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Spatial cognitive models obtained by multidimensional scaling represent cognitive structure by defining alternatives as points in a coordinate space based on relevant dimensions such that interstimulus dissimilarities perceived by the individual correspond to distances between the respective alternatives. The dependence of spatial models on the context of the judgments required of the individual was investigated. Context, which is defined as a perceptual interpretation and cognitive understanding of a judgment situation, was analyzed and classified with respect to five characteristics: physical environment, social environment, task definition, individual perspective, and temporal setting. Four experiments designed to produce changes in the characteristics of context and to test the effects of these changes upon individual cognitive spaces are described with focus on experiment design, objectives, statistical analysis, results, and conclusions. The hypothesis is advanced that an individual can be characterized as having a master cognitive space for a set of alternatives. When the context changes, the individual appears to change the dimension weights to give a new spatial configuration. Factor analysis was used in the interpretation and labeling of cognitive space dimensions.

This article is from BMC Infectious Diseases , volume 10 . Abstract Background: The incidence and prevalence of sexually transmitted infection (STI) in China has been on the rise in the past decade. Delineation of epidemiologic pattern is often hampered by its uneven distribution. Spatial distribution is often a neglected aspect of STI research, the description of which may enhance epidemiologic surveillance and inform service development. Methods: Over a one month-period, all first time attendees of 6 public STI clinics in Hong Kong were interviewed before clinical consultation using a standard questionnaire to assess their demographic, clinical and behavioural characteristics. A GIS (geographic information system)-based approach was adopted with mapping performed. The cases attending the clinics in different locations were profiled. A comparison was made between neighbourhood cases (patients living near a clinic) and distant cases (those farther off), by calculating the odds ratio for demographic, behavioural and geographic characteristics. Results: Of the 1142 STI patients evaluated, the residence locations of 1029 (90.1%) could be geocoded, of which 95.6% were ethnic Chinese and 63.4% male. Geographically only about a quarter lived in the same district as the clinic. STI patients aged 55 or above were more likely to be living in the vicinity of the clinic, located in the same or adjacent tertiary planning unit (a small geographic unit below district level). A majority of patients came from locations a few kilometers from the clinic, the distance of which varies between clinics. Overall, more syphilis cases were reported in patients residing in the same or adjacent tertiary planning unit, while distant cases tended to give a higher risk of inconsistent condom use. There were otherwise no significant clinical and epidemiologic differences between neighbourhood and distant STI cases. Conclusions: There was no specific relationship between STI and the residence location of patients as regards their clinical and epidemiologic characteristics in the territory of Hong Kong. Older STI patients were however more inclined to attend the nearby STI clinics. Most patients have travelled a variable distance to access the STI service. The relationship between STI clinic cases and distance could be a complex issue intertwined between psychosocial characteristics and STI service coverage.

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In today’s world, information is the most valuable resource. Geospatial information, which refers to the location of various features on earth, plays a crucial role in policymaking, implementation, and monitoring the policy outcomes. The information about forests, roads, water bodies, health and education facilities, population, human settlements etc. is geospatial. Due to financial and human resource constraints a single government department cannot collect such diverse information. Therefore, each department is mandated to collect and maintain one particular type of information. The information collected is used as evidence in policymaking and to ensure its efficacy, various types of information collected by departments is integrated and utilized. The dilemma is, government departments often do not share their collected information, despite them being funded by public money. Consequently, informed decision-making is hampered. The reasons for non-sharing of the information may include lack of technical capacity, fear of loss of control over information assets, poor quality of the information and lack of legal and policy framework to share information.  This article focuses on policy and legal barriers to geospatial information sharing in Pakistan. The study follows content analysis method, specifically used for deriving relevant information from the data. The data is collected through reviews of policy documents, minutes of meetings, and focused group discussions with experts on the subject. The article discusses how the current provisions are inadequate to deal with new developments in geospatial information sharing, and proposes recommendations for amending and updating existing laws and policies. The study finds that policymakers in Pakistan are still not aware of the potential of geospatial information and its sharing through NSDI for informing, and implementing public policies. Accordingly, the study recommends approving NSDI Act at the earliest.

In today’s world, information is the most valuable resource. Geospatial information, which refers to the location of various features on earth, plays a crucial role in policymaking, implementation, and monitoring the policy outcomes. The information about forests, roads, water bodies, health and education facilities, population, human settlements etc. is geospatial. Due to financial and human resource constraints a single government department cannot collect such diverse information. Therefore, each department is mandated to collect and maintain one particular type of information. The information collected is used as evidence in policymaking and to ensure its efficacy, various types of information collected by departments is integrated and utilized. The dilemma is, government departments often do not share their collected information, despite them being funded by public money. Consequently, informed decision-making is hampered. The reasons for non-sharing of the information may include lack of technical capacity, fear of loss of control over information assets, poor quality of the information and lack of legal and policy framework to share information.  This article focuses on policy and legal barriers to geospatial information sharing in Pakistan. The study follows content analysis method, specifically used for deriving relevant information from the data. The data is collected through reviews of policy documents, minutes of meetings, and focused group discussions with experts on the subject. The article discusses how the current provisions are inadequate to deal with new developments in geospatial information sharing, and proposes recommendations for amending and updating existing laws and policies. The study finds that policymakers in Pakistan are still not aware of the potential of geospatial information and its sharing through NSDI for informing, and implementing public policies. Accordingly, the study recommends approving NSDI Act at the earliest.

This study follows our prior study registered in OSF (https://osf.io/6eg5y). The study employed the contextual cueing paradigm that shows, repetitive search for the same target in the same scene forms associative memory of the distractor locations and the target location, and it shortens reaction time for the target (e.g., Chun & Jiang, 1998; Brady & Chun, 2007). With repetitive search experience, distractors serve as context to guide attention to the target as well as to inhibit attention to the distractors (Ogawa et al., 2007). However, when there is an instruction that a certain distractor is a future target, the context also facilitates searching for it when it becomes the search target (Conci et al., 2011; Conci & Müller, 2012). Likewise, when participants in pairs simultaneously search for different targets from each other, a partner’s target might capture attention and its position might be encoded and associated with the context. Therefore, the purpose of the prior study was to investigate whether the location of a partner’s target was encoded as well as participants’ own target. To test it, we examined whether a partner’s target could be found more quickly in the learned context than the non-learned context when it became a new search target. The task of our prior study was consisted of two phases: the learning phase and the transfer phase. While friend pairs of participants searched for each target in the learning phase, search targets changed into the friend’s target (i.e., the partner’s-target group) or one of the distractors (i.e., the no-one’s-target group) in the transfer phase. The results showed that the reaction times for the partner’s target in the learned context and the non-learned context were not significantly different in the first epoch of the transfer phase but significantly different in the second epoch. This contextual cueing effect for the new target in the second epoch was not significantly different between the partner’s target group and the no-one’s-target group. An exploratory analysis, however, revealed a correlation between the size of the contextual cueing effect in the last epoch of the learning phase and the first epoch of the transfer phase in the partner’s-target group. This correlation was not found in the no-one’s-target group. This result can be interpreted as the contextual memory that guided attention to the participants’ old target could also guide attention to the partner’s target but not for no-one’s target in the transfer phase. This preliminary finding supports our hypothesis that the location of the friend’s target as well as the location of their own target is intensely encoded when people learn spatial layouts of their search filed. However, this result was found by an exploratory analysis and needs to be tested again with a new sample. Therefore, we conduct another experiment with three modifications and investigate the same research question. The first modification is to recruit pairs of strangers instead of friends as participants. As literatures of joint action mostly investigate with the sample of pairs of strangers, our study can be compared with the results of the previous studies. The second modification is to present search display for a fixed duration. Search display disappeared as soon as both participants made their responses in the previous version. After the experiments, some of the participants commented that they sometimes concerned the friend’s target when they were finished with response and the search display was remained (i.e., in a case where the friend has not yet made response). Therefore, we would present search display for 2.5 seconds. This makes participants have room for concerning the partner’s target after they responded. The third modification is to exclude the data of the participants who do not show the contextual cueing effect in the last epoch of the learning phase when we test the transfer phase. Since our question is whether the location of the partner’s target is intensely encoded in memory during contextual learning, we should remove the participants who do not learn context in the learning phase. We focus on the last epoch of the learning phase for participants selection for two reasons. First, in our prior study, individual data showed that the difference between the reaction time for the repeated context and the non-repeated context was little fluctuated across the epochs. Second, in the partner’s-target group, the last epoch was more predictive for the contextual cueing effect of the transfer phase than the average of the entire learning phase or the average from the second to the last epochs. Some of the participants initially exhibited shorter reaction time for the control condition (i.e., the opposite direction to the contextual cueing), gradually decreased that tendency, and finally displayed the contextual cueing effect at the last epoch. Therefore, the last epoch would reflect the extent of participants’ contextual learning in the learning phase more clearly. In addition to these modifications, we also put a transparent partition between a pair since the current study is conducted after the outbreak of the COVID-19.

Modeling instance-level context and object-object relationships is extremely challenging. It requires reasoning about bounding boxes of different classes, locations \etc. Above all, instance-level spatial reasoning inherently requires modeling conditional distributions on previous detections. Unfortunately, our current object detection systems do not have any {\bf memory} to remember what to condition on! The state-of-the-art object detectors still detect all object in parallel followed by non-maximal suppression (NMS). While memory has been used for tasks such as captioning, they mostly use image-level memory cells without capturing the spatial layout. On the other hand, modeling object-object relationships requires {\bf spatial} reasoning -- not only do we need a memory to store the spatial layout, but also a effective reasoning module to extract spatial patterns. This paper presents a conceptually simple yet powerful solution -- Spatial Memory Network (SMN), to model the instance-level context efficiently and effectively. Our spatial memory essentially assembles object instances back into a pseudo "image" representation that is easy to be fed into another ConvNet for object-object context reasoning. This leads to a new sequential reasoning architecture where image and memory are processed in parallel to obtain detections which update the memory again. We show our SMN direction is promising as it provides 2.2\% improvement over baseline Faster RCNN on the COCO dataset so far.

The focus of this paper is on image segmentation processes, collectively referred to as a 'low-level' vision system. The programs which will be discussed here transform a large spatial array of pixels (picture elements) into a more compact representation through the exploitation of visual features, e.g., intensity, color, texture, etc. The goal is to detect a relative feature invariance across an area of the image and then to label all the pixels in any such area as belonging to the same region. Regions can be detected through global analyses (e.g., histogram clustering) which find interesting areas by ignoring the local textural configurations of the data, in conjunction with local anlayses (e.g., relaxation) which act as a fine-tuning mechanisms both to resolve global ambiguities and to accurately delimit region boundaries. (Author)

Sleep is essential for the consolidation of memories. Studies in animals and humans provide evidence that memories are reactivated during sleep and that this reactivation is essential for establishing long-term memories (Diekelmann and Born, 2010; Wilson and McNaughton, 1994). It has been shown that the reactivation of material which were encoded prior to sleep can be can be experimentally triggered, using a technique called „targeted memory reactivation“ (TMR; Oudiette and Paller, 2013): During encoding, items are associated with a sound. The sound is presented again during sleep, acting as a memory cue. Recall for items that are reactivated by TMR is improved compared to not-reactivated items (Rudoy et al., 2009; Schreiner and Rasch, 2014). The reactivation of items during sleep can be tracked in the participants’ EEG (Schreiner et al., 2018). Studies investigating the neural correlates of memory reactivation during sleep focused so far on the reactivation of non-spatial material (e.g., words). Whether real-world spatial context and its neuronal signatures can be reactivated and tracked during sleep remains unknown. In the present study, we will set out to investigate the reactivation of spatial context during sleep in humans. To this end, we will use TMR to reactivate real-world head directions. Head directions and associated sounds will serve as contextual memory cues in a memory paradigm prior to sleep. New sounds which were not part of the learning procedure will serve as control. We will record EEG and EOG while auditory TMR is applied during non-rapid eye movement sleep and test the participants’ memory performance before and after sleep.

Sleep is essential for the consolidation of memories. Studies in animals and humans provide evidence that memories are reactivated during sleep and that this reactivation is essential for establishing long-term memories (Diekelmann and Born, 2010; Wilson and McNaughton, 1994). It has been shown that the reactivation of material which were encoded prior to sleep can be can be experimentally triggered, using a technique called „targeted memory reactivation“ (TMR; Oudiette and Paller, 2013): During encoding, items are associated with a sound. The sound is presented again during sleep, acting as a memory cue. Recall for items that are reactivated by TMR is improved compared to not-reactivated items (Rudoy et al., 2009; Schreiner and Rasch, 2014). The reactivation of items during sleep can be tracked in the participants’ EEG (Schreiner et al., 2018). Studies investigating the neural correlates of memory reactivation during sleep focused so far on the reactivation of non-spatial material (e.g., words). Whether real-world spatial context and its neuronal signatures can be reactivated and tracked during sleep remains unknown. In the present study, we will set out to investigate the reactivation of spatial context during sleep in humans. To this end, we will use TMR to reactivate real-world head directions. Head directions and associated sounds will serve as contextual memory cues in a memory paradigm prior to sleep. New sounds which were not part of the learning procedure will serve as control. We will record EEG and EOG while auditory TMR is applied during non-rapid eye movement sleep and test the participants’ memory performance before and after sleep.

Sleep is essential for the consolidation of memories. Studies in animals and humans provide evidence that memories are reactivated during sleep and that this reactivation is essential for establishing long-term memories (Diekelmann and Born, 2010; Wilson and McNaughton, 1994). It has been shown that the reactivation of material which were encoded prior to sleep can be can be experimentally triggered, using a technique called „targeted memory reactivation“ (TMR; Oudiette and Paller, 2013): During encoding, items are associated with a sound. The sound is presented again during sleep, acting as a memory cue. Recall for items that are reactivated by TMR is improved compared to not-reactivated items (Rudoy et al., 2009; Schreiner and Rasch, 2014). The reactivation of items during sleep can be tracked in the participants’ EEG (Schreiner et al., 2018). Studies investigating the neural correlates of memory reactivation during sleep focused so far on the reactivation of non-spatial material (e.g., words). Whether real-world spatial context and its neuronal signatures can be reactivated and tracked during sleep remains unknown. In the present study, we will set out to investigate the reactivation of spatial context during sleep in humans. To this end, we will use TMR to reactivate real-world head directions. Head directions and associated sounds will serve as contextual memory cues in a memory paradigm prior to sleep. New sounds which were not part of the learning procedure will serve as control. We will record EEG and EOG while auditory TMR is applied during non-rapid eye movement sleep and test the participants’ memory performance before and after sleep.

Sleep is essential for the consolidation of memories. Studies in animals and humans provide evidence that memories are reactivated during sleep and that this reactivation is essential for establishing long-term memories (Diekelmann and Born, 2010; Wilson and McNaughton, 1994). It has been shown that the reactivation of material which were encoded prior to sleep can be can be experimentally triggered, using a technique called „targeted memory reactivation“ (TMR; Oudiette and Paller, 2013): During encoding, items are associated with a sound. The sound is presented again during sleep, acting as a memory cue. Recall for items that are reactivated by TMR is improved compared to not-reactivated items (Rudoy et al., 2009; Schreiner and Rasch, 2014). The reactivation of items during sleep can be tracked in the participants’ EEG (Schreiner et al., 2018). Studies investigating the neural correlates of memory reactivation during sleep focused so far on the reactivation of non-spatial material (e.g., words). Whether real-world spatial context and its neuronal signatures can be reactivated and tracked during sleep remains unknown. In the present study, we will set out to investigate the reactivation of spatial context during sleep in humans. To this end, we will use TMR to reactivate real-world head directions. Head directions and associated sounds will serve as contextual memory cues in a memory paradigm prior to sleep. New sounds which were not part of the learning procedure will serve as control. We will record EEG and EOG while auditory TMR is applied during non-rapid eye movement sleep and test the participants’ memory performance before and after sleep.

This registration has been withdrawn

This research explores how people regulate their physical distance from others or objects, guided by what has been called affective fields (Blaison, 2022). According to this framework, individuals mentally construct subjective maps of space based on the affective properties (pleasant or unpleasant) of their environment, which in turn influence approach or avoidance behaviors. Despite its theoretical appeal, the idea that affective fields constrain behavior remains empirically untested. This project aims to address that gap by examining how both the perceived Evaluation (pleasantness) and the perceived potency (power) of social stimuli shape the affective field and thus behavior.

This project aims to examine the underlying mechanisms of the CSPC effect.

This project aims to examine the underlying mechanisms of the CSPC effect.

This project aims to examine the underlying mechanisms of the CSPC effect.

This article is from Frontiers in Human Neuroscience , volume 8 . Abstract The perceptual localization of an object is often more prone to illusions than an immediate visuomotor action towards that object. The induced Roelofs effect (IRE) probes the illusory influence of task-irrelevant visual contextual stimuli on the processing of task-relevant visuospatial instructions during movement preparation. In the IRE, the position of a task-irrelevant visual object induces a shift in the localization of a visual target when subjects indicate the position of the target by verbal response, key-presses or delayed pointing to the target (“perception” tasks), but not when immediately pointing or reaching towards it without instructed delay (“action” tasks). This discrepancy was taken as evidence for the dual-visual-stream or perception-action hypothesis, but was later explained by a phasic distortion of the egocentric spatial reference frame which is centered on subjective straight-ahead (SSA) and used for reach planning. Both explanations critically depend on delayed movements to explain the IRE for action tasks. Here we ask: first, if the IRE can be observed for short-latency reaches; second, if the IRE in fact depends on a distorted egocentric frame of reference. Human subjects were tested in new versions of the IRE task in which the reach goal had to be localized with respect to another object, i.e., in an allocentric reference frame. First, we found an IRE even for immediate reaches in our allocentric task, but not for an otherwise similar egocentric control task. Second, the IRE depended on the position of the task-irrelevant frame relative to the reference object, not relative to SSA. We conclude that the IRE for reaching does not mandatorily depend on prolonged response delays, nor does it depend on motor planning in an egocentric reference frame. Instead, allocentric encoding of a movement goal is sufficient to make immediate reaches susceptible to IRE, underlining the context dependence of visuomotor illusions.

This paper adresses the statistical behaviour of spatial smoothing subspace DoA estimation schemes using a sensor array in the case where the number of observations $N$ is significantly smaller than the number of sensors $M$, and that the smoothing parameter $L$ is such that $M$ and $NL$ are of the same order of magnitude. This context is modelled by an asymptotic regime in which $NL$ and $M$ both converge towards $\infty$ at the same rate. As in recent works devoted to the study of (unsmoothed) subspace methods in the case where $M$ and $N$ are of the same order of magnitude, it is shown that it is still possible to derive improved DoA estimators termed as Generalized-MUSIC with spatial smoothing (G-MUSIC SS). The key ingredient of this work is a technical result showing that the largest singular values and corresponding singular vectors of low rank deterministic perturbation of certain Gaussian block-Hankel large random matrices behave as if the entries of the latter random matrices were independent identically distributed. This allows to conclude that when the number of sources and their DoA do not scale with $M,N,L,$ a situation modelling widely spaced DoA scenarios, then both traditional and Generalized spatial smoothing subspace methods provide consistent DoA estimators whose convergence speed is faster than $\frac{1}{M}$. The case of DoA that are spaced of the order of a beamwidth, which models closely spaced sources, is also considered. It is shown that the convergence speed of G-MUSIC SS estimates is unchanged, but that it is no longer the case for MUSIC SS ones.

In this paper, evidences that visuo-spatial perception in the peri-personal space is not an abstract, disembodied phenomenon but is rather shaped by action constraints are reviewed. Locating a visual target with the intention of reaching it requires that the relevant spatial information is considered in relation with the body-part that will be used to perform the task. This entails the selection of body-scaled visual information in regard to an action-dependent system of reference. In this regard, experimental data are presented which suggest that (1) what is visually perceived as reachable depends on anthropometrical and motor factors. (2) The location of what is visually reachable is defined according to body limbs, which serve as system of reference in the specification of the spatial dimensions that characterise the reachable object. (3) The system of reference is specified from a combination of visual and somatic information, what is accounted for by the notion of "allelocentric" system of reference. (4) The specification of the independent spatial dimensions determining the location of a visual object, i.e. distance and direction, is based on visual signals of different nature. (Contains 5 figures and 3 footnotes.)

Dimensionality reduction is a crucial preprocessing for hyperspectral data analysis - finding an appropriate subspace is often required for subsequent image classification. In recent work, we proposed supervised angular information based dimensionality reduction methods to find effective subspaces. Since unlabeled data are often more readily available compared to labeled data, we propose an unsupervised projection that finds a lower dimensional subspace where local angular information is preserved. To exploit spatial information from the hyperspectral images, we further extend our unsupervised projection to incorporate spatial contextual information around each pixel in the image. Additionally, we also propose a sparse representation based classifier which is optimized to exploit spatial information during classification - we hence assert that our proposed projection is particularly suitable for classifiers where local similarity and spatial context are both important. Experimental results with two real-world hyperspectral datasets demonstrate that our proposed methods provide a robust classification performance.

The aim of this study was to examine whether there is a relationship between the spatial reasoning skills and mathematical thinking profiles of elementary school students. The quantitative method of descriptive survey model was used in the study. The sample of the study comprised 103 fourth grade elementary school students in Turkey. The Mathematical Process Test and Spatial Reasoning Test, which are valid and reliable, were used as data collection tools. According to the answers given by the students to the Mathematical Process test, it was decided based on the upper and lower limits of each group determined beforehand that the students had a thinking profile. Scores were also collected from the Spatial Reasoning Test. MANOVA test was performed to examine whether the spatial reasoning skills differed from the mathematical thinking profiles of the students. The results revealed that students with a visual thinking profile were more successful in both the Mathematical Process Test and the Spatial Reasoning Test.

This article is from Frontiers in Psychology , volume 5 . Abstract In the present study, a time discrimination task was used to investigate the effect of different contexts for intervals varying from 400 to 1600 ms. A potential time-space interaction was controlled, and participants used both manual responses (Experiments 1 and 2) and vocal responses (Experiment 3). Three ranges of durations were employed (short, middle and long), and within each range condition, three standard values were used (400, 700, and 1000 ms; 700, 1000, and 1300 ms; and 1000, 1300, and 1600 ms). Within each range, standard intervals were randomized (Experiments 1 and 3) or remained constant (Experiment 2) within a block of trials. Our results suggest that context influences time discrimination performances only when the temporal range under investigation is below 1300 ms and the temporal intervals varied within blocks. In the case of temporal intervals longer than 1300 ms, participants presented a tendency to respond “long” independently of the procedure used. Moreover, our results suggested that performances in a discrimination task are mainly influenced by the fact of varying standard durations within blocks, and not much by the time-space compatibility.

This article is from Frontiers in Psychology , volume 5 . Abstract In the present study, a time discrimination task was used to investigate the effect of different contexts for intervals varying from 400 to 1600 ms. A potential time-space interaction was controlled, and participants used both manual responses (Experiments 1 and 2) and vocal responses (Experiment 3). Three ranges of durations were employed (short, middle and long), and within each range condition, three standard values were used (400, 700, and 1000 ms; 700, 1000, and 1300 ms; and 1000, 1300, and 1600 ms). Within each range, standard intervals were randomized (Experiments 1 and 3) or remained constant (Experiment 2) within a block of trials. Our results suggest that context influences time discrimination performances only when the temporal range under investigation is below 1300 ms and the temporal intervals varied within blocks. In the case of temporal intervals longer than 1300 ms, participants presented a tendency to respond “long” independently of the procedure used. Moreover, our results suggested that performances in a discrimination task are mainly influenced by the fact of varying standard durations within blocks, and not much by the time-space compatibility.

The purpose of this study was to investigate kindergartners' geometric (shape, area and symmetry) and spatial (spatial orientation and spatial visualization) thinking skills, in the context of gender and age. Whether kindergartners' geometric and spatial thinking skills vary by their age or gender was questioned. A total of 73 kindergartners (40 boys and 33 girls) aged between 4-5 ([image omitted] = 4,6) participated this study. Survey Design was used for this study. Participants were selected according to Convenience Sampling method. Accessibility of educational institutions and willingness of teachers, were decisive. "Geometric and Spatial Thinking Skills Test" (GEOST-ST) was used to collect the data. MANOVA (Multivariate ANOVA) was performed for data analysis. According to the results of this study, difference between children's mean scores of relevant geometric and spatial thinking skills, aren't statistically significant for gender and age.

An experimental investigation on the use of spatial demonstratives, introducing a new interactive experimental paradigm.

Compound decision theory is employed to develop a general statistical model for classifying image data using spatial context. The classification algorithm developed from this model exploits the tendency of certain ground-cover classes to occur more frequently in some spatial contexts than in others. A key input to this contextural classifier is a quantitative characterization of this tendency: the context function. Several methods for estimating the context function are explored, and two complementary methods are recommended. The contextural classifier is shown to produce substantial improvements in classification accuracy compared to the accuracy produced by a non-contextural uniform-priors maximum likelihood classifier when these methods of estimating the context function are used. An approximate algorithm, which cuts computational requirements by over one-half, is presented. The search for an optimal implementation is furthered by an exploration of the relative merits of using spectral classes or information classes for classification and/or context function estimation.

An experimental investigation on the use of spatial demonstratives, introducing a new interactive experimental paradigm.

Technology development produces terabytes of data generated by hu- man activity in space and time. This enormous amount of data often called big data becomes crucial for delivering new insights to decision makers. It contains behavioral information on different types of human activity influenced by many external factors such as geographic infor- mation and weather forecast. Early recognition and prediction of those human behaviors are of great importance in many societal applications like health-care, risk management and urban planning, etc. In this pa- per, we investigate relevant geographical areas based on their categories of human activities (i.e., working and shopping) which identified from ge- ographic information (i.e., Openstreetmap). We use spectral clustering followed by k-means clustering algorithm based on TF/IDF cosine simi- larity metric. We evaluate the quality of those observed clusters with the use of silhouette coefficients which are estimated based on the similari- ties of the mobile communication activity temporal patterns. The area clusters are further used to explain typical or exceptional communication activities. We demonstrate the study using a real dataset containing 1 million Call Detailed Records. This type of analysis and its application are important for analyzing the dependency of human behaviors from the external factors and hidden relationships and unknown correlations and other useful information that can support decision-making.

Technology development produces terabytes of data generated by hu- man activity in space and time. This enormous amount of data often called big data becomes crucial for delivering new insights to decision makers. It contains behavioral information on different types of human activity influenced by many external factors such as geographic infor- mation and weather forecast. Early recognition and prediction of those human behaviors are of great importance in many societal applications like health-care, risk management and urban planning, etc. In this pa- per, we investigate relevant geographical areas based on their categories of human activities (i.e., working and shopping) which identified from ge- ographic information (i.e., Openstreetmap). We use spectral clustering followed by k-means clustering algorithm based on TF/IDF cosine simi- larity metric. We evaluate the quality of those observed clusters with the use of silhouette coefficients which are estimated based on the similari- ties of the mobile communication activity temporal patterns. The area clusters are further used to explain typical or exceptional communication activities. We demonstrate the study using a real dataset containing 1 million Call Detailed Records. This type of analysis and its application are important for analyzing the dependency of human behaviors from the external factors and hidden relationships and unknown correlations and other useful information that can support decision-making.

TER M2 University of Paris

We explore the power of spatial context as a self-supervisory signal for learning visual representations. In particular, we propose spatial context networks that learn to predict a representation of one image patch from another image patch, within the same image, conditioned on their real-valued relative spatial offset. Unlike auto-encoders, that aim to encode and reconstruct original image patches, our network aims to encode and reconstruct intermediate representations of the spatially offset patches. As such, the network learns a spatially conditioned contextual representation. By testing performance with various patch selection mechanisms we show that focusing on object-centric patches is important, and that using object proposal as a patch selection mechanism leads to the highest improvement in performance. Further, unlike auto-encoders, context encoders [21], or other forms of unsupervised feature learning, we illustrate that contextual supervision (with pre-trained model initialization) can improve on existing pre-trained model performance. We build our spatial context networks on top of standard VGG_19 and CNN_M architectures and, among other things, show that we can achieve improvements (with no additional explicit supervision) over the original ImageNet pre-trained VGG_19 and CNN_M models in object categorization and detection on VOC2007.

We explore the power of spatial context as a self-supervisory signal for learning visual representations. In particular, we propose spatial context networks that learn to predict a representation of one image patch from another image patch, within the same image, conditioned on their real-valued relative spatial offset. Unlike auto-encoders, that aim to encode and reconstruct original image patches, our network aims to encode and reconstruct intermediate representations of the spatially offset patches. As such, the network learns a spatially conditioned contextual representation. By testing performance with various patch selection mechanisms we show that focusing on object-centric patches is important, and that using object proposal as a patch selection mechanism leads to the highest improvement in performance. Further, unlike auto-encoders, context encoders [21], or other forms of unsupervised feature learning, we illustrate that contextual supervision (with pre-trained model initialization) can improve on existing pre-trained model performance. We build our spatial context networks on top of standard VGG_19 and CNN_M architectures and, among other things, show that we can achieve improvements (with no additional explicit supervision) over the original ImageNet pre-trained VGG_19 and CNN_M models in object categorization and detection on VOC2007.

We will conduct an additional experiment for our previous experiment registered in OSF (https://osf.io/bkwgq). We employed the contextual cueing paradigm. In this paradigm, participants repeat to search for a target in the same position within the same layout of distractors while they also search for a target within a random layout of distractors. The reaction time for the target decreases when the participants search in the repeated layout than in the random layout. It is considered based on associative memory between the target position and the distractor layout, which guides participants’ attention to the target (e.g., Chun & Jiang, 1998; Brady & Chun, 2007). Moreover, previous studies show that associative memory can also be formed between a salient distractor and the distractor layout. In these studies, target and a salient distractor were shown to participants and they were instructed that the distractor was going to be their target in the latter part of the experiment. Then, they searched for the target within the same layout. Followingly, when the distractor becomes target, the reaction time was shorter in the repeated layouts than in the random layouts (Conci et al., 2011; Conci & Müller, 2012). We predicted that when pairs of participants search for different targets in parallel, a partner’s target might be salient and associative memory may be formed between the partner’s target and the distractor layout. To test it, we asked pairs of participants to search for different targets in parallel at first and then to search for what their partner had searched for (i.e., a partner’s target) or what nobody had searched for (i.e., a simple distractor). We examined whether reaction time for a partner’s target but not for nobody’s target became shorter in the repeated layout than the random layout. Our previous experiment consisted of two phases: the learning phase and the transfer phase. At first, the learning phase was conducted, where pairs of stranger participants were allocated to different targets from three categories (i.e., bird, shoe, and tricycle). They search for their targets within the repeated layouts (i.e., the repeated trials) and the random layouts (i.e., the control trials). Subsequently, in the transfer phase, they were re-allocated to either what their partner had searched for in the learning phase (i.e., the partner-target group) or what nobody had searched for (i.e., the nobody-target group). They searched for their re-allocated targets with the repeated layouts in the repeated trials, which were the same as in the learning phase, and the random layouts in the control trials. The results of the transfer phase showed that the reaction time was not significantly different between the repeated and control trials in the first epoch but significantly different in the second epoch. This effect, however, was not significantly different between the partner’s target group and the no-one’s-target group. For our previous experiment, there was a concern that the power for the statistical test may have been low. We collected a sample of 42 participants for each group and excluded some participants in accordance with a pre-registered criterion (i.e., removing those who did not exhibit reaction time difference between the repeated and control trials in the last epoch of the learning phase), and it left a sample of 30 participants for each group. We set this criterion because the previous studies (Conci et al., 2011; Conci & Müller, 2012) set a similar criterion. However, this reduced the data for the analyses. Moreover, we determined our sample size for analysis (i.e., 30 for each group) based on the effect size that we calculated from another experiment of our study with 18 participants for each group (https://osf.io/6eg5y). However, this rationale of being based on an effect size of a small sample may not be reliable (see Brysbaert, 2019). To solve this concern, we conduct an additional experiment with the following modifications. First, we increase the sample size before exclusion up to 56 for each group (see below for the rationale). Second, to expect a larger effect size, we also increase the learning phase. Specifically, while we did 25 blocks of the learning phase in our previous experiment, we increase up to 40 blocks. With this modification, participants search for the target in the same position within the same layout for 40 times rather than 25 times, which may lead to enlarging the effect size of the difference between the repeated and control trials in the partner-target group at the first epoch of the transfer phase. For the last, while we conduct analyses with excluding those who do not exhibit the contextual cueing effect for our main analyses, we also conduct exploratory analyses with including all the participants to examine with a larger sample.

Visual information is a vital sensory input for spatial wayfinding in real-world and virtual environments. Naturally, other sensory inputs such as, auditory and somatosensory, could be leveraged in the absence of sight. In recent years, many have explored and demonstrated the viability of 3D or spatial audio sonification of non-verbal audio cues for greater wayfinding efficacy as compared to non-directional verbal instructions and tactile feedback systems. Such non-verbal audio cues have potential to serve as effective anti-veering guides at complex signalled pedestrian crossings. However, the design and playback parameters of these wayfinding audio cues still remain an open question especially in the presence of traffic noise.

An experimental investigation on the use of spatial demonstratives, introducing a new interactive experimental paradigm.

An experimental investigation on the use of spatial demonstratives, introducing a new interactive experimental paradigm.

Past research has shown that consistent contexts present at encoding and retrieval facilitate recall of encoded information. However, the vast majority of past literature on context-dependent memory focused on learnt word lists and spatial memory has received sparse attention. Therefore, this study aims to examine if virtual reality (VR) can facilitate recall of previously seen objects and their spatial location by providing a replica of the encoding context. Memory of objects and their location will be assessed across three different retrieval contexts: a physical environment that is the same as the encoding context (same room condition), a VR replica of the encoding context (VR room condition), and a novel real-world environment (different room condition). Given VR’s ability to reconstruct scenes that are highly similar to real-world settings, virtual environments modelled after the encoding context are likely to offer sufficient contextual cues for memory retrieval. As such, it is hypothesized that memory performance will be similar across the same room and VR room conditions, and the weakest performance is expected to be observed in the different room condition.

This article is from Neural Development , volume 7 . Abstract Background: In holometabolous insects such as Drosophila melanogaster, neuroblasts produce an initial population of diverse neurons during embryogenesis and a much larger set of adult-specific neurons during larval life. In the ventral CNS, many of these secondary neuronal lineages differ significantly from one body segment to another, suggesting a role for anteroposterior patterning genes. Results: Here we systematically characterize the expression pattern and function of the Hox gene Ultrabithorax (Ubx) in all 25 postembryonic lineages. We find that Ubx is expressed in a segment-, lineage-, and hemilineage-specific manner in the thoracic and anterior abdominal segments. When Ubx is removed from neuroblasts via mitotic recombination, neurons in these segments exhibit the morphologies and survival patterns of their anterior thoracic counterparts. Conversely, when Ubx is ectopically expressed in anterior thoracic segments, neurons exhibit complementary posterior transformation phenotypes. Conclusion: Our findings demonstrate that Ubx plays a critical role in conferring segment-appropriate morphology and survival on individual neurons in the adult-specific ventral CNS. Moreover, while always conferring spatial identity in some sense, Ubx has been co-opted during evolution for distinct and even opposite functions in different neuronal hemilineages.

This article is from Frontiers in Human Neuroscience , volume 8 . Abstract Spatial navigation requires memory representations of landmarks and other navigation cues. The retrosplenial cortex (RSC) is anatomically positioned between limbic areas important for memory formation, such as the hippocampus (HPC) and the anterior thalamus, and cortical regions along the dorsal stream known to contribute importantly to long-term spatial representation, such as the posterior parietal cortex. Damage to the RSC severely impairs allocentric representations of the environment, including the ability to derive navigational information from landmarks. The specific deficits seen in tests of human and rodent navigation suggest that the RSC supports allocentric representation by processing the stable features of the environment and the spatial relationships among them. In addition to spatial cognition, the RSC plays a key role in contextual and episodic memory. The RSC also contributes importantly to the acquisition and consolidation of long-term spatial and contextual memory through its interactions with the HPC. Within this framework, the RSC plays a dual role as part of the feedforward network providing sensory and mnemonic input to the HPC and as a target of the hippocampal-dependent systems consolidation of long-term memory.

For many teachers, an appointment to a rural school is their first experience of living and working in a context where they are highly visible and are likely to be known of and known about by far more people than they know of and know about. Space for "making errors" and recovering from them without impairment to becoming an effective teacher, is very limited compared to teachers and other professionals who work in cities and can become largely anonymous once they leave their working contexts. The concept of a mental map is derived from my experience as a teacher in a rural town and Soja's (1996) challenge to think differently about space and spatiality. It focuses on three domain--personal, professional and public--and is presented as a way of supporting teachers to navigate and negotiate rural places which, contrary to some popular views, are complex and challenging.

This article is from Frontiers in Psychology , volume 5 . Abstract Three decades of research suggests that cognitive simulation of motion is involved in the comprehension of object location, bodily configuration, and linguistic meaning. For example, the remembered location of an object associated with actual or implied motion is typically displaced in the direction of motion. In this paper, two experiments explore context effects in spatial displacement. They provide a novel approach to estimating the remembered location of an implied motion image by employing a cursor-positioning task. Both experiments examine how the remembered spatial location of a person is influenced by subtle differences in implied motion, specifically, by shifting the orientation of the person’s body to face upward or downward, and by pairing the image with motion language that differed on intentionality, fell versus jumped. The results of Experiment 1, a survey-based experiment, suggest that language and body orientation influenced vertical spatial displacement. Results of Experiment 2, a task that used Adobe Flash and Amazon Mechanical Turk, showed consistent effects of body orientation on vertical spatial displacement but no effect of language. Our findings are in line with previous work on spatial displacement that uses a cursor-positioning task with implied motion stimuli. We discuss how different ways of simulating motion can influence spatial memory.

This article is from Frontiers in Human Neuroscience , volume 8 . Abstract Previous work has demonstrated that perceived surface reflectance (lightness) can be modeled in simple contexts in a quantitatively exact way by assuming that the visual system first extracts information about local, directed steps in log luminance, then spatially integrates these steps along paths through the image to compute lightness (Rudd and Zemach, 2004, 2005, 2007). This method of computing lightness is called edge integration. Recent evidence (Rudd, 2013) suggests that human vision employs a default strategy to integrate luminance steps only along paths from a common background region to the targets whose lightness is computed. This implies a role for gestalt grouping in edge-based lightness computation. Rudd (2010) further showed the perceptual weights applied to edges in lightness computation can be influenced by the observer's interpretation of luminance steps as resulting from either spatial variation in surface reflectance or illumination. This implies a role for top-down factors in any edge-based model of lightness (Rudd and Zemach, 2005). Here, I show how the separate influences of grouping and attention on lightness can be modeled in tandem by a cortical mechanism that first employs top-down signals to spatially select regions of interest for lightness computation. An object-based network computation, involving neurons that code for border-ownership, then automatically sets the neural gains applied to edge signals surviving the earlier spatial selection stage. Only the borders that survive both processing stages are spatially integrated to compute lightness. The model assumptions are consistent with those of the cortical lightness model presented earlier by Rudd (2010, 2013), and with neurophysiological data indicating extraction of local edge information in V1, network computations to establish figure-ground relations and border ownership in V2, and edge integration to encode lightness and darkness signals in V4.

India's Chandrayaan-1 successfully launched October 22, 2008 and went into lunar orbit a few weeks later. Commissioning of instruments began in late November and was near complete by the end of the year. Initial data for NASA's Moon Mineralogy Mapper (M3) were acquired across the Orientale Basin and the science results are discussed here. M 3 image-cube data provide mineralogy of the surface in geologic context. A major new result is that the existence and distribution of massive amounts of anorthosite as a continuous stratigraphic crustal layer is now irrefutable.