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Florian Schiller

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YNIMG Journal 2022 Journal Article

Action-based predictions affect visual perception, neural processing, and pupil size, regardless of temporal predictability

  • Christina Lubinus
  • Wolfgang Einhäuser
  • Florian Schiller
  • Tilo Kircher
  • Benjamin Straube
  • Bianca M. van Kemenade

Sensory consequences of one's own action are often perceived as less intense, and lead to reduced neural responses, compared to externally generated stimuli. Presumably, such sensory attenuation is due to predictive mechanisms based on the motor command (efference copy). However, sensory attenuation has also been observed outside the context of voluntary action, namely when stimuli are temporally predictable. Here, we aimed at disentangling the effects of motor and temporal predictability-based mechanisms on the attenuation of sensory action consequences. During fMRI data acquisition, participants (N = 25) judged which of two visual stimuli was brighter. In predictable blocks, the stimuli appeared temporally aligned with their button press (active) or aligned with an automatically generated cue (passive). In unpredictable blocks, stimuli were presented with a variable delay after button press/cue, respectively. Eye tracking was performed to investigate pupil-size changes and to ensure proper fixation. Self-generated stimuli were perceived as darker and led to less neural activation in visual areas than their passive counterparts, indicating sensory attenuation for self-generated stimuli independent of temporal predictability. Pupil size was larger during self-generated stimuli, which correlated negatively with the blood oxygenation level dependent (BOLD) response: the larger the pupil, the smaller the BOLD amplitude in visual areas. Our results suggest that sensory attenuation in visual cortex is driven by action-based predictive mechanisms rather than by temporal predictability. This effect may be related to changes in pupil diameter. Altogether, these results emphasize the role of the efference copy in the processing of sensory action consequences.

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YNICL Journal 2019 Journal Article

Prognosis of conversion of mild cognitive impairment to Alzheimer's dementia by voxel-wise Cox regression based on FDG PET data

  • Arnd Sörensen
  • Ganna Blazhenets
  • Gerta Rücker
  • Florian Schiller
  • Philipp Tobias Meyer
  • Lars Frings

AIM: F-fluorodeoxyglucose (FDG) PET for the prognosis of conversion from mild cognitive impairment (MCI) to Alzheimer's dementia (AD) is controversial. In the present work, the identification of cerebral metabolic patterns with significant prognostic value for conversion of MCI patients to AD is investigated with voxel-based Cox regression, which in contrast to common categorical comparisons also utilizes time information. METHODS: FDG PET data of 544 MCI patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were randomly split into two equally-sized datasets (training and test). Within a median follow-up duration of 47 months (95% CI: 46-48 months) 181 patients developed AD. In the training dataset, voxel-wise Cox regressions were used to identify regions associated with conversion of MCI to AD. These were compared to regions identified by a classical group comparison (analysis of covariance (ANCOVA) with statistical parametric mapping (SPM) 8) between converters and non-converters (both adjusted for apolipoprotein E (APOE) genotype, mini-mental state examination (MMSE) score, age, sex and education). In the test dataset, normalized FDG uptake within significant brain regions from voxel-wise Cox- and ANCOVA analyses (Cox- and ANCOVA- regions of interest (ROI), respectively) and clinical variables APOE status, MMSE score and education were tested in different Cox models (adjusted for age, sex) including: (1) only clinical variables, (2) only normalized FDG uptake in ANCOVA-ROI, (3) only normalized FDG uptake from Cox-ROI, (4) clinical variables plus FDG uptake in ANCOVA-ROI, (5) clinical variables plus FDG uptake from Cox-ROI. RESULTS: Conversion-related regions with relative hypometabolism comprised parts of the temporo-parietal and posterior cingulate cortex/precuneus for voxel-wise ANCOVA, plus frontal regions for voxel-wise Cox regression (both p < .01, false discovery rate (FDR) corrected). The clinical-only model (1) and the models based on normalized FDG uptake from Cox-ROI only (2) and ANCOVA-ROI only (3) all significantly predicted conversion to AD (Wald Test (WT): p < .001). The clinical model (1) was significantly improved by adding imaging information in model (4) (Akaike information criterion (AIC) relative likelihood (RL) (1) vs (4): RL < 0.018). There were no significant differences between models (2) and (3), as well as (4) and (5). CONCLUSIONS: Voxel-wise Cox regression identifies conversion-related patterns of cerebral glucose metabolism, but is not superior to classical group contrasts in this regard. With imaging information from both FDG PET patterns, the prediction of conversion to AD was improved.

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