In this functional magnetic resonance imaging study we tested whether the predictability of stimuli affects responses in primary visual cortex (V1). The results of this study indicate that visual stimuli evoke smaller responses in V1 when their onset or motion direction can be predicted from the dynamics of surrounding illusory motion. We conclude from this finding that the human brain anticipates forthcoming sensory input that allows predictable visual stimuli to be processed with less neural activation at early stages of cortical processing.

SummaryNon-human primate neuroimaging is a rapidly growing area of research that promises to transform and scale translational and cross-species comparative neuroscience. Unfortunately, the technological and methodological advances of the past two decades have outpaced the accrual of data, which is particularly challenging given the relatively few centers that have the necessary facilities and capabilities. The PRIMatE Data Exchange (PRIME-DE) addresses this challenge by aggregating independently acquired non-human primate magnetic resonance imaging (MRI) datasets and openly sharing them via the International Neuroimaging Data-sharing Initiative (INDI). Here, we present the rationale, design, and procedures for the PRIME-DE consortium, as well as the initial release, consisting of 25 independent data collections aggregated across 22 sites (total = 217 non-human primates). We also outline the unique pitfalls and challenges that should be considered in the analysis of non-human primate MRI datasets, including providing automated quality assessment of the contributed datasets.

Previous experience allows the brain to predict what comes next. How these expectations affect conscious experience is poorly understood. In particular, it is unknown whether and when expectations interact with sensory evidence in granting access to conscious perception, and how this is reflected electrophysiologically. Here, we parametrically manipulate sensory evidence and expectations while measuring event-related potentials in human subjects to assess the time course of evoked responses that correlate with subjective visibility, the properties of the stimuli, and/or perceptual expectations. We found that expectations lower the threshold of conscious perception and reduce the latency of neuronal signatures differentiating seen and unseen stimuli. Without expectations, this differentiation occurs ϳ300 ms and with expectations ϳ200 ms after stimulus in occipitoparietal sensors. The amplitude of this differentiating response component (P2) decreases as visibility increases, regardless of whether this increase is attributable to enhanced sensory evidence and/or the gradual buildup of perceptual expectations. Importantly, at matched performance levels, responses to seen and unseen stimuli differed regardless of the physical stimulus properties. These findings indicate that the latency of the neuronal correlates of access to consciousness depend on whether access is driven by stimulus saliency or by a combination of expectations and sensory evidence.

Perception is an active inferential process in which prior knowledge is combined with sensory input, the result of which determines the contents of awareness. Accordingly, previous experience is known to help the brain “decide” what to perceive. However, a critical aspect that has not been addressed is that previous experience can exert 2 opposing effects on perception: An attractive effect, sensitizing the brain to perceive the same again (hysteresis), or a repulsive effect, making it more likely to perceive something else (adaptation). We used functional magnetic resonance imaging and modeling to elucidate how the brain entertains these 2 opposing processes, and what determines the direction of such experience-dependent perceptual effects. We found that although affecting our perception concurrently, hysteresis and adaptation map into distinct cortical networks: a widespread network of higher-order visual and fronto-parietal areas was involved in perceptual stabilization, while adaptation was confined to early visual areas. This areal and hierarchical segregation may explain how the brain maintains the balance between exploiting redundancies and staying sensitive to new information. We provide a Bayesian model that accounts for the coexistence of hysteresis and adaptation by separating their causes into 2 distinct terms: Hysteresis alters the prior, whereas adaptation changes the sensory evidence (the likelihood function).