Seongtak Kang

Daegu Gyeongbuk Institute of Science and Technology

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Ji‐Woong Choi

Seoul National University

Jong‐Cheol Rah

Daegu Gyeongbuk Institute of Science and Technology

Yong‐Seok Oh

Korea Brain Research Institute

Samhwan Kim

Daegu Gyeongbuk Institute of Science and Technology

Jeongrak Park

Daegu Gyeongbuk Institute of Science and Technology

Kyung‐In Jang

Daegu Gyeongbuk Institute of Science and Technology

Jin‐Mo Kim

Daegu Gyeongbuk Institute of Science and Technology

Yunho Jeong

Daegu Gyeongbuk Institute of Science and Technology

Taeyoon Lee

Yonsei University

Han Hee Jung

Hannam University

Cooperative Institutions

Daegu Gyeongbuk Institute of Science and Technology

Korea Brain Research Institute

Korea Advanced Institute of Science and Technology

Korea Research Institute of Bioscience and Biotechnology

Yonsei University

Gwangju Institute of Science and Technology

University of California, San Diego

Korea Institute of Industrial Technology

Jeonbuk National University

Seoul National University

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ICoRD: Iterative correlation-based ROI detection method for the extraction of neural signals in calcium imaging

bioRxiv (Cold Spring Harbor Laboratory) (2021)

Seongtak Kang Ji Ho Park Kyung-Soo Kim Sung‐Ho Lim Samhwan Kim

Abstract In vivo calcium imaging is a standard neuroimaging technique that allows selective observation of target neuronal activities. In calcium imaging, neuron activation signals provide key information for the investigation of neural circuits. For efficient extraction of the calcium signals of neurons, selective detection of the region of interest (ROI) pixels corresponding to the active subcellular region of the target neuron is essential. However, current ROI detection methods for calcium imaging data exhibit a relatively low signal extraction performance from neurons with a low signal-to-noise power ratio (SNR). This is problematic because a low SNR is unavoidable in many biological experiments. Therefore, we propose an iterative correlation-based ROI detection (ICoRD) method that robustly extracts the calcium signal of the target neuron from a calcium imaging series with severe noise. ICoRD extracts calcium signals closer to the ground-truth calcium signal than the conventional method from simulated calcium imaging data in all low SNR ranges. Additionally, this study confirmed that ICoRD robustly extracts activation signals against noise, even within in vivo environments. ICoRD showed reliable detection from neurons with a low SNR and sparse activation, which were not detected by conventional methods. ICoRD will facilitate our understanding of neural circuit activity by providing significantly improved ROI detection in noisy images.

Region of interest

Calcium imaging

SIGNAL (programming language)

10.1101/2021.12.16.473055

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향기 및 조명의 스트레스 이완효과에 대한 조사 연구

양윤라 강성탁 신항식 Yoon Yang Seongtak Kang

스트레스는 인체 생리에 영향을 미쳐 과도한 스트레스가 지속되는 경우 신체적 질환으로 이어질 가능서이 크다. 따라서 스트레스 감소의 필요성이 증가하고 있으며 향기요법과 조명을 활용하여 스트레스를 감소시키기 위한 활동이 활발해지고 있다. 본 연구에서는 향기요법과 조명이 스트레스에 미치는 영향에 대한 기존 연...

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Template matching-based event-related ROI detection method for calcium imaging

IBRO Reports (2019)

Kyung‐Soo Kim Seongtak Kang Ji Ho Park Young-Eun Han Jong‐Cheol Rah

Template matching

10.1016/j.ibror.2019.07.1622

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Highly Deformable Double‐Sided Neural Probe with All‐in‐One Electrode System for Real‐Time In Vivo Detection of Dopamine for Parkinson's Disease

Advanced Functional Materials (2023)

Han Hee Jung Jeongdae Ha Jeongrak Park Seongtak Kang Jin‐Mo Kim

Abstract Precise monitoring of neurotransmitters, such as dopamine (DA), is critical for understanding brain function and treating neurological disorders since dysregulation of DA implicates in a range of disorders, including Parkinson's disease (PD), schizophrenia, and addiction. This study proposes a multi‐deformable double‐sided (MDD) DA‐sensing probe with the three‐electrode system in all‐in‐one form for reliable real‐time monitoring of DA dynamics by integrating working, reference, and counter electrodes on a single probe. The proposed probe achieves high DA sensitivity and selectivity in virtue of enzyme immobilization on the 3D nanostructures grown on working electrode. Also, the serpentine design is employed for the electrodes to withstand in various deformations by achieving high stretchability and manage the stress induced on the probe. Experimental and computational analysis demonstrates an effective reduction in induced‐stress on the electrodes. The MDD DA‐sensing probe is implanted into the brain with success to enable real‐time, in vivo monitoring of DA levels in rodents. Furthermore, DA dynamic changes are monitored before and after treatment with L‐DOPA in hemi‐PD mice. This extremely deformable implantable probe has the potential for use in the study and treatment of neurodegenerative diseases, providing reliable monitoring of DA dynamics with minimal damage to brain tissue.

10.1002/adfm.202311436

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Simultaneous Estimation of Tonic Dopamine and Serotonin with High Temporal Resolution In Vitro Using Deep Learning

2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2023)

Seongtak Kang Yunho Jeong Ji‐Woong Choi

Quantitative measurement of the phasic (changes in several seconds) and tonic (changes in minutes to hours) level changes of neurotransmitters is an essential technique for understanding brain functions and brain diseases regulated by the neurotransmitters. However, monitoring phasic and tonic levels of multiple neurotransmitters is still a challenging technology. Microdialysis can measure the tonic levels of multiple neurotransmitters simultaneously but has a low temporal resolution (minute) to analyze precisely. Fast-scan cyclic voltammetry (FSCV) has high temporal resolution and high sensitivity, but it was not able to simultaneously measure the tonic level of multiple neurotransmitters. The recently proposed deep learning-based FSCV method was still only capable of phasic concentration estimation of neurotransmitters. In this study, we estimate the tonic levels of dopamine and serotonin simultaneously by training a deep-learning network with the extracted tonic information from the FSCV. The proposed deep learning model was validated in vitro to simultaneously estimate tonic concentrations of two neurotransmitters with statistically significantly higher accuracy than previously proposed background subtraction-based models (p<0.001). In particular, in the case of serotonin concentration estimation error, the proposed model showed higher prediction performance than the background subtraction-based model (48 nM and 73 nM, respectively). We expect that the proposed technique will help simultaneous measurement of the phasic and tonic levels of numerous neurotransmitters in vivo soon.Clinical Relevance— This study proposes a method to simultaneously measure tonic dopamine and tonic serotonin with high temporal resolution with a single electrode in the brain.

Tonic (physiology)

Subtraction

Microdialysis

10.1109/embc40787.2023.10341045

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ICoRD: iterative correlation-based ROI detection method for the extraction of neural signals in calcium imaging

Journal of Neural Engineering (2022)

Seongtak Kang Ji Ho Park Kyung-Soo Kim Sung‐Ho Lim Samhwan Kim

Abstract Objective. In vivo calcium imaging is a standard neuroimaging technique that allows selective observation of target neuronal activities. In calcium imaging, neuron activation signals provide key information for the investigation of neural circuits. For efficient extraction of the calcium signals of neurons, selective detection of the region of interest (ROI) pixels corresponding to the active subcellular region of the target neuron is essential. However, current ROI detection methods for calcium imaging data exhibit a relatively low signal extraction performance from neurons with a low signal-to-noise power ratio (SNR). This is problematic because a low SNR is unavoidable in many biological experiments. Approach. Therefore, we propose an iterative correlation-based ROI detection (ICoRD) method that robustly extracts the calcium signal of the target neuron from a calcium imaging series with severe noise. Main results. ICoRD extracts calcium signals closer to the ground-truth calcium signal than the conventional method from simulated calcium imaging data in all low SNR ranges. Additionally, this study confirmed that ICoRD robustly extracts activation signals against noise, even within in vivo environments. Significance. ICoRD showed reliable detection from neurons with a low SNR and sparse activation, which were not detected by conventional methods. ICoRD will facilitate our understanding of neural circuit activity by providing significantly improved ROI detection in noisy images.

Region of interest

10.1088/1741-2552/ac84aa

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High-order thalamic and motor cortex inputs integrate sublinearly into tuft dendrites of pyramidal neurons in mouse somatosensory cortex

bioRxiv (Cold Spring Harbor Laboratory) (2022)

Young-Eun Han Joon Ho Choi Kyung-Soo Kim Seongtak Kang Hyungju Park

Abstract Tuft dendrites of pyramidal neurons housed in layer 1 of the neocortex form extensive excitatory synaptic connections with long-range cortical and high-order thalamic axons, along with diverse inhibitory inputs. Recently, we reported that synapses from the vibrissal primary motor cortex (vM1) and posterior medial thalamic nucleus (POm) are spatially clustered together in the same set of distal dendrites, suggesting a close functional interaction. In this study, we evaluated how these two types of synapses interact with each other using in vivo two-photon Ca 2+ imaging and electrophysiology. We observed that dendritic Ca 2+ responses could be efficiently evoked by electrical stimulation of POm or vM1 in the overlapping set of dendritic branches, rejecting the idea of branch-wise origin-selective synaptic wiring. Surprisingly, the Ca 2+ responses upon coincident POm and vM1 stimulation summed sublinearly. We attribute this sublinearity to mutual inhibition via inhibitory neurons because synaptic currents generated by POm and vM1 also integrated sublinearly, but pharmacologically isolated direct synaptic currents summed linearly. Inhibitory neurons receiving POm inputs in the superficial cortical layer negatively regulated vM1-evoked responses. Finally, POm and vM1 innervated overlapping but distinct populations of somatostatin-expressing inhibitory neurons. Thus, POm and vM1 inputs negatively modulate each other in the mouse somatosensory cortex.

Neocortex

Barrel cortex

10.1101/2022.07.05.498894

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Second-Derivative-Based Background Drift Removal for Tonic Dopamine Measurement in Fast-Scan Cyclic Voltammetry

Seongtak Kang Jeongrak Park Yunho Jeong Yong‐Seok Oh Ji‐Woong Choi

The dysregulation of dopamine, a neuromodulator, is associated with a broad spectrum of brain disorders, including Parkinson’s disease, addiction, and schizophrenia. Quantitative measurements of dopamine are essential for understanding dopamine functional dynamics. Fast-scan cyclic voltammetry (FSCV) is the most widely used electrochemical technique for measuring real-time in vivo dopamine level changes. Standard FSCV has only been used to analyze “phasic dopamine” (changes in seconds), because the gradual generation of background charging current is inevitable, and acts as the main noise source in the low-frequency band. Although “tonic dopamine” (changes in minutes to hours) is key for understanding the dopamine system, an electrochemical technique capable of simultaneously measuring phasic and tonic dopamine in an in vivo environment has not been established. Several modified voltammetric techniques have been developed for measuring tonic dopamine, but the sampling rates (0.1-0.05 Hz) are too low to be useful. Further investigation of the in vivo applicability of previously developed background drift removal methods for measuring tonic dopamine levels is required. We developed a second-derivative-based background removal (SDBR) method for simultaneously measuring phasic and tonic neurotransmitter levels in real-time. The performance of this technique was tested via in silico and in vitro tonic dopamine experiments. Furthermore, its applicability was tested in vivo. SDBR is a simple, robust, post-processing technique that can extract tonic neurotransmitter levels from all FSCV data. As SDBR is calculated in individual-scan voltammogram units, it can be applied to any real-time closed-loop system that uses a neurotransmitter as a biomarker.

Tonic (physiology)

10.26434/chemrxiv-2022-fthql

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Continuous long-range measurement of tonic dopamine with advanced FSCV for pharmacodynamic analysis of levodopa-induced dyskinesia in Parkinson’s disease

Frontiers in Bioengineering and Biotechnology (2024)

Jeongrak Park Seongtak Kang Yaebin Lee Ji‐Woong Choi Yong‐Seok Oh

Levodopa, a dopamine prodrug, alleviates the motor symptoms of Parkinson’s disease (PD), but its chronic use gives rise to levodopa-induced dyskinesia (LID). However, it remains unclear whether levodopa pharmacodynamics is altered during the progressive onset of LID. Using in vivo fast-scan cyclic voltammetry and second-derivative-based background drift removal, we continuously measured tonic dopamine levels using high temporal resolution recording over 1-h. Increases to tonic dopamine levels following acute levodopa administration were slow and marginal within the naïve PD model. However, these levels increased faster and higher in the LID model. Furthermore, we identified a strong positive correlation of dyskinetic behavior with the rate of dopamine increase, but much less with its cumulative level, at each time point. Here, we identified the altered signature of striatal DA dynamics underlying LID in PD using an advanced FSCV technique that demonstrates the long-range dynamics of tonic dopamine following drug administration.

Tonic (physiology)

Pharmacodynamics

10.3389/fbioe.2024.1335474

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Citations (1)

takang0902/Open_SDBR

Zenodo (CERN European Organization for Nuclear Research) (2022)

Seongtak Kang Jeongrak Park Yunho Jeong Yong‐Seok Oh Ji‐Woong Choi

This is data for "Second-Derivative-Based Background Drift Removal for Tonic Dopamine Measurement in Fast-Scan Cyclic Voltammetry"

10.5281/zenodo.6332991

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