Delta/theta-rhythmically interleaved gamma and beta oscillations in striatum: modeling and data analysis
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Striatal oscillatory activity associated with movement, reward, and decision-making is observed in several interacting frequency bands. Rodent striatal local field potential recordings show dopamine- and reward-dependent transitions between a 'spontaneous' state involving beta (15-30 Hz) and low gamma (40-60 Hz) and a 'dopaminergic' state involving theta (4-8 Hz) and high gamma (60-100 Hz) activity. The mechanisms underlying these rhythmic dynamics and their functional consequences are not well understood. In this thesis, I construct a biophysical model of striatal microcircuits that comprehensively describes the generation and interaction of these rhythms as well as their modulation by dopamine and rhythmic inputs, and test its predictions using human electroencephalography (EEG) data. Chapter 1 describes the striatal model and its dopaminergic modulation. Building on previous work suggesting striatal projection neuron (SPN) networks can generate beta oscillations, I construct a model network of striatal fast-spiking interneurons (FSIs) capable of generating delta/theta (2-6 Hz) and gamma rhythms. This FSI network produces low gamma oscillations under low (simulated) dopaminergic tone, and high gamma activity nested within a delta/theta oscillation under high dopaminergic tone. In a combined model under high dopaminergic tone SPN network beta oscillations are interrupted by delta/theta-periodic bursts of gamma-frequency FSI inhibition. This high dopamine-induced periodic inhibition may enable switching between beta-rhythmic SPN cell assemblies representing motor programs, suggesting that dopamine facilitates movement in part by allowing for rapid, periodic changes in motor program execution. Chapter 2 describes the model's response to square-wave periodic cortical inputs. Comparing models with and without FSIs reveals that the FSI network: (i) prevents the SPN network's generation of phase-locked beta oscillations in response to beta's harmonic frequencies, ensuring fidelity of transmission of cortical beta rhythms; and (ii) limits or entrains SPN activity in response to certain gamma frequency inputs. Chapter 3 describes an analysis of phase-amplitude coupling at cortical electrodes in human EEG data during a reward task. The alternating rhythms predicted by the model appear in response to positive feedback. While the origins of these rhythms remain unclear, if they represent striatal signals, they provide a direct link between human behavior and striatal cellular function.
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