Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception – Science Magazine

Ensemble activity and perception

The mechanisms by which sensory percepts are encoded in neural ensembles are still incompletely understood. Chong et al. used single-spot optogenetic stimulation to control neuronal activity in mouse olfactory glomeruli in space and time. Animals were trained to recognize a learned activity pattern that was likely perceived as a specific odor. The authors then systematically varied the activity patterns by changing either the activated glomeruli or the timing between activation of glomeruli to evaluate their impact on odor recognition. Glomeruli that were activated early during the synthetic odor contributed more to odor recognition than glomeruli that were subsequently activated. This approach allows neuroscience to explain how features combine in complex patterns to generate perception.

Science, this issue p. eaba2357

Advances in monitoring brain activity at large and fine scales have revealed tremendous complexity in how the brain responds to, and represents, the external world. Although many features in brain activity patterns (which brain cells fire and when) are found to correlate with changes in the external sensory world, it is not yet known which activity features are consequential for perception and how they are combined to generate percepts. Some studies have shown that many of these correlated changes in activity may be redundant or even epiphenomenal.

To address how brain activity generates perception, we directly and systematically manipulated neural activity in the mouse olfactory system while measuring perceptual responses. Mouse olfaction is an attractive model system because the relevant brain circuitry has already been carefully mapped out and is accessible for direct manipulation. We used genetically engineered mice in which brain cells can be activated simply by shining light on thema technique known as optogenetics. Optogenetics allowed us to directly generate and manipulate brain activity in a precise and parametric manner. We first trained mice to recognize light-driven activity patterns in the olfactory system, or synthetic odors. Subsequently, we measured how recognition changed as we systematically manipulated learned activity patterns. Some manipulations led to larger changes in recognition than others, and the degree of change reflected the importance of each manipulated feature to perception. By the additional manipulation of multiple features simultaneously, we could precisely quantify how individual features combined to produce perception.

The perceptual responses of mice not only depended on which groups of cells were activated, but also on their activation latencies, i.e., temporal sequences akin to timed notes in a melody. Critically, the most perceptually relevant activation latencies were defined relative to other cells in a sequence and not to brain or body rhythms (e.g., animal sniffing) as previously hypothesized from observational studies.Moreover, earlier-activated cells in the sequence had a larger effect on behavioral responses; modifying later cells in the sequence had small effects.To account for all results, we formulated a simple computational model based on template matching, in which new activity sequences are compared with learned sequences or templates.The model weighs relative timing within each sequence and also accounts for the greater importance of earlier-activated cells.Based on our model, the degree of mismatch between the new sequence and learned template predicts the extent to which recognition should degrade as neural activity changes across many different manipulations.

We developed an experimental and theoretical framework to map a broad space of precisely and systematically manipulated brain activity patterns to behavioral responses. Using this framework, we uncovered key computations made by the olfactory system on neural activity to generate percepts and derived a systematic model of olfactory processing directly relevant for perception. Our framework forms a powerful, general approach for causally testing the links between brain activity and perception or behavior. This framework is especially pertinent given the continued development of advanced tools for manipulating brain activity at fine scales across various brain regions.

(A) We trained mice to recognize synthetic odor patterns: artificially stimulated neural activity in the olfactory bulb. Patterns were defined in space (top right) and time (bottom right). (B) Perceptual responses were measured across systematic modifications of trained patterns. (C) Template-matching model of pattern activity (left) accounts for perceptual responses (right).

How does neural activity generate perception? Finding the combinations of spatial or temporal activity features (such as neuron identity or latency) that are consequential for perception remains challenging. We trained mice to recognize synthetic odors constructed from parametrically defined patterns of optogenetic activation, then measured perceptual changes during extensive and controlled perturbations across spatiotemporal dimensions. We modeled recognition as the matching of patterns to learned templates. The templates that best predicted recognition were sequences of spatially identified units, ordered by latencies relative to each other (with minimal effects of sniff). Within templates, individual units contributed additively, with larger contributions from earlier-activated units. Our synthetic approach reveals the fundamental logic of the olfactory code and provides a general framework for testing links between sensory activity and perception.

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