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Byron M. Yu

4 accepted papers

2025

OMiSO: Adaptive optimization of state-dependent brain stimulation to shape neural population states

NeurIPS 2025poster

The coordinated activity of neural populations underlies myriad brain functions. Manipulating this activity using brain stimulation techniques has great potential for scientific and clinical applications, as it provides a tool to causally influence brain function. To improve the accuracy by which on…

Cited by 0SourceScholar
2024

MiSO: Optimizing brain stimulation to create neural activity states

NeurIPS 2024poster

Brain stimulation has the potential to create desired neural population activity states. However, it is challenging to search the large space of stimulation parameters, for example, selecting which subset of electrodes to be used for stimulation. In this scenario, creating a model that maps the conf…

Cited by 1SourcePDFScholar
2023

Uncovering motifs of concurrent signaling across multiple neuronal populations

NeurIPS 2023spotlight

Modern recording techniques now allow us to record from distinct neuronal populations in different brain networks. However, especially as we consider multiple (more than two) populations, new conceptual and statistical frameworks are needed to characterize the multi-dimensional, concurrent flow of s…

2017

Adaptive stimulus selection for optimizing neural population responses

NeurIPS 2017poster

Adaptive stimulus selection methods in neuroscience have primarily focused on maximizing the firing rate of a single recorded neuron. When recording from a population of neurons, it is usually not possible to find a single stimulus that maximizes the firing rates of all neurons. This motivates optim…

Cited by 21SourcePDFScholar