An increasing number of projects in neuroscience require statistical analysis of high-dimensional data, as, for instance, in the prediction of behavior from neural firing or in the operation of artificial devices from brain recordings in brain-machine interfaces. Although prevalent, classical linear analysis techniques are often numerically fragile in high dimensions due to irrelevant, redundant, and noisy information. We developed a robust Bayesian linear regression algorithm that automatically detects relevant features and excludes irrelevant ones, all in a computationally efficient manner. In comparison with standard linear methods, the new Bayesian method regularizes against overfitting, is computationally efficient (unlike previously proposed variational linear regression methods, is suitable for data sets with large numbers of samples and a very high number of input dimensions) and is easy to use, thus demonstrating its potential as a drop-in replacement for other linear regression techniques. We evaluate our technique on synthetic data sets and on several neurophysiological data sets. For these neurophysiological data sets we address the question of whether EMG data collected from arm movements of monkeys can be faithfully reconstructed from neural activity in motor cortices. Results demonstrate the success of our newly developed method, in comparison with other approaches in the literature, and, from the neurophysiological point of view, confirms recent findings on the organization of the motor cortex. Finally, an incremental, real-time version of our algorithm demonstrates the suitability of our approach for real-time interfaces between brains and machines.
Recently, we developed a generalizable brain network marker for the diagnosis of major depressive disorder (MDD) across multiple imaging sites using resting-state functional magnetic resonance imaging. Here, we applied this brain network marker to newly acquired data to verify its test-retest reliability and anterograde generalization performance for new patients. We tested the sensitivity and specificity of our brain network marker of MDD using data acquired from 43 new patients with MDD as well as new data from 33 healthy controls (HCs) who participated in our previous study. To examine the test-retest reliability of our brain network marker, we evaluated the intraclass correlation coefficients (ICCs) between the brain network marker-based classifier's output (probability of MDD) in two sets of HC data obtained at an interval of approximately 1 year. Test-retest correlation between the two sets of the classifier's output (probability of MDD) from HCs exhibited moderate reliability with an ICC of 0.45 (95 % confidence interval, 0.13–0.68). The classifier distinguished patients with MDD and HCs with an accuracy of 69.7 % (sensitivity, 72.1 %; specificity, 66.7 %). The data of patients with MDD in this study were cross-sectional, and the clinical significance of the marker, such as whether it is a state or trait marker of MDD and its association with treatment responsiveness, remains unclear. The results of this study reaffirmed the test-retest reliability and generalization performance of our brain network marker for the diagnosis of MDD.
Recently, exposure to sounds with ultrasound (US) components has been shown to modulate brain activity. However, the effects of US on emotional states remain poorly understood. We previously demonstrated that the olfactory bulbectomized (OBX) rat depression model is suitable for examining the effects of audible sounds on emotionality. Here, we investigated the impact of US exposure on the emotional state of OBX rats. In naive rats, exposure to 100 kHz US for 1 h did not increase the number of c-Fos-positive cells in auditory-related cortical areas, and US, as a tone cue, did not elicit a conditioned fear response in the auditory fear conditioning test. These results indicate that the frequency of 100 kHz is hard to hear for rats. However, US improved hyperemotionality (HE) scores and decreased plasma corticosterone levels in OBX rats, suggesting ameliorative effects on depression-like symptoms and stress. In contrast to HE scores, US exposure did not influence anxiety-like behaviors in the elevated plus maze. In conclusion, we demonstrated that exposure to airborne US can alleviate depressive-like symptoms in the OBX rat depression model. This is the first study to show that exposure to airborne US alone produces changes in emotional states in an animal model.
The function of the lateral part of the human cerebellum was investigated through cerebro-cerebellar functional connectivity. We propose a laterality index method to reveal a functional and possibly anatomical pathway between the cerebral cortex and the cerebellum. The brain activity involved in learning a visually-guided tracking skill using a novel computer mouse was measured by functional magnetic resonance imaging. The imaging data analyzed using the method suggest that the simple lobule and semilunar lobule of the lateral cerebellum have connections with the pars opercularis and pars triangularis in the inferior frontal gyrus. A possible function of this cerebro-cerebellar communication loop is tool usage, which is in-between the cognitive and motor functions of the human cerebellum.
Abstract Background and Purpose Irritable bowel syndrome (IBS) is a common condition that is challenging to treat, and novel drugs are needed for this condition. Previously, a chronic vicarious social defeat stress (cVSDS) mouse model exhibits IBS‐like symptoms. Also agonists of the opioid δ‐receptor exert anti‐stress effects in rodents with minimal adverse effects. Here, we evaluated the effects of δ‐receptor agonists on the IBS‐like symptoms in cVSDS mice. Experimental Approach cVSDS mice (male C57BL/6J mice) were prepared following a 10‐day exposure to witness of social defeat stress. Subsequently, intestinal peristaltic motility and abdominal hyperalgesia were evaluated using the charcoal meal test (CMT) and capsaicin‐induced hyperalgesia test (CHT), respectively. Extracellular glutamate levels were measured using in vivo brain microdialysis. The drug was singly administrated 30 min before testing. Key Results In cVSDS mice, systemic (10 mg kg −1 ) and intracerebroventricular (30 nmol) administration of a δ‐receptor agonist regulated intestinal peristalsis in the CMT and relieved abdominal pain in the CHT. Effects of systemic administration were blocked by intracerebroventricular injection of a δ‐receptor inhibitor. Local infusion of the δ‐receptor agonist (0.6 nmol) into the insular cortex improved cVSDS‐induced intestinal hypermotility. The in vivo brain microdialysis study showed that re‐exposure to VSDS elevated the extracellular glutamate levels in the IC, which was restored by the δ‐receptor agonist. Conclusions and Implications We propose that agonists of opioid δ‐receptors are potential drugs for the radical treatment of IBS because they can ameliorate IBS‐like symptoms via the CNS, specifically the insular cortex.
Recent study has demonstrated that anti-alcoholism drug disulfiram (DSF) inhibits chemokine receptor-mediated migration signals. Several studies have reported that the chemokine receptors are associated with emotion regulation. Therefore, this study was performed to clarify the effect of DSF on emotional behavior in rodents.
