In the past, I have been interested on how the visual system processes natural scenes. To this end, I have recorded naturalistic movies using micro-cameras carried by cats while they were actively exploring a natural environment. I used these movies to train neuronal networks in an unsupervised manner and compared learnt features to the known properties of neurons in visual cortex. I also used these videos as stimuli during physiological recordings to gain insights on the principles of natural signal processing in the visual cortex.
Recently, I started working on how humans make generalizations based on what they have previously learnt. To this end, I am using a variety of methodologies including fMRI (1), autonomous (2), as well as eye-movement recordings (3). This research emanates from the well-established field of "stimulus generalization" following mainly the "lineage" of Hovland, Hull and Roger Shepard (4), and including the more recent computational work of Josua Tenenbaum (5). Furthermore, it integrates work on anxiety disorders, as it is believed that these mechanisms are impaired in people suffering from anxiety problems.
Export SPM results table to spreadsheet for publication
When using SPM (Statistical Parametric Mapping) for the analysis of fMRI data, one soon or later needs to export the numbers in the "SPM Results Table" to a spreadsheet format to include in a publication. While the SPM Table is neatly organized within a Matlab Figure, it is not easy to export the numbers to a friendly format.
SPM results table.
Here is a small Matlab function that simplifies the process. It neatly dumps all values in an SPM table into a .txt file.
Same table in the text editor.
You can then easily import this text file to your spreadsheet engine (excel, gdoc, etc.) as a tab separated .txt file. With little cosmetic efforts, it is ready to be inserted in your next publication.