Rainer Goebel

A critical assessment of LGN segmentation quality based on volume, contour, and location

This study benchmarks seven automated methods and manual segmentation for LGN delineation, finding HIPS-THOMAS and DeepThalamus perform best, while manual segmentation remains precise but variable.

All signals considered: Data quality partially explains inter-individual task differences in a large, open fNIRS dataset

The paper examines how signal quality affects inter-individual variability in fNIRS data and introduces an open dataset with multi-task recordings and peripheral physiology measures.

Intracortical vessel density mapping at mesoscale reveals regionally specific angioarchitecture in the human brain

The paper maps mesoscopic vascular networks in the human brain using the BigBrain dataset, revealing non-uniform vascular density related to cortical areas.

Searchlight Optimization Using Representational Similarity Analysis for Subject-Level Voxel Selection in Emotional State Decoding

This paper introduces a subject-level searchlight optimization framework combining univariate and multivariate analyses to identify condition-sensitive voxels for emotional state decoding in fMRI.

Early Vision Shapes Recurrent Processing in the Human Visual Cortex

The paper investigates how early visual experience affects feedback processing in the human visual cortex using an occlusion paradigm and decoding methods.

Toward navigating emotional states using real-time representational similarity analysis fMRI neurofeedback - a feasibility study

This study explores using real-time representational similarity analysis in fMRI neurofeedback to navigate emotional states, showing feasibility and improved performance with repeated sessions.

Whole-brain meso-vein imaging in living humans using fast 7 T MRI

This paper introduces a fast whole-brain MRI protocol for mesoscopic venous imaging in humans, enabling detailed vascular mapping in under seven minutes without contrast agents.

Multimodal laminar characterization of visual areas along the cortical hierarchy

This paper characterizes laminar organization across four visual areas using multimodal data, finding parvalbumin profiles as the most discriminative feature.

Laminar CBV and BOLD response-characteristics over time and space in the human primary somatosensory cortex at 7T

This study characterizes laminar BOLD and VASO responses to digit stimulation in human somatosensory cortex, revealing triphasic dynamics and potential excitation-inhibition mechanisms.

Visual and auditory object representations in ventral visual cortex after restoring sight in humans

This study investigates whether visual category-selectivity in VOTC emerges after sight restoration in congenitally blind humans, finding reduced face-selectivity and a double dissociation between visual and auditory decoding in VOTC.

In the brain of the beholder: bi-stable motion reveals mesoscopic-scale feedback modulation in V1

This study uses fMRI to investigate how V1 and hMT+ interact during bistable motion perception, finding stronger feedback coupling in V1 during ambiguous stimuli.

PrediRep: Modelling hierarchical predictive coding with an unsupervised deep learning network

PrediRep is a deep learning model designed to align closely with hierarchical predictive coding principles while maintaining computational performance in next-frame prediction tasks.

In the brain of the beholder: whole brain dynamics shape the perception during ambiguous motion

This study uses fMRI to investigate how neural dynamics in the brain resolve ambiguous motion perception, finding distinct interactions between frontal and parietal regions during transitions and sustained perceptions.

Optimal placement of high-channel visual prostheses in human retinotopic visual cortex

This paper develops an automatic method to optimize electrode placement for visual prostheses by matching phosphene distributions using retinotopic predictions and individual anatomy data.

Navigating the Maze: Identifying Potential Pitfalls in Attention State Classification from fMRI Brain Patterns

This study identifies classification inaccuracies in fMRI-based attention state decoding due to design choices and confounders like motion artifacts and task timing.

Online self-evaluation of fMRI-based neurofeedback performance

This study examines how participants evaluate their performance in fMRI neurofeedback tasks, finding that prediction accuracy improves with learning but confidence remains stable.

Tactile Stimulation Designs Adapted to Clinical Settings Result in Reliable fMRI-based Somatosensory Digit Maps

This study evaluates two fMRI-based digit mapping designs for clinical use, showing both produce reliable activation locations but less consistent extent and overlap across sessions.

Riemannian Geometry for the Classification of Brain States with fNIRS

This paper introduces a Riemannian geometry-based classification method for fNIRS data, achieving higher accuracy in brain-state classification compared to traditional methods.

Characterisation of laminar and vascular spatiotemporal dynamics of CBV and BOLD signals using VASO and ME-GRE at 7T in humans

This paper characterizes cortical depth-dependent CBV and BOLD hemodynamic responses across stimulus durations using VASO and ME-GRE at 7T in humans, finding that longer durations improve CBV specificity but may reduce efficiency.

AngoraPy: A Python Toolkit For Modelling Anthropomorphic Goal-Driven Sensorimotor Systems

AngoraPy enables training of complex recurrent convolutional neural networks for sensorimotor systems, facilitating goal-driven modeling in computational neuroscience.

Layered Structure of Cortex Explains Reversal Dynamics in Bistable Perception

This paper shows that the layered structure of the cortex explains increased alternation rates in bistable perception through mechanisms like interlaminar inhibition and input suppression.

Acquisition and processing methods of whole-brain layer-fMRI VASO and BOLD: The Kenshu dataset.

The paper develops acquisition protocols and processing pipelines for whole-brain layer-fMRI and introduces the Kenshu dataset for benchmarking and analysis.

Fast layer-fMRI VASO with short stimuli and event-related designs at 7T

This paper develops a fast VASO fMRI method with short stimuli and event-related designs to capture layer-specific hemodynamic responses with high spatio-temporal resolution.

Retrieving fMRI data in real-time: difficulties and pitfalls

The paper addresses real-time fMRI data export challenges, showing delays in data transfer and proposing a solution for Siemens MRI devices that reduces delays and improves quality measures.

Neural Correlates of High-Level Visual Saliency Models

This study investigates the neural correlates of high-level visual saliency using computational models and the Natural Scenes Dataset, identifying hV4 as a key region for saliency computations.

Imaging the columnar functional organization of human area MT+ to axis-of-motion stimuli using VASO at 7 Tesla

This study uses CBV-sensitive fMRI to quantify columnar organization in human hMT+ for axis-of-motion stimuli, showing higher specificity with VASO over BOLD.

Learning Equivariant Object Recognition and its Reverse Application to Imagery

This paper develops a capsule network model of the visual ventral stream that can recognize objects and reconstruct fMRI activation patterns from imagery.

Unlocking the Secrets of the Primate Visual Cortex: A CNN-Based Approach Traces the Origins of Major Organizational Principles to Retinal Sampling

The paper shows that CNNs with retinal sampling layers replicate primate visual cortex organizational principles, revealing spatial frequency-dependent radial bias.

Mesoscopic in vivo human T2* dataset acquired using quantitative MRI at 7 Tesla

The paper provides a high-resolution T2* MRI dataset of the human brain at 7 Tesla, revealing cortical substructures and consistent depth-dependent T2* values across subjects.

Improved correspondence of fMRI visual field localizer data after cortex-based macroanatomical alignment

This study shows that cortex-based macroanatomical alignment improves the consistency and statistical power of fMRI visual field localizer data in group analyses.