Dear Vladimir,
¡¡¡¡Thanks for your detailed explanation, I have already understood what you said.
¡¡¡¡Best wishes to you!
¡¡¡¡Haoran.
--
Haoran LI (MS)
Brain Imaging Lab,
Research Center for Learning Science,
Southeast University
2 Si Pai Lou , Nanjing, 210096, P.R.China
At 2011-03-11 01:07:57£¬"Vladimir Litvak" <[log in to unmask]> wrote:
>2011/3/10 ·ÉÄñ <[log in to unmask]>:
>> Dear Vladimir,
>> ¡¡¡¡Thanks for your detailed reply. As for what you said just now, I still
>> have two questions:
>> ¡¡¡¡1. You said that 'There are
>> some other cases when they might be used, when it is known that two
>> areas are at the same level of cortical hierarchy. '
>> ¡¡¡¡¡¡Do you mean that two different sources may have lateral connections as
>> long as they are in the same level ? Or at least, I can assume there exist
>> lateral connections between them when I construct a specific model ?
>
>Yes
>
> In
>> addition, could you recommend me any literatures about cortical hierachy ?
>
>The classical reference is http://www.ncbi.nlm.nih.gov/pubmed/1822724
>There might be also more recent reviews on the topic.
>
>> 2. I'm not very clear about 'Note that if
>> there is bi-lateral symmetry in your model it wouldn't make sense to
>> assign different types to symmetric connections in the two hemispheres. '
>> ¡¡¡¡Do you mean that whether it is forward connections or backward connection
>> has no influences on the model in that case?
>
>
>I meant that if you have in your model left V1, right V1, left V2 and
>right V2 it wouldn't make sense if the connection between V1 and V2 is
>forward on the left and backward on the right. They should either both
>be forward or both backward and in this particular example you can
>find from the literature that forward is more likely.
>
>Best,
>
>Vladimir
>
>
>
>> ¡¡¡¡Thanks a lot!
>> Haoran.
>>
>> --
>> Haoran LI (MS)
>> Brain Imaging Lab,
>> Research Center for Learning Science,
>> Southeast University
>> 2 Si Pai Lou , Nanjing, 210096, P.R.China
>>
>> At 2011-03-10 18:16:32£¬"Vladimir Litvak" <[log in to unmask]> wrote:
>>
>>>Dear Haoran,
>>>
>>>2011/3/10 ·ÉÄñ <[log in to unmask]>:
>>>> Dear SPM's users,
>>>> ¡¡¡¡When we construct a specific DCM model, we should specify different kinds
>>>> of connections to those sources, but:
>>>> ¡¡¡¡1. I wonder that whether the lateral connections only exist between the
>>>> sources which are in the same level ? And, what does ' the same level ' mean
>>>
>>>Typically, lateral connections are for connecting bi-lateral symmetric
>>>sources i.e. for modelling inter-hemispheric connections. There are
>>>some other cases when they might be used, when it is known that two
>>>areas are at the same level of cortical hierarchy. Usually such
>>>information is available for the well-studied visual system.
>>>
>>>> ? Does it mean the two regions own the same function, such as the left
>>>> visual region and the right visual region ?
>>>
>>>That's one example.
>>>
>>>> ¡¡¡¡2. Does forward connections only exist between the sources which are in
>>>> the different level ? Such as low-level and the high-level ?
>>>> ¡¡¡¡3. Do backward connections are always generate from high-level regions and
>>>> terminate in those low-level regions ?
>>>
>>>Yes, that's the idea.
>>>
>>>> ¡¡¡¡All in a word, how could we specify the different connections among those
>>>> sources ? Any help will be appreciated.
>>>>
>>>
>>>A principled way of doing this is model comparison. Of course if you
>>>want to try the 3 possible options for each connection, you'll
>>>probably have very large number of possibilities. But typically you
>>>would have information about at least some of the connections from the
>>>literature. So if you are not sure about a particular connection, you
>>>can try all the relevant options and do model comparison. Note that if
>>>there is bi-lateral symmetry in your model it wouldn't make sense to
>>>assign different types to symmetric connections in the two
>>>hemispheres. This further constraints your options.
>>>
>>>Best,
>>>
>>>Vladimir
>>>
>>>> --
>>>> Haoran LI (MS)
>>>> Brain Imaging Lab,
>>>> Research Center for Learning Science,
>>>> Southeast University
>>>> 2 Si Pai Lou , Nanjing, 210096, P.R.China
>>>>
>>>>
>>
>>
>>