Hippocampal function is critical for spatial and contextual learning, and its decline with age contributes to cognitive impairment. Exercise can improve hippocampal function, however, the amount of exercise and mechanisms mediating improvement remain largely unknown. Here, we show exercise reverses learning deficits in aged (24 months) female mice but only when it occurs for a specific duration, with longer or shorter periods proving ineffective. A spike in the levels of growth hormone (GH) and a corresponding increase in neurogenesis during this sweet spot mediate this effect because blocking GH receptor with a competitive antagonist or depleting newborn neurons abrogates the exercise-induced cognitive improvement. Moreover, raising GH levels with GH-releasing hormone agonist improved cognition in nonrunners. We show that GH stimulates neural precursors directly, indicating the link between raised GH and neurogenesis is the basis for the substantially improved learning in aged animals.
The brain is the seat of body weight homeostasis. However, our inability to control the increasing prevalence of obesity highlights a need to look beyond canonical feeding pathways to broaden our understanding of body weight control. Here we used a reverse-translational approach to identify and anatomically, molecularly and functionally characterize a neural ensemble that promotes satiation. Unbiased, task-based functional magnetic resonance imaging revealed marked differences in cerebellar responses to food in people with a genetic disorder characterized by insatiable appetite. Transcriptomic analyses in mice revealed molecularly and topographically -distinct neurons in the anterior deep cerebellar nuclei (aDCN) that are activated by feeding or nutrient infusion in the gut. Selective activation of aDCN neurons substantially decreased food intake by reducing meal size without compensatory changes to metabolic rate. We found that aDCN activity terminates food intake by increasing striatal dopamine levels and attenuating the phasic dopamine response to subsequent food consumption. Our study defines a conserved satiation centre that may represent a novel therapeutic target for the management of excessive eating, and underscores the utility of a ‘bedside-to-bench’ approach for the identification of neural circuits that influence behaviour.
When we remember a city that we have visited, we retrieve places related to finding our goal but also non-target locations within this environment. Yet, understanding how the human brain implements the neural computations underlying holistic retrieval remains unsolved, particularly for shared aspects of environments. Here, human participants learned and retrieved details from three partially overlapping environments while undergoing high-resolution functional magnetic resonance imaging (fMRI). Our findings show reinstatement of stores even when they are not related to a specific trial probe, providing evidence for holistic environmental retrieval. For stores shared between cities, we find evidence for pattern separation (representational orthogonalization) in hippocampal subfield CA2/3/DG and repulsion in CA1 (differentiation beyond orthogonalization). Additionally, our findings demonstrate that medial prefrontal cortex (mPFC) stores representations of the common spatial structure, termed schema, across environments. Together, our findings suggest how unique and common elements of multiple spatial environments are accessed computationally and neurally.
Increased levels of peripheral cytokines have been previously associated with depression in preclinical and clinical research. Although the precise nature of peripheral immune dysfunction in depression remains unclear, evidence from animal studies points towards a dysregulated response of peripheral leukocytes as a risk factor for stress susceptibility. This study examined dynamic release of inflammatory blood factors from peripheral blood mononuclear cells (PBMC) in depressed patients and associations with neural and behavioral measures of reward processing. Thirty unmedicated patients meeting criteria for unipolar depressive disorder and 21 healthy control volunteers were enrolled. PBMCs were isolated from whole blood and stimulated ex vivo with lipopolysaccharide (LPS). Olink multiplex assay was used to analyze a large panel of inflammatory proteins. Participants completed functional magnetic resonance imaging with an incentive flanker task to probe neural responses to reward anticipation, as well as clinical measures of anhedonia and pleasure including the Temporal Experience of Pleasure Scale (TEPS) and the Snaith-Hamilton Pleasure Scale (SHAPS). LPS stimulation revealed larger increases in immune factors in depressed compared to healthy subjects using an aggregate immune score (t49 = 2.83, p = 0.007). Higher peripheral immune score was associated with reduced neural responses to reward anticipation within the ventral striatum (VS) (r = −0.39, p = 0.01), and with reduced anticipation of pleasure as measured with the TEPS anticipatory sub-score (r = −0.318, p = 0.023). Our study provides new evidence suggesting that dynamic hyper-reactivity of peripheral leukocytes in depressed patients is associated with blunted activation of the brain reward system and lower subjective anticipation of pleasure.
Several epidemiological and preclinical studies supported the protective effect of coffee on Alzheimer’s disease (AD). However, it is still unknown whether coffee is specifically related with reduced brain AD pathologies in human. Hence, this study aims to investigate relationships between coffee intake and in vivo AD pathologies, including cerebral beta-amyloid (Aβ) deposition, the neurodegeneration of AD-signature regions, and cerebral white matter hyperintensities (WMH). A total of 411 non-demented older adults were included. Participants underwent comprehensive clinical assessment and multimodal neuroimaging including [11C] Pittsburgh compound B-positron emission tomography (PET), [18F] fluorodeoxyglucose PET, and magnetic resonance imaging scans. Lifetime and current coffee intake were categorized as follows: no coffee or
Importance Influenza has been associated with the risk of developing Parkinson disease, but the association is controversial. Objective To examine whether prior influenza and other infections are associated with Parkinson disease more than 10 years after infection. Design, Setting, and Participants This case-control study used data from 1977 to 2016 from the Danish National Patient Registry. All individuals with Parkinson disease, excluding those with drug-induced parkinsonism, were included and matched to 5 population controls on sex, age, and date of Parkinson diagnosis. Data were analyzed from December 2019 to September 2021. Exposures Infections were ascertained between 1977 and 2016 and categorized by time from infection to Parkinson disease diagnosis. To increase specificity of influenza diagnoses, influenza exposure was restricted to months of peak influenza activity. Main Outcomes and Measures Parkinson disease diagnoses were identified between January 1, 2000, and December 31, 2016. Crude and adjusted odds ratios (ORs) and 95% CIs were calculated by conditional logistic regression overall and stratified by time between infection and Parkinson disease (5 years or less, more than 5 to 10 years, more than 10 years). Results Of 61 626 included individuals, 23 826 (38.7%) were female, and 53 202 (86.3%) were older than 60 years. A total of 10 271 individuals with Parkinson disease and 51 355 controls were identified. Influenza diagnosed at any time during a calendar year was associated with Parkinson disease more than 10 years later (OR, 1.73; 95% CI, 1.11-2.71). When influenza exposure was restricted to months of highest influenza activity, an elevated OR with a wider confidence interval was found (OR, 1.52; 95% CI, 0.80-2.89). There was no evidence of an association with any type of infection more than 10 years prior to Parkinson disease (OR, 1.04; 95% CI, 0.98-1.10). Several specific infections yielded increased odds of Parkinson disease within 5 years of infection, but results were null when exposure occurred more than 10 years prior. Conclusions and Relevance In this case-control study, influenza was associated with diagnoses of Parkinson disease more than 10 years after infection. These observational data suggest a link between influenza and Parkinson disease but do not demonstrate causality. While other infections were associated with Parkinson disease diagnoses soon after infection, null associations after more than 10 years suggest these shorter-term associations are not causal.
Dynamic Causal Modeling (DCM) is a Bayesian framework for inferring on hidden (latent) neuronal states, based on measurements of brain activity. Since its introduction in 2003 for functional magnetic resonance imaging data, DCM has been extended to electrophysiological data, and several variants have been developed. Their biophysically motivated formulations make these models promising candidates for providing a mechanistic understanding of human brain dynamics, both in health and disease. However, due to their complexity and reliance on concepts from several fields, fully understanding the mathematical and conceptual basis behind certain variants of DCM can be challenging. At the same time, a solid theoretical knowledge of the models is crucial to avoid pitfalls in the application of these models and interpretation of their results. In this paper, we focus on one of the most advanced formulations of DCM, i.e. conductance-based DCM for cross-spectral densities, whose components are described across multiple technical papers. The aim of the present article is to provide an accessible exposition of the mathematical background, together with an illustration of the model's behavior. To this end, we include step-by-step derivations of the model equations, point to important aspects in the software implementation of those models, and use simulations to provide an intuitive understanding of the type of responses that can be generated and the role that specific parameters play in the model. Furthermore, all code utilized for our simulations is made publicly available alongside the manuscript to allow readers an easy hands-on experience with conductance-based DCM.
Major depressive disorder (MDD) is a prevalent psychiatric disorder, and exposure to stress is a robust risk factor for MDD. Clinical data and rodent models have indicated the negative impact of chronic exposure to stress-induced hormones like cortisol on brain volume, memory, and cell metabolism. However, the cellular and transcriptomic changes that occur in the brain after prolonged exposure to cortisol are less understood. Furthermore, the astrocyte-specific contribution to cortisol-induced neuropathology remains understudied. Here, we have developed an in vitro model of “chronic stress” using human induced pluripotent stem cell (iPSC)-derived astrocytes treated with cortisol for 7 days. Whole transcriptome sequencing reveals differentially expressed genes (DEGs) uniquely regulated in chronic cortisol compared to acute cortisol treatment. Utilizing this paradigm, we examined the stress response transcriptome of astrocytes generated from MDD patient iPSCs. The MDD-specific DEGs are related to GPCR ligand binding, synaptic signaling, and ion homeostasis. Together, these data highlight the unique role astrocytes play in the central nervous system and present interesting genes for future study into the relationship between chronic stress and MDD.
This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as the inversion of a generative model of viscerosensory inputs allows for a formal definition of dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence for the brain's model of bodily states) and allostasis (as a change in prior beliefs or predictions which define setpoints for homeostatic reflex arcs). Critically, we propose that the performance of interoceptive-allostatic circuitry is monitored by a metacognitive layer that updates beliefs about the brain's capacity to successfully regulate bodily states (allostatic self-efficacy). In this framework, fatigue and depression can be understood as sequential responses to the interoceptive experience of dyshomeostasis and the ensuing metacognitive diagnosis of low allostatic self-efficacy. While fatigue might represent an early response with adaptive value (cf. sickness behavior), the experience of chronic dyshomeostasis may trigger a generalized belief of low self-efficacy and lack of control (cf. learned helplessness), resulting in depression. This perspective implies alternative pathophysiological mechanisms that are reflected by differential abnormalities in the effective connectivity of circuits for interoception and allostasis. We discuss suitably extended models of effective connectivity that could distinguish these connectivity patterns in individual patients and may help inform differential diagnosis of fatigue and depression in the future.
Brain function relies on efficient communications between distinct brain systems. The pathology of major depressive disorder (MDD) damages functional brain networks, resulting in cognitive impairment. Here, we reviewed the associations between brain functional connectome changes and MDD pathogenesis. We also highlighted the utility of brain functional connectome for differentiating MDD from other similar psychiatric disorders, predicting recurrence and suicide attempts in MDD, and evaluating treatment responses. Converging evidence has now linked aberrant brain functional network organization in MDD to the dysregulation of neurotransmitter signaling and neuroplasticity, providing insights into the neurobiological mechanisms of the disease and antidepressant efficacy. Widespread connectome dysfunctions in MDD patients include multiple, large-scale brain networks as well as local disturbances in brain circuits associated with negative and positive valence systems and cognitive functions. Although the clinical utility of the brain functional connectome remains to be realized, recent findings provide further promise that research in this area may lead to improved diagnosis, treatments, and clinical outcomes of MDD.