ICMS

Neurodynamics: a workshop on heterogeneity, noise, delays, and plasticity in neural systems

Mar 05, 2012 - Mar 07, 2012

ICMS, 15 South College Street, Edinburgh, EH8 9AA

Organisers

Name	Institution
Coombes, Stephen	University of Nottingham
Timofeeva, Yulia	University of Warwick

Training Workshop "Tutorial Day" Organiser:
Mark van Rossum, University of Edinburgh

 

Although mathematical work on Neurodynamics has increased in recent years, the study of heterogeneity, noise, delays, and plasticity needs much further attention.  A firmer mathematical framework for treating dynamical systems with these attributes will pave the way for a more comprehensive understanding of the dynamic states of biological neural networks, and their role in facilitating natural computation.  This three-day conference will bring together experts in these key areas to seed a new phase of theoretical work to develop those pieces of mathematical theory which are critical for future realistic modelling studies of the brain.

The meeting will consist of invited speakers and registered participants, though will be limited to 100 people. The schedule will allow for a number of poster presentations.
This event is sponsored by the EPSRC in association with the UK Mathematical Neuroscience Network.

 

Arrangements

Please note that the main workshop will begin with registration from 09.00-10.30 on Monday 5 March (first talk at 10.45) and will close at 16.15 on Wednesday 7 March.   Please take these timings into account when booking your travel. 

Participation
Registration is now open:  CLICK HERE FOR APPLICATION FORM.   Places are limited to 100 and will be allocated mainly on a first-come/first-served basis.  Early application is encouraged.   The application period will close as soon as capacity is reached.
Invited Speakers will receive a personalised e-mailed invitation with a link to their own registration form.

Training Workshop "Tutorial Day" - Informatics Forum, Edinburgh (please note that this training workshop has a different venue from the main meeting).
This is a one-day tutorial on PhD student-level, covering key concepts in mathematical neuroscience, in particular those relevant for the main meeting.  The event will take place  (on Sunday 4 March 2012) in the Informatics Forum jointly with the DTC for Neuroinformatics.  This tutorial day will be organised by Mark van Rossum.   For further information about the Tutorial Day click here .  Map showing Informatics Forum. 

Further information and details about the Training Workshop Tutorial Day will be announced here in due course.  Click here for a map showing Informatics Forum. 

Venue for main conference (15 South College Street, Edinburgh)
The workshop will be held at ICMS, 15 South College Street, Edinburgh, EH8 9AA. All lectures will be held in the Newhaven Lecture Theatre. To view this room and a list of the visual equipment available click here. In addition, two blackboards have recently been installed. Follow this link for a map showing the location of 15 South College Street, or this map may also prove useful. Invited speakers can either bring talks on a memory/usb stick or laptop.

Travel
Information about travel to the UK and Edinburgh is available here.  Please note that it is your responsibility to have adequate travel insurance to cover medical and other emergencies that may occur on your trip.

A taxi directly from the airport will cost approximately 15.00 to 20.00 GBP to the city centre for a one-way journey.     There is also a bus service direct from the airport to the city centre which will cost 3.50 single or 6.00 GBP return - the Airlink 100.  This is a frequent service (every 10 minutes during peak times) and will bring you close to Waverley Railway Station and the workshop venue. 

Lothian buses charge £1.40 for a single, £3.50 for a day ticket. Please note that the exact fare is required and no change is given.

If travelling by train, please note that Edinburgh has two railway stations; Waverley Railway Station being the main station and closest to the workshop venue at 15 South College Street. If you alight at Edinburgh Waverley, the workshop venue is an easy 10 minute walk over North and South Bridge. The second railway station is called Haymarket and is at the West End of the city centre.

UK Visas
If you are travelling from overseas you may require an entry visa. A European visa does not guarantee entry to the UK. Please use this link to the UK Visas site to find out if you need a visa and if so how to apply for one.

Accommodation
Participants are asked to make their own accommodation arrangements. A list of Edinburgh accommodation of various sorts and prices is available here. 
Invited Speakers will be contacted separately by email regarding accommodation - ICMS will book hotel accommodation for Invited Speakers and will email full details of the booking.

Financial Assistance
Some financial assistance is available to assist graduate students who attend BOTH the training workshop and the main workshop.  Applicants should provide a brief résumé including degrees and at least one recommendation letter explaining their suitability for the activity.  The résumé and letter should be emailed to audrey.brown at icms.org.uk .  Students requesting financial support will be notified of the outcome by 13 January 2012.  

Registration Fee and Financial Matters
The registration fee for this workshop is 100.00 GBP.  Further details regarding payment will follow at a later date. 

Poster Sessions
Only A1 Portrait posters will be accepted due to space restrictions and the number of posters submitted.   Those wishing to present a poster should indicate this on the application form and supply a provisional title for the poster.   The title can updated nearer the time of the workshop.  Further details regarding the Poster Sessions will follow at a later date. 

Meals and Refreshments
Refreshments will be provided during the breaks in the Programme.  On Tuesday 6 March and Wednesday 7 March there will be a light buffet lunch provided.  The Conference Dinner will take place on Tuesday 6 March at 19.00 at Howie's Restaurant, 29 Waterloo Place, Edinburgh, EH1 3BQ (see map).

Wireless Access
The workshop venue, 15 South College Street, has wireless access throughout. On arrival you will be given instructions and a code for accessing the wireless network.

Registration Fee and Financial Matters
The registration fee for this meeting is 100.00 GBP.  This should be paid by FRIDAY 10 FEBRUARY by completing the details on this credit/debit card payment form.   As email is not secure, please print the form and return it by fax using the fax number at the top of the form.   ICMS will take your payment and a receipt will be sent to you.  Alternatively, we can accept sterling cheques, made payable to Heriot-Watt University but sent to Audrey Brown, ICMS, 15 South College Street, Edinburgh, EH8 9AA.  If you have any difficulty in paying in advance, please email Audrey Brown (email address below).   For Speakers only - no registration fee is required - you will be given a claim form for travel expenses when you arrive at Registration.  

All enquiries about arrangements for this workshop should be addressed to audrey.brown at icms.org.uk   

 

Programme

Sunday 4 Mar 2012   One-day training course for PhD students at the Informatics Forum, covering key concepts in heterogeneity, noise, delays, and plasticity in neural systems.  Tutorial lectures by Wechselberger, Kuske, Clopath and Wolf.

 

Monday 5 Mar 2012 

09.00 - 10.30	Registration - ground floor, 15 South College Street
10.30 - 10.45	Welcome and introductions
10.45 - 11.15	Toni Guillamon (Universitat Politècnica de Catalunya) Isochron-based extensions of phase response curves
11.15 - 11.45	Martin Wechselberger (University of Sydney) Pseudo-plateau bursting in a pituitary cell model - a geometric theory
11.45 - 12.15	Peter Ashwin (University of Exeter) Criteria for robustness of heteroclinic cycles in neural microcircuits
12.15 - 14.00	Lunch break
14.00 - 14.30	Rachel Kuske (University of British Columbia) Interactions of noise and bifurcation structure in neural dynamics
14.30 - 15.00	Stephen Coombes (University of Nottingham) Interface dynamics in planar neural field models
15.00 - 17.00	Open discussion of new and important research areas in Mathematical Neuroscience (panel led)
17.00 - 18.30	Poster session and wine reception - 15 South College Street

 

Tuesday 6 Mar 2012

09.00 - 09.30	Boris Gutkin (École Normale Supérieure) Uncovering intrinsic spike generating dynamics with noise: case of inverse stochastic resonance in neurons
09.30 - 10.00	Nicholas Swindale (University of British Columbia) The relationship between spikes and local field potentials during periods of spontaneous activity in cat visual cortex
10.00 - 10.45	Coffee
10.45 - 11.15	Stefan Rotter (University of Freiburg) Spike train correlations derived from anatomical microstructure
11.15 - 11.45	Alessandro Torcini (Consiglio Nazionale delle Ricerche) Stability of the splay state in networks of pulse-coupled neurons
11.45 – 12.15	Fred Wolf (Max Planck Institute for Dynamics and Self-Organization) Theoretical neuroscience, nonlinear dynamics and synchronization in cortical neural networks, function and development of the visual cortex, sensory processing in the auditory system
12.15 -13.00	Buffet lunch (in the Chapterhouse, ground floor – to coincide with posters)
12.45 - 14.15	Poster session - 15 South College Street
14.15 – 18.00	Breakout sessions focusing on new scientific ideas arising at the conference
19.00	Conference Dinner - Howies, Waterloo Place

 

Wednesday 7 Mar 2012

09.00 - 09.30	Gabriel Lord (Heriot-Watt University) Stochastic travelling waves and neural dendrites
09.30 - 10.00	Jonathan Touboul (College de France) Stochastic neural fields: mean-field limits and dynamics
10.00 - 10.45	Coffee
10.45 – 11.15	Dmitri Chklovskii (Janelia Farm Research Campus) Predictive coding in sensory systems
11.15 - 11.45	Carina Curto (University of Nebraska-Lincoln) Encoding memories as perturbations of rank 1 threshold-linear networks
11.45 - 12.15	Claudia Clopath (Columbia University) Storage of correlated patterns in binary and bistable Purkinje cell models
12.15 - 14.00	Buffet lunch (in the Chapterhouse, ground floor)
14.00 - 16.00	Open discussion of future challenges and new directions in Neurodynamics (panel led)
16.00 – 16.15	Conclusion

 

Presentations:

Presentation Details
Ashwin, Peter
Criteria for robustness of heteroclinic cycles in neural microcircuits
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Heteroclinic behaviour or winnerless competition is a complex but analysable behaviour of dynamical switching between linearly unstable states that can appear in a range of neural microcircuit models both of Lotka-Volterra type and for more general coupled nonlinear systems of cells. We will discuss a simple but versatile test [1] to determine where a particular heteroclinic cycle in the dynamics is robust, depending on the invariant subspace structure. We use this to show that the robustness of heteroclinic cycles observed in a particular neural microcircuit [2] is due to the assumed form of synaptic coupling. [1] P. Ashwin, O. Karabacak and T. Nowotny, J. Mathematical Neuroscience 2011 [2] T. Nowotny and M. Rabinovich, Phys Rev Letts, 2007, 98:128126
Chklovskii, Dmitri
Predictive coding in sensory systems
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Early stages of sensory systems face the challenge of compressing information from a large number of receptors onto a much smaller number of projection neurons, a so called communication bottleneck. To make more efficient use of limited bandwidth, compression may be achieved using predictive coding, whereby predictable, or redundant, components of the stimulus are removed. In the case of the retina, Srinivasan et al. (1982) suggested that feedforward subtraction of a linear prediction generated from nearby receptors implements such compression, resulting in biphasic center-surround receptive fields. However, inhibition often operates in a feedback manner and with non-linear input output transformations, considerably complicating the dynamics of such circuits. Here, we solve the transient non-linear recurrent dynamics of a generic early sensory circuit in response to a step-like stimulus. We then demonstrate that the non-linearity improves compression. We show that interneuron activity in time constructs progressively less sparse but more accurate representations of the stimulus, thus providing a powerful theoretical framework to understand the dynamics of early sensory processing in a variety of physiological experiments. More generally, our results demonstrate that highly non-trivial computations, at the forefront of modern signal processing, can be mapped onto a concrete neuronal circuit.
Clopath, Claudia
Storage of correlated patterns in binary and bistable Purkinje cell models
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Purkinje cells (PCs) of the cerebellar cortex have long been considered to perform similarly as perceptrons: Given an input pattern in the granular layer, they should learn to provide an adequate motor output, thanks to plasticity of the parallel fiber (PF) to PC synapses, under the supervision of the climbing fiber input which is assumed to carry an error signal (Marr 1969, Albus 1971). Supervised learning in the perceptron model has been studied extensively in the case of random uncorrelated input/output associations. In particular, it is known that when synapses are constrained to be positive (to account for the fact that PF-PC synapses are excitatory), the synaptic weight distribution at maximal storage capacity is composed of a large fraction of zero-weight synapses (‘silent’ synapses, Brunel et al. 2004). However, in the case of the cerebellum, the assumption of uncorrelated inputs and outputs is clearly unrealistic, as any naturalistic inputs/motor sequences will carry some substantial degree of temporal correlations. We therefore investigated both the capacity and the optimal connectivity in feed-forward networks learning associations between temporally correlated input/output sequences. We then consider a bistable output to mimic the postulated bistability of the PC (Yartsev et al. 2009, Loewenstein et al. 2005, Williams et al. 2002, Oldfield et al. 2010). We show that bistability can increase capacity, when the output correlation is bigger than the input correlation. Moreover, the weight distribution of the PF-PC synapses consists in any case of a large number of silent synapses and does not depend on the level of correlations.
Coombes, Stephen
Interface dynamics in planar neural field models
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Neural field models describe the coarse-grained activity of populations of interacting neurons. Because of the laminar structure of real cortical tissue they are often studied in two spatial dimensions, where they are well known to generate rich patterns of spatiotemporal activity. Such patterns have been interpreted in a variety of contexts ranging from the understanding of visual hallucinations to the generation of electroencephalographic signals. Typical patterns include localized solutions in the form of travelling spots, as well as intricate labyrinthine structures. These patterns are naturally defined by the interface between low and high states of neural activity. Here we derive the equations of motion for such interfaces and show, for a Heaviside firing rate, that the normal velocity of an interface is given in terms of a non-local Biot-Savart type interaction over the boundaries of the high activity regions. This exact, but dimensionally reduced, system of equations is solved numerically and shown to be in excellent agreement with the full nonlinear integral equation defining the neural field. We develop a linear stability analysis for the interface dynamics that allows us to understand the mechanisms of pattern formation that arise from instabilities of spots, rings, stripes and fronts. We further show how to analyze neural field models with linear adaptation currents, and determine the conditions for the dynamic instability of spots that can give rise to breathers and travelling waves.
Curto, Carina
Encoding memories as perturbations of rank 1 threshold-linear networks
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It is widely believed that networks of neurons in the brain encode memories via their patterns of synaptic connections. Given a list of memories, however, it is still an unsolved problem how to arrange the connectivity matrix of a network so that exactly those memories are encoded, while avoiding unwanted "spurious" states. The problem is especially challenging when overlapping memory patterns are encoded, although this case is prevalent in the brain. Here we develop a perturbative approach to the encoding problem, where we fix a background architecture for the network and investigate what sets of memory patterns can be encoded via small perturbations of the synaptic weights. We find large families of sets of overlapping memories that can be encoded exactly as fixed point attractors of threshold-linear networks.
Guillamon, Toni
Isochron-based extensions of phase response curves
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The phase of an oscillator such as a spiking neuron is one of the main indicators of the eects of external stimuli on the (membrane potential) dynamics. Experimentally, the phase advancement is mostly computed through phase response curves (PRCs) obtained from recordings of the time variations in reaching the next peak of the membrane potential; successful methods have been used to predict it by means of theoretical PRCs evaluated on the attractor (limit cycle). However, stimulation in transient states may induce phase advancements that differ from the predictions given in the asymptotic state. By computing the isochrons (curves of constant phase) in a vicinity of the limit cycle, we are able to accurately generalize the PRCs to the transient states and, as well, to provide a methodology to compute the phase advancement under any type of stimulus (weak or strong, instantaneous or long-lasting). We will use theoretical examples to illustrate the goodness of the generalized PRCs, especially in cases of "weak" attractors or high-frequency stimuli;we will also remark how the knowledge of second-order PRCs, together with a geometrical interpretation of the isochrons, can help to use the contribution of successive return times to refine experimentally computed PRCs. Collaborators: Oriol Castejón (UPC) and Gemma Huguet (NYU).
Gutkin, Boris
Uncovering intrinsic spike generating dynamics with noise: case of inverse stochasitc resonance in neurons
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It is widely appreciated that adding noise in the inputs of integrator-to-threshold models, such as integrate and fire neurons, tends to increase their activity. Tuning of such noise modulated response to a signal has been called Stochastic Resonance. Here we will report on a phenomenon where activity is selectively quenched by noise inputs. First we will discuss results for single neurons with type II dynamics, with emphasis on noise-induced changes in the repetitive firing of Hodgkin-Huxley model neurons. When such models are stimulated with a constant additive current, there is a critical input current density µ=µc at which sustained periodic firing occurs. For a range of values of the mean current density near the critical value, we find that the firing rate is greatly reduced by noise, even of quite a small amplitude. We also find that the firing rate undergoes a minimum as the noise increases, a phenomenon which is opposite in character to the familiar one of stochastic resonance and hence can be named "inverse stochastic resonance" or ISR. We discuss the geometric and dynamical conditions for this phenomenon to occur, including the bistability between the stable rest point (a stable focus) and sustained firing (stable limit cycle). We suggest that the observation of the noise-induced inhibition and its tuning with noise strength may be an indicator of such bistability. We then show that such inverse stochastic resonance occurs in Purkinje neurons, that are the output cells of the cerebellar cortex. This suggests that Purkinje neurons are indeed bistable and that this bistability is an intrinsic membrane property, which allows them to switch rapidly between active (up) and quiescent (down) states. Finally I will discuss a reduced model of Purkinje neuron firing that shows ISR and how properly tuned noise can control the operating mode of the Purkinje neuron (between memory-holding and transient signal-transduction).
Kuske, Rachel
Interactions of noise and bifurcation structure in neural dynamics
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We consider the impact of stochastic effects interacting with bifurcation structure in the nonlinear dynamics of neural models. A variety of phenomena can play a significant role, including variations on coherence resonance, noise-induced mixed mode oscillations, competition between in-phase/anti-phased and localized states, different types of spike time reliability, as well as feedback between amplitude and phase. The roles of multiple timescales, delays, and different types of coupling, including coupling through external noise, are discussed.
Lord, Gabriel
Stochastic travelling waves and neural dendrites
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We will examine numerical solution of travelling waves in stochastically forced PDEs and the effects of noise in the Spike-diffuse-spike (SDS) and Baer-Rinzel (BR) models. We show that the speed of wave propagation in the SDS and BR models respectively decreases and increases as the noise intensity in the spine heads increases. We show that the correlation time and length scales of the noise can enhance propagation of travelling wave solutions where the white noise dominates the signal and produces noise induced phenomena.
Rotter, Stefan
Spike train correlations derived from anatomical microstructure
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Spike train correlations reflect the structure of the network. Correlations are caused, for instance, by direct synaptic interaction and by shared input. In recent work, we considered the contributions of more indirect, multi-synaptic pathways by accounting for the connectivity motifs that arise in recurrent networks of arbitrary topology. Mathematical analysis using Hawkes processes allowed us to relate rates and correlations of spike trains to the fine-scale anatomical structure of the network. Numerical simulations demonstrate that the dynamic point process model also provides an excellent approximation to networks of LIF neurons, via linear response theory. Specifically, we considered power series expansions of firing rates and pairwise correlations, respectively, in terms of the kernel matrix encoding synaptic connectivity. Its components correspond directly to the relevant structural motifs of the network. Depending on the degree of recurrence, one can predict the influence of multi-synaptic pathways on activity dynamics, and thus identify those network motifs that make significant contributions to spike train correlations. This work demonstrates that the microstructure of neuronal networks in the brain exerts strong and specific influence on its activity dynamics. Interacting stochastic point processes represent an efficient tool to characterize the spiking dynamics of recurrent networks with arbitrary topology.
Swindale, Nicholas
The relationship between spikes and local field potentials during periods of spontaneous activity in cat visual cortex
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Recordings of spontaneous neural spike activity and local field potentials (LFP) (1 – 200 Hz bandwidth) were made with 54-channel polytrodes in anesthetised cat visual cortex. Spectral analysis of the LFP recordings revealed peaks at multiple frequencies in non-integer ratios that varied in intensity with position along the electrode and over time. Variability in peak frequency over time was also noted, with some bands wandering ±10 Hz over periods of minutes. The particular frequencies of the peaks were variable across animals but tended to be consistent within animals over periods of several hours. Spike-triggered averages of the LFP (ST-LFP waveforms) were calculated and analysed in the time and frequency domains. Spike-triggered averages of locally phase-randomised LFP waveforms were used as controls. In the time domain, ST-LFP waveforms for individual neurons were oscillatory with energy preceding and following spikes typically for 200 – 500 ms. Spectral analysis of these waveforms usually revealed one or more frequency peaks that were sub-sets of those present in the raw LFP signal, but which varied distinctively from cell to cell and across layers. These frequencies were often not present in the spike trains of the individual neurons. It has not so far been possible to prove that spontaneous firing is associated with different LFP frequency components acting in combination rather than at different times. Nevertheless, the results point to the possibility that during spontaneous activity some neurons fire in response to phase alignments of oscillatory inputs, with different cells responsive to different frequency combinations. The results also suggest that within the visual cortex there are networks, or groupings of cells, characterised by differing responsiveness to frequency-labelled pathways. (Martin A. Spacek, co-author)
Torcini, Alessandro
Stability of the splay state in networks of pulse-coupled neurons
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The stability of the dynamical states characterised by a uniform firing rate ("splay states") is analysed in a network of N globally pulse-coupled rotators (neurons) subjected to a generic velocity field. This is done by reducing the set of differential equations to an event driven map that is investigated in the limit of large network size. We show that the Floquet spectrum characterising the stability of the splay state can be decomposed in two components: (i) a long-wavelength component which is the only one usually considered in mean-field analysis [Abbott-van Vreesvijk, 1993]; (ii) a short-wavelenght component measuring the instability of "finite-frequency" modes. By developing a perturbative technique, we have found analytically that, in the limit of large N, the short-wavelenght spectrum scales as 1/N^2 for generic discontinuous velocity fields. Moreover, the stability of this component is determined by the sign of the jump at the discontinuity. Altogether, the form of the spectrum depends on the pulse shape but is independent of the velocity field. Furthermore, numerical results indicate that in the case of continuous velocity fields, the Floquet exponents scale faster than 1/N^2 (namely, as 1/N^4) and we even find strictly neutral directions in a wider class than the sinusoidal velocity fields considered by Watanabe and Strogatz in Physica D 74 (1994) 197-253. References R. Zillmer, R. Livi, A. Politi, and A. Torcini, Phys. Rev. E 76 (2007) 046102 M. Calamai, A. Politi, and A. Torcini, Phys. Rev. E 80, 036209 (2009) S. Olmi, A.Politi, and A. Torcini, "Stability of the splay state in networks of pulse-coupled neurons", submitted to J. Mathematical Neuroscience (2012)
Touboul, Jonathan
Stochastic neural fields: mean-field limits and dynamics
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In this talk I will consider large spatially extended ensembles of stochastic neurons nonlinearly interacting, gathering into different populations that cover a continuous space (a piece of cortex or a functional space). Due to the space locations, delays in the transmission of information need to be taken into account. I will present the derivation of the asymptotic equations related to such networks as the number of neurons go to infinity. The resulting equations are intricate infinite-dimensional McKean-Vlasov equations. In order to uncover the dynamics of such large networks, we instantiate a particular neuron model yielding in the limit Gaussian processes. The mean and standard deviation will satisfy deterministic delayed integro-differential equations allowing to uncover the role of noise in the dynamics: noise induced transition will be exhibited.
Wechselberger, Martin
Pseudo-plateau bursting in a pituitary cell model - a geometric theory
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I will present results on complex relaxation oscillatory patterns known as pseudo-plateau bursting using geometric singular perturbation theory. Such patterns are experimentally observed in, e.g., pituitary cells. I will show that 'canards' are responsible for these complex patterns and line out how to identify this canard phenomenon. Due to the singular nature of the problem, complex pattern generation can be directly related to ("almost discontinuous") return maps, a fascinating field within dynamical systems theory.

Participants

Name	Institution
Ashwin, Peter	University of Exeter
Avramidis, Eleftherios	University of Exeter
Bamber, Jon	University of Edinburgh
Bennett, James	University of Oxford
Bick, Christian	Max Planck Institute for Dynamics and Self-Organization
Borisyuk, Roman	Plymouth University
Botcharova, Maria	University College London
Bouchekhima, Nacer	The University of Warwick
Caudron, Quentin	University of Warwick
Chadwick, Angus	University of Edinburgh
Chklovskii, Dmitri	Janelia Farm Research Campus
Chua, Yam Song	University of Freiburg
Clopath, Claudia	Columbia Universtiy
Coombes, Stephen	University of Nottingham
Corcoran, Thomas	University of Sussex
Curto, Carina	University of Nebraska-Lincoln
Cutts, Catherine	University of Cambridge
Deniz, Taskin	University of Freiburg
Donnelly, Simon	University of Edinburgh
Elibol, Rahmi	Istanbul Technical University
Fontolan, Lorenzo	École Normale Supérieure
Garcia del Molino, Luis Carlos	Collège de France
Garry, Daniel	University of Manchester
Goodfellow, Marc	University of Manchester
Guillamon, Toni	Universitat Politècnica de Catalunya
Gutkin, Boris	École Normale Supérieure
Harris, Kenneth	Imperial College London
Hartley, Caroline	University College London
Hass, Joachim	Universität Heidelberg-Mannheim
Hebden, Peter	University of Warwick
Hennig, Matthias	University of Edinburgh
Hjorth, Johannes	University of Cambridge
Hyafil, Alexandre	École Normale Supérieure
Jarvis, Sarah	University of Freiburg
Kuske, Rachel	University of British Columbia
Lagzi, Fereshteh	University of Freiburg
Legros, Alexandre	Lawson Health Research Institute
Lewis, Sarah	Imperial College London
Lobov, Sergey	Institute of Applied Physics, Russian Academy of Sciences
Lord, Gabriel	Heriot-Watt University
Lowe, Scott	University of Edinburgh
Lynch, Stephen	Manchester Metropolitan University
Merrison, Robert	University of Plymouth
Michieletto, Davide	University of Warwick
Modolo, Julien	Lawson Health Research Institute
Mugruza Vassallo, Carlos	University of Dundee
Muthmann, Jens-Oliver	University of Edinburgh
Olmi, Simona	Istituto Nazionale di Fisica Nucleare
Padmanabhan, Ajith	University of Freiburg
Pelko, Miha	University of Edinburgh
Perez, Toni	Newcastle University
Pieczkowski, Jan	Kungliga Tekniska högskolan/University of Edinburgh
Puggioni, Paolo	University of Edinburgh
Rotter, Stefan	University of Freiburg
Russell, Noah	University of Nottingham
Santamaria, Fidel	University of Texas at San Antonio
Schmidt, Helmut	University of Nottingham
Schumacher, Johannes	University of Osnabrück
Sengor, Neslihan Serap	Istanbul Technical University
Shippi, Maria	University of Edinburgh
Sixt, Joerg	Springer UK
Smith, Ruth	University of Nottingham
Solanka, Lukas	University of Edinburgh
Sterratt, David	University of Edinburgh
Sweeney, Yann	University of Edinburgh
Swindale, Nicholas	University of British Columbia
Taylor, Peter	University of Manchester
Terry, John	University of Exeter
Thul, Ruediger	University of Nottingham
Timofeeva, Yulia	University of Warwick
Tomsett, Richard	Newcastle University
Torcini, Alessandro	Consiglio Nazionale delle Ricerche
Touboul, Jonathan	Collège de France
Tsaparin, Sergey	Saint Petersburg State University
Tucker, Colin	Morganic
van Rossum, Mark	University of Edinburgh
Wang, Yujiang	University of Manchester
Ward, Nick	University of Sussex & University College London
Wechselberger, Martin	University of Sydney
Wedgwood, Kyle	University of Nottingham
Williamson, David	University of Leeds
Wolf, Fred	Max Planck Institute for Dynamics and Self-Organisation
Yger, Pierre	Imperial College London
Yim, Man Yi	University of Freiburg
Zachariou, Margarita	University of Cyprus