Ensemble encoding of conditioned fear by prefrontal somatostatin interneurons

Neurons preferentially activated by learning have been ascribed the unique potential to encode memory. However, it remains unclear which genetically-defined cell types are recruited as part of such an ensemble, or what role discrete subpopulations play in behavior. Here we show that fear conditioning activates a heterogeneous neural ensemble in the medial prefrontal cortex (mPFC), comprised to a large degree of GABAergic interneurons immunoreactive for somatostatin (SST-INs). Using an intersectional genetic approach, we demonstrate that fear learning-activated SST-INs exhibit distinct circuit properties, are preferentially reactivated during memory retrieval, and mediate the expression of defensive freezing. We further show that a rewarding experience, morphine treatment, activates an orthogonal SST-IN population that exerts opposing control over fear. These results outline an important role for discrete GABAergic ensembles in fear memory encoding, and point to an unappreciated capacity for functional specialization among SST-INs.

Global and local interference effects in ensemble encoding are best explained by interactions between summary representations of the mean and the range

Through ensemble encoding, the visual system compresses redundant statistical properties from multiple items into a single summary metric (e.g., average size). Numerous studies have shown that global summary information is extracted quickly, does not require access to single-item representations, and often interferes with reports of single items from the set. Yet a thorough understanding of ensemble processing would benefit from a more extensive investigation at the local level. Thus, the purpose of this study was to provide a more critical inspection of global-local processing in ensemble perception. Taking inspiration from Navon (Cognitive Psychology, 9(3), 353-383, 1977), we employed a novel paradigm that independently manipulates the degree of interference at the global (mean) or local (single item) level of the ensemble. Initial results were consistent with reciprocal interference between global and local ensemble processing. However, further testing revealed that local interference effects were better explained by interference from another summary statistic, the range of the set. Furthermore, participants were unable to disambiguate single items from the ensemble display from other items that were within the ensemble range but, critically, were not actually present in the ensemble. Thus, it appears that local item values are likely inferred based on their relationship to higher-order summary statistics such as the range and the mean. These results conflict with claims that local information is captured alongside global information in summary representations. In such studies, successful identification of set members was not compared with misidentification of items within the range, but which were nevertheless not presented within the set.

Spike-timing-dependent ensemble encoding by non-classically responsive cortical neurons

Neurons recorded in behaving animals often do not discernibly respond to sensory input and are not overtly task-modulated. These non-classically responsive neurons are difficult to interpret and are typically neglected from analysis, confounding attempts to connect neural activity to perception and behavior. Here, we describe a trial-by-trial, spike-timing-based algorithm to reveal the coding capacities of these neurons in auditory and frontal cortex of behaving rats. Classically responsive and non-classically responsive cells contained significant information about sensory stimuli and behavioral decisions. Stimulus category was more accurately represented in frontal cortex than auditory cortex, via ensembles of non-classically responsive cells coordinating the behavioral meaning of spike timings on correct but not error trials. This unbiased approach allows the contribution of all recorded neurons – particularly those without obvious task-related, trial-averaged firing rate modulation – to be assessed for behavioral relevance on single trials.

Prior Experience Informs Ensemble Encoding

People quickly form summary representations that capture the statistical structure in a set of simultaneously presented objects. We present evidence that such ensemble encoding is informed not only by the presented set of objects, but also by a meta-ensemble, or prototype, that captures the structure of previously viewed stimuli. Participants viewed four objects (shaded squares in Experiment 1; emotional expressions in Experiment 2) and estimated their average by adjusting a response object. Estimates were biased toward the central value of previous stimuli, consistent with Bayesian models of how people combine hierarchical sources of information. The results suggest that an inductively learned prototype may serve as a source of prior information to adjust ensemble estimates. To the extent that real environments present statistical structure in a given moment as well as consistently over time, ensemble encoding in real-world situations ought to take advantage of both kinds of regularity.