Sensory Systems Research Articles

Non-responsive neurons improve population coding of object location.

Understanding how heterogeneous neural populations represent sensory input to give rise to behavior remains a central problem in systems neuroscience. Here we investigated how midbrain neurons within the electrosensory system of Apteronotus leptorhynchus code for object location in space. In vivo simultaneous recordings were achieved via Neuropixels probes, high-density electrode arrays, with the stimulus positioned at different locations relative to the animal. Midbrain neurons exhibited heterogeneous response profiles, with a significant proportion (65%) seemingly non-responsive to moving stimuli. Remarkably, we found that non-responsive neurons increased population coding of object location through synergistic interactions with responsive neurons by effectively reducing noise. Mathematical modeling demonstrated that increased response heterogeneity together with the experimentally observed correlations was sufficient to give rise to independent encoding by responsive neurons. Further, addition of non-responsive neurons in the model gave rise to synergistic population coding. Taken together, our findings reveal that non-responsive neurons, which are frequently excluded from analysis, can significantly improve population coding of object location through synergistic interactions with responsive neurons. Combinations of responsive and non-responsive neurons have been observed in sensory systems across taxa; it is likely that similar synergistic interactions improve population coding across modalities and behavioral tasks.Significance Statement Here we show that including the activities of non-responsive neurons with those of responsive neurons increases Fisher information about stimulus location. Further analysis revealed that this is because including non-responsive neurons led to reduced noise levels for responsive neurons. A combination of multi-unit recordings from neural populations and mathematical modeling reveals that response heterogeneity and spatially decaying correlations are necessary to observe this effect. It is likely that synergistic population coding by responsive and non-responsive neurons will be observed in other systems.

Recent Advances in Artificial Sensory Neurons: Biological Fundamentals, Devices, Applications, and Challenges.

Spike-based neural networks, which use spikes or action potentials to represent information, have gained a lot of attention because of their high energy efficiency and low power consumption. To fully leverage its advantages, converting the external analog signals to spikes is an essential prerequisite. Conventional approaches including analog-to-digital converters or ring oscillators, and sensors suffer from high power and area costs. Recent efforts are devoted to constructing artificial sensory neurons based on emerging devices inspired by the biological sensory system. They can simultaneously perform sensing and spike conversion, overcoming the deficiencies of traditional sensory systems. This review summarizes and benchmarks the recent progress of artificial sensory neurons. It starts with the presentation of various mechanisms of biological signal transduction, followed by the systematic introduction of the emerging devices employed for artificial sensory neurons. Furthermore, the implementations with different perceptual capabilities are briefly outlined and the key metrics and potential applications are also provided. Finally, we highlight the challenges and perspectives for the future development of artificial sensory neurons.

Functional localization of the human auditory and visual thalamus using a thalamic localizer functional magnetic resonance imaging task

Abstract Functional magnetic resonance imaging (fMRI) of the auditory and visual sensory systems of the human brain is an active area of investigation in the study of human health and disease. The medial geniculate nucleus (MGN) and lateral geniculate nucleus (LGN) are key thalamic nuclei involved in the processing and relay of auditory and visual information, respectively, and are the subject of blood-oxygen-level-dependent (BOLD) fMRI studies of neural activation and functional connectivity in human participants. However, localization of BOLD fMRI signal originating from neural activity in MGN and LGN remains a technical challenge, due, in part, to the poor definition of boundaries of these thalamic nuclei in standard T1-weighted and T2-weighted magnetic resonance imaging sequences. Here, we report the development and evaluation of an auditory and visual sensory thalamic localizer (TL) fMRI task that produces participant-specific functionally-defined regions of interest (fROIs) of both MGN and LGN, using 3 Tesla multiband fMRI and a clustered-sparse temporal acquisition sequence, in less than 16 minutes of scan time. We demonstrate the use of MGN and LGN fROIs obtained from the TL fMRI task in standard resting-state functional connectivity (RSFC) fMRI analyses in the same participants. In RSFC analyses, we validated the specificity of MGN and LGN fROIs for signals obtained from primary auditory and visual cortex, respectively, and benchmarked their performance against alternative atlas- and segmentation-based localization methods. The TL fMRI task and analysis code (written in Presentation and MATLAB, respectively) have been made freely available to the wider research community.

Bio-Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics.

Inspired by the extensive signal processing capabilities of the human nervous system, neuromorphic artificial sensory systems have emerged as a pivotal technology in advancing brain-like computing for applications in humanoid robotics, prosthetics, and wearable technologies. These systems mimic the functionalities of the central and peripheral nervous systems through the integration of sensory synaptic devices and neural network algorithms, enabling external stimuli to be converted into actionable electrical signals. This review delves into the intricate relationship between synaptic device technologies and neural network processing algorithms, highlighting their mutual influence on artificial intelligence capabilities. This study explores the latest advancements in artificial synaptic properties triggered by various stimuli, including optical, auditory, mechanical, and chemical inputs, and their subsequent processing through artificial neural networks for applications in image recognition and multimodal pattern recognition. The discussion extends to the emulation of biological perception via artificial synapses and concludes with future perspectives and challenges in neuromorphic system development, emphasizing the need for a deeper understanding of neural network processing to innovate and refine these complex systems.

Annual Prize Lecture 2024: Endogenous physiological mechanisms as basis for the treatment of obesity and type 2 diabetes.

In 1964, it was proven that postprandial insulin secretion is largely regulated by gut hormones and, in 1973, it was proposed that a gut hormone would also regulate appetite and food intake. Several gut hormones were tested for metabolic actions with disappointing results until the discovery of the proglucagon derivative, glucagon-like peptide-1 (GLP-1). This peptide from the distal intestine has preserved activity on insulin secretion in people with type 2 diabetes and turned out to regulate both secretion and motility in the gastrointestinal tract and importantly, appetite and food intake, thus functioning as an efficient 'ileal brake' hormone. However, the natural hormone acts predominantly via sensory afferent systems and is extremely rapidly removed from the circulation by enzymatic degradation and renal elimination, and increasing the doses merely results in nausea and vomiting. Lipidation of analogs turned out to provide both stability and limit renal elimination, and very slow up-titration of dosing improves tolerance. Indeed, the most recent agonists may near-normalize glycaemic control in type 2 diabetes, may cause weight losses of up to 25% of body weight, and significantly reduce cardiovascular risk, effects that resemble those of bariatric surgery. Thus, a solution to one of the most serious health problems of modern civilization, the increased morbidity and mortality of the metabolic syndrome, may be addressed by mobilization of one of the body's own regulatory mechanisms.

Quantitative Assessment of the Effect of Instability Levels on Reactive Human Postural Control Using Different Sensory Organization Strategies

Reactive postural control (RPC), essential for maintaining balance during daily activities, relies on a complex sensory system integrating visual, vestibular, and proprioceptive inputs. Deficits in RPC can lead to falls, especially in unpredictable environments where sensory inputs are challenged. Traditional rehabilitation often fails to prepare patients adequately for real-world conditions. This study aims to explore the effects of varying instability levels (ILs) and sensory integration strategies (SIS) on RPC by evaluating balance disturbances without applying additional external force. Twenty-five healthy participants (12 men, 13 women, 24.5 ± 6.1 years) performed balance tasks on Abili® platforms with adjustable ILs (0, 1, 2, 3) while altering sensory strategies (Basic, Visual, Proprioception, Vestibular) using the Modified Clinical Test of Sensory Integration and Balance (mCTSIB). RPC efficiency was measured using the 95th percentile confidence interval for chest movement’s ellipsoid volume and average velocity, analyzed with Wilcoxon signed-rank tests and Cliff’s delta effect size. Results showed significant increases in chest movement velocity and volume, particularly with the Vestibular strategy at higher ILs, with a 7176% increase in chest volume from Basic strategy at 0IL to Vestibular strategy at 3IL. Additionally, removing visual input (Visual and Vestibular strategies) had a greater impact on chest movement than increasing instability levels. These findings underscore the significant role of combined platform instability and reduced sensory input on postural control. This study presents a novel method for challenging balance and suggests that sensory integration with variable instability could be valuable in training and rehabilitation, even for healthy individuals.

Sensory Navigation System for Indoor Localization and Orientation of Users with Cognitive Disabilities in Daily Tasks and Emergency Situations

Sensory Navigation System for Indoor Localization and Orientation of Users with Cognitive Disabilities in Daily Tasks and Emergency Situations

The geometry of correlated variability leads to highly suboptimal discriminative sensory coding.

The brain represents the world through the activity of neural populations; however, whether the computational goal of sensory coding is to support discrimination of sensory stimuli or to generate an internal model of the sensory world is unclear. Correlated variability across a neural population (noise correlations) is commonly observed experimentally, and many studies demonstrate that correlated variability improves discriminative sensory coding compared to a null model with no correlations. However, such results do not address whether correlated variability is for discriminative sensory coding. If the computational goal of sensory coding is discriminative, then correlated variability should be optimized to support that goal. We assessed optimality of noise correlations for discriminative sensory coding in diverse datasets by developing two novel null models, each with a biological interpretation. Across datasets, we found correlated variability in neural populations leads to highly suboptimal discriminative sensory coding according to both null models. Furthermore, biological constraints prevent many subsets of the neural populations from achieving optimality, and subselecting based on biological criteria leaves discriminative coding performance suboptimal. Finally, we show that optimal subpopulation are exponentially small as the population size grows. Together, these results demonstrate that the geometry of correlated variability leads to highly suboptimal discriminative sensory coding.

The ecomorphological radiation of phyllostomid bats

Abstract Neotropical leaf-nosed bats (Family Phyllostomidae) underwent an impressive adaptive radiation primarily characterized by the diversification of dietary strategies in tandem with functional morphological diversification of their craniodental and sensory systems. In this perspective, we integrate information from extensive research across multiple fields to outline the interplay between extrinsic and intrinsic drivers of the phyllostomid adaptive radiation and the resulting ecomorphological diversity of the clade. We begin by exploring the relationship between phyllostomids and their environments, focusing on the ecogeographical drivers of their radiation. Then, we detail current knowledge about the role of genes and development in enabling morphological diversification of the group. Finally, we describe the breathtaking ecomorphological diversification of phyllostomids, trying to unveil functional connections underlying their diverse dietary niches.

Construction of Sensory Evaluation System of Purple Sweet Potato Rice Steamed Sponge Cake Based on Fuzzy Mathematics.

This paper presents the establishment of a sensory evaluation system for purple sweet potato rice steamed sponge cake (PSPRSSC) utilizing fuzzy mathematics. Initially, eight key sensory evaluation indices were identified through expert consultations. These indices were subsequently prioritized using fuzzy binary comparison, resulting in the following order: aroma, taste, crust color, elasticity, viscosity, chewiness, hardness, and brightness. The corresponding weight values assigned to each index were 23%, 18%, 16%, 13%, 12%, 8%, 6%, and 4%, respectively. Notably, aroma was found to have a more significant impact than visual attributes in the sensory evaluation of PSPRSSC. Based on this prioritization, comprehensive sensory evaluation criteria for PSPRSSC were formulated. Verification tests confirmed the efficacy of the proposed evaluation system. This study provides critical data and theoretical support for the sensory quality assessment of PSPRSSC, thereby facilitating its industrialization and enhancing its market viability.

Wing–antenna interaction reduces odour fatigue in butterfly odour-tracking flight

Flying insects exhibit remarkable capabilities in coordinating their olfactory sensory system and flapping wings during odour plume-tracking flights. While observations have indicated that their flapping wing motion can ‘sniff’ up the incoming plumes for better odour sampling range, how flapping motion impacts the odour concentration field around the antennae is unknown. Here, we reconstruct the body and wing kinematics of a forwards-flying butterfly based on high-speed images. Using an in-house computational fluid dynamics solver, we simulate the unsteady flow field and odourant transport process by solving the Navier–Stokes and odourant advection-diffusion equations. Our results show that, during flapping flight, the interaction between wing leading-edge vortices and antenna vortices strengthens the circulation of antenna vortices by over two-fold compared with cases without flapping motion, leading to a significant increase in odour intensity fluctuation along the antennae. Specifically, the interaction between the wings and antennae amplifies odour intensity fluctuations on the antennae by up to 8.4 fold. This enhancement is critical in preventing odour fatigue during odour-tracking flights. Further analysis reveals that this interaction is influenced by the inter-antennal angle. Adjusting this angle allows insects to balance between resistance to odour fatigue and the breadth of odour sampling. Narrower inter-antennal angles enhance fatigue resistance, while wider angles extend the sampling range but reduce resistance. Additionally, our findings suggest that while the flexibility of the wings and the thorax's pitching motion in butterflies do influence odour fluctuation, their impact is relatively secondary to that of the wing–antenna interaction.

Sensory systems: Geckos shake up our understanding of vertebrate audition

A newly discovered auditory pathway in geckos processes low-frequency vibrations using the saccule, an inner ear organ previously thought to serve only vestibular functions in amniotes. These findings challenge our understanding of hearing evolution and suggest greater conservation of auditory function across vertebrates.

Iontronic tactile sensory system for plant species and growth-stage classification

Iontronic tactile sensory system for plant species and growth-stage classification

Analysis of anticipatory and compensatory postural adjustment in women of different age groups using surface electromyography.

Postural balance is crucial for daily activities, relying on the coordination of sensory systems. Balance impairment, common in the elderly, is a leading cause of mortality in this population. To analyze balance, methods like postural adjustment analysis using electromyography (EMG) have been developed. With age, women tend to experience reduced mobility and greater muscle loss compared to men. However, few studies have focused on postural adjustments in women of different ages using EMG of the lower limbs during laterolateral and anteroposterior movements. This gap could reveal a decrease in muscle activation time with aging, as activation time is vital for postural adjustments. This study aimed to analyze muscle activation times in women of different ages during postural adjustments. Thirty women were divided into two groups: young and older women. A controlled biaxial force platform was used for static and dynamic balance tests while recording lower limb muscle activity using EMG. Data analysis focused on identifying muscle activation points and analyzing postural adjustment times. Results showed significant differences in muscle activation times between the two groups across various muscles and platform tilt conditions. Younger women had longer muscle activation times than older women, particularly during laterolateral platform inclinations. In anteroposterior movements, older women exhibited longer activation times compared to their laterolateral performance, with fewer differences between the groups. Overall, older women had shorter muscle activation times than younger women, suggesting a potential indicator of imbalance and increased fall risk.

Two tiers, not one: Different sources of extrinsic mortality have opposing effects on life history traits.

Guided by concepts from life history (LH) theory, a large human research literature has tested the hypothesis that exposures to extrinsic mortality (EM) promote the development of faster LH strategies (e.g., earlier/faster reproduction, higher offspring number). A competing model proposes that, because EM in the past was intimately linked to energetic constraints, such exposures specifically led to the development of slower LH strategies. We empirically address this debate by examining (1) LH variation among small-scale societies under different environmental conditions; (2) country-, regional- and community-level correlations between ecological conditions, mortality, maturational timing, and fertility; (3) individual-level correlations between this same set of factors; and (4) natural experiments leveraging the impact of externally-caused changes in mortality on LH traits. Partially supporting each model, we found that harsh conditions encompassing energetic stress and ambient cues to EM (external cues received through sensory systems) have countervailing effects on the development of LH strategies, both delaying pubertal maturation and promoting an accelerated pace of reproduction and higher offspring number. We conclude that, although energetics are fundamental to many developmental processes, providing a first tier of environmental influence, this first tier alone cannot explain these countervailing effects. An important second tier of environmental influence is afforded by ambient cues to EM. We advance a 2-tiered model that delineates this second tier and its central role in regulating development of LH strategies. Consideration of the first and second tier together is necessary to account for the observed countervailing shifts toward both slower and faster LH traits.

A Drosophila-inspired intelligent olfactory biomimetic sensing system for gas recognition in complex environments

The olfactory sensory system of Drosophila has several advantages, including low power consumption, high rapidity and high accuracy. Here, we present a biomimetic intelligent olfactory sensing system based on the integration of an 18-channel microelectromechanical system (MEMS) sensor array (16 gas sensors, 1 humidity sensor and 1 temperature sensor), a complementary metal‒oxide‒semiconductor (CMOS) circuit and an olfactory lightweight machine-learning algorithm inspired by Drosophila. This system is an artificial version of the biological olfactory perception system with the capabilities of environmental sensing, multi-signal processing, and odor recognition. The olfactory data are processed and reconstructed by the combination of a shallow neural network and a residual neural network, with the aim to determine the noxious gas information in challenging environments such as high humidity scenarios and partially damaged sensor units. As a result, our electronic olfactory sensing system is capable of achieving comprehensive gas recognition by qualitatively identifying 7 types of gases with an accuracy of 98.5%, reducing the number of parameters and the difficulty of calculation, and quantitatively predicting each gas of 3–5 concentration gradients with an accuracy of 93.2%; thus, these results show superiority of our system in supporting alarm systems in emergency rescue scenarios.

Multimodal In-Sensor Computing System Using Integrated Silicon Photonic Convolutional Processor.

Photonic integrated circuits offer miniaturized solutions for multimodal spectroscopic sensory systems by leveraging the simultaneous interaction of light with temperature, chemicals, and biomolecules, among others. The multimodal spectroscopic sensory data is complex and has huge data volume with high redundancy, thus requiring high communication bandwidth associated with high communication power consumption to transfer the sensory data. To circumvent this high communication cost, the photonic sensor and processor are brought into intimacy and propose a photonic multimodal in-sensor computing system using an integrated silicon photonic convolutional processor. A microring resonator crossbar array is used as the photonic processor to implement convolutional operation with 5-bit accuracy, validated through image edge detection tasks. Further integrating the processor with a photonic spectroscopic sensor, the in situ processing of multimodal spectroscopic sensory data is demonstrated, achieving the classification of protein species of different types and concentrations at various temperatures. A classification accuracy of 97.58% across 45 different classes is achieved. The multimodal in-sensor computing system demonstrates the feasibility of integrating photonic processors and photonic sensors to enhance the data processing capability of photonic devices at the edge.

A Biomimetic Nociceptor Based on a Vertical Multigate, Multichannel Neuromorphic Transistor.

Nociceptors, crucial sensory receptors within biological systems, are essential for survival in diverse and potentially hazardous environments. Efforts to replicate nociceptors through advanced electronic devices, such as memristors and neuromorphic transistors, have achieved limited success, capturing basic nociceptive functions while more advanced characteristics like various forms of central sensitization and analgesic effect remain out of reach. Here, we introduce a vertical multigate, multichannel electrolyte-gated transistor (Vm-EGT), designed to mimic nociceptors. Utilizing the hybrid mechanism combining electric-double-layer (EDL) with ion intercalation/deintercalation in EGTs, our approach successfully replicates peripheral sensitization and desensitization characteristics of nociceptors. The intricate multigate and multichannel design of the Vm-EGT enables the emulation of more advanced nociceptive functionalities, including central sensitization and analgesic effect. Furthermore, we demonstrate that by exploiting the inherent current-voltage relationship, the Vm-EGT can simulate these advanced nociceptive features and seamlessly transition between them. Integrating a Vm-EGT with a thermistor and a heating plate, we have developed an artificial thermal nociceptor that closely mirrors the sensory attributes of its biological counterpart. Our approach significantly advances the emulation of nociceptors, providing a basis for the development of sophisticated artificial sensory systems and intelligent robotics.

Development augmented reality assisted teaching modules human sensory system to improve student learning outcomes

In the era of digital transformation, the use of technology to improve the quality of learning is very important. This research aimed to develop a teaching module for human sensory system material assisted by augmented reality media to improve students' biology learning outcomes. This research uses research and development methods. The subjects of this research were 22 Biology Education students at the University of Papua. Data collection instruments include validation sheets and questionnaires to determine the validity and responses of students to teaching modules as well as providing multiple choice questions to measure learning outcomes. The data analysis technique is descriptive by calculating validation results, analyzing student response questionnaires and student learning outcomes. The research results show that media and material expert validation test results obtained a percentage of 93.33% with a very valid category. The results of assessing student responses in the trial obtained an average percentage of 85.13% in the very good category. Student biology learning results show an average of 61.36 in the sufficient category. The conclusion of the research on Augmented Reality-assisted teaching modules meets the criteria of being valid, practical and effective and improving students' biology learning outcomes.

Reduction in the olfactory ability in aging Mitf mutant mice without evidence of neurodegeneration.

Age-related decline occurs in most brain structures and sensory systems. An illustrative case is olfaction. The olfactory bulb (OB) undergoes deterioration with age, resulting in reduced olfactory ability. A decline in olfaction is also associated with early symptoms of neurodegenerative diseases, including Alzheimer's disease (AD) and Parkinson's disease (PD). However, the underlying reasons are unclear. The microphthalmia-associated transcription factor (MITF) is expressed in the projection neurons (PNs) of the OB-the mitral and tufted (M/T) cells. Primary M/T cells from Mitf mutant mice show hyperactivity, potentially attributed to the reduced expression of a key potassium channel subunit, Kcnd3/Kv4.3. This influences intrinsic plasticity, an essential mechanism involving the non-synaptic regulation of neuronal activity. As neuronal hyperactivity often precedes neurodegenerative conditions, the current study aimed to determine whether the absence of Mitf causes degenerative effects during aging. Aged Mitf mutant mice showed reduced olfactory ability without inflammation. However, an increase in the expression of potassium channel subunit genes in the OBs of aged Mitf mi-vga9/mi-vga9 mice suggests that during aging, compensatory mechanisms lead to stabilization.