X-Chromosome Insufficiency Alters Receptive Fields across the Human Early Visual Cortex

Abstract

Here, we investigated processing by receptive fields, a fundamental property of neurons in the visual system, using fMRI and population receptive field (pRF) mapping in 20 human females with monosomic Turner syndrome (TS) (mean age, 10.3 Ϯ 2.0 years) versus 22 ageand sex-matched controls (mean age, 10.4 Ϯ 1.9 years). TS, caused by X-chromosome haploinsufficiency in females, is associated with well-recognized effects on visuospatial processing, parieto-occipital cortical anatomy, and parietal lobe function. However, it is unknown whether these effects are related to altered brain structure and function in early visual areas (V1-V3) versus downstream parietal cortical regions. Results show that girls with TS have the following: (1) smaller volume of V1-V3, (2) lower average pRF eccentricity in early visual areas, and (3) sparser pRF coverage in the periphery of the visual field. Further, we examined whether the lower volume of early visual areas, defined using retinotopic mapping, in TS is due to smaller surface area or thinner cortex. Results show that girls with TS had a general reduction in surface area relative to controls in bilateral V1 and V2. Our data suggest the possibility that the smaller cortical surface area of early visual areas in girls with TS may be associated with a lower number of neurons, which in turn, leads to lesser coverage of the peripheral visual field compared to controls. These results indicate that X-chromosome haploinsufficiency associated with TS affects the functional neuroanatomy of early visual areas, and suggest that investigating pRFs in TS may shed insights into their atypical visuospatial processing.

Opposing transcriptomic gradients explain orthogonal maps in human visual areas

“…We verify the feasibility of this prediction with CXorf58 (Fig 3), an X chromosome gene whose expression negatively correlated with eccentricity and has been linked to retinitis pigmentosa (RP), which results in perceptual deficits of the peripheral visual field. Mutations in CXorf58 may also explain recent findings 9 showing that females with Turner Syndrome (TS) -a condition in which an X chromosome is damaged or missing 10 -present with deficits in RF coverage of the peripheral visual field specifically in V2 and V3, where CXorf58 is negatively correlated with eccentricity ( Fig 3). Additional mutations in SLITRK4 and RAI2 -both X chromosome genes involved in axonogenesis 11 and cell growth 12 and identified here -could adversely impact peripheral representations where tissue microstructure reductions would hinder the fidelity of neural circuits underlying the pooling of visual information.…”

“…While the condition is hallmarked by a number of physical atypicalities, genes on the short arm of the X chromosome (e.g., short stature homeobox gene, SHOX) have been linked to the stunted bone and limb growth that characterizes the small stature of those with Turner syndrome. Recent research has demonstrated that females with Turner syndrome present with visual deficits in the coverage of the periphery 9 . Retinotopic mapping of population receptive fields (pRF) in these individuals using functional MRI revealed that in V2 and V3, Turner females show reduced pRF coverage of the periphery compared to control females.…”

Population receptive fields in non-human primates from whole-brain fMRI and large-scale neurophysiology in visual cortex

“…The population receptive field (pRF) mapping technique (Dumoulin and Wandell, 2008) has rapidly become a popular method in human neuroimaging, allowing a relatively fast characterization of the retinotopic organization of the brain. Furthermore, since it describes the tuning properties of the underlying voxels, it can also provide insight into more complex visual and cognitive functions (Binda et al, 2018;Ekman et al, 2020;Harvey et al, 2020Harvey et al, , 2015He et al, 2019;Hughes et al, 2019;Mo et al, 2017;Poltoratski et al, 2019;Poltoratski and Tong, 2020;Shao et al, 2013;Shen et al, 2020;Silson et al, 2018;Stoll et al, 2020;Thomas et al, 2015;Welbourne et al, 2018;Zuiderbaan et al, 2017), dysfunctions (Ahmadi et al, 2020;Alvarez et al, 2020;Best et al, 2019;Dumoulin and Knapen, 2018;Green et al, 2019;Schwarzkopf et al, 2014), brain development (Dekker et al, 2019), cortical evolution (Zhu and Vanduffel, 2019), and information transfer across different brain areas (Haak et al, 2013). Human pRFs from neuroimaging studies qualitatively resemble receptive fields recorded with invasive electrophysiological techniques in animal experiments, but since these signals are derived from different species, often with different analytical or experimental methods, it remains an important question what type of neuronal population characteristic is actually measured by the fMRI BOLD-signal (Dumoulin and Wandell, 2008).…”

Extensive individual differences of category information in ventral temporal cortex in the congenitally blind

“…5). The possibility that group effects could mask effects at the individual subject level is also applicable to any study comparing the functional or structural organization of cortical areas between two or more groups -for example, comparing functional representations between a) children and adults (Cantlon et al, 2006;Golarai et al, 2007;Scherf et al, 2007b;Deen et al, 2016) or b) between neurotypical controls and individuals in a clinical population (Temple et al, 2001;Avidan et al, 2005;Duchaine and Nakayama, 2005;Rykhlevskaia et al, 2009;Green et al, 2019bGreen et al, , 2019a. Future studies can also quantify how different types of stimuli such as soundscapes (Amedi et al, 2007) or haptic substitution (Amedi et al, 2001;Pascual-leone et al, 2005;Reich et al, 2011;Murty et al, 2020) influence individual differences in the blind.…”

“…An individual differences hypothesis predicts that irrespective of group-level differences, category representations are significantly more heterogenous among group members to the point that there are similarities between individuals across groups that are larger than similarities between individuals within a group. Empirically supporting either hypothesis has implications for future studies comparing populations at the group and individual level (Temple et al, 2001;Avidan et al, 2005;Duchaine and Nakayama, 2005;Cantlon et al, 2006;Golarai et al, 2007;Scherf et al, 2007a;Rykhlevskaia et al, 2009;Deen et al, 2016;Green et al, 2019bGreen et al, , 2019a .…”