def predict_pRF_radius(eccentricity, visual_area='<STR_LIT>', source='<STR_LIT>'):
visual_area = visual_area.lower()<EOL>if pimms.is_str(source):<EOL><INDENT>source = source.lower()<EOL>if source not in pRF_data:<EOL><INDENT>raise ValueError('<STR_LIT>' % source)<EOL><DEDENT>dat = pRF_data[source]<EOL>dat = dat[visual_area]<EOL><DEDENT>else:<EOL><INDENT>dat = {'<STR_LIT:m>':source[<NUM_LIT:0>], '<STR_LIT:b>':source[<NUM_LIT:1>]}<EOL><DEDENT>return dat['<STR_LIT:m>']*eccentricity + dat['<STR_LIT:b>']<EOL>
predict_pRF_radius(eccentricity) yields an estimate of the pRF size for a patch of cortex at the
  given eccentricity in V1.
predict_pRF_radius(eccentricity, area) yields an estimate in the given visual area (may be given
  by the keyword visual_area).
predict_pRF_radius(eccentricity, area, source) uses the given source to estimate the pRF size
  (may be given by the keyword source).

The following visual areas can be specified:
  * 'V1' (default), 'V2', 'V3'
  * 'hV4'
  * 'V3a', 'V3b'
  * 'VO1', 'VO2'
  * 'LO1', 'LO2'
  * 'TO1', 'TO2'

The following sources may be given:
  * 'Wandell2015': Wandell BA, Winawer J (2015) Computational neuroimaging and population
                   receptive fields. Trends Cogn Sci. 19(6):349-57.
                   doi:10.1016/j.tics.2015.03.009.
  * 'Kay2013: Kay KN, Winawer J, Mezer A, Wandell BA (2013) Compressive spatial summation in
              human visual cortex. J Neurophysiol. 110(2):481-94.
The default source is 'Wandell2015'.