Neuroimaging Evidence of a Bilateral Representation for Visually Presented Numbers.

The clustered architecture of the brain for different visual stimulus categories is one of the most fascinating topics in the cognitive neurosciences. Interestingly, recent research suggests the existence of additional regions for newly acquired stimuli such as letters (letter form area; LFA; Thesen et al., 2012) and numbers (visual number form area; NFA; Shum et al., 2013). However, neuroimaging methods thus far have failed to visualize the NFA in healthy participants, likely due to fMRI signal dropout caused by the air/bone interface of the petrous bone (Shum et al., 2013). In the current study, we combined a 64-channel head coil with high spatial resolution, localized shimming, and liberal smoothing, thereby decreasing the signal dropout and increasing the temporal signal-to-noise ratio in the neighborhood of the NFA. We presented subjects with numbers, letters, false numbers, false letters, objects and their Fourier randomized versions. A group analysis showed significant activations in the inferior temporal gyrus at the previously proposed location of the NFA. Crucially, we found the NFA to be present in both hemispheres. Further, we could identify the NFA on the single-subject level in most of our participants. A detailed analysis of the response profile of the NFA in two separate experiments confirmed the whole-brain results since responses to numbers were significantly higher than to any other presented stimulus in both hemispheres. Our results show for the first time the existence and stimulus selectivity of the NFA in the healthy human brain. SIGNIFICANCE STATEMENT: This fMRI study shows for the first time a cluster of neurons selective for visually presented numbers in healthy human adults. This visual number form area (NFA) was found in both hemispheres. Crucially, numbers have gained importance for humans too recently for neuronal specialization to be established by evolution. Therefore, investigations of this region will greatly advance our understanding of learning and plasticity in the brain. In addition, these results will aid our knowledge regarding related neurological illnesses (e.g., dyscalculia). To overcome the fMRI signal dropout in the neighborhood of the NFA, we combined high spatial resolution with liberal smoothing. We believe that this approach will be useful to the broad neuroimaging community.