Recent Findings & New Explanations
It is necessary to examine findings from different laboratories to test whether their experimental results can be interpreted in terms of formation of inter-postsynaptic functional LINKs (IPLs) derived by semblance hypothesis.
A. In physiological conditions/ artificial systems
Synapse-specific representation of the identity of overlapping memory
engrams.
Abdou K, Shehata
M, Choko K, Nishizono H, Matsuo M, Muramatsu SI, Inokuchi K
(2018)
Science. 360(6394):1227-1231.
(Unfortunately, I saw this paper only on the 20th
March 2023. So, posting this explanation very late).
Semblance hypothesis has provided a mechanistic explanation for both memory (inner sensation of features of the item/event whose memory is being retrieved) and motor action reminiscent of arrival of that item/event.
Work by Abdou et al., has two implicit assumptions. One is that engram cells interconnect between memories and secondly, synapse-specific plasticity ensures the identity and storage of individual memories. The findings in this work need mechanistic explanations for both behavioral motor action (withdrawal of foot) and, if possible, for inner sensation of memory of foot shock. Following is an explanation how the findings in this paper can be explained in terms of semblance hypothesis. Alternatively speaking, findings in this paper allow us to look at semblance hypothesis from a new angle.
In fear conditioning experiments, two stimuli are associated. Out of this one (foot shock) generates a motor response (foot withdrawal). The other one has no motor response. The one with motor response is called unconditioned stimulus (US). The one that does not trigger any motor response on its own is called conditioned stimulus (CS). Authors associated between US and CS. After learning when CS arrives, motor action in response to the US (that occurred prior to learning) takes place.
At this juncture, we would like to find an explicit answer to the questions a) where does associative learning stored and how does memories get retrieved, and b) how behavioral motor activity reminiscent of arrival of a stimulus whose memory is being retrieved. We should understand them with such a clarity that we can explain them to an engineer who wants to replicate the mechanism in an engineered system. For this, the issue can be simplified as given in figure 1.
CS arrives through the auditory cortex (AC) & medial geniculate body. Medial
division of the medial geniculate body (MGm or MGN) receive both auditory and
somatosensory inputs (LeDoux et al., 1987;
Bordi and LeDoux, 1994) and project to LA (LeDoux
et al., 1990). Furthermore, it was verified that the US (foot
shock) activates lateral amygdala neurons (
Figure 1. Conditioned stimulus (CS) arrives through neurons of the auditory cortex (ACN). Unconditioned stimulus (US) arrives through neurons of the medical geniculate nucleus (MGN). They synapse with different spines on a lateral amygdala (LA) neuron. All three of the above neurons are referred to as engram neurons. The question is "After associative learning, when the CS alone arrives, how does it trigger motor response (foot withdrawal) as if it is receiving a foot shock?" To answer this, it is necessary to show at least some evidence for an interaction between the spines of LA that synapse with stimuli arriving through both ACN and MGN in the figure.
The first question is, “What is the mechanistic explanation for the firing of lateral amygdala (LA) neuron when US comes after the associative learning between US and CS?” Authors provide and implicit explanation that plasticity changes occur at the spines of LA neuron on which inputs from CS and US synapse. A mechanistic explanation needs to meet 2 requirements. 1) How does arrival of CS alone cause firing of LA neuron reminiscent of arrival of US? 2) How does arrival of CS generate an internal sensation of arrival of US? If a single explanation can provide answers to both these two questions, then there is a good chance that it can be found correct after verification.
At this time, readers can have more questions. First, why can't the inputs from two associatively learned item be shown synapsing to two neighboring spines on one LA neuron as follows (Figure 2)?
Figure 2. Inputs from two associatively learned stimuli arrive and synapse on to two neighboring spines on one LA neuron. Can this explain associative learning mechanism?
Looking at figure 2, we can ask the question, "Can it provide an explanation?" An interpretation of clustered plasticity along with synaptic tagging was explained previously by Govindarajan et al., 2006. The problems with this model are 1) there is no evidence for the formation of an electric cable between two neighboring spines, 2) there are no evidence for the formation of such a cable through the extracellular matrix space, 3) no evidence for the formation of specific tag molecules that can form in physiological timescales of milliseconds to explain function.
So, let us examine the underlying issue more closely by asking the following questions. 1) How does arrival of CS cause firing of LA neuron reminiscent of arrival of US? An engineer will want to see at least the formation of a cable between the spines to which CS (ACN neuron) and US (MGN neuron) synapses. But there is no evidence for an electrical cable between them. Synaptic tagging was put forward as a mechanism (Frey and Morris, 1998). But sufficient number of specific tag molecules that can form and act at physiological timescales are not found. The solution must provide a mechanistic explanation.
2) Since there are no evidence for a long-lasting direct interaction betwen two spines that receive CS and US on an LA neuron, the configuration given Figure 2 is not compatible with the actual mechanism of learning. So, is there an alternative?
3) We can also ask, "How does arrival of CS generate an internal sensation of memory of arrival of US?" An ideal solution for the first question is expected to answer this question as well. Currently, we are not searching for a mechanism that generates inner sensations of memory due to several reasons that we can only assume. But an engineer who wants to replicate the mechanism will need to see a blueprint that explains a mechanism for this.
So, the question is, "How to move forward to provide an explanation for both behavioral motor action reminiscent of memory retrieval and the very process of memory retrieval itself?" Both these are intricately connected parts of a single mechanism. Hence, we need to find such a mechanism that will also allow us to explain how brain can store very large number of associated memories that are associated with firing of neuronal ensembles. Results from the present paper demands that the mechanism should be able to explain how memories are stored apparently using the same neuron in such way that they can be distinguished from each other.
This needs a renewed approach. First, let us see how the dendritic tree is organized. Are the tree branches of a neuron similar to the tree branches of a tree in a forest? Tree branches of a tree in a forest usually don't overlap with each other so that the leaves can get maximum sunlight. But the dendritic arbor of neighboring neurons overlap intensely so that we cannot separate the arbor of one neuron from another one (Figure 3).
Figure 3. Left side: Trees in a forest. The arbors of even closely located trees do not overlap with each other. Basic reason is that more trees beyond a limit cannot grow in forests due to limited sunlight that they can get. Right side: Drawing by Ramon y Cajal taken from "Comparative study of the sensory areas of the human cortex" page 363 showing Golgi-stained cortex of a 1.5-month-old infant. Cajal once referred to them as "impenetrable jungle". Here, we can see overlapping and intermingling of dendritic arbors of neighboring neurons. If we take a picture of the top view of the cortex to get a comparable view (like that of the forest), we won't be able to recognize any single neuronal arbor even if we paint each neuron differently. Note that Golgi staining stains only a small fraction of neurons! So in reality, it is an "impenetrable jungle" (Figure on the left side is taken from Wikipedia). To get a clear picture of the functional importance of overlapping dendritic arbors, we must ask, "Spines of one neuron abut with spines of how many other neurons?"
What does this indicate? This means that there can be some functional significance for this. Also, dendritic branches of neurons from different cortical layers overlap with each other since their apical tuft regions stay attached to the inner surface of the pia mater, which is the covering of the cortex. This happens due to the descent of neurons from the subpial region towards the ventricle during development. I have explained this in figure 1 in a paper (Vadakkan, 2016). The advantage for such an organization is that a spine from one neuron can be present in between spines of a second neuron. Now we can ask, "Is there a possibility for interactions between neuronal processes of different neurons?" Specifically since spines are the projecting parts on the dendrites of a neuron, we can ask, "Is there a possibility for the spines of a neuron to interact with neuronal process of other neurons?" For the occurrence of some physical interaction between the spine of one neuron and one of the neuronal processes of another neuron, it is reasonable to expect some space between the neighboring spines on the dendrite, even though in a 3D space this is not a necessity. So we can ask, "Is the inter-spine distance more than spine diameter?". Yes, it was found that mean inter-spine distance is more than mean spine diameter (Konur et al., 2003).
Remember, US is a stimulus that will evoke foot withdrawal by itself. CS is a stimulus that does not evoke foot withdrawal. So naturally, CS won't synapse to an LA neuron that is connected to lower motor neurons to cause foot withdrawal. Hence, a configuration where inputs from both CS and US synapsing to the same LA neuron may appear to beat the very purpose of conditioned learning. So, for now we must change the configuration/components of all the above figures (Figures 1, 2 & 3) such that the LA neuron that receives input from CS is a different neuron than the LA neuron that receives input from US for demonstration purpose. Once everything become explainable, we will come back and ask this question again. So, for now inputs arriving towards LA neurons should be as in Figure 4. We can also assume that in the background state, LAN1 neuron is being held at a subthreshold activated state that will allow sufficient potentials from MGN neuron (by the foot shock) to fire it. Let us see if this works.
Figure 4. In this configuration, inputs from associatively learned stimuli arrive to two different LA neurons through AC and MG neurons, so that only US stimulus can reult in foot withdrawal before learning. According to this configuration, LA neurons that receive inputs from AC alone will not fire those LA neurons so that there won't be any foot withdrawal.
Now, if the spines of one LA neuron are located in the inter-spine spaces of the other LA neurons, then an inter-neuronal inter-spine interaction called inter-postsynaptic functional LINK (IPL) is formed between spines that belong to two different lateral amygdala (LA) neurons during learning. After learning, when the CS arrives, it can depolarize the spine on the second LA neuron that propagated stimuli from the US before learning and cause foot withdrawal (Figure 5). This can explain how motor action take place reminiscent of the arrival of US even though US does not arrive at that time. Furthermore, reactivation of IPL by CS will depolarize the inter-LINKed spine of LAN1 in the absence of arrival of any stimulus from US. This will generate units of inner sensations (semblance) on the inter-LINKed spine of LAN1. For details, see FAQ section of this site.
Figure 5. Formation of inter-neuronal inter-spine IPL. Here, output from only LAN1 causes foot withdrawal. After learning, arrival of CS to LAN2 results in propagation of depolarization of the spine of LAN2 through the IPL to the spine of LAN1 to which US arrived at the time of learning. This will cause firing of subthreshold activated neuron LAN1 and cause foot withdrawal reminiscent of arrival of US. Also, the reactivation of spine of LAN1 through the IPL will result in inner sensation of arrival of US (even though US does not arrive). For details, see FAQ section. The fact that a) dendritic arbors of neighboring neurons overlap with each other, and b) mean inter-spine distance is more than mean spine diameter (Konur et al., 2003), provide an opportunity for the presence of abutted spines that belong to different LA neurons. If associative learning can remove hydration layer between the outer layer of neuronal cell membranes over their spines, then it can lead to an electrical connection between them. When CS arrives, potentials will propagate through this connection and reach the LA (which is being maintained at a subthreshold level) that can fire and result in a motor action (foot withdrawal) reminiscent of the arrival of US. For the duration of presence of inter-neuronal inter-spine connection, conditioned reflex can be elicited. The same electrical connection is referred to as inter-postsynaptic functional LINK (IPL) by semblance hypothesis. Reactivation of IPL by CS can explain generation of first-person inner sensation of memory of US (please see FAQ section of this website for details). ACN = Auditory cortical neuron. MGN = Medial geniculate neuron. LAN = Lateral amygdala neuron.
Now, one may ask a question, "Are there LA neurons with inputs only from CS (ACNs)?". The answer is "Not necessarily". LA neurons can have inputs from both CS and US. So contrary to what was said in the paragraph before figure 4, how does this work? Two conditions need to be satisfied. Before learning when CS arrives, LA neurons should not fire to generate foot withdrawal. Before learning when US arrives, LA neurons should fire to generate foot withdrawal. So, we can think of a configuration where an LA neuron receives inputs from both CS and US. The inputs from US provide more inputs (potentials) to allow the LA neuron to cross the threshold for firing; whereas inputs from CS provide very minimal inputs that will not allow LA neurons to fire. During learning, IPLs are formed between spines (that receive inputs from CS and US) that belong to different LA neurons. This will lead to the following change after learning - i. e. when CS arrives after learning, the stimuli will propagate through the IPLs formed during learning to generate foot withdrawal. It is reasonable to assume that after learning enough inputs will arrive from CS through several IPLs to one LA neuron that is held at subthreshold activation state to cause its firing and lead to foot withdrawal. So the figure 5 can be modified as figure 6.
Figure 6. Slight modification of figure 5 to indicate that an LA neuron receives inputs from both CS and US. CS alone will not generate sufficient potentials to fire the LA neuron to cause foot withdrawal. But after fear conditioning (associative learning), CS alone will lead to propagation of sufficient potentials through several IPLs to arrive at an LA neuron from the neighboring neurons whose spines have made IPLs with the spines of LA neuron under examination. This will allow the net potential to cross the threshold for firing an action potential. Hence, unlike figure 5, this figure allows all the LA neurons capable of generating action potentials responsible for foot shock. Theoretically, any LA neuron that can cross the threshold for firing and participate in allowing sufficient muscle fibers responsible for foot withdrawal to contract can provide the motor output.
Effect of inducing LTP & LTD
A mechanistic explanation for LTP occlusion experimental results in the paper can be explained in terms of the explanation of LTP based on semblance hypothesis (Vadakkan, 2019). This is as follows. Based on semblance hypothesis, both addition and removal of vesicles at the lateral borders of spines can increase and decrease membrane length respectively at these regions has an important consequence in the formation and reversal of IPLs. AMPA receptor exocytosis takes place at the lateral borders of spine head close to the synapse, a location where IPL formation is expected to take place.
In normal conditions, GluR1subunits of AMPA receptors are located on the spine membrane up to 25 nm away from the synaptic junction (Jacob and Weinberg, 2015). This indicates a high probability that vesicles containing AMPAR subunits get exocytosed at this location and along with providing AMPAR subunits to form functional AMPARs, these vesicles increase spine surface areas at their lateral margins that can favor the formation of different types of IPLs. Studies have shown synaptic addition of GluR1 subunit–containing AMPA receptors during experimental induction of long-term potentiation (LTP) (Hayashi et al., 2000; Passafaro et al., 2001).
Since, removal of membranes from lateral borders of spines is expected to occur during formation of vesicles for endocytosis, any endocytosis of AMPA receptors can reverse the IPLs. It is known that modest depolarization used in inducing long-term depression (LTD) cause AMPAR endocytosis (Lüscher and Malenka, 2012). Furthermore, it is known that modest depolarization by LTD stimulation protocols cause AMPA receptor endocytosis following activation of phosphatases that dephosphorylate AMPA receptors (Lüscher and Malenka, 2012). It was demonstrated that surface AMPARs are removed during induction of both NMDAR-dependent LTD (Beattie et al., 2000; Carroll et al., 2001), and mGluR-LTD (Waung et al., 2008; Park et al., 2008).
Fear conditioning generate large number of IPLs. So, between the stimulating and recording electrodes there are large number of IPLs. Hence, LTD stimulation is expected to reverse some of these IPLs located between the electrodes. Since endocytosis of the AMPAR subunits and reduction in the size of enlarged spines can explain LTP decay (Dong et al., 2015), LTD can be explained in terms of reversal of existing IPLs in the brain tissue formed as a result of fear conditioning.
Effect of inducing autophagy
Effect of tat-beclin in erasing a memory can be explained as follows. Induction of autophagy by peptide tat-beclin leads autophagosome to fuse with endosome-lysosome system and degrades contents of the latter. This will lead to degradation of endosomes including those that contain AMPA receptors (glutamate receptor subtype with fast kinetics). When endosomes are formed and degraded on a continuously, IPLs will reverse back to form independent spines. This will result in failure to induce semblances when the cue stimulus (CS) arrives. Without further specific associative learning, these specific sets of IPLs will not be formed. This can explain how tat-beclin cause long-lasting memory erasure.
Independent storage of two memories in a shared ensemble of neurons
Authors used two types of CS (CS1 & CS2) to associate with one type of US. They have shown that erasing the association between one type of CS and US does not affect the association between second CS and US. Based on the semblance hypothesis, associations between different types of CS and US result in formation of specific IPLs. Autophagy results in memory destabilization and erasure of auditory fear memory associated with AMPAR endocytosis (Shehata et al., 2018). This can also lead to loss of membrane segments for endocytosis from the lateral borders of spines since GluR1subunits of AMPA receptors are located on the spine membrane up to 25 nm away from the synaptic junction (Jacob and Weinberg, 2015). This can lead to reversal of IPL formed with another spine of a second neuron. Reactivation of specific IPLs by a specific CS makes those IPLs vulnerable to reversal by endocytosis using membrane segments from lateral borders of the spines (how this occur in contrast to a resting IPL need to be studied) along with autophagy of the endocytosed vesicles containing AMPA receptor subunits.
Functional connectivity between engram cells (LA neurons). Where is it taking place?
Authors suggest the occurrence of a "functional connectivity" between engram cells. What contributes to these functional connectivity? How does the brain store enormous number of specific memories, retrieved in response to specific cue stimulus, in shared cell assemblies? Explanations of the findings in the paper by Abdou et al., were made based on the views that memories are formed by changes in synaptic plasticity and are stored in specific neuronal ensembles. Semblance hypothesis used inductive reasoning approaches to derive a mechanism that takes place during learning that has the potential for generating both behavioral motor actions and induce first-person inner sensation of memory. Based on this, inter-neuronal inter-spine functional LINKs are formed during learning and are reactivated during memory retrieval providing the functions. This mechanism operate in synchrony with the normal synaptic functions and neuronal firing.
Based on the semblance hypothesis, specific IPLs are formed between spines that belong to specific neurons during a specific learning. Depending on the specific features of a cue stimulus, a set of IPLs get reactivated. Those IPL reactivations that contribute to potentials allowing subthreshold neurons to cross the threshold will fire. These firing cells are called "engram cells". Along with this, IPL reactivations generate inner sensations (semblance) of memory of the associatively learned item. This takes place as a system property of systems where synaptic transmission and propagation of potentials across the IPL contribute vector components to the oscillating extracellular potentials. Note that brain functions only during a narrow range of frequency of oscillating extracellular potentials. Thus, IPLs provide what the authors refer to as "functional connectivity" between assemblies of firing cells. Since large number of different IPL reactivations can independently contribute potentials to neurons that are being held at subthreshold states, it will provide an apparent view that large number of memories are stored using shared cell assemblies.
Explanations provided here constitute a retrodictive evidence in support of the semblance hypothesis.
References:
Beattie EC, Carroll RC, Yu X, Morishita W, Yasuda H, von Zastrow M,
Malenka RC (2000) Regulation of AMPA receptor endocytosis by a signaling
mechanism shared with LTD, Nat. Neurosci. 312 (2000) 1291–1300.
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RJ, Tonegawa S (2006) A clustered plasticity model of long-term memory
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D, Fenstermaker VL, Yuste R (2003) Systematic regulation of spine sizes
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Evidence for long-term potentiation in
phospholipid membranes.
Scott HL, Bolmatov D, Podar PT, Liu Z, Kinnun
JJ, Doughty B, Lydic R, Sacci RL, Collier CP, Katsaras J
(2022 December
13th) Proc
Natl Acad Sci U S A. 119(50):e2212195119.
PubMed
Long-term potentiation (LTP) is an
electrophysiological finding observed in large number of brain regions
where different inputs converge. Large number of correlations were found
between LTP and the ability of animals to store associatively learned
information and retrieve their memories. However, it is necessary to
verify whether LTP can generate cellular changes similar to that occur
in physiological conditions in vivo.
It was shown that the
least path required to induce LTP is the stimulation of postsynaptic
terminals (dendritic spines) (Kullmann et
al. 1992). Later, it was shown
that inhibitors that block postsynaptic membrane fusion attenuate LTP (Lledo
et al., 1998) even though it is not clear where exactly this
fusion takes place. Using a derived mechanism for generating
first-person inner sensations (that provides testable predictions), it
was possible to explain LTP in terms of inter-neuronal inter-spine
membrane interactions that were called inter-postsynaptic functional
LINKs (IPLs). Structure of IPLs varies depending on the inter-membrane
interaction that can range between exclusion of hydration layer between
membranes and membrane hemifusion (Vadakkan,
2019a). The delay for induction of LTP was explained in terms of
time taken for the dendritic spines in a field (containing large number
of synapses at a location between stimulating and recording electrodes)
to expand and start interacting (Vadakkan,
2019a) (video). Testable
predictions for the operational mechanism of IPLs were provided (Vadakkan,
2019b).
Before undertaking any in vivo experiments, it is necessary to obtain evidence to suggest whether inter-spine membrane interactions can cause a long-lasting electrical connection between them. Semblance hypothesis proposed displacement of hydration water, from the extracellular space between spine membranes of different neurons at the location of their convergence, that can progress up to the formation of hemifusion between those spine membranes. Semblance hypothesis also proposed that the area of membrane interaction can act as a passive conductive location between spines that belong to different neurons. Furthermore, this interaction enables input signals arriving from one of the associatively learned stimuli to depolarize the interacting second membrane to generate inner sensation of the second stimulus due to certain specific features at the synapses (explained in Vadakkan, 2013).
A new evidence suggests
that inter-membrane interactions between lipid monolayers can lead to
membrane hemifusion and generates capacitance at those locations where
energy can be stored (Scott et al., 2022).
Slow discharge from this capacitor enables these hemifused locations to
produce a long-lasting potentiated effect similar to that of LTP. The
ability to store charge and its discharge is subsequently match with a
property having time-scales suitable to explain working memory. But
storing and releasing charge can only explain the electrical findings.
More questions remain. "Can such a property be explained between
vesicles whose membranes are lipid bilayers?", “How does such
inter-membrane interaction contribute to inner sensation of memories?”
Semblance hypothesis has provided an explanation how semblances can be
induced at the second inter-LINKed spine as a system property when one
of the associatively learned stimuli arrive at the first inter-LINKed
spine (Vadakkan, 2013, 2019).
The findings in Scott et al’s work show that
inter-membrane interaction has the ability to retain hemifused area for
certain length of time. If such changes can occur in biological system,
it will enable the neuronal cells to take steps to stabilize those
interactive areas for a long period. If two associated stimuli continue
to arrive frequently, then it is better for the neuronal cells to
stabilize the inter-neuronal inter-spine interactive region, if it
provides certain cellular level benefits. While this is the primary aim
as far as the cells are concerned, it leaves the system with a
functional advantage to generate semblances for inner sensations that
will enable the animal to survive, which can be viewed as an
evolutionarily gained feature.
Scott et al’s work
provides an explanation that the hemifusion between lipid monolayers can
remain stable for certain period without causing mixing of the vesicle
contents. It also indicates the possibility that hemifusion between
double membranes can be undertaken in future studies to examine for such
possibilities. How does capacitance development found by Scott et al at
the locations of hemifusion influence the hemifused areas between lipid
bilayers of spines that belong to different neurons? Due to the reason
that mean inter-spine distance is more than mean spine head diameter (Konur
et al., 2003), inter-neuronal inter-spine interaction leading to
IPL formation has been viewed as a candidate mechanism.
Biological systems have
several transmembrane proteins whose extracellular domains can interact
in such a way to exclude hydration layer between membranes to promote
inter-membrane interactions. For example, SNARE (soluble NSF
(N-ethylmaleimide sensitive fusion protein) attachment protein receptor)
proteins are known to provide energy for bringing together membranes
against repulsive charges and overcome energy barrier related to
curvature deformations during hemifusion between abutted membranes (Martens
and McMahon, 2008; Oelkers et al., 2016). They also generate
force to pull together abutted membranes as tightly as possible (Hernandez
et al., 2012). By initiating the fusion process by supplying
energy (Jahn and Scheller, 2006),
SNARE proteins can lead to the formation of characteristic hemifusion
intermediates (Lu et al., 2005; Liu et al.,
2008). These properties of SNARE proteins highlight their
functional significance to form hemifusion intermediates that can
possibly contribute to IPL formation. These intracellular factors can
contribute to a short-lasting inter-spine membrane interaction leading
to the generation of a short-lived IPL.
There are several avenues
for futures studies in lipid chemistry to understand inter-membrane
interactions at locations in the nervous system where extracellular
matrix space is very minimal. Manipulating membrane fusion stages using
SNARE modulators (Khvotchev and Soloviev,
2022) to understand its effects on LTP, associative learning and
memory can lead to further advancements in this area of research.
References
Hernandez JM, Stein A, Behrmann E, Riedel D, Cypionka A, Farsi Z,
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Scott HL, Bolmatov D, Podar PT, Liu Z,
Kinnun JJ, Doughty B, Lydic R, Sacci RL, Collier CP, Katsaras J (2022)
Evidence for long-term potentiation in phospholipid membranes. Proc Natl
Acad Sci U S A. 119(50):e2212195119.
PubMed
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Entorhinal cortex directs learning-related changes in CA1 representations (Grienberger and Magee, November 2nd 2022) Nature. doi: 10.1038/s41586-022-05378-6 PubMed
Rapid synaptic plasticity contributes to a learned conjuctive code of position and choice-related information in the hippocampus (Zhao X, Hsu CL, Spruston N, January 5, 2022) Neuron. 110(1):96-108.e4. PubMed)
It is known that
Entorhinal cortex (EC) input to hippocampus (HP) is via two different
projections. 1) A trisynaptic path from EC layer II (ECII) to CA1
neurons via CA3 neurons and a monosynaptic pathway directly connecting
EC layer III (ECIII) to CA1 neurons (Fig.1).
Figure 1. Figure showing both trisynaptic and monosynaptic pathways between one entorhinal cortical (EC) neurons and one CA1 pyramidal neuron. Trisynaptic path from EC2 neurons connects through granule neurons and neurons of the CA3 layer. Monosynaptic path from EC3 neurons synapse to a CA1 neuron located at stratum lacunosum-moleculare layer at apical tuft region of CA1 neuron. At the very least, it is necessary to explain how inner sensation of memory of location is generated and how it is related to firing of a set of CA1 neurons in the presence of a cue stimulus. Note: Colored circles are neurons.
CA1 pyramidal neurons that
fire somatic action potentials when the animal reaches a specific
location are called place cells (Moser et al.,
2015).
Results from one study has led to the
inference that EC3 to CA1 connections are involved in temporal
association memory (Suh et al, 2010).
Later, it was noticed that ability to associatively learn and memorize a
location in response to a cue stimulus is correlated with increased
firing of CA1 neurons (Zhao et al., 2020)
as if there is an “overrepresentation” of these neurons to place memory.
It was also noticed that firing of CA1 neurons is associated with
long-term dendritic voltage signals initiated by inputs from EC3
sub-domain of EC (Magee and Grienberger, 2020).
Authors attribute this to occurrence of behavioral timescale synaptic
plasticity (BTSP) in the EC3-CA1 synapses. Recent experiments that
showed increased elevation of both EC3 activity and CA1 place field
density in response to a prominent reward-predictive cue stimulus in a
new environment led to the interpretation that EC directs
learning-related changes in CA1 representations (Grienberger
and Magee, 2022).
To provide a
mechanistic explanation for the above findings, it is necessary to
arrive at a mechanism that can provide explanations for the following
questions (Table 1).
1.
How can internal
sensation of a particular memory be explained?
2. How can internal
sensation of a particular memory in response to a cue stimulus
explained?
3. Since memory is associated with internal sensation of a conscious state
how can they both be explained in an interconnected manner?
4. Explain
how the mechanism provides signals for a motor response at the same
time?
5. Explain what learning-mechanism can lead to firing of set of CA1 neurons (place cells) that prompt one to call it as "overrepresentation" of these neurons in place memory?
7. Explain features of the mechanism that qualify it as an evolved
mechanism?
6. How to explain formation of long-duration dendritic voltage signals and
Ca2+ plateau potentials associated with learning changes in a
single trial (Takahashi and Magee,
2009; Grienberger et al., 2014; Bittner et al., 2015)?
8. Is it possible to explain various features exhibited by the system at
different levels of its operation?
Table 1.
Questions that a solution for the nervous system is expected to provide
answers for in an interconnected manner.
Challenges and features of a possible solution
Work by Grienberger and Magee (Grienberger
and Magee, 2022) infers that there are
synaptic plasticity changes at the EC3-CA1 synapses that lead to
dendritic voltage signals in the dendrites of CA1 neurons, which is
associated with/in turn leads to firing of CA1 neurons. Increased firing
of CA1 neurons is being interpreted as “overrepresentation”. A
mechanistic explanation is necessary to explain both “plasticity” and
“overrepresentation” with the type of clarity that will allow its
replication in engineered systems. Above requirements given in Table 1
can be summarized to two questions. What synaptic changes
inferred from
dendritic voltage signals, which are being referred to as synaptic
plasticity changes, can generate first-person inner sensation of memory?
How is the same mechanism linked to sudden firing of previously silent
CA1 neurons that made us to infer that they acquire place field
property?
Ability to retrieve memory
is currently being studied using surrogate markers such as behavioral
motor actions and speech. Instead of examining surrogate markers,
semblance hypothesis searched for a mechanism for first-person inner
sensations directly by asking the question, “At what location and by
what mechanism do the first-person inner sensations get sparked?” Even
though, third person experimenter cannot sense or identify the formation
for first-person properties at this location, reaching a solution point
provides a mechanistic explanation for the most important function of
the nervous system. It can lead to finding methods to treat its
disorders and replicating the mechanism in engineered systems. This
motivated derivation of semblance hypothesis (Vadakkan,
2007, 2013, 2019b). It was based on
the argument that if it becomes possible to formulate a mechanism for
generating inner
sensations that can also explain all features of the system exhibited in
different levels by an interconnectable mechanism, then the formulated
mechanism can be correct. It will then be possible to make testable
predictions that can be verified.
Explanation
Towards achieving this,
first a conditional definition for memory was made (Vadakkan, 2007).
This was followed by examining works that were carried out with an aim
to undertake the gold standard test of replicating the mechanism in
engineered systems, which will eventually lead to the development of
true artificial intelligence (AI). A pioneering work (Minsky,
1980) that viewed memories as hallucinations (internal sensations
of something in its absence) matched with the expectations of search for
a mechanism of first-person inner sensations. This laid a foundational
framework for a testable mechanism. Motivated by this, a search was
carried out in the nervous system to identify a change that can occur
during associative learning and can be used by one of the associatively
learned stimuli to generate hallucinations of second stimulus at the
time of memory retrieval.
In the background state, head region of a dendritic spine (postsynaptic or input terminal) is continuously getting depolarized by quantal release of neurotransmitter molecules, in addition to occasional volleys of release of neurotransmitter molecules when action potentials arrive at its presynaptic terminal. Simultaneous activation of two abutted spines by environmental stimuli is expected to form inter-postsynaptic (inter-spine) functional LINK (IPL) during associative learning (Vadakkan, 2013), which forms the linchpin of derived mechanism. At the time of memory retrieval, reactivation of this IPL by one of the associatively learned stimuli leads to propagation of potentials to the inter-LINKed spine previously activated by the second stimulus whose memory is expected to get retrieved. In the background state of continuous depolarization of spine head by quantal release of neurotransmitter molecules, any sudden lateral activation of inter-LINKed spine (in the absence of arrival of action potentials at its presynaptic terminal) is expected to generate a hallucination that the inter-LINKed spine is receiving a stimulus from the environment through its presynaptic terminal. Qualia of first-person inner sensations of a retrieved memory can be estimated by retrograde extrapolation from the inter-LINKed spine towards identifying all the sensory receptors (see figures 6 and 7 in FAQ section of this website). A unit of semblance (semblion) is equivalent to minimum sensory stimuli capable of stimulating a minimum subset of sensory receptors that will stimulate the inter-LINKed spine. A natural retrograde extrapolation is expected to occur at the time of memory retrieval as a system property of systems where synaptic transmission and propagation of potentials across the IPLs contribute intracellular potentials, whose corresponding changes in the extracellular matrix (ECM) space form vector components of oscillating extracellular potentials taking place within in a narrow range of frequencies. Answers to questions in Table1 are given in Table 2.
1 &
2. How can internal
sensation of a particular memory in response to a cue stimulus
explained?
3. Since memory is associated with internal sensation of a conscious state
how can they both be explained in an interconnected manner?
4. Explain how the mechanism provides signals for a motor response at the same time? (see Fig.7 in FAQ section in this website)
5. Explain what learning-mechanism can lead to firing of set of CA1 neurons (Vadakkan, 2013, 2019a; & Fig.11 of FAQ).
7. Explain features of the mechanism that qualify it as an evolved
mechanism?
6. How to explain formation of long-duration dendritic voltage signals and
Ca2+ plateau potentials associated with learning changes in a
single trial (Takahashi and Magee,
2009; Grienberger et al., 2014; Bittner et al., 2015)?
8. Is it possible to explain various features exhibited by the system at
different levels of its operation?
Table 2. Answers to questions that a solution for the nervous system is expected to provide
answers for in an interconnected manner.
IPL mechanism has provided
interconnected explanations for large number of findings in the system
and has generated several testable predictions (Vadakkan,
2019b).
EC3 inputs to a CA1 neuron
synapse stratum lacunosum-moleculare at the dendritic apical tuft
region, whereas EC axonal terminals synapse with CA3 neurons whose
axonal terminals synapse with dendritic spines of CA1 neurons located in
the more proximal stratum radiatum (Fig.2).
Figure 2. Figure showing how trisynaptic and monosynaptic pathways from entorhinal cortical (EC) neurons and a CA1 pyramidal neuron form islets of inter-LINKed spines in the stratum lacunosum-moleculare and stratum radiatum layers respectively. In this demonstration, only five CA1 neurons with one of their spines participating in the islets of inter-LINKed spines is shown. Also, inter-LINKed spines in one islet are expected to belong to different CA1 pyramidal neurons as indicated by different colors (This can vary. For example, in dendritic excrescences of CA3 neurons). Since dendritic arbor at the apical tuft region where EC3 direct input arrives is relatively bigger, it is reasonable to expect formation of large number of IPLs at this location. This may explain an increased horizontal component contributing to low frequency theta waveforms at this location. Even though semblions from stratum lacunosum-moleculare and stratum radiatum layers appear to be occurring at two different locations, large extracellular waveforms such as theta that connects both these locations (see Fig.1 in Fernández-Ruiz et al., 2017) informs about a mechanism for integrating (binding) semblions from these two locations. Note: Small colored circles are dendritic spines participating in inter-postsynaptic functional LINKs (IPLs). Note: Colored circles are denditic spines (postsynaptic terminals).
Oscillating
extracellular potentials show characteristic waveforms in these two
layers (Fernández-Ruiz et al., 2017)
reflecting the nature of spines that are involved in forming IPLs in
these locations. Both amplitude and frequency of these wave forms can be
explained in terms of vector components contributed by IPLs at these
locations. Low frequency theta waveforms can also be explained as the
net effect of the vector components contributed by IPLs in a larger
area. (see Fig.1 in
https://www.cell.com/neuron/pdfExtended/S0896-6273(17)30101-0 and extracellular recordings:
https://www.nature.com/articles/nn.2894/figures/1).
Large number of interneurons are present in the L-M region (Capogna,
2011) indicates presence of IPLs
between their spines and spines of CA1 neurons modifying the qualia of
internal sensations generated at this location. The net potential
generated at the islet of inter-LINKed spines propagates to the axon
hillock of the CA1 neurons, allowing some of the sub-threshold activated
CA1 neurons to fire somatic action potential.
Firing of EC3
neurons followed by firing of CA1 neurons prompt one to infer
involvement of EC3-CA1 synaptic changes. Inhibition of NMDA receptor
channels at these synapses cause inhibition of both learning and memory
retrieval. The involvement of synapses towards the formation and
reactivation of IPLs can be interpreted as synaptic plasticity changes
involving EC3-CA1 synapses. Since IPL mechanism can explain generation
of inner sensations can occur concurrent with firing of CA1 neurons, it
can be viewed as a better explanation. Large amplitude synaptic inputs
delivered by EC3 axons in apical dendritic tree of CA1 (Megias
et al., 2001; Steward and Scoville, 1976)
can lead to the
formation of IPLs between spines of different CA1 neurons located in the
stratum lacunosum-moleculare layer at apical tuft region of CA1 neuron.
Both increased
probability and duration of plateau
potentials (Takahashi and Magee, 2009; Bittner
et al., 2015) can be explained in terms of propagation of
potentials through islets of inter-LINKed spines formed by large number
of abutted spines stimulated. IPL reactivation provides additional
potentials to sub-threshold activated CA1 neurons allowing them to fire
an action potential.
Using CA1 neurons that fire, hippocampal maps were created to
study their association for spatial memory performance (Dupppret
et al., 2010), which led to the inference that accumulation of
place fields is responsible for spatial learning. A pyramidal neuron
that has thousands of input terminals can fire a somatic action
potential when nearly 140 inputs signals arrive at any combination of
input terminals (Eyal et al., 2018).
Extreme degeneracy of input signals in firing a CA1 neuron makes firing
of a CA1 neuron non-specific with respect to the location from where
potentials arrive. Furthermore, large plateau potential anticipated to
be generated by islet of inter-LINKed spines leads to more
non-specificity of CA1 neuronal firing with respect to the input
signals. Inhibition of CA1 firing by AP5
(antagonize NMDA receptors at the synapses of spines of CA1 neuron) or
inhibitor of plateau firing CAV2-3 channel blocker SNX-482 occur due to
inhibition of neurons. Since synapses are necessary for IPL
mechanism to operate, chemicals that block synaptic functions will stop
cognitive function and CA1 neuronal firing (place cell firing).
Conclusion
Many times,
interpretations of experimental findings are carried out with the
presupposition that a single neuron process information. What prompts
such interpretations? A neuron having thousands of input terminals and
receiving nearly any 140 input signals (less than this during temporal
summation) can fire a somatic action potential (Eyal
et al., 2018). Hence, firing property of a neuron cannot be
viewed as something that process information. But there is an
information processing that must be occurring in the neighborhood of a
neuron. Since there is extreme degeneracy of input signals in firing a
neuron (Vadakkan, 2018), information
processing mechanism is expected to take place in the vicinity of input
terminals. It is necesary to ask basic questions
to obtain a mechanistic explanation. The solution for the
system should be able to explain how first-person property of inner
sensation of a place occur in the nervous system along with remaining
features such as 1) optional concurrent behavioral motor actions, and 2)
firing of CA1 neurons. Interaction between spines of different neurons
separated by narrow extracellular matrix provides a solution for the
system. EC3 inputs synapse with spines of CA1 neuron in the stratum
lacunosum-moleculare layer at the dendritic apical tuft region. Since
spines of adjacent pyramidal neurons overlap with each other,
interaction between these spines is expected to occur to generate inner
sensations. When these interactions contribute to additional potentials
to a subthreshold activated pyramidal neuron, it fires a somatic action
potential, which is being viewed as place cells.
The observation
that CA1 firing is inhibited by inhibitor of plateau firing Cav2.3
Ca2+channel blocker indicates that it is capable of blocking
somewhere along the route from EC3 to CA1. Explanations for different
phenomena indicated presence of IPLs between spines of different CA1
neurons. For example, Cav2.3
Ca2+ channels mediate epileptiform activity such as afterdepolarization,
plateau potentials and exacerbation of low-threshold Ca2+
spikes resulting in seizure initiation and propagation (Wormuth
et al., 2016). It was shown how IPL mechanism can explain seizure
generation (Vadakkan, 2016). Cav2.3
Ca2+ channels in the presynaptic terminals are involved in
LTP (Breustedt et al., 2003).
It was
previously explained how synapses are involved in IPL formation and
reactivation to influence LTP (Vadakkan, 2019a).
Furthermore,
Cav2.3 Ca2+
channels have a highly organized spatial distribution with predominant
expression in the proximal or distal dendrites (Westenbroek
et al., 1995).
The IPL mechanism provided by semblance
hypothesis can explain how “engram neurons” that are
often seen as “representations” of memory and “synaptic plasticity”
changes. Conducting experiments to study interaction between abutted
spines that belong to different neurons by the arrival of two
associatively learned stimuli can be used to verify the presence of
IPLs. GFP-reconstitution method across synaptic partners (GRASP) (Feinberg
et al., 2008; Gordon and Scott, 2009; Fan et al., 2013; Macpherson et
al., 2015; Shearin et al., 2018) was used to study synaptic
connections. Trans-Tango (Talay et al., 2017)
and TRACT (Huang et al., 2017)
were
invented for anterograde trans-synaptic tracing. Retrograde
trans-synaptic tracing was carried out using a method called BAcTrace,
(Cachero
et al., 2020). Recently, retro-Tango
method of retrograde synaptic tracing was developed (Sorkaç
et al., 2022). Since TRACT,
trans-Tango and retro-Tango methods allow neurons to show synaptic
partners, similar approaches can be utilized to develop inter-spine
tracers to study IPL links between spines that belong to different
neurons of one neuronal order. Explanations provided here are expected
to motivate verification of interactions between spines belonging
to different neurons.
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Invariant stimulus decoding using correlated neuronal fluctuations
(Ebrahimi et al., (2022) Nature. May 605(7911):713-721.
Current studies in
neuroscience are carried out by examining neuronal firing as a unitary
property of the nervous system. Patterns of neuronal firing called
neural population codes are used to make correlations with different
brain functions. It is also used to make representations of sensory
perception using animal behavior in response to sensory stimuli. By
analyzing neuronal firing in response to a specific stimulus over
different timescales, it is found that variations of elements (neurons
that fire) occur within each set of neurons that fire (Rumyantsev et
al., 2020; Driscoll et al., 2017; Montijn et al., 2016). A recent study
(Ebrahimi et al., 2022) shows occurrence of a) sensory coding redundancy
near the beginning of perception of a sensory stimulus, and b) shared
co-fluctuations of neuronal firing in different areas of brain.
To decode
behavioral response and to progress from representation to causation, it
is necessary to understand a mechanistic explanation how first-person
property of sensory perception is generated and how it is associated
with firing of different sets of neurons. Since sensory perception
occurs in a conscious mind, it is necessary to examine how first-person
properties occur within the nervous system and how this mechanism is
correlated with the third person observation such as firing of neurons.
Studies have shown that oscillating extracellular potentials need to be
maintained in a narrow range for conscious perception. Oscillating
extracellular potentials is a reflection of ionic changes occurring
across neuronal cellular membranes that in turn reflect the nature of
propagation of potentials across the neuronal processes. Since
oscillations across three-dimensional space of extracellular matrix
(ECM) can only be explained by the occurrence of vector components that
contribute to these oscillations, it is necessary to find mechanisms
that lead to generation of these vector components. Since there are
oscillations of potentials with different amplitudes and frequencies in
space, it is also necessary to explain how and where the vector
components contributing to these oscillations occur. This also provides
an opportunity to hypothesize mechanism/s that can lead towards a
solution for the system that can explain how first-person properties are
formed within the system.
Since inner sensations of memories are
first-person properties, it is possible to ask, “What type of a change
should occur within the system during associative learning that can be
used to generate first-person inner sensations of retrieved memories?”
Once it becomes possible to generate a hypothesis for such a mechanism,
it allows us to test for the occurrence of a change during learning.
With this aim, semblance hypothesis synthesized a general framework of a
mechanism (Vadakkan, 2007).
When attempts are made to generate artificial intelligence by
transferring mechanism of natural intelligence to engineered systems, it
becomes necessary to understand how first-person properties are
generated within the system. Towards this attempt, memories were viewed
as hallucinations (inner sensation of a sensory stimulus in its absence)
and a framework for a mechanism was developed (Minsky,
1980). When semblance hypothesis was
further examined in line with K-lines proposed by Marvin Minsky, it was
possible to derive formation of inter-postsynaptic functional LINK (IPL)
as linchpin change occurring during learning whose reactivation is
expected to generate internal sensation of memory (Vadakkan,
2013). Accordingly, reactivation of
IPLs from a lateral direction by a specific cue stimulus is capable of
generating units of inner sensations. Propagation of potentials through
established IPLs provides one of the vector components to oscillating
extracellular potentials at the locations where postsynaptic terminals
of the same neuronal order interact with each other in their orthogonal
organization with respect to linear orientation of neurons in the
consecutive neuronal orders. Synaptic transmission between
linearly-oriented neurons of different neuronal orders provide the
second vector component perpendicular to that occur through the IPLs.
Many neurons are held at subthreshold
activation states. Background subthreshold activation of a neuron
depends on natural environmental stimuli (for example, gravity), phase
of oscillation of oscillating extracellular potentials and spatial and
temporal summations of potentials. Using propagation of potentials that
contribute vector components, it is possible to explain both generation
of oscillating extracellular potentials and addition of potentials to
several neurons that are held at subthreshold activation levels. In
other words, stimulus under investigation provides additional EPSPs to
different sets of neurons that are being held at subthreshold activation
states and allows them to fire action potentials. This is demonstrated
in Figure 1.
Figure.1.
Sensory coding redundancy explained using an example. When a stimulus
arrives, it will provide sufficient stimulus to several first order
neurons that leads to their firing. Action potential triggered by an
excitatory neuron will lead to synaptic transmission at the synapses on
all its axonal terminals. The EPSP generated at a postsynaptic terminal
gets spatially or temporally summated with the rest of the ESPSs
arriving at the axonal hillock. Depending on whether the net summated
EPSP crosses the threshold for firing, the postsynaptic neuron either
fires or does not fire. This is pictorially depicted by the example of
three neurons A, B and C that receive sub-threshold activations short of
two EPSPs at their baseline resting states. A specific stimulus under
investigation is marked “S1”. It provides EPSPS to all three neurons A,
B and C. EPSPs 2, 3 and 4 reaching neurons A, B and C respectively
arrive from either internal or external stimulus at the same time. If
neuron A receives EPSP 1 and 2 simultaneously, it will lead to its
firing.
If neuron B receives EPSP 1 and 3
simultaneously, it will lead to its firing.
If neuron C receives EPSP 1 and 4
simultaneously, it will lead to its firing. Hence, when EPSP1 arrives,
firing of neurons A, B and C depends on whether they are receiving
additional EPSPs concurrently or temporally so that these neurons fire.
If D is a neuron of the second order of neurons and if it is being held
at subthreshold state short of one EPSP and if it has inputs from
neurons A, B, and C, then firing of either one of the neurons A or B or
C will cause its firing. Hence, a stimulus under examination can cause
firing of sets of A and D or A, B and D or A, B, C and D or B and D or
B, C, and D or C and D, or A, C and D simultaneously.
Second explanation is needed for the
observation of sensory coding redundancy at the start of perception (Ebrahimi
et al., 2022). Redundancy of inputs is
expected to minimize the effect of variations in the sets of neurons
that fire. But the stochastic nature informs that something new is
taking place within the circuitry. This provides a unique opportunity to
examine any proposed hypothesis of brain functions for its explanatory
capabilities. Since any set of nearly 140 input signals arriving through
nearly tens of thousands of input terminals of a pyramidal neuron in the
cortex can fire a neuron (Palmer
et al. 2014; Eyal et al., 2018), there
is presence of extreme degeneracy of input signals in firing a neuron (Vadakkan,
2019). Since many neurons are being
held at subthreshold activation levels in the background state, and
since there is presence of continuously varying internal stimuli
originating from within the system, arrival of different combinations of
input signals can lead to firing of the same neuron. By extension, it I
possible to infer that stimulus from a sensory stimulus under
examination can generate potentials that can reach neurons where they
get summated with potentials from a) input signals generated either
internally or externally, and b) reactivation of IPLs that also
contribute to oscillating extracellular potentials. As the interval
between testing increases, occurrence of different associative learning
events will add more IPLs to the system. In addition, some IPLs will get
reversed back over time. These can lead to changes in the net EPSPs
arriving at the axonal hillocks of neurons that are held at subthreshold
activation states. This can explain variations of neuronal sets that
fire in response to a specific stimulus over different timescales (Rumyantsev
et al., 2020;
Driscoll
et al., 2017;
Montijn et al.,
2016).
Thirdly, it is necessary to explain how
different areas of brain show shared co-fluctuations of neuronal firing.
As explained in the previous paragraph, addition and deletion of IPLs
over time will lead to changes in the sets of neurons that fire. Both
propagation of potentials along projection neurons between different
brain areas, and maintenance of both frequency and amplitude of
waveforms of oscillating extracellular potentials are expected to allow
maintenance of correlated subthreshold states of sets of neurons at two
locations. When a stimulus arrives, this can provide inputs to
subthreshold-activated neurons at those two locations and allow them to
cross thresholds for firing.
Both
correlated fluctuations and visual coding redundancy that are
time-varying throughout stimulus presentation rise within 100ms and peak
around 200ms after sensory stimulus onset (Ebrahimi
et al., 2022).
This time delay matches with the time needed for expansion of several
spines that eventually leads the formation of more IPLs. These
late-forming IPLs have no role in early perception. However, their
physiological utility is in maintaining continuity of perception of a
stimulus. The inference made in the work that some neurons have greater
intrinsic variability in the fidelity of stimulus encoding than others
can be explained by 1) Different combinations of inputs add potentials
that will allow the summated EPSPs to cross the threshold to fire a
neuron, and 2) IPLs are formed in excess such that same semblance can be
generated from different combinations of units of semblance generated at
those IPLs. Inference from all the observations tempted the authors to
speculate for presence of “non-interfering communication channels” in
the neocortex, which can be explained in terms of the IPL mechanism.
Driscoll LN, Pettit, NL, Minderer M, Chettih SN, Harvey CD (2017)
Dynamic reorganization of neuronal activity patterns in parietal cortex.
Cell 170:986-999.
Ebrahimi S, Lecoq J, Rumyantsev O, Tasci T, Zhang Y, Irimia C, Li J,
Ganguli S, Schnitzer MJ (2022) Emergent reliability in sensory cortical
coding and inter-area communication. Nature 605(7911):713-721.
Eyal G, Verhoog MB, Testa-Silva G, Deitcher Y, Benavides-Piccione R,
DeFelipe J, de Kock CPJ, Mansvelder HD, Segev I (2018)
Human cortical pyramidal neurons: From spines to spikes via models.
Front. Cell Neurosci.
12:181.
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Montijn JS, Meijer GT, Lansink CS, Pennartz CM (2016) Population-level
neural codes are robust to single-neuron variability from a
multidimensional coding perspective. Cell Rep. 16:2486-2498.
Palmer LM, Shai AS, Reeve JE, Anderson HL, Paulsen O, Larkum ME (2014)
NMDA spikes enhance action potential generation during sensory input.
Nat. Neurosci. 17(3):383-390
PubMed
Rumyantsev OI, Lecoq JA, Hernandez O, Zhang Y, Savall J, Chrapkiewicz R,
Li J, Zeng H, Ganguli S, Schnitzer MJ (2020) Fundamental bounds on the
fidelity of sensory cortical coding. Nature 580:100-105.
PubMed
Activation of a specific glomerulus by human odour in Aedes mosquitos
Human odor stimulus leads to
activation of a specific glomerulus in Aedes mosquitos. Every
glomerulus receives more than on sensory neuronal input. For example, in
Drosophila melanogaster a single glomerulus that senses CO2
has more than one sensory neuron arriving to that glomerulus (Jones
et al., 2007). Close examination of
the findings in a recent work (Zhao
et al., 2022) shows that more than one
sensory neuron is necessary for a specific sensory perception to occur.
It is known that neurons that express the same complement of
ligand-specific receptors send axons to a single olfactory glomerulus
(Vosshall & Stocker, 2007). Hence, it is generally thought that
glomerulus is an ideal location to study sensory perception (Wang
et al., 2003; Semmelhack & Wang, 2009).
Since more than one sensory neuron (olfactory
neuron) is needed for perception to occur, it is reasonable to assume
about the presence of an interactive change occurring between these
neurons or their immediate output neurons. This matches with the
previous explanation for the generation of first-person property of
perception by the semblance hypothesis (Fig.1;
Vadakkan, 2015).
Based on the semblance hypothesis, units of
internal sensation of perception namely perceptons are generated at the
locations where two sensory inputs converge (Vadakkan,
2015). But the question is how does
the fly recognize human odor for the first time as something beneficial?
Generation of the first-person property of internal sensation concurrent
with motor actions to fly towards humans during first instance is most
likely to occur automatically by virtue of an inherited wiring
mechanism. Hence, the first instance of flight towards a human most
likely occurs as expected from an automaton. This and future events of
flights towards humans can lead to associations between sensory inputs
taste of the blood or filling of stomach or satiety can lead to
formation of IPLs that can generate both internal sensations necessary
for survival concurrent with appropriate motor actions. Hence, during
later times, this becomes a learned behavior.
Figure 1.
Schematic diagram showing the mechanism of olfactory percept formation
within a glomerulus. a) Spread of activity through the neuronal
processes in the absence of odorants. The baseline firing of the
olfactory receptor neurons (ORNs) leads to spread of activity to the
synapses between the ORNs and the projection neurons (PNs). Spread of
activity through the excitatory local neurons (ELNs) from one glomerulus
to other glomeruli results in oscillating activity across different
glomeruli in the antennal lobe. Two postsynaptic terminals each from the
corresponding three different sister PNs whose dendrites are located
within a single glomerulus are shown. Based on the present work,
existing inter-postsynaptic LINKs within each of the different glomeruli
can contribute to horizontal component that can trigger oscillations of
potentials among the glomeruli. The integral of all the non-specific
semblances induced at the inter-postsynaptic LINKs is called C-semblance
that can contribute to the attention of the fly. A and C are the
presynaptic terminals of the ORNs. B and D are the postsynaptic
terminals (dendritic spines) of two different PNs within a glomerulus.
b) Induction of perceptons in the presence of an odorant. Two synapses
between two ORNs and two sister PNs within the glomerulus along with
their interpostsynaptic LINK (IPL) B–D is shown. In the context of
background C-semblance, the stimulus-semblion U-loops form at the
inter-postsynaptic LINK B–D to induce perceptons. Note that the
semblions are shown to overlap closer to the olfactory receptors than
the actual source of the odorant. This enables localization of the odor
close to the olfactory receptors, in contrast to the visual perception.
The entanglement of perceptons provides the conformation for the percept
of a specific smell. Percept of a specific attractive smell formed
within a glomerulus can trigger motor actions to the fly along the
concentration gradient as a response to increasing percepts, the fly can
reach towards the source of food. Note that the oscillating potential
wave form that extend beyond the single glomerulus in the absence of
odorants gets limited to that glomerulus alone due to the spread of
inhibitory activity to the other glomeruli through the inhibitory local
neurons (ILNs) during perception (Figure from
Vadakkan, 2015).
Jones WD, Cayirlioglu P, Kadow IG, Vosshall LB (2007) Two
chemosensory receptors together mediate carbon dioxide detection in
Drosophila. Nature 445(7123):86-90.
Semmelhack JL &
Wang JW (2009) Select Drosophila glomeruli mediate innate olfactory
attraction and aversion. Nature 459:218-223.
Vadakkan KI (2015)
A framework for the first-person internal sensation of visual perception
in mammals and a comparable circuitry for olfactory perception in
Drosophila. Springerplus 4:833.
Vosshall LB. &
Stocker RF (2007) Molecular architecture of smell and taste in.
Drosophila. Annu. Rev. Neurosci. 30:505-533.
Wang JW, Wong AM,
Flores J, Vosshall LB, Axel R (2003) Two-photon calcium imaging reveals
an odor-evoked map of activity in the fly brain. Cell
112:271-282.
Spine enlargement
following associative learning
Dopamine reduce excitatory postsynaptic currents (EPSCs) generated by
paraventricular thalamus (PVT) inputs to NAc, when carried out by whole
cell recording from medium spiny neurons (MSNs) of NAc
(Christoffel et al., 2021). This naturally leads to
the question, “What mechanistic explanation can satisfy the inference
that dopamine filter excitatory inputs to NAc?”
Based on IPL mechanism, formation of IPLs between dendritic spines of
MSNs that synapse with excitatory inputs from PVT neurons and dendritic
spines of MSNs that synapse with inhibitory inputs from ventral
tegmental area (VTA) takes place when dopaminergic inputs from VTA cause
expansion of spines of MSNs that synapse with excitatory inputs
(Vadakkan, 2019). The net effect will provide results equivalent to
filtering of excitatory inputs to NAc by dopamine.
Christoffel DJ, Walsh JJ, Hoerbelt P, Heifets
BD, Llorach P, Lopez RC, Ramakrishnan C, Deisseroth K,
Malenka RC
(2021)
Selective filtering of excitatory inputs to nucleus accumbens by
dopamine and serotonin.
Proc
Natl Acad Sci U S A.118(24):e2106648118.
PubMed
Vadakkan K.I (2019) Internal sensation of pleasure can be explained as a specific conformation of semblance: Inference from electrophysiological findings. Peerj Preprints Article
Drift in the set of neurons in
the primary olfactory cortex that fire in response to an odour
Several studies have observed correlation
between odorants and specific sets of neurons that fire in response to
them. Continuous recording from these neurons show that this correlation
is lost after several weeks (Schoonover et al., 2021). Authors suspected that this instability reflects the
unstructured connectivity of piriform cortex. What property of the
circuitry will cause such a drift? It further leads to more fundamental
questions such as “What is a percept?” “Where is it formed?”
It
was possible to explain a framework of a mechanism of perception based
on the IPL mechanism (Vadakkan, 2011).
During associative learning events, new IPL are formed in the cortices.
Even though olfactory stimuli propagate directly to the hippocampus
without propagating to an intermediate association cortex (Zhou
et al., 2021), outputs from the
hippocampus can generate IPLs in the cortex. Insertion of new neurons in
the pathways (in the granule layer of hippocampus) through which signals
from associatively learned items/events propagate, along with exposure
of the system to new associative learning items/events that share
elements of the previously associated items/events, will lead to
continuous formation of new IPLs in the cortices (Vadakkan,
2010; 2016). This will lead to changes
in the summated potentials arriving to the neurons in the olfactory
cortex. Hence, firing property of neurons in the primary olfactory
cortex during perception of the same stimulus is expected to show
continuous drift.
Based on the semblance
hypothesis, when perception is viewed as first-person internal
sensations, it was possible to find a framework of a mechanism for
perception (Vadakkan, 2015). Accordingly, internal sensation of a
percept is formed by integral of all perceptons, unitary mechanisms of
perception. Large number of redundant perceptons are expected to form.
Hence, the net integral of all perceptons remain almost same, even with
changes in the locations from where perceptons are formed. Furthermore,
extreme degeneracy of attenuating input signals in firing a neuron
(Vadakkan, 2019) indicates that perceptons are generated at the input
level. Correlations with neuronal firing will only be true for those
neurons that are being held at sub-threshold activation state and
receive additional potentials through inter-postsynaptic functional
LINKs (IPLs) at the time of perception. Hence, internal sensation of
perception continues to take place even when the set of neurons that
fires changes over time due to changes in the circuitry.
Schoonover CE, Ohashi SN, Axel R,
Fink AJP
(2021)
Representational drift in primary olfactory cortex.
Nature. 2021 594(7864):541-546.
Zhou G, Olofsson JK, Koubeissi MZ, Menelaou
G, Rosenow J, Schuele SU, Xu P, Voss JL, Lane G,
Zelano C
(2021) Human hippocampal connectivity
is stronger in olfaction than other sensory systems.
Prog Neurobiol. 201:102027.
Vadakkan KI (2011)
A possible mechanism of transfer of memories from the hippocampus to the
cortex.
Med Hypotheses. 77(2):234-43.
A framework for the first-person internal sensation of visual perception
in mammals and a comparable circuitry for olfactory perception in
Drosophila.
Springerplus. 4:833.
PubMed
Vadakkan KI (2016)
The functional role of all postsynaptic potentials examined from a
first-person frame of reference. Rev Neurosci. 27(2):159-84.
Vadakkan KI (2019) Extreme degeneracy of
inputs in firing a neuron leads to loss of information when neuronal
firing is examined.
Peerj Preprints. Article
Pathological features of Alzheimer's disease such as tangles & plaques start appearing in normally aging brains (Was able to explain this recently: Aging as a loss of an adaptation that stabilizes last developmental stage of the nervous system)
Examination of IPLs derived by semblance
hypothesis has led to the inference that the last stage of its development
undergoes an adaptation whereby inter-neuronal inter-spine fusion
is prevented by arresting it at/before the stage of hemifusion
(Vadakkan, 2020). This is based on the following observations. In the
mouse, neuronal precursor cells in the ventricular zone (VZ) undergo
cell division.
While in the VZ,
100% of precursors in G2 and S phases of the cell cycle couple
together and form clusters (Bittman et al., 1997). During this stage,
injection of dye into one cell spread to neighouring cells (Bittman et
al., 1997). This indicates formation of fusion pores between these
cells. This is followed by
death of nearly
70% of these cells and survival of the remaining 30% cells (Blaschke et
al., 1996). The surviving 30% of cells are expected to have acquired an
adaptation most probably during inter-cellular coupling. The adaptation
most likely prevents any future coupling between neurons that may result
in inter-neuronal fusion. This adaptation is suitable for maintaining IPLs
(that generated inner sensations) and prevents any IPL fusion. Aging can be viewed as resulting from gradual loss of this
adaptation. Augmented formation IPL fusion events can lead to
pathological changes such as those observed in neurodegenerative
disorders (Vadakkan, 2019). For example, pathological changes of
neurofibrillary tangles and amyloid plaques can result from
precipitation of proteins & leakages of certain precipitated proteins
through defective fusion pores to the extracellular matrix space in Alzheimer’s disease.
If semblance hypothesis is
correct, then its corollary that these pathological findings should also be
found in normal aging can be verified. Since senile
neurofibrillary tangles and amyloid plaques appear in normally aging brains (Anderson, 1997;
),
this forms sufficient verification. This reinforces the need for testing
the predictions of semblance hypothesis.
Vadakkan KI (2020) A derived mechanism of nervous system functions
explains aging-related neurodegeneration as a gradual loss of an
evolutionary adaptation. Curr Aging Sci 13(2):136–152.
Bittman K, Owens DF, Kriegstein AR, LoTurco JJ (1997) Cell coupling and uncoupling in the ventricular zone of developing neocortex. Journal of Neuroscience 17(18):7037-7044. PubMed
Vadakkan KI (2016) Neurodegenerative disorders share common features of
"loss of function" states of a proposed mechanism of nervous system
functions. Biomed Pharmacother. 83:412-430.
Anderton BH (1997) Changes in the ageing brain in health and disease.
Philos Trans R Soc Lond B Biol Sci. 352(1363):1781-1792.
Heterogeneity of neurons in the cortex
Studies of cortical neurons show significant heterogeneity in transcriptomic analyses (; Tasic et al., 2018; Hodge et al., 2019). In fact, these findings show that there won't be two neurons with same sets of transcripts within them. The above findings naturally raise the question, "What is the functional importance of such a finding?" The actual operational mechanism of the nervous system is expected to provide clues for a suitable explanation. Based on the IPL mechanism, this heterogeneity is necessary for the formation of IPL fusion between spines that belong to different neurons at one stage of development supported by the diffusion of dye injected into on neuron to neighboring neurons (see, Vadakkan, 2020). If neurons are not heterogeneous, then fusion between them will not evoke cellular reactions, which is responsible for cell death of majority of neurons. Most importantly, this IPL fusion is expected to trigger an adaptation in surviving neurons, responsible for restricting IPL fusion to the stage of IPL hemifusion. Thus, neuronal heterogeneity can be viewed as a marker of an adaptation that occurred during that last stages of the developmental of the nervous system. It is most likely that maintaining heterogeneity is essential for maintaining the above adaptation throughout the life-span of the neurons. This prompts to make a testable prediction that, any deficiencies in maintaining this adaptation will trigger IPL fusion between heterogeneous neurons, which can explain aging and other disease associated neurodegeneration.
Tasic et al., (2016) Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat Neurosci. 19(2):335-346. PubMed
Spatial gene-expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons. Neuron. 89(2):351-68. PubMed
Tasic et al., (2018) Shared and distinct transcriptomic cell types
across neocortical areas. Nature 2018 563 (7729):72-78
Hodge et al., (2019) Conserved cell types with divergent features in
human versus mouse cortex. Nature 573 (7772):61-68
Spine depolarization without dendritic depolarization
It was found that in excitatory synapses, large spine depolarization recruit voltage-dependent channels without dendritic depolarization, due to high spine neck resistance (Beaulieu-Laroche and Harnett, 2018). Hence, it leads to the questions, "What is the functional importance of seemingly isolated spine depolarization?" and "Since this is a conserved property, how to provide a mechanistic explanation in terms of brain functions?" Another finding from the same laboratory is that distal human dendrites provide limited excitation to the soma even in the presence of dendritic spikes (Beaulieu-Laroche et al., 2018). The observation that even dendritic spikes have only a limited role in neuronal firing is of huge significance. This again reinforces the need for figuring out the functions achieved by depolarization of spine heads in excitatory cortical neurons. IPL mechanism can explain how depolarization of spines is associated with generation of units of internal sensations independent of neuronal firing. These experimental findings compel us to undertake dedicated experimental verification of the IPL mechanism.
Beaulieu-Laroche L and Harnett MT. 2018. Dendritic spines prevent synaptic voltage clamp. Neuron 97(1): 75–82.e3. PubMed
Beaulieu-Laroche L, Toloza EHS, van der Goes MS, Lafourcade M, Barnagian D, Williams ZM, Eskandar EN, Frosch MP, Cash SS, Harnett MT. 2018. Enhanced dendritic compartmentalization in human cortical neurons. Cell 175(3): 643–651.e14. PubMed
Largest class of neurons in the visual cortex is not reliably responsive
to any of the visual stimuli
In a recent report by de Vries et al.,
(de Vries et al., 2020), the authors examined firing of nearly 60,000 visual cortical
neurons in response to different visual stimuli. They found that while
most classes of these neurons respond to specific subsets of stimuli,
the largest class is not reliably responsive to any of the stimuli. The
latter
finding supports
the observations made by semblance hypothesis during visual perception
(Vadakkan, 2016). Accordingly, the internal sensation of perception
takes place at the inter-LINKed spines and is independent of firing of
their neurons. Moreover, postsynaptic potentials generated by visual
stimuli at these inter-LINKed spines need not necessarily add potentials
to raise the summated potentials to reach the threshold level
for firing those neurons (Vadakkan, 2019). Therefore, as per semblance hypothesis, the
expectation is that a huge set of neurons will not be responsive to any
visual sensory stimuli even when internal sensation of vision takes
place. Report by de Vries et al., (de Vries
et al., 2020) is in agreement with the
expectations of the mechanism of visual perception provided by semblance hypothesis.
Their finding that most
classes of visual cortical neurons respond to specific subsets of
stimuli indicates that the propagation of stimuli to higher cortical
areas is necessary for performing secondary functions such as a) “where”
and “what” associative properties of visual stimuli at higher cortical
areas, and b) associative learning with other sensory stimuli at
different associative cortical areas.
de Vries et al.,
(2020)
A large-scale standardized physiological survey reveals functional
organization of the mouse visual cortex.
Nat Neurosci.
2020 Jan;23(1):138-151. doi: 10.1038/s41593-019-0550-9.
PubMed
Vadakkan KI
(2016)
A framework for the first-person internal sensation of visual perception
in mammals and a comparable circuitry for olfactory perception in
Drosophila.
Springerplus.
2015 Dec 30;4:833. doi: 10.1186/s40064-015-1568-4. eCollection 2015.
PubMed
Artificial firing of a neuron leads to firing of a set of neurons of the same neuronal order
In a recent work
by Chettih and Harvey (Chettih &
Harvey, 2019), authors artificially triggered several
spikes (action potentials) in single neurons in layer 2/3 of mouse
visual cortex V1area. This resulted in spiking activity in a group of
sparsely distributed neighbouring neurons in the same neuronal order and
were correlated in time.
The small population of neurons that were excited were located at
short distance (25–70µm) from the stimulated neuron. The stimulation had no influence beyond 300µm
(for a summary, see News and Views article by Ikuko Smith (Smith,
2019).
The authors
called this lateral spread of activity between neurons
"influence-mapping."
There is one important question. How does
excitation reach at the laterally located neurons in a time-correlated
manner, which is responsible for influence-mapping? This can be
explained by the testable mechanism derived by semblance hypothesis (Fig.1).
It is related to the previous explanation of visual perception as a
first-person property using the derived mechanism of generation of
internal sensation at physiological time-scales (Vadakkan,
2016). The units of internal sensation
of perception are induced at the inter-LINKed spines that belong to
different neurons. When a single neuron is artificially fired, the back
propagating action potentials will reach the dendritic spines. It will
then continue to propagate through the inter-LINKed spines to the
neuronal soma of the inter-LINKed spine’s neuron (Fig. 2). The spines
that inter-LINK can belong to neurons that are separated by up to 300µm,
a distance beyond which the probability of overlapping of dendritic
arbor between neurons diminishes substantially.
Figure 1. Schematic diagram
showing the route of propagation of action potential from the
artificially fired neuron N1 towards the sparsely located neuron N2
within the layer2/3 in visual cortex. This spread taking place through
the inter-LINKed spines Post1 and Post2 can explain what the authors
describe as “influence-mapping.” Note that the inter-postsynaptic
functional LINK (IPL) between Post1 and Post2 was explained as
responsible of induction of internal sensation for perception (Vadakkan,
2015).
Overlapping of the dendritic arbors between the neurons N1 and N2
increases the probability of IPL formation when neurons N1 and N2 are
separated only by a short distance (25–70µm).
b) When a neuron was fired, the majority of
neurons that were tuned to respond to similar features to that neuron
were strongly suppressed than the neurons with a different tuning
regardless of the distance from the stimulated neuron. Inhibition of the
spikes in the neighbouring neurons can be explained by activation of
surrounding inhibitory interneurons. Burst of action potentials in
excitatory neurons can activate somatostatin expressing inhibitory
interneurons (Kwan and Dan
2012).
Similar type of inhibition of surrounding areas is seen in locations
where the internal sensation of perception is expected to occur in the
olfactory glomeruli in Drosophila. When one glomerulus is activated,
inhibitory local interneurons (ILN) inhibit all the remaining glomeruli
(Hong and Wilson, 2015)
enabling the specificity of the percept for that particular smell (Vadakkan,
2015).
Orientation tuning is tested by a source of
light. This will cause activation of a large number of islets of
inter-LINKed spines within one cortical column. But when single neurons
are artificially fired the backpropagation of potentials will reach only
specific sets of inter-LINKed spines. This explains why only neurons
that are located sparsely are fired, correlated in time.
Verification: Based on semblance hypothesis,
the prediction that can be made is the presence of inter-postsynaptic
functional LINKs (IPLs) between spines that belong to the artificially
fired neuron and the sparsely located neurons that were fired in a
time-correlated manner.
Chettih SN, Harvey CD (2019) Single-neuron
perturbations reveal feature-specific competition in V1. Nature doi:
10.1038/s41586-019-0997-6.
PubMed
Smith IT (2019) The influence of a single neuron on its network. Nature. 567(7748):320-321 PubMed
Kwan AC, Dan Y (2012) Dissection of
cortical microcircuits by single-neuron stimulation in vivo. Current
Biology 22, 1459–1467.
PubMed
Vadakkan KI (2015) A framework for the
first-person internal sensation of visual perception in mammals and a
comparable circuitry for olfactory perception in Drosophila.
Springerplus 4:833.
PubMed
Hong EJ, Wilson RI (2015) Simultaneous
encoding of odors by channels with diverse sensitivity to inhibition.
Neuron 85(3):573–589.
PubMed
Memory retrieval occurs at a frequency of oscillating extracellular potentials similar to that was present during learning
A recent study examined the nature of oscillating extracellular
potential both during learning and memory retrieval (Vaz et al.. 2019).
In order to reactivate the same set of IPLs
that formed during learning at the time of memory retrieval, it is
necessary to have almost similar conditions that were present at the
time of learning. Maintaining the same frequency of oscillating
extracellular potentials is a major factor in achieving this. Based on
the semblance hypothesis, the synaptic transmission in one direction and
propagation of potentials in a near-perpendicular direction through the
inter-postsynaptic functional LINK (IPL) contribute vector components to
the oscillating extracellular potentials, which is essential for binding
and integration of units of internal sensations for providing the
sensory qualia of memory. The findings of this study that show that
similar frequency of oscillating extracellular potentials are present
both during learning and memory retrieval support the expectations of
semblance hypothesis.
Vaz AP, Inati SK, Brunel N, Zaghloul KA (2019) Coupled ripple oscillations between the medial temporal lobe and neocortex retrieve human memory. Science. 363:975-978. PubMed
Dendritic calcium spikes that are related to behavior and cognitive function
Similar to the action potentials (axonal spikes or neuronal firing) occurring at the axonal hillock, there are spikes occurring at the dendrites. These are called dendritic spikes. Based on the strength of summated potentials, a rough estimate shows that they constitute synchronous activation of nearly 10 to 50 neighboring glutamatergic synapses triggering a local regenerative potential (Antic et al., 2010). Depending on the channels involved, there are different types of dendritic spikes. Recently, it was found that distal dendrites generate dendritic spikes whose firing rate is nearly five times greater than at the cell body (Moore et al., 2017). Another group of investigators who have previously shown that dendritic spikes are related to behavior and cognitive function recently found that dendritic calcium spikes contribute to surface potentials that are recorded as electroencephalogram (EEG) (Suzuki et al., 2017). Surface EEG recording is generated by current sink that reflects the net potential changes within the extracellular matrix space. This is expected to be contributed by several factors. It is known that the surface positive potentials are generated mainly by synaptic inputs from other cortical and subcortical regions to the pyramidal neurons located between L2/3 to L4 regions (Douglas and Martin, 2004). Recent studies by Suzuki et al., has found that dendritic calcium spikes at the main bifurcation points of the apical dendrites of L5 pyramidal neurons (note that L5 pyramidal neurons are upper motor neurons that direct motor movement of the body) also generate the surface positive potentials (Suzuki et al., 2017).
The last two findings lead to the questions, “How can two different sources of potentials provide similar surface positive potentials?" "Can we provide an interconnected explanation?" Since dendritic spikes are related to both behavior and cognitive functions and since IPL mechanism can explain generation of concurrent internal sensation of memory and behavioral motor action, can IPL mechanism explain the above findings? Since the apical tuft regions of all the pyramidal neurons are anchored to the pial surface, the dendritic arbor of all the pyramidal neurons is overlapped at the recording location of Suzuki et al., (Suzuki et al., 2017). In this context, it is necessary to examine the potential changes occurring at the neuronal processes around the recording electrode. In the context of the IPL mechanism, it is anticipated that the dendritic spines of different neurons have formed a large number of islets of IPLs between them at these locations. By examining the zone from where low-threshold calcium spikes were recorded (Suzuki et al., 2017; Larkum and Zhu, 2002), the following is possible.
Spatially, main bifurcation points of the apical dendrites of L5 pyramidal neurons are also locations where spines of the L2/3 pyramidal neurons receive their input. Based on the IPL mechanism, several of these spines are expected to be inter-LINKed to form large islets. These islets are also expected to be inter-LINKed with spines of L5 pyramidal neurons for initiating or controlling motor actions. The potentials through the IPLs are expected to arrive at the axon hillock of the L5 motor neurons that are kept at a sub-threshold state (see figure 5 in the FAQ section of this website) for the motor action (Fig.2). For a system that operates to generate internal sensations and initiates or controls concurrent motor actions, the islets at appropriate locations are expected to transmit potentials to the axon hillock of the L5 pyramidal neurons that are upper motor neurons. Calcium spikes are generated at the postsynaptic locations within the islet of inter-LINKed spines possibly due to an increased density of these channels at these locations. Since the pyramidal neurons are found to be under the influence of an inhibitory blanket (Karnani et al., 2014), a function of dendritic spikes is to generate sufficient potentials to overcome this inhibition. In other words, there is a provision for increasing the inhibitory blanket around an L5 pyramidal neuron axon hillock as the size of the islets of inter-LINKed spines that are connected to these neurons increases. This will make sure that the L5 neuron fires only at the activation of specific sets of IPLs that generates a specific conformation of semblance for both the internal sensation and concurrent behavioral motor action.
Figure 2. Figure explaining a potential mechanism occurring at the level of the main bifurcation point of an apical dendrite of an L5 pyramidal neuron (based on semblance hypothesis). The circles with different colors represent an islet of inter-LINKed spines (dendritic spines or postsynaptic terminals) that belong to different pyramidal neurons at the level of the main bifurcation point of the apical dendrite of L5 neuron. Note that one of the spines (in violet) belongs to one of the L2/3 pyramidal neurons. Also note that the inter-LINKed spine on the far right end of the islet (in green) belongs to L5 pyramidal neuron. During development, neurons of different cortical neuronal orders descend from the inner pial surface area by anchoring the apical dendritic terminals to the inner pial region. This allows overlapping of the dendritic arbors of neurons from different orders, which leads to abutting of their spines that eventually leads to the formation of inter-LINKs between these spines during learning. The waveform shown at the level of the inter-LINKed spines indicates that the oscillating extracellular potentials recorded have a major contribution from the propagation of potentials through the islets of inter-LINKed spines. Secondary factors can determine different wave forms depending on the locations from where recording is carried out. They include a number of neuronal layers, recurrent collaterals, connections with the projection neurons from other ares of the brain, etc. Figure not to scale (spines in the islet are drawn disproportionately large compared to the size of neurons).
The explanation that synaptic transmission and propagation of potentials through the IPLs provide vector components of oscillating extracellular potentials also becomes suitable. If the arrival of potentials from sensory stimuli evokes dendritic calcium spikes along with the reactivation of specific inter-LINKed spines (and their islets) inducing units of specific internal sensations concurrent with activation of specific sets of motor neurons, it can provide an explanation how dendritic calcium spikes are related to behavior and cognitive function. The findings of Suzuki et al., necessitate examining the role of background EEG wave forms, frequency of which correlates with normal level of consciousness. In this regard, the explanation by the IPL mechanism that the net background semblance induced by reactivation of inter-LINKed spines contributes to the internal sensation of consciousness (Vadakkan, 2010) becomes a suitable mechanism that can be subjected to further studies.
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AL, Vuong C, Mehta MR (2017) Dynamics of cortical dendritic membrane
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Dendritic calcium spikes are clearly detectable at the cortical surface.
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Regenerative spikes at the dendritic arbor - a mechanism for internal sense of a place that reflects binding at the time of learning
Each place field consists
of a unique set of CA1 neurons that fire action potential. At the
dendritic regions, calcium transients inform about a change in
potentials occurring regeneratively either due to back propagating
action potentials (bAP) or by dendritic spikes. Recent studies observed
calcium transients secondary to regenerative dendritic events in place
cells that can predict place field properties (Sheffield and Dombeck,
2015a; Sheffield et al., 2017). These calcium transients have a highly
spatiotemporally variable prevalence throughout the dendritic arbor. In
some cases only a subset of the observed branches displayed detectable
spikes, which indicates that spikes originated at these dendritic
branches. None of the observed branches in many cases displayed
detectable spikes during place field traversals while the soma (and
axon) fired. This means that the bAP did not reach these locations.
The above finding can be
explained by the occurrence of dendritic spike occurs at an islet of
inter-LINKed spines that belong to different CA1 neurons
(Vadakkan, 2013). This has the following advantages.
a) Activation of inter-LINKed spines within an islet of inter-LINKed
spines induces units of internal sensations for a specific place. b) One
dendritic spike at an islet of inter-LINKed spines that belong to
different neurons can explain the firing of different CA1 neurons that
are being maintained in a sub-threshold state at the time of the dendritic
spike. It also supports why a high percentage of place cells are shared
between different places. c) Since potentials degrade as they reach the
axonal hillock, it may require potentials arriving from more than one spike to contribute to the
firing of a CA1 neuron depending on latter’s sub-threshold level. d) The
highly
spatiotemporally variable nature of spike depends on the qualia of
internal sensations that they induce in response to and matching with
the place (which depends on previous associative learning events with
different places).
Sheffield MEJ, Dombeck DA (2015a) Calcium transient prevalence across the dendritic arbour predicts place field properties. Nature. 517(7533):200-204. PubMed
Sheffield MEJ, Adoff MD,
Dombeck DA (2017) Increased Prevalence of Calcium Transients across the
Dendritic Arbor during Place Field Formation. Neuron. 96(2):490-504.e5
PubMed
Vadakkan KI (2013) A supplementary circuit rule-set for neuronal wiring. Frontiers in Human Neuroscience. 7:170 PubMed
Sheffield ME, Dombeck DA (2015b) The binding solution? Nature Neuroscience. 18(8):1060-102 PubMed
B. In pathological conditions
Spread of epileptic activity
Epileptic activity in the hippocampus propagates with or without synaptic transmission at a speed of nearly 0.1m/s (Jefferys, 2014). Experiments showed that the longitudinal propagation of epileptic activity from one end of a neuronal order to its other end in the hippocampus takes place independent of chemical or electrical synaptic transmission (Zhang et al., 2014). Since this spread of epileptic activity occurs at a speed of 0.1 m/s and is not compatible with ionic diffusion or pure axonal conduction (Jefferys 2014; Zhang et al., 2014), it requires an explanation at the cellular and electrophysiological levels. In this regard, rapid chain propagation through the inter-postsynaptic functional LINKs (IPLs) explained by the semblance hypothesis (Vadakkan, 2015) offers a suitable explanation for a mechanism.
Jefferys JG (2014) How does epileptic
activtiy spread? Epilepsy Currents. 14(5): 289-290
PubMed
Zhang M, Ladas TP, Qiu C, Shivacharan RS,
Gonzalez-Reyes LE, Durand DM (2014) Propagation of epileptiform activity
can be independent of synaptic transmission, gap junctions, or diffusion
and is consistent with electrical field transmission. Journal of
Neuroscience. 2014 34(4):1409-1419
PubMed
Vadakkan KI (2016) Rapid chain generation
of interpostsynaptic functional LINKs can trigger seizure generation:
Evidence for potential interconnections from pathology to behavior.
Epilepsy & Behavior. 59:28-41
PubMed
Heterogeneity of clinical and pathological findings in Alzheimer's disease
Alzheimer's disease (and most other neurodegenerative disorders) are
highly heterogeneous in its clinical and pathological features (Lam et
al., 2013;
Tasic et al., (2016) Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat Neurosci. 19(2):335-346. PubMed
Spatial gene-expression gradients underlie prominent heterogeneity of CA1 pyramidal neurons. Neuron. 89(2):351-68. PubMed
Tasic et al., (2018) Shared and distinct transcriptomic cell types
across neocortical areas. Nature 2018 563 (7729):72-78
Hodge et al., (2019) Conserved cell types with divergent features in
human versus mouse cortex. Nature 573 (7772):61-68