Preserved extrastriate visual network in a monkey with substantial, naturally occurring damage to primary visual cortex

Abstract

Lesions of primary visual cortex (V1) lead to loss of conscious visual perception with significant impact on human patients. Understanding the neural consequences of such damage may aid the development of rehabilitation methods. In this rare case of a Rhesus macaque (monkey S), likely born without V1, the animal’s in-group behaviour was unremarkable, but visual task training was impaired. With multi-modal magnetic resonance imaging, visual structures outside of the lesion appeared normal. Visual stimulation under anaesthesia with checkerboards activated lateral geniculate nucleus of monkey S, while full-field moving dots activated pulvinar. Visual cortical activation was sparse but included face patches. Consistently across lesion and control monkeys, functional connectivity analysis revealed an intact network of bilateral dorsal visual areas temporally correlated with V5/MT activation, even without V1. Despite robust subcortical responses to visual stimulation, we found little evidence for strengthened subcortical input to V5/MT supporting residual visual function or blindsight-like phenomena.

Roux-en-Y gastric bypass surgery progressively alters radiologic measures of hypothalamic inflammation in obese patients

“…In the present study, we asked whether RYGB attenuates obesity-associated hypothalamic inflammation in humans using established radiologic techniques (28)(29)(30)(31)(32)(42)(43)(44)(45)(46). We also used a potentially novel, more sensitive analysis method that entails a straightforward division of T2W by T1W images to enhance waterbased contrast (39,40). Unexpectedly, we found that hypothalamic T2W SI values, and particularly T2W/ T1W SI ratios, gradually increased while hypothalamic FA values gradually decreased after RYGB.…”

“…T1W and T2W MRI data were aligned onto the Montreal Neurological Institute (MNI) standard template using the Functional MRI of the Brain (FMRIB) Linear Registration Tool (FLIRT) application within the FMRIB Software Library (FSL) (68). This approach builds on the approach used to more sensitively assess gray matter myelination from dividing T1W images by T2W images, which exponentially increases fat-based contrast (39,40). If water is represented by x in the T2W image and by 1/x in the T1W image, and if the receive bias field is represented by b in both images, then: T2W/T1W = x*b / (1/x)*b = x 2 This eliminates receive bias field and exponentially increases water-based contrast (39).…”

“…Therefore, to assess in more detail whether RYGB attenuates obesity-associated hypothalamic inflammation in the clinical setting, we performed analyses on T2W and DW MRI brain datasets of 27 morbidly obese patients obtained at baseline and 6 and 12 months after surgery (38). In a potentially novel approach, we further calculated hypothalamic T2W/T1-weighted (T1W) SI ratios on the basis that they may more sensitively reflect changes in hypothalamic inflammation status by exponentially enhancing water-based contrast (39,40).…”

Combining Brain Perturbation and Neuroimaging in Non-human Primates

“…V1 itself shows limited reorganisation following lesions to the retina in adult monkeys (Smirnakis et al, 2005). However, after naturally occurring neonatal lesions of V1, the extrastriate visual network connectivity was largely intact (Bridge et al, 2019). The time-course of lesion impact on network reorganisation and behavior could be more effectively demonstrated in future studies by investigating the effects of similar lesions at different developmental stages and as a function of aging.…”

A comprehensive macaque fMRI pipeline and hierarchical atlas

“…The NMT is a high-resolution template generated through iterative nonlinear alignment of 31 adult rhesus macaques; it was designed for group analyses and to facilitate collaboration and replicability in macaque research. The NMT has been used as a standardized space for a multitude of macaque imaging studies (Ainsworth et al, 2020;Arcaro et al, 2019;Ball and Seal, 2019;Bridge et al, 2019Bridge et al, , 2018Guehl et al, 2020;Menon et al, 2019;Milham et al, 2018;Ortiz-Rios et al, 2018;Seidlitz et al, 2018), and it serves as a standardized macaque space in which data can be aligned, displayed and analyzed within Neurovault (Gorgolewski et al, 2015), AFNI (Cox, 1996) and CIVET (Lepage et al, this issue).…”