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The ability to allocate visual attention is known to be impaired in patients with mild traumatic brain injury (mTBI). In the present study, we investigated a possible neural correlate of this cognitive deficit by examining the pupil response of patients with mTBI whilst performing a modified Posner visual search task. Two experiments were conducted in which the target location was either not cued (Experiment 1) or cued (Experiment 2). Additionally, in Experiment 2, the type of cue (endogenous vs exogenous cue) and cue validity were treated as independent variables. In both experiments, search efficiency was varied by changing shape similarity between target and distractor patterns. The reaction time required to judge whether the target was present or absent and pupil dilation metrics, particularly the pupil dilation latency (PDL) and amplitude (PDA), were measured. Thirteen patients with chronic mTBI and 21 age-, sex-, and IQ -matched controls participated in the study. In Experiment 1, patients with mTBI displayed a similar PDA for both efficient and inefficient search conditions, while control participants had a significantly larger PDA in inefficient search conditions compared to efficient search conditions. As cognitive load is positively correlated with PDA, our findings suggest that mTBI patients were unable to apply more mental effort whilst performing visual search, particularly if the task is difficult when visual search is inefficient. In Experiment 2, when the target location was cued, patients with mTBI displayed no significant pupil dilation response to the target regardless of the efficiency of the search, nor whether the cue was valid or invalid. These results contrasted with control participants, who were additionally sensitive to the validity of the cue in which PDA was smaller for cue-valid conditions than invalid conditions, particularly for efficient search conditions. Pupillometry provided further evidence of attention allocation deficits following mTBI. [ABSTRACT FROM AUTHOR]

Observers adopt attentional control setting (ACS) based on their goals; stimuli that match the current goal will capture attention, whereas stimuli that do not match the current goal will not. In the present study, we revisited the role of VWM in maintaining ACSs capable of guiding attentional capture. Participants completed a Posner cueing task while either remembering a colour (Experiments 1a/1b) or searching for a colour (Experiments 2/3). To encourage the use of VWM, the colour changed on each trial. Results indicate that merely remembering a colour using VWM did not prevent memory non-matching colours from capturing attention (Experiments 1a/1b). Conversely, when participants searched for one colour, VWM supported an ACS that eliminated capture by non-matching colours (Experiments 2/3), though not if participants searched for two colours (Experiment 3). We conclude that VWM can maintain an ACS of one searched-for item that is capable of guiding attentional capture. [ABSTRACT FROM AUTHOR]

Our attention is constantly captured and guided by visual and/or auditory inputs. One key contributor to selecting relevant information from the environment is reward prospect. Intriguingly, while both multimodal signal processing and reward effects on attention have been widely studied, research on multimodal reward signals is lacking. Here, we investigated this using a Posner task featuring peripheral cues of different modalities (audiovisual/visual/auditory), reward prospect (reward/no-reward), and cue-target stimulus-onset asynchronies (SOAs 100–1,300 ms). We found that audiovisual and visual reward cues (but not auditory ones) enhanced cue-validity effects, albeit with different time courses (Experiment 1). While the reward-modulated validity effect of visual cues was pronounced at short SOAs, the effect of audiovisual reward cues emerged at longer SOAs. Follow-up experiments exploring the effects of visual (Experiment 2) and auditory (Experiment 3) reward cues in isolation showed that reward modulated performance only in the visual condition. This suggests that the differential effect of visual and auditory reward cues in Experiment 1 is not merely a result of the mixed cue context, but confirms that visual reward cues have a stronger impact on attentional guidance in this paradigm. Taken together, it seems that adding an auditory reward cue to the inherently dominant visual one led to a shift/extension of the validity effect in time – instead of increasing its amplitude. While generally being in line with a multimodal cuing benefit, this specific pattern highlights that different reward signals are not simply combined in a linear fashion but lead to a qualitatively different process. [ABSTRACT FROM AUTHOR]

• An explainable machine-learning approach was successfully applied to reveal spatiotemporal characteristics of cortical activities underlying impaired visuospatial attention in idiopathic REM sleep behavior disorder (iRBD). • A convolutional neural network (CNN) was devised to discriminate cortical current source activities of iRBD patients from those of normal controls. • The results suggest that the recognized dysfunction in visuospatial attention of iRBD patients originates from neural activity impairment in relevant cortical regions. Idiopathic rapid eye movement sleep behavior disorder (iRBD) is a prodromal stage of neurodegeneration and is associated with cortical dysfunction. The purpose of this study was to investigate the spatiotemporal characteristics of cortical activities underlying impaired visuospatial attention in iRBD patients using an explainable machine-learning approach. An algorithm based on a convolutional neural network (CNN) was devised to discriminate cortical current source activities of iRBD patients due to single-trial event-related potentials (ERPs), from those of normal controls. The ERPs from 16 iRBD patients and 19 age- and sex-matched normal controls were recorded while the subjects were performing visuospatial attentional task, and converted to two-dimensional images representing current source densities on flattened cortical surface. The CNN classifier was trained based on overall data, and then, a transfer learning approach was applied for the fine-tuning to each patient. The trained classifier yielded high classification accuracy. The critical features for the classification were determined by layer-wise relevance propagation, so that the spatiotemporal characteristics of cortical activities that were most relevant to cognitive impairment in iRBD were revealed. These results suggest that the recognized dysfunction in visuospatial attention of iRBD patients originates from neural activity impairment in relevant cortical regions and may contribute to the development of useful iRBD biomarkers based on neural activity. [ABSTRACT FROM AUTHOR]