Hippocampal Diversity in Neural Firing Dynamics

 

Science 25 Mar 2016 : 1440-1443

Diversity in neural firing dynamics supports both rigid and learned hippocampal sequences

Andres D. Grosmark, György Buzsáki

Department of Neuroscience, Columbia University Medical Center, New York, NY 10019, USA.

The Neuroscience Institute, School of Medicine, New York University, New York, NY 10016, USA.

Center for Neural Science, New York University, New York, NY 10016, USA.

[paraphrase]

Cell assembly sequences during learning are “replayed” during hippocampal ripples and contribute to the consolidation of episodic memories. However, neuronal sequences may also reflect preexisting dynamics. We report that sequences of place-cell firing in a novel environment are formed from a combination of the contributions of a rigid, predominantly fast-firing subset of pyramidal neurons with low spatial specificity and limited change across sleep-experience-sleep and a slow-firing plastic subset. Slow-firing cells, rather than fast-firing cells, gained high place specificity during exploration, elevated their association with ripples, and showed increased bursting and temporal coactivation during postexperience sleep. Thus, slow- and fast-firing neurons, although forming a continuous distribution, have different coding and plastic properties.

The restructuring of hippocampal networks through synaptic plasticity is necessary for the formation of new episodic memories.    Replay of hippocampal place-cell sequences during sharp wave ripples (SPW-Rs)    of waking immobility    and non–rapid eye movement sleep after learning has been proposed to support memory consolidation. Replay is conceptualized and typically studied as a phenomenon with higher-order interactions within populations of neurons taken to have similar properties. However, networks built from similar neurons are unstable, and recent findings demonstrate that biophysical properties of cortical pyramidal neurons are highly diverse and characterized by lognormal distributions of synaptic weights,    long-term firing rates, and spike bursts. Furthermore, temporal correlations of hippocampal neurons are largely preserved across brain states and environmental situations,    suggesting that learning-induced changes are constrained within a dynamically stable network. An example of a preexisting bias between place-cell sequences in a novel environment and sleep before the novel experience (preplay) has been described, although its computational relevance has been questioned recently. To clarify the relationship between preexisting biophysical properties of neurons and their contribution to learning, characterization of individual neurons is necessary. We performed such analyses during sleep in rats before and after they explored a novel environment.

We demonstrate that sequences of place cells in a novel environment are formed from a combination of relatively fast-firing group of pyramidal neurons with relatively unchanging temporal dynamics and a slow-firing plastic subset of neurons. Firing properties of neurons predicted their rigid and plastic features. Slow-firing neurons gained high place specificity during maze exploration and showed increased ripple-related recruitment during POST-experience sleep. In contrast, fast-firing neurons had low selectivity, have been shown previously to project to multiple targets and to form an interactive subnetwork responsible for global stability, thus allowing plasticity to take place in the remaining majority of slow-firing cells. Fast-firing neurons may generalize across situations, whereas slow-firing neurons may differentiate among them. Because replay sequence-forming neurons are drawn from the wide span of a continuous log-rate distribution with varying coding, biophysical, circuit, and plasticity properties, these events can forward a synthesis of preexisting and new information to downstream observer neurons.

[end of paraphrase]

 

Return to — Hippocampus