Subject: Re: subtraction and distribution function (was ACI/TI) From: FATIMA HUSAIN <fthusain(at)HELIX.NIH.GOV> Date: Wed, 14 Dec 2005 12:26:45 -0500Dear Al, Chris, Richard and list Just wanted to second what Chris wrote about interpreting brain activations. Very few people hold on to the view of single brain entity doing a single task. The buzz word for a while has been "distributed network". Thinking of distributed network allows us to use techniques like functional connectivity that measure strengths of connections between regions, across or within conditions and subjects. At the risk of tooting our own horn, let me tell you about the large-scale multiple-level type of modeling that we do, which allows us to interpret the fMRI data and investigate mechanisms underlying the activations. This goes beyond data-fitting in that the assumptions we make are based on cellular level data and the predictions we make are matched or tested against fMRI data. I chose just one type of the auditory continuity illusions alluded by Richard Warren (Btw, an excellent book and chapter, I seem to have highlighted almost all of it). The reason glides were chosen because I already had a model (matched with fMRI data) that processed glides. So all I had to do was input the ACI stimuli. And it worked. So now the question is why did it work? I did not create the model to accomplish this illusion nor were any parameters changed. This what I think: Yes, the periphery is involved, but it is not the "seat" or primary source of this illusion. I would guess MGN or higher, and in fact would put my money (btw, I am looking for a job) on a distributed network of regions with the Superior temporal gyrus/sulcus at the apex (in a hierarchical sort of way). The divergent connections from MGN->Primary Auditory Cortex -> Secondary Auditory Cortex -> STG/S result increasing "fan-out" which in turn results in increasing spectro-temporal windows of integration. (The sources for this claim are listed in Husain et al, 2004, Neuroimage). This allows the system to fill in over the noise-filled gaps in the stimuli. I tried different ways to "break" the illusion. I decreased the lateral inhibition in the model in primary auditory cortex (details at Husain et al, Journal of Cognitive Neuroscience, 2005). But this caused the cells to not select for direction of the glides. Then I decreased the fan-out (the divergence of the connections) and found that while the sweeps were processed fine, the illusion disappeard. And in my model, the crucial connection was from PAC to SAC and from SAC to STG/S. (I have speculated on other types of illusion like phonemic restoration but because I have not modeled them, they will remain speculations) I can of course be wrong. But this is a testable hypothesis and we hope to have more data within a few years to verify it. And I think that some version of this mechanism (increasing spectro-temporal windows of integration) is the key, whether it is cortical (as I say) or somewhere else in the central auditory system. Regards, --fatima Fatima T. Husain, Ph.D. Research Fellow Brain Imaging and Modeling Section NIDCD, NIH > > Date: Tue, 13 Dec 2005 19:47:28 -0500 > From: Al Bregman <bregman(at)HEBB.PSYCH.MCGILL.CA> > Subject: Re: subtraction and distributed function [was Re: The Auditory Continuity Illusion/Temporal Induction] > > Dear Chris, > > Thank you for your thoughtful reply. It is clear that using imaging data > is a lot more complicated than people think. You wrote: > > "The question, as you suggest, should be "how" distributed > functions take place, and is unlikely to be answered by any one method, > but rather through the development of computational models on the basis > of descriptive data about the brain and behavior." > > The approach that you suggest (fitting models to data) could be a > productive one, assuming that the models are based on assumptions about > actual types of processing rather than being of the "hip bone is connected > to the ankle bone" type (North American readers will know the song). > > Best wishes, > > Al > > ---------------------------------------------------- > Albert S. Bregman, > Emeritus Professor > Psychology Dept., McGill University > 1205 Docteur Penfield Avenue > Montreal, Quebec > Canada H3A 1B1 > > Voice & Fax: +1 (514) 484-2592 > > Aug 15 - Sept 15 annually: > Voice & Fax +1 (207) 729-0986 > ---------------------------------------------------- > > ----- Original Message ----- > From: "Chris Stecker" <cstecker(at)UMICH.EDU> > To: <AUDITORY(at)LISTS.MCGILL.CA> > Sent: Monday, December 12, 2005 2:57 PM > Subject: subtraction and distributed function [was Re: The Auditory > Continuity Illusion/Temporal Induction] > > >> Hello Al and list, >> >> I'd just like to interject that the difficulty (folly?) of localizing >> distributed functions in the brain is not lost on (all) fMRI >> researchers. I've tried to focus attention on this issue when describing >> to others the direction of my own work in auditory fMRI. There are >> really two kinds of approaches through which we could imagine using the >> subtraction technique. The first depends on assuming modularity of >> function in the brain. If that assumption holds, then two carefully >> designed conditions---one that includes the process of interest, and one >> identical to the first except for the lack of that process---can be used >> via subtraction to identify the module in question. (This is of course >> not a new idea and has been used to look at chronometry, etc. for quite >> some time now.) Many of us, however, doubt the applicability of strict >> modularity, and instead recognize that---even with perfectly designed >> conditions---many things are likely to change in related modules (if one >> expects modularity to hold weakly) or throughout an extremely >> distributed system that subserves the process of interest along with >> many others (if one does not). The second approach is to use subtraction >> as a tool to examine the effects of specific manipulations upon the >> "activations" observed in the brain, and interpret those effects mainly >> in a descriptive sense. For example, we might look at tone-evoked >> activations at different sound levels. We might use subtraction to >> isolate sound-related activity ("sound" - "silence") which we then >> compare across levels, or we might directly compare activations produced >> at different levels ("intense" - "soft"). Either way, we try to describe >> the sensitivity to tone level in different regions of the brain (which >> might in turn tell us a lot about the kinds of computations each region >> is likely to be involved in) rather than to localize the "module that >> processes sound level" or the "module that processes intense sound." [It >> might also be worth pointing out that "subtraction" in this case can be >> replaced by correlation or another statistical technique for assessing >> sensitivity to manipulation of the independent variable across >> potentially many levels; I'm not sure how to interpret such data via the >> modularity assumption, but it makes good sense for the descriptive >> approach.] >> >> Personally, I think the evidence for distributed function (throughout >> the auditory cortex at least) is pretty good, and strongly prefer the >> second, descriptive, approach to interpreting fMRI data. So I agree with >> your post, especially regarding concerns about designing appropriate >> conditions for subtraction and about the interpretation of subtraction >> results via an implicit assumption of modularity. But I want list >> members to realize that the method of subtraction can be employed >> without that assumption, even though they are often encountered >> together. The question, as you suggest, should be "how" distributed >> functions take place, and is unlikely to be answered by any one method, >> but rather through the development of computational models on the basis >> of descriptive data about the brain and behavior. >> >> -Chris Stecker >> >> >