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E-print Articles: Recent submissions

  • Temporal synchronization analysis: a model-free method for detecting robust and nonlinear brain activation in fMRI data 
    Fialoke, Suruchi; Deb, Aniruddha; Rode, Kushagra; Tripathi, Vaibhav; Garg, Rahul (Cold Spring Harbor Laboratory, 2025-04)
    The sluggishness of the fMRI blood oxygenation level dependent (BOLD) signal has motivated the use of block or trial-based experimental designs that rely on the assumption of linearity, typically modeled using the General ...
  • Can EEG resting state data benefit data-driven approaches for motor-imagery decoding? 
    Mehta, Rishan; Rajpura, Param; Meena, Yogesh Kumar (Cornell University Library, 2024-10)
    Resting-state EEG data in neuroscience research serve as reliable markers for user identification and reveal individual-specific traits. Despite this, the use of resting-state data in EEG classification models is limited. ...
  • Eye-tracking the determinants of shopping behaviour 
    Miyapuram, Krishna Prasad; Adewumi, Bukunmi O. (Cornell University Library, 2022-08)
    According to previous research, colour and price do influence shopping behaviour. Previous studies found that fixation duration on price decreases as price increases (Menon et al., 2016), and participants' fixation duration ...
  • Verbal labels facilitate tactile texture discrimination in a perceptual learning task 
    Arun, Ishita; Lazar, Leslee (Cold Spring Harbor Laboratory, 2021-02)
    The influence of language on perceptual processes, referred to as the Whorfian hypothesis, has been a contentious issue. Cross-linguistic research and lab-based experiments have shown that verbal labels can facilitate ...
  • Classifying songs with EEG 
    Lawhatre, Prashant; Shiraguppi, Bharatesh R.; Sharma, Esha; Miyapuram, Krishna Prasad; Lomas, Derek (Cornell University Library, 2020-10)
    This research study aims to use machine learning methods to characterize the EEG response to music. Specifically, we investigate how resonance in the EEG response correlates with individual aesthetic enjoyment. Inspired ...
  • PsychFM: predicting your next gamble 
    Ranjan, Prakash; Miyapuram, Krishna P. (Cornell University Library, 2020-07)

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