Federico De Martino

Temporal Progression of Prior Precision, Surprisal, Model Updating and Tone Adaptation in Human Auditory Cortices

The paper investigates the temporal dynamics of auditory processing in human brains using MEG, revealing a hierarchical sequence of predictive and adaptive mechanisms.

Learned Audiovisual Predictability Modulates Depth-Resolved Hippocampal-Cortical Functional Coupling

The paper investigates how learned auditory predictability affects depth-resolved functional coupling between hippocampal subfields and cortical regions using 7T fMRI.

Predictive perception via simultaneous learning and inference

This paper introduces a model that performs exact Bayesian inference over a discrete state space using a local Hebbian rule, demonstrating its ability to account for perception and decision-making under noise.

Stimulus dependent modulation of perceptual filling-in is predicted by the properties of early visual cortex

The paper tests a two-stage model of perceptual filling-in by examining how early visual cortex properties like the oblique effect and surround suppression influence the phenomenon.

Representational structure of perceived food attributes in human occipitotemporal cortex

The paper uses fMRI and RSA to show that food-related neural representations in occipitotemporal cortex reflect perceived calorie, health, and category structure, but not isolated calorie coding.

Predictive acoustical processing in human cortical layers

This study uses laminar fMRI to investigate predictive auditory processing in human cortical layers, showing hierarchical organization of prediction violations and their association with specific cortical layers.

Feedback to deep layers in human V1 during perceptual filling-in

This study investigates perceptual filling-in in human V1 using fMRI, finding that deep cortical layers show neural correlates associated with feedback input during the phenomenon.

Dissociable dynamic effects of expectation during statistical learning.

This study investigates the dynamic effects of expectation during statistical learning, finding dissociable patterns in decoding accuracy within and across trials that support the opposing process theory.

Neural correlates of implicit memory for reoccurring sound patterns

This study investigates implicit memory for reoccurring sound patterns using UHF fMRI, finding that reoccurrence enhances perceptual precision and engages specific brain regions.

Neural encoding of biomechanically (im)possible human movements in occipitotemporal cortex

This study uses fMRI to show that occipitotemporal cortex encodes biomechanically possible and impossible movements, with different regions processing detailed biomechanical features versus abstract categorical information.

Distinct Roles of Deep and Superficial Cortical Layers in Tone Prediction, Comparison, and Adaptation in Human Auditory Cortex

The paper investigates how different cortical layers in human auditory cortex process tone prediction, comparison, and adaptation using fMRI and computational modeling.

Context-dependent benefits of training and reminders in visual skill learning

The paper investigates how training and reminders affect visual skill learning, finding that reminders can be as effective as full training in certain contexts.

Unveiling early visual cortical mechanisms in perceptual filling-in: a parametric study of eccentricity and movement dependence

This study investigates how eccentricity and movement of visual stimuli affect perceptual filling-in by measuring neural adaptation in early visual areas.

Spanning spatial scales with functional imaging in the human brain; initial experiences at 10.5 Tesla

This paper presents initial results of 10.5 Tesla fMRI in humans, showing improved spatial resolution and functional contrast compared to 7 Tesla.

Linguistic modulation of the neural encoding of phonemes

This study investigates how linguistic processes modulate the neural encoding of phonemes using fMRI, showing that acoustic analysis is influenced by linguistic context and that both acoustic and phonetic information are necessary for this modulation.

Unbiased estimation of the coefficient of determination in linear models: an application to fMRI encoding model comparison

The paper shows that out-of-sample R2 in fMRI encoding models is biased and develops a framework to correct it for unbiased model comparison.

Evaluating the effect of denoising submillimeter auditory fMRI data with NORDIC

This study evaluates two versions of NORDIC denoising on submillimeter auditory fMRI data, finding improved detection sensitivity and reliability but reduced average response amplitude.

Cerebral blood volume sensitive layer-fMRI in the human auditory cortex at 7 Tesla: Challenges and capabilities

This paper develops and applies a VASO protocol to study laminar responses and tonotopy in the human auditory cortex at 7 Tesla.

Voxelwise encoding models of body stimuli reveal a representational gradient from low-level visual features to postural features in extrastriate body area.

This study uses fMRI and encoding models to show that the EBA represents body stimuli through a combination of low-level visual features and postural features.

Selective attention reduces responses to relevant sounds in human auditory cortex

This study shows that selective attention reduces auditory cortex responses to attended frequencies in humans using high-resolution fMRI, contrasting with previous findings.

Lowering the Thermal Noise Barrier in Functional Brain Mapping with Magnetic Resonance Imaging

This paper introduces a novel fMRI denoising technique that improves temporal-SNR and functional map detection without altering signal amplitudes or spatial precision.

Modulation of the primary auditory thalamus when recognising speech with background noise

The paper shows that left ventral MGB modulation increases during speech recognition in noisy conditions compared to clear speech or speaker identity tasks.

Improving a probabilistic cytoarchitectonic atlas of auditory cortex using a novel method for inter-individual alignment

The paper improves a probabilistic cytoarchitectonic atlas of auditory cortex by introducing CBA+, a method that aligns individual brains more accurately than existing methods.

Multivoxel Pattern of Blood Oxygen Level Dependent Activity can be sensitive to stimulus specific fine scale responses

The paper evaluates the spatial precision of stimulus-specific BOLD responses using MVPA across cortical depths in V1, finding that multivoxel patterns can achieve sub-millimeter resolution.

Layer-specific ultra-high field 7T fMRI showing that threat anticipation is mediated by the pulvinar input to the superficial layers of primary visual cortex (V1)

The paper uses 7T fMRI to show pulvinar input to V1 superficial layers mediates threat anticipation, not just threat perception.

Motion displaces population receptive fields in the direction opposite to motion

The paper investigates how motion affects population receptive field estimates in humans using fMRI and psychophysical measurements, finding that low-contrast motion shifts pRFs opposite to motion direction.

Mapping the human subcortical auditory system using histology, post mortem MRI and in vivo MRI at 7T

The paper maps the human subcortical auditory system using histology, post mortem MRI, and in vivo 7T MRI, creating atlases and connectivity maps with high-resolution data.

Predicting stimulus representations in the visual cortex using computational principles.

The paper presents a method to predict representational dissimilarity matrices by combining perceptual, categorical, and deep neural network-derived RDMs.

Methods for computing the maximum performance of computational models of fMRI responses

This paper introduces a new analytical method for estimating the noise ceiling in fMRI data, comparing it to existing methods and showing its advantages for real data.

A scalable method to improve gray matter segmentation at ultra high field MRI

The paper introduces a method to improve gray matter segmentation in ultra high field MRI by using 2D histograms, showing improved borders and providing an open implementation.