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.

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.

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.

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.

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.

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.

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.

Event Abstract Back to Event Neural correlates of statistical learning in the inferior-temporal cortex of rhesus monkeys. Peter Kaposvari1*, Susheel Kumar1 and Rufin Vogels1 1 KU Leuven, Laboratorium Neuro - en Psychofysiologie, Belgium We learn to implicitly extract the statistical regularities in the environment around us, e.g. sequences of stimuli that follow each other (e.g. letters in specific words). In the visual domain, human observers can extract regular sequences of visual stimuli from a continuous stream of visual shapes. The neural correlates of such visual sequence learning are still unclear. Here, we determined whether a neural correlate of short sequences of visual images, presented in a continuous stream, is present in macaque inferior temporal (IT) cortex. Two monkeys passively fixated while a continuous stream of 3 fixed sequences of 5 grayscale images of animals of various species each were presented in a random order. After a passive exposure of two months, we assessed whether the responses of IT neurons showed a correlate of the sequences by introducing deviant stimuli in the fixed standard sets. We compared the multiunit neuronal responses for the deviant stimuli with identical stimuli when presented in the standard, learned sequence. We observed a significant enhancement of the responses to the deviant stimulus and the trailing standard stimuli, when the deviant was either from the same sequence (p <0.05 for each monkey) or from the other two sequences (p <0.05 for each monkey). The neuronal responses to a second deviant stimulus (which followed the first deviant in the standard set) did not differ significantly from the standard. These results demonstrate that monkey IT cortex encodes at least part of a learned temporal sequence in which a stimulus is presented. Acknowledgements This work was supported by Fonds voor Wetenschappelijk Onderzoek Vlaanderen (G.0582.12N), Interuniversitaire Attractiepool, Programma Financiering (PF 10/008), European Community’s Seventh Framework Programme FP7/2007-2013 under grant agreement number PITN-GA-2008-290011 and Odysseus grant (G.007.12N). Keywords: sequence learning, statistical learning, rhesus macaque, Inferotemporal cortex, single-unit Conference: 11th National Congress of the Belgian Society for Neuroscience, Mons, Belgium, 22 May - 22 May, 2015. Presentation Type: Poster presentation Topic: Neuroscience Citation: Kaposvari P, Kumar S and Vogels R (2015). Neural correlates of statistical learning in the inferior-temporal cortex of rhesus monkeys.. Front. Neurosci. Conference Abstract: 11th National Congress of the Belgian Society for Neuroscience. doi: 10.3389/conf.fnins.2015.89.00063 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 30 Apr 2015; Published Online: 05 May 2015. * Correspondence: PhD. Peter Kaposvari, KU Leuven, Laboratorium Neuro - en Psychofysiologie, Leuven, 3000, Belgium, Peter.Kaposvari@med.kuleuven.be Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Peter Kaposvari Susheel Kumar Rufin Vogels Google Peter Kaposvari Susheel Kumar Rufin Vogels Google Scholar Peter Kaposvari Susheel Kumar Rufin Vogels PubMed Peter Kaposvari Susheel Kumar Rufin Vogels Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

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.

Inconsistent information from different modalities can be delusive for perception. This phenomenon can be observed with simultaneously presented inconsistent numbers of brief flashes and short tones. The conflict of bimodal information is reflected in double flash or fission, and flash fusion illusions, respectively. The temporal resolution of the vision system plays a fundamental role in the development of these illusions. As the parallel, dorsal and ventral pathways have different temporal resolution we presume that these pathways play different roles in the illusions. We used pathway-optimized stimuli to induce the illusions on separately driven visual streams. Our results show that both pathways support the double flash illusion, while the presence of the fusion illusion depends on the activated pathway. The dorsal pathway, which has better temporal resolution, does not support fusion, while the ventral pathway which has worse temporal resolution shows fusion strongly.

Visual perception declines with age. Perceptual deficits may originate not only in the optical system serving vision but also in the neural machinery processing visual information. Since homologies between monkey and human vision permit extrapolation from monkeys to humans, data from young, middle aged and old monkeys were analyzed to show age-related changes in the neuronal activity in the inferotemporal cortex, which is critical for object and shape vision. We found an increased neuronal response latency, and a decrease in the stimulus selectivity in the older animals and suggest that these changes may underlie the perceptual uncertainties found frequently in the elderly.

Simultaneous processing of pieces of information spread in space and/or in time depends on multiple factors [Chatterjee et al. 2011]. Studies regarding the effects of context on the visual target perception are generally addressing the spatial variables. For a deeper understanding of contextual effects in the temporal domain this study is aimed to gain information about one of the unimodal illusions called Phantom flashes. Here, a single target flash with multiple inducer flashes can be perceived as several flashes.

Invariant sensory processing enables the sense of locality among the information units of the surroundings, but at the same time it also needs to be variable to adapt to a continuously changing environment.Robust coding guarantees the invariability and it also makes the sensory system able to learn by plasticity.Current research based on the investigation of the inferior temporal cortex of the macaque monkey in our laboratory supports the same view.Most of the cells in this brain area are selective for the shape of the visual images.This feature was strongly consistent despite the change of the stimuli parameters, while some changes could cause modulation of response attributes, such as firing rate or latency.This thesis reports on one hand about the processing of Kanizsa type of illusory contours in the inferotemporal cortex (robustness) and, on the other hand, about the changes in neural responses caused by auditory stimulation in this visual area (plasticity). Összefoglalás

We performed a systematic study to check whether neurons in the area TE (the anterior part of inferotemporal cortex) in rhesus monkey, regarded as the last stage of the ventral visual pathway, could be modulated by auditory stimuli. Two fixating rhesus monkeys were presented with visual, auditory or combined audiovisual stimuli while neuronal responses were recorded. We have found that the visually sensitive neurons are also modulated by audiovisual stimuli. This modulation is manifested as the change of response rate. Our results have shown also that the visual neurons were responsive to the sole auditory stimuli. Therefore, the concept of inferotemporal cortex unimodality in information processing should be re-evaluated.