Rainer Goebel

The paper shows that convNets trained with retinal ganglion cell-based sampling replicate key organizational principles of the primate visual cortex without significantly affecting classification performance.

This paper introduces a fast pRF mapping method suitable for real-time applications, validated on simulated and empirical fMRI data.

This study shows participants can learn to self-regulate stress-related brain network balance using real-time fMRI neurofeedback and transfer this skill to a stressor scenario.

The paper compares optode-layout design approaches for fNIRS using individual fMRI data, finding that incorporating more individual MRI data improves signal quality and sensitivity.

This paper validates layer-specific VASO fMRI across species by comparing it to optical imaging and MION contrast enhanced fMRI in rats and humans, confirming its reliability for estimating layer-specific CBV changes.

LayNii is a software suite designed for analyzing layer-specific functional MRI data with SNR and coverage constraints, offering tools for layerification, smoothing, and artifact mitigation.

This study investigates how subjective understanding of actions and emotions involves the semantic and action observation networks using fMRI and word embeddings.

This paper introduces a real-time fMRI neurofeedback method using semantic representations to allow participants to navigate mental states by controlling neural activity towards target brain states.

This study investigates adaptive visual processing in the human brain using ultra-high field imaging, revealing suppressive recurrent processing and dissociable connectivity mechanisms.

The paper uses statistical modeling and anatomical analysis to establish a cortical hierarchy based on laminar profiles and functional connectivity, highlighting the role of top-down generative networks.

This paper develops a functional atlas of early visual and category-selective regions in human occipito-temporal cortex, showing it outperforms volumetric alignment and accurately predicts ROI locations.

This study shows that fMRI neurofeedback can modulate ipsilateral motor cortex activity and induce opposite changes in corpus callosum white matter microstructure in healthy adults.

The paper improves a probabilistic cytoarchitectonic atlas of auditory cortex by introducing CBA+, a method that aligns individual brains more accurately than existing methods.

This study investigates how experience shapes perceptual decisions by examining plasticity in cortical layers using high-resolution fMRI and orientation discrimination training.

This paper demonstrates reliable single-trial decoding of somatosensory imagery using fMRI, showing high accuracy in distinguishing left-foot and right-hand imagery and developing a real-time BCI communication system.

This paper transfers deep neural network features to fMRI data to improve decoding performance by reconstructing CNN features from imaging data.

The paper investigates how motion affects population receptive field estimates in humans using fMRI and psychophysical measurements, finding that low-contrast motion shifts pRFs opposite to motion direction.

This study shows that tactile feedback via medical tape reduces head motion during MRI, improving image quality, with greater reduction for subjects with more motion without feedback.

This study uses fMRI and machine learning to show that visual imagery of letters preserves the topographic organization of perceived shapes in early visual cortex.

The paper defines 19 FOC features using analytical geometry and evaluates their contribution to perceived faceness in abstract stimuli through psychophysical experiments.

The paper shows that the cortical rich club increases outgoing effective connectivity during tasks, enabling fast communication with specific peripheral regions while maintaining constant incoming connectivity.