Several brain disorders exhibit sex differences in onset, presentation, and prevalence. Increased understanding of the neurobiology of sex-based differences in variability across the lifespan can provide insight into both disease vulnerability and resilience. In n = 3069 participants, from 8 to 95 years of age, we found widespread greater variability in males compared with females in cortical surface area and global and subcortical volumes for discrete brain regions. In contrast, variance in cortical thickness was similar for males and females. These findings were supported by multivariate analysis accounting for structural covariance, and present and stable across the lifespan. Additionally, we examined variability among brain regions by sex. We found significant age-by-sex interactions across neuroimaging metrics, whereby in very early life males had reduced among-region variability compared with females, while in very late life this was reversed. Overall, our findings of greater regional variability, but less among-region variability in males in early life may aid our understanding of sex-based risk for neurodevelopmental disorders. In contrast, our findings in late life may provide a potential sex-based risk mechanism for dementia.

Several brain disorders exhibit sex differences in onset, presentation, and prevalence.Increased understanding of the neurobiology of sex-based differences across the lifespan can provide insight into potential disease risk and protective mechanisms. We focused on sex-related differences in variability, which may be indicative of both disease vulnerability and resilience. In n=3,069 participants, from 8-95 years of age, we first analyzed the variance ratio in females vs. males of cortical surface area and global and subcortical volumes for discrete brain regions, and found widespread greater variability in males. In contrast, variance in cortical thickness was similar for males and females. Multivariate analysis that accounts for structural covariance supported variance ratio findings. Findings were present from early life and stable with age. We then examined variability among brain regions by sex. We found significant age-by-sex interactions across neuroimaging metrics, whereby in very early life males had reduced among-region variability compared to females, while in very late life this was reversed. Overall, our findings of greater regional variability but less among-region variability in males in early life may aid our understanding of sex-based risk for neurodevelopmental disorders. In contrast, our findings in late life may provide a potential sex-based risk mechanism for dementia.

Transsaccadic memory is a process by which remembered object information is updated across a saccade. To date, studies on transsaccadic memory have used simple stimuli-that is, a single dot or feature of an object. It remains unknown how transsaccadic memory occurs for more realistic, complex objects with multiple features. An object's location is a central feature for transsaccadic updating, as it is spatially variant, but other features such as size are spatially invariant. How these spatially variant and invariant features of an object are remembered and updated across saccades is not well understood. Here we tested how well 14 participants remembered either three different features together (location, orientation, and size) or a single feature at a time of a bar either while fixating either with or without an intervening saccade. We found that the intervening saccade influenced memory of all three features, with consistent biases of the remembered location, orientation, and size that were dependent on the direction of the saccade. These biases were similar whether participants remembered either a single feature or multiple features and were not observed with increased memory load (single vs. multiple features during fixation trials), confirming that these effects were specific to the saccade updating mechanisms. We conclude that multiple features of an object are updated together across eye movements, supporting the notion that spatially invariant features of an object are bound to their location in memory.

Background: Spatial patterns of brain functional connectivity can vary substantially at the individual level. Applying cortical surface-based approaches with individualized rather than group templates may accelerate the discovery of biological markers related to psychiatric disorders. We investigated cortico-subcortical networks from multi-cohort data in people with schizophrenia spectrum disorders (SSDs) and healthy controls using individualized connectivity profiles. Methods: We utilized resting state and anatomical MRI data from n=406 participants (n = 203 SSD, n = 203 healthy controls) from four cohorts. For each participant, functional timeseries were extracted from 80 cortical regions of interest, representing 6 intrinsic networks using 1) a volume-based approach 2) a surface-based group atlas approach, and 3) Personalized Intrinsic Network Topography (PINT), a personalized surface-based approach (Dickie et al., 2018). Timeseries were also extracted from previously defined intrinsic network subregions of the striatum (Choi et al 2011), thalamus (Ji et al 2019), and cerebellum (Buckner et al 2011). Results: Compared to a volume-based approach, the correlations between all cortical networks and the expected subregions of the striatum, cerebellum, and thalamus were increased using a surface-based approach (Cohen's D volume vs surface 0.27-1.00, all p<10^-6) and further increased after PINT (Cohen's D surface vs PINT 0.18-0.96, all p <10^-4). In SSD vs HC comparisons, controlling for age, sex, scanner and in-scanner motion, we observed robust patterns of dysconnectivity that were strengthened using a surface-based approach and PINT (Number of differing pairwise-correlations: volume: 357, surface: 562, PINT: 630, FDR corrected). These patterns were found from four different cortical networks -- frontal-parietal, sensory-motor, visual, and default mode -- to subcortical regions. Conclusion: Our results indicate that individualized approaches can more sensitively delineate cortical network dysconnectivity differences in people with SSDs. These robust patterns of dysconnectivity were visibly organized in accordance with the cortical hierarchy, as predicted by computational models (Murray et al 2019). Our results also change our understanding of the specific network-network functional connectivity alterations in people with SSDs, and the extent of those alterations. Future work will examine these new patterns of dysconnectivity with behaviour using dimensional models.

8Brain lesion and stimulation studies have suggested posterior parietal cortex and the medial 9 intraparietal sulcus in particular as a crucial hub for online movement error corrections. However, 10 causal evidence for this is still sparse. Indeed, lesion studies are potentially confounded by 11 compensatory reorganization mechanisms while brain stimulation studies have produced 12 heterogeneous results when employing transcranial magnetic stimulation. Here we employed a 13 complementary approach using fMRI-guided high-definition transcranial direct current stimulation 14 (HD-tDCS) of the left medial intraparietal sulcus (mIPS) to re-examine the role of mIPS in online 15 reach corrections to jumping targets. We obtained two independent measures of stimulation-induced 16 changes in brain activity by modeling current flow in the brain and through EEG recordings before 17 and after the stimulation. To quantify behavioral effects we computed movement curvature as a 18 measure of online correction. We demonstrate that both of our measurements of brain activity were 19 consistent with a polarity-specific modulation of the online correction for targets jumping to the 20 contralateral side of the stimulation. Importantly, using a mediation analysis of the relationship 21 between stimulation current and movement curvature, we provide causal evidence that the induced 22 current modifies brain activity, which then leads to the observed behavioral changes. This unique 23 combination of methods and analysis thus provides complementary evidence for the crucial role of the 24 posterior parietal cortex in online error correction, while at the same time setting a new 25 methodological standard with respect to the causal influence of transcranial direct current stimulation. 26