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.
Designing novel imaging probes and methods for clinical fluorine-19 MRI cell tracking
10-11 am Friday 30th of June 2017, IoPPN boardroom
Aging under the Free Energy Principle
2:30-3:30pm Thursday 4th of May 2017, CNS 3.11A and B
Prediction and predictive codes are now ubiquitous computational viewpoints from which we may better understand neural circuit organization and signal transmission in the brain.
In this talk I will present a predictive view of changing brains, over lifespans, based on the Free Energy Principle, a theory of hierarchical empirical Bayesian inference in the brain (Friston 2013). This particular formulation of the Bayesian brain produces predictive coding schemes that have been used to inform the principles of perception, action and decision-making, accounting for how sensory information combines with our own prior beliefs about the world to shape brain activity and behavior. There are many ways that a brain could perform Bayesian inference and the hypothesized scheme under the Free Energy Principle in the perceptual domain posits a variational algorithm where posterior density estimation is recast as an optimization problem. In this guise the scheme becomes a predictive coding algorithm, with hierarchical structure and attribution of optimization dynamics to particular components of neuronal circuits.
In this talk I will present evidence from neuroimaging studies of brain circuits (using dynamic causal models) that age-related connectivity changes are commensurate with long-term Free-Energy minimization. I will present work from sensory learning, memory and decision making paradigms that show that the neurobiological implementations of prior beliefs grow stronger in older brains. I will explore how this relates to faster timescales of prediction in terms of electrophysiological correlates.
Unravel the heterogeneity and complexity of Alzheimer’s disease with the help of MRI
10:00-11:00 Friday 7th April 2017, IoPPN boardroom, Main Building
Considering fractal dimensionality as a measure of age-related differences in brain morphology
10:00-11:00 Friday 3rd February 2017, IoPPN boardroom, Main Building
Different measures of cortical morphology have been shown to index distinct aspects of inter-individual differences (e.g., volume, thickness, surface area, gyrification). Here I consider the additional measure of structural complexity, as quantified by fractal dimensionality. Using several open-access MRI datasets, providing a combined sample of over 1000 adults across the adult lifespan, I examined the relationship between each measure and age-related differences in brain morphology. In a separate set of analyses I further examined the test-retest reliability of each measure. When examining the relationship between brain morphology and inter-individual differences, it is important to consider the most appropriate measure. For instance, it has been established that age-related differences are reflected most in cortical thickness, rather than surface area or volume. Here I demonstrate that fractal dimensionality, which incorporates shape-related properties, to be a more sensitive measure of age-related differences in cortical and subcortical structures. Limitations of this fractal dimensionality measure will also be discussed.
A role for autism genes in the cerebellum
14:00-15:00 Tuesday 22nd November 2016, Seminar room 5, Main Building
I will present data from both a hypothesis-driven approach as well as from transcriptomic profiling of developing Purkinje cells that link specific autism genes to the developing cerebellum. I will also present a new method of differentiating cerebellar neurons from human induced pluripotent stem cells (iPSCs) that our group has established.
The Becker group is interested in elucidating the genetic and molecular mechanisms that underlie cerebellar development and that how impairment of these processes results in cerebellar diseases including autism spectrum disorder.
The coolest magnetometer is no longer the best one
10:00-11:00 Friday 18th November 2016, Seminar room 4, Main Building
Optically Pumped Magnetometers (OPMs) are small (~1cm3) and ultrasensitive devices which measure magnetic fields but do not require cryogenic cooling. They have recently become commercially available and can be placed directly and flexibly on the scalp, increasing sensitivity 5-10-fold relative to conventional Superconducting Quantum Interference Device (SQUID)-based MEG systems. The potential for these sensors to become wearable technology means that the range of possible experimental paradigms, as well as subject and patient groups, will be significantly broadened. I will cover the physical principles underlying their functionality, and discuss both simulation and ongoing empirical work as well as future applications and challenges in relation to their usefulness for basic and clinical MEG research.