Cross-frequency coupling in EEG revealed by adaptive oscillation tracking.

Introduction: Neuronal oscillations have been the focus of increasing interest in the neuroscientific community, in part because they have been considered as a possible integrating mechanism through which internal states can influence stimulus processing in a top-down way (Engel et al., 2001). Moreover, increasing evidence indicates that oscillations in different frequency bands interact with one other through coupling mechanisms (Jensen and Colgin, 2007). The existence and the importance of these cross-frequency couplings during various tasks have been verified by recent studies (Canolty et al., 2006; Lakatos et al., 2007). In this study, we measure the strength and directionality of two types of couplings - phase-amplitude couplings and phase-phase couplings - between various bands in EEG data recorded during an illusory contour experiment that were identified using a recently-proposed adaptive frequency tracking algorithm (Van Zaen et al., 2010). Methods: The data used in this study have been taken from a previously published study examining the spatiotemporal mechanisms of illusory contour processing (Murray et al., 2002). The EEG in the present study were from a subset of nine subjects. Each stimulus was composed of 'pac-man' inducers presented in two orientations: IC, when an illusory contour was present, and NC, when no contour could be detected. The signals recorded by the electrodes P2, P4, P6, PO4 and PO6 were averaged, and filtered into the following bands: 4-8Hz, 8-12Hz, 15-25Hz, 35-45Hz, 45-55Hz, 55-65Hz and 65-75Hz. An adaptive frequency tracking algorithm (Van Zaen et al., 2010) was then applied in each band in order to extract the main oscillation and estimate its frequency. This additional step ensures that clean phase information is obtained when taking the Hilbert transform. The frequency estimated by the tracker was averaged over sliding windows and then used to compare the two conditions. Two types of cross-frequency couplings were considered: phase-amplitude couplings and phase-phase couplings. Both types were measured with the phase locking value (PLV, Lachaux et al., 1999) over sliding windows. The phase-amplitude couplings were computed with the phase of the low frequency oscillation and the phase of the amplitude of the high frequency one. Different coupling coefficients were used when measuring phase-phase couplings in order to estimate different m:n synchronizations (4:3, 3:2, 2:1, 3:1, 4:1, 5:1, 6:1, 7:1, 8:1 and 9:1) and to take into account the frequency differences across bands. Moreover, the direction of coupling was estimated with a directionality index (Bahraminasab et al., 2008). Finally, the two conditions IC and NC were compared with ANOVAs with 'subject' as a random effect and 'condition' as a fixed effect. Before computing the statistical tests, the PLV values were transformed into approximately normal variables (Penny et al., 2008). Results: When comparing the mean estimated frequency across conditions, a significant difference was found only in the 4-8Hz band, such that the frequency within this band was significantly higher for IC than NC stimuli starting at ~250ms post-stimulus onset (Fig. 1; solid line shows IC and dashed line NC). Significant differences in phase-amplitude couplings were obtained only when the 4-8 Hz band was taken as the low frequency band. Moreover, in all significant situations, the coupling strength is higher for the NC than IC condition. An example of significant difference between conditions is shown in Fig. 2 for the phase-amplitude coupling between the 4-8Hz and 55-65Hz bands (p-value in top panel and mean PLV values in the bottom panel). A decrease in coupling strength was observed shortly after stimulus onset for both conditions and was greater for the condition IC. This phenomenon was observed with all other frequency bands. The results obtained for the phase-phase couplings were more complex. As for the phase-amplitude couplings, all significant differences were obtained when the 4-8Hz band was considered as the low frequency band. The stimulus condition exhibiting the higher coupling strength depended on the ratio of the coupling coefficients. When this ratio was small, the IC condition exhibited the higher phase-phase coupling strength. When this ratio was large, the NC condition exhibited the higher coupling strength. Fig. 3 shows the phase-phase couplings between the 4-8Hz and 35-45Hz bands for the coupling coefficient 6:1, and the coupling strength was significantly higher for the IC than NC condition. By contrast, for the coupling coefficient 9:1 the NC condition gave the higher coupling strength (Fig. 4). Control analyses verified that it is not a consequence of the frequency difference between the two conditions in the 4-8Hz band. The directionality measures indicated a transfer of information from the low frequency components towards the high frequency ones. Conclusions: Adaptive tracking is a feasible method for EEG analyses, revealing information both about stimulus-related differences and coupling patterns across frequencies. Theta oscillations play a central role in illusory shape processing and more generally in visual processing. The presence vs. absence of illusory shapes was paralleled by faster theta oscillations. Phase-amplitude couplings were decreased more for IC than NC and might be due to a resetting mechanism. The complex patterns in phase-phase coupling between theta and beta/gamma suggest that the contribution of these oscillations to visual binding and stimulus processing are not as straightforward as conventionally held. Causality analyses further suggest that theta oscillations drive beta/gamma oscillations (see also Schroeder and Lakatos, 2009). The present findings highlight the need for applying more sophisticated signal analyses in order to establish a fuller understanding of the functional role of neural oscillations.

Evaluation of Iowa's Driver Improvement Program, 2009

This study examines the effectiveness of Iowa’s Driver Improvement Program (DIP), measured as the reduction in the number of driver convictions subsequent to the DIP. The analysis involved a random sample of 9,055 drivers who had been instructed to attend DIP and corresponding data on driver convictions, crashes, and driver education training history that were provided by the Iowa Motor Vehicle Division. The sample was divided into two groups based on DIP outcome: satisfactory or unsatisfactory completion. Two evaluation periods were considered: one year after the DIP date (probation period) and the period from the 13th to 18th month after the DIP date. The evaluation of Iowa’s DIP showed that there is evidence of effectiveness in terms of reducing driver convictions subsequent to attending the DIP. Among the 6,790 (75%) drivers who completed the course satisfactorily, 73% of drivers had no actions and 93% were not involved in a crash during the probation period. Statistical tests confirmed these numbers. However, the positive effect of satisfactory completion of DIP on survival time (that is, the time until the first conviction) was not statistically significant 13 months after the DIP date. Econometric model estimation results showed that, regardless of the DIP outcome, the likelihood of conviction occurrence and frequency of subsequent convictions depends on other factors, such as age, driver history, and DIP location, and interaction effects among these factors. Low-cost, early intervention measures are suggested to enhance the effectiveness of Iowa’s DIP. These measures can include advisory and warning letters (customized based on the driver’s age) sent within the first year after the DIP date and soon after the end of the probation period, as well as a closer examination of DIP instruction across the 17 community colleges that host the program. Given the large number of suspended drivers who continued to drive, consideration should also be given to measures to reduce driving while suspended offenses.

Estimation of forest canopy cover : a comparison of field measurement techniques

Abstract

Effects of computing parameters and measurement locations on the estimation of 3D NPS in non-stationary MDCT images.

The goal of this study was to investigate the impact of computing parameters and the location of volumes of interest (VOI) on the calculation of 3D noise power spectrum (NPS) in order to determine an optimal set of computing parameters and propose a robust method for evaluating the noise properties of imaging systems. Noise stationarity in noise volumes acquired with a water phantom on a 128-MDCT and a 320-MDCT scanner were analyzed in the spatial domain in order to define locally stationary VOIs. The influence of the computing parameters in the 3D NPS measurement: the sampling distances bx,y,z and the VOI lengths Lx,y,z, the number of VOIs NVOI and the structured noise were investigated to minimize measurement errors. The effect of the VOI locations on the NPS was also investigated. Results showed that the noise (standard deviation) varies more in the r-direction (phantom radius) than z-direction plane. A 25 × 25 × 40 mm(3) VOI associated with DFOV = 200 mm (Lx,y,z = 64, bx,y = 0.391 mm with 512 × 512 matrix) and a first-order detrending method to reduce structured noise led to an accurate NPS estimation. NPS estimated from off centered small VOIs had a directional dependency contrary to NPS obtained from large VOIs located in the center of the volume or from small VOIs located on a concentric circle. This showed that the VOI size and location play a major role in the determination of NPS when images are not stationary. This study emphasizes the need for consistent measurement methods to assess and compare image quality in CT.

Magnitude and Frequency of Iowa Floods, 1966

Flood records for regular and partial-record gaging stations are contained in the following pages. Each listing contains the station number .and name, descriptive paragraphs pertaining to the station, and a listing of the flood peaks available through the 1965 water year 2/. 2/ A water year is the period from October 1 to the following September 30 and has the same yearly designation as September. Peaks above a base as well as annual peaks are listed. These provide the data for a partial-duration flood-frequency curve. Most of the material is self-explanatory and needs no discussion. However, a few items may be made clearer by the brief explanation which follows.

Workers exposed to wood dust have an increased micronucleus frequency in nasal and buccal cells: results from a pilot study

Wood dust is recognised as a human carcinogen, based on the strong association of wood dust exposure and the elevated risk of malignant tumours of the nasal cavity and paranasal sinuses [sino-nasal cancer (SNC)]. The study aimed to assess genetic damage in workers exposed to wood dust using biomarkers in both buccal and nasal cells that reflect genome instability events, cellular proliferation and cell death frequencies. Nasal and buccal epithelial cells were collected from 31 parquet layers, installers, carpenters and furniture workers (exposed group) and 19 non-exposed workers located in Switzerland. Micronucleus (MN) frequencies were scored in nasal and buccal cells collected among woodworkers. Other nuclear anomalies in buccal cells were measured through the use of the buccal micronucleus cytome assay. MN frequencies in nasal and buccal cells were significantly higher in the exposed group compared to the non-exposed group; odds ratio for nasal cells 3.1 [95% confidence interval (CI) 1.8-5.1] and buccal cells 1.8 (95% CI 1.3-2.4). The exposed group had higher frequencies of cells with nuclear buds, karyorrhectic, pyknotic, karyolytic cells and a decrease in the frequency of basal, binucleated and condensed cells compared to the non-exposed group. Our study confirms that woodworkers have an elevated risk for chromosomal instability in cells of the aerodigestive tract. The MN assay in nasal cells may become a relevant biomonitoring tool in the future for early detection of SNC risk. Future studies should seek to standardise the protocol for MN frequency in nasal cells similar to that for MN in buccal cells.

Adding tobacco to cannabis: its frequency and likely implications.

INTRODUCTION: Young cannabis users are at increased risk of later cigarette initiation and progression to nicotine addiction. The present study addresses the frequency at which mulling (adding tobacco to cannabis smoked as joints) is performed and in which way this practice varies according to cigarette smoking status. METHODS: Data were issued from the Swiss 2007 European School Survey Project on Alcohol and other Drugs (ESPAD). A total of 881 past month cannabis users (mean age 15 years, boys 60.1%) were inquired on mulling using an anonymous self-administered questionnaire. Participants were further grouped according to their cigarette smoking status (daily, occasional, former, and never-smokers). RESULTS: Four of every 5 cannabis users depicted mulling as frequently performed. The highest occurrence was found among daily cigarette smokers (DSC; 90.3%), while former cigarette smokers reported the lowest (58.9%). The multinomial logistic regression showed DSC more likely reporting mulling as frequent compared with never-smokers (risk ratio = 3.56 [95% CI 1.55-8.21]). Conclusions: Mulling appears to be a very common process among young cannabis users, especially among concomitant cigarette smokers. Nevertheless, the majority of cigarette abstainers also reported frequently adding tobacco to the cannabis they smoke. Because it may represent a significant exposition to nicotine, mulling should be taken into account when assessing substance use among adolescents and in supporting their quitting attempts.

Soybean crop area estimation by Modis/Evi data

The objective of this work was to develop a procedure to estimate soybean crop areas in Rio Grande do Sul state, Brazil. Estimations were made based on the temporal profiles of the enhanced vegetation index (Evi) calculated from moderate resolution imaging spectroradiometer (Modis) images. The methodology developed for soybean classification was named Modis crop detection algorithm (MCDA). The MCDA provides soybean area estimates in December (first forecast), using images from the sowing period, and March (second forecast), using images from the sowing and maximum crop development periods. The results obtained by the MCDA were compared with the official estimates on soybean area of the Instituto Brasileiro de Geografia e Estatística. The coefficients of determination ranged from 0.91 to 0.95, indicating good agreement between the estimates. For the 2000/2001 crop year, the MCDA soybean crop map was evaluated using a soybean crop map derived from Landsat images, and the overall map accuracy was approximately 82%, with similar commission and omission errors. The MCDA was able to estimate soybean crop areas in Rio Grande do Sul State and to generate an annual thematic map with the geographic position of the soybean fields. The soybean crop area estimates by the MCDA are in good agreement with the official agricultural statistics.

Stratified estimation of forest inventory variables using spatially summarized stratifications

Abstract

Bone mineral density (BMD), micro-architecture estimation (TBS) and vertebral fracture assessment (VFA) extracted from a single DXA device in combination with clinical risk factors improve significantly the identification of women at high risk of fracture.

Osteoporosis (OP) is a systemic skeletal disease characterized by a low bone mineral density (BMD) and a micro-architectural (MA) deterioration. Clinical risk factors (CRF) are often used as a MA approximation. MA is yet evaluable in daily practice by the trabecular bone score (TBS) measure. TBS is very simple to obtain, by reanalyzing a lumbar DXA-scan. TBS has proven to have diagnosis and prognosis values, partially independent of CRF and BMD. The aim of the OsteoLaus cohort is to combine in daily practice the CRF and the information given by DXA (BMD, TBS and vertebral fracture assessment (VFA)) to better identify women at high fracture risk. The OsteoLaus cohort (1400 women 50 to 80 years living in Lausanne, Switzerland) started in 2010. This study is derived from the cohort COLAUS who started in Lausanne in 2003. The main goal of COLAUS is to obtain information on the epidemiology and genetic determinants of cardiovascular risk in 6700 men and women. CRF for OP, bone ultrasound of the heel, lumbar spine and hip BMD, VFA by DXA and MA evaluation by TBS are recorded in OsteoLaus. Preliminary results are reported. We included 631 women: mean age 67.4 ± 6.7 years, BMI 26.1 ± 4.6, mean lumbar spine BMD 0.943 ± 0.168 (T-score − 1.4 SD), and TBS 1.271 ± 0.103. As expected, correlation between BMD and site matched TBS is low (r2 = 0.16). Prevalence of VFx grade 2/3, major OP Fx and all OP Fx is 8.4%, 17.0% and 26.0% respectively. Age- and BMI-adjusted ORs (per SD decrease) are 1.8 (1.2-2.5), 1.6 (1.2-2.1), and 1.3 (1.1-1.6) for BMD for the different categories of fractures and 2.0 (1.4-3.0), 1.9 (1.4-2.5), and 1.4 (1.1-1.7) for TBS respectively. Only 32 to 37% of women with OP Fx have a BMD < − 2.5 SD or a TBS < 1.200. If we combine a BMD < − 2.5 SD or a TBS < 1.200, 54 to 60% of women with an osteoporotic Fx are identified. As in the already published studies, these preliminary results confirm the partial independence between BMD and TBS. More importantly, a combination of TBS subsequent to BMD increases significantly the identification of women with prevalent OP Fx which would have been misclassified by BMD alone. For the first time we are able to have complementary information about fracture (VFA), density (BMD), micro- and macro architecture (TBS and HAS) from a simple, low ionizing radiation and cheap device: DXA. Such complementary information is very useful for the patient in the daily practice and moreover will likely have an impact on cost effectiveness analysis.

Bayesian estimation of diameter distribution during harvesting

Abstract