The spontaneous component of neuropathic pain (NP) has not been explored sufficiently with neuroimaging techniques, given the difficulty to coax out the brain components that sustain background ongoing pain. Here, we address for the first time the correlates of this component in an fMRI study of a group of eight patients suffering from diabetic neuropathic pain and eight healthy control subjects. Specifically, we studied the functional connectivity that is associated with spontaneous neuropathic pain with spatial independent component analysis (sICA). Functional connectivity analyses revealed a cortical network consisting of two anti-correlated patterns: one includes the left fusiform gyrus, the left lingual gyrus, the left inferior temporal gyrus, the right inferior occipital gyrus, the dorsal anterior cingulate cortex bilaterally, the pre and postcentral gyrus bilaterally, in which its activity is correlated negatively with pain and positively with the controls; the other includes the left precuneus, dorsolateral prefrontal, frontopolar cortex (both bilaterally), right superior frontal gyrus, left inferior frontal gyrus, thalami, both insulae, inferior parietal lobuli, right mammillary body, and a small area in the left brainstem, in which its activity is correlated positively with pain and negatively with the controls. Furthermore, a power spectra analyses revealed group differences in the frequency bands wherein the sICA signal was decomposed: patients' spectra are shifted towards higher frequencies. In conclusion, we have characterized here for the first time a functional network of brain areas that mark the spontaneous component of NP. Pain is the result of aberrant default mode functional connectivity.

Several studies have attempted to characterize morphological brain changes due to chronic pain. Although it has repeatedly been suggested that longstanding pain induces gray matter modifications, there is still some controversy surrounding the direction of the change (increase or decrease in gray matter) and the role of psychological and psychiatric comorbidities. In this study, we propose a novel, network-oriented, meta-analytic approach to characterize morphological changes in chronic pain. We used network decomposition to investigate whether different kinds of chronic pain are associated with a common or specific set of altered networks. Representational similarity techniques, network decomposition and model-based clustering were employed: i) to verify the presence of a core set of brain areas commonly modified by chronic pain; ii) to investigate the involvement of these areas in a large-scale network perspective; iii) to study the relationship between altered networks and; iv) to find out whether chronic pain targets clusters of areas. Our results showed that chronic pain causes both core and pathology-specific gray matter alterations in large-scale networks. Common alterations were observed in the prefrontal regions, in the anterior insula, cingulate cortex, basal ganglia, thalamus, periaqueductal gray, post- and pre-central gyri and inferior parietal lobule. We observed that the salience and attentional networks were targeted in a very similar way by different chronic pain pathologies. Conversely, alterations in the sensorimotor and attention circuits were differentially targeted by chronic pain pathologies. Moreover, model-based clustering revealed that chronic pain, in line with some neurodegenerative diseases, selectively targets some large-scale brain networks. Altogether these findings indicate that chronic pain can be better conceived and studied in a network perspective.

This article investigates the functional connectivity patterns of the nucleus accumbens (NAcc) in 18 healthy participants using a resting state functional connectivity (rsFC) protocol. Also, a meta-analytic connectivity modeling (MACM) was used to characterize patterns of functional coactivations involving NAcc: The results of a structure-based meta-analyses of 57 fMRI and PET studies were submitted to activation likelihood estimation analysis to estimate consistent activation patterns across the different imaging studies. The results of the combined rsFC and MACM analyses show that spontaneous activity in NAcc predicts activity in regions implicated in reward circuitries, including orbitomedial prefrontal cortex, globus pallidus, thalamus, midbrain, amygdala, and insula. This confirms the key role of NAcc in the mesocorticolimbic system, which integrates inputs from limbic and cortical regions. We also detected activity in brain regions having few or no direct anatomical connections with NAcc, such as sensorimotor cortex, cerebellum, medial and posterior parietal cortex, and medial/inferior temporal cortex, supporting the view that not all functional connections can be explained by anatomical connections but can also result from connections mediated by third areas. Our rsFC findings are in line with the results of the structure-based meta-analysis: MACM maps are superimposable with NAcc rsFC results, and the reward paradigm class is the one that most frequently generates activation in NAcc. Our results overlap considerably with recently proposed schemata of the main neuron systems in the limbic forebrain and in the anterior part of the limbic midbrain in rodents and nonhuman primates.