Vertebrate brain theory

Monograph of Dr. rer. nat. Andreas Heinrich Malczan

ISBN 978-3-00-064888-5

5.7  The formation of cortical divergence grids in the olfactory cortex

The olfactory system was able to recognise individual scents because scent receptors reacted to certain classes of molecules. However, many odours were mixtures of scentsand they were able to identify their originators more clearly. The recognition of scent mixtures was therefore on the evolutionary agenda. A solution similar to the detection of joint angles should accelerate this development: The need for redundant signal transmission.


Therefore, a process that caused signal redundancy in the olfactory cortex began quite early. The output of the receptors of a receptor class that detected an assigned molecular class was divergently distributed to several cortical projection neurons. This happened because the class 4 neurons received the excitations and divergently passed them on to many more class 3 neurons.

If there were two, three or more types of scent in a fragrance mixture, there were also two, three or more class 4 projection neurons from the olfactory system that projected into the olfactory cortex, each neuron exciting a whole group of related class 3 cortical neurons. Thus, the failure of one cortical neuron had no serious disadvantages. The neighbouring ones took over the signal transmission. However, here too, the incoming olfactory signals were superimposed. Cortical neurons therefore received the excitation of several different scent signals. And as in the olive, distance-dependent attenuation occurred because the excitation was transmitted subliminally. Therefore the signal propagation was exponentially attenuated. This resulted in minima of excitation within the cortical surface between the entry points of the original olfactory excitation. These minima therefore encoded, as in the nucleus olivaris, the signal strength ratio of the different olfactory excitations. This corresponded to a minimum coding of the odour mixtures. Each minimum coded the signal strength ratio of the olfactory components of an olfactory mixture. This minimum coded signal had to be subjected to a further signal inversion in order to achieve maximum coding. And the signal maxima after this inversion could then actively target muscles and start the attack on the prey or activate a necessary escape.

Signaldivergenz im olfaktorischen Cortex

Figure 71- Signal divergence in the olfactory cortex

After the development of signal divergence to ensure redundant signal transmission, the olfactory cortex represented a flat divergence grid with horizontal signal propagation. Relatively few input neurons supplied relatively many output neurons. The excitation spread subliminally via the axon branches, interneurons and dendrite trees. Each cortical input neuron, which received its signals directly from the olfactory receptors, was surrounded by a myriad of interneurons, which ensured the excitation transport to the numerous output neurons. This gave the impression that the associated cortex was made up of cell columns. Similar cell column structures are found in many primary cortex areas, for example as barrel columns of rat whiskers or as eye dominant columns in the primary visual cortex. These cell columns are - according to the author - a classical feature of flat divergence grids or convergence grids with horizontal signal propagation. The output neurons are (mostly) minimum coded, the position of the local minimum encodes the signal strength ratio of the adjacent input neurons.

Theorem of the formation of plane divergence grids in the olfactory cortex

A signal divergence of the olfactory signals developed in the olfactory cortex. The involved interneurons had non-markless axons, therefore a distance dependent and exponential signal attenuation according to the cable equation for non-markless fibers occurred. Thus the olfactory cortex became a flat divergence grating, its output were minimum coded signals of the fragrance mixtures.

Monograph of Dr. rer. nat. Andreas Heinrich Malczan