Spatial Processing Research Articles

Using virtual reality to study spatial mapping and threat learning

Using spatial mapping processes to discriminate between threat and safety is crucial for survival. Little is known why some fail to discriminate during contextual conditioning. We used a virtual reality (VR) contextual conditioning paradigm to elucidate the effects of state and trait anxiety on contextual threat learning. Participants (n = 70) “picked” flowers in a VR environment. Dangerous zone flowers predicted an electric shock, while safe zone flowers did not. Between trials, participants completed a spatial memory task. Galvanic skin response (GSR) and State Trait Anxiety Inventory scores were recorded. Participants were considered learners for correctly identifying both zones. Non-learners, compared to learners, performed worse during the spatial memory task and demonstrated higher state anxiety scores and GSR. Learners showed higher skin conductance response (SCR) in the dangerous compared to the safe zone, while non-learners showed no SCR differences between zones. Results indicate state anxiety may impair spatial mapping, disrupting contextual threat learning.

Prioritizing tidal marsh restoration in grazing lands.

Prioritizing tidal marsh restoration in grazing lands.

Meta-analysis of a megafish: assessing patterns and predictors of Alligator Gar movement across multiple populations

BackgroundFreshwater megafishes are among some of the most commercially and ecologically important aquatic organisms yet are disproportionately threatened with range and population reduction. Anthropogenic alterations of rivers influencing migrations are among the most significant causes for these declines. However, migratory fishes do not always respond similarly to movement barriers and thus it is necessary to develop models to predict movements of freshwater migratory fishes in the face of anthropogenic alteration. Predicting movement of freshwater fishes is often investigated using statistical packages. However, empirical studies assessing these packages have led to mixed results, questioning its applicability to all taxa. We argue that spatial, temporal, and environmental attributes are more influential for movement of a migratory megafish, the Alligator Gar (Atractosteus spatula), than the current parameters explored in a globally relevant fish movement model.MethodsThis study explored two independent mobile telemetry datasets investigating Alligator Gar movement on the Brazos and Trinity rivers. Environmental associations were investigated to predict Alligator Gar displacement and dispersal using generalized additive models, generalized linear models, and model selection. Leptokurtosis of Alligator Gar populations was also assessed. Predictability of the movement model was tested by comparing observed to model derived stationary and mobile components making up a leptokurtic movement distribution.ResultsOur study suggests that current and antecedent measures of discharge and water temperature are positively correlated with Alligator Gar displacement and dispersal. However, these patterns are only detectable when monthly relocation intervals are explored rather than seasonal scales. Leptokurtosis was observed in both Alligator Gar populations. However, movement was normally distributed (i.e., mesokurtic) under tracking events following high flood pulses. Additionally, predicted Alligator Gar movement was significantly farther under modeled values compared to observed values, in part because the species undergoes cyclical migrations for reproduction that are sensitive to water temperature and discharge.DiscussionIn conclusion, this study provides an alternative framework to assess the movement patterns of migratory fishes, which could be tested on additional freshwater fishes, and suggests that assessing spatial, environmental, and temporal processes simultaneously are necessary to capture the complexities of fish movement which currently are unavailable for the movement model we investigated.

An interpretable and transferable model for shallow landslides detachment combining spatial Poisson point processes and generalized additive models

Abstract Shallow landslides are rapidly moving and strongly dangerous slides. In the present work, the probabilistic distribution of the landslide detachment points within a valley is modelled as a spatial Poisson point process, whose intensity depends on geophysical covariates according to a generalized additive model. This jointly allows to obtain good predictive performance and to preserve the interpretability of the effects of the geophysical predictors on the intensity of the process. We propose a novel workflow, based on Random Forests, to select the geophysical predictors entering the model for the intensity. The statistically significant effects are interpreted as activating or stabilizing factors for landslide detachment. The transferability of the resulting model is guaranteed by training, validating and testing the algorithms on mutually disjoint valleys in the Alps of Lombardy (Italy). Finally, the uncertainty around the estimated intensity of the process is quantified via semiparametric bootstrap.

The Conditions of the Working Class in 1960s Beirut: Fire and Everyday Struggles in Karantina

AbstractIn this paper, I examine the spatial processes of class formation within informal urban spaces. To do so, I consider Karantina in the 1960s, an outgrowth of one of the oldest refugee camps in the world situated in northeastern Beirut, Lebanon. I focus on the struggles of those living in precarious informal shacks, known as tanaké, who repeatedly fought against arson likely instigated by local landowners seeking to evict them. This analysis underscores the decisive role material conditions play in fostering class consciousness among a diverse population, primarily composed of factory and informal workers, as they assert their “right to the city”. I argue that these galvanising confrontations, experienced as recurrent displacement by fire, catalysed a political struggle that transformed this group from a class‐in‐itself into a class‐for‐itself. A socio‐spatial analysis of the material living conditions of the working class, defined by everyday struggles, is essential to understanding political subjectivity.

Development of the Persian Listening in Spatialized Noise Sentence Test: A Preliminary Study

Background and Aim: Listening in Spatialized Noise Sentence (LiSN-S) is one of the auditory processing disorder test battery that specifically diagnose spatial processing disorders. This research aimed to develop The Persian version of the LiSN-S, for assessing auditory processing disorders in the Persian speakers’ population. Methods: The PLiSN-S test was developed based on its original Australian version. The speech stimuli were convolved with Head-Related Transfer Functions (HRTFs) to generate speech in the presence of spatialized noise. In total, 120 target sentences (consisting of five 1-3-syllable words) and competing stories were presented in four conditions. These included the Same Voice co-located condition (SV0°), Different Voice co-located condition (DV0°), Same Voice separated condition (SV±90°), and Different Voice separated condition (DV±90°). Then, data from 30 adults aged 18–23 with normal hearing were obtained. Results: The results from the normal-hearing subjects showed that the Speech Reception Threshold (SRT) scores, expressed as Signal to Noise Ratios (SNR), varied across the four conditions (SV0°, DV0° SV±90°, DV±90°) the highest and lowest SRTs belonged to the first and last conditions, respectively. The amount of advantage in all conditions was lower than in the previously published English versions. Conclusion: Considering the impact of spatial separation on the SRTs, PLiSN-S appears to be an effective tool for measuring spatial processing skills. Keywords: Auditory stream segregation; spatial hearing; speech in noise

Enhancing Scalability in Bayesian Nonparametric Factor Analysis of Spatiotemporal Data

This article introduces novel and practicable Bayesian factor analysis frameworks that are computationally feasible for moderate to large spatiotemporal data. Previous Bayesian analysis of spatiotemporal data has utilized a Bayesian factor model with separable temporal latent factors and spatial factor loadings, along with stick-breaking process priors on the loadings to enable clustering of spatial locations. Such a flexible Bayesian model, however, faces a prohibitively high computational cost in posterior sampling when the spatial and temporal dimensions increase to a couple hundred. We address this computational challenge with several speed-up proposals. We integrate a new slice sampling algorithm that permits varying numbers of spatial mixture components across all latent factors and guarantees them to be non-increasing through the posterior sampling iterations, thus effectively reducing the number of mixture parameters. Additionally, we introduce a spatial latent nearest-neighbor Gaussian process prior and new sequential updating algorithms for the spatially varying latent variables in the stick-breaking process prior. Our new models and sampling algorithms exhibit significantly enhanced computational scalability and storage efficiency and possess powerful inferential capabilities for both spatiotemporal prediction and clustering of spatial locations with similar temporal trajectories. The improvement in computational efficiency and inferential performance is substantiated by extensive simulation experiments.

Understanding interactive effects between habitat configuration and pesticide use for pollination: towards better informed landscape management

BackgroundThe restoration of natural landscape elements is a frequently adopted pathway to improve wild pollinator abundance, diversity, and their pollination services in intensively used agricultural landscapes. However, pollinators in the intended refuges can become exposed to agrochemicals when foraging in surrounding agricultural fields. In order to effectively design pollinator conservation measures such as habitat restoration or pesticide reduction schemes, the effect of land use configuration on pesticide exposure and pollination service requires further investigation.MethodsWe developed a pollination model that extends existing approaches by simulating both pollination flights and concurrent pollinator exposure to toxic pesticides, enabling the estimation of pesticide impacts on pollination services. We calculated pollination service and pollinator health for a set of artificial landscapes, which varied in the percentage of pollinator habitat and agriculture, in the clustering of these land uses, as well as in the pollinator mortality hazard arising from the pesticides applied on agriculture.ResultsOur results show that in landscapes with less than 10% habitat and highly toxic pesticides, pollination services are mostly safeguarded by compact patches of habitat, as this configuration shelters more habitat from pesticide exposure. With increasing habitat amount or with pesticide applications causing less than 50% mortality in pollinators, more dispersed patches of habitat achieve a better pollination service for the landscape. We further tested the effect of pesticide application for different foraging ranges in a more realistic land use scenario. For pollinators with shorter foraging ranges, pesticide exposure from the immediate surroundings determines the achieved pollination. For species with longer foraging ranges, the availability of resources and the application of pesticides at landscape scale controls the pollination.ConclusionOur study highlights the importance of assessing spatial configuration effects on pesticide exposure for local pollinators. By applying these insights, land managers can devise land use arrangements to protect pollinator habitats and establish buffer zones to support pollinator activity in pesticide-intensive landscapes. As current guidelines largely lack spatially-explicit measures, we suggest to direct future research and policies towards the underlying spatial processes and their facilitation on parcel, farm, and landscape scale.

Estimating Spatially Explicit Survival and Mortality Risk From Telemetry Data With Thinned Point Process Models.

Mortality risk for animals often varies spatially and can be linked to how animals use landscapes. While numerous studies collect telemetry data on animals, the focus is typically on the period when animals are alive, even though there is important information that could be gleaned about mortality risk. We introduce a thinned spatial point process (SPP) modelling framework that couples relative abundance and space use with a mortality process to formally treat the occurrence of mortality events across the landscape as a spatial process. We show how this model can be embedded in a hierarchical statistical framework and fit to telemetry data to make inferences about how spatial covariates drive both space use and mortality risk. We apply the method to two data sets to study the effects of roads and habitat on spatially explicit mortality risk: (1) VHF telemetry data collected for willow ptarmigan in Alaska, and (2) hourly GPS telemetry data collected for black bears in Colorado. These case studies demonstrate the applicability of this method for different species and data types, making it broadly useful in enabling inferences about the mechanisms influencing animal survival and spatial population processes while formally treating survival as a spatial process, especially as the development and implementation of joint analyses continue to progress.

Evaluation of dynamic spatial auditory processing in Persian-Speaking elderly with normal hearing aged 55 to 70

Background and Aims: In noisy listening environments, one of the skills that is critical for speech perception is spatial auditory processing. It is predicted that the spatial auditory processing ability of elderly people decreases due to structural and physiological changes in auditory cortex, central auditory pathways and peripheral auditory system. The aim of this study is to investigate dynamic spatial auditory processing in elderly with normal hearing. Materials and methods: This study was conducted on 35 people (16 men and 19 women) in the age range of 55 to 70 years with normal hearing and the results were compared with the results of 35 healthy people (15 men and 20 women) in the age range of 18 to 25 years. To investigate the dynamic spatial auditory processing, after performing preliminary examinations such as otoscopy, audiometry and tympanometry, the Persian version of speech perception, spatial hearing and quality of hearing questionnaire (SSQ) and the spatial hearing questionnaire (SHQ) were completed in the form of an interview. Then, the dynamic spatial quick speech in noise (DS-QSIN) and the binaural masking level difference (BMLD) test were performed using the relevant applications and the values of signal noise ratio (SNR) loss, SNR50 and MLD were recorded for each person. Results: There is a significant difference (P<0.05) between the elderly and young groups according to the results of the SSQ, SHQ questionnaire, the SNR50 and SNR loss index, and the value of MLD. In this study did not reveal a statistically significant difference between two genders (P>0.05). Conclusion: The findings of this study showed that despite normal hearing, dynamic spatial auditory processing in the elderly has a weaker performance than in young people.

A Busse Balloon in the Lagoon: Herbivore Behaviour Generates Spatial Patterns in Coral Reef Ecosystems.

Spatial processes, particularly scale-dependent feedbacks, may play important and underappreciated roles in the dynamics of bistable ecosystems. For example, self-organised spatial patterns can allow for stable coexistence of alternative states outside regions of bistability, a phenomenon known as a Busse balloon. We used partial differential equations to explore the potential for such dynamics in coral reefs, focusing on how herbivore behaviour and mobility affect the stability of coral- and macroalgal-dominated states. Herbivore attraction to coral resulted in a Busse balloon that enhanced macroalgal resilience, with patterns persisting in regions of parameter space where nonspatial models predict uniform coral dominance. Thus, our work suggests herbivore association with coral (e.g., for shelter) can prevent reefs from reaching a fully coral-dominated state. More broadly, this study illustrates how consumer space use can prevent ecosystems from undergoing wholesale state transitions, highlighting the importance of explicitly accounting for space when studying bistable systems.

Pathological Mechanisms of Irradiation-Induced Neurological Deficits in the Developing Brain.

Cranial irradiation or radiotherapy (CRT) is one of the essential therapeutic modalities for central nervous system (CNS) tumors, and its efficacy is well known. Nevertheless, CRT is also associated with brain damages such as focal cerebral necrosis, neuroinflammation, cerebral microvascular anomalies, neurocognitive dysfunction, and hormone deficiencies in children. Children's brains are much more sensitive to CRT compared to the adult's brains. Thus, children's brains are also more likely to develop long-term CRT complication, which severely lessens their long-term quality of life after treatment. CRT to the juvenile rat led to a retardation of growth of the cerebellum; both the gray and white matter and neurogenic regions like the subventricular zone and the dentate gyrus in the hippocampus were predominantly vulnerable to CRT. Also, CRT-induced cognitive changes typically manifested as deficits in hippocampal-related functions of learning as well as memory, such as spatial information processing. Fractionated CRT-stimulated cognitive decline and hormone deficiencies were precisely associated with augmented neuronal cell death, blockade of neurogenesis, and stimulation of astrocytes and microglia. Thus, the aim of this review is to highlight the pathological mechanism of CRT-induced neurological deficits in the developing brain.

Spatial audio signal processing for augmented telepresence applications

Spatial audio signal processing for augmented telepresence applications

Retention and migration of microplastics in stepped paddy fields: A study on microplastic dynamics in the special irrigation system.

Retention and migration of microplastics in stepped paddy fields: A study on microplastic dynamics in the special irrigation system.

Spatio-Temporal Decoding of the Navon Task Challenges Rigid Hemispheric Asymmetries in Global-Local Processing.

Functional hemispheric asymmetries are considered a key factor in intra- and interindividual variability of global precedence effects. However, research in this area is permeated by a considerable number of inconsistent findings which may stem from significant methodological limitations. In pursuit of a more detailed model of global-local processing by combining both high temporal and spatial resolution, we employed Multivariate Pattern Analysis (MVPA) on Magnetoencephalography (MEG) recordings from 63 participants performing a divided visual field, divided attention Navon paradigm. The resulting decoding accuracies between various hierarchical letter forms and target levels were used to pinpoint potentially involved spatial networks and temporal processing sequences. Linear Discriminant Analysis (LDA) revealed temporal precedence of global over local letter form decoding accuracy peaks. Furthermore, searchlight analysis provided a nuanced spatial mapping that not only validated previously established core regions (lingual gyrus for local processing; inferior occipital gyrus for global processing) but also identified potential regions implicated in global-local integration. Yet, we observed substantial variation in lateralization patterns across our study sample, challenging the conventional assumption of right-hemispheric dominance for global and left-hemispheric dominance for local processing in the context of MVPA. Overall, our findings validate and broaden the scope of prior research by providing, for the first time, accurate temporal and spatial data on global-local processing from a single measurement. Moreover, we introduce interindividual variability in lateralization patterns as a potential factor contributing to past inconsistencies.

Designed 2D/2D F-doped TiO2@ZnIn2S4 heterojunction for efficient photo-utilization hydrogen generation.

Designed 2D/2D F-doped TiO2@ZnIn2S4 heterojunction for efficient photo-utilization hydrogen generation.

Detection and segmentation of pulmonary embolism in 3D CT pulmonary angiography using a threshold adjustment segmentation network

Pulmonary embolism is a life-threatening condition where early diagnosis and precise localization are crucial for improving patient outcomes. While CT pulmonary angiography (CTPA) is the primary method for detecting pulmonary embolism, existing segmentation algorithms struggle to effectively distinguish thrombi from vascular structures in complex 3D CTPA images, often leading to both false positives and false negatives. To address these challenges, the Threshold Adjustment Segmentation Network (TSNet) is proposed to enhance segmentation performance in 3D CTPA images. TSNet incorporates two core modules: the Threshold Adjustment Module (TAD) and the Geometric-Topological Axial Feature Module (GT-AFM). TAD utilizes logarithmic scaling, adaptive adjustments, and nonlinear transformations to optimize the probability distributions of thrombi and vessels, reducing false positives while improving the sensitivity of thrombus detection. GT-AFM integrates geometric features and topological information to enhance the recognition of complex vascular and thrombotic structures, improving spatial feature processing. Experimental results show that TSNet achieves a sensitivity of 0.761 and a false positives per scan of 1.273 at ε = 0 mm. With an increased tolerance of ε = 5 mm, sensitivity improves to 0.878 and false positives per scan decreases to 0.515, significantly reducing false positives. These results indicate that TSNet demonstrates superior segmentation performance under various tolerance levels, showing robustness and a well-balanced trade-off between sensitivity and false positives, making it highly promising for clinical applications.

Environmental context influences visual processing in thalamus.

Environmental context influences visual processing in thalamus.

Changes in cognition and astrocytic reactivity in a female rodent model of chemotherapy-induced cognitive impairment are variable both acutely and chronically.

Changes in cognition and astrocytic reactivity in a female rodent model of chemotherapy-induced cognitive impairment are variable both acutely and chronically.

Motor and visuospatial processing profile in a cross-conditions study: A comparison between developmental coordination disorder and nonverbal learning disability.

Neurodevelopmental conditions often exhibit overlapping symptoms, posing challenges for differential diagnosis. Developmental Coordination Disorder (DCD) manifests as fundamental motor impairments, often along with co-occurring visuospatial difficulties. Nonverbal Learning Disorder (NLD) features visuospatial core challenges, with a less consistent characterization of its motor profile. Strikingly, to date no study has directly compared DCD and NLD profiles. The present study aimed to analyze whether DCD and NLD share any characteristics by contrasting their motor and visuospatial performances, comparing them with non-diagnosed (ND) peers. A total of 102 participants (8-16 years; DCD N = 29, NLD N = 29, ND N = 44) completed motor and visuospatial tasks. The groups' performance was compared, and the discriminatory power of the measures administered was analyzed. Our findings support the substantial motor and visuospatial impairments in DCD and NLD, respectively. Regarding diagnostic efficacy, motor and visuospatial tasks effectively differentiated DCD or NLD from ND, with specificities related to each condition. Balance, and to a lesser extent, Spatial Processing revealed significant predictive power in distinguishing between DCD and NLD. Our results revealed cross-disorder similarities and highlighted specific hallmarks, corroborating the need of a comprehensive motor and visuospatial assessment for distinguishing between DCD and NLD.