Spatial Search Strategies Research Articles

An improved variable neighborhood search algorithm embedded temporal and spatial synchronization for vehicle and drone cooperative routing problem with pre-reconnaissance

Drones are increasingly utilized for transportation reconnaissance due to their expansive field of view, cost-effectiveness, and agility. They can pre-reconnaissance the traveling routes of the ground vehicles carrying valuable goods to ensure the safety of vehicles and their goods. This rises a novel routing problem for the Vehicles and their Pre-Reconnaissance Drones, which is an integrated point and arc routing problem with temporal and spatial synchronization. A mixed integer linear programming model is developed to formulate the problem with complex synchronization constraints. The Variable Neighborhood Search algorithm integrated with the Temporal & Spatial synchronization-based Greedy search and simulated annealing strategy is designed to solve the model. A practical case based on real urban data from Beijing, China, and random instances with different sizes are tested and compared with the proposed algorithm. Computational results indicated that the proposed algorithm can solve the problem efficiently and outperform the simulated annealing algorithm and the greedy algorithm.

Unbiased analysis of spatial learning strategies in a modified Barnes maze using convolutional neural networks

Assessment of spatial learning abilities is central to behavioral neuroscience and a useful tool for animal model validation and drug development. However, biases introduced by the apparatus, environment, or experimentalist represent a critical challenge to the test validity. We have recently developed the Modified Barnes Maze (MBM) task, a spatial learning paradigm that overcomes inherent behavioral biases of animals in the classical Barnes maze. The specific combination of spatial strategies employed by mice is often considered representative of the level of cognitive resources used. Herein, we have developed a convolutional neural network-based classifier of exploration strategies in the MBM that can effectively provide researchers with enhanced insights into cognitive traits in mice. Following validation, we compared the learning performance of female and male C57BL/6J mice, as well as that of Ts65Dn mice, a model of Down syndrome, and 5xFAD mice, a model of Alzheimer’s disease. Male mice exhibited more effective navigation abilities than female mice, reflected in higher utilization of effective spatial search strategies. Compared to wildtype controls, Ts65Dn mice exhibited delayed usage of spatial strategies despite similar success rates in completing this spatial task. 5xFAD mice showed increased usage of non-spatial strategies such as Circling that corresponded to higher latency to reach the target and lower success rate. These data exemplify the need for deeper strategy classification tools in dissecting complex cognitive traits. In sum, we provide a machine-learning-based strategy classifier that extends our understanding of mice’s spatial learning capabilities while enabling a more accurate cognitive assessment.

A Controllable Response Power Beam Localization Method and System Implementation

Sound source localization technology has gradually become one of the main methods for fault source target localization in dangerous and difficult-to-discover applications. In order to locate the target fault sound source more intuitively, accurately and in real time in practical applications, an audio-visual positioning system is developed. A 64-channel microphone array is designed, which is evenly distributed in a circular shape, and has a video acquisition target at the same time. The system uses GCC-PHAT to estimate the relative time delay between the signal source arriving at two microphones, and then uses SRP-PHAT algorithm to obtain weighted sum beamforming. A spatial grid search strategy based on spherical coordinate spatial contraction method is proposed. When the output power is maximum, the direction corresponding to the beam is regarded as the sound source direction. Using the same sound source signal, the proposed positioning method is compared with the direct Newton iterative method and the Cartesian coordinate scanning SRP-based maximum method. The simulation results show that the Cartesian coordinate value and spherical coordinate value of the positioning algorithm in this article are closer to the real coordinates of the sound source position than the other two methods, and the positioning operation time is the shortest. In addition, in the actual corona discharge power source positioning experiment, the system can accurately locate the insulator pollution discharge point, which is consistent with the infrared detection and positioning results and has good robustness. Therefore, the system location method can provide a new choice for sound source location applications.

Research on transformer fault diagnosis based on active learning with imbalanced data of dissolved gas in oil.

The power transformer is the core equipment of the power system, a sudden failure of which will seriously endanger the safety of the power system. In recent years, artificial intelligence techniques have been applied to the dissolved gas analysis evaluation of power transformers to improve the accuracy and efficiency of power transformer fault diagnosis. However, most of the artificial intelligence techniques are data-driven algorithms whose performance decreases when the data are limited or significantly imbalanced. In this paper, we propose an active learning framework for power transformer dissolved gas analysis, in which the model can be dynamically trained based on the characteristics of the data and the training process. In addition, this paper also improves the original active learning spatial search strategy and uses the product of sample feature differences instead of the original sum of differences as a measure of sample difference. Compared to passive learning algorithms, the novel approach could significantly reduce the data labeling effort while improving prediction accuracy.

Ablation of Iron Regulatory Protein 2 produces a neurological disorder characterized by motor, somatosensory, and executive dysfunction in mice

Iron is an important cofactor for many proteins and is used to create Fe-S clusters and heme prosthetic groups that enzymes use to catalyze enzymatic reactions. Proteins involved in the import, export, and sequestration of iron are regulated by Iron Regulatory Proteins (IRPs). Recently, a patient with bi-allelic loss of function mutations in IREB2 leading to the absence of IRP2 protein was discovered. The patient failed to achieve developmental milestones and was diagnosed with dystonic cerebral palsy, epilepsy, microcytic hypochromic anemia, and frontal lobe atrophy. Several more IREB2 deficient patients subsequently identified manifested similar neurological problems. To better understand the manifestations of this novel neurological disease, we subjected an Irp2-null mouse model to extensive behavioral testing. Irp2-null mice had a significant motor deficit demonstrated by reduced performance on rotarod and hanging wire tests. Somatosensory function was also compromised in hot and cold plate assays. Their spatial search strategy was impaired in the Barnes maze and they exhibited a difficulty in flexibly adapting their response in the operant touchscreen reversal learning task. The latter is a cognitive behavior known to require an intact prefrontal cortex. These results suggest that loss of Irp2 in mice causes motor and behavioral deficits that faithfully reflect the IREB2 patient's neurodegenerative disorder.

Refinement of the Barnes and Morris water maze protocols improves characterization of spatial cognitive deficits in the lithium-pilocarpine rat model of epilepsy

Temporal lobe epilepsy (TLE) often causes cognitive impairment, especially a decline in spatial memory. Reductions in spatial memory and learning are also common in rodent models of TLE. The Morris water maze and the Barnes maze are the standard methods for evaluating spatial learning and memory in rodents. However, animals with TLE may exhibit agitation, distress, and fail to follow the paradigmatic context of these tests, making the interpretation of experimental data difficult. This study optimized the procedure of the Morris water maze and the Barnes maze to evaluate spatial learning and memory in rats with the lithium-pilocarpine TLE model (LPM rats). It was demonstrated that LPM rats required a mandatory and prolonged habituation stage for both tests. Therefore, the experimental rats performed relatively well on these tests. Nevertheless, LPM rats exhibited a slower learning process compared to the control rats. LPM rats also showed a reduction in spatial memory formation. This was more pronounced in the Barnes maze. Also, LPM rats utilized a sequential strategy for searching in the Barnes maze and were incapable of developing a more efficient spatial search strategy that is common in control animals. The Barnes maze may be a better choice for assessing search strategies, learning deficits, and spatial memory in rats with TLE when choosing between the two tests. This is because of the risk of unexpected seizure occurrence during the Morris water maze tests, and the potential risks for animal welfare.

3D smooth path planning of AUV based on improved ant colony optimization considering heading switching pressure

A smooth and secure spatial path planning algorithm that integrates the improved ant colony optimization with the corrective connected spatial search strategy is proposed, aiming at heavy heading switching pressure of autonomous underwater vehicles sailing in complex marine environment. On the one hand, to overcome the low-dimensional search domain and inaccurate spatial communication information in traditional spatial path planning, the spatial connectivity adjacency domain search strategy is designed based on grid environment model. On the other hand, to alleviate heading switching pressure due to large path steering angles and redundant path turning points, the heuristic functions and pheromone update criterion based on ant colony optimization are introduced to improve the solution quality of smooth paths. The simulation results show that the space search strategy can improve the success probability of safe path planning without reducing the scope of explorable free space. Additionally, the simulations demonstrate that the improved ant colony optimization using the spatial search strategy can guarantee the shortest path with lowest tortuous degree and fewest turning times in the same grid environment.

Energy receiver positioning using a spatial search strategy in MWPT

This paper proposes a space search method combining the Г-type layout of receiving antenna array of pilot signal for energy receiver positioning in MWPT systems. Based on the retrodirective technology, the spatial coordinate identification function (SCIF) of the energy receiver is generated. The study also investigates how to determine the spatial search range and search point interval. In addition, we propose a Criss-cross space search strategy (CSSS) to accelerate target positioning by summarizing the distribution features of the results obtained by SCIF. The simulation and physical experiment results demonstrate that the proposed method effectively overcomes the phase ambiguity problem and greatly improves the speed and accuracy of energy receiver positioning.

Absolute Winding Number Differentiates Mouse Spatial Navigation Strategies With Genetic Risk for Alzheimer's Disease.

Spatial navigation and orientation are emerging as promising markers for altered cognition in prodromal Alzheimer’s disease, and even in cognitively normal individuals at risk for Alzheimer’s disease. The different APOE gene alleles confer various degrees of risk. The APOE2 allele is considered protective, APOE3 is seen as control, while APOE4 carriage is the major known genetic risk for Alzheimer’s disease. We have used mouse models carrying the three humanized APOE alleles and tested them in a spatial memory task in the Morris water maze. We introduce a new metric, the absolute winding number, to characterize the spatial search strategy, through the shape of the swim path. We show that this metric is robust to noise, and works for small group samples. Moreover, the absolute winding number better differentiated APOE3 carriers, through their straighter swim paths relative to both APOE2 and APOE4 genotypes. Finally, this novel metric supported increased vulnerability in APOE4 females. We hypothesized differences in spatial memory and navigation strategies are linked to differences in brain networks, and showed that different genotypes have different reliance on the hippocampal and caudate putamen circuits, pointing to a role for white matter connections. Moreover, differences were most pronounced in females. This departure from a hippocampal centric to a brain network approach may open avenues for identifying regions linked to increased risk for Alzheimer’s disease, before overt disease manifestation. Further exploration of novel biomarkers based on spatial navigation strategies may enlarge the windows of opportunity for interventions. The proposed framework will be significant in dissecting vulnerable circuits associated with cognitive changes in prodromal Alzheimer’s disease.

Air Quality Index Prediction Based on an Adaptive Dynamic Particle Swarm Optimized Bidirectional Gated Recurrent Neural Network–China Region

AbstractAccurate predictions of the air quality index (AQI) is critical for pollution control and air quality warning. However, this is challenging because of the nonlinearity of data and the uncertainty between data relationships. This paper proposes a combinatorial model based on an improved adaptive dynamic particle swarm optimization (ADPSO) algorithm to optimize a bidirectional gated recurrent unit (BiGRU) neural network to predict AQI time series and capture data dependence. The ADPSO method incorporates a dynamic spatial search strategy into the standard particle swarm optimization method, allowing the parameters to be dynamically adjusted to balance global and local search capabilities, thus improving the performance and effectiveness of this optimization process. Compared to the BiGRU model, the PSO‐BiGRU model, and the radial basis neural,the results of the improved algorithm reveal that the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) of the ADPSO‐BiGRU predicted air pollution index are smaller than the errors of the other three models. The accuracy of the ADPSO‐BiGRU prediction model is higher than that of the other models, and it aids in the development of effective regional air quality management policies to reduce the negative impacts of pollution.

In aged rats, differences in spatial learning and memory influence the response to late-life Environmental Enrichment

It has clearly been demonstrated that cognitive stimulation, physical exercise, and social engagement help counteract age-related cognitive decline. However, several important issues remain to be addressed. Given the wide differences in cognitive impairment found among individuals of the same age, identifying the subjects who will benefit most from late-life interventions is one such issue. Environmental Enrichment (EE) is a particularly valuable approach to do this. In this study, aged (21-month-old) rats were assigned to a better (BL) or a worse (WL) learner group (training phase) and to a non-impaired (NI) or an impaired (I) group (probe phase) by their performance on the Morris Water Maze, using the test performances of adult (12-month-old) rats as the cut-offs. The aged rats were retested after a 12-week EE or standard housing (SH) protocol. After 12weeks, the performances of SH rats had deteriorated, whereas all rats benefited from EE, albeit in different ways. In particular, the animals assigned to the BL and the NI groups prior to EE still performed as well as the adult rats (performance preservation) whereas, critically, the animals assigned to the WL and the I groups before EE showed such improved performances that they reached the level of the adult rats (performance improvement), despite having aged further. EE seems to induce the preservation in BLs and the improvement in WLs of spatial search strategies and the preservation in NIs and the increase in Is of a focused and protract research of the escape point. Our findings suggest that late-life EE prevents spatial learning and memory decline in still cognitively preserved animals and stimulates residual functional reserve in already cognitively compromised animals. Future research should focus on individually tailored stimulation protocols to improve their effect and afford a better understanding of the underlying processes.

Pharmacological inhibition of phosphodiesterase 7 enhances consolidation processes of spatial memory

Augmentation of cAMP signaling through inhibition of phosphodiesterases (PDE) is known to enhance plasticity and memory. Inhibition of PDE4 enhances consolidation into memory, but less is known about the role of other cAMP specific PDEs. Here, we tested the effects of oral treatment with a selective inhibitor of PDE7 of nanomolar potency on spatial and contextual memory. In an object location task, doses of 0.3–3 mg/kg administered 3 h after training dose-dependently attenuated time-dependent forgetting in rats. Significant enhancement of memory occurred at a dose of 3 mg/kg with corresponding brain levels consistent with PDE7 inhibition. The same dose given prior to training augmented contextual fear conditioning. In mice, daily dosing before training enhanced spatial memory in two different incremental learning paradigms in the Barnes Maze. Drug treated mice made significantly less errors locating the escape in a probe-test 24 h after the end of training, and they exhibited hippocampal-dependent spatial search strategies more frequently than controls, which tended to show serial sampling of escape locations. Acquisition and short-term memory, in contrast, were unaffected. Our data provide evidence for a role of PDE7 in the consolidation of hippocampal-dependent memory. We suggest that targeting PDE7 for memory enhancement may provide an alternative to PDE4 inhibitors, which tend to have undesirable gastrointestinal side-effects.

Sex-Specific Effects of Chronic Creatine Supplementation on Hippocampal-Mediated Spatial Cognition in the 3xTg Mouse Model of Alzheimer's Disease.

The creatine (Cr) energy system has been implicated in Alzheimer’s disease (AD), including reductions in brain phosphoCr and Cr kinase, yet no studies have examined the neurobehavioral effects of Cr supplementation in AD, including the 3xTg mouse model. This studied investigated the effects of Cr supplementation on spatial cognition, plasticity- and disease-related protein levels, and mitochondrial function in the 3xTg hippocampus. Here, 3xTg mice were fed a control or Cr-supplemented (3% Cr (w/w)) diet for 8–9 weeks and tested in the Morris water maze. Mitochondrial oxygen consumption (Seahorse) and protein levels (Western blots) were measured in the hippocampus in subsets of mice. Overall, 3xTg females exhibited impaired memory as compared to males. In females, Cr supplementation decreased escape latency and was associated with increased spatial search strategy use. In males, Cr supplementation decreased the use of spatial search strategies. Pilot data indicated mitochondrial enhancements with Cr supplementation in both sexes. In females, Cr supplementation increased CREB phosphorylation and levels of IκB (NF-κB suppressor), CaMKII, PSD-95, and high-molecular-weight amyloid β (Aβ) species, whereas Aβ trimers were reduced. These data suggest a beneficial preventative effect of Cr supplementation in females and warrant caution against Cr supplementation in males in the AD-like brain.

The Wald Test of Common Factors in Spatial Model Specification Search Strategies

AbstractDistinguishing substantively meaningful spillover effects from correlated residuals is of great importance in cross-sectional studies. Both forms of spatial dependence not only hold different implications for the choice of an unbiased estimator but also for the validity of inferences. To guide model specification, different empirical strategies involve the estimation of an unrestricted spatial Durbin model and subsequently use the Wald test to scrutinize the nonlinear restriction of common factors implied by pure error dependence. However, the Wald test’s sensitivity to algebraically equivalent formulations of the null hypothesis receives scant attention in the context of cross-sectional analyses. This article shows analytically that the noninvariance of the Wald test to such reparameterizations stems from the application of a Taylor series expansion to approximate the restriction’s sampling distribution. While asymptotically valid, Monte Carlo simulations reveal that alternative formulations of the common factor restriction frequently produce conflicting conclusions in finite samples. An empirical example illustrates the substantive implications of this problem. Consequently, researchers should either base inferences on bootstrap critical values for the Wald statistic or use the likelihood ratio test which is invariant to such reparameterizations when deciding on the model specification that adequately reflects the spatial process generating the data.

4-Hydroxynonenal Immunoreactivity Is Increased in the Frontal Cortex of 5XFAD Transgenic Mice.

Oxidative stress was implicated in the functional impairment of the frontal cortex observed in early Alzheimer’s disease (AD). To elucidate this role in an animal AD model, we assessed cognitive function of 4-month-old five familial AD (5XFAD) transgenic (Tg) mice using a learning strategy-switching task requiring recruitment of the frontal cortex and measuring levels of 4-hydroxy-2-trans-nonenal (4-HNE), a marker of oxidative stress, in their frontal cortex. Mice were sequentially trained in cued/response and place/spatial versions of the water maze task for four days each. 5XFAD and non-Tg mice exhibited equal performance in cued/response training. However, 5XFAD mice used spatial search strategy less than non-Tg mice in the spatial/place training. Immunoblot and immunofluorescence staining showed that 4-HNE levels increased in the frontal cortex, but not in the hippocampus and striatum, of 5XFAD mice compared to those in non-Tg mice. We report early cognitive deficits related to the frontal cortex and the frontal cortex’s oxidative damage in 4-month-old 5XFAD mice. These results suggest that 4-month-old 5XFAD mice be a useful animal model for the early diagnosis and management of AD.

Pathfinder: open source software for analyzing spatial navigation search strategies.

Spatial navigation is a universal behavior that varies depending on goals, experience and available sensory stimuli. Spatial navigational tasks are routinely used to study learning, memory and goal-directed behavior, in both animals and humans. One popular paradigm for testing spatial memory is the Morris water maze, where subjects learn the location of a hidden platform that offers escape from a pool of water. Researchers typically express learning as a function of the latency to escape, though this reveals little about the underlying navigational strategies. Recently, a number of studies have begun to classify water maze search strategies in order to clarify the precise spatial and mnemonic functions of different brain regions, and to identify which aspects of spatial memory are disrupted in disease models. However, despite their usefulness, strategy analyses have not been widely adopted due to the lack of software to automate analyses. To address this need we developed Pathfinder, an open source application for analyzing spatial navigation behaviors. In a representative dataset, we show that Pathfinder effectively characterizes the development of highly-specific spatial search strategies as male and female mice learn a standard spatial water maze. Pathfinder can read data files from commercially- and freely-available software packages, is optimized for classifying search strategies in water maze paradigms, and can also be used to analyze 2D navigation by other species, and in other tasks, as long as timestamped xy coordinates are available. Pathfinder is simple to use, can automatically determine pool and platform geometry, generates heat maps, analyzes navigation with respect to multiple goal locations, and can be updated to accommodate future developments in spatial behavioral analyses. Given these features, Pathfinder may be a useful tool for studying how navigational strategies are regulated by the environment, depend on specific neural circuits, and are altered by pathology.

Pathfinder: open source software for analyzing spatial navigation search strategies

Spatial navigation is a universal behavior that varies depending on goals, experience and available sensory stimuli. Spatial navigational tasks are routinely used to study learning, memory and goal-directed behavior, in both animals and humans. One popular paradigm for testing spatial memory is the Morris water maze, where subjects learn the location of a hidden platform that offers escape from a pool of water. Researchers typically express learning as a function of the latency to escape, though this reveals little about the underlying navigational strategies. Recently, a number of studies have begun to classify water maze search strategies in order to clarify the precise spatial and mnemonic functions of different brain regions, and to identify which aspects of spatial memory are disrupted in disease models. However, despite their usefulness, strategy analyses have not been widely adopted due to the lack of software to automate analyses. To address this need we developed Pathfinder, an open source application for analyzing spatial navigation behaviors. In a representative dataset, we show that Pathfinder effectively characterizes the development of highly-specific spatial search strategies as male and female mice learn a standard spatial water maze. Pathfinder can read data files from commercially- and freely-available software packages, is optimized for classifying search strategies in water maze paradigms, and can also be used to analyze 2D navigation by other species, and in other tasks, as long as timestamped xy coordinates are available. Pathfinder is simple to use, can automatically determine pool and platform geometry, generates heat maps, analyzes navigation with respect to multiple goal locations, and can be updated to accommodate future developments in spatial behavioral analyses. Given these features, Pathfinder may be a useful tool for studying how navigational strategies are regulated by the environment, depend on specific neural circuits, and are altered by pathology.

An indoor spatial accessible area generation approach considering distance constraints

ABSTRACTIndoor objects’ accessible area generation considering distance constraints is of important realistic significance for spatial analysis. To the best of our knowledge, few studies have been conducted on indoor accessible area generation considering distance constraints. And because of different spatial characteristics between indoor and outdoor environment, the commonly used approach in outdoor space is not suitable for indoor space. In this paper, based on the hybrid spatial data model of geometric and symbolic model, an accessible area generation approach considering distance constraints for indoor environment is proposed by improving traditional spatial buffer zone generation technique. The buffer zone generation with a predefined distance around indoor objects within their located subspace is executed first; then, based on the indoor spatial connectivity, buffer generation around exit points is successively executed in its next connected subspaces until the distance decreases to zero. The merge of these generated buffer zones is the result of accessible area generation with a predefined distance constraint. During the process, two kinds of spatial search strategies, depth-first search and breadth-first search, are presented. Two sets of experiments are conducted to validate the correctness and efficiency of the proposed approach. Results show that the approach can be effectively used to solve the problem of indoor objects’ accessible area generation with distance constraints. Moreover, the potential use, as well as the limitation of the proposed approach is discussed in this paper.

Pathfinder: open source software for analyzing spatial navigation search strategies.

Spatial navigation is a universal behavior that varies depending on goals, experience and available sensory stimuli. Spatial navigational tasks are routinely used to study learning, memory and goal-directed behavior, in both animals and humans. One popular paradigm for testing spatial memory is the Morris water maze, where subjects learn the location of a hidden platform that offers escape from a pool of water. Researchers typically express learning as a function of the latency to escape, though this reveals little about the underlying navigational strategies. Recently, a number of studies have begun to classify water maze search strategies in order to clarify the precise spatial and mnemonic functions of different brain regions, and to identify which aspects of spatial memory are disrupted in disease models. However, despite their usefulness, strategy analyses have not been widely adopted due to the lack of software to automate analyses. To address this need we developed Pathfinder, an open source application for analyzing spatial navigation behaviors. In a representative dataset, we show that Pathfinder effectively characterizes the development of highly-specific spatial search strategies as male and female mice learn a standard spatial water maze. Pathfinder can read data files from commercially- and freely-available software packages, is optimized for classifying search strategies in water maze paradigms, and can also be used to analyze 2D navigation by other species, and in other tasks, as long as timestamped xy coordinates are available. Pathfinder is simple to use, can automatically determine pool and platform geometry, generates heat maps, analyzes navigation with respect to multiple goal locations, and can be updated to accommodate future developments in spatial behavioral analyses. Given these features, Pathfinder may be a useful tool for studying how navigational strategies are regulated by the environment, depend on specific neural circuits, and are altered by pathology.

Effects of valence on selecting and memorizing spatial information from road maps

Abstract. Movements in unfamiliar environments require navigational tasks, which can be supported by selecting and memorizing spatial information from maps. However, this process of information extraction from maps is initiated and surrounded by a personal, emotional context. Since emotion and cognition are interlaced aspects and the visual search for information acquisition is influenced by mood and memory (Kruijne & Meeter, 2015; Storbeck & Clore, 2005), this research aims at determining the effects of valence on selecting and memorizing spatial information from road maps (e.g. google maps). Thereby it shall be evaluated, if common cartographic practices of visual appearance, e.g. saliency or hierarchy of objects, or the represented information itself, are in accordance with a users` need or notion of space under different emotional contexts.Since subjective emotional contexts occur in a huge variety with low predictability and in various dimensions, this research uses a mental pre-activation of possible emotional contexts via audio-visual priming of positive and negative valence (Mayr, S., Buchner, A., 2007) before a memory task with road maps. The subsequent memory task aims at understanding “higher cognitive functions such as comprehension” (Borkin et al., 2016), by determining which information users acquire from road maps of unfamiliar space under different emotional contexts, and why they choose this information. The qualitative studies investigate on insights into the selection, learning, and recall of spatial information while being under different types of valence, such as either in an induced, acute, extrinsic stressful situation (negative valence) or in a more relaxed state (positive valence). Further they address on object selection strategies applied in the two group conditions, and on the participants' associations of object and location (Postma et al., 2004). Moreover, this research aims to contribute to a better understanding of how the emotional context affects object-location memory.The results suggest that valence has an impact on the selection, learning, and recall of spatial information from road maps of unknown spaces while being under different emotional contexts. Judgements on spatial strategy, object selection and visual search strategy were affected stronger by the negative than positive arousal. Negative valence (stress) promotes strategic object selection strategies, higher memory retrieval and more accurate object-location memory, as well as a faster memory implementation of visually represented content. Positive valence promotes the development of personal associations of object and location. Findings show, that common cartographic practices (e.g. saliency, represented information) are just partly in accordance with what users select and memorize under emotional contexts.