Anthony M. Norcia

The paper shows that strong mnemonic prediction errors enhance cognitive control, attention, and arousal, leading to better learning of unexpected stimuli.

This study shows that ultrasound-induced tissue displacement predicts functional neuromodulation in the human brain during transcranial ultrasound stimulation.

This study validates auditory noise masks to reduce the perceptibility of transcranial ultrasound, finding that high masker levels are needed and spectrum-tuned masks do not outperform white noise.

This study investigates the effects of transcranial focused ultrasound on visual perception and SSVEP in humans but finds no significant impact despite accurate targeting.

MatClassRSA v2 is a MATLAB toolbox for M/EEG classification, RDM computation, and visualization, offering updated modules and functionalities for cognitive neuroscience research.

This study investigates how spatial attention and session day affect human visual cortical plasticity using SSRP and EEG, finding that potentiation increases with repeated sessions and attention enhances it in naive participants.

The paper uses SSVEP phase information to measure neural latency in visual word form recognition and shows it predicts reading fluency and comprehension in children.

The paper investigates when visual category representations emerge in infants' brains using EEG and finds that responses to faces appear first, followed by limbs and places, with more distinct patterns by 6-15 months.

This study shows that two weeks of classroom vocabulary instruction can produce neural responses similar to long-term vocabulary learning, correlating with phonological decoding skills.

This study examines time-varying neural engagement during music listening using EEG inter-subject correlations, finding significant correlations during musical tension but not at climactic peaks.

The paper investigates contrast and blur sensitivity of two disparity processing channels in human visual cortex using SSVEPs to DRDS stimuli and relates them to monocular input properties.

The paper measures ON and OFF pathway responses in different visual fields using EEG and finds that OFF responses are larger, especially in the lower visual field, with differences in non-linearity across visual fields.

The paper assesses the stability of steady-state visual evoked potential contrast response functions over time, finding them stable enough for repeated-measures studies of neuroplasticity.

The paper investigates the temporal processing of absolute and relative disparity cues in scene perception using EEG, finding that absolute disparity is processed first and task effects emerge after relative disparity is extracted.

The paper investigates the temporal dynamics of absolute and relative disparity processing in human visual cortex using EEG and stereograms, finding sustained and transient mechanisms for each.

This study shows that V1 neurons in macaques rapidly and strongly respond to natural images across all cortical layers within 60 ms of stimulus onset.

This paper shows that making neural networks more robust to image perturbations aligns their features with macaque V1 neural responses and improves predictivity.

The paper uses SSVEPs and RCA to detect sublexical and lexical processing in early readers, finding early evidence of lexical fine-tuning in kindergarteners.

This study uses MR-guided TUS to modulate visual evoked potentials and cortical oscillations in a sheep model by targeting the lateral geniculate nucleus.

The paper uses SSVEP and RCA to identify distinct neural sources in visual word recognition, finding two components with different latencies and topographies.

This study re-examines symmetry processing in macaques using fMRI, finding cortical responses comparable to humans, suggesting macaques as a relevant model for studying symmetry at the microscopic level.

This study measures fixation disparity using an autostereoscopic display, finding that disparity and target eccentricity affect the magnitude and direction of fixation errors in both practiced and naive observers.

This paper develops a computational model of mouse visual cortex, finding that self-supervised contrastive learning produces better matches to mouse cortex than supervised methods, suggesting a resource-efficient, general-purpose visual system.

The paper investigates contrast decrement and increment responses in human visual cortex using VEPs, finding differences in amplitude, latency, and spatial tuning that mirror findings in animal models.

The paper shows that slow SSVEP stimulation rates can reveal parietal cortex involvement in abstract numerosity processing, with stronger responses to suprathreshold number changes.

This study compares CNN layer representations with EEG data to find hierarchical and non-hierarchical correlations in object processing timing.

This study examines neural correlations during music listening, finding that disrupted musical structures increase time-domain correlations while beat-related frequencies show peak coherence.

This study investigates tACS effects on binocular rivalry using phase and frequency-specific stimulation, finding frequency-specific modulation but no phase preference.

The paper investigates how human visual cortex processes relative motion and disparity cues for image segmentation, finding retinotopic organization and attentional modulation in early visual areas and candidate regions for cue integration.

This paper identifies a shared visual processing dysfunction in Nhe3 mutant Drosophila and autistic humans, suggesting a genetic basis for autism-related sensory alterations.