Neuronal networks within the brain exhibit an extraordinary complexity, laying the groundwork for behavioral and cognitive processing. External cues profoundly impact critical functions like learning and motor control by gating environmental information to the brain. Dynamic modulation of neural connectivity in response to external cues underscores the brain's adaptability and plasticity, while network dysfunction leads to neurological disorders. High-performance neural activity indicators have facilitated the study of neuronal networks at single-cell level during behavior. In this dissertation, we employed calcium imaging and local field potential (LFP) recordings complemented by customized algorithms, to investigate the influence of external cues on neural network dynamics during learning and locomotion. In the first study, we examined how sensory cue dependent learning relates to the dynamic changes of hippocampal neuronal networks. We performed calcium imaging of hippocampal CA1 neurons in mice during trace eye-blink conditioning and subsequent extinction learning. We examined cellular and network changes using both conventional data analytical approaches and a novel co-activity-based network approach algorithm to monitor trial-by-trial evolution of population responses. Our findings revealed that unique
pairs of neurons are differentially activated leading to distinct network patterns encoding the two types of learning, although the connectivity density of the network remained constant. These results underline the hippocampus’s role in encoding behaviorally relevant external cues. In parallel, to understand the role of sensory cues on motor behavior, we investigated the impact of sensory cues on neural network dynamics and locomotion in the dorsal striatum, a brain region critical for motor control. Focusing on beta (10–30 Hz) rhythms, known for their significance in motor circuits, we examined how beta-frequency
sensory stimulation impacts motor circuit regulation during stepping. We delivered audiovisual stimulation at 10 Hz or 145 Hz in mice voluntarily locomoting and conducted multimodal analysis using calcium imaging and LFP. Our findings indicate that sensory stimulation enhances locomotion and desynchronizes the striatal network. Notably, only 10 Hz stimulation effectively entrains striatal LFPs, improves stepping rhythmicity, and enhances the coupling between stepping and striatal LFP delta and beta oscillations. These results underscore the therapeutic potential of non-invasive beta-frequency sensory stimulation for improving gait.Overall, this dissertation sheds light on the neural mechanisms in sensory driven learning and locomotion, from single-cell to network levels. These insights offer avenues for developing therapeutic strategies by targeted modulation of specific network features. Moreover, this work provides a robust toolkit for studying neural network dynamics in response to external cues, deepening our understanding of brain function and dysfunction and revealing the complex orchestration of neural activity that drives adaptive behavior.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/48871 |
| Date | 24 May 2024 |
| Creators | Sridhar, Sudiksha |
| Contributors | Han, Xue |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution-NonCommercial-ShareAlike 4.0 International, http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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