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Functional Magnetic Resonance Imaging Adaptation (fMRIa)

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Functional magnetic resonance imaging adaptation (fMRIa) is a noninvasive psychophysical tool used to study neuronal functioning[1]. This technique could also be referred to as repetition suppression.[2] fMRI is a magnetic resonance imaging procedure that uses blood oxygen level dependent responses to measure brain activity[3]. It is a brain scan that uses a magnetic field to align the neurons in the brain that are being studied in a specific area. fMRI signals are used because they represent changes in neuronal activity that are responsible for a specific task[1]. The adaptation aspect of fMRIa refers to the sensitivity adjustment in response to a stimulus[4]. In a basic fMRIa experiment, a stimulus is presented which ignites a set of neurons in the brain that are sensitive to this specific stimulus. After presenting the stimulus for some time, the set of neurons tend to adapt to the stimulus. After the first group of neurons have adapted, a second stimulus is presented that is either similar to the adapter stimulus or one that is different in some dimension. If the fMRI signals are stronger for the different stimulus rather than the similar stimulus then it is inferred that neurons in that specific area have selective sensitivity to that manipulated dimension[4]. In other words, if only one set of neurons have adapted, the other region of neurons should elicit a stronger response because they have not adapted. This is because the group of neurons receives less restriction from the adapted population[1]. Recently, there has been an abundance of fMRI studies that are using adaptation as tool to make presumptions about neural selectivity in specific cortical regions[5]. Over the ten years that fMRIa has been around, it has been extensively applied to various visual phenomena. This technique is very complex and results can only be obtained with great care[6]. The very first study to use functional magnetic resonance imaging adaptation was Tootell et al. in 1995. Tootell et al. measured blood oxygen level dependent (BOLD) responses as stimuli switched from one orientation to another, or as what he referred to as motion aftereffect[7]. Their main finding was that new visual orientations stimulated new subpopulations of neurons. It is worth noting that the timescale of the presented stimulus and duration of which the neurons have adapted, have a large influence of the susceptibility of adaptation in a region[6]. The major downfall of Tootell’s study was that attention, or therefore lack of, was misinterpreted as evidence of rebound from adaptation. Other studies have found that even though adaptation is reduced in the absence of attention, it does not totally disappear.[8]

Visual Perception

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fMRIa has heavily focused on visual perception in the last few years. In the visual cortex, the susceptibility of an area for adaptation is majorly influenced by the duration of adaptation.[5] Several conclusions have been made in various studies involving the visual cortex and fMRIa. Fang et al., found that humans have a distributed yet constricted viewer-centered representation in the visual system. This is due to the finding that there was face viewpoint adaptation in several face-selective regions but not in the non-face-selective areas. There is also evidence suggesting that fMRI adaptation in the visual cortex is category-specific.[5] Other studies have tested the invariance of object representation to other visual properties. The conclusion is that no adaptation occurs in a specific brain area when an object is transformed across a visual property. Therefore it seems as though representations in that specific region are sensitive to that visual property.[9] Functional magnetic resonance imaging has also been used to study the nature of face representation in the visual cortex. Showing a subject the same face several times results in adaptation in the fusiform face area(FFA).[6] Interestingly, adaptation disappeared if the same face was presented from a different angle.[10] These results provide significant insight into human face processing, and the single-cell input support them.[8]

Discoveries

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Several discoveries have arisen over the past ten years. There is no doubt that fMRIa provides novel insight in the human brain in regards of neural representations.[6] Ganel et al. have concluded that functional magnetic resonance imaging adaptation can be distinguished from repetition priming.[11] Repetition priming is the finding that the way an individual responds to an initial presentation of a stimulus will determine the way in which an individual will respond to that same stimulus when it is presented at a later time.[12] The strongest evidence for this claim was that when fMRIa and repetition priming were combined, the effects were additive rather than subtractive, in the object-selective brain regions. Though not so much a discovery, something useful that was found is that attention can modify fMRIa signals.[4] Eye fixation and attention are important during fMRIa because losing focus from the adapting stimulus may weaken the adaptation effect.[4] This discovery is important because it will aid others in future research. Not only is specific stimulus adaptation a property special to the visual modality, but also to the auditory cortex of anesthetized cats.[13]

Advantages

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There are great advantages to functional magnetic resonance imaging adaptation. First and foremost, it is a noninvasive tool that does not require probing of any sort. Due to this noninvasive measure, fMRIa provides information on neural processes that may be different from information obtained in invasive animal experiments.[1] This technique is very sensitive to change, for example, if a subject shifts his or her attention for a split second, the fMRI scans will recognize it.[2] In other words, it is a significant tool for analyzing fine-scale spatial sensitivity.[14] It is extremely useful because it specifically shows where and how information is represented in the brain.[6] Lastly, it allows one to study the functional response of a brain area at a subvoxel level.[2]

Limitations

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The main limitation of fMRIa is that because it is a new technique, it is still not fully understood. Since fMRIa is very complex, it needs to be done with extreme care and precision.[6] fMRIa does not yet have adequate spatial resolution or temporal resolution therefore it has difficulties determining the timing and nature of the neuronal mechanisms.[11] Another pitfall is that fMRI may fail to detect the actual site of origin of adaptation, and stress sites that are just receiving input from the adapted sites.[1] Across and array of studies, three findings were considered to confuse the interpretation of fMRIa results: disinhibition, inherited adaptation and adaptation-induced change in tuning. Disinhibition refers to the process in which adaptation of one neuron decreases the inhibitory input to other neurons, therefore inducing their response which could lead to false results. Inherited adaptation refers to the idea that adaptations at the focus level could be "inherited" from earlier levels in the cortical area. Lastly, adaptation-induced change in tuning refers to the concern that adaptation does not necessarily slow down the firing rate, rather it changes the tuning curves in regards to speed and direction.[6]

Future Research

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In future research, researchers need to make sure that they find a way to control spatial attention in order to get adequate results[8]. As mentioned previously, to this day fMRIa is still not fully understood. Future research should try to explain the factors that influence fMRIa whether it be the amount of repetitions, the duration of repetitions, the temporal separation between them, or the number of intervening stimuli. It is still in question as to whether the source of fMRIa is a local, prompt and automatic effect, or whether it is impacted by top-down processes.[15] Another factor to keep in mind in future research is the existing interaction between the test stimulus and the adapting stimulus. This interaction affects the interpretation of the fMRIa results[6]. Once all of the knots get worked out in fMRIa, it will be even more of a useful tool in the field of psychophysics.

References

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  1. ^ a b c d e Bartels, A., Logothetis, N. K., & Moutoussis, K. (2008). fMRI and its interpretations: An illustration on directional selectivity in area V5/MT. Trends in Neurosciences, 31(9), 444-453. doi: http://dx.doi.org/10.1016/j.tins.2008.06.004
  2. ^ a b c Weigelt, S., Muckli, L., & Kohler, A. (2008). Functional magnetic resonance adaptation in visual neuroscience. Reviews in the Neurosciences, 19(4-5), 363-380. doi:http://dx.doi.org/10.1515/REVNEURO.2008.19.4-5.363
  3. ^ Huettel, S. A.; Song, A. W.; McCarthy, G. (2009), Functional Magnetic Resonance Imaging (2 ed.), Massachusetts: Sinauer, ISBN 978-0-87893-286-3
  4. ^ a b c d Fang, F., Murray, S.O., Kersten, D., & He, S. (2005). Orientation-tuned fmri adaptation in human visual cortex. Journal of neurophysiology, 94(6), 4188-4195. doi: 10.1152/jn.00378.2005
  5. ^ a b c Fang, F., Murray, S.O., Kersten, D., & He, S. (2007). Duration-dependent fMRI adaptation and distributed viewer-centered face representation in human visual cortex. Cerebral cortex, 17(6), 1402-1411. doi: 10.1093/cercor/bhl053
  6. ^ a b c d e f g h Krekelberg, B., Boynton, G.M., & van Wezel, R.J.A. (2006). Adaptation: From single cells to BOLD signals. Trends in Neurosciences, 29(5), 250-256. doi: 10.1016/j.tins.2006.02.008
  7. ^ Tootell, R. B. H., Reppas, J. B., Dale, A. M., Look, R. B., Sereno, M. I., Malach, R., . . .Rosen, B. R. (1995). Visual motion aftereffect in human cortical area MT revealed by functional magnetic resonance imaging. Nature, 375(6527), 139-141. doi: http://dx.doi.org/10.1038/375139a0
  8. ^ a b c Larsson, J., & Smith, A. T. (2012). fMRI repetition suppression: Neuronal adaptation or stimulus expectation? Cerebral Cortex, 22(3), 567-576. Retrieved from https://www.lib.uwo.ca/cgibin/ezpauthn.cgi/docview/1017617225?accountid=15115
  9. ^ Freud, E., Ganel, T., & Avidan, G. (2013). Representation of possible and impossible objects in the human visual cortex: Evidence from fMRI adaptation. NeuroImage, 64(1), 685-692. doi: http://dx.doi.org/10.1016/j.neuroimage.2012.08.070
  10. ^ Lee, Y., Grady, C. L., Habak, C., Wilson, H. R., & Moscovitch, M. (2011). Face processing changes in normal aging revealed by fMRI adaptation. Journal of Cognitive Neuroscience, 23(11), 3433-3447. doi: http://dx.doi.org/10.1162/jocn_a_00026
  11. ^ a b Ganel, T., Gonzalez, C.L.R., Valyear, K.F., Culham, J.C., Goodale, M.A., & Kohlera, S. (2006). The relationship between fMRI adaptation and repetition priming. Neuroimage 32, 1432-1440.
  12. ^ Goldstein, E.B. (2008). Cognitive Psychology: connecting mind, research, and everyday experience (2nd ed.) Wadsworth: Australia.
  13. ^ Sawamura, H., Orban, G.A., & Vogels, R. (2006). Selectivity of neuronal adaptation does not match response selectivity: A single-cell study of the fMRI adaptation paradigm. Neuron, 49(2), 307-318. doi: 10.1016/j.neuron.2005.11.028
  14. ^ Murray, S. O., Olman, C. A., & Kersten, D. (2006). Spatially specific fMRI repetition effects in human visual cortex. Journal of Neurophysiology, 95(4), 2439-2445. doi: http://dx.doi.org/10.1152/jn.01236.2005
  15. ^ Grill-Spector, K., & Malach, R. (2001). fMRI-adaptation: A tool for studying the functional properties of human cortical neurons. Acta Psychologica 107(2001), 293-321. PII: S 0 0 0 1 – 6 9 1 8 0 0 1 ) 0 0 0 1 9 – 1