Tony Carricarte

Visual object perception is mediated by information flow between regions of the ventral visual stream along feedforward and feedback anatomical connections. However, feedforward and feedback signals during naturalistic vision are rapid and overlapping, complicating their identification and precise functional specification. Here we recorded human layer-specific fMRI responses to naturalistic object images in early visual cortex (EVC) and lateral occipital complex (LOC) to isolate feedforward and feedback information signals spatially by their cortical layer-specific termination pattern. We combined these layer-specific fMRI responses with electroencephalography (EEG) responses for the same images to segregate feedforward and feedback signals in both time and space. Feedforward signals emerge early in the middle layers of EVC and LOC, followed by feedback signals in the superficial layer of LOC. Comparing the identified dynamics in LOC to a visual deep neural network (DNN), revealed that early feedforward signals in LOC encode medium-to-high complexity features, whereas later feedback signals increase the representational format to high complexity features. Together this specifies the spatiotemporal dynamics and functional role of feedforward and feedback information flow mediating visual object perception.

Visual object perception is mediated by information flow between regions of the ventral visual stream along feedforward and feedback anatomical connections. However, feedforward and feedback signals during naturalistic vision are rapid and overlapping, complicating their identification and precise functional specification. Here we recorded human layer-specific fMRI responses to naturalistic object images in early visual cortex (EVC) and lateral occipital complex (LOC) to isolate feedforward and feedback information signals spatially by their cortical layer-specific termination pattern. We combined these layer-specific fMRI responses with electroencephalography (EEG) responses for the same images to segregate feedforward and feedback signals in both time and space. Feedforward signals emerge early in the middle layers of EVC and LOC, followed by feedback signals in the superficial layer of LOC. Comparing the identified dynamics in LOC to a visual deep neural network (DNN), revealed that early feedforward signals in LOC encode medium-to-high complexity features, whereas later feedback signals increase the representational format to high complexity features. Together this specifies the spatiotemporal dynamics and functional role of feedforward and feedback information flow mediating visual object perception.

Visual imagery and veridical perception are phenomenologically related, suggesting that they share neural machinery. Previous research confirmed this assumption at the macroscale of human cortical organization in category-selective regions in ventral visual cortex. However, imagery and perception differ fundamentally in the information flow that underlies them: perception is driven by the integration of sensory feedforward and internally-generated feedback information, whereas imagery depends on feedback only. This suggests that while visual imagery and perception may activate common cortical regions, they do so in fundamentally distinctive ways. To investigate, we resolved neural activity during imagery and perception in the ventral visual cortex at the level of laminar organization that anatomically and functionally distinguishes feedforward from feedback information flow. We found distinctive laminar profiles for imagery and perception of scenes and faces in parahippocampal place area (PPA) and fusiform face area (FFA) respectively. Our findings clarify the neural basis of the phenomenology of visual imagery versus perception, and shed new light on how feedforward and feedback information processing in high-level ventral visual cortex orchestrates human object vision.