Rate Codes and Synchrony

Your body is electrical. Each cell has a system of ion pumps that tightly regulate the trans-membrane passage of potassium, sodium, calcium, and chloride whose concentrations affect the voltage within the cell. The nervous system has evolved the ability to transmit pulses of electrical activity called “action potentials” for rapid communication over distances from millimeters up to meters.

(Brown, S.L., Joseph, J. & Stopfer, M.Nature Neuroscience 8, 1568 – 1576)

The figure above has several examples of voltage recordings from single neurons; those are the black, noisy traces. In each of them, there are many “spikes,” the large vertical deflections which simply look like line segments. These are Action Potentials. Up close, APs look like this:

They have a highly sterotyped form reflective of the underlying generative mechanism. The work of Edgar Adrian made it clear that Action Potentials are the universal signal I’ve pronounced them to be. It was he who demonstrated that APs are used by the brain for both outward bound signals to muscles, and inward ones from sensory apparati. However, since this time, understanding exactly how information is encoded in these Action Potentials has been the source of great debate.

Each neuron has a baseline level of activity, an average firing rate, or number of spikes per second (between 5-100 spikes/second is the physiologically relevant range). An elevated frequency (more per-second) of APs to a muscle means greater contraction, more action potentials also signals warmer temperatures when coming from the appropriate sensor. Both of these are examples of Rate Codes. That is to say that the relevant part of the code is how often the pulses arrive. However, this is not the whole story.

Many researchers have noticed that ensembles of constituitively excited neurons have a tendency to fire their spikes simultaneously. The degree of coincident firing by a pair of neurons can be quantified by a measure called covariance. This synchrony has been implicated in everything from working memory to attention; from perceptual grouping (our tendency to compartmentalize objects as individual wholes out of the continuity of sensory experiences) to consciousness itself.

That synchronous firing happens at all is no great surprise as there is a large degree of correlation in sensory data. If I throw a red ball across your field of vision, for instance, it is highly likely that the report of red by individual neurons in your brain will happen at the same time as they are being stimulated at the same time; there is high temporal correlation in the many sensory inputs to the brain. The idea that synchrony might be at work in settings lacking such obvious sources of correlation, is intriguing.

These two ideas, rate codes and synchrony, represent major branches on the tree of theoretical efforts to describe information encoding at a basic level in the brain. A recent paper from the lab of Alex Reyes at NYU’s Center for Neural Science, has given those interested in such endeavors something new to keep their gears turning (ref. 1).

The authors of this letter to Nature describe a series of experiments in which they measure the degree of synchrony in the outputs of a pair of neurons which are not connected to each-other. The experimental variable they manipulate is input correlation. Each neuron receives an input signal which is made partly from a joint source and partly from some other, random signal. In this way, they can control the amount of commonality in the signal that each neuron receives. It is no surprise that as the correlation in the two inputs is increased, so too is the output correlation. What is surprising is that if one leaves the correlation between the inputs constant and increases their overall amplitude, the correlation in the output again increases.

This is a strange state of affairs because, as I said, the signal is made of two parts: one is the bit that is common to both inputs, lets call that A, the other is unique to each neuron, lets call those B & C respectively. This means that neuron 1 receives a signal = A+B; while neuron 2 receives a signal = A+C. If we simply increase the amplitude of both signals by some factor, D (S1 = D*(A+B), S2 = D*(A+C)), then both parts of the signal are scaled up. A, which would tend to produce correlated outputs, and B & C which would tend to produce random, uncorrelated output. This means that there is something intrinsic to the transformation that neurons perform between their inputs and outputs, which somehow enhances input correlations.

The scaling of inputs mentioned above is tantamount to increasing the firing rate of the received signals. This means that the authors have found a link between Rate Coding and Synchrony. These two concepts, once distinct, have become linked.

The Letter progresses nicely, from modeling work done with artificial neurons, into a more biologically plausible setting combining single neurons with simulation, and finally to a more pared down mathematical exposition which seems to capture the essence of this phenomenon, namely the “threshold linear” transformation which neurons perform.

This is brave work, it makes clear how little we understand of the brain, how far we have to go. Several theorists have studied synchrony in the setting of artificially constructed networks, in vitro and in vivo (refs. 2,3,4,5). None, however, have achieved the kind of generality of this result. Understanding the underlying behavioral rules of single neurons is paramount to building a complete theoretical understanding of the mystery that is the brain. These authors have set an example of how we might move forward if we ask the right question in the right way.

References

1. Jaime de la Rocha, Brent Doiron, Eric Shea-Brown, Kres caronimir Josic & Alex Reyes (2007) Correlation between neural spike trains increases with firing rate Nature 448, 802-806 doi:10.1038/nature06028

2. Ritz R, Sejnowski TJ. (1997) Synchronous oscillatory activity in sensory systems: new vistas on mechanisms. Curr Opin Neurobiol. 7(4):536-46.

3. Vogels TP, Abbott LF. (2005) Signal propagation and logic gating in networks of integrate-and-fire neurons. J Neurosci. 25(46):10786-95.

4. Ikegaya Y, Aaron G, Cossart R, Aronov D, Lampl I, Ferster D, Yuste R. (2004) Synfire chains and cortical songs: temporal modules of cortical activity. Science 304(5670):559-64.

5. Mehring C, Hehl U, Kubo M, Diesmann M, Aertsen A. (2003) Activity dynamics and propagation of synchronous spiking in locally connected random networks. Biol Cybern. 88(5):395-408.

Language Acquisition

Apparently these things start to learn words at an accelerated rate around the two year mark. That is to say that they seem to abruptly begin to amass and employ a wide variety of words. This phenomenon is referred to as “vocabulary explosion.”

Convincing generalized theories of language acquisition have been around for around 30 years, the most successful of which is probably Noam Chomsky’s theory of Universal Grammar. But such theories do not attempt to describe the dynamics of communication mastery introduced above. That is one of the tasks of the ingenious minds at work on the subject today.

A recent submission to Science Magazine by the Psychologist Bob McMurray (ref. 1) attempts to computationally model the observed acceleration of the word uptake process. Although past explanations of this phenomenon have invoked specialized and well timed brain mechanisms, Dr. McMurray’s work attempts a more parsimonious description.

He concludes:

“Acceleration is guaranteed in any system in which (i) words are acquired in parallel, that is, the system builds representations for multiple words simultaneously, and (ii) the difficulty of learning words is distributed such that there are few words that can be acquired quickly and a greater number that take longer. This distribution of difficulty derives from many factors, including frequency, phonology, syntax, the child’s capabilities, and the contexts where words appear.”

He goes on to demonstrate that languages seem to display such a distribution of word difficulty, and to show that his model captures the accelerating behavior well.

The real beauty of the work however, is the posited inherent parallelism. Such ability in the human brain has long been suggested by a wide variety of scientists and philosophers. Indeed, I scarcely need use the word suggested, as we know that certain things happen in parallel, the processing of visual information, for instance, does not happen one pixel at a time but rather proceeds by working on the entire pattern of light that falls on the retina at once.

Dr. McMurray has thus figured out an elegant way to apply what should be thought of as a basic property of the brain to explain what seemed an exceedingly difficult problem, something everybody who works on complex systems hopes to be able to do.

1. McMurray B., (2007) Defusing the childhood vocabulary explosion.
Science 317 (5838):631.

The Look of Touch

Consciousness feels whole. That is to say that the various sensory experiences that our brains process in parallel feel like one coherent thing, our own individual consciousness. However, the electrical activity generated by different sensory experiences are largely segregated to different parts of the brain and it is possible to turn them off selectively. For instance, form and motion are represented by different parts of the visual cortex. By using a technique such as TCMS, it would be possible to eliminate sensations of motion in an image while retaining static vision. This would no doubt be a very strange state to be in. There are also many pathologies, induced by head injury or otherwise, that produce abnormal combinations of sensory data and qualities of consciousness in general (Dr. Oliver Sacks has written extensively on this topic).

On the other hand, different cortical sensory areas are highly connected to each other; this is at least partly why our sensations feel so unitary. This means that simply hearing something move or feeling the touch (ref. 1) of something moving can produce measurable responses in the parts of the visual cortex most sensitive to movement. Some recent research has gone farther than this, since, as the authors of this work (ref. 2) point out: it is no surprise that the feeling of something moving can elicit such a reaction because merely imagining motion can have the same effect. These experiments demonstrate that a highly specialized area of the visual cortex called MST is sensitive to “vibrotacticle” stimuli: those incongruent with motion.

Because consciousness is often thought of as an emergent property of our massively interconnected system of neurons, understanding interactions between parts of the brain at many different scales (from single neurons to large collections or areas as in this case) is integral to understanding how this efflorescence works. The work highlighted here is one step in that direction.

References

  1. Hagen MC, Franzen O, McGlone F, Essick G, Dancer C, Pardo JV (2002) Tactile motion activates the human middle temporal/V5 (MT/V5) complex. Eur. J. Neurosci. 16:957–964.
  2. Beauchamp MS, Yasar NE, Kishan N, Ro T. (2007) Human MST but not MT responds to tactile stimulation. J. Neurosci. 27(31):8261-8267

Life Span

It is somewhat paradoxical that we cannot perform experiments on the animal we are most interested in studing, ourselves. It is difficult enough to deal with the moral implications of experimenting on non-humans. I frequently remind myself that the study of other creatures mitigates the suffering of my own species and this sometimes seems a paltry justification. Humans are investiaged non-invasively, or further when such intrusion is neccessary for medical purposes, but we are still limited in our understanding by such restrictions, the following science included.

It will come as no suprise that there is quite a bit of research into the possibility of extending the length of time that a living thing spends alive. To date, the only effective means of doing so have been based in some way on the concept of Calorie Restriction(CR), see ref. 1 for a review. This simply means that an animal takes in fewer calories than normal while maintaining adequate levels of nutrients. The results are reasonably unequivocal, from nematoads to mammals, lifespan is increased by this method. As one can see from the graph above, increased caloric restriction is effective up to around 65% fewer calories being taken in, at which point it plateaus.

Some recent research, however, (ref. 2) has found a seemingly non-CR-intertwined mechanism that also has an effect on mammalian lifespan. The authors of this study bred mice which lack the gene which codes for adenylyl cyclase 5 (AC5). ACs in general play a key role in beta-adrenergic receptor (β-AR) signaling. In the interest of brevity, I will not delve into the molecular biology of cell-to-cell communications, howiver it is important to know that the blockade of this particular signalling pathway has recently been demonstrated to sucessfully treat mild-to-moderate chronic heart failure (ref. 3). The research into mice which lack the AC5 gene shows that their lifespan is ~30% longer, “are protected from reduced bone density and susceptibility to fractures of aging. Old AC5 KO mice are also protected from aging-induced cardiomyopathy, e.g., hypertrophy, apoptosis, fibrosis, and reduced cardiac function.” (ref. 1)

With both of these examples of extended lifespan, however, a question arises. What quality of life do these animals have? This is perhaps more relevant for the research on calorie restriction, but the animals studied can never report to us how they are feeling though the scientist involved always take pains to minimize any outward signs of discomfort. Until such techniques have been tried in human beings the complete effects of these therapies remains a bit of a quesion mark in my mind. That is not to say that I’m not amazed and optimistic about this direction of progress, I simply find it incredible that such simple things as eating less or disrupting a single gene could have universally positive effects.

References

  1. D.A. Sinclair (2005) Toward a unified theory of caloric restriction and longevity regulation, Mech. Ageing Dev. 126, 987–1002.
  2. Lin Yan, Dorothy E. Vatner, J. Patrick O’Connor, Andreas Ivessa, Hui Ge, Wei Chen, Shinichi Hirotani, Yoshihiro Ishikawa, Junichi Sadoshima, and Stephen F. Vatner (2007) Type 5 Adenylyl Cyclase Disruption Increases Longevity and Protects Against Stress, Cell 130, 247-258
  3. M.R. Bristow (2000) beta-adrenergic receptor blockade in chronic heart failure, Circulation 101, 558–569.