Niknam, K., Akbarian Aghdam, A., Noudoost, B., Nategh, N. " Characterizing Saccadic Modulation of Visual Processing Using a State-based Statistical Model of Spiking Responses". Under review.

Akbarian Aghdam, A., Niknam, K., Parsa, MB., Clark, K., Noudoost, B., Nategh, N. Developing a Nonstationary Computational Framework with Application to Modeling Dynamic Modulations in Neural Spiking Responses. IEEE Transactions on Biomedical Engineering, 5(2):241-253, 2018.

Nategh, N., Manu, M., Baccus, S.A. (2018) Diverse Nonlinear Modulation of Visual Features by Retinal Amacrine Cells. bioRxiv doi: 10.1101/273730

Noudoost, B., Nategh. N., Clark, K., Esteky, H. Stimulus Context Alters Neural Representations of Faces in Inferotemporal Cortex. J Neurophysiol., 117(1):336-347, 2017.

Niknam, K., Akbarian Aghdam, A., Noudoost, B., Nategh, N. Characterizing Unobserved Factors Driving Local Field Potential Dynamics Underlying a Time-varying Spike Generation. The 6th IEEE Global Conference on Signal and Information Processing (GlobalSIP 2018). Accepted.

Zamani, Y., Nategh N. Developing a Convolutional Neural Network-Based Model of Inhibitory Computations in the Retina. Computational and Systems Neuroscience (Cosyne 2019). Under review.

Niknam, K., Akbarian Aghdam, A., Noudoost, B., Nategh, N. A Novel Computational Model Capturing Dynamic Changes in the Perisaccadic Response of Visual Neurons. Computational and Systems Neuroscience (Cosyne 2019). Under review. 

Zamani, Y., Nategh N. A Deep Learning Model Of Retinal Responses Using Excitatory-Inhibitory Mixture Network Models. The 9th International IEEE EMBS Conference on Neural Engineering, (NER 2019). Under review.

Zamani, Y., Nategh N., Computationally Robust Convolutional Neural Network-based Models of Retinal Responses. The 17th IEEE International Conference on Machine Learning and Applications (ICMLA 2018), Under review.

Niknam, K., Akbarian Aghdam, A., Noudoost, B., Nategh, N. Model-based Decoding of Time-varying Visual Information During Saccadic Eye Movements Using Single- and Multi-neuron MT Responses. Proceedings of the 51st Annual Asilomar Conference on Signals, Systems and Computers, 2017.

Niknam, K., Akbarian Aghdam, A., Noudoost, B., Nategh, N. A Computational Model for Characterizing MT Visual Information Using Both Spikes and Local Field Potentials. Proceedings of the 8th International IEEE EMBS Conference on Neural Engineering, pp. 656-659, 2017.

Nategh, N. Adaptive Image Processing and Computational Vision. (Invited Paper) Computational Optical Sensing and Imaging (COSI), The Optical Society.

Niknam, K., Akbarian Aghdam, A., Noudoost, B., Nategh, N. Modeling Perisaccadic Visual Representation in MT Neurons by Incorporating Population-level Information. Presented at Neuroscience 2016, Society for Neuroscience Meeting, San Diego, CA, Oct. 12-16, 2016.

Akbarian Aghdam, A., Parsa, MB., Nategh, N., Noudoost, B. MT Neurons Preserve Visually Selective Signals Across Eye Movements. Presented at Neuroscience 2016, Society for Neuroscience Meeting.

Akbarian Aghdam, A., Parsa, MB., Noudoost, B., Nategh, N. Spatiotemporal Dynamics of MT Receptive Fields During Eye Movements. (Nanosymposium) Presented at Neuroscience 2015, Society for Neuroscience Meeting.

Nategh, N., Manu, M., Baccus, S.A. Understanding Modulatory Computations in Neural Pathways of the Retina. (Nanosymposium) Presented at Neuroscience 2014, Society for Neuroscience Meeting.

Nategh, N., Manu, M., Baccus, S.A. Characterizing the Modulatory Contribution of a Sensory Interneuron in the Retina. Presented at Neuroscience 2012, Society for Neuroscience Meeting.

Nategh, N., Manu, M., Baccus, S.A. Contribution of Amacrine Transmission to Fast Adaptation of Retinal Ganglion Cells, Presented at Computational and Systems Neuroscience (Cosyne 2010).

Nategh, N., Manu, M., Baccus, S.A. Feature-specific Control of Retinal Ganglion Cell Gain and Kinetics by Amacrine Cells. Presented at Neuroscience 2009, Society for Neuroscience Meeting.