Inhibition of orienting during a memory-guided saccade task shows a Mexican-hat distribution

Conservative significance testing of tripartite statistical relations in multivariate neural data

An important goal in systems neuroscience is to understand the structure of neuronal interactions, frequently approached by studying functional relations between recorded neuronal signals. Commonly used pairwise measures (e.g., correlation coefficient) offer limited insight, neither addressing the specificity of estimated neuronal interactions nor potential synergistic coupling between neuronal signals. Tripartite measures, such as partial correlation, variance partitioning, and partial information decomposition, address these questions by disentangling functional relations into interpretable information atoms (unique, redundant, and synergistic). Here, we apply these tripartite measures to simulated neuronal recordings to investigate their sensitivity to noise. We find that the considered measures are mostly accurate and specific for signals with noiseless sources but experience significant bias for noisy sources.We show that permutation testing of such measures results in high false positive rates even for small noise fractions and large data sizes. We present a conservative null hypothesis for significance testing of tripartite measures, which significantly decreases false positive rate at a tolerable expense of increasing false negative rate. We hope our study raises awareness about the potential pitfalls of significance testing and of interpretation of functional relations, offering both conceptual and practical advice.

Awareness-Dependent Normalization Framework of Visual Bottom-up Attention

Although bottom-up attention can improve visual performance with and without awareness to the exogenous cue, whether they are governed by a common neural computation remains unclear. Using a modified Posner paradigm with backward masking, we found that the cueing effect displayed a monotonic gradient profile (Gaussian-like), both with and without awareness, whose scope, however, was significantly wider with than without awareness. This awareness-dependent scope offered us a unique opportunity to change the relative size of the attention field to the stimulus, differentially modulating the gain of attentional selection, as proposed by the normalization model of attention. Therefore, for each human subject (male and female), the stimulus size was manipulated as their respective mean attention fields with and without awareness while stimulus contrast was varied in a spatial cueing task. By measuring the gain pattern of contrast-response functions on the spatial cueing effect derived by visible or invisible cues, we observed changes in the cueing effect consonant with changes in contrast gain for visible cues and response gain for invisible cues. Importantly, a complementary analysis confirmed that subjects' awareness-dependent attention fields can be simulated by using the normalization model of attention. Together, our findings indicate an awareness-dependent normalization framework of visual bottom-up attention, placing a necessary constraint, namely, awareness, on our understanding of the neural computations underlying visual attention.SIGNIFICANCE STATEMENT Bottom-up attention is known to improve visual performance with and without awareness. We discovered that manipulating subjects' awareness can modulate their attention fields of visual bottom-up attention, which offers a unique opportunity to regulate its normalization processes. On the one hand, by measuring the gain pattern of contrast-response functions on the spatial cueing effect derived by visible or invisible cues, we observed changes in the cueing effect consonant with changes in contrast gain for visible cues and response gain for invisible cues. On the other hand, by using the normalization model of attention, subjects' awareness-dependent attention fields can be simulated successfully. Our study supports important predictions of the normalization model of visual bottom-up attention and further reveals its dependence on awareness.

Inhibitory and Facilitatory Cueing Effects: Competition between Exogenous and Endogenous Mechanisms

Inhibition of return is characterized by delayed responses to previously attended locations when the cue-target onset asynchrony (CTOA) is long enough. However, when cues are predictive of a target’s location, faster reaction times to cued as compared to uncued targets are normally observed. In this series of experiments investigating saccadic reaction times, we manipulated the cue predictability to 25% (counterpredictive), 50% (nonpredictive), and 75% (predictive) to investigate the interaction between predictive endogenous facilitatory (FCEs) and inhibitory cueing effects (ICEs). Overall, larger ICEs were seen in the counterpredictive condition than in the nonpredictive condition, and no ICE was found in the predictive condition. Based on the hypothesized additivity of FCEs and ICEs, we reasoned that the null ICEs observed in the predictive condition are the result of two opposing mechanisms balancing each other out, and the large ICEs observed with counterpredictive cueing can be attributed to the combination of endogenous facilitation at uncued locations with inhibition at cued locations. Our findings suggest that the endogenous activity contributed by cue predictability can reduce the overall inhibition observed when the mechanisms occur at the same location, or enhance behavioral inhibition when the mechanisms occur at opposite locations.