Human Olfaction

Olfaction, or sense of smell, is one of the many sensory/perceptual systems that humans use to process external stimuli. Human olfaction is relatively understudied. More literature has focused on olfaction in animals for which olfaction plays a larger role in critical functioning and survival. This bibliography provides key resources for information about human olfaction and then outlines twelve general topics that are of considerable value to understanding this primary sensory system. It begins by providing some general resources that outline the functions of olfaction in humans. Next, it explores the anatomy and physiology of the human olfactory system, recognizing that our understanding has been largely guided by studying animals. It addresses several important theories of human olfaction, including ones that have attempted to understand the initial receptor-level processing of stimuli and ones that have been developed to explain the whole system. After considering some historical issues in studying olfaction, it outlines the various ways that human olfaction is studied. It considers some issues in olfaction that are related to cognitive processes, such as language and memory. A critical topic in the chemical senses of smell and taste that is somewhat less relevant in other sensory systems is that of hedonics (pleasure or liking). This bibliography explores sex differences, which, though small, seem to be more prevalent than in other sensory systems. In addition, this bibliography explores the effect of age on olfaction, both in terms of the development of olfaction in children and the decline of olfaction in aging. The entry ends with clinical implications, primarily of smell loss. In light of the Covid-19 pandemic, which brought newfound appreciation for the importance of sense of smell in human experience, a summary of the effect of Covid-19 on human sense of smell is included. In this bibliography pioneering studies are emphasized, although reviews are included in cases where the literature is too extensive to be summed up by single studies.

Can associative learning be the general process for intelligent behavior in non-human animals?

The general process- and adaptive specialization hypotheses represent two contrasting explanations for understanding intelligence in non-human animals. The general process hypothesis proposes that associative learning underlies all learning, whereas the adaptive specialization hypothesis suggests additional distinct learning processes required for intelligent behavior. Here, we use a selection of experimental paradigms commonly used in comparative cognition to explore these hypotheses. We tested if a novel computational model of associative learning --- A-learning --- could solve the problems presented in these tests. Results show that this formulation of associative learning suffices as a mechanism for general animal intelligence, without the need for adaptive specialization, as long as adequate motor- and perceptual systems are there to support learning. In one of the tests, however, the addition of a short-term trace memory was required for A-learning to solve that particular task. We further provide a case study showcasing the flexibility, and lack thereof, of associative learning, when looking into potential learning of self-control and the development of behavior sequences. From these simulations we conclude that the challenges do not so much involve the complexity of a learning mechanism, but instead lie in the development of motor- and perceptual systems, and internal factors that motivate agents to explore environments with some precision, characteristics of animals that have been fine-tuned by evolution for million of years.

Sounds familiar(?): Expertise with specific musical genres modulates timing perception and micro-level synchronization to auditory stimuli

Musical expertise improves the precision of timing perception and performance – but is this expertise generic, or is it tied to the specific style(s) and genre(s) of one’s musical training? We asked expert musicians from three musical genres (folk, jazz, and EDM/hip-hop) to align click tracks and tap in synchrony with genre-specific and genre-neutral sound stimuli to determine the perceptual center (“P-center”) and variability (“beat bin”) for each group of experts. We had three stimulus categories – Organic, Electronic, and Neutral sounds – each of which had a 2 × 2 design of the acoustic factors Attack (fast/slow) and Duration (short/long). We found significant effects of Genre expertise, and a significant interaction for both P-center and P-center variability: folk and jazz musicians synchronize to sounds typical of folk and jazz in a different manner than the EDM/hip-hop producers. The results show that expertise in a specific musical genre affects our low-level perceptions of sounds as well as their affordance(s) for joint action/synchronization. The study provides new insights into the effects of active long-term musical enculturation and skill acquisition on basic sensorimotor synchronization and timing perception, shedding light on the important question of how nature and nurture intersect in the development of our perceptual systems.

Deep neural network models reveal interplay of peripheral coding and stimulus statistics in pitch perception

Perception is thought to be shaped by the environments for which organisms are optimized. These influences are difficult to test in biological organisms but may be revealed by machine perceptual systems optimized under different conditions. We investigated environmental and physiological influences on pitch perception, whose properties are commonly linked to peripheral neural coding limits. We first trained artificial neural networks to estimate fundamental frequency from biologically faithful cochlear representations of natural sounds. The best-performing networks replicated many characteristics of human pitch judgments. To probe the origins of these characteristics, we then optimized networks given altered cochleae or sound statistics. Human-like behavior emerged only when cochleae had high temporal fidelity and when models were optimized for naturalistic sounds. The results suggest pitch perception is critically shaped by the constraints of natural environments in addition to those of the cochlea, illustrating the use of artificial neural networks to reveal underpinnings of behavior.

An implicit representation of stimulus ambiguity in pupil size

To guide behavior, perceptual systems must operate on intrinsically ambiguous sensory input. Observers are usually able to acknowledge the uncertainty of their perception, but in some cases, they critically fail to do so. Here, we show that a physiological correlate of ambiguity can be found in pupil dilation even when the observer is not aware of such ambiguity. We used a well-known auditory ambiguous stimulus, known as the tritone paradox, which can induce the perception of an upward or downward pitch shift within the same individual. In two experiments, behavioral responses showed that listeners could not explicitly access the ambiguity in this stimulus, even though their responses varied from trial to trial. However, pupil dilation was larger for the more ambiguous cases. The ambiguity of the stimulus for each listener was indexed by the entropy of behavioral responses, and this entropy was also a significant predictor of pupil size. In particular, entropy explained additional variation in pupil size independent of the explicit judgment of confidence in the specific situation that we investigated, in which the two measures were decoupled. Our data thus suggest that stimulus ambiguity is implicitly represented in the brain even without explicit awareness of this ambiguity.

A Spiking Visual Neuron for Depth Perceptual Systems

The biological visual system encodes information into spikes and processes them parallelly by the neural network, which enables the perception with high throughput of visual information processing at an energy budget of a few watts. The parallelism and efficiency of bio-visual system motivates electronic implementation of this biological computing paradigm, which is challenged by the lack of bionic devices, such as spiking neurons that can mimic its biological counterpart. Here, we present a highly bio-realistic spiking visual neuron based on an Ag/TaOX/ITO memristor. Such spiking visual neuron collects visual information by a photodetector, encodes them into action potentials through the memristive spiking encoder, and interprets them for recognition tasks based on a network of neuromorphic transistors. The firing spikes generated by the memristive spiking encoders have a frequency range of 1-200 Hz and sub-micro watts power consumption, very close to the biological counterparts. Furthermore, a spiking visual system is demonstrated, replicating the distance-dependent response and eye fatigue of biological visual systems. The mimicked depth perception shows a recognition improvement by adapting to sights at different distance. Our design presents a fundamental building block for energy-efficient and biologically plausible artificial visual systems.

NATURE OF COGNITIVE EXPERIENCE: UNITY OF PERCEPTION, THINKING, BODY AND LANGUAGE

The article analyzes the nature of cognitive experience in the context of non-classical epistemology and critically interprets the dogmatic concept of cognitive process as a special form of reality reflection. Borrowing his arguments from neurobiology, cognitive science and cross-cultural studies, the author makes the following conclusions: the modular architecture of perceptual systems and embodied cognition impose certain restrictions on the way of presenting perceptual data, determining what stimulus diversity should be reduced to in order for it to be perceived and comprehended. At the same time, perception involves cooperation with other cognitive abilities – attention, memory, and thinking. In this regard, the perception of sensory stimuli depends on the subject’s set of categories, anticipatory schemes, and linguistic frameworks. All these means provide procedures for the selection and categorization of information. As a result, sensory data receive objective meanings, and perception turns out to be irreducible to the passive «copying» of reality.

Knowledge from the Outside

Knowledge may be examined from the third-person perspective, as psychologists and sociologists do, or it may be examined from the first-person perspective, as each of us does when we reflect on what we ought to believe. This chapter takes the third-person perspective. One obvious source of knowledge is perception, and some general features of how our perceptual systems are able to pick up information about the world around us are highlighted. The role of the study of visual illusions in this research is an important focus of the chapter. Our ability to draw out the consequences of things we know by way of inference is another important source of knowledge, and some general features of how inference achieves its successes are discussed. Structural similarities between the ways in which perception works and the ways in which inference works are highlighted.

Newly learned novel cues to location are combined with familiar cues but not always with each other

Mature perceptual systems can learn new arbitrary sensory signals (novel cues) to properties of the environment, but little is known about the extent to which novel cues are integrated into normal perception. In normal perception, multiple uncertain familiar cues are combined, often near-optimally (reliability-weighted averaging), to increase perceptual precision. We trained observers to use abstract novel cues to estimate horizontal locations of hidden objects on a monitor. In Experiment 1, four groups of observers each learned to use a different novel cue. All groups benefitted from a suboptimal but significant gain in precision using novel and familiar cues together after short-term training (3 x ~1.5 hour sessions), extending previous reports of novel-familiar cue combination. In Experiment 2, we tested whether two novel cues may also be combined with each other. One pair of novel cues could be combined to improve precision but the other could not, at least not after three sessions of repeated training. Overall, our results provide extensive evidence that novel cues can be learned and combined with familiar cues to enhance perception, but mixed evidence for whether perceptual and decision-making systems can extend this ability to the combination of multiple novel cues with only short-term training.