Identification of Pattern Completion Neurons in Neuronal Ensembles Using Probabilistic Graphical Models
Year: 2021
Type: article
Abstract: Neuronal ensembles are groups of neurons with coordinated activity that could represent sensory, motor, or cognitive states. The study of how neuronal ensembles are built, recalled, and involved in the guiding of complex behaviors has been limited by the lack of experimental and analytical tools to reliably identify and manipulate neurons that have the ability to activate entire ensembles. Such pattern completion neurons have also been proposed as key elements of artificial and biological neural networks. Indeed, the relevance of pattern completion neurons is highlighted by growing evidence that targeting them can activate neuronal ensembles and trigger behavior. As a method to reliably detect pattern completion neurons, we use conditional random fields (CRFs), a type of probabilistic graphical model. We apply CRFs to identify pattern completion neurons in ensembles in experiments usingin vivotwo-photon calcium imaging from primary visual cortex of male mice and confirm the CRFs predictions with two-photon optogenetics. To test the broader applicability of CRFs we also analyze publicly available calcium imaging data (Allen Institute Brain Observatory dataset) and demonstrate that CRFs can reliably identify neurons that predict specific features of visual stimuli. Finally, to explore the scalability of CRFs we apply them toin siliconetwork simulations and show that CRFs-identified pattern completion neurons have increased functional connectivity. These results demonstrate the potential of CRFs to characterize and selectively manipulate neural circuits. SIGNIFICANCE STATEMENTWe describe a graph theory method to identify and optically manipulate neurons with pattern completion capability in mouse cortical circuits. Using calcium imaging and two-photon optogeneticsin vivowe confirm that key neurons identified by this method can recall entire neuronal ensembles. This method could be broadly applied to manipulate neuronal ensemble activity to trigger behavior or for therapeutic applications in brain prostheses.
Source: Journal of Neuroscience
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Awards: Optical methods for imaging and manipulating dendritic spines in vivo, G1480873338, G1501260534, CRCNS Research Project: Solving the neural code of Hydra, G2941508635, G5754284256, Imaging Functional Connectivity in Visual Cortex, G6688908050, CRCNS: Modeling the nanophysiology of dendritic spines, G7220467006, Effect of GABAergic inhibition of dendritic spines on synaptic pruning in the medial prefrontal cortex during adolescence
OpenAlex ID: W3195873474