Petra Hermann

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.

The contribution of surprise to the prediction based modulation of fMRI responses

In recent years, several functional magnetic resonance imaging (fMRI) studies showed that correct stimulus predictions reduce the neural responses when compared to surprising events (Egner et al., 2010). Further, it has been shown that such fulfilled expectations enhance the magnitude of repetition suppression (RS, i.e. a decreased neuronal response after the repetition of a given stimulus) in face selective visual cortex as well (Summerfield et al., 2008). Current MEG and neuroimaging studies suggest that the underlying mechanisms of expectation effects are independent from these of RS (Grotheer and Kovács, 2015; Todorovic and Lange, 2012). However, it is not clear as of today how perceptual expectations modulate the neural responses: is the difference between correctly predicted and surprising stimuli due to a genuine response reduction for correctly predicted stimuli or is it due to an increased response for surprising stimuli? Therefore, here we used a modified version of the paradigm of Grotheer and Kovács (2015) to induce predictions independently from repetition probability by presenting pairs of faces (female, male or infant) that were either repeated or alternating. Orthogonally to this, predictions were manipulated by the gender of the first face within each pair so that it signaled high, low or equal probability of repetitions. An unpredicted, neutral condition with equal probabilities for alternating and repeated trials was used to identify the role of surprising and enhancing modulations. Similarly, to Grotheer and Kovács (2015), we found significant RS and significant expectation effect in the FFA. Importantly, we observed larger response for surprising events in comparison to the neutral and correctly predicted conditions for alternating trials. Altogether, these results emphasize the role of surprise in prediction effects.

Resting State fMRI Functional Connectivity Analysis Using Dynamic Time Warping

Traditional resting-state network concept is based on calculating linear dependence of spontaneous low frequency fluctuations of the BOLD signals of different brain areas, which assumes temporally stable zero-lag synchrony across regions. However, growing amount of experimental findings suggest that functional connectivity exhibits dynamic changes and a complex time-lag structure, which cannot be captured by the static zero-lag correlation analysis. Here we propose a new approach applying Dynamic Time Warping (DTW) distance to evaluate functional connectivity strength that accounts for non-stationarity and phase-lags between the observed signals. Using simulated fMRI data we found that DTW captures dynamic interactions and it is less sensitive to linearly combined global noise in the data as compared to traditional correlation analysis. We tested our method using resting-state fMRI data from repeated measurements of an individual subject and showed that DTW analysis results in more stable connectivity patterns by reducing the within-subject variability and increasing robustness for preprocessing strategies. Classification results on a public dataset revealed a superior sensitivity of the DTW analysis to group differences by showing that DTW based classifiers outperform the zero-lag correlation and maximal lag cross-correlation based classifiers significantly. Our findings suggest that analysing resting-state functional connectivity using DTW provides an efficient new way for characterizing functional networks.

The relationship between repetition suppression and face perception

Repetition of identical face stimuli leads to fMRI response attenuation (fMRI adaptation, fMRIa) in the core face-selective occipito-temporal visual cortical network, involving the bilateral fusiform face area (FFA) and the occipital face area (OFA). However, the functional relevance of fMRIa observed in these regions is unclear as of today. Therefore, here we aimed at investigating the relationship between fMRIa and face perception ability by measuring in the same human participants both the repetition-induced reduction of fMRI responses and identity discrimination performance outside the scanner for upright and inverted face stimuli. In the correlation analysis, the behavioral and fMRI results for the inverted faces were used as covariates to control for the individual differences in overall object perception ability and basic visual feature adaptation processes, respectively. The results revealed a significant positive correlation between the participants’ identity discrimination performance and the strength of fMRIa in the core face processing network, but not in the extrastriate body area (EBA). Furthermore, we found a strong correlation of the fMRIa between OFA and FFA and also between OFA and EBA, but not between FFA and EBA. These findings suggest that there is a face-selective component of the repetition-induced reduction of fMRI responses within the core face processing network, which reflects functionally relevant adaptation processes involved in face identity perception.

Correction to: Reducing task-based fMRI scanning time using simultaneous multislice echo planar imaging

The original version of this article contained a mistake. The correct Affiliation 2 is Semmelweis University, János Szentágothai PhD School, MR Research Centre, Balassa Street 6, Budapest 1083, Hungary.

P242 Dynamic time warping distance based connectivity: A new method for resting-state FMRI functional connectivity analysis

Objectives Traditionally resting-state networks are analysed with methods implying zero-lag linear dependence between brain regions, i.e. functional connectivity strength between voxel pairs is characterized by the correlation-coefficient of the two measured signal. It is known that the shape and timing of hemodynamic response function differs between brain regions and this introduces artefacts in linear measures. Methods We proposed Dynamic Time Warping (DTW) distance to be used as an alternative similarity-measure between BOLD signals. Our method was validated in a longitudinal single-subject study where seed-based and whole-brain functional connectivity was calculated based on both DTW similarity and correlation. DTW connectivity’s sensitivity was assessed in a classification task, where a preprocessed public dataset was used: 126 subjects’ resting-state data and phenotypic information, including diagnosis for ADHD. Results The results of the single-subject measurements revealed that DTW similarity-based connectivity map calculation is more stable in multiple measurements than a correlation-based paradigm, as DTW-based connectivity strengths are similarly stable within and between sessions, while correlation yields larger variations between sessions. Furthermore, the stability of the DTW-based connectivity patterns result in significantly higher classification performance than the same classifiers trained on correlation-based features of connectivity. Discussion As DTW handles non-stationery processes, it results in stable connectivity patterns in multiple measurements, while its sensitivity for group differences is higher than correlation’s as the classification study shows. Conclusion The results demonstrate that DTW similarity is indeed an applicable and advantageous tool of resting-state functional connectivity analysis. Significance DTW-based connectivity can be efficiently used in longitudinal studies and in connectome-based classification tasks.

Erratum to: The relationship between repetition suppression and face perception

1 Brain Imaging Centre, Research Centre for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2, Budapest 1117, Hungary 2 Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary 3 Institute of Psychology, Friedrich-Schiller-University of Jena, Jena, Germany 4 DFG Research Unit Person Perception, Friedrich-Schiller-University of Jena, Jena, Germany 5 Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary Brain Imaging and Behavior (2017) 11:1225 DOI 10.1007/s11682-016-9590-x