skip to primary navigation skip to content

With a background in neural engineering and an interest in method development for neuroimaging analysis (EEG, MEG and fMRI), I pursue three main research questions:

How does the brain support visual object recognition?

How is information transferred across the brain's attention networks (e.g. the multiple-demand network) to support cognitive control?

How does the brain encode information and how we can decode them more effectively for brain-computer interfacing?

Other journal publications (¥ = equally contributing authors):
  1. Karimi-Rouzbahani, H., Shahmohammadi, M., Vahab, E., Setayeshi, S., Carlson, T., (2021) Temporal variabilities provide additional category-related information in object category decoding: a systematic comparison of informative EEG features. (accepted in Neural Computation)
  2. ¥Merrikhi, Y., ¥Shams-Ahmar, M., ¥Karimi-Rouzbahani, H., Clark, K., Ebrahimpour, R., Noudoost, B. (2021) Dissociable contribution of extrastriate responses to representational enhancement of gaze targets. Journal of Cognitive Neuroscience, 1-14.
  3. Karimi-Rouzbahani, H., Woolgar, A., Rich, A. (2021) Neural signatures of vigilance decrements predict behavioural errors before they occur. eLife, 10:e60563.
  4. Karimi-Rouzbahani, H., Ramezani, F., Woolgar, A., Rich, A., Ghodrati, M. (2021) Perceptual difficulty modulates the direction of information flow in familiar face recognition. NeuroImage, 117896.
  5. Pavlov, Y., …, Karimi-Rouzbahani, H., …, (2021) #EEGManyLabs:‌ ‌Investigating‌ ‌the‌ ‌Replicability‌ ‌of‌ ‌Influential‌ ‌EEG‌ ‌Experiments‌.  Cortex.
  6. Karimi-Rouzbahani, H., Vahab, E., Ebrahimpour, R., & Menhaj, MB. (2019) Spatiotemporal analysis of category and target-related information processing in the brain during object detection. Behavioral Brain Research, 369, 224-239.
  7. Karimi-Rouzbahani, H., Bagheri, N., & Ebrahimpour, R. (2017). Invariant object recognition is a personalized selection of invariant features in humans, not simply explained by hierarchical feed-forward vision models. Scientific reports, 7(1), 14402.
  8. Karimi-Rouzbahani, H., Bagheri, N., & Ebrahimpour, R. (2017). Hard-wired feed-forward visual mechanisms of the brain compensate for affine variations in object recognition. Neuroscience, 349, 48-63.
  9. Karimi-Rouzbahani, H., Bagheri, N., & Ebrahimpour, R. (2017). Average activity, but not variability, is the dominant factor in the representation of object categories in the brain. Neuroscience, 346, 14-28.
  10. Karimi-Rouzbahani, H. (2018). Three-stage processing of category and variation information by entangled interactive mechanisms of peri-occipital and peri-frontal cortices. Scientific reports, 8(1), 12213.
  11. Karimi-Rouzbahani, H., Ebrahimpour, R., & Bagheri, N. (2016). Quantitative evaluation of human ventral visual stream in invariant object recognition: Human behavioral experiments and brain-plausible computational model simulations. Machine Vision and Image Processing, 3(2), 59-72.
  12. Karimi-Rouzbahani, H., & Daliri, M. R. (2011). Diagnosis of Parkinson’s disease in human using voice signals. Basic and Clinical Neuroscience, 2(3), 12-20.