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IScience Jan 2024Multimodal cues can improve behavioral responses by enhancing the detection and localization of sensory cues and reducing response times. Across species, studies have...
Multimodal cues can improve behavioral responses by enhancing the detection and localization of sensory cues and reducing response times. Across species, studies have shown that multisensory integration of visual and olfactory cues can improve response accuracy. However, in real-world settings, sensory cues are often noisy; visual and olfactory cues can be deteriorated, masked, or mixed, making the target cue less clear to the receiver. In this study, we use an associative learning paradigm (Free Moving Proboscis Extension Reflex, FMPER) to show that having multimodal cues may improve the accuracy of bees' responses to noisy cues. Adding a noisy visual cue improves the accuracy of response to a noisy olfactory cue, despite neither the clear nor noisy visual cue being sufficient when paired with a novel olfactory cue. This may provide insight into the neural mechanisms underlying multimodal processing and the effects of environmental change on pollination services.
PubMed: 38161424
DOI: 10.1016/j.isci.2023.108587 -
Empirical Software Engineering 2024Test smells are symptoms of sub-optimal design choices adopted when developing test cases. Previous studies have proved their harmfulness for test code maintainability...
Test smells are symptoms of sub-optimal design choices adopted when developing test cases. Previous studies have proved their harmfulness for test code maintainability and effectiveness. Therefore, researchers have been proposing automated, heuristic-based techniques to detect them. However, the performance of these detectors is still limited and dependent on tunable thresholds. We design and experiment with a novel test smell detection approach based on machine learning to detect four test smells. First, we develop the largest dataset of manually-validated test smells to enable experimentation. Afterward, we train six machine learners and assess their capabilities in within- and cross-project scenarios. Finally, we compare the ML-based approach with state-of-the-art heuristic-based techniques. The key findings of the study report a negative result. The performance of the machine learning-based detector is significantly better than heuristic-based techniques, but none of the learners able to overcome an average F-Measure of 51%. We further elaborate and discuss the reasons behind this negative result through a qualitative investigation into the current issues and challenges that prevent the appropriate detection of test smells, which allowed us to catalog the next steps that the research community may pursue to improve test smell detection techniques.
PubMed: 38456065
DOI: 10.1007/s10664-023-10436-2 -
Cell Reports May 2024Shifts in the magnitude and nature of gut microbial metabolites have been implicated in Alzheimer's disease (AD), but the host receptors that sense and respond to these...
Shifts in the magnitude and nature of gut microbial metabolites have been implicated in Alzheimer's disease (AD), but the host receptors that sense and respond to these metabolites are largely unknown. Here, we develop a systems biology framework that integrates machine learning and multi-omics to identify molecular relationships of gut microbial metabolites with non-olfactory G-protein-coupled receptors (termed the "GPCRome"). We evaluate 1.09 million metabolite-protein pairs connecting 408 human GPCRs and 335 gut microbial metabolites. Using genetics-derived Mendelian randomization and integrative analyses of human brain transcriptomic and proteomic profiles, we identify orphan GPCRs (i.e., GPR84) as potential drug targets in AD and that triacanthine experimentally activates GPR84. We demonstrate that phenethylamine and agmatine significantly reduce tau hyperphosphorylation (p-tau181 and p-tau205) in AD patient induced pluripotent stem cell-derived neurons. This study demonstrates a systems biology framework to uncover the GPCR targets of human gut microbiota in AD and other complex diseases if broadly applied.
Topics: Alzheimer Disease; Humans; Gastrointestinal Microbiome; Receptors, G-Protein-Coupled; Induced Pluripotent Stem Cells; tau Proteins; Proteomics; Phosphorylation; Brain; Neurons; Multiomics
PubMed: 38652661
DOI: 10.1016/j.celrep.2024.114128 -
Proceedings of the National Academy of... Jul 2023One major question in neuroscience is how to relate connectomes to neural activity, circuit function, and learning. We offer an answer in the peripheral olfactory...
One major question in neuroscience is how to relate connectomes to neural activity, circuit function, and learning. We offer an answer in the peripheral olfactory circuit of the larva, composed of olfactory receptor neurons (ORNs) connected through feedback loops with interconnected inhibitory local neurons (LNs). We combine structural and activity data and, using a holistic normative framework based on similarity-matching, we formulate biologically plausible mechanistic models of the circuit. In particular, we consider a linear circuit model, for which we derive an exact theoretical solution, and a nonnegative circuit model, which we examine through simulations. The latter largely predicts the ORN [Formula: see text] LN synaptic weights found in the connectome and demonstrates that they reflect correlations in ORN activity patterns. Furthermore, this model accounts for the relationship between ORN [Formula: see text] LN and LN-LN synaptic counts and the emergence of different LN types. Functionally, we propose that LNs encode soft cluster memberships of ORN activity, and partially whiten and normalize the stimulus representations in ORNs through inhibitory feedback. Such a synaptic organization could, in principle, autonomously arise through Hebbian plasticity and would allow the circuit to adapt to different environments in an unsupervised manner. We thus uncover a general and potent circuit motif that can learn and extract significant input features and render stimulus representations more efficient. Finally, our study provides a unified framework for relating structure, activity, function, and learning in neural circuits and supports the conjecture that similarity-matching shapes the transformation of neural representations.
Topics: Animals; Drosophila; Olfactory Receptor Neurons; Smell; Larva; Connectome
PubMed: 37428907
DOI: 10.1073/pnas.2117484120 -
Biomolecules Dec 2023The detection of Parkinson's disease (PD) in its early stages is of great importance for its treatment and management, but consensus is lacking on what information is...
The detection of Parkinson's disease (PD) in its early stages is of great importance for its treatment and management, but consensus is lacking on what information is necessary and what models should be used to best predict PD risk. In our study, we first grouped PD-associated factors based on their cost and accessibility, and then gradually incorporated them into risk predictions, which were built using eight commonly used machine learning models to allow for comprehensive assessment. Finally, the Shapley Additive Explanations (SHAP) method was used to investigate the contributions of each factor. We found that models built with demographic variables, hospital admission examinations, clinical assessment, and polygenic risk score achieved the best prediction performance, and the inclusion of invasive biomarkers could not further enhance its accuracy. Among the eight machine learning models considered, penalized logistic regression and XGBoost were the most accurate algorithms for assessing PD risk, with penalized logistic regression achieving an area under the curve of 0.94 and a Brier score of 0.08. Olfactory function and polygenic risk scores were the most important predictors for PD risk. Our research has offered a practical framework for PD risk assessment, where necessary information and efficient machine learning tools were highlighted.
Topics: Humans; Parkinson Disease; Algorithms; Genetic Risk Score; Hospitalization; Machine Learning
PubMed: 38136632
DOI: 10.3390/biom13121761 -
Frontiers in Neuroscience 2023In deep neural networks, representational learning in the middle layer is essential for achieving efficient learning. However, the currently prevailing backpropagation...
In deep neural networks, representational learning in the middle layer is essential for achieving efficient learning. However, the currently prevailing backpropagation learning rules (BP) are not necessarily biologically plausible and cannot be implemented in the brain in their current form. Therefore, to elucidate the learning rules used by the brain, it is critical to establish biologically plausible learning rules for practical memory tasks. For example, learning rules that result in a learning performance worse than that of animals observed in experimental studies may not be computations used in real brains and should be ruled out. Using numerical simulations, we developed biologically plausible learning rules to solve a task that replicates a laboratory experiment where mice learned to predict the correct reward amount. Although the extreme learning machine (ELM) and weight perturbation (WP) learning rules performed worse than the mice, the feedback alignment (FA) rule achieved a performance equal to that of BP. To obtain a more biologically plausible model, we developed a variant of FA, FA_Ex-100%, which implements direct dopamine inputs that provide error signals locally in the layer of focus, as found in the mouse entorhinal cortex. The performance of FA_Ex-100% was comparable to that of conventional BP. Finally, we tested whether FA_Ex-100% was robust against rule perturbations and biologically inevitable noise. FA_Ex-100% worked even when subjected to perturbations, presumably because it could calibrate the correct prediction error (e.g., dopaminergic signals) in the next step as a teaching signal if the perturbation created a deviation. These results suggest that simplified and biologically plausible learning rules, such as FA_Ex-100%, can robustly facilitate deep supervised learning when the error signal, possibly conveyed by dopaminergic neurons, is accurate.
PubMed: 37886676
DOI: 10.3389/fnins.2023.1160899 -
Molecular Psychiatry Nov 2023Early life adversity (ELA) causes aberrant functioning of neural circuits affecting the health of an individual. While ELA-induced behavioural disorders resulting from...
Early life adversity (ELA) causes aberrant functioning of neural circuits affecting the health of an individual. While ELA-induced behavioural disorders resulting from sensory and cognitive disabilities can be assessed clinically, the neural mechanisms need to be probed using animal models by employing multi-pronged experimental approaches. As ELA can alter sensory perception, we investigated the effect of early weaning on murine olfaction. By implementing go/no-go odour discrimination paradigm, we observed olfactory learning and memory impairments in early life stressed (ELS) male mice. As olfactory bulb (OB) circuitry plays a critical role in odour learning, we studied the plausible changes in the OB of ELS mice. Lowered c-Fos activity in the external plexiform layer and a reduction in the number of dendritic processes of somatostatin-releasing, GABAergic interneurons (SOM-INs) in the ELS mice led us to hypothesise the underlying circuit. We recorded reduced synaptic inhibitory feedback on mitral/tufted (M/T) cells, in the OB slices from ELS mice, explaining the learning deficiency caused by compromised refinement of OB output. The reduction in synaptic inhibition was nullified by the photo-activation of ChR2-expressing SOM-INs in ELS mice. The role of SOM-INs was revealed by learning-dependent refinement of Cadynamics quantified by GCaMP6f signals, which was absent in ELS mice. Further, the causal role of SOM-INs involving circuitry was investigated by optogenetic modulation during the odour discrimination learning. Photo-activating these neurons rescued the ELA-induced learning deficits. Conversely, photo-inhibition caused learning deficiency in control animals, while it completely abolished the learning in ELS mice, confirming the adverse effects mediated by SOM-INs. Our results thus establish the role of specific inhibitory circuit in pre-cortical sensory area in orchestrating ELA-dependent changes.
Topics: Mice; Male; Animals; Olfactory Bulb; Adverse Childhood Experiences; Interneurons; Neurons; Somatostatin
PubMed: 37726451
DOI: 10.1038/s41380-023-02244-3 -
ArXiv Feb 2024Animals adjust their behavioral response to sensory input adaptively depending on past experiences. The flexible brain computation is crucial for survival and is of...
Animals adjust their behavioral response to sensory input adaptively depending on past experiences. The flexible brain computation is crucial for survival and is of great interest in neuroscience. The nematode C. elegans modulates its navigation behavior depending on the association of odor butanone with food (appetitive training) or starvation (aversive training), and will then climb up the butanone gradient or ignore it, respectively. However, the exact change in navigation strategy in response to learning is still unknown. Here we study the learned odor navigation in worms by combining precise experimental measurement and a novel descriptive model of navigation. Our model consists of two known navigation strategies in worms: biased random walk and weathervaning. We infer weights on these strategies by applying the model to worm navigation trajectories and the exact odor concentration it experiences. Compared to naive worms, appetitive trained worms up-regulate the biased random walk strategy, and aversive trained worms down-regulate the weathervaning strategy. The statistical model provides prediction with $>90 \%$ accuracy of the past training condition given navigation data, which outperforms the classical chemotaxis metric. We find that the behavioral variability is altered by learning, such that worms are less variable after training compared to naive ones. The model further predicts the learning-dependent response and variability under optogenetic perturbation of the olfactory neuron AWC$^\mathrm{ON}$. Lastly, we investigate neural circuits downstream from AWC$^\mathrm{ON}$ that are differentially recruited for learned odor-guided navigation. Together, we provide a new paradigm to quantify flexible navigation algorithms and pinpoint the underlying neural substrates.
PubMed: 38013890
DOI: No ID Found -
Conservation Physiology 2023Many migratory fishes are thought to navigate to natal streams using olfactory cues learned during early life stages. However, direct evidence for early-life olfactory...
Many migratory fishes are thought to navigate to natal streams using olfactory cues learned during early life stages. However, direct evidence for early-life olfactory imprinting is largely limited to Pacific salmon, and other species suspected to imprint show life history traits and reproductive strategies that raise uncertainty about the generality of the salmonid-based conceptual model of olfactory imprinting in fishes. Here, we studied early-life olfactory imprinting in lake sturgeon (), which have a life cycle notably different from Pacific salmon, but are nonetheless hypothesized to home via similar mechanisms. We tested one critical prediction of the hypothesis that early-life olfactory imprinting guides natal homing in lake sturgeon: that exposure to odorants during early-life stages results in increased activity when exposed to those odorants later in life. Lake sturgeon were exposed to artificial odorants (phenethyl alcohol and morpholine) during specific developmental windows and durations (limited to the egg, free-embryo, exogenous feeding larvae and juvenile stages), and later tested as juveniles for behavioral responses to the odorants that were demonstrative of olfactory memory. Experiments revealed that lake sturgeon reared in stream water mixed with artificial odorants for as little as 7 days responded to the odorants in behavioral assays over 50 days after the initial exposure, specifically implicating the free-embryo and larval stages as critical imprinting periods. Our study provides evidence for olfactory imprinting in a non-salmonid fish species, and supports further consideration of conservation tactics such as stream-side rearing facilities that are designed to encourage olfactory imprinting to targeted streams during early life stages. Continued research on lake sturgeon can contribute to a model of olfactory imprinting that is more generalizable across diverse fish species and will inform conservation actions for one of the world's most imperiled fish taxonomic groups.
PubMed: 37405172
DOI: 10.1093/conphys/coad045 -
Scientific Reports Nov 2023Temperature is a primary factor affecting the physiology of ectothermic animals and global warming of water bodies may therefore impact aquatic life. Understanding the...
Temperature is a primary factor affecting the physiology of ectothermic animals and global warming of water bodies may therefore impact aquatic life. Understanding the effects of near-future predicted temperature changes on the behaviour and underlying molecular mechanisms of aquatic animals is of particular importance, since behaviour mediates survival. In this study, we investigate the effects of developmental temperature on locomotory behaviour and olfactory learning in the zebrafish, Danio rerio. We exposed zebrafish from embryonic stage to either control (28 °C) or elevated temperature (30 °C) for seven days. Overall, warming reduced routine swimming activity and caused upregulation of metabolism and neuron development genes. When exposed to olfactory cues, namely catfish cue, a non-alarming but novel odour, and conspecifics alarming cue, warming differently affected the larvae response to the two cues. An increase in locomotory activity and a large transcriptional reprogramming was observed at elevated temperature in response to novel odour, with upregulation of cell signalling, neuron development and neuron functioning genes. As this response was coupled with the downregulation of genes involved in protein translation and ATP metabolism, novel odour recognition in future-predicted thermal conditions would require energetic trade-offs between expensive baseline processes and responsive functions. To evaluate their learning abilities at both temperatures, larvae were conditioned with a mixture of conspecifics alarm cue and catfish cue. Regardless of temperature, no behavioural nor gene expression changes were detected, reinforcing our findings that warming mainly affects zebrafish molecular response to novel odours. Overall, our results show that future thermal conditions will likely impact developing stages, causing trade-offs following novel olfactory detection in the environment.
Topics: Animals; Zebrafish; Odorants; Larva; Swimming; Temperature; Fever
PubMed: 38030737
DOI: 10.1038/s41598-023-48287-y