Editorial: Limbic-Brainstem Roles in Perception, Cognition, Emotion, and Behavior

Commonality and variance of resting-state networks in common marmoset brains

Animal models of brain function are critical for the study of human diseases and development of effective interventions. Resting-state network (RSN) analysis is a powerful tool for evaluating brain function and performing comparisons across animal species. Several studies have reported RSNs in the common marmoset (Callithrix jacchus; marmoset), a non-human primate. However, it is necessary to identify RSNs and evaluate commonality and inter-individual variance through analyses using a larger amount of data. In this study, we present marmoset RSNs detected using > 100,000 time-course image volumes of resting-state functional magnetic resonance imaging data with careful preprocessing. In addition, we extracted brain regions involved in the composition of these RSNs to understand the differences between humans and marmosets. We detected 16 RSNs in major marmosets, three of which were novel networks that have not been previously reported in marmosets. Since these RSNs possess the potential for use in the functional evaluation of neurodegenerative diseases, the data in this study will significantly contribute to the understanding of the functional effects of neurodegenerative diseases.

Implicit Selective Attention: The Role of the Mesencephalic-basal Ganglia System

The ability of the brain to recognize and orient attention to relevant stimuli appearing in the visual field is highlighted by a tuning process, which involves modulating the early visual system by both cortical and subcortical brain areas. Selective attention is coordinated not only by the output of stimulus-based saliency maps but is also influenced by top-down cognitive factors, such as internal states, goals, or previous experiences. The basal ganglia system plays a key role in implicitly modulating the underlying mechanisms of selective attention, favouring the formation and maintenance of implicit sensory-motor memories that are capable of automatically modifying the output of priority maps in sensory-motor structures of the midbrain, such as the superior colliculus. The article presents an overview of the recent literature outlining the crucial contribution of several subcortical structures to the processing of different sources of salient stimuli. In detail, we will focus on how the mesencephalic- basal ganglia closed loops contribute to implicitly addressing and modulating selective attention to prioritized stimuli. We conclude by discussing implicit behavioural responses observed in clinical populations in which awareness is compromised at some level. Implicit (emergent) awareness in clinical conditions that can be accompanied by manifest anosognosic symptomatology (i.e., hemiplegia) or involving abnormal conscious processing of visual information (i.e., unilateral spatial neglect and blindsight) represents interesting neurocognitive "test cases" for inferences about mesencephalicbasal ganglia closed-loops involvement in the formation of implicit sensory-motor memories.

Effects of Neural Mechanisms of Pretask Resting EEG Alpha Information on Situational Awareness: A Functional Connectivity Approach

OBJECTIVE

In this study, the influence of pretask resting neural mechanisms on situational awareness (SA)-task is studied.

BACKGROUND

Pretask electroencephalography (EEG) information and Stroop effect are known to influence task engagement independently. However, neural mechanisms of pretask resting absolute alpha (PRAA) and pretask resting alpha frontal asymmetry (PRAFA) in influencing SA-task which is undergoing Stroop effect is still not understood.

METHOD

The study involved pretask resting EEG measurements from 18 healthy individuals followed by functional magnetic resonance imaging (fMRI) acquisition during SA-task. To understand the effect of pretask alpha information and Stroop effect on SA, a robust correlation between mean reaction time, SA Index, PRAA, and PRAFA were assessed. Furthermore, neural underpinnings of PRAA, PRAFA in SA-task, and functional connectivity were analyzed through the EEG-informed fMRI approach.

RESULTS

Significant robust correlation of reaction time was observed with SA Index (Pearson: r = .50, pcorr = .05) and PRAFA (Pearson: r = .63; pcorr = .01), respectively. Similarly, SA Index significantly correlated with PRAFA (Pearson: r = .56, pcorr = .01; Spearman: r = .61, pcorr = .007), and PRAA (Pearson: r = .59, pcorr = .005; Spearman: r = .59, pcorr = .002). Neural underpinnings of SA-task revealed regions involved in visual-processing and higher-order cognition. PRAA was primarily underpinned at frontal-temporal areas and functionally connected to SA-task regions pertaining to the emotional regulation. PRAFA has correlated with limbic and parietal regions, which are involved in integration of visual, emotion, and memory information of SA-task.

CONCLUSION

The results suggest a strong association of reaction time with SA-task and PRAFA and strongly support the hypothesis that PRAFA, PRAA, and associated neural mechanisms significantly influence the outcome of SA-task.

APPLICATION

It is beneficial to study the effect of pretask resting information on SA-task to improve SA.

Increased Functional Connectivity Between Medulla and Inferior Parietal Cortex in Medication-Free Major Depressive Disorder

Emerging evidence has documented the abnormalities of primary brain functions in major depressive disorder (MDD). The brainstem has shown to play an important role in regulating basic functions of the human brain, but little is known about its role in MDD, especially the roles of its subregions. To uncover this, the present study adopted resting-state functional magnetic resonance imaging with fine-grained brainstem atlas in 23 medication-free MDD patients and 34 matched healthy controls (HC). The analysis revealed significantly increased functional connectivity of the medulla, one of the brainstem subregions, with the inferior parietal cortex (IPC) in MDD patients. A positive correlation was further identified between the increased medulla-IPC functional connectivity and Hamilton anxiety scores. Functional characterization of the medulla and IPC using a meta-analysis revealed that both regions primarily participated in action execution and inhibition. Our findings suggest that increased medulla-IPC functional connectivity may be related to over-activity or abnormal control of negative emotions in MDD, which provides a new insight for the neurobiology of MDD.

Multimodal hyper-connectivity of functional networks using functionally-weighted LASSO for MCI classification

Recent works have shown that hyper-networks derived from blood-oxygen-level-dependent (BOLD) fMRI, where an edge (called hyper-edge) can be connected to more than two nodes, are effective biomarkers for MCI classification. Although BOLD fMRI is a high temporal resolution fMRI approach to assess alterations in brain networks, it cannot pinpoint to a single correlation of neuronal activity since BOLD signals are composite. In contrast, arterial spin labeling (ASL) is a lower temporal resolution fMRI technique for measuring cerebral blood flow (CBF) that can provide quantitative, direct brain network physiology measurements. This paper proposes a novel sparse regression algorithm for inference of the integrated hyper-connectivity networks from BOLD fMRI and ASL fMRI. Specifically, a least absolution shrinkage and selection operator (LASSO) algorithm, which is constrained by the functional connectivity derived from ASL fMRI, is employed to estimate hyper-connectivity for characterizing BOLD-fMRI-based functional interaction among multiple regions. An ASL-derived functional connectivity is constructed by using an Ultra-GroupLASSO-UOLS algorithm, where the combination of ultra-least squares (ULS) criterion with a group LASSO (GroupLASSO) algorithm is applied to detect the topology of ASL-based functional connectivity networks, and then an ultra-orthogonal least squares (UOLS) algorithm is used to estimate the connectivity strength. By combining the complementary characterization conveyed by rs-fMRI and ASL fMRI, our multimodal hyper-networks demonstrated much better discriminative characteristics than either the conventional pairwise connectivity networks or the unimodal hyper-connectivity networks. Experimental results on publicly available ADNI dataset demonstrate that the proposed method outperforms the existing single modality based sparse functional connectivity inference methods.

Modified Xiaoyaosan (MXYS) Exerts Anti-depressive Effects by Rectifying the Brain Blood Oxygen Level-Dependent fMRI Signals and Improving Hippocampal Neurogenesis in Mice

As the traditional Chinese herbal formula, Xiaoyaosan and its modified formula have been described in many previous studies with definite anti-depressive effects, but its underlying mechanism remains mystery. Previous work in our lab has demonstrated that depression induced by chronic stress could generate brain blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals disorder, accompanied by the impairment of hippocampal neuronal plasticity, decrease of brain-derived neurotrophic factor, and reduction of the number and complexity of adult neurons in the dentate gyrus. We hypothesized that herbal formula based on Xiaoyaosan could exert anti-depressive effects through restoring these neurobiological dysfunctions and rectifying BOLD-fMRI signals. To test this hypothesis, we examined the effect of modified Xiaoyaosan (MXYS) on depressive-like behaviors, as well as hippocampal neurogenesis and BOLD signals in a mice model of chronic unpredictable mild stress (CUMS)-induced depression. MXYS exerted anti-depressant effects on CUMS-induced depression that were similar to the effects of classical antidepressants drug (fluoxetine hydrochloride), with a significant alleviation of depressive-like behaviors, an improvement of hippocampal neurogenesis, and a reversal of activation of BOLD in the limbic system, particularly in the hippocampus. These results suggested that MXYS attenuated CUMS-induced depressive behaviors by rectifying the BOLD signals in the mice hippocampus. These novel results demonstrated that MXYS had anti-depressive effects accompanied by improving BOLD signals and hippocampal neurogenesis, which suggested that BOLD-fMRI signals in brain regions could be a key component for the evaluation of novel antidepressant drugs.