Hippocampus最新文献

The anterior portion of the medial temporal lobe (MTL) is one of the first regions targeted by pathology in sporadic Alzheimer's disease (AD) and limbic-predominant age-related TDP-43 encephalopathy (LATE) indicating a potential for metrics from this region to serve as imaging biomarkers. Leveraging a unique post-mortem dataset of histology and magnetic resonance imaging (MRI) scans, we aimed to (1) develop an anatomically valid segmentation protocol for anterior entorhinal cortex (ERC), Brodmann area (BA) 35, and BA36 for in vivo 3 T MRI and (2) incorporate this protocol in an automated approach. We included 20 cases (61–97 years old, 50% females) with and without neurodegenerative diseases (11 vs. 9 cases) to ensure generalizability of the developed protocol. Digitized MTL Nissl-stained coronal histology sections from these cases were annotated and registered to same-subject post-mortem MRI. The protocol was developed by determining the location of histological borders of the MTL cortices in relation to anatomical landmarks. Subsequently, the protocol was applied to 15 cases twice, with a 2-week interval, to assess intra-rater reliability with the Dice Similarity Index (DSI). Thereafter, it was implemented in our in-house Automatic Segmentation of Hippocampal Subfields (ASHS)-T1 approach and evaluated with DSIs. The anterior histological border distances of ERC, BA35 and BA36 were evaluated with respect to various anatomical landmarks, and the distance relative to the beginning of the hippocampus was chosen. To formulate segmentation rules, we examined the histological sections for the location of borders in relationship to anatomical landmarks in the coronal sections. The DSI for the anterior MTL cortices for the intra-rater reliability was 0.85–0.88, and for the ASHS-T1 against the manual segmentation, it was 0.62–0.65. We developed a reliable segmentation protocol and incorporated it in an automated approach. Given the vulnerability of the anterior MTL cortices to tau deposition in AD and LATE, the updated approach is expected to improve imaging biomarkers for these diseases.

Valproic acid (VPA), a first-line antiepileptic and mood-stabilizing drug, has been linked to congenital malformations, cognitive disabilities, and an elevated risk of autism spectrum disorder (ASD) when used during pregnancy. ASD is a lifelong developmental disorder characterized by impaired social interaction, repetitive behaviors, and cognitive deficits, with a higher prevalence in males. Growing evidence highlights that hippocampal circuits, particularly CA1 and dentate gyrus (DG) subregions, are crucial for cognitive and social functions often impaired in ASD. Notably, VPA exposure at embryonic day 12.5 (E12.5) coincides with critical neurodevelopmental processes in the hippocampus, making it highly susceptible to oxidative damage and structural disruptions. Using a mouse model of ASD induced by a single prenatal VPA injection (400 mg/kg) at E12.5, this study assessed morphological and oxidative changes in the hippocampus. Male and female offspring were evaluated for core behavioral and cognitive alterations of ASD. After the behavioral tests, their brains were processed for Golgi-Cox staining and antioxidant enzyme dosage. The results showed that prenatal exposure to VPA indeed induces ASD-like behaviors, including reduced sociability, increased repetitive behaviors, and impaired working memory. Sholl analysis showed increased dendritic branching in granule and CA1 pyramidal neurons of VPA male mice, while VPA female mice exhibited hypoarborization in dentate gyrus granule cells. Both male and female VPA mice displayed higher dendritic spine density. Concurrently, oxidative stress was increased in the hippocampi of the VPA mice, as evidenced by alterations in oxidative stress biomarkers. Our work underscores gender differences in the effects of prenatal VPA exposure and points to a possible role for hippocampal neuron morphology and oxidative stress in the pathophysiology of ASD.

Neurons linked to spatial navigation and toroidal dynamics in the mouse medial entorhinal cortex (MEC) show unexpected minute-scale (< 0.01 Hz) oscillatory sequences without neural organization or clear relation to behavior. However, the conditions sustaining these’ ultraslow' equences remain uncertain. Since dopaminergic modulation of spike-timing-dependent plasticity (STDP) enables infraslow (< 0.1 Hz) oscillations in sparse neural networks (SNN), we hypothesize that SNN might sustain minute-scale (ultraslow) oscillatory sequences when bypassing the modulation. Using computational simulations through detailed numerical investigations, the conditions that enable the MEC-like ultraslow rhythms are characterized in an Izhikevich's SNN with dopaminergic STDP modulation. To induce the ultraslow sequences, a few active neurons are defined at each simulation step following a toroid-like trajectory. The results indicate that even when disrupting the dopamine-based STDP learning, the ultraslow oscillations require a second-scale resetting of the membrane potential to keep the sequential firing. Interestingly, separate oscillations on synapses that do not contribute to the firing rate at a specific time step (silent synaptic connections) are observed in the presence of the sequences. Since the mechanisms underlying the experimental finding are unknown, the present manuscript generates hypotheses on the conditions that sustain minute-scale sequences, which will be relevant for the community studying population dynamics in the MEC.

The anterior and posterior hippocampus exhibit distinct patterns of connectivity and are consequently hypothesized to have distinct functions. While there is evidence that the posterior hippocampus interacts with the default network and the anterior hippocampus interacts with the attention network during memory processes, there are conflicting hypotheses regarding connectivity between the hippocampus and other brain regions during rest. If hippocampal connectivity during rest parallels connectivity during memory, we would expect the anterior hippocampus and posterior hippocampus to have preferential connectivity with the attention network and the default network, respectively. Alternatively, given the association between the hippocampus and the default network, both regions of the hippocampus may have similar levels of connectivity with the default network. We used data from the Human Connectome Project (with 864 participants) to investigate resting-state functional connectivity with the anterior and posterior hippocampus and evaluated the degree of overlap between these patterns of connectivity and the attention network and default network. In direct opposition to the connectivity pattern during memory, resting-state data revealed preferential connectivity between the anterior hippocampus and the default network and between the posterior hippocampus and the attention network. These findings indicate that connectivity with the anterior and posterior hippocampus may differ between rest and active memory processing. One possible explanation for this discrepancy is that, during rest, the specific connectivity patterns supporting memory are less engaged. This does not imply an overall suppression of hippocampal connectivity but rather a relative reduction in engagement with the attention and default networks compared to task-based memory states. Such a shift may facilitate more dynamic network reconfiguration during memory encoding and retrieval.