Lost in Time and Space: States of High Arousal Disrupt Implicit Acquisition of Spatial and Sequential Context Information

Biased cognition during high arousal states is a relevant phenomenon in a variety of topics: from the development of post-traumatic stress disorders or stress-triggered addictive behaviors to forensic considerations regarding crimes of passion. Recent evidence indicates that arousal modulates the engagement of a hippocampus-based “cognitive” system in favor of a striatum-based “habit” system in learning and memory, promoting a switch from flexible, contextualized to more rigid, reflexive responses. Existing findings appear inconsistent, therefore it is unclear whether and which type of context processing is disrupted by enhanced arousal. In this behavioral study, we investigated such arousal-triggered cognitive-state shifts in human subjects. We validated an arousal induction procedure (three experimental conditions: violent scene, erotic scene, neutral control scene) using pupillometry (Preliminary Experiment, n = 13) and randomly administered this method to healthy young adults to examine whether high arousal states affect performance in two core domains of contextual processing, the acquisition of spatial (spatial discrimination paradigm; Experiment 1, n = 66) and sequence information (learned irrelevance paradigm; Experiment 2, n = 84). In both paradigms, spatial location and sequences were encoded incidentally and both displacements when retrieving spatial position as well as the predictability of the target by a cue in sequence learning changed stepwise. Results showed that both implicit spatial and sequence learning were disrupted during high arousal states, regardless of valence. Compared to the control group, participants in the arousal conditions showed impaired discrimination of spatial positions and abolished learning of associative sequences. Furthermore, Bayesian analyses revealed evidence against the null models. In line with recent models of stress effects on cognition, both experiments provide evidence for decreased engagement of flexible, cognitive systems supporting encoding of context information in active cognition during acute arousal, promoting reduced sensitivity for contextual details. We argue that arousal fosters cognitive adaptation towards less demanding, more present-oriented information processing, which prioritizes a current behavioral response set at the cost of contextual cues. This transient state of behavioral perseverance might reduce reliance on context information in unpredictable environments and thus represent an adaptive response in certain situations

Clothes make the leader! How leaders can use attire to impact followers' perceptions of charisma and approval

Abstract Sneakers at a product launch, a leather jacket when heads of state meet, sunglasses at a formal reception. While popular media relishes leaders who catch the eye by way of such distinctive fashion, we know little about how this salient daily practice of dress specifically affects perceptions of leaders in their daily business. Addressing this gap, we investigated how dress impacts perceptions and approval of a leader. Firstly, we found formal attire to lead to ascriptions of prototypicality but not charisma (Study 1). Secondly, leaders' charisma and approval were higher when a person's clothing style contrasted their organization's culture (Study 2). Lastly, we replicated the impact of informal clothing on both leader approval and charisma in a sample of CEOs of Fortune 1000 companies (Studies 3 and 4). Findings lend support to the notion that leaders can manipulate their style of attire to actively shape their followers' impressions of themselves

Entrepreneurial leadership: An experimental approach investigating the influence of eye contact on motivation

Small, new firms lack the resources of most larger, established firms, which makes effectively motivating employees challenging. Charismatic leadership is effective in increasing the performance of both groups and entire organizations. Specifically, the impact of charismatic leadership practices on followers stems from nonverbal communication and construed immediacy. The purpose of this study is to investigate the impact of an entrepreneurial leader’s eye contact and smiling on followers’ objective motivation in an experimental leadership situation. A sample of 129 young adults was tested in a 2×2 (nonverbal tactics: high eye contact/low eye contact × high smile/low smile) experimental design. Motivation was measured by objective performance in a motoric reaction time task. The conditions were operationalized by manipulating gaze behavior and facial expressions of the leader in a staged instructional video, showing a start-up entrepreneur attempting to enhance the performance of his employees as part of a competitive comparison. Regardless of whether the leader smiled or not, participants showed faster responses and therefore performed more effectively when the leader maintained high eye contact.These findings support the hypothesis that increased eye contact is a strong nonverbal signal, which in the immediate context of leader-follower interactions, stimulates an increase in performance. In fact, eye contact could induce an increased level of motivational arousal in followers, resulting in improved confidence and self-reference when taking instructions. This study advances the existing research on learnable skills that can be used to appear more charismatic and thus potentially increasing follower performance by adopting simple nonverbal rules in communication behavior. This offers an invaluable and low-cost tool for leaders founding a start-up business

The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers

A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling

Short-term mindfulness meditation training improves antecedents of opportunity recognition

Entrepreneurial venture creation hinges on opportunity recognition, which is enabled by malleable cognitive characteristics such as alertness, creativity, and entrepreneurial self-efficacy. Meditation presents a promising strategy for cultivating these antecedents. In two studies, we examined the immediate effects of meditation on the antecedents of opportunity recognition. In Study 1, a 12-min guided meditation was administered to nascent entrepreneurs in a pre-post within-subjects experimental design. In Study 2, a 15-min breath counting task was used to assess how variations in accuracy and breathing rate shaped differences in outcomes. We found that the intervention in Study 1 had a small effect on alertness (d = 0.44), a medium effect on creativity (d = 0.79), and a large effect on entrepreneurial self-efficacy (d = 0.93). Study 2 revealed a more nuanced relationship, whereby faster breathing rates predicted greater counting accuracy and alertness; in contrast, slower breathing rates and more frequent mind-wandering predicted greater uniqueness in the generated ideas. These findings suggest that meditation is useful for nascent entrepreneurs to prime their minds for successful opportunity recognition. The improvement in creativity may not solely be due to meditative practice itself but rather to the periods of mind-wandering that occur during the practice

Overcoming automaticity through meditation

Objectives Meditation practice has recently moved into applied research to improve cognitive functions. However, it is a multifaceted practice, with focused attention meditation relying on a sharp focus, and open monitoring meditation relying on a diffuse awareness. This study aims to assess the effects of differential alterations of cognition following distinct meditative training and focuses on practitioners’ tendency to fall victim to erroneous automaticity in responding when faced with cognitive conflict. Methods Seventy-three individuals were randomly assigned to one of three intervention groups (internally focused attention meditation, externally focused attention meditation, open monitoring meditation) or a wait list control group. The meditation groups were trained over the course of 4 weeks and eight sessions. Changes in proneness to erroneous automatic responding were tested using two cognitive performance tasks that induce learned or instructed automaticity (Dot Pattern Expectancy paradigm, NEXT-paradigm). Results Overall, meditation training generally improved overcoming learned automaticity (rs?=?.26–.36, ps?=?.002–.031) but not instructed automaticity compared to the control condition. Furthermore, data suggest open monitoring outperformed focused attention in overcoming learned automaticity in one task (rs?=?.31–.56, ps?=?.001–.009). Conclusions Our results provide evidence for meditative training to facilitate practitioners’ ability to select the most appropriate course of action against overlearned habits in light of the peculiarities of their current situation. Open monitoring meditation is a particularly promising avenue for reducing one’s liability to erroneous habits

Quantifying eloquent locations for glioblastoma surgery using resection probability maps

OBJECTIVE Decisions in glioblastoma surgery are often guided by presumed eloquence of the tumor location. The authors introduce the "expected residual tumor volume" (eRV) and the "expected resectability index" (eRI) based on previous decisions aggregated in resection probability maps. The diagnostic accuracy of eRV and eRI to predict biopsy decisions, resectability, functional outcome, and survival was determined. METHODS Consecutive patients with first-time glioblastoma surgery in 2012-2013 were included from 12 hospitals. The eRV was calculated from the preoperative MR images of each patient using a resection probability map, and the eRI was derived from the tumor volume. As reference, Sawaya's tumor location eloquence grades (EGs) were classified. Resectability was measured as observed extent of resection (EOR) and residual volume, and functional outcome as change in Karnofsky Performance Scale score. Receiver operating characteristic curves and multivariable logistic regression were applied. RESULTS Of 915 patients, 674 (74%) underwent a resection with a median EOR of 97%, functional improvement in 71 (8%), functional decline in 78 (9%), and median survival of 12.8 months. The eRI and eRV identified biopsies and EORs of at least 80%, 90%, or 98% better than EG. The eRV and eRI predicted observed residual volumes under 10, 5, and 1 ml better than EG. The eRV, eRI, and EG had low diagnostic accuracy for functional outcome changes. Higher eRV and lower eRI were strongly associated with shorter survival, independent of known prognostic factors. CONCLUSIONS The eRV and eRI predict biopsy decisions, resectability, and survival better than eloquence grading and may be useful preoperative indices to support surgical decisions

On the cutting edge of glioblastoma surgery:where neurosurgeons agree and disagree on surgical decisions

OBJECTIVE: The aim of glioblastoma surgery is to maximize the extent of resection while preserving functional integrity. Standards are lacking for surgical decision-making, and previous studies indicate treatment variations. These shortcomings reflect the need to evaluate larger populations from different care teams. In this study, the authors used probability maps to quantify and compare surgical decision-making throughout the brain by 12 neurosurgical teams for patients with glioblastoma. METHODS: The study included all adult patients who underwent first-time glioblastoma surgery in 2012-2013 and were treated by 1 of the 12 participating neurosurgical teams. Voxel-wise probability maps of tumor location, biopsy, and resection were constructed for each team to identify and compare patient treatment variations. Brain regions with different biopsy and resection results between teams were identified and analyzed for patient functional outcome and survival. RESULTS: The study cohort consisted of 1087 patients, of whom 363 underwent a biopsy and 724 a resection. Biopsy and resection decisions were generally comparable between teams, providing benchmarks for probability maps of resections and biopsies for glioblastoma. Differences in biopsy rates were identified for the right superior frontal gyrus and indicated variation in biopsy decisions. Differences in resection rates were identified for the left superior parietal lobule, indicating variations in resection decisions. CONCLUSIONS: Probability maps of glioblastoma surgery enabled capture of clinical practice decisions and indicated that teams generally agreed on which region to biopsy or to resect. However, treatment variations reflecting clinical dilemmas were observed and pinpointed by using the probability maps, which could therefore be useful for quality-of-care discussions between surgical teams for patients with glioblastoma

Preoperative Brain Tumor Imaging:Models and Software for Segmentation and Standardized Reporting

For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the lack of standardized and automatic methods for tumor detection and generation of clinical reports, incorporating a wide range of tumor characteristics, represents a major hurdle. In this study, we investigate the most occurring brain tumor types: glioblastomas, lower grade gliomas, meningiomas, and metastases, through four cohorts of up to 4,000 patients. Tumor segmentation models were trained using the AGU-Net architecture with different preprocessing steps and protocols. Segmentation performances were assessed in-depth using a wide-range of voxel and patient-wise metrics covering volume, distance, and probabilistic aspects. Finally, two software solutions have been developed, enabling an easy use of the trained models and standardized generation of clinical reports: Raidionics and Raidionics-Slicer. Segmentation performances were quite homogeneous across the four different brain tumor types, with an average true positive Dice ranging between 80 and 90%, patient-wise recall between 88 and 98%, and patient-wise precision around 95%. In conjunction to Dice, the identified most relevant other metrics were the relative absolute volume difference, the variation of information, and the Hausdorff, Mahalanobis, and object average symmetric surface distances. With our Raidionics software, running on a desktop computer with CPU support, tumor segmentation can be performed in 16-54 s depending on the dimensions of the MRI volume. For the generation of a standardized clinical report, including the tumor segmentation and features computation, 5-15 min are necessary. All trained models have been made open-access together with the source code for both software solutions and validation metrics computation. In the future, a method to convert results from a set of metrics into a final single score would be highly desirable for easier ranking across trained models. In addition, an automatic classification of the brain tumor type would be necessary to replace manual user input. Finally, the inclusion of post-operative segmentation in both software solutions will be key for generating complete post-operative standardized clinical reports