Decoding Color Visual Working Memory from EEG Signals Using Graph Convolutional Neural Networks

Color has an important role in object recognition and visual working memory (VWM). Decoding color VWM in the human brain is helpful to understand the mechanism of visual cognitive process and evaluate memory ability. Recently, several studies showed that color could be decoded from scalp electroencephalogram (EEG) signals during the encoding stage of VWM, which process visible information with strong neural coding. Whether color could be decoded from other VWM processing stages, especially the maintaining stage which processes invisible information, is still unknown. Here, we constructed an EEG color graph convolutional network model (ECo-GCN) to decode colors during different VWM stages. Based on graph convolutional networks, ECo-GCN considers the graph structure of EEG signals and may be more efficient in color decoding. We found that (1) decoding accuracies for colors during the encoding, early, and late maintaining stages were 81.58%, 79.36%, and 77.06%, respectively, exceeding those during the pre-stimuli stage (67.34%), and (2) the decoding accuracy during maintaining stage could predict participants’ memory performance. The results suggest that EEG signals during the maintaining stage may be more sensitive than behavioral measurement to predict the VWM performance of human, and ECo-GCN provides an effective approach to explore human cognitive function.

Using Behavior Science to Maximize Human Performance

Authors use behavior science to help organizations maximize human performance through a cost-effective and sustainable approach. Such approach is based on transformational leaders and employees’ engagement, so they embrace a humanized management system by conviction, not by imposition. This paper shows how to use organizational psychology principles in real case applications, resulting in holistic business improvements, including financial, safety and service quality performance. The authors developed the Engineering Human Performance (EHP) methodology, by improving the Behavior Engineering Methodology (Lopez, et. al., 2020) to help organizations achieve outstanding and sustainable levels of human performance. Over the last ten years, this methodology was successfully applied to more than 50 business processes in an oilfield services company. The EHP four-stages process uses frontline employees’ wisdom to identify sources of behavioral variance, measure adherence to expected behaviors and formulate changes to the operational context to pursue high levels of procedural adherence, sustainably. EHP incorporated statistic models to demonstrate its significant impact to business results, using a fit-for-purpose digital platform. A combination of a coaching program for managers to embrace a leading with purpose approach (Sinek, 2020), and workshops with the front-line associates, generate a healthy flow of communication across the organization. The leading with purpose program improves managers’ leadership by voluntarily selecting and engineering transformational behaviors they adapt and adopt to improve the effectiveness of their leadership style. The impact of the program is measured for statistical significance by applying the Multi-Factor Leadership Questionnaire (Boss, Avolio, 1996) before the coaching program starts, and 90 days after the last session. Workshops with front-line associates use scientific principles to understand the sources of behavioral variance and formulate intervention plans that drive procedural adherence by conviction, not by imposition. An innovative element of EHP is the ‘behavior empowerment center (BEC)’. The BEC coordinates the systematic measurement of adherence to critical behaviors in the front-line, captures and verifies statistical significance of the data, analyzes trends, and prepares reports depicting the levels of behavioral adherence, so crews receive soon, certain, and positive feedback on a regular basis. This feedback loop elicits levels of adherence above 90%, sustainably, and eliminates losses associated to behavioral variance. The BEC uses a unique digital platform designed to bring consistency to the feedback loop to front-line employees and managers. A case study is used to exemplify how EHP is being applied by a major rig company, to improve human performance in workover operations. The paper illustrates the remarkable results of the leading with purpose program and describes the Stages 1 (select processes that are causing loss), 2 (behavior analysis), 3 (baseline and intervention) and Stage 4 (scale-up) of the EHP methodology. Authors consider that EHP offers an innovative, and cost-effective approach to helping organizations maximize human performance, in a systematic and sustainable manner. The application of the methodology shall not be limited to the oil and gas industry, as the focus on incorporating the human factor to inconsistently applied processes is affecting many industries, if not all. The main challenge faced by authors in the implementation of the methodology is management commitment. Some managers expect improvement programs to bring immediate results, which could undermine the sustainability of the benefits. EHP grants sustainable improvements, provided the organization is committed to scale-up the program until results are significant. Achieving these milestones require time (from 6 months to 2 years), resources, and persistency. The leading with purpose program has proven effective in getting the proper levels of management commitment, to support EHP and deliver outstanding results. The paper shows a statistically significant improvement in the leadership style of the management team and how it is helping the business of the case-study company. As for the way forward, authors are exploring options to incorporate artificial intelligence into the behavioral measurement, not to replace the face-to-face interactions, but to increase the accuracy of the behavioral measurement and speed up the feedback loop.

Environmental Enrichment Ameliorates Anxiety-Like Behavior in Rats without Altering Plasma Corticosterone Level

BACKGROUND: Anxiety disorder is one of the most common psychiatric problems. Prolonged stress gives rise to anxiety-like behavior in animals. Environmental interventions influence the outcome of anxiety treatment. Environmental enrichment (EE) can modulate brain’s structure and function. AIM: The objective of the study was to evaluate EE effects on anxiety-like behavior and corticosterone (CORT) level after unpredictable chronic mild stress (UCMS). METHODS: A total of 28 rats were assigned into four groups randomly: Control, UCMS, UCMS+EE, and UCMS+fluoxetine. UCMS, EE, and fluoxetine were given for 21 days. Anxiety behavior was measured on day 22nd using Elevated Plus Maze. Behavioral measurement was based on the total time spent and total entries onto open and closed arms. CORT was measured using ELISA. RESULTS: UCMS increased anxiety-like behavior as seen from reduced number of entries and time spent in open arms as well as increased number of entries and time spent in in closed arms in UCMS group than control. Rats in EE group spent more time and made more entries in the open arms than UCMS group (both p = 0.002). Anxiolytic effect of EE was stronger than fluoxetine. Plasma CORT level among groups did not differ significantly (p = 0.351). CONCLUSION: EE can ameliorate stress-induced anxiety-like behavior without affecting CORT level.

Automated Pose Estimation in Primates

Understanding the behavior of primates is important for primatology, for psychology, and for biology more broadly. It is also important for biomedicine, where primates are an important model organism, and whose behavior is often an important variable of interest. Our ability to rigorously quantify behavior has, however, long been limited. On one hand, we can rigorously quantify low-information measures like preference, looking time, and reaction time; on the other, we can use more gestalt measures like behavioral categories tracked via ethogram, but at high cost and with high variability. Recent technological advances have led to a major revolution in behavioral measurement that offers affordable and scalable rigor. Specifically, digital video cameras and automated pose tracking software can provide measures of full body position (i.e., pose) of primates over time (i.e., behavior) with high spatial and temporal resolution. Pose-tracking technology in turn can be used to infer behavioral states, such as eating, sleeping, and mating. We call this technological approach behavioral imaging. In this review, we situate the behavioral imaging revolution in the history of the study of behavior, argue for investment in and development of analytical and research techniques that can profit from the advent of the era of big behavior, and propose that primate centers and zoos will take on a more central role in relevant fields of research than they have in the past.

Proof of Principle: Is a Pre-treatment Behavior Approach Test a Potential Predictor for Response to Intensive Residential Treatment in Patients With Treatment Refractory Obsessive Compulsive Disorder?

Patients with severe and treatment refractory obsessive compulsive disorder (OCD) are usually referred to a specialized center for intensive residential treatment (IRT), consisting of exposure and response prevention (EX/RP), pharmacotherapy and additional therapies. About 50% of the patients does not respond to IRT. Currently we are not able to predict treatment response. If we were to have predictive tools, we could personify treatment at an earlier stage. Recent studies show that early adherence and willingness to EX/RP and low avoidance during EX/RP measured during treatment were associated with treatment response. In this observational study willingness and ability of patients with severe and treatment refractory OCD (N = 58) is conceptualized by a behavioral measurement, measured before the start of 12 weeks of IRT, using a Behavior Approach Test (BAT), as opposed to relying on self-report measurements. A medium or strong association between pre-treatment performance on the BAT and treatment response would justify next steps to test the BAT as a predictive tool for IRT. Results of regression analyses showed that there is a significant association between the performance on the BAT and change in OCD symptom severity after IRT. However, the effect-size is too small to use the BAT in its current form as predictor in clinical practice. The principle of the association between pre-treatment behaviorally measured willingness and ability to fully engage in EX/RP, and treatment response has now been proven. To ultimately design a predictive tool, future research is needed to refine a behavioral measurement of pre-treatment willingness and ability.

Capturing Behavior in Small Doses: A Review of Comparative Research in Evaluating Thin Slices for Behavioral Measurement

Thin slices are used across a wide array of research domains to observe, measure, and predict human behavior. This article reviews the thin-slice method as a measurement technique and summarizes current comparative thin-slice research regarding the reliability and validity of thin slices to represent behavior or social constructs. We outline decision factors in using thin-slice behavioral coding and detail three avenues of thin-slice comparative research: (1) assessing whether thin slices can adequately approximate the total of the recorded behavior or be interchangeable with each other (representativeness); (2) assessing how well thin slices can predict variables that are different from the behavior measured in the slice (predictive validity), and (3) assessing how interpersonal judgment accuracy can depend on the length of the slice (accuracy-length validity). The aim of the review is to provide information researchers may use when designing and evaluating thin-slice behavioral measurement.

Complete the triangulation: Quantifying differential fear conditioning with a noninterfering and sensitive behavioral measure along with self-report and physiological measures

According to the multi-component view, emotion is expressed through subjective feelings and thoughts, physiological activation, and behavioral responses. In human fear conditioning research, the former two are much more popular than the third category. One concern is that concurrent behavioral probes may interfere with the conditioning process. To allow triangulation of emotion research through simultaneous employment of subjective, physiological, and behavioral measurement, it is necessary to find behavioral measures that meet the criteria of causing no interference while being sensitive to conditioning. In this study, a basic visual attention task was examined in terms of its impact on differential fear conditioning as measured by both subjective (i.e., self-reported fear, shock estimation) and physiological (i.e., skin conductance response/SCR) expression; and its ability to detect fear conditioning indicated by a reaction time (RT) or accuracy difference between the two conditioned stimuli (CS+ vs CS-). While participants in the probe group (n = 86) completed differential fear conditioning with the behavioral task, those in the no-probe group (n = 76) underwent conditioning by itself. Based on self-reported fear, shock estimation, and SCR, both groups successfully acquired differential fear with no apparent between-group difference in the degree of conditioning. In the probe group, RT but not accuracy exhibited a difference between CS+ and CS-. These findings suggest that the selected visual attention task qualifies as a non-interfering behavioral probe and produces a sensitive measure of differential conditioning. Exploratory individual analyses also revealed significant relationships between the above measures.

Psychometric evaluation of the Functional Analytic Psychotherapy Intimacy Scale in obsessive-compulsive and related disorders

Functional Analytic Psychotherapy (FAP) is a contextual behavioral therapy that targets specific ideographic behaviors related to interpersonal functioning and intimacy. There is a scarcity of measures specifically focused on behavioral measurement of intimacy as well as limited studies that examine intimacy in obsessive-compulsive and related disorders (OCRDs). Leonard and colleagues (2014) created the Functional Analytic Psychotherapy Intimacy Scale (FAPIS). The purpose of this study was to investigate the validity of the FAPIS in evaluating those with OCRDs. The FAPIS and other measures of intimacy were administered to 549 nonreferred adults endorsing OCRD symptoms. Several confirmatory factor analyses were conducted to assess the best fitting factor structure, and convergent validity and divergent validity were also assessed. Given the psychometric properties of the FAPIS in this sample, future research may be helpful in assessing if the FAPIS would be beneficial in measuring change related to intimacy when working with people with OCRDs.

Saliency-based Rhythmic Coordination of Perceptual Predictions

Objects, shown explicitly or held in mind internally, compete for limited processing resources. Recent studies have demonstrated that attention samples locations and objects rhythmically. Interestingly, periodic sampling not only operates over objects in the same scene but also occurs for multiple perceptual predictions that are held in attention for incoming inputs. However, how the brain coordinates perceptual predictions that are endowed with different levels of bottom–up saliency information remains unclear. To address the issue, we used a fine-grained behavioral measurement to investigate the temporal dynamics of processing of high- and low-salient visual stimuli, which have equal possibility to occur within experimental blocks. We demonstrate that perceptual predictions associated with different levels of saliency are organized via a theta-band rhythmic course and are optimally processed in different phases within each theta-band cycle. Meanwhile, when the high- and low-salient stimuli are presented in separate blocks and thus not competing with each other, the periodic behavioral profile is no longer present. In summary, our findings suggest that attention samples and coordinates multiple perceptual predictions through a theta-band rhythm according to their relative saliency. Our results, in combination with previous studies, advocate the rhythmic nature of attentional process.

Are Cyber Attackers Thinking Fast and Slow? Exploratory Analysis Reveals Evidence of Decision-Making Biases in Red Teamers

We report on whether cyber attacker behaviors contain decision making biases. Data from a prior experiment were analyzed in an exploratory fashion, making use of think-aloud responses from a small group of red teamers. The analysis provided new observational evidence of traditional decision-making biases in red team behaviors (confirmation bias, anchoring, and take-the-best heuristic use). These biases may disrupt red team decisions and goals, and simultaneously increase their risk of detection. Interestingly, at least part of the bias induction may be related to the use of cyber deception. Future directions include the development of behavioral measurement techniques for these and additional cognitive biases in cyber operators, examining the role of attacker traits, and identifying the conditions where biases can be induced successfully in experimental conditions.