Persistence of neuronal representations

Science  23 Aug 2019: Vol. 365, Issue 6455, pp. 821-825

Persistence of neuronal representations through time and damage in the hippocampus

Walter G. Gonzalez, et.al. Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA. [paraphrase] How do neurons encode long-term memories? Bilateral imaging of neuronal activity in the mouse hippocampus reveals that, from one day to the next, ~40% of neurons change their responsiveness to cues, but thereafter only 1% of cells change per day. Despite these changes, neuronal responses are resilient to a lack of exposure to a previously completed task or to hippocampus lesions. Unlike individual neurons, the responses of which change after a few days,    groups of neurons with inter- and intrahemispheric synchronous activity show stable responses for several weeks. The likelihood that a neuron maintains its responsiveness across days is proportional to the number of neurons with which its activity is synchronous.    Information stored in individual neurons is relatively labile, but it can be reliably stored in networks of synchronously active neurons. Memories are processed and stored by complex networks of neurons across several circuits in the brain; however, little is known about how stable information is encoded in these neurons. The hippocampus plays an essential role in the formation of memories, and neurons in this brain area show robust responses to space (via place cells) or other cues relevant to the task. Neuronal activity in the hippocampus changes during learning and reexposure to an environment. However, what aspects of neuronal activity in the hippocampus persist during future visits to a familiar environment, how information is encoded in groups of neurons, and how lesions perturb the long-term maintenance of these neuronal patterns remain poorly understood. Neuronal representations in the hippocampus change over time as information is transferred from other brain areas, but how these changes are regulated is unknown. Long-term imaging of neuronal activity showed that during repeated visits to a familiar environment only 31% of neurons are active in any given session and 2.8 ± 0.3% are active in all sessions. To investigate the stability of neuronal representations in CA1, we studied both place cells and end cells (cells firing during periods of immobility at the ends of the track) Theoretical models have suggested that groups of neurons with synchronized activity may form cell assemblies able to encode learned representations for long periods of time. Cell assemblies that encode task-dependent cues have been observed in the hippocampus, but how these groups of neurons develop during learning, persist across days, or encode stable information is not known. Neuron pairs encoded higher information content (as defined by calculation of mutual information) than individual place or end cells, and the likelihood of a neuron maintaining its responsiveness to the same or a different field was proportional to its correlation with the other neuron in the pair. Do synchronized neurons form part of a larger neuronal network storing stable task information? Network graphs of correlated neuronal activity showed a clear behavior- dependent topology, evolving through learning and reorganizing upon transition from the home cage to the linear track. Graphs revealed dense clusters of neurons with preferences for specific behaviors or cues. Synchronization within cell groups was specific to the task performed. Using graphs, we observed that the likelihood of a neuron to remain a place cell or an end cell was proportional to the number of graph connections with other neurons. The cell group participation of a neuron in the graph could also be used to classify a neuron as a place cell, an end cell, or neither, without the need to observe the animal’s behavior. We could decode the field centroid location of place and end cells on the basis of the properties of near neighbors in the graph. We observed that, although the firing rate changed across sessions and tasks, the majority of neurons were active on most days. Altogether, these results support a model with three complementary features. First, neuronal representations in the hippocampus spontaneously change over time, such that it is rare to find cells whose fields persist longer than 35 days. Second, attractor-like mechanisms ensure the persistence of representations over short periods of time (days), even if the animals are not exposed to the task or if the circuit is perturbed by lesions. Third, our results suggest that information is dynamically stored in CA1. Our results show that stable representations of a task are stored in groups of CA1 neurons with synchronous activity. On the basis of the known connectivity of CA1 neurons, this synchrony may arise from local inhibition within CA1 or common input from CA3. We observe that the firing patterns of neurons that are neighbors in a graph can be used to decode current and future drifts in the response field of a neuron, suggesting that future changes in place cells are, to some extent, encoded during task performance. Overall, we demonstrate that activity patterns of individual neurons gradually change over time, whereas the activity of groups of synchronously active neurons ensures the persistence of representations in CA1. [end of paraphrase]