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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.
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Saltamontes/fisiología , Odorantes , Neuronas Receptoras Olfatorias/fisiología , Animales , Modelos Neurológicos , Vías Olfatorias/fisiología , Percepción Olfatoria/fisiología , OlfatoRESUMEN
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.
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Colorantes , Microscopía Fluorescente/métodosRESUMEN
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.
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Modelos Neurológicos , Red Nerviosa/fisiología , Neuronas/fisiología , Vías Olfatorias/fisiología , Potenciales de Acción/fisiología , Animales , Femenino , Saltamontes , MasculinoRESUMEN
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.
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Adaptación Fisiológica , Discriminación en Psicología , Percepción Olfatoria , Animales , Saltamontes , Neuronas Receptoras Olfatorias/fisiología , OlfatoRESUMEN
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.
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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.
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Behavioral responses to many odorants are not fixed but are flexible, varying based on organismal needs. How such variations arise and the role of various neuromodulators in achieving flexible neural-to-behavioral mapping is not fully understood. In this study, we examined how serotonin modulates the neural and behavioral responses to odorants in locusts (Schistocerca americana). Our results indicated that serotonin can increase or decrease appetitive behavior in an odor-specific manner. On the other hand, in the antennal lobe, serotonergic modulation enhanced odor-evoked response strength but left the temporal features or the combinatorial response profiles unperturbed. This result suggests that serotonin allows for sensitive and robust recognition of odorants. Nevertheless, the uniform neural response amplification appeared to be at odds with the observed stimulus-specific behavioral modulation. We show that a simple linear model with neural ensembles segregated based on behavioral relevance is sufficient to explain the serotonin-mediated flexible mapping between neural and behavioral responses.
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Saltamontes , Odorantes , Serotonina , Animales , Serotonina/metabolismo , Odorantes/análisis , Saltamontes/fisiología , Conducta Animal/fisiología , Olfato/fisiologíaRESUMEN
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.
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Odorantes , Olfato , Animales , Olfato/fisiología , Odorantes/análisis , Nanotecnología/métodos , Insectos/fisiología , Nanoestructuras/química , NeurotransmisoresRESUMEN
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.
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Saltamontes , Odorantes , Animales , Aprendizaje , Condicionamiento Clásico/fisiología , Recompensa , Olfato/fisiologíaRESUMEN
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.
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Neurología , Neuronas , Animales , Neuronas/metabolismo , Neurogénesis/fisiología , Encéfalo/metabolismo , Nanotecnología , MamíferosRESUMEN
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.
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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.
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Materiales Biocompatibles/química , Nariz Electrónica , Oro/química , Nanopartículas del Metal/química , Odorantes/análisis , Compuestos Orgánicos Volátiles/análisis , Ensayo de MaterialesRESUMEN
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.
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Calcio , Tomografía Computarizada por Rayos X , Animales , Encéfalo/diagnóstico por imagen , Ratones , Neuronas , Imagen Óptica/métodosRESUMEN
Odorants are represented as spatiotemporal patterns of spikes in neurons of the antennal lobe (AL; insects) and olfactory bulb (OB; vertebrates). These response patterns have been thought to arise primarily from interactions within the AL/OB, an idea supported, in part, by the assumption that olfactory receptor neurons (ORNs) respond to odorants with simple firing patterns. However, activating the AL directly with simple pulses of current evoked responses in AL neurons that were much less diverse, complex, and enduring than responses elicited by odorants. Similarly, models of the AL driven by simplistic inputs generated relatively simple output. How then are dynamic neural codes for odors generated? Consistent with recent results from several other species, our recordings from locust ORNs showed a great diversity of temporal structure. Furthermore, we found that, viewed as a population, many response features of ORNs were remarkably similar to those observed within the AL. Using a set of computational models constrained by our electrophysiological recordings, we found that the temporal heterogeneity of responses of ORNs critically underlies the generation of spatiotemporal odor codes in the AL. A test then performed in vivo confirmed that, given temporally homogeneous input, the AL cannot create diverse spatiotemporal patterns on its own; however, given temporally heterogeneous input, the AL generated realistic firing patterns. Finally, given the temporally structured input provided by ORNs, we clarified several separate, additional contributions of the AL to olfactory information processing. Thus, our results demonstrate the origin and subsequent reformatting of spatiotemporal neural codes for odors.
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Percepción Olfatoria/fisiología , Neuronas Receptoras Olfatorias/fisiología , Potenciales de Acción , Animales , Simulación por Computador , Femenino , Saltamontes , Masculino , Modelos Neurológicos , Odorantes , Vías Olfatorias/fisiología , Factores de TiempoRESUMEN
How does the nervous system encode complex sensory stimuli? A recent study reveals the fly olfactory system compensates for variability in sensory input as odor representations are restructured for enhanced discriminability and coding efficiency.
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Drosophila/fisiología , Odorantes , Neuronas Receptoras Olfatorias/fisiología , Olfato/fisiología , Animales , Proteínas de Drosophila/metabolismo , Proteínas de Drosophila/fisiología , Receptores Odorantes/metabolismo , Receptores Odorantes/fisiología , Estimulación QuímicaRESUMEN
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.
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Señales (Psicología) , Insectos , Animales , Insectos/genéticaRESUMEN
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.
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Neurociencias , Optogenética , Animales , Calcio , Insectos/genética , NeuronasRESUMEN
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.
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Materiales Biocompatibles/química , Indoles/química , Nanopartículas/química , Polímeros/química , Potenciales de Acción/efectos de los fármacos , Animales , Materiales Biocompatibles/farmacología , Supervivencia Celular/efectos de los fármacos , Colágeno/química , Frecuencia Cardíaca/efectos de los fármacos , Rayos Infrarrojos , Miocitos Cardíacos/citología , Miocitos Cardíacos/fisiología , Neuronas/efectos de los fármacos , Neuronas/fisiología , Ratas , Ratas Sprague-Dawley , TemperaturaRESUMEN
Artificial olfaction is a potential tool for noninvasive chemical monitoring. Application of "electronic noses" typically involves recognition of "pretrained" chemicals, while long-term operation and generalization of training to allow chemical classification of "unknown" analytes remain challenges. The latter analytical capability is critically important, as it is unfeasible to pre-expose the sensor to every analyte it might encounter. Here, we demonstrate a biologically inspired approach where the recognition and generalization problems are decoupled and resolved in a hierarchical fashion. Analyte composition is refined in a progression from general (e.g., target is a hydrocarbon) to precise (e.g., target is ethane), using highly optimized response features for each step. We validate this approach using a MEMS-based chemiresistive microsensor array. We show that this approach, a unique departure from existing methodologies in artificial olfaction, allows the recognition module to better mitigate sensor-aging effects and to better classify unknowns, enhancing the utility of chemical sensors for real-world applications.
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Biomimética/métodos , Técnicas de Química Analítica/instrumentación , Olfato , Metales/química , Sistemas Microelectromecánicos , Óxidos/química , Reproducibilidad de los Resultados , Temperatura , Factores de TiempoRESUMEN
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.