Stay tuned for upcoming talks!
Oct 6: Dr. Nick Puts
Sensory impairments and inhibitory dysfunction in neurodevelopmental disorders
10-11 am Friday 6th of October 2017, IoPPN Boardroom
Sensory, e.g. touch, impairments are common in children with neurodevelopmental disorders, such as Autism (ASD) and Tourette syndrome (TS). Such impairments can substantially affect daily functioning, but the underlying neurophysiology is not well known. Several lines of evidence suggest that GABA, the main inhibitory neurotransmitter in the human brain, is affected in Autism and TS and it is well known that GABA plays an important role in encoding tactile information. Edited MRS of GABA allows for in vivo measurements of neurotransmitter levels in the human brain. In my talk I will introduce MRS of GABA and our newly developed battery of tasks assessing tactile function. I will then discuss our recent findings showing relationships between altered tactile function and GABAergic dysfunction in neurodevelopmental disorders. Finally, I will discuss some recent developments from our lab, including pediatric MRS at 7T and novel faster-editing techniques at 3T that can substantially change the type of studies we can do in the future.
Nick Puts is assistant professor in the Russell H. Morgan Department of Radiology and Radiological Science at The Johns Hopkins University School of Medicine in Baltimore, USA. Originally from the Netherlands, he did his PhD in Biosciences/Psychology at Cardiff University in Wales, UK, studying the cortical dynamics of touch processing using psychophysics, MEG, and Magnetic Resonance Spectroscopy (MRS) of GABA. During his Autism Speaks postdoctoral fellowship at Hopkins, he started studying the role of inhibition on tactile impairments in children with Autism using psychophysics and MRS. He recently started applying TMS in autism as well. Nick also works with children with ADHD, Tourette Syndrome, and concussion, as well as healthy populations. He also contributes to the development, support, and dissemination of MRS methods and the Gannet analysis package.
Oct 20: Cancelled
Nov 3: Dr. Tiffany Bell
Multimodal imaging of the human striatal cholinergic system
10-11 am Friday 3rd of November 2017, IoPPN Boardroom
Animal studies have shown that the striatal cholinergic system plays a role in reversal learning, but there has been no attempt to study this in humans due to a lack of appropriate non-invasive techniques. This body of work aimed to address the gap in the literature concerning the role of the human striatal cholinergic system and its thalamic inputs in cognitive flexibility in vivo. To do this, we used a combination of proton magnetic resonance spectroscopy (1H-MRS) and high-resolution functional magnetic resonance imaging (fMRI), together with a reversal learning task and computational modelling to investigate the relationship between cholinergic function and cognitive flexibility. These experiments provide multimodal in vivo evidence to demonstrate a role for the human cholinergic system in the striatum in behavioural flexibility as measured using a reversal learning paradigm. Additionally, this body of work demonstrates that it is possible to use in-vivo proton MRS, both at rest and as a functional measure, to investigate the human striatal cholinergic system. This method not only helps to bridge the gap between animal and human studies, but importantly may provide a novel method of studying disorders characterised by cholinergic dysfunction (e.g. Parkinson’s Disease, Alzheimer’s Disease), extending our understanding of the neural mechanisms underlying these disorders.
Nov 17: Dr. Enrico Grisan
Nov 24: TBA
Dec 8: Dr. Emma Robinson
The Human Connectome Project’s multi-modal cortical parcellation: new avenues for research
10-11 am Friday 8th of December 2017, IoPPN Boardroom
The Human Connectome Project’s multi-modal parcellation represents the most cyto-architecturally consistent, mapping of the cortical surface to-date. In this talk I will discuss the methodological advances that made this possible, before discussing the potential for modelling trends in behaviour, cognition and the development of disease from this data; finally presenting the challenges that must be overcome before we can predict these traits in individuals with high accuracy.