Human brain theory

ISBN 978-3-00-068559-0

Monograph of Dr. rer. nat. Andreas Heinrich Malczan

8.  The memory module in the pontocerebellum

The cerebellum emerged very early in evolutionary history and symbolises the beginning of the transition from Bilateria to Chordates. The spinocerebellum even represents the transition from water-dwelling animals to land animals, as it made it possible to stabilise the body by introducing the co-activation of the motor counterparts, which also took into account the effects of gravity.

The development of the cerebellum was described in detail in my monograph "Brain Theory of Vertebrates". Of course, my description there should be seen as a hypothesis, but there is a great deal of evidence in favour of it.

In order to understand the development of the pontocerebellum, we have to go back to the beginnings of the development of the central nervous system of the simple, segmented Bilateria. There was one sensory and one motor centre in each segment on each side of the body. Class 6 average neurons collected the available excitation with their larger dendrite trees and thus obtained average signals for the various average centres.

With the development of neighbour inhibition, the mean value systems of the various segments also competed with each other, and many fell victim to the neuronal competition. What remained, for example, in the seventh floor of the segmented nervous system was the dopaminergic median system of the substantia nigra pars compacta with the subdivision of the VTA as well as the formatio reticularis, which probably extends over several segments.

In the second segment, directly below the thalamus, an average nucleus was able to assert itself, which developed into the subthalamic nucleus. It received the output of the class 6 median neurones from the sensory and motor nuclei of the first floor, which became the cortex.

Its output was used to control the various life support systems. To do this, its signals had to descend and thus reached (among other places) the output nucleus of the primal brain in the seventh floor. This nucleus was the nucleus ruber.

However, the nucleus ruber projected not only descending to the motor neurones of the trunk, but also quite early to the lateral alternating nucleus of this floor (this segment). This nucleus was the nucleus olivaris. The purpose of the projection was initially contralateral inhibition, as the two halves of the body were initially in neuronal competition with each other. This was caused by inhibitory interneurones of the contralateral nucleus ruber, which were excited by the opposite side.

Later, when these inhibitory interneurons had separated to form a new nucleus, the Purkinje nucleus, this caused the contralateral inhibition.

However, its signals eventually reached the reticular formation. This was a mean value nucleus in this floor. The inhibition of the mean value signals by the Purkinje nucleus led to the signal inversion of precisely these signals. The neurones of the formatio reticularis, which received the inhibitory input from the Purkinje nucleus, inverted it and sent it to the nucleus ruber, soon formed their own nucleus. This is how the first cerebellar nucleus was formed. From then on, the Purkinje nucleus can be referred to as the cerebellum, and the cerebellar nucleus is regarded as a subsystem of this cerebellum.

The cerebellum now supplied the opposite side of the body with inverted but excitatory signals. The contralateral inhibition of the motor counterparts was replaced by co-activation, i.e. inverse excitation. This meant that both muscles of a simple joint were tensed, one more, the other less. This meant that any joint angle could be set, even under external load, such as gravity. Only then were the (future) tetrapods able to leave the water and walk on land.

The cerebellum received its complete set of signals from the nucleus ruber - this was the simplest solution. Since some of the signals came from the overlying median nuclei, the median signals from the subthalamic nucleus also reached the ruberous nucleus and from there via the olive nucleus to the cerebellum.

In the course of evolution, signals and neurons tended to organise themselves according to modalities. From a certain stage of development, the neurons of the different layers were also categorised as different modalities and took part in the process of separating the modalities.

As a result, the signals in the olive, the nucleus olivaris, were organised according to the nature of their modalities. The segmental division of the body was retained. This is illustrated in the following diagram.

Illustration 37Original nucleus olivaris with the mean value area of the projection to the future pontocerebellum

In the primordial nucleus olivaris, the neurons of signal class 6, which are assigned to the mean value signals, began to arrange themselves in two stripes. These mean value neurones were greatly outnumbered. The mean value signals of class 6 arose in each neuronal centre of each segment. They were also able to overcome the segment boundaries in the course of evolution. They were able to reach all other segments in both ascending and descending order. Ascending, they also reached the uppermost segment, which later became the cortex, moved to the motor side and descended again. In this way, the cortex also had all these mean value signals.

Descending, these signals reached the nucleus ruber, which, however, also passed them on to the olive. There, these mean value signals ended at switch neurones, which formed a horizontal and rather narrow strip of neurones, as shown in the figure above.

The olivary nucleus was therefore a body model of the signalling receptors; it was segmented like the body. It was also bilaterally symmetrical, with one half representing one half of the body. When the animals' bodies were still worm-shaped, they also looked worm-shaped. And for each half of the body, it also received the mean value signals in each segment, which now came together in a small spatial area, as they were in the minority. This created a small strip of neurones in the olivary nucleus, which received the mean value signals from the different segments.

These neurones projected into the cerebellum and also formed such a strip on the left and right (i.e. for each half of the body). At that time, the nucleus olivaris and the cerebellum were still very similar; both were just as worm-shaped as the body of the animals at that time. The pontocerebellum emerged from the slender stripe of the midline signals. This is my firm conviction. There are many reasons in favour of this.

During the expansion phases of the cerebellum, a mossy fibre projection arose from the olive in addition to the climbing fibre projection. The input of the mossy fibres came from the cortex via the bridge nuclei, where they changed sides. The moss fibre input thus originated from the cortex side, which also fed the climbing fibres. The fact that the cerebellum could now also receive the descending signals from the cortex must be considered a major step forward.

Here, the topology of the cortex was transferred to the pontocerebellum.

The cortex contained the parvocellular subsystem, which consisted of layers 3 and 4 on the sensory side. On the motor side, the parvocellular system consisted of layers 2 and 5. Layer 1 of the cortex was a pure input layer.

The magnocellular system consisted of the midline layer 6, which was represented both sensory and motor.

We analyse the cortical projections to the pontocerebellum. The parvocellular system projects via the bridge nuclei into the pontocerebellum, where the signals supply the granule cells via the mossy fibre system, whose axons cross the Purkinje cells at right angles and contact them directly or via interneurons.

Layer 6 of the sensory and motor cortex projects to the median nucleus of the thalamic floor, i.e. to the subthalamic nucleus. There, large averaging neurons integrate the excitation, with several neighbouring averaging neurons of the cortex projecting into a common averaging neuron of the subthalamic nucleus. In this monograph, we will refer to the cortex area that projects via the cortical average neurons into a common average neuron of the subthalamic nucleus as a cortex cluster. It is assigned exactly one average neuron in the subthalamic nucleus. Its second-level mean value signal reaches the cerebellum via a diversion from the nucleus ruber to the olive and from there as a climbing fibre to the Purkinje cells.

Each Purkinje cell is assigned a climbing fibre that represents the mean signal value of a cortex cluster. The class 3 cortex neurons project via the bridge nuclei and the mossy fibres into a cerebellum area in which - among other things - precisely this Purkinje cell is located. We will refer to this area as the cerebellum cluster.

Furthermore, we agree to refer to the signals of class 3 cortical neurons as elementary signals.

The cortical elementary signals then project into the granule cells of a cerebellum cluster, while their second-level mean signal feeds the climbing fibres of the cerebellum cluster. The first-stage mean value signal is generated in the sixth layer of the cortex by the magnocellular pyramidal cells there. The second mean value signal is generated by the subthalamic nucleus.

The cortical mean value signals gained strength in the course of evolution because the receptive fields became larger and the number of cortex neurones increased almost explosively (in many species). This is particularly true in primates, but especially in humans. Nevertheless, the pontocerebellum began its work in the service of vertebrates much earlier. In many simple animals, the cortex is still quite small, but their cerebellum already forms a prominent structure of considerable size.

As the subthalamic nucleus performed further averaging from the output of neuron class 6, the average firing rate of its output neurons increased more and more in the course of evolution. Thus, each Purkinje cell - if its cortex cluster had active neurons - received a strong averaging excitation. And neurons were almost always active in many head segments, as there were constant environmental signals of an olfactory, visual, vestibular or tactile nature.

Now a long-lasting, stronger signal leads to an overload of the neurones. It was therefore favourable if signal pauses were inserted. These signal pauses were caused by an inhibitory projection from the striatum.

We assume that the average neurons of the subthalamic nucleus also projected into the dopaminergic average nucleus of the seventh floor, because every signal should be considered in average nuclei. Therefore, the substantia nigra pars compacta received these second-level averaging signals. It treated these signals in the same way as all signals. They were switched to dopamine and sent to the striatum, where they terminated at inhibitory striosome neurones and excited them. These striosome neurones were now excited as long as the substantia nigra excited them.

In the course of evolution, an inhibitory back-projection from the striatum to the substantia nigra pars compacta also developed. Naturally, the inhibitory signals needed a certain amount of time to reach the substantia nigra from the striatum. During this time, the striosome signals were able to inhibit the median neurons of the nucleus ruber, so that the associated climbing fibre signals came to a standstill because they were inhibited.

However, when the inhibitory striosome signals finally reached the substantia nigra pars compacta, they were able to inhibit it completely. From this point onwards, the substantia nigra could not send any action potentials to the striosomes. Once those that had already travelled had been used up, the striosomes no longer received any excitatory signals and their neurons fell silent. This removed the inhibition of the nucleus ruber, so that the mean value signals of the nucleus subthalamicus were transmitted from the nucleus ruber to the nucleus olivaris and thus to the Purkinje cells.

However, as the substantia nigra was simultaneously excited by the subthalamic nucleus, it again produced excitatory action potentials, which arrived in the striosomes after a certain period of time and sent inhibitory action potentials in the direction of the substantia nigra and the nucleus ruber. In this way, the signalling permeability of the nucleus ruber was constantly briefly interrupted by the striosomes and then restored. This resulted in the typical oscillation form of the climbing fibre signals in the pontocerebellum: a tetanic oscillation that is constantly interrupted by short pauses. This avoided overloading the neurones involved.

 

 

Illustration 38Periodic inhibition of mean climbing fibre signals by the striatum

This gave the climbing fibre signals in the pontocerebellum the following appearance:

einfache_limbische_Schwingung.png

Illustration 39Climbing fibre signals in the pontocerebellum - basic appearance

A strong mean value signal - always present where strong cortical activity occurred - could cause the process of long-term potentiation (LTP) and long-term depression (LTD) in a Purkinje cell. This process took place when the Purkinje cell received two types of input simultaneously:

·       Cortical input via the parallel fibres.

·       Tetanic (higher frequency) input via the climbing fibres.

This is because a tetanic climbing fibre input caused an increase or decrease in synaptic coupling in a very short time (in the range of seconds) precisely at those synapses that were simultaneously excited by the cortical input. A remodelling process in the synapses caused a permanent change in the coupling strength.

The change in coupling strength was permanently maintained. This was due to remodelling work in the cell itself, the start of which was triggered by the tetanic excitation. In this monograph, we will refer to the permanent change in synaptic strength as imprinting.

If the exact signal that was present during the LTP or LTD process occurred after imprinting, the Purkinje cell reacted with a clear change in its firing rate. With LTP it now fired much more strongly, with LTP much more weakly.

The cerebellum thus became capable of learning.

But how was it possible to control which parallel fibres took part in the LTP and which in the LTD?

To do this, we need to consider the structure of the cortex and pontocerebellum from clusters.

To analyse the topology of the cortex and cerebellum clusters, we assume that the axons of the granule cells already branched in a T-shape and aligned themselves parallel to each other so that they crossed the plane of the dendrite trees of the Purkinje cells at right angles.

To analyse the signal projection from the cortex to the pontocerebellum, we use the cluster model. A cluster (both in the cortex and in the cerebellum) is a simplified square section of the cortex. A cortex cluster contains a large number of class 6 average neurones, which absorb class 5 or 3 signals in the sixth layer of the cortex with its large receptive fields and generate average activity from them. In sensory cortex fields, it is the class 3 neurones that feed the class 6 average neurones. In motor cortex fields - and each gyrus has a sensory and a motor part - it is the class 5 neurones that activate the class 6 average neurones.

A larger number of the average neurons from an equally larger cortex area now send the axons of the class 6 average neurons to a common average neuron of the subthalamic nucleus. This special neuron is our level 2 average neuron.

Now we can define exactly what a cortex cluster is:

A cortex cluster is a cortex area whose class 6 average neurons converge on exactly one neuron of the subthalamic nucleus.

For example, a cortex cluster in the primary visual thalamus could consist of 25 brightness modules with spatial signal propagation. A square consisting of 5 neighbouring modules in width and 5 neighbouring modules in length would then be a cortex cluster.

We assume here (hypothetically) that the output signals of the different visual modules are also treated as different modalities and that their average neurons in the subthalamic nucleus are also split according to modality (light/dark, colour, line elements, ...).

These different modalities have their own connected areas in both the subthalamic nucleus and the pontocerebellum.

We will now look at such cortical clusters and their properties.

Neighbouring clusters are approximately the same size. We can summarise neighbouring clusters in cluster groups.

A cluster group consists of 9 clusters and is also square. The cluster with the number 5 is the inner clusterand the others are called outer clusters. Clusters 1, 3, 7 and 9 are the corner clusters. The direction in which clusters 4, 5 and 6 are arranged is referred to as horizontal; they are arranged in a row.

We call the direction of clusters 2, 5 and 8 vertical; these clusters form a column.

The following figure shows a cluster group, the 9 clusters are numbered as described.

In the cluster group of the cerebellum, the parallel fibres may run from top to bottom if the figure below shows the cortex and cerebellum cortex from above.

 

Illustration 40Cluster group in the cortex

 

We refer to cluster 5 as the inner cluster and the others as outer clusters or peripheral clusters of the cluster group. We can assign a signal to each cluster, so the signal S5 belongs to cluster 5.

Within a cluster, the signalling neurons are distributed at approximately equal distances. These signalling neurons belong to neuron class 3 on the sensory side of the cortex and class 5 on the motor side. We refer to their signals as cortical elementary signals. They project via the bridge nuclei to the pontocerebellum.

As an example, a cluster with 25 output neurones is shown below, arranged in 5 rows of 5 neurones each. The real number of signalling neurons in the cortex is certainly many times higher in higher vertebrates. Here we are only concerned with the organisational principle of the cluster topology.

Illustration 41Structure of a cluster of neurons in the cortex

It becomes clear that a cluster signal, such as S5 , is made up of many elementary signals that can be arranged and indexed in columns and rows. If the output O5,2,4 belongs to cluster 5 in the second row and fourth column and the number 5 represents the number of rows and columns, the signal S5 can be written as a matrix (greatly simplified):

 


s5,1,1

s5,1,2

s5,1,3

s5,1,4

s5,1,5

s5,2,1

s5,2,2

s5,2,3

s5,2,4

s5,2,5

s5,3,1

s5,3,2

s5,3,3

s5,3,4

s5,3,5

s5,4,1

s5,4,2

s5,4,3

s5,4,4

s5,4,5

s5,5,1

s5,5,2

s5,5,3

s5,5,4

s5,5,5

 

 

                     =   S5                             

 

 

Here, s5,k,l represents the elementary signal in the k-th row and the l-th column, which is supplied by the signalling neuron in the k-th row and the l-th column in cluster number 5.

 

We postulate a signal projection of the signal neurons of the cortex clusters via the mossy fibres into the granule cells of the cerebellum clusters and assume that this signal mapping is topologically faithful in the sense that the cluster number is preserved.

A special feature of the pontocerebellum must be mentioned at the beginning. The output of the pontocerebellum is normally zero. This is because the excitation of a neuron of the dentate nucleus by the signal arriving via the climbing fibre is cancelled out by the fact that the Purkinje cell is also excited by exactly the same signal. Both have an equally strong excitation. However, the Purkinje cell uses an inhibitory transmitter, so it inhibits the output neuron in the dentate nucleus. This is why there is normally no output in the pontocerebellum.

A structure without benefits would certainly have been eliminated in the long run. So there must be a benefit. This lies in the fact that the parallel fibres can excite the Purkinje cells directly, but can also inhibit them indirectly via intermediate stellate and basket cells.

This is where the important aspect of the signalling relationship comes into play.

·       The cortex neurones of layers 3 and 5 within a cluster are related in terms of signalling. This signalling relationship arises in two stages.

·       These cortex neurons each supply (usually only) one average neuron in its receptive field.

·       This average neuron supplies exactly one neuron in the subthalamic nucleus together with all the other average neurons in the cluster.

·       Signalling affinity is passed on in neuron chains in both directions.

·       Therefore, the cortex neurons of a cortex cluster are related to each other because there is a common signal receiver in the subthalamic nucleus.

In neuron chains, signalling relationships are passed on in both directions.

If neurons are not signalling-related, they are in neuronal competition with each other. They then inhibit each other.

Parallel fibres that receive input from the edge clusters can therefore inhibit the Purkinje cell in the inner cluster, as they are in neuronal competition with each other. The inhibition takes place via intermediate interneurones, which we refer to as stellate cells and basket cells.

And parallel fibres that receive input from the inner cluster excite the Purkinje cells of the inner cluster.

This can upset the finely balanced equilibrium between the excited dentate neuron and the associated inhibitory Purkinje cell, whereupon there is suddenly an output from the pontocerebellum after all.

By default, however, the Purkinje cell is excited by the cortex signals from its own cluster, so that it still inhibits the output neuron from the dentate nucleus. However, as the dentate neuron also receives the input from the inner cluster, both excitation components cancel each other out and the output is the zero signal.

Only if the signals from the outer clusters arrive simultaneously from the cortex via the parallel fibres do they inhibit the Purkinje cell because they excite the intermediate stellate and basket cells. The excitatory component originating from the inner cluster then remains in the dentate neurone. There is an excitatory output to the cortex.

This is interesting from a mathematical point of view: an output is only generated if internal signals and external signals act simultaneously.

Internal signal + external signal = output signal.

The inside signal does not generate an output, nor can the outside signal alone. Only both together can do this.

This is a signal link via an and relationship. Mathematicians refer to this as a conjunction. This is how complex signals are created. Complex signals are therefore always made up of an excitation component from the inner cluster and an excitation component from the outer clusters.

But the pontocerebellum could do even more: it could also learn these complex signals.

Learning means that the cerebellum, which does not yet recognise a complex signal, reacts to it only weakly or not at all. Once the cerebellum has learnt this complex signal, it fires much more strongly as soon as this complex signal is presented as input.

We will refer to the process of learning a signal in the pontocerebellum as imprinting. This imprinting occurs through LTP and LTD, which permanently and permanently changes the synaptic coupling between the neurones involved.

The following organisational principles form the basis for the coinage:

·       The topology of the cortex clusters and the cerebellum clusters.

·       The neighbour inhibition of signals that are not (sufficiently) related to each other.

·       The tetanic mean excitation of the mean neuron. It occurs in a cortex cluster when a subset of neurons in the cluster is sufficiently active.

·       The process of imprinting (learning) by LTP and LTD using this tetanic mean signal.

·       The process of de-imprinting (forgetting) with the help of a low-frequency climbing fibre signal

This means that the tetanic mean value signal is the save command, comparable to the save command in conventional computers, while the low-frequency mean value signal corresponds to the delete command.

How does signalling affinity come about? It is transmitted in neurons from neuron to neuron. Mean value signals are descendants of cluster signals. There is therefore a signalling relationship between them.

I hypothesise that there seem to be two types of basic rules for neurons:

·       Arouse the one who is not yet aroused (if he can be reached).

·       Inhibit the competition.

This is how the average neurons developed, for example. Any neuron that was active while the average neuron was inactive could dock onto it and now also excite it. Provided that its axon was long enough. In this way, each neuron is signalling-related to its average neuron.

However, if a neuron has an inhibitory transmitter, it can only make synaptic contact with another neuron if both are active at the same time. Therefore, a neuron also inhibits every average neuron in whose signal set its own signal is already present. This is why dopaminergic signals also inhibit the average neurons to which they themselves have contributed. But now on to the pontocerebellum.

How do the four organisational principles influence imprinting in the pontocerebellum?

We assume a more complex form of LTP and LTD in the pontocerebellum, which causes an output neuron of the dentate nucleus to react much more strongly to a certain signalling constellation. We refer to this signalling constellation as an imprinting signal. We refer to the process of LTD and LTP as imprinting.

The imprinting signal originates from a cluster group of the cortex and may consist of two partial signals:

-        The inner signal Si from the inner cluster of a cluster group.

-        The external signal SA from the outer clusters of this cluster group.

The inner signal must not be the zero signal; a sufficient subset of the cortex neurones from the inner cluster must be active. It forms the basis for the average signal value.

The corresponding mean value signal ends at the Purkinje cell of a cerebellum inner cluster and at the corresponding dentate neuron.

The inner signal Si ends at excitatory parallel fibres of the Purkinje cell of the cerebellum inner cluster and at the associated dentate neuron.

The outer signal SA ends at inhibitory stellate and basket cells of the same cerebellum inner cluster. The dentate neurones of the inner cluster cannot be excited by the signals of the outer clusters, as the distance between the neurones is far too great.

If the output neuron of the dentate nucleus is to react more strongly to the complex signal S = Si + SA , the Purkinje cell must be less excited by these signals.

This would require the following:

-        The inner signal is applied to parallel fibres whose synaptic coupling is reduced by the tetanic climbing fibre signal (LTD), for example from a coupling value of 1 to a coupling value of ½. This means that the Purkinje cell is less excited by the inner fibre signal.

-        The external signal is located at the stellate and basket cells, which inhibit the Purkinje cell in the sense of lateral inhibition. The synaptic coupling strength may have the value k. The effect of the tetanic excitation by the climbing fibre signal increases the synaptic coupling between the stellate and basket cells to the Purkinje cell (LTP), e.g. from k to 2k. This means that the Purkinje cell is more strongly inhibited by the external signal. As a result, it will be even less excited.

-        As a result, the associated output neuron in the dentate nucleus is much less inhibited, so that its output is significantly stronger.

-        Since the tetanic climbing fibre signal also terminates at the output neuron of the dentate nucleus, the synaptic coupling between the active mossy fibres of the complex signal and the dentate neurons (LTP) also (probably) becomes stronger, e.g. from 1 to 2, making the output signal even stronger.

-        The synaptic coupling values altered by the tetanic climbing fibre signal remain permanently at the new level, so that an identical mossy fibre signal to the one at the time of imprinting now generates much stronger output signals in the dentate nucleus.

These several effects overlap and cause the excitatory output neuron in the dentate nucleus to react much more strongly to the complex signal than before the imprinting, because this output neuron is more strongly excited and less inhibited.

If the imprinting signal occurs again later, the response is significantly stronger. We refer to the imprinting signal after imprinting as an intrinsic signal of the Purkinje cell on.

Re-imprinting by the mean value signal is not possible with this Purkinje cell. The mossy fibre signals have a significantly shorter transit time via the bridge nuclei than the climbing fibre signal via the subthalamic nucleus, the ruber nucleus and the olivary nucleus. As a result, the Purkinje cell is already inhibited by the mossy fibre input from the outer clusters before the climbing fibre signal arrives. This renders it ineffective, as inhibited neurones represent a kind of short circuit for excitatory signals.

In nature, we observe a tendency to form reserves. In the cerebellum, this is realised by the interconnection of Purkinje cells to form Purkinje groups. A Purkinje group usually consists of up to three Purkinje cells that learn the same imprinting signal. This provides the system with additional security.

A Purkinje group can be recognised by the fact that it ends with a Golgi cell. All Purkinje cells in a Purkinje group project to a common, excitatory output neuron in the dentate nucleus. The function of the Golgi cells will be described later.

Let us summarise:

Imprinting using LTD and LTP turns the imprinting signal of a cortical of a cortical cluster group becomes the intrinsic signal of the Purkinje cells of a Purkinje group of the associated cerebellum cluster. After imprinting, these react to the repeated occurrence of their own signal with significantly reduced inhibition of the excited output neuron in the dentate nucleus, so that its output is significantly stronger in response to the own signal. This allows the pontocerebellum to learn and later recognise exactly one imprinting signal per Purkinje group in each cluster. The recognition output reaches the pontocerebellum.

Each Purkinje group can therefore learn exactly one imprinting signal together with its output neuron in the dentate nucleus and store it as an intrinsic signal by permanently changing the synaptic coupling strengths for this complex signal. for this complex signal are permanently and permanently changed. In this respect, the synapses of the interneurons involved in the cerebellum are the material locations where the signal is stored. takes place.

Initially, there was exactly one Purkinje group per output neuron in the subthalamic nucleus. Two different options were developed so that more than just one complex signal could be learnt for the associated cortex cluster.

The first possibility was that a climbing fibre contacted several Purkinje groups by increasing its length. Along this now significantly longer climbing fibre, several Purkinje groups could be contacted, as well as several associated neurons of the dentate nucleus. We will refer to this solution as sequential divergence.

In the course of evolution, a climbing fibre contacted several Purkinje cells by sequential divergence, their number slowly increasing in the evolutionary series.

This created a new problem that had to be solved. If Purkinje groups are contacted by the same climbing fibre and receive the same cortical signals via the granule cells, then they will all learn the same imprinting signal at the same time. This would be a waste of resources. This is where the Golgi cells come into play.

How can the development of Golgi cells be explained? Whose descendants are they?

Between the signalling neurons of class 6 in the cortex, a lateral inhibition for contrast enhancement of the output has existed since time immemorial. The class 6 mean neurones transferred this cluster competition to the class 5 neurones of the clusters. This neuronal competition between the clusters was taken over by the mossy fibres and passed on to the granule cells. Therefore, granule cells that belonged to a cerebellum cluster inhibited the granule cells of the neighbouring clusters. The interneurons required for this can be interpreted as descendants of the inhibitory interneurons of the cortex, which realised the cluster inhibition.

Golgi cells are descendants of the inhibitory interneurons of the cortical floor, mossy fibre neurons are the descendants of the cortical signalling neurons. Granule cells are descendants of the mossy fibre neurons.

The lateral inhibition between the cortical signals in the mossy fibre system is carried out by inhibitory interneurons, whose descendants in the granule cell system are the Golgi cells.

The granule cell input of a cluster excited the Golgi cells of this cluster, which in turn docked with their axons to the dendrites of the granule cells of the neighbouring clusters and inhibited them if they themselves were excited. This is how the mutual inhibition of the clusters in the pontocerebellum was realised. There was an analogue development in the spinocerebellum and the vestibulocerebellum. In the pontocerebellum, however, this algorithm made it possible to prevent so-called multiple imprinting. This is explained in the following text.

The number of Golgi cells is somewhat smaller than that of Purkinje cells. As an example, we assume that there are three Purkinje cells for every Golgi cell.

Golgi cells are excited by the climbing fibre signal and inhibited by Purkinje cells. This is because the climbing fibre signal is the mean value of the cluster signals, and these excite the Golgi cell.

To put it simply: Golgi cells and Purkinje cells are related in terms of signalling, which is why they make contact.

As an example, we consider a group of three Purkinje cells arranged one behind the other, which are contacted one after the other by the same climbing fibre. The climbing fibre may contact a Golgi cell as the fourth neuron. The further course of the climbing fibre may not be of interest at first.

We assume that the three Purkinje cells are imprinted with an imprinting signal S1 . They may activate exactly one common output neuron in the dentate nucleus due to their identical output. This means that there is only one common output neuron in the dentate nucleus for these three Purkinje cells. There are therefore two reserve Purkinje cells for each imprinted signal; if one fails, the circuit remains functional. Only the failure of all three Purkinje cells leads to the loss of the learnt intrinsic signal.

Purkinje cells of the same Purkinje groups each end with a Golgi cell and are activated by the same climbing fibre. They are imprinted identically. Their output converges on the same dentate neurone. This reports the recognition of the imprinted intrinsic signal to the cortex.

Each Golgi cell is synaptically connected to the climbing fibre, which contacts the Purkinje cells arranged in front of it. During imprinting, this climbing fibre also activates the Golgi cell with its strong climbing fibre signal, which is strongly excited and interrupts the signal flow to the granule cells. As a result, the subsequent Purkinje cells receive less strong parallel fibre signals because an entire population of parallel fibres (the foreign signals) is virtually pinched off. Without the influence of extraneous signals, however, the output of a Purkinje cell is zero.

After imprinting, Purkinje cells recognise the imprinting signal during the oscillation pause of the climbing fibre signals, as it has become their own signal. The inhibitory pathway leads to a strong output signal from the associated neurone in the dentate nucleus.

This is where the inhibitory feedback effect of the dentate nucleus on the olivary nucleus comes into play. Each excitatory output neuron of the dentate nucleus also activates an inhibitory projection neuron with its excitation, the axon of which moves to the olivary nucleus and docks there precisely on the input neuron that generated the formative climbing fibre signal. This greatly weakens the climbing fibre signal so that subsequent Purkinje groups can no longer be imprinted with this complex signal.

The inhibitory back projection of the dentate nucleus to the olivary nucleus serves to prevent multiple imprinting. Without Golgi cells and without this inhibitory feedback, all Purkinje groups of a cerebellum cluster would be imprinted with the same imprinting signal.

The pontocerebellum was now able to learn several different complex signals per cortex cluster using LTD and LTP, because it was possible to prevent multiple imprinting of different Purkinje groups of a climbing fibre with an identical imprinting signal.

Each imprinted Purkinje group reacts to its own signal with significantly less inhibition of the assigned output neuron. As a result, the output neuron reacts much more strongly to this signal. It reports the recognition to the cortex and simultaneously excites a connected inhibitory output neuron, which interrupts the climbing fibre signal in the olivary nucleus. This means that all other Purkinje cells connected to the same climbing fibre lack the tetanic excitation by the climbing fibre signal that is essential for LTD and LTP. No other Purkinje group on this climbing fibre can now be imprinted with the same complex signal. Multiple imprinting is actively prevented.

If a climbing fibre contacted several consecutive Purkinje groups and the Golgi cells located between them during its propagation in the pontocerebellum, as many different complex signals could be learned as there were Purkinje groups.

In the pontocerebellum, the same number of different complex signals can be learnt in each cortex cluster as there are Purkinje groups connected to the climbing fibre derived from this cortex cluster.

As a reminder, the climbing fibre signal was obtained from the mean value signal of the cortex cluster and the striosome signal derived from it and distributed sequentially to the Purkinje groups arranged in a row.

The sequential divergence of climbing fibre signals may have been developed to different degrees in different species. The more different complex signals a vertebrate was able to learn, the more specific and adapted its reactions to complex stimuli became. This gave it an advantage over other species that were not as good at this.

A much greater increase in the number of Purkinje cells occurred due to signalling divergence in the olivary nucleus. One input was distributed there (after a long evolutionary development) to a large number of output neurones of the olivary nucleus.

In the course of evolution, a signalling divergence occurred in the olivary nucleus in which the number of output neurons increased. Each input neuron transmitted its excitation to many neighbouring output neurons. In this way, the number of climbing fibres assigned to one and the same cortex cluster was gradually increased. At the same time, the number of Purkinje cells in the associated cerebellum cluster increased.

Each mean value signal of the subthalamic nucleus, which had previously contacted exactly one Purkinje cell in the associated cerebellum cluster, now split into dozens, hundreds, thousands or tens of thousands of climbing fibres due to signal divergence in the olivary nucleus and contacted an equally large number of Purkinje cells in the associated cluster. This number was further increased by sequential divergence, in which each climbing fibre contacted several Purkinje groups.

If instead of one climbing fibre there was a whole series of climbing fibres running parallel to each other, the same imprinting algorithm took place on each of them. So if the first Purkinje group of the climbing fibre with the number 1 learnt an imprint signal, exactly the same imprint signal was also present on the climbing fibre with the number 100. Therefore, the first Purkinje group on this climbing fibre number 100 learnt exactly this signal. To generalise, one could say that all first Purkinje groups on all climbing fibres to the same input neuron in the olivary nucleus were imprinted in the same way with the first imprinting signal. This means that there was multiple imprinting on a large scale. This would be an enormous waste of resources.

A neuronal competition had to be organised, which only one Purkinje group won.

The basis was laid by the signal attenuation in the olivary nucleus. Those output neurons that were located very close to the input neuron with the cortical mean signal were supplied with more input and had the stronger climbing fibre signal within the cerebellum cluster. A distance-dependent attenuation occurred. They were the first to be imprinted with a complex signal. Their imprinting took place with a time delay. The other Purkinje groups had not yet reached the imprinting threshold. However, several Purkinje groups were still imprinted, even if the imprinting strength was different.

When this complex signal reappeared, these already imprinted Purkinje cells in the olivary nucleus inhibited the input neuron providing the signal. This inhibited its previously tetanic excitation, so that its excitation became low-frequency.

The Purkinje cells that were pre-imprinted with the first signal, but not yet imprinted, then underwent a process of de-imprinting. As a result, the partially learnt signal was forgotten again.

Low-frequency climbing fibre excitation reverses the change in synaptic coupling strength caused by LTP and LTD. This requires a low-frequency climbing fibre excitation (e.g. of 5 Hz) for a duration of around 5 minutes. This has been shown in studies by renowned neurologists.

Thus, a Purkinje group in the cluster that was the first to reach the imprinting threshold was able to reverse the changes caused by LTP and LTD in the others, so that they became unimprinted (free) Purkinje groups again. These were now able to learn the second, third and each subsequent new signal by simply repeating this imprinting process for the new signals.

The low-frequency climbing fibre signal took on the role of an extinction signal. This created neuronal competition between the final Purkinje group and the only partially imprinted Purkinje groups, which freed up the occupied memory space in the partially imprinted Purkinje groups. This enabled the cerebellum to utilise its resources effectively and sparingly.

The output of the dentate nucleus - i.e. the pontocerebellum - moved headwards into the cortex into an association area, where it established a secondary cortex area of first-level complex signals. This cortex area also had median neurones that enabled cluster formation. The cortical projection via the bridge nuclei and the olive established new second-level cortex clusters in the cerebellum, which now received complex signals as input and were able to learn new, higher complex signals. These moved back to the cortex and established association areas of the next higher level. This process was recursive.

The only thing missing now was the possibility of transforming complex signals back into elementary signals so that the original input - which had "disappeared" in the cerebellum - could be restored, as it was needed for the previously assigned tasks. There were several ways to do this.

On the one hand, the axon of the dentate nucleus travelled to a class 4 cortex neuron and was transferred there to a class 3 cortex neuron. Its axon travelled to the motor cortex and contacted all those cortex neurons whose elementary signals were assigned to the complex signal. In this way, the complex signal diverged back to its elementary signals. Whether this possibility is actually utilised is currently still uncertain. The probability that this divergence variant will actually be used is rather unlikely, as signal convergence was the predominant variant on the motor side. Just think of Betz's giant pyramidal cells.

Another possibility is an inverse circuit to the pontocerebellum, which produces the elementary signals again from the complex signals. I searched for this inverse circuit for almost a decade and found it in 2012 in the cerebellum, more precisely in the pontocerebellum. I called this circuit the inverse cerebellum. Since then, I have had to revise my previous findings several times.

Many people will think that I am artificially constructing a complicated system here just to spread my ideas about how the brain works. However, there are three facts that are internationally recognised among neurologists. These three facts are sufficient to prove the existence of an inverted cerebellum. I will simply list these three facts and explain their significance.

Fact 1:

The pontocerebellum projects into secondary cortex areas, which in turn project back into the cerebellum via the bridge nuclei, where the signals reach the granule cells.

Fact 2:

All cortical elementary signals project back into the nucleus ruber. The nucleus ruber in turn (also) projects via the nucleus olivaris into the climbing fibres of the cerebellum.

Fact 3:

There is only one wiring principle in the cerebellum.

 

If one recognises that the mossy fibre projection and the climbing fibre projection into the pontocerebellum follow exactly one principle, i.e. that there are not two or even more differently functioning pontocerebellum areas, then one has already accepted the existence of the inverse pontocerebellum.

How can the work of the inverted pontocerebellum be explained?

The secondary cortex receives the complex signals from the pontocerebellum and sends them to the inverted cerebellum via the mossy fibre projection. These complex signals are the granule cell input in the inverted cerebellum.

The primary cortex sends its elementary signals to the nucleus ruber. This sends them to the olive. From the olive, these elementary signals reach the pontocerebellum as climbing fibre signals in the sections in which the mossy fibre signals of the complex signals form a separate cerebellum cluster. We assign this cluster to the inverse pontocerebellum.

This means that the elementary signals and the complex signals have reversed their roles. Whereas in the (non-inverted) pontocerebellum the mossy fibre signals represent the output of the cortical elementary signals, in the inverted pontocerebellum the climbing fibres are assigned to the cortical elementary signals.

Whenever an ensemble of elementary signals that have already been assigned to a complex signal in the pontocerebellum is active, as many climbing fibres are active in the inverted pontocerebellum as there are associated elementary signals. This is because every elementary signal that belongs to the complex signal is active and projects into the inverted cerebellum via the nucleus ruber and the olive. The activity of the climbing fibres sooner or later causes an imprint through LTP and LTD, in which the active complex signal excites precisely those Purkinje cells that represent the elementary signals of this complex signal.

As soon as the complex signal is then activated, the Purkinje cells that represent its elementary signals are automatically activated in the inverted cerebellum. Their output reaches the thalamus and docks precisely onto the neurones that are assigned to this complex signal. The thalamus projects these signals back to the cortex.

Once a complex signal has been recognised, it activates all the elementary signals assigned to it in the thalamus and the cortex. These activate the associated complex neuron in the pontocerebellum, i.e. the Purkinje cell of this complex signal. Its output in turn activates all the associated elementary signals in the inverted cerebellum. This results in a signal rotation that keeps this signal in consciousness.

Of course, this signalling rotation does not last forever. As in the limbic system, it becomes weaker as the firing rate decreases over time. And it is ultimately interrupted by lateral inhibition. As soon as other, sufficiently strong signals reach the thalamus in the area where the signal rotation is currently taking place, these will activate inhibitory interneurons that weaken or even interrupt the signal oscillation.

During signal oscillation between the cortex, cerebellum, inverse cerebellum and the cortex, the signal form is constantly changing. We distinguish between two signal forms: the elementary form and the complex form.

In the elementary form, the class 3 or 5 signalling neurons of the cortex are active and project into the pontocerebellum. The associated complex neuron - a Purkinje cell or the Purkinje cells of a Purkinje group - recognise this complex signal and respond with an output. This output is in the complex form. It reaches the secondary cortex area and projects from there into the mossy fibres of the inverted cerebellum, while the elementary signals project into the climbing fibre system of this area. The mossy fibres excite these Purkinje cells, whose output is again precisely the elementary signals. This completes the change from the complex form to the elementary form and the oscillation starts all over again.

This signalling oscillation is actually observed in the human brain.

What benefits does it bring for people?

One benefit is the longer service life of a complex signal. It is temporarily stored in the rotation loops, so to speak. Some thoughts simply cannot be suppressed.

A much greater benefit lies in the fact that the brain can now automatically complete incomplete signals.

We all know crossword puzzles. The aim is to find letters for which there are certain clues. Over time, more and more letters fill the rows and columns of the puzzle, but there are still many gaps in the letters, especially at the beginning. Humans are able to recognise the missing letters in words with gaps.

How does it work?

If a complete word is stored in the pontocerebellum in a Purkinje group, while the individual letters - each separately - on a mossy fibre excite the Purkinje cells of an associated "speech recognition cluster" in the pontocerebellum, then for the word "bicycle", which is incomplete in the form of "F hr ad", each Purkinje cell is activated, which taps into the mossy fibres of the partial letters f,h,r,a and d and is activated by them. The Purkinje cell assigned to the word bicycle will recognise the word. However, its output is weaker than if the complete word were present. Each missing letter reduces the output of the responsible dentate neurone.

If there are many words with the partial letters f, h, r, a and d, there are several solutions. In this case, several Purkinje cells are active at the same time and report several solutions to the cortex. Depending on the match, with varying strength. In our case, however, there are hardly any words other than the word bicycle. The solution is clear.

The cerebellum system can therefore complete incomplete signals.

We recognise a horse, even if we can't see it completely. The question "Who eats oats?" is enough to name the horse. But we can also recognise other animals that eat oats. And in a very abstract way, we could even assume that a combine harvester eats oats because they disappear into it. Partial information is often enough to recognise the missing information.

If incomplete signals are interpreted as questions, the cerebellum system provides the answer. The answer emerges from the subconscious: "A horse eats oats." And now this subconscious has a name and a material representation in the brain. It is the pontocerebellum that provides the answer. More precisely, the inverted cerebellum, which completes the signal.

If one considers that the secondary cortex areas that receive the complex signals from the cerebellum are also only ordinary cortex areas, one can predict the further development. The complex signals activate cortex neurones, which in turn can be interpreted as elementary signals. This is because an elementary signal is present if it is represented by the activity of a single cortex neuron. Thus, the complex signals of the first level are practically elementary signals of the second level. They project again via bridge nuclei and the mossy fibres into the granule cells of a new cluster in the pontocerebellum. This could also be described as a second-level cluster.

Similarly, in this secondary cortex area, class 6 average neurones form the average signals, which in turn converge on neurones in the subthalamic nucleus. They reach the olive and the pontocerebellum via the nucleus ruber. This is how the cerebellum cluster of stage 2 receives its climbing fibre projection. The learning process - the imprinting of new second-stage complex signals - can begin.

This process is recursive. Complex signals of level k become elementary signals of level k+1 in a new cortex area of level k. These cause the formation of new complex signals of level k+1 in the pontocerebellum. This continues until the number of granule cells, Golgi cells, stellate and basket cells and, above all, Purkinje cells involved is exhausted.

And in each of these stages, an associated inverse cerebellum is created in the pontocerebellum, which is able to transform the new complex signals from the complex form back into the elementary form. In each level, a signal rotation takes place in which the signal form constantly oscillates between the complex form and the elementary form of the respective signal.

This process takes on a life of its own here.

At the lower levels - for example in the primary cortex - the elementary signals from the inverted cerebellum arrive in the thalamus and are usually suppressed by the current incoming signals through inhibition. This is also due to the close proximity of these signals.

This is no longer the case for complex signals at higher levels. As they involve significantly more elementary neurones, which are therefore also distributed over a larger area in the thalamus, they have greater distances between them. This reduces neighbour inhibition. If even different modalities are coupled with each other in the complex signal, lateral inhibition is impossible. At a certain level, the distance between the elementary neurons is so great that there is effectively no lateral neighbour inhibition. The signal rotation is then no longer interrupted. In practice, the necessary interruption of the signalling rotation then takes place via the inhibition of the thalamus, which is controlled by the circadian rhythm of the suprachiasmatic nucleus and takes place during sleep.

We are constantly aware of these rotating complex signals. And they are simultaneously present in elementary form, so that we instinctively know what the horse that eats the oats looks like. And we know what it smells like, how it walks, gallops and neighs. It's not just the abstract concept of "horse" that rotates in our heads, but also - at a deeper level - all the characteristics we are familiar with. This is obviously a characteristic of our consciousness.

This shows the great weakness of the Human Brain Project. People who have never seen or heard of a horse will not have the synaptic connections of the complex signal "horse" in the pontocerebellum and inverse pontocerebellum, in the thalamus and cortex. However, it is precisely these synaptic connections that those who know horses have.

But while one person thinks that a horse ploughs the farmer's field, another thinks that horses are mammals, while a third thinks of horses only in terms of riding. The synaptic connections of these people to the subject of horses are therefore completely different. In particular, the areas of association in the brains of different people differ in the specific type of synaptic connections. The synaptic connections in the higher association areas of the cortex, in the clusters of the pontocerebellum, in the matrix of the basal ganglia, in the rotational loops of the limbic system and in many other substructures that still need to be recognised are just as different as their cultural background, their level of education, their interests, their native languages and the knowledge they translate into complex signals.

Only the primary cortex areas, which contain visual divergence modules for colour vision, directional vision, etc., are structured in the same way. However, even here there are differences in the thickness of the layers, the number of input neurons and output neurons as well as in the specific structure of the inverse modules. Therefore, the virtual replica of a brain with all its synapses is only ever a replica of a specific human brain, which is personalised. Whether the huge amount of work involved is worthwhile and transferable to other brains is a matter for critical scrutiny.

The approach described here is much more promising. It can explain how thoughts, feelings, ideas and consciousness can arise in the brain.

I already formulated this realisation in my first monograph.

Theorem about the emergence of consciousness in the brain

 

With the increasing number of signals in the recursively structured system from the cerebellum clusters of the direct and inverse pontocerebellum, the inhibition strength in the receptive neighbouring inhibition of the thalamus decreases with increasing number of recursion levels.

This allows the output of the inverse systems to take on a life of its own and create an inner, multimodal and time-varying image of the world in superposition and feedback with the current and previous, temporarily stored input, which can be described as consciousness.

 

Three signalling stages occur in the brain, which form three subsystems. Each subsystem consists of an ascending projecting module and a descending projecting module, which works inversely to the ascending module. At the lowest level, the signals are available in analogue form. A firing rate is assigned to each analogue signal when it is active. We refer to this stage as the primary subsystem.

In the secondary system, the signals are present in extreme value-encoded form. A neuron population of active neurons is characterised by a local excitation maximum, which encodes the parameters.

In the third, tertiary system, all signals are present in the complex form. This is explained in more detail in the last chapter.

For fans of neuronal networks, it should be briefly noted here that a cluster in the pontocerebellum is a simplified associative matrix. The horizontal rows correspond to the mossy fibres, the vertical rows to the Purkinje cells. The crossing points represent the synapses. The output of the cluster feeds a second associative matrix, in which the input and output are swapped: The output signals of the first associative matrix feed the horizontal rows of the second associative matrix, while the vertical columns of the second associative matrix receive their input from the horizontal rows.

This represents a feedback loop in which each signal recognised in the first matrix is used as input for the second matrix and is broken down into its original elementary signals again. In this way, signal rotation also takes place.

In this simplified model, the only thing missing is the integration of the climbing fibre signals in such a way that the lengthy process of "imprinting", which is common in neural networks, is accelerated by means of mean value-controlled write impulses. A target function to control the imprinting process is then completely superfluous.

 

Monografie von Dr. rer. nat. Andreas Heinrich Malczan