Augmenting insect olfaction performance through nano-neuromodulation.

Biological olfactory systems are highly sensitive and selective, often outperforming engineered chemical sensors in highly complex and dynamic environments. As a result, there is much interest in using biological systems to build sensors. However, approaches to read-out information from biological systems, especially neural signals, tend to be suboptimal due to the number of electrodes that can be used and where these can be placed. Here we aim to overcome this suboptimality in neural information read-out by using a nano-enabled neuromodulation strategy to augment insect olfaction-based chemical sensors. By harnessing the photothermal properties of nanostructures and releasing a select neuromodulator on demand, we show that the odour-evoked response from the interrogated regions of the insect olfactory system can not only be enhanced but can also improve odour identification.

Neuronal maturation-dependent nano-neuro interaction and modulation.

Nanotechnology-enabled neuromodulation is a promising minimally-invasive tool in neuroscience and engineering for both fundamental studies and clinical applications. However, the nano-neuro interaction at different stages of maturation of a neural network and its implications for the nano-neuromodulation remain unclear. Here, we report heterogeneous to homogeneous transformation of neuromodulation in a progressively maturing neural network. Utilizing plasmonic-fluors as ultrabright fluorescent nanolabels, we reveal that negative surface charge of nanoparticles renders selective nano-neuro interaction with a strong correlation between the maturation stage of the individual neurons in the neural network and the density of the nanoparticles bound on the neurons. In stark contrast to homogeneous neuromodulation in a mature neural network reported so far, the maturation-dependent density of the nanoparticles bound to neurons in a developing neural network resulted in a heterogeneous optical neuromodulation (i.e., simultaneous excitation and inhibition of neural network activity). This study advances our understanding of nano-neuro interactions and nano-neuromodulation with potential applications in minimally-invasive technologies for treating neuronal disorders in parts of the mammalian brain where neurogenesis persists throughout aging.

Neural manifolds for odor-driven innate and acquired appetitive preferences.

Sensory stimuli evoke spiking neural responses that innately or after learning drive suitable behavioral outputs. How are these spiking activities intrinsically patterned to encode for innate preferences, and could the neural response organization impose constraints on learning? We examined this issue in the locust olfactory system. Using a diverse odor panel, we found that ensemble activities both during ('ON response') and after stimulus presentations ('OFF response') could be linearly mapped onto overall appetitive preference indices. Although diverse, ON and OFF response patterns generated by innately appetitive odorants (higher palp-opening responses) were still limited to a low-dimensional subspace (a 'neural manifold'). Similarly, innately non-appetitive odorants evoked responses that were separable yet confined to another neural manifold. Notably, only odorants that evoked neural response excursions in the appetitive manifold could be associated with gustatory reward. In sum, these results provide insights into how encoding for innate preferences can also impact associative learning.

Plasmon-Enhanced Expansion Microscopy.

Expansion microscopy (ExM) is a rapidly emerging super-resolution microscopy technique that involves isotropic expansion of biological samples to improve spatial resolution. However, fluorescence signal dilution due to volumetric expansion is a hindrance to the widespread application of ExM. Here, we introduce plasmon-enhanced expansion microscopy (p-ExM) by harnessing an ultrabright fluorescent nanoconstruct, called plasmonic-fluor (PF), as a nanolabel. The unique structure of PFs renders nearly 15000-fold brighter fluorescence signal intensity and higher fluorescence retention following the ExM protocol (nearly 76%) compared to their conventional counterparts (<16% for IR-650). Individual PFs can be easily imaged using conventional fluorescence microscopes, making them excellent "digital" labels for ExM. We demonstrate that p-ExM enables improved tracing and decrypting of neural networks labeled with PFs, as evidenced by improved quantification of morphological markers (nearly a 2.5-fold increase in number of neurite terminal points). Overall, p-ExM complements the existing ExM techniques for probing structure-function relationships of various biological systems.

Conserved neural dynamics and computations across species in olfaction.

Interpreting chemical information and translating it into ethologically relevant output is a common challenge of olfactory systems across species. Are computations performed by olfactory circuits conserved across species to overcome these common challenges? To understand this, we compared odor responses in the locust antennal lobe (AL) and mouse olfactory bulb (OB). We found that odors activated nearly mutually exclusive neural ensembles during stimulus presentation ('ON response') and after stimulus termination ('OFF response'). Strikingly, ON and OFF responses evoked by a single odor were anticorrelated with each other. 'Inverted' OFF responses enhanced contrast between odors experienced close together in time. Notably, OFF responses persisted long after odor termination in both AL and OB networks, indicating a form of short-term memory. Taken together, our results reveal key neurodynamic features underlying olfactory computations that are conserved across insect and mammalian olfactory systems.

Multiscale photoacoustic tomography of neural activities with GCaMP calcium indicators.

SIGNIFICANCE: Optical imaging of responses in fluorescently labeled neurons has progressed significantly in recent years. However, there is still a need to monitor neural activities at divergent spatial scales and at depths beyond the optical diffusion limit. AIM: To meet these needs, we aim to develop multiscale photoacoustic tomography (PAT) to image neural activities across spatial scales with a genetically encoded calcium indicator GCaMP. APPROACH: First, using photoacoustic microscopy, we show that depth-resolved GCaMP signals can be monitored in vivo from a fly brain in response to odor stimulation without depth scanning and even with the cuticle intact. In vivo monitoring of GCaMP signals was also demonstrated in mouse brains. Next, using photoacoustic computed tomography, we imaged neural responses of a mouse brain slice at depths beyond the optical diffusion limit. RESULTS: We provide the first unambiguous demonstration that multiscale PAT can be used to record neural activities in transgenic flies and mice with select neurons expressing GCaMP. CONCLUSIONS: Our results indicate that the combination of multiscale PAT and fluorescent neural activity indicators provides a methodology for imaging targeted neurons at various scales.

Invariant odor recognition with ON-OFF neural ensembles.

Invariant stimulus recognition is a challenging pattern-recognition problem that must be dealt with by all sensory systems. Since neural responses evoked by a stimulus are perturbed in a multitude of ways, how can this computational capability be achieved? We examine this issue in the locust olfactory system. We find that locusts trained in an appetitive-conditioning assay robustly recognize the trained odorant independent of variations in stimulus durations, dynamics, or history, or changes in background and ambient conditions. However, individual- and population-level neural responses vary unpredictably with many of these variations. Our results indicate that linear statistical decoding schemes, which assign positive weights to ON neurons and negative weights to OFF neurons, resolve this apparent confound between neural variability and behavioral stability. Furthermore, simplification of the decoder using only ternary weights ({+1, 0, -1}) (i.e., an "ON-minus-OFF" approach) does not compromise performance, thereby striking a fine balance between simplicity and robustness.

In Situ Grown Gold Nanoisland-Based Chemiresistive Electronic Nose for Sniffing Distinct Odor Fingerprints.

Chemiresistors based on metal-insulator-metal structures are attractive transducers for rapid tracing of a wide repertoire of (bio)chemical species in the vapor phase. However, current fabrication techniques suffer greatly from sensor-to-sensor variability, limiting their reproducible and reliable application in real-world settings. We demonstrate a novel, facile, and ubiquitously applicable strategy for fabricating highly reliable and reproducible organothiol-functionalized gold nanoisland-based chemiresistors. The novel fabrication technique involves iterative in situ seeding, growth, and surface functionalization of gold nanoislands on an interdigitated electrode, which in turn generates a multi-layered densely packed continuous gold nanoisland film. The chemiresistors fabricated using the proposed strategy exhibited high sensor-to-sensor reproducibility owing to the controlled iterative seeding and growth-based fabrication technique, long-term stability, and specificity for detection and identification of a wide variety of volatile organic compounds. Upon exposure to a specific odor, the chemiresistor ensemble comprised nine different chemical functionalities and produced a unique and discernable odor fingerprint that is reproducible for at least up to 90 days. Integrating these odor fingerprints with a simple linear classifier was found to be sufficient for discriminating between all six odors used in this study. We believe that the fabrication strategy presented here, which is agnostic to chemical functionality, enables fabrication of highly reliable and reproducible sensing elements, and thereby an adaptable electronic nose for a wide variety of real-world gas sensing applications.

Genetic and viral approaches to record or manipulate neurons in insects.

The development of genetically encoded tools to record and manipulate neurons in vivo has greatly increased our understanding of how neuronal activity affects behavior. Recent advances enable the use of these tools in species not typically considered genetically tractable. This progress is revolutionizing neuroscience in general, and insect neuroethology in particular. Here we cover the latest innovations and some of their applications in phylogenetically diverse insect species. We discuss the importance and implications of these approaches for both basic and translational research. We focus on genetically encoded and virally encoded tools used for calcium imaging, optogenetics, and synaptic silencing. Finally, we discuss potential future developments of universally applicable, modular, and user-friendly genetic toolkits for neuroethological studies of insect behavior.

Recent approaches to study the neural bases of complex insect behavior.

Recent advances in biocompatible materials, miniaturized instrumentation, advanced computational algorithms, and genetic tools have enabled the development of novel methods and approaches to quantify the behavior of individuals or groups of animals. In conjunction with technologies that allow simultaneous monitoring of neural responses, quantitative studies of complex behaviors can reveal tighter links between the external sensory cues in the vicinity of the organism and neural responses they elicit, and how internal neural representations finally get mapped onto the behavior generated. In this review, we examine a few approaches that are beginning to be widely exploited for understanding neural-behavioral response transformations.

Reversible Photothermal Modulation of Electrical Activity of Excitable Cells using Polydopamine Nanoparticles.

Advances in the design and synthesis of nanomaterials with desired biophysicochemical properties can be harnessed to develop non-invasive neuromodulation technologies. Here, the reversible modulation of the electrical activity of neurons and cardiomyocytes is demonstrated using polydopamine (PDA) nanoparticles as photothermal nanotransducers. In addition to their broad light absorption and excellent photothermal activity, PDA nanoparticles are highly biocompatible and biodegradable, making them excellent candidates for both in vitro and in vivo applications. The modulation of the activity (i.e., spike rate of the neurons and beating rate of cardiomyocytes) of excitable cells can be finely controlled by varying the excitation power density and irradiation duration. Under optimal conditions, reversible suppression (≈100%) of neural activity and reversible enhancement (two-fold) in the beating rate of cardiomyocytes is demonstrated. To improve the ease of interfacing of photothermal transducers with these excitable cells and enable spatial localization of the photothermal stimulus, a collagen/PDA nanoparticle foam is realized, which can be used as an "add-on patch" for photothermal stimulation. The non-genetic optical neuromodulation approach using biocompatible and biodegradable nanoparticles represents a minimally invasive method for controlling the activity of excitable cells with potential applications in nano-neuroscience and engineering.

Neural Circuit Dynamics for Sensory Detection.

We consider the question of how sensory networks enable the detection of sensory stimuli in a combinatorial coding space. We are specifically interested in the olfactory system, wherein recent experimental studies have reported the existence of rich, enigmatic response patterns associated with stimulus onset and offset. This study aims to identify the functional relevance of such response patterns (i.e., what benefits does such neural activity provide in the context of detecting stimuli in a natural environment). We study this problem through the lens of normative, optimization-based modeling. Here, we define the notion of a low-dimensional latent representation of stimulus identity, which is generated through action of the sensory network. The objective of our optimization framework is to ensure high-fidelity tracking of a nominal representation in this latent space in an energy-efficient manner. It turns out that the optimal motifs emerging from this framework possess morphologic similarity with prototypical onset and offset responses observed in vivo in locusts (Schistocerca americana) of either sex. Furthermore, this objective can be exactly achieved by a network with reciprocal excitatory-inhibitory competitive dynamics, similar to interactions between projection neurons and local neurons in the early olfactory system of insects. The derived model also makes several predictions regarding maintenance of robust latent representations in the presence of confounding background information and trade-offs between the energy of sensory activity and resultant behavioral measures such as speed and accuracy of stimulus detection.SIGNIFICANCE STATEMENT A key area of study in olfactory coding involves understanding the transformation from high-dimensional sensory stimulus to low-dimensional decoded representation. Here, we examine not only the dimensionality reduction of this mapping but also its temporal dynamics, with specific focus on stimuli that are temporally continuous. Through optimization-based synthesis, we examine how sensory networks can track representations without prior assumption of discrete trial structure. We show that such tracking can be achieved by canonical network architectures and dynamics, and that the resulting responses resemble observations from neurons in the insect olfactory system. Thus, our results provide hypotheses regarding the functional role of olfactory circuit activity at both single neuronal and population scales.

SnO2 Nanostructured Thin Films for Room-Temperature Gas Sensing of Volatile Organic Compounds.

We demonstrated room-temperature gas sensing of volatile organic compounds (VOCs) using SnO2 nanostructured thin films grown via the aerosol chemical vapor deposition process at deposition temperatures ranging from 450 to 600 °C. We investigated the film's sensing response to the presence of three classes of VOCs: apolar, monopolar, and biopolar. The synthesis process was optimized, with the most robust response observed for films grown at 550 °C as compared to other temperatures. The role of film morphology, exposed surface planes, and oxygen defects were explored using experimental techniques and theoretical calculations to improve the understanding of the room-temperature gas sensing mechanism, which is proposed to be through the direct adsorption of VOCs on the sensor surface. Overall, the improved understanding of the material characteristics that enable room-temperature sensing gained in this work will be beneficial for the design and application of metal oxide gas sensors at room temperature.

Dynamic contrast enhancement and flexible odor codes.

Sensory stimuli evoke spiking activities patterned across neurons and time that are hypothesized to encode information about their identity. Since the same stimulus can be encountered in a multitude of ways, how stable or flexible are these stimulus-evoked responses? Here we examine this issue in the locust olfactory system. In the antennal lobe, we find that both spatial and temporal features of odor-evoked responses vary in a stimulus-history dependent manner. The response variations are not random, but allow the antennal lobe circuit to enhance the uniqueness of the current stimulus. Nevertheless, information about the odorant identity is conf ounded due to this contrast enhancement computation. Notably, predictions from a linear logical classifier (OR-of-ANDs) that can decode information distributed in flexible subsets of neurons match results from behavioral experiments. In sum, our results suggest that a trade-off between stability and flexibility in sensory coding can be achieved using a simple computational logic.

Differential effects of adaptation on odor discrimination.

Adaptation of neural responses is ubiquitous in sensory systems and can potentially facilitate many important computational functions. Here we examined this issue with a well-constrained computational model of the early olfactory circuits. In the insect olfactory system, the responses of olfactory receptor neurons (ORNs) on the antennae adapt over time. We found that strong adaptation of sensory input is important for rapidly detecting a fresher stimulus encountered in the presence of other background cues and for faithfully representing its identity. However, when the overlapping odorants were chemically similar, we found that adaptation could alter the representation of these odorants to emphasize only distinguishing features. This work demonstrates novel roles for peripheral neurons during olfactory processing in complex environments. NEW & NOTEWORTHY Olfactory systems face the problem of distinguishing salient information from a complex olfactory environment. The neural representations of specific odor sources should be consistent regardless of the background. How are olfactory representations robust to varying environmental interference? We show that in locusts the extraction of salient information begins in the periphery. Olfactory receptor neurons adapt in response to odorants. Adaptation can provide a computational mechanism allowing novel odorant components to be highlighted during complex stimuli.

Engaging and disengaging recurrent inhibition coincides with sensing and unsensing of a sensory stimulus.

Even simple sensory stimuli evoke neural responses that are dynamic and complex. Are the temporally patterned neural activities important for controlling the behavioral output? Here, we investigated this issue. Our results reveal that in the insect antennal lobe, due to circuit interactions, distinct neural ensembles are activated during and immediately following the termination of every odorant. Such non-overlapping response patterns are not observed even when the stimulus intensity or identities were changed. In addition, we find that ON and OFF ensemble neural activities differ in their ability to recruit recurrent inhibition, entrain field-potential oscillations and more importantly in their relevance to behaviour (initiate versus reset conditioned responses). Notably, we find that a strikingly similar strategy is also used for encoding sound onsets and offsets in the marmoset auditory cortex. In sum, our results suggest a general approach where recurrent inhibition is associated with stimulus 'recognition' and 'derecognition'.

Non-invasive aerosol delivery and transport of gold nanoparticles to the brain.

Targeted delivery of nanoscale carriers containing packaged payloads to the central nervous system has potential use in many diagnostic and therapeutic applications. Moreover, understanding of the bio-interactions of the engineered nanoparticles used for tissue-specific delivery by non-invasive delivery approaches are also of paramount interest. Here, we have examined this issue systematically in a relatively simple invertebrate model using insects. We synthesized 5 nm, positively charged gold nanoparticles (AuNPs) and targeted their delivery using the electrospray aerosol generator. Our results revealed that after the exposure of synthesized aerosol to the insect antenna, AuNPs reached the brain within an hour. Nanoparticle accumulation in the brain increased linearly with the exposure time. Notably, electrophysiological recordings from neurons in the insect brain several hours after exposure did not show any significant alterations in their spontaneous and odor-evoked spiking properties. Taken together, our findings reveal that aerosolized delivery of nanoparticles can be an effective non-invasive approach for delivering nanoparticles to the brain, and also presents an approach to monitor the short-term nano-biointeractions.

The I/O transform of a chemical sensor.

A number of sensing technologies, using a variety of transduction principles, have been proposed for non-invasive chemical sensing. A fundamental problem common to all these sensing technologies is determining what features of the transducer's signal constitute a chemical fingerprint that allows for precise analyte recognition. Of particular importance is the need to extract features that are robust with respect to the sensor's age or stimulus intensity. Here, using pulsed stimulus delivery, we show that a sensor's operation can be modeled as a linear input-output (I/O) transform. The I/O transform is unique for each analyte and can be used to precisely predict a temperature-programmed chemiresistor's response to the analyte given the recent stimulus history (i.e. state of an analyte delivery valve being open or closed). We show that the analyte specific I/O transforms are to a certain degree stimulus intensity invariant and can remain consistent even when the sensor has undergone considerable aging. Significantly, the I/O transforms for a given analyte are highly conserved across sensors of equal manufacture, thereby allowing training data obtained from one sensor to be used for recognition of the same set of chemical species with another sensor. Hence, this proposed approach facilitates decoupling of the signal processing algorithms from the chemical transducer, a key advance necessary for achieving long-term, non-invasive chemical sensing.

Behavioural correlates of combinatorial versus temporal features of odour codes.

Most sensory stimuli evoke spiking responses that are distributed across neurons and are temporally structured. Whether the temporal structure of ensemble activity is modulated to facilitate different neural computations is not known. Here, we investigated this issue in the insect olfactory system. We found that an odourant can generate synchronous or asynchronous spiking activity across a neural ensemble in the antennal lobe circuit depending on its relative novelty with respect to a preceding stimulus. Regardless of variations in temporal spiking patterns, the activated combinations of neurons robustly represented stimulus identity. Consistent with this interpretation, locusts reliably recognized both solitary and sequential introductions of trained odourants in a quantitative behavioural assay. However, predictable behavioural responses across locusts were observed only to novel stimuli that evoked synchronized spiking patterns across neural ensembles. Hence, our results indicate that the combinatorial ensemble response encodes for stimulus identity, whereas the temporal structure of the ensemble response selectively emphasizes novel stimuli.

Bioinspired Polarization Imaging Sensors: From Circuits and Optics to Signal Processing Algorithms and Biomedical Applications: Analysis at the focal plane emulates nature's method in sensors to image and diagnose with polarized light.

In this paper, we present recent work on bioinspired polarization imaging sensors and their applications in biomedicine. In particular, we focus on three different aspects of these sensors. First, we describe the electro-optical challenges in realizing a bioinspired polarization imager, and in particular, we provide a detailed description of a recent low-power complementary metal-oxide-semiconductor (CMOS) polarization imager. Second, we focus on signal processing algorithms tailored for this new class of bioinspired polarization imaging sensors, such as calibration and interpolation. Third, the emergence of these sensors has enabled rapid progress in characterizing polarization signals and environmental parameters in nature, as well as several biomedical areas, such as label-free optical neural recording, dynamic tissue strength analysis, and early diagnosis of flat cancerous lesions in a murine colorectal tumor model. We highlight results obtained from these three areas and discuss future applications for these sensors.