Alejandro Weinstein

This study evaluates how different QRS detection algorithms affect HRV metrics across various recording setups and conditions, finding significant variability in performance and recommending context-specific algorithm selection.

This study identifies disease-specific spectro-temporal signatures in Alzheimer's and Parkinson's disease using EEG and machine learning, revealing increased variability and distinct spectral markers.

This paper uses a physics-based model of brain networks to show that frequency-selective stimulation entrains specific sub-networks, with lower frequencies promoting broader synchrony and higher frequencies producing localized effects, determined by network structure and oscillatory dynamics.

This study uses a human connectome-coupled oscillators model to show that multiple coherent subnetworks emerge at maximum spectral entropy, reflecting brain metastability and cognitive flexibility.

The paper introduces an open-source LED display system for steady-state visual stimulation, validated for generating SSVEPs with precise frequency and phase control.

This study examines acoustic and electroencephalography changes during the Lombard effect in participants with normal hearing and voice, finding increased vocal intensity and altered ERP responses.

This study examines how averaging methods affect auditory steady-state response (ASSR) amplitudes in rats, finding that independent epochs yield higher amplitudes and better detection rates.