Figure 9. | Demixed principal component analysis of neural population data

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Demixed principal component analysis of neural population data

Figure 9.

Affiliation details

Champalimaud Centre for the Unknown, Portugal; École Normale Supérieure, France; Centre for Integrative Neuroscience, University of Tübingen, Germany; Wake Forest University School of Medicine, United States; Cold Spring Harbor Laboratory, United States; Universidad Nacional Autónoma de México, Mexico; El Colegio Nacional, Mexico; Harvard University, United States
Figure 9.
Download figureOpen in new tabFigure 9. Balanced and unbalanced data.

(a) In this toy example there are two task parameters (factors), with two possible values each. Parameter A (left) is represented by the size of the dot, parameter B (middle) is represented by the color of the dot, noise is Gaussian with zero mean and zero correlation (right). Interaction term is equal to zero. (b) Balanced case with N=10 data points in each of the four parameter combinations. Overall correlation is zero. (c) Unbalanced case with N=10 for two parameter combinations and N=100 for the other two. Overall correlation is 0.8.