For over 80 years, researchers have observed rhythmic electrical activity in the neocortex, the outer shell of neurons covering the mammalian brain. Despite the prevalence of these oscillations, their meaning for computation--if and how they help us move, perceive and/or think--is a topic of intense debate. Beta oscillations, rhythmic activity at 15‐29 Hz, are prominent in neocortex. Overexpression of beta is a hallmark of Parkinson's disease, and treatments that relieve its motor symptoms also diminish beta. Similarly, beta oscillations predict failure by human subjects to perceive sensory stimuli. These findings directly implicate beta as important for information processing and healthy brain function. Understanding the detailed origins of beta is crucial to knowing its role and to potentially guiding targeted therapies.
The present study will test a recently developed hypothesis that explains the natural expression patterns of beta in the human brain. This hypothesis emerged from a detailed biophysically accurate and multi‐area computational neural model. To test this hypothesis, the proposed research will use detailed simulations of multiple brain areas to guide experimental recordings and brain stimulation. These data will in turn be used to advance and constrain the model. As part of this research, the model will be elaborated to include interconnected elements from the basal ganglia, thalamus and neocortex.
These same areas will be targets for neural recording, to understand how their activity correlates with neocortical beta in anesthetized and behaving preparations processing sensory information. Causal testing of model predictions will be achieved by leveraging recent innovations in optogenetics, the application of light pulses to turn neurons on and off with millisecond precision and cell-type specificity. Optogenetics will test in a real brain the sufficiency and necessity of the activity patterns that are predicted by the model to lead to expression of this brain rhythm.
Beta rhyhtms (14-29Hz) are one of the most dominant activities recorded non-invasively in humans with techniques such as electro- and magneto-encephalography. There expression changes with attention and is a direct predictor of perception and motor action. However, the underlying cellular level events creating this rhythm is unknown, limiting our understanding of its contribution to perception andaction. We invetigated the cellular and network mechanisms creating neocortical beta by combinging MEG imgaing biophysiologicaly principled computational modeling, and laminar electrophysiological recordings in anesthetized mice and awake monkeys. The model provided a interpretative link between the macroscipically measured MEG signals and the meso- and microscopic level activity, which were validated with the animal local field potential recordings (see Figure 1). Our results showed that beta events emerged from the integration of synchronous bursts of excitatory synaptic drive targeting proximal and distal pyramidal neuron dendrites, such that the distal drive was stronger and lasted one beta period. Further, when this pattern of synaptic drive emerged during stochastic 10-Hz rhythmic drives, global features of the continuous somatosensory rhythms were also reproduced, including co-occurring bouts of alpha (7-14Hz) activity. This novel mechanism rigorously accounted for beta event profiles in human MEG signals while prior theorized mechanisms of beta generation did not (Figure 2). Laminar recordings in anesthetized mice and awake macaques supported these predictions (Figure 3 ad Figure 4), suggesting this mechanism is conserved across species and recording modalities. This beta mechanism makes several predictions about optimal states for perceptual and motor performance and guides causal interventions to modulate beta for optimal function.
