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Title: Quantifying sensory information in continuous brain signals
Author: Siadatnejad, Sohail
ISNI:       0000 0004 7655 1888
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2014
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How is information processed in the brain? This is one of the main and most challenging questions in Neuroscience. The established hypothesis is that information is encoded in the temporal dynamics of spikes. However, there is growing evidence that continuous signals such as Local Field Potentials (LFP) can play an important role in coding neural information. Recently, Montemurro et al. [2008] reported that the phase-of-firing code, a mechanism previously observed in the hippocampus, is used in the sensory cortices for information encoding. In the phase-of-firing code, the neurons communicate spikes with respect to the phase of continuous signals produced by population activity, such as the LFP. Using information-theoretic measures, it was shown that when the timing of spikes was measured with respect to the phase of the LFP, an extra amount of sensory information was revealed in the responses that was not available from the spike codes alone. On the one hand, it still remains to be established how widespread this novel coding mechanism is. So far it has been verified in a few sensory modalities and it is not clear whether it is a universal coding mechanism. On the other, the estimation of information from continuous signals poses serious challenges from a technical point of view. The main reason is that accurate estimations of information measures require unrealistic amount of experimental data, mostly due to the presence of correlated activity. When these measures are applied to assess the information content in continuous responses, they lead to severe biases in the results, which can affect the conclusions regarding the validity of specific neural codes. The main goal of this Thesis is to explore the universality of the phase-of-firing code by studying it in novel systems, establish the origin of this code, and to develop more effcient numerical methods to accurately quantify information encoded in continuous brain signals. In particular, in this Thesis we investigate the role of continuous signals in sensory modalities where it has not been explored so far. We verified the presence of a phase-of-firing code in both the somatosensory cortex of the rat, and the visual thalamus of mice, thus giving support to the possible universality of this coding mechanism. While the phase-of-firing code found in these systems shares common features with those found in previous studies, we also characterised important differences. In the rat whisker system it was found that high frequency bands of the LFP play a more prominent role than that observed in the visual and auditory cortices of monkeys. This is compatible with the behavioural and mechanical constraints of this system, which require a high discrimination of finely structured temporal information in the stimulus. In the case of the visual thalamus of mice, we found that the phase-of-firing code contributes significantly to the encoding of irradiance information conveyed by melanopsin photoreceptors in the retina. We also investigated the source of the phase-of-firing codes in cortex by modelling the relationship between population spikes and LFP. In particular, we studied the interplay between the effective spatial integration of information resulting from population activity and the temporal memory imprinted in the LFP as a consequence of filtering mechanisms in the neural tissue. We found that most of the information in the LFP comes from a neural neighbourhood of a radius of about 150-350 μm, and a temporal history of 200-300 msec. Finally, we developed novel practical methods for quantifying the information content of continuous signals in the brain, which yield accurate results under realistic experimental conditions. These methods are based on the projection of the statistics of the response space into a lower dimensional manifold. In particular, we modelled continuous neural responses as a hierarchy of Markov models of increasing order, and found that the structure of temporal dependencies of real LFP can be captured by the lowest orders. This helped us put a new light on the previous studies regarding the phase-of-firing code. Altogether, these results contribute an advance both at the level of understanding information coding strategies combining spike and continuous signals, and the required computational methods to quantify accurately information in experimental neural responses.
Supervisor: Montemurro, Marcelo Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Local field potential ; Phase-of-firing code ; Neural code ; Information Theory