Publications

Refereed Journal Papers

  • Shaw, S. B., Dhindsa, K., Reilly, J. P., & Becker, S. (2019). Capturing the Forest but Missing the Trees: Microstates Inadequate for Characterizing Shorter-Scale EEG Dynamics.  Neural Computation. 31:11.
  • Dhindsa, K., Acai, A., Wagner, N., Bosynak, D., Kelly, S., Bhandari, M., Petrisor, B., & Sonnadara, R. R. (2019). Individualized pattern recognition for detecting mind wandering from EEG during live lectures. PloS one14(9), e0222276. LINK
  • Boshra, R., Dhindsa, K., Boursalie, O., Ruiter, K. I., Sonnadara, R., Samavi, R., Doyle, T. E., & Connolly, J. F. (2019). From Group-Level Statistics to Single-Subject Prediction: Machine Learning Detection of Concussion in Retired Athletes. IEEE Transactions on Neural Systems and Rehabilitation Engineering 27(7): 1492:1501. LINK
  • Dhindsa, K., Gauder, K. D., Marszalek, K., Terpou, B., & Becker, S. (2018). Progressive Thresholding: Shaping in Automated Neurofeedback Training. IEEE Transactions on Neural Systems and Rehabilitation Engineering 26(12): 2297-2305. LINK
  • Dhindsa, K., Bandhari, M., & Sonnadara, R. R. (2018). The big data revolution in healthcare: What’s the holdup?. BMJ 363, k5357. LINK
  • Dhindsa, K., Carcone, D. & Becker, S. (2017). Towards an open ended BCI: a user-centred co-adaptive design. Neural Computation 29:10. LINK
  • Dhindsa, K. (2017). Filter-bank artifact rejection: high performance real-time single-channel artifact detection for EEG. Biomedical Signal Processing and Control, 38: 224-235LINK
  • Engchuan, W., Dhindsa, K., Lionel, A. C., Scherer, S. W., Chan, J. H., & Merico, D.(2015). Performance of case-control rare copy number variation annotation in classification of autism. BMC medical genomics, 8(1), 1. LINK
  • Dhindsa, K., Drobinin, V., King, J., Hall, G. B., Burgess, N., & Becker, S. (2014). Examining the role of the temporo-parietal network in memory, imagery, and viewpoint transformations. Frontiers in human neuroscience, 8, 709. LINK

Refereed Conference Proceedings

  • Dhindsa, K., Smail, L. C., McGrath, M., Braga, L. H., Becker, S., & Sonnadara, R. R. (2018). Grading Prenatal Hydronephrosis from Ultrasound Imaging using Deep Convolutional Neural Networks. 15th Conference on Computer and Robot Vision. IEEE. LINK
    *Awarded best oral presentation
  • Dhindsa, K. & Becker, S. (2017, June). Emotional Reaction Recognition from EEG. 7th International Workshop on Pattern Recognition in Neuroimaging 2017. IEEExplore. LINK
  • Dhindsa, K., Carcone, D. & Becker, S. (2017, July). A Brain-Computer Interface Based on Abstract Visual and Auditory Imagery: Evidence for an Effect of Artistic Training. In International Conference on Augmented Cognition (pp. 313-332). Springer, Cham. LINK
  • Dhindsa, K., Carcone, D. & Becker, S. (2015). An Open-Ended Approach to BCI: Embracing Individual Differences by Allowing for User-Defined Mental Commands. Front. Comput. Neurosci. Conference Abstract: German-Japanese Adaptive BCI Workshop. LINK