Hippocampal subfield volumes and memory discrimination in the developing brain.

The ability to keep distinct memories of similar events is underpinned by a type of neural computation called pattern separation (PS). Children typically report coarse-grained memories narratives lacking specificity and detail. This lack of memory specificity is illustrative of an immature or impaired PS. Despite its importance for the ontogeny of memory, data regarding the maturation of PS during childhood is still scarce. PS is known to rely on the hippocampus, particularly on hippocampal subfields DG and CA3. In this study, we used a memory discrimination task, a behavioral proxy for PS, and manually segmented hippocampal subfields volumes in the hippocampal body in a cohort of 26 children aged from 5 to 12 years. We examined the association between subfields volumes and memory discrimination performance. The main results were: (1) we showed age-related differences of memory discrimination suggesting a continuous increase of memory performance during early to late childhood. (2) We evidenced distinct associations between age and the volumes of hippocampal subfield, suggesting distinct developmental trajectories. (3) We showed a relationship between memory discrimination performance and the volumes of CA3 and subiculum. Our results further confirm the role of CA3 in memory discrimination, and suggest to scrutinize more closely the role of the subiculum. Overall, we showed that hippocampal subfields contribute distinctively to PS during development.

Attention-gated 3D CapsNet for robust hippocampal segmentation.

Purpose: The hippocampus is organized in subfields (HSF) involved in learning and memory processes and widely implicated in pathologies at different ages of life, from neonatal hypoxia to temporal lobe epilepsy or Alzheimer's disease. Getting a highly accurate and robust delineation of sub-millimetric regions such as HSF to investigate anatomo-functional hypotheses is a challenge. One of the main difficulties encountered by those methodologies is related to the small size and anatomical variability of HSF, resulting in the scarcity of manual data labeling. Recently introduced, capsule networks solve analogous problems in medical imaging, providing deep learning architectures with rotational equivariance. Nonetheless, capsule networks are still two-dimensional and unassessed for the segmentation of HSF. Approach: We released a public 3D Capsule Network (3D-AGSCaps, https://github.com/clementpoiret/3D-AGSCaps) and compared it to equivalent architectures using classical convolutions on the automatic segmentation of HSF on small and atypical datasets (incomplete hippocampal inversion, IHI). We tested 3D-AGSCaps on three datasets with manually labeled hippocampi. Results: Our main results were: (1) 3D-AGSCaps produced segmentations with a better Dice Coefficient compared to CNNs on rotated hippocampi (p=0.004, cohen's d=0.179); (2) on typical subjects, 3D-AGSCaps produced segmentations with a Dice coefficient similar to CNNs while having 15 times fewer parameters (2.285M versus 35.069M). This may greatly facilitate the study of atypical subjects, including healthy and pathological cases like those presenting an IHI. Conclusion: We expect our newly introduced 3D-AGSCaps to allow a more accurate and fully automated segmentation on atypical populations, small datasets, as well as on and large cohorts where manual segmentations are nearly intractable.

A fast and robust hippocampal subfields segmentation: HSF revealing lifespan volumetric dynamics.

The hippocampal subfields, pivotal to episodic memory, are distinct both in terms of cyto- and myeloarchitectony. Studying the structure of hippocampal subfields in vivo is crucial to understand volumetric trajectories across the lifespan, from the emergence of episodic memory during early childhood to memory impairments found in older adults. However, segmenting hippocampal subfields on conventional MRI sequences is challenging because of their small size. Furthermore, there is to date no unified segmentation protocol for the hippocampal subfields, which limits comparisons between studies. Therefore, we introduced a novel segmentation tool called HSF short for hippocampal segmentation factory, which leverages an end-to-end deep learning pipeline. First, we validated HSF against currently used tools (ASHS, HIPS, and HippUnfold). Then, we used HSF on 3,750 subjects from the HCP development, young adults, and aging datasets to study the effect of age and sex on hippocampal subfields volumes. Firstly, we showed HSF to be closer to manual segmentation than other currently used tools (p < 0.001), regarding the Dice Coefficient, Hausdorff Distance, and Volumetric Similarity. Then, we showed differential maturation and aging across subfields, with the dentate gyrus being the most affected by age. We also found faster growth and decay in men than in women for most hippocampal subfields. Thus, while we introduced a new, fast and robust end-to-end segmentation tool, our neuroanatomical results concerning the lifespan trajectories of the hippocampal subfields reconcile previous conflicting results.

Breath-hold diving strategies to avoid loss of consciousness: speed is the key factor.

The aim of this study was to investigate the impact of breath-hold diving strategies regarding loss of consciousness (LOC). Three international competitions were examined through video in constant weight diving with (CWT) or without (CNF) fins. We analysed three breath-hold parameters (time, speed, and movements count) for the following phases: active descent, passive descent, turning, and ascent. Divers who had LOC during CNF were slower in the active descent phase, faster in the passive descent phase with a longer turn, and slower in the ascent phase than divers who did not have LOC. They also had lower amplitude and higher frequency. Men were deeper (72.9 m vs. 56.3 m) for a longer dive time (181.1 s vs. 154.6 s), faster, with a greater amplitude than women. In CWT, divers with an LOC had longer dive times (197 s vs. 167 s) with a faster active descent phase. Men had lower amplitude and greater frequency than women. This is the first study showing that breath-hold divers undergoing an LOC event shown differences in efficiency during CWT and CNF regarding velocities, amplitudes, and frequencies. In conclusion, our results suggest that the speed parameter during active descent phase influence the LOC.