An assistive computer vision tool to automatically detect changes in fish behavior in response to ambient odor

The analysis of fish behavior in response to odor stimulation is a crucial component of the general study of cross-modal sensory integration in vertebrates. In zebrafish, the centrifugal pathway runs between the olfactory bulb and the neural retina, originating at the terminalis neuron in the olfactory bulb. Any changes in the ambient odor of a fish’s environment warrant a change in visual sensitivity and can trigger mating-like behavior in males due to increased GnRH signaling in the terminalis neuron. Behavioral experiments to study this phenomenon are commonly conducted in a controlled environment where a video of the fish is recorded over time before and after the application of chemicals to the water. Given the subtleties of behavioral change, trained biologists are currently required to annotate such videos as part of a study. This process of manually analyzing the videos is time-consuming, requires multiple experts to avoid human error/bias and cannot be easily crowdsourced on the Internet. Machine learning algorithms from computer vision, on the other hand, have proven to be effective for video annotation tasks because they are fast, accurate, and, if designed properly, can be less biased than humans. In this work, we propose to automate the entire process of analyzing videos of behavior changes in zebrafish by using tools from computer vision, relying on minimal expert supervision. The overall objective of this work is to create a generalized tool to predict animal behaviors from videos using state-of-the-art deep learning models, with the dual goal of advancing understanding in biology and engineering a more robust and powerful artificial information processing system for biologists.

An Assistive Computer Vision Tool to Automatically Detect Changes in Fish Behavior In Response to Ambient Odor

The analysis of fish behavior in response to odor stimulation is a crucial component of the general study of cross-modal sensory integration in vertebrates. In zebrafish, the centrifugal pathway runs between the olfactory bulb and the neural retina, originating at the terminalis neuron in the olfactory bulb. Any changes in the ambient odor of a fish's environment warrants a change in visual sensitivity and can trigger mating-like behavior in males due to increased GnRH signaling in the terminalis neuron. Behavioral experiments to study this phenomenon are commonly conducted in a controlled environment where a video of the fish is recorded over time before and after the application of chemicals to the water. Given the subtleties of behavioral change, trained biologists are currently required to annotate such videos as part of a study. This process of manually analyzing the videos is time-consuming, requires multiple experts to avoid human error/bias and cannot be easily crowdsourced on the Internet. Machine learning algorithms from computer vision, on the other hand, have proven to be effective for video annotation tasks because they are fast, accurate, and, if designed properly, can be less biased than humans. In this work, we propose to automate the entire process of analyzing videos of behavior changes in zebrafish by using tools from computer vision, relying on minimal expert supervision. The overall objective of this work is to create a generalized tool to predict animal behaviors from videos using state-of-the-art deep learning models, with the dual goal of advancing understanding in biology and engineering a more robust and powerful artificial information processing system for biologists.

What Makes a Better Smeller?

Olfaction is often viewed as difficult, yet the empirical evidence suggests a different picture. A closer look shows people around the world differ in their ability to detect, discriminate, and name odors. This gives rise to the question of what influences our ability to smell. Instead of focusing on olfactory deficiencies, this review presents a positive perspective by focusing on factors that make someone a better smeller. We consider three driving forces in improving olfactory ability: one’s biological makeup, one’s experience, and the environment. For each factor, we consider aspects proposed to improve odor perception and critically examine the evidence; as well as introducing lesser discussed areas. In terms of biology, there are cases of neurodiversity, such as olfactory synesthesia, that serve to enhance olfactory ability. Our lifetime experience, be it typical development or unique training experience, can also modify the trajectory of olfaction. Finally, our odor environment, in terms of ambient odor or culinary traditions, can influence odor perception too. Rather than highlighting the weaknesses of olfaction, we emphasize routes to harnessing our olfactory potential.

Effects of a Pleasant Natural Odor on Mood: No Influence of Age

Certain fragrances significantly influence affective and cognitive states in humans as shown not only in the laboratory but also in natural outdoor settings. The aim of the present study was to investigate the influence of age on the relationship between a complex, natural odor and affective states, i.e., calmness, alertness and positive mood, in the field. The effect of a selected ambient odor on emotional well-being as well as on evaluations of odor intensity and pleasantness was assessed in healthy human subjects and compared with a control condition involving the same outdoor environment without the tested natural odor. The influence of age was studied in three different age groups, i.e., school children, young adults and elderly subjects. Despite overall emotional differences as a function of age, the tested ambient odor compared with the control condition improved subjective ratings of calmness, alertness and positive mood in all groups. Differences were found between age groups in regard to odor pleasantness, but not intensity. We concluded that the beneficial effect of the natural odor on affective states is not constrained by age. Furthermore, we replicated our previous finding that pleasant natural fragrances in outdoor environments improve mood state in humans.

Sniffing the mood for cooperation: Personality and odor induced affective states effects

The paper explores situational and dispositional underpinnings of cooperative behavior. According to psychological research, cooperation is strongly related to affective states (Forgas, 1998) and personality dimensions (Volk, Thöni, & Ruigrok, 2011). In an experimental study we examined the conditions under which people cooperate with each other. The dispositional traits of co-workers (personality), the contribution to a collaborative effort, and a situational factor – ambient odor condition were taken into consideration. A one-way ANOVA revealed that compared to a malodorous condition, both the pleasant odor condition and the natural odor condition showed higher rates of cooperation. Further analysis indicated that only malodors influenced affective states which in turn determined social decisions. Although we found effects for the participants’ agreeableness and the coworker’s contribution to a joint work, they appeared to play a less critical role than affective states induced by the experimental odor conditions tested here.