Trade-Off between Task Accuracy, Task Completion Time and Naturalness for Direct Object Manipulation in Virtual Reality

Virtual reality devices are used for several application domains, such as medicine, entertainment, marketing and training. A handheld controller is the common interaction method for direct object manipulation in virtual reality environments. Using hands would be a straightforward way to directly manipulate objects in the virtual environment if hand-tracking technology were reliable enough. In recent comparison studies, hand-based systems compared unfavorably against the handheld controllers in task completion times and accuracy. In our controlled study, we compare these two interaction techniques with a new hybrid interaction technique which combines the controller tracking with hand gestures for a rigid object manipulation task. The results demonstrate that the hybrid interaction technique is the most preferred because it is intuitive, easy to use, fast, reliable and it provides haptic feedback resembling the real-world object grab. This suggests that there is a trade-off between naturalness, task accuracy and task completion time when using these direct manipulation interaction techniques, and participants prefer to use interaction techniques that provide a balance between these three factors.

FREE STATION TASK WITH DRONE

Using drones with different purposes than only taking photos is nowadays the main direction of drone development. Drones are made for package delivery, people transport, etc. Drone equipped by GNSS RTK and prism can be used as orientation point for the free station. The idea is using drone to get coordinates of total stations inappropriate for GNSS. such as high buildings and forest. The drone can fly above the obstacle causing inappropriate, so the GNSS will compute the position coordinates correctly. Total station will measure distance and angles on prism to get free station coordinates. This article deals with the accuracy of using two points in the free station task. Accuracy of measurement and data is based on real values. Drone can be used as the target if it is not windy, the position accuracy of the target on drone is 5 cm. Wind has no effect on the vertical position accuracy of the the drone. The results show that the same principles and limitations must be observed when measuring the free station task. Horizontal angle between orientation points must be bigger than 100 gon and the zenith angle must be at least 50 gon. The distance between orientation and free station must longer than consequent measured points.

Compressing RNNs to Kilobyte Budget for IoT Devices Using Kronecker Products

Micro-controllers (MCUs) make up most of the processors in the world with widespread applicability from automobile to medical devices. The Internet of Things promises to enable these resource-constrained MCUs with machine learning algorithms to provide always-on intelligence. Many Internet of Things applications consume time-series data that are naturally suitable for recurrent neural networks (RNNs) like LSTMs and GRUs. However, RNNs can be large and difficult to deploy on these devices, as they have few kilobytes of memory. As a result, there is a need for compression techniques that can significantly compress RNNs without negatively impacting task accuracy. This article introduces a method to compress RNNs for resource-constrained environments using the Kronecker product (KP). KPs can compress RNN layers by 16× to 38× with minimal accuracy loss. By quantizing the resulting models to 8 bits, we further push the compression factor to 50×. We compare KP with other state-of-the-art compression techniques across seven benchmarks spanning five different applications and show that KP can beat the task accuracy achieved by other techniques by a large margin while simultaneously improving the inference runtime. Sometimes the KP compression mechanism can introduce an accuracy loss. We develop a hybrid KP approach to mitigate this. Our hybrid KP algorithm provides fine-grained control over the compression ratio, enabling us to regain accuracy lost during compression by adding a small number of model parameters.

Cognitive Empathy and Longitudinal Changes in Temporo-Parietal Junction Thickness in Schizophrenia

Objective: Deficits in cognitive empathy are well-documented in individuals with schizophrenia and are related to reduced community functioning. The temporoparietal junction (TPJ) is closely linked to cognitive empathy. We compared the relationship between baseline cognitive empathy and changes in TPJ thickness over 24 months between individuals with schizophrenia and healthy controls.Methods: Individuals with schizophrenia (n = 29) and healthy controls (n = 26) completed a cognitive empathy task and underwent structural neuroimaging at baseline and approximately 24 months later. Symmetrized percent change scores were calculated for right and left TPJ, as well as whole-brain volume, and compared between groups. Task accuracy was examined as a predictor of percent change in TPJ thickness and whole-brain volume in each group.Results: Individuals with schizophrenia demonstrated poorer accuracy on the cognitive empathy task (p < 0.001) and thinner TPJ cortex relative to controls at both time points (p = 0.01). In schizophrenia, greater task accuracy was uniquely related to less thinning of the TPJ over time (p = 0.02); task accuracy did not explain changes in left TPJ or whole-brain volume. Among controls, task accuracy did not explain changes in right or left TPJ, or whole-brain volume.Conclusions: Our findings suggest that greater cognitive empathy may explain sustained integrity of the right TPJ in individuals with schizophrenia, suggesting a contributory substrate for the long-term maintenance of this process in psychosis. Cognitive empathy was not related to changes in whole-brain volume, demonstrating the unique role of the TPJ in cognitive empathy.

The role of dopamine D1 receptors in MDMA-induced memory impairments

(±) 3,4-methylenedioxymethamphetamine (MDMA) is a recreationally abused psychostimulant that impairs memory performance. This effect is often attributed to a working memory impairment resulting from compromised serotonin systems. However, recent evidence from non-human animal experimental studies suggests that acute MDMA may indirectly impair memory performance through overstimulation of dopamine (DA) D1 receptors, which increases perseverative responding during memory tasks. This hypothesis was explored using DA D1 mutant (DAD1-/-) rats which possess a selective down-regulation in functional D1 receptors. Adult male Wistar DAD1-/- rats and wild type controls were trained over 25 sessions on a spatial working memory T-maze task, delayed non-matching to position (DNMTP). Once trained, the rats were administered MDMA (1.5, 2.25 and 3 mg/kg) or saline fifteen minutes prior to testing on DNMTP with all subjects experiencing all drug doses and saline three times. We predicted that controls would demonstrate decreased task accuracy following MDMA, driven by an increase in perseverative errors. In contrast, we predicted that DAD1-/- rats would be protected from MDMA-induced perseverative errors due to their reduced D1 receptor function. As predicted, during the third block of MDMA administration, control rats demonstrated decreased task accuracy following 2.25 and 3 mg/kg doses, driven by an increase in perseverative errors. In addition, DAD1-/- rats were protected from MDMA-induced task deficits. These findings challenge the assumption that MDMA’s acute effects on memory performance are predominantly due to serotonergic mechanisms and provide support for the hypothesis that acute MDMA impairs memory performance in rats via overstimulation of D1 receptors by increasing perseverative behaviour.

S66. USING UNITIZATION TO CIRCUMVENT RELATIONAL MEMORY DEFICITS IN SCHIZOPHRENIA

Background Relational memory (RM) is disproportionately affected in schizophrenia. Unitization is a cognitive strategy that compensates for RM deficits by facilitating the combination of disparate pieces of information to form a single functional unit. Unitization has been effective in circumventing RM impairment in hippocampal amnesia and older adults with RM deficits when performing a Transverse Patterning (TP) task. We developed a brief intervention using unitization to circumvent RM impairment in individuals with schizophrenia when learning arbitrary item-relations in a TP task. We subsequently developed the Relational Trip Task (RTT), which uses pairs of real-life stimuli (faces, places, objects) and a narrative frame for encoding to investigate if unitization generalizes to a more relatable real-life context. Methods Twenty-two individuals with an RM deficit and a diagnosis of schizophrenia or related disorder were pseudo-randomized to either the unitization or control condition, from which 19 completed all TP tasks and 17 completed RTT. TP performance was measured at screening. TP and RTT task performances were measured pre-post learning unitization. During the RTT-unitized task, participants created their own unitizations, with assistance (50% of the task) and on their own. The control group received unitization training following study participation. The TP-unitized control group results were included in the analysis. Results TP task performance (percentage of correct trials) did not significantly differ between control (M = 49%, SD = 13%) and unitization groups (M= 60%, SD = 18%) at screening (t(17) = -1.506, p = 0.15). A 2-way mixed analysis of variance (ANOVA) did not reveal a group-task interaction for unitization and control group accuracy in the four TP versions (F(3,51) = 2.38, p = 0.08). A main effect of task (F(3, 51) = 9.43, p > 0.001) was decomposed using Tukey HSD pairwise post-hoc analyses and showed significantly higher TP task accuracy following unitization (M = 85%, SD = 19%) compared to the TP task at screening (M = 55%, SD = 16% p > 0.001), before unitization (M = 61%, SD = 19%, p = 0.001) and when prompting self-unitization (M = 68%, SD = 28%, p = 0.04). No other significant differences in task accuracies were revealed. Group accuracies in the RTT were compared using a 2-way mixed ANOVA, and yielded a significant interaction between group and task accuracy (F(1,15) = 4.93, p = 0.042). Simple main effect analysis showed that accuracy in the RTT post unitization training (M = 90%, SD = 9%) was higher than before training (M = 77%, SD = 14%, p = 0.046), but performance between the same versions of the RTT did not significantly differ in the control group (M1 = 73%, SD = 19%; M2 = 70%, SD = 23%; p = 0.26). Discussion TP performance improved when the unitization strategy was provided, but not when the self-generation of unitization was encouraged. Improved RTT performance was limited to the unitization group, suggesting that effects were unitization-specific rather than lead by practice. Logic follows that this strategy may be generalizable to more relatable, real-life contexts. Self-generation of unitization was effective in improving task performance when assistance was provided rather than merely encouraged, suggesting that patients may benefit from guidance generating their own unitizations rather than integrating this strategy on their own. These findings should be replicated in a larger sample, and strategies to provide effective self-generation of unitization should be explored. Moreover, the extent to which the RTT can detect differential relational memory impairment in individuals with schizophrenia when compared to healthy controls warrants further investigation.

Contributions of White Matter Connectivity and BOLD Modulation to Cognitive Aging: A Lifespan Structure-Function Association Study

The ability to flexibly modulate brain activation to increasing cognitive challenge decreases with aging. This age-related decrease in dynamic range of function of regional gray matter may be, in part, due to age-related degradation of regional white matter tracts. Here, a lifespan sample of 171 healthy adults (aged 20–94) underwent magnetic resonance imaging (MRI) scanning including diffusion-weighted imaging (for tractography) and functional imaging (a digit n-back task). We utilized structural equation modeling to test the hypothesis that age-related decrements in white matter microstructure are associated with altered blood-oxygen-level-dependent (BOLD) modulation, and both in turn, are associated with scanner-task accuracy and executive function performance. Specified structural equation model evidenced good fit, demonstrating that increased age negatively affects n-back task accuracy and executive function performance in part due to both degraded white matter tract microstructure and reduced task-difficulty-related BOLD modulation. We further demonstrated that poorer white matter microstructure integrity was associated with weakened BOLD modulation, particularly in regions showing positive modulation effects, as opposed to negative modulation effects. This structure-function association study provides further evidence that structural connectivity influences functional activation, and the two mechanisms in tandem are predictive of cognitive performance, both during the task, and for cognition measured outside the scanner environment.

Contributions of white matter connectivity and BOLD modulation to cognitive aging: A lifespan structure-function association study

The ability to flexibly modulate brain activation to increasing cognitive challenge decreases with aging. This age-related decrease in dynamic range of function of regional gray matter may be, in part, due to age-related degradation of regional white matter tracts. Here, a lifespan sample of 171 healthy adults (aged 20-94) underwent MRI scanning including diffusion-weighted imaging (for tractography) and functional imaging (a digit n-back task). We utilized structural equation modeling to test the hypothesis that age-related decrements in white matter microstructure are associated with altered BOLD modulation, and both in turn, are associated with scanner-task accuracy and executive function performance. Specified structural equation model evidenced good fit, demonstrating that increased age negatively affects n-back task accuracy and executive function performance in part due to both degraded white matter tract microstructure and reduced task-difficulty related BOLD modulation. We further demonstrated that poorer white matter microstructure integrity was associated with weakened BOLD modulation, particularly in regions showing positive modulation effects, as opposed to negative modulation effects. This structure-function association study provides further evidence that structural connectivity influences functional activation, and the two mechanisms in tandem are predictive of cognitive performance, both during the task, and for cognition measured outside the scanner environment.