Jan Churan

Perception of Temporal Order: The Effects of Age, Sex, and Cognitive Factors

ABSTRACT The present paper investigates the effects of age, sex, and cognitive factors on temporal-order perception. Nine temporal-order tasks were employed using two and four stimuli presented in the auditory and visual modalities. Significantly increased temporal-order thresholds (TOT) in the elderly were found for almost all tasks, while sex differences were only observed for two tasks. Multiple regression analyses show that the performance on most temporal-order tasks can be predicted by cognitive factors, such as speed of fluid reasoning, short-term memory, and attention. However, age was a significant predictor of TOT in three tasks using visual stimuli. We conclude (1) that age-related differences can often be attributed to cognitive factors involved in temporal-order perception, and (2) that the concept of temporal-order perception is more complex than implied by the current models.

Temporal processing and context dependency of phoneme discrimination in patients with aphasia

Standard diagnostic procedures for assessing temporal-processing abilities of adult patients with aphasia have so far not been developed. In our study, temporal-order measurements were conducted using two different experimental procedures to identify a suitable measure for clinical studies. Additionally, phoneme-discrimination abilities were tested on the word, as well as on the sentence level, as a relationship between temporal processing and phoneme-discrimination abilities is assumed. Patients with aphasia displayed significantly higher temporal-order thresholds than control subjects. The detection of an association between temporal processing and speech processing, however, depended on the stimuli and the phoneme-discrimination tasks used. Our results also suggest top-down feedback on phonemic processing.

Stimulus-dependent processing of temporal order

Two distinct conceptualisations of processing mechanisms have been proposed in the research on the perception of temporal order, one that assumes a central-timing mechanism that is involved in the detection of temporal order independent of modality and stimulus type, another one assuming feature-specific mechanisms that are dependent on stimulus properties. In the present study, four different temporal-order judgement tasks were compared to test these two conceptualisations, that is, to determine whether common processes underlie temporal-order thresholds over different modalities and stimulus types or whether distinct processes are related to each task. Measurements varied regarding modality (visual and auditory) and stimulus properties (auditory modality: clicks and tones; visual modality: colour and position). Results indicate that the click and the tone paradigm, as well as the colour and position paradigm, correlate with each other. Besides these intra-modal relationships, cross-modal correlations show dependencies between the click, the colour and the position tasks. Both processing mechanisms seem to influence the detection of temporal order. While two different tones are integrated and processed by a more independent, possibly feature-specific mechanism, a more central, modality-independent timing mechanism contributes to the click, colour and position condition.

Duration discrimination in the context of age, sex, and cognition

It has been proposed that the perception of very short duration is governed by sensory mechanisms, whereas the perception of longer duration depends on cognitive capacities. Four duration discrimination tasks (modalities: visual, auditory; base duration: 100 ms, 1000 ms) were used to study the relation between time perception, age, sex, and cognitive abilities (alertness, visual and verbal working memory, general fluid reasoning) in 100 subjects aged between 21 and 84 years. Temporal acuity was higher (Weber fractions are lower) for longer stimuli and for the auditory modality. Age was related to the visual 100 ms condition only, with lower temporal acuity in elder participants. Alertness was significantly related to auditory and visual Weber fractions for shorter stimuli only. Additionally, visual working memory was a significant predictor for shorter visual stimuli. These results indicate that alertness, but also working memory, are associated with temporal discrimination of very brief duration.

Functional neuroimaging of duration discrimination on two different time scales

Analyses of neural mechanisms of duration processing are essential for the understanding of psychological phenomena which evolve in time. Different mechanisms are presumably responsible for the processing of shorter (below 500 ms) and longer (above 500 ms) events but have not yet been a subject of an investigation with functional magnetic resonance imaging (fMRI). In the present study, we show a greater involvement of several brain regions - including right-hemispheric midline structures and left-hemispheric lateral regions - in the processing of visual stimuli of shorter as compared to longer duration. We propose a greater involvement of lower-level cognitive mechanisms in the processing of shorter events as opposed to higher-level mechanisms of cognitive control involved in longer events.

Region of interest based independent component analysis

The over-complete case remains a difficult problem in the field of independent component analysis (ICA). In this article we combine a technique called “region of interest” (ROI) with a standard complete ICA. We show how to create a mask using ICA, then using the masked data for a second ICA. At the same time this method eliminates a commonly necessary model-based step in fMRI data analysis. We also demonstrate our approach on a real world fMRI data set example.

Model-free Region Of Interest Based Analysis of fMRI Data

Blind source separation is being established as a new kind of analysis method in the field of fMRI data analysis. Its model-free approach renders it an important tool for investigation. In this article we present a method based on BSS/ICA to create a region of interest (ROI) mask for a BSS based fMRI data analysis. This eliminates a commonly necessary model-based step in fMRI data analysis. We demonstrate our approach on a real world fMRI data set example