A rightward shift in the visuospatial attention vector with healthy aging

The study of lateralised visuospatial attention bias in non-clinical samples has revealed a systematic group-level leftward bias (pseudoneglect), possibly as a consequence of right hemisphere dominance for visuospatial attention. Pseudoneglect appears to be modulated by age, with a reduced or even reversed bias typically present in elderly participants. It has been suggested that this shift in bias may arise due to disproportionate aging of the right hemisphere and/or an increase in complementary functional recruitment of the left hemisphere for visuospatial processing. In this study, we report rightward shifts in subjective midpoint judgement relative to healthy young participants whilst elderly participants performed a computerized version of the landmark task (in which they had to judge whether a transection mark appeared closer to the right or left end of a line) on three different line lengths. This manipulation of stimulus properties led to a similar behavioural pattern in both the young and the elderly: a rightward shift in subjective midpoint with decreasing line length, which even resulted in a systematic rightward bias in elderly participants for the shortest line length (1.98° of visual angle). Overall performance precision for the task was lower in the elderly participants regardless of line length, suggesting reduced landmark task discrimination sensitivity with healthy aging. This rightward shift in the attentional vector with healthy aging is likely to result from a reduction in right hemisphere resources/dominance for attentional processing in elderly participants. The significant rightward bias in the elderly for short lines may even suggest a reversal of hemisphere dominance in favour of the left hemisphere/right visual field under specific conditions

Automated annotation of multimedia audio data with affective labels for information management

The emergence of digital multimedia systems is creating many new opportunities for rapid access to huge content archives. In order to fully exploit these information sources, the content must be annotated with significant features. An important aspect of human interpretation of multimedia data, which is often overlooked, is the affective dimension. Such information is a potentially useful component for content-based classification and retrieval. Much of the affective information of multimedia content is contained within the audio data stream. Emotional features can be defined in terms of arousal and valence levels. In this study low-level audio features are extracted to calculate arousal and valence levels of multimedia audio streams. These are then mapped onto a set of keywords with predetermined emotional interpretations. Experimental results illustrate the use of this system to assign affective annotation to multimedia data

An affect-based video retrieval system with open vocabulary querying

Content-based video retrieval systems (CBVR) are creating new search and browse capabilities using metadata describing significant features of the data. An often overlooked aspect of human interpretation of multimedia data is the affective dimension. Incorporating affective information into multimedia metadata can potentially enable search using this alternative interpretation of multimedia content. Recent work has described methods to automatically assign affective labels to multimedia data using various approaches. However, the subjective and imprecise nature of affective labels makes it difficult to bridge the semantic gap between system-detected labels and user expression of information requirements in multimedia retrieval. We present a novel affect-based video retrieval system incorporating an open-vocabulary query stage based on WordNet enabling search using an unrestricted query vocabulary. The system performs automatic annotation of video data with labels of well defined affective terms. In retrieval annotated documents are ranked using the standard Okapi retrieval model based on open-vocabulary text queries. We present experimental results examining the behaviour of the system for retrieval of a collection of automatically annotated feature films of different genres. Our results indicate that affective annotation can potentially provide useful augmentation to more traditional objective content description in multimedia retrieval

Music-reading expertise modulates the visual span for English letters but not Chinese characters.

Recent research has suggested that the visual span in stimulus identification can be enlarged through perceptual learning. Since both English and music reading involve left-to-right sequential symbol processing, music-reading experience may enhance symbol identification through perceptual learning particularly in the right visual field (RVF). In contrast, as Chinese can be read in all directions, and components of Chinese characters do not consistently form a left-right structure, this hypothesized RVF enhancement effect may be limited in Chinese character identification. To test these hypotheses, here we recruited musicians and nonmusicians who read Chinese as their first language (L1) and English as their second language (L2) to identify music notes, English letters, Chinese characters, and novel symbols (Tibetan letters) presented at different eccentricities and visual field locations on the screen while maintaining central fixation. We found that in English letter identification, significantly more musicians achieved above-chance performance in the center-RVF locations than nonmusicians. This effect was not observed in Chinese character or novel symbol identification. We also found that in music note identification, musicians outperformed nonmusicians in accuracy in the center-RVF condition, consistent with the RVF enhancement effect in the visual span observed in English-letter identification. These results suggest that the modulation of music-reading experience on the visual span for stimulus identification depends on the similarities in the perceptual processes involved

The Effects of Chronic Sleep Deprivation on Sustained Attention: A Study of Brain Dynamic Functional Connectivity

It is estimated that about 35-40% of adults in the U.S. suffer from insufficient sleep. Chronic sleep deprivation has become a prevalent phenomenon because of contemporary lifestyle and work-related factors. Sleep deprivation can reduce the capabilities and efficiency of attentional performance by impairing perception, increasing effort to maintain concentration, as well as introducing vision disturbance. Thus, it is important to understand the neural mechanisms behind how chronic sleep deprivation impairs sustained attention. In recent years, more attention has been paid to the study of the integration between anatomically distributed and functionally connected brain regions. Functional connectivity has been widely used to characterize brain functional integration, which measures the statistical dependency between neurophysiological events of the human brain. Further, evidence from recent studies has shown the non-stationary nature of brain functional connectivity, which may reveal more information about the human brain. Thus, the objective of this thesis is to investigate the effects of chronic sleep deprivation on sustained attention from the perspective of dynamic functional connectivity. A modified spatial cueing paradigm was used to assess human sustained attention in rested wakefulness and chronic sleep deprivation conditions. Partial least squares approach was applied to distinguish brain functional connectivity for the experimental conditions. With the integration of a sliding-window approach, dynamic patterns of brain functional connectivity were identified in two experimental conditions. The brain was modeled as a series of dynamic functional networks in each experimental condition. Graph theoretic analysis was performed to investigate the dynamic properties of brain functional networks, using network measures of clustering coefficient and characteristics path length. In the chronic sleep deprivation condition, a compensation mechanism between highly clustered organization and ineffective adaptability of brain functional networks was observed. Specifically, a highly clustered organization of brain functional networks was illustrated with a large clustering coefficient. This organization suggested that brain utilizes more connections to maintain attention in the chronic sleep deprivation condition. A smaller impact of clustering coefficient variation on characteristics path lengths indicated an ineffective adaptability of brain functional networks in the chronic sleep deprivation condition. In the rested wakefulness condition, brain functional networks showed the small-world topology in general, with the average small-world topology index larger than one. Small-world topology was identified as an optimal network structure with the balance between local information processing and global integration. Given the fluctuating values of the index over time, small-world brain networks were observed in most cases, indicating an effective adaptability of the human brain to maintain the dominance of small-world networks in the rested wakefulness condition. On the contrary, given that the average small-world topology index was smaller than one, brain functional networks generally exhibited random network structure. From the perspective of dynamic functional networks, even though there were few cases showing small-world brain networks, brain functional networks failed to maintain the dominance of small-world topology in the chronic sleep deprivation condition. In conclusion, to the best of our knowledge this thesis was the first to investigate the effects of chronic sleep deprivation on sustained attention from the perspective of dynamic brain functional connectivity. A compensation mechanism between highly clustered organization and ineffective adaptability of brain functional networks was observed in the chronic sleep deprivation condition. Furthermore, chronic sleep deprivation impaired sustained attention by reducing the effectiveness of brain functional networks\u27 adaptability, resulting in the disrupted dominance of small-world brain networks