the anterior cingulate cortex and classification and functions of different gamma-aminobutyric acidergic neurons; it also describes the neurotransmitters/neuromodulators affecting these neurons, their intercommunication with other neurons, and their importance in mental comorbidities associated with chronic pain disorders. Improving understanding on their role in pain-related mental comorbidities may facilitate the development of more effective treatments for these conditions. However, the mechanisms that regulate gamma-aminobutyric acidergic systems remain elusive. It is also unclear as to whether the mechanisms are presynaptic or postsynaptic. Further exploration of the complexities of this system may reveal new pathways for research and drug development.

Spared ulnar nerve injury results in increased layer III-VI excitability in the pig somatosensory cortex

This study describes cortical recordings in a large animal nerve injury model. We investigated differences in primary somatosensory cortex (S1) hyperexcitability when stimulating injured and uninjured nerves and how different cortical layers contribute to S1 hyperexcitability after spared ulnar nerve injury. We used a multielectrode array to record single-neuron activity in the S1 of ten female Danish landrace pigs. Electrical stimulation of the injured and uninjured nerve evoked brain activity up to 3 h after injury. The peak amplitude and latency of early and late peristimulus time histogram responses were extracted for statistical analysis. Histological investigations determined the layer of the cortex in which each electrode contact was placed. Nerve injury increased the early peak amplitude compared with that of the control group. This difference was significant immediately after nerve injury when the uninjured nerve was stimulated, while it was delayed for the injured nerve. The amplitude of the early peak was increased in layers III-VI after nerve injury compared with the control. In layer III, S1 excitability was also increased compared with preinjury for the early peak. Furthermore, the late peak was significantly larger in layer III than in the other layers in the intervention and control group before and after injury. Thus, the most prominent increase in excitability occurred in layer III, which is responsible for the gain modulation of cortical output through layer V. Therefore, layer III neurons seem to have an important role in altered brain excitability after nerve injury.

A neural circuit for alcohol withdrawal-induced hyperalgesia in a nondependent state

Alcohol use disorder is highly prevalent worldwide, with characteristically severe pain sensitivity during withdrawal. Here, we established a mouse model of hyperalgesia during ethanol withdrawal (EW) before addiction to investigate the window for onset and underlying mechanisms. Viral tracing with in vivo microendoscopic and two-photon calcium imaging identified a circuit pathway from dorsal hippocampal CA1 glutamatergic neurons (dCA1Glu) to anterior cingulate cortex glutamatergic neurons (ACCGlu) activated in EW mice with hyperalgesia. Chemogenetic inhibition of this pathway can alleviate hyperalgesia in EW mice, whereas artificial activation recapitulates EW-induced hyperalgesia in naïve mice. These findings demonstrate that the dCA1Glu → ACCGlu neuronal pathway participates in driving EW-induced hyperalgesia before ethanol dependence in mice.

Decoding pain from brain activity

Pain is a dynamic, complex and multidimensional experience. The identification of pain from brain activity as neural readout may effectively provide a neural code for pain, and further provide useful information for pain diagnosis and treatment. Advances in neuroimaging and large-scale electrophysiology have enabled us to examine neural activity with improved spatial and temporal resolution, providing opportunities to decode pain in humans and freely behaving animals. This topical review provides a systematical overview of state-of-the-art methods for decoding pain from brain signals, with special emphasis on electrophysiological and neuroimaging modalities. We show how pain decoding analyses can help pain diagnosis and discovery of neurobiomarkers for chronic pain. Finally, we discuss the challenges in the research field and point to several important future research directions.