Sickness absence due to common mental disorders  is a problem in many Western countries. Long-term sickness absence leads to substantial societal and financial costs. In workers with common mental disorders, sickness absence costs are much higher than medical costs. In the Netherlands, a practice guideline was developed that promotes an activating approach of the occupational physician to establish faster return-to-work by enhancing the problem-solving capacity of workers, especially in relation to their work environment. Studies on this guideline indicate a promising association between guideline adherence and a shortened sick leave duration, but also minimal adherence to the guideline by occupational physicians. Therefore, this study evaluates the effect of guideline-based care on the full return-to-work of workers who are sick listed due to common mental disorders.This is a two-armed cluster-randomised controlled trial with randomisation at the occupational physician level. During one year, occupational physicians in the intervention group receive innovative training to improve their guideline-based care whereas occupational physicians in the control group provide care as usual. A total of 232 workers, sick listed due to common mental disorders and counselled by participating occupational physicians, will be included. Data are collected via the registration system of the occupational health service, and by questionnaires at baseline and at 3, 6 and 12 months. The primary outcome is time to full return-to-work. Secondary outcomes are partial return-to-work, total number of sick leave days, symptoms, and workability. Personal and work characteristics are the prognostic measures. Additional measures are coping, self-efficacy, remoralization, personal experiences, satisfaction with consultations with the occupational physician and with contact with the supervisor, experiences and behaviour of the supervisor, and the extent of guideline adherence.If the results show that guideline-based care in fact leads to faster and sustainable return-to-work, this study will contribute to lowering personal, societal and financial costs.ISRCTN86605310 Sickness absence due to common mental disorders (CMD), such as depression, anxiety disorder and adjustment disorder, is a problem in many Western countries, including Sweden, Germany, the UK and the Netherlands . MoreoveIn 2000, the Netherlands Society of Occupational Medicine (NVAB) developed a practice guideline entitled ‘The management of mental health problems of workers by occupational physicians’ and revised it in 2007 ,11. ThisTo evaluate the effect of guideline-based care by OPs on the full RTW of workers sick listed due to CMD.In describing the design of this study the CONSORT 2010 statement was followed to improve the reporting quality for randomized controlled trials (RCT) .The study is designed as a two-armed cluster RCT with randomisation at the OP level Figure . All parThe Medical Research Ethics Committee of Elisabeth Hospital in Tilburg approved the study design, protocol, information letter and brochure, questionnaires, and informed consent. Participation of workers is voluntary and all participants signed an informed consent. Each participant was informed about their right to withdraw from the study at any time.The Dutch guideline ‘The management of mental health problems of workers by occupational physicians’ promotes an activating approach of the OP as case and care manager to enhance the problem-solving capacity of the workers to achieve RTW. The guideline is based on cognitive behavioural principles to enhance the problem-solving capacity of workers in relation to their work environment, and process-based evaluation.The guideline consists of four consecutive steps:1) Problem orientation and Diagnosis: an early involvement of the OP is promoted (first assessment and start of counselling about 2 weeks after the worker reported sick). A simplified classification of mental health problems is introduced in four categories: i) Stress-related complaints, ii) depression, iii) anxiety disorder, and iv) other psychiatric disorders. Furthermore, problem inventory should focus on factors related to the worker and their work environment and the interaction between these two.2) Intervention/Treatment: the OP acts as case manager by monitoring and evaluating the process of recovery . When recovery stagnates OPs should intervene by acting as care manager by using cognitive behavioural techniques to enhance the problem-solving capacity of the worker, providing the worker and work environment with information/advice on the recovery and the RTW process, contact the general practitioner when problems remain the same or increase, and refer the worker to a specialised intervention when necessary. In addition, the OP should advise the work environment  how to support the worker and enhance the recovery and RTW process.3) Relapse prevention: Integration of relapse prevention from the first contact with the worker by enhancing the problem-solving capacity of the worker.4) Evaluation: During follow-up meetings evaluation of the recovery process includes the perspectives of the worker, supervisor, and other involved professionals. Follow-up meetings with the worker should take place every 3 weeks during the first 3 months, and then every 6 weeks thereafter. The supervisor or work environment should be contacted once a month. Follow-up contacts with the general practitioner or other professionals should take place when the recovery process stagnates or when there is doubt about the diagnosis or treatment.OPs participating in the study and allocated to the intervention group received training in the guideline before the start of the study. This training was specifically designed for the purpose of this study and consisted of 8 meetings within 12 months. Each meeting took 2 h and was provided in groups of 4-6 OPs under the guidance of a trainer. The aim of the training was to enhance guideline adherence of the participating OPs by focussing on barriers that prevent OPs from using the guideline and finding solutions to overcome these barriers. This is considered to be a successful strategy for the implementation of guidelines ,16.During the 8 meetings the (key) recommendations within each consecutive step of the guideline were discussed. These discussions first focussed on barriers that would hinder OPs from using the specific recommendation in practice. The analysis of barriers was structured and based on an existing framework of barriers . AccordiThe OPs in the control group do not receive additional training. They provide care as usual to workers on sick leave. In the Netherlands this means that the OP guides the sick-listed worker during sickness absence, recovery, and RTW. In this process the OP makes a diagnosis, assesses the ability to work, gives advice on work adaptations to the worker and the work environment, and provides relapse prevention. Although OPs are expected to work in accordance with the Dutch guideline, their actual adherence is low ,13.The extent of guideline adherence of the participating OPs will be measured by auditing the medical records of workers.All 66 participating OPs were recruited between October 2010 and January 2011 from the collaborative OHS. A researcher presented the study during OP meetings at several agencies of the OHS, provided written information about the study, and provided a registration form and informed consent. OPs participated on a voluntary basis; after completing the training the OPs in the intervention group received educational credits.The study is conducted in the southern part of the Netherlands. The workers eligible for this study are on sick leave due to CMD diagnosed by the OP, counselled by an OP participating in the study, have had a first meeting with the OP, and are aged 18–65 years. From all eligible workers data on sick leave and RTW will be extracted from the registration system of the OHS anonymously.Workers eligible for the data collection by means of the questionnaires work at one of the ± 320 companies served by this collaborating OHS that gave permission to invite their workers. The companies vary in size and serve different sectors. These workers are selected from the registration system of the OHS after their first consultation with the OP. They are sent an invitation letter from the OHS, as well as written information about the study. Workers who do not want to be contacted further can indicate this on a reply card. All eligible participants are contacted for additional information, and to check the inclusion and exclusion criteria. If the worker is willing to participate in the study and meets all the selection criteria, an informed consent and the baseline questionnaire will be sent to the worker.Inclusion criteria for this study are: 1) CMD is the primary reason for sick leave diagnosed by an OP according to the Dutch Classification of Diseases (CAS) which is based on the ICD-10, 2) on current sick leave when selected from the registration system of the OHS after the first meeting with the OP, and 3) adequate command of the Dutch language. Exclusion criteria are: being suicidal, and a physical problem being the primary reason for sick leave at the time of study inclusion.Table The primary outcome is the time to full RTW. For this purpose the number of calendar days between the first day of sickness absence due to CMD and the first day of full RTW is calculated. Working the same hours as prior to the sickness absence in own or equivalent work for at least 4 weeks is considered full RTW. This means that reporting sick within 4 weeks of full RTW is not considered as a new period of sickness absence.•Partial RTW is defined as the number of calendar days between the first day of sickness absence due to CMD and the first day of RTW, irrespective of the number of working hours per week.•Total number of calendar days of sick leave is calculated for the 1-year follow-up period.•CMD symptoms are measured by the Four Dimensional Symptoms Questionnaire (4DSQ), a self-report questionnaire measuring the four dimensions of common psychopathology: distress, depression, anxiety and somatisation. The 4DSQ consists of 50 items  and refers to symptoms during the past week. The 4DSQ has good psychometric properties .•Burnout symptoms are measured by the Utrechtse Burnout Scale-General Survey (UBOS) , which i•Workability is measured by three questions  of the shortened version of the Work Ability Index (WAI) ,22. The •Personal characteristics such as age, gender, level of education, sick leave in the previous year, history of mental disorders, and expectations about full RTW are measured at baseline.•Work characteristics such as number of working hours, contract type, type of work, profession and job content are measured at baseline. Job content is measured with the Dutch version of the Job Content Questionnaire (JCQ) , a self-Factors which can be influenced by the intervention and thereby can influence RTW are also measured. The results of these additional measures will be reported separately from the results of this RCT.•Coping style is measured with the shortened 19-item version of the Utrecht Coping List (UCL) , a self-•Self-efficacy with regard to RTW is measured by the RTW-SE for workers with mental problems. The RTW-SE is a self-report questionnaire which assesses the self-efficacy in the RTW process. The RTW-SE shows promising reliability, validity and prediction of actual RTW within 3 months .•Remoralization (perception of recovery) is measured with the 12-item Remoralization Scale (RS-12). The RS-12 is a self-report questionnaire which indicates the level of morale in mental health care and has shown promising reliability and validity .•Workers’ experiences with the consultations with their OP, and the contact with their supervisor, are measured. For example, the number and content of the consultations, and the topics of the conversations. Satisfaction with the counselling by the OP is measured with an adapted version of the Patient Satisfaction with Occupational Health Professionals Questionnaire (PSOHPQ) .•Experiences of the supervisor are measured using self-formulated questions. This questionnaire includes topics such as the contact with worker and the OP, previous experience with CMD and sick leave in general, and policy on sick leave and RTW [see Additional file A power analysis was performed to determine the sample size needed to detect a difference between the control and intervention group with respect to the time workers fully return to their work (primary outcome measure). Proportions of full RTW were adopted from previous studies ,30. It wRandomisation takes place at the OP level, because workers cannot be randomly allocated to an OP in the intervention group or an OP in the control group since every OP is allied to a specific company. All participating OPs are randomised by computerised allocation to the intervention group or control group at OHS agency level.Workers and companies are blinded for randomisation since they are not aware of the allocation of their OP. The researcher who performs the analyses (KvB) is blinded for allocation to intervention or care as usual.Survival analyses will be used to analyse the primary outcome (time to full RTW) and the time to partial RTW comparing the intervention and the control group, while taking into account the effect of clustering of workers within OPs. Longitudinal multilevel analysis will be used to analyse the secondary outcomes.To detect significant differences in the baseline characteristics between the intervention group and control group descriptive analyses will be used. If necessary these differences will be taken into account in the effect evaluation.The societal relevance of this study consists of substantial personal, social and financial savings if guideline-based care leads to faster and sustainable RTW of workers with CMD. Since previous studies indicate that guideline adherence of OPs can lead to a shortened sick leave duration ,12,13, tA strength of this study is the collaboration with one of the largest OHS in the Netherlands; this provides a diversity of companies covering many sectors, yielding a heterogeneous population which allows to generalise the results to a larger working population. Furthermore, because the innovative training is spread over one year, OPs can explore the barriers, apply solutions, evaluate their experiences, and adapt the solutions until they are useful in daily practice. This is in contrast to earlier studies which evaluated short term training only. Another strength is that the participating workers are selected by the registration system of the OHS and not by OPs; this may prevent selection bias from the individual OPs. Finally, the workers are blinded for randomisation to the intervention or control group to prevent performance bias.Limitations: although the extent of guideline adherence by OPs will be measured by auditing the medical records of workers, there is a risk that this will not provide accurate information on guideline adherence: e.g. OPs might not document everything that occurred during the counselling. Another limitation might be that 232 workers are needed and followed during one year, whereas earlier studies had a problem recruiting sufficient workers. However, collaborating with one of the largest OHS in the Netherlands should ensure sufficient sick-listed workers, i.e. 60 OPs need to counsel 3-4 workers each to reach the total of 232 workers.This study will show whether guideline-based care in fact leads to faster and sustainable RTW. If the results are promising, this study will contribute to lower societal and financial costs and less negative consequences for workers with CMD. The training may also give OPs the tools to better handle the guideline in daily practice. Moreover, the approach applied in this study may be relevant for the implementation of this and other  guidelines in daily practice. Results of this study will become available in 2015.CMD: Common mental disorders; RTW: Return-to-work; OP: Occupational physician; OHS: Occupational health service; NVAB: The Netherlands society of occupational medicine; CAS: Dutch classification of diseases; 4DSQ: Four dimensional symptoms questionnaire; UBOS: Utrechtse burnout scale; WAI: Work ability index; JCQ: Job content questionnaire; UCL: Utrecht coping list; RTW-SE: Return-to-work self-efficacy scale; RS-12: 12-Item remoralization scale; PSOHPQ: Patient satisfaction with occupational health professionals questionnaireBT is the copyright owner of the 4DSQ and receives copyright fees from companies that use the 4DSQ on a commercial basis . BT received fees from various institutions for workshops on the application of the 4DSQ in primary care settings.JvdK was manager and main author in the development of the NVAB guideline. JvdK does not receive fees for the use of the guideline.KvB, EB, MJ declare that they have no competing interests.EB, BT, JvdK, JvW, KvB, MJ designed the study and developed the intervention. KvB drafted the manuscript and is responsible for the data collection of the effect study. All authors provided comments on the drafts of the manuscript and approved the final version of the manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2458/13/193/prepubAn additional file shows this questionnaire for supervisors.Click here for file


Telehealth is the exchange of health information and the provision of health care services through electronic information and communications technology, where participants are separated by geographic, time, social and cultural barriers. The shift of telemedicine from desktop platforms to wireless and mobile technologies is likely to have a significant impact on healthcare in the future. It is therefore crucial to develop a general information exchange e-medical system to enables its users to perform online and offline medical consultations through diagnosis. During the medical diagnosis, image analysis techniques combined with doctor's opinions could be useful for final medical decisions. Quantitative analysis of digital images requires detection and segmentation of the borders of the object of interest. In medical images, segmentation has traditionally been done by human experts. Even with the aid of image processing software (computer-assisted segmentation tools), manual segmentation of 2D and 3D CT images is tedious, time-consuming, and thus impractical, especially in cases where a large number of objects must be specified. Substantial computational and storage requirements become especially acute when object orientation and scale have to be considered. Therefore automated or semi-automated segmentation techniques are essential if these software applications are ever to gain widespread clinical use. The main purpose of this work is to analyze segmentation techniques for the definition of anatomical structures under telemedical systems. Access to medical care is sometimes very difficult to be reached from people living in rural and underserved areas. The implementation of systems support different telehealth technologies as well as on evidence-based medicine. A fundamental change in the management and delivery of healthcare, by leveraging telehealth applications and solutions, is crucial to get the most cost-effective and efficient use out of available healthcare resources. It is therefore crucial to develop a general information exchanged e-medical system to enable its users to perform online and offline medical consultations. This means by consultation of additional medical experts, medical diagnosis can be stated more precisely, and certified. During the medical diagnosis, image analysis techniques combined with doctor's opinions could be useful for final medical decisions.Telehealth is the exchange of health information and the provision of health care services through electronic information and communications technology, where participants are separated by geographic, time, social and cultural barriers . It reprOver the past years, simulator-assisted training in healthcare has become increasingly important. Simulation refers to the artificial generation, representation, and interaction of a complex-real-world process. In the medical area the trainee has the ability to realistically learn a number of skills without the physical presence of a real patient. The benefits are availability and evaluation of different medical cases; clinical human performance and mastering complex or even critical situations offers a safe study environment in absence of the physical patient, especially in cases where the distance is a crucial parameter for the diagnosis and treatment. Because there is a close relation between telemedicine and medical imaging, it is essential to develop e-medical systems appropriate to provide information for the anatomical structure of the human body.Moreover the online-mode gives the opportunity to communicate over far distances with a given partner in real time. In this case both partners look at the same image material and through text messages (chat window) and transfer mouse actions to the remote PC, where they can discuss interactively over a medical case.Methods for providing that kind of information are based on segmentation techniques. Methods for performing segmentations vary widely depending on the specific application, imaging modality, and other factors like treatment  or diagnostic imaging –4.In this work we will present segmentation techniques that improve the time and interaction one needs to define one or more structures. This methodology involves interpolation methods for the volume definition  and methods for the semiautomatic organ shape extraction. Once an accurate segmentation is obtained, this information may be used by the doctors to compare the volume and morphology characteristics of each region against known anatomical norms, other regions in the same image set, and corresponding regions in related image sets.Telemedicine, and recently e-health, are the names of telecommunication tools, which are able to improve the equitable access to healthcare. The ability of telemedicine to facilitate medical care, irrespective of distance and availability of medical specialists on site, makes it attractive to the healthcare sector. Telemedicine allows better utilization of scarce medical personnel and resources. Telemedicine promises to enhance continued on-the-job medical training of doctors, nurses, and other healthcare practitioners in rural areas, and this perspective is extremely useful for all developing countries.Telemedicine is defined as the practice of medicine at a distance, where a messenger carrying over a medical advice from a distant expert to the bed of a patient. Medical care can be provided through these systems almost anywhere at anytime. The physicians and health care organizations are therefore able to guarantee high-quality care, without the patient having to travel and being carried over long distances.Effectiveness of the telemedical systems could be seen especially in demanding diagnostics (cancer disease) where distance is an important factor in patient treatment (radiotherapy). Radiotherapy is one of the most effective forms of cancer treatment, undergone by roughly a third of all cancer patients. Once cancer has been diagnosed, patients generally have three fundamental treatment alternatives: surgery, radiotherapy, or chemotherapy. None of these options is particularly comfortable, and they each have positive and negative aspects. Radiotherapy is the only choice in certain cases, such as fast-growing tumors, in the postoperative treatment of breast or lung cancer, some prostate types and many others, where radiotherapy is often used to prevent the regrowth of malignant tissue.The scope is on the one hand the virtualization of the complete treatment planning procedure , on the other hand to make the virtual patient available on different sites than those of its physical location and therefore allow telematics cooperation of radiooncology centers. The first fact will mainly increase efficiency of personnel and accuracy  of treatment, while the second will mainly reduce costs by allowing virtual sharing of extremely expensive devices as well as remote expert assistance/service. Although system demonstration will be based on a worldwide commercially available radiotherapy planning system which will extend its efficiency by adding telematics components, mainly based on generally available networks .The main efforts will be entirely focused on developing the innovative telematics tasks and implementing these on existing professional and commercially available technology. Due to the availability of telematics components expensive devices such as CT (Computed Tomography) scanners will become virtually available to hospitals without such devices physically present. In addition, remote experts can generate the treatment plan of a patient and/or validate plans of their colleagues on-line (consultation conference) or off-line (desktop system).Powell III  states tTo generate views from different anatomical structures contained in CT data sets or to perform treatment planning techniques, it is essential (1) to extract the corresponding data from the image and (2) to accurately define the target volumes as well as the organs at risk for the treatment outcome; both methods can be done via segmentation process.The first fact will mainly increase efficiency of personnel and accuracy  of treatment, while the second will mainly reduce costs by allowing virtual sharing of extremely expensive devices as well as remote expert assistance/service. The main efforts will be entirely focused on developing the innovative telematics tasks and implementing these on existing professional and commercially available technology.In order to make possible the data transference, a telemedical platform must be implemented. Aim of the platform is the collaboration between doctors and/or citizens located in countries with different health care systems, different technology infrastructure, and different needs, in order to enhance the quality of health care services and the equal access to the health care systems. Through the platform will be possible the efficient handling of patients with chronic diseases, the early response to emergency incidents, and the reduction of human lives losses. Based on the system platform users are able to perform online and offline medical consultations. In addition to the given possibilities telemedical systems offer the following features: (1) sending and receiving of multimedia messages with text, image material, and audiomessages, over Internet, ISDN and analog phone line in offline and online mode. (2) Graphical and textual annotations and pictograms can be added to the images. (3) In the online mode interactive communication via usage of a chat window, mouse, exchanged images, and a consolidated screen view is possible. Support of the operation in a telemedicine center and consultation clients through a client-server database all image of the patient and message-information will be stored constantly. The principle of the online teleconsultations is to bring two geographically distanced doctors together in an online session. During that session, both doctors will have the same view on the images and can communicate through additional communication features like chat, annotations, and so forth. In that way, expert knowledge and advice is provided to doctors in rural and crisis situation areas, or simply to any doctor in the field, who needs help in diagnosing a clinical case and do not want or is not able to send the patient to the expert physically . ExtendeThese systems have the ability to generate 2D and 3D images using only the original CT data of the patient. The 2D images displayed are the original axial CT, MR, or PET. Multiplanar reconstructions (MPR) can be generated in real time in the orthogonal, coronal, and sagittal directions, and any oblique direction. The 3D reconstructed images are a must in CT-Sim systems in order to simulate the patient anatomy and the images generated from the real simulator or the treatment machine. The first layout contains four windows and the displayed images are the Beam's Eye View (BEV), the Observer's Eye View (OEV) and the Room View (RM), together with the axial slices. The second layout is composed again of four windows, containing the three orthogonal slice directions and the OEV. This layout is ideal for navigation through the CT volume, for volume delineation and to observe complex radiation field arrangements. The last layout contains every image described above. This layout has six windows emphasizing the size of the BEV image, since the physicians feel comfortable working with this image. In both rendering views, OEV and BEV, the volume orientation is controlled using a mouse track ball. The important RTP imaging is the dynamic X-ray image on the Simulator monitor, which is generated from the viewpoint of the beam source, called Beam's Eye View (BEV) image, see the BEV view direction in The system can use large amounts of data, from 40 up to 300 slices, in order to produce high-quality anatomical images. It enables reading of CT data, acquired not only with a single slice CT scanner (such as a Siemens SOMATOM Plus 4), but also multislice data ranges, acquired in this study with four slices (SOMATOM Volume Zoom). It can be connected via network directly to any CT scanner that supports DICOM protocol. The system allows the adaptation to any LINAC configuration through a machine configuration module that is designed according to the international standard for radiotherapy equipment (IEC 1217). This configuration involves limitation on movements of the mechanical component and description of the component's dimensions .Instead of the presence of the physical patient's body, a virtual patient's body as well as the VS machine is displayed, which is called the Simulator Window. Through the Simulator window, the physicians can investigate the movements of the machine as they observe it through the lead glass in their Simulator operation room; see the Sim view direction in The effect of the radiotherapy treatment is based on the precise delivery of high irradiation dose on the tumor site without damaging the surrounding healthy tissues. Therefore patient positioning, target volume definition, and irradiation field placement are very critical steps while planning the irradiation process. One of the significant technological advances in radiotherapy in the past 20 years is the implementation of CT or Virtual Simulators (VS), in the clinical routine. Sherouse et al. in 1987 . Using VCollect patient's CT data including attached aluminium markers.Transfer CT data to VS. The physician defines the tumour volume and the organs at risk and she/he will place the necessary fields relative to the tumour volume.The simulation plan and the CT data are transferred via DICOM  server to the TPS for dose calculation and final treatment plan optimization.Verify patient position on LINAC before irradiation.Perform treatment on the treatment machine (Linear Accelerator or LINAC).During the images' transferring in teleradiology important factor for effective diagnosis is the exchanging time. Crucial involvement to this achieved has the volume rendering process. Volume rendering is the technique according to which a scalar field of data with discrete values, volume data, is selectively sampled in order to generation a useful image in relation to the sampled values. A volume data set is typically a set of discrete samples of one or more physical properties in a limited object space.V(x), x ∈ Rn, in which {x} is a set of sampling points; n is the dimension of the sampling space, usually n = 3, that is, 3D volume data; V represents the sampling values, it can be a single-valued or multivalued function. According to the distribution of sampling points , volume data sets are classified into structured and unstructured data sets. In medical imaging, volume data is usually a structured data set, typically organised as a stack of slices; V can be single valued  or multivalued . The resulting data structure is an orthogonal 3D array of voxels, each representing a sampling value.A volume data set is typically a set of discrete samples of one or more physical properties in a limited object space, Kλ is the attenuation coefficient and λ is the wavelength in distance D  and around normal tissues and organs of interest on a slice-by-slice basis. This provides at the same time, a cross-reference to planar images.Organs with large differences in their radiation dose distributions can be segmented semiautomatically. In terms of user effort the only action required from the user is the selection of a starting point for the algorithm on the original axial slices. The complete 3D geometry of the organ will be traced automatically. Performance analysis of the system is taking place where the experiments are performed on a double processor (2xPentium III 450 MHz) PC with physical memory 512 Mb. For each view we performed time measurements for several rendering image sizes using different data resolution. The goal of this experiment is to examine the volume rendering interactivity as well as to prove the effectiveness of the system for large amount of data.A comparison for the system memory relative to different amount of data is presented in Accuracy of the system is very important for the system implementation especially for the investigation of (1) CT volume data orientation and (2) treatment parameters, including table translation, gantry, collimator, and table rotation, reference point placement, beam, and block size. Commonly slices thickness between 3 mm to 5 mm and total number of slices maximum to 120 slices are used to implement segmentation analysis or radiotherapy treatment planning dose. A cubic phantom of size 120 × 120 mm was initially used to exam the accuracy of the system. Inside the phantom spheres of diameter 2 mm are placed in constant distance. The phantom was scanned using 1 mm slice thickness. The total number of produced slices was 120, in square CT matrices of 512 × 512 pixels. The recorded system error concerning the table translation is at ±1 mm. The beam size and the projected light field size matched completely. No isocenter sphere effect occurred during component rotation. The interactive landmark registration routine might have the error of the slice thickness. The accuracy of the routines automatic field and block adaptation is related to the resolution of the BEV image . In mostCT-Sim is a technological advance that has already been tested in our clinical environment with demonstrable advantages particularly for complicated field arrangements. The new, innovative virtual simulator system is a very useful additional tool for the radiation oncologist and makes the requirement for a conventional X-ray simulator redundant. A significant advantage of the software is that it can run on portable computers such as laptops. This makes the CT-Sim concept extremely cost-effective. The system can be integrated immediately into the clinical environment via a direct interface to the CT scanner. The advantages of CT-Sim are not limited only to those mentioned above. Combination of different diagnostic  and radiotherapy  imaging modalities will make the CT-Sim an even more effective tool in radiotherapy. This technology could be combined with telemetrically techniques for the improvements of health services telemedicine applications are largely image-based. The main purpose of this work is to represent an efficient interactive, easy-to-use medical system that provides modules for online and offline collaboration of medical doctors together with software products. Moreover new improvements for the system starts to be implemented based on telemedical applications (this work is under development) where an online mode gives the opportunity to communicate over far distances with a given partner in real time. In this case both partners look at the same image material and through text messages (chat window) and transferred mouse actions to the remote PC, they can discuss interactively over a medical case. The system combines low price, low weight, mobility, and a wide range of nonradiating examinations. As a result the proposed platform reduces the disparity in the level of medical services, between the main centers and the less assisted areas, contributing to improvement of the quality of life.


Only few studies have looked at electromyography (EMG) during prosthetic gait. Differences in EMG between normal and prosthetic gait for stance and swing phase were never separately analyzed. These differences can give valuable information if and how muscle activity changes in prosthetic gait.In this study EMG activity during gait of the upper leg muscles of six transfemoral amputees, measured inside their own socket, was compared to that of five controls. On and off timings for stance and swing phase were determined together with the level of co-activity and inter-subject variability.Gait phase changes in amputees mainly consisted of an increased double support phase preceding the prosthetic stance phase. For the subsequent (pre) swing phase the main differences were found in muscle activity patterns of the prosthetic limb, more muscles were active during this phase and/or with prolonged duration. The overall inter-subject variability was larger in amputees compared to controls. During rehabilitation transfemoral amputees learn to adapt their gait pattern to walk with a prosthesis. Several of these adaptations are already known. During gait the stance phase of the amputated limb shortens compared to that of the intact limb. Therefore the swing phase is longer for the amputated limb. The double support phase elongates when the amputated limb becomes the stance limb and shortens when the intact limb becomes the stance limb ,2. The cHowever, little research has been performed on electromyography (EMG) during amputee gait. EMG of residual limb muscles of TFA may give valuable information on adaptations besides those that can already be found using the kinetic and spatio-temporal data . Some stIn the current study we focus on muscle activity during the stance and swing phase of prosthetic gait. Do the muscle activity patterns of the prosthetic limb change and how do they change for the stance and swing phase, compared to normal gait? We intended to have as little interventions to the prosthesis and the subsequent walking pattern as possible. Therefore we measured EMG inside the socket, without modifications, of six amputees and compared this to data of five controls. Previous studies have shown that it is possible to measure EMG with acceptable quality inside the socket of amputees ,10.From this data we determined if the timings of the muscle activity changed with respect to the different phases of gait compared to normal gait. We hypothesized that the general EMG patterns during walking are comparable to those in controls, but we expected to find differences related to specific adaptations in amputees. Three muscles at the contralateral lower leg were also measured to determine the adaptations at the intact lower leg. We determined how the inter-subject variability of amputees compares to that of controls. Spatio-temporal and kinematic data were also measured for gait phase determination and to relate the results to other studies to determine the gait phases and to compare the results to previous studies.Eleven healthy subjects participated in the study, five controls and six unilateral amputees. All subjects were recruited between April and July 2011. Of the amputees there were three transfemoral amputees (TFA) and three through the knee amputees (TKA). An overview of the amputees can be found in Table EMG recording was performed on eight upper leg muscles in all subjects: m. gluteus maximus (GMa), m. gluteus medius (GMe), m. tensor fasciae latae (TFL), m. rectus femorus (RF), m. vastus lateralis (VL), m. biceps femoris (BF), m. semitendinosis (ST), m. adductor magnus (Add). In amputees these were measured on the residual limb, in controls these muscles were measured at one limb, which was alternated between dominant and non-dominant limb. For amputees and controls this limb will be called the “prosthetic limb” and “mimicked prosthetic limb” respectively.At the contralateral lower limb three more muscles were measured, the m. tibialis anterior (TA), m. gastrocnemius medialis (GaM) and the m. soleus (Sol). For amputees and controls this limb will be called the “intact limb” and the “mimicked intact limb” respectively.Electrodes were placed according to the SENIAM standards , by an eFootswitches, placed mid-heel and under the first metatarsal head of each the foot, gave information about initial contact and initial swing. Footswitch data was registered with the Porti-system.Kinematic data were measured (100Hz) using inertial sensors from Xsens , with 3D accelerometers, 3D gyroscopes and 3D magnetometers. Two inertial sensors were placed at the upper and lower (mimicked) prosthetic limb. Subjects wore their own low-heeled shoes.To synchronize EMG, footswitches and inertial sensors a synchronization pulse (sync) was given at the start and end of each measurement which was visible in all data sets.For the experiments the subjects were asked to walk at a self selected walking speed. After data recording was started, the sync was pressed and subjects started walking. After five steps they were asked to stop, turn around, wait 2-3 seconds, press the sync and walk back; this constituted one trial. Four trials were performed in all subjects.From the footswitch data the timings of initial contact (IC), terminal stance, initial swing and loading response of each limb were determined . Foot swThe inertial sensor data was expressed in the body coordinate system based on a sensor-segment calibration procedure as described by Wentink et al. . This daEMG data was first high pass filtered at 10Hz and subsequently low pass filtered at 500Hz, both with a second order butterworth filter. In Figures The stance and swing phase of the (mimicked) prosthetic limb were calculated per subject and expressed as percentage of the total stride time. Using the average muscle on/off timings per subject, we subsequently calculated for which percentage of the stance or swing phase the muscles were active. These were subsequently averaged for the controls and the amputees. Differences between controls and amputees were analyzed using a Kruskal-Wallis test. The level of alpha was set at 0.05.The inter-subject variability of the EMG data was determined using the variance ratio (VR) for each subject and muscle for the stance and the swing phase ,18. The er group .In Table Table In Figure During the (prosthetic) stance phase, the GMa of the amputee group is active for a longer period after initial contact. All other upper leg muscles are active for a similar or shorter period. In the amputee group, some muscles, become active a second time during stance; the TFL, VL, BF, ST and Add. In the controls this second phase of activity during stance for these muscles is not seen. The first period of activity shown for the RF is probably crosstalk by the VL ,21. The During the stance phase of the intact limb, activity of the GaM starts around the same time in controls and amputees, Sol activity of amputees starts a little earlier. The activity of the TiA in amputees continues longer during the stance phase of the intact limb, compared to controls. No significant differences were found between the activation patterns of the stance phase between controls and amputees.The differences in muscle activity during the swing phase are larger than for the stance phase. The GMe and GMa of the amputees become active in the second half of the swing phase, whereas in the controls they become active at the end of the swing phase. This increased duration of activation is also seen for the RF, the VL and the BF. The TFL is also active at the transition from stance to swing, and has a later “second” activity onset at the end of the swing phase. The Add is active in amputees before initial swing and at the beginning of the swing phase, which is not the case in controls.TiA activity during the swing phase of the intact limb starts later in amputees compared to controls. No differences are seen in GaM activity during the swing phase of the intact limb, but the Sol of the amputees shows activity during the first part of the swing phase, where controls do not show this activity. No significant differences were found between the activation patterns of the swing phase of controls and amputees.The overall inter-subject variability of the EMG data of amputees is significantly lower (p = 0.011) than that of controls Figure . The varThe kinematic data showed that the stance phase duration of the intact limb increases and the prosthetic swing phase duration also increases in amputees. This coincides with the general concept that amputees tend to stand longer on their intact limb than on their prosthetic limb, which has also been found in other studies ,2. Knee The differences found in muscle activity between prothetic users and controls are mainly present in the (pre)swing phase. Muscle activity of controls resembles that of previous studies, although muscles show activity for a longer period of time ,22. ThisWhen the gait stance and swing phases are compared separately, muscles in amputees do not seem to be active for much longer than in controls. At the end of the stance phase a period of activity is seen in most of the upper leg muscles, starting around the beginning of the second double support phase. This may be the mechanism by amputees to increase socket fitting at the end of the stance phase, to prepare for lifting of the prosthesis in the swing phase . Lower lSome of the upper leg muscles of the amputees, the BF and the VL, remain active for almost the complete swing phase. The other muscles all become active again at the end of the swing phase to prepare for initial contact. These muscles show an earlier activity onset than in controls, which may be explained by the walking strategy of amputees. Many amputees try to fully extend the knee to ensure it is locked at the end of the swing phase which is also confirmed by the reduced knee flexion during initial stance.Our results resemble the results presented by Jaegers et al. , as far TFA showed a different activation pattern in some phases of the gait cycle, which shows that they adapt to their new prosthetic situation. Although the results show that consistent muscle activity can be measured inside the socket of TFA, the usability for prosthetic control is questionable. Variability between the amputees is higher, although patterns within the amputees are consistent. Although muscle activity patterns can change due to the disturbed anatomy by the amputation and by use of the prothesis, training may allow TFA to learn new walking patterns which in turn may need adaptations in the muscle activity patterns to control a prosthesis .The overall inter-subject variability of the EMG data from the amputees was significantly higher than that from controls. VRs per muscle were however for none of the muscles significantly different. Granata et al.  reportedMany of the muscles in the upper leg of the amputees are cleaved. The electrodes were placed and tested for activity according to the SENIAM standards. However, due to the amputation some muscles may have a different location and the location of the electrodes may not have been ideal. Rotations in the socket may also affect the position of the electrodes with respect to the muscle. Poor socket fitting will affect the repeatability of the signal, this will induce more noise and the prosthetic user may show more muscle activity to properly control or fit the prosthesis. One subject complained of non-optimal socket fitting as it was too large. This subject had a higher VR. None of the subjects complained about the EMG electrodes, they did not seem to effect the socket fitting. However, this does not explain the increased VR in the lower leg muscles of the contralateral limb and the hip muscles. This might indicate that the walking pattern of amputees is less consistent than that of controls. The standard deviations within amputees for spatio-temporal and kinematic data were also larger than in controls.The amputees were a mixed group. No inclusion criteria for type of amputation or time since amputation were added. The average age (52.3) was larger than that of the controls (23). Previous studies have shown that aging may affect the spinal cord activity, walking speed and cause a higher spread in muscle activation ,26. AlsoA more homogeneous and larger group of amputees with similar prosthesis may reduce the variability between the subjects. We did not find any obvious differences between the different knees, but this may also be caused by the low number of amputees. Including amputees with a short residual limb as Jaegers et al. ,3 did, cIn amputees the double support phase before the prosthetic stance phase increases significantly and the prosthetic swing phase shortens. EMG patterns mainly differ at the end of the stance phase and in the swing phase. These changes can explain the changes in walking strategy, but are likely also required to improve socket fitting. In this study EMG was measured inside the socket of amputees, and the data showed to be of comparable quality compared to that of controls. Variance within each amputee is higher than in controls, but variability in the kinematic data between the amputees is also higher. The increased variance may mainly be caused by the variability in walking pattern and cleavage of muscles.The authors declare that they have no competing interests.EW was involved in the study design, the setup of the measurement protocol, the measurements, the data analysis, writing and revision of the manuscript. EP participated in the setup of the measurement protocol, the measurements, drafting, and revision of the manuscript. HR contributed to the study design and drafting of the manuscript. PV participated in the study design, the data analysis and drafting of the manuscript. All authors read and approved the final manuscript.


The DRIMust algorithm is based on the minimum hypergeometric statistical framework and uses suffix trees for an efficient enumeration of motif candidates. DRIMust takes as input ranked lists of sequences in FASTA format and returns motifs that are over-represented at the top of the list, where the determination of the threshold that defines top is data driven. The resulting motifs are presented individually with an accurate P-value indication and as a Position Specific Scoring Matrix. Comparing DRIMust with other state-of-the-art tools demonstrated significant advantage to DRIMust, both in result accuracy and in short running times. Overall, DRIMust is unique in combining efficient search on large ranked lists with rigorous P-value assessment for the detected motifs.Cellular regulation mechanisms that involve proteins and other active molecules interacting with specific targets often involve the recognition of sequence patterns. Short sequence elements on DNA, RNA and proteins play a central role in mediating such molecular recognition events. Studies that focus on measuring and investigating sequence-based recognition processes make use of statistical and computational tools that support the identification and understanding of sequence motifs. We present a new web application, named DRIMust, freely accessible through the website  The study of sequence elements that enable molecular recognition in a variety of cellular processes is an important component in improving our understanding of regulation in living cells. Transcription factor (TF) activity, for example, often depends on the identification of specific targets using molecular pattern recognition mechanisms that involve sequence motifs. Sequence recognition plays a role in other molecular levels, as well. The occurrence of short binding motifs in RNA molecules plays a central role in enabling controlled regulation by RNA-binding proteins (RBPs) and by microRNAs. For example, the Pumilio family proteins regulate target messenger RNAs by recognizing and binding sequence elements in 3′ untranslated regions (UTRs) . ProteinStudies using techniques such as ChIP-chip , ChIP-PEP-value is indicated. DRIMust is freely accessible through the website http://drimust.technion.ac.il/.In this work, we introduce the DRIMust web server and describe its utility in supporting the search of rank imbalanced motifs. DRIMust takes as input ranked lists of sequences in FASTA format and returns motifs that are over-represented at the top of the list, where the determination of the threshold that defines top is data driven. In cases where sequence ranking is not relevant or not available, DRIMust allows the user to upload positive and negative sets of sequences. In the latter case, DRIMust will search for enriched motifs in the positive set using the negative set as the background. DRIMust is efficient and thus allows searching in large data sets, searching for long motifs as well as searching motifs over large alphabets in short running times. The resulting motifs are presented as a Position Specific Scoring Matrix (PSSM) in a graphical WebLogo format; the matrix can also be downloaded as a text file. For every motif, a et al. , the probability that b or more genes from the target set are also in A is given by the tail of a hypergeometric random variable (HGT):We have previously described an algorithm to identify the enrichment of a set of genes, atistics . Given aA, that is, For a ranked genes list P-value of a given mHG score is described in  time, where A suffix tree is a data structure that represents all the suffixes of a given string in a way that allows fast implementation of many string operations. A path from the root to a leaf in the tree represents a suffix. Each leaf of the tree holds information about the indices of strings that contain the suffix, and the starting positions of this suffix within each such string. Restoring all occurrences of a suffix is thus enabled, which further allows for the detection of DNA, RNA or protein substrings that manifest a significant occurrence pattern in a set of biologically related sequences. There are several algorithmic approaches to the efficient construction of a suffix tree for a collection  strings . DRIMusttruction .k in the generalized suffix tree generated for the input sequences. Next, the statistical significance of the k-mers is calculated using the mHG statistics .


Purpose. A standard coronectomy  is recommended for mandibular third molar (MTM) extraction cases with a high risk of inferior alveolar nerve injury (IANI). However, complications such as inadvertent intraoperative root removal, post-op root migration, second molar (MSM) periodontal defects and others do exist. This report presents a new technique, the Modified and Grafted Coronectomy (MGC), describes the measures to prevent or minimize the known drawbacks of the standard coronectomy, and reviews the literature for comparison with three other IANI-prevention techniques. Materials and Methods. MGC was performed on two MTMs with nerve involvement and severe periodontal pockets on the distal of MSM. Modifications were: stabilizing the root stump to prevent intraoperative movement, creation of a large intrabony space for bone graft material, and grafting for periodontal healing while minimizing the possibility of post-op root migration. Results. Excellent overall periodontal improvement, with probing depths reduced to 3-4 mm. Panoramic radiograph displayed remarkable bone regeneration. No residual root migration was evident at the two year follow up. Conclusion. MGC may be a good alternative, especially in cases with periodontal defects on the distal of MSM. It may also help to minimize inadvertent intraoperative root removal and postoperative root migration. The removal of impacted mandibular third molar (MTM) in close proximity to the mandibular canal has proven to be problematic. One of the more severe risks is inferior alveolar nerve injury (IANI). The prevalence of this type of nerve injury in the twenty-four prospective studies reviewed varies between a minimum of 0% , 2 and aCoronectomy is the oldest and the best researched of the IANI-risk reducing procedures –19. FirsIn the regular coronectomy, the aspect of the third molar root/s in the closest proximity to the inferior alveolar nerve (IAN) is intentionally retained. The clear benefit of a successful coronectomy is the avoidance of IANI. The disadvantages of this technique include deep periodontal pockets on the distal of the second molars (similar to those after extractions in comparable circumstances), root migration with the possible need of a second procedure, dry sockets, local postoperative infections, postoperative pain and inadvertent root removal, or root walk-out during surgery which may increase the risk of IANI  , 21, 22.Deep pockets and other periodontal damages have been previously reported on the distal of the second molar teeth after third molar removal –26. The This paper provides a description of a case of a Modified and Grafted Coronectomy (MGC), developed by the authors. The goals of the technique are to decrease the incidence of intraoperative root walkout, to minimize the potential and/or preexisting periodontal pockets distal to the second molar similar to the “Preservation of periodontal health of adjacent teeth” Specific Therapeutic Goal of ParCare 2012 [A 37-year-old female, a smoker for the past 15 years but otherwise in good general health, was repeatedly referred for extractions of her MTM due to severe localized periodontal disease at the distal of the mandibular second molar (MSM) teeth. She stated that over the last four years she had consulted five oral surgeons who each suggested third molar extraction. The patient was also advised that she would have a higher than normal chance of bilateral permanent paresthesia. She reported that her periodontist warned her about the deteriorating periodontal health of both of her lower second molar teeth. She also reported occasional pressure and intermittent pain associated with the lower right third molar. At her consultation appointment, the patient presented with a panoramic radiograph and multiple dental treatment plans, all of which included extraction of the MTMs. A new panoramic radiograph was taken  which coThe patient was given the options and risks of observation, extractions with grafting, and Modified Grafted Coronectomy. The patient chose to have bilateral MGC performed. The treatment plan was reviewed and her consent was obtained.Due to the presence of infection, she was placed on oral Clindamycin 150 mg, 40 tablets, QID, and 0.12% chlorhexidine mouth rinse twice a day beginning two days prior to the procedure. The surgery was performed with i.v. sedation and local anesthesia. A lower right full thickness distally released envelope flap was reflected. No lingual retraction was used. A bony window was created for access. An initial vertical cut with a #703 cross cut fissure carbide FG bur, 2.1 mm diameter was made above the CEJ and oriented at a 20° angle to the distal root of the second molar, to facilitate coronal fragment removal. The cut was completed at 3/4 of the tooth diameter to avoid cutting into the lingual wall and/or IAN and to avert possible lingual nerve injury or IANI. The crown was broken off, without excessive apical pressure. After the removal of the first fragment, rest seats were created in the root portion at each of the subsequent steps. These were used to apply gentle apical pressure on the distal section with the sharp end of a Molt 9A periosteal elevator while grinding, cutting, and fracturing off the coronal fragments. This action stabilized the root portion, dampened the vibration, and helped to prevent inadvertent movement and therefore pressure of the remaining root against the IAN. Next, a #10 round carbide HP bur, 2.7 mm diameter was used to grind away the distoocclusal section of the remaining stump above the IAN, well below the bone crest level . Due to The patient was seen for a follow-up visit at six days postoperatively. The surgical sites appeared to be healing within normal limits. The absence of paresthesia in the IAN and lingual nerve distribution was assessed by the patient's subjective report of normal sensation with sharp, blunt, and light touch. A follow-up panoramic radiograph was obtained . Instructions were given for the patient to return for reassessment and radiographs every six months for the first two years, and once more after the third year. The patient was advised, if there are no problems found during the first three years, to return only if she experiences any unusual symptoms.The patient and the referring dentist were advised to exercise special care with the grafted sites for the first six to nine months following treatment by not traumatizing them needlessly and to allow the graft to mature. This included no periodontal pocket charting, scaling on the distal of the second molars, and/or manipulating with any hard objects by the patient. According to the manufacturer, the grafted area becomes radiopaque in comparison to the surrounding bone indicating that the resorbable HA graft has matured.At the two-year follow-up the patient stated the areas felt fine with no sensitivity around the second molars. Periodontal examination revealed decreased periodontal pocket depths, down to three and four mm. Panoramic radiograph was obtained , displayRegular coronectomy is the best studied alternative to the extraction of teeth, which are at a high risk for IANI, as determined by radiographic signs , 33–37. IANI was the most serious complication which occurred during some failed coronectomies, where the remaining root was inadvertently mobilized during surgery. This mandated the surgeons to proceed with the extraction of the entire root in 4–38% of the cases –9, 17, aOther known complications are deep periodontal pockets on the distal of the second molar, delayed postoperative root migration with the possible need of a second procedure, postoperative pain, dry socket, and infection , 21, 22.These drawbacks could be a possible motivation for the recent emergence of additional IANI-risk reducing procedures: staged removal  , pericorWith only one recorded case of permanent IANI in its history , there iUltimately, the technique used in the case reported above appears to have the most encouraging outcome. In it we introduced a series of amendments to the standard coronectomy procedure and called it a Modified and Grafted Coronectomy. As with the standard coronectomy, MGC involves the removal of the crown and part of the root/s of an impacted MTM in cases with a high risk of IANI. This modified procedure introduces steps to prevent the complication of inadvertent intraoperative root loosening. It accomplishes this by stabilizing the radicular fragment during cutting as well as when separating the coronal section off, thus overall decreasing the risk of nerve injury. Yet as another modification, to reduce or prevent periodontal pockets on the distal of the second molar, the technique calls for the creation of periodontal “scaffolding,” which is achieved through grafting, thus the name Modified and Grafted Coronectomy. Scaling and debridement , 28 as wIn our experience with grafting, it is important to create a larger vertical space to allow for bone regeneration. According to Hatano “even if appropriate trimming 2 to 3 mm below the alveolar crest is done, bone coverage on the resected surface is sometimes delayed because of significant root migration” . CombiniMGC appears to be an alternate technique that could be considered for nearly all coronectomy cases of vertical, mesioangular, or horizontal impactions and especially in the cases which have preexisting periodontal lesions or are expected to have large postsurgical defects. A possible additional benefit is the potential prevention for the need of further pocket reduction surgery on the distal of the lower second molar, minimizing the need of subsequent treatments and visits.Possible considerations of the technique are the additional costs of the graft and the time required to perform the procedure. Further modifications and enhancements could include the use of different graft materials and/or the use of a membrane. Additional research with a large cohort of patients and randomized prospective studies are needed to verify the outcome. While more research is absolutely necessary, this new technique and/or just some of its steps appears to offer a viable alternative for a coronectomy practitioner, helpful in obtaining superior results in addition to the existing IANI-risk reduction procedures.


Analyzing the neuronal organizational structures and studying the changes in the behavior of the organism is key to understanding cognitive functions of the brain. Although some studies have indicated that spatiotemporal firing patterns of neuronal populations have a certain relationship with the behavioral responses, the issues of whether there are any relationships between the functional networks comprised of these cortical neurons and behavioral tasks and whether it is possible to take advantage of these networks to predict correct and incorrect outcomes of single trials of animals are still unresolved.This paper presents a new method of analyzing the structures of whole-recorded neuronal functional networks (WNFNs) and local neuronal circuit groups (LNCGs). The activity of these neurons was recorded in several rats. The rats performed two different behavioral tasks, the Y-maze task and the U-maze task. Using the results of the assessment of the WNFNs and LNCGs, this paper describes a realization procedure for predicting the behavioral outcomes of single trials. The methodology consists of four main parts: construction of WNFNs from recorded neuronal spike trains, partitioning the WNFNs into the optimal LNCGs using social community analysis, unsupervised clustering of all trials from each dataset into two different clusters, and predicting the behavioral outcomes of single trials. The results show that WNFNs and LNCGs correlate with the behavior of the animal. The U-maze datasets show higher accuracy for unsupervised clustering results than those from the Y-maze task, and these datasets can be used to predict behavioral responses effectively.The results of the present study suggest that a methodology proposed in this paper is suitable for analysis of the characteristics of neuronal functional networks and the prediction of rat behavior. These types of structures in cortical ensemble activity may be critical to information representation during the execution of behavior. The cerebral cortex is a dynamic network composed of a large number of neurons joined to each other by synaptic connections. Early theories maintained that brain information was represented by the firing rates of single neurons. The new theories of brain functions propose that the information transmission and processing of the central nervous system are represented by the spatiotemporal firing patterns of large neuronal populations. Spatiotemporal patterns refer to a series of regular and ordered interval spikes among neurons. In recent years, the discovery and analysis of the spatiotemporal firing patterns have been the focus of neuroscience research One of the questions addressed in this study is how animals control the different behaviors that they perform under different stimulation conditions. This is a crucial issue in developing brain-computer interface With the development of multi-electrode recording techniques, the activity of dozens of neurons can be recorded at one time The spike activities of these neuronal populations can be used to construct the WNFNs, and these networks can be divided into sub-modules. It is not known whether these network features can be used to represent behavior information. The issue of whether the functional network measurements can be used to make predictions of behavioral outcome of single trials is also unresolved. There are no relevant studies to illustrate these key issues. To solve this problem, we present a new method for investigation of the relationship between functional networks and rat behavioral choice based on the WNFNs and LNCGs obtained from multi-electrode recordings, and of using functional networks of single trials to predict the correct and incorrect outcomes of these trials. We recorded the spike activities of neurons in several rats in three areas of the cerebral cortex. The rats were trained to perform two different tasks (Y-maze and U-maze). In each behavioral task, each rat must select one of two directions in which to move. In the Y-maze task, the rat was required to choose to move left choice (L-choice) the first time and right choice the second time (R-choice). In the U-maze task, their two trial types are clockwise and counterclockwise direction. Each type is considered a trial. The spike trains between the start and end of this trial were extracted and used to construct the neuronal functional network. Each dataset of each task contained several trials. This method consists of four parts: construction of WNFNs from recorded neuronal spike trains, partitioning of these WNFNs into the optimal LNCGs using social community analysis method, unsupervised clustering all trials in each task into two different clusters, and predicting the behavioral outcomes of single trials. The results show that this method can be used to analyze the characteristics of the network structure and to predict single trial outcomes for behavior tasks. To the best of our knowledge, this is the first such study of functional brain networks and behavior prediction.All rat work described in this study have been conducted according to Animals Act, 2006 (China) and approved by the Institutional Animal Care and Use Committee of the East China Normal University and Institutes of Brain Science of Fudan University.Seven male Sprague-Dawley rats  were trained. We recorded the neuronal firing activities from seven adult male rats. The rats were deprived of drinking water for one day. The rats had to perform the two different behavioral tasks. Multi-electrode arrays were inserted into different cortical areas . Because the tasks were relatively simple, the rats could learn the behavior easily and became fully trained after several days. None of the rats made many incorrect choices, which less than 10%, during the remainder of the experiment. We then began to record the activity of neurons.The Y-maze training box is a Y-shaped box. It has three arms at angles of 120 degrees. The choice arm was 71 cm and the two award arms were 42 cm. The height of the maze was 20 cm. In the Y-maze task, the rats ran from the waiting area to left arm or right arm of the box and received a water reward, indicating the completion of the trial. The rats were supposed to choose a different arm in each trial. For example, if the first correct choice was the right arm of the Y-maze (R-choice), then in the next trial, the correct choice would be the left arm of the Y-maze (L-choice). The rats need to go back to the end of the choice arm to start the next trial after the reward was consumed. The rat was to make an R-choice and then an L-choice in alternation for the duration of the test .The U-maze training box is a rectangular track (100×80 cm). The rat had to run back and forth along the track. The rat ran from the start point (red dot) to the end point (green dot) in the correct direction (clockwise or the counterclockwise). This was considered one trial. The rat received the water reward at both ends of the track. The experimental platform is shown in The activities of neuronal populations were recorded using multi-electrode arrays . The arrays were inserted into the cerebral cortex vertically. In the Y-maze task, a microdrive array was implanted in the PFC . After surgery, the rats were allowed to recover for several days and then signals were recorded. In the U-maze task, a 64-channel (a bundle of 16 tetrodes) electrode was positioned above the bilateral dorsal hippocampi . The electrodes were then reached the hippocampal CA1 region for recording. Offline sorter software  was used to cluster the neuronal firing waveforms of each electrode and distinguish the individual neuronal action potentials. For each neuron, the spikes constituted spike trains of that single neuron.All experiments were performed in accordance with animal protocols approved by the United States National Institutes of Health (NIH). All experimental process and recording process was controlled by computer. The experimental process was monitored by a video system.In this study, a total of ten spike trains datasets were used. Five datasets were selected from the Y-maze task and five others from the U-maze task. The number of neurons, site of the cortical recording, and number of trials per each dataset are displayed in In the above datasets, Data 1–5 were recorded from five different rats at different times. Data 6 was recorded from another rat, and Data 7–10 were recorded from the same rat at different times. Due to the different times of the recordings, the number of neurons and trials in each dataset are different.Each trial was composed of neuronal spike trains. Multiple neuronal spike trains per trial were built into a neuronal functional network. Several networks can be constructed for each dataset. Each neuronal spike trains were divided into short, non-overlapping time windows (referred to as bins) and the number of spikes in each time window was calculated. In this way, the original spike trains were represented with multi-dimensional vectors. Then, the correlations between pairs of neurons were calculated using Pearson correlation coefficient kx and ky denote the number of spikes of the xth and yth neurons in the kth bin, which have means of xyr is between 0 and 1. A value of 1 indicates a strongest functional connection between a pair of neurons, and 0 indicates no connection.For simple studies, traditional methods of analyzing brain functional networks usually involve converting the network into a binary network, formed by thresholding matrix R by a threshold T. All values of the correlation matrix >T were then set to 1, and others were set to 0 The networks shown in l is the total weight of all connections in the network, ijw  =  ijR, and ik and jk are the degrees of each node. ijδ is the Kronecker delta symbol and i and j are in the same community and 0 otherwise.To assess the best division of the WNFNs into LNCGs, we used a widely used modularity function Q, which was proposed by Newman Given a partitioning, Q represents the difference between the actual connections and randomly connected networks with the same partition. Therefore, if a brain network is not a random network, we can divide the network into different sub-modules by maximizing the value of Q. The process consists of two steps. The first step is to obtain two partitioning results. We used a hierarchical clustering algorithm to obtain a division of neuronal functional network using the functions “linkage” and “dendrogram” in the MATLAB Toolbox. Of course, other spectral clustering methods can also be used As shown in Each dataset consisted of multiple trials of each behavioral task. These can be represented by multiple neuronal functional networks. Whether these networks have a relationship with the behavior choices of the rats remains unclear. This was because each behavioral task only contained two different behavioral trial types. In this way, this is a typical two-way partitioning problem. Assuming that we do not know the rat's choice of action in advance, there is some question regarding whether we can divide all trials in each dataset into two groups corresponding to the two types of behavioral choice processes. Here, we used unsupervised clustering methods to divide the WNFNs and LNCGs of a dataset into two groups, and to calculate the accuracy of the clustering results.ith trial. The functional similarity between the ith trial and jth trial is defined as Gaussian kernel function, which is commonly used in graph-based approaches.For a dataset consisting of k trials on N neurons, 1, v2, vk) and then using a traditional K-means algorithm to divide the new vectors V into k clusters. The Ncut algorithm is very relevant to the spectral clustering algorithm. It actually used the second small eigenvectors of Laplace matrix (the Fiedler vector). A two-way normalized cut is defined as follows:Because neuronal functional networks are represented by a graph, graph theory is a superb tool for partitioning networks. To compare the experimental results of the different methods, we realized two state-of-the-art graph-based partitioning approaches, the Ng-Jordan-Weiss (NJW), and the normalized cut (Ncut) spectral clustering algorithm Unsupervised clustering methods can be used to divide multiple trials of each dataset into two groups according to their self-similarity, corresponding to two different kinds of trial types. It remains unknown, however, whether these neuronal functional networks can be employed to predict the behavioral choices in a single trial. The prediction realization procedure can serve as a classifier for the final prediction stage of the methodology, as shown in We used the leave one cross-validation method (LOO) to evaluate the accuracy of the predictions made using the proposed classifier. Each time that the cross-validation method used a trial as a test data, the remaining N-1 trials served as the training set and trained into a two-cluster classification. This process was repeated N times. Prediction accuracy was here defined as the number of correctly classified trials over the total number of trials. The average accuracy of classification determines the overall accuracy of the prediction classifier. We also realized two methods: pattern matching prediction method and KNN prediction method.ith trial (1≤i≤N). Then the other N-1 trials were classified into two groups  depending on the rat's actual choices. The similarity of ith trial to each group was determined by averaging its similarities to all functional connectivity patterns in that group.ith trials to all N1 trials of group 1.The process of predicting pattern recognition is computed using the following steps: The first step is to select the ith trial, selecting the k neighbor trials which have the maximum similarity to the ith trial. c(j) belonging to group 1 is greater than the number of trials belonging to the group 2, then the label of ith trial is assigned to group 1. Otherwise, it is assigned to group 2.Another method of classification is k-nearest neighbor (KNN) method. The basic idea underlying this algorithm is, for the ith trial iv being classified as group 1 is given by the ratio of the number of the correctly classified trials in group 1 to the number of all trials.In order to calculate the correctness of unsupervised clustering of all trials into two classes and the accuracy of predictions of trial outcomes made using the classifier, we used the Jaccard coefficient measure to evaluate the experimental results. The Jaccard coefficient is an intuitive and effective performance evaluation method. In our experiments, unsupervised clustering and prediction classification were all two-way classification problems. Given an initial partition, let The entire Jaccard coefficient is defined by the sum of the coefficients of label 1 and 2, respectively.The value of s is between 0 and 1. The larger the value of s, the better the performance of the experimental results.One-way ANOVA statistical test was used for statistical comparisons. A p value <0.001 was used as the criterion for a significant statistical difference. A linear regression analysis was conducted to compare the relationship between results of unsupervised clustering and results of single-trial predictions.We applied the NJW algorithm and the Ncut algorithm to the ten datasets (using 1 s bins). Gaussian scale parameter was set as σ = 4.We applied the pattern matching method and KNN method to predictions of the behavioral outcome. The parameter of the number of k nearest neighbor was set as k = 7.To indicate whether certain functional connections were associated with particular behavioral choices, we gave out the relationship of Ncut results to KNN prediction accuracy of Y-maze and U-maze datasets.As shown in A large number of studies have shown that there are precise time relationships between neuronal firings in cerebral cortex correspondence to behavior Our study expanded upon earlier works, which used the spatiotemporal activity patterns of rat cortical neurons to predict rat behavior. In our study, the analysis is based on functional connections between pairs of simultaneously recorded neurons on single trials. These correlations are then used to build whole-recorded neuronal functional networks. These networks are then used to divide into local neuronal circuit groups for each trial based on the maximization of modularity Q. To our knowledge, there are no published reports in which the functional connections of neurons were used to study rat behavioral choices.We found that datasets of U-maze task to have a significant difference from the Y-maze task with respect to functional connections in the two different trial types. The accuracy of unsupervised clustering trials and prediction outcomes of trials was found to be very high, as indicated using different forms of analysis, indicating obvious differences in neuronal functional connections when rats perform clockwise and counterclockwise tasks. However, the accuracy of the Y-maze datasets is low, indicating that there are no particularly obvious differences among the neuronal functional connections associated with the L-choice task and R-choice task.In the U-maze task, the two different trajectories (from point A to B or from point B to A) are represented much like two different locations would be. This may be related to the place cells within the hippocampus In our experiments, the number of recorded neurons was limited. The constructed neuronal functional networks were relatively simple, and the corresponding generated neuronal circuit groups were also relatively simple. The results of analysis of two functional connectivity cases showed them to have no significant differences. However, the method proposed in this paper still provides meaningful information that may be suitable for future analysis of large-scale neuronal networks. As the number of recorded neurons increased, the partitioning of neuronal networks into circuits became more complex Although the results of studies that use electrodes to record neuronal activity cannot be translated directly to the human brain functional network, the method proposed in this paper can also be used to analyze the functional community of the brain and investigate human brain disease pathology based on EEG and fMRI In the present study, the experimental results were controlled by the three parameters, the size of the time window of the bins, the value of the nearest neighbor k, and Gaussian scale parameter σ. In this way, the structures of the neuronal functional networks differed as the size parameters differed. These parameters were found to directly affect the results of the experiment, and we constructed a number of networks using different parameters. Although some variations appeared in the results, these did not contradict the conclusions of this paper, so no details of these results are provided here. Parameter selection was the most difficult part of the study, and most decisions were based on trial and error. The best way to improve this study would be to reduce the use of parameters.The current study was limited by the multi-electrode recordings and the method of online spike sorting. In our experiments, although the neuronal activity was observed in vivo, individual neurons were sorted offline by hand, which was highly subjective. In this way, it also limits the ability to predict animal behavior by using online firing patterns of neurons. In addition, a community structure partitioning method based on the maximization of modularity Q has the limitations as a “resolution limit” In conclusion, using the activity patterns of cortical neurons to predict animal behavior of the animals is a key issue in neuroscience. The achievements made in this area may help to solve the brain machine interface problems and facilitate the development of techniques that could promote the recovery of behavioral function after brain disease. This paper presents a new method that incorporates the neuronal functional networks to predict the trial types of rats. We performed an experimental comparison of two kinds of cognitive behavioral tasks datasets. The results show that this method can predict the behavior of different rats effectively. The results presented here provide definite evidence that neuronal functional networks exist in the cortex of moving rats of a behavioral task and that the different networks become active during different tasks. We believe that these results, along with the progress that has recently been made in neuronal recording techniques and in prediction methods, may improve the researchers' ability to predict animal behavior through the functional networks.