Impact of pressure as a tactile stimulus on working memory in healthy participants

Visual perceptual load and processing of somatosensory stimuli in primary and secondary somatosensory cortices

Load theory assumes that neural activation to distractors in early sensory cortices is modulated by the perceptual load of a main task, regardless of whether task and distractor share the same sensory modality or not. While several studies have investigated the question of load effects on distractor processing in early sensory areas, there is no functional magnetic resonance imaging (fMRI) study regarding load effects on somatosensory stimuli. Here, we used fMRI to investigate effects of visual perceptual load on neural responses to somatosensory stimuli applied to the wrist in a study with 44 participants. Perceptual load was manipulated by an established sustained visual detection task, which avoided simultaneous target and distractor presentations. Load was operationalized by detection difficulty of subtle or clear color changes of one of 12 rotating dots. While all somatosensory stimuli led to activation in somatosensory areas SI and SII, we found no statistically significant difference in brain activation to these stimuli under high compared to low sustained visual load. Moreover, exploratory Bayesian analyses supported the absence of differences. Thus, our findings suggest a resistance of somatosensory processing to at least some forms of visual perceptual load, possibly due to behavioural relevance of discrete somatosensory stimuli and separable attentional resources for the somatosensory and visual modality.

Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults

Cardiorespiratory fitness was found to influence age-related changes of resting state brain network organization. However, the influence on dedifferentiated involvement of wider and more unspecialized brain regions during task completion is barely understood. We analyzed EEG data recorded during rest and different tasks (sensory, motor, cognitive) with dynamic mode decomposition, which accounts for topological characteristics as well as temporal dynamics of brain networks. As a main feature the dominant spatio-temporal EEG pattern was extracted in multiple frequency bands per participant. To deduce a pattern’s stability, we calculated its proportion of total variance among all activation patterns over time for each task. By comparing fit (N = 15) and less fit older adults (N = 16) characterized by their performance on a 6-min walking test, we found signs of a lower task specificity of the obtained network features for the less fit compared to the fit group. This was indicated by fewer significant differences between tasks in the theta and high beta frequency band in the less fit group. Repeated measures ANOVA revealed that a significantly lower proportion of total variance can be explained by the main pattern in high beta frequency range for the less fit compared to the fit group [F(1,29) = 12.572, p = .001, partial η² = .300]. Our results indicate that the dedifferentiation in task-related brain activation is lower in fit compared to less fit older adults. Thus, our study supports the idea that cardiorespiratory fitness influences task-related brain network organization in different task domains.

Neural correlates of individual variation in two-back working memory and the relationship with fluid intelligence

Working memory has been examined extensively using the N-back task. However, less is known about the neural bases underlying individual variation in the accuracy rate (AR) and reaction time (RT) as metrics of N-back performance. Whereas AR indexes the overall performance, RT may more specifically reflect the efficiency in updating target identify. Further, studies have associated fluid intelligence (Gf) with working memory, but the cerebral correlates shared between Gf and N-back performance remain unclear. We addressed these issues using the Human Connectome Project dataset. We quantified the differences in AR (critical success index or CSI) and RT between 2- and 0-backs (CSI_2–0 and RT_2–0) and identified the neural correlates of individual variation in CSI_2–0, RT_2–0, and Gf, as indexed by the number of correct items scored in the Raven’s Standard Progressive Matrices (RSPM) test. The results showed that CSI_2–0 and RT_2–0 were negatively correlated, suggesting that a prolonged response time did not facilitate accuracy. At voxel p < 0.05, FWE-corrected, the pre-supplementary motor area (preSMA), bilateral frontoparietal cortex (biFPC) and right anterior insula (rAI) showed activities in negative correlation with CSI_2–0 and positive correlation with RT_2–0. In contrast, a cluster in the dorsal anterior cingulate cortex (dACC) bordering the SMA showed activities in positive correlation with CSI_2–0 and negative correlation with RT_2–0. Further, path analyses showed a significant fit of the model dACC → RT_2–0 → CSI_2–0, suggesting a critical role of target switching in determining performance accuracy. Individual variations in RT_2–0 and Gf were positively correlated, although the effect size was small (f² = 0.0246). RT_2–0 and Gf shared activities both in positive correlation with the preSMA, biFPC, rAI, and dorsal precuneus. These results together suggest inter-related neural substrates of individual variation in N-back performance and highlight a complex relationship in the neural processes supporting 2-back and RSPM performance.