Cooperative actions of interneuron families support the hippocampal spatial code.
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| Title: | Cooperative actions of interneuron families support the hippocampal spatial code. |
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| Authors: | Valero, Manuel, Abad-Perez, Pablo, Gallardo, Andrea, Picco, Marta, García-Hernandez, Raquel, Brotons, Jorge, Martínez-Félix, Anel, Machold, Robert, Rudy, Bernardo, Buzsáki, György |
| Source: | Science. 9/4/2025, Vol. 389 Issue 6764, p1-12. 12p. |
| Subjects: | Aminobutyric acid, Interneurons, Pyramidal neurons, Machine learning, Optogenetics |
| Abstract: | 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. Editor's summary: Neurogenetics has identified many distinct types of inhibitory interneurons. However, how this interneuron diversity contributes to network functions remains elusive. Valero et al. identified the distinct properties of optogenetically identified pyramidal cells and members of the major interneuron families (see the Perspective by Craig and González-Rueda). These properties include their firing rate statistics in different brain states and their contributions to various population activities. Using the electrophysiological fingerprints of this dataset, the researchers trained a machine learning algorithm to infer the different neuronal types in large-scale recordings and then constructed a connectivity graph of these major cell types through targeted optogenetic stimulations and functional connectivity analysis. These findings highlight the crucial role of cooperative interactions between interneuron types in the hippocampal network and demonstrate that such interaction is fundamental for the hippocampal cognitive map. —Peter Stern INTRODUCTION: The dynamic interactions between the hippocampus and its partner structures create a cognitive map that enables flexible spatial and mental navigation. Single pyramidal cells contribute to this map with their place fields. Most physiological studies assume that the recurrent excitatory system of the CA3 region or the entorhinal grid system generates place fields. In turn, flexibility and remapping are induced by plastic changes in excitatory synapses. An alternative consideration of this flexibility is the contribution of diverse inhibitory microcircuits that shape the place field properties of pyramidal neurons. The multiple interactions among the large diversity of genetically defined interneuron families and their joint effect on the pyramidal neuron can, in principle, regulate the various place field features. Testing this hypothesis requires the simultaneous recording of members from various interneuron families in behaving animals. RATIONALE: Current optogenetic and pharmacogenetic methods typically enable the identification and manipulation of only one or, occasionally, two families in a given experiment. Our first goal was to characterize and validate the interneuron family divisions by demonstrating reliable physiological boundaries among them, using optogenetic identification of the four major interneuron families in individual mice. In turn, these physiological fingerprints allowed us to recognize members of these families in large-scale, unlabeled populations. Thus, we could examine the nature of interactions among them and their relationship to the firing of pyramidal cells in the same experiment. Optogenetic perturbation of the interneuron families, in turn, provided further support for their role in circuit control and their ability to shape the place field features of their target principal cells. RESULTS: We combined multiple-shank silicon probe recordings with optogenetic identification of neurons expressing channelrhodopsin-2 (ChR2) in the four major interneuron families (Pvalb, Sst, Vip, and Id2 neurons) and pyramidal cells expressing calcium- and calmodulin-dependent protein kinase II alpha (CaMK2α) in the hippocampus and neocortex. The physiological features of opto-tagged neurons collected during spontaneous behaviors in the home cage were used to train a machine learning classifier. The high accuracy of physiology-based interneuron classification (>89%) enabled the identification of members of interneuron families in large-scale recording experiments and the study of their interactions. The fractions of the predicted families in unlabeled populations showed a strong correlation with gene expression–based fractions. The identified differentiating physiological features are communicable across different experiments and laboratories. Spiking activity of the members of the four interneuron families showed distinctive correlations with place field features, such as stability, selectivity, generalization, and mutual information between firing rates and the animal's position. Our family-specific perturbation experiments validated these correlational results. Optogenetic activation of Pvalb neurons predominantly suppressed the first half of the place fields of pyramidal cells, whereas Sst and Id2 activation suppressed place field spiking in the second half, demonstrating time-division control of pyramidal cells. CONCLUSION: We demonstrate the reliability of physiological fingerprinting with genetically defined interneuron families. Our findings reveal a fundamental role for the cooperative function of interneuron families in the emergence of the hippocampal cognitive map. Because our physiological fingerprinting strategy is paradigm independent, it is also generalizable to nonspatial functions of the hippocampus and other brain regions. Interneuron diversity shapes place field features of the hippocampal cognitive map.: Gene expression clusters neocortical and hippocampal neurons into five families: Pvalb, Sst, Id2, Vip, and CaMK2α. We recorded opto-tagged neurons and trained a classifier using physiological properties across families. By combining targeted manipulation with large-scale recordings and neuron classification, we show that interneuron families differentially shape the spatial coding features of pyramidal neurons. [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | 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. Editor's summary: Neurogenetics has identified many distinct types of inhibitory interneurons. However, how this interneuron diversity contributes to network functions remains elusive. Valero et al. identified the distinct properties of optogenetically identified pyramidal cells and members of the major interneuron families (see the Perspective by Craig and González-Rueda). These properties include their firing rate statistics in different brain states and their contributions to various population activities. Using the electrophysiological fingerprints of this dataset, the researchers trained a machine learning algorithm to infer the different neuronal types in large-scale recordings and then constructed a connectivity graph of these major cell types through targeted optogenetic stimulations and functional connectivity analysis. These findings highlight the crucial role of cooperative interactions between interneuron types in the hippocampal network and demonstrate that such interaction is fundamental for the hippocampal cognitive map. —Peter Stern INTRODUCTION: The dynamic interactions between the hippocampus and its partner structures create a cognitive map that enables flexible spatial and mental navigation. Single pyramidal cells contribute to this map with their place fields. Most physiological studies assume that the recurrent excitatory system of the CA3 region or the entorhinal grid system generates place fields. In turn, flexibility and remapping are induced by plastic changes in excitatory synapses. An alternative consideration of this flexibility is the contribution of diverse inhibitory microcircuits that shape the place field properties of pyramidal neurons. The multiple interactions among the large diversity of genetically defined interneuron families and their joint effect on the pyramidal neuron can, in principle, regulate the various place field features. Testing this hypothesis requires the simultaneous recording of members from various interneuron families in behaving animals. RATIONALE: Current optogenetic and pharmacogenetic methods typically enable the identification and manipulation of only one or, occasionally, two families in a given experiment. Our first goal was to characterize and validate the interneuron family divisions by demonstrating reliable physiological boundaries among them, using optogenetic identification of the four major interneuron families in individual mice. In turn, these physiological fingerprints allowed us to recognize members of these families in large-scale, unlabeled populations. Thus, we could examine the nature of interactions among them and their relationship to the firing of pyramidal cells in the same experiment. Optogenetic perturbation of the interneuron families, in turn, provided further support for their role in circuit control and their ability to shape the place field features of their target principal cells. RESULTS: We combined multiple-shank silicon probe recordings with optogenetic identification of neurons expressing channelrhodopsin-2 (ChR2) in the four major interneuron families (Pvalb, Sst, Vip, and Id2 neurons) and pyramidal cells expressing calcium- and calmodulin-dependent protein kinase II alpha (CaMK2α) in the hippocampus and neocortex. The physiological features of opto-tagged neurons collected during spontaneous behaviors in the home cage were used to train a machine learning classifier. The high accuracy of physiology-based interneuron classification (>89%) enabled the identification of members of interneuron families in large-scale recording experiments and the study of their interactions. The fractions of the predicted families in unlabeled populations showed a strong correlation with gene expression–based fractions. The identified differentiating physiological features are communicable across different experiments and laboratories. Spiking activity of the members of the four interneuron families showed distinctive correlations with place field features, such as stability, selectivity, generalization, and mutual information between firing rates and the animal's position. Our family-specific perturbation experiments validated these correlational results. Optogenetic activation of Pvalb neurons predominantly suppressed the first half of the place fields of pyramidal cells, whereas Sst and Id2 activation suppressed place field spiking in the second half, demonstrating time-division control of pyramidal cells. CONCLUSION: We demonstrate the reliability of physiological fingerprinting with genetically defined interneuron families. Our findings reveal a fundamental role for the cooperative function of interneuron families in the emergence of the hippocampal cognitive map. Because our physiological fingerprinting strategy is paradigm independent, it is also generalizable to nonspatial functions of the hippocampus and other brain regions. Interneuron diversity shapes place field features of the hippocampal cognitive map.: Gene expression clusters neocortical and hippocampal neurons into five families: Pvalb, Sst, Id2, Vip, and CaMK2α. We recorded opto-tagged neurons and trained a classifier using physiological properties across families. By combining targeted manipulation with large-scale recordings and neuron classification, we show that interneuron families differentially shape the spatial coding features of pyramidal neurons. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00368075 |
| DOI: | 10.1126/science.adv5638 |
