Se‐Bum Paik
Korea Advanced Institute of Science and Technology · 神経科学
研究室紹介
Professor Se-Bum Paik's research lab investigates the neural basis of perception and cognition using computational and systems neuroscience approaches. The lab focuses on understanding how fundamental visual processing features—such as number sense, face selectivity, and orientation tuning—emerge in the brain, often through innate mechanisms rather than requiring extensive learning. By combining deep neural network modeling, large-scale neuroanatomical data, and experimental validation, the lab explores the principles underlying cortical map formation, neuronal selectivity, and the pathophysiology of neurological disorders like epilepsy. Their work bridges theoretical neuroscience with empirical data, aiming to uncover universal design principles of the visual brain.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Number sense, the ability to estimate numerosity, is observed in naïve animals, but how this cognitive function emerges in the brain remains unclear. Here, using an artificial deep neural network that models the ventral visual stream of the brain, we show that number-selective neurons can arise spontaneously, even in the complete absence of learning. We also show that the responses of these neurons can induce the abstract number sense, the ability to discriminate numerosity independent of low-le
Face-selective neurons are observed in the primate visual pathway and are considered as the basis of face detection in the brain. However, it has been debated as to whether this neuronal selectivity can arise innately or whether it requires training from visual experience. Here, using a hierarchical deep neural network model of the ventral visual stream, we suggest a mechanism in which face-selectivity arises in the complete absence of training. We found that units selective to faces emerge robu
In the mammalian primary visual cortex, neural tuning to stimulus orientation is organized in either columnar or salt-and-pepper patterns across species. For decades, this sharp contrast has spawned fundamental questions about the origin of functional architectures in visual cortex. However, it is unknown whether these patterns reflect disparate developmental mechanisms across mammalian taxa or simply originate from variation of biological parameters under a universal development process. In thi
Recent breakthroughs in neuroanatomical tracing methods have helped unravel complicated neural connectivity in whole-brain tissue at single-cell resolution. However, in most cases, analysis of brain images remains dependent on highly subjective and sample-specific manual processing, preventing precise comparison across sample animals. In the present study, we introduce AMaSiNe, software for automated mapping of single neurons in the standard mouse brain atlas with annotated regions. AMaSiNe auto
Maps representing the preference of neurons for the location and orientation of a stimulus on the visual field are a hallmark of primary visual cortex. It is not yet known how these maps develop and what function they play in visual processing. One hypothesis postulates that orientation maps are initially seeded by the spatial interference of ON- and OFF-center retinal receptive field mosaics. Here we show that such a mechanism predicts a link between the layout of orientation preferences around
OBJECTIVE: Low-level somatic mosaicism in the brain has been shown to be a major genetic cause of intractable focal epilepsy. However, how a relatively few mutation-carrying neurons are able to induce epileptogenesis at the local network level remains poorly understood. METHODS: To probe the origin of epileptogenesis, we measured the excitability of neurons with MTOR mutation and nearby nonmutated neurons recorded by whole-cell patch-clamp and array-based electrodes comparing the topographic dis
Abstract NMDA receptor (NMDAR) and GABA neuronal dysfunctions are observed in animal models of autism spectrum disorders, but how these dysfunctions impair social cognition and behavior remains unclear. We report here that NMDARs in cortical parvalbumin (Pv)-positive interneurons cooperate with gap junctions to promote high-frequency (>80 Hz) Pv neuronal burst firing and social cognition. Shank2 –/– mice, displaying improved sociability upon NMDAR activation, show impaired cortical social rep
Spike-timing-dependent plasticity (STDP) is considered critical to learning and memory functions in the human brain. Across various types of synapse, STDP is observed as different profiles of Hebbian and anti-Hebbian learning rules. However, the specific roles of diverse STDP profiles in memory formation still remain elusive. Here, we show that the symmetry of the learning rate profile in STDP is crucial to determining the character of stored memory. Using computer simulations, we found that an
Synchronized oscillation is very commonly observed in many neuronal systems and might play an important role in the response properties of the system. We have studied how the spontaneous oscillatory activity affects the responsiveness of a neuronal network, using a neural network model of the visual cortex built from Hodgkin-Huxley type excitatory (E-) and inhibitory (I-) neurons. When the isotropic local E-I and I-E synaptic connections were sufficiently strong, the network commonly generated g
Correlated neural activities such as synchronizations can significantly alter the characteristics of spike transfer between neural layers. However, it is not clear how this synchronization-dependent spike transfer can be affected by the structure of convergent feedforward wiring. To address this question, we implemented computer simulations of model neural networks: a source and a target layer connected with different types of convergent wiring rules. In the Gaussian-Gaussian (GG) model, both th
Many anatomical and physiological features of cortical circuits, ranging from the biophysical properties of synapses to the connectivity patterns among different neuron types, exhibit consistent variation along the hierarchical axis from sensory to association areas. Notably, the temporal correlation of neural activity at rest, known as the intrinsic timescale, increases systematically along this hierarchy in both primates and rodents, analogous to the increasing scale and complexity of spatial
Synchronized gamma frequency oscillations in neural networks are thought to be important to sensory information processing, and their effects have been intensively studied. Here we describe a mechanism by which the nervous system can readily control gamma oscillation effects, depending selectively on visual stimuli. Using a model neural network simulation, we found that sensory response in the primary visual cortex is significantly modulated by the resonance between "spontaneous" and "stimulus-d
In higher mammals, the primary visual cortex (V1) is organized into diverse tuning maps of visual features. The topography of these maps intersects orthogonally, but it remains unclear how such a systematic relationship can develop. Here, we show that the orthogonal organization already exists in retinal ganglion cell (RGC) mosaics, providing a blueprint of the organization in V1. From analysis of the RGC mosaics data in monkeys and cats, we find that the ON-OFF RGC distance and ON-OFF angle of
The serial-position effect in working memory is considered important for studying how a sequence of sensory information can be retained and manipulated simultaneously in neural memory circuits. Here, via a precise analysis of the primacy and recency effects in human psychophysical experiments, we propose that stable and flexible codings take distinct roles of retaining and updating information in working memory, and that their combination induces serial-position effects spontaneously. We found t