Journal:

Article Title: Semi-automated Region of Interest Generation for the Analysis of Optically Recorded Neuronal Activity

doi: 10.1016/j.neuroimage.2009.04.016

Figure Lengend Snippet: Simulated data were used to estimate type 1 and type 2 error under conditions of varying noise. A. i. simulated image series were based on a 20X image of indicator- loaded tissue. ii. Regions of time-varying fluorescence retained naturalistic morphology and distribution, as they were defined by thresholding the raw image to generate a binary image. iii. Pixels in black regions of the binary image were assigned random values; pixels in white regions were assigned values representing the sum of a time-varying signal and noise; so as to maintain constant dynamic range, as noise was increased the amplitude of the time-varying signal was decreased. B. Time-varying signals assigned to white regions of the binary image were obtained from fluorescence measurements from a respiration modulated neuron (i) or from simulation of sparse activity generated by splicing two peaks associated with inspiratory activity between epochs of random values scaled to 10% of burst amplitude (ii). Upper traces show traces in which signal and noise components were of equal amplitude (S/N=1); lower traces were obtained at S/N=0.33. Traces were scaled so that ΔF/F bars matched. C. Plot of type 1 (□) and type 2 (■) errors as a function of S/N for rhythmic (i) and sparse (ii) simulated datasets. Type 1 error was calculated as the ratio of ROIs that picked out “cells” to the total number of ROIs generated; type 2 error was calculated as the ratio of identified “cells” to the actual number of “cells” in the simulation. Both errors are minimized as these ratios approach 1; to convey conditions under which both types of error are minimized, (1-ratio) is plotted. As S/N decreased the lowest threshold applied to the summed image was increased so as to reduce type 1 error, and more accurately estimate type 2 error (with sufficiently high ROI numbers, all “cells” will be identified). Lowest thresholds are expressed as percent of the simulated image’s dynamic range (right axis), and are indicated by bars.

Article Snippet: Respiratory activity was recorded extracellularly from ventral root C2 at 1 kHz, and optical signals, visualized using an upright microscope (Axioskop 2 FS, Carl Zeiss AG, Oberkochen, DE) through 10X or 20X water-immersion lenses (Achroplan 20x/0.5W/0; Achroplan 10x/0.3 W Ph1, Carl Zeiss AG, Oberkochen, DE), illuminated using a xenon arc lamp (Lambda DG-4, Sutter Instruments, Novato CA) and filtered (480 nm excitation / 505 nm long-pass dichroic mirror / 535 emission; Chroma Technology Corp., Rockingham VT).

Techniques: Fluorescence, Activity Assay, Generated