Back

Improved spatial memory in a modular network mimicking the prefrontal-thalamo-hippocampal triangular circuit

Takaku, M.; Fukai, T.

2026-02-28 neuroscience
10.64898/2026.02.27.708561 bioRxiv
Show abstract

The hippocampus (HPC), prefrontal cortex (PFC), and thalamic nuclei, such as reuniens (Re), form a reciprocally connected circuit that plays a critical role in processing hippocampus-dependent memory. Accumulating evidence suggests that this triangular modular circuit is crucial for performing cognitive tasks that require context-dependent memory, which belong to a class of behavioral tasks difficult for animals to learn. Experiments are gradually revealing what behavioral information these brain regions represent, but how the triangular circuit gives rise to the observed divisions of labor remains unknown. It is also unclear whether the triangular modular circuit brings any advantage in solving such tasks. Here, we addressed these questions by constructing a prefrontal-thalamo-hippocampal circuit model comprising interconnected long-short-term memory (LSTM) units and training it on contextual memory-dependent spatial navigation tasks. Our model revealed the critical roles of the distinct brain modules. The HPC module encoded spatial information, whereas the PFC module represented the spatiotemporal task structure in a context-dependent manner. The Re module integrated task-relevant information to facilitate learning in the PFC and HPC modules, dynamically harmonizing these modules. The thalamic coordination of the other modules enhanced the systems robustness in learning to navigate complex environments. This division of labor between the HPC, PFC, and Re modules was not specified a priori but emerged through learning, showing an interesting coincidence with the task-related activities of the prefrontal-thalamo-hippocampal circuit. Our results demonstrate that the multi-modular network structure is crucial for robust processing of context-dependent memory.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Frontiers in Computational Neuroscience
53 papers in training set
Top 0.1%
12.7%
2
PLOS Computational Biology
1633 papers in training set
Top 2%
12.7%
3
Nature Communications
4913 papers in training set
Top 17%
10.1%
4
iScience
1063 papers in training set
Top 0.6%
8.4%
5
Progress in Neurobiology
41 papers in training set
Top 0.1%
6.4%
50% of probability mass above
6
Cell Reports
1338 papers in training set
Top 7%
6.4%
7
eLife
5422 papers in training set
Top 13%
6.4%
8
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 14%
4.9%
9
Neural Networks
32 papers in training set
Top 0.1%
4.9%
10
Advanced Science
249 papers in training set
Top 5%
3.7%
11
Communications Biology
886 papers in training set
Top 4%
2.6%
12
Scientific Reports
3102 papers in training set
Top 50%
2.1%
13
National Science Review
22 papers in training set
Top 0.9%
1.7%
14
Science Advances
1098 papers in training set
Top 21%
1.3%
15
Neuron
282 papers in training set
Top 6%
1.3%
16
Cerebral Cortex
357 papers in training set
Top 1%
1.2%
17
The Journal of Neuroscience
928 papers in training set
Top 7%
0.9%
18
Frontiers in Systems Neuroscience
19 papers in training set
Top 0.3%
0.9%
19
eneuro
389 papers in training set
Top 9%
0.7%
20
Frontiers in Neural Circuits
36 papers in training set
Top 0.7%
0.7%
21
Current Biology
596 papers in training set
Top 14%
0.7%
22
Neuroscience Research
14 papers in training set
Top 0.3%
0.6%
23
Neuroscience Bulletin
11 papers in training set
Top 0.8%
0.6%