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Elucidating how the molecular building blocks at synapses shape complex behaviour and cognition

The Synapse Biology & Cognition Laboratory is focused on understanding the critical role synaptic genes and proteins play in establishing and regulating the coordinated wiring and connectivity in the brain, that enables complex cognition and higher order processing in the healthy brain, and in mental disorders where these processes go awry.

Vertebrate synapses contain a large yet intricately organised signalling complex of proteins encompassing neurotransmitter receptors, scaffold proteins and cell adhesion proteins that are critical for synapse specification, function and plasticity; thus, formation and plasticity of circuits that underlie the regulation of behaviour.

Human genetic studies continue to increasingly highlight that disruption of postsynaptic genes is a hub for a range of mental health disorders, namely neurodevelopmental and neuropsychiatric disorders. These include anxiety and mood disorders (Depression, Bipolar), Autism Spectrum Disorders and schizophrenia, that share overlapping symptom domains. While the importance of postsynaptic proteins in  synaptic function and plasticity are strongly appreciated, we know much less about the impact of postsynaptic gene mutations in regulating distinct components of cognition and higher order processing.

Modelling the complex cognitive processes routinely assessed in the clinical setting has been challenging in animal models. Bridging the gap between preclinical and clinical cognitive testing, the touchscreen methodology that A/Prof Nithianantharajah was involved in early during its development, application and commercialisation at the University of Cambridge, provides an innovative tool for dissecting higher cognitive functions in rodents that is highly analogous to cognitive assessment of clinical populations.

In our laboratory, we use genetically modified mice as models to study how genes important for regulating synapse function and plasticity selectively modulate cognitive behaviour. Our approaches combine in-depth behavioural analysis with advanced in vivo molecular, cellular and imaging techniques.

Current Projects

  1. Excitatory-inhibitory imbalance on neural networks responsible for reward-based learning: In vivo calcium imaging of neural activity using miniscopes in behaving mice during reward-based learning in touchscreen tasks. 
  2. Understanding the neural basis of decision-making under uncertainty: Development of novel rodent touchscreen tasks to interrogate decision-making in mice, combined with in vivo manipulations (optogenetics, photometry, calcium imaging) to elucidate underlying processes.
  3. Molecular and biochemical analysis of novel disease variants in neurodevelopmental disorders: Using advanced protein binding and stability assays to measure the structural and functional impacts of novel synapse gene mutations identified in neurodevelopmental disorders including Autism Spectrum Disorder, Intellectual Disability and schizophrenia.

Ph.D, Masters and Honours placements are available.

References

Luo J, Tan JM, Nithianantharajah J. A molecular insight into the dissociable regulation of associative learning and motivation by the synaptic protein neuroligin-1. BMC Biology (2020, in press).

Norris RJ, Churilov L, Hannan AJ, Nithianantharajah J. Mutations in neuroligin-3 in male mice impact behavioral flexibility but not relational memory in a touchscreen test of visual transitive inference. Molecular Autism 2019, 10, 42.

Nithianantharajah J, McKechanie AG, Stewart TJ, Johnstone M, Blackwood DH, St Clair D, Grant SGN, Bussey TJ, Saksida LM. Bridging the translational divide: identical cognitive touchscreen testing in mice and humans carrying mutations in a disease-relevant homologous gene. Scientific Reports 2015; 5, 14613.

Nithianantharajah J, Komiyama NH, McKechanie A, Johnstone M, Blackwood DH, St Clair D, Emes RD, van de Lagemaat LN, Saksida LM, Bussey TJ, Grant SGN. Synaptic scaffold evolution generated components of vertebrate cognitive complexity. Nature Neuroscience 2013; 16, 16-24

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