Centre for Computational Neuroscience and Robotics - CCNR


Showcase of recent publications

How active behaviour stabilises neural activity

Buckley CL, Toyoizumi T (2018) A theory of how active behavior stabilises neural activity: Neural gain modulation by closed-loop environmental feedback. PLoS Comput Biol 14(1): e1005926.

Animals actively exploring or interacting with their surroundings must process a cyclical flow of information from the environment through sensory receptors, the central nervous system, the musculoskeletal system and back to the environment. This closed-loop sensorimotor system is essential for an animal's ability to adapt and survive in complex environments. Importantly, closed loop feedback signals also regulate brainwide neural circuits for behavior. Specifically, the activity of coherent populations of neurons inform motor behaviours and in turn are influenced by sensory feedback signals mediated by the environment. We develop a theory that suggests that this feedback can explain the marked changes in large-scale neural dynamics and sensory processing (together referred to as brain state) that coincide with the onset of active behaviours. This feedback may contribute to flexible context dependent neural computations in brain systems.  

Propagation of beta/gamma rhythms in the cortico-basal ganglia circuits of the parkinsonian rat

West, T. O., Berthouze, L., Halliday, D. M., Litvak, V., Sharott, A., Magill, P. J., & Farmer, S. F. (2018). Propagation of beta/gamma rhythms in the cortico-basal ganglia circuits of the parkinsonian rat. Journal of neurophysiology119(5), 1608-1628.

We present a novel analysis of electrophysiological recordings in the cortico-basal ganglia network with the aim of evaluating several hypotheses concerning the origins of abnormal brain rhythms associated with Parkinson’s disease. We present evidence for changes in the directed connections within the network following chronic dopamine depletion in rodents. These findings speak to the plausibility of a “short-circuiting” of the network that gives rise to the conditions from which pathological synchronization may arise.

Neuronal energy consumption: biophysics, efficiency and evolution.

Niven, J E (2016) Neuronal energy consumption: biophysics, efficiency and evolution. Current Opinion in Neurobiology, 41. pp. 129-135. ISSN 0959-4388

Electrical and chemical signaling within and between neurons consumes energy. Recent studies have sought to refine our understanding of the processes that consume energy and their relationship to information processing by coupling experiments with computational models and energy budgets. These studies have produced insights into both how neurons and neural circuits function, and why they evolved to function in the way they do.

How do small neural populations support visually guided behaviours?

Dewar ADM, Wystrach A, Philippides A, Graham P (2017) Neural coding in the visual system of Drosophila melanogaster: How do small neural populations support visually guided behaviours? PLoS Comput Biol 13(10): e1005735.

A general problem in neuroscience is understanding how sensory systems organise information to be at the service of behaviour. Computational approaches can be useful for such studies as they allow one to simulate the sensory experience of a behaving animal whilst considering how sensory information should be encoded. In flies, small subpopulations of identifiable neurons are known to be necessary for particular visual tasks, and the response properties of these populations have now been described in detail. Surprisingly, these populations are small, with only 14 or 28 neurons each, which suggests something of a sensory bottleneck. In this paper, we consider how the population code from these neurons relates to the information required to control specific behaviours. We conclude that, despite previous claims, flies are unlikely to possess a general-purpose pattern-learning ability. However, implicit information about the shape and size of objects, which is necessary for many ecologically important visually guided behaviours, does pass through the sensory bottleneck. These findings show that nervous systems can be particularly economical when specific populations of cells are paired with specific visual behaviours. This is a general-interest finding for computer vision and biomimetics, as well as sensory neuroscience.

An inexpensive flying robot design for embodied robotics

Sabo, C., Yavuz, E., Cope, A., Gumey, K., Vasilaki, E., Nowotny, T., & Marshall, J. A. (2017, May). An inexpensive flying robot design for embodied robotics research. In Neural Networks (IJCNN), 2017 International Joint Conference on(pp. 4171-4178). IEEE.

Flying insects are capable of a wide-range of flight and cognitive behaviors which are not currently understood. The replication of these capabilities is of interest to miniaturized robotics, because they share similar size, weight, and energy constraints. Currently, embodiment of insect behavior is primarily done on ground robots which utilize simplistic sensors and have different constraints to flying insects. This limits how much progress can be made on understanding how biological systems fundamentally work. To address this gap, we have developed an inexpensive robotic solution in the form of a quadcopter aptly named BeeBot. Our work shows that BeeBot can support the necessary payload to replicate the sensing capabilities which are vital to bees' flight navigation, including chemical sensing and a wide visual field-of-view. BeeBot is controlled wirelessly in order to process this sensor data off-board; for example, in neural networks. Our results demonstrate the suitability of the proposed approach for further study of the development of navigation algorithms and of embodiment of insect cognition.