Video Stimuli Research Articles

Potent and Quick Responses to Conspecific Faces and Snakes in the Anterior Cingulate Cortex of Monkeys.

Appropriate processing of others’ facial emotions is a fundamental ability of primates in social situations. Several moods and anxiety disorders such as depression cause a negative bias in the perception of facial emotions. Depressive patients show abnormalities of activity and gray matter volume in the perigenual portion of the anterior cingulate cortex (ACC) and an increase of activation in the amygdala. However, it is not known whether neurons in the ACC have a function in the processing of facial emotions. Furthermore, detecting predators quickly and taking avoidance behavior are important functions in a matter of life and death for wild monkeys. the existence of predators in their vicinity is life-and-death information for monkeys. In the present study, we recorded the activity of single neurons from the monkey ACC and examined the responsiveness of the ACC neurons to various visual stimuli including monkey faces, snakes, foods, and artificial objects. About one-fourth of the recorded neurons showed a significant change in activity in response to the stimuli. The ACC neurons exhibited high selectivity to certain stimuli, and more neurons exhibited the maximal response to monkey faces and snakes than to foods and objects. The responses to monkey faces and snakes were faster and stronger compared to those to foods and objects. Almost all of the neurons that responded to video stimuli responded strongly to negative facial stimuli, threats, and scream. Most of the responsive neurons were located in the cingulate gyrus or the ventral bank of the cingulate sulcus just above or anterior to the genu of the corpus callosum, that is, the perigenual portion of the ACC, which has a strong mutual connection with the amygdala. These results suggest that the perigenual portion of the ACC in addition to the amygdala processes emotional information, especially negative life-and-death information such as conspecifics’ faces and snakes.

Adapting therapy for a new world: storytelling therapy in EVA Park

ABSTRACT Background Storytelling is fundamental to human communication yet is under-represented in aphasia therapy research and clinical practice. Access to care may be one obstacle; in the broader healthcare context, remote modes of treatment delivery can increase individuals’ access to care. EVA Park is a highly novel, online platform designed with people with aphasia that has shown capacity to improve aspects of language and communication. Aims This study explored whether it is feasible to deliver a storytelling intervention in EVA Park and whether therapy brought about improvements in the content and organisation of their narratives. Changes in functional communication and technology use were also examined. Methods and procedures In a pilot feasibility study, three individuals with aphasia were recruited in the UK and Australia. Over five weeks, participants received 20 hours of therapy in EVA Park, consisting of three weekly sessions with a speech therapist and one weekly session in which the participant told the story to a volunteer who was blinded to the content of their story. A repeated-measures, case series design was used to evaluate therapy. The primary measure assessed the content of narratives elicited by novel video stimuli twice before and twice after therapy. Secondary measures investigated structural features of the video narratives and of personal narratives. Functional communication was assessed with the Communication Activities of Daily Living assessment, and technology use was probed via a Technology Screen. Outcomes and results Delivery of storytelling therapy via EVA Park was feasible; technology challenges arose and were resolved using multiple strategies. Following therapy, participants’ storytelling improved in content, with a large effect size for the group, and in structure. Generalisation to personal narratives was not observed. Some improvements were seen in functional communication. Conclusions Storytelling therapy delivered via an online platform is feasible and may improve the content and organisation of participants’ storytelling, with some evidence of generalisation to functional communication.

A parietal region processing numerosity of observed actions: An FMRI study.

When observing others' behavior, it is important to perceive not only the identity of the observed actions (OAs), but also the number of times they were performed. Given the mounting evidence implicating posterior parietal cortex in action observation, and in particular that of manipulative actions, the aim of this study was to identify the parietal region, if any, that contributes to the processing of observed manipulative action (OMA) numerosity, using the functional magnetic resonance imaging technique. Twenty‐one right‐handed healthy volunteers performed two discrimination tasks while in the scanner, responding to video stimuli in which an actor performed manipulative actions on colored target balls that appeared four times consecutively. The subjects discriminated between two small numerosities of either OMAs (“Action” condition) or colors of balls (“Ball” condition). A significant difference between the “Action” and “Ball” conditions was observed in occipito‐temporal cortex and the putative human anterior intraparietal sulcus (phAIP) area as well as the third topographic map of numerosity‐selective neurons at the post‐central sulcus (NPC3) of the left parietal cortex. A further region of interest analysis of the group‐average data showed that at the single voxel level the latter area, more than any other parietal or occipito‐temporal numerosity map, favored numerosity of OAs. These results suggest that phAIP processes the identity of OMAs, while neighboring NPC3 likely processes the numerosity of the identified OAs.

The Effect of Media Intervention to Stabilize Psychological Distress

본 연구는 심리적 안정화에 효과적인 영상 개발을 위해 영상자극에 따른 정서생리적 반응 지표 차이를 검증하였다. 12명의 대학(원)생을 단일종류 영상 집단과 혼합종류 영상 집단에 무선할당하여 처치를 실시하고, 뇌파와 심박수, 정서, 상태불안을 측정하여 통계 검증하였다. 그 결과, 단일경관 처치에 따라 정적정서 및 부적정서 총합, 개별단어 중 흥미진진한, 과민한, 원기왕성한, 신경질적인, 주의깊은, 열정적인, 활기찬이 유의한 차이를 나타냈다. 뇌파의 경우, Alpha파, Slow Alpha파, High Beta파, Gamma파가 증가하고, Theta파, Ratio Alpha to High Beta파는 감소하였다. 이로써 단일 자연경관 영상으로 긍정정서가 고양되고, 기억의 통합 및 주의와 같은 인지적 기능 향상을 확인하였다. 혼합경관집단에서는 정적정서 및 부적정서 총합, 개별단어 중 흥미진진한, 신경질적인, 적대적인, 두려운, 그리고 상태불안이 유의한 차이가 있었다. 뇌파는 Slow Alpha파, Ratio Alpha to High Beta가 감소하였고, Fast Alpha, Low Beta, Mid Beta, High Beta, Slow Theta파는 증가하였다. 이로써 혼합경관 영상이내면으로의 집중과 부적정서 감소에 효과가 있음을 확인하였다. 심박수는 변화가 유의하지 않았다. 이후 본 연구의 의의와 제한점, 후속 연구에 대한 시사점을 논하였다.The purpose of this study was to develop a video intervention tool for psychological stabilization by verifying differences in psychophysiological indicators (positive affect, negative affect, state anxiety, EEG, HRV) in response to video stimulation. Twelve university students were randomly assigned to the group “Only” where participants watched single-typed video stimuli or to the group “Mix” where they watched mixed-typed video stimuli. Before and after each video stimulus, the participants completed the PANAS scale and STAI-X scale, and HRV and EEG was recorded during the video stimulation. For the group “Only”, a total score of positive and negative affect, an individual score of interested , irritable , inspired , nervous, attentive , enthusiastic , and active , and the brain index such as ‘RT’ at Fp1, Fp2, and T5, ‘RA’ and ‘RSA’ at F7, ‘RG’ at Fp1, Fp2 and T3, ‘RHB’ at C3 and C4, ‘RAHB’ at Fz showed significant difference between video stimuli. For the group “Mix”, significant differences were found in a total score of positive and negative affect, interested, nervous, hostile, afraid, state anxiety, and brain index such as ‘RSA’ at P3 and Fz, ‘RHB’ and ‘RAHB’ at P3, ‘RFA’ at F8 and O2, ‘RLB’ at F8, F4 and P4, ‘RMB’ at Fp2, ‘RST’ at Cz, and asymmetry between P3 and P4. No significant difference was found for HRV.

Mentalising and conversation-following in autism.

Some people with autism spectrum disorders have been observed to experience difficulties with making correct inferences in conversations in social situations. However, the nature and origin of their problem is rarely investigated. This study used manipulations of video stimuli to investigate two questions. The first question was whether it is the number of people involved in social situations, that is, the source of problems in following conversations, or whether it is the increased mentalising demands required to comprehend interactions between several people. The second question asked was whether the nature and pattern of the errors that autism spectrum disorder participants show are the same as typically developing people make when they make an error. In total, 43 typically developed adults and 30 adults diagnosed with autism spectrum disorder were studied. We found that it was the amount of mentalising required, rather than the number of people involved, which caused problems for people with autism spectrum disorder in following conversations. Furthermore, the autism spectrum disorder participants showed a more heterogeneous pattern of errors, showing less agreement among themselves than the typically developed group as to which test items were hardest. So, fully understanding the observed behaviour consequent upon weakness in mentalising ability in people with autism spectrum disorders requires consideration of factors other than mentalising.People with autism spectrum disorders sometimes report difficulties with following observed conversations in social situations, especially those where several people are interacting with each other. But this has rarely been investigated directly. This study determines whether people with autism spectrum disorders do indeed have problems following observed conversations even when they perform well on IQ tests and investigates two possible reasons for any difficulty found: (1) some people may have a problem integrating stimuli from multiple speakers; (2) following a conversation between many people might make particularly high demands on mentalising abilities. We used a variety of video clips of people conversing together to investigate these two possibilities in 30 adults diagnosed with autism spectrum disorder and 43 age- and IQ-matched typical-developing adults. We found that it was the amount of mentalising required, rather than the number of people involved, which caused problems for people with autism spectrum disorder in following conversations. Furthermore, when the autism spectrum disorder participants made a mistake, the error they made was frequently not the same error that typically developed participants made, and the autism spectrum disorder population made a more varied set of errors than the typically developed participants. Together, these results suggest that people with autism spectrum disorders observe significant problems with following conversations between many people when they contain a lot of mentalising material, but where they do make a mistake, the conclusions they draw from the conversation they are observing may have a more complex cause than an impairment in mentalising alone.

Detecting Personality Traits Using Inter-Hemispheric Asynchrony of the Brainwaves.

Affective personality traits have been associated with a risk of developing mental and cognitive disorders and can be informative for early detection and management of such disorders. However, conventional personality trait detection is often biased and unreliable, as it depends on the honesty of the subjects when filling out the lengthy questionnaires. In this paper, we propose a method for objective detection of personality traits using physiological signals. Subjects are shown affective images and videos to evoke a range of emotions. The electrical activity of the brain is captured using EEG during this process and the multi-channel EEG data is processed to compute the inter-hemispheric asynchrony of the brainwaves. The most discriminative features are selected and then used to build a machine learning classifier, which is trained to predict 16 personality traits. Our results show high predictive accuracy for both image and video stimuli individually, and an improvement when the two stimuli are combined, achieving a 95.49% accuracy. Most of the selected discriminative features were found to be extracted from the alpha frequency band. Our work shows that personality traits can be accurately detected with EEG data, suggesting possible use in practical applications for early detection of mental and cognitive disorders.

An open-source toolbox for measuring dynamic video framerates and synchronizing video stimuli with neural and behavioral responses

BackgroundResearchers rely on the specified capabilities of their hardware and software even though, in reality, these capabilities are often not achieved. Considering that the number of experiments examining neural oscillations has increased steadily, easy-to-implement tools for testing the capabilities of hardware and software are necessary. New methodWe present an open-source MATLAB toolbox, the Schultz Cigarette Burn Toolbox (SCiBuT) that allows users to benchmark the capabilities of their visual display devices and align neural and behavioral responses with veridical timing of visual stimuli. Specifically, the toolbox marks the corners of the display with black or white squares to indicate the timing of the onset of static images and the timing of frame changes within videos. Using basic hardware (i.e., a photodiode, an Arduino microcontroller, and an analogue input box), the light changes in the corner of the screen can be captured and synchronized with EEG recordings and/or behavioral responses. ResultsWe demonstrate that the SCiBuT is sensitive to framerate inconsistencies and provide examples of hardware setups that are suboptimal for measuring fine timing. Finally, we show that inconsistencies in framerate during video presentation can affect EEG oscillations. ConclusionsThe SCiBuT provides tools to benchmark framerates and frame changes and to synchronize frame changes with neural and behavioral signals. This is the first open-source toolbox that can perform these functions. The SCiBuT can be freely downloaded (www.band-lab.com/scibut) and be used during experimental trials to improve the accuracy and precision of timestamps to ensure videos are presented at the intended framerate.

Targeting humor to cope with an unpleasant emotion: Disgust

Rooted both in cognitive and emotional aspects, humor has generally been assumed to function to facilitate coping with a variety of social, emotional, and cognitive challenges and threats. Humor is intricately linked as a function of distancing one from negative stimuli, but can also foster changing one’s perspective on negative stimuli through reappraisal. The current study explored the mechanisms underlying the relationship between humor and negative stimuli. Disgusting things often evoke amusement along with revulsion in a unique mixed emotional state. It was predicted that when participants connect a humorous experience with disgusting situations, they would better be able to handle that disgusting situation. One hundred and twenty undergraduates were presented with video stimuli to evoke emotions of amusement, disgust, a combination of both amusement and disgust, or no emotion, and then rated their willingness to respond to a matching disgusting situation. Supporting our predictions, disgust-evoking videos produced lower willingness and amusement-evoking videos produced higher willingness. However, our main hypothesis was not supported because the combined amusement-disgust video did not increase willingness significantly beyond that of the disgust-only condition. A secondary post hoc analysis based on actual emotional responses to the videos regardless of assigned condition, supported the finding that amusement increased willingness to respond to the disgust situation, but did not support the main hypothesis. Difficulties in carrying out the study in a precise manner and future directions are discussed.

A novel strategy for classifying perceived video quality using electroencephalography signals

Video streaming through the Internet is abundant nowadays. While video quality is continuously demanded, monitoring users’ quality of experience (QoE) is essential when watching video contents. QoE can be evaluated directly through subjective assessment which is the human ground truths; however, such assessment is generally expensive and time consuming, and cannot be implemented in real time. QoE can also be evaluated by video quality models; however, the evaluation is fully based on video contents but human physical states cannot be taken into account. To tackle the limitations, detection of a prominent electroencephalography (EEG) signal feature namely P300 correlated to QoE can be used, when users are viewing videos. P300 is a positive deflection pulse that appears around 300 ms after a significant video distortion appears. QoE can be indicated by P300 pulses. However, the captured EEG signal is generally contaminated with noise. Strong noise generates P300 although video carries no distortion. Hence, detections of P300 patterns are not accurate. In this paper, a double classifier consisting of a first and second classifier is proposed. The first classifier attempts to determine whether the captured EEG feature is abnormal or not, where the abnormal caption behaves opposite to the normal P300 characteristic when showing the distorted video. The second classifier is developed to perform classifications for either normal or abnormal features. We evaluate the performance of the proposed double classifier based on the EEG samples, which are captured when showing video stimuli to participants. The proposed classifier is implemented by the support vector machine and logistic regression, which are commonly used for detection of EEG patterns and are computationally much simpler than deep learning. The performance of the proposed classifier is compared to those of the single classifiers, which determine the QoE directly when the EEG signal is given. Cross-validations showed that generally more than 5% improvement can be achieved by the proposed double classifier. Statistical tests indicate that the proposed double classifier can generally obtain better classification rates than solely using the single classifier at a 97.5% confidence level.

Autonomy Raises Productivity: An Experiment Measuring Neurophysiology.

Employees have been given increasing autonomy to work from home, from virtual offices, and during travel. Understanding why autonomy affects work behaviors has relied to date on self-reported data in which employees may consciously or unconsciously misattribute their own causal actions. We designed a neuroscience experiment to investigate the mechanisms through which greater autonomy affects individual and team performance and if this had an effect on mood. Participants (N = 100) were shown a three-min video that described the productivity impact of greater autonomy at work (treatment) or the productivity benefits of work-flow management software. Electrodermal responses were captured to measure physiologic effort and were related to the video stimuli, productivity, and mood. The treatment group had a 5.2% (p = 0.047) greater average productivity and 31% (p = 0.000) higher positive affect after the video than the control group average. Productivity was directly related to the physiologic effort put into the task for both the treatment and control groups, but the video prime did not increase effort compared to the control. The impact of physiologic effort on productivity continued to hold when controlling for participants’ intrinsic motivation. We also found that individual productivity was associated with an increase in positive affect, while group productivity increased positive affect only for those in the treatment group. Our findings indicate that increased perceived autonomy can significantly improve individual and group productivity and that this can have a salubrious impact on mood, but the neurologic mechanism through which this occurs remains to be identified.

Tuning Support Vector Machines for Improving Four-Class Emotion Classification in Virtual Reality (VR) using Heart Rate Features

The main objective of this paper is to conduct three experiments using Support Vector Machine (SVM) with different parameter settings to find and compare the accuracy of each SVM setting. Heart rate (HR) signals were collected with a medical-grade wearable heart rate monitor from Empatica (E4 Wristband) and processed using the Empatica Realtime Monitor application during this investigation. HR was employed as the method to capture the test subjects’ physiological signals via plethysmography. The three experiments were conducted using a wrist-worn monitor to gain HR signal, and a VR Headset for subjects to view 360 degrees video stimuli. A total of 10 subjects participated in this experiment. Data from the 10 subjects were then processed with Python with SVM. The data was classified for four distinct emotion classes using both inter-subject classification and intra-subject classification testing approaches, with inter-subject classification yielding an accuracy of 53.39% while intra-subject classification ranges from 56.92% to 86.15%. These results demonstrate the potential of achieving higher accuracy results using different parameter settings via the use of HR as the input feature to the machine learning classifier, which appears to be a promising sensor modality for four-class emotion classification in virtual reality using wearable technology.

Can Climate Skeptics Be Convinced? The Effect of Nature Videos on Environmental Concern

Much research has demonstrated that videos can function as primers or nudges that influence attitudes and behaviors. Studies to date suggest that this includes influence over individual pro-environmental attitudes. However, the existing evidence all stems from samples comprised of university students. In this paper, we describe the results of a randomized online experiment in a sample of 468 climate skeptics. We presented 3-min nature documentary videos that highlighted either the beauty of nature, the endangerment of nature by humans, or a mixture of both. The results suggest that the mixed stimulus video, which shows first the beauty of nature and then its endangerment by humans does indeed increase environmental concern by almost half a standard deviation. However, none of the video treatments increased donations to pro-environmental organizations. Still, the results suggest that nudging by video also works in samples of climate skeptics, which demonstrates the external validity of former findings.

Do 15-month-old infants prefer helpers? A replication of Hamlin et al. (2007).

Hamlin et al. found in 2007 that preverbal infants displayed a preference for helpers over hinderers. The robustness of this finding and the conditions under which infant sociomoral evaluation can be elicited has since been debated. Here, we conducted a replication of the original study, in which we tested 14- to 16-month-olds using a familiarization procedure with three-dimensional animated video stimuli. Unlike previous replication attempts, ours uniquely benefited from detailed procedural advice by Hamlin. In contrast with the original results, only 16 out of 32 infants (50%) in our study reached for the helper; thus, we were not able to replicate the findings. A possible reason for this failure is that infants' preference for prosocial agents may not be reliably elicited with the procedure and stimuli adopted. Alternatively, the effect size of infants’ preference may be smaller than originally estimated. The study addresses ongoing methodological debates on the replicability of influential findings in infant cognition.

Why Are Scientific Experts Perceived as Trustworthy? Emotional Assessment within TV and YouTube Videos

Due to the rise of the Internet, the effects of different science communication formats in which experts appear cannot be neglected in communication research. Through their emotional and more comprehensible communication ‘sciencetubers’—who frequently differ from the stereotypical image of scientists as white, old men—may have a considerable effect on the public’s perceived trustworthiness of scientists as well as their trust in science. Thus, this study aims to extend trust and trustworthiness research to consider the role of emotion in science communication in the context of emerging online video content. Therefore, perceived trustworthiness was examined in an experimental online survey of 155 people aged 18–80. We considered different potential influencing variables for trustworthiness (expertise, integrity, benevolence) and used six different video stimuli about physics featuring scientific experts. The video stimuli varied according to format (TV interviews vs. YouTube videos), gender (male vs. female), and age of the experts depicted (old vs. young). The results suggest that: (1) Scientific experts appearing in TV interviews are perceived as more competent but not higher in integrity or benevolence than sciencetubers—while scientists interviewed on TV are regarded as typical scientists, sciencetubers stand out for their highly professional communication abilities (being entertaining and comprehensible); (2) these emotional assessments of scientists are important predictors of perceived trustworthiness; and (3) significantly mediate the effect of the stimulus (TV interview vs. YouTube video) on all dimensions of perceived trustworthiness of scientific experts.

Electrophysiological indicators of gesture perception.

Electroencephalography (EEG) activity in the mu frequency band (8-13Hz) is suppressed during both gesture performance and observation. However, it is not clear if or how particular characteristics within the kinematic execution of gestures map onto dynamic changes in mu activity. Mapping the time course of gesture kinematics onto that of mu activity could help understand which aspects of gestures capture attention and aid in the classification of communicative intent. In this work, we test whether the timing of inflection points within gesture kinematics predicts the occurrence of oscillatory mu activity during passive gesture observation. The timing for salient features of performed gestures in video stimuli was determined by isolating inflection points in the hands' motion trajectories. Participants passively viewed the gesture videos while continuous EEG data was collected. We used wavelet analysis to extract mu oscillations at 11Hz and at central electrodes and occipital electrodes. We used linear regression to test for associations between the timing of inflection points in motion trajectories and mu oscillations that generalized across gesture stimuli. Separately, we also tested whether inflection point occurrences evoked mu/alpha responses that generalized across participants. Across all gestures and inflection points, and pooled across participants, peaks in 11Hz EEG waveforms were detected 465 and 535ms after inflection points at occipital and central electrodes, respectively. A regression model showed that inflection points in the motion trajectories strongly predicted subsequent mu oscillations ([Formula: see text]<0.01); effects were weaker and non-significant for low (17Hz) and high (21Hz) beta activity. When segmented by inflection point occurrence rather than stimulus onset and testing participants as a random effect, inflection points evoked mu and beta activity from 308 to 364ms at central electrodes, and broad activity from 226 to 800ms at occipital electrodes. The results suggest that inflection points in gesture trajectories elicit coordinated activity in the visual and motor cortices, with prominent activity in the mu/alpha frequency band and extending into the beta frequency band. The time course of activity indicates that visual processing drives subsequent activity in the motor cortex during gesture processing, with a lag of approximately 80ms.

Factors affecting trust in high-vulnerability human-robot interaction contexts: A structural equation modelling approach

The current research proposed and tested a structural equation model (SEM) that describes hypothesized relationships among factors affecting trust in human-robot interaction (HRI) such as trustworthiness, human-likeness, intelligence, perfect automation schema (PAS), and affect. A video stimulus depicting an autonomous guard robot interacting with humans was employed as a stimulus via Amazon's Mechanical Turk to recruit 233 participants. Human-related and robot-related metrics were found to affect trustworthiness that subsequently affected trust. In particular, ability (as a trustworthiness facet) was a dominant factor affecting trust in HRI. Integrity was found to mediate the relationships between robot- and human-related metrics and trustworthiness. This study also showed a correlation between intelligence and trustworthiness, as well as between PAS and trustworthiness. The findings of the present study have significant implications for both theory and practice on factors and levels that affect trust in HRI.

Analysis of Facial Expressions Made While Watching a Video Eliciting Compassion.

The aim of the study was to describe the spontaneous facial expressions elicited by viewers of a compassionate video in terms of the respondents’ muscular activity of single facial action units (AUs). We recruited a convenience sample of 111 undergraduate psychology students, aged 18-25 years ( M = 20.53; SD = 1.62) to watch (at home alone) a short video stimulus eliciting compassion, and we recorded the respondents’ faces using webcams. We used both a manual analysis, based on the Facial Action Coding System, and an automatic analysis of the holistic recognition of facial expressions as obtained through EmotionID software. Manual facial analysis revealed that, during the compassionate moment of the video stimulus, AUs 1 = inner-brow raiser, 4 = brow lowerer, 7 = lids tight, 17 = chin raiser, 24 = lip presser, and 55 = head tilt left occurred more often than other AUs. These same AUs also occurred more often during the compassionate moment than during the baseline recording. Consistent with these findings, automatic facial analysis during the compassionate moment showed that anger occurred more often than other emotions; during the baseline moment, contempt occurred less often than other emotions. Further research is necessary to fully describe the facial expression of compassion.

A Multiplex Connectivity Map of Valence-Arousal Emotional Model

high number of studies have already demonstrated an electroencephalography (EEG)-based emotion recognition system with moderate results. Emotions are classified into discrete and dimensional models. We focused on the latter that incorporates valence and arousal dimensions. The mainstream methodology is the extraction of univariate measures derived from EEG activity from various frequencies classifying trials into low/high valence and arousal levels. Here, we evaluated brain connectivity within and between brain frequencies under the multiplexity framework. We analyzed an EEG database called DEAP that contains EEG responses to video stimuli and users’ emotional self-assessments. We adopted a dynamic functional connectivity analysis under the notion of our dominant coupling model (DoCM). DoCM detects the dominant coupling mode per pair of EEG sensors, which can be either within frequencies coupling (intra) or between frequencies coupling (cross-frequency). DoCM revealed an integrated dynamic functional connectivity graph (IDFCG) that keeps both the strength and the preferred dominant coupling mode. We aimed to create a connectomic mapping of valence-arousal map via employing features derive from IDFCG. Our results outperformed previous findings succeeding to predict in a high accuracy participants’ ratings in valence and arousal dimensions based on a flexibility index of dominant coupling modes.

Motion tracking in developmental research: Methods, considerations, and applications.

In this chapter, we explore the use of motion tracking methodology in developmental research. With motion tracking, also called motion capture, human movements can be precisely recorded and analyzed. Motion tracking provides developmental researchers with objective measurements of motor and (socio-)cognitive development. It can further be used to create carefully-controlled stimuli videos and can offer means of measuring development outside of the lab. We discuss three types of motion tracking that lend themselves to developmental applications. First, marker-based systems track optical or electromagnetic markers or sensors placed on the body and offer high accuracy measurements. Second, markerless methods entail image processing of videos to track the movement of bodies without participants being hindered by physical markers. Third, inertial motion tracking measures three-dimensional movements and can be used in a variety of settings. The chapter concludes by examining three example topics from developmental literature in which motion tracking applications have contributed to our understanding of human development.

The temporal dynamics of infants' joint attention: Effects of others' gaze cues and manual actions

Infants' development of joint attention shows significant advances between 9 and 12 months of age, but we still need to learn much more about how infants coordinate their attention with others during this process. The objective of this study was to use eye tracking to systematically investigate how 8- and 12-month-old infants as well as adults dynamically select their focus of attention while observing a social partner demonstrate infant-directed actions. Participants were presented with 16 videos of actors performing simple infant-directed actions from a first-person perspective. Looking times to faces as well as hands-and-objects were calculated for participants at each age, and developmental differences were observed, although all three groups looked more at hands-and-objects than at faces. In order to assess whether visual attention was coordinated with the actors' behaviors, we compared participants looking at faces and objects in response to gaze direction as well as infant-directed actions vs. object-directed actions. By presenting video stimuli that involved continuously changing actions, we were able to document that the likelihood of joint attention changes in both real and developmental time. Overall, adults and 12-month-old infants' visual attention was modulated by gaze cues as well as actions, whereas this was only partially true for 8-month-old infants. Our results reveal that joint attention is not a monolithic process nor does it develop all at once.