Keiichiro Inagaki

Method for the construction and use of carbon fiber multibarrel electrodes for deep brain recordings in the alert animal.

Microiontophoresis of neuroactive substances during single unit recording in awake behaving animals can significantly advance our understanding of neural circuit function. Here, we present a detailed description of a method for constructing carbon fiber multibarrel electrodes suitable for delivering drugs while simultaneously recording single unit activity from deep structures, including brainstem nuclei and the cerebellum, in the awake behaving primate. We provide data that should aid in minimizing barrel resistance and the time required to fill long, thin multibarrel electrodes with solutions. We also show successful single unit recording from a variety of areas in the awake squirrel monkey central nervous system, including the vestibular nuclei, Interstitial Nucleus of Cajal, and the cerebellum. Our descriptions and data should be useful for investigators wishing to perform single unit recordings during microiontophoresis of neuroactive substances, particularly in deep structures of animals with chronically implanted recording chambers.

2011 Special Issue: A model-based theory on the signal transformation for microsaccade generation

The eyes are continuously fluctuating even during fixation. The fluctuations are called miniature eye movements and consist of microsaccades, drifts, and tremors. It has been revealed that these miniature eye movements aid our vision; they improve the visibility of high spatial frequency components, and prevent retinal adaptation during fixation. Although the functional roles of the miniature eye movements have gradually been uncovered, their generation mechanism remains a mystery. Here, we focused on microsaccades, and constructed a neuronal network model to explore their generation mechanism. Several lines of evidence ensure that microsaccades and saccades share the same neuronal circuitry because they fall on the same main sequence, a relationship between their amplitudes and peak velocities. In the saccade pathway, saccade commands generated in the superior colliculus are relayed to motoneurons via burst neurons (BNs) and the integrator network. The BNs are inhibited by omnipause neurons (OPNs) except when saccades are generated. We configured a model for microsaccades based on the well-defined saccade neuronal pathway including tonic neurons, BNs, OPNs, the integrator network, and the eye plant. The model successfully reproduced various characteristics of microsaccade: square-wave jerk, single-sided microsaccades, and the main sequence. Moreover, during microsaccades, BNs showed low-rate spikes due to a partial release from the OPN inhibition. These results suggest that microsaccades are generated when BNs are partially, but not completely, released from tonic inhibition by OPNs during fixation, in contrast to the generation of ordinary saccades in which OPNs pause firing and release BNs from their strong inhibition.

2011 Special Issue: PLATO: Data-oriented approach to collaborative large-scale brain system modeling

The brain is a complex information processing system, which can be divided into sub-systems, such as the sensory organs, functional areas in the cortex, and motor control systems. In this sense, most of the mathematical models developed in the field of neuroscience have mainly targeted a specific sub-system. In order to understand the details of the brain as a whole, such sub-system models need to be integrated toward the development of a neurophysiologically plausible large-scale system model. In the present work, we propose a model integration library where models can be connected by means of a common data format. Here, the common data format should be portable so that models written in any programming language, computer architecture, and operating system can be connected. Moreover, the library should be simple so that models can be adapted to use the common data format without requiring any detailed knowledge on its use. Using this library, we have successfully connected existing models reproducing certain features of the visual system, toward the development of a large-scale visual system model. This library will enable users to reuse and integrate existing and newly developed models toward the development and simulation of a large-scale brain system model. The resulting model can also be executed on high performance computers using Message Passing Interface (MPI).

A Next Generation Modeling Environment PLATO: Platform for Collaborative Brain System Modeling

To understand the details of brain function, a large scale system model that reflects anatomical and neurophysiological characteristics needs to be implemented. Though numerous computational models of different brain areas have been proposed, these integration for the development of a large scale model have not yet been accomplished because these models were described by different programming languages, and mostly because they used different data formats. This paper introduces a platform for a collaborative brain system modeling (PLATO) where one can construct computational models using several programming languages and connect them at the I/O level with a common data format. As an example, a whole visual system model including eye movement, eye optics, retinal network and visual cortex is being developed. Preliminary results demonstrate that the integrated model successfully simulates the signal processing flow at the different stages of visual system.

Computational Theory Underlying Acute Vestibulo-ocular Reflex Motor Learning with Cerebellar Long-Term Depression and Long-Term Potentiation

The vestibulo-ocular reflex (VOR) can be viewed as an adaptive control system that maintains compensatory eye movements during head motion. As the cerebellar flocculus is intimately involved in this adaptive motor control of the VOR, the VOR has been a popular model system for investigating cerebellar motor learning. Long-term depression (LTD) and long-term potentiation (LTP) at the parallel fiber–Purkinje cell synapses are considered to play major roles in cerebellar motor learning. A recent study using mutant mice demonstrated cerebellar motor learning with hampered LTD; the study concluded that the parallel fiber–Purkinje cell LTD is not essential. More recently, multiple forms of plasticity have been found in the cerebellum, and they are believed to contribute to cerebellar motor learning. However, it is still unclear how synaptic plasticity modifies the signal processing that underlies motor learning in the flocculus. A computational simulation suggested that the plasticity present in mossy fiber–granule cell synapses improves VOR-related sensory-motor information transferred into granule cells, whereas the plasticity in the molecular layer stores this information as a memory under guidance from climbing fiber teaching signals. Thus, motor learning and memory are thought to be induced mainly by LTD and LTP at parallel fiber–Purkinje cell synapses and by rebound potentiation at molecular interneuron–Purkinje cell synapses among the multiple forms of plasticity in the cerebellum. In this study, we focused on the LTD and LTP at parallel fiber–Purkinje cell synapses. Based on our simulation, we propose that acute VOR motor learning accomplishes by simultaneous enhancement of eye movement signals via LTP and suppression of vestibular signals via LTD to increase VOR gain (gain-up learning). To decrease VOR gain (gain-down learning), these two signals are modified in the opposite directions; namely, LTD suppresses eye movement signals, whereas LTP enhances vestibular signals.

A modeling study on the signal transformation for the microsaccade generation

During visual fixation, stationary images are thought to be input to the visual system. However the actual input images are continuously fluctuating due to miniature eye movements. The miniature eye movements consist of microsaccade, drift, and tremor [1]. To date, while the functional roles of the miniature eye movements in perception, and their kinematic properties are gradually understood [1-3]; the mechanisms of their generation remain unknown. Here we focused on microsaccade, and constructed a model to explore the mechanisms of microsaccade generation.

Bihemispheric Cerebellar Spiking Network Model to Simulate Acute VOR Motor Learning

The vestibuloocular reflex (VOR) is an adaptive control system. The cerebellar flocculus is intimately involved in the VOR adaptive motor control. The cerebellar flocculus has bihemispheric architecture and the several lines of unilateral lesion study indicated that each cerebellar hemisphere plays different roles in the leftward and rightward eye movement control and learning. However, roles of bihemispheric cerebellar architecture underlying the VOR motor learning have not been fully understood. Here we configure an anatomically/physiologically plausible bihemispheric cerebellar neuronal network model composed of spiking neurons as a platform to unveil roles and capacities of bihemispheric cerebellar architecture in the VOR motor learning.

Different roles for ipsilateral positive feedback and commissural inhibitory networks in oculomotor velocity to position neural integration

Saccadic eye movements are made about twice a second to shift our gaze either consciously or unconsciously. Brainstem burst neurons trigger each saccade with a bursting activity closely related to saccadic velocity that must be transformed into persistent firing activity to maintain post-saccadic eye position. A conceptual neural mechanism achieving this velocity to position integration is the oculomotor neural integrator (NI). Neurons in the nucleus of prepositus hypoglossi (NPH) in mammals and equivalently Area I (AI) in goldfish have been demonstrated to exhibit persistent activity relating to eye position. Ipsilateral positive feedback found in NPH and AI [1], and commissural inhibition between these bilateral areas [2] are proposed to be the two candidate neuronal networks for the integration. However, how these networks contribute to generate persistent firing is still unknown. Recent behavioral and optogenetic experiments demonstrated that eye position holding properties are individually modifiable for nasal and temporal hemi-fields of the eye, thereby suggesting existence of at least two NIs in each nucleus [3,4]. In the present study, we constructed a NI neuronal network model closely following anatomical and physiological evidence to better understand the roles of the two NI networks. The model consists of an excitatory burst neuron (EBN), an inhibitory burst neuron (IBN), a tonic neuron (TN), and a bilateral NI network in which 15 integrator neurons (INs) are included unilaterally. Each IN receives input from TN, EBN, and IBN, and also has positive recurrent feedback connections from all ipsilateral INs including commissural inhibitory connections from all contralateral INs. The output of EBN, IBN, and each NI are weighted-summed at a motor neuron whose output is sent to an eye plant model to simulate eye movements. These neuron models are described as conductancebased spiking neurons. Synaptic weights in the model were carefully tuned to reproduce saccades and post-saccadic stable eye positions. Following individual modification of either the synaptic weights of ipsilateral feedback connection or those of commissural inhibition we measured post-saccadic eye position drift. Simulation results showed that persistent firing activity of INs is maintained principally by the ipsilateral positive feedback. By contrast, commissural inhibition contributed mainly to null eye position which is the asymptote from which the NI becomes leaky. These findings are the first demonstration by a NI neuronal network model assigning specific and different roles to the ipsilateral positive feedback and the commissural inhibition. In future work, we will use this model to evaluate the elective eye holding properties within the two hemi-field NIs.

Model on Visualization and Analysis for Peripheral Drift Illusion

The peripheral drift illusion yields rotating motion on our peripheral vision. It has been reported that the order of four different luminance regions is essential for this illusion (black, blue (dark gray), yellow (light-gray), and white). Moreover, it has been suggested that luminance or contrast dependent latency of V1/MT direction selective cells contributes on induction of the rotating illusory motion. In the present work, we modeled V1 and MT as a retinotopic map of those direction selective cells and investigated whether the illusory rotating motions in peripheral drift illusion can be reproduced. In our simulation, the illusory rotating motions are represented in the transition of neuronal responses in both V1 and MT when the responses are visualized in contrast domain, but not in luminance domain, suggesting that the contrast is key information for induction of the rotating motion in the peripheral drift illusion.

Visualization and analysis of peripheral drift illusion

The peripheral drift illusion (e.g. Rotating snake [1]) yields rotating motion on our peripheral vision. It was reported that the order of different four luminance regions is essential for the illusion [1]. Moreover, Conway et al. have suggested that luminance or contrast dependent latency in response of V1/MT direction selective cells for those kinds of luminance (black, dark-gray (blue), light-gray (yellow), and white) was contributed on perception of the rotating illusory motion [2]. In the present work, we modeled V1 and MT as a retinotopic map using those direction selective cells [2] and investigated whether this model can reproduce the rotating illusory motion.