Human Pheromones: theory vs models

By: James V. Kohl | Published on: October 8, 2012

Einstein pointed out to Heisenberg in a famous conversation: “It is theory that determines what can be observed.” (See Louisa Gilder’s The Age of Entanglement, p. 87).
My comment: Models determine what can be explained in context.
In my model (below), the prenatal migration of GnRH neurosecretory neurons allow human pheromones to effect GnRH pulsatility, which modulates the concurrent maturation of the neuroendocrine, reproductive, and central nervous systems, thus influencing the development of human reproductive sexual behavior and other behavior.
The obvious complexity of the model and its bottom-up / top-down representations of organization and activation are discussed in the context of an article published in Science Magazine on October 5, 2012 and my comments on the article at the Science Magazine site.
Article abstract: Modeling work in neuroscience can be classified using two different criteria. The first one is the complexity of the model, ranging from simplified conceptual models that are amenable to mathematical analysis to detailed models that require simulations in order to understand their properties. The second criterion is that of direction of workflow, which can be from microscopic to macroscopic scales (bottom-up) or from behavioral target functions to properties of components (top-down). We review the interaction of theory and simulation using examples of top-down and bottom-up studies and point to some current developments in the fields of computational and theoretical neuroscience.
Comment 1:
A bottom-up/top-down reward mechanism: It is becoming clearer that the primary emotional functions of affective processing associated with the gene, cell, tissue, organ, organ-system pathway and with food acquisition are the foundation for secondary-process learning and memory mechanisms, which interface with tertiary-process cognitive-thoughtful functions and behavior (Panksepp, 2011). This is demonstrable in the following bottom-up sequence: (1) food odors and pheromones; (2) GnRH; (3) LH; (4) steroidogenesis and feedback; (5) white matter/gray matter development; (6) hippocampal neurogenesis; (7) learning and memory; and (8) behavior.
Behaviors associated with the neurophysiological rewards of food acquisition and reproduction typically reactivate the sequence that conditions the hormonal responses and behavioral affects that are associated with food odors and pheromones. This relatively simplistic representation of an 8-stage sequence incorporates the gene, cell, tissue, organ, organ-system pathway that links sensory input to behavior. It also allows for consideration of how higher and lower levels of control participate in the regulation of the organism via its affective experiences, which may not involve any cognitive-thoughtful functions (Kohl, Atzmueller, Fink, & Grammer, 2001).
Affective disorders might best be approached using the same pathway. As is the case with honeybees and in other animal models, cognition is not required to decode the neurophysiological activity of primal affective experiences. Instead, these primal affective experiences are directly associated with reciprocal relationships involving food odors and pheromones in all animal species. They are only indirectly, if ever, associated with human cognition.
Comment 2:
In my model of adaptive evolution via ecological, social, neurogenic, and socio-cognitive niche construction: “Olfaction and odor receptors provide a clear evolutionary trail that can be followed from unicellular organisms to insects to humans.”
Linking evolutionary theory via examples of top-down and bottom-up studies in model organisms (e.g., the honeybee) extends current developments in the fields of computational and theoretical neuroscience to their practical applications.
Open access citation reads: Kohl, J.V. (2012) Human pheromones and food odors: epigenetic influences on the socioaffective nature of evolved behaviors. Socioaffective Neuroscience & Psychology, 2: 17338. DOI: 10.3402/snp.v2i0.17338.


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