30th Jan: Thilo Gross
Room: SM3 (Mathematics)
Criticality as an ingredient for Information Processing (not just in the Brain)
Consider a computer. At its core we find a microprocessor that is essentially a complex circuit of semiconductor elements. If I took some hundred billion of these element and linked them up randomly, would I get a usable computer? The answer is no. What if I took an equal number of neural cells and wired them up randomly, would I get a functional brain? Again, the answer is no.However, comparing the two systems it is striking that for the neural cells it is much less important that I get the connectivity, right. To build a functional microprocessor, every element needs to be connected with with a precisely prescribed set of other elements. One wrong connection can ruin everything. By contrast, even the random-neuron-network can already show brain-like dynamics and our own brains remain functional while undergoing changes to their connectivity in the course of development and aging. So unlike the computer, the brain does not rely on some carefully designed and hard-wired microscopic connectivity. Instead it is, within reason, able to do its job regardless of the underlying configuration. One can therefore ask, what is the common property of these configurations that allow information processing to take place?
In this talk I focus on criticality, a concept from physics, that is a necessary ingredient for all information processing. I will show that the hallmarks of criticality are found not only in neural recordings, but also in other systems such as insect swarms and fish schools that need to process information collectively. From the perspective of neuroscience recognizing the necessity for criticality may lead to a new way of looking at data and to new diagnostic tools.
6th Feb: Bob Merrison-Hort
Room: SM3 (Mathematics)
Using a computational model to understand swimming and synchrony in the Xenopus tadpole spinal cord
Experimental recordings demonstrate that in addition to alternating left/right “swimming” patterns, the hindbrain/spinal cord of immobilised Xenopus tadpoles can also generate transient bouts of synchrony. During these synchrony bouts, central pattern generator (CPG) neurons on both sides of the body fire in-phase at approximately double the frequency of swimming. Investigating hypotheses about the neuronal mechanism underlying synchrony is difficult in real animals, so we instead use a large-scale computational model of the spinal cord. This “virtual spinal cord” combines synaptic connectivity obtained from a model of axon growth with a physiological model of neuronal activity based on the Hodgkin-Huxley equations. Under normal circumstances, the model produces stable realistic swimming behaviour in response to simulated touch input. However, by applying a suitable perturbation during swimming we found that the model could temporarily switch to a synchronous mode of firing, similar to that seen in experimental recordings. Normally the synchrony regime appears to be unstable, but we found that small increases in the commissural axonal delay stabilises synchrony, and can produce behaviour that is tri-stable between quiescence, swimming and synchrony. These results suggest that the system is close to a bifurcation. I will discuss the possible biological significance of this, and present preliminary results from computational experiments that attempt to use a reduced model to analyse the behaviour of the system more formally.
13th Feb: Garrett Greene
Room: SM3 (Mathematics)
Stabilising the World: Using retinal non-linearities to stabilise visual percepts.
Fixational Eye Movements are unconscious, involuntary and unpredictable eye movements, which continually shift our gaze even during attempted fixation (holding the gaze steady). These movements cause continual motion of the visual image on the retina, leading to an ambiguity between real-world motion and eye motion. Despite this, our perception of the visual world is stable, and these eye movements are rarely – if ever – perceived. Hence there must exist a mechanism to stabilise the visual image, and distinguish visual motion in the outside world from that caused by FEM.
I present a model for such a mechanism which takes advantage of the non-linear response of certain types of retinal ganglion cells which are ubiquitous in the mammalian retina. This model allows for the correction of motion percepts under FEM, without the need for explicit eye movement information. Furthermore, the model offers an explanation for a set of well-known visual illusions, which can be understood as failure modes of this correction mechanism.
20th Feb: Mark Rogers
Room: C44 (Medical Sciences)
Generation and Analysis of Next-Generation Sequencing Data
Deep transcriptome sequencing with next-generation sequencing technologies is providing unprecedented opportunities for researchers to probe the transcriptomes of many species. Two important goals in these studies are (a) to predict changes in gene expression between different conditions and (b) to assess the extent of alternative splicing, a process that increases transcriptome and proteome diversity, and plays a key role in regulating gene expression and protein function.
A number of tools have been developed that can make these predictions automatically, but the old adage “garbage in, garbage out” still applies. Hence to make accurate predictions, one should understand the methods used to obtain data, the limitations of sequence alignment tools, and aspects of experimental design that will have the biggest impact on statistical power.
27th Feb: Ullrich Bartsch
Room: SM3 (Mathematics)
Macro and microstructure of sleep in health and disease
Sleep is a process that exhibits complex dynamics on multiple time scales. There are lifelong changes in sleep patterns (napping in young and old ages), diurnal rhythms of sleep and wake and distinct patterns of sleep stages during the night. Moreover, one can describe sleep on a micro scale where prominent oscillations during specific sleep stages occur and synchronise with millisecond precision.
The observation of these dynamics through methods such as actigraphy and electrophysiology allows a detailed characterisation of sleep dynamics. This may in turn inform models of underlying neuronal processes with potential applications in preclinical and clinical research. Indeed, various psychiatric diseases, such as schizophrenia, depression and Alzheimer’s are associated with dramatic changes in sleep patterns, yet little is known about how much abnormal sleep contributes to symptoms experienced by patients. More recently, sleeps role in overnight memory consolidation has been emphasized which suggest sleep disturbances as a candidate mechanism for cognitive symptoms in psychiatry.
I will present some background on how sleep could be viewed from a dynamical systems perspective and how this could benefit the analysis of preclinical and clinical sleep data. I will show some preliminary analysis on global brain states defined as spectral clusters during sleep in an animal model of schizophrenia. I will also present some recent analysis describing the coordination of sleep oscillations during NREM sleep in patients diagnosed with schizophrenia, and how the microstructure of sleep reveals changes in network connectivity related to overnight memory consolidation.
6th March: Helen Scott
Room: SM3 (Mathematics)
A high content imaging siRNA screen for novel modulators of mitophagy
The selective autophagic removal of damaged mitochondria, known as mitophagy, has been implicated in numerous neurodegenerative diseases. Therefore elucidating the details of this process and its (mis)regulation may lead to therapeutic targets. An imaging based assay has been developed and used to screen a druggable genome siRNA library for novel genes involved in and / or regulating mitophagy. The presentation will focus on the methods used to extract quantitative data from the images and to reveal ‘hit’ genes.
13th March: Steve Coombes
Room: SM3 (Mathematics)
Next generation neural field models
I will introduce neural field models — that is, mathematical theories of brain dynamics in which the interaction of billions of neurons is treated as a continuum process. To date such models have had a major impact in understanding a variety of neural phenomena, including electroencephalogram rhythms, geometric visual hallucinations, mechanisms for short term memory, feature selectivity in the visual cortex, binocular rivalry, and anaesthesia. They have also found applications in autonomous robotic behaviour, embodied cognition, and dynamic causal modelling. Since their inception as integro-differential equations in the 1970s, by Wilson, Cowan, Nunez and Amari, solid mathematical progress has been made in understanding their behaviour. This has included the use of powerful tools from functional analysis and dynamical systems, including geometric singular perturbation analysis, Evans functions, numerical bifurcation techniques, and homogenisation theory. However, the pace of model evolution has been relatively slow and, from a biological point of view, modern day models are almost as minimal as their ancestors. I would like to discuss the development of next generation neural field models that will be more relevant to current challenges in neuroscience, such as large scale brain dynamics for neuroimaging, feature based computation for vision and motion, and solving spatial navigation problems via reward learning.
20th March: Lucia Marucci
Room: C44 (Medical Sciences)
Modelling and engineering dynamics of the Wnt pathway in mouse Embryonic Stem Cells
Complex non-linear dynamics have recently been reported as a signature of pluripotency: Embyonic Stem Cells (ESCs) and cells reprogrammed to a stem-like state (induced Pluripotent Stem Cells, iPSCs) show heterogeneous expression levels and temporal fluctuations of a number of genes. In this talk, I will focus on the dynamics of the Wnt/β-catenin pathway, highly implicated in both pluripotency and somatic cell reprogramming. A combined experimental and modelling approach revealed bistable or oscillatory dynamics of the pathway depending on the culture condition, with important biological implications. Also, I will suggest a synthetic biology strategy to engineer and control the mentioned dynamics in live cells.