Emergence of Functional Circuits in the Early Visual Pathway

1. Auflage 2022
ISBN: 978-981-19-0033-4
Verlag: Springer

Buch, Englisch, 121 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 230 g

Reihe: KAIST Research Series

This book discusses the emergence of diverse functional organizations in the visual pathway which could be spontaneously and solely initiated by the random feedforward wiring of neural circuits. It demonstrates that the structure of ON and OFF retinal ganglion cell (RGC) mosaics is projected onto V1 by retino-cortical feedforward mapping to induce higher cognitive functions. This book will be beneficial for both theoretical and experimental neuroscientists, as well as for researchers using brain-inspired neural network models.

Zielgruppe

Research

Autoren/Hrsg.

Jang, Jaeson

Paik, Se-Bum

Fachgebiete

• Sozialwissenschaften Psychologie Allgemeine Psychologie Kognitionspsychologie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Neurologie, Klinische Neurowissenschaft
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
• Interdisziplinäres Wissenschaften Wissenschaften Interdisziplinär Neurowissenschaften, Kognitionswissenschaft

Inhaltsverzeichnis

Chapter 1. Introduction

-          Early visual circuits from the retina to visual cortex

-          Major characteristics of functional circuits in visual cortex

-          Higher cognitive function – Number sense

In this chapter, diverse visual functions observed in neurons of the primary visual cortex (V1) will be mainly introduced. For example, as the functional unit processing the basic visual function, neurons in the primary visual cortex are tuned to the orientation of visual stimuli, and the preferred orientation of neurons is arranged quasi-periodically across the cortical surface, termed an orientation map. Regarding their developmental mechanisms, the previous notion focusing on the refinement of cortical circuits and my new idea about the origin projected from the retina will be compared.

Chapter 2.  Cortical map consistency developed by spatial tiling of retinal cell mosaics

- Local repulsive interaction as the developmental mechanism of hexagonal mosaics

- Heterotypic interaction restricts alignment between ON and OFF retinal cell mosaics    

- Validation of heterotypic interaction in observed retinal cell mosaics                

A consistent spatial periodicity of the cortical orientation map is achieved by a restricted interference pattern of ON and OFF retinal ganglion cell (RGC) mosaics that is initiated by a simple repulsive interaction between nearby RGCs that induces gradual shifts of cell positions. Using a model simulation, I first observed that homotypic (ON-to-ON or OFF-to-OFF) interactions could induce a long-range hexagonal organization in each type of RGC mosaic. More importantly, the presence of heterotypic (ON-to-OFF) interactions plays an important role in restricting the alignment angle between ON and OFF RGC mosaics to a small range, resulting in a consistent spatial periodicity of the interference pattern. To validate the model, I quantitatively analyzed the structure of the RGC mosaics observed in animal data and found evidence that the heterotypic repulsive interaction is in effect during the development, contrary to the notion from previous research.

 

Chapter 3. Parametric classification of different organizations of orientation tuning

- Failure of predicting V1 organization from single anatomical parameters

- Parametric division of species based on retino-cortical mapping ratio

- Model simulation of parametric division of V1 organization

In this chapter, it will be shown that disparate organizations of orientation tuning observed in diverse species - columnar orientation maps or salt-and-pepper organizations - are initiated by different mapping conditions of the retino-cortical feedforward pathway. From the analysis of anatomical data for eight mammalian species, I found that the ratio between the size of V1 and that of the retina (or between the number of RGCs and V1 neurons) appear higher for species with columnar maps, so the V1 organization of a species could be predicted from these ratios. With a dense mapping condition, the following model simulations show that common retinal afferents are sampled by neighboring V1 neurons, resulting in a continuous and columnar organization of orientation tuning. These results suggest that both columnar and salt-and-pepper organization in V1 develop universally with the retinal origin, but may bifurcate due to variation of the feedforward circuit.

Chapter 4. Projection of orthogonal tiling from the retina to the visual cortex

- Orthogonal organization of ON and OFF retinal ganglion cells

- Topographical correlation between ON/OFF afferents and cortical tunings        

The development of the orthogonal relationship of tuning modules in V1 is initiated by the projections of an orthogonal organization that already exists in retinal mosaics. First, from an analysis of RGC mosaics data in cats and monkeys, I found that the spatial separation of the ON-OFF feedforward afferents (ON-OFF distance) intersects orthogonally with the ON-OFF alignment angle (ON-OFF angle). These results imply a topographical correlation between the ON-OFF distance and other cortical tunings. As expected, this analysis of published V1 recording data measured in cats shows that the ocular dominance and spatial frequency in V1 are correlated with the spatial separation of the ON and OFF subdomains of the receptive fields. By combining these analyses of RGC mosaics and V1 recording data, I demonstrate that the regularly structured retinal circuits provide a common framework of various functional maps and topographic correlations among the maps in V1.

Chapter 5. Number selectivity from bottom-up projections of monotonic activity units

            - Emergence of number selectivity in untrained networks

            - Abstract number sense independent of low-level visual cues

            - Number tuning by monotonically decreasing and increasing units

Number 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-level visual cues. We found that number tuning in a randomly initialized network originating from a combination of monotonically decreasing and increasing neuronal activities, which emerges spontaneously from the statistical properties of bottom-up projections. We confirmed that the responses of these number-selective neurons show the single- and multi-neuron characteristics observed in the brain, and enable the network to perform number comparison tasks. These findings provide new insight into the origin of innate cognitive functions.

Chapter 6. Discussion

In this chapter, the biological implication and the limitation of the above model studies will be discussed, suggesting various topics for further experimental and computational studies.

Über Autor(innen)

Dr. Jaeson Jang studied bio-engineering and mathematical sciences at Korea Advanced Institute of Science and Technology (KAIST) and graduated in 2013. He remained there for his graduate studies, working under the supervision of Prof. Se-Bum Paik on computational neuroscience. During his doctorate, he proposed how the emergence of diverse functional circuits in the primary visual cortex could be initiated by the feedforward visual inputs from the retina, even without any further development of recurrent cortical circuits. Furthermore, he applied a similar notion to the deep learning and showed that various functional units spontaneously arise from the statistical variation in randomly initialized neural networks, even in the complete absence of learning. He completed his doctoral research in 2020 and embarked on a research project in the diagnosis of mental disorders at Looxid Labs, a start-up that develops recording devices for brain signals in VR.

Dr. Se-Bum Paik is the associate professor in the Department of Bio and Brain Engineering at Korea Advanced Institute of Science and Technology (KAIST) and is the head of the Visual System Neural Network Laboratory. After receiving his B.S in Nuclear Engineering and Physics from Seoul National University and M.S. in Physics from Seoul National University, Dr. Paik obtained his Ph.D. in Physics from the University of California at Berkeley. Dr. Paik’s research has focused on finding a theory that explains how the architecture of the visual system is initially created to generate the building blocks of the visual information process. Dr. Paik introduced the Paik-Ringach model, arguably the most plausible theory of the origin of functional maps in the visual cortex, and his developmental models lay the groundwork for a unified theory of the origin of fundamental functions in the brain. Currently, Dr. Paik is on the board of directors of both the Society for Computational Neuroscience and the Brain Engineering Society of Korea.