Cross-modal and non-monotonic representations of statistical regularity are encoded in local neural response patterns

Abstract

Current neurobiological models assign a central role to predictive processes calibrated to environmental statistics. Neuroimaging studies examining the encoding of stimulus uncertainty have relied almost exclusively on manipulations in which stimuli were presented in a single sensory modality, and further assumed that neural responses vary monotonically with uncertainty. This has left a gap in theoretical development with respect to two core issues: (i) are there cross-modal brain systems that encode input uncertainty in way that generalizes across sensory modalities, and (ii) are there brain systems that track input uncertainty in a non-monotonic fashion? We used multivariate pattern analysis to address these two issues using auditory, visual and audiovisual inputs. We found signatures of cross-modal encoding in frontoparietal, orbitofrontal, and association cortices using a searchlight cross-classification analysis where classifiers trained to discriminate levels of uncertainty in one modality were tested in another modality. Additionally, we found widespread systems encoding uncertainty non-monotonically using classifiers trained to discriminate intermediate levels of uncertainty from both the highest and lowest uncertainty levels. These findings comprise the first comprehensive report of cross-modal and non-monotonic neural sensitivity to statistical regularities in the environment, and suggest that conventional paradigms testing for monotonic responses to uncertainty in a single sensory modality may have limited generalizability.

Stimulating Intrinsic Motivation in Millennial Students: A New Generation, a New Approach

“…Hence, these studies have been designed with the implicit assumption that when learning material is delivered via one sensory modality it is processed in the brain independently from material delivered via other sensory modalities (Bhagat et al, ; Jacobs et al, ; Baig and Mallu, ; Luthar, ; Rowland and Kumagai, ; Sahoo and Mohammed, ). However, contrasting scientific evidence demonstrates that multiple sensory modalities in the brain are always analyzed and interlinked by cross‐modal processing (Cerasoli and Ford, ; Tal et al, ; Nastase, et al, ) and interconnectivity (Haro et al, ; Hanganu‐Opatz et al, ; Strombach et al, ; Schwille, ) in the brain.…”

Threat‐induced anxiety and selfishness in resource sharing: Behavioral and neural evidence

“…We then chose 90/10 and 70/30 because the entropy for 90/10 was $0.47, which can be considered as a low uncertainty level (compared to the lowest point: 0.3); meanwhile, the entropy for 70/30 was $0.88, which can be considered as a high uncertainty level (compared to the highest point: 1). Similar practice has been successfully applied in the literature (Nastase et al, 2018;Peng et al, 2020). Four conditions were generated accordingly: highly predictable threat (HT) (90 ± 3% to receive a threat), moderately predictable threat (MT) (70 ± 3% to receive a threat), highly predictable safe (HS) (90 ± 3% to receive a safe stimulus), and moderately predictable safe (MS) (70 ± 3% to receive a safe stimulus) (Figure 1b).…”