ETRI
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Observing Individual Atoms in 3D Nanomaterials and Their Surfaces
Atoms are the basic building blocks for all materials. To tailor functional properties, it is essential to accurately determine their atomic structures. KAIST researchers observed the 3D atomic structure of a nanoparticle at the atom level via neural network-assisted atomic electron tomography.
Using a platinum nanoparticle as a model system, a research team led by Professor Yongsoo Yang demonstrated that an atomicity-based deep learning approach can reliably identify the 3D surface atomic structure with a precision of 15 picometers (only about 1/3 of a hydrogen atom’s radius). The atomic displacement, strain, and facet analysis revealed that the surface atomic structure and strain are related to both the shape of the nanoparticle and the particle-substrate interface.
Combined with quantum mechanical calculations such as density functional theory, the ability to precisely identify surface atomic structure will serve as a powerful key for understanding catalytic performance and oxidation effect.
“We solved the problem of determining the 3D surface atomic structure of nanomaterials in a reliable manner. It has been difficult to accurately measure the surface atomic structures due to the ‘missing wedge problem’ in electron tomography, which arises from geometrical limitations, allowing only part of a full tomographic angular range to be measured. We resolved the problem using a deep learning-based approach,” explained Professor Yang.
The missing wedge problem results in elongation and ringing artifacts, negatively affecting the accuracy of the atomic structure determined from the tomogram, especially for identifying the surface structures. The missing wedge problem has been the main roadblock for the precise determination of the 3D surface atomic structures of nanomaterials.
The team used atomic electron tomography (AET), which is basically a very high-resolution CT scan for nanomaterials using transmission electron microscopes. AET allows individual atom level 3D atomic structural determination.
“The main idea behind this deep learning-based approach is atomicity—the fact that all matter is composed of atoms. This means that true atomic resolution electron tomogram should only contain sharp 3D atomic potentials convolved with the electron beam profile,” said Professor Yang.
“A deep neural network can be trained using simulated tomograms that suffer from missing wedges as inputs, and the ground truth 3D atomic volumes as targets. The trained deep learning network effectively augments the imperfect tomograms and removes the artifacts resulting from the missing wedge problem.”
The precision of 3D atomic structure can be enhanced by nearly 70% by applying the deep learning-based augmentation. The accuracy of surface atom identification was also significantly improved.
Structure-property relationships of functional nanomaterials, especially the ones that strongly depend on the surface structures, such as catalytic properties for fuel-cell applications, can now be revealed at one of the most fundamental scales: the atomic scale.
Professor Yang concluded, “We would like to fully map out the 3D atomic structure with higher precision and better elemental specificity. And not being limited to atomic structures, we aim to measure the physical, chemical, and functional properties of nanomaterials at the 3D atomic scale by further advancing electron tomography techniques.”
This research, reported at Nature Communications, was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research M3I3 Project.
-Publication
Juhyeok Lee, Chaehwa Jeong & Yongsoo Yang
“Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography”
Nature Communications
-Profile
Professor Yongsoo Yang
Department of Physics
Multi-Dimensional Atomic Imaging Lab (MDAIL)
http://mdail.kaist.ac.kr
KAIST
2021.05.12 View 11927 -
COVID-Update: KAIST on High Alert amid Spring Resurgence
COVID-19 Task Force responds 24-7 and ISSS provides returning international students with a comfort package during 14-day mandatory quarantine
In response to the upsurge of COVID-19 cases in the proximate college districts in Daejeon, KAIST announced the enforcement of stricter health and safety regulations. Korean health authorities expected another surge of COVID-19 cases this spring as Korea’s daily new COVID-19 cases have rebounded to the high 600s and over 700 in April, which is the most in over three months.
New guidelines issued on April 5 banned faculty, staff, and students from engaging in off-campus activities and utilizing external public facilities. Such facilities include, but are not limited to, bars, cafes, clubs, gyms, karaoke rooms, PC rooms, restaurants, and other crowded indoor spaces. All class and research activities, work meetings, and school events were moved exclusively online, and working from home and flexible working hours were highly encouraged in order to minimize face-to-face interactions on campus. In particular, having meals outside of KAIST cafeterias in groups of two or more was prohibited, while food delivery and take-outs were allowed.
Executive Vice President and Provost Seung Seob Lee said in a letter to the KAIST community on April 5 that “the school considers the risk of the current situation to be very high, likely the highest since the outbreak of COVID-19.” Provost Lee then called for more team efforts to contain the current phase of the pandemic and asked everyone to do their part.
The school installed new temperature scanners equipped with hand sanitizer dispensers in front of the dormitory entrances to further control the spread of the disease on campus, following confirmed COVID-19 cases among dormitory residents.
As the COVID-19 pandemic continues with no clear end in sight, the Task Force for the Prevention of COVID-19 and the International Scholar and Student Services (ISSS) Team at KAIST are working around the clock to reduce the risk of infection spread not only within the campus, but also coming from outside the campus.
Under strict health and safety guidelines, KAIST has allowed international students to come back to campus. Currently about 600 international students, mostly graduate students reside on campus. All returning students should complete the mandatory 14-day self-quarantine required by the Korean government at their own expense.
The KAIST COVID-19 Task Force is in charge of enacting on-campus health and safety guidelines, responding to reports and inquiries from the KAIST community 24-7, and controlling outsider access, among other responsibilities.
The ISSS Team requires returning international students to fill out an entry authorization form and receive approval from the KAIST COVID-19 Task Force prior to returning to campus from their home countries. Once students arrive at their designated quarantine facility, the KAIST ISSS Team sends care packages, which includes some toiletries, instant food, a multipot, a thermometer, and other daily necessities. During the quarantine period, returning students are also advised to follow the directions given by government officials and to coordinate with the ISSS Team. The team also provides useful Korean phrases for international students to help them with communication.
The self-quarantine period ends at 12 p.m. 14 days after arrival. Within two days of finishing the 14 days of self-isolation, these students are required to undergo a polymerase chain reaction (PCR) test for COVID-19 at the nearest health center. After confirmed negative, they are allowed to move into on-campus accommodations. KAIST will maintain the current method of remote education and distancing methods until further notice.
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2021.04.16 View 10091 -
EPO: KAIST the 7th Leading Innovation Cluster Globally
A study published by the European Patent Office (EPO) shows that Korea is the second leading hub for technologies related to the Fourth Industrial Revolution. According to the study, Korea has the second highest innovation intensity for the Fourth Industrial Revolution worldwide with 526 international patent families (IPFs) per million inhabitants, after Finland (654) and well ahead of Japan (405) and the US (258). Korea specializes in IT hardware, power supply, smart goods and services.
The study also reported that the contribution of universities and public research organizations in Korea is very high, standing at 12% compared to the world average of 5.6%. Among others, ETRI (Electronics and Telecommunications Research Institute) topped the universities and public research organizations globally with filings of over 1,500 IPFs between 2010 and 2018. KAIST ranks the 7th with filings of 185, ahead of MIT (179).
The EPO released its study titled 'Patents and the Fourth Industrial Revolution: the Global Technology Trends Enabling the Data-Driven Economy' on December 10. It analyzed all IPFs related to the Fourth Industrial Revolution worldwide between 2000 and 2018. The study found that nearly 40,000 new IPFs were filed for these technologies in 2018 alone. This means they accounted for more than 10% of all patenting activity worldwide that year.
The analysis also showed that Seoul was the world’s most important cluster for Fourth Industrial Revolution patenting activity, accounting for almost 10% of all patents in this field worldwide, growing by 22.7% on average per year between 2010 and 2018, the third highest growth rate of the top 20 clusters. The cluster represented 86% of all Fourth Industrial Revolution patenting activities in Korea. Samsung and LG had a combined share of two-thirds of the cluster’s patent filings, while another 15% was contributed by ETRI.
In the industry sector, Samsung was the clear global leader with over 12,000 IPFs, which corresponds to 4.6% of all Fourth Industrial Revolution inventions between 2000 and 2018. Samsung is followed, albeit by a wide gap of almost 6,000 IPFs filed, by Sony (6,401), and the second Korean company, LG, in third place (6,290).
The patent analysis in this report is based on IPFs. Each IPF represents a unique invention and includes patent applications filed and published in at least two countries or filed with and published by a regional patent office, as well as published international patent applications. The EPO, headquartered in Munich, Germany, is one of the largest patent offices in the world and the leading authority on patent information and searching.
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2020.12.11 View 6237 -
Three Professors Named to Highly Cited Researchers 2020 List
Distinguished Professor Sukbok Chang from the Department of Chemistry, Distinguished Professor Sang-Yup Lee from the Department of Chemical & Biomolecular Engineering, and Professor Jiyong Eom from the College of Business were named to Clarivate’s Highly Cited Researchers 2020 list.
Clarivate announced the researchers who rank in the top 1% of citations by field and publication year in the Web of Science citation index. A total of 6,167 researchers from more than 60 countries were listed this year and 37 Korean scholars made the list.
The methodology that determines the “Who’s Who” of influential researchers draws on data and analyses performed by bibliometric experts and data scientists at the Institute for Scientific Information at Clarivate. It also uses the tallies to identify the countries and research institutions where these scientific elite are based. More than 6,000 researchers from 21 fields in the sciences, social sciences, and cross field categories were selected based on the number of highly cited papers they produced over an 11-year period from January 2009 to December 2019.
Professor Chang made the list six years in a row, while Professor Lee made it for four consecutive years, and Professor Eom for the last two years. Professor Chang’s group (http://sbchang.kaist.ac.kr) investigates catalytic hydrocarbon functionalization. Professor Lee (http://mbel.kaist.ac.kr) is a pioneering scholar in the field of metabolic engineering, systems, and synthetic biology. Professor Eom’s (https://kaistceps.quv.kr) research extends to energy and environmental economics and management, energy big data, and green information systems.
2020.11.30 View 9569 -
Scientist of October: Professor Jungwon Kim
Professor Jungwon Kim from the Department of Mechanical Engineering was selected as the ‘Scientist of the Month’ for October 2020 by the Ministry of Science and ICT and the National Research Foundation of Korea. Professor Kim was recognized for his contributions to expanding the horizons of the basics of precision engineering through his research on multifunctional ultrahigh-speed, high-resolution sensors. He received 10 million KRW in prize money.
Professor Kim was selected as the recipient of this award in celebration of “Measurement Day”, which commemorates October 26 as the day in which King Sejong the Great established a volume measurement system.
Professor Kim discovered that the time difference between the pulse of light created by a laser and the pulse of the current produced by a light-emitting diode was as small as 100 attoseconds (10-16 seconds). He then developed a unique multifunctional ultrahigh-speed, high-resolution Time-of-Flight (TOF) sensor that could take measurements of multiple points at the same time by sampling electric light. The sensor, with a measurement speed of 100 megahertz (100 million vibrations per second), a resolution of 180 picometers (1/5.5 billion meters), and a dynamic range of 150 decibels, overcame the limitations of both existing TOF techniques and laser interferometric techniques at the same time. The results of this research were published in Nature Photonics on February 10, 2020.
Professor Kim said, “I’d like to thank the graduate students who worked passionately with me, and KAIST for providing an environment in which I could fully focus on research. I am looking forward to the new and diverse applications in the field of machine manufacturing, such as studying the dynamic phenomena in microdevices, or taking ultraprecision measurement of shapes for advanced manufacturing.”
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2020.10.15 View 11789 -
Deep Learning-Based Cough Recognition Model Helps Detect the Location of Coughing Sounds in Real Time
The Center for Noise and Vibration Control at KAIST announced that their coughing detection camera recognizes where coughing happens, visualizing the locations. The resulting cough recognition camera can track and record information about the person who coughed, their location, and the number of coughs on a real-time basis.
Professor Yong-Hwa Park from the Department of Mechanical Engineering developed a deep learning-based cough recognition model to classify a coughing sound in real time. The coughing event classification model is combined with a sound camera that visualizes their locations in public places. The research team said they achieved a best test accuracy of 87.4 %.
Professor Park said that it will be useful medical equipment during epidemics in public places such as schools, offices, and restaurants, and to constantly monitor patients’ conditions in a hospital room.
Fever and coughing are the most relevant respiratory disease symptoms, among which fever can be recognized remotely using thermal cameras. This new technology is expected to be very helpful for detecting epidemic transmissions in a non-contact way. The cough event classification model is combined with a sound camera that visualizes the cough event and indicates the location in the video image.
To develop a cough recognition model, a supervised learning was conducted with a convolutional neural network (CNN). The model performs binary classification with an input of a one-second sound profile feature, generating output to be either a cough event or something else.
In the training and evaluation, various datasets were collected from Audioset, DEMAND, ETSI, and TIMIT. Coughing and others sounds were extracted from Audioset, and the rest of the datasets were used as background noises for data augmentation so that this model could be generalized for various background noises in public places.
The dataset was augmented by mixing coughing sounds and other sounds from Audioset and background noises with the ratio of 0.15 to 0.75, then the overall volume was adjusted to 0.25 to 1.0 times to generalize the model for various distances.
The training and evaluation datasets were constructed by dividing the augmented dataset by 9:1, and the test dataset was recorded separately in a real office environment.
In the optimization procedure of the network model, training was conducted with various combinations of five acoustic features including spectrogram, Mel-scaled spectrogram and Mel-frequency cepstrum coefficients with seven optimizers. The performance of each combination was compared with the test dataset. The best test accuracy of 87.4% was achieved with Mel-scaled Spectrogram as the acoustic feature and ASGD as the optimizer.
The trained cough recognition model was combined with a sound camera. The sound camera is composed of a microphone array and a camera module. A beamforming process is applied to a collected set of acoustic data to find out the direction of incoming sound source. The integrated cough recognition model determines whether the sound is cough or not. If it is, the location of cough is visualized as a contour image with a ‘cough’ label at the location of the coughing sound source in a video image.
A pilot test of the cough recognition camera in an office environment shows that it successfully distinguishes cough events and other events even in a noisy environment. In addition, it can track the location of the person who coughed and count the number of coughs in real time. The performance will be improved further with additional training data obtained from other real environments such as hospitals and classrooms.
Professor Park said, “In a pandemic situation like we are experiencing with COVID-19, a cough detection camera can contribute to the prevention and early detection of epidemics in public places. Especially when applied to a hospital room, the patient's condition can be tracked 24 hours a day and support more accurate diagnoses while reducing the effort of the medical staff."
This study was conducted in collaboration with SM Instruments Inc.
Profile: Yong-Hwa Park, Ph.D.
Associate Professor
yhpark@kaist.ac.kr
http://human.kaist.ac.kr/
Human-Machine Interaction Laboratory (HuMaN Lab.)
Department of Mechanical Engineering (ME)
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.kr/en/
Daejeon 34141, Korea
Profile: Gyeong Tae Lee
PhD Candidate
hansaram@kaist.ac.kr
HuMaN Lab., ME, KAIST
Profile: Seong Hu Kim
PhD Candidate
tjdgnkim@kaist.ac.kr
HuMaN Lab., ME, KAIST
Profile: Hyeonuk Nam
PhD Candidate
frednam@kaist.ac.kr
HuMaN Lab., ME, KAIST
Profile: Young-Key Kim
CEO
sales@smins.co.kr
http://en.smins.co.kr/
SM Instruments Inc.
Daejeon 34109, Korea
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2020.08.13 View 16281 -
Energy Storage Using Oxygen to Boost Battery Performance
Researchers have presented a novel electrode material for advanced energy storage device that is directly charged with oxygen from the air. Professor Jeung Ku Kang’s team synthesized and preserved the sub-nanometric particles of atomic cluster sizes at high mass loadings within metal-organic frameworks (MOF) by controlling the behavior of reactants at the molecular level. This new strategy ensures high performance for lithium-oxygen batteries, acclaimed as a next-generation energy storage technology and widely used in electric vehicles.
Lithium-oxygen batteries in principle can generate ten times higher energy densities than conventional lithium-ion batteries, but they suffer from very poor cyclability. One of the methods to improve cycle stability is to reduce the overpotential of electrocatalysts in cathode electrodes. When the size of an electrocatalyst material is reduced to the atomic level, the increased surface energy leads to increased activity while significantly accelerating the material’s agglomeration.
As a solution to this challenge, Professor Kang from the Department of Materials Science and Engineering aimed to maintain the improved activity by stabilizing atomic-scale sized electrocatalysts into the sub-nanometric spaces. This is a novel strategy for simultaneously producing and stabilizing atomic-level electrocatalysts within metal-organic frameworks (MOFs).
Metal-organic frameworks continuously assemble metal ions and organic linkers.
The team controlled hydrogen affinities between water molecules to separate them and transfer the isolated water molecules one by one through the sub-nanometric pores of MOFs. The transferred water molecules reacted with cobalt ions to form di-nuclear cobalt hydroxide under precisely controlled synthetic conditions, then the atomic-level cobalt hydroxide is stabilized inside the sub-nanometric pores.
The di-nuclear cobalt hydroxide that is stabilized in the sub-nanometric pores of metal-organic frameworks (MOFs) reduced the overpotential by 63.9% and showed ten-fold improvements in the life cycle.
Professor Kang said, “Simultaneously generating and stabilizing atomic-level electrocatalysts within MOFs can diversify materials according to numerous combinations of metal and organic linkers. It can expand not only the development of electrocatalysts, but also various research fields such as photocatalysts, medicine, the environment, and petrochemicals.”
This study was reported in Advanced Science (Title: Autogenous Production and Stabilization of Highly Loaded Sub-Nanometric Particles within Multishell Hollow Metal-Organic Frameworks and Their Utilization for High Performance in Li-O2 Batteries).
This research was mainly supported by the Global Frontier R&D Program of the Ministry of Science, ICT & Planning (Grant No. 2013M3A6B1078884) funded by the Ministry of Science, ICT & Future Planning, and the National Research Foundation of Korea (Grant No. 2019M3E6A1104196).
Profile:Professor Jeung Ku Kang
jeungku@kaist.ac.kr
http://nanosf.kaist.ac.kr/
Nano Materials Simulation and Fabrication Laboratory
Department of Materials Science and Engineering
KAIST
2020.06.15 View 12967 -
A Deep-Learned E-Skin Decodes Complex Human Motion
A deep-learning powered single-strained electronic skin sensor can capture human motion from a distance. The single strain sensor placed on the wrist decodes complex five-finger motions in real time with a virtual 3D hand that mirrors the original motions. The deep neural network boosted by rapid situation learning (RSL) ensures stable operation regardless of its position on the surface of the skin.
Conventional approaches require many sensor networks that cover the entire curvilinear surfaces of the target area. Unlike conventional wafer-based fabrication, this laser fabrication provides a new sensing paradigm for motion tracking.
The research team, led by Professor Sungho Jo from the School of Computing, collaborated with Professor Seunghwan Ko from Seoul National University to design this new measuring system that extracts signals corresponding to multiple finger motions by generating cracks in metal nanoparticle films using laser technology. The sensor patch was then attached to a user’s wrist to detect the movement of the fingers.
The concept of this research started from the idea that pinpointing a single area would be more efficient for identifying movements than affixing sensors to every joint and muscle. To make this targeting strategy work, it needs to accurately capture the signals from different areas at the point where they all converge, and then decoupling the information entangled in the converged signals. To maximize users’ usability and mobility, the research team used a single-channeled sensor to generate the signals corresponding to complex hand motions.
The rapid situation learning (RSL) system collects data from arbitrary parts on the wrist and automatically trains the model in a real-time demonstration with a virtual 3D hand that mirrors the original motions. To enhance the sensitivity of the sensor, researchers used laser-induced nanoscale cracking.
This sensory system can track the motion of the entire body with a small sensory network and facilitate the indirect remote measurement of human motions, which is applicable for wearable VR/AR systems.
The research team said they focused on two tasks while developing the sensor. First, they analyzed the sensor signal patterns into a latent space encapsulating temporal sensor behavior and then they mapped the latent vectors to finger motion metric spaces.
Professor Jo said, “Our system is expandable to other body parts. We already confirmed that the sensor is also capable of extracting gait motions from a pelvis. This technology is expected to provide a turning point in health-monitoring, motion tracking, and soft robotics.”
This study was featured in Nature Communications.
Publication:
Kim, K. K., et al. (2020) A deep-learned skin sensor decoding the epicentral human motions. Nature Communications. 11. 2149. https://doi.org/10.1038/s41467-020-16040-y29
Link to download the full-text paper:
https://www.nature.com/articles/s41467-020-16040-y.pdf
Profile: Professor Sungho Jo
shjo@kaist.ac.kr
http://nmail.kaist.ac.kr
Neuro-Machine Augmented Intelligence Lab
School of Computing
College of Engineering
KAIST
2020.06.10 View 12530 -
Professor Sukyung Park Named Presidential Science and Technology Adviser
Professor Sukyung Park from the Department of Mechanical Engineering was appointed as the science and technology adviser to the President Jae-in Moon on May 4. Professor Park, at the age of 47, became the youngest member of the president’s senior aide team at Chong Wa Dae.
A Chong Wa Dae spokesman said on May 4 while announcing the appointment, “Professor Park, a talent with a great deal of policymaking participation in science and technology, will contribute to accelerating the government’s push for science and technology innovation, especially in the information and communications technology (ICT) sector.”
Professor Park joined KAIST in 2004 as the first female professor of mechanical engineering. She is a biomechanics expert who has conducted extensive research on biometric mechanical behaviors. Professor Park is also a member of the KAIST Board of Trustees. Before that, she served as a senior researcher at the Korea Institute of Machinery and Materials (KIMM) as well as a member of the Presidential Advisory Council on Science and Technology.
After graduating from Seoul Science High School as the first ever two-year graduate, Professor Park earned a bachelor and master’s degrees in mechanical engineering at KAIST. She then finished her Ph.D. from the University of Michigan.
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2020.05.06 View 13484 -
A Global Campaign of ‘Facts before Rumors’ on COVID-19 Launched
- A KAIST data scientist group responds to facts and rumors on COVID-19 for global awareness of the pandemic. -
Like the novel coronavirus, rumors have no borders. The world is fighting to contain the pandemic, but we also have to deal with the appalling spread of an infodemic that is as contagious as the virus. This infodemic, a pandemic of false information, is bringing chaos and extreme fear to the general public.
Professor Meeyoung Cha’s group at the School of Computing started a global campaign called ‘Facts before Rumors,’ to prevent the spread of false information from crossing borders. She explained, “We saw many rumors that had already been fact-checked long before in China and South Korea now begin to circulate in other countries, sometimes leading to detrimental results. We launched an official campaign, Facts before Rumors, to deliver COVID-19-related facts to countries where the number of cases is now increasing.” She released the first set of facts on March 26 via her Twitter account @nekozzang.
Professor Cha, a data scientist who has focused on detecting global fake news, is now part of the COVID-19 AI Task Force at the Global Strategy Institute at KAIST. She is also leading the Data Science Group at the Institute for Basic Science (IBS) as Chief Investigator.
Her research group worked in collaboration with the College of Nursing at Ewha Woman’s University to identify 15 claims about COVID-19 that circulated on social networks (SNS) and among the general public. The team fact-checked these claims based on information from the WHO and CDCs of Korea and the US. The research group is now working on translating the list of claims into Portuguese, Spanish, Persian, Chinese, Amharic, Hindi, and Vietnamese. Delivering facts before rumors, the team says, will help contain the disease and prevent any harm caused by misinformation.
The pandemic, which spread in China and South Korea before arriving in Europe and the US, is now moving into South America, Africa, and Southeast Asia. “We would like to play a part in preventing the further spread of the disease with the provision of only scientifically vetted, truthful facts,” said the team.
For this campaign, Professor Cha’s team investigated more than 200 rumored claims on COVID-19 in China during the early days of the pandemic. These claims spread in different levels: while some were only relevant locally or in larger regions of China, others propagated in Asia and are now spreading to countries that are currently most affected by the disease.
For example, the false claim which publicized that ‘Fireworks can help tame the virus in the air’ only spread in China. Other claims such as ‘Eating garlic helps people overcome the disease’ or ‘Gargling with salt water prevents the contraction of the disease,’ spread around the world even after being proved groundless.
The team noted, however, that the times at which these claims propagate are different from one country to another. “This opens up an opportunity to debunk rumors in some countries, even before they start to emerge,” said Professor Cha.
Kun-Woo Kim, a master’s candidate in the Department of Industrial Design who joined this campaign and designed the Facts before Rumors chart also expressed his hope that this campaign will help reduce the number of victims. He added, “I am very grateful to our scientists who quickly responded to the Fact Check in these challenging times.”
2020.03.27 View 12620 -
A Single Biological Factor Predicts Distinct Cortical Organizations across Mammalian Species
-A KAIST team’s mathematical sampling model shows that retino-cortical mapping is a prime determinant in the topography of cortical organization.-
Researchers have explained how visual cortexes develop uniquely across the brains of different mammalian species. A KAIST research team led by Professor Se-Bum Paik from the Department of Bio and Brain Engineering has identified a single biological factor, the retino-cortical mapping ratio, that predicts distinct cortical organizations across mammalian species.
This new finding has resolved a long-standing puzzle in understanding visual neuroscience regarding the origin of functional architectures in the visual cortex. The study published in Cell Reports on March 10 demonstrates that the evolutionary variation of biological parameters may induce the development of distinct functional circuits in the visual cortex, even without species-specific developmental mechanisms.
In the primary visual cortex (V1) of mammals, neural tuning to visual stimulus orientation is organized into one of two distinct topographic patterns across species. While primates have columnar orientation maps, a salt-and-pepper type organization is observed in rodents.
For decades, this sharp contrast between cortical organizations has spawned fundamental questions about the origin of functional architectures in the V1. However, it remained unknown whether these patterns reflect disparate developmental mechanisms across mammalian taxa, or simply originate from variations in biological parameters under a universal development process.
To identify a determinant predicting distinct cortical organizations, Professor Paik and his researchers Jaeson Jang and Min Song examined the exact condition that generates columnar and salt-and-pepper organizations, respectively. Next, they applied a mathematical model to investigate how the topographic information of the underlying retinal mosaics pattern could be differently mapped onto a cortical space, depending on the mapping condition.
The research team proved that the retino-cortical feedforwarding mapping ratio appeared to be correlated to the cortical organization of each species. In the model simulations, the team found that distinct cortical circuitries can arise from different V1 areas and retinal ganglion cell (RGC) mosaic sizes. The team’s mathematical sampling model shows that retino-cortical mapping is a prime determinant in the topography of cortical organization, and this prediction was confirmed by neural parameter analysis of the data from eight phylogenetically distinct mammalian species.
Furthermore, the researchers proved that the Nyquist sampling theorem explains this parametric division of cortical organization with high accuracy. They showed that a mathematical model predicts that the organization of cortical orientation tuning makes a sharp transition around the Nyquist sampling frequency, explaining why cortical organizations can be observed in either columnar or salt-and-pepper organizations, but not in intermediates between these two stages.
Professor Paik said, “Our findings make a significant impact for understanding the origin of functional architectures in the visual cortex of the brain, and will provide a broad conceptual advancement as well as advanced insights into the mechanism underlying neural development in evolutionarily divergent species.”
He continued, “We believe that our findings will be of great interest to scientists working in a wide range of fields such as neuroscience, vision science, and developmental biology.”
This work was supported by the National Research Foundation of Korea (NRF).
Image credit: Professor Se-Bum Paik, KAIST
Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of news coverage of this paper only.
Publication:
Jaeson Jang, Min Song, and Se-Bum Paik. (2020). Retino-cortical mapping ratio predicts columnar and salt-and-pepper organization in mammalian visual cortex. Cell Reports. Volume 30. Issue 10. pp. 3270-3279. Available online at https://doi.org/10.1016/j.celrep.2020.02.038
Profile:
Se-Bum Paik
Assistant Professor
sbpaik@kaist.ac.kr
http://vs.kaist.ac.kr/
VSNN Laboratory
Department of Bio and Brain Engineering
Program of Brain and Cognitive Engineering
http://kaist.ac.kr
Korea Advanced Institute of Science and Technology (KAIST)
Daejeon, Republic of Korea
Profile:
Jaeson Jang
Ph.D. Candidate
jaesonjang@kaist.ac.kr
Department of Bio and Brain Engineering, KAIST
Profile:
Min Song
Ph.D. Candidate
night@kaist.ac.kr
Program of Brain and Cognitive Engineering, KAIST
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2020.03.11 View 14007 -
Stress-Relief Substrate Helps OLED Stretch Two-Dimensionally
Highly functional and free-form displays are critical components to complete the technological prowess of wearable electronics, robotics, and human-machine interfaces.
A KAIST team created stretchable OLEDs (Organic Light-Emitting Diodes) that are compliant and maintain their performance under high-strain deformation. Their stress-relief substrates have a unique structure and utilize pillar arrays to reduce the stress on the active areas of devices when strain is applied.
Traditional intrinsically stretchable OLEDs have commercial limitations due to their low efficiency in the electrical conductivity of the electrodes. In addition, previous geometrically stretchable OLEDs laminated to the elastic substrates with thin film devices lead to different pixel emissions of the devices from different peak sizes of the buckles.
To solve these problems, a research team led by Professor Kyung Cheol Choi designed a stretchable substrate system with surface relief island structures that relieve the stress at the locations of bridges in the devices. Their stretchable OLED devices contained an elastic substrate structure comprising bonded elastic pillars and bridges. A patterned upper substrate with bridges makes the rigid substrate stretchable, while the pillars decentralize the stress on the device.
Although various applications using micropillar arrays have been reported, it has not yet been reported how elastic pillar arrays can affect substrates by relieving the stress applied to those substrates upon stretching. Compared to results using similar layouts with conventional free-standing, flat substrates or island structures, their results with elastic pillar arrays show relatively low stress levels at both the bridges and plates when stretching the devices. They achieved stretchable RGB (red, green, blue) OLEDs and had no difficulties with material selection as practical processes were conducted with stress-relief substrates.
Their stretchable OLEDs were mechanically stable and have two-dimensional stretchability, which is superior to only one-direction stretchable electronics, opening the way for practical applications like wearable electronics and health monitoring systems.
Professor Choi said, “Our substrate design will impart flexibility into electronics technology development including semiconductor and circuit technologies. We look forward this new stretchable OLED lowering the barrier for entering the stretchable display market.”
This research was published in Nano Letters titled Two-Dimensionally Stretchable Organic Light-Emitting Diode with Elastic Pillar Arrays for Stress Relief. (https://dx.doi.org/10.1021/acs.nanolett.9b03657). This work was supported by the Engineering Research Center of Excellence Program supported by the National Research Foundation of Korea.
-Profile
Professor Kyung Cheol Choi
kyungcc@kaist.ac.kr
http://adnc.kaist.ac.kr/
School of Electrical Engineering
KAIST
2020.02.27 View 9398