Cluster Size Threshold Research Articles

Accuracy of a deep learning-based algorithm for the detection of thoracic aortic calcifications in chest computed tomography and cardiovascular surgery planning.

To assess the accuracy of a deep learning-based algorithm for fully automated detection of thoracic aortic calcifications in chest computed tomography (CT) with a focus on the aortic clamping zone. We retrospectively included 100 chest CT scans from 91 patients who were examined on second- or third-generation dual-source scanners. Subsamples comprised 47 scans with an ECG-gated aortic angiography and 53 unenhanced scans. A deep learning model performed aortic landmark detection and aorta segmentation to derive eight vessel segments. Associated calcifications were detected and their volumes measured using a mean-based density thresholding. Algorithm parameters (calcium cluster size threshold, aortic mask dilatation) were varied to determine optimal performance for the upper ascending aorta that encompasses the aortic clamping zone. A binary visual rating served as a reference. Standard estimates of diagnostic accuracy and inter-rater agreement using Cohen's Kappa were calculated. Thoracic aortic calcifications were observed in 74% of patients with a prevalence of 27% to 70% by aorta segment. Using different parameter combinations, the algorithm provided binary ratings for all scans and segments. The best-performing parameter combination for the presence of calcifications in the aortic clamping zone yielded a sensitivity of 93% and a specificity of 82% with an area under the receiver operating characteristic curve of 0.874. Using these parameters, the inter-rater agreement ranged from κ 0.66 to 0.92 per segment. Fully automated segmental detection of thoracic aortic calcifications in chest CT performs with high accuracy. This includes the critical preoperative assessment of the aortic clamping zone.

Brain structural and functional abnormalities associated with acute post-traumatic headache: iron deposition and functional connectivity

BackgroundThe purpose of this study was to interrogate brain iron accumulation in participants with acute post-traumatic headache (PTH) due to mild traumatic brain injury (mTBI), and to determine if functional connectivity is affected in areas with iron accumulation. We aimed to examine the correlations between iron accumulation and headache frequency, post-concussion symptom severity, number of mTBIs, and time since most recent TBI.MethodsSixty participants with acute PTH and 60 age-matched healthy controls (HC) underwent 3T magnetic resonance imaging including quantitative T2* maps and resting-state functional connectivity imaging. Between group T2* differences were determined using T-tests (p < 0.005, cluster size threshold of 90 voxels). For regions with T2* differences, two analyses were conducted. First, the correlations with clinical variables including headache frequency, number of lifetime mTBIs, time since most recent mTBI, and Sport Concussion Assessment Tool (SCAT) symptom severity scale scores were investigated using linear regression. Second, the functional connectivity of these regions with the rest of the brain was examined (significance of p < 0.05 with family wise error correction for multiple comparisons).ResultsThe acute PTH group consisted of 60 participants (22 male, 38 female) with average age of 42 ± 14 years. The HC group consisted of 60 age-matched controls (17 male, 43 female, average age of 42 ± 13). PTH participants had lower T2* values compared to HC in the left posterior cingulate and the bilateral cuneus. Stronger functional connectivity was observed between bilateral cuneus and right cerebellar areas in PTH compared to HC. Within the PTH group, linear regression showed negative associations of T2* in the left posterior cingulate with SCAT symptom severity score (p = 0.05) and T2* in the left cuneus with headache frequency (p = 0.04).ConclusionsIron accumulation in posterior cingulate and cuneus was observed in those with acute PTH relative to HC; stronger functional connectivity was detected between the bilateral cuneus and the right cerebellum. The correlations of decreased T2* (suggesting higher iron content) with headache frequency and post mTBI symptom severity suggest that the iron accumulation that results from mTBI might reflect the severity of underlying mTBI pathophysiology and associate with post-mTBI symptom severity including PTH.

Does right hemisphere compensate for the left in school-age children with large left middle fossa arachnoid cysts?

BackgroundTo assess the cognitive function changes and brain network neuroplasticity in school-age children having large (diameter > 5 cm) left middle fossa arachnoid cyst (MFACs).MethodsEleven patients and 22 normal controls (NC) between 6 and 14 years of age were included. The CNS Vital Signs (CNS VS) were administered for cognitive assessment. The differences of cognitive data and functional connectivity (FC) in resting-state functional magnetic resonance imaging (rs-fMRI) were compared between the patient group and the NC group. The correlations between the altered FC and cognitive data in the patient group were assessed.ResultsPatient group had significantly poorer attention (including Complex Attention, Sustained Attention, Simple Attention, Cognitive Flexibility, and Executive Function) and memory function (Visual Memory and Working Memory) than the NC group (uncorrected p-value, p-unc < 0.05). Whole-brain local correlation (LCOR) analysis showed an extensively lower LCOR in the patient group (voxel threshold p-unc < 0.001, cluster-size threshold of false discovery rate adjusted p (p-FDR) < 0.001). Functional connectivity (FC) analysis showed that bilateral frontal and temporal lobes connectivity in the patient group was significantly lower than the NC group (p-FDR < 0.05). Seed-based FC analysis indicated that there was altered FC between the right temporal lobe and the left temporal-parietal/temporal-occipital area (p-FDR < 0.05). In the patient group, most of the altered FC had a negative correlation to the cognitive score, while the FC in the right temporal lobe-left temporal-occipital area positively correlated to Verbal/Visual Memory (r = 0.41–0.60, p-FDR < 0.05). In correlation analysis between clinical data and cognitive score, the only significant result was a low correlation between cyst size and Reaction Time (-0.30–-0.36, P-FDR < 0.05).ConclusionsSchool-aged children with large left MFAC showed significantly lower cognitive performance primarily in attention and memory domains. Distinct from neuroplasticity in a unilateral brain lesion, compensation in the healthy hemisphere in MFAC patients was sparse.

Inverse Association Between Resting-State Putamen Activity and Iowa Gambling Task Performance in Patients With Obsessive-Compulsive Disorder and Control Subjects.

BackgroundSymptoms of obsessive-compulsive disorder (OCD) have been conceptualized as manifestations of decision-making deficits. Patients with OCD exhibit impairment during the decision-making process, as assessed by the Iowa Gambling Task (IGT). This impairment is independent of clinical severity and disease progression. However, the association between the decision-making deficit and resting-state brain activity of patients with OCD has not been examined.MethodsFifty unmedicated patients with OCD and 55 matched control subjects completed IGT. Resting-state brain activity was examined using the fractional amplitude of low-frequency fluctuations (fALFFs). fALFF analysis focused on the slow-4 and 5 bands. Group comparisons were performed to determine the association between IGT performance and fALFFs.ResultsThere was a significant group difference in the association between the IGT total net score and slow-4 fALFFs in the left putamen (voxel height threshold of p < 0.001; cluster size threshold of p < 0.05; family wise error-corrected). Higher putamen slow-4 fALFFs were correlated with lower IGT scores for OCD patients (r = −0.485; p < 0.0005) and higher IGT scores for control subjects (r = 0.402; p < 0.005). There was no group difference in the association between the IGT total net score and slow-5 fALFFs.ConclusionsThese findings in unmedicated patients demonstrate the importance of resting-state putamen activity for decision-making deficit associated with OCD, as measured by IGT. The inverse correlation may be explained by the hypersensitive response of the putamen in patients with OCD.

Detection and Response to an HIV Cluster: People Living Homeless and Using Drugs in Seattle, Washington

The HIV epidemic in King County, Washington has traditionally been highly concentrated among men who have sex with men, and incidence has gradually declined over 2 decades. In 2018, King County experienced a geographically concentrated outbreak of HIV among heterosexual people who inject drugs. Data sources to describe the 2018 outbreak and King County's response were partner services interview data, HIV case reports, syringe service program client surveys, hospital data, and data from a rapid needs assessment of homeless individuals and people who inject drugs. In 2020, the authors examined the impact of delays in molecular sequence analyses and cluster member size thresholds, for identifying genetically similar clusters, on the timing of outbreak identification. In 2018, the health department identified a North Seattle cluster, growing to 30 people with related HIV infections diagnosed in 2008-2019. In total, 70% of cluster members were female, 77% were people who inject drugs, 87% were homeless, and 27% reported exchanging sex. Intervention activities included a rapid needs assessment, 2,485 HIV screening tests in a jail and other outreach settings, provision of 87,488 clean syringes in the outbreak area, and public communications. A lower cluster size threshold and more rapid receipt and analyses of data would have identified this outbreak 4-16 months earlier. This outbreak shows the vulnerability of people who inject drugs to HIV infection, even in areas with robust syringe service programs and declining HIV epidemics. Although molecular HIV surveillance did not identify this outbreak, it may have done so with a lower threshold for defining clusters and more rapid receipt and analyses of HIV genetic sequences.

T2* reduction in patients with acute post-traumatic headache.

Although iron accumulation in pain-processing brain regions has been associated with repeated migraine attacks, brain structural changes associated with post-traumatic headache have yet to be elucidated. To determine whether iron accumulation is associated with acute post-traumatic headache, magnetic resonance transverse relaxation rates (T2*) associated with iron accumulation were investigated between individuals with acute post-traumatic headache attributed to mild traumatic brain injury and healthy controls. Twenty individuals with acute post-traumatic headache and 20 age-matched healthy controls underwent 3T brain magnetic resonance imaging including quantitative T2* maps. T2* differences between individuals with post-traumatic headache versus healthy controls were compared using age-matched paired t-tests. Associations of T2* values with headache frequency and number of mild traumatic brain injuries were investigated using multiple linear regression in individuals with post-traumatic headache. Significance was determined using uncorrected p-value and cluster size threshold. Individuals with post-traumatic headache had lower T2* values compared to healthy controls in cortical (bilateral frontal, bilateral anterior and posterior cingulate, right postcentral, bilateral temporal, right supramarginal, right rolandic, left insula, left occipital, right parahippocampal), subcortical (left putamen, bilateral hippocampal) and brainstem regions (pons). Within post-traumatic headache subjects, multiple linear regression showed a negative association between T2* in the right inferior parietal/supramarginal regions and number of mild traumatic brain injuries and a negative association between T2* in bilateral cingulate, bilateral precuneus, bilateral supplementary motor areas, bilateral insula, right middle temporal and right lingual areas and headache frequency. Acute post-traumatic headache is associated with iron accumulation in multiple brain regions. Correlations with headache frequency and number of lifetime mild traumatic brain injuries suggest that iron accumulation is part of the pathophysiology or a marker of mild traumatic brain injury and post-traumatic headache.

O2.1. LOCAL AND LONG-RANGE CONNECTIVITY PATTERNS OF AUDITORY PERCEPTUAL DISTURBANCE IN SCHIZOPHRENIA

BackgroundAuditory hallucinations are a prevalent, debilitating symptom of schizophrenia (Sz). Lack of detailed phenomenological assessments of perceptual disturbances in large psychiatric imaging datasets limits our ability to disentangle the underlying neural mechanisms of hallucinations. Our study investigates how changes in local functional communication dynamics may be associated with wide-ranging auditory disturbances in Sz.MethodsLocal functional connectivity was estimated using regional homogeneity (ReHo) analysis of resting fMRI data, which quantifies synchronization of fMRI activity of a voxel to its neighboring voxels. Resting fMRI data of 99 Sz patients was analyzed (mean age=36.2±13.3 y, sex=71/28 m/f); Auditory perceptual disturbance in the past week was estimated using the auditory perception state (APS) subscale score of the recently validated Auditory Perceptual Trait and State Scale (http://www.mdbrain.org/APTS.pdf). Voxelwise regression analysis of ReHo was performed including APS score as a regressor of interest. Significant results were thresholded using AFNI’s 3dClustSim with autocorrelation function option to yield corrected p<0.05, corresponding to cluster-size threshold of 49 voxels at voxelwise p=0.001.ResultsHigher APS scores were associated with reduced ReHo in clusters in left putamen, right putamen, left temporoparietal junction, and right hippocampus. In a follow-up analysis using these clusters as seeds in whole-brain resting-state functional connectivity analysis (rsFC) analysis, higher APS scores were significantly associated with reduced rsFC between the right putamen seed and clusters in the contralateral putamen and auditory cortex.DiscussionOur findings are consistent with those of a prior study that reported abnormal ReHo in left and right putamen of a unmedicated first-episode Sz patients (Cui et al. 2016). However, in that small sample (n=32), striatal ReHo was elevated relative to controls, and AH severity was not significantly correlated with striatal ReHo measures. Our study investigated ReHo in a large sample of chronic, medicated patients (all except 4 were taking antipsychotic medication at time of study). While it is widely accepted that striatal signaling is disrupted in Sz, future work is needed to better understand how striatal signaling deficits may change over the course of illness and how this relates to particular symptoms such as hallucinations. Implications for development of novel therapies that account for these nuanced findings will be discussed.

A Monte Carlo approach for improving transient dopamine release detection sensitivity

Current methods using a single PET scan to detect voxel-level transient dopamine release—using F-test (significance) and cluster size thresholding—have limited detection sensitivity for clusters of release small in size and/or having low release levels. Specifically, simulations show that voxels with release near the peripheries of such clusters are often rejected—becoming false negatives and ultimately distorting the F-distribution of rejected voxels. We suggest a Monte Carlo method that incorporates these two observations into a cost function, allowing erroneously rejected voxels to be accepted under specified criteria. In simulations, the proposed method improves detection sensitivity by up to 50% while preserving the cluster size threshold, or up to 180% when optimizing for sensitivity. A further parametric-based voxelwise thresholding is then suggested to better estimate the release dynamics in detected clusters. We apply the Monte Carlo method to a pilot scan from a human gambling study, where additional parametrically unique clusters are detected as compared to the current best methods—results consistent with our simulations.

Personalized microstructural evaluation using a Mahalanobis-distance based outlier detection strategy on epilepsy patients' DTI data - Theory, simulations and example cases.

Quantitative MRI methods have recently gained extensive interest and are seeing substantial developments; however, their application in single patient vs control group comparisons is often limited by inherent statistical difficulties. One such application is detecting malformations of cortical development (MCDs) behind drug resistant epilepsies, a task that, especially when based solely on conventional MR images, may represent a serious challenge. We aimed to develop a novel straightforward voxel-wise evaluation method based on the Mahalanobis-distance, combining quantitative MRI data into a multidimensional parameter space and detecting lesion voxels as outliers. Simulations with standard multivariate Gaussian distribution and resampled DTI-eigenvalue data of 45 healthy control subjects determined the optimal critical value, cluster size threshold, and the expectable lesion detection performance through ROC-analyses. To reduce the effect of false positives emanating from registration artefacts and gyrification differences, an automatic classification method was applied, fine-tuned using a leave-one-out strategy based on diffusion and T1-weighted data of the controls. DWI processing, including thorough corrections and robust tensor fitting was performed with ExploreDTI, spatial coregistration was achieved with the DARTEL tools of SPM12. Additional to simulations, clusters of outlying diffusion profile, concordant with neuroradiological evaluation and independent calculations with the MAP07 toolbox were identified in 12 cases of a 13 patient example population with various types of MCDs. The multidimensional approach proved sufficiently sensitive in pinpointing regions of abnormal tissue microstructure using DTI data both in simulations and in the heterogeneous example population. Inherent limitations posed by registration artefacts, age-related differences, and the different or mixed pathologies limit the generalization of specificity estimation. Nevertheless, the proposed statistical method may aid the everyday examination of individual subjects, ever so more upon extending the framework with quantitative information from other modalities, e.g. susceptibility mapping, relaxometry, or perfusion.

Structural and functional MRI abnormalities of cerebellar cortex and nuclei in SCA3, SCA6 and Friedreich's ataxia.

Spinocerebellar ataxia type 3, spinocerebellar ataxia type 6 and Friedreich's ataxia are common hereditary ataxias. Different patterns of atrophy of the cerebellar cortex are well known. Data on cerebellar nuclei are sparse. Whereas cerebellar nuclei have long been thought to be preserved in spinocerebellar ataxia type 6, histology shows marked atrophy of the nuclei in Friedreich's ataxia and spinocerebellar ataxia type 3. In the present study susceptibility weighted imaging was used to assess atrophy of the cerebellar nuclei in patients with spinocerebellar ataxia type 6 (n = 12, age range 41-76 years, five female), Friedreich's ataxia (n = 12, age range 21-55 years, seven female), spinocerebellar ataxia type 3 (n = 10, age range 34-67 years, three female), and age- and gender-matched controls (total n = 23, age range 22-75 years, 10 female). T1-weighted magnetic resonance images were used to calculate the volume of the cerebellum. In addition, ultra-high field functional magnetic resonance imaging was performed with optimized normalization methods to assess function of the cerebellar cortex and nuclei during simple hand movements. As expected, the volume of the cerebellum was markedly reduced in spinocerebellar ataxia type 6, preserved in Friedreich's ataxia, and mildy reduced in spinocerebellar ataxia type 3. The volume of the cerebellar nuclei was reduced in the three patient groups compared to matched controls (P-values < 0.05; two-sample t-tests). Atrophy of the cerebellar nuclei was most pronounced in spinocerebellar ataxia type 6. On a functional level, hand-movement-related cerebellar activation was altered in all three disorders. Within the cerebellar cortex, functional magnetic resonance imaging signal was significantly reduced in spinocerebellar ataxia type 6 and Friedreich's ataxia compared to matched controls (P-values < 0.001, bootstrap-corrected cluster-size threshold; two-sample t-tests). The difference missed significance in spinocerebellar ataxia type 3. Within the cerebellar nuclei, reductions were significant when comparing spinocerebellar ataxia type 6 and Friedreich's ataxia to matched controls (P < 0.01, bootstrap-corrected cluster-size threshold; two-sample t-tests). Susceptibility weighted imaging allowed depiction of atrophy of the cerebellar nuclei in patients with Friedreich's ataxia and spinocerebellar ataxia type 3. In spinocerebellar ataxia type 6, pathology was not restricted to the cerebellar cortex but also involved the cerebellar nuclei. Functional magnetic resonance imaging data, on the other hand, revealed that pathology in Friedreich's ataxia and spinocerebellar ataxia type 3 is not restricted to the cerebellar nuclei. There was functional involvement of the cerebellar cortex despite no or little structural changes.

Outlier detection for scanned point clouds using majority voting

When scanning an object using a 3D laser scanner, the collected scanned point cloud is usually contaminated by numerous measurement outliers. These outliers can be sparse outliers, isolated or non-isolated outlier clusters. The non-isolated outlier clusters pose a great challenge to the development of an automatic outlier detection method since such outliers are attached to the scanned data points from the object surface and difficult to be distinguished from these valid surface measurement points. This paper presents an effective outlier detection method based on the principle of majority voting. The method is able to detect non-isolated outlier clusters as well as the other types of outliers in a scanned point cloud. The key component is a majority voting scheme that can cut the connection between non-isolated outlier clusters and the scanned surface so that non-isolated outliers become isolated. An expandable boundary criterion is also proposed to remove isolated outliers and preserve valid point clusters more reliably than a simple cluster size threshold. The effectiveness of the proposed method has been validated by comparing with several existing methods using a variety of scanned point clouds.

Sensitivity and Specificity of Interictal EEG-fMRI for Detecting the Ictal Onset Zone at Different Statistical Thresholds.

There is currently a lack of knowledge about electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) specificity. Our aim was to define sensitivity and specificity of blood oxygen level dependent (BOLD) responses to interictal epileptic spikes during EEG-fMRI for detecting the ictal onset zone (IOZ). We studied 21 refractory focal epilepsy patients who had a well-defined IOZ after a full presurgical evaluation and interictal spikes during EEG-fMRI. Areas of spike-related BOLD changes overlapping the IOZ in patients were considered as true positives; if no overlap was found, they were treated as false-negatives. Matched healthy case-controls had undergone similar EEG-fMRI in order to determine true-negative and false-positive fractions. The spike-related regressor of the patient was used in the design matrix of the healthy case-control. Suprathreshold BOLD changes in the brain of controls were considered as false positives, absence of these changes as true negatives. Sensitivity and specificity were calculated for different statistical thresholds at the voxel level combined with different cluster size thresholds and represented in receiver operating characteristic (ROC)-curves. Additionally, we calculated the ROC-curves based on the cluster containing the maximal significant activation. We achieved a combination of 100% specificity and 62% sensitivity, using a Z-threshold in the interval 3.4–3.5 and cluster size threshold of 350 voxels. We could obtain higher sensitivity at the expense of specificity. Similar performance was found when using the cluster containing the maximal significant activation. Our data provide a guideline for different EEG-fMRI settings with their respective sensitivity and specificity for detecting the IOZ. The unique cluster containing the maximal significant BOLD activation was a sensitive and specific marker of the IOZ.

Application of mean-shift clustering to Blood oxygen level dependent functional MRI activation detection

BackgroundFunctional magnetic resonance imaging (fMRI) analysis is commonly done with cross-correlation analysis (CCA) and the General Linear Model (GLM). Both CCA and GLM techniques, however, typically perform calculations on a per-voxel basis and do not consider relationships neighboring voxels may have. Clustered voxel analyses have then been developed to improve fMRI signal detections by taking advantages of relationships of neighboring voxels. Mean-shift clustering (MSC) is another technique which takes into account properties of neighboring voxels and can be considered for enhancing fMRI activation detection.MethodsThis study examines the adoption of MSC to fMRI analysis. MSC was applied to a Statistical Parameter Image generated with the CCA technique on both simulated and real fMRI data. The MSC technique was then compared with CCA and CCA plus cluster analysis. A range of kernel sizes were used to examine how the technique behaves.ResultsReceiver Operating Characteristic curves shows an improvement over CCA and Cluster analysis. False positive rates are lower with the proposed technique. MSC allows the use of a low intensity threshold and also does not require the use of a cluster size threshold, which improves detection of weak activations and highly focused activations.ConclusionThe proposed technique shows improved activation detection for both simulated and real Blood Oxygen Level Dependent fMRI data. More detailed studies are required to further develop the proposed technique.

The Effect of Acupuncture Needle Combination on Central Pain Processing-An fMRI Study

BackgroundEmpirical acupuncture treatment paradigm for acute pain utilizing Tendinomuscular Meridians (TMM) calls for the stimulation of Ting Points (TPs) and Gathering point(GP). This study aims to compare the supraspinal neuronal mechanisms associated with both TPs and GP needling (EA3), and TPs needling alone (EA2) with fMRI.ResultsA significant (P < 0.01) difference between pre-scan (heat Pain) HP, and post-EA HP VAS scores in both paradigms was noted (n = 11). The post-EA HP VAS score was significantly (P < 0.05) lower with EA3 comparing to EA2 Within-group random effect analysis indicated that EA3+HP>EA3 (condition EA3+HP subtracted by condition EA3) appeared to exert a significant degree of activity suppression in the affective supraspinal regions including the IPL, anterior cingulate cortex (ACC) and the insular cortex (IN). This level of suppression was not observed in the EA2+HP>EA2 (condition EA2+HP subtracted by condition EA2) within-group random effect analysis Between-group random effect analysis indicated that EA3 induced a significantly (P < 0.01, cluster size threshold 150) higher degree of deactivation than EA2 in several pain related supraspinal regions including the right prefrontal cortex, rostral anterior cingulate (rACC), medial cingulate cortex, left inferior frontal lobe and posterior cerebellum. The 2-factor ANOVA in those regions indicated both rACC and posterior cerebellum had a significant (P < 0.01) needle effect, and the right prefrontal area showed a significant (P < 0.01) HP effect. However, a significant interaction between the two factors was only found in the right prefrontal lobe. Granger causality analysis showed EA3 induced a much higher degree of inference among HP related supraspinal somatosensory, affective and modulatory components than EA2. Deactivation pattern at the medullary-pontine area casted a direct inference on the deactivation pattern of secondary somatosensory cortices which also affected the deactivation of the IN.ConclusionsWhile both EA2 and EA3 induced a significant degree of deactivation in the human brain regions related to pain processing, the addition of GP stimulation further exerts an inhibitory effect on the ascending spinoreticular pain pathway. Therefore, different needling position as mandated in different empirical acupuncture treatment paradigms may play a different role in modulating pain related neuronal functions.

Functional connectivity and cannabis use in high-risk adolescents

Background: Adolescence is a unique neurodevelopmental period when regions of the brain most able to assess risk and reward are still in development. Cannabis use during adolescence has been associated with persistent negative outcomes. Although measures of resting brain activity are useful in assessing functional connectivity, such measures have not been broadly applied in adolescent cannabis-users. Objectives: The goal of the present study was to analyze the associations between cannabis use and resting brain activity in a sample of high-risk adolescents. Methods: Eighty-two high-risk youth between 14–18 years old were recruited from a juvenile justice day program. Youth completed a brief neurocognitive battery including assessments of cannabis use and a 5-minute resting functional magnetic resonance imaging (fMRI) scan. Intrinsic connectivity networks were extracted using the GIFT toolbox. Brain activity in a fronto-temporal network was compared in youth with high cannabis use vs. low cannabis use using an independent-samples t-test with alcohol use entered as a covariate. Results: Analysis revealed two elements within the fronto-temporal network related to cannabis use: one in middle frontal gyrus related to high cannabis use, and one in middle temporal gyrus related to low cannabis use. Only the frontal source survived application of a cluster size threshold and was significant at p < 0.005. Conclusions: These results are consistent with patterns of activity in adult cannabis-users. The observed effect may reflect either pre-existing risk factors or near-term consequences of cannabis use. Prevention and intervention strategies that address fronto-temporal functioning may be particularly helpful in this population.

Functional Magnetic Resonance Imaging of the Brain in Women With Overactive Bladder

OBJECTIVES: To identify abnormal function of the limbic cortex (LC) in response to urinary urgency among patients with Overactive Bladder (OAB) using brain functional MRI (fMRI) METHODS: 5 OAB subjects and 5 Controls underwent bladder filling and rated urgency sensations while fMRI measured activation in discrete volumes (voxels) within the brain. Changes in brain activation were related to bladder distension and individual subject's rating of urgency via multiple regression analysis. Beta weights from regression equations were converted into percent signal change (PSC) for each voxel and PSC compared to the null hypothesis using T-tests. Significance threshold of P<.05 was applied along with a cluster size threshold of.32 ml (5 voxels). RESULTS: OAB patients showed increased brain activation in LC, specifically the insula (IN) and Anterior Cingulate Gyrus (ACG), associated with increased urgency. Urgency sensations during low volumes were associated with bilateral IN activation in OAB subjects (7,621 voxels right IN, 4,453 voxels left IN, mean beta weights .018 +/- .014 and .014 +/- .011) Minimal activation was present in Controls (790 voxels right IN, beta weight =.010 +/- .007). Urgency sensations during high volumes were associated with bilateral ACG activation in OAB subjects (2,304 voxels right IN, 5,005 voxels left IN, mean beta weights of 005 +/- .003 and 004+/-.003) without activation in Controls. CONCLUSIONS: Urinary urgency in patients with OAB is associated with increased activation of the LC. This activation likely represents abnormal processing of sensory input in brain regions associated with emotional response to discomfort.

When Giving Is Good: Ventromedial Prefrontal Cortex Activation for Others' Intentions

In social decision-making, people care both about others' outcomes and their intentions to help or harm. How the brain integrates representations of others' intentions with their outcomes, however, is unknown. In this study, participants inferred others' decisions in an economic game during functional magnetic resonance imaging. When the game was described in terms of donations, ventromedial prefrontal cortex (VMPFC) activation increased for inferring generous play and decreased for inferring selfish play. When the game was described in terms of individual savings, however, VMPFC activation did not distinguish between strategies. Distinct medial prefrontal regions also encoded consistency with situational norms. A separate network, including right temporoparietal junction and parahippocampal gyrus, was more activated for inferential errors in the donation than in the savings condition. These results demonstrate that neural responses to others' generosity or selfishness depend not only on their actions but also on their perceived intentions.

Type I and Type II error concerns in fMRI research: re-balancing the scale

Statistical thresholding (i.e. P-values) in fMRI research has become increasingly conservative over the past decade in an attempt to diminish Type I errors (i.e. false alarms) to a level traditionally allowed in behavioral science research. In this article, we examine the unintended negative consequences of this single-minded devotion to Type I errors: increased Type II errors (i.e. missing true effects), a bias toward studying large rather than small effects, a bias toward observing sensory and motor processes rather than complex cognitive and affective processes and deficient meta-analyses. Power analyses indicate that the reductions in acceptable P-values over time are producing dramatic increases in the Type II error rate. Moreover, the push for a mapwide false discovery rate (FDR) of 0.05 is based on the assumption that this is the FDR in most behavioral research; however, this is an inaccurate assessment of the conventions in actual behavioral research. We report simulations demonstrating that combined intensity and cluster size thresholds such as P < 0.005 with a 10 voxel extent produce a desirable balance between Types I and II error rates. This joint threshold produces high but acceptable Type II error rates and produces a FDR that is comparable to the effective FDR in typical behavioral science articles (while a 20 voxel extent threshold produces an actual FDR of 0.05 with relatively common imaging parameters). We recommend a greater focus on replication and meta-analysis rather than emphasizing single studies as the unit of analysis for establishing scientific truth. From this perspective, Type I errors are self-erasing because they will not replicate, thus allowing for more lenient thresholding to avoid Type II errors.

Electron attachment to strongly polar clusters

Electron localization is studied in formamide cluster anions. The isolated formamide molecule has a large dipole moment and its clusters can give birth to multipole-bound anions as well as valence anions. The vertical valence electron affinity of the isolated molecule is determined by electron transmission spectroscopy. The anion formation process is studied as a function of cluster size with Rydberg electron transfer spectroscopy. DFT calculations of the neutral and negatively-charged cluster structures show that the anion excess electron localizes on a single molecule. The adiabatic valence electron affinity of isolated formamide is deduced from the observation of the cluster size threshold for valence attachment.

Magnetic properties, magnetic cluster size, and read-write performance of CoPtCr-SiO/sub 2/ perpendicular recording media

The characteristics of CoPtCr-SiO/sub 2/ perpendicular media were investigated, especially focusing on the dependence of magnetic properties and read-write performance on magnetic cluster size. H/sub c/ increases with reducing magnetic cluster size. As magnetic cluster size decreases, media noise and signal-to-noise ratio are improved and magnetic write width becomes narrower, indicating that reducing the magnetic cluster size is an effective means to increase both bit and track densities. However, diminution of magnetic cluster size degrades thermal stability. Lowering the magnetic cluster size threshold, above which a medium is thermally stable, is necessary in order to obtain a low noise and thermally stable medium.