Interactions between multisensory integration and attention were studied using a combined audiovisual streaming design and a rapid serial visual presentation paradigm. Event-related potentials (ERPs) following audiovisual objects (AV) were compared with the sum of the ERPs following auditory (A) and visual objects (V). Integration processes were expressed as the difference between these AV and (A + V) responses and were studied while attention was directed to one or both modalities or directed elsewhere. Results show that multisensory integration effects depend on the multisensory objects being fully attended--that is, when both the visual and auditory senses were attended. In this condition, a superadditive audiovisual integration effect was observed on the P50 component. When unattended, this effect was reversed; the P50 components of multisensory ERPs were smaller than the unisensory sum. Additionally, we found an enhanced late frontal negativity when subjects attended the visual component of a multisensory object. This effect, bearing a strong resemblance to the auditory processing negativity, appeared to reflect late attention-related processing that had spread to encompass the auditory component of the multisensory object. In conclusion, our results shed new light on how the brain processes multisensory auditory and visual information, including how attention modulates multisensory integration processes.

One finding in attention research is that visual and auditory attention mechanisms are linked together. Such a link would predict a central, amodal capacity limit in processing visual and auditory stimuli. Here we show that this is not the case. Letter streams were accompanied by asynchronously presented streams of auditory, visual, and audiovisual objects. Either the letter streams or the visual, auditory, or audiovisual parts of the object streams were attended. Attending to various aspects of the objects resulted in modulations of the letter-stream-elicited steady-state evoked potentials (SSVEPs). SSVEPs were larger when auditory objects were attended than when either visual objects alone or when auditory and visual object stimuli were attended together. SSVEP amplitudes were the same in the latter conditions, indicating that attentional capacity between modalities is larger than attentional capacity within one and the same modality.

Threatening faces have a privileged status in the brain, which can be reflected in a processing advantage. However, this effect varies among individuals, even healthy adults. For example, one recent study showed that fearful face detection sensitivity correlated with trait anxiety in healthy adults (Japee, Crocker, Carver, Pessoa, & Ungerleider, 2009). Here, we expanded upon those findings by investigating whether intersubject variability in fearful face detection is also associated with state anxiety, as well as more broadly with other traits related to anxiety. To measure fearful face detection sensitivity, we employed a masked face paradigm where the target face was presented for only 33 ms and was immediately followed by a neutral face mask. Subjects then rated their confidence in detecting either fear or no fear in the target face. Fearful face detection sensitivity was calculated for each subject using signal detection theory. Replicating previous results, we found a significant positive correlation between trait anxiety and fearful face detection sensitivity. However, this behavioral advantage did not correlate with state anxiety. We also found that fearful face detection sensitivity correlated with other personality measures, including neuroticism and harm avoidance. Our data suggest that fearful face detection sensitivity varies parametrically across the healthy population, is associated broadly with personality traits related to anxiety, but remains largely unaffected by situational fluctuations in anxiety. These results underscore the important contribution of anxiety-related personality traits to threat processing in healthy adults.

We examined the relationship between COMT Val158Met genotype and temporal lobe volumes, including the caudate as a control region. 31 healthy subjects completed 1.5T brain MRI and genotyping. After controlling for demographics, Val158 allele homozygotes exhibited significantly smaller temporal lobe and hippocampal volumes, with a trend for smaller amygdala volumes.

The amygdala is hypothesized to play a critical role in mood regulation, yet its involvement in bipolar disorder remains unclear. The aim of the present study was to compare measurements of amygdala volumes in a relatively large sample of bipolar disorder patients and healthy controls ranging in age from 18 to 49 yrs. Fifty-four adult patients meeting DSM-IV criteria for bipolar disorder and 41 healthy controls matched for age, sex, and education underwent structural 1.5 Tesla MRI scanning. Volumetric measurements of the amygdala were obtained using a manual region-of-interest tracing method with software that allowed simultaneous visualization of the amygdala in three orthogonal planes. The anterior head of the hippocampus was removed in the sagittal plane prior to amygdala volumetry measurement. Multiple regression analysis was computed on amygdala volume measurements as a function of diagnosis, age, sex, and cerebral volume. Bipolar patients showed an age-related reduction of amygdala volume but controls did not. Among bipolar subjects, amygdala volume was unrelated to medication history. There were no significant hemispheric or sex interactions with the main effects. Results support a role for amygdala dysfunction in bipolar disorder which appears most robustly in older relative to younger adult patients. Differential aging effects in bipolar disorder may compromise amygdala integrity and contribute to mood dysregulation.

Knowing how an individual responds to sleep deprivation is a requirement for developing personalized fatigue management strategies. Here we describe and validate the 2B-Alert App, the first mobile application that progressively learns an individual's trait-like response to sleep deprivation in real time, to generate increasingly more accurate individualized predictions of alertness. We incorporated a Bayesian learning algorithm within the validated Unified Model of Performance to automatically and gradually adapt the model parameters to an individual after each psychomotor vigilance test. We implemented the resulting model and the psychomotor vigilance test as a smartphone application (2B-Alert App), and prospectively validated its performance in a 62-hr total sleep deprivation study in which 21 participants used the app to perform psychomotor vigilance tests every 3 hr and obtain real-time individualized predictions after each test. The temporal profiles of reaction times on the appconducted psychomotor vigilance tests were well correlated with and as sensitive as those obtained with a previously characterized psychomotor vigilance test device.The app progressively learned each individual's trait-like response to sleep deprivation throughout the study, yielding increasingly more accurate predictions of alertness for the last 24 hr of total sleep deprivation as the number of psychomotor vigilance tests increased. After only 12 psychomotor vigilance tests, the accuracy of the model predictions was comparable to the peak accuracy obtained using all psychomotor vigilance tests. With the ability to make real-time individualized predictions of the effects of sleep deprivation on future alertness, the 2B-Alert App can be used to tailor personalized fatigue management strategies, facilitating self-management of alertness and safety in operational and non-operational settings. K E Y W O R D Salertness, caffeine, individualized predictions, psychomotor vigilance test, sleep, smartphoneThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Caffeine appears to have limited efficacy for maintaining alertness and wakefulness across 5 days of sleep restriction. Perhaps more importantly, there may be recovery costs associated with caffeine use following conditions of prolonged sleep loss.

Stimuli that signal threat show considerable variability in the extent to which they enhance behavior, even among healthy individuals. However, the neural underpinning of this behavioral variability is not well understood. By manipulating expectation of threat in an fMRI study of fearful vs. neutral face categorization, we uncovered a network of areas underlying variability in threat processing in healthy adults. We explicitly altered expectation by presenting face images at three different expectation levels: 80%, 50%, and 20%. Subjects were instructed to report as fast and as accurately as possible whether the face was fearful (signaled threat) or not. An uninformative cue preceded each face by 4 seconds (s). By taking the difference between response times (RT) to fearful compared to neutral faces, we quantified an overall fear RT bias (i.e. faster to fearful than neutral faces) for each subject. This bias correlated positively with late trial fMRI activation (8 s after the face) during unexpected fearful face trials in bilateral ventromedial prefrontal cortex, the left subgenual cingulate cortex, and the right caudate nucleus and correlated negatively with early trial fMRI activation (4 s after the cue) during expected neutral face trials in bilateral dorsal striatum and the right ventral striatum. These results demonstrate that the variability in threat processing among healthy adults is reflected not only in behavior but also in the magnitude of activation in medial prefrontal and striatal regions that appear to encode affective value.