Activation of Mitogen-Activated Protein Kinase in Descending Pain Modulatory System

The descending pain modulatory system is thought to undergo plastic changes following peripheral tissue injury and exerts bidirectional (facilitatory and inhibitory) influence on spinal nociceptive transmission. The mitogen-activated protein kinases (MAPKs) superfamily consists of four main members: the extracellular signal-regulated protein kinase1/2 (ERK1/2), the c-Jun N-terminal kinases (JNKs), the p38 MAPKs, and the ERK5. MAPKs not only regulate cell proliferation and survival but also play important roles in synaptic plasticity and memory formation. Recently, many studies have demonstrated that noxious stimuli activate MAPKs in several brain regions that are components of descending pain modulatory system. They are involved in pain perception and pain-related emotional responses. In addition, psychophysical stress also activates MAPKs in these brain structures. Greater appreciation of the convergence of mechanisms between noxious stimuli- and psychological stress-induced neuroplasticity is likely to lead to the identification of novel targets for a variety of pain syndromes

Variance and Autocorrelation of the Spontaneous Slow Brain Activity

Slow (<0.1 Hz) oscillatory activity in the human brain, as measured by functional magnetic imaging, has been used to identify neural networks and their dysfunction in specific brain diseases. Its intrinsic properties may also be useful to investigate brain functions. We investigated the two functional maps: variance and first order autocorrelation coefficient (r1). These two maps had distinct spatial distributions and the values were significantly different among the subdivisions of the precuneus and posterior cingulate cortex that were identified in functional connectivity (FC) studies. The results reinforce the functional segregation of these subdivisions and indicate that the intrinsic properties of the slow brain activity have physiological relevance. Further, we propose a sample size (degree of freedom) correction when assessing the statistical significance of FC strength with r1 values, which enables a better understanding of the network changes related to various brain diseases

Severity of Premenstrual Symptoms Predicted by Second to Fourth Digit Ratio

Women of reproductive age often experience a variety of unpleasant symptoms prior to the onset of menstruation. While genetics may influence the variability of these symptoms and their severity among women, the exact causes remain unknown. We hypothesized that symptom variability originates from differences in the embryonic environment and thus development caused by variation in exposure to sex hormones. We measured the second to fourth digit ratios (2D:4D) in 402 young women and investigated the potential relationships of this ratio premenstrual symptoms using a generalized linear model. We found that two models (one with two predictors such as both hands’ digit ratios and the other with the difference between the two digit ratios, Dr-l) were significantly different from the constant model as assessed by chi-square test. The right digit ratio and Dr-l were negatively related to the symptom scores, and the left digit ratio was related to the scores. When premenstrual symptoms were classified into eight categories, five categories, including pain, concentration, autonomic reaction, negative affect, and control were associated with the digit ratios and Dr-l. Behavioral changes and water retention were not predicted by them. Arousal was predicted by Dr-l. The right 2D:4D is thought to be determined by the balance of testosterone and estrogen levels during early embryogenesis and is not affected by postpartum levels of sex hormones, while the left 2D:4D might be affected by the other prenatal environmental factors. We conclude that the embryonic environment, including the relative concentration of sex hormones an embryo is exposed to, is associated with the severity of premenstrual symptoms once menarche is reached

Interhemispheric disconnectivity in the sensorimotor network in bipolar disorder revealed by functional connectivity and diffusion tensor imaging analysis

Background: Little is known regarding interhemispheric functional connectivity (FC) abnormalities via the corpus callosum in subjects with bipolar disorder (BD), which might be a key pathophysiological basis of emotional processing alterations in BD. Methods: We performed tract-based spatial statistics (TBSS) using diffusion tensor imaging (DTI) in 24 healthy control (HC) and 22 BD subjects. Next, we analyzed the neural networks with independent component analysis (ICA) in 32HC and 25 BD subjects using resting-state functional magnetic resonance imaging. Results: In TBSS analysis, we found reduced fractional anisotropy (FA) in the corpus callosum of BD subjects. In ICA, functional within-connectivity was reduced in two clusters in the sensorimotor network (SMN) (right and left primary somatosensory areas) of BD subjects compared with HCs. FC between the two clusters and FA values in the corpus callosum of BD subjects was significantly correlated. Further, the functional within-connectivity was related to Young Mania Rating Scale (YMRS) total scores in the right premotor area in the SMN of BD subjects. Limitations: Almost all of our BD subjects were taking several medications which could be a confounding factor. Conclusions: Our findings suggest that interhemispheric FC dysfunction in the SMN is associated with the impaired nerve fibers in the corpus callosum, which could be one of pathophysiological bases of emotion processing dysregulation in BD patients

High <b><i>r</i></b><b>₁</b> cortical regions: Brodmann’s area (BA); Z-score (Z, mean (SD)).

<p>High <b><i>r</i></b><b>₁</b> cortical regions: Brodmann’s area (BA); Z-score (Z, mean (SD)).</p

Z-scores of the variance (<i>v</i>) and <i>r</i>₁ in the 4 subdivisions of the precuneus.

<p>Significant differences in the <b><i>v</i></b> values among the 4 regions were revealed by the paired <b><i>t</i></b>-test (<i>p</i>-values were corrected with Bonferroni’s method). In contrast, there was no significant difference in the <b><i>r</i></b><b>₁</b> values among the 4 regions. Sm, sensorimotor region; tz, transitional zone; cg, cognitive/associative regions; vs, visual region.</p

Effect of sample size correction.

<p>The top images show the distribution of the cross correlation coefficients (p<0.05, <b><i>t</i></b>-test for each paired voxels’ data) between the ventral PCC and the other brain voxels without sample size correction (i.e., <i>N</i> = 102). The bottom images show the distribution of the voxels with the cross correlation coefficients that are significantly different from zero (p<0.05). The effective sample size (<i>N</i>’) (see text) was calculated for each pair of voxels with their autocorrelation coefficients and each pair’s <i>N</i>’ was used to assess the significance of the cross-correlation coefficient. For this subject, ∼46% of voxels were revealed not to be significant after sample size correction.</p

Z-scores of the variance (<i>v</i>) and <i>r</i>₁ in the 2 subdivisions of the PCC.

<p>Both values were significantly higher in the ventral PCC than in the dorsal PCC (p<0.0001, paired <b><i>t</i></b>-test).</p

Relative locations of the seeds in the subdivisions of the precuneus and PCC shown with mean Z-score maps of <i>v</i> and <i>r</i>₁.

<p>The mean Z-score map for the variance (<b><i>v</i></b>) is shown in the middle and the map for <b><i>r</i></b><b>₁</b> is shown in the bottom of the figure. Note that the distribution pattern for <b><i>v</i></b> is different from that for <b><i>r</i></b><b>₁</b> especially in the precuneus and PCC. <b>a</b>: ventral PCC; <b>b</b>: dorsal PCC; <b>c</b>: visual precueal region; <b>d</b>: cognitive/associative precuneal region; <b>e</b>: transitional zone; <b>f</b>: sensorimotor precuneal region.</p

Distribution of the <i>r</i>₁ values for the gray matter voxels in one subject.

<p>The value ranges from 0.3 to 0.7 though most of the data are between 0.5 and 0.6.</p