scipy.io.loadmat nested structures (i.e. dictionaries)

Using the given routines (how to load Matlab .mat files with scipy), I could not access deeper nested structures to recover them into dictionaries

To present the problem I run into in more detail, I give the following toy example:

load scipy.io as spio
a = {'b':{'c':{'d': 3}}}
# my dictionary: a['b']['c']['d'] = 3
spio.savemat('xy.mat',a)

Now I want to read the mat-File back into python. I tried the following:

vig=spio.loadmat('xy.mat',squeeze_me=True)

If I now want to access the fields I get:

>> vig['b']
array(((array(3),),), dtype=[('c', '|O8')])
>> vig['b']['c']
array(array((3,), dtype=[('d', '|O8')]), dtype=object)
>> vig['b']['c']['d']
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)

/<ipython console> in <module>()

ValueError: field named d not found.

However, by using the option struct_as_record=False the field could be accessed:

v=spio.loadmat('xy.mat',squeeze_me=True,struct_as_record=False)

Now it was possible to access it by

>> v['b'].c.d
array(3)