Identifying the computational roles of different neuron families is crucial for understanding neural networks. Most neural diversity is embodied in various types of γ-aminobutyric acid-mediated (GABAergic) interneurons, grouped into four major families. We collected datasets of opto-tagged neurons from all four families, along with excitatory neurons, from both the neocortex and hippocampus. The physiological features of these neurons were used to train a machine learning classifier, which subsequently inferred specific interneuron families in large-scale recordings. This combined approach enabled the reconstruction of synaptic connectivity motifs across interneuron family members. We further showed that these motifs differentially control the place field features of pyramidal neurons. Our findings attribute a prominent role to interneurons in the formation of a flexible cognitive map.
Cooperative actions of interneuron families support the hippocampal spatial code.
Manuel Valero,P. Abad-Perez,Andrea Gallardo,Marta Picco,Raquel García-Hernandez,Jorge Brotons,Anel Martínez-Félix,Robert Machold,Bernardo Rudy,György Buzsáki
Published 2025 in Science
ABSTRACT
PUBLICATION RECORD
- Publication year
2025
- Venue
Science
- Publication date
2025-09-04
- Fields of study
Biology, Medicine, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
CITATION MAP
EXTRACTION MAP
CLAIMS
- No claims are published for this paper.
CONCEPTS
- No concepts are published for this paper.
REFERENCES
Showing 1-84 of 84 references · Page 1 of 1
CITED BY
Showing 1-6 of 6 citing papers · Page 1 of 1