Cracking the brain’s code: How do brain rhythms support information processing?

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Abstract

The brain processes information sensed from the environment and guides behaviour. A fundamental component in this process is the storage and retrieval of past experiences as memories, which relies on the hippocampal formation. Although there has been a great progress in understanding the underlying neural code by which neurons communicate information, there are still open questions.Neural activity can be measured extracellularly as either spikes or field potentials. Isolated spikes and bursts of high-frequency spikes followed by silent periods can transmit messages to distant networks. The local field potential (LFP) reflects synaptic activity within a local network. The interplay between the two has been linked to cognitive functions, such as memory, attention and decision making. However, the code by which this neural communication is achieved is not well understood.We investigated a mechanism by which local network information contained in LFP rhythms can be transmitted to distant networks in the formof spike patterns fired by bursting neurons. Since rhythms within different frequency bands are prevalent during behavioural states, we studied this encoding during different states within the hippocampal formation. In the first paper, using a computational model we show that bursts of different size preferentially lock to the phase of the dominant rhythm within the LFP.We also present examples showing that bursting activity in the subiculum of an anaesthetised rat was phase-locked to delta or theta rhythms as predicted by the model.In the second paper, we explored possible neural codes by which bursting neurons can encode features of the LFP.We used the computational model reported in the first paper and analysed recordings from the subiculum of anaesthetised rats and the medial entorhinal cortex of an awake behaving rat. We show that bursting neurons encoded information about the instantaneous voltage, phase, slope and/or amplitude of the dominant LFP rhythm (delta or theta) in their firing rate. In addition, some neurons encoded about 10-15% of this information in intra-burst spike counts.We subsequently studied how the interactions between delta or theta rhythms can transfer information between different areas within the hippocampal formation. In the third paper, we show that delta and theta rhythms can act as separate routes for simultaneously transferring segregate information between the hippocampus and the subiculum of anaesthetised mice. We found that the phase of the rhythms conveyed more information than amplitude.We next investigated whether neurodegenerative pathology affects this information exchange. We compared information transfer within the hippocampal formation of young transgenic mice exhibiting Alzheimer’s disease-like pathology and healthy aged-matched control mice and show that at early stages of the disease the information transmission by LFP rhythm interactions appears to be intact but with some differences.The outcome of this project supports a burst code for relaying information about local network activity to downstream neurons and underscores the importance of LFP phase, which provides a reference time frame for coordinating neural activity, in information exchange between neural networks.

Keyword(s)

Bursting; Computational neuroscience; Entorhinal cortex; Hippocampus; Information theory; Local field potential; Neural coding; Subiculum; Transfer entropy

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