Peter Dayan of Theoretical Neuroscience fame gave a talk today at Harvard University that I was fortunate enough to attend. One of the great things about Boston/Cambridge area is the sheer pull of our collective universities in bringing top neuroscientists to the area. Anyway, some of his newer work that he was presenting today was entitled, “Norepinepherine and Neural Interrupts.”
There are about four main neuromodulatory systems that each use a particular neurotransmitter as its chemical of action. They seem to have wide ranging connections that span large neural surfaces, and they include dopamine (DA), acetylcholine (ACh), serotonin (5-HT), and norepinepherine (NE). As much as brain chemistry is certainly important, the effects of these particular neuromodulators on the systems that they innervate is incredibly complex, as they make millions of synapses on a what seems to be a wide variety of neurons. Dayan was presenting an interesting viewpoint on the role of NE involved in uncertainty states. The essential idea is that uncertainty must be a top-down mediated process, which starts either with an expectation or no expectation at all. Both of these states are uncertain states, which can be restated as either an expected uncertainty or an unexpected uncertainty. In either case, the brain’s environment must be favorable to a learning condition.
Consider your walk through your school or office. Let’s say that you know that they have been remodeling your wing of the office, so as soon as you turn the last corner, you have an expectation that things will look different. You know already that uncertainty exists. This situation may be neurobiologically different from if you had no idea that they painted the walls pink with green dots, so when you turn the corner, there is (certainly!) an unexpected uncertainty.
Presumably, ACh mediates the former – that is, the expected uncertainty, where NE may modulate the unexpected uncertainty. The experimental evidence seems to come primary from non-human primate studies that measure levels of NE modulation during a target-response visual task that shows a spike in NE pathway activation after the salient target is presented, and no change from baseline levels of activation with the presence of a distractor.
Dayan’s model was a simple state dependent modulation between either the target and distractor that included probabilities of NE activation due to being presented with the two stimuli. He had a pretty simple error predictor that was pointed out did not account for motor type errors, which presumably should be averaged and removed across task difficulty – that is, as task difficulty increases, the number of motor specific mistakes may stay relatively constant. I think this is a reasonable assumption for present purposes.
However good the model was at reproducing the qualitative features of the experimental evidence – and it was, more or less – it was very difficult not to call into question several possible shortcomings. The model set an arbitrary threshold for activation, at 95% probability required for activation, but there did not seem to be any physiological reason for such a threshold. There were also some unexplained qualitative microfeatures of the model’s output that also seemed curious. Additionally, the model included some features such as the random resetting after a certain number of trials that did not seem to have an immediate physiological basis, though I may well just not understand the particulars of the system.
For being a model that simply takes into account the states of NE pathway activation based on the evidence of target presentation, there seemed to emerge some interesting features. However, I think that the next step might be to suggest a mechanism by which this system is acting.
To address this particular question, Dayan suggested a top-down neural interrupt hypothesis presumably governed by the prefrontal cortex and the anterior cingulate cortex. Thus control over the NE neuromodulatory pathway via locus coeruleus may have the ability to globally set the system up for learning in the cases of unexpected uncertainty.
Clearly, many questions remain concerning this proposal, especially considering the lack of a biophysical mechanism, as well as the basic understanding of cortical specificity.
However the idea is certainly interesting nonetheless, in the sense that yet another neuromodulatory system may have a tangible role in a complex behavior such as uncertainty mediation.