How to be rational about empirical success in ongoing science: The case of the quantum nose and its critics

More than meets the AI: The possibilities and limits of machine learning in olfaction

Can machine learning crack the code in the nose? Over the past decade, studies tried to solve the relation between chemical structure and sensory quality with Big Data. These studies advanced computational models of the olfactory stimulus, utilizing artificial intelligence to mine for clear correlations between chemistry and psychophysics. Computational perspectives promised to solve the mystery of olfaction with more data and better data processing tools. None of them succeeded, however, and it matters as to why this is the case. This article argues that we should be deeply skeptical about the trend to black-box the sensory system's biology in our theories of perception. Instead, we need to ground both stimulus models and psychophysical data on real causal-mechanistic explanations of the olfactory system. The central question is: Would knowledge of biology lead to a better understanding of the stimulus in odor coding than the one utilized in current machine learning models? That is indeed the case. Recent studies about receptor behavior have revealed that the olfactory system operates by principles not captured in current stimulus-response models. This may require a fundamental revision of computational approaches to olfaction, including its psychological effects. To analyze the different research programs in olfaction, we draw on Lloyd's "Logic of Research Questions," a philosophical framework which assists scientists in explicating the reasoning, conceptual commitments, and problems of a modeling approach in question.

Sensory Perception of Non-Deuterated and Deuterated Organic Compounds

The chemical background of olfactory perception has been subject of intensive research, but no available model can fully explain the sense of smell. There are also inconsistent results on the role of the isotopology of molecules. In experiments with human subjects it was found that the isotope effect is weak with acetone and D6 -acetone. In contrast, clear differences were observed in the perception of octanoic acid and D15 -octanoic acid. Furthermore, a trained sniffer dog was initially able to distinguish between these isotopologues of octanoic acid. In chromatographic measurements, the respective deuterated molecule showed weaker interaction with a non-polar liquid phase. Quantum chemical calculations give evidence that deuterated octanoic acid binds more strongly to a model receptor than non-deuterated. In contrast, the binding of the non-deuterated molecule is stronger with acetone. The isotope effect is calculated in the framework of statistical mechanics. It results from a complicated interplay between various thermostatistical contributions to the non-covalent free binding energies and it turns out to be very molecule-specific. The vibrational terms including non-classical zero-point energies play about the same role as rotational/translational contributions and are larger than bond length effects for the differential isotope perception of odor for which general rules cannot be derived.

Imaging the living brain: An argument for ruthless reductionism from olfactory neurobiology

Should theories of "higher-level" cognitive effects originate in "lower-level" molecular mechanisms? This paper supports reductionist explanations of sensory perception via molecular mechanisms in neurobiology. It shows that molecular and cellular mechanisms must constitute the material foundation to derive better theories and models for neuroscience. In support of "bottom-up theorizing", I explore the recent application of a new real-time molecular imaging technique (SCAPE microscopy) to mixture coding in olfaction. Seemingly emergent "higher-level" psychological effects in odor perception, irreducible to the physical stimulus, are linked back to underlying molecular mechanisms at the receptor level. The SCAPE study has notable theoretical impact. It provides a possible answer to the neurocomputational challenge in olfaction from combinatorial coding at the periphery: how does the brain discriminate different complex mixtures from widespread and overlapping receptor activation? The failure of previous reductionist structure-odor explanations is shown to reside in misconceptualizations of the critical causal elements involved. Causally fundamental features are not of parts independently of a mechanism. Components and their relevant features are units via their causal role within a mechanism. Here, new technologies allow revisiting our understanding of the ontology and levels of organization of a system.

The Value of Failure in Science: The Story of Grandmother Cells in Neuroscience

The annals of science are filled with successes. Only in footnotes do we hear about the failures, the cul-de-sacs, and the forgotten ideas. Failure is how research advances. Yet it hardly features in theoretical perspectives on science. That is a mistake. Failures, whether clear-cut or ambiguous, are heuristically fruitful in their own right. Thinking about failure questions our measures of success, including the conceptual foundations of current practice, that can only be transient in an experimental context. This article advances the heuristics of failure analysis, meaning the explicit treatment of certain ideas or models as failures. The value of failures qua being a failure is illustrated with the example of grandmother cells; the contested idea of a hypothetical neuron that encodes a highly specific but complex stimulus, such as the image of one's grandmother. Repeatedly evoked in popular science and maintained in textbooks, there is sufficient reason to critically review the theoretical and empirical background of this idea.

Molecular Basis of Mammalian Odor Discrimination: A Status Report

Humans have 396 unique, intact olfactory receptors (ORs), G-protein coupled receptors (GPCRs) containing receptor-specific binding sites; other mammals have more. Activation of these transmembrane proteins by an odorant initiates a signaling cascade, evoking an action potential leading to perception of a smell. Because the number of distinguishable odorants vastly exceeds the number of ORs, research has focused on mechanisms of recognition and signaling processes for classes of odorants. In this review, selected recent examples will be presented of "deorphaned" mammalian receptors, where the OR ligands (odorants) as well as key aspects of receptor-odorant interactions were identified using odorant-mediated receptor activation data together with site-directed mutagenesis and molecular modeling. Based on cumulative evidence from OR deorphaning and olfactory receptor neuron activation studies, a receptor-ligand docking model rather than an alternative bond vibration model is suggested to best explain the molecular basis of the exquisitely sensitive odor discrimination in mammals.