A Research Blog

Asst Prof Julian Lim from the Duke-NUS Centre for Cognitive Neuroscience

There are times in a person’s life when sleeping enough doesn’t seem possible. Most of these times tend to coincide with having to take final exams. So, the question is, when a person is sleep deprived, should they take a nap, take a break, or power through and keep studying - for the best result?

This question was answered in a recently published Journal of Sleep Research study by a team of researchers from the Centre
for Cognitive Neuroscience (CCN) at Duke-NUS Medical School (Duke-NUS).

Many things affect cognitive performance. Some of these factors include circadian rhythms, taking a rest break and how long a person spends doing a continuous task. However, how these factors interact to influence cognitive performance is poorly understood.

To shed more light on this topic, Assistant Professor Julian Lim and team from the CCN decided to investigate the effects of napping on the processing speed of a sleep restricted person. Processing speed, or how quickly a person is able to carry out simple or automatic cognitive tasks, is an important contributor to cognitive performance.

The study observed 57 healthy adolescents (26 female, 31 male, aged 15 to 19) as part of the CCN’s Need For Sleep 2 study. In the course of this study, participants were sleep deprived. They were allowed to sleep for five hours a night, over five days, which was followed by nine hours of recovery sleep for two days.

Psychedelic cerebrum


A coronal section of a mouse brain is set ablaze with the fluorescent glow of different markers. Myelin in green, axons in red, microglia in magenta and nuclei in blue brings the structure of the hippocampus, striatum, thalamus and hypothalamus into focus.

 Image by Chan Jia Pei, PhD student in the laboratory of Professor David Silver
Cardiovascular and Metabolic Disorders Programme
Duke-NUS Medical School


Prof Michael Chee

This article was contributed by Professor Michael Chee, Director, Centre for Cognitive Neuroscience, Duke-NUS Medical School

fMRI, a brain imaging technique, can detect spontaneous fluctuations in blood flow that are synchronized across functionally related but physically separate brain regions. More recently, it has been shown that this type of functional connectivity, evaluated by when a person simply lies down in a MRI scanner with his / her eyes open, is not static. Instead, it displays recurrent shifting patterns not unlike a restless sea. Although dynamic shifts in functional connectivity have been suspected to signify changing mental states, clear proof that the shifts have behavioral significance has been elusive.

A team led by Michael Chee and Juan Zhou of Duke-NUS Medical School, Singapore and communicated in the Aug 8th issue of the Proceedings of the National Academy of Sciences (USA) found the missing link between shifting mental gears and imaging data through sophisticated analyses anchored on the everyday observation that when we are sleepy, our eyelids tend to shut.

Brain web


Human pluripotent stem cells (hPSCs)-induced GABAergic neurons can be seen here with the help of immunostaining. Neuronal dendrites are in red and identify neurons, while GABA positive sections in green further proves these neurons are GABAergic. These human GABAergic neurons were generated using a rapid and highly efficient single-step protocol published in Cell Reports by Duke-NUS Assistant Professor Shawn Je, National Neuroscience Institute Research Fellow Dr Alfred Sun and NUS Graduate School PhD student Mr Yuan Qiang, which can be taken advantage of to study human neuropsychiatric and neurological disorders related to GABAergic neuron dysfunction. More about their work can be read here.

Image by Yuan Qiang, NUS Graduate School PhD Student
Duke-NUS Medical School

Events at synaptic terminal underlying glutamate releaseFirst steps taken in understanding psychiatric disorders

A team from Duke-NUS Medical School and the National University of Singapore discovered how a major susceptibility gene for mental illness – Disrupted-In-Schizophrenia-1 (DISC1) – regulates glutamate release and neurotransmission across synapses. This discovery provides welcome progress to the development of targeted therapies for mental illness, a field facing decline as it has been plagued by detrimental side effects, high costs, and the inability to develop treatments to treat the disease rather than just the symptoms.

Glutamate is the main excitatory neurotransmitter in the brain. The release of glutamate from nerve terminals into the synaptic cleft underlies neuron-to-neuron communication in brain regions involved in higher cognitive functions, such as learning and memory, executive planning, and mental imagery. Not surprisingly, abnormal glutamate neurotransmission is linked to major psychiatric diseases, like schizophrenia, autism and bipolar disorder. However, pinpointing the cause of abnormal neurotransmitter release in these mental illnesses has been elusive.

Enjoying some time away from the bench. (L to R: Dr Farhan Mohammad, Asst Prof Adam Claridge-Chang, Dr Joses Lim)

Adam Claridge-Chang is Assistant Professor with the Neuroscience & Behavioural Disorders Programme at Duke-NUS Medical School. We talked to him about his most recent publication in Neuroscience & Biobehavioural Reviews: Concordance and incongruence in preclinical anxiety models: systematic review and meta-analyses.

Q: How did this paper come about?

Anxiety disorders are the most prevalent mental illnesses, but pharmaceutical companies have not been successful in finding effective treatments due to poor understanding of the underlying causes of mental illness. We were interested in finding new ways to understand anxiety by utilising the powerful genetic tools available in fruit fly (Drosophila melanogaster) research. Specifically,

Dr Farhan Mohammad, a talented postdoc in my lab, was working to set up a fruit fly model for anxiety. When he turned to the rodent anxiety literature to guide the development of the fly model, he was surprised to find a lack of consensus about which genes regulated anxiety. This posed an obstacle, since our strategy to validate the fly model relied on a direct comparison with preclinical data. At this point, conducting a meta-analysis seemed the best way to make sense of what the rodent data on anxiety was really telling us.


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