Recurrent Excitatory Feedback From Mossy Cells Enhances Sparsity and Pattern Separation in the Dentate Gyrus via Indirect Feedback Inhibition
It is generally appreciated that storing memories of specific events in the mammalian brain, and associating features of the environment with behavioral outcomes requires fine-tuning of the strengths of connections between neurons through synaptic plasticity. It is less understood whether the organi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-02-01
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| Series: | Frontiers in Computational Neuroscience |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fncom.2022.826278/full |
| _version_ | 1818331783520845824 |
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| author | Alessandro R. Galloni Aya Samadzelkava Kiran Hiremath Reuben Oumnov Aaron D. Milstein |
| author_facet | Alessandro R. Galloni Aya Samadzelkava Kiran Hiremath Reuben Oumnov Aaron D. Milstein |
| author_sort | Alessandro R. Galloni |
| collection | DOAJ |
| description | It is generally appreciated that storing memories of specific events in the mammalian brain, and associating features of the environment with behavioral outcomes requires fine-tuning of the strengths of connections between neurons through synaptic plasticity. It is less understood whether the organization of neuronal circuits comprised of multiple distinct neuronal cell types provides an architectural prior that facilitates learning and memory by generating unique patterns of neuronal activity in response to different stimuli in the environment, even before plasticity and learning occur. Here we simulated a neuronal network responding to sensory stimuli, and systematically determined the effects of specific neuronal cell types and connections on three key metrics of neuronal sensory representations: sparsity, selectivity, and discriminability. We found that when the total amount of input varied considerably across stimuli, standard feedforward and feedback inhibitory circuit motifs failed to discriminate all stimuli without sacrificing sparsity or selectivity. Interestingly, networks that included dedicated excitatory feedback interneurons based on the mossy cells of the hippocampal dentate gyrus exhibited improved pattern separation, a result that depended on the indirect recruitment of feedback inhibition. These results elucidate the roles of cellular diversity and neural circuit architecture on generating neuronal representations with properties advantageous for memory storage and recall. |
| first_indexed | 2024-12-13T13:25:20Z |
| format | Article |
| id | doaj.art-96ecb0a0d5ab4fb1bf744351b965f30d |
| institution | Directory Open Access Journal |
| issn | 1662-5188 |
| language | English |
| last_indexed | 2024-12-13T13:25:20Z |
| publishDate | 2022-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computational Neuroscience |
| spelling | doaj.art-96ecb0a0d5ab4fb1bf744351b965f30d2022-12-21T23:44:18ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882022-02-011610.3389/fncom.2022.826278826278Recurrent Excitatory Feedback From Mossy Cells Enhances Sparsity and Pattern Separation in the Dentate Gyrus via Indirect Feedback InhibitionAlessandro R. GalloniAya SamadzelkavaKiran HiremathReuben OumnovAaron D. MilsteinIt is generally appreciated that storing memories of specific events in the mammalian brain, and associating features of the environment with behavioral outcomes requires fine-tuning of the strengths of connections between neurons through synaptic plasticity. It is less understood whether the organization of neuronal circuits comprised of multiple distinct neuronal cell types provides an architectural prior that facilitates learning and memory by generating unique patterns of neuronal activity in response to different stimuli in the environment, even before plasticity and learning occur. Here we simulated a neuronal network responding to sensory stimuli, and systematically determined the effects of specific neuronal cell types and connections on three key metrics of neuronal sensory representations: sparsity, selectivity, and discriminability. We found that when the total amount of input varied considerably across stimuli, standard feedforward and feedback inhibitory circuit motifs failed to discriminate all stimuli without sacrificing sparsity or selectivity. Interestingly, networks that included dedicated excitatory feedback interneurons based on the mossy cells of the hippocampal dentate gyrus exhibited improved pattern separation, a result that depended on the indirect recruitment of feedback inhibition. These results elucidate the roles of cellular diversity and neural circuit architecture on generating neuronal representations with properties advantageous for memory storage and recall.https://www.frontiersin.org/articles/10.3389/fncom.2022.826278/fullneuronal circuitscomputational modelingdentate gyruspattern separationsparse codingmossy cells |
| spellingShingle | Alessandro R. Galloni Aya Samadzelkava Kiran Hiremath Reuben Oumnov Aaron D. Milstein Recurrent Excitatory Feedback From Mossy Cells Enhances Sparsity and Pattern Separation in the Dentate Gyrus via Indirect Feedback Inhibition Frontiers in Computational Neuroscience neuronal circuits computational modeling dentate gyrus pattern separation sparse coding mossy cells |
| title | Recurrent Excitatory Feedback From Mossy Cells Enhances Sparsity and Pattern Separation in the Dentate Gyrus via Indirect Feedback Inhibition |
| title_full | Recurrent Excitatory Feedback From Mossy Cells Enhances Sparsity and Pattern Separation in the Dentate Gyrus via Indirect Feedback Inhibition |
| title_fullStr | Recurrent Excitatory Feedback From Mossy Cells Enhances Sparsity and Pattern Separation in the Dentate Gyrus via Indirect Feedback Inhibition |
| title_full_unstemmed | Recurrent Excitatory Feedback From Mossy Cells Enhances Sparsity and Pattern Separation in the Dentate Gyrus via Indirect Feedback Inhibition |
| title_short | Recurrent Excitatory Feedback From Mossy Cells Enhances Sparsity and Pattern Separation in the Dentate Gyrus via Indirect Feedback Inhibition |
| title_sort | recurrent excitatory feedback from mossy cells enhances sparsity and pattern separation in the dentate gyrus via indirect feedback inhibition |
| topic | neuronal circuits computational modeling dentate gyrus pattern separation sparse coding mossy cells |
| url | https://www.frontiersin.org/articles/10.3389/fncom.2022.826278/full |
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