Visually evoked neuronal ensembles reactivate during sleep

Neural ensembles: role of intrinsic excitability and its plasticity

Synaptic connectivity defines groups of neurons that engage in correlated activity during specific functional tasks. These co-active groups of neurons form ensembles, the operational units involved in, for example, sensory perception, motor coordination and memory (then called an engram). Traditionally, ensemble formation has been thought to occur via strengthening of synaptic connections via long-term potentiation (LTP) as a plasticity mechanism. This synaptic theory of memory arises from the learning rules formulated by Hebb and is consistent with many experimental observations. Here, we propose, as an alternative, that the intrinsic excitability of neurons and its plasticity constitute a second, non-synaptic mechanism that could be important for the initial formation of ensembles. Indeed, enhanced neural excitability is widely observed in multiple brain areas subsequent to behavioral learning. In cortical structures and the amygdala, excitability changes are often reported as transient, even though they can last tens of minutes to a few days. Perhaps it is for this reason that they have been traditionally considered as modulatory, merely supporting ensemble formation by facilitating LTP induction, without further involvement in memory function (memory allocation hypothesis). We here suggest-based on two lines of evidence-that beyond modulating LTP allocation, enhanced excitability plays a more fundamental role in learning. First, enhanced excitability constitutes a signature of active ensembles and, due to it, subthreshold synaptic connections become suprathreshold in the absence of synaptic plasticity (iceberg model). Second, enhanced excitability promotes the propagation of dendritic potentials toward the soma and allows for enhanced coupling of EPSP amplitude (LTP) to the spike output (and thus ensemble participation). This permissive gate model describes a need for permanently increased excitability, which seems at odds with its traditional consideration as a short-lived mechanism. We propose that longer modifications in excitability are made possible by a low threshold for intrinsic plasticity induction, suggesting that excitability might be on/off-modulated at short intervals. Consistent with this, in cerebellar Purkinje cells, excitability lasts days to weeks, which shows that in some circuits the duration of the phenomenon is not a limiting factor in the first place. In our model, synaptic plasticity defines the information content received by neurons through the connectivity network that they are embedded in. However, the plasticity of cell-autonomous excitability could dynamically regulate the ensemble participation of individual neurons as well as the overall activity state of an ensemble.

Cortical reactivations predict future sensory responses

Many theories of offline memory consolidation posit that the pattern of neurons activated during a salient sensory experience will be faithfully reactivated, thereby stabilizing the pattern1,2. However, sensory-evoked patterns are not stable but, instead, drift across repeated experiences3-6. Here, to investigate the relationship between reactivations and the drift of sensory representations, we imaged the calcium activity of thousands of excitatory neurons in the mouse lateral visual cortex. During the minute after a visual stimulus, we observed transient, stimulus-specific reactivations, often coupled with hippocampal sharp-wave ripples. Stimulus-specific reactivations were abolished by local cortical silencing during the preceding stimulus. Reactivations early in a session systematically differed from the pattern evoked by the previous stimulus-they were more similar to future stimulus response patterns, thereby predicting both within-day and across-day representational drift. In particular, neurons that participated proportionally more or less in early stimulus reactivations than in stimulus response patterns gradually increased or decreased their future stimulus responses, respectively. Indeed, we could accurately predict future changes in stimulus responses and the separation of responses to distinct stimuli using only the rate and content of reactivations. Thus, reactivations may contribute to a gradual drift and separation in sensory cortical response patterns, thereby enhancing sensory discrimination7.