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Neural basis of somatosensory target detection independent of uncertainty, relevance, and reports.

ABSTRACT: Research on somatosensory awareness has yielded highly diverse findings with putative neural correlates ranging from activity within somatosensory cortex to activation of widely distributed frontoparietal networks. Divergent results from previous studies may reside in cognitive processes that often coincide with stimulus awareness in experimental settings. To scrutinise the specific relevance of regions implied in the target detection network, we used functional magnetic resonance imaging (n = 27) on a novel somatosensory detection task that explicitly controls for stimulus uncertainty, behavioural relevance, overt reports, and motor responses. Using Bayesian Model Selection, we show that responses reflecting target detection are restricted to secondary somatosensory cortex, whereas activity in insular, cingulate, and motor regions is best explained in terms of stimulus uncertainty and overt reports. Our results emphasise the role of sensory-specific cortex for the emergence of perceptual awareness and dissect the contribution of the frontoparietal network to classical detection tasks.

SUBMITTER: Schroder P

PROVIDER: S-EPMC6440741 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Neural basis of somatosensory target detection independent of uncertainty, relevance, and reports.

Schröder Pia P Schmidt Timo Torsten TT Blankenburg Felix F

eLife 20190329

Research on somatosensory awareness has yielded highly diverse findings with putative neural correlates ranging from activity within somatosensory cortex to activation of widely distributed frontoparietal networks. Divergent results from previous studies may reside in cognitive processes that often coincide with stimulus awareness in experimental settings. To scrutinise the specific relevance of regions implied in the target detection network, we used functional magnetic resonance imaging (n = 2 ...[more]

PMID: 30924769

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Project description:A central challenge in the study of conscious perception lies in dissociating the neural correlates of perceptual awareness from those reflecting its precursors and consequences. No-report paradigms have been instrumental in this endeavor, demonstrating that the event-related potential P300, recorded from the human scalp, reflects reports rather than awareness. However, these paradigms cannot probe the degree to which stimuli are consciously processed from trial to trial and, thus, leave open the possibility that the P300 is a genuine correlate of conscious access enabling reports. Here, instead of removing report requirements, we took the opposite approach and equated postperceptual task demands across conscious and unconscious trials by orthogonalizing target detection and overt reports in a somatosensory detection task. We used Bayesian model selection to track the transformation from physical to perceptual processing stages in the EEG data of 24 male and female participants and show that the early P50 component scaled with physical stimulus intensity, whereas the N140 component was the first correlate of target detection. The late P300 component was elicited for both perceived and unperceived stimuli and was not substantially modulated by target detection. This was in stark contrast to a control experiment using a classical direct report task, which replicated the P50 and N140 effects but additionally showed a strong effect of target detection in the P300 time range. Our results demonstrate the task dependence of the P300 in the somatosensory modality and show that late cortical potentials dissociate from perceptual awareness even when stimuli are always reported.SIGNIFICANCE STATEMENT The time it takes for sensory information to enter our conscious experience can be an indicator of the neural processing stages that lead to perceptual awareness. However, because many cognitive processes routinely correlate with perception, isolating those signals that uniquely reflect perceptual awareness is not a trivial task. Here, we show that late electroencephalography signals cease to correlate with somatosensory awareness when common task confounds are controlled. Importantly, by balancing report requirements instead of abolishing them, we show that the lack of late effects cannot be explained by a lack of conscious access. Instead, we propose that conscious access occurs earlier, at ∼150 ms, supporting the view that early activity in sensory cortices is a neural correlate of conscious perception.

Project description:Building an efficient and reliable small target motion detection visual system is challenging for artificial intelligence robotics because a small target only occupies few pixels and hardly displays visual features in images. Biological visual systems that have evolved over millions of years could be ideal templates for designing artificial visual systems. Insects benefit from a class of specialized neurons, called small target motion detectors (STMDs), which endow them with an excellent ability to detect small moving targets against a cluttered dynamic environment. Some bio-inspired models featured in feed-forward information processing architectures have been proposed to imitate the functions of the STMD neurons. However, feedback, a crucial mechanism for visual system regulation, has not been investigated deeply in the STMD-based neural circuits and its roles in small target motion detection remain unclear. In this paper, we propose a time-delay feedback STMD model for small target motion detection in complex backgrounds. The main contributions of this study are as follows. First, a feedback pathway is designed by transmitting information from output-layer neurons to lower-layer interneurons in the STMD pathway and the role of the feedback is analyzed from the view of mathematical analysis. Second, to estimate the feedback constant, the existence and uniqueness of solutions for nonlinear dynamical systems formed by feedback loop are analyzed via Schauder's fixed point theorem and contraction mapping theorem. Finally, an iterative algorithm is designed to solve the nonlinear problem and the performance of the proposed model is tested by experiments. Experimental results demonstrate that the feedback is able to weaken background false positives while maintaining a minor effect on small targets. It outperforms existing STMD-based models regarding the accuracy of fast-moving small target detection in visual clutter. The proposed feedback approach could inspire the relevant modeling of robust motion perception robotics visual systems.

Dataset Information

Neural basis of somatosensory target detection independent of uncertainty, relevance, and reports.

Publications

Neural basis of somatosensory target detection independent of uncertainty, relevance, and reports.

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