Ian Charest

A Python Toolbox for Representational Similarity Analysis

The paper introduces an open-source Python toolbox for representational similarity analysis, providing tools to evaluate neural representations and models.

Neural computations in prosopagnosia

This study identifies neural computations underlying face identification loss in a prosopagnosia patient using EEG, RSA, and deep neural networks, revealing impaired high-level visual and semantic processing.

Decoding face recognition abilities in the human brain

The paper decodes face recognition abilities from brain activity in super-recognisers and typical recognisers using multivariate pattern analysis and compares them to computational models.

Re-expression of CA1 and entorhinal activity patterns preserves temporal context memory at long timescales

The paper shows that re-expression of CA1 and entorhinal activity patterns predicts temporal context memory over long timescales in humans.

Reconstructing Spatio-Temporal Trajectories of Visual Object Memories in the Human Brain

This study uses EEG-fMRI fusion to show that visual object memory retrieval follows a backward spatio-temporal trajectory from conceptual to perceptual brain regions.

Disentangling five dimensions of animacy in human brain and behaviour

The paper investigates five animacy-related object dimensions in brain and behavior using fMRI, EEG, and similarity judgments, finding they explain variance in both brain representations and behavior.

GLMsingle: a toolbox for improving single-trial fMRI response estimates

GLMsingle improves single-trial fMRI response estimates using custom HRFs, noise regressors, and ridge regression, enhancing reliability and decoding performance across datasets.

Sleep spindles track cortical learning patterns for memory consolidation

The paper shows that sleep spindles correlate with learning patterns and predict memory consolidation in humans.

A massive 7T fMRI dataset to bridge cognitive and computational neuroscience

The paper introduces a large-scale 7T fMRI dataset of natural scenes to advance cognitive and computational neuroscience research.

The hippocampus as the switchboard between perception and memory

The paper identifies hippocampal gamma power as a marker of the switch from perceptual cues to mnemonic representations during memory recall, revealing hippocampal-cortical dynamics.

Spatiotemporal Dynamics of Sound Representations Reveal a Hierarchical Progression of Category Selectivity

This study reveals a hierarchical progression of category selectivity in sound processing by analyzing spatiotemporal dynamics using MEG and fMRI.

Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision

This paper shows recurrent neural networks outperform feedforward models in visual recognition tasks, enabling flexible speed-accuracy trade-offs and better prediction of human reaction times.

Individuals with clinically relevant autistic traits tend to have an eye for detail

The paper shows that individuals with higher autistic traits rely more on fine image details for natural image recognition.

Value shapes the structure of schematic representations in the medial prefrontal cortex

The paper shows that the medial prefrontal cortex encodes value-weighted schemas, where edge strength is influenced by value, experience, and node centrality.

Alpha/beta power decreases track the fidelity of stimulus-specific information

The paper shows that decreases in alpha/beta power correlate with increased fidelity of stimulus-specific information in the brain across different cognitive tasks.

Conscious perception of natural images is constrained by category-related visual features

The paper investigates how category-related visual features influence conscious perception of natural images using the Attentional Blink paradigm and deep neural network activation patterns.

Testing the fast consolidation hypothesis of retrieval-mediated learning

This study investigates the neurocognitive mechanisms of retrieval-mediated learning using fMRI, finding that retrieval increases prefrontal cortex activity and decreases hippocampal activity, supporting a fast consolidation hypothesis.

GLMdenoise improves multivariate pattern analysis of fMRI data

GLMdenoise improves replicability and classification accuracy in multivariate pattern analysis of fMRI data by reducing noise in GLM estimates.

Alpha/beta power compresses time in sub-second temporal judgments

The paper investigates how alpha and beta oscillatory activity relates to sub-second temporal judgments, finding that higher power correlates with shorter perceived time.

Neural dynamics of real-world object vision that guide behaviour

The paper investigates how brain activity links visual stimuli to behaviour, finding that behaviour-related activity emerges rapidly in the ventral visual pathway and cannot be explained by visual features or semantic categories alone.

The brain of the beholder: honouring individual representational idiosyncrasies

This paper reviews advances in neuroimaging analysis that move beyond traditional averaging by modeling individual representational idiosyncrasies using multivariate pattern analysis and representational dissimilarity matrices.