Diffusion magnetic resonance imaging connectome features are predictive of functional lateralization of semantic processing in the anterior temporal lobes

Relationship of left piriform cortex network centrality with temporal lobe epilepsy duration and drug resistance

BACKGROUND

We investigated the relationship of piriform cortex (PC) structural network centrality with drug resistance and epilepsy duration as markers of sustained epileptic activity.

METHODS

PCs were manually delineated on retrospectively collected 3D-T1-MRI images of patients with temporal lobe epilepsy (TLE). Connectomes were computed from diffusion MRI scans, including the PC as network nodes. Betweenness centrality (BC) and node degree were computed and compared across drug-resistant versus drug-sensitive patients. Correlations of centrality metrics with the duration of epilepsy were calculated.

RESULTS

Sixty-two patients (36 females, 43/62 drug-resistant) were included in the main analysis. Greater centrality of the left PC was associated with drug resistance (degree: p = 0.00696, d = 0.85; BC: p = 0.00859, d = 0.59; alpha = 0.0125). Furthermore, left PC centrality was correlated with epilepsy duration (degree: rho = 0.39, p = 0.00181; BC: rho = 0.35, p = 0.0047; alpha = 0.0125). Results were robust to analysis of different parcellation schemes. Exploratory whole-network analysis yielded the largest effects in the left PC. Finer parcellations showed stronger effects for both analyses in the left olfactory cortex rostral to PC. In 28 subjects who had received epilepsy surgery, a trend of smaller centrality in patients with ILAE I outcome was observed in this area.

CONCLUSIONS

We demonstrated an increased centrality of the left PC in patients with drug-resistant TLE, which was also associated with the epilepsy duration. Recurring seizures over long periods may lead to changes of network properties of the PC. Large effects immediately rostral to our delineated PC region suggest a role of olfactory cortex anterior to the limen insulae in epileptogenic networks.

Rest2Task: Modeling task-specific components in resting-state functional connectivity and applications

The networks observed in the brain during resting-state activity are not entirely "task-free." Instead, they hint at a hierarchical structure prepared for adaptive cognitive functions. Recent studies have increasingly demonstrated the potential of resting-state fMRI to predict local activations or global connectomes during task performance. However, uncertainties remain regarding the unique and shared task-specific components within resting-state brain networks, elucidating local activations and global connectome patterns. A coherent framework is also required to integrate these task-specific components to predict local activations and global connectome patterns. In this work, we introduce the Rest2Task model based on the partial least squares-based multivariate regression algorithm, which effectively integrates mappings from resting-state connectivity to local activations and global connectome patterns. By analyzing the coefficients of the regression model, we extracted task-specific resting-state components corresponding to brain local activation or global connectome of various tasks and applied them to the brain lateralization prediction and psychiatric disorders diagnostic. Our model effectively substitutes traditional whole-brain functional connectivity (FC) in predicting functional lateralization and diagnosing brain disorders. Our research represents the inaugural effort to quantify the contribution of patterns (components) within resting-state FC to different tasks, endowing these components with specific task-related contextual information. The task-specific resting-state components offer new insights into brain lateralization processing and disease diagnosis, potentially providing fresh perspectives on the adaptive transformation of brain networks in response to tasks.

Functional mapping of the somatosensory cortex using noninvasive fMRI and touch in awake dogs

Dogs are increasingly used as a model for neuroscience due to their ability to undergo functional MRI fully awake and unrestrained, after extensive behavioral training. Still, we know rather little about dogs' basic functional neuroanatomy, including how basic perceptual and motor functions are localized in their brains. This is a major shortcoming in interpreting activations obtained in dog fMRI. The aim of this preregistered study was to localize areas associated with somatosensory processing. To this end, we touched N = 22 dogs undergoing fMRI scanning on their left and right flanks using a wooden rod. We identified activation in anatomically defined primary and secondary somatosensory areas (SI and SII), lateralized to the contralateral hemisphere depending on the side of touch, and importantly also activation beyond SI and SII, in the cingulate cortex, right cerebellum and vermis, and the sylvian gyri. These activations may partly relate to motor control (cerebellum, cingulate), but also potentially to higher-order cognitive processing of somatosensory stimuli (rostral sylvian gyri), and the affective aspects of the stimulation (cingulate). We also found evidence for individual side biases in a vast majority of dogs in our sample, pointing at functional lateralization of somatosensory processing. These findings not only provide further evidence that fMRI is suited to localize neuro-cognitive processing in dogs, but also expand our understanding of in vivo touch processing in mammals, beyond classically defined primary and secondary somatosensory cortices.