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Best practices for avoiding dominant experimental bias in analysis of multielectrode array signals

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(A) Principal components analysis biplots using all 60 electrodes. Each marker is a recording. Colors indicate batches: Batch 1 (purple), Batch 2 (red), Batch 3(orange), Batch 4 (light green), Batch 5 (grey), Batch 6 (blue), Batch 7 (pink), and Batch 8 (dark green). The large black circle is the dense core of recordings showing weak spike activity. Classes A, B and C are also labeled. (B) PCA biplots using the 47 electrodes following deletion of biased ones. Some regions are associated with specific cultures identified by culture numbers and batch colors.
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Figure 1: (A) Principal components analysis biplots using all 60 electrodes. Each marker is a recording. Colors indicate batches: Batch 1 (purple), Batch 2 (red), Batch 3(orange), Batch 4 (light green), Batch 5 (grey), Batch 6 (blue), Batch 7 (pink), and Batch 8 (dark green). The large black circle is the dense core of recordings showing weak spike activity. Classes A, B and C are also labeled. (B) PCA biplots using the 47 electrodes following deletion of biased ones. Some regions are associated with specific cultures identified by culture numbers and batch colors.

Mentions: We utilize 878 recordings from embryonic rat cortex cell cultures collected from 60-electrode, grid-type (200 μm) MEA’s. We modeled each recording as a 60-node directed weighted graph with weights describing electrode connectivity and nodal clustering coefficients [1] as features. Principal components analysis (PCA) reduced the dimensionality of this feature space [2]. We observe a dense core of recordings showing weak spike activity, and 3 classes defined by batch (labeled in Figure 1A). Surprised at this structure, we sought a non-biological explanation. We identified 13 defective or biased electrodes as sources of systematic measurement error. Removing the affected electrodes produced a more complex interplay of inter- and intra-batch variability (Figure 1B).


Best practices for avoiding dominant experimental bias in analysis of multielectrode array signals
(A) Principal components analysis biplots using all 60 electrodes. Each marker is a recording. Colors indicate batches: Batch 1 (purple), Batch 2 (red), Batch 3(orange), Batch 4 (light green), Batch 5 (grey), Batch 6 (blue), Batch 7 (pink), and Batch 8 (dark green). The large black circle is the dense core of recordings showing weak spike activity. Classes A, B and C are also labeled. (B) PCA biplots using the 47 electrodes following deletion of biased ones. Some regions are associated with specific cultures identified by culture numbers and batch colors.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4126412&req=5

Figure 1: (A) Principal components analysis biplots using all 60 electrodes. Each marker is a recording. Colors indicate batches: Batch 1 (purple), Batch 2 (red), Batch 3(orange), Batch 4 (light green), Batch 5 (grey), Batch 6 (blue), Batch 7 (pink), and Batch 8 (dark green). The large black circle is the dense core of recordings showing weak spike activity. Classes A, B and C are also labeled. (B) PCA biplots using the 47 electrodes following deletion of biased ones. Some regions are associated with specific cultures identified by culture numbers and batch colors.
Mentions: We utilize 878 recordings from embryonic rat cortex cell cultures collected from 60-electrode, grid-type (200 μm) MEA’s. We modeled each recording as a 60-node directed weighted graph with weights describing electrode connectivity and nodal clustering coefficients [1] as features. Principal components analysis (PCA) reduced the dimensionality of this feature space [2]. We observe a dense core of recordings showing weak spike activity, and 3 classes defined by batch (labeled in Figure 1A). Surprised at this structure, we sought a non-biological explanation. We identified 13 defective or biased electrodes as sources of systematic measurement error. Removing the affected electrodes produced a more complex interplay of inter- and intra-batch variability (Figure 1B).

View Article: PubMed Central - HTML

No MeSH data available.