Pronociceptive effects mediated by adenosinergic A2A activity at the nucleus accumbens, but what about the autonomic nervous system?

Functional brain networks and neuroanatomy underpinning nausea severity can predict nausea susceptibility using machine learning

KEY POINTS

Nausea is an adverse experience characterised by alterations in autonomic and cerebral function. Susceptibility to nausea is difficult to predict, but machine learning has yet to be applied to this field of study. The severity of nausea that individuals experience is related to the underlying morphology (shape) of the subcortex, namely of the amygdala, caudate and putamen; a functional brain network related to nausea severity was identified, which included the thalamus, cingulate cortices (anterior, mid- and posterior), caudate nucleus and nucleus accumbens. Sympathetic nervous system function and sympathovagal balance, by heart rate variability, was closely related to both this nausea-associated anatomical variation and the functional connectivity network, and machine learning accurately predicted susceptibility or resistance to nausea. These novel anatomical and functional brain biomarkers for nausea severity may permit objective identification of individuals susceptible to nausea, using artificial intelligence/machine learning; brain data may be useful to identify individuals more susceptible to nausea.

ABSTRACT

Nausea is a highly individual and variable experience. The central processing of nausea remains poorly understood, although numerous influential factors have been proposed, including brain structure and function, as well as autonomic nervous system (ANS) activity. We investigated the role of these factors in nausea severity and if susceptibility to nausea could be predicted using machine learning. Twenty-eight healthy participants (15 males; mean age 24 years) underwent quantification of resting sympathetic and parasympathetic nervous system activity by heart rate variability. All were exposed to a 10-min motion-sickness video during fMRI. Neuroanatomical shape differences of the subcortex and functional brain networks associated with the severity of nausea were investigated. A machine learning neural network was trained to predict nausea susceptibility, or resistance, using resting ANS data and detected brain features. Increasing nausea scores positively correlated with shape variation of the left amygdala, right caudate and bilateral putamen (corrected P = 0.05). A functional brain network linked to increasing nausea severity was identified implicating the thalamus, anterior, middle and posterior cingulate cortices, caudate nucleus and nucleus accumbens (corrected P = 0.043). Both neuroanatomical differences and the functional nausea-brain network were closely related to sympathetic nervous system activity. Using these data, a machine learning model predicted susceptibility to nausea with an overall accuracy of 82.1%. Nausea severity relates to underlying subcortical morphology and a functional brain network; both measures are potential biomarkers in trials of anti-nausea therapies. The use of machine learning should be further investigated as an objective means to develop models predicting nausea susceptibility.

Systematic review with meta-analysis: conditioned pain modulation in patients with the irritable bowel syndrome

BACKGROUND

Irritable bowel syndrome (IBS) is common and is characterised by recurrent abdominal pain, which is a major contributor to healthcare seeking. The neurobiological basis of this pain is incompletely understood. Conditioned pain modulation is a neuromodulatory mechanism through which the brain inhibits the nociceptive afferent barrage through the descending pathways. Reduced conditioned pain modulation has been implicated in the pathophysiology of IBS, although to date only in studies with relatively small sample sizes.

AIM

To clarify the relationship between conditioned pain modulation and IBS by undertaking a systemic review and meta-analysis METHODS: A systematic review of MEDLINE and Web of Science databases was searched (up to 10 May 2018). We included studies examining conditioned pain modulation in adults with IBS and healthy subjects. Data were pooled for meta-analysis to calculate the odds ratio and effect size of abnormal conditioned pain modulation in IBS, with 95% confidence intervals (CI).

RESULTS

The search strategy identified 645 studies, of which 13 were relevant and 12 met the inclusion criteria. Conditioned pain modulation in IBS patients vs healthy subjects was significantly reduced, odds ratio 4.84 (95% CI: 2.19-10.71, P < 0.0001), Hedges' g effect size of 0.85 (95% CI: 0.42-1.28, P < 0.001). There was significant heterogeneity in effect sizes (Q-test χ² = 52, P < 0.001, I² = 78.8%) in the absence of publication bias.

CONCLUSION

Conditioned pain modulation is significantly diminished in patients with IBS vs healthy controls. These data suggest that abnormal descending pathways may play an important pathophysiological role in IBS, which could represent an investigation and a therapeutic target in IBS.

Preliminary report: parasympathetic tone links to functional brain networks during the anticipation and experience of visceral pain

The mechanisms that underpin the anti-nociceptive effect of the parasympathetic nervous system (PNS) on visceral pain remain incompletely understood. We sought to describe the effect of resting parasympathetic tone on functional brain networks during the anticipation and experience of oesophageal pain. 21 healthy participants had their resting cardiac vagal tone (CVT), a validated measure of the PNS, quantified, and underwent functional magnetic resonance imaging during the anticipation and experience of painful oesophageal distention. The relationship between resting CVT and functional brain networks was examined using 11 hypothesis-driven nodes and network-based statistics. A network comprising all nodes was apparent in individuals with high resting CVT, compared to those with low CVT, during oesophageal pain (family wise error rate (FWER)-corrected p < 0.048). Functional connections included the thalamus-amygdala, thalamus-hypothalamus, hypothalamus-nucleus accumbens, amygdala-pallidum, pallidum-nucleus accumbens and insula-pallidum. A smaller network was seen during pain anticipation, comprising the amygdala, pallidum and anterior insula (FWER-corrected p < 0.049). These findings suggest that PNS tone is associated with functional brain networks during the anticipation and experience of visceral pain. Given the role of these subcortical regions in the descending inhibitory modulation of pain, these networks may represent a potential neurobiological explanation for the anti-nociceptive effect of the PNS.