Hey all. - I'm a working neuroscientist who's spent some time thinking through some of these issues.
I would say that there's a significant proportion of the field that is, shall we say, "skeptical" of the Buzsaki-style view on oscillations. Everyone agrees that the oscillations exist, and that changes in the oscillations are often correlated with changes in brain state, but making *causal* statements about their impact has proven much more difficult. There are certainly some suggestive data in the hippocampus pointing towards the importance of things like theta-band power and sharp wave ripples, but even there you get inconvenient data points like the fact that bats have a completely normal, functioning hippocampus with no apparent theta band oscillations: https://www.sciencedirect.com/science/article/pii/S0092867418312297
More broadly, it's hard to shake the feeling that the brain has some natural resonances for various states - sleep/unconsciousness is low frequency, low activity is ~alpha/beta, high activity is ~gamma. A statement like:
"Ask someone to think about a certain topic, and cells representing that topic will form a neuronal assembly (ie they will start oscillating together at the same frequency) in gamma rhythm."
is really just saying that those cells are active, and neurons in an active brain area tends to follow a gamma rhythm. In fact, I'm reasonably confident that if you were to look at the internal activity of cells in the same area that do NOT represent that topic, they would also be following the same gamma rhythm, just with less tonic input and thus less spiking activity.
People like to study oscillations because they're brain-wide phenomena that are (relatively) easy to detect in humans with non-invasive methods like EEG. However, anyone who's looked at neural activity using more finely-tuned, invasive methods (e.g. single neuron electrophysiology) knows that individual neurons close by each other can be tuned to very different sets of variables, and that when you average signals from large populations of neurons you lose a lot of useful information.
To be clear, I think everyone in the field agrees that neurons act together in assemblies, that patterns of activity that are shared across neural populations are important, and that sometimes these population patterns of activity can oscillate. The problem is that there are many, many, many of these subnetworks active at any given time, and that when you average them all together you get a signal that's easy to measure, but is limited in its ability to explain anything beyond basic brain function. You have 86 billion neurons in your brain. You should be skeptical of theories that tell you just 4-5 frequency bands are the secret to understanding it.
Hey all. - I'm a working neuroscientist who's spent some time thinking through some of these issues.
I would say that there's a significant proportion of the field that is, shall we say, "skeptical" of the Buzsaki-style view on oscillations. Everyone agrees that the oscillations exist, and that changes in the oscillations are often correlated with changes in brain state, but making *causal* statements about their impact has proven much more difficult. There are certainly some suggestive data in the hippocampus pointing towards the importance of things like theta-band power and sharp wave ripples, but even there you get inconvenient data points like the fact that bats have a completely normal, functioning hippocampus with no apparent theta band oscillations: https://www.sciencedirect.com/science/article/pii/S0092867418312297
More broadly, it's hard to shake the feeling that the brain has some natural resonances for various states - sleep/unconsciousness is low frequency, low activity is ~alpha/beta, high activity is ~gamma. A statement like:
"Ask someone to think about a certain topic, and cells representing that topic will form a neuronal assembly (ie they will start oscillating together at the same frequency) in gamma rhythm."
is really just saying that those cells are active, and neurons in an active brain area tends to follow a gamma rhythm. In fact, I'm reasonably confident that if you were to look at the internal activity of cells in the same area that do NOT represent that topic, they would also be following the same gamma rhythm, just with less tonic input and thus less spiking activity.
People like to study oscillations because they're brain-wide phenomena that are (relatively) easy to detect in humans with non-invasive methods like EEG. However, anyone who's looked at neural activity using more finely-tuned, invasive methods (e.g. single neuron electrophysiology) knows that individual neurons close by each other can be tuned to very different sets of variables, and that when you average signals from large populations of neurons you lose a lot of useful information.
To be clear, I think everyone in the field agrees that neurons act together in assemblies, that patterns of activity that are shared across neural populations are important, and that sometimes these population patterns of activity can oscillate. The problem is that there are many, many, many of these subnetworks active at any given time, and that when you average them all together you get a signal that's easy to measure, but is limited in its ability to explain anything beyond basic brain function. You have 86 billion neurons in your brain. You should be skeptical of theories that tell you just 4-5 frequency bands are the secret to understanding it.