High-throughput Morphometric Analysis of Individual Neurons

Chi Cheng Wu, John F. Reilly, Warren G. Young, John Morrison, Floyd E. Bloom

Research output: Contribution to journalArticlepeer-review

32 Scopus citations


To facilitate high-throughput quantitative analysis of neuronal structure, this study optimized the diOlistic method of whole neuron labeling to examine multiple neurons in fixed brain, and optimized image acquisition parameters to preserve signal for subsequent photoconversion. Fluorescent dye-coated gold particles were successively delivered by helium-powered ejection to 250 μm thick brain slices with loading density and penetration depth optimized to maximize the yield of labeled neurons within the slice while avoiding overlapping labeled dendritic processes in the x-y plane and z-axis. Labeled neurons were imaged using confocal laser-scanning microscopy with pinhole aperture and scan speed enhanced to minimize capture time and fluorescence degradation. Optimized image acquisition parameters preserved fluorescence signal and facilitated subsequent oxygen-enriched photoconversion for higher magnification dendritic spine analysis. Sampling criteria limited analysis to neurons whose z-axis dendritic processes were fully contained within the tissue slice and in which dye transport extended to the most distal portions of the dendrites. The yield of completely labeled neurons was, on average, more than 20 cells per brain region per animal. With optimized spatio-temporal diOlistic loading parameters, along with image acquisition parameters optimized for subsequent photoconversion, the present protocol provides a high-throughput strategy for full-scale quantitative analysis of three-dimensional neuronal morphology.

Original languageEnglish (US)
Pages (from-to)543-554
Number of pages12
JournalCerebral Cortex
Issue number5
StatePublished - May 1 2004
Externally publishedYes


  • Cell morphology
  • DiOlistic
  • Photoconversion
  • Single-cell resolution

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience


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