Ageing and selective inhibition of irrelevant information in an attention-demanding rapid serial visual presentation task.

Attention involves both an ability to selectively focus on relevant information and simultaneously ignore irrelevant information (i.e. inhibitory control). Many factors impact inhibitory control such as individual differences, relative timing of stimuli presentation, distractor characteristics, and participant age. Previous research with young adults responding to an attention-demanding rapid serial visual presentations of pictures superimposed with task-irrelevant words evaluated the extent to which unattended information may be subject to inhibitory control. Surprise recognition tests following the rapid serial visual presentation task showed that recognition for unattended words presented with non-targets (i.e. non-aligned or 'NA' words) during the rapid serial visual presentation task were recognised at chance levels. However, when the unattended words were infrequently paired with the attended picture targets (i.e. target-aligned or 'TA' words), recognition rates were significantly below chance and significantly lower compared to NA words, suggesting selective inhibitory control for the previously unattended TA words. The current study adapted this paradigm to compare healthy younger and older adults' ability to engage in inhibitory control. In line with previous research, younger adults demonstrated selective inhibition with recognition rates for TA words significantly lower than NA words and chance, while NA words were recognised at chance levels. However, older adults showed no difference in recognition rates between word types (TA versus NA). Rather all items were recognised at rates significantly below chance suggesting inhibited recognition for all unattended words, regardless of when they were presented during the primary task. Finally, older adults recognised significantly fewer NA words compared to young adults. These findings suggest that older adults may experience a decline in their ability to selectively inhibit the processing of irrelevant information, while maintaining the capacity to exercise global inhibition over unattended lexical information.

Fast variational alignment of non-flat 1D displacements for applications in neuroimaging.

BACKGROUND: In the context of signal analysis and pattern matching, alignment of 1D signals for the comparison of signal morphologies is an important problem. For image processing and computer vision, 2D optical flow (OF) methods find wide application for motion analysis and image registration and variational OF methods have been continuously improved over the past decades. NEW METHOD: We propose a variational method for the alignment and displacement estimation of 1D signals. We pose the estimation of non-flat displacements as an optimization problem with a similarity and smoothness term similar to variational OF estimation. To this end, we can make use of efficient optimization strategies that allow real-time applications on consumer grade hardware. RESULTS: We apply our method to two applications from functional neuroimaging: The alignment of 2-photon imaging line scan recordings and the denoising of evoked and event-related potentials in single trial matrices. We can report state of the art results in terms of alignment quality and computing speeds. EXISTING METHODS: Existing methods for 1D alignment target mostly constant displacements, do not allow native subsample precision or precise control over regularization or are slower than the proposed method. CONCLUSIONS: Our method is implemented as a MATLAB toolbox and is online available. It is suitable for 1D alignment problems, where high accuracy and high speed is needed and non-constant displacements occur.