Neuroscience and Biomedical Engineering (Discontinued) - Volume 5, Issue 1, 2017

Background: To make such a large-scale digital PET, we are mainly facing the following technical challenges. First of all, the number of nodes in a large-scale digital PET is generally more than hundreds, how to manage them? When the hundreds of nodes are queried or configured or monitored at the same time, there will always be a high concurrency of data transmission, how to ensure the real-time of communication and reliability? Objective: Managing hundreds of Detector Unit effectivelly and with good scalability. Methods: We and other investigators have proposed a communication control subsystem based on CAN and Ethernet in all-Digital PET. It mainly contains three modules: Control Center, System Communication & Switch (SCS) Unit and Detector Unit (DU). Control Center connects one or several SCS units via 100Mbps or Gigabit Ethernet. The two modules exchange control information through the TCP/IP protocol. The SCS Unit is connected with dozens of detectors through the CAN bus Results: With Ethernet and CAN bus in our Digital Pet, the Control Center can connect up to 100 SCS Units with Gigabit Ethernet. Each SCS Unit can communicate with almost 100 DUs with 500kbps CAN bus. Conclusion: The good scalability and high bandwidth of CAN and Ethernet perfectly solve the problem that the complex communication of hundreds of detector nodes in digital PET system.

Objective: To minimize the risk inherent to the use of medical radiation and robotic radiosurgery, this research introduced the basis and method of beam commissioning data acquisition for the Iris variable aperture collimator of CyberKnife VSI. Methods: In this study, clinical dosimetry measurements of the Iris collimator such as tissue-phantom ratios (TPRs), off-center ratios (OCRs), and secondary collimator output factors (OFs) were conducted, and the data was contrasted with that of the Fixed collimator. Results: The Iris data and the Fixed data were not quite different in TPRs in the same radiation field size. Since the difference of the hardware structure,the OCRs and OFs were quite different, especially in small aperture (5, 7.5 and 10 mm) under the same condition of SAD. For example, the maximum discrepancy of the OFs was 26.67% (5mm aperture, 650mm SAD). Conclusion: When Iris aperture makes some change, tungsten segments move fast and form an aperture smaller than that we need, and then recover to the right size, which may affect the results of the measurement, and also the dodecagonal design of Iris results in a problem of leakage radiation on the edge.

Background: To make such a large-scale digital PET, we are mainly facing the following technical challenges. First of all, the number of nodes in a large-scale digital PET is generally more than hundreds, how to manage them? When the hundreds of nodes are queried or configured or monitored at the same time, there will always be a high concurrency of data transmission, how to ensure the real-time of communication and reliability? Objective: Managing hundreds of Detector Unit effectivelly and with good scalability Methods: We and other investigators have proposed a communication control subsystem based on CAN and Ethernet in all-Digital PET. It mainly contains three modules: Control Center, System Communication & Switch (SCS) Unit and Detector Unit (DU). Control Center connects one or several SCS units via 100Mbps or Gigabit Ethernet. The two modules exchange control information through the TCP/IP protocol. The SCS Unit is connected with dozens of detectors through the CAN bus Results: With Ethernet and CAN bus in our Digital Pet, the Control Center can connect up to 100 SCS Units with Gigabit Ethernet. Each SCS Unit can communicate with almost 100 DUs with 500kbps CAN bus. Conclusion: The good scalability and high bandwidth of CAN and Ethernet perfectly solve the problem that the complex communication of hundreds of detector nodes in digital PET system.

Introduction: This paper presents a software-based data acquisition and processing unit (DAPU) architecture for an all-digital positron emission tomography (PET) system based on 352 LYSO/ SiPM detectors with local digitization. By obtaining raw data directly from individual detector via 10-Gigabit Ethernet in UDP protocol, a self-adapting calibration method for PET is proposed. The architecture is designed to be scalable across an Ethernet network as well as for multi-CPU computer systems. Besides that, more accurate and computationally complex, iterative algorithms could be employed and easily reformed with flexible configuration in DAPU for higher quality and accurate PET image. Background: By comparison with the traditional PET detector module, which outputs singles or coincidences, the detector module in all digital PET system outputs raw detector data in UDP sockets directly, including digitized timestamps and identifiers of triggered SiPM pixels. To obtain the detector raw data, a high bandwidth data transmission system is required. Objective: The aim was to present a high performance data acquisition unit to collect and process the digital data of the original flash pulse in order to meet real-time data acquisition and processing of the digital PET system. Methods: A software based data acquisition and processing unit for digital PET system is presented, which is based on SiPM detector coupled with LYSO crystal arrays. The data acquisition and processing server (DAPS) receives detector raw data and outputs coincidence data by using memory cache and parallel computing. Results: Due to the use of cache and parallel computing, the result of experiment shows that it is possible to acquire and process the detector raw data simultaneously even the data rate is as high as 1Gbps. Conclusion: A software based data acquisition and processing unit meets the needs of data acquisition in digital PET system by using memory cache and parallel computing.

Purpose: To study the beam characteristics of CyberKnife system, especially the features in standardization and calibration of small-field dosimetry under non-standard condition, this research utilized Monte Carlo method to simulate the transporting process of beams in G4 CyberKnife and compared the results with the outcomes of actual measurement so that the accuracy of the established model can be verified. Materials and Methods: BEAMnrc/DOSXYZnrc Monte Carlo system was used for simulating the physical structure of G4 CyberKnife model (containing 12 collimators of different sizes). With the adjustment of parameters (the average energy, full width at half maximum of intensity distribution) of electron beam, data of dose distribution for the fields (percentage depth dose, off-axis ratio, output factor, beam quality, correction factor, etc.) in the water phantom could be acquired and compared with the actual measurement so as to determine the parameters of electron beam in the simulated model. Results: In the comparisons of percentage depth dose, the errors with more than 90% of the points were smaller than 1% (except 5mm and 7.5mm collimators). And for the off-axis ratios, the errors with more than 90% of the points were smaller than 1% (except 5mm, 7.5mm and 10mm collimators). The values of beam output factors in a Monte Carlo system were consistent with the measured values when the collimator sizes were larger than 20mm, and when the collimator size were smaller than 15mm, a certain deviation for output factor existed. The value of beam quality in Monte Carlo model was 0.639, which was close to that of the measured beam quality, 0.635. Conclusion: The parameters of electron beam were finally determined (the average energy was 6.9MeV and the full width at half maximum of intensity distribution was 0.4 cm). The Monte Carlo model established in this research was able to accurately simulate the beam transporting process of CyberKnife and thus might lay the foundation for the further research.

Background: Principle A of the Government and Binding Theory (Norm Chomsky, 1981, 1986) prescribes that a reflexive should refer to the local (short-distance) antecedent within the local syntactic domain. However, the Chinese bare reflexive “ziji” does not accord with Principle A. “Ziji” can refer to a local or long-distance antecedent, directly determined by context (co-text). Objective: The present study aims to explore when context begins affecting “ziji” anaphora processing. Methods: Using the semantic priming technique, we examined the nature of the earliest stage of context- manipulated “ziji” anaphora processing. Results: A priming effect on target words under (semantically) relevant contexts was detected; we also found the priming effect on the L-target under the long-distance contextual condition, but found no priming effect on the relevant target (the S-target) under the local (short-distance) contextual condition. Conclusion: The present study suggests that contextual information begins affecting “ziji” anaphora at its earliest processing stage; that is, context immediately affects “ziji” anaphora processing once it is available. However, at the earliest processing stage, the activation of contextual information is still asymmetric or inadequate.

Background: The cone beam computed tomography (CBCT), as a non-destructive tool, provides a fast and convenient method for clinicians to diagnose related diseases. Even though some debates still exist among researchers, some studies have demonstrated the feasibility of bone mineral density measurement using CBCT images. Periodontal disease is one of the most common oral diseases. Accurate assessment of periodontal support and alveolar bone condition is very important. However, measuring BMD using CBCT imaging is still controversial. Objective: In this paper, an experiment was carried out to demonstrate the feasibility of bone mineral density measurement using CBCT images. Methods: A step-wedge phantom was used to estimate the effective spectrum of X-ray. And the spectrum was to eliminate and correct beam hardening artifact. Calculate BMD from the corrected images. Conclusion: The result showed that it is possible to measure bone mineral density using CBCT images.

Background: Disability can be defined as a condition that may limit an individual's ability to use a particular limb or part of the body. Disability in the lower limb may be the consequence of a stroke, an accident, infection or can be congenital. This results in increased or total inability to perform everyday tasks. Rehabilitation procedures aim to help patients regain control of their everyday tasks with short-term intervention or life-time assistive support, based upon the kind of limb infarction. Objective: Present review aims to cite the neuro-rehabilitation methods that support recovery in lower limb function. Articles were screened based upon the inclusion criteria of lower limb motor actions and its genesis being recorded, primarily from the sensorimotor areas of the brain. Studies using electroencephalography (EEG) as the non-invasive method for brain data acquisition only were included. Results: The detailed analysis of 27 studies was performed after grouping them according to the methodological approach followed. Of all the studies selected, 16 of those corresponded to lower limb motor actions being performed while sitting, whereas only 11 reported the actions during actual bipedal locomotion. Only five interfaced the neuronal signals with electromechanical devices for practical implementation of the rehabilitation procedure. Conclusion: Qualitative analysis showed that neural rehabilitative procedures does induce plasticity in human brain, but a critical analysis in hospitals or outside environment is necessary to verify the approaches. Future prospects suggest the targeted use of EEG based rehabilitative procedure to uphold the present findings.

Background: Various kinds of rule induction methods have been proposed, such as induction from decision trees, decision lists, and the AQ family. Several symbolic inductive learning methods have been proposed, such as the induction of decision trees [1, 2, 3], and the AQ family [4, 5, 6]. These methods and many variants initially introduced in the 1980s and 1990s are useful for finding frequent patterns from databases. However, conventional rule mining methods apply to a given dataset when the data has been fixed in the first run, but these methods must run from scratch every time new data appears. Since the computational complexity is n2, a repeated run would limit the applicability of these methods in the era of “Big Data”. To solve this problem, incremental learning methods have been introduced. However, most of the methods have several problems: First, they do not perform worse than conventional rule learning methods. Secondly, those methods do not generate probabilistic rules. Third, computational complexity is heavier than conventional complexity. Methods: By using a framework of the rough set rule induction model, the authors first investigate the theoretical aspects of updates of statistical indices with additional examples used for rule selection criteria. The authors have found four possibilities for the update of indices, which in turn lead to two new rule selection criteria. If the statistical indices of a rule satisfy the first selection condition, the rule can be used even if an additional example does not support the classification of the rules. If the statistical indices of a rule satisfy the second pair of inequalities, the rule may be removed from the list of classification rules in the above case, or the rule may be included in the list if an additional example supports the classification. These rules belong to subrule layers. Based on rough set theory, we develop a new rule induction method, called PRIMEROSE-INC5 (Probabilistic Rule Induction Method based on Rough Sets for Incremental Learning Methods), which induces probabilistic rules incrementally. Results: The system was evaluated based on the following two medical datasets, which were previously used for evaluation on conventional rule induction methods. One dataset was on the differential diagnosis of headaches, which consists of 1477 examples with 10 disease classes and 20 attributes. The other dataset was on meningitis, which consists of 198 examples with 3 classes and 25 attributes. The system was compared with other conventional rule induction methods by using repeated 10-fold crossvalidation (repeated times: 100), whose experimental results showed that the proposed system outperformed the previously introduced methods.

Background: Neuroimaging techniques with high spatio-temporal resolution would are crucial for the advancement in brain research, improvement of clinical diagnosis and management of neuropsychiatric disorders. Functional MRI (fMRI) is characterized by its high spatial resolution. On the other hand, the techniques measuring electromagnetic features of neurons, such as electroencephalography (EEG), provide millisecond order temporal resolution. Therefore, integrative analyses of the fMRI and EEG are expected to provide information with high spatio-temporal resolution enabling to clarify dynamic multiple cortical activities Objective: We propose a novel fMRI-EEG integrative reconstruction method for multiple cortical activities using EEG data, and we validate the accuracy of our method by comparing it with other popular reconstruction approaches that are assumed to have obtained prior information from fMRI. Methods: We determined the first model via fMRI data, and we obtained the final model which contained the source that the fMRI could not capture through iterative model selection procedures based on the Akaike information criterion (AIC). We then used a linearly constrained generalized least-squares (LCGLS) filter to suppress unconscious activities. We carried out numerical simulations to validate the proposed method and compared it to two commonly used representative reconstructions method, sLORETA and the LCMV beamformer methods, using the residual sum of the squares. Results: The proposed method gave a good estimation of the multiple cortical activities by suppressing other fMRI-visible and fMRI-invisible sources. Conclusion: These results demonstrate that the proposed method can reconstruct cortical activities more accurately than either sLORETA or the LCMV beamformer methods.

Background: If human touch an object, even if they are blindfolded, they can reliably perceive its properties, such as temperature, material, length, height, texture and so on. In this study, we focused on investigating length perception, because length perception was an essential factor of object perception. Objective and Methods: 15 young and 15 old subjects participated in this experiment. They were blindfolded during experiment and actively grasped the displayed length with thumb and index finger and then perceived it. Two working memory-related experiments, varied delay times experiment and n-back experiment were performed separately, in order to investigate whether length discrimination abilities of young and old subjects degraded with aging. Results and Conclusion: With the increment of delay times, length discrimination threshold of both young and old subjects increased, delay times significantly affected length discrimination. No agerelated differences were found in varied delay times length discrimination experiment. However, we did confirm age-related differences in n-back length discrimination experiment.

Background: Pain is a common and troublesome non-motor symptom in Parkinson's disease (PD). Similarly, severe postoperative pain is common after major spinal surgery and may become chronic. The pathophysiologic mechanism underlying those conditions remains unclear. In this study, we recorded pain-related evoked potentials induced by intra-epidermal electrical stimulation in patients with PD and patients with persistent pain after spinal surgery and compared the results between the two groups. Objective: The purpose of this study was to investigate the pathophysiology of pain in patients with persistent pain after spinal surgery and in patients with PD. Methods: We recorded pain-related evoked potentials in 23 patients with PD (64.0 years), 6 patients with persistent pain after spinal surgery (69.5 years) and 12 healthy controls (59.6 years). Results: Major negative (N1) and positive (P1) deflections were observed after each stimulation. The amplitudes between N1 and P1 (N1-P1), which are thought to originate from the anterior cingulate cortex and insula, were significantly lower in both patients with PD and persistent pain after spinal surgery than in the controls (both P<0.01). However, there was no significant difference in N1-P1 amplitude between the patients with PD and the patients with persistent pain after spinal surgery. No significant differences in N1 and P1 latencies were observed among the three groups. Conclusion: These results suggest that abnormal central processing of pain is present in patients with PD and those with chronic persistent pain after spinal surgery and that these two conditions share similar pathophysiologic mechanisms, at least partially.