Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2006 Jan;27(1):37-46.
doi: 10.1002/hbm.20165.

Repetition-induced changes in BOLD response reflect accumulation of neural activity

Affiliations

Repetition-induced changes in BOLD response reflect accumulation of neural activity

Thomas W James et al. Hum Brain Mapp. 2006 Jan.

Abstract

Recent exposure to a stimulus improves performance with subsequent identification of that same stimulus. This ubiquitous, yet simple, memory phenomenon is termed priming and has been linked to another widespread phenomenon called repetition suppression, which is a repetition-induced reduction in human brain activation as measured using fMRI. Here, competing models of the neural basis of repetition suppression were tested empirically. In a backward masking paradigm, we found that effectively masked object stimuli showed repetition enhancement of brain activation instead of suppression. This finding is consistent with an Accumulation model, but is inconsistent with a Suppression model of neural activity. Enhanced activation and the improved behavioral performance usually associated with priming are both explained by a shift in peak latency of the population neural activity elicited during identification.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Suppression model. The right graph illustrates a simulated neural response to a single repeated (gray) and nonrepeated (black), nondegraded stimulus. The left graph illustrates a simulated BOLD response to those same stimuli. Note that the neural activity and BOLD response graphs use different time scales. The primed neural activity is suppressed and produces a smaller BOLD response.
Figure 2
Figure 2
Accumulation model. The right graph illustrates a simulated neural response to a single repeated (gray) and nonrepeated (black), nondegraded stimulus. The left graph illustrates a simulated BOLD response to those same stimuli. Note that the neural activity and BOLD response graphs use different time scales. The primed neural activity is shifted leftward in time and produces a smaller BOLD response.
Figure 3
Figure 3
Backward masking predictions. The right graphs illustrate a simulated neural response to a single repeated (gray) and nonrepeated (black), stimulus embedded in noise and masked. The left graphs illustrate a simulated BOLD response to those same stimuli. Note that the neural activity and BOLD response graphs use different time scales. Termination of activity due to masking produces opposite results in BOLD response for Accumulation and Suppression models.
Figure 4
Figure 4
Lateral occipital complex. Stimuli used in the localizer runs were high‐contrast intact and scrambled images of familiar objects. Brain images show the extent of the acquired functional data and, within that area, the location of group LOC averaged across nine observers (stereotaxic coordinates: x = 39, y = −61, z = 3; x = −39, y = −64, z = −1). [Color figure can be viewed in the online issue, which is available at www.interscience.wiley.com.]
Figure 5
Figure 5
Backward masking results. Stimuli used in the event‐related runs, shown in A, were images of familiar objects presented at three levels of contrast and embedded in Gaussian noise. Half of the images were preexposed during the localizer runs (primed). Stimulus presentation (83 ms) was preceded by a warning fixation cross (800 ms) and followed by the mask stimulus (117 ms), then followed by 8 s of rest. Activation time courses are shown in B for identified (top) and unidentified or effectively masked (bottom) objects. Black lines: nonprimed; gray lines: primed. Error bars are square root of MSE/n. Accumulation predictions for the upper and lower graphs can be found in Figures 2 and 3, respectively.

Similar articles

Cited by

References

    1. Bar M, Tootell RBH, Schacter DL, Greve DN, Fischl BR, Mendola JD, Rosen BR, Dale AM (2001): Cortical mechanisms specific to explicit visual object recognition. Neuron 29: 529–535. - PubMed
    1. Becker S, Moscovitch MM, Behrmann M, Joordens S (1997): Long‐term semantic priming: a computational account and empirical evidence. J Exp Psychol Learn Mem Cogn 23: 1059–1082. - PubMed
    1. Bichot NP, Schall JD (1999): Effects of similarity and history on neural mechanisms of visual selection. Nat Neurosci 2: 549–554. - PubMed
    1. Bichot NP, Schall JD (2002): Priming in macaque frontal cortex during popout visual search: feature‐based facilitation and location‐based inhibition of return. J Neurosci 22: 4675–4685. - PMC - PubMed
    1. Boynton GM, Engel SA, Glover GH, Heeger DJ (1996): Linear systems analysis of functional magnetic resonance imaging in human V1. J Neurosci 16: 4207–4221. - PMC - PubMed