"Number sense", the ability to quickly perceive approximate object quantities in the visual scene, is a crucial cognitive capacity of humans and other animals thought to depend on higher-level brain regions. But how responses to number are derived from visual images and the role of lower-level brain structures in this is not well understood. This project proposes to investigate subcortical areas which have been largely neglected in the study of human cognition, although recent findings in other animals suggest they could contribute to visual number sense. Unlike most non-invasive cognitive neuroscience techniques, ultra-high field functional imaging can measure activity in small and deep subcortical structures. We will use 7 or 11.7T fMRI to study how subcortical visual regions distinguish numbers of objects and their non-numerical properties, compared to cortical regions. Our results could potentially on the longer term provide novel explanations for disturbed numerosity processing.

Numbers, an essential underpinning of human science and technology, do in their most concrete meaning refer to quantities of objects. The ability to rapidly perceive these in an approximate fashion, without serial counting relying on language, is found across human cultures and animal species (1). More advanced numerical abilities of humans, and their impairments in math learning difficulties such as dyscalculia, can to some extent be predicted by differences in the precision of this basic non-verbal “number sense” (2–4). As a consequence, substantial interest in the cognitive neuroscience community concerns the neural bases of visual number sense. Human brain regions associated with number processing encompass a particular fronto-parietal cortical network, and individual neurons selectively responsive to different numbers of items have been described in related brain areas of other animals (1, 5).
A key unresolved question is how such neuronal responses to numerosity are derived from the signals impinging onto our retina, where continuous physical variables co-vary with numbers of objects and a given number can lead to profoundly different stimulation depending on object types and their surroundings. Another question is how numerical responses in high-level brain areas of the human cerebral cortex fit with the presence of number sense in many animal species that lack similarly developed higher brain structures.
Visual inputs in vertebrate species are processed by a series of evolutionarily conserved regions in the midbrain and thalamus before reaching higher cognitive areas (6). The midbrain’s tectum which corresponds to the superior colliculus in mammals, while considered less important for conscious visual recognition in primates, can represent a map of the locations of salient objects in the environment with some degree of independence of those objects’ defining features (7, 8), which could make it particularly suitable as an intermediate step in the extraction of discrete numerosity. Although findings supporting a role of such early regions in numerosity processing have been absent or scarce until recently, results from optical imaging in zebrafish now show that number responsive neurons are indeed not limited to the forebrain but also found in the tectum (9), and specific early visual circuits that according to some views are comparable to those of the vertebrate tectum (10) are required for behavioral numerosity discrimination in flies (11). In humans, behavioral results suggesting that numerosity discrimination may partly rely on monocular parts of the visual system have been interpreted as pointing to an involvement of the subcortex (12), although they cannot determine the region of origin of these effects without ambiguity. In a reanalysis of human fMRI data from subcortical structures from one of our previously published studies (13), we find that pattern signals in regions of the thalamus which receive inputs from the superior colliculus do also to some extent distinguish between different numbers of visual items, although this study was not optimized to achieve best signal in the subcortex and did not precisely focus on distinguishing discrimination of numbers of items per se from differences in other visual features.
In this project, we therefore aim to benefit from the enhanced signal-to-noise ratio offered by functional imaging at ultra-high magnetic fields (14), to conduct more focused high-resolution acquisitions in subcortical areas of interest (superior colliculus and different parts of the thalamus) in addition to parietal cortex, and to understand how those regions represent numbers of objects across changes in non-numerical quantities and types of features defining the objects. The experiments will make use of fMRI at 7 or 11.7 Tesla (15). Given the prevalent focus on the cerebral cortex in human cognitive neuroscience, the idea that evolutionarily older subcortical areas should still have functional relevance for numerical abilities in humans may appear unconventional, but could also be seen as timely given recent reports of a role of regions like the superior colliculus in aspects of higher-level cognition (16). If confirmed, our hypothesis has the potential to profoundly change current ways of thinking about human number cognition, and possibly on the longer term contribute novel explanatory accounts of disturbed number processing (as in dyscalculia).
This project takes place within the Cognitive Neuroimaging Unit (UNICOG) located at the NeuroSpin center in the greater Paris area. The UNICOG laboratory has been a leader in the cognitive neuroscience of number processing and other areas of human cognition for many years and offers a stimulating international work environment. NeuroSpin is France’s most advanced neuroimaging center housing a multi-disciplinary combination of researchers, from experts in data acquisition methods to neuroscientists and clinicians. The center has in recent years developed the Iseult 11.7T human MRI scanner, the highest field strength currently available for human studies in the world. This project will be one of the first to attempt to exploit this system to answer relevant questions about the neural basis of cognition.

References
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