The degree and salience of pain have been known to be constantly monitored and modulated by the brain. In the case of maladaptive neural responses as reported in centralized pain conditions such as complex regional pain syndrome (CRPS), the perception of pain is amplified and remains elevated even without sustained peripheral pain inputs. Given that the attentional state of the brain greatly influences the perception and interpretation of pain, we investigated the role of the attention network and its dynamic interactions with other pain-related networks of the brain in CRPS. We examined alterations in the intra- and inter-network functional connectivities in 21 individuals with CRPS and 49 controls. CRPS-related reduction in intra-network functional connectivity was found in the attention network. Individuals with CRPS had greater inter-network connectivities between the attention and salience networks as compared with healthy controls. Furthermore, individuals within the CRPS group with high levels of pain catastrophizing showed greater inter-network connectivities between the attention and salience networks. Taken together, the current findings suggest that these altered connectivities may be potentially associated with the maladaptive pain coping as found in CRPS patients.
Val66Met, a naturally occurring polymorphism in the human brain-derived neurotrophic factor (BDNF) gene resulting in a valine (Val) to methionine (Met) substitution at codon 66, plays an important role in neuroplasticity. While the effect of the BDNF Val66Met polymorphism on local brain structures has previously been examined, its impact on the configuration of the graph-based white matter structural networks is yet to be investigated. In the current study, we assessed the effect of the BDNF polymorphism on the network properties and robustness of the graph-based white matter structural networks. Graph theory was employed to investigate the structural connectivity derived from white matter tractography in two groups, Val homozygotes (n = 18) and Met-allele carriers (n = 55). Although there were no differences in the global network measures including global efficiency, local efficiency, and modularity between the two genotype groups, we found the effect of the BDNF Val66Met polymorphism on the robustness properties of the white matter structural networks. Specifically, the white matter structural networks of the Met-allele carrier group showed higher vulnerability to targeted removal of central nodes as compared with those of the Val homozygote group. These findings suggest that the central role of the BDNF Val66Met polymorphism in regards to neuroplasticity may be associated with inherent differences in the robustness of the white matter structural network according to the genetic variants. Furthermore, greater susceptibility to brain disorders in Met-allele carriers may be understood as being due to their limited stability in white matter structural connectivity.
This study identified the regional pattern of brain perfusion that distinguished depressed from nondepressed PD patients. Hyperperfusion in the occipital areas and hypoperfusion in the fronto-temporo-limbic regions may be potential imaging biomarkers for depression in PD.
Brain network is organized to maximize the efficiency of both segregated and integrated information processing that may be related to human intelligence. However, there have been surprisingly few studies that focus on the topological characteristics of brain network underlying extremely high intelligence that is intellectual giftedness, particularly in adolescents. Here, we examined the network topology in 25 adolescents with superior intelligence (SI-Adol), 25 adolescents with average intelligence (AI-Adol), and 27 young adults with AI (AI-Adult). We found that SI-Adol had network topological properties of high global efficiency as well as high clustering with a low wiring cost, relative to AI-Adol. However, contrary to the suggested role that brain hub regions play in general intelligence, the network efficiency of rich club connection matrix, which represents connections among brain hubs, was low in SIAdol in comparison to AI-Adol. Rather, a higher level of local connection density was observed in SI-Adol than in AI-Adol. The highly intelligent brain may not follow this efficient yet somewhat stereotypical process of information integration entirely. Taken together, our results suggest that a highly intelligent brain may communicate more extensively, while being less dependent on rich club communications during adolescence.Intelligence is known as the general cognitive capability to reason, plan, solve problem, appraise, and learn quickly from experience 1 . Moreover, intelligence is strongly associated with behavioral patterns and important life outcomes, including health and longevity 2 .Since the earlier research which investigated the correlation between brain size and intelligence 3 , considerable efforts have been made to identify the neural basis underlying inter-individual differences in intelligence 4-7 . In the early days of research, the alterations in the fronto-parietal gray matter regions as an indexing marker for intelligence have attracted much attention, due to their implicated role in information processing 8 . However, as a growing number of studies have examined white matter connections and network metrics, integrative roles of the brain in networking multiple cortical and subcortical regions have become an increasing interest in investigating intelligence 4 . Recent evidence indicated that inter-individual differences in intelligence may be attributed to the global efficiency and strength of white matter connectivity network across the brain regions [9][10][11] . Furthermore, the relationships between intellectual ability and functional efficiency of brain network were more pronounced in the frontal and parietal regions [12][13][14] . Interestingly, the fronto-parietal regions along with the subcortical structures including the thalamus, putamen, and hippocampus are considered as highly inter-connected brain hubs, also referred to as "rich clubs" 5 . Connections between these rich clubs play a key role in promoting efficient information flow in the brain network, despite the high cost of ...
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