Matthias Niemeier

Predictive Coding Explains Asymmetric Connectivity in the Brain: A Neural Network Study

The paper uses neural network models to study how asymmetric feedback connections improve grasp detection in noisy visual conditions.

From Tasks to Topology: Dorsal and Ventral Streams Emerge in Optimized Neural Networks

This paper shows that dual-stream visual pathways emerge in optimized neural networks without architectural constraints, reflecting task-driven specialization and temporal dynamics.

Action intentions reactivate representations of task-relevant cognitive cues

The paper shows that newly learned colour-weight contingencies are reactivated early during grasp planning, suggesting deliberate processing of weight information based on intention.

Action intentions result in the task-specific integration of object features

This study investigates how task-relevancy modulates the integration of grasp-relevant object features during action planning using EEG and multivariate analyses.

A Meta-Analysis of Functional Neuroimaging Tasks associated with Perceptual Pseudoneglect

This study conducts a meta-analysis of functional neuroimaging tasks to identify the neural network associated with perceptual pseudoneglect, finding a right-hemisphere biased network.

Computation on demand: Action-specific representations of visual task features arise during distinct movement phases

The paper investigates how visual task features are represented during different movement phases in grasping and knuckling tasks using EEG data.

Saccades and pre-saccadic stimulus repetition alter cortical network topology and dynamics: evidence from EEG and graph theoretical analysis

This study uses EEG and graph theory analysis to show that saccades and pre-saccadic stimulus repetition alter cortical network topology and dynamics, with specific effects on network hubs and synchronization.

Linear vector models of time perception account for saccade and stimulus novelty interactions

The paper tests time perception models against visual phenomena, finding that a vector model best explains interactions between saccades and stimulus novelty.

Multimodal evidence on shape and surface information in individual face processing

This study uses image reconstruction to assess shape and surface information in face processing across behavioral, EEG, and fMRI data, finding surface information is better recovered and more cross-modal consistent.