Explanations - Semblancehypothesis.org

Finding	Explanation
Absence of cellular changes during memory retrieval.	Reactivation of IPL to generate units of inner sensations is a passive process.
Memory can be retrieved by either one of the associated stimuli.	IPL operates bidirectionally.
Even partial features of one associatively learned item can trigger the memory of the second item.	Integration of units of inner sensations are expected to provide a general framework of the memorized item (Vadakkan, 2010; 2013; 2019).
Long-term memory has had both working and short-term memories at different time points.	IPLs can be stabilized for different durations (Vadakkan, 2010; 2013).
The qualia of long-term memory changes compared to that of the working memory.	The net semblance changes gradually due to loss of spines, insertion of new granule neurons in the circuitry etc. (Vadakkan, 2009).
The capacity to store large number of memories.	IPLs within the islets of inter-LINKed spines (IILSPs) can be reactivated in a combinatorial fashion (Vadakkan, 2009).
Instant access to very large memory stores.	Cue stimulus is provided access to all the unitary mechanisms (Vadakkan, 2009).
Transfer of learning between different locations.	Formation of IPLs in different brain regions reaches a stage when sufficient number of units of inner sensations gets integrated from one region alone (Vadakkan, 2011).
Motivation enhances learning (Wang et al., 2004) & is associated with the release of dopamine (lino et al., 2020). Dopamine is associated with persistence of long-term memory storage (Rossato et al., 2009).	Dopamine may induce spine expansion (Yagishita et al., 2014) enhancing IPL formation. When IPLs last for long, it may lead to its stabilization.
Most excitatory glutamatergic synapses are located on dendritic spines, which enlarge during learning.	Glutamate induces spine enlargement in hippocampal slices (95%) (Matsuzaki et al., 2004) & in neocortex in vivo (22%) (Noguchi et al.,2019) - promotes IPL formation.
Most learning events result only in working memory that lasts only for a short period.	IPL formation is an energy-intensive process, as demonstrated in experiments with artificial membranes (Rand & Parsegian, 1984; Martens & McMahon, 2008; Harrison, 2015).
Previously, it was found that memories involve time-dependent “tritrace” mechanisms (McGaugh, 1966).	IPLs are inherently rapidly reversible, stabilizable for different durations.
The ability to store new memories without overwriting existing ones.	Inter-LINKed spines within IILSPs can be shared by different stimuli to generate units of inner sensations that can be integrated to form memory (Vadakkan, 2010; 2013).
Memory consolidation refers to the apparent transfer of memory storage from the hippocampus to the cortex over a span of 5 to 8 years.	Repetition of learning, related learning, and learning events containing shared elements continue, coupled with the insertion of new neurons in the granule layer of the hippocampus, result in the formation of a surplus of new sparse IPLs in the cortex over time (Vadakkan, 2011). Eventually, net semblance for the item from the cortex alone will become sufficient to form memory of the item in response to a cue.
The mechanism utilizes pre-existing schemas (Tse et al., 2007), which are expected to be used interchangeably.	Pre-existing inter-LINKed spines are utilized by common sensory elements present in a new learning event (Vadakkan, 2010a; 2013).
A dynamically adapting circuit mechanism.	Inter-LINKing of spines that synapse to inhibitory inputs can regulate how specific inter-LINKed spines within an IILSPs can get selectively reactivated. Reversal of IPLs, deletion & formation of new spines also contribute.
A framework for a mechanism that enables the system to generate hypotheses (Abbott, 2008).	When a spine from each of two IILSPs gets inter-LINKed, every spine in the first islet forms a relationship with every spine in the second, thus increasing the search space. This allows generation of hypotheses about all possible relationships when a stimulus arrives to one of the inter-LINKed spines (Vadakkan, 2010; 2013).
The system requires a sleep state for approximately one-third of its operating time.	A state of sleep is necessary to maintain postsynaptic depolarization induced by the presynaptic terminal as the system's dominant state. This dominance is crucial for enabling a cue stimulus to trick that postsynaptic terminal to hallucinate arrival of activity at its presynaptic terminal evoking memory (Vadakkan, 2016). See Minsky, 1980.
While living aboard a space station, the need for sleep decreases by more than an hour (Dijk et al., 2001; Gonfalone, 2016).	Reduced sensory stimuli from environment is associated with lesser reactivation of inter-LINKed spines. This allows restoring the system to its baseline dominant state with lesser duration of sleep (Vadakkan, 2016).
During memory retrieval, the inner sensation of memory can occur either with or without motor actions, such as speech or behavioral movements.	Motor outputs can be voluntarily inhibited through inhibitory inputs to motor neurons while maintaining the ability of IPLs to generate inner sensations (Vadakkan, 2010; 2013).
A study noticed that memory retrieval occurs at a frequency of oscillating extracellular potentials similar to that was present during learning (Vaz et al., 2019).	When memory retrieval take place soon after learning, vector components from IPLs at specific locations contributing to the oscillating potentials are likely to maintain the later at similar frequency.
It is challenging to inhibit a memory voluntarily.	It is not possible to voluntarily inhibit an IPL immediately. However, by a) inter-LINKing existing inter-LINKed spines with spines that receive inhibitory inputs, & b) rewiring the circuitry with feedback loops by new learning events (Vadakkan, 2007; 2010) it is possible to modify a memory.
The firing of an ensemble of neurons during a higher brain function.	Reactivation of IPLs during a higher brain function (which generates units of inner sensation) enables potentials to propagate from inter-LINKed spines to their postsynaptic neurons. If these potentials bring the neurons to threshold, they will fire (Vadakkan, 2010; 2016).
It is challenging to inhibit a memory voluntarily	It is not possible to voluntarily inhibit an IPL immediately. However, by a) inter-LINKing existing inter-LINKed spines with spines that receive inhibitory inputs, & b) rewiring the circuitry with feedback loops by new learning events (Vadakkan, 2007; 2010) it is possible to modify a memory.
The firing of an ensemble of neurons during a higher brain function.	Reactivation of IPLs during a higher brain function (which generates units of inner sensation) enables potentials to propagate from inter-LINKed spines to their postsynaptic neurons. If these potentials bring the neurons to threshold, they will fire (Vadakkan, 2010; 2016).
During memory retrieval, a subset of neurons that were previously unresponsive to the cue stimulus become active (Schlack & Albright, 2007; Furtak et al., 2007). Similar findings are also observed in lateral amygdala in fear conditioning experiments (Schoenbaum et al., 1998; Tye et al., 2008).	Exposure to the same stimulus long after learning will activate an additional set of neurons, through the propagation of potential across many IPLs formed from subsequent learning events. Also newly incorporated granule neurons introduce new paths that a cue stimulus propagates & fire neurons.
Learning & memory retrieval are associated with the activation of different sets of neurons.	During learning firing depends on inputs from both stimuli & the effect of newly forming IPLs. During retrieval, cue stimulus & the effect of IPLs will be there. These changes will be seen in downstream of the IPL locations.
Place cells (CA1 neurons that fire in response to an animal's specific spatial location) are activated by particular spatial stimuli.	Reactivation of IPLs formed between spines on overlapping dendrites of CA1 neurons provide additional potentials to their postsynaptic CA1 neurons that are being held at subthreshold activation levels. This explains firing of place cells (Vadakkan, 2013; 2016).
Hippocampal neurons in chickadees exhibit patterns of CA1 neuronal firing that are specific to the locations of hidden food (to check safety of food). These are independent of place fields (set of CA1 neurons that fire when the birds reach the same location during a casual flight (Chettih et al., 2024).	CA1 neuron have their spines inter-LINKed spines in many IILSPs. Based on the inputs reaching an islet (search) to generate first-person property of safety, a specific set of inter-LINKed spines get activated that result in potentials reaching their subthreshold postsynaptic CA1 neurons to fire. Place cells respond to activation of a different set of inter-LINKed spines.
An inhibitor of AMPA receptor (AMPAR) endocytosis partially rescued long-term memory deficits in mice with elevated levels of amyloid-β (Yan et al., 2024).	IPL formation takes place between the lateral margins of the abutted spines due to the organization of the endocytic machinary at the lateral spine regions (Racz et al., 2004; Makino & Malinow, 2009; Jacob & Weinberg, 2015). Endocytosis of vesicles containing AMPARs uses of membrane segments to form endosomes, reduces size of spine heads. Inhibiting endocytosis these vesicles help maintain spine heads at their maximum size, thereby facilitating the formation of IPLs.
Mice injected with histone acetyltransferase (HAT) exhibited enhanced fear memory. Neurons in which HAT was overexpressed are part of the engram (Santoni et al., 2024).	To maintain enlarged spines to form & maintain IPLs, it is necessary to synthesize fatty acids (primarily palmitic acid) through a multi-enzyme complex, followed by the actions of desaturase & elongase enzymes, synthesis of phospholipids, & their transport to plasma membranes. HAT is expected to remove histones from the DNA sequences facilitating expression their corresponding genes.
Rapid changes in both the magnitude & correlational structure of cortical network activity (Benisty et al., 2024).	Changes in environmental stimuli, self-triggered thought processes, & various inner sensations such as fear, anticipation, hunger, & comfort fluctuate moment by moment, forming & reactivating new sets of IPLs. These continue to modify the network activity (Vadakkan, 2019).
Even nearby neurons with similar orientation tuning show virtually no correlated variability between trials (Ecker et al., 2010).	Recent modeling studies have shown that a pyramidal neuron can fire an action potential through spatial summation (simultaneous summation) of nearly 140 EPSPs at the axonal hillock, originating from randomly located dendritic spines (Palmer et al., 2014; Eyal et al., 2018). However, based on energy calculations per bit of information, around 2,000 synaptic inputs are required for neuronal firing (Levy & Calvert, 2021). Both the degeneracy of inputs in firing a neuron & propagation of depolarization across the IPLs can explain the observed decorrelated firing events among neighboring cortical neurons.
In the above study (Ecker et al., 2010), nearby neurons, despite substantial amounts of shared input, show arbitrarily low mean spiking correlations.	IPL function is to generate first-person property & corresponding motor actions. Shared sensory drive can activate potential IPL substrates, but recurrent circuit constraints limit simultaneous expression of IPL-mediated internal states, leading to low observable spike correlations despite shared input. This explains functional properties of the system operations.
Any set of 140 input signals arriving from random locations across the dendritic tree can trigger the firing of a neuron (Palmer et al., 2014; Eyal et al., 2018). This results in extreme degeneracy of input signals in neuronal firing. As there is no input specificity required for firing a neuron, information could potentially be lost. Nevertheless, a system operating under this scheme was selected from a range of variations because it provides functional advantages to the system.	Contribution of potentials from each of the inter-LINKed spine (depending on nature of neighboring inter-LINKed spine's inputs) determine whether their subthreshold postsynaptic neurons fire or not. Limited number of muscles in the body must execute a vast array of motor outputs in response to a large number of sensory inputs. Hence, degeneracy of inputs in firing a neuron, and combinatorial motor unit activation enhance efficiency (for example, the muscles of the face & tongue generating speech).
Many neurons are being held in a sub-threshold activation state (Seong et al., 2014).	The subthreshold value determines the quantity of inputs that needs to reach those neurons to fire them. This enables control of motor outputs that for behavior and speech.
An operational mechanism is expected to occur in an energy-efficient location.	Expectation of IPLs to form between the head regions of abutted spines that belong to different neurons (Vadakkan, 2010; 2016).
A dendritic spike occurs when the summation of approximately 10 to 50 postsynaptic potentials (on the spines) takes place at the dendritic region (Antic et al., 2010).	Potentials generated within a large IILSPs of inter-LINKed spines that synapse with mainly with excitatory inputs explain voltage of a dendritic spike (Vadakkan, 2016).
Some dendritic spikes do not lead to somatic action potentials (Golding & Spruston, 1998), even though it is thought that dendritic spikes ensure neuronal output (action potential) (Gasparini et al., 2004).	Potentials from an IILSPs propagate to all the postsynaptic neurons of its inter-LINKed spines. The potentials reaching those neurons may not always become sufficient to cross the threshold for firing.
When current is injected into the dendrites of human layer 2/3 neurons, they generate repetitive trains of fast dendritic calcium spikes, which can occur independently of somatic action potentials (Gidon et al., 2020).	The net potential of a dendritic spike may drain through some of the inter-LINKed spines to their respective neuronal cell bodies that are not being recorded (Vadakkan, 2016). This can occur especially when one of the inter-LINKs of the spine of the neuron under examination is with a spine that synapse to an inhibitory input.
The prevalence of dendritic spikes on the dendrites of place cells (CA1 neurons) in behaving mice is predictive of spatial precision (Sheffield & Dombeck, 2015).	Large EPSPs of a dendritic spike signify the summation of multiple EPSPs on the dendrite. The arrival of several EPSPs via IPLs to an IILSPs summate to generate a dendritic spike.
Orientation of tuning (in response to a visual stimulus) of dendritic spikes corresponds to that of the orientation tuning of action potential firing from its soma (Smith et al., 2013).	Dendritic spikes are expected to form at the IILSPs. This aligns with the sources of potentials that give rise to dendritic spikes. The propagation of these potentials to soma can trigger neuronal firing. Hence, the orientation tuning of dendritic spikes can correspond to the neuronal firing pattern.
The classical model of synaptic integration assumes that EPSPs from individual spines summate linearly on the dendritic branch. For an NMDA spike to occur, the depolarization from multiple spines must summate locally in the dendritic branch to unblock the voltage-dependent Mg²⁺ block of neighboring NMDA receptors. However, the high electrical resistance of the spine neck, which can range from 100MΩ to >1GΩ (Grunditzet al., 2008; Tamada et al., 2020), severely attenuates synaptic current entering the dendritic shaft (Koch and Zador, 1993; Acker and White, 2007) and forms a critical biophysical constraint. Consequently, activation of even 40 spatially clustered spines would not summate in the dendrite to reach nearly -30 mV needed to unblock a critical mass of NMDA receptors de novo for a regenerative NMDA spike. The relation I = C.dV/dt informs that generating a fast voltage change (a spike) requires a large current. The spine neck resistance in the standard model limits this current. Most of the synaptic current (especially the fast AMPA component) is sunk locally into the spine head capacitance and does not effectively reach the dendrite (Bloodgood & Sabatini, 2005; Harnett et al., 2012).	The IILSPs has inter-LINKed spines that belong to different neurons that removes the bottleneck of spine head resistance, allowing sparse natural inputs to generate the large currents needed to rapidly charge dendritic capacitance and produce a full NMDA spike. The IPLs provide low-resistance connections between inter-LINKed spines so that depolarization of an inter-LINKed spine from a sensory stimulus is shared almost instantaneously with its inter-LINKed neighbors within an IILSPs. This collective depolarization rapidly unblocks the Mg²⁺ block on the entire population of NMDA receptors within the IILSPs. This will result in massive, synchronous inward current through these NMDA receptors. The parallel positioning of spine necks (resistance in parallel) of inter-LINKed spines within an IILSPs will significantly reduce net spine neck resistance. This will allow the very large current through the NMDA receptor channels to rapidly charge dendritic capacitance on the dendritic segment under examination. This is what is measured as an "NMDA spike" in the recorded dendritic branch.
The inner experience of certain higher brain functions can occur without any accompanying motor actions.	Apical dendrites in human layer 5 neurons are electrically isolated from the somatic compartment (Beaulieu-Laroche et al., 2018). This suggests the possibility of independent operations occurring in IILSPs at those distal dendritic regions.
The apical tuft regions of neurons across all cortical neuronal orders are anchored to the inner pial surface. This arrangement results from a sequence of movements of neuronal precursors during development.	It promotes formation of inter-neuronal order IPLs. Since inputs from distant locations reach the 2, 3 & 4^th layer, & since 5^th layer has upper motor neurons, this organization enables the integration of inner sensation units & supports behavioral motor actions.
Following learning, there is initially conscious retrieval of memory in response to a cue stimulus. With repeated retrievals, this process eventually becomes subconscious.	Routinely arriving stimuli may become neither essential nor detrimental to survival. Semblances induced by them merge together to form C-semblance bringing novel, beneficial & deleterious stimuli to attention.
Several seizures spread laterally to adjacent cortical regions. Focal seizures may present with a Jacksonian march, affecting both sensory & motor functions.	Seizures can be explained as rapid, chain-like formation of IPLs in the cortex (Vadakkan, 2016). This explains development of sensory & motor features from adjacent cortical areas.
Various seizures are associated with distinct types of hallucinations.	The lateral spread of seizures via rapid IPL formation across the sensory cortices provides a mechanism for the internal perception of various sensations (Vadakkan, 2016).
The pathological changes associated with amyotrophic lateral sclerosis (ALS) spread laterally.	IPL structure can progress to fusion between spines that belong to different neurons leads to mixing of their cytoplasm, which in turn lead to lateral spread of pathological changes such as spine loss & ultimately neuronal degeneration, as seen in ALS (Vadakkan, 2016).
In animal models of seizures, the transfer of injected dye from one CA1 neuron to neighboring CA1 neurons has been observed (Colling et al., 1996).	Excessive excitation can result in the pathological conversion of IPLs (that are normally limited to inter-spine membrane hemifusion) into inter-neuronal inter-spine membrane fusion (Vadakkan, 2016). This process can explain the observed dye spread between neurons.
Loss of dendritic spines occurs after kindling, during seizures, & following the induction of long-term potentiation (LTP).	Inter-neuronal inter-spine fusion can lead to mixing of cytoplasmic contents between neurons. Given that the expression profiles of even adjacent neurons of the same type can differ (Kamme et al., 2003; Cembrowski et al., 2016), cytoplasmic mixing is detrimental to both neurons. Hence, homeostatic mechanisms will trigger to cause loss of spines to protect neurons from further damage (Vadakkan, 2016).
The CA2 region of the hippocampus is resistant to seizures (Correa et al., 2025).	Perineuronal net proteins surrounding the spine heads in the CA2 region (Carstens et al., 2016) can inhibit IPL formation between spines of different neurons, offering an explanation for the region's resistance to seizures (Vadakkan, 2016).
The CA2 region of the hippocampus is spared in different models of hypoxia or ischemia (Kirino, 1982; Sadowski et al., 1999).	An explanation for the Golgi staining reaction led to the inference that oxygen plays a role in reversing IPLs (Vadakkan, 2021). Conversely, hypoxia can promote increased IPL formation, potentially progressing to membrane fusion. Due to the presence of perineuronal net proteins surrounding the spine heads (Dansie & Ethell, 2011), CA2 region is resistant to IPL formation that pathologically undergoes inter-neuronal inter-spine fusion.
Herpes simplex viral (HSV) encephalitis is associated with seizures & memory loss.	HSV fusion proteins has the potential to cause rapid formation of large number of non-specific IPLs & lead to seizures. Conversion of IPL hemifusion to fusion state, cause mixing cytoplasms of different neurons. Since expression profiles of even adjacent neurons of the same type are different (Kamme et al., 2003; Cembrowski et al., 2016), homeostatic mechanisms lead to loss of spines involved in fusion. If not successful, it can lead to neuronal death leading to cognitive defects (Vadakkan, 2016).
Anesthetic agents are known to alleviate seizures.	Anesthetic molecules are expected to generate a large number of non-specific IPLs, linking multiples of IILSPs. This enhances the horizontal component of oscillating potentials, significantly lowering the frequency of extracellular oscillations. Consequently, both specific inner sensations & motor actions are suppressed (Vadakkan, 2016).
Memory impairment is a common symptom observed in patients with seizure disorders (Mazarati, 2008).	Seizure pathology involves the rapid formation of numerous non-specific IPLs, as well as IPL fusion between spines, which can result in spine loss & even neuronal degeneration (Vadakkan, 2016).
The intracellular electrophysiological correlate of epileptiform activity is the paroxysmal depolarizing shift (PDS), characterized as a giant excitatory postsynaptic potential (EPSP) (Johnson & Brown, 1981).	PDS is a large EPSP is generated through a postsynaptic mechanism (Johnson & Brown, 1981). Since distal dendrites typically generate EPSPs with amplitudes around 10 mV (Spruston, 2008), & the maximum voltage of a PDS can reach up to 50 mV, spatial summation of multiple EPSPs presents a plausible mechanism for the PDS (Vadakkan, 2016).
Although a simultaneous decrease in extracellular Ca²⁺ & an increase in K⁺ during seizures can impede action potential propagation along axons (Seignuer & Timofeev, 2011), seizure activity persists in status epilepticus.	The formation of a large number of non-specific IPLs between closely apposed spines of different neurons offers an alternative pathway that can facilitate the summation of EPSPs & propagation of PDS-like activity across the cortex (Vadakkan, 2016).
Cell swelling is commonly observed during the "spreading depression" phase of seizures (Kempski et al., 2000; Olsson et al., 2006; Colbourn et al., 2021).	Enlargement of dendritic spines is likely to displace the hydration layer of the ECM between abutted spines & promote formation of non-specific IPLs that facilitate seizure generation.
The ketogenic diet is commonly used to prevent seizures (Martin-McGill et al., 2020; Kossoff et al., 2021). It has been shown to increase the serum concentration of long-chain polyunsaturated fatty acids (LC-PUFA) (Anderson et al., 2001; Fraser et al., 2002).	The membrane lipid composition remains optimal when dietary n-3 polyunsaturated fatty acids (PUFAs) account for more than 10% of total PUFAs (Abbott et al., 2012). LC-PUFAs from ketogenic diet, or their modified forms form ester bonds on the triglyceride backbone of lipid membranes. These triglycerides may prevent formation of non-specific IPLs between spine membranes & prevent seizures (Vadakkan, 2016).
Seizure disorders are often linked to neurodegenerative changes (Farrell et al., 2017).	Though IPLs are expected to remain limited to the hemifusion stage, several factors can promote conversion of hemifusion to IPL fusion. When cytoplasms of neurons mix, it leads to spine loss & subsequent neuronal degeneration (Vadakkan, 2016).
Loss of consciousness is a common feature during complex seizures.	The reactivation of a large number of IPLs in response to both internal & external stimuli generate a background semblance that forms a framework for inner experience of consciousness. The rapid formation of numerous IPLs during seizures induces a multitude of non-specific semblances, disrupting the coherence of the semblance necessary for maintaining consciousness & leading to its loss (Vadakkan, 2016).
Multiple vertical subpial resections have been shown to alleviate seizures (Morrell et al, 1989).	The effect of IPLs forming lateral connections will be lost. This can inhibit IPL-mediated rapid chain lateral propagation of seizure activity (Vadakkan, 2016).
In status epilepticus (continuous seizures), anesthetics are administered to achieve a state of "burst suppression" in the EEG. This condition is characterized by intermittent periods of electrical inactivity lasting several seconds, alternating with high-voltage bursts of activity (Meierkord et al., 2010).	Formation of such a vast number of non-specific IPLs by anesthetic agents is anticipated to create a substantial horizontal component, causing oscillating extracellular potentials to flatten into a straight line. This mechanism can explain the reversible state of "burst suppression." As a result, the firing of downstream neurons is reduced, leading to a decrease in the muscle contractions associated with seizures (Vadakkan, 2016).
The ictal (during seizure) & postictal characteristics observed in electroconvulsive therapy (ECT) are essentially similar to those seen in patients with generalized tonic-clonic seizures (Pottkämper et al., 2021)	The high energy used in ECT induces rapid chain formation of a large number of non-specific IPLs similar to the proposed mechanism of seizures by IPL pathology (Vadakkan, 2016).
Electroconvulsive therapy (ECT) has been shown to alleviate endogenous depression (Subramanian et al., 2022) & has remained a standard treatment for the past 70 years.	The application of substantial energy to cortical regions can induce the formation of a large number of non-specific inter-postsynaptic functional links (IPLs) can alter the net semblance responsible for depressive state.
Short-term memory loss has been observed following electroconvulsive therapy (ECT) using methods employed before the 1980s (Duncan, 1949; Squire, 1977; Frith et al., 1983). However, with the introduction of low-energy ECT in the 1990s, memory impairment has been significantly reduced (Meeter et al., 2011).	Higher stimulation energy used in earlier versions of ECT can lead to a larger number of non-specific IPLs compared to the lower energy used in present-day ECT.
Dementia is a common feature of neurodegenerative disorders, where the loss of dendritic spines &, eventually, neuronal death is frequently observed.	The loss of dendritic spines & neurons leads to a reduction in the number of specific IPLs required to generate the distinct units of inner sensation associated with a specific memory (Vadakkan, 2016).
The perceived location of the stimulus differs from its actual location.	The inner sensation of a percept produced by the integration of multiple units of perception called perceptons has a spatial projection towards environment. Computation of perceptons result in a different location for the percept (Vadakkan, 2015).
A stimulus presented at a frequency above the flicker fusion threshold is perceived as a homogeneous, continuous percept.	Since units of perception (perceptons) from IPLs generated in a temporal pattern from consecutive flickers overlap it results in a continuous percept (Vadakkan, 2015).
Perception of object borders.	Stimuli from inside the border form a percept with a different depth than stimuli from outside the border. thereby defining the border. This explains border contrasting with the background (Vadakkan, 2015).
First-person inner sensation of pressure-induced phosphenes.	Stimulation of sensory pathways anywhere along the input path (e.g. retina), before their convergence in the visual cortex, can form IPLs generating perceptons (Vadakkan, 2015).
Continuous perception of moving objects without interruption.	Smooth pursuit eye movements enable visual stimuli to fall on either side of the same set of IPLs in the visual cortex. If the object moves faster than a threshold, saccadic eye movements are triggered, ensuring the overlap of perceptons for continuous perception.
Behaviorally relevant patterns of PN response variation providing individuality are observed. In this study changes were present only occur at the ORN-PN synapses (Churgin et al., 2025) & is associated with odor elicited oscillations in the glomerulus (Tanaka & Stopfer, 2009).	Based on the semblance hypothesis, oscillating potentials integrate first-person property of the system. Oscillations among the interneurons in the glomerulus facilitates this. Excessive branching & arbor of PN neurons favor IPL formation for perception (Vadakkan, 2015).
It is possible to discriminate between two odorants when sniffed at a 60-millisecond interval (Wu et al., 2024).	Perception occurs through the rapid, reversible formation of IPLs. This allows for the formation of new sets of IPLs upon the arrival of the second odorant, generating distinct perceptons for the perception of the second odor (Vadak kan, 2015).
Orientation tuning of a population of neurons in V1, before & after training on a visuo-motor task, revealed different sets of neurons responding (Failor et al., 2021).	Perception occurs by the rapid formation of IPLs (to form perceptons) between abutted spines in V1. Lack of consistency in the set of firing neurons in response to the same visual stimulus don't affect perception (Vadakkan, 2015). Firing of postsynaptic neurons depends on: a) additional depolarization reaching these neurons via the newly formed IPLs & b) the sub-threshold activation state of the neurons.
The flash-lag effect (FLE) occurs when a flash is briefly presented at a specific location adjacent to the path of a uniformly moving object, causing the flash to be perceived as lagging behind the object.	For a newly appearing flash, 12ms delay is attributed to synaptic and conduction delays across 5 synapses % through neurons. The remaining delay is due to IPL formation, reactivation, generation of perceptons, & the integration of these processes for percept formation (Vadakkan, 2022). The total perceptual latency for the flash is therefore: T_percept ≈ Δt_cond + Δt_transm + Δt_IPL-form + Δt_percepton + Δt_integr ≈ 70–100 ms. However, continuous perception of a moving object can leverage already formed IPLs, enabling its perception before the flash. Hence, the update latency for the moving object is: T_{update[motion]} ≈ 36–42 ms. This temporal offset is converted into a spatial lag: FLE ≈ v · T_{percept(flash)} - T_update) ≈ ~46 ms, matching the magnitude of controlled measurements reporting FLE magnitudes of 30–60 ms (Krekelberg & Lappe, 2001; E agleman & Sejnowski, 2000a; Whitney & Murakami, 1998).
A moving object that abruptly appears & begins to move is initially invisible for some distance, a phenomenon known as the Frohlich effect (Fröhlich, 1929). The duration of this spatial displacement was quantified as corresponding to a temporal delay of approximately 80–120 ms (Müsseler & Aschersleben, 1998).	Total reactive perceptual delay for a novel, unpredictable event = T_{motion-onset latency} = ≈ 80–120 ms). This matches with the delay of at least 100ms between retinal photoreceptor cell stimulation & conscious perception (De Valois & De Valois, 1991; Nijhawan 2008). By the time the perceptons of the first percept of the moving object are integrated (after T_motion-onset), the physical object has already moved a distance Δx = v · T_motion-onset. This provides a plausible explanation for the Fröhlich effect (Vadakkan, 2022).
A moving object is perceived slightly beyond the endpoint of its actual trajectory (Hubbard, 2005), & this percept decays within a few hundred milliseconds after the object disappears (Hubbard, 2018).	After the final moment of stimulus arrival from a moving object, synaptic & conduction delays, reactivation of continuously maintained IPLs, formation and integration of perceptons continue. Hence, percept gets spatially shifted (Vadakkan, 2022).To maintain perceptual continuity, the percept of a moving object is integrated forward over a forward integration horizon τ_proj defined by the sum of the final motion update & the latency for detecting a new motion direction (τ_proj ≈ T_update + T_motion-onset ≈ 116–162 ms).
Perception of a stimulus (S1) can be blocked or modified if it is followed in rapid succession by a second stimulus (S2), which is called backward masking (Bachmann, 1994).	Perceptons of the first stimulus are integrated with the overlapping perceptons of the second stimulus. overlapped by integration of perceptons (Vadakkan, 2022). For masking to be effective, S2 must arrive & begin processing before S1's percepton assembly is complete & integrated into a conscious percept. This requires the stimulus onset asynchrony to be shorter than S1's processing latency up to the point of integration.
When successive stimuli are presented at frequencies above the critical flicker frequency (e.g., >~20 Hz), they are perceived as a single continuous stimulus (Jensen, 2006).	Above certain frequency, the formed perceptons from subsequent frames get overlapped, which allow them to get integrated (Vadakkan, 2022). This occurs when the input rate exceeds the system's ability to segregate individual perceptual epochs. The critical condition is that the inter-stimulus interval is shorter than the integration window itself such that ISI < Δt_integr (Jensen, 2006). Under this regime, the Δt_integr phases of successive stimuli perpetually overlap.
When a stationary object is presented for 2.5 seconds, then briefly removed for a short interval – such as 30 milliseconds – & subsequently reappears in motion, it may be perceived as moving continuously (Whitney & Cavanagh, 2000).	Perceptual continuity across a brief (~30 ms) interruption (gap) after a long presentation (Whitney & Cavanagh, 2000) is enabled by the persistence (absence of rapid reversal of perception) & rapid reactivation of the underlying IPL network. T_gap < Δt_rev. During the initial presentation, a stable IPL network is established. Upon offset, this network begins to decay with a time constant Δt_rev (variable, 30–300 ms). For a short gap (T_gap = 30 ms), the condition T_gap < Δt_rev holds. So, when the stimulus reappears after the brief interruption, its neural representation remains above the threshold for recognition (Vadakkan, 2022).
In the 'high-ϕ illusion,' when a rotating texture is abruptly replaced by a random texture, the observer perceives the texture as jerking backward (Wexler et al., 2013).	During continuous rotation, a stable semblance of motion is maintained by fast IPL reactivation cycles (T_update). When the pattern is suddenly replaced, 2 parallel processes begin. 1) Decay of motion semblance: The active IPL network supporting the rotation representation decays with a time constant Δt_rev (~30–300 ms). 2) Formation of novel static semblance: Perception of random texture requires slow de novo IPL formation, with a latency on the order of T_{percept(novel)} ≈ 70–100 ms. This creates a temporal conflict within the postdictive integration window. For a period after the switch, brain has simultaneous access to 1) a decaying neural representation signaling continued rotation, & 2) an incomplete, new representation of a static pattern. The perceptual system resolves this conflict by assigning the definitive sensory evidence to the perceptual "now." The lingering rotational activity is interpreted as having occurred just prior to this "now," creating the vivid illusion of a backward jump. (Vadakkan, 2022).
Observers do not perceive an object as extending beyond the point at which it changes direction (Eagleman & Sejnowski, 2000).	FLE is nullified at a direction change because the flash acts as a spatial anchor that collapses the forward integration horizon (τ_proj ≈ 116–162 ms) of the moving object. At the moment of reversal, the old motion vector begins to deactivate within one fast update cycle (T_update ≈ 36–42 ms before the turn), while the new direction (a novel event) requires slow de novo IPL formation (T_motion-onset ≈ 80–120 ms). The flash’s slowly assembling perceptons (T_{percept(flash)} ≈ 70–100 ms) provide a static spatial tag at the turn vertex. When reversal occurs early (~26 ms after the flash), the forward integration is still labile, and no new directional signal has consolidated; the flash’s anchor therefore collapses the integration to the vertex, aligning the percepts of the flash & moving object. For later reversals (> ~67 ms), forward IPLs stabilize, a new direction emerges, & the latency difference is re-expressed, restoring the FLE. Thus, cancellation at a turn reflects dynamic re anchoring within a postdictive integration window.
The flash-lag effect (FLE) is not perceived if the moving object stops at the same time the flash is presented as a stationary object (Kanai et al., 2004; Hubbard 2014).	Slowly assembled perceptons of the flash provide a definitive, static spatial tag for the point of coincidence. Within the postdictive integration window, this static tag directly conflicts with the ongoing forward integration of the motion path (which began τ_proj ms earlier, where τ_proj ≈ T_update + T_{motion onset}). The integration process cannot reconcile a static anchor with continued motion extrapolation. Consequently, the forward integration collapses to the flash's spatial coordinate. The motion percept is terminated at that point, & the delayed flash percept is assigned to the same location. Thus, physical alignment results in perceptual alignment (Vadakkan, 2022).
No flash-lag effect (FLE) is perceived when both the moving object & the flash disappear simultaneously (Eagleman & Sejnowski, 2000).	For a tracked moving object, the percept is maintained by an active forward integration spanning τ_proj (≈ T_update + T_{motion onset}). When a flash occurs concurrently with the object’s offset, it resets this integration. The sensory evidence for the stop, a null motion vector, is then rapidly integrated via the fast T_update pathway. This allows the postdictive assembly to anchor both the flash’s delayed percept (T_{percept(flash)}) & the object’s last updated position to the same physical point of coincidence, abolishing the FLE.
When a flash stimulus reaches the retinal periphery, making it more eccentric compared to one that reaches the fovea, it leads to poorer performance on visual tasks (Staugaard et al., 2016). Moreover, the FLE increases with greater eccentricity (Hubbard, 2014).	In fovea photoreceptors are densely packed (Kolb et al., 2020). At the periphery, their concentration decreases significantly. Hence, longer time required for the integration of perceptons to generate a percept of an eccentric flash (Vadakkan, 2022). Flash requires de novo IPL formation, which is highly sensitive to input quality; weaker signal from the periphery significantly increases the IPL formation time. In contrast, moving object's percept is sustained by fast IPL reactivation (Δt_IPL-react).
The flash-lag effect (FLE) is more pronounced when the flash is less predictable (Hubbard, 2014).	For a predictable flash, pre activation of neural pathways reduces the time required for de novo IPL formation. Thus, its perceptual latency decreases. This directly shrinks the differential delay driving the FLE: FLE_predictable ≈ v ⋅ (T_{percept(predictable)} − T_update) < FLE_{unpredictable}. Concurrently, predictable motion is maintained via fast IPL reactivation cycles (T_update) within an established internal model.
Predictable moving dots at the leading edge are associated with suppressed blood oxygenation level-dependent (BOLD) responses (Schellekens et al., 2016).	Predictable motion is maintained via fast IPL reactivation cycles (T_update) within an established internal model, which is a metabolically efficient, low oxygenation requiring state. Stabilized IPLs are associated with reduced oxygen release demands, manifesting as lower BOLD signals. This is consistent with the inference made from Golgi staining reactions that IPLs are more stable under reduced oxygenation (Vadakkan, 2023).
A percept occurs even when an object moves into the peripheral regions of the blind spot (Maus & Nijhawan, 2008).	When the bar's leading edge reaches the boundary of the blind spot (∂ R_bs) at time t₀, it has established a propagating pattern of activated IPLs along its contour, IPL_contour(t0). Despite the absence of new input within R_bs, the perceptual integration process (ℐ) over its window Δt_integr continues. It extrapolates the contour forward using the established motion vector. The persistence of the IPL network enables bridging. For a seamless percept to form, extrapolated IPL decay time must persist longer than the traversal time. It allows representation to be sustained in the absence of direct input.
Brain inflammation can lead to psychosis (Comer et al., 2020; Crespi et al., 2024).	Inflammation leads to the swelling of cells & their processes, which leads to formation of non-specific IPLs, triggering hallucinations.
Inner sensations of consciousness.	Specific inner sensation of a large number of non-deleterious & non-beneficial stimuli can be prevented by integrating their units to form a net inner sensation of self that may explain C-semblance (Vadakkan, 2010; 2015). It allows generating specific inner sensations to specific stimuli.
Loss of consciousness is induced by anesthetic agents.	Anesthetic agents partition into the hydrophobic core of the lipid membrane and alter physical properties (Rózsa et al., 2023). They also interact with the outer leaflet of the lipid bilayer, causing spontaneous curvature that creates asymmetry between the outer & inner leaflets (Lipowsky, 2014). This is expected to form numerous non-specific IPLs, which in turn alters the inner sensation of consciousness.
The potency of an inhaled anesthetic agent is proportional to its partition coefficient – the concentration ratio between olive oil & water – which reflects its hydrophobic solubility. This relationship has a correlation coefficient of 0.997 (Firestone et al., 1986), representing one of the strongest correlations observed in biological systems (Halsey, 1992).	Lipid solubility of anesthetic agents influences membrane properties in a manner that proportionally promotes the formation of non-specific IPLs. The non-specific semblances generated across the inter-LINKed spines of these IPLs result in a corresponding loss of consciousness (Vadakkan, 2015).
Anesthetic agents are known to exert diverse actions, including functioning as GABA-A receptor agonists, alpha-adrenergic receptor agonists, NMDA receptor antagonists, dopamine receptor antagonists, & opioid receptor agonists (Kopp et al., 2009).	Anesthetic agents interact with the outer leaflet of the lipid bilayer, inducing spontaneous curvature that creates asymmetry between the outer & inner leaflets (Lipowsky, 2014). This facilitates formation of a large number of non-specific IPLs altering C-semblance (Vadakkan, 2015). This is the interconnecting main path even though other mechanisms of actions exist.
General anesthesia induced by anesthetic agents can be reversed by applying external pressure to an animal enclosed in a sealed container – achieved by increasing air pressure for terrestrial animals or water pressure for aquatic animals (Lever et al., 1971; Halsey et al., 1986).	External pressure propagates through the middle ear, perilymph, CSF & paravascular space, ultimately reaching neuronal processes (Iliff et al., 2012). According to Le Chatelier’s principle, when a system at equilibrium is subjected to a disturbance, the equilibrium will shift in a direction that mitigates the effect of the applied pressure. Increase in pressure causes anesthetic molecules to be displaced from the lipid membranes into ECM, from where they escape through the paravenular space into the venous system (Iliff et al., 2012). This results in reversal of non-specific IPLs generated by the anesthetics (Vadakkan, 2015).
Only reduced amounts of anesthetic agents are required to induce anesthesia in the presence of levodopa (Segal et al., 1990).	Dopamine cause enlargement of dendritic spines (Yagishita et al., 2014), which is expected to facilitate formation of a large number of non-specific IPLs by anesthetic agents. Hence, reduced anesthetic agents needed when levodopa is co-administered (Vadakkan, 2016).
Low doses of anesthetics preserve short-term memory to the point where patients can engage in conversation & appear lucid (Wang & Orser, 2011). However, as the anesthetic dose gradually increases, there is a progressive decline in short-term memory, along with a shortening of the time interval between learning & the retrieval of memories.	Learning-induced new IPLs necessary for working memory are highly reversible. Hence, low dose of anesthetic agents may not affect short-term memories. But at higher doses, formation of more non-specific IPLs will generate more non-specific semblances will prevent retrieval of specific memories (Vadakkan, 2015).
General anesthetics typically do not impair existing long-term memory (Bramham & Srebro, 1989).	IPLs responsible for maintaining long-term memory remain stabilized through inter-membrane interactions (Vadakkan, 2015). Therefore, these stable regions are not affected by anesthetic agents.
There have been several reports of cognitive decline following surgeries involving the use of general anesthetic agents (Baranov et al., 2009).	Since anesthesia is expected to generate a large number of non-specific IPLs, some of them may undergo IPL fusion, resulting in spine & neuronal loss as a consequence (Vadakkan, 2015). This can explain cognitive impairment following repeated general anesthesia.
As the dose of anesthetic is increased, patients may enter a state of excitation characterized by euphoria or dysphoria, defensive or purposeless movements, & incoherent speech. This phase is referred to as "paradoxical" because, although the anesthetic is intended to induce unconsciousness, it initially produces a state of heightened neural activity & excitation. (Brown et al., 2010).	Motor neurons in layer 5 of the motor cortex are typically maintained at a sub-threshold level of activation, allowing them to fire when additional excitatory inputs arrive. During the initial stages of anesthesia, the induction of numerous non-specific IPLs can generate certain inner sensations & simultaneously cause the firing of these sub-threshold-activated motor neurons, leading to unintended motor activity.
Loss of consciousness occurs during a generalized seizure & typically resolves once the seizure ends.	The rapid chain formation of numerous non-specific IPLs, triggered by alterations in extracellular matrix (ECM) properties (e.g., markedly low serum sodium) or by factors that enhance neuronal excitability, leads to seizure generation (Vadakkan, 2016). This alters conformation of net semblance during background state, disrupting C-semblance (Vadakkan, 2010).
Phantom limb sensation.	As long as the IPLs that once received input from the lost limb remain stable in the brain, their reactivation by stimuli from an alternative sensory source can evoke the sensation of a phantom limb. This may occur when the same nerve root in the proximal region of the lost limb is stimulated.
Phantom pain sensation.	Stimuli arriving from the same dermatome can activate the same nerve root. This can lead to reactivation of IPLs in the pain-processing regions of the primary somatosensory cortex & the emotion-processing anterior cingulate cortex that in turn can lead to the experience of phantom pain.
Innate behaviors, such as the sucking reflex, are hardwired responses present at birth that support survival.	To enable cognitive function at birth, IPLs are expected to be pre-formed during prenatal period. Developmental organization of neural pathways likely facilitate the formation of IPLs between certain abutted spines.
A higher level of education, marked by an increased number of associative learning experiences, is associated with a reduced risk of developing dementia (Maccora et al., 2020).	Associative learning involves multiple shared components. Also, new neurons are continuously integrated into the granule layer of the hippocampus, generating more IPLs in the cortex. Consequently, more learning experiences can lead to the formation of excess IPLs in the cortex (Vadakkan, 2013; 2019) that allows individuals with advanced education to tolerate more loss of IPLs before exhibiting cognitive impairments.
Certain brain regions seem to be linked to specific functions, as evidenced by lesion studies.	Units of first-person property are generated at locations inter-LINKed spines, which are formed mainly in regions of convergence of inputs. Different sensations (sensory cortices), associative learning (hippocampus) & emotions (multi-convergent areas) mainly occur at corresponding regions.
Astrocytic pedicels cover less than 50% of the peri-synaptic area in approximately 60% of the synapses within the CA1 region of the hippocampus (Ventura & Harris, 1999).	They clear spill over neurotransmitter molecules, recycle them for reuse by the neurons. Since nearly all spines have nearly 50% area not covered by astrocytic pedicels, each spine has the potential to form IPLs.
Modern nervous systems have evolved over millions of years & are also shaped by a series of accidental coincidences.	When fast or first arriving features of predator or prey reactivated IPLs & generated first-person inner sensations of the remaining properties, it conferred survival advantages. It was naturally selected & conserved throughout evolution (Vadakkan, 2020).
As cortical neurons migrate from the periventricular region to their final destinations, the diffusion of dye from an injected neuron to neighboring neurons suggests the presence of intercellular fusion pores (Bittman et al., 1997). This phenomenon is observed in all migrating neurons. This stage is followed by the death of approximately 70% of these cells, with only about 30% surviving.	Inter-neuronal fusion may have induced adaptive responses to prevent progression of IPL structure to full fusion, which is necessary for the continued IPL function. Consequently, initial inter-neuronal pore formation is thought to have triggered an adaptive mechanism that restricts further fusion, playing a key role in the evolutionary success of organisms with this capability.
Aging is considered the primary risk factor for neurodegenerative disorders, including Alzheimer’s disease (Guerreiro & Bras, 2015).	The above explained adaptation triggered in the surviving cells has prevents any future inter-neuronal fusion, spine loss, & neuronal death. Age-related defects in this adaptation can result in cell-cell fusion, spine loss & neuronal death (Vadakkan, 2021).
In prematurely born infants, the oscillating extracellular potentials in the electroencephalogram (EEG) display discontinuities in the waveform (Selton et al., 2000).	A smaller number of IPLs is likely insufficient to contribute continuous horizontal vector components below a certain developmental stage. Subsequent arrival of additional associative stimuli then provides horizontal components to the oscillations (Vadakkan, 2021).
A study found that infants are capable of forming memories, but difficulties with memory retrieval likely explain infantile amnesia (Yates et al., 2025).	Relatively small number of IPLs, less robust C-semblance, new granule neurons altering the circuitry without generating additional IPLs in the cortex, less mature oscillating extracellular potentials to integrate semblances are likely causes.
Humans take a comparatively longer time to develop motor functions after birth than most animals.	As humans develop, a single motor response needs to be associated with inputs from increasing number of IPLs. Hence the subthreshold state of motor neurons needs to be regulated to enable execution of motor actions in response to the reactivation of different IPLs (Vadakkan, 2021).
Artificially triggering spikes in a single cortical neuron induces spiking activity in a group of neighboring neurons within the same cortical layer, located at a distance between 25 & 70 µm from the stimulated neuron (Chettih & Harvey, 2019).	Can be explained in terms of propagation of depolarization across the IPLs between spines belonging to different neurons (Vadakkan, 2013). This also accounts for why only sparsely distributed neurons fire in a time-correlated manner.
The protein complexin inhibits SNARE-mediated fusion by preventing the intermediate stage of hemifusion. Both SNARE proteins and complexin are present in the spines.	SNARE proteins provide the energy required to bring membranes together, (Oelkers et al., 2016). They also generate the force needed to pull the membranes as tightly together as possible (Hernandez et al., 2012). By initiating the fusion process through energy supply (Jahn & Scheller, 2006), SNARE proteins can facilitate the formation of characteristic hemifusion intermediates (Lu et al., 2005; Giraudo et al., 2005; Liu et al., 2008). The protein complexin, present within postsynaptic terminals (Ahmad et al., 2012), is known to interact with the neuronal SNARE core complex, arresting fusion at the hemifusion stage (Schaub et al., 2006). These suggest the possibility of inter-spine interactions mediated by SNARE proteins & regulated by complexin.
The cortex contains hundreds of distinct types of neurons (Huntley et al., 2020; Mao & Staiger, 2024).	IPL formation is independent of the neuronal type of the inter-LINKing spines. e.g. Both spines that synapse with inhibitory inputs & spines of inhibitory neurons form IPLs. The net polarity inter-LINKed spines within an IILSPs determines the conformation of net semblance that defines the qualia of inner sensations (Vadakkan, 2019).
Transcriptomic analyses reveal considerable heterogeneity even among adjacent neurons of the same type within the cortex (Kamme et al., 2003; Cembrowski et al., 2016).	The distinct mRNA profiles of adjacent neurons, even of the same type, suggest that any mixing of cytoplasmic contents would trigger homeostatic mechanisms, such as spine loss, to prevent further damage (Vadakkan, 2016). This aligns with the structural limitation of IPLs to hemifusion.
Heterogeneity in clinical features & pathological changes is observed in Alzheimer's disease & other neurodegenerative disorders.	Pathological fusion is responsible for neurodegeneration. Clinical features are determined by the formation of non-specific IPLs at different locations, & the locations of IPL fusion, which can lead to spine loss & even neuronal death (Vadakkan, 2016). This explains the observed heterogeneity.
In excitatory neurons, spine depolarization can occur without subsequent dendritic depolarization (Beaulieu-Laroche et al., 2018a). Moreover, distal dendrites in humans contribute only limited excitation to the soma, even during dendritic spikes (Beaulieu- Laroche et al., 2018b).	Only the depolarization of inter-LINKed spine heads is needed to generate units of inner sensations. Firing of postsynaptic neuron is needed for motor outputs. Observed spine depolarization without subsequent dendritic depolarization aligns with the ability to produce inner sensations without corresponding motor actions.
The histological features of amyloid (senile) plaques & neurofibrillary tangles, typically associated with Alzheimer's disease & a range of neurodegenerative disorders, are also observed in normal aging (Anderton, 1997).	The formation of extracellular plaques can reduce the number of specific IPLs. Individuals with a surplus of specific IPLs can afford to lose a fraction of IPLs. However, individuals with only a borderline number of IPLs (just enough to generate specific memories) will be vulnerable to the effects of amyloid plaque accumulation in the ECM.
"Representational drift" refers to the phenomenon in which the specific set of neurons activated during a repeated brain function gradually changes over time (Schoonover et al., 2021; Marks & Goard, 2021; Deitch et al., 2021).	Formation of new unrelated learning increases input combinations to a neuron. Enlargement of IILSPs, inter-LINKs with spines that synapse with inhibitory inputs, insertion of new granule neurons altering the circuitry can lead to the formation and reactivation of new set of IPLs. As a result, when a brain function is repeated, it activates a new set of neurons (Vadakkan, 2019).
When rewards or conditioned stimuli predicting reward are presented, dopamine neurons in the VTA increase their firing (Schultz, 1998; Roitman et al., 2004) , releasing dopamine at their terminals that synapse onto the spines of medium spiny neurons (MSNs) in the nucleus accumbens (NAc).	Dopamine is known to induce spine expansion (Yagishita et al., 2014). Expanding spines can enhance IPL formation & maintain these formed IPLs for an extended period. Since some of the spines involved in IPL formation receive excitatory inputs while others receive inhibitory inputs, the net effect of dopamine is the augmentation of depression (Vadakkan, 2021).
Drugs of abuse, such as cocaine, elevate dopamine levels in the NAc (Lüscher & Malenka, 2011).	Dopamine promotes spine expansion & the formation of IPLs, contributing to the internal sensation of pleasure. Long exposure leads to IPL fusion, spine loss & result in dependency on cocaine to maintain a normal comfort level (Vadakkan, 2021).
Exposure to cocaine results in the attenuation of postsynaptic potentials in the MSN spines of the nucleus accumbens (NAc) (Beurrier & Malenka, 2002; Park et al., 2008).	Dopamine is known to induce expansion of spine that receive excitatory inputs (Yagishita et al., 2014). This expansion promotes spine's ability to form IPLs with spines that receive inhibitory inputs, altering the conformation of the semblance generating the internal sensation of pleasure (Vadakkan, 2021).
In response to natural rewards & cocaine exposure, a significant subset of MSNs in the NAc exhibit a depression in firing rate (Carelli, 2002; Ishikawa et al., 2009; Kourrich & Thomas, 2009).	As a result of the factors mentioned above, the reduction in postsynaptic potentials leads to a decrease in firing rate (Vadakkan, 2021).
Dopamine reduces the excitability of medium spiny neurons (MSNs) in the nucleus accumbens (NAc) in vitro (O'Donnell & Grace, 1996).	Dopamine enhances IPL formation between spines receiving excitatory & receiving inhibitory inputs. The net effect leads to the inhibition of excitatory input to the MSN (Vadakkan, 2021).
Synchronization of membrane potential states across a population of neurons in the NAc (Goto & O'Donnell, 2001).	Inhibitory interneurons are electrically coupled through gap junctions & generate oscillatory activity. IILSPs are also expected to contribute vector components to oscillating extracellular potentials. These oscillations play a critical role in binding the units of inner sensations (Vadakkan, 2021).
Camillo Golgi developed the Golgi staining method, which enabled the visualization of a network-like reticulum of neuronal cells in brain tissue. Ramón y Cajal later refined this technique, allowing for the visualization of individual neurons. Golgi expressed controversial views (PDF), disputing Cajal’s interpretation that the modified staining revealed discrete, individual neurons.	Golgi used a single oxidizing agent to pre-treat brain tissue prior to staining, while Cajal introduced an additional oxidizing agent during the same step. This suggests that a higher oxidation state limits the spread of the Golgi staining reaction across neurons, likely by blocking certain inter-neuronal channels. Notably, blood oxygenation level-dependent (BOLD) signals have been observed to peak in specific brain regions approximately 3 to 4 seconds after learning (Monti et al., 2010; Murayama et al., 2010), & most working memories tend to fade over time. These observations suggest that oxygen likely play a role in reversing learning-induced channels. These match with the properties of IPLs (Vadakkan, 2022).
The formation of new granule neurons in the hippocampus, known as adult hippocampal neurogenesis has a critical role in cognitive functions.	With insertion of granule neurons, repeated instances of the same associative learning leads to formation of new sparse IPLs at higher neuronal levels (Vadakkan, 2011).
Learning entails a dynamic interplay between the loss of existing dendritic spines & the formation of new ones, reflecting the neural changes required to accommodate additional learning-associated modifications (Frank et al., 2018).	Formation of new spines likely increases the number of IPLs to accommodate the need for enhanced units of inner sensations. Spine loss can be triggered by specific computational demands.
Permanent changes in the motor response to a single stimulus, resulting from repeated exposure to that stimulus, are known as non-associative forms of learning.	Any environmental stimulus is a high-dimensional sensory input, composed of multiple newly associated components that can lead to the formation of IPLs. Hence, repeated exposures to a single stimulus repeatedly reactivate same set of IPLs & stabilize them. The stimulus must propagate through newly incorporated granule neurons in the circuit, which results in the formation of new IPLs at higher neuronal levels. As the learning experience is repeated, the number of IPLs increases & they become stabilized, leading to permanent changes in the motor response to a stimulus.
The standard model of dendritic spike generation during natural sensory stimuli (Smith et al., 2013) assumes that natural stimuli can produce the near-simultaneous activation of dozens of synapses on a single dendritic branch of a neuron. However, in vivo functional imaging studies demonstrate that sensory stimuli drive sparse, scattered synaptic activity across the dendritic arbor, not dense branch-specific clusters (Jia et al., 2010; Iacaruso et al., 2017). This distributed pattern of activation is a consequence of the underlying synaptic connectome, where axons from a common source make sparse, randomly distributed connections onto a target neuron's dendrites (Kasthuri et al., 2015). Therefore, the biophysical requirement of dense co-activation of ~40 synapses within a short dendritic segment for generating an NMDA spike is not yet observed under natural sensory driving.	Sparse natural inputs likely give only one or a few inputs to an IILSPs. One EPSP can increase the spine RMP by ~5–20 mV. Background oscillating potentials likely provide some potentials to some of the inter-LINKed spines within the IILSPs. a) These depolarizations propagate through low-resistance electrical connections between spines of the IILSPs. When they get summated to change RMP to -30 mV, it rapidly unblocks the Mg²⁺ block on the entire population of NMDA receptors within the IILSPs. The resulting massive, synchronous inward current through these NMDA receptors is measured as an "NMDA spike" in the recorded dendritic branch. If there is/are spines that directly receive inputs from that sensory stimulus, their coincident activation will also contribute. b) The parallelly positioned spine necks (resistance in parallel) of inter-LINKed spines within an IILSPs will contribute only very less net spine neck resistance. This will lead to very large current needed to rapidly charge dendritic capacitance on the dendritic segment to produce a full NMDA spike.
Hippocampal neurons fire when an animal reach a specific place. They also fire during different extra-spatial cognitive functions such as motion trajectory (Frank et al., 2000), localization & memory retrieval in different contexts (Pastalkova et al., 2008), response to reward (Gauthier & Tank, 2018), response to auditory frequency in cognitive tasks (Aronov et al., 2017), formation of visual map (Killian et al., 2012), mental navigation (Neupane et al., 2024), organization of conceptual knowledge (Constantinescu et al., 2016), & abstract learning (Schuck & Niv, 2019; Park et al., 2020). Visual images lead to firing of sparsely located hippocampal neurons (Waydo et al., 2006). In other words, hippocampal neurons fire during different tasks independent of each other (Samborska et al., 2022, Tang et al., 2023, Courellis et al., 2024).	IPLs inter-LINKing spines on different dendritic branches – often of distinct CA1 neurons – offer a mechanism for these phenomena. A pyramidal cell fires when its membrane potential crosses threshold. There is extreme degeneracy of input signals in firing a neuron (Vadakkan, 2018). Potentials propagated through IPLs can allow a subthreshold CA1 neuron to cross the threshold and cause its firing. Hence, a CA1 neuron can fire during many unrelated cognitive functions.
CA1 pyramidal‐cell firing corresponds to the animal’s self‐position. Within each cycle of the hippocampal theta oscillation (as seen in extracellular recordings), the sequence of spikes encodes the trajectory. Moreover, place cells generate a positional signal that sweeps linearly outward from the animal’s current location into the surrounding space. Notably, the direction of these sweep alternates in a stereotyped left–right pattern across successive theta cycles (Vollan et al., 2025).	Detailed, explanation on this site’s "Evidence" page. It explains a) how a specific subset of CA1 neurons fires at a given location, b) the first-person spatial experience of that location, c) the vector components that shape theta waveforms, d) the emergence of theta sweeps, and e) why certain neurons fire before the animal arrives –producing “predictive firing sequences.” A waveform‐formation mechanism – observed during extracellular recordings – is linked to CA1 neurons firing across successive theta cycles.
Using simulation studies, when state spaces are constructed from existing building blocks, hippocampal responses could be interpreted as compositional memories that bind these elements together. This allows the system to represent knowledge that has not been directly learned. When a landmark was shifted, CA1 firing fields in response to the new landmark also shifted to a new firing field, maintaining the same vector relative to the new location (Bakermans et al., 2025).	These findings point to the existence of compositional memories – memories constructed from discrete memory units – & to a mechanism linked to CA1 neuronal firing. IPL mechanism & contribution of potentials from inter-LINKed spines to the postsynaptic neurons that integrate the system’s unitary operations with place fields is a universal mechanism that can be shifted. Hence, when a landmark is moved, the place fields shift by the same vector to the new location.
Both consolidation of long-term memory (Flexner et al., 1967; Davis & Squire, 1984) & late-phase long-term potentiation (LTP) in in vitro slices (Krug et al., 1984; Huang et al., 1996) are dependent on protein synthesis. However, after exposure to a protein synthesis inhibitor in consolidated memory engram cells, direct optogenetic activation of these cells still retained the ability to retrieve specific memories (Ryan et al., 2015).	Learning is hypothesized to generate IPLs between the spines of different output engram neurons. The results of the experiment by Ryan et al., (2015) suggest that if IPLs are the mechanism of learning, then they must be non-protein synthesis dependent. Inter-neuronal inter-spine membrane interactions during learning is not protein synthesis dependent during the formation of IPLs.
Fear learning generates local connectivity between lateral amygdala (LA) neurons (Abatis et al., 2024). Electrophysiological studies have shown that stimulation of a single LA neuron induces depolarization in a small subset of neighboring LA neurons.	Stimulation of a single LA neuron cause backpropagation of potentials along its dendritic branches towards spines, which propagates through the IPLs to the postsynaptic neurons of the inter-LINKed spines. When these LA neurons of the same neuronal order cross their thresholds, they fire.
Fear conditioning is associated with enlarged synapses on the dendritic spines of LA neurons (Ostroff et al., 2010; Choi et al., 2021).	Enlargement of spines can enhance IPL formation by displacing the hydration layer between the membranes of the spines.
Synapses on the dendritic spines of LA neurons exhibit a higher ratio of postsynaptic density (PSD) area relative to that of presynaptic structures (Ostroff et al., 2012).	IPLs are expected to form between the lateral regions of dendritic spines, aligning with findings that vesicle exocytosis involved in AMPA receptor insertion also occurs at these lateral spine regions (Rácz et al., 2004; Makino & Malinow, 2009; Jacob & Weinberg, 2015).
Astrocytic pedicels cover nearly less than 50% of the perisynaptic area in approximately 60% of synapses within the CA1 region of the hippocampus (Ventura & Harris, 1999). Synapses devoid of astrocytic coverage emerge in the amygdala during the consolidation of Pavlovian threat conditioning (Ostroff et al., 2014).	Removal of astrocytic pedicels increases the abutted surface area between neighboring spines, which in turn may enhance the number of IPLs that a single spine can form. This can increase efficiency in fear learning & provides indirect support for the role of IPLs in both learning & their maintenance during memory consolidation.
A disconnect between dendritic depolarization & neuronal firing has been observed during fear conditioning (d’Aquin et al., 2022).	IPL mechanism occurs between abutted spines that primarily belonging to different neurons. The potentials from an inter-LINKed spine may not reach the soma. This can explain the dichotomy between the operational mechanisms at the dendritic level & neuronal firing.
Contextual fear conditioning recruits newly synthesized GluA1-containing AMPA receptors into the spines of hippocampal memory-ensemble cells in a learning-specific manner (Matsuo et al., 2008).	GluA1-containing AMPA receptors (AMPARs) are located approximately 25 nm from the synaptic margins (Jacob & Weinberg, 2015). This aligns with the lateral spine head region, where IPLs are expected to form. Insertion of vesicle membrane segments into the lateral spine head region can facilitate IPL formation.
Autophagy leads to memory destabilization & the erasure of auditory fear memories, a process associated with AMPAR endocytosis (Shehata et al., 2018).	GluA2-dependent AMPAR endocytosis is a prerequisite for autophagy to induce memory destabilization (Shehata et al., 2018). Endocytosis removes membrane segments from the spine head region cause reversal of existing IPLs & cause memory loss.
Circuits with identical synaptic connectivity can function differently (Mardar, 2012).	IPLs propagate additional potentials through certain synapses, making circuits with identical synaptic connectivity to function differently.
Neither the synaptic connectivity of the neuronal circuit nor the computational task performed by the synaptically connected neurons alone can uniquely determine the mechanism of circuit function (Biswas & Fitzgerald, 2022).	The function of IPLs, which can operate in unison with the synaptically connected neuronal circuitry can explain how the system operates to generate both first-person property & behavioral motor actions.
The firing of the same individual neurons in the prefrontal cortex prior to speaking identical phonetic words, such as 'sea' & 'see.' (Khanna et al., 2024).	IILSPs serves as a suitable candidate mechanism to explain how a query navigates through prior relational patterns within a given context to generate first-person meaning, followed by motor output using appropriate phonemes to effectively convey the message to others (Vadakkan, 2024).
When mice were injected with a histone acetyltransferase (HAT) enzyme to enhance transcription, the strength of their fear memory increased (Santoni et al., 2024). The study also found that a) neurons in which HAT is overexpressed are the neurons that fire during memory retrieval, & b) optogenetic silencing of these specific set of neurons prevents fear memory recall.	HAT removes histones from DNA increasing transcription of proteins necessary to synthesize phospholipids that promotes exocytosis & facilitates IPL formation of its spines. Silencing the neurons will prevent motor output functions necessary for fear expression.
Firing of LA neurons becomes more synchronized through modulation of theta frequency within the LA (Pare´ & Collins, 2000). Synchronous oscillations in the theta & gamma bands are observed between the basolateral amygdala (BLA) & interconnected brain regions during the retrieval & consolidation of fear memories (Bauer et al.,2004; Seidenbecher et al., 2003).	Reactivation of IPLs within the IILSPs on the dendrites of LA neurons contributes vector components to the oscillations, which in turn integrate units of semblances for fear. This integration of both vector components and units of inner sensations is expected to be a system-wide process involving different brain regions.
Memory retrieval induces synchronized rhythmic activity between basolateral amygdala (BLA) & interconnected brain structures, accompanied by the reactivation of certain sets of neurons that are called fear engram neurons (Bocchio et al., 2017).	IPL mechanism provides vector components to the oscillating potentials. When these vector components contribute potentials to subthreshold activated LA neurons, they fire - making them engram neurons.
Artificial stimulation of neurons within the nervous system can evoke various types of hallucinations (Selimbeyoglu & Parvizi, 2010). Electrical stimulation of the medial temporal lobe elicits vivid autobiographical memories (Vignal et al., 2007). It implies that the stimulated neurons serve as an intermediate pathway between sensory input & the mechanism underlying perception.	Stimulation of an intermediate pathway is sufficient to reactivate both sides of an IPL in the sensory cortices for perception to take place (Vadakkan, 2015). This is similar to the explanation for phosphenes when a close eye is slightly compressed from the lateral aspect in a dark room (Vadakkan, 2015).
Auditory hallucinations are a common symptom of schizophrenia. These hallucinations are first-person inner sensations of meaningful sound in the absence of corresponding external auditory stimuli.	Auditory perception occurs when IPLs are generated in the auditory cortex & are activated on both sides (Vadakkan, 2015). When pathological non-specific IPLs are formed between spines in auditory cortex, then a natural auditory stimuli may reactivate them or they get reactivated autonomously during normal oscillations of potentials resulting in pathological hallucinations (Vadakkan, 2010).
Spontaneous activity of dopaminergic neurons in the ventral tegmental area (VTA) has been linked to the emergence of psychotic symptoms (Liddle et al., 2000; Lodge et al., 2007). Also, hyperactivity of the striatal dopamine system is associated with schizophrenia (Brunelin et al., 2013).	Dopamine is known to cause spine expansion (Yagishita et al., 2014). Hence, hyperdopaminergic conditions can promote the formation of non-specific IPLs, potentially resulting in hallucinations & cognitive impairments.
Neuronal oscillations undergo alterations in schizophrenia (Uhlhaas & Singer, 2010).	Non-specific IPLs can induce changes in oscillatory activity of their postsynaptic neurons (Vadakkan, 2010).
Altered consciousness in schizophrenia (Tononi & Edelman, 2000; Berkovitch et al., 2017).	Presence of non-specific IPLs leads to altered semblance generation causing hallucinations. These non-specific IPLs are also responsible for altering the conformation of C-semblance.
Dopamine antagonists are a primary class of medications used to treat schizophrenia.	Dopamine can facilitate the formation of non-specific IPLs exacerbating symptoms. Dopamine antagonists, in contrast, counteract this effect, helping to alleviate the symptoms.
Schizophrenia is characterized by impaired working memory performance (Goldman-Rakic, 1994).	Non-specific IPLs will reduce the specificity of retrieved memories.
Abnormally low gamma power during working memory is seen in schizophrenia (Woo et al., 2010; Uhlhaas & Singer, 2013).	Non-specific IPLs will reduce the specificity of retrieved memories. They also convert structured, phase-locked microcircuit oscillations into spatially diffuse, temporally jittered activity, which manifests as reduced gamma power despite ongoing neural activity.