Hi Marco,
Given jitter as suggested by Matt, and given that there is a sufficiently
long temporal interval between the critical word and the sentence
onset, a pragmatic approach might be to model the sentence onset
(or more generally portions of the sentence you are not interested in)
and the critical word with separate events. I think this could on the one hand
ensure that your critical word does not 'drown' in the average
signal elicited by the sentence (when modeling the whole sentence
as an epoch) and on the other hand also make sure that
signal related to the sentence onset is not modeled as the
implicit baseline.
Not absolutely sure about that, but maybe someone else can
comment on this.
Best,
Christian
On Wed, 10 May 2006 15:49:55 +0100
Matt Davis <[log in to unmask]> wrote:
> Hi Marko and Marco,
>
> I would agree with Marko that the problem is with HRF measurements rather than knowing when
>words were presented to participants. However, I would suggest that the slow TR of typical fMRI
>studies provides a more serious limitation on the temporal resolution that can be achieved when
>trying to identify the timing of events within sentences.
>
> Assuming that the rise time of the evoked HRF is consistent for different events then any model
>that is time-locked to your events of interest would seem to be suitable (FIR, or hrf +
>derivatives would be ok, but I'm not sure that a Fourier set is suitable). However, if you are
>trying to distinguish events that occur 1 second apart, and your TR is 3 seconds, then it seems
>unlikely to me that you'll have be able to make reliable inferences about timing differences.
>
> Might this be a situation in which the nyquist sampling theory applies? That is, to detect
>events that are n seconds apart requires a TR < n/2. We have a recent paper (Schwarzbauer et al,
>2006, NeuroImage) that detected events three seconds apart within sentences using a semi-sparse
>sequence with a TR of 1 second - consistent with the nyquist limit. However, I am also aware of
>papers on BOLD latency measurement (e.g. Bellgowan, PNAS, 2003; Henson et al., 2002; NeuroImage),
>that seem to do better than this - perhaps because they reduce the effective TR by ensuring that
>the SOA is not an integer multiple of the TR - ie. adding some jitter as Marko also suggested.
>
> hope this is helpful,
>
> matt
>
>
> At 14:36 10/05/2006, Marko Wilke wrote:
>>Hi Marco,
>>
>>>I am also facing a similar problem, as I have tried to model time-locked events occurring within
>>>auditorily presented sentences (of more or less constant duration) in an event-related design
>>>with continuous fMRI sampling. Up to now, I have tried modelling the appearance of the verb with
>>>an informed set of hemodynamic basis functions (hrf + 2 derivatives) with very little success.
>>
>>This is just an uninformed destructive opinion, but I would think that the principal problem is
>>that your excellent timing on the input side (knowing exactly when which word appears) is
>>somewhat destroyed on the output side (the brain) by the smearing occurring by the real
>>hemodynamic response.
>>
>>However, we have recently investigated the effect of removing certain key words from a sentence
>>and replacing them with a 750ms sinus tone (Wilke et al, NeuroReport 2005). While there was a
>>difference between a simple block design analysis and an event-related analysis, it was not huge,
>>and our stimulus was certainly more discrete than a simple verb within a sentence.
>>
>>>I was now considering to use a FIR basis set time-locked to the beginning of each sentence, in
>>>order to try to capture responses associated to the processing of the entire sentence and/or to
>>>early or late sentence components.
>>
>>I would think it's the brain that's the problem (not the basis functions), but perhaps you can
>>overcome some of the issues by additional jittering.
>>
>>>Does anybody have an idea of whether a FIR model would be appropriate for such a purpose? Would a
>>>Fourier basis set be better/worse?
>>
>>No idea.
>>Best,
>>Marko
>>--
>>=====================================================================
>>Marko Wilke (Dr.med./M.D.)
>> [log in to unmask]
>>
>>Universitäts-Kinderklinik University Children's Hospital
>>Abt. III (Neuropädiatrie) Dept. III (Pediatric neurology)
>> Hoppe-Seyler-Str. 1, D - 72076 Tübingen
>>Tel.: (+49) 07071 29-83416 Fax: (+49) 07071 29-5473
>>=====================================================================
>
> ****************************************************
> Dr Matt Davis
> MRC Cognition and Brain Sciences Unit
> 15 Chaucer Road, Cambridge, CB2 2EF
>
> email: [log in to unmask]
> tel: 01223 273 637 (direct line)
> tel: 01223 355 294 (reception)
> fax: 01223 359 062
>
> ****************************************************
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