Abstract
A key challenge in neuroimaging remains to understand where, when, and now particularly how human brain networks compute over sensory inputs to achieve behavior. To study such dynamic algorithms from mass neural signals, we recorded the magnetoencephalographic (MEG) activity of participants who resolved the classic XOR, OR, and AND functions as overt behavioral tasks (N = 10 participants/task, N-of-1 replications). Each function requires a different computation over the same inputs to produce the task-specific behavioral outputs. In each task, we found that source-localized MEG activity progresses through four computational stages identified within individual participants: (1) initial contralateral representation of each visual input in occipital cortex, (2) a joint linearly combined representation of both inputs in midline occipital cortex and right fusiform gyrus, followed by (3) nonlinear task-dependent input integration in temporal-parietal cortex, and finally (4) behavioral response representation in postcentral gyrus. We demonstrate the specific dynamics of each computation at the level of individual sources. The spatiotemporal patterns of the first two computations are similar across the three tasks; the last two computations are task specific. Our results therefore reveal where, when, and how dynamic network algorithms perform different computations over the same inputs to produce different behaviors.
Highlights
Extensive studies revealed that the primate visual system comprises the ventral and dorsal pathways, with specific anatomical and functional hierarchical organization (Van Essen et al, 1992; Kravitz et al, 2013)
These pathways compute over the high-d imensional visual input, starting separately in each hemisphere with contralateral detection of simple, small features with small receptive fields, that are hierarchically integrated into more complex, broader receptive field features (Bugatus et al, 2017; Hubel and Wiesel, 1962; Kay et al, 2015), leading to the integrated face, object, and scene features (DiCarlo and Cox, 2007; Grill-Spector and Weiner, 2014; Kriegeskorte et al, 2008; Sigala and Logothetis, 2002) that are compared with memory to produce behavior
Our analyses reveal that individual MEG source responses reflect changing representations of the visual inputs in the brain, revealing four different stages of neural computations that lead to behavior in each task
Summary
Extensive studies revealed that the primate visual system comprises the ventral and dorsal pathways, with specific anatomical and functional hierarchical organization (Van Essen et al, 1992; Kravitz et al, 2013) These pathways compute over the high-d imensional visual input, starting separately in each hemisphere with contralateral detection of simple, small features with small receptive fields, that are hierarchically integrated into more complex, broader receptive field features (Bugatus et al, 2017; Hubel and Wiesel, 1962; Kay et al, 2015), leading to the integrated face, object, and scene features (DiCarlo and Cox, 2007; Grill-Spector and Weiner, 2014; Kriegeskorte et al, 2008; Sigala and Logothetis, 2002) that are compared with memory to produce behavior We achieved such systems-level algorithmic understanding with magnetoencephalographic (MEG) measurements, in the context of well-d efined visual inputs and tasks
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