Default Dataset for Final Project (Section 001)#
Note: if you do not want to use this dataset, you will need to propose your desirable dataset(s) to Dr. Mengsen Zhang for approval before proceeding to develop your project. The goal is to have a dataset (or combo of multiple datatsets) that is complex enough to accommodate a wide range of methods covered in class.
The data: The Freiwald Tsao Face View AM dataset#
A zip containing csv datasets can be download here.
The data was initially downloaded from Neural Decoding Toolbox website.
What is it about#
The Freiwald Tsao Face Views AM dataset was collected by Winrich Freiwald (Rockefeller University) and Doris Tsao (UC Berkeley), and was originally published in Freiwald and Taso (2010).
This dataset is used for “neural decoding”, which meaning figuring out what a person/animal is doing, seeing, or hearing from the neural activities alone!
The data consists of recordings of neuron activities from anterior medial face patch (AM), a specific brain region that is activated when an animal sees a face. The animal was passively viewed images of 25 individuals from 8 different head orientations. Face images were presented to the animal in random order in a rapid sequence where each image was shown for 200 ms followed by a 200 ms blank interval. A value of 1 means s neuron is active in a specific time interval (or one say the neuron spiked), while 0 means the neuron is quiet. Labels are provided for each presented imaged in terms of the identify of the individual in the image and the orientation of the individual’s face.
The data is in raster format, which are essentially a [num_trials x num_times] matrix, where the rows is neuron activity from one trial, i.e., during and shortly after when the animal sees one specific face image. Each column represents time in the trial from the time when the image first show up on the screen (the recoding goes up to 800 ms, but only the first 400 ms is relevant for the labeled image).
A decoding analysis of this data was published in Meyers et al (2015).
Citations#
You will need to cite the publications below in your project:
Freiwald, W. A., & Tsao, D. Y. (2010). Functional compartmentalization and viewpoint generalization within the macaque face-processing system. Science, 330(6005), 845-851.
Meyers, E. M., Borzello, M., Freiwald, W. A., & Tsao, D. (2015). Intelligent information loss: The coding of facial identity, head pose, and non-face information in the macaque face patch system. Journal of Neuroscience, 35(18).
You may also read them to better understand the dataset.