Tomas H. J. Knapen

This paper develops a method combining fMRI and MEG to non-invasively map the temporal hierarchy of visual processing in the human brain with millisecond precision.

The paper demonstrates image-specific foveal feedback during saccade preparation using fMRI, showing decoding of peripheral targets from foveal areas and a u-shaped decoding curve.

This study investigates how psilocybin affects visual-contextual computations using psychophysics, fMRI, and computational modeling, finding altered perception and cortical responses.

This paper investigates the neural mechanisms of binocular rivalry using fMRI, finding that eye-specific response modulation occurs in V1 ocular dominance columns and that IPS and ventral pulvinar enhance connectivity to resolve visual competition.

The paper shows that attentional precision affects how much population receptive fields are attracted to the attended location in visual space.

The paper investigates whether attention-driven attraction of population receptive fields towards the attended locus is affected by stimulus contrast, finding no such effect.

The paper maps somatosensory and visual field tuning in the brain, showing aligned somatotopic body maps in the visual cortex during movie watching.

The paper examines hierarchical cortical plasticity in congenital sight impairment by comparing rod-only and typically developed visual systems, finding stability in early stages and compensatory reorganization in higher-order cortex.

This study investigates the spatial reference frame of visual processing in human visual cortex using fMRI and finds that visual-spatial processing is encoded in a retinotopic frame rather than a spatiotopic one.

The paper investigates pupil responses during perceptual multistability, identifying distinct components linked to task execution and perceptual changes.

The paper uses naturalistic audiovisual data to reveal tonotopic organization in human auditory cortex, showing nonlinear response properties and speech selectivity in remote regions.

The paper demonstrates that the human hippocampus exhibits a contralateral visual field bias, extending retinotopic sensitivity beyond early visual cortex.

The paper uses ultra-high resolution fMRI to study feedforward and feedback activity in human V1 ocular dominance columns across cortical depths.

The paper shows that visual-spatial representations in the brain are condition-dependent and reveal widespread visual organization beyond traditional visual areas.

This study shows that dopaminergic medication in Parkinson’s disease reduces striatal sensitivity to negative outcomes during learning and affects subsequent approach/avoidance behavior.

This study shows that visual cortex activity predicts future value-based choices, suggesting a role for visual regions in supporting striatal bias during decision-making.

This study identifies five ipsilateral visual field maps in the human cerebellum, located in specific brain regions associated with visual and attention networks.

This study investigates how implicit and explicit learning contribute to saccade adaptation in reactive versus voluntary tasks, finding that explicit learning is reduced in voluntary saccades.

The paper investigates how spatial and feature-based attention interact to modulate spatial sampling in visual cortex, showing their combined effect on visual space resampling.

This study uses pupil responses to track value-based decision-making and reinforcement learning during a task, finding distinct patterns linked to value beliefs and reward prediction errors.

This study investigates whether tDCS over the frontal eye field affects saccade latency or accuracy, finding no significant effects.

Porcupine is a visual tool that creates reproducible neuroimaging analysis pipelines by generating code and Docker environments, improving transparency and shareability.

The paper investigates how fronto-basal ganglia circuitry contributes to response inhibition and conflict-induced slowing using fMRI and reinforcement-learning models.

This study shows that default network deactivations are spatially tuned to visual stimuli, enabling decoding of stimulus location from DN regions.