12th Oct: David Coyle
Intelligent machines and human agency
Intelligent computing systems – particularly in research contexts – are becoming increasing complex. These systems have the potential to infer human intentions and then provide assistance or act on these inferences. This raises important questions regarding the ownership and control of actions when humans use, and interact with, new technologies. In neuroscience literature the sense of agency is defined as the experience of being in control of one’s own actions and, through this control, affecting the external word and having responsibility for the consequences of our actions. This talk will describe research I have undertaken over the past two years, in collaboration with psychiatrists and cognitive neuroscientists at the Behavioural and Clinical Neuroscience Institute in Cambridge. We have applied neuro-cognitive experimental techniques to investigate peoples’ experience of agency when interacting with intelligent computer interfaces, and with changing modalities of human-computer interactions. I will discuss two specific experiments, but would also like to discuss the ways in which inter-disciplinary collaborations, between human-computer interaction and neuroscience researchers, offers new opportunities to extend both disciplines. David Coyle is Lecturer in Human Computer Interaction with the Department of Computer Science, in the University of Bristol.
19th Oct: Alan Roberts
How to build the connectome of a small CNS controlling rhythmic activity’
The brainstem and spinal neurons and networks controlling swimming in hatchling frog tadpoles have been defined in some detail. A simple axon growth model can match real neuron populations and generate a synaptic connection map or “connectome”. When this connectome is mapped onto a functional model it can swim in response to brief “sensory” stimuli. Our knowledge of this system allows detailed questions to be asked about the crucial features of the neurons and network controlling a rhythmic activity, in particular a population of electrically coupled pacemaker neurons.
26th Oct: Jonathan Brooks
Exploring brainstem – spinal cord connectivity during distraction based analgesia
Distraction based analgesia is a robust finding from human and experimental animal studies. The amount of pain perceived by a subject can be modified by attention related processes, which allow continued performance at tasks during the experience of pain. The first point at which painful stimuli are processed in the central nervous system lies in the dorsal horn of spinal cord, and key areas in the brainstem (peri-aqueductal grey matter) and rostral ventromedial medulla have been shown to influence these incoming pain-related signals. I will present data from a recent functional magnetic resonance imaging (fMRI) study which explored these interactions through a 2×2 factorial design (factors: task difficulty – hard or easy; applied temperature – high or low). The question remains whether (in man) there is a tight coupling between the brainstem and spinal cord activity that facilitates the suppression of incoming nociceptive (i.e. pain-related) signals.
2nd Nov: Ruth Betterton
Brain waves: Gamma Oscillations in the Hippocampus
A neuronal oscillation can be broadly described as the synchronised firing of a population of cells. Gamma oscillations (30-100 Hz) are associated with a variety of cognitive functions including attention, sensory processing and learning and memory. We developed an in vitro preparation to study the properties of gamma oscillations within CA3 of the rat hippocampus. This system enabled concomitant local field potential and whole cell electrophysiological recordings. Simulations run in a computational model showed many of the properties observed in the slice preparation and in vivo work by others. Future work will extend both models for the investigation of the cholinergic modulation of these processes.
9th Nov: Rafal Bogacz
New evidence for Bayes’ theorem being hardwired in the basal ganglia
This talk will present results of two experiments testing predictions of a model assuming that during decision making the cortico-basal-ganglia circuit computes probabilities that considered alternatives are correct, according to Bayes theorem. The talk will start with a review of the model. Then it will present results of an experiment from the lab of Peter Magill in Oxford on the microcircuitry of globus pallidus (Mallet et al., 2012, Neuron), and an experiment performed by Chrystalina Antoniades from Oxford on the effect of deep brain stimulation on patients representation of probabilities.
16th Nov: Tom Jahans-Price
Hippocampal-prefrontal information coding during spatial decision-making
In order to investigate information processing during decision-making, we introduce a computational model describing a maze-based task in which rats have choose between a left or right turn depending on the direction of their previous turn (Jones & Wilson 2005, PLoS Biology 3 e402). The model uses differential equations to describe the behaviour and interactions of populations of neurons, and integrates sensory input with working memory and rule-learning to produce learning and performance that accurately recapitulate behavioural data from rats. The model predicts the occurrence of turn- and memory-dependent activity in neuronal networks subserving task performance.
We tested these model predictions using a new software toolbox (Maze Query Language, MQL) to analyse activity of prefrontal cortical (PFC) and hippocampal (CA1) neurons recorded from 6 adult rats during task performance. The firing rates of CA1 neurons discriminated context (i.e. precise trajectory between reward points on a given trial) but were not turn-selective. In contrast, we found a subset of PFC neurons selective for turn–direction and/or trajectory that display a gradual buildup of activity before the decision turn; turn-selectivity in PFC was significantly reduced during error trials. We found some PFC neurons selective for turn, some selective for context and some conjunctively encoding both.
These analyses complement data from neurophysiological recordings in non-human primates indicating that firing rates of cortical neurons correlate with integration of sensory evidence during perceptual decision-making. Further analyses of the rodent data will allow us to link this cortical processing to input from subcortical structures including hippocampus and striatum.
23rd Nov: Stafford Lightman and Jamie Walker
Neuroendocrine Dynamics
Oscillating levels of adrenal glucocorticoid hormones are essential for optimal gene expression, and for maintaining physiological and behavioural responsiveness to stress. The biological basis for these oscillations is not known, but a neuronal pulse generator within the hypothalamus has remained a popular hypothesis. We have used mathematical modelling combined with experiments to show that pulsatile hypothalamic activity is not required for generating ultradian glucocorticoid oscillations, and that the oscillations are generated by a sub-hypothalamic pituitary-adrenal system, which functions as a deterministic peripheral hormone oscillator with a characteristic ultradian frequency. We will present these findings and discuss some of the new challenges that follow on from our results
30th Nov: Alex Pavlides
A key pathology of Parkinson’s disease is the occurrence of persistent beta oscillations. We investigate a model of the circuit composed of subthalamic nucleus and globus pallidus, which receives delayed feedback. This feedback models the closed loop structure of the basal ganglia. I will show how the network’s stability and frequency is influenced by the delayed feedback and discuss how this model builds on earlier work.