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Binocular disparity provides critical information about three-dimensional (3D) structures to support perception and action. In the past decade significant progress has been made in uncovering human brain areas engaged in the processing of binocular disparity signals. Yet, the fine-scale brain processing underlying 3D perception remains unknown. Here, we use ultra-high-field (7T) functional imaging at submillimeter resolution to examine fine-scale BOLD fMRI signals involved in 3D perception. In particular, we sought to interrogate the local circuitry involved in disparity processing by sampling fMRI responses at different positions relative to the cortical surface (i.e., across cortical depths corresponding to layers). We tested for representations related to 3D perception by presenting participants (male and female, N = 8) with stimuli that enable stable stereoscopic perception [i.e., correlated random dot stereograms (RDS)] versus those that do not (i.e., anticorrelated RDS). Using multivoxel pattern analysis (MVPA), we demonstrate cortical depth-specific representations in areas V3A and V7 as indicated by stronger pattern responses for correlated than for anticorrelated stimuli in upper rather than deeper layers. Examining informational connectivity, we find higher feedforward layer-to-layer connectivity for correlated than anticorrelated stimuli between V3A and V7. Further, we observe disparity-specific feedback from V3A to V1 and from V7 to V3A. Our findings provide evidence for the role of V3A as a key nexus for disparity processing, which is implicated in feedforward and feedback signals related to the perceptual estimation of 3D structures. SIGNIFICANCE STATEMENT Binocular vision plays a significant role in supporting our interactions with the surrounding environment. The fine-scale neural mechanisms that underlie the brain9s skill in extracting 3D structures from binocular signals are poorly understood. Here, we capitalize on recent advances in ultra-high-field functional imaging to interrogate human brain circuits involved in 3D perception at submillimeter resolution. We provide evidence for the role of area V3A as a key nexus for disparity processing, which is implicated in feedforward and feedback signals related to the perceptual estimation of 3D structures from binocular signals. These fine-scale measurements help bridge the gap between animal neurophysiology and human fMRI studies investigating cross-scale circuits, from micro circuits to global brain networks for 3D perception.

The brain’s capacity to adapt to sensory inputs is key for processing sensory information efficiently and interacting in new environments. Following repeated exposure to the same sensory input, brain activity in sensory areas is known to decrease as inputs become familiar, a process known as adaptation. Yet, the brain-wide mechanisms that mediate adaptive processing remain largely unknown. Here, we combine multimodal brain imaging (functional magnetic resonance imaging [fMRI], magnetic resonance spectroscopy) with behavioral measures of orientation-specific adaptation (i.e., tilt aftereffect) to investigate the functional and neurochemical mechanisms that support adaptive processing. Our results reveal two functional brain networks: 1) a sensory-adaptation network including occipital and dorsolateral prefrontal cortex regions that show decreased fMRI responses for repeated stimuli and 2) a perceptual-memory network including regions in the parietal memory network (PMN) and dorsomedial prefrontal cortex that relate to perceptual bias (i.e., tilt aftereffect). We demonstrate that adaptation relates to increased occipito-parietal connectivity, while decreased connectivity between sensory-adaptation and perceptual-memory networks relates to GABAergic inhibition in the PMN. Thus, our findings provide evidence that suppressive interactions between sensory-adaptation (i.e., occipito-parietal) and perceptual-memory (i.e., PMN) networks support adaptive processing and behavior, proposing a key role of memory systems in efficient sensory processing.

Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalize on the sub-millimetre resolution afforded by ultra-high field imaging to examine BOLD-fMRI signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive visual processing. We demonstrate suppressive recurrent processing within visual cortex, as indicated by stronger BOLD decrease in superficial than middle and deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show dissociable connectivity mechanisms for adaptive processing: enhanced feedforward connectivity within visual cortex, while feedback occipito-parietal connectivity, reflecting top-down influences on visual processing. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.

Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet, evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer-scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high field (7T) functional imaging at sub-millimetre resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths. Our results provide evidence for recurrent plasticity, by contrast to sensory encoding vs. feedback mechanisms. We demonstrate that learning alters orientation-specific representations in superficial rather than middle V1 layers, suggesting changes in read-out rather than input signals. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings propose finer-scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro-circuits of experience-dependent plasticity.

Summary Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high-field (7T) functional imaging at sub-millimeter resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths that are known to support dissociable brain computations. We demonstrate that learning alters orientation-specific representations in superficial rather than middle or deeper V1 layers, consistent with recurrent plasticity mechanisms via horizontal connections. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings reveal finer scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro-circuits of experience-dependent plasticity., Highlights • Discrimination training alters orientation representations in superficial V1 layers • Orientation-specific V1 plasticity is independent of task context • Discrimination training alters orientation representations in middle IPS layers • Learning enhances feedforward connectivity from visual to parietal cortex, Using high-field laminar fMRI, Jia et al. show that learning alters orientation-specific representations in superficial V1 layers and enhances connectivity from visual to parietal cortex, suggesting that recurrent visual plasticity and feedforward connectivity gate perceptual decision making.

Visual perception is strongly influenced by contextual information. A good example is reference repulsion, where subjective reports about the direction of motion of a stimulus are significantly biased by the presence of an explicit reference. These perceptual biases could arise early, during sensory encoding, or alternatively, they may reflect decision-related processes occurring relatively late in the task sequence. To separate these two competing possibilities, we asked (human) subjects to perform a fine motion-discrimination task and then estimate the direction of motion in the presence or absence of an oriented reference line. When subjects performed the discrimination task with the reference, but subsequently estimated motion direction in its absence, direction estimates were unbiased. However, when subjects viewed the same stimuli but performed the estimation task only, with the orientation of the reference line jittered on every trial, the directions estimated by subjects were biased and yoked to the orientation of the shifted reference line. These results show that judgements made relative to a reference are subject to late, decision-related biases . A model in which information about motion is integrated with that of an explicit reference cue, resulting in a late, decision-related re-weighting of the sensory representation, can account for these results.