arXiv subjects

Eli J. Müller

Publications and source records attributed to Eli J. Müller.

3 recordsLinked to original sources

arXiv2025

Modeling the influences of non-local connectomic projections on geometrically constrained cortical dynamics

The function and dynamics of the cortex are fundamentally shaped by the specific wiring configurations of its constituent axonal fibers, also known as the connectome. However, many dynamical properties of macroscale cortical activity are well captured by instead describing the activity as propagating waves across the cortical surface, constrained only by the surface's two-dimensional geometry. It thus remains an open question why the local geometry of the cortex can successfully capture macroscale cortical dynamics, despite neglecting the specificity of Fast-conducting, Non-local Projections (FNPs) which are known to mediate the rapid and non-local propagation of activity between remote neural populations. Here we address this question by developing a novel mathematical model of macroscale cortical activity in which cortical populations interact both by a continuous sheet and by an additional set of FNPs wired independently of the sheet's geometry. By simulating the model across a range of connectome topologies, external inputs, and timescales, we demonstrate that the addition of FNPs strongly shape the model dynamics of rapid, stimulus-evoked responses on fine millisecond timescales ($\lessapprox 30~\text{ms}$), but contribute relatively little to slower, spontaneous fluctuations over longer timescales ($> 30~\text{ms}$), which increasingly resemble geometrically constrained dynamics without FNPs. Our results suggest that the discrepant views regarding the relative contributions of local (geometric) and non-local (connectomic) cortico-cortical interactions are context-dependent: While FNPs specified by the connectome are needed to capture rapid communication between specific distant populations (as per the rapid processing of sensory inputs), they play a relatively minor role in shaping slower spontaneous fluctuations (as per resting-state functional magnetic resonance imaging).

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arXiv2024

Analyzing the Brain's Dynamic Response to Targeted Stimulation using Generative Modeling

Generative models of brain activity have been instrumental in testing hypothesized mechanisms underlying brain dynamics against experimental datasets. Beyond capturing the key mechanisms underlying spontaneous brain dynamics, these models hold an exciting potential for understanding the mechanisms underlying the dynamics evoked by targeted brain-stimulation techniques. This paper delves into this emerging application, using concepts from dynamical systems theory to argue that the stimulus-evoked dynamics in such experiments may be shaped by new types of mechanisms distinct from those that dominate spontaneous dynamics. We review and discuss: (i) the targeted experimental techniques across spatial scales that can both perturb the brain to novel states and resolve its relaxation trajectory back to spontaneous dynamics; and (ii) how we can understand these dynamics in terms of mechanisms using physiological, phenomenological, and data-driven models. A tight integration of targeted stimulation experiments with generative quantitative modeling provides an important opportunity to uncover novel mechanisms of brain dynamics that are difficult to detect in spontaneous settings.

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arXiv2023

Noradrenergic neuromodulation of nonlinear bursting neurons controls critical dynamics

In order to remain adaptable to a dynamic environment, neural activity must be simultaneously both sensitive and stable. To solve this problem, the brain has been hypothesised to sit near a critical boundary. Yet, precisely how criticality and these opposing information processing modes are implemented in the brain remains elusive. A potential solution to this problem involves modulating intrinsically nonlinear neurons within the cerebral cortex with neuromodulatory neurotransmitters such as noradrenaline, a highly-conserved chemical released from the pontine locus coeruleus. Here we confirm that neuronal spiking in mice is poised close to the critical point of a branching process and that time-varying signatures of criticality fluctuate with neuromodulatory tone, as assessed by dynamic alterations in pupil diameter. We explore these results theoretically by creating a dual-compartment model of non-linear pyramidal neurons - capable of both regular spike and bursting modes - that replicates our main empirical findings of slightly subcritical dynamics. We then probe our model at a resolution impossible in vivo to demonstrate that noradrenaline differentially alters spiking- and bursting-criticality to facilitate sensitive and stable dynamics following an inverted-U profile that peaks at intermediate noradrenergic tone. Finally, we demonstrate that this intermediate noradrenergic regime displays burst avalanches with power-law size and duration distributions and scaling relationship belonging to the universality class of self-organized criticality. Our results confirm that the noradrenergic ascending arousal system acts as a control parameter for emergent critical dynamics in the brain. This methodology could be extended to explore other neuromodulators as control parameters of the brain.

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