modeling-functional-network-for-spatial-navigation-human

Modeling the Functional Network for Spatial Navigation in the Human Brain

Spatial navigation is a complex function involving the integration and manipulation of multisensory information. Using different navigation tasks, many ...

Max Planck Institute for Empirical Aesthetics

Recent evidence shows that hippocampal theta oscillations, usually linked to memory and navigation, are also observed during online language processing, suggesting a shared neurophysiological mechanism between language and memory. However, it remains to be established what specific roles hippocampal theta oscillations may play in language, and whether and how theta mediates the communication between the hippocampus and the perisylvian cortical areas, generally thought to support language processing. With whole-head magnetoencephalographic (MEG) recordings, the present study investigated these questions with two experiments. Using a violation paradigm, extensively used for studying neural underpinnings of different aspects of linguistic processing, we found increased theta power (4-8 ​Hz) in the hippocampal formation, when participants read a semantically incorrect vs. correct sentence ending. Such a pattern of results was replicated using different sentence stimuli in another cohort of participants. Importantly, no significant hippocampal theta power increase was found when participants read a semantically correct but syntactically incorrect sentence ending vs. a correct sentence ending. These findings may suggest that hippocampal theta oscillations are specifically linked to lexical-semantic related processing, and not general information processing in sentence reading. Furthermore, we found significantly transient theta phase coupling between the hippocampus and the left superior temporal gyrus, a hub area of the cortical network for language comprehension. This transient theta phase coupling may provide an important channel that links the memory and language systems for the generation of sentence meaning. Overall, these findings help specify the role of hippocampal theta in language, and provide a novel neurophysiological mechanism at the network level that may support the interface between memory and language.

Theta oscillations support the interface between language and memory.

Hippocampal rhythms are important for spatial navigation. This study examined whether gender differences in human navigation performance are associated with differences in hippocampal rhythms. We measured brain activities in males and females with whole-head magnetoencephalography (MEG), while they performed a virtual Morris water maze task. Behavioural results showed clear gender differences: males were significantly faster than females; unlike males, females did not show improved navigation performance in a familiar vs. new environment. MEG results showed that the magnitudes of right hippocampal/parahippocampal theta rhythm were similar between the two groups during navigation in a new environment; however, unlike males who exhibited a significant decrease in right hippocampal/parahippocampal theta power in the familiar environment shown before, females showed no change. This result may suggest faster environmental learning in males vs. females. After navigating in the new environment during the inter-trial (ITI) rest periods, males showed significantly higher right hippocampal/parahippocampal high-gamma power than females, suggesting greater consolidation in males. Moreover, right hippocampal/parahippocampal theta power during navigation correlated with navigation performance in both genders; high-gamma power during the ITI was correlated with navigation performance only in males. These associations may provide further support for the functional importance of theta and high-gamma rhythms in navigation. Overall, this study provides new insights into the neurophysiological mechanisms underlying gender differences in spatial navigation.

Gender differences in navigation performance are associated with differential theta and high-gamma activities in the hippocampus and parahippocampus.

In memory, our continuous experiences are broken up into discrete events. Boundaries between events are known to influence the temporal organization of memory. However, how and through which mechanism event boundaries shape temporal order memory (TOM) remains unknown. Across four experiments, we show that event boundaries exert a dual role: improving TOM for items within an event and impairing TOM for items across events. Decreasing event length in a list enhances TOM, but only for items at earlier local event positions, an effect we term the local primacy effect. A computational model, in which items are associated to a temporal context signal that drifts over time but resets at boundaries captures all behavioural results. Our findings provide a unified algorithmic mechanism for understanding how and why event boundaries affect TOM, reconciling a long-standing paradox of why both contextual similarity and dissimilarity promote TOM.

Event boundaries shape temporal organization of memory by resetting temporal context.

Lateralization is a fundamental characteristic of many behaviors and the organization of the brain, and atypical lateralization has been suggested to be linked to various brain-related disorders such as autism and schizophrenia. Right-handedness is one of the most prominent markers of human behavioural lateralization, yet its neurobiological basis remains to be determined. Here, we present a large-scale analysis of handedness, as measured by self-reported direction of hand preference, and its variability related to brain structural and functional organization in the UK Biobank (N = 36,024). A multivariate machine learning approach with multi-modalities of brain imaging data was adopted, to reveal how well brain imaging features could predict individual's handedness (i.e., right-handedness vs. non-right-handedness) and further identify the top brain signatures that contributed to the prediction. Overall, the results showed a good prediction performance, with an area under the receiver operating characteristic curve (AUROC) score of up to 0.72, driven largely by resting-state functional measures. Virtual lesion analysis and large-scale decoding analysis suggested that the brain networks with the highest importance in the prediction showed functional relevance to hand movement and several higher-level cognitive functions including language, arithmetic, and social interaction. Genetic analyses of contributions of common DNA polymorphisms to the imaging-derived handedness prediction score showed a significant heritability (h=7.55%, p <0.001) that was similar to and slightly higher than that for the behavioural measure itself (h=6.74%, p <0.001). The genetic correlation between the two was high (r=0.71), suggesting that the imaging-derived score could be used as a surrogate in genetic studies where the behavioural measure is not available. This large-scale study using multimodal brain imaging and multivariate machine learning has shed new light on the neural correlates of human handedness.

Machine learning of large-scale multimodal brain imaging data reveals neural correlates of hand preference.

Understanding the evolutionarily conserved feature of functional laterality in the habenula has been attracting attention due to its potential role in human cognition and neuropsychiatric disorders. Deciphering the structure of the human habenula remains to be challenging, which resulted in inconsistent findings for brain disorders. Here, we present a large-scale meta-analysis of the left-right differences in the habenular volume in the human brain to provide a clearer picture of the habenular asymmetry. We searched PubMed, Web of Science, and Google Scholar for articles that reported volume data of the bilateral habenula in the human brain, and assessed the left-right differences. We also assessed the potential effects of several moderating variables including the mean age of the participants, magnetic field strengths of the scanners and different disorders by using meta-regression and subgroup analysis. In total 52 datasets (N = 1427) were identified and showed significant heterogeneity in the left-right differences and the unilateral volume per se. Moderator analyses suggested that such heterogeneity was mainly due to different MRI scanners and segmentation approaches used. While inversed asymmetry patterns were suggested in patients with depression (leftward) and schizophrenia (rightward), no significant disorder-related differences relative to healthy controls were found in either the left-right asymmetry or the unilateral volume. This study provides useful data for future studies of brain imaging and methodological developments related to precision habenula measurements, and also helps to further understand potential roles of the habenula in various disorders.

Yi Pu

Department of Neuroscience

Max Planck Institute for Empirical Aesthetics

Modeling the Functional Network for Spatial Navigation in the Human Brain

Yi Pu

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Neuroscience

Max Planck Institute for Empirical Aesthetics

Modeling the Functional Network for Spatial Navigation in the Human Brain

Department of Neuroscience