APA   Click to copy
Mischler, G., Keshishian, M., Bickel, S., Mehta, A. D., & Mesgarani, N. (2023). Deep neural networks effectively model neural adaptation to changing background noise and suggest nonlinear noise filtering methods in auditory cortex. NeuroImage, 266. https://doi.org/10.1016/j.neuroimage.2022.119819

Chicago/Turabian   Click to copy
Mischler, Gavin, Menoua Keshishian, Stephan Bickel, Ashesh D Mehta, and Nima Mesgarani. “Deep Neural Networks Effectively Model Neural Adaptation to Changing Background Noise and Suggest Nonlinear Noise Filtering Methods in Auditory Cortex.” NeuroImage 266 (2023).

MLA   Click to copy
Mischler, Gavin, et al. “Deep Neural Networks Effectively Model Neural Adaptation to Changing Background Noise and Suggest Nonlinear Noise Filtering Methods in Auditory Cortex.” NeuroImage, vol. 266, 2023, doi:10.1016/j.neuroimage.2022.119819.

@article{gavin2023a,
  title = {Deep neural networks effectively model neural adaptation to changing background noise and suggest nonlinear noise filtering methods in auditory cortex},
  year = {2023},
  journal = {NeuroImage},
  volume = {266},
  doi = {10.1016/j.neuroimage.2022.119819},
  author = {Mischler, Gavin and Keshishian, Menoua and Bickel, Stephan and Mehta, Ashesh D and Mesgarani, Nima}
}