How biological attention mechanisms improve task performance in a large-scale visual system model.
Ontology highlight
ABSTRACT:
SUBMITTER: Lindsay GW
PROVIDER: S-EPMC6207429 | biostudies-literature | 2018 Oct
REPOSITORIES: biostudies-literature
Publications
How biological attention mechanisms improve task performance in a large-scale visual system model.
Lindsay Grace W GW Miller Kenneth D KD
eLife 20181001
How does attentional modulation of neural activity enhance performance? Here we use a deep convolutional neural network as a large-scale model of the visual system to address this question. We model the feature similarity gain model of attention, in which attentional modulation is applied according to neural stimulus tuning. Using a variety of visual tasks, we show that neural modulations of the kind and magnitude observed experimentally lead to performance changes of the kind and magnitude obse ...[more]
Similar Datasets
Project description:In the present study, we tested a visual feedback triggering system based on real-time tracking of response time (RT) in a sustained attention task. In our task, at certain points, brief visual feedback epochs were presented without interrupting the task itself. When these feedback epochs were performance-linked-meaning that they were triggered because participants were responding more quickly than usual-RTs were slowed after the presentation of feedback. However, visual feedback epochs displayed at predetermined times that were independent of participants' performance did not slow RTs. Results from a second experiment support the idea that this is not simply a return to baseline that would have occurred had the feedback not been presented, but instead suggest that the feedback itself was effective in altering participants' responses. In a third experiment, we replicated this result across with both written word feedback and visual symbolic feedback, as well as in cases where the participant was explicitly told that the feedback was linked to their performance. All together, these data provide insight into potential mechanisms for detecting and disrupting lapses in sustained attention without interrupting a continuous task.
| S-EPMC10226944 | biostudies-literature
Project description:Extant literature suggests that performance on visual arrays tasks reflects limited-capacity storage of visual information. However, there is also evidence to suggest that visual arrays task performance reflects individual differences in controlled processing. The purpose of this study is to empirically evaluate the degree to which visual arrays tasks are more closely related to memory storage capacity or measures of attention control. To this end, we conducted new analyses on a series of large data sets that incorporate various versions of a visual arrays task. Based on these analyses, we suggest that the degree to which the visual arrays is related to memory storage ability or effortful attention control may be task-dependent. Specifically, when versions of the task require participants to ignore elements of the target display, individual differences in controlled attention reliably provide unique predictive value. Therefore, at least some versions of the visual arrays tasks can be used as valid indicators of individual differences in attention control. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
| S-EPMC9045334 | biostudies-literature
Project description:Consistent spatial patterns of coherent activity, representing large-scale networks, have been reliably identified in multiple populations. Most often, these studies have examined "stationary" connectivity. However, there is a growing recognition that there is a wealth of information in the time-varying dynamics of networks which has neural underpinnings, which changes with age and disease and that supports behavior. Using factor analysis of overlapping sliding windows across 25 participants with Parkinson disease (PD) and 21 controls (ages 41-86), we identify factors describing the covarying correlations of regions (dynamic connectivity) within attention networks and the default mode network, during two baseline resting-state and task runs. Cortical regions that support attention networks are affected early in PD, motivating the potential utility of dynamic connectivity as a sensitive way to characterize physiological disruption to these networks. We show that measures of dynamic connectivity are more reliable than comparable measures of stationary connectivity. Factors in the dorsal attention network (DAN) and fronto-parietal task control network, obtained at rest, are consistently related to the alerting and orienting reaction time effects in the subsequent Attention Network Task. In addition, the same relationship between the same DAN factor and the alerting effect was present during tasks. Although reliable, dynamic connectivity was not invariant, and changes between factor scores across sessions were related to changes in accuracy. In summary, patterns of time-varying correlations among nodes in an intrinsic network have a stability that has functional relevance.
| S-EPMC4313397 | biostudies-literature
Project description:Older adults show higher dual task performance decrements than younger adults. While this is assumed to be related to attentional capacity reductions, the precise affected functions are not specified. Such specification is, however, possible based on the "theory of visual attention" (TVA) which allows for modeling of distinct attentional capacity parameters. Furthermore, it is unclear whether older adults show qualitatively different attentional effects or whether they show the same effects as younger adults experience under more challenging conditions. By varying the complexity of the secondary task, it is possible to address this question. In our study, participants performed a verbal whole report of briefly presented letter arrays. TVA-based fitting of report performance delivered parameters of visual threshold t0, processing speed C, and visual short-term memory (VSTM) storage capacity K. Furthermore, participants performed a concurrent motor task consisting of continuous tapping of a (simple or complex) sequence. Both TVA and tapping tasks were performed under single and dual task conditions. Two groups of 30 younger adults each performed either the simple or complex tapping, and a group of 30 older adults performed the simple tapping condition. In older participants, VSTM storage capacity declined under dual task conditions. While no such effect was found in younger subjects performing the simple tapping sequence under dual task conditions, the younger group performing the complex tapping task under dual task conditions also showed a significant VSTM capacity reduction. Generally, no significant effect on other TVA parameters or on tapping accuracy was found. Comparable goodness-of-fit measures were obtained for the TVA modeling data in single and dual tasks, indicating that tasks were executed in a qualitatively similar, continuous manner, although quantitatively less efficiently under dual- compared to single-task conditions. Taken together, our results show that the age-specific effects of motor-cognitive dual task interference are reflected by a stronger decline of VSTM storage capacity. They support an interpretation of VSTM as central attentional capacity, which is shared across visual uptake and concurrent motor performance. Capacity limits are reached earlier, and already under lower motor task complexity, in older compared to younger adults.
| S-EPMC6129777 | biostudies-literature
Project description:Selective attention is an important component of cognitive control and is essential for day-to-day functioning. The Simon task is a common test of visual selective attention that has been widely used to probe response selection, inhibition and cognitive control. However, to date, there is a dearth of literature that has focused on the oscillatory dynamics serving task performance in the selective attention component of this task. In this study, 32 healthy adults (mean age: 33.09 years, SD: 7.27 years) successfully completed a modified version of the Simon task during magnetoencephalography. All magnetoencephalographic data were pre-processed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach, and peak task-related neural activity was extracted to examine the temporal dynamics. Across both congruent and Simon conditions, our results indicated robust decreases in alpha (8-12 Hz) activity in the bilateral occipital regions and cuneus during task performance, while increases in theta (3-6 Hz) oscillatory activity were detected in regions of the dorsal frontoparietal attention network, including the dorsolateral prefrontal cortex, frontal eye fields and insula. Lastly, whole-brain condition-wise analyses showed Simon interference effects in the theta range in the superior parietal region and the alpha range in the posterior cingulate and inferior frontal cortices. These findings provide network-specific insights into the oscillatory dynamics serving visual selective attention.
| S-EPMC10162684 | biostudies-literature
Project description:Humans use saccades to inspect objects of interest with the foveola, the small region of the retina with highest acuity. This process of visual exploration is normally studied over large scenes. However, in everyday tasks, the stimulus within the foveola is complex, and the need for visual exploration may extend to this smaller scale. We have previously shown that fixational eye movements, in particular microsaccades, play an important role in fine spatial vision. Here, we investigate whether task-driven visual exploration occurs during the fixation pauses in between large saccades. Observers judged the expression of faces covering approximately 1°, as if viewed from a distance of many meters. We use a custom system for accurately localizing the line of sight and continually track gaze position at high resolution. Our findings reveal that active spatial exploration, a process driven by the goals of the task, takes place at the foveal scale. The scanning strategies used at this scale resemble those used when examining larger scenes, with idiosyncrasies maintained across spatial scales. These findings suggest that the visual system possesses not only a coarser priority map of the extrafoveal space to guide saccades, but also a finer-grained priority map that is used to guide microsaccades once the region of interest is foveated.
| S-EPMC6431186 | biostudies-literature
Project description:Summary:MODE-TASK, a novel and versatile software suite, comprises Principal Component Analysis, Multidimensional Scaling, and t-Distributed Stochastic Neighbor Embedding techniques using Molecular Dynamics trajectories. MODE-TASK also includes a Normal Mode Analysis tool based on Anisotropic Network Model so as to provide a variety of ways to analyse and compare large-scale motions of protein complexes for which long MD simulations are prohibitive. Beside the command line function, a GUI has been developed as a PyMOL plugin. Availability and implementation:MODE-TASK is open source, and available for download from https://github.com/RUBi-ZA/MODE-TASK. It is implemented in Python and C++. It is compatible with Python 2.x and Python 3.x and can be installed by Conda. Supplementary information:Supplementary data are available at Bioinformatics online.
| S-EPMC6198866 | biostudies-literature
Project description:The general research question of the present study was to assess the impact of visually salient online adverts on children's task-oriented internet use. In order to answer this question, an experimental study was constructed in which 9- and 12-year-old Swedish children were asked to solve a number of tasks while interacting with a mockup website. In each trial, web adverts in several saliency conditions were presented. By both measuring children's task accuracy, as well as the visual processing involved in solving these tasks, this study allows us to infer how two types of visual saliency affect children's attentional behavior, and whether such behavioral effects also impacts their task performance. Analyses show that low-level visual features and task relevance in online adverts have different effects on performance measures and process measures respectively. Whereas task performance is stable with regard to several advert saliency conditions, a marked effect is seen on children's gaze behavior. On the other hand, task performance is shown to be more sensitive to individual differences such as age, gender and level of gaze control. The results provide evidence about cognitive and behavioral distraction effects in children's task-oriented internet use caused by visual saliency in online adverts. The experiment suggests that children to some extent are able to compensate for behavioral effects caused by distracting visual stimuli when solving prospective memory tasks. Suggestions are given for further research into the interdiciplinary area between media research and cognitive science.
| S-EPMC3921552 | biostudies-literature
Project description:Advances in the development of high-throughput screening and automated chemistry have rapidly accelerated the production of chemical and biological data, much of them freely accessible through literature aggregator services such as ChEMBL and PubChem. Here, we explore how to use this comprehensive mapping of chemical biology space to support the development of large-scale quantitative structure-activity relationship (QSAR) models. We propose a new deep learning consensus architecture (DLCA) that combines consensus and multitask deep learning approaches together to generate large-scale QSAR models. This method improves knowledge transfer across different target/assays while also integrating contributions from models based on different descriptors. The proposed approach was validated and compared with proteochemometrics, multitask deep learning, and Random Forest methods paired with various descriptors types. DLCA models demonstrated improved prediction accuracy for both regression and classification tasks. The best models together with their modeling sets are provided through publicly available web services at https://predictor.ncats.io .
| S-EPMC8381874 | biostudies-literature
Project description:The fast development of high throughput genotyping has opened up new possibilities in genetics while at the same time producing considerable data handling issues. TheSNPpit is a database system for managing large amounts of multi panel SNP genotype data from any genotyping platform. With an increasing rate of genotyping in areas like animal and plant breeding as well as human genetics, already now hundreds of thousand of individuals need to be managed. While the common database design with one row per SNP can manage hundreds of samples this approach becomes progressively slower as the size of the data sets increase until it finally fails completely once tens or even hundreds of thousands of individuals need to be managed. TheSNPpit has implemented three ideas to also accomodate such large scale experiments: highly compressed vector storage in a relational database, set based data manipulation, and a very fast export written in C with Perl as the base for the framework and PostgreSQL as the database backend. Its novel subset system allows the creation of named subsets based on the filtering of SNP (based on major allele frequency, no-calls, and chromosomes) and manually applied sample and SNP lists at negligible storage costs, thus avoiding the issue of proliferating file copies. The named subsets are exported for down stream analysis. PLINK ped and map files are processed as in- and outputs. TheSNPpit allows management of different panel sizes in the same population of individuals when higher density panels replace previous lower density versions as it occurs in animal and plant breeding programs. A completely generalized procedure allows storage of phenotypes. TheSNPpit only occupies 2 bits for storing a single SNP implying a capacity of 4 mio SNPs per 1MB of disk storage. To investigate performance scaling, a database with more than 18.5 mio samples has been created with 3.4 trillion SNPs from 12 panels ranging from 1000 through 20 mio SNPs resulting in a database of 850GB. The import and export performance scales linearly with the number of SNPs and is largely independent of panel and database size. Import speed is around 6 mio SNPs/sec, export between 60 and 120 mio SNPs/sec. Being command line based, imports and exports can easily be integrated into pipelines. TheSNPpit is available under the Open Source GNU General Public License (GPL) Version 2.
| S-EPMC5079601 | biostudies-literature