Divergent hippocampal output via covariant local and long-range neuronal structure

Understanding the brain's structural architecture and organizational logic is essential for interpreting brain function. Morphological properties are well-known to discretely separate distinct types of cells and influence their respective computations, but whether finer-scale morphological differences within narrowly-defined cell types can govern disparate computations remains unknown. Here, we address this question by focusing on long-range projection neurons of the subiculum, the primary output cells of the hippocampus. We used high-resolution whole-brain neuronal reconstructions to concomitantly examine local and long-range neuronal architecture, as well as computational modeling to identify how projection-specific morphology shapes circuit computation. Our results reveal that subiculum projection neurons have a high degree of "matched complexity" between dendritic and axonal patterning, and that this dendritic-axonal covariation can lead to projection-specific input-output operations. Extending this work with viral circuit tracing, we further illustrate that subiculum neurons embedded within different long-range circuits exhibit spatially distinct local dendritic domains, suggesting these projection streams also receive fundamentally distinct types of input. This covariance of single-cell dendritic morphology with long-range neural targets illustrates a new form of organizational logic for hippocampal circuits, and likely plays a key role in driving distinct computations across hippocampal output pathways.

Authors

Institutions

Publication Details

Journal
Progress in Neurobiology
Published
2026-02-18
DOI
https://doi.org/10.1016/j.pneurobio.2026.102893
Citations
1
Primary Topic
Memory and Neural Mechanisms
Type
article
Field-Weighted Citation Impact
29.71
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Divergent hippocampal output via covariant local and long-range neuronal structure

Regan Campbell, M Zhang, Mark S. Cembrowski, Derek N. Merryweather
1 citations
Progress in Neurobiology
Memory and Neural Mechanisms
29.71
article

Divergent hippocampal output via covariant local and long-range neuronal structure

Regan Campbell, M Zhang, Mark S. Cembrowski, Derek N. Merryweather
article en
1 citations

Abstract

Understanding the brain's structural architecture and organizational logic is essential for interpreting brain function. Morphological properties are well-known to discretely separate distinct types of cells and influence their respective computations, but whether finer-scale morphological differences within narrowly-defined cell types can govern disparate computations remains unknown. Here, we address this question by focusing on long-range projection neurons of the subiculum, the primary output cells of the hippocampus. We used high-resolution whole-brain neuronal reconstructions to concomitantly examine local and long-range neuronal architecture, as well as computational modeling to identify how projection-specific morphology shapes circuit computation. Our results reveal that subiculum projection neurons have a high degree of "matched complexity" between dendritic and axonal patterning, and that this dendritic-axonal covariation can lead to projection-specific input-output operations. Extending this work with viral circuit tracing, we further illustrate that subiculum neurons embedded within different long-range circuits exhibit spatially distinct local dendritic domains, suggesting these projection streams also receive fundamentally distinct types of input. This covariance of single-cell dendritic morphology with long-range neural targets illustrates a new form of organizational logic for hippocampal circuits, and likely plays a key role in driving distinct computations across hippocampal output pathways.

Progress in NeurobiologyVol. 259
University of British Columbia (CA), Department of Physiological Sciences (RU)
Openalex Percentile: Top 1%
Memory and Neural Mechanisms
29.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Divergent hippocampal output via covariant local and long-range neuronal structure — Regan Campbell, M Zhang, et al. · Progress in Neurobiology (2026) | TGRS Research Map | TGRS