Guided attention in biologically-plausible neural networks

Several researchers have postulated process (Wolfe, 2021) and neural (Grossberg, 1994) computational models of visual attention and perception; however, core tenants of these frameworks are seldom integrated into human-inspired algorithms of computer vision. Here, we illustrate a novel computer vision framework that simulates guided visual attention and processing in humans using a biologically-plausible neurocognitive architecture (Leabra; O’Reilly et al., 2017). We provide an initial demonstration of its efficacy in simulating realistic human visual processing in noisy and degraded visual environments and argue for its potential as a simulation of human visual search with cognitive and biological plausibility.