We are interested in two aspects of neural circuits; how they perform computation and how they store information. To understand this we focus on the computations performed by neural circuits in sensory pathways and how information is stored in learning centres such as the hippocampus and amygdala.
Computation by Neural Circuits
Neural circuits are built from two main types of neuron, excitatory or inhibitory and have 3 main properties:
- They receive an input, this can be from a different neural circuit or directly from receptor neurons.
- They are composed of a group of neurons forming synapses (connections) with one another.
- They have output neurons, neurons that transmit information from its neural circuit to form the input to other neural circuits or to directly excite muscles. Excellent books detailing some neural circuits can be found here and here
A computation is just a series of steps or operations that transform some information into a different, often more useful form. The building blocks of any computation involve operators, e.g. arithmetic or logical operators. Single neurons can perform all of these operations on their synaptic inputs. They can achieve this via different mechanisms, an example is illustrated in the figure below, showing that the particular arrangement of excitatory and inhibitory synapses can generate different logic gates.
Very simple arrangements of neurons can implement signal processing algorithms, for example, the simple circuit shown below acts as a high-pass filter with automatic gain control. When a new input signal arrives both the excitatory and inhibitory neurons become active, but the excitatory neuron will only respond to the stimulus onset as it is subsequently suppressed by the inhibitory neuron (Feedforward inhibition). The activity of the inhibitory neuron also reduces the size of subsequent inputs (Feedback inhibition).
We have two general questions on neural circuits: What computations are performed and how does biology solve these computations?
Learning
Brain vs Computer Modern computers perform computation using software that runs on general purpose hardware. Brains are distinctly different; they have tailored hardware to perform different computations. Neural circuits fulfil the role of both the hardware and software.
To learn new tasks, associate events with positive or negative outcomes, neural circuits must change themselves. They do this through molecular, synaptic and cellular changes which result in new brain wide circuits being formed, where the same ensembles of neurons get activated when carrying out a task or in response to a previous salient experience. Together with Dr Steven Clapcote’s lab we are investigating how molecular changes give rise to altered information storage in neural circuits and how these changes affect behaviour and cognition.
Previous projects
Orientation & Dynamic Predictive Coding in the Retina
Sensory systems must reduce the transmission of redundant information to function efficiently. One strategy is to continuously adjust the sensitivity of neurons to suppress responses to common features of the input while enhancing responses to new ones. In this project we used 2-photon imaging of the synaptic transmitter glutamate. Taking advantage of the genetically encoded […]
Motion Anticipation in the retina
General Features of the retinal connectome determine the computation of motion anticipation Light is converted into electrical signals by specialized cells in the retina called photoreceptors. This conversion process, termed phototransduction, is relatively slow, taking around a tenth of a second. Although this might not sound like a long time, it is enough for a […]
Rapid mapping of receptive fields
And its application to multi-neuronal electrophysiology and imaging Neurons in sensory systems have receptive fields. In the somatosensory system, this might be an area of the skin to which the neuron is responsive, whereas in the visual system the receptive field is an area on the retina. Several properties of the receptive field are of […]
Olfactory bulb microcircuit
This project explored the intrinsic properties of olfactory bulb output neurons. We showed that input from the olfactory nerve activates Ca2+channels located in the primary dendrites and these contribute to dendritic glutamate release. The resulting depolarisation and boosted glutamate release synchronises the activity of multiple output neurons belonging to the same glomerulus. The papers can be found here […]
Potassium channels in the auditory brainstem
A series of projects examined how different voltage-gated K+ channels enable a fast inverting relay neuron in the auditory brainstem to fulfil its specialised role in sound source localisation. Key papers from this work are here and here. The image to the left shows Kv3.1 staining in the MNTB, note the puncta in the axons where the nodes of […]
Spinal Sensory Neurons with novel action potentials
This project explored the physiological properties of the intriguing cerebrospinal fluid contacting neurons within the spinal cord. These sensory neurons are able to sense bending of the spinal cord and are involved in regulating motor output from the spinal cord. We showed that these sensory neurons have unusual action potentials, rather than using the typical […]
Computations in neural circuits 