To Unfold The Secret of Protein Folding, Foldit!

Genes in living cells dictate the cellular machinery to form proteins, the ultimate product of genetic information that is encoded in the DNA. These proteins perform various functions in the body. Some maintain the structure of the cells, some act as enzymes thereby catalyzing reactions, some act as pumps and ion channels thus maintaining ionic equilibrium and events like muscle contraction and action potentials in neurons, some act as receptors which recognizes ligands and binds them and so on.

However, genes merely determine the sequence of amino acids in the protein. These amino acids form the primary structure of proteins by joining themselves by peptide bonds, just as different colored beads make up a string. Some amino acids in the protein undergo post-translational modification such as carboxyllation, phosphorylation, once the primary structure has been determined. Then the protein folds in such a way that it is most stable in the tissue conditions like pH etc. Indeed, living tissues try to make order (stable protein configuration) out of seeming disorder (random amino acids) in an apparent violation of the second law of thermodynamics.

Folding also saves valuable space. But why and how should the protein fold? There are interactions between amino acid residues in the form of covalent bonding such as disulfide bonds; non covalent interactions like hydrogen bonding (between hydrogen and oxygen atoms in the peptide backbone), electrostatic or salt bonds between oppositely charged residues, and hydrophobic interactions whereby hydrophobic (water hating) portions of the molecule stay away from water. So, the protein folds to a conformation where the conflict is kept to a minimum. X-ray crystallography, NMR spectroscopy, computational biology and atomic force microscopy are useful tools in elucidating protein structure. Although the way it folds has been simulated in the computer, having humans do it as a computer game and then trying to figure out how the computer did so is surely worth trying. That’s where Foldit comes in.

I first knew of Foldit about a week ago in the print version of the August edition of HHMI Bulletin. After a user downloads the program and installs it, he can see proteins as multicolored structures. All he has to do is to grab the mouse, then pull, twist and wiggle the structure so that it has the most optimal position using the mouse. The program will give you a hint should the atoms be too close or if the hydrophobic ends are sticking out. The program relies on the pattern recognition ability and visuospatial scratchpad (of the working memory) of individuals. Intuition plays a big role and thus scientists may not be much good at this game. The ABCs of Foldit are Apart(sidechains), Buried (hydrophobic domains) and Compact (protein).Users could also play online so that their scores were kept on the servers, and collaborated with each other evolving the game further (Online Darwinism?) Persons having exceptional folding solving abilities are aptly called 'foldit savants', possibly deriving its name from 'idiot savants', persons belonging to the autism spectrum but having extraordinary abilities in certain subjects like mathematics. Albert Einstein was thought to be autistic.

Previously I have used Wolfram’s Mathematica and NanoCAD written by my friend Will Ware. NanoCAD is indeed an outstanding tool, given that it was programmed more than 10 years ago. The basics of NanoCAD and Foldit look rather similar to me, only the complexity and online participation is differing.

Anyway, you always win because you are playing for a cause. A definite and stable protein structure prediction might help researchers the right antibody, the right vaccine, develop better drugs with little side effects and so on. Who knows if this paves the way for the treatment of Alzheimer’s disease, cancer or AIDS?

Since this game exploits intuition rather than intellect, we could perhaps also measure hemisphere dominance in the participants. The effects of psychotropic drugs on game performance could also perhaps be measured.

As of me, I could not play above a certain level. My CPU usage, as shown in the task manager was 100%.
P.S. I still use a Celeron 1.2 GHz CPU and have only 256 MB SD RAM. I could not connect with the server as well.

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Reference: hyper-links, unless specifically mentioned

Capturing Thought, in Real Time

Wouldn't it be nice if we mapped how the thought processes traveled across our brain, in real time? That's exactly what Mazahir Hasan et al of Max Planck Institute for Medical Research in Heidelberg, have enabled us to view, when an action potential (AP) is underway in the central nervous system (CNS). The researchers introduced fluorescent calcium indicator proteins (FCIP) into the brain cells of mice by means of viral gene vectors. Each time an AP was underway, a lot of ionic phenomena happened. For example, the fast Sodium channels (Na+) opened (letting positive charges to the interior of the cell) leading to depolarization, Potassium (K+) channels opened (to bring back the resting membrane potential to normal, since K+ egress out of the cells) and so on.

Next , the impulse is transmitted to the post-synaptic neuron through the agency of neurotransmitters. But, for this 'coupling' between the presynaptic and postsynaptic neurons to occur; Calcium ion (Ca++) levels in the synaptic knobs of the presynaptic neurons must rise for effective degranulation of the presynaptic vesicles. And that's precisely these researchers were banking upon.

Just before the degranulation of synaptic vesicles begins; calcium ion concentration surges. Such short calcium currents peak within milliseconds, making them the appropriate ions for studying fast neuronal activity. Previously scientists had measured such currents by using microelectrodes implanted within the brain; but this method was quite unsuitable in studying moving animals or for a longer time period. So, they went on to produce stable transgenic mouse lines responding to functional calcium indicators; (including 'inverse pericam' and 'camgaroo-2') using viral vectors. These transgenic mouse lines were under TET inducible promoter (tetracycline, a broad-spectrum antibiotic) control. The TET system offered the advantage of targeting combination of different neuronal cell assemblies. The other side of the Ptetbi (bidirectional promoter tetracycline) promoter was attached to the firefly luciferase gene. They were also sensitive to doxicline (another antibiotic belonging to the same category as tetracycline) in terms of regulation of luciferase, as well.

They then used a heteromeric sensor protein called D3cpv, which was made to produce in the nerve cells of the transgenic mice. Two subunits of this protein reacted to the binding of calcium ions in a way that when the yellow-fluorescent protein (YFP) lit up and the cyan-fluorescent protein (CFP) intensity diminished. When calcium was bound to the D3cpv complex; CFP (cyan fluorescent protein) and YFP (yellow fluorescent protein) came closer together bringing about FRET, in such a way that there was a visible color change, 'visually' or optically indicating the progression of action potential in real time. CFP and YFP are spectral variants of GFP linked together by a Ca++ sensitive linker.

They used 'two-photon imaging microscopy' to study this phenomenon. They excited thinned out rat skulls using two-photons simultaneously using 'mode-locked' Titanium-sapphire laser. They then amplified the signal using photomultipliers and analyzed them.

The resolution of the experiment was limited to less than 1 Hz (frequency of action potentials). They conferred that human thought processes might be mapped in much the same 'opto-physiologic way', in contrast to the usual electrophysiologic approach. Not only does the experiment throw light on the thought processes in real-time, but also, it is expected that it will be useful in the pathophysiology and treatment of Alzheimer's disease, Parkinson's disease and Huntington's chorea.

FCIP-positive cells were found in the hippocampal CA1 and CA3 regions, mossy fiber areas of the dentate gyrus, neocortical pyramidal cells and olfactory receptor neurons, they remarked. They studied cortical pyramidal cell, olfactory and optical responses in the mice in their experiment.

Hasan, M., Friedrich, R., Euler, T., Larkum, M., Giese, G., Both, M., Duebel, J., Waters, J., Bujard, H., Griesbeck, O., Tsien, R., Nagai, T., Miyawaki, A., & Denk, W. (2004). Functional Fluorescent Ca2+ Indicator Proteins in Transgenic Mice under TET Control PLoS Biology, 2 (6) DOI: 10.1371/journal.pbio.0020163
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Reference: Damian J Wallace, Stephan Meyer zum Alten Borgloh, Simone Astori, Ying Yang, Melanie Bausen, Sebastian Kügler, Amy E Palmer, Roger Y Tsien, Rolf Sprengel, Jason N D Kerr, Winfried Denk & Mazahir T Hasan. doi:10.1038/nmeth.1242

Brains of Guitarists in Unison Harmonize Too

During the 80's, I listened to heavy metal bands like Iron Maiden and Metallica, although I couldn't follow their lyrics always. What used to captivate me in awe was how the guitarists synchronized themselves together so well. It apparently seemed as if only one guitar was playing in the background, which on closer scrutiny revealed the actual truth: it was really a duet. It is only now that scientists are beginning to find the secret behind this 'time and phase synchrony'.

Scientists at the Max Planck Institute for Human Development in Berlin, have shown that musicians playing the same tune have their brains 'coupled' together. They started off experimenting with 8 such musician pairs. They first recorded the brain activity of each
'duetter' by taking their electroencephalographic recordings (EEG). The musicians kept the EEG set-up atop their heads throughout the experiment.

After taking the baseline EEG recordings, the researchers then made the guitarists to listen to metronome beats. Metronome beats are beats of sound that occur periodically and are used to keep track of time. They found that the EEG activities of the players were synchronized to that of the metronome beats. Next, the lead guitarist of the pair had to tap his guitar in a gesture to signal his partner as to when and at what speed they would begin. At this point, the researchers looked at the brainwaves of the guitarists again and found that the EEG of both the guitarists were in synchrony to each other (and no longer to the metronome beats). Curiously, this happened even before the actual performance began. This oscillatory synchronization was found to be especially stronger at the frontal and central electrode sites (of the EEG leads). This may indicate simultaneous firing of the motor and somatosensory neurons.

This experiment also throws light as to how empathy and the 'mirror neuron network' might be working. These inter-personally coordinated behaviors will only result if they happen fast and both the sensory and the motor actions are coordinated. Certainly, there has to be some kind of a feedback between the pair for effective harmonization to occur.

It has been previously seen that in addition to the EEG coupling; magnetoencephalography (MEG; measures the magnetic field around the skull) and electromyography (EMG: measures the muscle activity) related well between neuronal activity of a person to the voluntary activity of the same person. The new finding may help us probe the basis of social interaction but it also poses a question: how do the performers synchronize and through which media? You can find videos of duetting guitarists and the corresponding EEG recordings at Biomedcentral.

P.S. Finally, let me allow to propose 2 mechanisms which may be responsible for this apparent 'phase lock'. Firstly, the performers have a very clear idea about the piece they were about to perform, since they are well rehearsed. Naturally, the guitarists are in tune with the next intermezzo and if they were to strum chord C major, their corresponding motor planning areas would become active. It is known that the motor planning areas become electrically active even before the execution of actual action (1). Secondly, we can also assume that they, being emphatically coupled to the music, get connected across by mirror neurons. The mirror neuron system then does the rest: driving the players in a rapturous synchrony.


Lindenberger, U., Li, S., Gruber, W., & Müller, V. (2009). Brains swinging in concert: cortical phase synchronization while playing guitar BMC Neuroscience, 10 (1) DOI: 10.1186/1471-2202-10-22 Last modified: Jan 19, 2010
Reference:(1) William F. Ganong, Control of Posture & Movement, 22nd Ed, Review of Medical Physiology, Page: 202

The Circle Of Life And Soul

Before embarking on this arcane topic, let us talk about death first. Clinically, death is said to occur when the heart and the lungs stop working (cardio-respiratory failure). However, with the advent of modern life support systems (such as cardiopulmonary resuscitation, artificial ventilation), quite a few such 'dead' persons have been brought back to life. Legally, death is now defined as when the activities in the brain stop: brain death. The EEG signals may cease completely or fall to undetectably low levels. Body organs may be taken from the 'dead' person and transplanted onto a 'living' recipient. Certainly, death does not mean that all the body tissues and organs die at once. However, death is considered an 'all or none' process and is irreversible. That some tissues remain alive in a dead person, it may be assumed that some as yet unexplained binding energy that keeps track of the living system, is amiss.

If you worked with computers, you may have noticed that there's a 'registry' which keeps note of the hardwares, softwares and other machine configurations vital to the computer's health. These informations are kept in the form of a 'tree' and are referred to as 'hive keys' (e.g. HKLM, HKCU etc). Should anything go wrong in the registry, the computer won't work; its dead. The hard disk is OK, the RAM is fine, even the CPU is intact; but the computer is dead. A similar analogy may be drawn with the BIOS (basic input output system) flash memories of the computer.

Do we have anything like this in our bodies that coordinate functions among various tissues (separated at a distance)? Could it be something like covalent or electrostatic interaction or some form of quantum entanglement between the tissues that works in an analogous way the system registry in computers does? Perhaps, interactions like the one observed among microtubular assembly (interactions at 'hydrophobic pockets') might be involved in a broader scale.

Looking from a different perspective, living systems may be thought of as a combination of different compounds and elements. They can be broken down into molecules, which may again be divided into atoms--> the so called 'elementary particles' like electrons, protons and neutrons. These can again be broken down into quarks and gluons and finally into the 'vibrating strings' of string theory.

Thus the whole gamut of living and non-living things may be construed in terms of a vast network of vibrating strings. This reminds of 'cosmic consciousness' of Carl Jung. Living beings may 'tap' onto this 'server' network by some form of electromagnetic resonance or quantum phenomena (disregarding decoherence for the moment). Life stops when we are 'off resonance', as if we get a DNS server error 769 or destination unreachable. May be there is some self sustaining oscillation that runs amok and cause a kind of 'thermal runaway' and entropy rises unmanageably.

Honestly, any endeavor to delve deeper into the topic will be futile at this point. First, we are bound by our senses and interpret things in the light of our past experiences. Second, we are prone to introduce Heisenberg's uncertainty errors, the closer we get to it. The more accurately we determine the location of 'soul' (if there's any) the further off we are to notice its properties. Thirdly, you can't really judge the velocity (not speed!) of a moving bus from inside (and blindfolded). You need to look from the outside.

Persons with 'near death experiences' (out of body experiences) and those who have undergone dissociative anesthesia (using ketamine) have reportedly 'seen' their bodies from a different dimension. Finally, intuition and not intellect, should be invoked to address this delicate issue as the former's approach is holistic, while the latter breaks an event down into its component parts (in the light of present knowledge) and analyzes them (and thus inherently error prone).

May be the souls is indestructible; it just relocates into another 'braneworld' having a few more dimensions and hence hidden from our views. As long as we can not definitively answer what life is, we certainly can not hope to speculate on what 'spirit' or soul is. A few more interesting points to ponder upon: Does a pregnant woman have 2 souls? Do individual cells and molecules have their own soul equivalents?

Disclaimer: While the facts described are true (hyperlinks given), this article is mostly a speculative 'synthesis' of sorts and largely reflects my own view.
Related: Is Science Killing the Soul? by Richard Dawkins, Steven Pinker

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Reference: hyper-links, unless specifically mentioned

Quantum Biology: The Spooky NanoWorld of Molecules

We are quite adept in solving numerical problems in our everyday ‘analog world’ using decimal rules developed by us. Digital computers, on the other hand, calculate using binary or Boolean (0, 1) rules, and then convert the result in decimal format with the help of dedicated binary to decimal converter ICs. In the molecular world, calculations ‘happen’ in a strange way.

Take for example the case of Fluorescent Resonant Energy Transfer or FRET. Also known as Forster Resonant Energy Transfer, this phenomenon is characterized by the emission of a photon of one frequency (upon stimulation) which, in turn, activates an acceptor molecule to emit a photon of another wavelength. There’s one clause that says that the first photon (from the donor molecule) will only be emitted when it can definitively be coupled with the ‘acceptor’. But in the first place, how is this ‘virtual photon’ to know whether its bride was waiting or not when it hasn’t even visited her? Yet FRET doesn’t fret, and the process goes on.

All plants use chlorophyll to trap sunlight and convert it to chemical energy in the form of carbohydrates by photosynthesis. The efficiency approximates 100%. The predominant classical approach was that the photons hopped from light capturing pigment biomolecules to the ultimate reaction center where the actual conversion was taking place. But this ‘first choose and then pick’ approach that classical physics suggested would mean considerable loss of energy as heat, as photons wasted time as they hopped down the energy ladder. Quantum mechanics bypassed this by allowing simultaneous sampling of all energy states at one go by its unique properties of ‘superposition’ and ‘entanglement’. Graham Fleming and researchers at Lawrence Berkeley National Laboratory and the University of California at Berkeley showed the existence of a process of ‘quantum beating’, (a phenomenon akin to 'heterodyning’ in radio sets that is used to obtain intermediate frequencies for amplification) occurred which allowed sampling of all energy states by interference of the propagating wave. They used two-dimensional electronic spectroscopy in order to probe the sequence of events that occurred.

That the RBCs (erythrocytes), actomyosin complexes use quantum mechanics for system optimization has been established. Cellular respiration in the mitochondria, DNA, and the brain too might exploit quantum computing.

Counting without disturbing the molecule may be achieved by quantum mechanics, for it allows a molecule to know as if ‘intuitively’, the state of another molecule placed at a distance. Erwin Schrödinger, in his book 'What is Life?', opined that biological systems could be using the principles of quantum theory to maintain biological order. Sir Roger Penrose along with Stuart Hamerhoff proposed that the brain could be working as a quantum computer. In reaction to this, Max Tegmark showed that environmentally induced decoherence would foil any quantum interaction taking place. But Tegmark assumed the average kinetic energy (temperature) of the brain as 310 K (273+37). While this is true in a macroscopic world, Koichiro Matsuno has shown, using black body radiation measurements, that actomyosin complexes which are abundant in the axons of nerve cells, can reach local temperatures as low as 1.6*10-3K. It is as if nature has evolved ways to ensure decoherence free subspaces where entanglement and quantum interaction were possible. Stephen Hawking in his book 'A Brief History of Time' observed that quantum mechanics was the basis of modern biology and chemistry and the only area where quantum mechanics was not properly integrated were gravity and the large-scale structure of the universe (page 60).

To quote Ogryzko "Indeed, if it has taken Humankind only few decades to approach the use of entanglement in quantum information technology, one can wonder why Life, in billions of years of evolution, could not also learn to take advantage, finding in entanglement an alternative resource for stabilizing biological order." It seems we need an entirely different approach if we wanted to probe the mysteries of life and quantum theory is poised to help us in this regard.

P.S. I am glad that the prestigious multidisciplinary journal "NeuroQuantology" published this article with the title "The Spooky NanoWorld of Molecules" and archived it in their "arNQ Eprints and Repository". I thought I could share this with you, my readers!

Last modified: Jun 29, 2010
References:
Quantum Biology
Vasily V Ogryzko (2008). Erwin Schroedinger, Francis Crick and epigenetic stability Biology Direct, 3 (1) DOI: 10.1186/1745-6150-3-15

Period Concatenation in The Brain, And The Synthesis of Beta 1 Rhythm

The principles of generation of EEG waves in the brain are still ill understood. Although the general mechanism of cortical dipoles and thalamocortical oscillations behind the generation holds true; there has been speculations that the alpha waves could actually be originating in the heart- the cardiac electromechanical hypothesis, which states that the arterial pulse ‘shocks’ the skull-brain mass (and interacts electrically and mechanically) to oscillate at its naturally resonant frequency of approximately 10 Hz.

Now, Kramer et al propose that beta 1 rhythm could be the result of a process called period concatenation (concatenation means chain forming or serial addition). Beta rhythms (18-30 Hz) were thought to be harmonics (integer multiples of the fundamental frequency) of alpha rhythms (8-12 Hz). Kramer et al observed that application of 400 nanomolar kainate to rat somatosensory cortex produced gamma rhythm in the superficial cortical layers and beta2 rhythms in the deep cortical layers.

They observed that after an initial interval of simultaneous gamma (~25 ms period) and beta2 (~40 ms period) rhythms in the superficial and deep cortical layers respectively, a resultant, synchronous beta1 (~65 ms period) rhythm in all cortical layers occurred. They concluded that the time period (the inverse of frequency, or 1/f) of gamma wave (25ms) concatenated with that of beta2 (40ms), to form the time period of 65 ms (40+25). That was the time period of the beta1 rhythm, which resulted as a consequence of this concatenation. They concluded that neural activity in the superficial and deep cortical layers of the brain could combine over time to generate a slower oscillation.

Frequency synthesis would, naturally, have both energy and space saving implications for the system concerned. That the brain economizes is not new in computational biology and electronics. For example, in the simplest and realistic model of the 40 Hz gamma rhythm, only 2 neurons (one excitatory and the other inhibitory) interconnected by reciprocal paths are required. The excitatory neuron will ‘charge’ the inhibitory neuron. The inhibitory neuron will suppress (inhibit) the activity of the excitatory neuron as a result, and any oscillation will be dampened. Hence, a decay in the inhibitory synapse will not inhibit the excitatory neuron anymore and thus cause oscillation; and clearly, the frequency of rhythm will depend on the decay time. This “gamma-motif” resembles a lot with the ‘flip-flop’ circuits in digital electronics.

Its not surprising that the human brain which had evolved as a result of nature’s selection process will learn to compute things so that the metabolic costs of additional neural pacemakers were curtailed to the bare minimum.

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References: Mark A. Kramer, Anita K. Roopun, Lucy M. Carracedo, Roger D. Traub, Miles A. Whittington, Nancy J. Kopell (2008). Rhythm Generation through Period Concatenation in Rat Somatosensory Cortex PLoS Computational Biology, 4 (9) DOI: 10.1371/journal.pcbi.1000169

A Cardiac Hypothesis for the Origin of EEG Alpha
Castillo, Horace T.
Digital Object Identifier: 10.1109/TBME.1983.325080

Molecular Basis of Genetic Switch In The Circadian Clock

It is said that the early bird gets the worm. So what is it that makes them rise early? Scientists have questioned it for long. It was in 1995, David Welsh, then a graduate student, discovered that individual cells dissected out from the 'suprachiasmatic nucleus' of rats' hypothalamus showed spontaneous oscillations. And this set the ball rolling!

All organisms from simple unicellular to humans have their own clock mechanisms. We for example, have not one but many oscillators. The master clock that oversees all the other clocks is located in a part of the brain called hypothalamus, the suprachiasmatic Nucleus or SCN for short. The clock circuit is based on transcription and translation of a genetic switch that resides in the SCN. In the nucleus, a gene, called the Per1 gene,  produces a protein called PER (for period). Like other proteins, its production is regulated by a promoter sequence of DNA, which is known as E-box. A heterodimer (dimer because it consists of two molecules; hetero because the molecular weights/size is different) consisting of proteins BMAL1 (also known as MOP 3) and CLOCK sit atop the E-box sequence. Together they regulate the Per1 gene (other clock genes like AVP or arginine-vasopressin genes are also regulated)  resulting in the production of PER1 protein. So, in a way the E-box may be considered as the genetic switch and the heterodimer of BMAL1 and CLOCK the regulator.

Lets suppose that Per1 gene is producing PER1 protein. So, the concentration of this protein in the cytoplasm will rise. This PER1 protein will now combine with other clock proteins namely, PER2 protein, CRY 1 and 2 proteins (CRY for cryptochrome) in the cytoplasm; and will finally reach the nucleus. In the nucleus, they inhibit the Bmal1 and Clock heterodimer transcription factor, which will lead to a drop in PER production. Thus, the positive feedback of BMAL1 and CLOCK on Per1 gene; and negative feedback of PER and CRY protein on the BMAL1 and CLOCK heterodimer keep the clock running. See the adjoining figure. Other proteins like TIM (timeless) and CK1e (casein kinase 1 epsilon; it degrades PER proteins) may also play some role. New research however suggests that CRY proteins, particularly CRY1 protein is a stronger repressor of the said heterodimer.

Research by Leloup et al showed that the mRNA of Bmal1 was in antiphase with that of Per and Cry. This was expected, because they are negatively correlated. Else both the proteins would peak at the same time and the periodicity would be lost. They also observed that the phase of the spontaneous circadian rhythm did not lock. This is because, circadian rhythm is very flexible. In humans, the cycle repeats about every 24.2 hours. The circadian clock is reset by light and our circadian apparatus is exquisitively sensitive to lights falling on the retina. The retina sends this light (for synchronization) to the SCN via the retino-hypothalamic tract. This synchronization or entrainment can now 'phase lock' the circadian rhythm.

Clinical implication of circadian (circa=about; dian=day) rhythm is enormous. Our sleep-wake cycle, growth hormone and cortisol secretion are only a few example. A person in whom the circadian period is short will rise early (early bird?) and a 'night owl' will have his/her circadian period short. Curiously, our sleepiness, tendency to sleep and occurrence of REM sleep peaks (resulting from endogenous circadian rhythm) when we are about to rise; and our endogenous clock reaches its peak about 1-3 hrs before our habitual bedtime. They say that it is a natural homeostatic mechanism, so that we fell less sleepy as daytime passes on and etc. But I not convinced.

But one thing I am sure to abide by is this that I won't deprive my SCN its daily dose of sunlight. I will also not expose myself to undue light (from computer monitor etc) at night and go to bed at a reasonably fixed time. Fiddling with these may result in insomnia or excessive somnolence as in night shift workers and in jet lag (due to latitude/time-zone changes).


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Reference: BMC Molecular Biology 2008, 9:41 doi:10.1186/1471-2199-9-J.-C. Leloup (2003). Toward a detailed computational model for the mammalian circadian clock Proceedings of the National Academy of Sciences, 100 (12), 7051-7056 DOI: 10.1073/pnas.1132112100

Do We Really Forget? Fathoming The Esoteric Realms of Memory

“Smells like teen spirit”, but it could be true that we never really loose any memory in our lifetime. Our memories are stored in the synapses (junction, more specifically, gaps between adjoining neurons) as a function of synaptic strength, in the nerve cells like dendrites as proteins, and some other processes which mostly encompasses a chemical interaction. I am excluding memories such as T cell or B cell memories here; memory, here, will refer to neural ones that occur in the CNS.

We know that in dementias such as global multi infarct dementia, Alzheimer’s disease; there are diffuse losses of neurons and losses of cholinergic neurons in particular, respectively. In surgical cases of epilepsy or brain tumor, there are losses of neurons too. In these cases, memory loss may be irrecoverable, though cases are on record which points to shifting of those memories into some other safe havens. But what about the rest of the population? Does an established long term memory vanish completely?

Let’s consider some facts. The numbers of synapses and their strengths are finite, though both can change in response to stimuli. Even the number of neuron themselves can increase, contrary to the belief held earlier. Neuronal stem cell pool has been identified in the brain. Memories stored in the brain are finite too. Memories are inherently dynamic in nature. Even long term memory stored in the neocortex (medial temporal lobe, on the other hand, stores memories as a buffer, like a D RAM chip, a temporary storage) can change location, as much as transferring itself to the other hemisphere (intercortical transfer), when needed; via the optic chiasm and corpus callosum. So, we see that the number of synapses, though finite, can rise to the demand of an enhanced input from sensory cues which are finite too, leading to memories that can jump across their own allocated territories. A finite brain capacity (say C) can certainly contain a finite memory (say M) as long as C is greater than/ equal to M. Certain computer softwares even trespass this limit; a zip file of 2 MB may deliver 3MB of contents on unzipping! Who knows if the brain isn't using this for the past thousand years.

Synapses, simplistically, may be thought of in binary terms: 1, when it is on; 0, when it is off. Both 1 and 0 is a bit in Boolean terms. We leave aside the synaptic strength part here for the sake of simplicity. In addition, memories may shuttle between synapses in such a way so that it is present in the brain, but not represented by any synapse. I will explain. We all have seen those jugglers juggling those colorful balls too many at a time using only their two hands. A similar thing like dipole dynamics may occur in the brain. Added to this is quantum superposition, which allows the situation of BOTH 1 and 0 state at the same time at the synapse. That the brain can be in a quantum state at the core body temperature and the brain can effectively avoid ‘decoherence’ in the background thermal noise has been discussed by Roger Penrose and Stuart Hameroff. We also know that memories aren’t kept as such, but they are fragmented into individual elements, which are mostly matched to existing elements and are associated. This is economic as it saves space, and useful for indexing and contextual retrieval.

Thus it seems that we ought to have immense memory storage. Haven’t we encountered long forgotten memories in our dreams? Electrical stimulations in some parts of the hippocampus (deep brain stimulation or DBS, figure shown) during routine surgical procedures have given rise to ‘deja vu’ phenomena. The patients remembered things considered long forgotten. We may not be aware of the vast database of memories and are liable to infer that we have “killed ‘em all”, but in reality this may not be the case as Norio Ota et al clearly points it out in their paper. It smells like another chapter from your favorite science fiction novel, but it could be true.

Last modified: never; N.B.There is a substantial amount of speculation in this paper. Please exercise your own judgment and enlighten me about any possible error.
Reference: hyper-links, unless specifically mentioned.

Scientists Simulate Learning In Amoeba Using Memristor

It is surprising how small insects get energy from a wide range of food (not merely petrol or diesel), crawl, fly, reproduce and do so many maneuvers. Now it has been seen that amoeba, a unicellular organism, can learn and memorize too. We are far from creating devices of such versatility, let alone making them as compact as they are.

Amoebae can move, and they do this by changing the physical state they are made of: sol-gel state. The interior of amoebae contains endoplasm, which is in sol state; while the surrounding ectoplasm remains in gel state. The ectoplasm, being in gel state, is more viscous than it’s inside counterpart. When the organism moves, its contractile elements made of actin myofilaments contract, pulling the inside of the amoeba. This causes tension in the endoplasm, creating a change in the sol-gel state. If you squeezed a sponge ball that had been dipped in water, you would notice that water would spurt out from the pores of the sponge. Likewise, the increased tension inside, will create channels through the more viscous ectoplasm, courtesy some parts of ectoplasm (gel state) giving away (to sol state).

We know that reptiles hibernate in winter, when the humidity and temperature is low (we too are no exception). Amoebae too, slow their locomotion in response to these conditions. There are inherent oscillations within the amoeba (alternate sol gel transformation, changes in ionic flux etc) which are continuously adjusted with external signals like temperature and humidity. We, complex multicellular organisms, too have our own master oscillator (circadian clock) in the suprachiasmatic nucleus, which also continuously adjusts by lights falling on the retina.

Yoshiki Kuramoto of Kyoto University and colleagues subjected Physarum polycephalum, an amoeba, to three regularly-spaced dips in temperature and humidity, and found that its locomotive activity decreased. Thereafter, they noticed that a single dip was sufficient to elicit this response. It seems they adjusted their oscillations to the external cue and developed a conditioning later. The study implied that the amoeba anticipated that other such dips might be forthcoming, from the memory it learned. Such response did not occur when the temperature and humidity changes were irregular.

Memory in this case occurs due to the persistence of the channels etched by the organism in the ectoplasm. But this ‘memory’ did not persist for long, if we continued giving them a single dip instead of a regular triplet. This plasticity (change due to reorganization as a function of a stimulus) in amoeba has now been simulated with the aid of electronics by Massimiliano Di Ventra et al.

They used a capacitor, a resistor, an inductor in series and connected a ‘memristor’ in parallel with the capacitor. Memristors (for memory resistors) are devices which consist of two layers of titanium dioxide (often present in medicine coatings and chewing gums). When current is applied to one layer, the resistance of the other changes. Leon Chua, of the University of California at Berkeley, predicted it long time ago; and now R. Stanley Williams and colleagues at Hewlett Packard have developed it. It can store memory like DRAM, but unlike DRAM it doesn’t forget when a current is no longer flowing. They hold promise as energy efficient chip for computers and we can also expect faster ‘booting’ of computers, since memory will already have been stored there. The adjoining figure shows ‘memristors’ in a row, as seen by atomic force microscopy (AFM).

Now when a current, fluctuating (AC) in a non periodical manner or a stable DC, was made to pass through the circuit, the memristor went to a low resistance state, virtually short circuiting and dampening the oscillation. However, with a regularly fluctuating current, whose frequency matched the resonant frequency of the circuit, the memristor went into a high resistance state, strengthening the oscillation. What connects electronics to amoeba is the memory that both the circuit retain. The memory of memristor, called memristance, is due to atomic rearrangement in the device. The high resistance state lingers for quite some time, so that next time one single pulse was necessary to put it into oscillation. This phenomenon is quite akin to the protozoal response.

It seems that those days are certainly not far when we will just need to jack-up a USB device in our head to boost up our memory.

Last modified: Nov 13, 2008
Reference: http://arxiv.org/abs/0810.4179?context=q-bio Tetsu Saigusa, Yoshiki Kuramoto (2008). Amoebae Anticipate Periodic Events Physical Review Letters, 100 (1) DOI: 10.1103/PhysRevLett.100.018101