One contribution of 16 to a theme issue 'Interoception beyond homeostasis: affect, cognition and mental health'.

Recursive social decision-making requires the use of flexible, context-sensitive long-term strategies for negotiation. To succeed in social bargaining, participants' own perspectives must be dynamically integrated with those of interactors to maximize self-benefits and adapt to the other's preferences, respectively. This is a prerequisite to develop a successful long-term self-other integration strategy. While such form of strategic interaction is critical to social decision-making, little is known about its neurocognitive correlates. To bridge this gap, we analysed social bargaining behaviour in relation to its structural neural correlates, ongoing brain dynamics (oscillations and related source space), and functional connectivity signatures in healthy subjects and patients offering contrastive lesion models of neurodegeneration and focal stroke: behavioural variant frontotemporal dementia, Alzheimer's disease, and frontal lesions. All groups showed preserved basic bargaining indexes. However, impaired self-other integration strategy was found in patients with behavioural variant frontotemporal dementia and frontal lesions, suggesting that social bargaining critically depends on the integrity of prefrontal regions. Also, associations between behavioural performance and data from voxel-based morphometry and voxel-based lesion-symptom mapping revealed a critical role of prefrontal regions in value integration and strategic decisions for self-other integration strategy. Furthermore, as shown by measures of brain dynamics and related sources during the task, the self-other integration strategy was predicted by brain anticipatory activity (alpha/beta oscillations with sources in frontotemporal regions) associated with expectations about others' decisions. This pattern was reduced in all clinical groups, with greater impairments in behavioural variant frontotemporal dementia and frontal lesions than Alzheimer's disease. Finally, connectivity analysis from functional magnetic resonance imaging evidenced a fronto-temporo-parietal network involved in successful self-other integration strategy, with selective compromise of long-distance connections in frontal disorders. In sum, this work provides unprecedented evidence of convergent behavioural and neurocognitive signatures of strategic social bargaining in different lesion models. Our findings offer new insights into the critical roles of prefrontal hubs and associated temporo-parietal networks for strategic social negotiation.

Neurodegeneration has multiscalar impacts, including behavioral, neuroanatomical, and neurofunctional disruptions. Can disease-differential alterations be captured across such dimensions using naturalistic stimuli? To address this question, we assessed comprehension of four naturalistic stories, highlighting action, nonaction, social, and nonsocial events, in Parkinson’s disease (PD) and behavioral variant frontotemporal dementia (bvFTD) relative to Alzheimer’s disease patients and healthy controls. Text-specific correlates were evaluated via voxel-based morphometry, spatial (fMRI), and temporal (hd-EEG) functional connectivity. PD patients presented action–text deficits related to the volume of action–observation regions, connectivity across motor-related and multimodal-semantic hubs, and frontal hd-EEG hypoconnectivity. BvFTD patients exhibited social–text deficits, associated with atrophy and spatial connectivity patterns along social-network hubs, alongside right frontotemporal hd-EEG hypoconnectivity. Alzheimer’s disease patients showed impairments in all stories, widespread atrophy and spatial connectivity patterns, and heightened occipitotemporal hd-EEG connectivity. Our framework revealed disease-specific signatures across behavioral, neuroanatomical, and neurofunctional dimensions, highlighting the sensitivity and specificity of a single naturalistic task. This investigation opens a translational agenda combining ecological approaches and multimodal cognitive neuroscience for the study of neurodegeneration.

Introduction Automated speech analysis has emerged as a scalable, cost‐effective tool to identify persons with Alzheimer's disease dementia (ADD). Yet, most research is undermined by low interpretability and specificity. Methods Combining statistical and machine learning analyses of natural speech data, we aimed to discriminate ADD patients from healthy controls (HCs) based on automated measures of domains typically affected in ADD: semantic granularity (coarseness of concepts) and ongoing semantic variability (conceptual closeness of successive words). To test for specificity, we replicated the analyses on Parkinson's disease (PD) patients. Results Relative to controls, ADD (but not PD) patients exhibited significant differences in both measures. Also, these features robustly discriminated between ADD patients and HC, while yielding near‐chance classification between PD patients and HCs. Discussion Automated discourse‐level semantic analyses can reveal objective, interpretable, and specific markers of ADD, bridging well‐established neuropsychological targets with digital assessment tools.

The hippocampus is regarded as the pivotal structure for episodic memory symptoms associated with Alzheimer's disease (AD) pathophysiology. However, what is often overlooked is that the hippocampus is 'only' one part of a network of memory critical regions, the Papez circuit. Other Papez circuit regions are often regarded as less relevant for AD as they are thought to sit 'downstream' of the hippocampus. However, this notion is oversimplistic, and

Background With the global population aging and life expectancy increasing, dementia has turned a priority in the health care system. In Chile, dementia is one of the most important causes of disability in the elderly and the most rapidly growing cause of death in the last 20 years. Cognitive complaint is considered a predictor for cognitive and functional decline, incident mild cognitive impairment, and incident dementia. The GERO cohort is the Chilean core clinical project of the Geroscience Center for Brain Health and Metabolism (GERO). The objective of the GERO cohort is to analyze the rate of functional decline and progression to clinical dementia and their associated risk factors in a community-dwelling elderly with subjective cognitive complaint, through a population-based study. We also aim to undertake clinical research on brain ageing and dementia disorders, to create data and biobanks with the appropriate infrastructure to conduct other studies and facilitate to the national and international scientific community access to the data and samples for research. Methods The GERO cohort aims the recruitment of 300 elderly subjects (> 70 years) from Santiago (Chile), following them up for at least 3 years. Eligible people are adults not diagnosed with dementia with subjective cognitive complaint, which are reported either by the participant, a proxy or both. Participants are identified through a household census. The protocol for evaluation is based on a multidimensional approach including socio-demographic, biomedical, psychosocial, neuropsychological, neuropsychiatric and motor assessments. Neuroimaging, blood and stool samples are also obtained. This multidimensional evaluation is carried out in a baseline and 2 follow-ups assessments, at 18 and 36 months. In addition, in months 6, 12, 24, and 30, a telephone interview is performed in order to keep contact with the participants and to assess general well-being. Discussion Our work will allow us to determine multidimensional risks factors associated with functional decline and conversion to dementia in elderly with subjective cognitive complain. The aim of our GERO group is to establish the capacity to foster cutting edge and multidisciplinary research on aging in Chile including basic and clinical research. Trial registration NCT04265482 in ClinicalTrials.gov. Registration Date: February 11, 2020. Retrospectively Registered.

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