Application of Neuromorphic Olfactory Approach for High-Accuracy Classification of Malts

Current developments in artificial olfactory systems, also known as electronic nose (e-nose) systems, have benefited from advanced machine learning techniques that have significantly improved the conditioning and processing of multivariate feature-rich sensor data. These advancements are complemented by the application of bioinspired algorithms and architectures based on findings from neurophysiological studies focusing on the biological olfactory pathway. The application of spiking neural networks (SNNs), and concepts from neuromorphic engineering in general, are one of the key factors that has led to the design and development of efficient bioinspired e-nose systems. However, only a limited number of studies have focused on deploying these models on a natively event-driven hardware platform that exploits the benefits of neuromorphic implementation, such as ultra-low-power consumption and real-time processing, for simplified integration in a portable e-nose system. In this paper, we extend our previously reported neuromorphic encoding and classification approach to a real-world dataset that consists of sensor responses from a commercial e-nose system when exposed to eight different types of malts. We show that the proposed SNN-based classifier was able to deliver 97% accurate classification results at a maximum latency of 0.4 ms per inference with a power consumption of less than 1 mW when deployed on neuromorphic hardware. One of the key advantages of the proposed neuromorphic architecture is that the entire functionality, including pre-processing, event encoding, and classification, can be mapped on the neuromorphic system-on-a-chip (NSoC) to develop power-efficient and highly-accurate real-time e-nose systems.

Study of the glial cytoarchitecture of the developing olfactory bulb of a shark using immunochemical markers of radial glia

During development of the olfactory bulb (OB), glial cells play key roles in axonal guiding/targeting, glomerular formation and synaptic plasticity. Studies in mammals have shown that radial glial cells and peripheral olfactory glia (olfactory ensheathing cells, OECs) are involved in the development of the OB. Most studies about the OB glia were carried out in mammals, but data are lacking in most non-mammalian vertebrates. In the present work, we studied the development of the OB glial system in the cartilaginous fish Scyliorhinus canicula (catshark) using antibodies against glial markers, such as glial fibrillary acidic protein (GFAP), brain lipid-binding protein (BLBP), and glutamine synthase (GS). These glial markers were expressed in cells with radial morphology lining the OB ventricle of embryos and this expression continues in ependymal cells (tanycytes) in early juveniles. Astrocyte-like cells were also observed in the granular layer and surrounding glomeruli. Numerous GS-positive cells were present in the primary olfactory pathway of embryos. In the developmental stages analysed, the olfactory nerve layer and the glomerular layer were the regions with higher GFAP, BLBP and GS immuno-reactivity. In addition, numerous BLBP-expressing cells (a marker of mammalian OECs) showing proliferative activity were present in the olfactory nerve layer. Our findings suggest that glial cells of peripheral and central origin coexist in the OB of catshark embryos and early juveniles. These results open the path for future studies about the differential roles of glial cells in the catshark OB during embryonic development and in adulthood.

Map-independent representation of an aggression-promoting social cue in the main olfactory pathway

While the olfactory system is required for proper social behaviors, the molecular basis for how social cues are detected via the main olfactory pathway of mammals is not well-characterized. Trimethylamine is a volatile, sex-specific odor found in adult male mouse urine that selectively activates main olfactory sensory neurons that express trace amine-associated receptor 5 (TAAR5). Here we show that trimethylamine, acting via TAAR5, elicits state-dependent attraction or aversion in male mice and drives inter-male aggression. Genetic knockout of TAAR5 significantly reduces aggression-related behaviors, while adding trimethylamine augments aggressive behavior towards juvenile males. We further show that transgenic expression of TAAR5 specifically in olfactory sensory neurons rescues aggressive behaviors in knockout mice, despite extensive remapping of TAAR5 projections to the olfactory bulb. Our results identify a specific main olfactory input that detects a prominent male-specific odor to induce inter-male aggression in a mammalian species and reveal that apparently innate behavioral responses are independent of patterned glomerular input to the olfactory bulb.

The Functional Logic of Odor Information Processing in the Drosophila Antennal Lobe

In the early olfactory pathway of Drosophila, Olfactory Sensory Neurons (OSNs) multiplicatively encode the odorant identity and the concentration profile. Projection Neurons (PNs) responses in the Antennal Lobe (AL), in turn, exhibit strong transients at odorant onset/offset and stable steady-state behavior. What is the functional logic the of diverse set of Local Neurons (LNs) in the AL Addressing this question may shed light on the key characteristics of odor information processing in the AL, and odorant recognition and olfactory associative learning in the downstream neuropils of the early olfactory system. To address the computation performed by each LN type, we exhaustively evaluated all circuit configurations of the Antennal Lobe. We found that, across model parameterizations, presynaptic inhibition of the OSN-to-PN synapse is essential for odorant identity recovery in steady-state, while postsynaptic excitation and inhibition facilitate on-/off-set event detection. The onset and offset events indicate changing odorant identities, and together with the identity recovery in steady-state, suggest that the AL is an event-based odorant identity recovery processor.

Drug Delivery Systems and Strategies to Overcome the Barriers of Brain

The transport of drugs to the central nervous system is the most challenging task for conventional drug delivery systems. Reduced permeability of drugs through the blood-brain barrier is a major hurdle in delivering drugs to the brain. Hence, various strategies for improving drug delivery through the blood-brain barrier are currently being explored. Novel drug delivery systems (NDDS) offer several advantages, including high chemical and biological stability, suitability for both hydrophobic and hydrophilic drugs, and can be administered through different routes. Furthermore, the conjugation of suitable ligands with these carriers tend to potentiate targeting to the endothelium of the brain and could facilitate the internalization of drugs through endocytosis. Further, the intranasal route has also shown potential, as a promising alternate route, for the delivery of drugs to the brain. This can deliver the drugs directly to the brain through the olfactory pathway. In recent years, several advancements have been made to target and overcome the barriers of the brain. This article deals with a detailed overview of the diverse strategies and delivery systems to overcome the barriers of the brain for effective delivery of drugs.

A neuromorphic model of olfactory processing and sparse coding in the Drosophila larva brain

Animal nervous systems are highly efficient in processing sensory input. The neuromorphic computing paradigm aims at the hardware implementation of neural network computations to support novel solutions for building brain-inspired computing systems. Here, we take inspiration from sensory processing in the nervous system of the fruit fly larva. With its strongly limited computational resources of <200 neurons and <1.000 synapses the larval olfactory pathway employs fundamental computations to transform broadly tuned receptor input at the periphery into an energy efficient sparse code in the central brain. We show how this approach allows us to achieve sparse coding and increased separability of stimulus patterns in a spiking neural network, validated with both software simulation and hardware emulation on mixed-signal real-time neuromorphic hardware. We verify that feedback inhibition is the central motif to support sparseness in the spatial domain, across the neuron population, while the combination of spike frequency adaptation and feedback inhibition determines sparseness in the temporal domain. Our experiments demonstrate that such small-sized, biologically realistic neural networks, efficiently implemented on neuromorphic hardware, can achieve parallel processing and efficient encoding of sensory input at full temporal resolution.

Selective CNS Targeting and Distribution with a Refined Region-Specific Intranasal Delivery Technique via the Olfactory Mucosa

Intranasal drug delivery is a promising approach for the delivery of drugs to the CNS, but too heterogenous, unprecise delivery methods without standardization decrease the quality of many studies in rodents. Thus, the lack of a precise and region-specific application technique for mice is a major drawback. In this study, a previously developed catheter-based refined technique was validated against the conventional pipette-based method and used to specifically reach the olfactory or the respiratory nasal regions. This study successfully demonstrated region-specific administration at the olfactory mucosa resulting in over 20% of the administered fluorescein dose in the olfactory bulbs, and no peripheral bioactivity of insulin detemir and Fc-dependent uptake of two murine IgG1 (11C7 and P3X) along the olfactory pathway to cortex and hippocampus. An scFv of 11C7 showed hardly any uptake to the CNS. Elimination was dependent on the presence of the IgG’s antigen. In summary, it was successfully demonstrated that region-specific intranasal administration via the olfactory region resulted in improved brain targeting and reduced peripheral targeting in mice. The data are discussed with regard to their clinical potential.

Prolonged and extended impacts of SARS-CoV-2 on the olfactory neurocircuit

The impact of SARS-CoV-2 on the olfactory pathway was studied over several time points using Syrian golden hamsters. We found an incomplete recovery of the olfactory sensory neurons, prolonged activation of glial cells in the olfactory bulb, and a decrease in the density of dendritic spines within the hippocampus. These data may be useful for elucidating the mechanism underlying long-lasting olfactory dysfunction and cognitive impairment as a post-acute COVID-19 syndrome.

Investigation of the Transport Pathways Associated with Enhanced Brain Delivery of Peptide Drugs by Intranasal Coadministration with Penetratin

We previously found that coadministering peptides and proteins with the cell-penetrating peptide L-penetratin intranasally significantly increased transport to the brain and enhanced pharmacological effects. The present study aimed to clarify the mechanisms of nose-to-brain drug delivery enhancement by L-penetratin coadministration. First, we compared the concentrations of Exendin-4 in plasma and brain after intranasal and subcutaneous administration and suggested that coadministration with L-penetratin facilitated the direct nose-to-brain transport of Exendin-4. Second, we demonstrated that L-penetratin did not stimulate the transport of Cy7-labeled Exendin-4 and insulin through the trigeminal nerves but shifted their distribution to the olfactory mucosal pathway. Third, we investigated the distribution of insulin into the deeper regions of the brain after delivery via the olfactory pathway and suggested that insulin had entered the olfactory bulb, bottom part of the brain, and perivascular space through the cerebrospinal fluid and had diffused throughout the brain. We further demonstrated that intranasally delivered insulin with L-penetratin specifically accumulated on the hippocampus neuronal cells. Thus, this study suggested that administrating peptide drugs intranasally with L-penetratin allows direct transport to the olfactory bulb, bottom part of the brain, and perivascular space of the cerebral artery. This technique also potentially allows targeting of specific brain areas.

Automatic Segmentation of the Olfactory Bulb

The olfactory bulb (OB) has an essential role in the human olfactory pathway. A change in olfactory function is associated with a change of OB volume. It has been shown to predict the prognosis of olfactory loss and its volume is a biomarker for various neurodegenerative diseases, such as Alzheimer’s disease. Thus far, obtaining an OB volume for research purposes has been performed by manual segmentation alone; a very time-consuming and highly rater-biased process. As such, this process dramatically reduces the ability to produce fair and reliable comparisons between studies, as well as the processing of large datasets. Our study aims to solve this by proposing a novel methodological framework for the unbiased measurement of OB volume. In this paper, we present a fully automated tool that successfully performs such a task, accurately and quickly. In order to develop a stable and versatile algorithm and to train the neural network, we used four datasets consisting of whole-brain T1 and high-resolution T2 MRI scans, as well as the corresponding clinical information of the subject’s smelling ability. One dataset contained data of patients suffering from anosmia or hyposmia (N = 79), and the other three datasets contained data of healthy controls (N = 91). First, the manual segmentation labels of the OBs were created by two experienced raters, independently and blinded. The algorithm consisted of the following four different steps: (1) multimodal data co-registration of whole-brain T1 images and T2 images, (2) template-based localization of OBs, (3) bounding box construction, and lastly, (4) segmentation of the OB using a 3D-U-Net. The results from the automated segmentation algorithm were tested on previously unseen data, achieving a mean dice coefficient (DC) of 0.77 ± 0.05, which is remarkably convergent with the inter-rater DC of 0.79 ± 0.08 estimated for the same cohort. Additionally, the symmetric surface distance (ASSD) was 0.43 ± 0.10. Furthermore, the segmentations produced using our algorithm were manually rated by an independent blinded rater and have reached an equivalent rating score of 5.95 ± 0.87 compared to a rating score of 6.23 ± 0.87 for the first rater’s segmentation and 5.92 ± 0.81 for the second rater’s manual segmentation. Taken together, these results support the success of our tool in producing automatic fast (3–5 min per subject) and reliable segmentations of the OB, with virtually matching accuracy with the current gold standard technique for OB segmentation. In conclusion, we present a newly developed ready-to-use tool that can perform the segmentation of OBs based on multimodal data consisting of T1 whole-brain images and T2 coronal high-resolution images. The accuracy of the segmentations predicted by the algorithm matches the manual segmentations made by two well-experienced raters. This method holds potential for immediate implementation in clinical practice. Furthermore, its ability to perform quick and accurate processing of large datasets may provide a valuable contribution to advancing our knowledge of the olfactory system, in health and disease. Specifically, our framework may integrate the use of olfactory bulb volume (OBV) measurements for the diagnosis and treatment of olfactory loss and improve the prognosis and treatment options of olfactory dysfunctions.