PhD Proposal Exam
Tuesday, June 12, 2018 at 10:10am, MW 229- University of Toronto at Scarborough
Colleen Gillon (Richards Lab)
“How does the brain learn about the statistical structure of the environment?”
Over the past decade, artificial intelligence has progressed at great speed, with impressive breakthroughs in fields like computer vision and speech processing using neural network algorithms. These can be broadly divided into two classes: (1) discriminative models, like feedforward, convolutional and recurrent neural nets, which learn to map inputs, like images, to specific outputs, like categories or classes and (2) generative models, like bidirectional Helmholtz machines, generative-adversarial networks and expectation maximization models, which are learn the underlying joint structure of the data. Studies of visual processing in the cortex strongly suggest that in learning to process environmental stimuli, our brains behave like generative models, developing internal models of the joint distribution over sensory stimuli in the environment. Thus, these algorithms could shed light on our brain’s remarkable ability to represent and process sensory information efficiently and accurately. We propose to investigate this by comparing how the brain and different algorithms trained on visual tasks process and adapt to major changes in the relationship between incoming visual stimuli and somatosensory or motor inputs. Specifically, we will record and analyse changes in the activity of layer 2/3 pyramidal neurons in primary visual cortex (V1) in response to a shift in the relationship between visual stimuli and sensory stimuli or motor commands. We predict that this shift will transiently increase activity in the apical dendrites, and alter the rate of apical trunk calcium spikes of these neurons while the system adapts. In parallel, we will train different generative algorithms on this same task, and analyze changes in network activity in order to identify those algorithms that show the greatest potential for explaining how our brains process sensory information.
PhD Exit Seminar
Monday, June 4, 2018 at 10:10am, Ramsay Wright Building, Room 432
Hiwote Belay (Sokolowski Lab)
“GENETIC VARIATION IN THE timeless GENE MEDIATES METABOLIC STATES OF Drosophila melanogaster IN RESPONSE TO PHOTOPERIOD”
Genetic variations in the circadian clock may regulate photoperiod-induced anticipatory metabolic adjustments that allow organisms to meet the changes in energetic demands associated with different seasons. Both mammalian and Drosophila studies have shown that perturbed circadian feeding rhythm and abberant light cycles result in disruptions in fat and glucose metabolism. In this thesis, Drosophila melanogaster was used to investigate the effect of genetic variation in the circadian system on the regulation of feeding and metabolic responses to photoperiod.
Here, we analyzed the metabolic responses of two naturally occurring variants of the Drosophila timeless (tim) gene to changes in photoperiod. We found that ls-tim variants, which are known to have attenuated light-sensitivity and are more responsive to diapause, display metabolic traits that are associated with enhanced energy stores and reduced energy expenditure in response to a short-day. Analysis of tim RNA levels in the fat body revealed that it is elevated in ls-tim in response to a short-day suggesting that altered regulation of the clock in the fat body of ls-tim may mediate these enhanced metabolic adjustments to short-day. To examine the role of the foraging gene as a mediator of metabolic outputs regulated by the clock, we analyzed the circadian feeding pattern of foraging variants. Genetic variation in the foraging gene, which encodes cGMP dependant protein kinase (PKG), is known to regulate feeding behavior and energy homeostasis in Drosophila. Our results suggest that foraging regulates the frequency and daily distribution of meals.
These findings demonstrate that genetic variations in the circadian system are important in mediating photoperiodic responses to feeding and metabolic state. Characterization of a role of genetic variations in clock genes on the regulation of feeding and metabolism by abberant light cycles is important in identifying candidate pathways involved in metabolic perturbations associated with shift-work and Seasonal Affective Disorder.
MSc Exit Seminar
Tuesday, May 29, 2018 at 2:10pm CCT -3000, University of Toronto at Mississauga
Delara Dadsepah (Levine Lab)
Anatomical and Behavioural Characterization of Dpr-Interacting Protein Beta in Drosophila melanogaster
The mammalian limbic system has many important biological functions. During development, the limbic-system associated membrane protein (LSAMP) plays a crucial role by ensuring proper neuronal connectivity within the system. Similarly, the LSAMP homologue in the Drosophila, the Dpr-interacting protein beta (DIP-β), is believed to assist in neuronal formation during the development of the fly central nervous system. Other data suggests that DIP-β even regulates social interactions. Researchers have only more recently begun investigating DIP-β however, and DIP-β remains to be extensively studied. Thus, the aim of this project was to fully characterize DIP-β expression in the brain and the behaviour of DIP-β mutants, to obtain a better understanding of DIP-β function. DIP-β’s predominant expression in the optic lobes and regions in the central brain, along with changes in behavioural rhythmicity observed in DIP-β mutants, suggests DIP-β may be associated with clock mechanisms.