Functional imaging of numerical processing in adults and 4-y-old children

Jessica F Cantlon, Elizabeth M Brannon, Elizabeth J Carter, Kevin A Pelphrey, Jessica F Cantlon, Elizabeth M Brannon, Elizabeth J Carter, Kevin A Pelphrey

Abstract

Adult humans, infants, pre-school children, and non-human animals appear to share a system of approximate numerical processing for non-symbolic stimuli such as arrays of dots or sequences of tones. Behavioral studies of adult humans implicate a link between these non-symbolic numerical abilities and symbolic numerical processing (e.g., similar distance effects in accuracy and reaction-time for arrays of dots and Arabic numerals). However, neuroimaging studies have remained inconclusive on the neural basis of this link. The intraparietal sulcus (IPS) is known to respond selectively to symbolic numerical stimuli such as Arabic numerals. Recent studies, however, have arrived at conflicting conclusions regarding the role of the IPS in processing non-symbolic, numerosity arrays in adulthood, and very little is known about the brain basis of numerical processing early in development. Addressing the question of whether there is an early-developing neural basis for abstract numerical processing is essential for understanding the cognitive origins of our uniquely human capacity for math and science. Using functional magnetic resonance imaging (fMRI) at 4-Tesla and an event-related fMRI adaptation paradigm, we found that adults showed a greater IPS response to visual arrays that deviated from standard stimuli in their number of elements, than to stimuli that deviated in local element shape. These results support previous claims that there is a neurophysiological link between non-symbolic and symbolic numerical processing in adulthood. In parallel, we tested 4-y-old children with the same fMRI adaptation paradigm as adults to determine whether the neural locus of non-symbolic numerical activity in adults shows continuity in function over development. We found that the IPS responded to numerical deviants similarly in 4-y-old children and adults. To our knowledge, this is the first evidence that the neural locus of adult numerical cognition takes form early in development, prior to sophisticated symbolic numerical experience. More broadly, this is also, to our knowledge, the first cognitive fMRI study to test healthy children as young as 4 y, providing new insights into the neurophysiology of human cognitive development.

Figures

Figure 1. Task Design
Figure 1. Task Design
Participants were given the experiment-irrelevant task of fixating on a central crosshair and pressing a joystick button when the crosshair turned red. They passively viewed a stream of visual arrays, the majority of which contained the same number of elements and element shape. Occasionally, a stimulus was presented that deviated from the standard stimuli ineither number of elements (number deviants)or local element shape (shape deviants). Cumulative surface area, density, element size, and spatial arrangement varied among standard stimuli so that participants were not habituated to these dimensions. Deviant and standard stimuli overlapped in cumulative surface area, density, element size, or spatial arrangement so that these dimensions were never novel for deviant stimuli. Number deviants differed by a 2:1 ratio from the standard number of elements such that half of the numerical deviants had a greater number of elements than the standard, and the other half had fewer elements. Elements in standard arrays were circles while shape deviants contained squares or triangles.
Figure 2. Adult Participant's fMRI Results
Figure 2. Adult Participant's fMRI Results
(A) Regions that were more active during the presentation of number compared to shape deviants (p < .05, cluster size > six functional voxels). (B) Regions that were more active during the presentation of shape compared to number deviants (p < .05, cluster size > six functional voxels). (C) Time course of activity (percent signal change) for number-selective (number > shape) regions in the IPS, averaged from individually-drawn functional regions of interest from the IPS, from 3 s pre-stimulus to 12 s post-stimulus.
Figure 3. Child Participant's fMRI Results
Figure 3. Child Participant's fMRI Results
(A) Regions that were more active during the presentation of number compared to shape deviants (p < .05, cluster size > six functional voxels). (B) Regions that were more active during the presentation of shape compared to number deviants (p < .05, cluster size > six functional voxels). (C) Time course of activity (percent signal change) for number-selective (number > shape) regions in the IPS, averaged from individually-drawn functional regions of interest from the IPS, from 3 s pre-stimulus to 12 s post-stimulus.
Figure 4. Data from Individual Children
Figure 4. Data from Individual Children
Each row presents an individual participant's activation map indicating regions that were more active during the presentation of number compared to shape deviants (p < .05, cluster size > eight functional voxels) overlaid on that child's own anatomical images. One child moved during the anatomical scan (which occurred after the functional scan) and is thus not included in this figure.
Figure 5. Child and Adult Number-Selective Brain…
Figure 5. Child and Adult Number-Selective Brain Regions
(Number > shape from Figures 2 and 3) plotted in same space. Adults showed more extensive areas of activation than children; however, the same brain regions were active for children as for adults in this study.

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