One way to save yourself a lot of time is to write analysis code that can automatically perform a first-pass analysis of an experiment, by 1) generating fits and calculating index values that are commonly used, and 2) generating simple plots so that you can examine the data. When I was a postdoc and had things working smoothly, I would run these automatic functions while I was cleaning up the experiment, and by the next morning the data would be ready to interpret.
I run these analyses after all the primary data collection is finished. That is
the log is complete
any little errors that occurred during data collection have been addressed
any directory that has improperly or poorly collected data (that is, a cell died or the image went blank) has been "neutered" by changing the reference.txt filename to reference0.txt or something similar.
spikes have been extracted, or fluorescence has been calculated from images
This is analyzetftraining.m, a file that analyzes the impact of motion training at one speed on direction selectivity at many speeds:
function [cells,cellnames]=analyzetftraining(thedir, redoresponses, redoanalysis, plotit, saveit)
% ANALYZESCRAMBLED - Perform fitting analysis for a tftraining training experiment
%
% [CELLS,CELLNAMES]=ANALYZETFTRAINING(THEDIR, REDORESPONSES, REDOANALYSIS,...
% PLOTIT, SAVEIT)
%
% Analyses data from the experiment in directory THEDIR.
% Inputs:
% DORESPONSES - If is 1, then the raw responses are re-extracted
% REDOANALSYS - If is 1, then fits are performed
% PLOTIT - If is 1, then a plot is made for each extraction or fit
% SAVEIT - If 1, the extractions/fit results are saved to the experiment.mat file
% STEP 1: READ IN THE CELLS
ds = dirstruct(thedir);
[cells,cellnames] = load2celllist(getexperimentfile(ds),'cell*','-mat');
allcellnames = cellnames;
% STEP 2: ADD INFORMATION THAT IDENTIFIES THE STIMULI IN EACH DIRECTORY
[dummy,cells] = add_testdir_info(ds,cells); % add the directory information
% STEP 3: If we are importing spikes from Plexon, we need our own records of unit quality
%cellinfo = read_unitquality(ds); % not needed since we're not importing from plexon
%[cells,cellnames]=filter_by_quality(ds,cells,cellnames,cellinfo); % limit by cell quality
% STEP 4: Limit the cells we will analyze to those that are numbered between 50 and 75
% for Neil's experiment, we want only the spikes sorted with the VH lab tool
[cells,cellnames] = filter_by_index(cells,cellnames,50,75); % only get VH lab sorted spikes
% STEP 5: Give the user a chance to see the names of the cells that are going to be analyzed
% this gives the user a chance to abort before hours of analysis run
disp(['Cells we have now:']);
cellnames,
pause(5);
% STEP 6: Identify the type of training that was used
training_assoc = read_trainingtype(ds,'ErrorIfNoTrainingType',1,'ErrorIfNoTrainingAngle',1,...
'ErrorIfNoTF',1);
% STEP 7: extract responses -- use spike times and stimulus times to determine stimulus responses
% get the list of all the stimulus types we know
[dirtestnamelist,velocitytestnamelist,tftrainingtestnamelist] = vhdirectiontrainingtypes(1);
if redoresponses,
for i=1:length(cells),
disp(['Now analyzing cell ... ' cellnames{i} ', (' int2str(i) ' of ' int2str(length(cells)) ')']);
for j=1:length(training_assoc),
% add training info to each cell's information in the database
cells{i} = associate(cells{i},training_assoc(j));
end;
% identify the time of each recording
cells{i}=extractstimdirectorytimes(ds,cells{i},...
'ErrorIfEmpty',1,'EarlyMorningCutOffTime',7);
% Now do the extraction for all stimulus types we know: See extraction notes below
cells{i}=performsingleunitgrating(ds,cells{i},cellnames{i},...
dirtestnamelist,'angle',plotit);
cells{i}=performsingleunitgrating(ds,cells{i},cellnames{i},...
velocitytestnamelist,'tFrequency',plotit);
cells{i}=performsingleunitgrating(ds,cells{i},cellnames{i},...
tftrainingtestnamelist,'stimnumber',plotit);
end;
if saveit,
saveexpvar(ds,cells,cellnames);
else,
disp(['Not saving per user request.']);
end;
end;
if redoanalysis,
for i=1:length(cells),
disp(['Now fitting cell ... ' cellnames{i} ...
', (' int2str(i) ' of ' int2str(length(cells)) ')']);
% perform orientation and direction fitting; see fitting notes below
cells{i} = performspperiodicgenericanalysis(ds,cells{i},cellnames{i},...
plotit,dirtestnamelist,'p.angle',...
'otanalysis_compute','',3);
end;
if saveit,
saveexpvar(ds,cells,cellnames);
else,
disp(['Not saving per user request.']);
end;
end;
[Notes here on performsingleunitgrating]
[Notes here on performspperiodicgenericanalysis]