Tijl Grootswagers

Sustained multidimensionality of object representations as a scaffold for diverse behaviours

The paper investigates how neural representations of objects support diverse behaviors, finding that multidimensional representations are accessible across tasks but limited by object familiarity.

The neural processes of illusory occlusion in object recognition

This study investigates whether illusory shape perception and object recognition share neural processes, finding no interaction and distinct neural time courses.

The Centroparietal Positivity Traces the Path of Evidence Accumulation During Dietary Decisions

The paper investigates whether the centroparietal positivity (CPP) reflects evidence accumulation during dietary decisions, finding it aligns with hypothesized accumulation trajectories.

Enhanced neural encoding of individual exemplars in the Super-Recogniser brain is specific to faces

The paper finds that Super-Recognisers show enhanced neural encoding of individual face identities but not other categories like dogs, cars, or houses.

An open dataset of human electroencephalographic and behavioural responses to food images

The paper introduces a dataset of EEG and behavioural responses to food images, along with normative ratings and questionnaire data, to study neural mechanisms of food choices.

Optimising analysis choices for multivariate decoding: creating pseudotrials using trial averaging and resampling

This study evaluates how trial averaging and resampling affect decoding accuracy in MVPA, finding that modest averaging improves results and provides code for parameter optimization.

Robust neural face identity codes in the Super-Recogniser brain

This study compares neural face identity coding between Super-Recognisers and typical recognisers, finding stronger and more consistent identity representations in Super-Recognisers during mid-latency processing.

A multibrain advantage for cooperative human behaviour

This study shows that successful cooperation involves complementary neural representations across brains, with combined signals carrying more target-related information than individual brains.

A comprehensive EEG dataset for investigating visual touch perception

The paper presents a comprehensive EEG dataset with self-report measures to study visual touch perception and its neural basis.

Robust Neural Decoding with low density EEG

This study investigates how electrode density affects EEG-based neural decoding accuracy using visual and natural stimuli, finding that reliable decoding is possible even with low-density setups.

Multiple Partially Overlapping Neural Modules Orchestrate Conflict Processing

The paper uses EEG data from three conflict tasks to show that conflict processing involves partially overlapping neural mechanisms rather than being fully domain-general or task-specific.

Unlocking information alignment between interacting brains

This study uses Interbrain RSA on EEG hyperscanning to show that interbrain information alignment occurs rapidly and strengthens with practice during social interactions.

Characterising the neural time-courses of food attribute representations

The paper examines how different food attributes are processed over time in the brain using EEG and ratings, finding distinct early and sustained neural time-courses for attribute representations.

Hierarchical Emergence Profiles of Human-Derived Dimensions are a Fundamental Property of Deep Neural Networks

The paper shows that human-derived dimensions in deep neural networks emerge hierarchically across layers, similar to human vision, and is influenced by architecture, learning objectives, and stimulus statistics.

Rapid visual engagement in neural processing of detailed touch interactions

The paper investigates how vision encodes sensory and emotional aspects of observed touch using EEG data, finding early visual processing of body cues and emotional details.

Mapping object space dimensions: new insights from temporal dynamics

The paper investigates how aspect ratio, animacy, and category information is represented over time during object processing using EEG data, finding that aspect ratio is represented earlier and more transiently than categorical dimensions.

Neural decoding of competitive decision-making in Rock-Paper-Scissors

This study uses EEG hyperscanning to decode neural representations during competitive Rock-Paper-Scissors gameplay, revealing cognitive biases and the influence of prior outcomes on decision-making.

Movement trajectories as a window into the dynamics of emerging neural representations.

The paper shows movement trajectories can track the dynamics of neural representations over time, correlating with MEG and fMRI data using RSA.

Mapping the Dynamics of Visual Feature Coding: Insights into Perception and Integration

This study examines how visual features are coded in the human early visual cortex and their relationship to perception using EEG and behavioural data.

Minimal condition repetitions required in rapid serial visual presentation decoding paradigms

This study determines that six repetitions per condition are sufficient for reliable decoding in RSVP paradigms, enabling efficient experiments for diverse populations.

Undivided attention: The temporal effects of attention dissociated from decision, memory, and expectation

This study investigates the dynamic effect of attention on visual processing using EEG data, showing preferential coding of attended stimuli around 230ms after stimulus onset, independent of target-related processes and temporal expectation.

An empirically-driven guide on using Bayes Factors for M/EEG decoding

This paper provides a guide on using Bayes Factors for M/EEG decoding results, examining their impact on statistical assessment of neural data.

Human electroencephalography recordings for 1,854 concepts presented in rapid serial visual presentation streams

The paper introduces THINGS-EEG, a dataset of EEG responses to 1,854 object concepts, to study visual object processing in the human brain.

Getting the gist faster: Blurry images enhance the early temporal similarity between neural signals and convolutional neural networks

This study shows that blurry images enhance early temporal similarity between neural signals and CNNs, revealing how image perturbations affect CNN-Brain correspondence.

The neural dynamics underlying prioritisation of task-relevant information

This study investigates how attention modulates neural responses to simultaneous visual stimuli, finding that attention enhances decodability of task-relevant information, particularly for smaller stimuli.

Overlapping neural representations for the position of visible and imagined objects

This study investigates how the brain tracks the position of visible and imagined objects using EEG and multivariate pattern analysis, finding that imagined object tracking uses similar perceptual processes but with different timing.

The influence of object-colour knowledge on emerging object representations in the brain

This study examines how object-colour knowledge influences brain activity patterns during object recognition, showing that conceptual knowledge affects representations after initial feature processing.

A humanness dimension to visual object coding in the brain

The paper investigates how the brain codes visual objects by testing models of animacy, agency, and human-similarity using MEG data.

Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children

This study uses EEG to show that neurotypical children have variable neural responses to lexical-semantic violations, suggesting individual analyses are needed for disorders like ASD.

Decoding Predictions and Violations of Object Position and Category in Time-resolved EEG

This study uses EEG and pattern analysis to test predictive coding theory in object vision, finding no difference in decoding accuracy between predictable and violation conditions but suggesting active anticipation of future input.