Dr. Sangkyun Lee

Address: Spemannstr. 38
72076 Tübingen


Picture of Lee, Sangkyun, Dr.

Sangkyun Lee

Position: Research Scientist  Unit: Alumni Logothetis

Topography of population receptive fields



Codes and supplementary infos


Introduction and Scientific Aims

The employment of functional magnetic resonance imaging (fMRI) in the visual neuroscience has allowed us to charaterize the functional organization of human visual cortex in a millimeter scale [1, 2]. Particularly, recent application of the population-receptive-field (pRF) model using a one-Gaussian model provides more accurate estimation of human visual pRFs with diverse stimuli [2]. Despite the recent advance in the pRF modeling, there are still limitations on modeling various properties of pRFs. For example, this model can not capture properties such as surround suppression, elongation of pRF (can be modeled with two sigmas), and so on. To overcome these limitations, we modeled visual pRF with a data-driven method.



Let vector p and a be a pRF model and a stimulus aperture. When visual stimuli present through the aperture, the pRF response is given as r = pa. As the pRF response is observed in the form of fMRI signal, it is required to convolve it with a canonical hemodynamic response function h. Therefore, the final pRF prediction x is given:

x = h*r = h*(pa)

Here, * denotes convolution. From this model, the pRF model vector p is directly estimated employing the least-square fit. From the estimated vector p, we modeled the different models in the vector p.


Results and Preliminary Conclusions

Our model could estimate reasonable pRF structures based on the assumption of the smoothness in space. In the typical topography, one strong positive peak was observed (Figure 1A), which corresponds to the pRF center since it is located in the most responsive position. From these pRFs (i.e, vector p in each voxel), one Gaussian with a covariance matrix was fit to the pRF (Figure 1B). Through our approach, it was capable of measuring a variety of pRF properties such as surround suppression, receptive field center elongation, orientation, location and size.



1. Engel S.A., Rumelhart D.E., Wandel B.A., Lee A.T., Glover G.H., Chichilnisky E.J., Shadlen M.N. (1994) fMRI of human visual cortex. Nature 369, 525.

2. Dumoulin S.O., Wandell B.A., (2008) Population receptive field estimates in human visual cortex. Neuroimage 39,647-660


Figure 1. Three Exemplars of population receptive field. (A) PRFs structures estimated with the proposed method. (B) PRF center models

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Articles (6):

Papanikolaou A, Keliris GA, Lee S, Logothetis NK and Smirnakis SM (October-2015) Nonlinear population receptive field changes in human area V5/MT + of healthy subjects with simulated visual field scotomas NeuroImage 120 176–190.
Lee S, Papanikolaou A, Keliris GA and Smirnakis SM (February-2015) Topographical estimation of visual population receptive fields by fMRI Journal of Visualized Experiments (96) 1-8.
Lee S, Papanikolaou A, Logothetis NK, Smirnakis SM and Keliris GA (November-2013) A new method for estimating population receptive field topography in visual cortex NeuroImage 81 144–157.
Rana M, Gupta N, Dalboni Da Rocha JL, Lee S and Sitaram R (October-2013) A toolbox for real-time subject-independent and subject-dependent classification of brain Frontiers in Neuroscience 7(170) 1-11.
Caria A, de Falco S, Venuti P, Lee S, Esposito G, Rigo P, Birbaumer N and Bornstein MH (February-2012) Species-specific response to human infant faces in the premotor cortex NeuroImage 60(2) 884–893.
Sitaram R, Lee S, Ruiz S, Rana M, Veit R and Birbaumer N (May-2011) Real-time support vector classification and feedback of multiple emotional brain states NeuroImage 56(2) 753–765.

Contributions to books (1):

Sitaram R, Lee S and Birbaumer N: BCIs That Use Brain Metabolic Signals, 301-314. In: Brain–Computer Interfaces: Principles and Practice, (Ed) J. Wolpaw, Oxford University Press, Oxford, UK, (May-2012).

Posters (2):

Lee AS, Moore MA, Saccomano ZT, Azmitia EC and Whitaker-Azmitia PM (November-16-2016): Increased microglial priming in autism spectrum disorder, an immunocytochemical study in postmortem human temporal cortex, 46th Annual Meeting of the Society for Neuroscience (Neuroscience 2016), San Diego, CA, USA.
Papanikolaou A, Keliris GA, Lee S, Logothetis NK and Smirnakis SM (October-21-2015): Population receptive field changes in hV5/MT+ of healthy subjects with simulated visual field scotomas, 45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015), Chicago, IL, USA.

Talks (2):

Papanikolaou A, Keliris GA, Lee S, Papageorgiou TD, Schiefer U, Logothetis NK and Smirnakis SM (November-19-2014) Abstract Talk: Organization of human area V5/MT+ and sensitivity to motion coherence after lesions of the primary visual cortex, 44th Annual Meeting of the Society for Neuroscience (Neuroscience 2014), Washington, DC, USA 772.07.
Lee S, Keliris GA, Papanikolaou A, Smirnakis SM and Logothetis NK (October-17-2012) Abstract Talk: Visualization of the population receptive field structures in human visual cortex, 42nd Annual Meeting of the Society for Neuroscience (Neuroscience 2012), New Orleans, LA, USA(723.08).

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Last updated: Monday, 22.05.2017