https://insubkim.com Insub Kim Sat, 28 Oct 2023 21:32:14 +0000 https://insubkim.com en https://insubkim.com/Front-page Sun, 25 Sep 2022 09:09:14 +0000 Insub Kim https://insubkim.com/Front-page &nbsp;︎︎︎︎<img width="1280" height="1280" width_o="1280" height_o="1280" data-src="https://freight.cargo.site/t/original/i/db8996db30d99f5c28e4d8c7f323710a91a89640ff86f1b9c21bf3b57ad18ff3/wood.JPG" data-mid="154055163" border="0" data-scale="48" src="https://freight.cargo.site/w/1000/i/db8996db30d99f5c28e4d8c7f323710a91a89640ff86f1b9c21bf3b57ad18ff3/wood.JPG" /> Insub Kim,&nbsp;PhD&nbsp;Stanford University I use machine learning and fMRI methods to investigate human behavior, perception and cognition. My research topics include optimal image generation, perception of space and time, color vision, and emotion processing.Contact me <img width="2818" height="2135" width_o="2818" height_o="2135" data-src="https://freight.cargo.site/t/original/i/6b091ce53f942e769b9fa374c8e0338c257e1538bb052d18b97fb93224b26731/myleftbrain.png" data-mid="154060243" border="0" src="https://freight.cargo.site/w/1000/i/6b091ce53f942e769b9fa374c8e0338c257e1538bb052d18b97fb93224b26731/myleftbrain.png" /> https://insubkim.com/Page-Index Sun, 25 Sep 2022 08:54:21 +0000 Insub Kim https://insubkim.com/Page-Index https://insubkim.com/OpExp Sat, 28 Oct 2023 21:32:14 +0000 Insub Kim https://insubkim.com/OpExp Generating brain-optimized image for advancing research efficiency Stanford University&nbsp; 2024 One of the fundamental goals of neuroscience is to understand how stimulus information is transformed into neuronal responses. To create a computational model that captures this transformation, it is necessary to collect neuronal responses across a diverse range of stimuli. However, due to the extensive range of possible stimuli, it is challenging to only select an optimal set of stimuli that can effectively elicit significant neural modulations. Moreover, there are practical limitations on the number of measurements and the duration of experiments that experimenters can perform at each time. As a result, experimenters rely heavily on their own prior knowledge to elicit the desired neural responses. However, this&nbsp;approach may not always result in an optimal experiment tailored to address their specific research questions. To tackle this problem, I am currently developing a novel software tool that generates an optimal set of stimuli, tailored to the specific hypotheses of each researcher. Specifically, I am leveraging recent advancements in generative deep neural networks, such as GANs and stable diffusion models, to generate stimuli in a manner directly optimized to the brain response itself.&nbsp; The goal is to produce a set of stimuli that would maximize the performance of a brain model, which, in turn, would most effectively modulate underlying neural responses. <img width="3478" height="1356" width_o="3478" height_o="1356" data-src="https://freight.cargo.site/t/original/i/59aaaeb49f5255cc7edf8cf034ca633b108e378b6af27c6f6194056123fb13f9/img1.png" data-mid="203277646" border="0" src="https://freight.cargo.site/w/1000/i/59aaaeb49f5255cc7edf8cf034ca633b108e378b6af27c6f6194056123fb13f9/img1.png" /> Examples of brain optimized images: Images optimized for early visual area (V1)<img width="515" height="268" width_o="515" height_o="268" data-src="https://freight.cargo.site/t/original/i/9e23961b3aeebe5b1adf102b0a7de9d788ebfa6007ee1eb0fa60f43a7310cfbc/early_visual.png" data-mid="195178115" border="0" src="https://freight.cargo.site/w/515/i/9e23961b3aeebe5b1adf102b0a7de9d788ebfa6007ee1eb0fa60f43a7310cfbc/early_visual.png" /> Images optimized for&nbsp;fusiform face area (FFA)<img width="515" height="268" width_o="515" height_o="268" data-src="https://freight.cargo.site/t/original/i/7a41cb9a30477638750c7c3698c7ea884b440dcfa727fe2bb5e7b613c586dcb9/face.png" data-mid="195178112" border="0" src="https://freight.cargo.site/w/515/i/7a41cb9a30477638750c7c3698c7ea884b440dcfa727fe2bb5e7b613c586dcb9/face.png" /> Images optimized for parahippocampal place area (PPA) <img width="515" height="268" width_o="515" height_o="268" data-src="https://freight.cargo.site/t/original/i/d4aaa490228b2184902ba6109e4a2a57b25ea3e76149613128b5cd23e7e6095f/scene.png" data-mid="195178114" border="0" src="https://freight.cargo.site/w/515/i/d4aaa490228b2184902ba6109e4a2a57b25ea3e76149613128b5cd23e7e6095f/scene.png" /> Testing pRF recovery profile with natrualistic images <img width="3313" height="1452" width_o="3313" height_o="1452" data-src="https://freight.cargo.site/t/original/i/8b45bcec81f20120fccc7620040bb7f9f4d21149cc11a6eea47ab42bd7b09f42/img2.png" data-mid="203277650" border="0" src="https://freight.cargo.site/w/1000/i/8b45bcec81f20120fccc7620040bb7f9f4d21149cc11a6eea47ab42bd7b09f42/img2.png" /> https://insubkim.com/spatiotemporal Sun, 25 Sep 2022 09:09:15 +0000 Insub Kim https://insubkim.com/spatiotemporal How does space and time information processed in&nbsp;human brain? Stanford University&nbsp; 2024 Published in Journal of Neurosience 2024&nbsp; (Link) <img width="1686" height="1700" width_o="1686" height_o="1700" data-src="https://freight.cargo.site/t/original/i/f7ee634f8271a3a15953c5cf40b3dc289004e66ee87b1ac0dfef9ecdfbbe9f4b/Screenshot-2024-01-31-at-9.32.27-AM.png" data-mid="203277889" border="0" src="https://freight.cargo.site/w/1000/i/f7ee634f8271a3a15953c5cf40b3dc289004e66ee87b1ac0dfef9ecdfbbe9f4b/Screenshot-2024-01-31-at-9.32.27-AM.png" /> Conference on Cognitive Computational Neuroscience 2022&nbsp; (Link) <img width="16384" height="11719" width_o="16384" height_o="11719" data-src="https://freight.cargo.site/t/original/i/e61083be862da68489cfa246b12b7341d7823cc9c58b23e3cfa4836afb636040/ccn_poster.jpg" data-mid="154042330" border="0" src="https://freight.cargo.site/w/1000/i/e61083be862da68489cfa246b12b7341d7823cc9c58b23e3cfa4836afb636040/ccn_poster.jpg" /> https://insubkim.com/emogan Sun, 25 Sep 2022 09:09:19 +0000 Insub Kim https://insubkim.com/emogan EmoGan: Generating Realistic Emotional Pictures with Matched Visual and Emotional Attributes Stanford University In collaboration with Jinxiao Zhang 2021 In the field of psychology, researchers need to make a specific claim about emotional responses that correspond only to emotional representations while controlling for the low-level visual features across different emotional categories.&nbsp; We created an EmoGAN that generates realitic emotional images while preserving visual and emotional attributes. Architecture of EmoGAN <img width="844" height="343" width_o="844" height_o="343" data-src="https://freight.cargo.site/t/original/i/f6adeaa96733605335931bb8281bf5c62293c643d7bad83b1d657ec01425fbd3/Screen-Shot-2022-09-25-at-5.50.59-PM.png" data-mid="154046410" border="0" src="https://freight.cargo.site/w/844/i/f6adeaa96733605335931bb8281bf5c62293c643d7bad83b1d657ec01425fbd3/Screen-Shot-2022-09-25-at-5.50.59-PM.png" /> GAN model arcitecture. This model consists of an U-Net generator with skipped connections and a two discriminators. One discriminator matched pixel-wise image information while the other discriminator matched emotional sentiment of the image. EmoGAN generates more realistic pictures than the conventional low-level matching model <img width="3680" height="1860" width_o="3680" height_o="1860" data-src="https://freight.cargo.site/t/original/i/6e39648e4774f9daf1a462729a21ff5fa7473efd4747af03d97085db314f0cc3/emgan_result.png" data-mid="154047198" border="0" src="https://freight.cargo.site/w/1000/i/6e39648e4774f9daf1a462729a21ff5fa7473efd4747af03d97085db314f0cc3/emgan_result.png" /> https://insubkim.com/colorvision Sun, 25 Sep 2022 09:09:18 +0000 Insub Kim https://insubkim.com/colorvision There is no color in light. Colors are from biological interpretations of our brain.&nbsp; SungKyunkwan University In collaboration with Steve Shevell and Won Mok Shim 2020 <img width="932" height="511" width_o="932" height_o="511" data-src="https://freight.cargo.site/t/original/i/3c74aeece15d0eba7d39ee216ff891b49aabb12bee83a8800d78b9f917426fa9/Screen-Shot-2022-09-25-at-1.51.08-PM.png" data-mid="154028955" border="0" data-scale="80" src="https://freight.cargo.site/w/932/i/3c74aeece15d0eba7d39ee216ff891b49aabb12bee83a8800d78b9f917426fa9/Screen-Shot-2022-09-25-at-1.51.08-PM.png" /> Our subjective color experience is derived from neural representations of the wavelength composition of light that enters the eyes. Which areas of our brains will have representations of the colors we experience? <img width="1902" height="1237" width_o="1902" height_o="1237" data-src="https://freight.cargo.site/t/original/i/ff9319964e750f0031039e4b52ace24e008f632c2bba29e7266394c8e030b501/color_1.png" data-mid="154045483" border="0" data-scale="62" src="https://freight.cargo.site/w/1000/i/ff9319964e750f0031039e4b52ace24e008f632c2bba29e7266394c8e030b501/color_1.png" /> Interocular switch rivalry. Two different chromatic stimuli were continuously presented to each eye to induce perceptual rivalry so that only one of the two colors was seen at a time. The chromatic stimuli were swapped between the two eyes at a frequency of 4.25 Hz so that identical stimuli were presented to each eye over a given time period. Observers indicated their moment-to-moment perceived colors by continuous button presses. We used chromatic interocular switch rivalry (Christiansen, D’Antona &amp; Shevell, 2017) to dissociate hue perception from retinal stimulation by light stimulus, measuring th neural activities of moment-to-moment subjective color experiences across the human visual system using fMRI. <img width="476" height="302" width_o="476" height_o="302" data-src="https://freight.cargo.site/t/original/i/7dba5be0968780dd490d214191cb5a63e1aab793f886891ce360e10906bf3227/color_2.png" data-mid="154045484" border="0" src="https://freight.cargo.site/w/476/i/7dba5be0968780dd490d214191cb5a63e1aab793f886891ce360e10906bf3227/color_2.png" /> Reconstuction of magenta color expereinces in visual area V1 and V4v.&nbsp;Rivalry: Each eye at a given time receive either magenta and green chromaticities (perception ≠&nbsp; light input). Replay: Each eye recives only magenta&nbsp;chromaticity (perception = light input). Each dot is reconstructed color represntation for on obersver. The magenta colored line is the target color. The solid black line is vector sum of the&nbsp;reconstructed color representations across observers. Using an model based encoding apporach (Brouwer &amp; Heeger, 2009), we found that population-level color-selective responses represented subjective, moment-to-moment color experiences, and the selectivity of these responses for the perceived color became progressively stronger across the cortical visual hierarchy. The reconstructed color responses in V4v, and VO1 closely resembled subjective color experiences, suggesting that the neural representation of color experiences emerges at later stages of cortical visual processing. https://insubkim.com/mri-physics Sun, 25 Sep 2022 09:09:18 +0000 Insub Kim https://insubkim.com/mri-physics 7T MRI and layer-specific imaging&nbsp; National Institue of Health (NIH)In collaboration with Peter Bandettini and Renzo Huber 2019 Recent developments of ultra-high-field fMRI provided an opportunity to investigate neural activities across cortical layers and columns in the human brain. <img width="434" height="285" width_o="434" height_o="285" data-src="https://freight.cargo.site/t/original/i/af5681a357f55fba070132eb5511b3bb2fd233b83cfdc1dabbbd8d7d39f6352f/Screen-Shot-2022-09-25-at-3.04.17-AM.png" data-mid="153997823" border="0" src="https://freight.cargo.site/w/434/i/af5681a357f55fba070132eb5511b3bb2fd233b83cfdc1dabbbd8d7d39f6352f/Screen-Shot-2022-09-25-at-3.04.17-AM.png" /> 7T Siemens MRI machine at NIH Actively shielded, body gradient, sub-mm anatomical (T1,T2) and funcitonal images (EPI) A higher magnetic field usually means higher imaging resolution. Previously, it was almost impossible to measure layer-specific neuronal activities in the living human brain. With the development of 7T MRI and an advanced fMRI imaging sequence (VASO), we can now push the fMRI resolution to be up to 0.8 mm. The thickness of the human visual cortex is usually around 2.5 ~ 3 mm, which means that we can obtain around 3 voxels across cortical depth (0.8 mm * 3 voxels&nbsp; = 2.4 mm)<img width="1003" height="450" width_o="1003" height_o="450" data-src="https://freight.cargo.site/t/original/i/1c58f299b9bf7299a371c0bce0c7f86cb4199d880d3653cfa569bc769d7162a8/Screen-Shot-2022-09-25-at-3.32.03-AM.png" data-mid="153998976" border="0" src="https://freight.cargo.site/w/1000/i/1c58f299b9bf7299a371c0bce0c7f86cb4199d880d3653cfa569bc769d7162a8/Screen-Shot-2022-09-25-at-3.32.03-AM.png" /> Layers provide information about directionality. Investigating relative contributions of each layer give insights into how feedforward and feedback information is processed.Defining V1 Layers <img width="515" height="475" width_o="515" height_o="475" data-src="https://freight.cargo.site/t/original/i/846c2d742fd99ef3f89fc9c6354b201a1b4487590312831d7265c12159b0d280/brain_layers.png" data-mid="154049044" border="0" src="https://freight.cargo.site/w/515/i/846c2d742fd99ef3f89fc9c6354b201a1b4487590312831d7265c12159b0d280/brain_layers.png" /> Manual parcellation of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF)Interpolated to 9 layers using equal Euclidean distances V1 activation profile (Stimulus - Blank) <img width="1024" height="573" width_o="1024" height_o="573" data-src="https://freight.cargo.site/t/original/i/eaa3d9ae5833a4ae025dc5dfba0a56d7d932a8a3bd66d5905e312634f42e69e1/Screen-Shot-2019-03-14-at-5.34.11-PM-1024x573.png" data-mid="153996864" border="0" data-scale="70" src="https://freight.cargo.site/w/1000/i/eaa3d9ae5833a4ae025dc5dfba0a56d7d932a8a3bd66d5905e312634f42e69e1/Screen-Shot-2019-03-14-at-5.34.11-PM-1024x573.png" /><img width="480" height="172" width_o="480" height_o="172" data-src="https://freight.cargo.site/t/original/i/d9be88a144e225e276c2a67e709c10aa2d6cf0ffba7ec02a9b6b8026a3b13f52/BOLD_VASO_flicker.gif" data-mid="153996908" border="0" src="https://freight.cargo.site/w/480/i/d9be88a144e225e276c2a67e709c10aa2d6cf0ffba7ec02a9b6b8026a3b13f52/BOLD_VASO_flicker.gif" /> Distinct layer profiles for two differnt imaging seqeunces: BOLD and VASO. BOLD sequence suffers from a blood drainage problem. BOLD showed a higher signal towards the upper layer, while VASO peaked towards the middle layer. Decoding Orientation across layers <img src="data:image/png;base64, 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"> Support Vector Machine, SVMTop 75 % voxel-selectionChance level: 16.6% <img width="785" height="294" width_o="785" height_o="294" data-src="https://freight.cargo.site/t/original/i/38ce4b509be2f39f469f59a099686bea1ce375a410915a258f2e22352bf8648f/layer-activity.png" data-mid="154049077" border="0" src="https://freight.cargo.site/w/785/i/38ce4b509be2f39f469f59a099686bea1ce375a410915a258f2e22352bf8648f/layer-activity.png" /> BOLD &amp; VASO higher than chance decodability across layers BOLD showed no specific pattern across layers, although a strong feed-forward signal towards the middle and deep layer was expectedOverall, VASO showed higher decodability than BOLD, although BOLD had higher signal change compared to VASO in the time series data.VASO showed layer-specific decoding that corresponds to known feed-forward signals having the highest decodability towards the middle layer, while BOLD did not. https://insubkim.com/face Sun, 25 Sep 2022 09:09:16 +0000 Insub Kim https://insubkim.com/face Emotional face perception McGill Univeristy In collaboration with Aislinn Sandre and Anna Weinberg 2018 <img width="625" height="240" width_o="625" height_o="240" data-src="https://freight.cargo.site/t/original/i/867ef4e8f2197f4e386d940fa449e3d8c62f4b47a30bf25651595bd847c8a10f/emoface.png" data-mid="154045930" border="0" data-scale="100" src="https://freight.cargo.site/w/625/i/867ef4e8f2197f4e386d940fa449e3d8c62f4b47a30bf25651595bd847c8a10f/emoface.png" /> <img width="864" height="213" width_o="864" height_o="213" data-src="https://freight.cargo.site/t/original/i/fe351309d463fe8639612ddca1bd4ddee6d193873bcc850f17c849395f57e195/faces_1.jpg" data-mid="154045837" border="0" src="https://freight.cargo.site/w/864/i/fe351309d463fe8639612ddca1bd4ddee6d193873bcc850f17c849395f57e195/faces_1.jpg" />NimStim dataset for facial expressions https://insubkim.com/ml Sun, 25 Sep 2022 09:09:19 +0000 Insub Kim https://insubkim.com/ml Machine Learning Programming Languages: Python, Matlab, R, Java, C, HTML, CSS, Bash I conduct research using:Generative AI (GAN, Stable-Diffusion) Deep Learning (CNN and RNN) Signal processing methodsImage-computable algorithmsBayesian optimizationPCA, SVD, SVM Statistical testing&nbsp;Hypothesis testingSimulation (sampling distributions, p-value, confidence interval, bootsrapping)Linear models (GLM, regression, ANOVA, linear-mixed-effects model)Model Comparison (AIC, BIC)Power analysis Teaching ExperiencePerception (PSYCH30, Stanford)&nbsp;Statistics&nbsp;(STATS60, Stanford)MRI physics (PSYCH204, Stanford) <img width="1092" height="737" width_o="1092" height_o="737" data-src="https://freight.cargo.site/t/original/i/15cccc54b4f9b140414929002275665e05c04e1c5d1e2e053023c3ba5d85b52b/Retino_gif.gif" data-mid="154060953" border="0" src="https://freight.cargo.site/w/1000/i/15cccc54b4f9b140414929002275665e05c04e1c5d1e2e053023c3ba5d85b52b/Retino_gif.gif" /> <img width="3024" height="3024" width_o="3024" height_o="3024" data-src="https://freight.cargo.site/t/original/i/8b420efed192bb0a2835bccd85a3f7ddb44bdbdb668b59f71babd3ea4c6dd301/20191031_184547.jpg" data-mid="154060952" border="0" src="https://freight.cargo.site/w/1000/i/8b420efed192bb0a2835bccd85a3f7ddb44bdbdb668b59f71babd3ea4c6dd301/20191031_184547.jpg" /> <img width="948" height="401" width_o="948" height_o="401" data-src="https://freight.cargo.site/t/original/i/a815cfd9f7972edfd0c5113b20e65e86656a422f35a316db12d39d8193791297/Screen-Shot-2022-09-26-at-2.29.11-PM.png" data-mid="154133754" border="0" src="https://freight.cargo.site/w/948/i/a815cfd9f7972edfd0c5113b20e65e86656a422f35a316db12d39d8193791297/Screen-Shot-2022-09-26-at-2.29.11-PM.png" /> https://insubkim.com/art Mon, 26 Sep 2022 04:46:23 +0000 Insub Kim https://insubkim.com/art Trust your intuition - coldie <img width="500" height="333" width_o="500" height_o="333" data-src="https://freight.cargo.site/t/original/i/078731e87316ec52154d5df8c4ac9ce90aa18d2d478abe8cf9200cf063f99b46/coldie_AdobeExpress.gif" data-mid="154058150" border="0" src="https://freight.cargo.site/w/500/i/078731e87316ec52154d5df8c4ac9ce90aa18d2d478abe8cf9200cf063f99b46/coldie_AdobeExpress.gif" />Multiple depths cues can be found in the above artwork. Overlapping. Objects that occlude the other one is percived to be closer.Linear perspective. Objects farther away look smaller while closer objects look bigger.Shades and shadows. Objects closer from the light source appear brighter. The shading can be used to infer depth relationships between objects.Atmospheric Attenuation. Farther away objects appear to be hazy and less sharp.Motion Parallax. Objects near to the observer move faster than objects farther away. Colorful Hermmann grid illusion [2018] <img width="2149" height="1879" width_o="2149" height_o="1879" data-src="https://freight.cargo.site/t/original/i/7808c1c09a42d6ad19a8d55a5f15f9780591ff5919840db44a7c6e42783d97ad/colorful-herman.png" data-mid="154059947" border="0" data-scale="60" src="https://freight.cargo.site/w/1000/i/7808c1c09a42d6ad19a8d55a5f15f9780591ff5919840db44a7c6e42783d97ad/colorful-herman.png" /> I created a colorful version of hermann grid illusion. Colors were chosen from an isoluminance plane of the DKL colorspace. Gray dots appear at the intersection points of the white grid lines. Gray dots only appear when you look away! If you try to fixate to a specific gray dot, it will disappear. Scintillating Grid illusion <img width="728" height="452" width_o="728" height_o="452" data-src="https://freight.cargo.site/t/original/i/c8500dadb5852ac6d80464692a23d97c293e6a49a74cc3f4a7a8d8cb51144887/scintillatingrid.png" data-mid="154058149" border="0" src="https://freight.cargo.site/w/728/i/c8500dadb5852ac6d80464692a23d97c293e6a49a74cc3f4a7a8d8cb51144887/scintillatingrid.png" />Dots out side of foveal vision appear to be fashing black and white. If you fixate your eye movement, dots appear to be constant white.