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. Author manuscript; available in PMC: 2020 Apr 9.
Published in final edited form as: J Neural Eng. 2019 Apr 10;16(4):046003. doi: 10.1088/1741-2552/ab1834

Figure 5.

Figure 5.

PatcherBot performance in brain slices. (a) Success rates of cell detection and whole-cell recordings as a function of cell depth in slices. Data from cortical and sub-cortical experiments were combined. The depth of the target cell did not significantly impact cell detection likelihood (OR = 1.00, CI: 0.98–1.03, P = 0.8, n = 126 attempts) and whole-cell recording likelihood (OR = 1.00, CI: 0.98–1.03, P = 0.65, n = 126 attempts). (b) Whole-cell success rate in brain slices. Reuses did not significantly decrease likelihood of whole-cell recording (OR = 1.07, CI: 0.97–1.17, P = 0.19, n = 245 attempts). (c) Success rate of cell detection and whole-cell recordings with and without machine vision (machine vision off: n = 18 attempts; machine vision on: n = 161 attempts). Cell detection (top): P = 2.4 × 10−5, whole-cell (bottom): P = 1.7 × 10−5, Fisher’s exact test. Alconox was used as the cleaning agent.