Parvalbumin+ interneurons obey unique connectivity rules and establish a powerful lateral-inhibition microcircuit in dentate gyrus

By Claudia Espinoza, Segundo Jose Guzman, Xiaomin Zhang, Peter Jonas. 2018

148 citations recorded by the source corpus.

Parvalbumin-positive (PV+) GABAergic interneurons in hippocampal microcircuits are thought to play a key role in several higher network functions, such as feedforward and feedback inhibition, network oscillations, and pattern separation. Fast lateral inhibition mediated by GABAergic interneurons may implement a winner-takes-all mechanism in the hippocampal input layer. However, it is not clear whether the functional connectivity rules of granule cells (GCs) and interneurons in the dentate gyrus are consistent with such a mechanism. Using simultaneous patch-clamp recordings from up to seven GCs and up to four PV+ interneurons in the dentate gyrus, we find that connectivity is structured in space, synapse-specific, and enriched in specific disynaptic motifs. In contrast to the neocortex, lateral inhibition in the dentate gyrus (in which a GC inhibits neighboring GCs via a PV+ interneuron) is ~ 10-times more abundant than recurrent inhibition (in which a GC inhibits itself). Thus, unique connectivity rules may enable the dentate gyrus to perform specific higher-order computations. GABAergic interneurons are known to provide inhibition to allow computational function of neuronal network. Here, Espinoza and colleagues show that connectivity of granule cells and interneurons in the dentate gyrus of mouse hippocampus are consistent with the circuit architecture capable of performing a winners-take-all mechanism.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Social Psychology, Neuroscience

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In Cellular and Molecular Neuroscience

1. Mikail Khona
2. Liyuan Wang
3. Jun Zhu
4. Hang Su
5. Xingxing Zhang
6. Ila Rani Fiete

In Cognitive Neuroscience

1. Mikail Khona
2. Liyuan Wang
3. Jun Zhu
4. Hang Su
5. Xingxing Zhang
6. Ila Rani Fiete
7. Yoshua Bengio
8. Chaopeng Shen

In Neuroscience

1. Liyuan Wang
2. Jun Zhu
3. Mikail Khona
4. Hang Su
5. Xingxing Zhang
6. Ila Rani Fiete

Citations in the corpus

• A Comprehensive Survey of Continual Learning: Theory, Method and Application (2023, methodology): “of synaptic plasticity” [3], [4], [77], corresponding to the use of meta-learning [118], [185], [360]; and (4) inhibitory synapses for excited neurons to reduce the activity of other neurons [20], [54], [112], [178], which acts similarly to the binary mask for parameter allocation [375], [427].”
• Re-evaluating circuit mechanisms underlying pattern separation (2019, neutral): “In addition, recent work has found that parvalbumin-expressing interneurons (which includes some basket cells as well as axo-axonic cells; Hu et al., 2014) establish powerful lateral inhibition between granule cells (Espinoza et al., 2018).”
• Attractor and integrator networks in the brain (2021, background): “…for continuous attractor networks described next, there are many likely candidate areas that exhibit activity dynamics suggestive of and consistent with discrete multistability, including in mammalian hippocampus and auditory cortex, and the fly olfactory system [ 154, 155, 156, 157, 145, 158 ] .”
• In vitro neurons learn and exhibit sentience when embodied in a simulated game-world (2021, unknown): “0001), including those that were more simplified like that used in the pilot where activity on the left moved the paddle left and conversely for the right (Figure S3: Configuration 0) and would be most easily influenced by various sources of bias (Espinoza et al., 2018; Fan et al., 2020; Obermayer e”