Here we present a high-resolution functional magnetic resonance (fMRI) dataset – 20 participants recorded at high field strength (7 Tesla) during prolonged stimulation with an auditory feature film (“Forrest Gump”). In addition, a comprehensive set of auxiliary data (T1w, T2w, DTI, susceptibility-weighted image, angiography) as well as measurements to assess technical and physiological noise components have been acquired. An initial analysis confirms that these data can be used to study common and idiosyncratic brain response patterns to complex auditory stimulation. Among the potential uses of this dataset are the study of auditory attention and cognition, language and music perception, and social perception. The auxiliary measurements enable a large variety of additional analysis strategies that relate functional response patterns to structural properties of the brain. Alongside the acquired data, we provide source code and detailed information on all employed procedures – from stimulus creation to data analysis. In order to facilitate replicative and derived works, only free and open-source software was utilized.
Avoiding distraction by conspicuous but irrelevant stimuli is critical to accomplishing daily tasks. Regions of prefrontal cortex control attention by enhancing the representation of task-relevant information in sensory cortex, which can be measured in modulation of both single neurons and event-related electrical potentials (ERPs) on the cranial surface [1, 2]. When irrelevant information is particularly conspicuous, it can distract attention and interfere with the selection of behaviorally relevant information. Such distraction can be minimized via top-down control [3-5], but the cognitive and neural mechanisms giving rise to this control over distraction remain uncertain and debated [6-9]. Bridging neurophysiology to electrophysiology, we simultaneously recorded neurons in prefrontal cortex and ERPs over extrastriate visual cortex to track the processing of salient distractors during a visual search task. Critically, when the salient distractor was successfully ignored, but not otherwise, we observed robust suppression of salient distractor representations. Like target selection, the distractor suppression was observed in prefrontal cortex before it appeared over extrastriate cortical areas. Furthermore, all prefrontal neurons that showed suppression of the task-irrelevant distractor also contributed to selecting the target. This suggests a common prefrontal mechanism is responsible for both selecting task-relevant and suppressing task-irrelevant information in sensory cortex. Taken together, our results resolve a long-standing debate over the mechanisms that prevent distraction, and provide the first evidence directly linking suppressed neural firing in prefrontal cortex with surface ERP measures of distractor suppression.
Due to an unfortunate miscommunication, the acknowledgments and authorship of this publication were incorrect. These corrections represent more accurately the funding, scientific, and technical contributions necessary to accomplish the reported research. The authors apologize for the error.
Perception of constant motion has been extensively studied both psychophysically and physiologically, but the human ability to detect dynamic changes in motion, such as rapid speed changes, is only poorly characterized and understood. Yet, perception and representation of such dynamic changes is of strong behavioral relevance, as illustrated by their potential for attentional capture. In the present study, we measured and compared detection thresholds for instantaneous accelerations and decelerations of drifting Gabor patches at different retinal eccentricities. As a main result, we find that detection performance depends strongly on eccentricity. Under foveal viewing conditions, average thresholds were lower for accelerations than for decelerations. However, between 5° and 15° eccentricity, this relation is inverted, and deceleration detection becomes better than acceleration detection. Results of an additional experiment suggest that this can be explained by a fast eccentricity-dependent adaptation effect. Our findings are discussed with special emphasis on their relation to data from neurophysiological experiments.
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