Activity in Both Hippocampus and Perirhinal Cortex Predicts the Memory Strength of Subsequently Remembered Information

SummaryIt has been suggested that hippocampal activity predicts subsequent recognition success when recognition decisions are based disproportionately on recollection, whereas perirhinal activity predicts recognition success when decisions are based primarily on familiarity. Another perspective is that both hippocampal and perirhinal activity are predictive of overall memory strength. We tested the relationship between brain activity during learning and subsequent memory strength. Activity in a number of cortical regions (including regions within the “default network”) was negatively correlated with subsequent memory strength, suggesting that this activity reflects inattention or mind wandering (and, consequently, poor memory). In contrast, activity in both hippocampus and perirhinal cortex positively correlated with the subsequent memory strength of remembered items. This finding suggests that both structures cooperate during learning to determine the memory strength of what is being learned

Information Filtering in Electronic Networks of Practice: An fMRI Investigation of Expectation (Dis)confirmation

Online forums sponsored by electronic networks of practice (ENPs) have become an important platform for technology-mediated knowledge exchange, yet relatively little is known about how ENP participants filter and evaluate the information they encounter on these forums. This study integrates perspectives from expectation confirmation theory, prospect theory, and neuroscience research to explore how ENP forum filtering judgments are influenced when expectations formed on the basis of contextual cues are confirmed or disconfirmed by the examination of solution quality. We summarize six different models of expectation confirmation explored in previous IS literature and report the results of a neuroimaging experiment using functional MRI (fMRI) that paired both positive and negative contextual cues with high- and low-quality solutions on a mock ENP forum interface. Results show that evaluation judgments are strongest in conditions where initial contextual cue judgments are confirmed by examination of solution quality except when the perceived expectation-experience gap is large, providing evidence for an assimilation-contrast model of expectation confirmation. We also found neural activation differences for expectation confirmation vs. disconfirmation and, consistent with prospect theory, differences in filtering behaviors with respect to unexpected gains vs. unexpected losses

Using Measures of Risk Perception to Predict Information Security Behavior: Insights from Electroencephalography (EEG)

Users’ perceptions of risks have important implications for information security because individual users’ actions can compromise entire systems. Therefore, there is a critical need to understand how users perceive and respond to information security risks. Previous research on perceptions of information security risk has chiefly relied on self-reported measures. Although these studies are valuable, risk perceptions are often associated with feelings—such as fear or doubt—that are difficult to measure accurately using survey instruments. Additionally, it is unclear how these self-reported measures map to actual security behavior. This paper contributes to this topic by demonstrating that risk-taking behavior is effectively predicted using electroencephalography (EEG) via event-related potentials (ERPs). Using the Iowa Gambling Task, a widely used technique shown to be correlated with real-world risky behaviors, we show that the differences in neural responses to positive and negative feedback strongly predict users’ information security behavior in a separate laboratory-based computing task. In addition, we compare the predictive validity of EEG measures to that of self-reported measures of information security risk perceptions. Our experiments show that self-reported measures are ineffective in predicting security behaviors under a condition in which information security is not salient. However, we show that, when security concerns become salient, self-reported measures do predict security behavior. Interestingly, EEG measures significantly predict behavior in both salient and non-salient conditions, which indicates that EEG measures are a robust predictor of security behavior

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

The impact of immediate breast reconstruction on the time to delivery of adjuvant therapy: the iBRA-2 study

Background: Immediate breast reconstruction (IBR) is routinely offered to improve quality-of-life for women requiring mastectomy, but there are concerns that more complex surgery may delay adjuvant oncological treatments and compromise long-term outcomes. High-quality evidence is lacking. The iBRA-2 study aimed to investigate the impact of IBR on time to adjuvant therapy. Methods: Consecutive women undergoing mastectomy ± IBR for breast cancer July–December, 2016 were included. Patient demographics, operative, oncological and complication data were collected. Time from last definitive cancer surgery to first adjuvant treatment for patients undergoing mastectomy ± IBR were compared and risk factors associated with delays explored. Results: A total of 2540 patients were recruited from 76 centres; 1008 (39.7%) underwent IBR (implant-only [n = 675, 26.6%]; pedicled flaps [n = 105,4.1%] and free-flaps [n = 228, 8.9%]). Complications requiring re-admission or re-operation were significantly more common in patients undergoing IBR than those receiving mastectomy. Adjuvant chemotherapy or radiotherapy was required by 1235 (48.6%) patients. No clinically significant differences were seen in time to adjuvant therapy between patient groups but major complications irrespective of surgery received were significantly associated with treatment delays. Conclusions: IBR does not result in clinically significant delays to adjuvant therapy, but post-operative complications are associated with treatment delays. Strategies to minimise complications, including careful patient selection, are required to improve outcomes for patients

Overcoming interference: An fMRI investigation of pattern separation in the medial temporal lobe

The medial temporal lobe (MTL) supports the formation and retrieval of long-term declarative memories, or memories for facts and everyday events. One challenge posed for this type of memory stems from the highly overlapping nature of common episodes. Within cognitive psychology, it is widely accepted that interference between information learned at different times is a major limitation on memory. In spite of several decades of intense research in the fields of interference theory and the neurobiological underpinnings of declarative memory, there is little direct evidence bearing on how the MTL resolves this interference to form accurate memories of everyday facts and events. Computational models of MTL function have proposed a mechanism in which the MTL, specifically the hippocampus, performs pattern separation, whereby overlapping representations are made less similar. However, there is little evidence bearing on how this process is carried out in the intact human MTL. Using high-resolution fMRI, we conducted a set of experiments that taxed behavioral pattern separation by using highly similar, interfering stimuli in a modified continuous recognition task. Regions within the parahippocampal gyrus demonstrated activity consistent with a “recall to reject” strategy. In contrast and critical to performing the task, activity within the hippocampus distinguished between correctly identified true stimulus repetitions, correctly rejected presentations of similar lure stimuli, and false alarms to similar lures. These data support the computational models’ assertion that the hippocampus plays a key role in pattern separation

Discrete pre-processing step effects in registration-based pipelines, a preliminary volumetric study on T1-weighted images.

Pre-processing MRI scans prior to performing volumetric analyses is common practice in MRI studies. As pre-processing steps adjust the voxel intensities, the space in which the scan exists, and the amount of data in the scan, it is possible that the steps have an effect on the volumetric output. To date, studies have compared between and not within pipelines, and so the impact of each step is unknown. This study aims to quantify the effects of pre-processing steps on volumetric measures in T1-weighted scans within a single pipeline. It was our hypothesis that pre-processing steps would significantly impact ROI volume estimations. One hundred fifteen participants from the OASIS dataset were used, where each participant contributed three scans. All scans were then pre-processed using a step-wise pipeline. Bilateral hippocampus, putamen, and middle temporal gyrus volume estimations were assessed following each successive step, and all data were processed by the same pipeline 5 times. Repeated-measures analyses tested for a main effects of pipeline step, scan-rescan (for MRI scanner consistency) and repeated pipeline runs (for algorithmic consistency). A main effect of pipeline step was detected, and interestingly an interaction between pipeline step and ROI exists. No effect for either scan-rescan or repeated pipeline run was detected. We then supply a correction for noise in the data resulting from pre-processing