Predicting stock movements is a valuable research field that can help investors earn more profits. As with time-series data, the stock market is time-dependent and the value of historical information may decrease over time. Accurate prediction can be achieved by mining valuable information with words on social platforms and further integrating it with actual stock market conditions. However, many methods still cannot effectively dig deep into hidden information, integrate text and stock prices, and ignore the temporal dependence. Therefore, to (...) solve the above problems, we propose a transformer-based attention network framework that uses historical text and stock prices to capture the temporal dependence of financial data. Among them, the transformer model and attention mechanism are used for feature extraction of financial data, which has fewer applications in the financial field, and effective analysis of key information to achieve an accurate prediction. A large number of experiments have proved the effectiveness of our proposed method. The actual simulation experiment verifies that our model has practical application value. (shrink)

In this paper, I discuss the relationship between bodily experiences in dreams and the sleeping, physical body. I question the popular view that dreaming is a naturally and frequently occurring real-world example of cranial envatment. This view states that dreams are functionally disembodied states: in a majority of dreams, phenomenal experience, including the phenomenology of embodied selfhood, unfolds completely independently of external and peripheral stimuli and outward movement. I advance an alternative and more empirically plausible view of dreams as (...) weakly phenomenally-functionally embodied states. The view predicts that bodily experiences in dreams can be placed on a continuum with bodily illusions in wakefulness. It also acknowledges that there is a high degree of variation across dreams and different sleep stages in the degree of causal coupling between dream imagery, sensory input, and outward motor activity. Furthermore, I use the example of movement sensations in dreams and their relation to outward muscular activity to develop a predictive processing account. I propose that movement sensations in dreams are associated with a basic and developmentally early kind of bodily self-sampling. This account, which affords a central role to active inference, can then be broadened to explain other aspects of self- and world-simulation in dreams. Dreams are world-simulations centered on the self, and important aspects of both self- and world-simulation in dreams are closely linked to bodily self-sampling, including muscular activity, illusory own-body perception, and vestibular orienting in sleep. This is consistent with cognitive accounts of dream generation, in which long-term beliefs and expectations, as well as waking concerns and memories play an important role. What I add to this picture is an emphasis on the real-body basis of dream imagery. This offers a novel perspective on the formation of dream imagery and suggests new lines of research. (shrink)

Sequential action makes up the bulk of human daily activity, and yet much remains unknown about how people learn such actions. In one motor learning paradigm, the serial reaction time (SRT) task, people are taught a consistent sequence of button presses by cueing them with the next target response. However, the SRT task only records keypress response times to a cued target, and thus it cannot reveal the full time‐course of motion, including predictive movements. This paper describes a mouse (...) class='Hi'>movement trajectory SRT task in which the cursor must be moved to a cued location. We replicated keypress SRT results, but also found that predictive movement—before the next cue appears—increased during the experiment. Moreover, trajectory analyses revealed that people developed a centering strategy under uncertainty. In a second experiment, we made prediction explicit, no longer cueing targets. Thus, participants had to explore the response alternatives and learn via reinforcement, receiving rewards and penalties for correct and incorrect actions, respectively. Participants were not told whether the sequence of stimuli was deterministic, nor if it would repeat, nor how long it was. Given the difficulty of the task, it is unsurprising that some learners performed poorly. However, many learners performed remarkably well, and some acquired the full 10‐item sequence within 10 repetitions. Comparing the high‐ and low‐performers’ detailed results in this reinforcement learning (RL) task with the first experiment's cued trajectory SRT task, we found similarities between the two tasks, suggesting that the effects in Experiment 1 are due to predictive, rather than reactive processes. Finally, we found that two standard model‐free reinforcement learning models fit the high‐performing participants, while the four low‐performing participants provide better fit with a simple negative recency bias model. (shrink)

Background. Positive schizophrenic symptoms, especially passivity phenomena, including auditory hallucinations, may be caused by an abnormal sense of agency, which people with schizotypal personality traits also tend to exhibit. A sense of agency asserts that it is oneself who is causing or generating an action. It is possible that this abnormal sense of self-agency is attributable to the abnormal prediction of one’s own movements in motor control. Method. We conducted an experiment using the “disappeared cursor” paradigm in which non-clinical, (...) healthy participants were required to click on a target using an invisible mouse cursor. Prediction error was defined as the distance between the target and the click point. Results. The results showed that schizotypal personality traits, but not depressive or anxious traits, were correlated with deficits in predicting movements of the subjects’ left hand. In particular, auditory hallucination proneness had the strongest relationship with movement prediction error. In this report, we also discuss the error tendency. Conclusions. This finding is in accordance with the idea that passivity phenomena or proneness may be caused by the abnormal prediction of one’s own actions or movements. (shrink)

Human interaction has two principle functions: building and maintaining relationships with others and exchanging information. The function of building and maintaining relationships with others relates to interpersonal coordination; this behavior pattern is expected to predict the outcome of social relationships, such as between therapists and patients. It is unclear, however, whether the exchange of information is associated with interpersonal coordination. In the present study, we tested a hypothesis of whether body movement synchrony occurs in a natural conversation and whether (...) this synchrony has a positive correlation with the degree of information exchange. Fifty participants were engaged in a conversation task; each had different roles in the conversation. We measured their body movements during this conversation using an optical motion capture system. Similar to methods that can be found in previous research, we calculated body movements and quantified their synchrony applying the methods previously reported that automatically quantified their body movements. Moreover, we determined the participants’ degree of information exchange concerning the conversation using a questionnaire. We observed that the body movement synchrony of pairs who talked with each other was significantly higher than that of pairs who did not talk with each other, and that this synchrony was positively associated with the degree of information exchange. These results suggest that body movement synchrony predicted information exchange. (shrink)

In order to solve the problem of unsmooth and inefficient human-computer interaction process in the information age, a method for human-computer interaction intention prediction based on electroencephalograph signals and eye movement signals is proposed. This approach is different from previous methods where researchers predict using data from human-computer interaction and a single physiological signal. This method uses the eye movements and EEG signals that clearly characterized the interaction intention as the prediction basis. In addition, this approach is (...) not only tested with multiple human-computer interaction intentions, but also takes into account the operator in different cognitive states. The experimental results show that this method has some advantages over the methods proposed by other researchers. In Experiment 1, using the eye movement signal fixation point abscissa Position X, fixation point ordinate Position Y, and saccade amplitude to judge the interaction intention, the accuracy reached 92%, In experiment 2, only relying on the pupil diameter, pupil size and fixed time, fixed time of eye movement signals can not achieve higher accuracy of the operator’s cognitive state, so EEG signals are added. The cognitive state was identified separately by combining the screened EEG parameters Rα/β with the eye movement signal pupil diameter and fixation time, with an accuracy of 91.67%. The experimental combination of eye movement and EEG signal features can be used to predict the operator’s interaction intention and cognitive state. (shrink)

Although mouse‐tracking has been taken as a real‐time window on different aspects of human decision‐making processes, whether purely semantic information affects response conflict at the level of motor output as measured through mouse movements is still unknown. Here, across two experiments, we investigated the effects of semantic knowledge by predicting participants’ performance in a standard keyboard task and in a mouse‐tracking task through distributional semantics, a usage‐based modeling approach to meaning. In Experiment 1, participants were shown word pairs and were (...) required to perform a two‐alternative forced choice task selecting either the more abstract or the more concrete word, using standard keyboard presses. In Experiment 2, participants performed the same task, yet this time response selection was achieved by moving the computer mouse. Results showed that the involvement of semantic components in the task at hand is observable using both standard reaction times (Experiment 1) as well as using indexes extracted from mouse trajectories (Experiment 2). In particular, mouse trajectories reflected the response conflict and its temporal evolution, with a larger deviation for increasing word semantic relatedness. These findings support the validity of mouse‐tracking as a method to detect deep and implicit decision‐making features. Additionally, by demonstrating that a usage‐based model of meaning can account for the different degrees of cognitive conflict associated with task achievement, these findings testify the impact of the human semantic memory on decision‐making processes. (shrink)

Sequential action makes up the bulk of human daily activity, and yet much remains unknown about how people learn such actions. In one motor learning paradigm, the serial reaction time (SRT) task, people are taught a consistent sequence of button presses by cueing them with the next target response. However, the SRT task only records keypress response times to a cued target, and thus it cannot reveal the full time‐course of motion, including predictive movements. This paper describes a mouse (...) class='Hi'>movement trajectory SRT task in which the cursor must be moved to a cued location. We replicated keypress SRT results, but also found that predictive movement—before the next cue appears—increased during the experiment. Moreover, trajectory analyses revealed that people developed a centering strategy under uncertainty. In a second experiment, we made prediction explicit, no longer cueing targets. Thus, participants had to explore the response alternatives and learn via reinforcement, receiving rewards and penalties for correct and incorrect actions, respectively. Participants were not told whether the sequence of stimuli was deterministic, nor if it would repeat, nor how long it was. Given the difficulty of the task, it is unsurprising that some learners performed poorly. However, many learners performed remarkably well, and some acquired the full 10‐item sequence within 10 repetitions. Comparing the high‐ and low‐performers’ detailed results in this reinforcement learning (RL) task with the first experiment's cued trajectory SRT task, we found similarities between the two tasks, suggesting that the effects in Experiment 1 are due to predictive, rather than reactive processes. Finally, we found that two standard model‐free reinforcement learning models fit the high‐performing participants, while the four low‐performing participants provide better fit with a simple negative recency bias model. (shrink)

It is argued here that a critical prediction of the E-Z Reader model is that experimental manipulations that disrupt early encoding of visual and orthographic features of the fixated word without affecting subsequent lexical processing should influence the processing difficulty of the fixated word without producing any processing effect on the next word. This prediction is explained and illustrated.

While explaining a large proportion of any variance, accounts of the speed and accuracy of targetting movements use techniques (e.g., log transforms) that typically reduce variability before ''explaining'' the data. Therefore the predictive power of such accounts are important. We consider whether Plamondon's model can account for kinematics of targetting movements of clinical populations.

Recent studies in pedestrian simulation have been able to construct a highly realistic navigation behaviour in many circumstances. However, when replicating the close interactions between pedestrians, the replicated behaviour is often unnatural and lacks human likeness. One of the possible reasons is that the current models often ignore the cognitive factors in the human thinking process. Another reason is that many models try to approach the problem by optimising certain objectives. On the other hand, in real life, humans do not (...) always take the most optimised decisions, particularly when interacting with other people. To improve the navigation behaviour in this circumstance, we proposed a pedestrian interacting model using reinforcement learning. Additionally, a novel cognitive prediction model, inspired by the predictive system of human cognition, is also incorporated. This helps the pedestrian agent in our model to learn to interact and predict the movement in a similar practice as humans. In our experimental results, when compared to other models, the path taken by our model’s agent is not the most optimised in certain aspects like path lengths, time taken and collisions. However, our model is able to demonstrate a more natural and human-like navigation behaviour, particularly in complex interaction settings. (shrink)

With two eye movements tracking experiments, present study sought to establish whether predictability of target words facilitate characters processing in Chinese reading. Target Words embedded in sentences in both experiments were composed by 2 Chinese characters. Predictability of target words were manipulated in both experiments, beyond that, frequency of targets' first characters were manipulated in Experiment 1, frequency of targets' second characters were manipulated in Experiment 2. Pervasive predictability effects were observed on almost all of eye movement measures in (...) both experiments. It also yield reliable characters frequency effect in Experiment 1 & 2, on some measures. None reliable interaction effects of predictability and first character frequency were observed in Experiment 1, but predictability and second character frequency interactively impacted on some measures of eye movement. Theoretical implications of the data are discussed. (shrink)

Vaesen suggests that motor control is not among the primary origins of the uniqueness of human tool use. However, recent findings show that cognitive processes involved in control of human limb movements may be much more sophisticated than it was believed previously. The sophistication of movement control may substantially contribute to the uniqueness of humans in tool use.

Although healthcare workers play a crucial role in helping curb the hazardous health impact of coronavirus disease 2019, their lives and major functioning have been greatly affected by the pandemic. This study examined the effects of the COVID-19 pandemic on the quality of life of Malaysian healthcare workers and its predictive factors. An online sample of 389 university-based healthcare workers completed questionnaires on demographics, clinical features, COVID-19-related stressors, psychological experiences, and perceived social support after the movement lockdown was lifted. (...) All domains of QoL were within the norms of the general population except for social relationship QoL, which was lower than the norm. Multiple linear regression analysis indicated that COVID-19-related stressors and psychological sequelae predicted lower QoL. Conversely, greater perceived social support from friends and significant others predicted higher QoL. Clinical and demographic characteristics predicted QoL to a lesser extent: A history of pre-existing medical illness was associated only with lower physical health QoL, whereas older age and being single, divorced, or widowed were only predictive of higher environmental QoL. Efforts to enhance QoL among healthcare workers in response to the pandemic should focus on mitigating COVID-19-related stressors and psychological sequelae and facilitating social support. (shrink)

Recent studies have documented substantial variability among typical listeners in how gradiently they categorize speech sounds, and this variability in categorization gradience may link to how listeners weight different cues in the incoming signal. The present study tested the relationship between categorization gradience and cue weighting across two sets of English contrasts, each varying orthogonally in two acoustic dimensions. Participants performed a four‐alternative forced‐choice identification task in a visual world paradigm while their eye movements were monitored. We found that (a) (...) greater categorization gradience derived from behavioral identification responses corresponds to larger secondary cue weights derived from eye movements; (b) the relationship between categorization gradience and secondary cue weighting is observed across cues and contrasts, suggesting that categorization gradience may be a consistent within‐individual property in speech perception; and (c) listeners who showed greater categorization gradience tend to adopt a buffered processing strategy, especially when cues arrive asynchronously in time. (shrink)

In this paper we aim to show that motor intentionality, as the underlying ground for social cognition, can be explained through the predictive engagement model. Sensorimotor processes seem to play central roles in social interaction, cognition and language. We question the phenomenological role of the body in social cognition and further investigate a causal neural explanation. We will adopt a different perspective by linking the role of the body and intercorporeality with recent findings in philosophy of neuroscience under the predictive (...) brain hypothesis. In fact, the living body seems to entertain a dialogical and enactive relationship with the surrounding context, as well as with neural circuits actively responding to external stimuli. The body is thus configured as a living organism, and not as a mere biological substratum, offering to phenomenology and empirical sciences further confirmations of the possibility-and need-for a cooperation. (shrink)

The λ model suggests that detailed kinematics arise from changes in control variables and need not be explicitly planned. However, we have shown that when moving a grasped object, grip force is precisely modulated in phase with acceleration-dependent inertial load. This suggests that the motor system can predict detailed kinematics. This prediction may be based on a forward model of the dynamics of the loaded limb.

In order to understand ongoing activity, observers segment it into meaningful temporal parts. Segmentation can be based on bottom‐up processing of distinctive sensory characteristics, such as movement features. Segmentation may also be affected by top‐down effects of knowledge structures, including information about actors' intentions. Three experiments investigated the role of movement features and intentions in perceptual event segmentation, using simple animations. In all conditions, movement features significantly predicted where participants segmented. This relationship was stronger when participants identified (...) larger units than when they identified smaller units, and stronger when the animations were generated randomly than when they were generated by goal‐directed human activity. This pattern suggests that bottom‐up processing played an important role in segmentation of these stimuli, but that this was modulated by top‐down influence of knowledge structures. To describe accurately how observers perceive ongoing activity, one must account for the effects of distinctive sensory characteristics, the effects of knowledge structures, and their interactions. (shrink)

This article offers a detailed examination of the content of predictive policing applications. Crime prediction machines are used by governments to shape the moral behavior of police. They serve not only to predict when and where crime is likely to occur, but also to regulate police work. They calculate equivalence ratios, distributing security across the territory based on multiple cost and social justice criteria. Tracing the origins of predictive policing in the Compstat system, this article studies the shift from (...) machines to explore intuitions to applications removing the reflexive dimension of proactivity, thus turning prediction into the medium for “dosage” metrics of police work quantities. Finally, the article discusses how, driven by a critical movement denouncing the discriminatory biases of predictive machines, developers seek to develop techniques to audit training dataset and ways to calculate the reasonable amount of stop and frisk over the population. (shrink)

Recent conjectures regarding the nature and mechanism of consciousness are extended to include the contribution of the cerebellum. The role of this brain structure appears to be a rather sophisticated form of prediction, as exemplified by certain dynamical capabilities of the visual system, and by the difficulty of self-administered tickling. The pars intermedia of the cerebellum is perceived as a direct feedback device, functioning in parallel to the primary neuronal circuit involved in consciousness; this leads to the suggestion that (...) it serves as a tutor for the putative master node, the latter governing the collective movements of all the body's muscles. The cerebellar hemispheres are believed to act as an internal feedback device, and to be more directly coupled to the master node; they are seen as serving plenisentient unconsciousness. The possible importance of muscular spindles for the generation of qualia is discussed, as are the significance of the frontal lobes, the basal ganglia and the limbic system for the content of consciousness. Finally, the stages through which infant consciousness gradually acquires its sophistication are tentatively identified. (shrink)

What are the effects of word-by-word predictability on sentence processing times during the natural reading of a text? Although information complexity metrics such as surprisal and entropy reduction have been useful in addressing this question, these metrics tend to be estimated using computational language models, which require some degree of commitment to a particular theory of language processing. Taking a different approach, this study implemented a large-scale cumulative cloze task to collect word-by-word predictability data for 40 passages and compute surprisal (...) and entropy reduction values in a theory-neutral manner. A separate group of participants read the same texts while their eye movements were recorded. Results showed that increases in surprisal and entropy reduction were both associated with increases in reading times. Furthermore, these effects did not depend on the global difficulty of the text. The findings suggest that surprisal and entropy reduction independently contribute to variation in reading times, as these metrics seem to capture different aspects of lexical predictability. (shrink)

Looking times and gaze behavior indicate that infants can predict the goal state of an observed simple action event (e.g., object‐directed grasping) already in the first year of life. The present paper mainly focuses on infants’ predictive gaze‐shifts toward the goal of an ongoing action. For this, infants need to generate a forward model of the to‐be‐obtained goal state and to disengage their gaze from the moving agent at a time when information about the action event is still incomplete. By (...) about 6 months of age, infants show goal‐predictive gaze‐shifts, but mainly for familiar actions that they can perform themselves (e.g., grasping) and for familiar agents (e.g., a human hand). Therefore, some theoretical models have highlighted close relations between infants’ ability for action‐goal prediction and their motor development and/or emerging action experience. Recent research indicates that infants can also predict action goals of familiar simple actions performed by non‐human agents (e.g., object‐directed grasping by a mechanical claw) when these agents display agency cues, such as self‐propelled movement, equifinality of goal approach, or production of a salient action effect. This paper provides a review on relevant findings and theoretical models, and proposes that the impacts of action experience and of agency cues can be explained from an action‐event perspective. In particular, infants’ goal‐predictive gaze‐shifts are seen as resulting from an interplay between bottom‐up processing of perceptual information and top‐down influences exerted by event schemata that store information about previously executed or observed actions. (shrink)

Three online mouse cursor-tracking experiments investigated predictive sentence processing at speed. Participants viewed visual arrays with objects like a bike and kite while hearing predictive sentences like, “What the man will ride, which is shown on this page, is the bike,” or non-predictive sentences like, “What the man will spot, which is shown on this page, is the bike.” Based on the selectional restrictions of “ride” (i.e., vs. “spot”), participants made mouse cursor movements to the bike before hearing the noun (...) “bike.” Compellingly, this effect was observed at speech rates of ∼3 (Experiment 1), ∼6 (Experiment 2), and ∼9 (Experiment 3) syllables/s. While prior research suggests striking limits on prediction, these results highlight temporal dynamics that may impact comprehenders’ ability to preactivate information when hearing impressively rapid speech. Implications for theories of sentence processing are discussed. (shrink)

Virtuosity in music performance is often associated with fast, precise, and efficient sound-producing movements. The generation of such highly skilled movements involves complex joint and muscle control by the central nervous system, and depends on the ability to anticipate, segment, and coarticulate motor elements, all within the biomechanical constraints of the human body. When successful, such motor skill should lead to what we characterize as fluency in musical performance. Detecting typical features of fluency could be very useful for technology-enhanced learning (...) systems, assisting and supporting students during their individual practice sessions by giving feedback and helping them to adopt sustainable movement patterns. In this study, we propose to assess fluency in musical performance as the ability to smoothly and efficiently coordinate while accurately performing slow, transitionary, and rapid movements. To this end, the movements of three cello players and three drummers at different levels of skill were recorded with an optical motion capture system, while a wireless electromyogrphy (EMG) system recorded the corresponding muscle activity from relevant landmarks. We analyze the kinematic and coarticulation characteristics of these recordings separately and then propose a combined model of fluency in musical performance predicting music sophistication. Results suggest movements from expert performers' are characterized by consistently smooth strokes and scaling of muscle phasic coactivation. The explored model of fluency as function of movement smoothness and coarticulation patterns was shown to be limited by the sample size but serves as a proof of concept. Results from this study show the potential of a technology-enhanced objective measure of fluency in musical performance, which could lead to improved practices for aspiring musicians, instructors, and researchers. (shrink)

BackgroundCoaching is increasingly viewed as a dyadic exchange of verbal and non-verbal interactions driving clients' progress. Yet, little is known about how the trajectory of dyadic interactions plays out in workplace coaching.MethodThis paper provides a multiple-step exploratory investigation of movement synchrony of dyads in workplace coaching. We analyzed a publicly available dataset of 173 video-taped dyads. Specifically, we averaged MS per session/dyad to explore the temporal patterns of MS across the cluster of dyads that completed 10 sessions, and a (...) set of 173 dyadic interactions with a varied number of sessions. Additionally, we linked that pattern to several demographic predictors. The results indicate a differential downward trend of MS.ResultsDemographic factors do not predict best fitting MS curve types, and only client age and coach experience show a small but significant correlation.DiscussionWe provide contextualized interpretations of these findings and propose conceptual considerations and recommendations for future coaching process research and practice. (shrink)

We know that reading involves coordination between textual characteristics and visual attention, but research linking eye movements during reading and comprehension assessed after reading is surprisingly limited, especially for reading long connected texts. We tested two competing possibilities: (a) the weak association hypothesis: Links between eye movements and comprehension are weak and short‐lived, versus (b) the strong association hypothesis: The two are robustly linked, even after a delay. Using a predictive modeling approach, we trained regression models to predict comprehension scores (...) from global eye movement features, using participant‐level cross‐validation to ensure that the models generalize across participants. We used data from three studies in which readers (Ns = 104, 130, 147) answered multiple‐choice comprehension questions ~30 min after reading a 6,500‐word text, or after reading up to eight 1,000‐word texts. The models generated accurate predictions of participants' text comprehension scores (correlations between observed and predicted comprehension: 0.384, 0.362, 0.372, ps <.001), in line with the strong association hypothesis. We found that making more, but shorter fixations, consistently predicted comprehension across all studies. Furthermore, models trained on one study's data could successfully predict comprehension on the others, suggesting generalizability across studies. Collectively, these findings suggest that there is a robust link between eye movements and subsequent comprehension of a long connected text, thereby connecting theories of low‐level eye movements with those of higher order text processing during reading. (shrink)

Previous studies have shown that the motion intention recognition for lower limb prosthesis mainly focused on the identification of performed gait. However, the bionic prosthesis needs to know the next movement at the beginning of a new gait, especially in complex operation environments. In this paper, an upcoming locomotion prediction scheme via multilevel classifier fusion was proposed for the complex operation. At first, two motion states, including steady state and transient state, were defined. Steady-state recognition was backtracking of (...) a completed gait, which would be used as prior knowledge of motion prediction. In steady-state recognition, surface electromyographic and inertial sensors were fused to improve recognition accuracy; five typical locomotion modes were recognized by random forest classifier with over 97.8% accuracy. The transient state was defined as an observation period at the initial stage of upcoming movement, in which only the sEMG signal was recorded due to the limitation of sliding window length. LightGBM classifier was validated to outperform other methods in the accuracy and prediction time of transient-state recognition. Finally, a simplified HMM model based on prior knowledge and observation result was constructed to predict upcoming locomotion. The results indicated that the locomotion prediction was over 91% accuracy. The proposed scheme implements the locomotion prediction at the initial stage of each gait and provides critical information for the gait control of lower limb prosthesis. (shrink)

When we read narrative texts such as novels and newspaper articles, we segment information presented in such texts into discrete events, with distinct boundaries between those events. But do our eyes reflect this event structure while reading? This study examines whether eye movements during the reading of discourse reveal how readers respond online to event structure. Participants read narrative passages as we monitored their eye movements. Several measures revealed that event structure predicted eye movements. In two experiments, we found that (...) both early and overall reading times were longer for event boundaries. We also found that regressive saccades were more likely to land on event boundaries, but that readers were less likely to regress out of an event boundary. Experiment 2 also demonstrated that tracking event structure carries a working memory load. Eye movements provide a rich set of online data to test the cognitive reality of event segmentation during reading. (shrink)

Hans Reichenbach was a formidable figure in early-twentieth-century philosophy of science. Educated in Germany, he was influential in establishing the so-called Berlin Circle, a companion group to the Vienna Circle founded by his colleague Rudolph Carnap. The movement they founded—usually known as "logical positivism," although it is more precisely known as "scientific philosophy" or "logical empiricism"—was a form of epistemology that privileged scientific over metaphysical truths. Reichenbach, like other young philosophers of the exact sciences of his generation, was deeply (...) impressed by the far-reaching changes in physics brought about by Einstein's special and general theories of relativity. Reichenbach responded to scientific advances by doing fundamental work in space-time theories, in quantum mechanics, in statistical mechanics, and in the development of probability theory—making him the most important philosopher of physics in the first generation of logical empiricism. Forced from his academic position by the Nazi race laws in 1933, Reichenbach wrote _Experience and Prediction_ at the University of Istanbul, where had had fled, expressly to introduce logical positivism to English speakers. In the two decades following World War II, during the explosion of scientific advances in North America, logical positivism was the reigning theory of the philosophy of science and Reichenbach was at the peak of his career. But, inevitably, support for logical positivism began to wane as it became obvious that the justification of scientific theories could not be entirely resolved by relying on strictly formal, technical processes. The growth of the discipline of the history of philosophy of science, which has created an audience of scholars eager for seminal classics in scientific philosophy, and the evidence supporting a historicist paradigm within logical positivism are two important reasons to make _Experience and Prediction_ available once again. "Hans Reichenbach's_ Experience and Prediction_ is one of the most important books in twentieth-century philosophy of science. Its author was, along with Rudolf Carnap, one of the two principal ambassadors to North America of the exciting new European philosophical movement known here under the names 'Logical Positivism' and 'Scientific Philosophy.' In 1938, when the book was published, Reichenbach was an exile from his native Germany, teaching in Istanbul, Turkey, and about to emigrate to the United States to take up a prestigious position at UCLA. He wrote_ Experience and Prediction_ in English as his calling card to his new American colleagues. More than any other single book,_ Experience and Prediction_ set the agenda for the new discipline of the philosophy of science that was to emerge after World War II as, perhaps, the most exciting new area in North American philosophy. Many of the problems still at the focus of discussion were given their classic formulations in this book. Long out of print,_ Experience and Prediction_ appears here in a new edition accompanied by a splendid historical introduction by the noted young philosopher and historian of the philosophy of science, Alan Richardson. A jewel of a book may once again be appreciated in its proper setting." —Don A. Howard, University of Notre Dame. (shrink)

Braitenberg et al.'s view that the cerebellum contributes to multijoint sequences of movement is too narrow to account adequately for results from new anatomical, neurobehavioral, and neuroimaging studies. A broader view is that the cerebellum modulates attention, sensory, motor, and other neural systems in order to accomplish its prime function, which is to learn to predict and prepare for imminent information acquisition, analysis, or action.

While numerous studies show that brain signals contain information about an individual’s current state that are potentially valuable for smoothing man-machine interfaces, this has not yet lead to the use of brain computer interfaces (BCI) in daily life. One of the main challenges is the common requirement of personal data that is correctly labelled concerning the state of interest in order to train a model, where this trained model is not guaranteed to generalize across time and context. Another challenge is (...) the requirement to wear electrodes on the head. We here propose a BCI that can tackle these issues and may be a promising case for BCI research and application in everyday life. The BCI uses EEG signals to predict head rotation in order to improve images presented in a Virtual Reality (VR) headset. When presenting a 360° video to a headset, Field-of-View approaches only stream the content that is in the current field of view and leave out the rest. When the user rotates the head, other content parts need to be made available soon enough to go unnoticed by the user which is problematic given the available bandwidth. By predicting head rotation, the content parts adjacent to the currently viewed part could be retrieved in time for display when the rotation actually takes place. Eleven participants generated left- and rightward head rotations while head movements were recorded using the headsets motion sensing system and EEG sensors. We trained neural network models to distinguish EEG epochs preceding rightward, leftward and no rotation. Applying these models to streaming EEG data that was withheld from the training showed that 400 ms before rotation onset, the probability ‘no rotation’ started to decrease and the probabilities of an upcoming right- or leftward rotation started to diverge in the correct direction. In the proposed BCI scenario, users already wear a device on their head allowing for integrated sensors. Moreover, it is possible to acquire accurately labeled training data on the fly, and continuously monitor and improve the model’s performance. The BCI can be harnessed if it will improve imagery and therewith enhance immersive experience. (shrink)

Parkinson's Disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms generally come on slowly over time. Early in the disease, the most obvious are shaking, rigidity, slowness of movement, and difficulty with walking. Doctors do not know what causes it and finds difficulty in early diagnosing the presence of Parkinson’s disease. An artificial neural network system with back propagation algorithm is presented in this paper for helping doctors in (...) identifying PD. Previous research with regards to predict the presence of the PD has shown accuracy rates up to 93% [1]; however, accuracy of prediction for small classes is reduced. The proposed design of the neural network system causes a significant increase of robustness. It is also has shown that networks recognition rates reached 100%. (shrink)

In tennis, service requires a variety of complicated movements. Given the importance of taking the initiative to obtain points in a tennis match, it is crucial to make full use of speed and spin rate of service. Generally, a service that requires a higher spin rate would slow down, and a service that has increased speed would have a decreased spin rate. For players who are disadvantaged in height, although controlling spin rate is essential, slowing down service speed should be (...) avoided. For these players, the challenge of service is to improve the speed without decreasing the spin rate. Players must also be trained to build physical strength required for this skill. It is not uncommon to work on physical training without a racket; however, few studies have reported on the effects of cultivated physical strength on on-court tennis performance. Therefore, this study aimed to propose physical measurements that could be used as indices to improve service performance in 58 elite Japanese junior male players. To test service performance, we used TrackMan tennis radar device to assess speed, spin rate, impact height, and impact depth. To test physical strength, we measured 5- and 20-m sprint, broad jump, medicine ball throw. We used a significant multiple regression equation to predict the first service speed obtained from the broad jump and the Medicine ball throw. Additionally, a strong correlation was obtained between the predicted and measured values. In addition to physical strength, we suggest that the depth of the impact point is important for improving the first service speed. However, we were not able to identify the physical strength test items that improve service spin rate. Other item should be examined in the future to determine the physical strength associated with spin rate. This result could help connect physical training and service performance. (shrink)

The current assessment of behaviors in the inventories to diagnose autism spectrum disorders (ASD) focus on observation and discrete categorizations. Behaviors require movements, yet measurements of physical movements are seldom included. Their inclusion however, could provide an objective characterization of behavior to help unveil interactions between the peripheral and the central nervous systems. Such interactions are critical for the development and maintenance of spontaneous autonomy, self-regulation and voluntary control. At present, current approaches cannot deal with the heterogeneous, dynamic and stochastic (...) nature of development. Accordingly, they leave no avenues for real-time or longitudinal assessments of change in a coping system continuously adapting and developing compensatory mechanisms. We offer a new unifying statistical framework to reveal re-afferent kinesthetic features of the individual with ASD. The new methodology is based on the non-stationary stochastic patterns of minute fluctuations (micro-movements) inherent to our natural actions. Such patterns of behavioral variability provide re-entrant sensory feedback contributing to the autonomous regulation and coordination of the motor output. From an early age, this feedback supports centrally driven volitional control and fluid, flexible transitions between intentional and spontaneous behaviors. We show that in ASD there is a disruption in the maturation of this form of proprioception. Despite this disturbance, each individual has unique adaptive compensatory capabilities that we can unveil and exploit to evoke faster and more accurate decisions. Measuring the kinesthetic re-afference in tandem with stimuli variations we can detect changes in their micro-movements indicative of a more predictive and reliable kinesthetic percept. Our methods address the heterogeneity of ASD with a personalized approach grounded in the inherent sensory-motor abilities that the individual has already developed. (shrink)

A postcompletion error is a type of procedural error that occurs after the main goal of a task has been accomplished. There is a strong theoretical foundation accounting for postcompletion errors (Altmann & Trafton, 2002; Byrne & Bovair, 1997). This theoretical foundation has been leveraged to develop a logistic regression model of postcompletion errors based on reaction time and eye movement measures (Ratwani, McCurry, & Trafton, 2008). This study further develops and extends this predictive model by (a) validating the (...) model and the general set of predictors on a new task to test the robustness of the model, and (b) determining which specific theoretical components are most important to postcompletion error prediction. (shrink)

TheConceptual Feature framework predicts that word meaning is represented within a high-dimensional semantic space bounded by weighted contributions of perceptual, affective, and encyclopedic information. The ACF, like latent semantic analysis, is amenable to distance metrics between any two words. We applied predictions of the ACF framework to abstract words using eyetracking via an adaptation of the classical “visual word paradigm”. Healthy adults selected the lexical item most related to a probe word in a 4-item written word array comprising the target (...) and three distractors. The relation between the probe and each of the four words was determined using the semantic distance metrics derived from ACF ratings. Eye movement data indicated that the word that was most semantically related to the probe received more and longer fixations relative to distractors. Importantly, in sets where participants did not provide an overt behavioral response, the fixation rates were nonetheless significantly higher for targets than distractors, closely resembling trials where an expected response was given. Furthermore, ACF ratings which are based on individual words predicted eye fixation metrics of probe-target similarity at least as well as latent semantic analysis ratings which are based on word co-occurrence. The results provide further validation of Euclidean distance metrics derived from ACF ratings as a measure of one facet of the semantic relatedness of abstract words and suggest that they represent a reasonable approximation of the organization of abstract conceptual space. The data are also compatible with the broad notion that multiple sources of information shape the organization of abstract concepts. While the adapted “VWP” is potentially a more metacognitive task than the classical visual world paradigm, we argue that it offers potential utility for studying abstract word comprehension. (shrink)