Characterizing the within-trial time course of attentional facilitation and inhibition across paradigms and effectors
Final Report Abstract
During the last decades, researchers have been searching for a new metaphor to replace the brain-as-computer metaphor. One option is that the brain is implementing a dynamical system, so that cognition is the behavior of a dynamical system. To understand cognition one should therefore take into account the passage of time explicitly. I therefore proposed to apply Event History Analysis (EHA) to time-to-event data such as response times, saccade latencies, fixation durations, etc. EHA refers to a set of well-established longitudinal techniques to statistically describe and model the shape of time-to-event distributions. In this project I proposed to study and compare the behavior of participants in various standard cognitive paradigms that have been developed to study attentional selection (visual search, spatial cueing, flanker, Stroop, and priming tasks), using EHA. Each of the six published studies provides new insights into the time-dispersed behavior of participants, compared to the established picture painted by mean performance measures (objective 1). By describing the hazard of response occurrence as a function of different time scales (within-trial, across-trial, across-block) one observes two principles from dynamic systems theory in overt behavior: multi-causality (i.e., the convergence of multiple forces to create behavior) and nesting of time scales (objective 3). For example, the hazard models that were fitted in many studies in this project show that at any single time point in a trial covered by the RT distribution, behavior (here: response hazard) can be concurrently affected by (a) task-relevant manipulations, (b) reactive cognitive control process, (c) shortterm plasticity due to trial-to-trial sequential effects, and (d) long-term plasticity due to proactive cognitive control across blocks of trials. In other words, differences in mean RT are non-exclusive measures for the process-of-interest, and they are biased in the sense that they invite explanations in terms of serial information processing concepts, and always conceal the underlying dynamic reality, which plays out on various time scales concurrently. The second objective – comparing attentional phenomena across paradigms and effectors – has only partially been reached due to the covid-19 pandemic. Specifically, I had to focus on comparing the time course of different attentional phenomena across paradigms using only manual responses. Unexpectedly, in many of the attentional paradigms, there are fast and premature overt responses that are typically triggered by early available, taskirrelevant information that resembles the task set, and these influence the measured differences in mean RT. Examples include cue onset in spatial cueing tasks, distractors in visual search tasks, and the prime identity in priming tasks. And if there is enough time, then these premature response tendencies are actively inhibited, as reflected in temporary dips in the hazard function of response occurrence, before target-triggered overt responses appear. As a result, the concept of attention was often not needed anymore to explain the experimental findings. This is consistent with a recent trend in the literature to reinterpret the results obtained in various experimental paradigms that were developed to study attentional selection processes. In conclusion, statistical control for the passage of time during data analysis is equally important as experimental control during the design of an experiment, to understand human behavior in our experimental paradigms. And only by studying how empirical and simulated response hazards change over time using EHA can we efficiently test dynamic theories and computational models of attentional selection processes.
Publications
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Analyzing Response Times and Other Types of Time-to-Event Data Using Event History Analysis: A Tool for Mental Chronometry and Cognitive Psychophysiology. i-Perception, 11(6).
Panis, Sven; Schmidt, Filipp; Wolkersdorfer, Maximilian P. & Schmidt, Thomas
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How can we learn what attention is? Response gating via multiple direct routes kept in check by inhibitory control processes. Open Psychology, 2(1), 238-279.
Panis, Sven
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Studying the dynamics of visual search behavior using RT hazard and micro-level speed–accuracy tradeoff functions: A role for recurrent object recognition and cognitive control processes. Attention, Perception, & Psychophysics, 82(2), 689-714.
Panis, Sven; Moran, Rani; Wolkersdorfer, Maximilian P. & Schmidt, Thomas
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Temporal dynamics of sequential motor activation in a dual-prime paradigm: Insights from conditional accuracy and hazard functions. Attention, Perception, & Psychophysics, 82(5), 2581-2602.
Wolkersdorfer, Maximilian P.; Panis, Sven & Schmidt, Thomas
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Response inhibition in the Negative Compatibility Effect in the absence of inhibitory stimulus features. Open Psychology, 4(1), 219-230.
Schmidt, Thomas; Panis, Sven; Wolkersdorfer, Maximilian P. & Vorberg, Dirk
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When does "inhibition of return” occur in spatial cueing tasks? Temporally disentangling multiple cue-triggered effects using response history and conditional accuracy analyses. Open Psychology, 4(1), 84-114.
Panis, Sven & Schmidt, Thomas
