The Positive Brain – Resting State Functional Connectivity in Highly Vital and Flourishing Individuals

Pohóczky

et al. 2020

IJMS

Somatostatin is an important mood and pain-regulating neuropeptide, which exerts analgesic, anti-inflammatory, and antidepressant effects via its Gi protein-coupled receptor subtype 4 (SST4) without endocrine actions. SST4 is suggested to be a unique novel drug target for chronic neuropathic pain, and depression, as a common comorbidity. However, its neuronal expression and cellular mechanism are poorly understood. Therefore, our goals were (i) to elucidate the expression pattern of Sstr4/SSTR4 mRNA, (ii) to characterize neurochemically, and (iii) electrophysiologically the Sstr4/SSTR4-expressing neuronal populations in the mouse and human brains. Here, we describe SST4 expression pattern in the nuclei of the mouse nociceptive and anti-nociceptive pathways as well as in human brain regions, and provide neurochemical and electrophysiological characterization of the SST4-expressing neurons. Intense or moderate SST4 expression was demonstrated predominantly in glutamatergic neurons in the major components of the pain matrix mostly also involved in mood regulation. The SST4 agonist J-2156 significantly decreased the firing rate of layer V pyramidal neurons by augmenting the depolarization-activated, non-inactivating K+ current (M-current) leading to remarkable inhibition. These are the first translational results explaining the mechanisms of action of SST4 agonists as novel analgesic and antidepressant candidates.

Section: Discussionsupporting

confidence: 64%

Characterization of Neurons Expressing the Novel Analgesic Drug Target Somatostatin Receptor 4 in Mouse and Human Brains

Pohóczky

et al. 2020

IJMS

“…Among these regions, right and left STG was strongly associated to social well-being according to a recent study (Kong, Xue, et al, 2016) and STG plays an important role social perception (Kanai et al, 2012; Yang et al, 2015). Also, by using SVM as a feature extraction technique instead of conventional statistical approaches, L MTG – L FusG connection was found as a reproduced result to discriminate flourishing (F. Goldbeck et al, 2018). FusG is widely known about its role in face perception (Grill-Spector et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…To objectively assess well-being, several neuroimaging studies have been performed to understand the neural correlates of well-being and it was reported that anterior cingulate cortex (ACC), orbitofrontal cortex (OFC), posterior cingulate cortex (PCC), superior temporal gyrus (STG) and thalamus was strongly associated to well-being and these regions are sub-components of default mode network (DMN) (see review (King, 2019)). This finding makes resting state functional connectivity (rsFC) based studies using fMRI (Kong, Liu, et al, 2015; Kong, Wang, et al, 2015; Kong, Wang, et al, 2016; Kong, Xue, et al, 2016; Luo et al, 2014; Luo et al, 2016; Luo et al, 2017; W. Sato et al, 2019) and fNIRS (F. Goldbeck et al, 2018) important to understand the underlying neural mechanisms of well-being.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Flourishing Levels of Individuals by Using Resting State fNIRS with Different Functional Connectivity Measures

Eken

2021

Preprint

Flourishing is an important criterion to assess wellbeing, however, controversies remain, particularly around assessing it with self-report measures. Due to this reason, to be able to understand the underlying neural mechanisms of well-being, researchers often utilize neuroimaging techniques. However, rather than individual answers, previous neuroimaging studies using statistical approaches provided an answer in average sense. To overcome these problems, we applied machine learning techniques to discriminate 43 highly flourishing from regular flourishing individuals by using a publicly available resting state functional near infrared spectroscopy (rs-fNIRS) dataset to get an answer in individual level. We utilized both Pearson’s correlation (CC) and Dynamic Time Warping (DTW) algorithm to estimate functional connectivity from rs-fNIRS data on temporo-parieto-occipital region as input to nine different machine learning algorithms. Our results revealed that by utilizing oxyhemoglobin concentration change with Pearson’s correlation (CC – ΔHbO) and deoxy hemoglobin concentration change with dynamic time warping (DTW – ΔHb), we could be able to classify flourishing individuals with 90 % accuracy with AUC 0.90 and 0.93 using nearest neighbor and Radial Basis Kernel Support Vector Machine. This finding suggests that temporo-parieto-occipital regional based resting state connectivity might be a potential biomarker to identify the levels of flourishing and using both connectivity measures might allow us to find different potential biomarkers.

“…Further, rumination is associated with cognitive malfunctioning 16 , 17 , reduced emotional wellbeing, emotion dysregulation 18 , 19 , and higher physiological stress parameters 20 . On a neural level, rumination has been shown to be related to increased activity in areas of the cognitive control network (CCN) and default mode network (DMN) during induction paradigms 21 – 25 , decreased activity in cognitive tasks 26 , 27 as well as aberrant functional connectivity between these networks 26 , 28 , 29 . The CCN is typically involved in tasks that require effortful control and top-down regulation and comprises areas such as the dorsolateral prefrontal cortex and posterior parietal cortex 30 , 31 .…”

Section: Introductionmentioning

confidence: 99%

Neural correlates of mindful emotion regulation in high and low ruminators

Rosenbaum

Kroczek

Hudak

et al. 2020

Sci Rep

Self Cite

Depressive rumination is considered a prominent risk factor for the occurrence, severity, and duration of depressive episodes. A variety of treatment options have been developed to treat depressive rumination of which mindfulness based programs are especially promising. In the current study, we investigated the neural underpinnings of a short mindfulness intervention and mindful emotion regulation in high and low trait ruminators in an ecologically valid environment using functional near-infrared spectroscopy (fNIRS). Participants were randomly assigned to a mindfulness instruction (MT) group or an instructed thinking (IT) group. Participants in the MT group were trained to either focus their attention mindfully on their breath or their emotions, while the IT group focused their attention on the past or future. Afterwards, all participants underwent an emotion regulation paradigm in which they either watched negative or neutral movie clips. During both paradigms cortical hemodynamic changes were assessed by means of fNIRS. Participants in the MT group showed lower activity in the cognitive control network (CCN) during the focus on breath condition in comparison to the focus on emotion condition. Additionally, oxygenated hemoglobin in the MT group tended to be lower than in the IT group. Further, self-reports of emotional distress during the instruction paradigm were reduced in the MT group. During the emotion regulation paradigm, we observed reduced emotional reactivity in terms of emotional distress and avoidance in the MT group in comparison to the IT group. Furthermore, on a neural level, we observed higher CCN activity in the MT group in comparison to the IT group. We did not find any effect of rumination, neither on the intervention nor on the emotion regulation task. The results of this pilot study are discussed in light of the present literature on the neural correlates of mindfulness based interventions in rumination and emphasize the use of fNIRS to track neural changes in situ over the course of therapy.