> EEG or fMRI data only tells us about electrical activity in the brain, specifically the firing of neurons in different patterns and areas of the brain. We are yet to make the absolute connection of how that electrical activity translates into thought.
To do that, I think we’d need much higher resolution imaging, both in space and in time.
It also says temporal resolution can be about a second. Whether that is sufficient isn’t clear to me. I think we know too little of the human brain to make a judgment on that. On the one hand, https://aiimpacts.org/rate-of-neuron-firing/ says a brain neuron, on average, fires less than 2 times a second. On the other hand https://www.frontiersin.org/articles/10.3389/fncel.2016.0023... talks of fast-spiking neurons that fire hundreds of times a second.
The current data is like trying to figure out how a CPU works from recordings that don’t show individual bits, but only show what parts get active when doing floating point calculations, when doing I/O, etc.
To do that, I think we’d need much higher resolution imaging, both in space and in time.
https://en.wikipedia.org/wiki/Functional_magnetic_resonance_... talks of submillimeter spatial for fMRI while a neuron is about 0.1mm.
It also says temporal resolution can be about a second. Whether that is sufficient isn’t clear to me. I think we know too little of the human brain to make a judgment on that. On the one hand, https://aiimpacts.org/rate-of-neuron-firing/ says a brain neuron, on average, fires less than 2 times a second. On the other hand https://www.frontiersin.org/articles/10.3389/fncel.2016.0023... talks of fast-spiking neurons that fire hundreds of times a second.
The current data is like trying to figure out how a CPU works from recordings that don’t show individual bits, but only show what parts get active when doing floating point calculations, when doing I/O, etc.