Winter 2018

 
September, 21st – Mark Humphries (University of Nottingham)
 
3.34 Physics Building
 
The plasticity of population activity in prefrontal cortex is independent of learning
 
The prefrontal cortex is thought to represent our knowledge about what action is worth doing in which context. But we do not know how the activity of neurons in prefrontal cortex collectively changes when learning which actions are relevant. Here we show in a trial-and-error task that population activity in rat prefrontal cortex is persistently changing, irrespective of whether the animal shows evidence of learning. Only during overt learning of the correct action are the accompanying changes to population activity carried forward into sleep, suggesting a long-lasting form of neural plasticity. Our results suggest that representations of relevant actions in prefrontal cortex are acquired by reward imposing a direction onto ongoing population plasticity.

  
 September, 28th – Tom Baden (University of Sussex)
 
3.34 Physics Building
 
The Evolution of Function in the Brain: What can we learn from the vertebrate retina? 
 
Sighted animals use their eyes in vastly different ways, and therefore evolved a staggering array of visual specialisations to navigate their individual visuo-ecological niches. These specialisations are deeply rooted at every level of visual systems, from the optical properties of eye to functional and structural retuning of neuronal microcircuits in the retina and brain. Taking advantage of the exquisite experimental accessibility of the larval zebrafish visual system and drawing on available knowledge gathered in the retina of other species with different visuo-ecological demands, I will present our lab’s recent efforts to better understand how animals can retune their retinal circuits for efficient sensory processing. Focussing on colour vision, I will highlight how zebrafish use different circuit motifs in different parts of their eyes to simultaneously support differential visual requirements imposed by the need for feeding, predator avoidance and object recognition.
 
Key References
Zimmermann MJY*, Nevala NE*, Yoshimatsu T*, Osorio D, Nilsson DE, Berens P, Baden T § . 2018. Zebrafish differentially process colour across visual space to match natural scenes. Current Biology 28(1-15).
Franke K*, Berens P*, Schubert T, Bethge M, Euler T § , Baden T § . 2017. Inhibition decorrelates visual feature representations in the inner retina. Nature; doi: 10.1038/nature21394. link. 
 Baden T*, Berens *P, Franke K*, Roman Roson M, Bethge M, Euler T § . The functional diversity of mouse retinal ganglion cells. Nature. doi:10.1038/nature16468.

 
October, 5th – Demian Battaglia (University Aix-Marseille)
 
Physics 3.34
Perception, cognition and behavior rely on flexible communication between microcircuits in distinct cortical regions.
It has been proposed based on growing experimental evidence that changing patterns of oscillatory coherence support flexible information routing. The stochastic and transient nature of oscillations in vivo, however, is hard to reconcile with such a function.
Here, through a computational modelling approach, we add a new chapter to this debate between “oscillo-partisans” and “oscillo-skeptics”, by showing  that models of cortical circuits near the onset of oscillatory synchrony are well able to selectively route input signals despite the short duration of oscillatory bursts and their stochastic-like irregularity. In canonical multi-areal circuits, we find that gamma bursts spontaneously arise with matched timing and frequency and that they organise information flow by large-scale routing states. We thus hypothesise that a self-organized network-wide re-organization of routing could be induced by suitable weak control perturbations or minor modulations of background activity.
Information routing constitutes nevertheless just a component of neural information processing by neural circuits. Moving to the analysis of actual electrophysiological recordings in hippocampus, enthorinal cortex and prefrontal cortex of anaesthetised and sleeping rats, we investigate whether dynamic changes between oscillatory modes also affect ongoing computational manipulations of information within local circuits, beyond inter-circuit routing. Through an unsupervised algorithmic approach, we are able to identify a multiplicity of internal “computing micro-states”, characterized by the flexible recruitment of alternative hub neurons, transiently specialising in different primitive operations of information processing (buffering and funneling). We find that global oscillatory states have an impact on both the “dictionary” of available computing micro-states and on the “syntax” of their sequences, whose complexity is systematically boosted by e.g. the presence of theta oscillations vs slow-oscillation dominated states.

 



October, 19th – Ruth Betterton (University of Bordeaux)
 
Physics 3.34
 
A biophysical network model of CA3, hippocampus: functional architecture and learning induced changes
A key function of the brain is the storage and recall of information as memories. The hippocampus and specifically area CA3 are involved in the rapid encoding of short-term spatial, episodic, and contextual memory. A unique feature of the CA3 network is the presence of recurrent excitatory cell connectivity which has led to the theory that CA3 acts as an attractor or auto-associative network. It is thought that, during encoding of new memories connection weights between activated excitatory cells within CA3 are rapidly enhanced through Hebbian plasticity creating a micro-network of cells known as an assembly. The potentiated assembly provides an attractive candidate for the location of the neuronal ‘engram’ or cellular correlate of memory. Using a combination of mathematical modelling and in vitro slice recordings we are gathering evidence of this theory of the importance of recurrent connectivity in hippocampal function. Presented here is the development of a network model of biophysical, multi-compartmental neurons carried out in the simulation environment NEURON. The network includes many features of the in vivo CA3 region including specific inputs, recurrent connectivity and region specific plasticity rules.


November, 2nd – Gareth Barnes (UCL)
 
Physics 3.34
 
A new generation of MEG scanners
 
I will talk about collaborative work between University College London and the University of Nottingham to use optically pumped magnetometers (OPMs) for human brain imaging. These sensors have comparable sensitivity to current cryogenic devices but do not require cooling. This means that the sensor array can be worn (rather than climbed into) and the smaller separation between sensor and brain means optimal (and improved) signal to noise ratio in all subject cohorts. I will talk about our initial modelling and experimental work with these new sensors. One of the exciting advances has been to keep these arrays operational during head-movement through a static magnetic field. This has opened up many new clinical and neuroscientific possibilities and I will talk about some of our experiences with these new paradigms.
 

November, 9th – George Stothart (University of Bath)

Physics 3.34

Using Fast-Periodic-Visual-Stimulation to assess cognition in neurological disorders 

 Fast Periodic Visual Stimulation (FPVS) provides a new objective method for assessing an individual’s ability to discriminate between different categories of visual stimuli. Using a combination of steady state visual evoked potentials and oddball paradigms it has been demonstrated to be a powerful measure of visual discrimination in single subjects. Importantly what defines the visual categories can range from low-level perceptual properties to abstract cognitive properties. We have adapted this approach to examine a range of cognitive processes and will demonstrate that the technique can be used to assess the integrity of semantic categorisation, short term memory and visuo-spatial processing in single subjects in as little as 3 minutes EEG recording time. The implications for the objective assessment of cognition in dementia and the potential as an early diagnosis tool will be discussed.

researchportal.bath.ac.uk/en/persons/george-stothart

 


November, 23th – Jiaxiang Zhang (Cardiff University)
 
Physics 3.34
 

The neurocognitive mechanisms of voluntary decision  

We can voluntarily make decisions to fulfil our goals and desires, even when all the options are similar to each other. This talk will discuss our work on using brain imaging, electrophysiology and computational modelling to understand the cognitive processes underlying such voluntary decisions. First, I will present fMRI evidence that during voluntary decision, a decision network in the medial frontal cortex accumulates action intention until a threshold is reached. Second, the behavioural randomness in a sequence of decisions fluctuates over time and correlated with both fMRI and MEG activity in the frontopolar cortex. This suggests a cortical network sensitive to information regularities, which concurrently monitor the choice in voluntary decisions. Last, I will present recent results on how perceptual salience and action outcomes affect the behavioural, EEG, and metacognitive measures in voluntary decisions. Our results highlight the potential and challenges of establishing a neurobiological theory of voluntary behaviour in humans.

 

 
November, 30th –  Dimitrije Marković (TU Dresden)
Physics 3.34

Anticipating changes: decision-making with temporal expectations 

Being able to experience time and build temporal expectations about future events is essential for our everyday activities and survival. Despite the central role that time plays in our lives, the neuronal and computational mechanisms that link our experience of time with decision-making remain poorly understood. In this talk, I will focus on the computational underpinning of decision-making with temporal expectations and present a probabilistic behavioural model that enables a systematic investigation of the interplay between temporal expectations and behaviour. The central assumption here is that humans form prior beliefs about the temporal regularities of a dynamic environment; these beliefs shape both the inference and the planning process. Using a sequential reversal learning task, I will illustrate the key properties of the model and demonstrate how it can be applied to behavioural data to infer prior beliefs of participants and to investigate interindividual behavioural differences.

Summer 2018

May, 11th – Rafal Bogacz (University of Oxford)
 
Life Sciences G13

Title: Theory of reinforcement learning and motivation in the basal ganglia


This talk will suggest a simple mathematical description of how subcortical circuits in the basal ganglia select actions on the basis of past experience and the current motivational state. According to the presented theory, the basal ganglia evaluate the utility of considered actions by combining the positive consequences (e.g. nutrition) scaled by the motivational state (e.g. hunger) with the negative consequences (e.g. effort). The theory proposes how the basal ganglia compute utility by combining the positive and negative consequences encoded in the synaptic weights of striatal Go and No-Go neurons, and the motivational state carried by neuromodulators including dopamine. Furthermore, the theory suggests how the striatal neurons learn separately about payoffs and costs of actions. The model accounts for the effects of dopaminergic modulation on behaviour, and patterns of synaptic plasticity in striatum.
 https://www.ndcn.ox.ac.uk/team/rafal-bogacz

 

 


May, 18th –  Simon Thorpe ( CerCo UMR 5549, CNRS-UT3)

Priory Road Complex, Senior Common Room, Level 2 (2D17 )
How can the brain store sensory memories that can last a lifetime? I will argue that if neurones can be made so selective that they remain silent unless they are presented with something close to the original stimuli (effectively Grandmother cells), they can keep their selectivity for very long periods. This suggests that the long term memory store may consist of large numbers of silent neurones (neocortical dark matter). I will describe some recent research showing that both the visual and auditory systems can store long lasting sensory memories  with only a small number of repeats. We have also some suggestions for Spike-Time Dependent Plasticity Rules that are capable of allowing this sort of rapid sensory learning.

 

May, 25th – Katarina Kolaric (University of Bristol)

Life Sciences G13
Title: The role of mossy cells in regulating the local dentate gyrus circuit and pattern separation 

The function of mossy cells in the dentate gyrus of the hippocampus, and their role in pattern separation memory, is still largely unknown. In this talk, I will present my PhD work, which investigated the role of mossy cells in the local dentate gyrus circuit using immunohistochemistry, in vitro electrophysiology and computational modelling techniques. Moreover, I will discuss how mossy cells are implicated in pattern separation memory by presenting behavioural data from a transgenic mouse model that specifically lack mossy cells. Finally, I will give a brief overview of my current work at the Integrative Epidemiology Unit (IEU), where I use Mendelian Randomisation as a method to detect potential risk factors in the human population for cognitive decline and Alzheimer’s Disease. 

  


June, 1st – Robert Schmidt  (University of Sheffield)
G13 Life Sciences
     
 Title: Basal ganglia transmission of motor signals to the thalamus: effect of correlations and sensory responses:      

One prominent feature of Parkinson’s disease is the emergence of correlated activity in basal ganglia output neurons. In contrast, in healthy animals, the activity in basal ganglia output regions is usually uncorrelated, potentially due to “active decorrelation”. We investigated the effect of correlations among basal ganglia output neurons on the transmission of motor signals via rebound spikes in a Hodgkin-Huxley model of a thalamocortical neuron. We found that correlations in the basal ganglia output decrease the signal-to-noise ratio in the transmission of motor signals to the thalamus, potentially related to the emergence of motor symptoms in Parkinson’s disease. In addition, our model indicates that thalamocortical neurons may be a key site for the integration of sensory and motor signals.


June, 8th – Adam Packer (University of Oxford)

G13 Life Sciences
 
Title: Technologies for all-optical interrogation of neural circuits in behaving animals

Neural circuits display complex spatiotemporal patterns of activity on the millisecond timescale during behavior. Understanding how these activity patterns drive behavior is a fundamental problem in neuroscience, and remains a major challenge due to the complexity of their spatiotemporal dynamics. The ability to manipulate activity in genetically defined sets of neurons on the millisecond timescale using optogenetics has provided a powerful new tool for making causal links between neuronal activity and behavior. I will discuss novel approaches that combine simultaneous two-photon calcium imaging and two-photon targeted optogenetic photostimulation with the use of a spatial light modulator (SLM) to provide ‘all-optical’ readout and manipulation of the same neurons in vivo. This approach enables reading and writing of activity in neural circuits with single-cell resolution and single action potential precision during behavior. I will describe the power, limitations and future potential of this approach; and discuss how it can be used to address many important problems in neuroscience, including transforming our search for the neural code and the links between neural circuit activity and behavior.


June, 15th – Tamar Makin (University of Oxford)

1.58 Queens Building

Title: From phantoms to artificial limbs
In this seminar I will present recent results and ideas about how the brain adapts to extreme changes in resources, due to hand loss and the need to pick up adaptive behavioural strategies. I will explore the neural correlates of a range of “alternative hands”, including phantom hands, extraordinarily dexterous foot usage, and artificial limbs. Based on these findings I will challenge some of the basic textbook assumptions about the triggers and barriers of brain plasticity, and suggest alternative frameworks, with reference to recent BMI developments.

Spring 2018

January 12th – Matt Jones (University of Bristol)

E204, Chemistry

Working memory: some stuff on my mind

Working memory (WM) reflects the temporary storage and manipulation of information pertinent to online behaviour. Sustained activity in recurrently interconnected prefrontal cortical neurons is commonly credited as central to WM. However, recent recordings of prefrontal neural dynamics portray an increasingly complex picture involving mixed selectivity, trajectories through state space, spectral signatures and other daunting words.

Could implanting arrays of microelectrodes and optrodes into and around rat prefrontal cortex help? Maybe – I will try to set some Jones Lab findings in the context of this knotty neurodynamical nebula.

http://www.bristol.ac.uk/phys-pharm/people/matt-w-jones/index.html


January 19th – Giovanni Diana (King’s College London)

E204, Chemistry

Inference of functional subtypes and spontaneous neuronal assemblies in the zebrafish optic tectum

Understanding the functional diversity of the nervous system is one of the most prominent questions in neuroscience. Neurons are often classified based on their tuning curves under selected stimuli, however describing how neural computation is orchestrated within a complex network requires a paradigm shift from single neurons to neuronal ensembles emerging in the brain. By applying functional imaging of calcium activity in the zebrafish optic tectum we could address these questions directly. In the presence of visual stimulation we identified neuronal sub-types involved in prey-capture and escape response. In the absence of visual input, tectal neurons display synchronous activity events. We will discuss the inference methodologies that can be reliably employed to detect these spontaneous ensembles as well as the clustering techniques used to classify evoked responses.

https://devneuro.org/cdn/people-detail.php?personID=1387


January 26th – Rasmus Petersen (University of Manchester)

SM3, Maths

Sensation and locomotion in behaving mice: Investigation using ‘Neuropixel’ probes

Despite the fact that almost all regions of the brain are richly interconnected, the standardview of sensory processing is that the subcortical, ascending sensory pathway simply encodes sensory stimuli and relays them onto the cerebral cortex. However, this view is derived from experiments on anaesthetised animals where motor and cognitive circuits are disengaged, and sensation can only be studied in a reduced, passive form. Using the whisker system as a model, we have developed a paradigm for studying active sensation in behaving mice that permits us to record the activity of neurons at the same time as measuring the mechanical input to the whiskers. In our most recent work, in collaboration with Karel Svoboda, we have used high-density Neuropixel silicon probes to record the spiking activity of neurons across >10 brain regions (including Ventro Posterior Medial thalamus, Posterior Medial thalamus and ZonaIncerta) whilst at the same time measuring sensory input to the whiskers and locomotor velocity. Surprisingly, even in relay nuclei conventionally considered simply to be sensory relays, we observed modulation of neural activity by locomotion velocity. Indeed, we observed such modulation in all recorded areas, including the hippocampal formation. Our data suggest that sensory processing, right from the earliest stages of the Central Nervous System, is substantially dependent on motor control context.

https://www.research.manchester.ac.uk/portal/en/researchers/rasmus-petersen(a96ce8ab-ae04-401d-844b-82fed7bbbc0e).html


February 2nd – Melanie Stefan (Edinburgh Medical School)

SM3, Maths

It’s not what it looks like: Counter-intuitive effects in synaptic biochemistry

A lot of what we know about Biochemistry comes from tightly controlled experiments with large numbers of molecules in well-mixed test-tubes. Real biological systems such as dendritic spines are often very different from that: Absolute numbers of any one molecular species can be very small, their spatial distribution is often highly non-uniform, and they compete for ligands that are in short supply. This can give rise to behaviours that are difficult to predict and often counter-intuitive. In such cases, computational modelling can uncover and explain system behaviours that are otherwise difficult to understand. In this seminar, I will talk about a few examples from our past and ongoing research on Calcium-regulated synaptic proteins.

http://melaniestefan.net/


February 9th – Nelson Totah (Max Planck Institute)

E204, Chemistry

The locus coeruleus is a complex and differentiated neuromodulatory system

Understanding forebrain neuromodulation by the noradrenergic locus coeruleus (LC) is fundamental for cognitive and systems neuroscience. The diffuse projections of individual LC neurons and their presumably synchronous spiking have long been perceived as features of the global nature of noradrenergic neuromodulation. Yet, the commonly referenced “synchrony” underlying global neuromodulation, has never been assessed in a large population, nor has it been related to projection target specificity. We recorded up to 52 single units simultaneously (3164 unit pairs in total) in rat LC and characterized projections by stimulating 15 forebrain sites. Spike count correlations were low and, surprisingly, only 13% of pairwise spike trains had synchronized spontaneous discharge. Notably, even noxious sensory stimulation did not activate the entire population. We also identified a novel firing pattern: infra-slow (0.01-1 Hz) fluctuations of LC unit spiking, which were also asynchronous across the population. A minority of LC neurons, synchronized possibly by gap junctions, was biased toward restricted (non-global) forebrain projection patterns. Finally, we characterized two types of LC single units differing by waveform shape, propensity for synchronization, and interactions with cortex. These cell types formed finely-structured ensembles. Our findings suggest that the LC conveys a highly complex, differentiated, and potentially target-specific neuromodulatory signal.

http://www.kyb.tuebingen.mpg.de/nc/employee/details/ntotah.html


February 16th – John Grogan (University of Bristol)

SM3, Maths

Dopamine and Parkinson’s disease’s effects on working memory: behaviour, pharmacology and genetics

Parkinson’s disease (PD) causes cognitive as well as motor impairments, some of which are improved by the dopaminergic medication prescribed for motor symptoms, while others are exacerbated by it. Working memory (WM) is one such function that shows both improvements and impairments caused by dopaminergic medication in healthy people and people with PD.

We have run several studies into different aspects of WM: using the digit span in PD patients and healthy older adults given levodopa; examining the influence of genetic polymorphisms in dopamine-related genes on digit span and n-back tasks; and looking at how dopaminergic medication affects spatial WM in PD patients. We use a simple model to analyse the spatial WM task which allows us to separate different sources of errors in participants’ responses, so we can examine the precision of memory, and the mis-binding of items and locations.

These diverse approaches allow us to combine large-sample, high-powered analyses with smaller more sensitive tasks to zero in on the range of WM deficits caused by PD, and how dopamine affects these deficits. This can help us understand dopamine’s function in WM in healthy brains.

http://www.bris.ac.uk/clinical-sciences/people/john-p-grogan/index.html


February 23rd – Friedemann Zenke (University of Oxford)

E204, Chemistry

Making Cell Assemblies: What can we learn about plasticity from spiking neural network models?

Long-term synaptic changes are thought to underlie learning and memory. Hebbian plasticity and homeostatic plasticity work in concert to combine neurons into functional cell assemblies. This is the story you know. In this talk, I will tell a different tale. In the first part, starting from the iconic notion of the Hebbian cell assembly, I will show the difficulties that synaptic plasticity has to overcome to form and maintain memories stored as cell assemblies in a network model of spiking neurons. Teetering on the brink of disaster, a diversity of synaptic plasticity mechanisms must work in symphony to avoid exploding network activity and catastrophic memory loss – in order to fulfill our preconception of how memories are formed and maintained in biological neural networks. I will introduce the notion of Rapid Compensatory Processes, explain why they have to work on shorter timescales than currently known forms of homeostatic plasticity, and motivate why it is useful to derive synaptic learning rules from a cost function approach. Cost functions will also serve as the motivation for the second part of my talk in which I will focus on the issue of spatial credit assignment. Plastic synapses encounter this issue when they are part of a network in which information is processed sequentially over several layers. I will introduce several recent conceptual advances in the field that have lead to algorithms which can train spiking neural network models capable of solving complex tasks. Finally, I will show that such algorithms can be mapped to voltage-dependent three-factor Hebbian plasticity rules and discuss their biological plausibility.

https://fzenke.net/


March 2nd – Mark Olenik (University of Bristol)

SM3, Maths

Modelling struggling tadpoles: Interactions of strong and weak synaptic coupling for burst rhythm generation

Xenopus hatchling tadpoles “struggle” when held at their tail, rhythmically bending their body in an attempt to free themselves. During struggling, neurons on opposite sides of the tadpole spinal cord fire bursts of spikes in alternation, resulting in motor activity and the rhythmic bends of the whole body. A central question of interest in tadpole struggling is the role of the excitatory and inhibitory coupling for the rhythm generation. In this talk we will therefore study a reduced biophysical model of tadpole struggling that contains weakly excitatory neurons and strongly inhibitory neurons, where the latter are also subject to short-term synaptic depression. We will discuss approaches to understanding the dynamics of such a network, focusing on reducing the complex model equations to a more tractable, and intuitive, quantity. For the reduction we will employ two useful mathematical techniques: geometric singular perturbation theory and phase response curves.

http://www.bristol.ac.uk/biology/people/mark-olenik/index.html


March 9th – Ramin Azodi Avval (University of Tübingen)

E204, Chemistry

Characterization of cortico-subthalamic networks during deep brain stimulation surgery in Parkinson’s disease

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a well-established symptomatic treatment for Parkinson’s diseases (PD). However, knowledge on local electrophysiological biomarkers within the STN and their cortical connectivity profile is still scarce. Such information would be necessary for optimal positioning of the DBS leads based on PD network pathophysiology. This talk describes the introduction and exploration of a novel technique for electrophysiological measurements during DBS surgery. Combined electroencephalography (EEG) with stepwise local field potentials recordings during insertion of the DBS lead was performed intraoperatively, thereby, allowing to capture local STN and cortico-subthalamic physiology with high speactral and spatial specificity. Our results revealed that strong beta oscillatory activity in the STN was located more dorsally than the STN-ipsilateral motor network phase coupling; the respective frequency bands were in the low and high beta-band, respectively. Moreover, the spot within the STN, where this STN-cortical phase coupling occurred, correlated highly with the STN spot where the phase of beta oscillations modulated the amplitude of high-frequency oscillations. This STN location was furthermore, characterized by information flowed from the ipsilateral motor cortex to the STN in the high beta-band suggesting a pathologically synchronized network with a direct STN-motor cortex connection via the hyperdirect pathway. Interestingly, the very same STN spot showed a resonance like responses to electrical stimulation suggesting a decoupling of pathologically synchronized STN-motor cortex connectivity during therapeutic DBS. In conclusion, we provide first evidence that macroelectrode recordings with the chronic electrode concurrent with EEG recordings are a reliable method for STN localization during DBS surgery. Additionally, combining LFP and EEG recordings during mapping of STN offered a new way of DBS targeting on the basis of pathological local biomarkers and network activity.

http://razodia.com/


March 16th – Tara Keck (UCL)

SM3, Maths

Interactions between different Hebbian and homeostatic plasticity

Homeostatic plasticity is thought to be mediated by mechanistic changes, such as synaptic scaling and shifts in the excitation/inhibition balance. These mechanisms are thought to be distinct from the Bienenstock, Cooper, Munro (BCM) learning rule, where the threshold for the induction of long-term potentiation and long-term depression slides in response to changes in activity levels; however, both mechanisms produce a homeostatic response of a relative increase (or decrease) in strength of excitatory synapses in response to overall activity-level changes. I will present a model that suggests how these two mechanisms may interact to facilitate firing-rate homeostasis, while maintaining functional properties of neurons.

http://www.kecklab.com/


March 23rd – Petroula Laiou (University of Exeter)

E204, Chemistry

Evaluation of epilepsy surgery using mathematical modelling

Surgery is one option for treating pharmacoresistant epilepsy patients. In this treatment, brain tissue is resected to render a patient free from seizures. However, epilepsy surgery is often ineffective. A basic reason for this is our insufficient understanding of the generation of seizures in the brain network. Mathematical modelling can be used to study normal and abnormal dynamical states of the brain. Moreover, it can elucidate the effects of brain surgery by quantifying the contribution of different brain regions (nodes in the brain network) to the generation of seizures. In this talk, I will present a mathematical framework which aims to identify the optimal set of nodes that has to be removed from a brain network in order to obtain seizure-free patients. The ultimate goal of this approach is to provide a support tool for epilepsy surgery to help in the presurgical evaluation.

http://emps.exeter.ac.uk/mathematics/staff/pl380


April 27th – Mark Olenik (University of Bristol)
W415, Chemistry
Modelling struggling tadpoles: Interactions of strong and weak synaptic coupling for burst rhythm generation
Xenopus hatchling tadpoles “struggle” when held at their tail, rhythmically bending their body in an attempt to free themselves. During struggling, neurons on opposite sides of the tadpole spinal cord fire bursts of spikes in alternation, resulting in motor activity and the rhythmic bends of the whole body. A central question of interest in tadpole struggling is the role of the excitatory and inhibitory coupling for the rhythm generation. In this talk we will therefore study a reduced biophysical model of tadpole struggling that contains weakly excitatory neurons and strongly inhibitory neurons, where the latter are also subject to short-term synaptic depression. We will discuss approaches to understanding the dynamics of such a network, focusing on reducing the complex model equations to a more tractable, and intuitive, quantity. For the reduction we will employ two useful mathematical techniques: geometric singular perturbation theory and phase response curves.

Autumn 2017

September 22nd – Antonis Asiminas (University of Edinburgh)

SM4, Maths

Sustained correction of associative learning deficits following brief, early treatment in a rat model of Fragile X Syndrome.’ Fragile X Syndrome (FXS) is a major heritable cause of intellectual disability and autism. Despite the early emergence of symptoms associated with FXS, it is still not clear whether treatments restricted to early development of brain circuits can permanently prevent impairments in cognitive function. In the work I’ll present, we examine the developmental trajectory of learning and memory in a rat model of FXS using spontaneous object exploration tasks and tested whether temporary early intervention can prevent the emergence of cognitive deficits later in life.

http://www.ccns.ed.ac.uk/People/Postdocs/asiminas.html


September 29th – Ole Jensen (University of Birmingham)

SM3, Maths

Hunting For Phase Coding

In 1993 O’Keefe and Recce demonstrated that hippocampal place cells fire in phase specific manner with respect to ongoing theta oscillations. This suggests that slower oscillations serve to organize a code in which individual objects are activated as a sequence within a cycle. I will discuss the functional consequences of this phenomenon and to what extend the principle generalized to other rhythms such as human alpha oscillations.

Suggested readings:

Jensen, O., Gips, B., Bergmann, T.O. and Bonnefond, M. (2014) Temporal coding organized by coupled alpha and gamma oscillations prioritize visual processing. Trends in Neurosciences
Lisman, J.E. and Jensen, O. (2013) The theta-gamma neural code. Neuron 77:1002-1016

http://www.birmingham.ac.uk/schools/psychology/people/profile.aspx?ReferenceId=125382


October 20th – Lisa Genzel (Donders Institute)

Sleep for systems consolidation

Distinct forms of memory consolidation (cellular and systems) influence the persistence of spatial memory within the hippocampus (cellular) and following hippocampal-neocortical interactions (systems). Factors influencing these processes include: (1) novelty exposure that enhances the persistence of hippocampal traces via neuromodulation; and (2) sleep that aids systems consolidation and thus cortical memory. In a sequence of experiments, we could show that sleep leads to systems consolidation via learning-dependent cortical consolidation. In contrast, novelty tags a memory to remain more hippocampal by increasing gene expression. Further, I will show evidence that different behaviour such as novelty and normal learning influence hippocampal-cortical communication during subsequent sleep and such behaviours after learning influence the behavioural expression of memory.

http://www.ru.nl/excellence/laureates-0/current-members-0/current-members/dr-lisa-genzel/


October 27th – Pooran Dewari (University of Edinburgh)

LT1, 43 Woodland Road

An efficient and scalable CRISPR/Cas9 pipeline for epitope tagging in mammalian stem cells

CRISPR-Cas9 technology has revolutionized genome editing at an unprecedented scale across multiple organisms and cell types. Knock-in of small epitope tags into endogenous genes simplifies antibody-based assays, overcoming issues of specificity and sensitivity. We have developed a highly efficient and scalable Cas9 ribonucleoprotein(RNP)-assisted method for epitope tagging in mouse and human primary neural stem (NS) cells and glioblastoma tumour-derived cultures. Delivery of RNP complexes containing synthetic dual-guide RNA (crRNA 36-mer and tracrRNAs 67-mer) facilitates efficient knock-in of V5 tag (5-30%) in mouse NS cells without requirements for any selection strategy. Similar efficiencies were achieved in human NS and glioma stem cells. Importantly, with these optimized conditions and a newly developed web-based tool for crRNA and donor DNA design, we were able to demonstrate medium-throughput epitope tagging in a 96-well plate format. 192 transcription factors (key regulators of neural stem cell self-renewal and differentiation) were tested for tagging in parallel, and 60 of these were effectively tagged with V5. Our method provides a step-change in our ability to interrogate mammalian proteins in stem cells and their glioma counterparts. As a proof-of –principle, we used the newly tagged Sox2-V5 glioma cell lines and performed ChIP-SICAP (selective isolation of chromatin associated proteins) to identify on-chromatin partners of Sox2 transcription factor. In summary, we have developed a highly efficient and scalable pipeline for tagging of endogenous proteins in mouse and human neural and glioma stem cells using off-the-shelf reagents. Our method will enable elucidation of the subcellular localisation and interaction partners for a multitude of mouse and human proteins.

http://www.crm.ed.ac.uk/people/pooran-dewari


November 3rd – James Rankin (University of Exeter)

Dynamics of visual and auditory perception

Ambiguous sensory stimuli provide a unique opportunity to characterize intrinsic neural dynamics of cortical processing. The perceptual interpretation of fixed sensory stimuli can switch spontaneously due to ambiguity, so-called perceptual bistability. Common examples discussed here include binocular rivalry, ambiguous motion and the auditory streaming paradigm. Dynamical systems modelling has helped to reveal the common computational mechanisms behind perceptual bistability. A canonical model that incorporates three competition mechanisms (mutual inhibition, slow adaptation and noise) is adapated to investigate processing across the different sensory modalities. The work helps to reveal the mechanisms behind attention, the role of contrast for visual stimuli and how sudden stimulus changes can drive perceptual switching.

http://emps.exeter.ac.uk/mathematics/staff/jar226


November 10th – Nicholas Robinson (UCL)

LT1, 43 Woodland Road

Hippocampal-Medial Entorhinal Interactions Underlying Memory Encoding and the All-Optical Interrogation of Hippocampal Function

The talk will initially cover work looking at the importance of medial entorhinal cortex activity for the expression of hippocampal neural correlates during epochs of spatial, temporal and object based experience, and the importance of this coding for on going memory performance. The study utilized large scale optogenetic inactivation while simultaneously performing tetrode recordings in animals performing an object-delay-response association task. It will then move onto current work using ‘all-optical physiology’, the 2-photon calcium imaging of the activity of a large population of neurons while using a second light path to provide cellular resolution optogenetic control of a chosen subset of the same population. This allows the manipulation of a functionally defined population of neurons rather than relying on genetic targeting. The technique is being applied to determine the link between specific place field firing, memory and behaviour.

https://iris.ucl.ac.uk/iris/browse/profile?upi=ROBIN13


November 17th – Stuart Allan (University of Manchester)

AIMS 2A/B

Inflammation and stroke: contributions across the whole patient journey, from risk to recovery

Stroke is a leading cause of death and disability yet there are few effective therapeutic interventions. It is now well recognised that inflammation is a key aspect of the different risk factors for stroke and also contributes to the acute injury. In addition inflammation likely plays an important role in the resolution of ischaemic injury and in the repair and recovery processes in the damaged brain. The pro-inflammatory cytokine interleukin-1 is a key mediator of sterile inflammation and there is a substantial body of evidence to suggest it may be an effective therapeutic target. In this seminar these different aspects of the role of inflammation in stroke will be discussed.

https://www.research.manchester.ac.uk/portal/stuart.allan.html


November 24th – Michael Kohl (University of Oxford)

LT1, 43 Woodland Road

Roles of hippocampus, retrosplenial cortex, and neocortex in learning and memory in mice – from synapse to behaviour

We identified a left-right dissociation of synaptic plasticity in the mouse hippocampus. To investigate possible effects on behaviour, we used optogenetics to unilaterally silence hippocampal CA3 pyramidal cells in mice performing hippocampus-dependent memory tasks. Whilst silencing of either the left or the right CA3 caused a short-term memory deficit, strikingly, only left CA3 silencing impaired long-term memory. Our data suggests that memory is routed via distinct left-right pathways within the mouse hippocampus. We are currently investigating whether this hemispheric specialisation extends to neocortical structures involved in associative memory. Recent data implicates the retrosplenial cortex in sensory preconditioning, a form of associative learning, and suggests that retrosplenial cortex aids learning in the neocortex by providing top-down inputs to primary sensory cortex.

https://www.neuroscience.ox.ac.uk/research-directory/michael-kohl


December 8th – Andrew Jarman (University of Edinburgh)

LT1, 43 Woodland Road

Mechanotransduction mechanisms in Drosophila mechanosensory neurons

We are interested in both the development and the physiology of mechanosensory neurons, primarily in Drosophila. In this presentation I will concentrate on physiology. I will initially talk about our attempts to define the mechanotransduction process in poorly studied larval stretch receptors that resemble mammalian muscle spindles. This will include some basic modelling, as well as electrophysiology and optogenetics. As time allows, I will also discuss a different class of mechanosensory neuron, required for hearing and proprioception. These neurons appear to generate active movements in response to sound (analogous to the movements of our inner ear hair cells that form the ‘cochlear amplifier’). I will discuss the possible molecular basis of this process.

https://www.ed.ac.uk/integrative-physiology/staff-profiles/research-groups/andrew-jarman


December 15th – Jess Gaunt (University of Bristol)

LT1, 43 Woodland Road

Exploring changes in the CA1 translatome during associative recognition memory formation
Gene expression is required for long term changes at the synapse underlying memory formation. Messenger RNAs undergoing translation into protein in specific cell types can be profiled using Translating Ribosome Affinity Purification (TRAP; Heiman et al, 2008; Doyle et al, 2008). Profiling the translatome instead of the transcriptome (as in standard RNAseq experiments) enables protein abundance to be estimated more accurately, has greater temporal specificity, and is sensitive to changes in both transcription and translation.
To investigate genome-wide gene expression in rats during associative recognition memory formation, a novel TRAP virus was targeted to neurons in CA1 of the hippocampus using intracerebral injections and combined with Next Generation Sequencing (NGS) andPaired Viewing (PV), a within-subjects paradigm to induce differential gene expression in CA1 when novel and familiar configurations of stimuli are presented (Wan et al, 1999). Leveraging recent developments in bioinformatics, changes in the translatome in the hours following PV were investigated. This talk will discuss making reliable inferences from multi-factor NGS data and interesting features of this complex dataset.

Summer 2017

May 19th – Jonathan Hanley (University of Bristol)

F40, Biomedical Sciences Building

Tuning trafficking and translation with dynamic protein interactions

Synaptic plasticity involves numerous changes to the molecular machinery at synapses. These include alterations in the number and subtype of AMPA receptors expressed at synapses by regulated trafficking, changes in dendritic spine morphology, and modulation of local protein synthesis by fine-tuning translation in dendrites. Dynamic protein-protein interactions are essential components of all of these processes.

In this presentation, I’ll aim to discuss our recent work on how specific protein interactions are regulated in response to the induction of synaptic plasticity to bring about changes in AMPAR trafficking and microRNA-mediated translational repression.

http://www.bris.ac.uk/biochemistry/people/jonathan-g-hanley/research.html


June 2nd – Neil Marrion (University of Bristol)

F40, Biomedical Sciences Building

How does Glutamate leave a vesicle?

The release of neurotransmitter is fundamental to communication between cells.  The excitatory neurotransmitter that mediates rapid transmission in our brains is glutamate.  The synaptic delay between presynaptic activation and the appearance of the postsynaptic response is only 200 μs, so any release mechanism has to be fast.  The standard release mechanism for vesicular glutamate is by ‘full fusion’, a process where the vesicle incorporates fully into the terminal membrane to dump its contents into the synaptic cleft.  This is energetically not favourable and an alternative release mechanism was identified to challenge this.  This alternative mechanism is termed ‘kiss-and-run’, where the vesicle remains intact and simply releases its contents into the synaptic cleft via a narrow pore.  This talk will present a hypothesis and data that support the proposal that ‘kiss-and-run’ exocytosis occurs in the mammalian brain and is the dominant mechanism for glutamate release.

http://www.bristol.ac.uk/phys-pharm/people/neil-v-marrion/index.html


June 9th – Chris Miall (University of Birmingham)

SM3, Maths

The cerebellum as a flexible predictor for motor control and for cognition

The talk will describe my team’s research showing that the cerebellum has an important role in predicting the sensory consequences of actions, a role evidenced by behavioural tasks, by electrophysiology, by interventions including brain stimulation and lesions, and by functional imaging. We have recently explored how these theoretical ideas can be extended to cognitive domains, and I will argue that the human cerebellum is involved in predictive language processing, and may be a general purpose predictor support all cognitive functions.

http://www.birmingham.ac.uk/schools/psychology/people/profile.aspx?ReferenceId=14488


June 30th – Claire Hales (University of Bristol)

SM3, Maths

Diffusion modelling of ambiguous decision making in rodents

Affective states alter cognitive processes. The measurable consequences of these alterations are referred to as affective biases. In both humans and animals, decision making about ambiguous cues is modified by changes in affective state. This is known as judgement or interpretation bias, and can be measured in rodents using a two-choice ambiguous cue interpretation task. In order to further investigate the decision making processes that underlie judgement biases measured in this task, I apply the Ratcliff diffusion model to rodent behavioural data. I will present results showing how ambiguous cue interpretation is altered by variety of affective state manipulations – both pharmacological and psychosocial, and spanning acute and chronic timescales – as well as the different diffusion model parameters that are altered in judgement biases caused by these various manipulations.

http://research-information.bristol.ac.uk/en/persons/claire-a-hales(f0242ef3-9c90-47de-a0bf-4d6850f2cacc).html

http://www.neuroscience.cam.ac.uk/directory/profile.php?acroberts


Spring 2017

January 27th – Robert Schmidt (University of Sheffield)

F40, Biomedical Sciences Building
Sensorimotor processing in the basal ganglia leads to transient beta oscillations during behaviour
The basal ganglia have been implicated in motor control including the initiation and suppression of actions. In Parkinson’s disease neural processing in the basal ganglia is impaired, and patients suffer from severe motor symptoms. Signatures of the impaired neural processing include oscillations in the beta band (~13-30 Hz), but beta oscillations have actually also been found in the basal ganglia of healthy animals and may reflect the utilisation of sensory cues for behaviour. To see whether healthy and pathological beta oscillations share neural mechanisms we combined computational models for beta oscillations in Parkinson’s disease with input patterns derived from single unit recordings in healthy rats. We found that movement-related increases in striatal activity lead to transient beta oscillations in the model with a time course that closely matches the experimentally measured oscillations. In addition, our model can account for further unintuitive aspects of beta modulation including beta phase resets following sensory cues and correlations with reaction time. Overall, our model can explain how sensorimotor neural activity in the basal ganglia leads to transient beta oscillations during behaviour.

https://www.shef.ac.uk/psychology/staff/academic/robert-schmidt

http://www.schmidt-lab.net/


February 10th – Rosalyn Moran (University of Bristol)

SM4, Maths

Neural Dynamics in Dynamic Causal Modeling
Dynamic Causal Modeling or DCM for electrophysiological responses uses neural mass models and mean field approaches to mimic the population activity observed in local field potentials, and their non-invasive source localised EEG and MEG correlates. In this talk I will describe the generative models underlying DCM for M/EEG and describe the inversion procedures which allows DCMs to be fit to subject specific data. I will outline recent validation studies in autoimmune NMDA encephalitis. Specifically I will demonstrate how DCM’s connectivity estimates, which are based explicitly on ion-channel dynamics, can be recovered to show particular deficits in NMDA-mediated connectivity in these interesting patients. I will finally show some examples of DCM applied to understanding neural hierarchical processing changes with age.

http://www.bristol.ac.uk/engineering/people/rosalyn-j-moran/index.html


February 17th – Aleks Domanski (University of Bristol)

SM4, Maths

Decoding Hippocampal-Frontal Cortical cell assemblies during spatial working memory
Functionally specialised brain regions such as the hippocampus (HP) and medial prefrontal cortex (mPFC) communicate under cognitive demand (such as during spatial working memory) to share information required for the successful completion of a behavioural task. The circuit mechanisms underlying this process remain poorly resolved, however population coding by “cell assemblies” – transiently synchronised groups of neurons – is favoured as a biologically-plausible candidate.
Here, using rat neurophysiology I will introduce a novel method for detecting cell assemblies from parallel single-unit recordings and present evidence that the activity of inter-structural cell assemblies provides superior and broader information encoding of task-related variables compared to individual single units. Moreover, cell assembly activity is stable in rest periods flanking the behavioural task in expert-performing rats. Together, our work argues that HP-mPFC cell assemblies provide a robust channel binding the specialised information encoded by each brain area.

http://research-information.bristol.ac.uk/en/persons/aleks-p-f-domanski(4dd1f5f5-8b94-4448-b5e5-4692cbc15794).html


February 24th – Tony Pickering (University of Bristol)

SM3, Maths

Noradrenaline / Norepinephrine : Facts / Alternate Facts

 

It is known that noradrenaline is an important neuromodulator in the brain; implicated in processes ranging from alerting, arousal and salience detection through novelty learning and emotional recall and including sensory discrimination, motor control and pain regulation.  Much of this appears to be attributable to the actions of a small cluster of neurones in the pons known as the locus coeruleus (LC).  We have been focussing on the role of the LC in the regulation of pain and have developed some novel tools and approaches to interventionally assess its function both in rodents and in man.  In so doing we have stumbled into the often apparently contradictory world of LC neurobiology and Nor-adrenaline/epinephrine (the clue is in the name(s)).  High profile papers are currently being published on these topics.  I will present the facts / the alternate facts (and their cognate models) and you can be the experts / members of the press who can pull me up on their interpretation.  It’s gonna be so great. (byo wall).

The contrasting views include:

  • LC is a primitive relic / important determinant of complex behaviour in vertebrates.
  • Acts via Noradrenaline / Dopamine release
  • Each neuron projects to the whole brain / to a discrete territory.
  • Volume transmission vs focussed synaptic release.
  • Signalling saliency to the cortex / preventing salient events from reaching the cortex.
  • Whether a modular organising principle can help account for these apparently opposing characteristics.

http://www.bris.ac.uk/phys-pharm/people/tony-e-pickering/index.html


March 17th – Nina Kazanina (University of Bristol)

SM3, Maths

http://www.bristol.ac.uk/expsych/people/nina-kazanina/index.html


March 23rd – Krasimira Tsaneva Atanasova (University of Exeter)

SM3, Maths

Socio-motor biomarkers in schizophrenia
In an effort to establish reliable indicators of schizophrenia we have developed a test that could detect deficits in movement and social interactions, both characteristics of the disorder. We asked people to perform movements alone, and to mirror the movements of a computer avatar or a humanoid robot. Using statistical learning techniques we were able to distinguish people with schizophrenia from healthy participants with accuracy and specificity slightly better than clinical interviews and comparable to tests based on much more expensive neuroimaging methods. This methodology could help with diagnosis of schizophrenia and to monitor patients’ responses to treatment, but needs to be tested further before being potentially widely applied in clincal practice.

http://emps.exeter.ac.uk/mathematics/staff/kt298


March 31st – Julijana Gjorgjieva (The Max Planck Institute for Brain Research)

SM3, Maths

Optimal coding in sensory populations

At the output of the retina, some ganglion cell classes consist of paired cell types that have very similar spatiotemporal response properties, except that one type is excited by light increments (ON), the other type by light decrements (OFF). Besides the retina, the ON-OFF dichotomy is also observed in other sensory modalities, which include invertebrate motion vision, thermosensation, chemosensation, audition, and electrolocaton in electric fish. The commonality in the splitting of sensory signals across neural systems and species suggests a strong evolutionary pressure driving the emergence of opposite response types to positive and negative stimuli. Why have the ON and OFF channels dierged in different species and sensory modalities? I will discuss how ON-OFF organization at the level of sensory neuronal populations emerges from an efficient coding strategy to maximize information transfer of incoming stimuli. Our work underscores the significance of external stimulus statistics and neural noise in governing how populations organize to efficiently encode and decode sensory information.

http://brain.mpg.de/research/computation-in-neural-circuits-group.html


April 7th – Tom Jahans-Price (University of Oxford)

SM3, Maths

Glutamatergic dysfunction leads to a hyper-dopaminergic phenotype: a possible cause of aberrant salience
Current thinking suggests that psychosis is a disorder of aberrant salience. This describes when a stimulus continues to grab inappropriately high levels of attention, and it is thought to be mediated via elevated dopamine (DA) levels, which have been robustly demonstrated in schizophrenia. However, the causes of this DA dysregulation are generally unspecified. Recent large scale GWAS meta-analyses have established genome-wide significant association to schizophrenia for the Gria1 locus which codes for the GluA1 subunit of the AMPA glutamate receptor. GluA1 KO mice have previously been studied in relation to schizophrenia but, notably, striatal whole tissue levels of dopamine and its metabolites appear normal in these animals. However, we might not expect to see changes in dopamine activity in anaesthetised animals, or in a home-cage environment. Indeed, changes in phasic DA responses are likely to be both behaviour-dependent and stimulus-specific.
To test this possibility we have recorded phasic DA signals with high temporal resolution, in freely moving, behaving wild-type and GluA1 KO mice, using fast-scan cyclic voltammetry (FSCV). I will present data showing that phasic dopamine signals in response to neutral light stimuli fail to habituate in Gria1-/- mice, resulting in a behaviourally relevant, hyper-dopaminergic phenotype in these animals. This parallels previous behavioural data from these mice. In addition, phasic dopamine responses to unsignalled rewards were also significantly enhanced in the knockout mice. This provides evidence for behaviourally-relevant hyper-dopaminergic responses in a genetically modified mouse model of glutamatergic dysfunction relevant to schizophrenia.

April 28th – Cian O’Donnell (University of Bristol)

SM3, Maths

Memory processing by molecular signals in neurons

The dominant models of long-term memory formation are based on Hebbian plasticity rules. These rules are usually given solely in terms of electrical spiking activity of pre- and post-synaptic neurons. However, in real cells, expression and consolidation of synaptic plasticity involves a complicated cascade of biochemical signals, protein synthesis, and gene transcription. Surprisingly little is understood about the computational function of these molecular signals for memory. In this talk I will present our recent work on how spatial patterning of protein synthesis in dendrites allows brains to choose what to remember and what to forget. Based on these results, we also propose a novel model for memory generalisation during sleep.

http://www.bris.ac.uk/engineering/people/cian-odonnell/index.html


May 5th – Angela Roberts (University of Cambridge)

SM3, Maths

A multidimensional approach to the study of positive and negative emotion regulation in the marmoset prefrontal cortex

Dysregulated emotions are a core feature of many neuropsychiatric disorders involving altered activity in limbic emotional circuitry that includes the amygdala, hippocampus and prefrontal cortex (PFC).  Front line treatments include drugs that target the serotonin system and more recently the glutamate system, but how they work, and in which patient, is poorly understood. Moreover, at least 40% of patients are resistant to such treatments emphasizing the need to understand better the neural circuits and cognitive and behavioural processes that underlie the regulation of positive and negative emotion. The prefrontal cortex is at its most highly developed in primates and so to further our understanding of its regulation of amygdala-dependent emotional learning and expression we have developed models of negative and positive emotional learning and expression in a new world primate, the common marmoset. Since emotional states are composed of both physiological and behavioural components we use an automated telemetry system to allow the simultaneous measurement of behavioural and cardiovascular emotional responses e.g. heart rate and blood pressure, in freely moving marmosets. We employ three main experimental strategies. The first, to determine the effects of localized prefrontal manipulations on emotional states, their impact on activity in downstream targets using fluorodeoxyglucose microPET and their sensitivity to drugs targeting the glutamate and serotonin system. Second, we have initiated a neuroimaging program to characterize the development of prefrontal circuits across childhood and adolescence in the marmoset since the majority of anxiety and mood disorders have their onset during these critical periods of development in humans. The third, to study the impact of known behavioural and genetic risk factors for mood and anxiety disorders, i.e. trait anxiety and a polymorphism in the upstream promotor region of the serotonin transporter gene, on these prefrontal circuits using microPET, structural mri, microdialysis and post mortem mRNA analysis. In this presentation I will illustrate these approaches in the study of anxiety and anhedonia.

Recent review: Shiba et al (2016) Frontiers in Systems Neuroscience 10:12.

http://www.neuroscience.cam.ac.uk/directory/profile.php?acroberts

Autumn 2016

23rd September, Professor Penny Lewis (Cardiff University)

SM3, Maths

 
Exploring sleep’s impact on memory with targeted reactivation

Memories are neurally replayed during sleep, and this is important for their consolidation and integration with prior knowledge.  Targeted Memory Reactivation (TMR) is a technique which can be used to trigger the replay of specific memories on demand.  In this talk I will first describe a study which suggests that sleep plays a role the in integrating new information into pre-existing knowledge frameworks (or schemas).  I will next describe two studies which use TMR to examine a) the role memory replay in facilitating the emergence of explicit knowledge from implicitly learned material, and b) the role of memory replay in reducing emotional content of memories.  I will finish up by discussing a new method for identifying TMR cued replay in sleep using EEG classifiers.

http://psych.cf.ac.uk/contactsandpeople/academics/lewispenny.php

 


30th September, Professor Myra Conway (University of the West of England)

SM3, Maths

Prof. Conway’s talk concerns the role of glutamatergic neurotransmission in memory and learning, and how disruptions contribute to Alzheimer’s disease.

Glutamatergic neurotransmission is important for memory and learning and is severely disrupted in Alzheimer’s disease.  Recent studies by our group have demonstrated that a metabolic protein involved in regulating brain glutamate is significantly upregulated in AD brain relative to age-matched controls.  In this talk I will focus on how this protein forms metabolons that can be influenced by the redox state and how this will influence glutamate regulation.  I will also introduce one of our current research questions, which asks if these proteins can also act as novel chaperones and consider their role in protein folding.  This is important as misfolded proteins and aggregate accumulation contributes to disease pathogenesis.

http://people.uwe.ac.uk/Pages/person.aspx?accountname=campus%5Cme-conway


7th October, ‘Supervisor Snapshots’ session

SM3, Maths

This session is exclusively for first year students of the Neural Dynamics programme. Supervisors from the university will be discussing the rotation projects they are offering to the new students.


14th October, ‘Supervisor Snapshots’ session

Location TBC

This session is exclusively for first year students of the Neural Dynamics programme. Supervisors from the university will be discussing the rotation projects they are offering to the new students.

21st October, Dr Wessel Woldman (University of Exeter)

SM3

Analysis and modelling of epileptiform discharges

I will discuss how the epileptic activity of the brain is distributed over the course of a day using a large clinical data-set. We studied dynamic patterns of epileptiform discharges captured on recordings of scalp electroencephalogram (EEG) from 107 people with generalised epilepsies. I will show that discharges are distributed non-randomly over the course of 24 hours both in frequency and duration, after which I will show how a particularly simple phenomenological model can be used to reproduce the discharge distributions of individual subjects. In a broader setting, this work provides further support for the emergent concept that epileptic activity emerges from the interplay between a global network structure and the individual dynamics of specific brain regions.

http://www.exeter.ac.uk/cbma/team/mrcfellows/


4th November, Dr Alain Nogaret (University of Bath)
SM3
 
 

11th November, Dr Francesca Spiga
SM3
 
Origin and regulations of glucocorticoids ultradian rhythms: insights from experimental and mathematical data
 
 

18th November, Dr Konstantinos Kalafatakis

SM3

Different patterns of glucocorticoid rhythmicity change resting state networks and brain’s responses to emotional stimulation in healthy male individuals

Background: Glucocorticoids’ (GCs) rhythmicity is a dynamic biological factor for their regulatory effects, particularly important in the parts of the brain that show high sensitivity to GCs. Such brain regions, like the corticolimbic structures, are abundant in glucocorticoid- and mineralocorticoid receptors, through which GCs modulate various cognitive and behavioural phenotypes in humans.

Aim: To examine the effect of different temporal patterns of glucocorticoid presentation on the corticolimbic areas’ resting state networks and neural processing of emotional faces with the application of functional magnetic resonance imaging (fMRI).

Methods: 15 healthy, male, right-handed individuals participated in an interventional, double-blinded, placebo-controlled, crossover study. The three treatment schemes had a duration of 5 days. All participants received oral metyrapone loading (gradually increasing total daily dose from 1g to 2.5g) to suppress endogenous cortisol adrenal activity. A fixed total daily dose of hydrocortisone 20mg was exogenously replaced via 3 different methods (1 per treatment arm): (a) orally, (b) subcutaneously in a continuous manner and (c) subcutaneously in a pulsatile manner. Individuals participated in a functional neuroimaging study on day 5.

Results: Under resting state conditions, the functional connectivity of various corticolimbic regions (like amygdala, orbitofrontal cortex, dorsal striatum, insula or cingulate) with regions implicated in the processing of visual and somatosensory stimuli and core components of the default mode and the salience network changes significantly between the 3 study groups. Moreover, across groups, these corticolimbic regions showed significantly different responses to emotional faces.

Conclusion: These data support the capability of altered GCs temporal dynamics to differentially modulate the level or mode of activation of susceptible brain areas under emotional stimulation and resting state condition. Implications about the role of GCs in the emotional control of cognition and development of psychopathology are discussed.

http://www.bristol.ac.uk/clinical-sciences/people/konstantinos-kalafatakis/index.html


25th November, Dr Nadia Cerminara

SM3

An action based map of C3 cerebellar microzones

A fundamental principle of cerebellar functional organization is its division into a series of longitudinally oriented modules. Each module is defined by its climbing fibre input from a specific subdivision of the contralateral inferior olive, which targets one or more longitudinal zones of Purkinje cells within the cerebellar cortex. In turn, Purkinje cells within each zone project to specific regions of the cerebellar or vestibular nuclei. Within several zones, smaller units known as ‘microzones’ have been identified electrophysiologically in anaesthetized animals. Within a given microzone, all Purkinje cells have climbing fibre-mediated input with similar receptive fields. Microzones and their associated input–output connections are thought to represent the basic operational units of the cerebellum. However, little is known about their function in awake, behaving animals. Experiments in the lab are investigating cerebellar microzones ‘in action’  by recording from single cerebellar neurones located in different microzones during performance of a visually guided forelimb reach/retrieval task in cats.

http://www.bristol.ac.uk/phys-pharm/people/nadia-l-cerminara/index.html


2nd December, Dr Gihan Weerasinghe (University of Oxford)

SM3
 
Deep brain stimulation (DBS) is a proven therapy for a variety of neurological disorders, including Parkinson’s disease and essential tremor. The current generation of technology operates on an open loop basis, where stimulation is delivered irrespective of a patient’s symptoms. In contrast, the closed loop approach, where the patient’s symptoms are continuously monitored and the stimulation delivered accordingly, has the potential to be both more effective and efficient than existing solutions. This talk will focus on the processing of measurement data in relation to closed loop DBS, in particular, the tremor data obtained from patients with essential tremor.
 
 

9th December, Associate Professor Yulia Timofeeva (University of Warwick)

SM3
Quantification of fast presynaptic Ca2+ kinetics using non-stationary single compartment model
 
Fluorescence imaging is an important tool in examining Ca2+-dependent machinery of synaptic transmission. Classically, deriving the kinetics of free Ca2+ from the fluorescence recorded inside small cellular structures has relied on singe-compartment models of Ca2+ entry, buffering and removal. In many cases, steady-state approximation of Ca2+ binding reactions in such a model allows elegant analytical solutions for the Ca2+ kinetics in question. However, the fast rate of action potential (AP)-driven Ca2+ influx can be comparable with the rate of Ca2+ buffering inside the synaptic terminal. In this case, computations that reflect non-stationary changes in the system might be required for obtaining essential information about rapid transients of intracellular free Ca2+. Based on the experimental data we propose an improved procedure to evaluate the underlying presynaptic Ca2+ kinetics. We show that in most cases the non-stationary single compartment model provides accurate estimates of action-potential evoked presynaptic Ca2+ concentration transients, similar to that obtained with the full 3D diffusion model. Based on this we develop a computational tool aimed at stochastic optimisation and cross-validation of the kinetic parameters based on a single set of experimental conditions. The proposed methodology provides robust estimation of Ca2+ kinetics even when a priori information about endogenous Ca2+ buffering is limited.
 
 

16th December, Dr Janine Bijsterbosch
SM3
 
The three slides of Christmas: Variability, Amplitude and Connectivity
 
The amplitudes of spontaneous fluctuations in brain activity are investigated rarely and are relatively poorly understood, despite their direct relevance to measures of functional connectivity (FC). However, resting state signal amplitudes may be a significant source of within-subject and between-subject variability, and this variability is likely to be carried through into FC estimates. In this talk I will describe both cross-subject and within-subject variability in the Human Connectome Project, and I will discuss the relationship between signal amplitude and estimated functional connectivity.
 

Summer 2016

20th May, Henry Darch

D3, Biomedical Sciences

Problem solving session

Summary of the problem: “I have simultaneously recorded 51 channels of continuous extracellular neural activity (LFP) during a reach-retrieve behaviour. Unfortunately, I have an artefact present as the animal’s paw is entering the tube. The artefact is present in a large proportion of recorded reaches, and so is reducing my ‘trial n’.  I wish to explore possible methods of detecting and removing these artefacts, without simply excluding the affected trials, and recovering as much neural signal as possible.”

 


26th May, Michael Knight

D3, Biomedical Sciences

 
Dynamics of MRI T2 in acute ischaemic stroke

Many changes occur in the brain during the hyperacute phase of ischaemic stroke. Certain physiological and chemical changes manifest themselves as changes in quantities measurable by magnetic resonance imaging (MRI), from which one might hope to infer details of the stroke event, in particular its time of onset, for this determines choice of treatment and is often unknown by the patient. We have developed a simplified model for the hyperacute phase of ischaemic stroke, intended to calculate the spatiotemporal changes in the apparent diffusion coefficient (ADC) for water, and the coherence lifetime (lifetime of MRI signal). These are easily measured by MRI. These have distinct kinetics, the ADC dropping quickly after onset and defining the infarct, the T2 dropping quickly then gradually increasing. I will present our model and how we might in future use it to guide treatment choices in stroke.

 


3rd June, Nathan Lepora

D3, Biomedical Sciences

A biomimetic brain for active touch


10th June, Chayanin Tangwiriyasakul (UCL)

SM3, Maths

Network decomposition in patients with IGE – an EEG-fMRI study

Many recent studies suggest that generalized seizures arise from abnormality in whole brain networks. Most evidence shows abnormalities in static networks (e.g. reduced default mode network connectivity). We investigated dynamic changes in the level of synchrony during generalized spike and wave discharge (GSW) period using simultaneous EEG-fMRI recordings. The results from this study suggest two possible causes of SWD generation: (1) transition between two states, which may cause instability in brain networks or (2) over synchronization of the brain networks.
http://epilepsy-london.org/doctor/chayanin-tangwiriyasakul/


 

17th June, Eder Zavala (Exeter)

F40, Biomedical Sciences

Modelling the Intra–Adrenal Regulatory Network Underlying Glucocorticoid Secretion During Stress

 

The stress response is mediated by glucocorticoid hormones (CORT) secreted by the adrenal glands upon stimulation by adrenocorticotropic hormone (ACTH) from the pituitary. These hormones exhibit a complex pattern of highly correlated ultradian oscillations that becomes altered during inflammation and disease. In particular, the role of intra-adrenal control mechanisms on the dynamic dissociation of these hormones during stress is poorly understood. Here, we develop a mathematical model of the intra-adrenal regulatory network controlling the synthesis of CORT, accounting for both genomic and non-genomic processes occurring at different time scales within the network. We test the model through computer simulations of ACTH perturbations, and successfully predict responses to acute stressors, as judged from experiments in rats injected with high doses of ACTH and a bacterial toxin (LPS) that triggers an inflammatory response. Our results show that post-transcriptional and post-translational regulatory mechanisms are key for a rapid response to stress, and suggest the presence of novel regulatory mechanisms that can be tested experimentally. Moreover, our model provides insight into the regulatory roles of some steroidogenic genes during normal and diseased states.

 



1st July, Stafford Lightman

SM3, Maths

Hormone rhythms and brain function

Spring 2016

6th January: Geoffrey Goodhill (University of Queensland)

SM3, Maths

Axon guidance, neural coding and visual maps: theories and experiments

I will review our recent and current work on the following topics: (i) how growing axons detect and respond to molecular gradients, (ii) decoding of visually-evoked neural activity in the developing visual system, and how spontaneous patterns of activity develop, and (iii) neural plasticity in visual cortex in response to altered visual experience during development. All these projects involve a combination of computational and experimental approaches (including microfluidics, 2-photon calcium imaging and optical imaging of intrinsic signals).

 


22nd January: Kate Jeffery (University College London) 

C44, Biomedical Sciences

The neural coding of three-dimensional space – properties and constraints

In the past several decades, great strides have been made in our knowledge concerning how neurons encode large-scale (navigable) space. Particularly important has been the discovery of how the metric properties of distance and direction are encoded, and of how the signals are updated following movement. These studies, however, were primarily made in two-dimensional environments. In three dimensions, which is how the natural world is structured, additional encoding complexities arise. This talk will explore the nature of some of these complexities, and review emerging data about how the brain may deal with these.

 


29th January: Andrew Bagshaw (University of Birmingham)

SM3, Maths

EEG-fMRI integration within an information theoretic framework:

The combined recording of electroencephalography (EEG) and functional MRI (fMRI) is an increasingly common technique for studying brain function, but one of the main outstanding questions regards the optimal way to combine these two very different and very rich data sets. The most common approach is within a general linear model framework, but whether a linearity assumption is valid when combining EEG, fMRI and behavioural data is unclear. An alternative is the use of information theory, and its fundamental quantity of mutual information. Information theory imposes no such linearity constraints, as well as providing a coherent framework to quantify relationships between electrophysiological, haemodynamic and behavioural variables. I will give an overview of the issues underlying EEG-fMRI integration and summarise our work implementing an information theoretic framework to accomplish it.

http://www.birmingham.ac.uk/staff/profiles/psychology/bagshaw-andrew.aspx

 


5th February, Sabine Hauert

SM3, Maths

From evolving artificial neural networks for robot swarms to engineering nanoparticles for brain tumours 

Swarm strategies inspired from nature (ant colonies and bird flocks) allow large numbers of simple agents to achieve complex tasks. The challenge is to engineer individual behaviours that give rise to desired emergent properties. To this end, we use artificial evolution to automatically design neural network controllers for robot swarms. Demonstrated applications include aerial robotics, or coordination of 1000 coin-sized robots at the Bristol Robotics Laboratory. Work in swarm robotics is also inspiring computational and microfluidic tools to improve the delivery of nanoparticles to brain tumours.

For more information on Dr Hauert’s work please see her website (http://sabinehauert.com/), with particular interests in applying swarm behaviour to nanomedicine.

 


19th February, Colin Davis

SM3, Maths

Modelling visual word recognition at the computational, algorithmic and implementation levels


26th February, Sarah Hulme

SM3, Maths

NMDAR clustering in layer 4 of developing barrel cortex

One surprising aspect of layer IV local excitatory circuit development in barrel cortex is a dramatic yet transient sensory input-dependent increase in both AMPAR and NMDAR mediated connectivity observed at postnatal day 6. This occurs prior to the emergence of dendritic spines but is hypothesised to be critical for the subsequent rapid and dramatic increase in AMPAR receptor-mediated connectivity observed upon spine emergence at postnatal day 9. A candidate mechanism for this phenomenon is the pattern postsynaptic receptor clustering. This talk will summarise the development of AMPAR/NMDAR connectivity we have characterised as well as discuss in more depth how we have approached characterising NMDAR clustering using multiphoton glutamate uncaging along developing dendrites, the challenges associated with this and the results thus far.

 


4th March, Pedro Martinez (Imperial College London)

SM3, Maths

Modelling cortical oscillations with BrainStudio

Cortical oscillations are an ubiquitous topic in Neuroscience research, playing a major role in the functioning of the mammalian brain. Oscillatory phenomena are often featured in the models we use to replicate experimental findings, and they have proven to be fruitful, but writing and testing these models is usually cumbersome for scientists without a strong background in programming. In this talk we will discuss the origin and relevance of cortical oscillations, and point out their role in resting state dynamics, epileptic seizures and in particular action selection in the basal ganglia. All examples will be implemented in two software packages, BrainStudio and JIDT. BrainStudio is a new software package for the design and real-time simulation of large-scale neural systems. We will highlight the features of BrainStudio as an effective, user-friendly simulation tool. JIDT is a toolbox for the calculation of information-theoretic measures of interest to Neuroscience, such as transfer entropy and mutual information. Combining both tools we can easily set up neural systems and analyse their dynamical and functional properties. This talk contains a total of zero equations, and the constant thrill of live (computational) experimentation. (Work in collaboration with Zafeirios Fountas and Dave Bhowmik.)

 


11th March, Claire Booth

SM3, Maths

Alterations to intrinsic, synaptic and network properties in the hippocampal formation in a neurodegenerative mouse model of tauopathy

 

The formation and deposition of tau protein aggregates is proposed to contribute to cognitive impairments in dementia by disrupting neuronal function in brain regions including the hippocampal formation. The rTg4510 transgenic mouse model overexpresses a mutant form of human tau protein and develops hyperphosphorylated tau, neurofibrillary tangles, neurodegeneration, and associated cognitive impairments in an age-dependent manner. We used a battery of in vivo and in vitro electrophysiological recordings in 7-8 month old rTg4510 mice to investigate the effects of tau pathology on neuronal function in hippocampal area CA1 and layer II medial entorhinal cortex (mEC).

 

CA1: In vitro recordings revealed shifted theta-frequency resonance properties of CA1 pyramidal neurons, deficits in synaptic transmission at Schaffer collateral synapses, and blunted plasticity and imbalanced inhibition at temporoammonic synapses. These changes were associated with aberrant CA1 network oscillations, pyramidal neuron bursting, and spatial information coding in vivo. Our findings relate tauopathy-associated changes in cellular neurophysiology to altered behavior-dependent network function.

 

mEC: In the mEC, the responsiveness of individual neurons to electrical and environmental stimuli varies along the dorsal–ventral axis in a manner that suggests this topographical organization plays a key role in neural encoding of geometric space. Our recordings revealed that dorsal aspects of the mEC were preferentially affected in rTg4510 mice, with alterations in certain intrinsic properties, gamma frequency oscillations in vitro and theta-gamma cross-frequency coupling in freely moving animals. Ventral regions were unaffected, resulting in flattened dorsal-ventral gradients of these properties in rTg4510 mice. We propose that the selective disruption to dorsal mEC, and the resultant flattening of certain dorsal-ventral gradients, may contribute to disturbances in spatial information processing observed in this model of dementia.

 


18th March, Nina Kazanina 

SM3, Maths

The role of oscillatory brain activity in tracking speech

In order to understand a spoken sentence the listener’s brain needs to extract words from a continuous acoustic signal, establish relations between words (e.g., who did what to whom) and interpret the resulting hierarchical structure. I will discuss recent neurocomputational ideas on how oscillatory brain activity may track speech segmentation and aid in encoding hierarchical relations between words.

22nd April, Romain Veltz (INRIA)

SM3, Maths

 
Some applications of hybrid systems in neurosciences
 
In this talk, I will present some recent results about stochastic processes that are becoming increasingly important in neuroscience. More precisely, I will talk about piecewise deterministic Markov processes (PDMP) that are midway between pure jumps processes and ordinary differential equations. After presenting a new simulation method that is now available as a Julia package, I will move to more theoretical results about a mean field model of neural network where each neuron is modelled with a PDMP.

29th April, Hannah Gill

SM3, Maths

Can EEG analysis reveal a cause for anaesthetic-induced toxicity in developing brain?

Processed EEG is available for depth of anaesthesia monitoring in adults. It has been demonstrated that avoidance of a bispectral index (one commercially available processed EEG measure) below 40 (equivalent to ‘deep anaesthesia’) improved outcomes following moderate to high risk surgery. The precise algorithms these monitors use is top secret, but it has been shown that bispectral index inversely correlates with increased burst suppression activity.

Exposure to surgery and anaesthesia during early life has been associated with poor neurodevelopmental outcomes and rodent models have shown an association between exposure to anaesthesia, seizure-like activity and cell death in the developing brain. This seizure-like activity has also been demonstrated in humans under anaesthesia during early life.
In this forum I will present the evidence that EEG analysis in immature rodents and humans offers potential to identify the causes and means to avoid anaesthetic toxicity in the developing brain.

6th May, Alan Champneys

SM3, Maths

 
Bifurcation, bi-stability and excitability in neural systems
 

This talk will give an introduction to a philosophy of mathematical modelling of neural systems based on techniques from nonlinear dynamics. The talk shall be illustrated with several examples where bifurcation, excitability or bi-stability have proved the key insight in understanding behaviour of a neural system. Examples include models for image segmentation, blood pressure control and the neuro-mechanics of hearing in insects and mammals.

Autumn 2015

2nd October: Mike Ashby

Room: SM3

Spatial clustering of new synapses


9th October: Naoki Masuda

Room: SM3

Energy landscape of human brain activity during bistable perception

Individual differences in the structure of parietal and prefrontal cortex predict the stability of bistable visual perception. However, the mechanisms linking such individual differences in brain structures to behaviour remain elusive. Here we demonstrate a systematic relationship between the dynamics of brain activity, cortical structure and behaviour underpinning bistable perception. Using fMRI in humans, we find that the activity dynamics during bistable perception are well described as fluctuating between three spatially distributed energy minimums in an energy landscape constructed from fMRI data. Transitions between these energy minimums predicted behaviour, with participants whose brain activity tend to reflect the visual-area-dominant energy minimum exhibiting more stable perception and those whose activity transits to the frontal-area-dominant energy minimum reporting more frequent perceptual switches. These brain activity dynamics are also correlated with individual differences in grey matter volume of the corresponding brain areas.


16th October: Aleks Domanski

Room: SM3

Capture, dissection and manipulation of complex cortical network dynamics in models of Autism

Cortical network function critically depends on many physiological parameters that develop in concert during early postnatal critical periods, notably intrinsic neuronal properties, synaptic function and appropriately balanced synaptic connectivity. Perturbation of normal network development processes by genetic insults associated with Autism can lead to complex network effects but it is unclear to what extent these individual factors contribute to the overall pathophysiology. Combining slice electrophysiology in a mouse model of Autism with single-cell and network simulation, I will dissect the mechanisms by which changes in multiple electrophysiological parameters lead to complex network-level effects, ask which are dominant drivers towards pathological network states, and provide insight into potential scenarios for pharmacological rescue.


23rd October: Alex Cope, Green Brain Project (University of Sheffield)

Room: SM3

Modeling the honeybee

The honeybee, with a brain consisting of 1 million neurons (100,000 times fewer than the human brain), is nevertheless capable of complex tasks normally considered the domain of advanced vertebrates. By studying this versatile insect we can therefore gain insight into the neural basis of such tasks.


30th October: Jon Hanley

Room: SM1

Predicting plasticity from protein-protein interactions

A multitude of interconnecting and highly regulated protein complexes are at the core of cell biology. Synaptic plasticity involves processes such as receptor trafficking, changes in dendritic spine morphology, and rapid, local regulation of protein synthesis. These processes are all underpinned by dynamic protein-protein interactions that are regulated by numerous signalling pathways. I will present a couple of examples of such protein complexes that we are studying, and discuss their importance in determining the outcome of plasticity-inducing stimuli.


6th November: Mark Humphries, University of Manchester

Room: SM3

Population dynamics in a locomotion neural network converge to a recurrent attractor 

Many neural systems are thought to implement some form of cyclical or periodic attractor, in which neural activity “rotates” over time to drive some periodic process, such as locomotion or heading direction. However, we lack direct evidence that such neural attractors exist. We tested the hypothesis that the crawling motor program of the sea-slug Aplysia is directly implemented by a periodic attractor in its pedal ganglion network. Evoking the locomotion program caused population activity to rapidly settle into a low-dimensional, slowly decaying rotational orbit. These recurrent dynamics were consistent between programs evoked in the same animal, indicating convergence on the same basin of attraction, but could differ considerably between animals. Despite this heterogeneity we could decode a specific portion of the motor program directly from the low-dimensional dynamics. Collectively our results support the hypothesis that Aplysia’s pedal ganglion is a cyclical attractor network.


13th November: Laurence Hunt, UCL

Room: SM3

Bridging microscopic and macroscopic choice dynamics in prefrontal cortex

The significance of prefrontal cortex for reward-guided choice is well known from both human imaging and animal neurophysiology studies. However, dialogue between human and animal research remains limited by difficulties in relating observations made across different techniques. A unified modelling framework may help reconcile these data. We have previously used attractor network models to demonstrate that varying decision values can elicit changes in local field potentials (LFP) dynamics, causing value correlates observable with human magnetoencephalography (Hunt et al., Nature Neuroscience 2012). Extended, hierarchical forms of such models can also predict human functional MRI signal in different frames of reference during a multi-attribute decision process (Hunt et al., Nature Neuroscience 2014). In light of this framework, we have recently sought to relate simultaneously recorded LFP and single-unit data from prefrontal cortex of macaque monkeys performing a cost-benefit decision task. I will discuss key findings from these studies, which help us to relate value correlates in human neuroimaging studies to their cellular origins.


20th November: Denize Atan

Room: SM3

From neural stem cells to neural networks: finding light in the dark

Human cognition and behaviour are functions of neuronal networks that comprise the mammalian brain. Of these cognitive abilities, the formation of new episodic memories is critically dependent on the hippocampal formation. The hippocampal dentate gyrus is one of a small number of brain regions in which neurogenesis continues throughout adulthood, and where neurogenesis is important for learning and memory.  Transcription factors play key roles in directing neural differentiation and circuit assembly through their precise spatial, temporal, and cell type-specific control of gene expression.  In this talk, I will describe how our recent investigations of gene regulation and expression have taken us on a journey from events that occur at a molecular level in differentiating neurons……to hippocampal circuit formation, network dynamics, learning and memory, and finally population genetics.


27th November: Marc Goodfellow (Exeter)

Room: SM3

The role of networks in seizure generation

Epilepsy is characterised by the repeated occurrence of seizures, which are periods of pathological brain activity that arise spontaneously from a predominantly healthy functional state. Since the goal of epilepsy treatment is to abolish or reduce the tendency of the brain to transition into seizures (its ictogenicity), it is important to better understand these transitions, and how we might interact with the brain to abate them. However, seizure dynamics emerge in, and affect, large-scale brain networks, and the network paradigm for ictogenesis introduces unfamiliar challenges and new opportunities to understand epilepsy.

In this talk I will introduce a mathematical model-based approach to quantify ictogenicity in brain networks. I will demonstrate how this approach can be used to quantify differences in brain networks between patients with generalised epilepsies and healthy controls. I will also describe how we can extend this approach to quantify the contribution of each component of a network to seizure generation. This quantification is based upon the effect that a treatment-specific perturbation has on network ictogenicity. Using exemplar networks I will explore how the apparent ictogenicity of nodes can vary according to network structure and the presence or absence of “pathological” nodes (seizure foci). I will explain how this approach can potentially provide an insightful and principled way to interpret and describe generalised or focal seizure dynamics, and may enhance our strategies for the classification and treatment of epilepsies.


4th December: 3 Short Talks

Room: SM3

1. Bridget Lumb

Dynamic alterations to prefrontal-midbrain-spinal cord networks and their contribution to pain chronification
2. Hans Reul 
Glucocorticoid action in the brain
3. Clea Warburton 
Mechanisms controlling hippocampal gene activation and memory formation

11th December: Rafal Bogacz (University of Oxford)

Room: SM2

Learning in cortical networks through error back-propagation

To efficiently learn from feedback, the cortical networks need to update synaptic weights on multiple levels of cortical hierarchy. An effective and well-known algorithm for computing such changes in synaptic weights is the error back-propagation. It has been successfully used in both machine learning and modelling of the brain’s cognitive functions. However, in the back-propagation algorithm, the change in synaptic weights is a complex function of weights and activities of neurons not directly connected with the synapse being modified. Hence it has not been known if it can be implemented in biological neural networks. This talk will discuss relationships between the back-propagation algorithm and the predictive coding model of information processing in the cortex, in which changes in synaptic weights are only based on activity of pre-synaptic and post-synaptic neurons. It will be shown that when the predictive coding model is used for supervised learning, it performs very similar computations to the back-propagation algorithm. Furthermore, for certain parameters, the weight change in the predictive coding model converges to that of the back-propagation algorithm. This suggests that it is possible for cortical networks with simple Hebbian synaptic plasticity to implement efficient learning algorithms in which synapses in areas on multiple levels of hierarchy are modified to minimize the error on the output.