Consciousness, Part II


There are many contentious debates surrounding consciousness and it’s easy to get lost in the network of epistemological objections that arise from different motivations for discussing consciousness, some of them spiritual and religious. Discussions on this blog will be based on an empirical stance only. Because the scientific method has proven useful in the pursuit of knowledge, this blog will adhere to its principles. That means we are going forward from a physicalist stance. Further, because my training is mostly in classical physics and neuroscience (and because the quantum consciousness approaches are highly criticized by mainstream quantum physicists and neuroscientists alike and have yielded no fruitful predictions) I will approach most of this from an emergent physicalist perspective – the idea that consciousness somehow emerges from the interactions between brain regions and this idea has some empirical evidence behind it that was discussed in Consciousness, Part I.


An understanding of how matter can have a subjective experience would have implications for the mechanism behind how we experience things, and how individuals experience things differently from one another.  While there is no such complete theory provided by neuroscience, there are empirical aspects of qualia examined by neuroscience.

The following paper compares the genetically-influenced receptor distribution of subjects to their qualitative descriptions of the qualia and finds meaningful correlations between genetics and qualitative descriptions.  These results demonstrate the compatibility of qualia with the scientific approach to consciousness.

Does a unique olfactory genome imply a unique olfactory world?

Variability within and between individuals

Below, a paper by Rabinovich demonstrates how perception dynamics rely on transient neural phenomena. As an analogy, consider setting a ball in a bowl. No matter where in the bowl you set it, the ball will eventually end up at the bottom, what we could call the stable node if we were to model the problem mathematically. However, even if you try to start the ball in the same place twice, you’ll notice the path is slightly different each time. That is because you can’t really put it in the same exact place twice with enough precision to avoid this variability. Rabinovich, using data from locust olfactory, shows that in responding to different stimuli, it is the state path of the neural network that is significant in determining behavioral responses to stimuli. This implies that perception itself may also be based on the transient path of neural states, not the final activity of the network. To carry the analogy over to neurons, the ball/bowl system state can be described by three variables, the x-y-z coordinates of the ball. In a neural system, the network’s state can be described by hundreds of unique variables (for each neuron in the network you would need the membrane voltage, the open/close state of ion channels in the neuron, and the abundance of molecular messengers that may affect ion channel performance). Rabinovich on transient encoding:

The intrinsic dynamics of neural networks produces firing patterns that encode informational inputs and relay them to further processing centers upstream. In general, this code is spatiotemporal and sequential, i.e., transient. Such encoding has been observed recently in experiments with olfactory and gustatory sensory systems (Jones et al., 2007; Rabinovich et al., 2008b; Fernandez et al., 2009).


Rabinovich further describes the WLC (winnerless competition) network in which the system can become multistable (in the ball and bowl analogy, this would be equivalent to having multiple bowls connected so that there are now many stable states the ball can rest in, each distinct). In the following image, such systems are dictated by their stable points (the bottom of each bowl) their unstable nodes (which would be more like a mountain peak which the ball would roll away from, rather than towards) and saddle nodes. Saddle nodes aren’t quite as intuitive, but you can imagine that a little ball on the Pringle above would roll towards or away from the center of the chip, depending on where the ball is on the chip.

Here we use the term WLC principle for the non-autonomous transient dynamics of neural systems receiving external stimuli and exhibiting sequential switching among temporal winners – different neurons or neuronal groups whose activity is sequentially switching. Thus, the main point of the WLC principle is the transformation of incoming inputs into spatiotemporal outputs based on the intrinsic switching dynamics of the neuronal ensemble.

If perception is encoded in transients, and transients are sensitive to perturbation, variability in some of the qualitative aspects of perception (and thus behavior) is bound to occur, even within a single individual. Of course, this is in addition to fact that when we are in different mental states, we process information differently:


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