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)

```