Biology subjects

Ungerleider, L.

Publications and source records attributed to Ungerleider, L..

6 recordsLinked to original sources

bioRxiv2023

Identifying the cortical face network with dynamic face stimuli: A large group fMRI study

Functional magnetic resonance imaging (fMRI) studies have identified a network of face-selective regions distributed across the human brain. In the present study, we analyzed data from a large group of gender-balanced participants to investigate how reliably these face-selective regions could be identified across both cerebral hemispheres. Participants (N=52) were scanned with fMRI while viewing short videos of faces, bodies, and objects. Results revealed that five face-selective regions: the fusiform face area (FFA), posterior superior temporal sulcus (pSTS), anterior superior temporal sulcus (aSTS), inferior frontal gyrus (IFG) and the amygdala were all larger in the right than in the left hemisphere. The occipital face area (OFA) was larger in the right hemisphere as well, but the difference between the hemispheres was not significant. The neural response to moving faces was also greater in face-selective regions in the right than in the left hemisphere. An additional analysis revealed that the pSTS and IFG were significantly larger in the right hemisphere compared to other face-selective regions. This pattern of results demonstrates that moving faces are preferentially processed in the right hemisphere and that the pSTS and IFG appear to be the strongest drivers of this laterality. An analysis of gender revealed that face-selective regions were typically larger in females (N=26) than males (N=26), but this gender difference was not statistically significant.

neuroscience↗

bioRxiv2022

Measuring the response to visually presented faces in the human lateral prefrontal cortex

Neuroimaging studies have identified multiple face-selective areas. In the current study we compared the functional response of the face area in the lateral prefrontal cortex to that of other face-selective areas. In Experiment 1 participants (N=32) were scanned viewing videos containing faces, bodies, scenes, objects, and scrambled objects. We identified a face-selective area in the right inferior frontal gyrus (rIFG). In Experiment 2 participants (N=24) viewed the videos or static images. Results showed that the rIFG, posterior superior temporal sulcus (pSTS) and occipital face area (OFA) exhibited a greater response to moving than static faces. In Experiment 3 participants (N=18) viewed face videos presented in the contralateral and ipsilateral visual fields. Results showed that the face areas in the IFG and pSTS responded equally to faces in both visual fields, while the OFA and fusiform face area (FFA) showed a contralateral bias. These experiments suggest two conclusions; firstly, in all three experiments the face area in the IFG was not as reliably identified as face areas in the occipitotemporal cortex. Secondly, the similarity of the response patterns in the IFG and pSTS face areas suggests that the areas are functionally connected, a conclusion consistent with neuroanatomical and functional connectivity evidence.

neuroscience↗

bioRxiv2020

CIVET-Macaque: an automated pipeline for MRI-based cortical surface generation and cortical thickness in macaques

The MNI CIVET pipeline for automated extraction of cortical surfaces and evaluation of cortical thickness from in-vivo human MRI has been extended for processing macaque brains. Processing is performed based on the NIMH Macaque Template (NMT), as the reference template, with the anatomical parcellation of the surface following the D99 and CHARM atlases. The modifications needed to adapt CIVET to the macaque brain are detailed. Results have been obtained using CIVET-macaque to process the anatomical scans of the 31 macaques used to generate the NMT and another 95 macaques from the PRIME-DE initiative. It is anticipated that the open usage of CIVET-macaque will promote collaborative efforts in data collection and processing, sharing, and automated analyses from which the non-human primate brain imaging field will advance.

neuroscience↗

bioRxiv2017

An open resource for nonhuman primate imaging

Non-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience.\n\nUnfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMate Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 13 independent data collections aggregated across 11 sites (total = 98 macaque monkeys). We also outline the unique pitfalls and challenges that should be considered in the analysis of the non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.

neuroscience↗

bioRxiv2017

The ventral stream receives spatial information from the dorsal stream during configural face processing

Configural face processing is considered to be vital for face perception. If configural face processing requires an evaluation of spatial information, might this process involve interactions between ventral stream face-processing regions and dorsal stream visuospatial-processing regions? We explored this possibility using thetaburst stimulation (TBS) with fMRI in humans. Participants were shown two faces that differed in either the shape (featural differences) or the spatial configuration (configural differences) of their features. TBS applied on dorsal location-processing regions: 1) reduced fMRI activity within ventral stream face-processing regions during configural but not featural face processing; and 2) reduced functional connectivity between these face regions significantly more for configural than featural face processing. No changes occurred when TBS was delivered on the vertex control site for either face task. We conclude that ventral stream face-processing regions receive visuospatial information from dorsal stream location-processing regions during configural face processing.\n\nSignificance statementFace perception is thought to be mediated exclusively by neural substrates within the ventral visual pathway. However, by using non-invasive brain stimulation (thetabust transcranial magnetic stimulation) in healthy human adults, we demonstrate that the face-processing regions of the ventral visual pathway receive information from visuospatial-processing regions of the dorsal visual pathway during configural face processing, a vital function in face perception. Our findings thus indicate that veridical face perception may depend on both the ventral and dorsal visual pathways.

neuroscience↗

bioRxiv2017

A population MRI brain template and analysis tools for the macaque

The use of standard anatomical templates is common in human neuroimaging, as it facilitates data analysis and comparison across subjects and studies. For non-human primates, previous in vivo templates have lacked sufficient contrast to reliably validate known anatomical brain regions and have not provided tools for automated single-subject processing. Here we present the \"National Institute of Mental Health Macaque Template\", or NMT for short. The NMT is a high-resolution in vivo MRI template of the average macaque brain generated from 31 subjects, as well as a neuroimaging tool for improved data analysis and visualization. From the NMT volume, we generated maps of tissue segmentation and cortical thickness. Surface reconstructions and transformations to previously published digital brain atlases are also provided. We further provide an analysis pipeline using the NMT that automates and standardizes the time-consuming processes of brain extraction, tissue segmentation, and morphometric feature estimation for anatomical scans of individual subjects. The NMT and associated tools thus provide a common platform for precise single-subject data analysis and for characterizations of neuroimaging results across subjects and studies.

neuroscience↗