Abstract
Animals can learn causal relationships between pairs of stimuli separated in time and this ability depends on the hippocampus. Such learning is believed to emerge from alterations in network connectivity, but large-scale connectivity is difficult to measure directly, especially during learning. Here, we show that area CA1 cells converge to time-locked firing sequences that bridge the two stimuli paired during training, and this phenomenon is coupled to a reorganization of network correlations. Using two-photon calcium imaging of mouse hippocampal neurons we find that co-time-tuned neurons exhibit enhanced spontaneous activity correlations that increase just prior to learning. While time-tuned cells are not spatially organized, spontaneously correlated cells do fall into distinct spatial clusters that change as a result of learning. We propose that the spatial re-organization of correlation clusters reflects global network connectivity changes that are responsible for the emergence of the sequentially-timed activity of cell-groups underlying the learned behavior.
DOI:http://dx.doi.org/10.7554/eLife.01982.001
Ivan Pavlov famously discovered that dogs would salivate upon hearing a bell that had previously been used to signal food, even when there was no food present. This ability to connect events that occur close together in time is known as associative learning. But how is it supported within the brain?
In the late 1940s, neuroscientist Donald Hebb proposed that if one neuron persistently and repeatedly takes part in firing a second neuron, the connection between the two neurons will be strengthened. Thus, if neurons that encode the sound of a bell are active at the same time as neurons that encode receiving food, connections between the two groups will be strengthened, and this might enable the dogs to associate the two events.
However, animals can also learn to associate events that do not overlap in time. For example, we can associate a bout of food poisoning with a meal we consumed several hours earlier. In rodents, this type of learning is often studied using a task known as trace eyeblink conditioning, in which a tone signals the delivery of a puff of air to the eye after a short delay. Rodents eventually begin to blink in response to the tone, even thought the tone and the air puff are never presented simultaneously.
Two possibilities have been proposed for how this might occur: either the neurons that encode the tone remain active until delivery of the air puff, or different groups of neurons are successively activated in a relay that spans the interval between the tone and the air puff. Now, Modi et al. have used in vivo imaging in awake mice to obtain evidence in favour of the second option.
Mice were trained on the conditioning task while imaging was used to follow the activity of neurons in a region of the brain known as the hippocampus. As animals learned the task, neurons in part of the hippocampus called CA1 began to reorganize their firing patterns so that distinct groups of cells were active at each time point in the interval between the tone and the air puff. By contrast, hardly any neurons were active across the entire delay. The organized firing became particularly apparent at the same time as the mice first began to blink in response to the tone, and was only ever seen in animals that learned the task successfully.
As well as providing evidence to distinguish between competing theories of associative learning across a delay, this study is the first to follow in real-time the reorganization of networks of neurons within the hippocampus during this common type of learning.
DOI:http://dx.doi.org/10.7554/eLife.01982.002
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