Current Directions

Theme 1: Systems and Cognitive Neuroscience

We, primates, use vision as our primary sense to deal with many objects that surround us. Our lifelong experience with objects teaches us that some objects are more valuable than others (e.g. our favorite foods, people etc). Despite the primacy of this phenomenon, little is known about the neural mechanism that learns and stores the objects’ values in primates’ brain. Recent evidence shows that different structures are involved in different time-scales of value learning and memory and depending on the context.

Current projects in this theme are looking at behavioral and neural correlates of value learning and memory using fMRI and electrophysiology in both humans and macaques. We also have some side projects for looking at cortical travelling waves, modeling object tracking using drift diffusion frame work and modeling human personality. For project details see members’ description of their projects.

Members involved: Mohammad Amin Fakharian, Kiomars Sharifi, Ali Vishkai, Parsa Delavari, MohammadAli Kheirkhah, Mohammad Amin Nazarzadeh, MohammadReza Heidari and, Taraneh Attary.

Theme 2:  Data Science and Physical Tools for Neuroscience

Understanding neuroscience data, be it neuronal or behavioral, requires new tools for crunching and making sense of experimental results. These tools can lead to new analysis methods or modeling. In particular, recent development in machine learning and deep learning, prompts us to actively work to adapt them to address our key questions in systems and cognitive neuroscience.

Current projects in this theme include, using causal graph learning to understanding brain networks involved in object value representation, using RNNs to predicting gaze when looking at valuable objects, using deep neural nets to enhancing the EEG source localization to the level of MRI, and better tools for quantifying neural response variability. We are also developing a low-cost high precision eye tracking system and improving optical imaging image processing. For project details see members’ description of their projects.

Members involved: Ali Ataei, MohammadAmin Fakharian, Farnaz Jazayeri, Saleh Fayyaz, MohammadAmin Alemohammad, Mehdi Cherakhloo, MohammadAmin Mamanpoosh, Farrokh Karimi

Members

Alumni

Mohammad Amin Nazerzadeh, BSc Student in CE Dept at SUT

Morteza Zangeneh Soroush, Postdoctoral researcher in Sharif Brain Center

Ali Ataei, PhD Candidate in BME in EE Dept at SUT

Leila Noorbala, PhD Student in Cognitive Science at SBU

Farrokh Karimi,Research Fellow in SCS at IPM

Mohammad Amin Fakharian, MSc Student in EE Dept at SUT

Ali A. Khoshvishkaie, MSc Student in AI in CE Dept at SUT

Kiomars Sharifi, MSc Student in BME in EE Dept at SUT

Mohammad Amin ma’manpoush, MSc Student in BME in EE Dept at SUT

Seyed Mohammad Amin Alemohammad, MSc Student in BME in EE Dept at SUT

Mahdi Cherakhloo, MSc Student in BME in EE Dept at SUT

Mohammad Reza Heydari, MSc Student in EE Dept at SUT

Saleh Fayyaz, MSc Student in EE Dept at SUT

Farnaz Jazayeri, MSc Student in CS Dept at SUT

Alireza khoshzaban, BSc Graduate in Pure Chemistry from SUT

Parsa Delavari, BSc Student in EE Dept at SUT

Mohammad Ali Kheirkhah, BSc Student in EE Dept at SUT

Mohammad Amin Nazerzadeh, BSc Student in CE Dept at SUT

Publications

• Ali Ghazizadeh, MohammadAmin Fakharian, Arash Amini, Whitney Griggs, David A Leopold, Okihide Hikosaka. “Object novelty and value coding segregate across functionally connected brain networks.” bioRxiv preprint (2019) [Link]
• Daneshi, Asieh, Hamed Azarnoush, Farzad Towhidkhah, Amin Gohari, and Ali Ghazizadeh. “Drift-diffusion explains response variability and capacity for tracking objects.” Scientific reports 9, no. 1 (2019): 1-15.‏ [Link]
• Heidarieh, S. M., M. Jahed, and A. Ghazizadeh. “A New Nonlinear Sparse Component Analysis for a Biologically Plausible Model of Neurons.” Neural computation (2019): 1-21.‏ [Link]
• Ali Ataie, Arash Amini, Ali Ghazizadeh, ‘Brain Activity Estimation using EEG-only Recordings Calibrated with joint EEG-fMRI Recordings using Compressive Sensing’, SAMPTA 2019. [PDF]

Relevant Past Publications

• Ali Ghazizadeh, Simon Hong, Okihide Hikosaka, Prefrontal cortex represent value memory of objects for months, Current Biology, 2018
• Ali Ghazizadeh, Whitney Griggs, David A. Leopold, Okihide Hikosaka, A long term high capacity memory system in temporal and prefrontal cortices for valuable objects, PNAS, 2018
• Whitney Griggs, Hyoung F Kim, Ali Ghazizadeh, M Gabriela Costello, Kathryn M Wall, Okihide Hikosaka, Flexible and stable value coding areas in caudate head and tail receive anatomically distinct cortical and subcortical inputs, Frontiers in Neuroanatomy, 2017
• Hikosaka, Okihide, Ali Ghazizadeh, Whitney Griggs, and Hidetoshi Amita. Parallel basal ganglia circuits for decision making. Journal of Neural Transmission (2017): 1-15.
• Ali Ghazizadeh, Whitney Griggs, Okihide Hikosaka, Object finding skill created by repeated reward experience, Journal of Vision, 16(10):17, 1–13, 2016
• Ali Ghazizadeh, Whitney Griggs, Okihide Hikosaka, Ecological origins of object salience: reward, uncertainty, aversiveness and novelty, Frontiers in Neuroscience, 10, 378, 2016
• Hyoung F Kim, Ali Ghazizadeh, Okihide Hikosaka, Dopamine neurons encoding long-term memory of object value for visual oculomotor habit, Cell, 163(5):1165-75, 2015
• Hyoung F Kim, Ali Ghazizadeh, Okihide Hikosaka, Separate Groups of Dopamine Neurons Innervate Caudate Head and Tail Encoding Flexible and Stable Value Memories. Frontiers in Neuroanatomy. 8:120, 2014