Faculty Bibliography

Animals are capable of detecting odorants in a single sniff, at extremely low concentrations. This ability is crucial for survival, yet it is unknown how the olfactory system supports detection at the perceptual limit. In the mouse olfactory bulb, inhalation of different odors leads to changes in the set of neurons activated, as well as when neurons are activated relative to each other (synchrony), and the onset of inhalation (latency). A key question is which features of stimulus evoked activity (e.g. rate, synchrony, or latency) are used to guide detection behavior? Here, we probed the sensitivity of mice to perturbations across each stimulus dimension using holographic two-photon (2P) optogenetic stimulation of olfactory bulb neurons, with cellular and single action potential resolution and millisecond precision. We found that mice can detect single action potentials evoked synchronously across <20 olfactory bulb neurons. Mice exhibited this sensitivity for artificial ensembles of mitral cells, as well as mixed ensembles of mitral and granule cells. Further, we discovered that detection depends strongly on the synchrony of activation across neurons, with detectability falling to near-chance levels with an imposed stimulus spread 3 30 ms, while detection performance was minimally perturbed by changes in the latency of activation relative to inhalation. These results reveal that mice are acutely attuned to single neurons and action potentials in olfactory circuits, and that synchrony across neurons may be a critical feature supporting the perceptibility of sparse ensemble activity signals

How does neural activity generate perception? The spatial identities and temporal latencies of activated units correlate with external sensory features, but finding the subspace of activity that is consequential for perception, remains challenging. We trained mice to recognize synthetic odors: optogenetically-driven spatiotemporal patterns of glomerular activity in the olfactory bulb. We then performed precise spatial or temporal perturbations on trained patterns and measured how recognition changes. Changes in recognition reflect the perceptual relevance of the modified feature. We modeled recognition as the matching of glomerular activity to learned templates, and uncovered what forms a perceptually-meaningful pattern template: activation sequences ordered by latencies relative to each other, with surprisingly minimal effect of sniff. Within templates, spatially-identified glomeruli contribute additively, with larger contributions from earlier-activated glomeruli. Template matching with these perceptually-meaningful features can account for animals' responses, with the degree of mismatch predicting changes in recognition. The model accurately generalizes to novel spatio-temporal manipulations of patterns, and produces non-linear responses that resemble the non-linear responses in the data. This is the first report to our knowledge, that not only establishes a causal role for neural activity sequences in perception, but also uncovers the perceptually-relevant coding schemes governing these sequences. Our synthetic approach reveals the fundamental logic of the olfactory code, and provides a general framework for testing links between sensory activity and perception

Sensory systems transform the external world into time-varying spike trains. What features of spiking activity are used to guide behavior? In the mouse olfactory bulb, inhalation of different odors leads to changes in the set of neurons activated, as well as when neurons are activated relative to each other (synchrony) and the onset of inhalation (latency). To explore the relevance of each mode of information transmission, we probed the sensitivity of mice to perturbations across each stimulus dimension (i.e., rate, synchrony, and latency) using holographic two-photon optogenetic stimulation of olfactory bulb neurons with cellular and single-action-potential resolution. We found that mice can detect single action potentials evoked synchronously across <20 olfactory bulb neurons. Further, we discovered that detection depends strongly on the synchrony of activation across neurons, but not the latency relative to inhalation.

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.

Olfactory inputs are organized in an array of functional units (glomeruli), each relaying information from sensory neurons expressing a given odorant receptor to a small population of output neurons, mitral/tufted (MT) cells. MT cells respond heterogeneously to odorants, and how the responses encode stimulus features is unknown. We recorded in awake mice responses from "sister" MT cells that receive input from a functionally- characterized, genetically identifed glomerulus, corresponding to a specifc receptor (M72). Despite receiving similar inputs, sister MT cells exhibit temporally diverse, concentration dependent, excitatory and inhibitory responses to most M72 ligands. In contrast, the strongest known ligand for M72 elicits temporally stereotyped, early excitatory responses in sister MT cells, consistent across a range of concentrations. Our data suggest that information about ligand affnity is encoded in the collective stereotypy or diversity of activity among sister MT cells within a glomerular functional unit. These fndings provide an evidence for spe-cifc network mechanisms, which implement a primacy coding model for concentration invariant odor recognition

Though the temporal precision of neural computation has been studied intensively, a data-driven determination of this precision remains a fundamental challenge. Reproducible spike patterns may be obscured on single trials by uncontrolled temporal variability in behavior and cognition and may not be time locked to measurable signatures in behavior or local field potentials (LFP). To overcome these challenges, we describe a general-purpose time warping framework that reveals precise spike-time patterns in an unsupervised manner, even when these patterns are decoupled from behavior or are temporally stretched across single trials. We demonstrate this method across diverse systems: cued reaching in nonhuman primates, motor sequence production in rats, and olfaction in mice. This approach flexibly uncovers diverse dynamical firing patterns, including pulsatile responses to behavioral events, LFP-aligned oscillatory spiking, and even unanticipated patterns, such as 7 Hz oscillations in rat motor cortex that are not time locked to measured behaviors or LFP.

Two-photon (2P) optogenetic stimulation is currently the only method for precise, fast, and non-invasive cellular excitation deep inside brain tissue; it is typically combined with holographic wavefront-shaping techniques to generate distributed light patterns and target them to multiple specific cells in the brain. During propagation in the brain, these light patterns undergo severe distortion, mainly due to scattering, which leads to a discrepancy between the desired and actual light distribution. However, despite its importance, measurement of these tissue-induced distortions and their effects on the light patterns has yet to be demonstrated in situ. To this end, holographic optogenetics confocally unraveled sculpting (HOCUS), a system for real-time in situ evaluation of holographic light patterns, based on confocally descanning the stimulation light's reflection from the brain, is developed. HOCUS measures both tissue and wave propagation properties and enables the real-time measurement and correction of the dimensions and positions of holographic spots relative to neurons targeted for stimulation. It can also be used to measure tissue attenuation length, and thus should facilitate future attempts to optimize the generated hologram to pre-compensate for tissue-induced distortions, thereby improving the reliability of 2P holographic stimulation experiments.

In the olfactory system, odor percepts retain their identity despite substantial variations in concentration, timing, and background. We study a novel strategy for encoding intensity-invariant stimulus identity that is based on representing relative rather than absolute values of stimulus features. For example, in what is known as the primacy coding model, odorant identities are represented by the conditions that some odorant receptors are activated more strongly than others. Because, in this scheme, odorant identity depends only on the relative amplitudes of olfactory receptor responses, identity is invariant to changes in both intensity and monotonic nonlinear transformations of its neuronal responses. Here we show that sparse vectors representing odorant mixtures can be recovered in a compressed sensing framework via elastic net loss minimization. In the primacy model, this minimization is performed under the constraint that some receptors respond to a given odorant more strongly than others. Using duality transformation, we show that this constrained optimization problem can be solved by a neural network whose Lyapunov function represents the dual Lagrangian and whose neural responses represent the Lagrange coefficients of primacy and other constraints. The connectivity in such a dual network resembles known features of connectivity in olfactory circuits. We thus propose that networks in the piriform cortex implement dual computations to compute odorant identity with the sparse activities of individual neurons representing Lagrange coefficients. More generally, we propose that sparse neuronal firing rates may represent Lagrange multipliers, which we call the dual brain hypothesis. We show such a formulation is well suited to solve problems with multiple interacting relative constraints.

Sampling regulates stimulus intensity and temporal dynamics at the sense organ. Despite variations in sampling behavior, animals must make veridical perceptual judgments about external stimuli. In olfaction, odor sampling varies with respiration, which influences neural responses at the olfactory periphery. Nevertheless, rats were able to perform fine odor intensity judgments despite variations in sniff kinetics. To identify the features of neural activity supporting stable intensity perception, in awake mice we measured responses of mitral/tufted (MT) cells to different odors and concentrations across a range of sniff frequencies. Amplitude and latency of the MT cells' responses vary with sniff duration. A fluid dynamics (FD) model based on odor concentration kinetics in the intranasal cavity can account for this variability. Eliminating sniff waveform dependence of MT cell responses using the FD model allows for significantly better decoding of concentration. This suggests potential schemes for sniff waveform invariant odor concentration coding.