Hippocampal connectivity patterns echo macroscale cortical evolution in the primate brain

TL;DR: HippoMaps is an open-access toolbox and data warehouse for mapping and contextualizing subregional hippocampal data, integrating 3D histology, MRI, and iEEG recordings, with tools for spatial map analysis and autocorrelation correction.

Abstract: Abstract The hippocampus supports episodic memory by binding spatial and semantic information, yet how this information is simultaneously organized along its long axis remains debated. Gradient accounts propose a continuous shift in representational scale, from coarse coding in anterior to fine coding in posterior regions, whereas modular accounts posit discrete subregions specialized for distinct functions. Using high-resolution fMRI together with eye tracking as a readout of spatial and semantic memory during sequence learning, we directly tested these competing models. During predictable sequences, hippocampal activity continuously varied along the long axis. In contrast, modular organization emerged when sequences mismatched memory. Subregions in the anterior and posterior hippocampus were sensitive to semantic and spatial mismatches, respectively. Notably, the intermediate hippocampus was specifically sensitive to concurrent mismatches in both dimensions, but not to mismatches in either dimension alone. These content-sensitive subregions were embedded within distinct cortical networks that reorganized according to memory demands. Together, our findings show the hippocampus flexibly combines gradient and modular dynamics to simultaneously represent the spatial and semantic content that defines episodic memory.

TL;DR: Past observations are synthesized to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment, and for understanding mental disorders including autism, schizophrenia, and Alzheimer's disease.

TL;DR: The methods and software engineering philosophy behind this new tool, ITK-SNAP, are described and the results of validation experiments performed in the context of an ongoing child autism neuroimaging study are provided, finding that SNAP is a highly reliable and efficient alternative to manual tracing.

TL;DR: In this paper, the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI data from 1,000 subjects and a clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex.