Face recognition is an important part of everyday human social behavior, yet the neural circuits underlying face processing are only beginning to be understood. In particular, it remains unclear how feedback recurrently modifies face representations at the neural level despite evidence that face processing is a dynamic process. Here, I will study the role of feedback in the face patch system in primate inferotemporal cortex (IT). In the mentored phase of the project (Aim 1), I will probe the dynamics of neural responses across the face pathway under challenging image conditions (noise, occlusion) designed to maximally engage recurrent processing. Preliminary data that I have collected show that neural responses in the middle face patch evolve over time to resolve ambiguous information in a manner that correlates with activity in the anterior patches. The next logical step, which is goal of the second half of the mentored phase (Aim 2), is to measure how the anterior face patches causally influence activity in the middle face patch, and pharmacological inactivation of anterior regions will be used to systematically map the locus of feedback. In the independent phase of the project (Aim 3), I will use newly developed optogenetic silencing tools to test how rapidly and precisely projections arising from within the feedback locus can modulate middle face patch activity. An innovative feature of this project is the use of a novel stereo microfocal x-ray syste for registering the precise spatial position of all feedback sources and targets allowing for reconstruction of large scale (Aim 2) and fine scale (Aim 3) maps of source-target interactions. This endeavor will eventually yield an engineer's version of a neural circuit diagram and constrain computational models proposing different roles (gain control, resonance, and prediction) for feedback. The proposed work will be initiated in the laboratory of Jim DiCarlo at MIT. Dr. DiCarlo is a committed mentor that leads a highly collaborative, interdisciplinary research group. During the mentored phase of the project (K99;
Aims 1 and 2), I will acquire training in techniques for population neural recording, pharmacological inactivation, and optogenetics providing an experimental platform for transition to an independent position in the second phase (R00;
Aim 3) of the project.
How the collective action of distributed neural systems leads to our rich percept of the visual world is not well understood, and disorders of the circuits involved in perception, especially those involved in face recognition, can impair normal social function. Understanding the neural circuitry underlying face processing will provide valuable insights into how humans see, will improve next generation brain prosthetics for restoring visual function, and will inspire artificial vision systems.
| Rajalingham, Rishi; Issa, Elias B; Bashivan, Pouya et al. (2018) Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks. J Neurosci 38:7255-7269 |
| Aparicio, Paul L; Issa, Elias B; DiCarlo, James J (2016) Neurophysiological Organization of the Middle Face Patch in Macaque Inferior Temporal Cortex. J Neurosci 36:12729-12745 |
| Issa, Elias B; Papanastassiou, Alex M; DiCarlo, James J (2013) Large-scale, high-resolution neurophysiological maps underlying FMRI of macaque temporal lobe. J Neurosci 33:15207-19 |
| Issa, Elias B; DiCarlo, James J (2012) Precedence of the eye region in neural processing of faces. J Neurosci 32:16666-82 |
