Higher Commission Errors Research Articles

Abnormal Centroparietal ERP Response in Predominantly Medication-Naive Adolescent Boys With ADHD During Both Response Inhibition and Execution

Abnormal event-related potential (ERP) responses have been reported in children and adolescents with attention deficit hyperactivity disorder (ADHD) and a medication history compared with in healthy controls during tasks of response control and conflict inhibition. This study reports neurophysiologic correlates of a task dependent on these cognitive functions in a large, predominantly medication naive, group of adolescents with ADHD compared with that in healthy age- and intelligence quotient (IQ)-matched controls using area-under-the-curve (AUC) analysis. Fifty-four adolescents with ADHD and 55 healthy comparisons completed a hybrid conflict and response inhibition Go/NoGo ERP task. The performance data showed that children with ADHD compared with controls had deficits in both the inhibitory measures (higher commission errors) and the Go process of the task (slower reaction times and enhanced omission errors). The ERP data showed significant impairments in brain function in the ADHD relative to the control group for late, endogenous ERPs (N2, P3a, and P3b), whereas no group differences were found for the earlier P200. All findings remained when a minority of children with medication history was excluded. Furthermore, deficits were not specific to the inhibitory processes of the task but were equally observed during the execution functions. Group differences were particularly pronounced over central and centroparietal sites across all time points, presumably reflecting the midline attention system mediated by anterior and posterior cingulate that is important for generic, condition-independent visual-spatial attention and response selection processes. The findings demonstrate that adolescents with ADHD have abnormal ERP responses not only during inhibitory, but also execution-related processes and, furthermore, that these deficits are independent from medication history.

Effects of species ecology and urbanization on accuracy of a cover-type model: A test using GAP analysis

Models of vertebrate distributions based on dominant vegetation cover or land-use classification are commonly used for conservation planning, but these models may be inappropriate for species that choose sites based on criteria other than land cover or within urban areas that are not adequately described by cover-type alone. We compared the accuracy of predicted occupancy of birds for a set of cover-type models—Alabama Gap Analysis Program's (ALGAP) vertebrate distribution maps—between an urban and a rural landscape in east-central Alabama. We performed analysis at two scales of investigation—0.03-km2 point-count surveys or 28.26-km2 landscapes—using point counts conducted during summers 2004–2006. We tested ALGAP's ability to predict the occupancy of habitat by birds grouped by life-history parameters: migrant, resident, insectivore, carnivore, and omnivore, forest dweller, and cavity nester. ALGAP performed well at the scale of entire landscapes but poorly at the scale of individual point counts. At the point-count scale, ALGAP was most accurate for species requiring interior forest conditions. At the landscape scale, ALGAP was more accurate in the rural landscape than the urban landscape, and it had higher commission errors in the urban landscape. Variation in the ability of ALGAP to predict species occupancy was likely due to (1) poor model performance when applied to species that choose sites using criteria other than cover type and (2) the inadequacy of ALGAP to describe a heterogeneous urbanized landscape. Our results highlight pitfalls of using land cover information to model species distributions in situations where it may be inappropriate.

Reference vs. present-day condition: early planning decisions influence the achievement of conservation objectives

1. A vast scientific literature has been devoted to identifying the best way to represent biodiversity for conservation in the last decade. Methods exist for deciding how to use scarce information and avoid omission and commission errors. The effect of these errors on reserve efficiency does not arise only from the accuracy of data representing conservation features, as usually considered. There are also several underlying assumptions associated with the type of data used that might affect accuracy of conservation decision-making and compromise achievement of conservation objectives. 2. Here the effects of two management scenarios on selection of priority areas for conservation are explored. The spatial distribution of 10 native freshwater fish species in an Iberian basin under present-day and reference conditions were modelled and priority areas for both scenarios using the same spatial and cost constraints were identified. 3. Priority areas identified under the present-day scenario reflected the up-to-date spatial distribution of species and avoided the selection of highly perturbed and costly areas. The isolated spatial distribution of native populations imposed by the current perturbation status limited the spatial connectivity between priority areas under the present-day scenario. Most importantly for the achievement of conservation objectives, priority areas selected under both scenarios did not overlap. 4. Given that the reference scenario was based on potential presence of native species the actual representation of species would be overestimated if consideration were not given to restoring reference conditions (high commission errors). Based on results obtained it is recommended that planners give more consideration to the current perturbation status when identifying priority areas for conservation.

How much is built? Quantifying and interpreting patterns of built space from different data sources

Land-use/cover change (LUCC) has emerged as a crucial component of applied research in remote sensing. This work compares two methodologies, based on two data sources, for assessing amounts of land transformed from open to built space in three regions in Israel. We use a decision-tree methodology to define open and built space from remotely sensed (RS) Landsat data and a geographic information systems (GIS) platform for analysing 1:50 000 scale survey maps. The methodologies are developed independently, used to quantify and characterize the spatial pattern of built space, and then analysed for their strengths and weaknesses. We then develop a method for combining the built area maps derived from each methodology, capitalizing on the strengths of each. The RS methodology had higher omission errors for built space in areas with high vegetation levels and low-density exurban development, but high commission errors in the arid region. The GIS analysis generally had fewer errors, although systematically missed built surfaces that were not specifically buildings or roads, as well as structures intentionally omitted from the maps. We recommend using maps for baseline estimates whenever possible and then complementing the estimates with clusters of built areas identified with the RS methodology. The results of this comparative study are relevant to both researchers and practitioners who need to understand the strengths and weaknesses of mapping techniques they are using.

Delineating new foot trails within the US-Mexico border zone using semi-automatic linear object extraction methods and very high resolution imagery

A consequence of illegal immigration and border law enforcement practices has been the development of a complex foot trail network in remote areas of San Diego County near the US–Mexico border. Comprehensive monitoring of changes in trail networks requires multitemporal remote sensing analyses. Three semi-automated, commercially available object extraction routines were evaluated for delineating new trails. Three types of multi-temporal image products were generated from two dates of scanned colour infrared (CIR) images of two US–Mexico border study sites, at four spatial resolutions (15, 30, 60 and 120 cm). Accuracy was assessed using reference data created by manual image interpretation. The semi-automated routines captured most of the new trail objects, but also contained gaps and high commission error. Products derived using a spatial contextual-based neural network classifier with CIR image difference or red band layer stack and 15 or 30 cm spatial resolution image inputs yielded the best extractions of new trails.

Delineating an exurban development footprint using SPOT imagery and ancillary data

Exurban development, characterized by low density residential development, is one of the leading anthropogenic causes of land transformation. A major hindrance to studying this phenomenon is a lack of spatially explicit data. In this paper, we explore a simple method based on NDVI recoding of SPOT 5 imagery (10 m resolution) to delineate exurban built pixels across large spatial extents. The study area is the heterogeneous Peterborough County (Ontario, Canada). While an accuracy assessment of the initial NDVI recoding had a producer’s accuracy of approximately 80%, the user’s accuracy was extremely low (20%) reflecting high commission error. To improve the latter, post-classification structural and contextual processing using readily available data were examined. The structural processing produced slight improvement, but the user’s accuracy was still mostly below 50%. The contextual processing using water, roads, and a dasymetric map also showed only slight improvement. Alternatively, the inclusion of parcel boundary data proved to be the most effective method for exurban mapping in the study area, with the user’s accuracy in most sections of the study area over 65% and the producer’s accuracy approximately 80%. This study highlights how the low density, dispersed nature of the exurban development compounds the normal challenges associated with mapping built cover, making most of the traditional post-classification processing methods ineffective. An exception to this appears to be contextual processing based on parcel size.

Land-use change simulation and assessment of driving factors in the loess hilly region—a case study as Pengyang County

The main objective of this study is to evaluate the land-use change and its relationship with its driving factors in the loess hilly region. In this study, a case study was carried out in Pengyang County. We set two land-use demand scenarios (a baseline scenario (scenario 1) and a real land-use requirement scenario (scenario 2)) during year 2001-2005 via assuming the effect of driving factors on land-use change keeps stable from 1993 to 2005. Two simulated land-use patterns of 2005 are therefore achieved accordingly by use of the conversion of land use and its effects model at small regional extent. Kappa analyses are conducted to compare each simulated land-use pattern with the reality. Results show that (1) the associated kappa values were decreased from 0.83 in 1993-2000 to 0.27 (in scenario 1) and 0.23 (in scenario 2) in 2001-2005 and (2) forest and grassland were the land-use types with highest commission errors, which implies that conversion of both the land-use types mentioned above is the main determinant of change of kappa values. Our study indicates the land-use change was driven by the synthetic multiply factors including natural and social-economic factors (e.g., slope, aspect, elevation, distance to road, soil types, and population dense) in 1993-2000 until "Grain for Green Project" was implemented and has become the dominant factor in 2001-2005.

Distribution of Capybaras in an Agroecosystem, Southeastern Brazil, Based on Ecological Niche Modeling

Southeastern Brazil has seen dramatic landscape modifications in recent decades, due to expansion of agriculture and urban areas; these changes have influenced the distribution and abundance of vertebrates. We developed predictive models of ecological and spatial distributions of capybaras (Hydrochoerus hydrochaeris) using ecological niche modeling. Most occurrences of capybaras were in flat areas with water bodies surrounded by sugarcane and pasture. More than 75% of the Piracicaba River basin was estimated as potentially habitable by capybara. The models had low omission error (2.3‐3.4%), but higher commission error (91.0‐98.5%); these ‘‘model failures’’ seem to be more related to local habitat characteristics than to spatial ones. The potential distribution of capybaras in the basin is associated with anthropogenic habitats, particularly with intensive land use for agriculture.

Some challenges in global land cover mapping: An assessment of agreement and accuracy in existing 1 km datasets

Many investigators need and use global land cover maps for a wide variety of purposes. Ironically, after many years of very limited availability, there are now multiple global land cover maps and it is not readily apparent (1) which is most useful for particular applications or (2) how to combine the different maps to provide an improved dataset. The existing global land cover maps at 1 km spatial resolution have arisen from different initiatives and are based on different remote sensing data and employed different methodologies. Perhaps more significantly, they have different legends. As a result, comparison of the different land cover maps is difficult and information about their relative utility is limited. In an attempt to compare the datasets and assess their strengths and weaknesses we harmonized the thematic legends of four available coarse-resolution global land cover maps (IGBP DISCover, UMD, MODIS 1-km, and GLC2000) using the LCCS-based land cover legend translation protocols. Analysis of the agreement among the global land cover maps and existing validation information highlights general patterns of agreement, inconsistencies and uncertainties. The thematic classes of Evergreen broadleaf trees, Snow and Ice, and Barren show high producer and user accuracy and good agreement among the datasets, while classes of mixed tree types show high commission errors. Overall, the results show a limited ability of the four global products to discriminate mixed classes characterized by a mosaic of trees, shrubs, and herbaceous vegetation. There is a strong relationship between class accuracy, spatial agreement among the datasets, and the heterogeneity of landscapes. Suggestions for future mapping projects include careful definition of mixed unit classes, and improvement in mapping heterogeneous landscapes.

Mapping Locust Habitats in the Amudarya River Delta, Uzbekistan with Multi-Temporal MODIS Imagery

Reed beds of Phragmites australis in the River Amudarya delta near the Aral Sea constitute permanent breeding areas of the Asian Migratory locust, Locusta migratoria migratoria. Every year, thousands of hectares are treated with broad-spectrum insecticides to prevent locust swarms from damaging crops in adjacent areas. To devise efficient locust monitoring and management plans, accurate and updated information about the spatial distribution of reeds is necessary. Given the vast geographic extent of the delta, traditional, ground survey methods are inadequate. Remotely sensed data collected by the MODIS sensor aboard the TERRA satellite provide a useful tool to characterize the spatial distribution of reeds. Multi-temporal MODIS data, collected at different times of the growing season, were used to generate spectral-temporal signatures for reeds and other land cover classes. These spectral-temporal signatures were matched with reed phenology. MODIS information was digitally classified to generate a land cover map with an overall accuracy of 74%. MODIS data captured 87% of the ground-verified reed locations. Estimates derived from MODIS data indicate that 18% of the study area was covered by reeds. However, high commission error resulted from misclassification of reeds mixed with shrubs class and shrubs class as reeds. This could have resulted in overprediction of the area covered by reeds. Additional research is needed to minimize the overlap between reeds and other vegetation classes (shrubs, and reed and shrub mix). Nevertheless, despite its relatively low spatial resolution (250 m), multi-temporal MODIS data were able to adequately capture the distribution of reeds. Instead of blanketing the fragile wetland ecosystem of the Amudarya delta with chemical anti-locust treatments, plant protection specialists can use this information to devise ecologically sound pest management plans aimed at reducing the adverse environmental impact in the zone of the Aral Sea ecological catastrophe. MODIS methodology to identify reed stands can be applicable to the Migratory locust habitats in other geographic areas.

Dissociation, memory commission errors, and heightened autonomic reactivity

If dissociative symptoms are manifestations of a psychological defense mechanism, one would expect people who have such symptoms to react with lower levels of physiological arousal and with memory omissions to emotionally provocative material. The current study tested this assumption in a sample of undergraduates. Sixty-two undergraduate students viewed a highly emotional video fragment. Pearson's product–moment correlations were calculated between dissociation (as indexed by the Dissociative Experiences Scale, DES) and all dependent measures. High dissociators exhibited elevated skin conductance responses (SCRs) to the fragment. Memory for the video fragment was then tested. While omission errors were unrelated to dissociation, high dissociators exhibited a tendency to produce commission errors. This could not be explained by a reduced working memory capacity. However, fantasy proneness was found related to high dissociators' commission errors. Thus, it seems that a pattern of heightened emotional reactivity and commission errors is typical for people with elevated dissociation scores. This pattern is difficult to reconcile with the defensive function ascribed to dissociation.

Predicting the distribution of non‐vagile taxa: a response to McNyset and Blackburn (2006) and re‐evaluation of Stockman et al. (2006)

ABSTRACTThis paper addresses the issues raised by McNyset and Blackburn (2006) in their response to Stockman et al. (2006). Re‐evaluation of our published GARP analyses by McNyset and Blackburn showed that a much improved ecological niche model is obtained for predicting the distribution of the trapdoor spider genus Promyrmekiaphila in central/northern California. The improved niche model results in a substantially reduced omission error rate and a predictive model comparable to models obtained using other methods (GLM and BIOCLIM). However, the improved GARP models have a high commission error rate (> 0.75); consequently, the inferences regarding difficulties in modelling non‐vagile taxa drawn by Stockman et al. remain valid. Finally, we discuss other relatively minor criticisms of our study raised by McNyset and Blackburn and issues related to the peer review of our original paper.

Assessing the extent of agriculture/pasture and secondary succession forest in the Brazilian Legal Amazon using SPOT VEGETATION data

There has been growing concern about land use/land cover change in tropical regions, as there is evidence of its influence on the observed increase in atmospheric carbon dioxide concentration and consequent climatic changes. Mapping of deforestation by the Brazil's National Space Research Institute (INPE) in areas of primary tropical forest using satellite data indicates a value of 587,727 km 2 up to the year 2000. Although most of the efforts have been concentrated in mapping primary tropical forest deforestation, there is also evidence of large-scale deforestation in the cerrado savanna, the second most important biome in the region. The main purpose of this work was to assess the extent of agriculture/pasture and secondary succession forest in the Brazilian Legal Amazon (BLA) in 2000, using a set of multitemporal images from the 1-km SPOT-4 VEGETATION (VGT) sensor. Additionally, we discriminated primary tropical forest, cerrado savanna, and natural/artificial waterbodies. Four classification algorithms were tested: quadratic discriminant analysis (QDA), simple classification trees (SCT), probability-bagging classification trees (PBCT), and k-nearest neighbors (K-NN). The agriculture/pasture class is a surrogate for those areas cleared of its original vegetation cover in the past, acting as a source of carbon. On the contrary, the secondary succession forest class behaves as a sink of carbon. We used a time series of 12 monthly composite images of the year 2000, derived from the SPOT-4 VGT sensor. A set of 19 Landsat scenes was used to select training and testing data. A 10-fold cross validation procedure rated PBCT as the best classification algorithm, with an overall sample accuracy of 0.92. High omission and commission errors occurred in the secondary succession forest class, due to confusion with agriculture/pasture and primary tropical forest classes. However, the PBCT algorithm generated the lower misclassification error in this class. Besides, this algorithm yields information about class membership probability, with ∼80% of the pixels with class membership probability greater or equal than 0.8. The estimated total area of agriculture/pasture and secondary succession forest in 2000 in the BLA was 966 × 10 3 and 140 × 10 3 km 2, respectively. Comparison with an existing land cover map indicates that agriculture/pasture occurred primarily in areas previously occupied by primary tropical forest (46%) and cerrado savanna (33%), and also in transition forest (19%), and other vegetation types (2%). This further confirms the existing evidence of extensive cerrado savanna conversion. This study also concludes that SPOT-4 VGT data are adequate for discriminating several major land cover types in tropical regions. Agriculture/pasture was mapped with errors of about 5%. Very high classification errors were associated with secondary succession forest, suggesting that a different methodology/sensor has to be used to address this difficult land cover class (namely with the inclusion of ancillary data). For the other classes, we consider that accurate maps can be derived from SPOT-4 VGT data with errors lower than 20% for the cerrado savanna, and errors lower than 10% for the other land cover classes. These estimates may be useful to evaluate impacts of land use/land cover change on the carbon and water cycles, biotic diversity, and soil degradation.

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To enhance effectiveness of natural resources evaluation an assessment on the trend of land- use and its impacts is necessary. This is needed by regions which are interacted each others and covering large areas. A remote sensing technology is a reliable and appropriate choice for such area. A study on the land-use assessment was employed using manual method through the implementation of Spot, Landsats, and Radar imageries. The results were as follows: 1) Until the year 1980, the concession area situated at Long Nah, administratively under authority of PT Inhutani I. East Kalimantan were mostly still covered by virgin forest with occasional and scattered small villages 2) Manual interpretation using imageries of Spot, Landsats and Radars disclosed the following results: (a) Spot imageries turned out to be 64. 7% as the correct figure and 35.3% as the false figure;, (b) Landsat imageries interpreted 53.3% as correct and 46.7% as false; (c) Radar imageris conducted in March and April 1998 revealed 38. 1% as correct and 61.9% as false. 3) Changes forest land-use during the period 1980-1998 occurred in low-land dry forest and partly in swampy forest, which were further converted to the plantation forest. Meanwhile, the changes for other land-uses among others agriculture were almost insignificant ( less than 3%). This is because soil layers in the corresponding land were thin and acidic rendering unsuitable for agriculture activities. 4) In order to reduce high commission error, the appropriate number of strata relevant to the land-use interpretation should not be too detailed but adequately established as simply aspossible.

Crop Identification in a Parkland Environment Using Aerial Photography

SUMMARYThe estimation of crop production using remote sensing techniques first requires a correct identification of the crops found in a given area. In Western Canada, the identification of field crops is hampered by the occurrence of confusion crops such as spring grains. These follow crop calendars and/or possess spectral signatures similar to each other. The results of an interpretation test using color and color infra-red photography show a higher percent correct identification of spring grains with the color photography. This is attributed in part to the differences in visible colors often noted in the field during the vegetative period between darker green wheat crops and lighter green oat and barley crops. A higher percent correct identification of fallow fields was attained with the color infra-red photography. Relatively high percent commission errors were made for grain and hay crops with both types of photography.

Neuroleptic interference with the cocaine cue: internal stimulus control of behavior and psychosis.

The ability of cocaine to exert internal stimulus control of behavior was investigated by training rats to discriminate 10 mg/kg cocaine from saline in a discrete-trial, two-lever, food-reward procedure. Acquisition of response control by cocaine (1) succeeded in all animals tested, (2) proceeded rapidly, and (3) was associated with a high Commission Error: Omission Error ratio. These findings support the hypothesis that cocaine, a prototype of drugs inducing a psychotic condition in humans, can act as a powerful internal stimulus in rats. The cocaine cue was also responsive to the action of the dopamine-receptor-blocking agents spiperone (ED50: 0.06 mg/kg), haloperidol (0.24 mg/kg), and pimozide (1.90 mg/kg). d, l-Amphetamine (1.25 mg/kg) induced stimulus generalization with cocaine, and this generalization was blocked by dosages of the same neuroleptics comparable to those of cocaine antagonism. The results are discussed in terms of internal stimulus control of behavior and its relevance to the psychophysiology of schizophrenia.