So, it's relatively easy to show how activity in motor areas causally leads to changes in muscle activity / movement. And, more generally, if Neuron A is synaptically connected to Neuron B, we have a very rich understanding of the electrical and molecular mechanisms that explain why an increase in activity of Neuron A causally increases the probability of activity in Neuron B. In so far as a mind is the product of 100 trillion neural connections, we know that each of those individual connections represents a causal chain that propagates increases in brain activity. There's lots of other very suggestive evidence, but these basic facts are, I think, why most neuroscientists feel comfortable hanging their hats on the idea that changes in behavior are tied to changes in neural activity somewhere.
In contrast, the structures of neural oscillations are (in most cases) set by emergent properties of densely connected neural networks. There's been amazing progress in trying to model these kinds of networks, but in truth we're still in the pre-statistical-mechanics era of neuroscience. We know a lot about individual neurons and neural connections, but we still don't have a well-accepted theoretical framework that allows us to understand how large populations of neurons interact and compute. This ignorance makes it hard to make confident statements about the causal impact of oscillations, or really of any other network-level phenomenon.
The philosophic argument for neural activation is that we understand its causality in very simple networks. The argument against oscillations is simply a lack of evidence, pending better models of network activity.
So, it's relatively easy to show how activity in motor areas causally leads to changes in muscle activity / movement. And, more generally, if Neuron A is synaptically connected to Neuron B, we have a very rich understanding of the electrical and molecular mechanisms that explain why an increase in activity of Neuron A causally increases the probability of activity in Neuron B. In so far as a mind is the product of 100 trillion neural connections, we know that each of those individual connections represents a causal chain that propagates increases in brain activity. There's lots of other very suggestive evidence, but these basic facts are, I think, why most neuroscientists feel comfortable hanging their hats on the idea that changes in behavior are tied to changes in neural activity somewhere.
In contrast, the structures of neural oscillations are (in most cases) set by emergent properties of densely connected neural networks. There's been amazing progress in trying to model these kinds of networks, but in truth we're still in the pre-statistical-mechanics era of neuroscience. We know a lot about individual neurons and neural connections, but we still don't have a well-accepted theoretical framework that allows us to understand how large populations of neurons interact and compute. This ignorance makes it hard to make confident statements about the causal impact of oscillations, or really of any other network-level phenomenon.
The philosophic argument for neural activation is that we understand its causality in very simple networks. The argument against oscillations is simply a lack of evidence, pending better models of network activity.