How does the brain navigate knowledge of social relations? Testing for shared neural mechanisms for shifting attention in space and social knowledge

Social knowledge about others is anchored to self-knowledge in the hippocampal formation

Mounting evidence suggests the human hippocampal formation (HF) maps how different people's attributes relate to each other. Yet, it's unclear if hippocampal map-like knowledge representations of other people are shaped by self-knowledge. Here, we test if a prominent heuristic involving an implicit reliance on self-knowledge when rating others, egocentric anchoring-and-adjustment, is present in the HF when relational information about different social entities is retrieved. Participants first provided likelihood ratings of partaking in everyday activities for themselves, fictitious individuals, and familiar social groups. During a neuroimaging task that doesn't require using self-knowledge, participants then learned a stranger's preference for an activity relative to one of the fictitious individuals and inferred how the stranger's preference related to the groups' preferences. Isolating the neural representation of egocentric anchoring when retrieving relational social knowledge, the HF and dorsomedial prefrontal cortex (dmPFC) represented group entities' preferences relative to the self. Furthermore, the HF selectively represented group identity over other learned entities, confirming the HF was primarily engaged by social comparisons in the more ample map-like reference frame. Taken together, these results imply that self-knowledge implicitly influences how the HF learns about others.

Modulation of Interbrain and Intrabrain Connectivity due to Social Presence and Task Difficulty: A Dual EEG/fNIRS Hyperscanning Study

This study employed fNIRS- and EEG-hyperscanning to investigate the effects of task sharing, social presence, and mental workload on intrabrain and interbrain functional connectivity, and neurophysiological responses of dyads during a dual n-back task. The findings indicated a positive correlation between the n-back level and reaction times, heart rate, and PFC oxygenation, whereas task accuracy and heart rate variability decreased with difficulty. The effect of social presence was smaller than the effect of task difficulty, suggesting a lower level of mental workload during the social condition, possibly due to social facilitation. In the social condition, interbrain connectivity tended to decrease as task difficulty increased, indicating that partners could monitor each other's actions to the extent that task demands allowed. The intrabrain connectivity analysis showed a larger difference between individual and social sessions compared with the difference between own and coactor's go trials in the social session. Overall, the EEG- and fNIRS-hyperscanning measures obtained during a dual n-back task in this study provide evidence regarding the differential modulation of interbrain and intrabrain functional connectivity due to the copresence of another actor responding to the same stimulus to pursue a different goal and changes in task difficulty.

Lost in space(s): Multimodal neuroimaging of disorientation along the Alzheimer's disease continuum

Orientation is a fundamental cognitive faculty and the bedrock of the neurologic examination. Orientation is defined as the alignment between an individual's internal representation and the external world in the spatial, temporal, and social domains. While spatial disorientation is a recognized hallmark of Alzheimer's disease (AD), little is known about disorientation beyond space in AD. This study aimed to explore disorientation in spatial, temporal, and social domains along the AD continuum. Fifty-one participants along the AD continuum performed an ecological orientation task in the spatial, temporal, and social domains while undergoing functional MRI. Disorientation in AD followed a three-way association between orientation domain, brain region, and disease stage. Specifically, patients with early amnestic mild cognitive impairment exhibited spatio-temporal disorientation and reduced brain activity in temporoparietal regions, while patients with AD dementia showed additional social disorientation and reduced brain activity in frontoparietal regions. Furthermore, patterns of hypoactivation overlapped different subnetworks of the default mode network, patterns of fluorodeoxyglucose hypometabolism, and cortical atrophy characteristic of AD. Our results suggest that AD may encompass a disorder of orientation, characterized by a biphasic process manifesting as early spatio-temporal and late social disorientation. As such, disorientation may offer a unique window into the clinicopathological progression of AD. SIGNIFICANCE STATEMENT: Despite extensive research into Alzheimer's disease (AD), its core cognitive deficit remains a matter of debate. In this study, we investigated whether orientation, defined as the ability to align internal representations with the external world in spatial, temporal, and social domains, constitutes a core cognitive deficit in AD. To do so, we used PET-fMRI imaging to collect behavioral, functional, and metabolic data from 51 participants along the AD continuum. Our findings suggest that AD may constitute a disorder of orientation, characterized by an early spatio-temporal disorientation and followed by late social disorientation, manifesting in task-evoked and neurodegenerative changes. We propose that a profile of disorientation across multiple domains offers a unique window into the progression of AD and as such could greatly benefit disease diagnosis, monitoring, and evaluation of treatment response.

The transitive inference task to study the neuronal correlates of memory-driven decision making: A monkey neurophysiology perspective

A vast amount of literature agrees that rank-ordered information as A>B>C>D>E>F is mentally represented in spatially organized schemas after learning. This organization significantly influences the process of decision-making, using the acquired premises, i.e. deciding if B is higher than D is equivalent to comparing their position in this space. The implementation of non-verbal versions of the transitive inference task has provided the basis for ascertaining that different animal species explore a mental space when deciding among hierarchically organized memories. In the present work, we reviewed several studies of transitive inference that highlighted this ability in animals and, consequently, the animal models developed to study the underlying cognitive processes and the main neural structures supporting this ability. Further, we present the literature investigating which are the underlying neuronal mechanisms. Then we discuss how non-human primates represent an excellent model for future studies, providing ideal resources for better understanding the neuronal correlates of decision-making through transitive inference tasks.

Neural correlates of transitive inference: An SDM meta-analysis on 32 fMRI studies

Transitive inference (TI) is a critical capacity involving the integration of relevant information into prior knowledge structure for drawing novel inferences on unobserved relationships. To date, the neural correlates of TI remain unclear due to the small sample size and heterogeneity of various experimental tasks from individual studies. Here, the meta-analysis on 32 fMRI studies was performed to detect brain activation patterns of TI and its three paradigms (spatial inference, hierarchical inference, and associative inference). We found the hippocampus, prefrontal cortex (PFC), putamen, posterior parietal cortex (PPC), retrosplenial cortex (RSC), supplementary motor area (SMA), precentral gyrus (PreCG), and median cingulate cortex (MCC) were engaged in TI. Specifically, the RSC was implicated in the associative inference, whereas PPC, SMA, PreCG, and MCC were implicated in the hierarchical inference. In addition, the hierarchical inference and associative inference both evoked activation in the hippocampus, medial PFC, and PCC. Although the meta-analysis on spatial inference did not generate a reliable result due to insufficient amount of investigations, the present work still offers a new insight for better understanding the neural basis underlying TI.