Neural Mechanisms of Mental Fatigue Revisited: New Insights from the Brain Connectome

Maintaining sustained attention during a prolonged cognitive task often comes at a cost: high levels of mental fatigue. Heuristically, mental fatigue refers to a feeling of tiredness or exhaustion, and a disengagement from the task at hand;it manifests as impaired cognitive and behavioral performance. In order to effectively reduce the undesirable yet preventable consequences of mental fatigue in many real-world workspaces, a better understanding of the underlying neural mechanisms is needed, and continuous efforts have been devoted to this topic. In comparison with conventional univariate approaches, which are widely utilized in fatigue studies, convergent evidence has shown that multivariate functional connectivity analysis may lead to richer information about mental fatigue. In fact, mental fatigue is increasingly thought to be related to the deviated reorganization of functional connectivity among brain regions in recent studies. In addition, graph theoretical analysis has shed new light on quantitatively assessing the reorganization of the brain functional networks that are modulated by mental fatigue. This review article begins with a brief introduction to neuroimaging studies on mental fatigue and the brain connectome, followed by a thorough overview of connectome studies on mental fatigue. Although only a limited number of studies have been published thus far, it is believed that the brain connectome can be a useful approach not only for the elucidation of underlying neural mechanisms in the nascent field of neuroergonomics, but also for the automatic detection and classification of mental fatigue in order to address the prevention of fatigue-related human error in the near future.

Systems Neuroengineering: Understanding and Interacting with the Brain

In this paper, we review the current stateof-the-art techniques used for understanding the inner workings of the brain at a systems level. The neural activity that governsour everyday lives involves anintricate coordination of many processes that can be attributed to a variety of brain regions. On the surface, many of these functions can appear to be controlled by speciflc anatomical structures; however, in reality, numerous dynamic networks within the brain contribute to its function through an interconnected web of neuronal and synaptic pathways. The brain, in its healthy or pathological state, can therefore be best understood by taking a systems-level approach. While numerous neuroengineering technologies exist, we focus here on three major thrusts in the field of systems neuroengineering: neuroimaging, neural interfacing, and neuromodulation. Neuroimaging enables us to delineate the structural and functional organization of the brain, which is key in understanding how the neural system functions in both normal and disease states. Based on such knowledge, devices can be used either to communicate with the neural system, as in neural interface systems, or to modulate brain activity, as in neuromodulation systems. The consideration of these three fields is key to the development and application of neuro-devices. Feedback-based neuro-devices require the ability to sense neural activity(via a neuroimaging modality) through a neural interface(invasive or noninvasive) and ultimately to select a set of stimulation parameters in order to alter neural function via a neuromodulation modality. Systems neuroengineering refers to the use of engineering tools and technologies to image, decode, and modulate the brain in order to comprehend its functions and to repair its dysfunction. Interactions between these fields will help to shape the future of systems neuroengineering—to develop neurotechniques for enhancing the understanding of wholebrain function and dysfunction, and the management of neurological and mental disorders.

DETECTING CEREBRAL ARTERIES AND VEINS:FROM LARGE TO SMALL

In this paper,a model-based reconstruction technique is proposed to simultaneously measure the relative deoxyhemoglobin concentration and the relative blood flow velocity in cerebral cortex.With the help of this model-based reconstruction technique,artifacts due to nonuniform laser illumination and curvature of cortex are efficiently corrected.The results of relative deoxyhemoglobin concentration and relative blood flow velocity are then used to detect and distinguish cerebral arteries and veins.In an experimental study on rat,cerebral blood vessels are segmented from the reconstructed blood flow image by Otsu multiple threshold method.Afterwards,arteries and veins are distinguished by a simple fuzzy criterion based on the information of relative deoxyhemoglobin concentration.

Modified Laser Speckle Imaging with Adaptive Window

激光点缀的优点之一正在检测通过图象处理微脉管。这份报纸建议为激光点缀处理方法的一幅新图象，适应地在空格处理激光点缀图象的适应窗口方法。常规固定窗户方法的劣势是它不管目标区域使用一样的窗户尺寸。内在地，激光点缀包含不希望得到的噪音。因此一扇大窗户对移开噪音有用，但是它导致图象的低分辨率。否则，一扇小窗户可以检测微脉管但是它在噪音有限制移动。克服这宗交易，适应窗口方法的概念最新被介绍给常规激光点缀图象分析。另外，修改适应窗户方法适用于另外的选择图象。我们以图象质量和处理复杂性把常规激光点缀对比分析(LASCA ) 和它的变体与建议方法作比较。而且比较，伴随的变化选择图象的结果也被比较了。

Using Variations of Somatosensory Evoked Potentials to Quantify Spinal Cord Injury Level

Existing work indicates that the degree of variation of somatosensory evoked potential (SEP) signals between a healthy spinal pathway and spinal pathway affected by spinal cord injury (SCI) can be used to evaluate the integrity of the spinal pathway. This paper develops a metric that exploits the time-domain features of SEP signals (relative amplitude, time scaling, and time duration) in order to quantify the level of SCI. The proposed method is tested on actual SEP signals collected from rodents afflicted with focal demyelination SCI. Results indicate that the proposed method provides a robust assessment of the different degrees of demyelination in the spinal cord.