The mean of the radial shifts is about 1.7 mm. The standard deviations of the shifts were 2.2 mm, 2.0 mm, and 2.6 mm in A‐P, R‐L and S‐I directions, respectively, which represent random patient setup errors with the BrainLAB mask. The BrainLAB mask provides a noninvasive, practical and flexible immobilization system that keeps the patients in place during treatment. Relying on this system for patient setup might be associated with significant setup errors. Image guidance with the kV on‐board imager provides an independent verification technique to ensure accuracy of patient setup. Since the patient may relax or move during treatment, uncontrolled and undetected setup errors may be produced with patients that are not well‐immobilized. Therefore, the combination of stereotactic immobilization and image guidance achieves more controlled and accurate patient setup within 2 mm in A‐P, R‐L and S‐I directions.The purpose of this study was to evaluate setup accuracy and quantify random and systematic errors of the BrainLAB stereotactic immobilization mask and localization system using kV on‐board imaging. Nine patients were simulated and set up with the BrainLAB stereotactic head immobilization mask and localizer to be treated for brain lesions using single and hypofractions. Orthogonal pairs of projections were acquired using a kV on‐board imager mounted on a Varian Trilogy machine. The kV projections were then registered with digitally‐reconstructed radiographs (DRR) obtained from treatment planning. Shifts between the kV images and reference DRRs were calculated in the different directions: anterior‐posterior (A‐P), medial‐lateral (R‐L) and superior‐inferior (S‐I). If the shifts were larger than 2 mm in any direction, the patient was reset within the immobilization mask until satisfying setup accuracy based on image guidance has been achieved. Shifts as large as 4.5 mm, 5.0 mm, 8.0 mm in the A‐P, R‐L and S‐I directions, respectively, were measured from image registration of kV projections and DRRs. These shifts represent offsets between the treatment and simulation setup using immobilization mask. The mean offsets of 0.1 mm, 0.7 mm, and PACS numbers: 87.56.‐v, 87.56.Da Stereotactic radiotherapy with invasive patient immobilization is mostly used to treat small intracranial lesions with large single or hypofractionated dose. These patients are usually treated using precise, accurate and reproducible immobilization systems. Several commercial stereotactic systems developed by different vendors(–) are available and commonly used to immobilize patients with intracranial lesions that are treated with stereotactic radiotherapy. A head ring is usually attached invasively with pins to the patient skull, which provides a reproducible patient setup between simulation and treatment with a positioning accuracy better than 2 mm. Other less invasive immobilization systems such as dental bite blocks, facial or head and neck masks are available for use to immobilize stereotactic radiotherapy patients. These systems are more flexible for treatments of lesions with broader dose regimen that include hypofractionated doses; however, the reproducibility and accuracy of patient setup is inferior to the rigid invasive head ring.Accurate tumor localization is essential for small intracranial or extracranial lesions that are treated with conformal1 or i With the development and clinical implementation of image‐guided radiation therapy techniques such as MV and kV on‐board imaging devices, new opportunities are available to perform rigorous evaluation of the accuracy of stereotactic radiotherapy immobilization and localization systems. The kV on‐board imaging system (OBI) provides diagnostic quality images with high position and contrast resolutions that can be employed to verify patient setup accuracy using patient's updated internal anatomy. In many clinics, the OBI is potentially used to obtain 2D projection or volumetric cone‐beam CT with patient current internal anatomy at the start of each treatment session. Then, these images are registered with reference 2D digitally‐reconstructed radiographs (DRRs) or volumetric CT obtained from treatment planning systems. The on‐line image registration tools allow anatomical matching between the two image sets and then three‐dimensional (3D) shifts between treatment and simulation setups are calculated. These shifts are then applied by moving the treatment couch to achieve anatomical match between reference and treatment images within a couple of millimeters of positioning accuracy.Several studies have investigated the setup accuracy of these commercial stereotactic radiotherapy systems.,–11In this work we used kV on‐board imaging to evaluate patient setup and tumor localization accuracy of the BrainLAB stereotactic mask immobilization and localization system  used for intracranial lesions treated with a single or hypofractionated stereotactic radiotherapy. The patients were first set up using the BrainLAB immobilization mask and localizer and then kV imaging was performed independently. The shifts obtained by anatomical match using kV OBI image guidance were employed to quantify random and systematic errors of the stereotactic mask system.The BrainLAB mask system provides a noninvasive immobilization setup that allows fixation of patients treated with cranial stereotactic radiotherapy or radiosurgery. As shown in Nine patients were simulated with the BrainLAB stereotactic head immobilization mask and CT localizer . The CT 40×30 cm2 and it was operated in 2×2 binning mode with resolution of 1024 × 786 pixels of the radiographic projections. The OBI was used to acquire an orthogonal pair of kV projection for the patients immobilized and localized using the BrainLAB stereotactic head mask and target positioner as shown in The setup accuracy of the BrainLAB mask and localization system was evaluated using the kV on‐board imager (OBI) that is mounted on our Trilogy Linac . This imaging system consists of a diagnostic quality kV X‐ray source and an amorphous‐silicon flat‐panel imager  that is mounted on the linac gantry and held by robotic arms. The imager has an effective area of  The random errors were calculated from the standard deviation (σ) of the normal distributions that provide best fit to the shifts histograms in three dimensions: A‐P, R‐L and S‐I. These shifts were calculated by registering the kV radiographic images to DRRs acquired directly after patient setup and represent daily variation in patient setup. Systematic shifts in patient setup result mainly from different sources of errors that include: (a) systematic errors associated with each immobilization mask, (b) systematic errors of the BrainLAB localizer and target positioner, (c) OBI systematic error, and (d) alignment of room lasers with radiation isocenter. We have assumed that the systematic error of a mask depends on the mean of the normal distribution of the shifts for a particular patient in a certain direction. To extract the systematic errors of the mask, the mean was considered to result from simple addition of systematic errors from the different sources. For example, the mean of the normal distribution of the medial‐lateral shifts  is given by the following:The shifts obtained from the kV image guidance were used to calculate the random and systematic errors associated with the BrainLAB immobilization mask and localizer. The statistical analysis approach employed in this work is similar to those reported in pervious works.Σ1.x is the mask systematic error, Σ2,x is the localizer systematic error, Σ3,x is the OBI systematic error, and Σ4,x is the systematic errors from the laser alignment with the radiation isocenter. The radial cumulative systematic error from the mask is obtained from quadratic addition of components in the different directions as follows:where The localization systematic error in a specific direction was assumed to depend on the mean of the normal distribution of the means of all masks for the different patients. This systematic error includes errors from BrainLAB CT localizer and target positioner, and it was called here, in short, as the localizer error. Analysis of the statistical significance of the means of the measured shifts in the different direction was performed using the t‐test of the null hypothesis at 95% confidence level. These errors were measured by a cubical phantom provided by the vendor  using standard OBI quality assurance procedures. This phantom is 5×5×5×cm3 and has a spherical metal marker with a diameter of 2 mm placed at its center. The marker was aligned with radiation isocenter by aligning the room lasers with crosshair markers on the phantom surface. An orthogonal pair of kV projections (A‐P and R‐L views) was acquired of the cubical phantom. The 3D shifts of the metal marker were calculated by image registration with reference images that has the metal marker aligned to radiation isocenter. The measured shifts of 0.6 mm, −0.5 mm and 0.7 mm represent the OBI systematic error in A‐P, R‐L and S‐I directions, respectively. The room lasers were aligned with the radiation isocenter using the Winston and Lutz procedure. This includes alignment of a pointer phantom (provided by BrainLAB) with the radiation isocenter. Several radiographic projections for small fields (1 cm2) that are defined with the multileaf collimator are acquired at different gantry angles using the portal imager. The position of the pointer phantom is adjusted to be within 0.5 mm from the center of the field and this represents the accuracy of the alignment of the metal marker with the radiation isocenter. Then, the lasers are aligned with the crosshairs on the pointer phantom. The machining accuracy of the cubical phantom was tested by film radiographic imaging and it was found that the metal marker is located in the center of the phantom and aligned with the crosshairs on its surface within 0.1 mm. On our Trilogy machine, the room lasers reproduce the position of the radiation isocenter within 0.5 mm in the different directions. Systematic errors of the OBI were subtracted from the means in order to obtain net systematic errors for the mask and localizer according to The OBI systematic errors result mainly from sagging shifts of the gantry because of its weight.21 The−2.0 mm, 2.0 mm, and −1.2 mm in the A‐P, R‐L and S‐I directions, respectively, include cumulative systematic errors of the OBI, BrainLAB mask and localizer as shown in .One patient was treated with normal fractionated regimen using the BrainLAB immobilization mask and localizer for 26 treatment sessions. This patient represented a special case where she was not setting up straight because of a tilt in her neck. Therefore, including this patient in the above data shown in −0.7 mm, 0.5 mm, −1.0 mm and 2.5 mm in the A‐P, R‐L, S‐I and radial directions, respectively, as shown in Patient setup accuracy with the BrainLAB immobilization mask and localization system is limited by different sources of errors that include random and systematic errors. The statistical analysis represented in this work provides a method to separate and quantify the contribution of random and systematic errors from different sources such as BrainLAB immobilization mask and localizer, OBI, and laser alignment with radiation isocenter. Random daily errors result from personnel judgment in setting up the patients with stereotactic immobilization mask and localization system. These errors can be reduced by establishing setup protocols, and by better training and education of the medical staff on the use of this system. The largest errors that we have measured were systematic errors that resulted from the masks used for patient immobilization according to the shifts calculated using kV imaging as shown in  reported large shifts using the BrainLAB mask immobilization, and showed that combining dental mold or upper jaw support with the mask improved the accuracy of patient setup in agreement with this work. Other studies measured the shifts required using the Exac‐Track system for patients who were immobilized using the BrainLAB immobilization mask system and reported large shifts to correct patient position.In contrast with the head ring which employs invasive patient immobilization and is appropriate only for single fraction treatment, the mask is a noninvasive immobilization system that provides the clinic with a more flexible tool to treat stereotactic patients with single or multiple fractions. However, based on the imaging data from the kV on‐board imager, significant shifts were measured sometimes when the patients were set up using only the stereotactic immobilization mask and localization system. Previous studies,10 r dental molds, or upper jaw supporting system, the setup accuracy may be compromised by uncontrolled offsets that result from ring slippage. An independent verification system of the patient setup is important where secondary shifts might be detected and corrected. Image‐guided radiation therapy with the kV on‐board imager provides shifts that are required to set up the patient at the time when the images were acquired prior or during patient treatment. Application of these shifts will correct both random and systematic errors from the stereotactic immobilization and localization systems. This leads us to propose that both techniques of patient stereotactic immobilization and localization combined with setup using kV on‐board image guidance are required for patient setup. The combination of rigid immobilization and image guidance before and during the treatment session will achieve more controlled and accurate patient setup, where patients are well‐immobilized and the treatment is delivered to the spot based on what is seen by kV imaging.In this work, we would like to stress the importance of image‐guided radiation therapy using kV on‐board imaging for patients immobilized and localized with stereotactic systems such as the BrainLAB mask. Even with more rigid immobilization systems such as the head ring,9 dentThe setup accuracy that we were able to achieve with image guidance was limited by locking the couch motion which was employed following the tradition of stereotactic radiation therapy. The couch was not moved to apply the shifts calculated by image registration of the kV orthogonal pair and DRRs. In our approach, we changed patient position within the mask in order to obtain better anatomical match based on kV image guidance. Image guidance was used only to verify that the shifts calculated by on‐line image registration in each direction was less than 2 mm. Patient setup accuracy may be improved by unlocking the couch and correcting the anatomical shifts that are calculated by on‐line image registration. However, this will require evaluation of the couch position reproducibility as well as accuracy and ability to perform kV image verification of patient setup, because most of the intracranial stereotactic patients are treated with different couch positions. In this work, 2D projections were acquired using the kV on‐board imager and registered with reference 2D images from DRRs created in TPS. 2D image guidance is limited by poor visibility of the soft tissue structures and inferior contrast resolution. Further, with 2D image registration, only three translation shifts are used to set up the patients. 3D imaging using on‐board kV cone‐beam CT and comparison with CT images from treatment planning provides better visibility of soft tissue and bones. Further, it is easier to determine 3D rotational offsets on 3D CBCT than 2D projections. Thus, further investigation is required to improve the outcome of patient setup using stereotactic immobilization and localization combined with image guidance using 3D imaging.The BrainLAB mask provides a noninvasive, practical and flexible immobilization system to treat single and hypofractionated doses for intracranial stereotactic radiosurgery or therapy. Relying on this system for patient setup only might be associated with significant positioning errors. On the other hand, image guidance with the kV on‐board imager provides shifts that are required to set up the patient at the time when the images were acquired prior to or during patient treatment. The patient may relax or move during treatment, and thus uncontrolled and undetected setup errors may be produced with patients who are not well‐immobilized. The combination of stereotactic immobilization and image guidance achieves more controlled and accurate patient setup.


BMI) and risk of contralateral breast cancer (CBC) have reported mixed findings. We previously showed that obese postmenopausal women with estrogen receptor (ER)‐negative breast cancer have a fivefold higher risk of CBC compared with normal weight women. In the current analysis, we reexamined this relationship in the expanded Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study, focusing on the impact of menopausal status and ER status of the first breast cancer. The WECARE Study is a population‐based case–control study of young women with CBC  and with unilateral breast cancer . Rate ratios (RR) and 95% confidence intervals (CI) were calculated to assess the relationship between BMI and risk of CBC stratified by menopausal and ER status. Positive associations with obesity and weight gain were limited to women who became postmenopausal following their first primary breast cancer. Among those with an ER‐negative first breast cancer, obesity  at first diagnosis was associated with an increased risk of CBC . Also, weight gain of ≥10 kg after first diagnosis was associated with an almost twofold increased risk of CBC . These results suggest that women with an ER‐negative first primary cancer who are obese at first primary diagnosis or who experience a large weight gain afterward may benefit from heightened surveillance. Future studies are needed to address the impact of weight loss interventions on risk of CBC.Studies examining the relationship between body mass index ( Body mass index (BMI) is positively associated with risk of first primary breast cancer in postmenopausal women BRCA1 or BRCA2 mutation Approximately 5–10% of breast cancer survivors will go on to develop a second primary tumor in the contralateral breast The Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study is a population‐based case–control study of young women with CBC (cases) and women with unilateral breast cancer . Patient recruitment for the WECARE Study took place in two phases (termed WECARE I and WECARE II). In WECARE I, we previously reported that BMI at first diagnosis was not associated with risk of CBC, except among obese postmenopausal women with a first primary ER‐negative breast cancer whose CBC risk was fivefold greater than that of normal weight women The WECARE Study is a multicenter, population‐based case–control study of young women where cases are women with asynchronous CBC and controls are women with UBC. Participants were identified through eight population‐based cancer registries: Los Angeles County Cancer Surveillance Program; Cancer Surveillance System of the Fred Hutchinson Cancer Research Center ; State Health Registry of Iowa; The Cancer Surveillance Program of Orange County/San Diego‐Imperial Organization for Cancer Control ; the Greater Bay Area Cancer Registry ; and the Sacramento and Sierra Center Registry . All these cancer registries contribute to the National Cancer Institute (NCI) Surveillance, Epidemiology and End Results (SEER) program in the United States. Patients were also recruited from two other sources, the Ontario Cancer Registry and the Danish Breast Cancer Cooperative Group Registry, supplemented by data from the Danish Cancer Registry. The institutional review board at each recruitment site and the ethical committee system in Denmark and Ontario approved the study. Details of eligibility, recruitment, and study questionnaire have been described previously for WECARE I Briefly, WECARE Study participants were diagnosed prior to age 55 years, between 1985 and 2008 with a first primary invasive breast cancer (stage I–III). Cases were also diagnosed with a second primary CBC (in situ or invasive) at least 1 year later and controls had no history of any other second cancer diagnosis up to their reference date (the date of their matched case's second breast cancer diagnosis). Cases must also have been living in the same study reporting area for both diagnoses, while controls were required to be living in the same cancer reporting area on their reference date as they did for their first breast cancer diagnosis. Additionally, controls must not have undergone prophylactic mastectomy of the contralateral breast. All women had to be alive at the time of contact, able to provide informed consent, complete a telephone interview, and donate a blood or saliva sample for DNA extraction. Controls were matched to cases (1:2 for WECARE I and 1:1 for WECARE II) on year of birth (in 5‐year strata), year of diagnosis (in 4‐year strata), cancer registry region, and race/ethnicity. In WECARE I, cases and controls were further counter‐matched based on the cancer registry reported radiation treatment such that two members of each case–control trio had received radiation treatment for their first breast cancer. Counter‐matching was not used in WECARE II; this was taken into account in all statistical analyses (see below).Across the eight cancer registries, a total of 2354 CBC cases (998 from WECARE I and 1356 from WECARE II) and 3599 UBC controls (2122 from WECARE I and 1487 from WECARE II) were identified as being eligible and were approached for the study. Of these women, 1521 (65%) CBC cases (708 from WECARE I and 813 from WECARE II) and 2212 (61%) UBC controls (1399 from WECARE I and 813 from WECARE II) completed the phone interview and provided a DNA sample. Reasons for nonparticipation of eligible women included physician refusal (14 cases and 36 controls), interview refusal (768 cases and 1350 controls), and biospecimen refusal (32 cases and 47 controls).WECARE Study participants were interviewed by telephone using a structured questionnaire which was designed to obtain information about events occurring before the diagnosis of the first primary breast cancer, as well as events that occurred during the at‐risk period  for UBC controls). During the structured interview, participants were asked about personal demographics, medical history, family and reproductive history, hormone use, body size, smoking status, and alcohol intake. Additionally, medical records, pathology reports, and hospital charts were used to collect detailed treatment information  for the first primary breast cancer and any recurrences experienced prior to reference date, and tumor characteristics of the first primary tumor  status, histology).2; three controls at first diagnosis and three cases at reference date) or low BMI  were excluded. A further four cases/12 controls and seven cases/11 controls were excluded for having weight values that were outliers (<36.3 kg or >136 kg) at first diagnosis and reference date, respectively (note that there is some overlap between the missing and outlier categories listed above). Women who had reported use of MHT at first diagnosis and/or during the at‐risk period (103 cases and 130 controls) or had unknown menopausal status at first diagnosis or reference date (seven cases and 13 controls) were excluded. After these exclusions, the final analytic dataset included 1386 CBC cases and 2045 UBC controls.Body size measures were based on self‐report and supplemented as needed with medical record data. These included height and weight at age 18 years, weight at first breast cancer diagnosis, and weight at second diagnosis/reference date. Data at first diagnosis were available from both sources  for 72% of cases and 78% of controls. Results did not differ when one source was taken first over the other (data not shown). Fifteen women (six cases and nine controls) with missing information from both sources for height and/or weight at first diagnosis, and 22 (nine cases and 13 controls) at reference date were therefore excluded from the analysis. Additionally, women with an implausibly high BMI  and 95% CI to assess the relationship between BMI and risk of CBC. Models were adjusted for known risk factors for CBC, including age at diagnosis (continuous), age at menarche , number of full‐term pregnancies , first‐degree family history of breast cancer , histology , stage , chemotherapy treatment for a first breast cancer , hormonal treatment for a first breast cancer , and radiation therapy for a first breast cancer . A log‐weight covariate was included in the model to account for the sampling probability of the counter‐matching for radiation treatment status used in WECARE I. WECARE II participants (who were not counter‐matched) were assigned an offset term of 1.2), overweight (from 25 to <30 kg/m2), and obese (≥30 kg/m2). Weight change between first diagnosis and reference date was calculated and classified as >3 kg loss, 3 kg loss to <3 kg gain, 3 to <10 kg gain, and ≥10 kg gain. Average weight change (kg) per year (during the at‐risk period) was also calculated. Menopausal status at first diagnosis was estimated by comparing the date or age a woman last reported menstruating with the date of her first diagnosis of breast cancer. If a woman reported that she was still menstruating within 2 years before first diagnosis, or was pregnant, she was classified as premenopausal at that time point. A lag of 2 years was used to ensure minimal misclassification caused by rounding errors in the self‐report of age at menopause. Analyses were stratified by menopausal status during the at‐risk period . Women who were classified as pre‐ to postmenopausal are those who were premenopausal at the time of first breast cancer diagnosis, and became postmenopausal during the at‐risk period such that they were postmenopausal at reference date. Analyses were also stratified by the ER status of the first primary breast cancer.Body mass index was categorized as normal weight (<25 kg/mTable P = 0.04). When compared with normal weight women (BMI < 25 kg/m2), this association only reached statistical significance in overweight women , the association between weight gain and risk of CBC was limited to women with a BMI < 25 kg/m2 at first diagnosis . Average weight change per year was also modestly associated with risk of CBC, such that a 5% increase in CBC risk was seen per kg gained per year  in women who became postmenopausal during the at‐risk period (results no shown).Among women who were premenopausal throughout the at‐risk period, there was a modest inverse association between BMI at first diagnosis and risk of CBC . No association between average weight change per year and risk of CBC was seen in analyses stratified by ER status .A modest inverse association between BMI at first diagnosis and risk of CBC was observed among women diagnosed with an ER‐positive first primary breast cancer who became postmenopausal during the at‐risk period. The reduced CBC risk associated with obesity was of borderline statistical significance  will mitigate the potential for selection bias somewhat. Further, because cases and controls were both diagnosed with cancer, participation is less likely to differ by BMI status. Additionally, the proportion of eligible cases and controls who participated in the study was similar suggesting that any potential bias would be nondifferential. Other limitations include the predominantly Caucasian study population, limiting generalizability to other racial/ethnic groups, the lack of data on physical activity, and incomplete data on ER status of the second primary breast cancer, which precluded us from taking these variables into account in the analysis. Further, the majority of women maintained a stable weight, or gained weight, between first diagnosis and reference date with a relatively small proportion of women losing weight between these two time points. We were therefore limited in our ability to assess with confidence the impact of weight loss on the risk of CBC following a first breast cancer diagnosis.Of particular interest for the current analysis was the examination of the impact of ER status of the first primary breast cancer on the relationship between BMI at first diagnosis and weight change and risk of CBC. Having an ER‐negative first primary breast cancer is itself associated with increased risk of CBC None delcared.


Risk maps are spatial models of environmental hazards such as predation on livestock. We tested the long-term validity of a published risk map built from locations where Wisconsin wolves attacked livestock from 1999–2006. Using data collected after model construction, we verified the predictive accuracy of the risk map exceeded 91% for the period 2007–2011. Predictive power lasting 5 years or more substantiates the claim that risk maps are both valid and verified tools for anticipating spatial hazards. Classification errors coincided with verifier uncertainty about which wolves might be responsible. Perceived threats by wolves to domestic animals were not as well predicted (82%) as verified attacks had been and errors in classification coincided with incidents involved domestic animals other than bovids and verifier uncertainty about which wolves were involved. We recommend risk maps be used to target interventions selectively at high-risk sites. Risk maps are predictive models with spatial components that distinguish locations by the probabilities that an environmental hazard occurs there. Risk maps have attracted growing interest in various environmental and crime prevention fields –4, becauCanis lupus) predation on cattle using 133 verified attacks in Wisconsin, USA, from 1999–2006 [Here we test the hypothesis that a risk map has predictive power up to 5 years beyond its construction date. We built a risk map of gray wolf  to the type of livestock involved (bovid or other), size  and to the certainty (? or no question mark in the verifier’s record) about which wolf pack was involved. We code certainty as “firm” when a field investigator implicated a specific wolf pack and as “unsure” when the investigator did not mention a pack or added a “?” in that field of the original Wisconsin Department of Natural Resources (WDNR) reports.Finally we tested a different type of incident we refer to as perceived threats–defined as complaints arising from perceived wolf threats to livestock that did not result in injury or loss from 2003–2011 –using the same methods as above.The source data are available at .The published risk map correctly predicted that 92% of the 122 new sites from 2010–2011 would face some risk of an incident (Fisher’s exact P<0.001). Therefore, the underlying model retained strong predictive power for 13 years (1999–2011).Regarding the validity of the categories of risk , 91% weWe also tested the published model on 96 perceived threats to domestic animals on private properties . The modA risk map built with data collected from 1999–2006 continued to accurately predict the locations that might risk wolf attacks on livestock, as late as 2011. Moreover the risk model situated almost half of all incidents in the highest-risk category of pixels, thereby usefully focusing attention on <7% of the statewide analysis area. All risky pixels summed to <33% of that same area. We infer that refocusing preventive action in that area comprising less than one-third of a state would improve management efficiency.Complaints of perceived threat from wolves from 2003–2011 were 10% less predictable, possibly because these complaints involved a high proportion of non-cattle that are rarely attacked by wolves , or becaDespite the publication of three verified risk maps for Wisconsin, Minnesota, and Michigan demonstrating that wolves attacked livestock in highly predictable locations , 7, 8, sS1 Dataset(XLSX)Click here for additional data file.


There is a large body of literature demonstrating the efficacy of maternal folic acid intake in preventing birth defects, as well as investigations into potential adverse consequences of consuming folic acid above the upper intake level (UL). Recently, two authoritative bodies convened expert panels to assess risks from high intakes of folic acid: the U.S. National Toxicology Program and the UK Scientific Advisory Committee on Nutrition. Overall, the totality of the evidence examined by these panels, as well as studies published since the release of their reports, have not established risks for adverse consequences resulting from existing mandatory folic acid fortification programs that have been implemented in many countries. Current folic acid fortification programs have been shown to support public health in populations, and the exposure levels are informed by and adherent to the precautionary principle. Additional research is needed to assess the health effects of folic acid supplement use when the current upper limit for folic acid is exceeded. Folic acid intake below the established tolerable upper intake level (UL) of 1000 μg/day for the general population is not associated with any adverse health outcomes. However, public health efforts to reduce the incidence of folic acid–responsive neural tube defects (NTDs) by increasing folic acid intake at levels below the UL have raised questions concerning the safety of elevated folic acid intake. Not all countries require that the food supply be fortified with folic acid for NTD prevention, despite the unequivocal evidence for its beneficial effects on reducing rates of NTDs and potentially other developmental anomalies.12 status resulting from a voluntary fortification program and/or supplement use revealed that, although consumption of fortified foods and supplements increased folate status, this increase was not consistent across the population.The U.S. Food and Drug Administration's (FDA) regulations on food “standards of identity” specify the ingredients a given food product must contain to market it under a specific name, as is the case for products carrying the “enriched” label as it applies to mandatory fortification programs. Use of the “enriched” label on products requires mandatory fortification with specified micronutrients at specified levels. Voluntary fortification refers to the optional fortification of foods that do not carry a “standard of identify” for enriched products. As described below, folic acid fortification in the United States is considered mandatory, as it applies to flour, grain, and cereal products carrying the “enriched” label. In general, mandatory micronutrient fortification programs result in more uniform exposure of a given micronutrient across individuals in a population compared with voluntary fortification programs, in terms of both coverage and exposure level. In Ireland, a cross‐sectional study that assessed folate and vitamin BTo reduce rates of NTDs in the United States, the FDA mandated that 140 μg of folic acid be added per 100 g of enriched flour, rice, pasta, cornmeal, and other grain products that carry the “enriched” label, with an effective date of January 1, 1998.12 deficiency, as assessed by hematological indices, and thereby minimize the risk of neurological complications in vitamin B12‐deficient individuals. The IOM stated, “The weight of the limited but suggestive evidence that excessive folate intake may precipitate or exacerbate neuropathy in vitamin B12‐deficient individuals justifies the selection of this end point as the critical end point for the development of a UL for folate.”12 deficiency, (2) data suggesting that pernicious anemia may develop at a younger age in some racial or ethnic groups,12 deficiency in younger age groups.” According to the IOM, “the prevalence of vitamin B12 deficiency in females in the childbearing years is very low and the consumption of supplemental folate at or above the UL in this subgroup is unlikely to produce adverse effects,”12 deficiency, as they have been replaced with the use of serum biomarkers;12 deficiency, is less meaningful today relative to when it was established nearly 20 years ago.There is no UL for natural reduced folates found in foods.Some countries have elected not to institute a folic acid fortification program because of concerns of unintended consequences. The “precautionary principle” is perhaps most well known in relation to environmental science and with respect to campaigns designed to limit environmental damage. The original definition states, “when an activity raises threats of harm to human health or the environment, precautionary measures should be taken even if some cause and effect relationships are not fully established scientifically” and was set forth by the Rio Declaration of 1992 and the 1998 Wingspread Statement.There are four unique aspects of folic acid fortification of enriched grains and cereal products compared with previous nutrient fortification initiatives, including (1) the health outcome, (2) targeting, (3) fortificant used, and (4) fundamental lack of knowledge of mechanism of action.First, folic acid fortification was the first nutrient fortification initiative where the primary goal was not to remedy a classical nutrient deficiency in the population on the basis of functional biomarkers of metabolism or a disease attributed solely to a nutrient deficiency in the population, but rather to reduce risk for a clinical condition whose etiology is complex and multifactorial, namely NTDs. The experience with folic acid fortification for NTD prevention has helped transform the paradigm for establishing nutrient requirements. Currently, there are ongoing initiatives to estimate dietary reference intakes using chronic disease end points, as opposed to functional indicators of nutrient deficiency or deficiency‐related disease.a priori identification of women who are at risk of folic acid–responsive NTDs.Second, the intervention exposed the entire population to folic acid, but was intended for a narrow segment of the population, namely women of reproductive age, especially those who are at increased risk for carrying a folic acid–responsive NTD‐affected pregnancy. NTDs are generally recognized to result from complex gene–nutrient–environment interactions.Third, the use of folic acid as the fortificant was controversial, because at high levels of intake it can appear in blood in an unmetabolized form (as described below). Folic acid is a synthetic and chemically stable form of folate and not the natural form of the vitamin found in whole foods. It is highly stable to oxidative degradation and therefore the preferred form of folate used in dietary supplements, ready‐to‐eat breakfast cereals, and fortified food. Folic acid has been present in multivitamin supplements and foods for infants and young children for over 50 years without any evidence of harm when intake levels are below the UL. Physiological forms of folate that function as enzyme cofactors in metabolism include tetrahydrofolates and dihydrofolate. These forms of the vitamin are unstable and often undergo irreversible degradation during food preparation and cooking.Once transported into a cell, folic acid is converted into the natural reduced forms of folate by the enzyme dihydrofolate reductase, although this reaction is slow and is readily saturated.12 deficiency…”12 deficiency can be common in older adults.12 deficiency is associated with megaloblastic anemia and neuropathies; while the anemia is reversible, neuropathies can be irreversible. A single study in primates reported that vitamin B12‐deficient animals receiving folic acid supplements developed neurological damage earlier than vitamin B12‐deficient animals not receiving folic acid.Folic acid has not been demonstrated to have any meaningful impact on human physiology when intake levels are below the UL. Folic acid has no established biological activity other than binding to folate receptors and transporters for cellular import. Once in the cell, folic acid cannot be converted to polyglutamate forms of folate; it first must be reduced to the tetrahydrofolate to serve as a metabolic cofactor.12 deficiency owing to high intake of synthetic folic acid in vitamin B12‐deficient individuals. It is important to note that the UL was established for folic acid, and not for reduced forms of folate or natural food folate.As described above, the UL for folic acid was established to avoid a delayed diagnosis of vitamin Bde novo synthesis of purines (adenine and guanine), de novo thymidylate (dTMP) biosynthesis, and the remethylation of homocysteine to methionine , hypersensitivity‐related outcomes, and thyroid‐ and diabetes‐related disorders. These areas of concern were based on previous studies reporting adverse effects in these health effect categories with intakes of greater than 400 μg/day folic acid, serum folates greater than 10 nM/L, or red blood cell folate greater than 340 nM/L.There is a large body of literature demonstrating the efficacy of maternal folic acid intake in preventing birth defects, as well as investigations into potential adverse consequences of consuming folic acid above the UL. Recently, two separate authoritative bodies convened expert panels to assess the risks from high intakes of folic acid. In May 2015, the U.S. National Toxicology Program (NTP) and the Office of Dietary Supplements convened an expert panel and performed systematic reviews of existing literature regarding the safe use of high folic acid intakes and was charged with developing future research priorities.12 status, cognitive decline in the elderly, cancer, and the appearance of UMFA in the systemic circulation. This group was tasked with conducting a review of new evidence, relying heavily on systematic reviews and meta‐analyses for all outcomes except UMFA in circulation, as there were fewer studies identified for this outcome.The UK SACN comprises appointed scientific experts who advise Public Health England and other UK governmental organizations on nutrition. A SACN panel was convened in April 2016 to update their previous recommendations in favor of mandatory folic acid fortification that were published in 2006 and 2009 and to review the literature on potential adverse effects of folic acid intake. A draft report submitted to public consultation in early 2017Additionally, the SACN summarized the results of five other evaluations conducted after their 2006 review, one of which was the NTP report.The following section provides an overview of each major putative adverse topic and then focuses on the NTP and SACN expert reviews summarized below by disease outcome, as well as relevant recent literature that was not included in the SCAN or NTP reports. Later in 2017, the SACN will offer a recommendation on whether its previous recommendations regarding mandatory folic acid fortification still applies for the United Kingdom.It is worth noting that both the NTP and SACN reports focus on population and clinical data from high‐income settings, although the application of these findings is expected to be widely applicable to low‐ and middle‐income contexts.A biological premise underpinning the role of folic acid intake and adverse cancer outcomes has been published.There is strong evidence that low folate status promotes cancer, especially colorectal cancer.in vivo are lacking, and it has not been established whether folate availability is rate limiting in tumor growth in individuals with adequate folate status.Elevated folate status has been proposed to promote tumorigenesis from preexisting foci of neoplasia and accelerate the growth of established tumors.The totality of the evidence from randomized controlled trials does not support folic acid supplementation or fortification increasing cancer risk. A recent meta‐analysis of randomized controlled trials that included over 50,000 individuals examined the relationship between folic acid supplementation (with folic acid doses approximately an order of magnitude greater than exposure levels from folic acid fortification) and cancer incidence from trials conducted before 2011. The analysis included site‐specific cancer rates.The NTP panel noted several gaps in current knowledge linking high folic acid intakes to cancer outcomes from animal model studies and human studies and highlighted the importance of understanding “whether existing evidence from clinical trials for increased risk is driven by effects in specific subgroups,” as well as identifying other interacting modifiers of the effect of folic acid, such as age, preexisting neoplasia, and/or genetics .In 2016, the SACN noted that many studies investigating the effects of folic acid intakes on cancer risk may not have been adequately powered to detect changes in cancer incidence, as many studies were not designed specifically for this outcome. Similarly, the committee noted that many of the studies may not have been of sufficient duration to detect an increase in cancer incidence, as cancer is known to develop over many years.ApcMin/+ mouse model of spontaneous intestinal tumor formation.et al. was that timing and dose of intervention varied markedly among studies in the ApcMin/+ mouse model, some studies used folic acid doses 10‐fold higher than what is considered adequate for mouse chow.As stated in the NTP report, data reporting on the relationship between folic acid and colon cancer in rodent models have been inconsistent12 deficiency is founded on case studies and observational studies. Folate and vitamin B12 interact in folate‐mediated one‐carbon metabolism. The two enzymatic cofactors converge in the homocysteine remethylation pathway, where they are both required by the enzyme methionine synthase for the remethylation of homocysteine to methionine. Hence, deficiency of either vitamin leads to elevated serum homocysteine.12 deficiency also induces a secondary, functional folate deficiency, known as a “5‐methyltetrahydrofolate trap.” Because methionine synthase is the only enzyme that metabolizes 5‐methyltetrahydrofolate, vitamin B12 deficiency results in its accumulation, thus “starving” other folate‐dependent metabolic pathways for folate cofactors, including nucleotide biosynthesis. Hence, one of the initial clinical presentations of vitamin B12 deficiency is megaloblastic anemia owing to inhibition of DNA synthesis. Dietary folic acid can rescue the anemia by providing new pools of cofactors for DNA synthesis that initially escape the methyl trap. However, elevated folic acid intake is not known to rescue neurological pathology resulting from vitamin B12 deficiency. There are no proposed biological premises or suggested mechanisms whereby elevated folic acid intake exacerbates vitamin B12 deficiency at the level of metabolism, cellular physiology, or human pathogenesis.The hypothesis that folic acid intake causes or accelerates cognitive impairment resulting from vitamin B12 deficiency arose initially from case reports.12 status, high serum folate was associated with anemia and cognitive impairment. When vitamin B12 status was normal, however, high serum folate was associated with protection against cognitive impairment.”12 status in the presence of high plasma folate or use of folic acid supplements.12 deficiency are more pronounced at higher levels of plasma folate.12; with vitamin B12 malabsorption driving the association.Concerns for adverse effects of high folic acid intakes on cognition in vitamin B12 status on accelerating cognitive decline, nor would they be ethical to perform in humans; the few studies supporting this finding are observational.To date, there are no results from controlled trials testing the association of elevated folate status with low vitamin B12 status that tested the efficacy of a single intramuscular injection of a vitamin mixture containing vitamin B12, vitamin B6, and vitamin B1 on neurophysiological function. This secondary analysis examined the association between subjects’ baseline folate status and their response at a single time point 4 months after the multivitamin treatment using a newly proposed combined status and functional vitamin B12 indicator (cB‐12). The cB‐12 indicator is a computed variable that combines plasma homocysteine concentration and serum concentrations of methylmalonic acid, holotranscobalamin, and vitamin B12. The authors reported weaker response of cB‐12 to the multivitamin treatment among subjects with serum folate levels above the median (33.9 nmol/L).12 status in deficient individuals after intramuscular B12 supplementation is attenuated by high folate status. Interestingly, baseline folate status was not associated with differences in response to the multivitamin treatment as related to nerve function, a primary outcome of the registered trial.12 treatment was neither a primary nor secondary outcome of the trial as registered. The strength of the evidence from this secondary data analysis is weak, which limits any conclusions drawn. The cB‐12 indicator is a relatively new concept that is not used clinically and has had limited evaluation by the research community. Evaluated individually, none of the four biochemical measures used to compute the cB‐12 had an interaction with folate status. The finding was only evaluated at 4 months after treatment and does not correlate with any clearly defined clinical outcome. Given the close biochemical relationship between folate and vitamin B12, it is biologically plausible that, among individuals with low vitamin B12 status, those with different underlying folate status could have different short‐term responses to injections of vitamin B12. It is well established in the literature that elevated intake of folate or folic acid can functionally compensate for vitamin B12 deficiency, as first reported for the masking of vitamin B12 deficiency–related megaloblastic anemia by folic acid.12‐deficient individuals with elevated folate status would be expected to exhibit less improvement in functional indicators as a result of vitamin B12 therapy than those with lower folate status because of the functional compensation afforded by folate in vitamin B12 deficiency. A well‐designed clinical trial among individuals with low vitamin B12 status to evaluate the association between clearly defined clinical outcomes and appropriate measures of folate status would be needed to validate these purported findings.A recent study published after the NTP report12 status. The SACN also stated that observational studies showed either no risk or protection from cognitive decline with higher folate status among individuals with normal vitamin B12 status.The SACN committee concluded that folic acid did not have a significant effect on cognitive decline in intervention trials, though it was also noted that studies were generally of short duration and neither focused on nor powered for assessment of effects in individuals with low vitamin B12 deficiency. The committee cited evidence indicating that the prevalence of vitamin B12 deficiency as defined by serum vitamin B12 less than 148 pmol/L was not affected by mandatory folic acid fortification in the United States, although it was also noted that the biochemical measures used to assess vitamin B12 deficiency are of limited reliability and that there is variation in cut off values used to define deficiency.The SACN addressed concerns that folic acid fortification may mask signs of vitamin B12 status and adequate folate status.12 levels were the most insulin resistant, leading the authors to conclude that “Low maternal vitamin B12 and high folate status may contribute to the epidemic of adiposity and type 2 diabetes in India.”Concern over adverse effects of high folic acid intakes on diabetes‐related disorders and/or thyroid disease arose from conflicting findings from two observational studiesThe NTP panel concluded that future work should follow up on the observational findings as related to prenatal exposures and that, on the basis of this very limited data, there was no consistent evidence that high intakes of folic acid and/or high folate status influences diabetes risk or glucose metabolism.As noted in the NTP report, observational studies reporting hypersensitivity‐related outcomes, such as childhood asthma and allergy, have emerged over the past 20 years.There is scant literature that has proposed that these disease outcomes are associated with high folic acid intake. The NTP systematic review process did not find sufficient evidence to warrant consideration of this literature by the panel owing to lack of sufficient evidence of adverse effects.Here, the evidence for the safety of folic acid fortification was reviewed, primarily on the basis of very thorough assessments conducted by the U.S. NTP in 2015 and the UK SACN in 2016. Neither the SACN nor the NTP reports identified conclusive evidence for adverse effects of folic acid. The NTP report emphasizes the uncertainty that exists in the present literature, proposes a research agenda, and emphasizes that “additional work is critical to fully evaluating the known public health benefits of folic acid, as well as the potential—but still unevaluated—risks that may exist.”Overall, the totality of the evidence of the literature fully supports the benefits of mandatory folic acid fortification in NTD prevention. Furthermore, there are no established risks for adverse consequences resulting from existing mandatory folic acid fortification programs that have been implemented in many countries. Current folic acid fortification programs have been shown to support public health in populations, and the exposure levels are informed by and adherent to the precautionary principle. Additional research is needed to assess the health effects of folic acid supplement use when the current UL for folic acid is exceeded.The authors declare no competing interests.


Within multiscale brain dynamics, the structure–function relationship between cellular changes at a lower scale and coordinated oscillations at a higher scale is not well understood. This relationship may be particularly relevant for understanding functional impairments after a mild traumatic brain injury (mTBI) when current neuroimaging methods do not reveal morphological changes to the brain common in moderate to severe TBI such as diffuse axonal injury or gray matter lesions. Here, we created a physiology-based model of cerebral cortex using a publicly released modeling framework  to explore the possibility that performance deficits characteristic of blast-induced mTBI may reflect dysfunctional, local network activity influenced by microscale neuronal damage at the cellular level. We operationalized microscale damage to neurons as the formation of pores on the neuronal membrane based on research using blast paradigms, and in our model, pores were simulated by a change in membrane conductance. We then tracked changes in simulated electrical activity. Our model contained 585 simulated neurons, comprised of 14 types of cortical and thalamic neurons each with its own compartmental morphology and electrophysiological properties. Comparing the functional activity of neurons before and after simulated damage, we found that simulated pores in the membrane reduced both action potential generation and local field potential (LFP) power in the 1–40 Hz range of the power spectrum. Furthermore, the location of damage modulated the strength of these effects: pore formation on simulated axons reduced LFP power more strongly than did pore formation on the soma and the dendrites. These results indicate that even small amounts of cellular damage can negatively impact functional activity of larger scale oscillations, and our findings suggest that multiscale modeling provides a promising avenue to elucidate these relationships. Iniin vitro nervous tissue directly to blast can induce acute changes in electrical activity in the absence of cell death, including three primary effects on in vitro hippocampal electrical activity: decreased neuronal synchrony, decreased neuronal firing, and decreased neuronal excitability  at the larger scale for coordinated activity among distributed cortical patches of neurons. The LFP signal is thought to be the basis of the electrical signals (EEG) and magnetic field fluctuations (MEG) recorded at the scalp that has been linked to task performance, so alterations in LFP activity serves as a proxy for potential decrements in cognitive performance following neuronal injury.A synapses.Simulated neurons in our model are biophysically detailed with each neuron being represented by multiple compartments and voltage dependent channels. Using biophysically detailed simulated neurons allows the model to generate realistic electrical activity as an emergent property of the underlying physics . NeuronsRm). Since the exact relationship between the number and size of membrane pores and changes in electrical resistance of the membrane has not been experimentally determined, we performed a parameter sweep to determine how changes in membrane resistance impact overall model electrical activity. We report these results as the level of damage to the neuronal membrane, and this terminology references a scalar quantity that represents the amount of reduction in membrane resistance where 10% cell damage corresponds to a simulation using a Rm at 90% of the baseline, whereas 50% cell damage corresponds to Rm at 50% of its baseline value. Changes in membrane resistance were made at equal percentage levels simultaneously across all simulated neurons.Nanoscale modeling of blast impact on the membrane of neurons found that microscale pores appeared on the surface of the neuronal membrane that were sufficiently large to allow the flow of ions through the membrane . Other sAdditionally, while there is a wealth of experimental evidence describing large-scale blast-induced damage to axons (in the form of white matter tracts –36), lesAdapted for the GENESIS simulation environment, our model was based on a previously published thalamocortical network model , 29. Allp = 0.01 to.25, except in the 36 inhibitory axo-axonic interneurons which were fully connected to the axon initial segments of all pyramidal cells and layer 4 spiny stellate cells. In our model, a total of 335,067 connections were simulated between 585 neurons, and neurons were organized into microcolumns containing 23 or 24 neurons each. Each microcolumn contains each of the 14 neuron types described in the Section “Our cortical network represents a 150 µm × 150 µm × 2,871 µm patch of cortex along with corresponding thalamic relay cells and downstream thalamic targets , allowing us to explore both intrinsically generated APs from the individual neurons and the LFP across a group of neurons. The first second of simulated data was excluded to allow the model to settle from initial conditions. Data were then processed using the MATLAB−8 V. The mean AP firing rate was then calculated as the total number of APs across all simulated neurons divided by the length of the simulation time.Action potentials were obtained by resampling the output to 5,000 Hz and then high-pass filtering the data using a ninth order Butterworth filter with a cutoff frequency of 50 Hz Figure B, top. Tz-coordinates) to keep distance-dependent effects to a minimum. LFPs were then obtained by resampling the membrane potentials from the model to 1,000 Hz and then low-pass filtering using an eighth order Butterworth filter with a roll off of 300 Hz . The model generates a stationary LFP time series from our relatively short (20 s) simulation runs, and the parametric spectral estimator allows us to obtain a smooth and consistent power estimate  and from 40 to 100 Hz (600 points). The variance of the overall power estimate was calculated as the sum of the variances of the individual power spectral density values. The significance of the difference between power estimates for baseline and simulated cell damage for each of the ranges and damage levels was then obtained from Student’s t cumulative distribution using the MATLAB® function tcdf. Finally, Bonferroni correction was applied to account for multiple comparisons.Confidence intervals were obtained by the resampling method embedded in the MATLABOur primary aim was to examine whether simulated cellular damage that mimicked membrane pore formation after blast could induce electrophysiological changes that negatively impact brain electrical activity in the absence of either cell death or large-scale structural lesions. We first examined the impact on functional activity following damage to the whole cell, and then we investigated whether this impaired functional activity was differentially modulated by damage to axons compared to damage to somas and dendrites.VM = −70 mV, VK = −95 mV, and VNa = +50 mV  to examine the effect of ionic flow disruption on functional neuronal activity. We expected that increasing membrane damage would reduce activity across all frequencies equally, given the broadband nature of the change  and that the reversal potential of the neuronal membrane is in the inhibitory range since it is closer to the reversal potential of potassium than it is to the reversal potential of sodium [= +50 mV ]. Our re= +50 mV , row 1, = +50 mV F–J.p < 0.01), while the largest drop in power was 6 dB/Hz in the 40–100 Hz frequency range (p < 0.01). At the 50% damage level, the reduction in power between low and high frequency ranges were similar with low frequency (1–40 Hz) power exhibiting a largest drop of 15 dB/Hz (p < 0.01) confidence interval, and high frequency (40–100 Hz) exhibiting a largest drop of 11 dB/Hz (p < 0.01). To put these values in context, an attenuation of 3 dB at a given frequency reflects a drop to half power from maximum. Damage at the 50% level was also associated with an absence of neuronal firing . Finally, at maximum levels of damage, the LFP power in the low frequency range hits the minimum value at 40% damage, while LFP power in the higher frequency range does not bottom out until 50%.Finally, we directly compared the power spectrum plots across all three tested conditions  to identify global patterns of simulated damage on neuronal activity. Results revealed that damage at the 10% level results in only small changes from baseline, but when simulated damage increases to 20–30%, damage to the entire cell is greater than the sum of damage to the axons and the soma and dendrites taken together , neuronal activity in the 1–40 Hz range will be more strongly disrupted than higher frequency neuronal activity within the 40–100 Hz range (Figures 0%, neuroMany diverse microscale damage mechanisms have been hypothesized to induce mTBI under blast conditions. Although we only directly examined pore formation and decreased membrane resistance, there are many other potential damage mechanisms that would impact model behavior in the ranges we present here, including a negative impact on brain activity in the 1–100 Hz frequency range. Future research could extend our results and investigate additional damage mechanisms with little to no additional variables or parameters in the model, such as damage to synapses, morphological changes, changes in connectivity, ion channel deformations, and changes in calcium regulation. Of particular interest, models could examine ionic conduction through voltage-gated sodium and potassium channels. This conduction critically depends on a highly structured set of charged proteins to be in a specific conformation for their proper function, and disruptions that reduce ionic flow through these channels are implicated in genetic disorders  and are In general, damage mechanisms that evolve on a longer time scale are more difficult to simulate without the addition of variables/parameters to standard electrophysiology-based models such as metabolic dysregulation, glial neuron interactions, learning and memory, g-protein-coupled processes, and protein synthesis. It is possible to simulate the end point of many of these damage mechanisms, like changes in ionic balance due to damage to glia, but it is exceedingly difficult to simulate this type of damage over the time course of days, weeks, or even years.Our simulations show a relationship between simulated cellular damage and the power spectrum of the LFP. Future work to expand our results could be accomplished by increasing the strength of both inherent model oscillatory activity and observing the influence of external input/stimulation on model behavior. Here, model activity was driven by a random Poisson process, which most closely corresponds to activity in a small patch of cortex in a resting state, or a cognitive state where the brain is not processing any specific external input. This results in simulated activity that does not have strong oscillatory behavior. With higher levels of membrane damage and absence of significant production of APs, the LFP power described here is dominated by subthreshold and independent membrane potential fluctuations. This limits the direct mapping of our results to resting EEG, since the human brain maintains the ability to generate strongly oscillatory activity following mild traumatic brain injuries. Thus, the expansion of our model to include simulated sensory inputs to cortex is a natural next step for our research which will allow for investigating the impact of membrane damage on oscillatory activity related to sensory input processing. More generally, our model provides a framework to understand the relationships between changes in membrane parameters and large-scale activity among cortical brain regions critical for everyday cognition and task performance.All authors contributed equally to the study conception and design. The modeling and simulation was executed by DB, AY, PK, and WA. DB, AY, JV, and PF all contributed to the data analysis and interpretation. The manuscript was written and approved for publication by all authors.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Hum Brain Mapp 38:4744–4759, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.Human behavior is supported by flexible neurophysiological processes that enable the fine‐scale manipulation of information across distributed neural circuits. Yet, approaches for understanding the dynamics of these circuit interactions have been limited. One promising avenue for quantifying and describing these dynamics lies in multilayer network models. Here, networks are composed of nodes (which represent brain regions) and time‐dependent edges . We use this approach to examine functional connectivity measured by non‐invasive neuroimaging techniques. These multilayer network models facilitate the examination of changes in the pattern of statistical interactions between large‐scale brain regions that might facilitate behavior. In this study, we define and exercise two novel measures of network reconfiguration, and demonstrate their utility in neuroimaging data acquired as healthy adult human subjects learn a new motor skill. In particular, we identify putative functional modules in multilayer networks and characterize the degree to which nodes switch between modules. Next, we define cohesive switches, in which a set of nodes moves between modules together as a group, and we define disjoint switches, in which a single node moves between modules independently from other nodes. Together, these two concepts offer complementary yet distinct insights into the changes in functional connectivity that accompany motor learning. More generally, our work offers statistical tools that other researchers can use to better understand the reconfiguration patterns of functional connectivity over time.  Dynamic network analysis has emerged as an important topic in recent years within the field of neuroimaging. The primary motivation for this type of analysis is driven by the concept that functional relationships in the brain are not static, but in fact change over time  and ω = [0.91 1.1] at increments of 0.01. At each value of γ and ω, we performed a permutation test  between the values of the dynamic community statistics (average cohesion strength and disjointedness) at each node between Day 1 and Day 2 of training. We report brain regions that showed significant differences in graph metric values between Day 1 and Day 2 after controlling for type I errors using a false discovery rate (FDR) correction.In the main findings presented in this article, we fix two parameters in the multilayer community detection technique to their default values in the field of applied mathematics, which are a structural resolution parameter not be simply expected in random network null models. We addressed this question in the context of dynamic networks extracted from task‐based fMRI data acquired during motor skill learning (see Methods). Using an independent‐samples t‐test, we compared the empirically observed values of cohesion strength  and of disjointedness  to those observed in a random network null model. Scans from all sessions for each participant were grouped together into the “Original” group (n = 48) and compared to a group of their null model equivalents (n = 48). The equivalent null model for each scan session was based on the average across 100 optimizations of the modularity quality function. We chose the most stringent null model currently developed for multilayer functional networks in human neuroimaging, which is known as the temporal null model. This null model enabled us to test the null hypothesis that the empirically measured functional brain networks displayed dynamic community statistics that were no different than those expected when the order of time windows was permuted uniformly at random. We observed that average cohesion strength was significantly higher than expected in the temporal null model, t(94) = 191.75, P = 7.08 × 10−162  = 13.18, P = 8.37 × 10−20 , a natural first question is whether the human brain displays values for these statistics that would F = 1.55, P = 0.23. Similarly, we observed no significant differences in disjointedness across days: F = 1.83, P = 0.18  on cohesion strength and disjointedness. In general, we observed no significant effect of day on the dynamic community statistics. First, we observed no significant differences in cohesion strength across days: F,15 = 1.5t‐test. Although cohesion strength did not show significant differences between day pairs , disjointedness showed significantly higher changes between Day 1 and Day 2 than between Day 2 and Day 3  , we next examined the degree of change in network statistics between consecutive days. Specifically, we computed differences in dynamic community statistics for each participant between Day 1 and Day 2, and between Day 2 and Day 3. Then, we tested whether the average difference between day pairs was statistically significant using a paired We next sought to determine if these dynamic community statistics had predictive value in explaining individual differences in task performance. In a prior report utilizing this data, it was shown that network flexibility was correlated with individual differences in the learning rate [Bassett et al., To address this question, we first quantified task performance by computing the learning rate for each individual. The learning rate is defined as the exponential drop‐off parameter of the MT as a function of trials; and MT is defined as the time between the first button press and the last button press of a 12‐note finger sequence (see Methods). If the learning rate is 0, then no behavioral change occurs, while if the learning rate is greater than 0, then behavioral change does occur. Larger values of learning rate indicate that the sequences were learned more quickly, while lower values of learning rate indicate that the sequences were learned more slowly. We observe in our data that learning rate differed over individuals and days of practice, covering a range from approximately 0 to approximately 0.13 Fig. .R2 = 0.39, P = 0.01)  and Day 3 . For disjointedness, we observed no significant relationship for Day 1 , Day 2 , or Day 3 . These results suggest that on the first day of practice, when the majority of the learning occurs for this task, functional brain network modules reconfigure in a cohesive manner: a set of brain regions that may have been functionally connected to one network module can change their activity profile and become functionally connected to another network module. Moreover, the greater the degree of cohesive movement, the better the learning. Note that relationships between disjointedness and learning rate in each of the 3 days were not significant . Bridging these results with those of the previous section, we conclude that while disjointedness may account for the significant changes in network dynamics observed between the first and second day of task practice, it does not correlate with individual differences in learning rate.With these estimates of subject and scan‐specific learning rates, we asked whether individual differences in average cohesion strength or disjointedness was related to individual differences in learning. We observed that cohesion strength on the first day was the best predictor of learning rate (01) Fig. , while nThe results presented thus far have focused on dynamic community statistics averaged across the entire brain. We next turn to examining the anatomical location of cohesive movers and disjoint movers. Specifically, we seek to identify brain regions that show significant changes in dynamic community statistics from the first day of training to the second day of training, the time interval in which we observe the greatest learning. Then, we map these significant regions onto the surface of the brain. Importantly, these maps include sensitivity to network dynamics over a range of temporal and spatial scales [Sasai et al., The study of brain network dynamics represents an area of research that is increasingly important for an understanding of time‐varying fluctuations in brain function. In this study, we introduced a new concept for measuring dynamic changes in a network, specifically how nodes change their allegiance to putative functional modules over time. In this study, we established that the manner in which nodes change their allegiance is significantly different from the manner observed in comparable null model networks. These results underscore how changes in temporal ordering of functional connectivity patterns inform the stability of putative functional modules supporting cognitive processes during skill learning. In particular, the level of cohesive and disjointed changes in the allegiance of regions to putative functional modules offers finer‐scale information about the changes in network dynamics that accompany task performance [Telesford et al., The findings presented in this article support a wider and growing literature on the time‐varying changes in functional brain network topology that can provide neural correlates of temporal variations in cognitive functions. These fluctuations can occur over long time periods, such as those observed in network topology over 18 months in recent longitudinal imaging studies [Shine et al., Prior work in multilayer network approaches has largely focused on network flexibility, which is a powerful metric for understanding changes in network communities during both task performance and during the resting state. When estimated across the whole brain, network flexibility is correlated with individual differences in motor skill learning [Bassett et al., On the backdrop of these general efforts in understanding reconfiguration of putative functional modules, it has been interesting to note that while flexibility appears to be a generally positive attribute of healthy cognitive function, excessive network reconfiguration appears to be a hallmark of psychiatric disease [Braun et al., P < 0.05, corrected for multiple comparisons using the Benjamini–Hochberg procedure with a FDR correction, q = 0.05). It is notable is how well these regions align with the regions showing significant changes in disjointedness between Day 1 and Day 2. With the exception of the central opercular cortex, all regions showing a significant correlation between cohesion strength and learning rate on Day 1 also demonstrated significant changes in disjointedness between Day 1 and Day 2 , is also associated with psychiatric disorders such as schizophrenia [Braun et al., Supporting InformationClick here for additional data file.