Chung-Chuan Lo

Assistant Professor

Institute of Systems Neuroscience
Department of Life Sciences
National Tsing Hua University

Curriculum Vitae
Ph.D. in Physics, Boston University (1998-2004)
M.S. in Physics, National Taiwan University (1995-1997)
B.S. in Physics, National Taiwan University (1991-1995)
PostDoc., Brandeis University (2004-2006)
PostDoc., Yale University (2006-2008)

Research Areas: Neural network modeling, cognitive neuroscience, non-linear biological data analysis
Lab website: http://life.nthu.edu.tw/~lablcc
Contact information:
E-mail cclo@life.nthu.edu.tw
Phone +886-3-574-2014
Fax +886-3-5715934
Address Department of Life Sciences
National Tsing Hua University
101, Sec. 2, Kuang Fu Road, Hsinchu 30013, Taiwan

Current Research in Chung-Chuan Lo's Laboratory

Our lab focuses on studying collective behavior of neural systems using computational modeling and advanced data analysis. Our approach is unique in two aspects: (1) we simulate large scale networks using biologically realistic spiking neuron models with detailed synaptic dynamics and membrane properties, and (2) we analyze data using statistical tools designed for non-stationary dynamics, which are commonly observed in neural systems. Furthermore, our research emphasizes close collaborations with experimentalists.

We have two main research focuses:

(1) Neural circuit mechanisms of flexible brain functions

In everyday life, we often need to evaluate sensory information in order to make a decision, to suppress an ongoing action or to resolve conflicts between automatic and voluntary responses. These flexible brain functions have been studied in psychology for centuries and have gradually became a major topic in neurophysiology in the past few decades. To integrate our understanding of the flexible brain functions in different disciplines at different levels, we build large-scale neural network models that connect neural activity at microscopic levels with behavioral observations at macroscopic levels.

We currently focus on the following brain functions:

  1. Learning and optimization in perceptual decision making. Decision making is an important cognitive function that has been studied for several decades in different fields such as psychology, economy, neurophysiology etc. Most studies have focused on the scenario that a subject has enough time to make decisions as accurate as possible. In contrast, when a timely response is required, a subject needs to speed up the decision process by sacrificing the accuracy. This poses computational problems that are very different from the scenario in which the subject has enough time. A recent spiking neural network model (Lo & Wang, Nat. Neurosci. 2006) suggested that the speed and accuracy in a decision making task can be changed by tuning the synaptic strength in the direct cortico-basal ganglia pathway. To further explore the neural mechanism of the speed-accuracy tradeoff that might be carried out by learning and optimization performed in basal ganglia, we will build a more detailed neural network model that includes cortico-striatal synaptic plasticity, modulations from dopaminergic neurons and interactions between different basal ganglia pathways.
  2. Adaptation in inhibitory control of action. Inhibitory control is a crucial brain function and impairment in the inhibitory control is associated with psychiatric disorders such as attention-deficit hyper activity disorder (ADHD) and schizophrenia. A recent spiking neural network model of inhibitory control (Lo et. al. submitted) suggests that a persistent top-down control from prefrontal cortex modulates the inhibitory circuits in frontal eye field and/or superior colliculus before a subject is required to stop. We will continue this line of work and ask the following key questions: (1) how can the neural system adapts and/or optimizes its inhibitory control by adjusting the top-down signal? (2) What are the differences in the functional roles between inhibitory circuits such as fixation neurons, direct and hyper-direct pathways of basal ganglia?

(2) Neural mechanisms of sleep-state transitions

The complex behavior of neural systems does not only occur during the vigilant state, but also observed in the sleep state. In previous studies, the state transitions during sleep in human (Lo et. al. Europhys. Lett. 2002) and in other mammalian species (Lo et. al. Proc. Natl. Acad. Sci. USA 2004) has been found to exhibit scale-free power-law dynamics in the arousal (wake) state and exponential dynamics with a specific time scale in the sleep state. Interestingly, the scale free dynamics of the arousal state are unchanged across these species while the time scales of the sleep state increases with the size of the species. The observed dynamics of sleep-wake transitions are unique in biological systems. However, they are remarkably similar to dynamics in other non-biological systems which exhibit self-organized criticality.

To explore the underlie neural mechanism that produces the observed scaling behavior, we are developing a neural network model for the neural circuits of "sleep-wake switch" in hypothalamus. The circuit consists of "sleep promoting" neurons in ventrolateral preoptic nucleus (VLPO) and "wake-promoting" neurons in nuclei such as tuberomammillary nucleus (TMN). Specifically, we ask the following key questions: (1) what is the neural mechanism that produces the difference in the dynamics (power-law vs. exponential) between the wake and sleep states? (2) What is the functional significance for such a difference? (3) why are the power-law dynamics invariant across species and why do the exponential dynamics increase with the size of species?

Papers published within last five years
  1. C.-C. Lo, L. Boucher, M. Pare, J. D. Schall and X.-J. Wang. Proactive inhibitory control and attractor dynamics in countermanding action: a spiking neural circuit model. J. Neurosci. 29, 9059-9071 (2009).
  2. C.-C. Lo and X.-J. Wang, Cortico-basal ganglia circuit mechanism for a decision threshold in reaction time tasks, Nat. Neurosci. 9, 957-963 (2006).
  3. C.-C. Lo, Chou T, Penzel T, Scammell TE, Strecker RE, Stanley HE, and Ivanov PCh. Common scale-invariant pattern of sleep-wake transitions across mammalian species. Proc. Natl. Acad. Sci. USA 50, 17545-17548 (2004)