Bernhard Spitzer

This study examines how gaze patterns and EEG reflect the temporal dynamics of multi-item working memory maintenance, finding stable gaze encoding and no rhythmic alternation between items.

The paper investigates how visuospatial working memory representations are organized in the human brain, finding both abstract and concrete visual representations coexisting in visual areas.

The paper investigates how retrieving information from prioritized or deprioritized working memory states affects long-term memory recall, finding a stronger benefit for deprioritized information.

The paper investigates how asymmetric learning biases affect transitive inference and adaptability to changes in relational structures, finding that winner-biased learning improves flexibility in certain hierarchy changes.

The paper investigates whether neural representational geometries reflect behavioral underweighting of extreme values in numerical judgment tasks, finding enhanced processing of extremes but no evidence for neural compression.

This study shows that small gaze shifts encode visual working memory information, including multiple orientations, and reveal changes in representational format during unattended memory storage.

The paper shows that semantic qualities are prioritized over visuo-perceptual aspects in multi-item working memory, similar to episodic memory retrieval.

The paper shows that having control over when to stop sampling improves decision accuracy, parietal decision signals, and EEG encoding of numerical information in human decisions from experience.

The paper shows that asymmetric learning, where beliefs about winners or losers are updated selectively, improves transitive inference in humans and aligns with cognitive distortions observed in psychophysics and behavioral economics.

The paper investigates how visual working memory (WM) interacts with perception during sequential integration of approximate number, finding that WM biases perception but is rapidly deprioritized.

The paper tests a selective integration model of decision-making using EEG, finding that neural signals encode locally preferred attributes with higher gain.

This study shows that reduced beta desynchronization in Parkinson’s disease is linked to impaired memory formation.

The paper shows that human neural representations of novel visual stimuli align with magnitude-based mental number line representations during reward-guided learning.