Prediction-related neural response alterations in the ventral visual stream

Theories of predictive coding (PC; Rao & Ballard, 1999) have dominated neurocognitive research in explaining thought and perception processes in various domains. The basic principle is that perception relies not only on bottom-up processing of sensory input but also on top-down predictions. The current thesis describes several neuronal response alterations in cortical visual areas measured with neuroimaging methods. The so-called repetition suppression (RS) effect was connected to predictive coding as repetitions make stimuli more expected, which results in a smaller prediction error and therefore attenuated neuronal activity. Still, it is questioned whether RS reflects the PE or is a local process by neuronal populations that occurs without top-down influences (Grill-Spector et al., 2006). Another often investigated effect is the reduced neuronal response to expected or predicted visual input called expectation suppression (ES). A considerable body of research on contextual response changes, such as RS and ES, relates to the visual system and the face-processing network in particular. Overall, we demonstrate the importance of stimulus predictability for studies using RS to uncover expectancy-related effects. Furthermore, we suggest that the influence of sensory precision on measures of RS and ES needs more attention in future research. Concerning the stimulus material in the presented studies - unfamiliar, visually familiar, and famous familiar faces - we also emphasize the importance of thoroughly considering the characteristics of faces in terms of prior belief and sensory input precision and predictability when using them for testing prediction-related effects

Repetition Probability Does Not Affect fMRI Repetition Suppression for Objects

Previously several functional magnetic resonance imaging (fMRI) studies point toward the role of perceptual expectations in determining adaptation or repetition suppression (RS) in humans. These studies showed that the probability of repetitions of faces within a block influences the magnitude of adaptation in face-related areas of the human brain (Summerfield et al., 2008). However, a current macaque single-cell/local field potential (LFP) recording study using objects as stimuli found no evidence for the modulation of the neural response by the repetition probability in the inferior temporal cortex (Kaliukhovich and Vogels, 2010). Here we examined whether stimulus repetition probability affects fMRI repetition suppression for nonface object stimuli in the human brain. Subjects were exposed to either two identical [repetition trials (RTs)] or two different [alternation trials (ATs)] object stimuli. Both types of trials were presented blocks consisting of either 75% [repetition blocks (RBs)] or 25% [alternation blocks (ABs)] of RTs. We found strong RS, i.e., a lower signal for RTs compared to ATs, in the object sensitive lateral occipital cortex as well as in the face-sensitive occipital and fusiform face areas. More importantly, however, there was no significant difference in the magnitude of RS between RBs and ABs in each of the areas. This is in agreement with the previous monkey single-unit/LFP findings and suggests that RS in the case of nonface visual objects is not modulated by the repetition probability in humans. Our results imply that perceptual expectation effects vary for different visual stimulus categories

Prior experience modulates top-down predictive processing in the ventral visual areas

Repetition suppression(RS)refers to that the reduction of neural activities for repeated presentations of a given stimulus compared to its first presentation. Summerfield et al(2008) found the magnitude of RS is affected by the repetition probability of stimuli, called as P(rep) effect. Based on the predictive coding theory, prior experience about the sensory inputs is necessary to optimally achieve cognitive processes. But it remains unclear how prior experience modulates predictive processes. To address this issue, in Study I, we estimated the P(rep) effects for Chinese characters and German words in native Chinese and German participants to test whether prior experience affects the P(rep) effect of lexical stimuli. The results showed that the P(rep) effect is only manifest for words of a language with which participants had prior experience. Study II performed fMRI measurements before and after a 10-day perceptual learning (PL) training for cars to test the modulation of short-term experience on the P(rep) effect. The results replicated the P(rep) effect for faces and cars. More interestingly, the P(rep) effect can be temporarily abolished by the short-term PL experience. The third study investigated how prior experience modulates sensory inputs. Study 3a adopted a classic stimulus repetition paradigm to measure RS for faces, together with either concurrent short-term memory (STM) load or a control condition. The results showed that RS is significantly attenuated when visual STM is loaded. Study 3b manipulates attention by a face inversion detection task. The results showed that the RS effect appears in the STM condition when participants attend to faces. The main conclusions: i) predictive processes, as measured by the P(rep) effect, require extensive prior experiences with stimuli, but ii) these can also be modulated by short-term learning experience. Further, iii) STM and attention are two modulators of prior experiences on predictive processes

Repetition probability effects for inverted faces

It has been shown, that the repetition related reduction of the blood-oxygen level dependent (BOLD) signal is modulated by the probability of repetitions (P(rep)) for faces (Summerfield et al., 2008), providing support for the predictive coding (PC) model of visual perception (Rao and Ballard, 1999). However, the stage of face processing where repetition suppression (RS) is modulated by P(rep) is still unclear. Face inversion is known to interrupt higher level configural/holistic face processing steps and if modulation of RS by P(rep) takes place at these stages of face processing, P(rep) effects are expected to be reduced for inverted when compared to upright faces. Therefore, here we aimed at investigating whether P(rep) effects on RS observed for face stimuli originate at the higher-level configural/holistic stages of face processing by comparing these effects for upright and inverted faces. Similarly to previous studies, we manipulated P(rep) for pairs of stimuli in individual blocks of fMRI recordings. This manipulation significantly influenced repetition suppression in the posterior FFA, the OFA and the LO, independently of stimulus orientation. Our results thus reveal that RS in the ventral visual stream is modulated by P(rep) even in the case of face inversion and hence strongly compromised configural/holistic face processing. An additional whole-brain analysis could not identify any areas where the modulatory effect of probability was orientation specific either. These findings imply that P(rep) effects on RS might originate from the earlier stages of face processing. © 2014 Elsevier Inc

Evaluating the neurophysiological evidence for predictive processing as a model of perception

For many years, the dominant theoretical framework guiding research into the neural origins of perceptual experience has been provided by hierarchical feedforward models, in which sensory inputs are passed through a series of increasingly complex feature detectors. However, the long‐standing orthodoxy of these accounts has recently been challenged by a radically different set of theories that contend that perception arises from a purely inferential process supported by two distinct classes of neurons: those that transmit predictions about sensory states and those that signal sensory information that deviates from those predictions. Although these predictive processing (PP) models have become increasingly influential in cognitive neuroscience, they are also criticized for lacking the empirical support to justify their status. This limited evidence base partly reflects the considerable methodological challenges that are presented when trying to test the unique predictions of these models. However, a confluence of technological and theoretical advances has prompted a recent surge in human and nonhuman neurophysiological research seeking to fill this empirical gap. Here, we will review this new research and evaluate the degree to which its findings support the key claims of PP

Inferring the direction of implied motion depends on visual awareness

Visual awareness of an event, object, or scene is, by essence, an integrated experience, whereby different visual features composing an object (e.g., orientation, color, shape) appear as an unified percept and are processed as a whole. Here, we tested in human observers whether perceptual integration of static motion cues depends on awareness by measuring the capacity to infer the direction of motion implied by a static visible or invisible image under continuous flash suppression. Using measures of directional adaptation, we found that visible but not invisible implied motion adaptors biased the perception of real motion probes. In a control experiment, we found that invisible adaptors implying motion primed the perception of subsequent probes when they were identical (i.e., repetition priming), but not when they only shared the same direction (i.e., direction priming). Furthermore, using a model of visual processing, we argue that repetition priming effects are likely to arise as early as in the primary visual cortex. We conclude that although invisible images implying motion undergo some form of nonconscious processing, visual awareness is necessary to make inferences about motion direction

fMRI adaptation revisited

Adaptation has been widely used in functional magnetic imaging (fMRI) studies to infer neuronal response properties in human cortex. fMRI adaptation has been criticised because of the complex relationship between fMRI adaptation effects and the multiple neuronal effects that could underlie them. Many of the longstanding concerns about fMRI adaptation have received empirical support from neurophysiological studies over the last decade. We review these studies here, and also consider neuroimaging studies that have investigated how fMRI adaptation effects are influenced by high-level perceptual processes. The results of these studies further emphasize the need to interpret fMRI adaptation results with caution, but they also provide helpful guidance for more accurate interpretation and better experimental design. In addition, we argue that rather than being used as a proxy for measurements of neuronal stimulus selectivity, fMRI adaptation may be most useful for studying population-level adaptation effects across cortical processing hierarchies