Jilai Cui


I am a graduate student in Rhanor Gillette group. My research interest is neuronal circuits for sensory-motor control and learning in invertebrates. To study this question, I am techniques in electrophysiology and computational modeling.

Outside the lab, I am enthusiastic in traditional Asiatic archery, and part of UIUC archery club.

Research topics

Sensory integration in the peripheral nervous system of the mollusks

Many mollusks have an extensive peripheral nervous system (PNS) with partly autonomous sensory-motor networks. In the sea slug Pleurobranchaea, a subepithelial network (SeN) of neurons is embedded in the animal’s oral veil and integrates chemotactile stimuli to output incentive and stimulus location to the central nervous system (CNS). In contrast, in octopus’ arms olfactory information at the suckers is integrated at the of sucker and associated brachial ganglia. Do sea slug SeN and octopus integrate with functionally analogous mechanisms? To explore function in the octopus’s arm, we train the animal with different odors paired with positive or negative rewards, and then record the isolated arm’s behavioral and electrophysiological responses to those stimuli. This experiment may tell whether the arm ganglia can locally store the memory.

Sensory-motor control in the octopus’s arms

Octopuses’ arms are impressive in their flexibility, agility, and independence in motor control, which can inspire the design of efficient soft body robotic arms. However, neuronal mechanisms for single-arm control and multi-arm coordination are still unclear. One hypothesis for their arm control mechanism is that the PNS in the arm has independent abilities to precept and react to environmental stimuli and learn from them through a network between the brachial and sucker ganglia that integrates sensory inputs and motor control, as mentioned previously.

The second plan of this project is study of the control of arm movements by the brain. Compared with the Pleurobranchaea CNS, the octopus has a more complex brain highly subdivided into lobes with different functions. However, a similar common design between the two suggests that the octopus’s lobes may express significant functional analogies of Pleurobranchaea CNS.

Simulation of the octopus arm network

Related to the above projects, I am developing a computational model for the sensory-motor network of the octopuses’ arms in a simulated environment. This network is embedded into the peripheral nervous system on the arms and suckers so they can integrate sensory information from the surrounding environment and control the motor response directly without command from a higher unit. This de-centralized model will be able to coordinate the movement of different parts in the arm. To further develop this model, I will add learning abilities derived from short-term and long-term memory formation mechanisms in sea slug Aplysia, so the arm model can learn to distinguish different stimuli and develop spatial recognition abilities based on that.

Fluid dynamic simulation of the Glymphatic system

In addition to the research of the mollusk’s nervous systems, I also have a side project on modeling the fluid dynamics of the glymphatic system in the brain. The glymphatic system is essential to clearance of metabolic wastes in the brain. The clearance is conducted by the convection of cerebrospinal fluid (CSF) and interstitial fluid (ISF). CSF enters the brain parenchyma from arterial perivascular spaces and the waste is cleared from brain by ISF drainage into the cervical lymphatic system at perivenous space. The flow of fluid in the glymphatic system is driven by multiple physical forces from the tissues and is affected by autophagy and circadian rhythms.

The fluid dynamics of the glymphatic system and the impacts of neurodegeneration on it are still not well documented, and a useful mathematical model is not yet available. This project is to build an interactive tool modeling the clearance function of the glymphatic system under normal and neurodegenerative conditions. In this simulation, the network connectivity is modified by percolation and homeostatic plasticity. By changing the connection strength, disruption in the glymphatic structure can be simulated. This model can be used to study the glymphatic system’s response to the disruption of its fluid network caused by neurodegenerative diseases.


I was TA of MCB 462: Integrative Neuroscience in 2023-2024 and MCB 461: Cell & Molecular Neuroscience in 2023