The preference for sugar over sweetener depends on a gut sensor cell

Guided by gut sensory cues, humans and animals prefer nutritive sugars over non-caloric sweeteners, but how the gut steers such preferences remains unknown. In the intestine, neuropod cells synapse with vagal neurons to convey sugar stimuli to the brain within seconds. Here, we found that cholecystokinin (CCK)-labeled duodenal neuropod cells differentiate and transduce luminal stimuli from sweeteners and sugars to the vagus nerve using sweet taste receptors and sodium glucose transporters. The two stimulus types elicited distinct neural pathways: while sweetener stimulated purinergic neurotransmission, sugar stimulated glutamatergic neurotransmission. To probe the contribution of these cells to behavior, we developed optogenetics for the gut lumen by engineering a flexible fiberoptic. We showed that preference for sugar over sweetener in mice depends on neuropod cell glutamatergic signaling. By swiftly discerning the precise identity of nutrient stimuli, gut neuropod cells serve as the entry point to guide nutritive choices.

Co-existing neuropeptide FF and gonadotropin-releasing hormone 3 coordinately modulate male sexual behavior

Animals properly perform sexual behaviors by using multiple sensory cues. However, neural mechanisms integrating multiple sensory cues and regulating motivation for sexual behaviors remain unclear. Here, we focused on peptidergic neurons, terminal nerve gonadotropin-releasing hormone (TN-GnRH) neurons, which receive inputs from various sensory systems and co-express neuropeptide FF (NPFF) in addition to GnRH. Our behavioral analyses using knockout medaka of GnRH (gnrh3) and/or NPFF (npff) demonstrated that some sexual behavioral repertoires were ‘delayed’, not disrupted, in gnrh3 and npff single knockout males, while the double knockout appeared to alleviate the significant defects that were observed in single knockouts. We also found anatomical evidence to show that both neuropeptides modulate the sexual behavior-controlling brain areas. Furthermore, we demonstrated that NPFF activates neurons in the preoptic area via indirect pathway, which is considered to induce the increase in motivation for male sexual behaviors. Considering these results, we propose a novel mechanism by which co-existing peptides of the TN-GnRH neurons, NPFF and GnRH3, coordinately modulate certain neuronal circuit for the control of behavioral motivation. Our results may go a long way toward understanding the functional significance of peptidergic neuromodulation in response to sensory information from the external environments.

The Application of Machine Learning ICA-VMD in an Intelligent Diagnosis System in a Low SNR Environment

This paper proposes a new method called independent component analysis–variational mode decomposition (ICA-VMD), which combines ICA and VMD. The purpose is to study the application of ICA-VMD in low signal-to-noise ratio (SNR) signal processing and data analysis. ICA is a very important method in the field of machine learning. It is an unsupervised learning algorithm that can dig out the independent factors hidden in the observation signal. The VMD method estimates each signal component by solving the frequency domain variational optimization problem, and it is very suitable for mechanical fault diagnosis. The advantage of ICA-VMD is that it requires two sensory cues to distinguish the original source from the unwanted noise. In the three cases studied here, the original source was first contaminated by white Gaussian noise. The three cases in this study are under different SNR conditions. The SNR in the first case is –6.46 dB, the SNR in the second case is –21.3728, and the SNR in the third case is –46.8177. The simulation results show that the ICA-VMD method can effectively recover the original source from the contaminated data. It is hoped that, in the future, there will be new discoveries and advances in science and technology to solve the noise interference problem through this method.

Targeting targeted memory reactivation: characteristics of cued reactivation in sleep

Targeted memory reactivation (TMR) is a technique in which sensory cues associated with memories during wake are used to trigger memory reactivation during subsequent sleep. The characteristics of such cued reactivation, and the optimal placement of TMR cues, remain to be determined. We built an EEG classification pipeline that discriminated reactivation of right- and left-handed movements and found that cues which fall on the up-going transition of the slow oscillation (SO) are more likely to elicit a classifiable reactivation. We also used a novel machine learning pipeline to predict the likelihood of eliciting a classifiable reactivation after each TMR cue using the presence of spindles and features of SOs. Finally, we found that reactivations occurred either immediately after the cue or one second later. These findings greatly extend our understanding of memory reactivation and pave the way for development of wearable technologies to efficiently enhance memory through cueing in sleep.

A striatal circuit balances learned fear in the presence and absence of sensory cues

During fear learning, defensive behaviors need to be finely balanced, to allow animals to return to normal behaviors after the termination of threat-indicating sensory cues. Nevertheless, the circuits underlying such balancing are largely unknown. Here, we investigate the role of direct (D1R+) - and indirect (Adora+) pathway neurons of the amygdala-striatal transition zone (AStria) in fear learning. In-vivo Ca2+ imaging revealed that fear learning increased the responses of D1R+ AStria neurons to an auditory CS, given that the animal moved. In Adora+ neurons, fear learning also induced a differential activity during freezing and movement, albeit with little influence of the CS. In-vivo optogenetic silencing during the training day showed that plasticity in D1R+ AStria neurons contributes to auditory-cued fear memories, whereas Adora+ neurons suppressed learned freezing when no CS was present. Circuit tracing experiments identified cortical input structures to the AStria, and recording of optogenetically-evoked EPSCs at the corresponding projection revealed different forms of long-term plasticity at synapses onto D1R+ and Adora+ AStria neurons. Taken together, direct- and indirect pathways neurons of the AStria show differential signs of in-vivo and ex-vivo plasticity after fear learning, and balance defensive behaviors in the presence and absence of aversively motivated sensory cues.

The effects of uncertain context inference on motor adaptation

Humans have been shown to adapt their movements when a sudden change to the dynamics of the environment is introduced, a phenomenon called motor adaptation. If the change is reverted, the adaptation is also quickly reverted. Human are also able to adapt to multiple changes in dynamics presented separately, and to be able to switch between adapted movements on the fly. Such switching relies on contextual information which is often noisy or misleading, which affects the switch between adaptations. In this work, we introduce a computational model to explain the behavioral phenomena effected by uncertain contextual information. Specifically, we present a hierarchical model for motor adaptation based on exact Bayesian inference. This model explicitly takes into account contextual information and how the dynamics of context inference affect adaptation and action selection. We show how the proposed model provides a unifying explanation for four different experimentally-established phenomena: (i) effects of sensory cues and proprioceptive information on switching between tasks, (ii) the effects of previously-learned adaptations on switching between tasks, (iii) the effects of training history on behavior in new contexts, in addition to (iv) the well-studied savings, de-adaptation and spontaneous recovery.

A persistent behavioral state enables sustained predation of humans by mosquitoes

Predatory animals first detect, then pursue, and ultimately capture prey. Sensory cues, including scent emitted by prey, are detected by the predator and used to guide pursuit. Because the pursuit phase can last for extended periods of time, it is critical for predators to persist in the chase even when prey is difficult to detect in a noisy sensory land-scape. It is equally important for predators to abandon pursuit if enough time has elapsed that prey capture is unlikely to occur. We studied prey detection and sustained pursuit in the mosquito Aedes aegypti, a micropredator of humans. These animals first detect hu-mans through sensory cues that are emitted at a distance such as carbon dioxide in breath and odor from skin. As the mosquito approaches a human, additional cues such as body heat and visual contrast signal the promise of a blood meal, which females need to produce eggs. To study how initial prey detection influences the duration of pursuit, we developed optogenetic tools to induce a brief fictive sensation of carbon dioxide and used machine learning-based classification of behavior to investigate how mosquitoes respond to subsequent human cues. We found that a 5-second optogenetic pulse of fictive carbon dioxide induced a persistent behavioral state in female mosquitoes that lasted for more than 10 minutes. This state is highly specific to females searching for a blood meal and was not induced in recently blood-fed females or in males, who do not feed on blood. In males that lack the gene fruitless, which controls persistent social behaviors in other insects, fictive carbon dioxide induced a long-lasting behavior response resembling the predatory state of females. Finally, we show that the persistent state triggered by detection of fictive carbon dioxide enabled females to engorge on a blood meal mimic offered up to 14 minutes after the initial stimulus. Our results demonstrate that a persistent internal state allows female mosquitoes to integrate multiple human sensory cues over long timescales, an ability that is key to their success as an apex micropredator of humans

How Does the Fusion of Sensory Information From Audition and Vision Impact Collective Behavior?

The present study investigates how combined information from audition and vision impacts group-level behavior. We consider a modification to the original Vicsek model that allows individuals to use auditory and visual sensing modalities to gather information from neighbors in order to update their heading directions. Moreover, in this model, the information from visual and auditory cues can be weighed differently. In a simulation study, we examine the sensitivity of the emergent group-level behavior to the weights that are assigned to each sense modality in this weighted composite model. Our findings suggest combining sensory cues may play an important role in the collective behavior and results from the composite model indicate that the group-level features from pure audition predominate.

Do Sand Smelt (Atherina presbyter Cuvier, 1829) Larvae Discriminate among Conspecifics Using Different Sensory Cues?

The ability of shoaling fish to recognise and differentiate between potential groupmates may affect their fitness and survival. Fish are capable of social recognition and multiple sensory cues mediate the recognition mechanisms. This has been comprehensively studied for juvenile and adult freshwater species. However, the recognition ability and mechanisms intervening during the larval phase of marine species are yet poorly understood. Fish larvae are capable of discriminating conspecifics from heterospecifics based on chemical and/or visual cues, but whether this recognition occurs at finer scales, such as discerning among conspecifics of different reefs, is yet understudied. Here, we tested the hypothesis that larvae of a marine fish species, the sand smelt (Atherina presbyter Cuvier, 1829), are able to recognise and associate with conspecifics of their natal reef versus conspecifics of a non-natal reef based on three sensory modalities—chemical, visual, and chemical and visual simultaneously. Results do not support our hypothesis, but still provide evidence of group cohesion and indicate large differences in the relative importance of the different senses when associating with conspecifics, with visual cues playing a more important role than chemical cues alone.

Why do some primate mothers carry their infant's corpse? A cross-species comparative study

Non-human primates respond to the death of a conspecific in diverse ways, some of which may present phylogenetic continuity with human thanatological responses. Of these responses, infant corpse carrying by mothers (ICC) is the most frequently reported. Despite its prevalence, quantitative analyses of this behaviour are scarce and inconclusive. We compiled a database of 409 published cases across 50 different primate species of mothers' responses to their infants' deaths and used Bayesian phylogenetic regressions with an information-theoretic approach to test hypotheses proposed to explain between- and within-species variation in ICC. We found that ICC was more likely when the infant's death was non-traumatic (e.g. illness) versus traumatic (e.g. infanticide), and when the mother was younger. These results support the death detection hypothesis, which proposes that ICC occurs when there are fewer contextual or sensory cues indicating death. Such an interpretation suggests that primates are able to attain an awareness of death. In addition, when carried, infant age affected ICC duration, with longer ICC observed for younger infants. This result suggests that ICC is a by-product of strong selection on maternal behaviour. The findings are discussed in the context of the evolution of emotion, and implications for evolutionary thanatology are proposed.