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Mynick, A.

Publications and source records attributed to Mynick, A..

3 recordsLinked to original sources

Scene perception and visuospatial memory converge at the anterior edge of visually-responsive cortex

To fluidly engage with the world, our brains must simultaneously represent both the scene in front of us and our memory of the immediate surrounding environment (i.e., local visuospatial context). How does the brains functional architecture enable sensory and mnemonic representations to closely interface, while also avoiding sensory-mnemonic interference? Here, we asked this question using first-person, head-mounted virtual reality (VR) and fMRI. Using VR, human participants of both sexes learned a set of immersive, real-world visuospatial environments in which we systematically manipulated the extent of visuospatial context associated with a scene image in memory across three learning conditions, spanning from a single field-of-view to a city street. We used individualized, within-subject fMRI to determine which brain areas support memory of the visuospatial context associated with a scene during recall (Exp. 1) and recognition (Exp. 2). Across the whole brain, activity in three patches of cortex was modulated by the amount of known visuospatial context, each located immediately anterior to one of the three scene perception areas of high-level visual cortex. Individual subject analyses revealed that these anterior patches corresponded to three functionally-defined place memory areas, which selectively respond when visually recalling personally familiar places. In addition to showing activity levels that were modulated by the amount of visuospatial context, multivariate analyses showed that these anterior areas represented the identity of the specific environment being recalled. Together, these results suggest a convergence zone for scene perception and memory of the local visuospatial context at the anterior edge of high-level visual cortex. Significance statementAs we move through the world, the visual scene around us is integrated with our memory of the wider visuospatial context. Here, we sought to understand how the functional architecture of the brain enables coexisting representations of the current visual scene and memory of the surrounding environment. Using a combination of immersive virtual reality and fMRI, we show that memory of visuospatial context outside the current field-of-view is represented in a distinct set of brain areas immediately anterior and adjacent to the perceptually-oriented scene-selective areas of high-level visual cortex. This functional architecture would allow efficient interaction between immediately adjacent mnemonic and perceptual areas, while also minimizing mnemonic-perceptual interference.

neuroscience↗

Visual Experience is not Necessary for the Development of Face Selectivity in the Lateral Fusiform Gyrus

Here we show robust face-selectivity in the lateral fusiform gyrus of congenitally blind participants during haptic exploration of 3D-printed stimuli, indicating that neither visual experience, nor fovea-biased input, nor visual expertise is necessary for face-selectivity to arise in its characteristic location. Similar resting fMRI correlation fingerprints in individual blind and sighted participants suggest a role for long-range connectivity in the specification of the cortical locus of face-selectivity.

neuroscience↗

The speed of human social interaction perception

The ability to detect and understand other peoples social interactions is a fundamental part of the human visual experience that develops early in infancy and is shared with other primates. However, the neural computations underlying this ability remain largely unknown. Is the detection of social interactions a rapid perceptual process, or a slower post-perceptual inference? Here we used magnetoencephalography (MEG) decoding and computational modeling to ask whether social interactions can be detected via fast, feedforward processing. Subjects in the MEG viewed snapshots of visually matched real-world scenes containing a pair of people who were either engaged in a social interaction or acting independently. The presence versus absence of a social interaction could be read out from subjects MEG data spontaneously, even while subjects performed an orthogonal task. This readout generalized across different scenes, revealing abstract representations of social interactions in the human brain. These representations, however, did not come online until quite late, at 300 ms after image onset, well after the time period of feedforward visual processes. In a second experiment, we found that social interaction readout occurred at this same latency even when subjects performed an explicit task detecting social interactions. Consistent with these latency results, a standard feedforward deep neural network did not contain an abstract representation of social interactions at any model layer. We further showed that MEG responses distinguished between different types of social interactions (mutual gaze vs joint attention) even later, around 500 ms after image onset. Taken together, these results suggest that the human brain spontaneously extracts the presence and type of others social interactions, but does so slowly, likely relying on iterative top-down computations.

neuroscience↗