Semblance Hypothesis

After more than a decade of examination by adhering to best available scientific methods1-6, mounting evidence forces me to regard semblance hypothesis as a theory. Despite several open invitations to disprove the hypothesis through both this website and a large number of scientific presentations and peer-reviewed publications, no objections were received. This is a theory of nervous system functions that provides testable predictions (pdf with methods to test them). I sincerely hope that scientific community will use the time-tested method of "testing the predictions of a theory"7 with an aim to disprove it. Please explain the importance of this to your community leaders and policy makers. I thank all those who have supported me during several difficult times of its development - Kunjumon Vadakkan, dated 21st March, 2020

References

                  1. Strobel N. Method for finding scientific truth. Website

                  2. Strobel N. What is a scientific theory? Website

                  3. Goodstein D (2007) A testable prediction. Nature Phys. 3:827 Article

                  4. Lee AS, Briggs RO, Dennis AR (2014) Crafting theory to satisfy the requirements of explanation. Article

                  5. Lee AS, Hovorka DS. (2015) Crafting theory to satisfy the requirements of interpretation. Article

                  6. Dutailly JC (2017) Chapter 1. What is science? Theoretical Physics. p1-24.

                  7. Bialek W (2018) Perspectives on theory at the interphase of physics and biology. Rep. Prog Phys. 81(1):0126001 Article

               

Recent Findings & New Explanations

Until now, there were no studies that examined the formation of IPLs. It is necessary to examine findings from different laboratories to examine whether they can be explained in terms of the present work.

A. In physiological conditions

Entorhinal cortex directs learning-related changes in CA1 representations (Grienberger and Magee, 2022) Nature. November, doi: 10.1038/s41586-022-05378-6

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).

                                                           ECII & ECIII to CA1

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.

CA1 pyramidal neurons that fire somatic action potentials when the animal reaches a specific location are called place cells (Moser et al., 2015). One study has led to the interference 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 associated 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 cell firing or place field)?

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)?

7.        Explain features of the mechanism that qualify it as an evolved mechanism?

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 sparks first-person inner sensations?” 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 led to derivation of semblance hypothesis (Vadakkan, 2007, 2013, 2019). It was based on the argument that if it becomes possible to formulate a mechanism for generating internal 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 be then possible to make testable predictions that can be verified.

Explanation

Towards achieving this, first a conditional definition for memory was made (Vadakkan, 2017). 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 (Fig.2). This mechanism has provided interconnected explanations for large number of findings in the system and has generated several testable predictions (Vadakkan, 2019).

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).

                                                                ECII & ECIII to CA1 IPLs

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. 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.

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.

Place cells are CA1 pyramidal neurons that fire a somatic action potential (somatic spike). 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 is 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

Moving away from making presupposition that a single neuron process information, basic questions were asked 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, 2019). 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 is able to 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 provide motivation to verify interaction between spines that belong to different neurons.

References

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Fan P, Manoli DS, Ahmed OM, Chen Y, Agarwal N, Kwong S, Cai AG, Neitz J, Renslo A, Baker BS, Shah NM (2013) Genetic and neural mechanisms that inhibit Drosophila from mating with other species. Cell. 154(1):89–102.  https://doi.org/10.1016/j.cell.2013.06.008

Feinberg EH, Vanhoven MK, Bendesky A, Wang G., Fetter RD, Shen K, Bargmann CI (2008) GFP reconstitution across synaptic partners (GRASP) defines cell contacts and synapses in living nervous systems. Neuron. 57(3):353–363.  https://doi.org/10.1016/j.neuron.2007.11.030

Fernández-Ruiz A, Oliva A, Nagy GA, Maurer AP, Berényi A, Buzsáki G (2017) Entorhinal-CA3 dual-input control of spike timing in the hippocampus by theta-gamma coupling. Neuron. 93(5):1213–1226.e5. doi: 10.1016/j.neuron.2017.02.017.

Gordon MD, Scott K (2009) Motor control in a Drosophila taste circuit. Neuron. 61(3):373–384. https://doi.org/10.1016/j.neuron.2008.12.033

Grienberger C, Chen X, Konnerth A (2014) NMDA receptor-dependent multidendrite Ca2+ spikes required for hippocampal burst firing in vivo. Neuron. 81:1274–1281. PubMed

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Macpherso LJ, Zaharieva EE, Kearney PJ, Alpert MH, Lin TY, Turan Z, Lee CH, Gallio M (2015) Dynamic labelling of neural connections in multiple colours by trans-synaptic fluorescence complementation. Nat. Commun. 6:10024. https://doi.org/10.1038/ncomms10024

Magee JC, Grienberger C (2020) Synaptic plasticity forms and functions. Annu. Rev. Neurosci. 43:95–117. PubMed

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Invariant stimulus decoding using correlated neuronal fluctuations (Ebrahimi et al., (2022) Nature. May 605(7911):713-721. PubMed)

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.

                                                                       Subthreshold activation to firing

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. PubMed

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. PubMed

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. PubMed

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. PubMed

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 (Zhao et al., (2022) Nature. May 605(7911):706-712)

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.

                               Formation of perceptons

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. PubMed

Semmelhack JL & Wang JW (2009) Select Drosophila glomeruli mediate innate olfactory attraction and aversion. Nature 459:218-223. 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

Vosshall LB. & Stocker RF (2007) Molecular architecture of smell and taste in. Drosophila. Annu. Rev. Neurosci. 30:505-533. PubMed

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. PubMed

Zhao Z, Zung JL, Hinze A, Kriete AL, Iqbal A, Younger MA, Matthews BJ, Merhof D, Thiberge S, Ignell R, Strauch M, McBride CS (2022) Mosquito brains encode unique features of human odour to drive host seeking. Nature. 605(7911):706-712. PubMed

 

Spine enlargement following associative learning (Choi et al., (2021) Neuron. Sept. 109(17):2717-2726)

Experiments have shown that activated ensembles of synapses have significantly larger spine morphology at the auditory cortex-to-lateral amygdala synaptic region after auditory fear conditioning. Fear extinction reversed these ensembles of enlarged spines, whereas re-conditioning with the same tone and shock restored the spine size of the synapses (Choi et al., 2021). In fear conditioning experiments, foot shock is a high energy stimulus and it is likely to generate several inter-postsynaptic functional LINKs (IPLs) in the amygdala in a time-dependent manner. This can explain why fear conditioning is observed after three hours following foot shock (Rumpel, 2005). Furthermore, it was observed that memory is reduced after three hours of blocking of synaptic incorporation of AMPA receptors in as few as 10 to 20% of lateral amygdala neurons (Rumpel, 2005). This needs a timescale-matched explanation. Based on the semblance hypothesis, IPL formation during learning takes place in milliseconds. Intra-spine GluR1 vesicle fusion to the lateral spine head membrane that incorporates membrane segments to the lateral spine head region enables IPLs to advance to more stabilizable states. If this is blocked, then it will lead to reversal of formed IPLs at specific locations of convergence of signals from associatively learned stimuli. It also matches with the delay in the induction of LTP after stimulation (Vadakkan, 2019). Another inference is that internal sensation of memory results from net semblance induced at a minimum number of inter-LINKed spines.

Choi DI, Kim J, Lee H, Kim JI, Sung Y, Choi JE, Venkat SJ, Park P, Jung H, Kaang BK (2021) Synaptic correlates of associative fear memory in the lateral amygdala. Neuron. S0896-6273(21)00502-X. PubMed

Rumpel S, LeDoux J, Zador A, Malinow R (2005) Postsynaptic receptor trafficking underlying a form of associative learning. Science. 308(5718):83-8. PubMed

Vadakkan KI (2009) A potential mechanism for first-person internal sensation of memory provides evidence for the relationship between learning and LTP induction. Behav Brain Res. 360:16-35. PubMed

 

How does dopamine filter excitatory inputs to nucleus accumbens (NAc)? (Christoffel et al., (2021 PNAS.118(24):e2106648118).

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 (Schoonover et al., (2021) Nature. 594(7864):541-546).

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). (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. PubMed

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. PubMed

Vadakkan KI (2011) A possible mechanism of transfer of memories from the hippocampus to the cortex. Med Hypotheses. 77(2):234-43. 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

Vadakkan KI (2016) The functional role of all postsynaptic potentials examined from a first-person frame of reference. Rev Neurosci. 27(2):159-84. PubMed

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; Saha and Sen, 2019), 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. PubMed

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

Blaschke AJ, Staley K, Chun J (1996) Widespread programmed cell death in proliferative and postmitotic regions of the fetal cerebral cortex. Development 122(4):1165-74. 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. PubMed

Anderton BH (1997) Changes in the ageing brain in health and disease. Philos Trans R Soc Lond B Biol Sci. 352(1363):1781-1792. PubMed

 

Heterogeneity of neurons in the cortex

Studies of cortical neurons show significant heterogeneity in transcriptomic analyses (Tasic et al., 2016; Cembrowski et al., 2016; 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

Cembrowski MS, et al., (2016) 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. PubMed

Hodge et al., (2019) Conserved cell types with divergent features in human versus mouse cortex. Nature 573 (7772):61-68. PubMed

  

  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., (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. The report by 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. Due to extreme degeneracy of inputs in firing a cortifcal neuron (Vadakkan, 2016), two findings are expected. a) a specific neuron will respond to a very large number of visual stimuli if that neuron is being kept at sub-threshold activation level at the baseline state, and b) internal sensation of perception will continue to occur at the inter-LINKed spine of a neuron even without any change in the firing status of that neuron which remains at a supra-threshold activation state.

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

Vadakkan KI (2019) Extreme degeneracy of inputs in firing a neuron leads to loss of information when neuronal firing is examined. Peerj Preprints Article

 

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 (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.

                                                                       Lateral propagtion of current in a cortical layer
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., (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.

                                                                     Islet of inter-LINKed spines

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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Vadakkan KI (2010) Framework of consciousness from semblance of activity at functionally LINKed postsynaptic membranes. Front Psychol. 1:168. PubMed

 

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. From the findings of Sheffield and Dombeck, it is clear that dendritic spikes relate to spatial precision. However, this finding needs a mechanistic explanation.

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). The latter property can explain the expected binding feature (Sheffield and Dombeck, 2015b).

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 activity 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; Esteves and Cardoso, 2020). Since transcriptomic analysis shows that no two neurons are same (Tasic et al., 2016; Cembrowski et al., 2016; Tasic et al., 2018; Hodge et al., 2019) and since IPL formation can occur between abutted spines that belong to different neurons at locations of convergence (Vadakkan, 2019), pathological IPL fusion changes expected to occur in neurodegenerative disorders occur between different sets of neurons in different patients. Hence, depending on the outcome of damage that can occur due to the specific combinations of fusion between different sets of neurons, huge heterogeneity can be expected.

Lam B, Masellis M, Freedman M, Stuss DT, Black SE. (2013) Clinical, imaging, and pathological heterogeneity of the Alzheimer's disease syndrome. Alzheimers Res Ther. 2013 Jan 9;5(1):1 PubMed

Esteves AR, Cardoso SM (2020) Differential protein expression in diverse brain areas of Parkinson’s and Alzheimer’s disease patients. Sci. Rep. 2020, 10:1–22. PubMed

Tasic et al., (2016) Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat Neurosci. 19(2):335-346. PubMed

Cembrowski MS, Bachman JL, Wang L, Sugino K, Shields BC, Spruston N (2016) 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. PubMed

Hodge et al., (2019) Conserved cell types with divergent features in human versus mouse cortex. Nature 573 (7772):61-68. PubMed