Perceptual Expectations Are Reflected by Early Alpha Power Reduction.

The predictability of a stimulus can be characterized by its transitional probability. Perceptual expectations derived from the transitional probability of the stimulus were found to modulate the early alpha oscillations in the sensory regions of the brain when neural responses to expected versus unexpected stimuli were compared. The objective of our study was to find out the extent to which this low-frequency oscillation reflects stimulus predictability. We aimed to detect the alpha-power difference with smaller differences in transitional probabilities by comparing expected stimuli with neutral ones. We studied the effect of expectation on perception by applying an unsupervised visual statistical learning paradigm with expected and neutral stimuli embedded in an image sequence while recording EEG. Time-frequency analysis showed that expected stimuli elicit lower alpha power in the window of 8-12 Hz and 0-400 msec after stimulus presentation, appearing in the centroparietal region. Comparing previous findings of expectancy-based alpha-band modulation with our results suggests that early alpha oscillation shows an inverse relationship with stimulus predictability. Although current data are insufficient to determine the origin of the alpha power reduction, this could be a potential sign of expectation suppression in cortical oscillatory activity.

Visual linguistic statistical learning is traceable through neural entrainment.

The human brain can detect statistical regularities in the environment across a wide variety of contexts. The importance of this process is well-established not just in language acquisition but across different modalities; in addition, several neural correlates of statistical learning have been identified. A current technique for tracking the emergence of regularity learning and localizing its neural background is frequency tagging (FT). FT can detect neural entrainment not only to the frequency of stimulus presentation but also to that of a hidden structure. Auditory learning paradigms with linguistic and nonlinguistic stimuli, along with a visual paradigm using nonlinguistic stimuli, have already been tested with FT. To complete the picture, we conducted an FT experiment using written syllables as stimuli and a hidden triplet structure. Both behavioral and neural entrainment data showed evidence of structure learning. In addition, we localized two electrode clusters related to the process, which spread across the frontal and parieto-occipital areas, similar to previous findings. Accordingly, we conclude that fast-paced visual linguistic regularities can be acquired and are traceable through neural entrainment. In comparison with the literature, our findings support the view that statistical learning involves a domain-general network.

Online measurement of learning temporal statistical structure in categorization tasks.

The ability to grasp relevant patterns from a continuous stream of environmental information is called statistical learning. Although the representations that emerge during visual statistical learning (VSL) are well characterized, little is known about how they are formed. We developed a sensitive behavioral design to characterize the VSL trajectory during ongoing task performance. In sequential categorization tasks, we assessed two previously identified VSL markers: priming of the second predictable image in a pair manifested by a reduced reaction time (RT) and greater accuracy, and the anticipatory effect on the first image revealed by a longer RT. First, in Experiment 1A, we used an adapted paradigm and replicated these VSL markers; however, they appeared to be confounded by motor learning. Next, in Experiment 1B, we confirmed the confounding influence of motor learning. To assess VSL without motor learning, in Experiment 2 we (1) simplified the categorization task, (2) raised the number of subjects and image repetitions, and (3) increased the number of single unpaired images. Using linear mixed-effect modeling and estimated marginal means of linear trends, we found that the RT curves differed significantly between predictable paired and control single images. Further, the VSL curve fitted a logarithmic model, suggesting a rapid learning process. These results suggest that our paradigm in Experiment 2 seems to be a viable online tool to monitor the behavioral correlates of unsupervised implicit VSL.

Statistical Learning Signals in Macaque Inferior Temporal Cortex.

Humans are sensitive to statistical regularities in their visual environment, but the nature of the underlying neural statistical learning signals still remains to be clarified. As in human behavioral and neuroimaging studies of statistical learning, we exposed rhesus monkeys to a continuous stream of images, presented without interstimulus interval or reward association. The stimulus set consisted of 3 groups of 5 images each (quintets). The stimulus order within each quintet was fixed, but the quintets were presented repeatedly in a random order without interruption. Thus, only transitional probabilities defined quintets of images. Postexposure recordings in inferior temporal (IT) cortex showed an enhanced response to stimuli that violated the exposed sequence. This enhancement was found only for stimuli that were not predicted by the just preceding stimulus, reflecting a temporally adjacent stimulus relationship, and was sensitive to stimulus order. By comparing IT responses with sequences with and without statistical regularities, we observed a short latency, transient response suppression for stimuli of the sequence with regularities, in addition to a later sustained response enhancement to stimuli that violated the sequence with regularities. These findings constrain models of mechanisms underlying neural responses in predictable temporal sequences, such as predictive coding.

Encoding of Predictable and Unpredictable Stimuli by Inferior Temporal Cortical Neurons.

Animals and humans learn statistical regularities that are embedded in sequences of stimuli. The neural mechanisms of such statistical learning are still poorly understood. Previous work in macaque inferior temporal (IT) cortex demonstrated suppressed spiking activity to visual images of a sequence in which the stimulus order was defined by transitional probabilities (labeled as "standard" sequence), compared with a sequence in which the stimulus order was random ("random" sequence). Here, we asked whether IT neurons encode the images of the standard sequence more accurately compared with images of the random sequence. Previous human fMRI studies in different sensory modalities also found a suppressed response to expected relative to unexpected stimuli but obtained various results regarding the effect of expectation on encoding, with one study reporting an improved classification accuracy of expected stimuli despite the reduced activation level. We employed a linear classifier to decode image identity from the spiking responses of the recorded IT neurons. We found a greater decoding accuracy for images of the standard compared with the random sequence during the early part of the stimulus presentation, but further analyses suggested that this reflected the sustained, stimulus-selective activity from the previous stimulus of the sequence, which is typical for IT neurons. However, the peak decoding accuracy was lower for the standard compared with the random sequence, in line with the reduced response to the former compared with the latter images. These data suggest that macaque IT neurons represent less accurately predictable compared with unpredictable images.

Illusory flashes and perception.

Information from the environment can be based on a single or several modalities. The simultaneous processing of information separated in space and/or time depends on multiple factors. Visual illusions serve as a good tool with which to investigate the parallel processing of information and their interactions. This study was designed to gain information about a unimodal illusion: a target that flashes once seems to flash more as a result of a simultaneously presented inducer flashing several times nearby. The first aim of this work was to understand whether the number of perceived flashes is merely a result of a bias in the criterion level or whether it is based on a real percept. We then clarified how the illusion finds its way into the percept. The final step was designed to establish the logic of the processing in the background by determining whether the modality appropriateness hypothesis, the information reliability hypothesis, or the discontinuity theory best explains the predominant role of the inducer.

Gamma oscillations in visual statistical learning correlate with individual behavioral differences.

Statistical learning is assumed to be a fundamentally general sensory process across modalities, age, other cognitive functions, and even species. Despite this general role, behavioral testing on regularity acquisition shows great variance among individuals. The current study aimed to find neural correlates of visual statistical learning showing a correlation with behavioral results. Based on a pilot study, we conducted an EEG study where participants were exposed to associated stimulus pairs; the acquisition was tested through a familiarity test. We identified an oscillation in the gamma range (40-70 Hz, 0.5-0.75 s post-stimulus), which showed a positive correlation with the behavioral results. This change in activity was located in a left frontoparietal cluster. Based on its latency and location, this difference was identified as a late gamma activity, a correlate of model-based learning. Such learning is a summary of several top-down mechanisms that modulate the recollection of statistical relationships such as the capacity of working memory or attention. These results suggest that, during acquisition, individual behavioral variance is influenced by dominant learning processes which affect the recall of previously gained information.

Audio-visual integration through the parallel visual pathways.

Audio-visual integration has been shown to be present in a wide range of different conditions, some of which are processed through the dorsal, and others through the ventral visual pathway. Whereas neuroimaging studies have revealed integration-related activity in the brain, there has been no imaging study of the possible role of segregated visual streams in audio-visual integration. We set out to determine how the different visual pathways participate in this communication. We investigated how audio-visual integration can be supported through the dorsal and ventral visual pathways during the double flash illusion. Low-contrast and chromatic isoluminant stimuli were used to drive preferably the dorsal and ventral pathways, respectively. In order to identify the anatomical substrates of the audio-visual interaction in the two conditions, the psychophysical results were correlated with the white matter integrity as measured by diffusion tensor imaging.The psychophysiological data revealed a robust double flash illusion in both conditions. A correlation between the psychophysical results and local fractional anisotropy was found in the occipito-parietal white matter in the low-contrast condition, while a similar correlation was found in the infero-temporal white matter in the chromatic isoluminant condition. Our results indicate that both of the parallel visual pathways may play a role in the audio-visual interaction.