A Heart Image Segmentation Method Based on Position Attention Mechanism and Inverted Pyramid

In the realm of modern medicine, medical imaging stands as an irreplaceable pillar for accurate diagnostics. The significance of precise segmentation in medical images cannot be overstated, especially considering the variability introduced by different practitioners. With the escalating volume of medical imaging data, the demand for automated and efficient segmentation methods has become imperative. This study introduces an innovative approach to heart image segmentation, embedding a multi-scale feature and attention mechanism within an inverted pyramid framework. Recognizing the intricacies of extracting contextual information from low-resolution medical images, our method adopts an inverted pyramid architecture. Through training with multi-scale images and integrating prediction outcomes, we enhance the network's contextual understanding. Acknowledging the consistent patterns in the relative positions of organs, we introduce an attention module enriched with positional encoding information. This module empowers the network to capture essential positional cues, thereby elevating segmentation accuracy. Our research resides at the intersection of medical imaging and sensor technology, emphasizing the foundational role of sensors in medical image analysis. The integration of sensor-generated data showcases the symbiotic relationship between sensor technology and advanced machine learning techniques. Evaluation on two heart datasets substantiates the superior performance of our approach. Metrics such as the Dice coefficient, Jaccard coefficient, recall, and F-measure demonstrate the method's efficacy compared to state-of-the-art techniques. In conclusion, our proposed heart image segmentation method addresses the challenges posed by diverse medical images, offering a promising solution for efficiently processing 2D/3D sensor data in contemporary medical imaging.

The Use of Contextual Information for Anticipation of Badminton Shots in Different Expertise Levels

Purpose: The current study investigated the use of contextual information for anticipation in badminton. Method: Participants were groups of elites (n = 26), competitive (n = 15) and novice players (n = 17) whose anticipation accuracy and reaction time were assessed using an ecologically valid badminton specific video-based occlusion test. Two conditions were presented, where either only kinematic information was available (Last Strokes condition, LS), or kinematic and contextual information were both available (Full Rally condition, FR). Results: Participants reacted slower in the FR condition, while no differences in accuracy were observed between the two conditions. Furthermore, all participants were better at side predictions than length, and elites outperformed novices in both side and length predictions. Among the elite group (which was split into adult elites, adult sub-elites & young elites), adult elite athletes showed faster responses for both the LS and FR conditions compared to their other elite counterparts who were much slower in both conditions. Conclusion: These results indicate that even at the highest level, anticipation performance can discriminate between groups of expert performers. In addition, the findings of this study indicate that the role of contextual information might not be as large as hypothesized, and further research is needed to clarify the role of contextual information toward anticipation.

Deep multi-modal intermediate fusion of clinical record and time series data in mortality prediction

In intensive care units (ICUs), mortality prediction is performed by combining information from these two sources of ICU patients by monitoring patient health. Respectively, time series data generated from each patient admission to the ICU and clinical records consisting of physician diagnostic summaries. However, existing mortality prediction studies mainly cascade the multimodal features of time series data and clinical records for prediction, ignoring thecross-modal correlation between the underlying features in different modal data. To address theseissues, we propose a multimodal fusion model for mortality prediction that jointly models patients' time-series data as well as clinical records. We apply a fine-tuned Bert model (Bio-Bert) to the patient's clinical record to generate a holistic embedding of the text part, which is then combined with the output of an LSTM model encoding the patient's time-series data to extract valid features. The global contextual information of each modal data is extracted using the improved fusion module to capture the correlation between different modal data. Furthermore, the improved fusion module can be easily added to the fusion features of any unimodal network and utilize existing pre-trained unimodal model weights. We use a real dataset containing 18904 ICU patients to train and evaluate our model, and the research results show that the representations obtained by themodel can achieve better prediction accuracy compared to the baseline.

Skill-Based Differences in the Detection and Utilization of Opponent Action Preferences Following Increasing Exposure and Changes in Tendencies

We examined skill-based differences in the detection and utilization of contextual information over a period of increasing exposure to an opponent's action preferences in soccer. Moreover, we investigated the ability of athletes to adapt to changes in these action preferences over time. In an initial detection phase, the attacking opponent demonstrated a proclivity to either pass or dribble, with these preferences being reversed in a subsequent adaptation phase of the same length. Skilled soccer players showed superior anticipation accuracy across both phases compared with less-skilled counterparts. The skilled participants significantly enhanced their performance over both phases, despite a significant drop in performance immediately following the change in opponent action preferences. In contrast, the less-skilled group only improved over the detection phase. Gaze data revealed that the skilled participants fixated more on kinematically relevant areas, compared with the less-skilled group, and increased the time spent fixating the player "off the ball" following greater volumes of exposure. Our novel findings elaborate on how skilled performers use both action preferences and motion information to anticipate an opponent's impending actions in sport.

Contextual Support for Less Salient Homophones and Pun Humor Appreciation: Evidence From Eye Movements in Reading Chinese Homophone Puns

Punning is an important means of creating humorous effects by intentionally exploiting semantic ambiguity. Previous psycholinguistic research on puns has mainly focused on the process of meaning retrieval in homograph puns, while it is still not entirely clear how readers dynamically utilize contextual information to understand homophone puns. In the current investigation, 68 native Chinese participants were recruited to read three types of experimental sentences while their eye movements were recorded: (1) the homophone-pun sentences where the less salient homophone was visually presented, (2) the homophone-salient sentences where the salient homophone was used, and (3) the homophone-error sentences where the critical context noun in the homophone puns was replaced with an unrelated word. Humor rating results of the homophone puns and the homophone-salient sentences demonstrated that the less salient homophones rather than the salient ones elicited much larger humor responses when presented visually in the same potential pun context. In addition, the reverse fixation pattern in the homophone area and the spill-over region also suggested that meanings of the salient homophones were more recoverable even when not presented visually. Statistical analyses of the homophone puns and the homophone-error sentences showed that the semantic relatedness between the critical context noun and the less salient homophone could significantly predict the humor rating scores of Chinese readers. Taken together, less salient homophones need to receive more contextual support to balance out the advantages of salient homophones before generating a humorous pun interpretation.

Haptic Feedback to Assist Blind People in Indoor Environment Using Vibration Patterns

Feedback is one of the significant factors for the mental mapping of an environment. It is the communication of spatial information to blind people to perceive the surroundings. The assistive smartphone technologies deliver feedback for different activities using several feedback mediums, including voice, sonification and vibration. Researchers 0have proposed various solutions for conveying feedback messages to blind people using these mediums. Voice and sonification feedback are effective solutions to convey information. However, these solutions are not applicable in a noisy environment and may occupy the most important auditory sense. The privacy of a blind user can also be compromised with speech feedback. The vibration feedback could effectively be used as an alternative approach to these mediums. This paper proposes a real-time feedback system specifically designed for blind people to convey information to them based on vibration patterns. The proposed solution has been evaluated through an empirical study by collecting data from 24 blind people through a mixed-mode survey using a questionnaire. Results show the average recognition accuracy for 10 different vibration patterns are 90%, 82%, 75%, 87%, 65%, and 70%.

Influence of Augmented Probabilistic Information on Defensive Motor Behaviors of 1 vs. 1 Basketball Play

In this study we assessed the contribution of augmented probabilistic information on the motor behavior of novice defenders during 1 vs. 1 basketball play. More specifically, we aimed to investigate the influence of different probabilities of attacks to the basket (Level 1: High-probability of a single attack action; Level 2: Equal probability of two attack actions; Level 3: No-probability of an attack) on defensive reactions and their efficacy. Twenty-six novice participants volunteered and were assigned into three groups, based on their reaction time performance. Each participant performed 10 trials defending against typical basket attacks on a standard basketball court. Three experimental groups were primed regarding the probabilities of two forms of attack, either shooting at the basket or dribbling-past the defender (Group 1: 80% vs 20%; Group 2: 50% vs 50%; Group 3: No-probability of attack). Participants reacted earlier and with greater accuracy in the high-probability condition (80% vs 20%), than in the remaining conditions. We found that, in absence of kinematic information about their opponents, novice basketball players may have relied on the prior information we provided regarding an opponents' preferred actions during 1 vs. 1 basketball play. The provision of probabilistic information could be used as a training strategy to guide the defensive motor behaviors of novice basketball players when facing their counterparts in ball possession by favoring the use of anticipatory information to react earlier and successfully to the opponents' actions.

A Robust Lane Detection Model Using Vertical Spatial Features and Contextual Driving Information

The quality of detected lane lines has a great influence on the driving decisions of unmanned vehicles. However, during the process of unmanned vehicle driving, the changes in the driving scene cause much trouble for lane detection algorithms. The unclear and occluded lane lines cannot be clearly detected by most existing lane detection models in many complex driving scenes, such as crowded scene, poor light condition, etc. In view of this, we propose a robust lane detection model using vertical spatial features and contextual driving information in complex driving scenes. The more effective use of contextual information and vertical spatial features enables the proposed model more robust detect unclear and occluded lane lines by two designed blocks: feature merging block and information exchange block. The feature merging block can provide increased contextual information to pass to the subsequent network, which enables the network to learn more feature details to help detect unclear lane lines. The information exchange block is a novel block that combines the advantages of spatial convolution and dilated convolution to enhance the process of information transfer between pixels. The addition of spatial information allows the network to better detect occluded lane lines. Experimental results show that our proposed model can detect lane lines more robustly and precisely than state-of-the-art models in a variety of complex driving scenarios.

On the Influence of Action Preference on Female Players' Gaze Behavior During Defense of Volleyball Attacks

Knowledge of an opponent's action preference may affect visual anticipation of their action outcome. Specifically, if an opponent acts according to their purported preference, anticipation may be facilitated. Conversely, if an opponent does not act according to their purported preference, anticipation may be unaffected or even harmed. The underlying perceptual-cognitive mechanisms of that effect, however, remain unclear. Here we tested the hypothesis that players might change their gaze behavior once provided with preference information. To this end, 27 female volleyball players anticipated the direction of attacks in two test blocks with 40 videos each. Videos were shown on a large screen and stopped 240 ms prior to hand-ball-contact. Participants simulated defensive reaction while their gaze was recorded using a mobile eye-tracker. One female attacker directed 75% of shots diagonally (25% longline), while another female attacker distributed shots equally to both directions. After block one, half of the participants were informed that either both attackers preferred diagonal shots in 75% of occasions (group preferred) or that both attackers distributed shots equally across directions (group non-preferred). Analysis of decision behavior (i.e., proportion of diagonal decisions), but not prediction accuracy (i.e., proportion of correct predictions), revealed that those instructions led both groups decide differently according to the purported preferences from block 1 to block 2. Analysis of gaze behavior did not reveal group-specific effects across blocks or attackers with/-out action preference. Findings underline the influence of contextual information on anticipation, but they leave open whether the availability of contextual information similarly affects gaze behavior.

The Impact of Pretrained Language Models on Negation and Speculation Detection in Cross-Lingual Medical Text: Comparative Study

Background

Negation and speculation are critical elements in natural language processing (NLP)-related tasks, such as information extraction, as these phenomena change the truth value of a proposition. In the clinical narrative that is informal, these linguistic facts are used extensively with the objective of indicating hypotheses, impressions, or negative findings. Previous state-of-the-art approaches addressed negation and speculation detection tasks using rule-based methods, but in the last few years, models based on machine learning and deep learning exploiting morphological, syntactic, and semantic features represented as spare and dense vectors have emerged. However, although such methods of named entity recognition (NER) employ a broad set of features, they are limited to existing pretrained models for a specific domain or language.

Objective

As a fundamental subsystem of any information extraction pipeline, a system for cross-lingual and domain-independent negation and speculation detection was introduced with special focus on the biomedical scientific literature and clinical narrative. In this work, detection of negation and speculation was considered as a sequence-labeling task where cues and the scopes of both phenomena are recognized as a sequence of nested labels recognized in a single step.

Methods

We proposed the following two approaches for negation and speculation detection: (1) bidirectional long short-term memory (Bi-LSTM) and conditional random field using character, word, and sense embeddings to deal with the extraction of semantic, syntactic, and contextual patterns and (2) bidirectional encoder representations for transformers (BERT) with fine tuning for NER.

Results

The approach was evaluated for English and Spanish languages on biomedical and review text, particularly with the BioScope corpus, IULA corpus, and SFU Spanish Review corpus, with F-measures of 86.6%, 85.0%, and 88.1%, respectively, for NeuroNER and 86.4%, 80.8%, and 91.7%, respectively, for BERT.

Conclusions

These results show that these architectures perform considerably better than the previous rule-based and conventional machine learning–based systems. Moreover, our analysis results show that pretrained word embedding and particularly contextualized embedding for biomedical corpora help to understand complexities inherent to biomedical text.

Imaginative Enrichment Produces Higher Preference for Unusual Music Than Historical Framing: A Literature Review and Two Empirical Studies

Does accompanying information (“framing”) such as in a program note influence our preference for music? To date the findings have been mixed, although a small body of research has suggested that when framing accompanies music considered unusual (characterized by extreme complexity and extreme unfamiliarity), the music may be preferred compared to when no such framing occurs. A literature review (study 1) revealed that for 50% of experiments where valenced framing (positive versus negative suggestions of prestige) was manipulated, positive framing was accompanied by significantly higher ratings of preference and/or quality judgements. However, only one example contained music that could be considered unusual (atonal music). We therefore conducted two follow-up experiments, with each examining the influence of valenced framing as well as historical framing (accompanying historical details) for music intended to be unusual. Study 2 manipulated framing for an excerpt using atonal music, although we were unable to find evidence that positively valenced historical framing increased preference for this piece. A surprising finding in study 2 was that our active control—requiring the participant to engage imaginatively with the music—produced a significant increase in preference. Subsequently, in study 3 we examined the same three framing conditions and included both an unusual excerpt (free jazz) as well as an over-familiar, typical excerpt for comparison (being a repeatedly pre-exposed classical piano piece). Study 3 produced no significant differences in preference ratings between the two historical conditions, although a positive impact of imagination was again evident. We concluded that the impact of historical framing may be highly subjective and not of favorable consequence to the typical listener. Furthermore, while imaginative engagement appears a fruitful avenue for further preference research, it has been largely ignored.

Inland Lakes Mapping for Monitoring Water Quality Using a Detail/Smoothing-Balanced Conditional Random Field Based on Landsat-8/Levels Data

The sustainable development of water resources is always emphasized in China, and a set of perfect standards for the division of inland water environment quality have been established to monitor water quality. However, most of the 24 indicators that determine the water quality level in the standards are non-optically active parameters. The weak optical characteristics make it difficult to find significant correlations between the single parameters and the remote sensing imagery. In addition, traditional on-site testing methods have been unable to meet the increasingly extensive water-quality monitoring requirements. Based on the above questions, it’s meaningful that the supervised classification process of a detail-preserving smoothing classifier based on conditional random field (CRF) and Landsat-8 data was proposed in the two study areas around Wuhan and Huangshi in Hubei Province. The random forest classifier was selected to model the association potential of the CRF. The results (the first study area: OA = 89.50%, Kappa = 0.841; the second study area: OA = 90.35%, Kappa = 0.868) showed that the water-quality monitoring based on CRF model is feasible, and this approach can provide a reference for water-quality mapping of inland lakes. In the future, it may only require a small amount of on-site sampling to achieve the identification of the water quality levels of inland lakes across a large area of China.

Exposure to Respirable Crystalline Silica in the GB Brick Manufacturing and Stone Working Industries

The aim of this work was to benchmark respirable crystalline silica (RCS) exposures in brick manufacturing and stone working sectors in Great Britain. This will contribute to a larger programme of work, which will be used to better understand the role of health surveillance in preventing the development of further cases of silicosis and chronic obstructive pulmonary disease. This work was undertaken by means of site visits to measure RCS and respirable dust exposures and assess exposure controls. In addition, historic exposure reports from the sites were collated to allow assessment of exposure trends. The survey, which was conducted in 20 sites (10 from each sector), found that in both sectors over 20% of the measured exposures exceeded the UK RCS 8-hour time-weighted averaged workplace exposure limit (WEL) of 0.1 mg/m3. In the stone sector over 40% of the 8 h time-weighted average RCS exposures were above the RCS WEL compared to 20% in the brick manufacturing sector. In the stone sector, 61% of RCS exposures where water suppression was present exceeded the RCS WEL. This indicates that a variety of exposure controls will be required to control RCS exposures, including respiratory protective equipment (RPE). The use of RPE in situations where RCS exposure exceeded the RCS WEL was more prevalent in stone working than in the brick sector. There were differences associated with RPE and the use of other exposure controls in both sectors. The contextual information in historic consultant's exposure reports was generally limited, with exposure controls either not mentioned or not fully described. This affects the usefulness of exposure monitoring to dutyholders. This work will provide information on exposures allowing construction of lifetime exposure estimates for use in analysis of the health effects data. A second survey to the sites is planned to determine how exposures have altered.

Object and place information processing by CA1 hippocampal neurons of C57BL/6J mice

Medial and lateral entorhinal cortices convey spatial/contextual and item/object information to the hippocampus, respectively. Whether the distinct inputs are integrated as one cognitive map by hippocampal neurons to represent location and the objects therein, or whether they remain as parallel outputs, to be integrated in a downstream region, remains unclear. Principal, or complex spike bursting, neurons of hippocampus exhibit location-specific firing, and it is likely that the activity of "place cells" supports spatial memory/navigation in rodents. Consistent with cognitive map theory, the activity of CA1 hippocampal neurons is also critical for nonspatial memory, such as object recognition. However, the degree to which CA1 neuronal activity represents the associations of object-context or object-in-place memory is not well understood. Here, the contributions of mouse CA1 neuronal activity to object recognition memory and the emergence of object-place conjunctive representations were tested using in vivo recordings and functional inactivation. Independent of arena configuration, CA1 place fields were stable throughout testing and object-place representations were not identified in CA1, although the number of fields per cell increased during object sessions, and few object-related firing CA1 neurons (nonplace) were recorded. The results of the inactivation studies confirmed the significant contribution of CA1 neuronal activity to object recognition memory when a delay of 20 min, but not 5 min, was imposed between encoding and retrieval. Together, our results confirm the delay-dependent contribution of the CA1 region to object memory and suggest that object information is processed in parallel with the ongoing spatial mapping function that is a hallmark of hippocampal memory.NEW & NOTEWORTHY We developed variations of the object recognition task to examine the contribution of mouse CA1 neuronal activity to object memory and the degree to which object-context conjunctive representations are formed during object training. Our results indicate that, within the CA1 region, object information is processed in a parallel but delay-dependent manner, with ongoing spatial mapping.

The Important Role of Contextual Information in Speech Perception in Cochlear Implant Users and Its Consequences in Speech Tests

This study investigated the role of contextual information in speech intelligibility, the influence of verbal working memory on the use of contextual information, and the suitability of an ecologically valid sentence test containing contextual information, compared with a CNC (Consonant-Nucleus-Consonant) word test, in cochlear implant (CI) users. Speech intelligibility performance was assessed in 50 postlingual adult CI users on sentence lists and on CNC word lists. Results were compared with a normal-hearing (NH) group. The influence of contextual information was calculated from three different context models. Working memory capacity was measured with a Reading Span Test. CI recipients made significantly more use of contextual information in recognition of CNC words and sentences than NH listeners. Their use of contextual information in sentences was related to verbal working memory capacity but not to age, indicating that the ability to use context is dependent on cognitive abilities, regardless of age. The presence of context in sentences enhanced the sensitivity to differences in sensory bottom-up information but also increased the risk of a ceiling effect. A sentence test appeared to be suitable in CI users if word scoring is used and noise is added for the best performers.

A Novel Routing Scheme for Creating Opportunistic Context-Virtual Networks in IoT Scenarios

The massive amount of traffic required by the emerging Internet of Things (IoT) paradigm can be supported by the imminent arrival of 5G next-generation networks. However, the limited capacity of resources in IoT nodes, e.g., battery lifetime or buffer space, opens a challenge to be taken into account when proposing new routing solutions on IoT scenarios with intermittent connectivity. In this paper, we propose the concept of Opportunistic Context-Virtual Networks (OCVNs). The novelty of this approach is to create virtual groups of nodes that share interests in common for routing purposes. Therefore, only the nodes that are interested in the content of the messages that are flowing throughout the network are used as relaying nodes, providing their own resources for the sake of the communication. By leveraging the use of store-carry-and-forward mechanisms, a novel routing algorithm is proposed and evaluated over two realistic scenarios. Experimental results reveal that our solution outperforms other well-known opportunistic routing algorithms in terms of delivery probability and overhead ratio, while resource usage of relaying nodes is significantly reduced.

Contextual Action Cues from Camera Sensor for Multi-Stream Action Recognition

In action recognition research, two primary types of information are appearance and motion information that is learned from RGB images through visual sensors. However, depending on the action characteristics, contextual information, such as the existence of specific objects or globally-shared information in the image, becomes vital information to define the action. For example, the existence of the ball is vital information distinguishing “kicking” from “running”. Furthermore, some actions share typical global abstract poses, which can be used as a key to classify actions. Based on these observations, we propose the multi-stream network model, which incorporates spatial, temporal, and contextual cues in the image for action recognition. We experimented on the proposed method using C3D or inflated 3D ConvNet (I3D) as a backbone network, regarding two different action recognition datasets. As a result, we observed overall improvement in accuracy, demonstrating the effectiveness of our proposed method.

Disturbed Processing of Contextual Information in HCN3 Channel Deficient Mice

Hyperpolarization-activated cyclic nucleotide-gated channels (HCNs) in the nervous system are implicated in a variety of neuronal functions including learning and memory, regulation of vigilance states and pain. Dysfunctions or genetic loss of these channels have been shown to cause human diseases such as epilepsy, depression, schizophrenia, and Parkinson's disease. The physiological functions of HCN1 and HCN2 channels in the nervous system have been analyzed using genetic knockout mouse models. By contrast, there are no such genetic studies for HCN3 channels so far. Here, we use a HCN3-deficient (HCN3^−/−) mouse line, which has been previously generated in our group to examine the expression and function of this channel in the CNS. Specifically, we investigate the role of HCN3 channels for the regulation of circadian rhythm and for the determination of behavior. Contrary to previous suggestions we find that HCN3^−/− mice show normal visual, photic, and non-photic circadian function. In addition, HCN3^−/− mice are impaired in processing contextual information, which is characterized by attenuated long-term extinction of contextual fear and increased fear to a neutral context upon repeated exposure.

Good Practices in Forensic Toxicology

This manuscript provides an overview for analysts, medical and scientific investigators, and laboratory administrators, the range of factors that should be considered to implement best practice forensic toxicology. These include laboratory influence over the collection of specimens, their proper transport and chain-of-custody before arrival in the laboratory. In addition, the laboratory needs to ensure properly trained staff use suitably validated and documented analytical procedures that meet the intended purpose and type of case in an accredited or suitably quality oriented management system. To assist the investigating officers laboratory results require an interpretation over their possible significance when sufficient details are available over the circumstances of the case. This requires a thorough understanding of the various factors that influence concentrations of substances and ultimately their likely physiological effect. These include consideration of the route of ingestion, influence over chronicity of usage on tissue concentrations and tolerance, possible combined drug effects or likely adverse reactions and consideration of relevant genetic factors that may have influenced pharmacokinetic or pharmacodynamic response.

Modes of Effective Connectivity within Cortical Pathways Are Distinguished for Different Categories of Visual Context: An fMRI Study

Context contributes to accurate and efficient information processing. To reveal the dynamics of the neural mechanisms that underlie the processing of visual contexts during the recognition of color, shape, and 3D structure of objects, we carried out functional magnetic resonance imaging (fMRI) of subjects while judging the contextual validity of the three visual contexts. Our results demonstrated that the modes of effective connectivity in the cortical pathways, as well as the patterns of activation in these pathways, were dynamical depending on the nature of the visual contexts. While the fusiform gyrus, superior parietal lobe, and inferior prefrontal gyrus were activated by the three visual contexts, the temporal and parahippocampal gyrus/Amygdala (PHG/Amg) cortices were activated only by the color context. We further carried out dynamic causal modeling (DCM) analysis and revealed the nature of the effective connectivity involved in the three contextual information processing. DCM showed that there were dynamic connections and collaborations among the brain regions belonging to the previously identified ventral and dorsal visual pathways.

Mirror neuron activation prior to action observation in a predictable context

A fundamental capacity of social animals consists in the predictive representation of upcoming events in the outside world, such as the actions of others. Here, we tested the activity of ventral premotor area F5 mirror neurons (MNs) while monkeys observed an experimenter performing (Action condition) or withholding (Inaction condition) a grasping action, which could be predicted on the basis of previously presented auditory instructions. Many of the recorded MNs discharged only during action observation (Action MNs), but one-third also encoded the experimenter's withheld action (Inaction MNs). Interestingly, while most of Action MNs exhibited reactive discharge during action observation, becoming active after the go signal, the majority of Inaction MNs showed predictive discharge. MN population activity as a whole displayed an overall predictive activation pattern, becoming active, on average, 340 ms before the go signal. Furthermore, MNs became active earlier when the observed action was performed in the monkeys' extrapersonal rather than peripersonal space, suggesting that context-based neural prediction of others' actions plays different roles depending on the monkeys' ability to interact with the observed agent.

Tissue slide-based microRNA characterization of tumors: how detailed could diagnosis become for cancer medicine?

miRNAs are short, non-coding, regulatory RNAs that exert cell type-dependent, context-dependent, transcriptome-wide gene expression control under physiological and pathological conditions. Tissue slide-based assays provide qualitative (tumor compartment) and semi-quantitative (expression levels) information about altered miRNA expression at single-cell resolution in clinical tumor specimens. Reviewed here are key technological advances in the last 5 years that have led to implementation of fully automated, robust and reproducible tissue slide-based assays for in situ miRNA detection on US FDA-approved instruments; recent tissue slide-based discovery studies that suggest potential clinical applications of specific miRNAs in cancer medicine are highlighted; and the challenges in bringing tissue slide-based miRNA assays into the clinic are discussed, including clinical validation, biomarker performance, biomarker space and integration with other biomarkers.

Context modulates the contribution of time and space in causal inference

Humans use kinematic temporal and spatial information from the environment to infer the causal dynamics (e.g., force) of an event. We hypothesize that the basis for these inferences are malleable and modulated by contextual temporal and spatial information. Specifically, the present research investigates whether the extent of a person’s ongoing experience with direct causal events (e.g., temporally contiguous and spatially continuous) alters their use of time and space in judgments of causality. Participants made inferences of causality on animated launching events depicting a blue ball colliding with and then “launching” a red ball. We parametrically manipulated temporal contiguity and spatial continuity by varying the duration of contact between the balls and the angle of the second ball’s movement. We manipulated participants’ level of exposure to direct causal events (i.e., events with no delay or angle change) between experiments (Experiment 1: 2%, Experiment 2: 25%, Experiment 3: 75%). We found that participants adjust the temporal and spatial parameters they use to judge causality to accommodate the context in which they apprehended launching events. Participants became more conservative in their use of temporal and spatial parameters to judge causality as their exposure to direct causal events increased. People use time and space flexibly to infer causality based on their ongoing experiences. Such flexibility in making causal inferences may have adaptive significance.

Two roles of the context in Pavlovian fear conditioning

At both empirical and theoretical levels, multiple functional roles of contextual information upon memory performance have been proposed without a clear dissociation of these roles. Some theories have assumed that contexts are functionally similar to cues, whereas other views emphasize the retrieval facilitating properties of contextual information. In Experiment 1, we observed that one critical parameter, the spacing of trials, could determine whether the context would function as a conditioned stimulus or as a retrieval cue for memories trained in different phases. Experiments 2 and 3 doubly dissociated these functions by selectively disrupting one role but not the other, and vice versa. Overall, these observations identify one determinant of different functions of contextual information and pose a major challenge to theories of learning that assume exclusively one or the other function of the context. Moreover, these data emphasize the importance of parametric variations on behavioral control, which has critical implications for studies designed to understand the role of the hippocampus in processing of contextual attributes.