Thanks for the replies Mark1023, nice catch! I feared the 2-3 year old thread would sink back into oblivion
So, research into spatial mapping is still at an early stage if I understand you correctly. Which leaves a lot of room for interpretation I guess. Learning more about how we store and access memories should be in the core of neural science I would imagine even though it's more about observing what's happening and not so much understanding the finer details of it at the present.
Edit: Thinking about it. Can you compare advances in neural science in part to astronomy? It received a significant boost from improved tools of observation in the latest decades, like the Hubble Obervatory. Are we still improving our methods of detecting neural activity? I think I remember a news story recently about how we're slowly getting to the point where we can translate neural patterns to actual images of what the person is thinking.
No we cannot translate activity into what the person is thinking except in the broadest sense like think of a song and there may be increased auditory cortex activity. This is however the critical question in Neuroscience IMO and it is what I work on. Essentially how is neural activity put together into a coherent representation?
There is an explosion in new technology in neuroscience. Some of what you may be thinking of is the neural silicon interface. It is possible apparently to take EEG signals and train animals (and people?) to use this activity to control certain computer actions. For example, a monkey can be trained to move a robotic arm with thinking causing a certain change in EEG that triggers the arm. It is very cool stuff but we don’t know the precise thoughts or even the precise activity patterns from EEG.
I work in animals with genetic tools. Our niche is that we have a way of taking the pattern of neural activity at a certain time and translating it into a genetic change in just those active neurons. We can thus have an animal learn something and put genes into those neurons that were active with learning that allow us to reactivate or silence those neurons artificially with a chemical or light. So in one experiment we have submitted recently we asked if we show an animal one room (room A) and then shock the animal in a different room (room B) while artifically firing the room A neurons what will the animal learn? Shocking the animal (very lightly) causes them to be afraid of the room they were shocked in so that is how we know they recognize it (by measuring fear responses). So what did the animal learn? They were not afraid of either room A or B alone but were afraid when we fired the room A neurons artifically while in room B. That is, they formed a hybrid representation incorporating elements of both. This was quite surprising for a number of complex reasons but the take home message is that you can incorporate ongoing and unrelated patterns of neural activity into a memory. Your brain is not silent after all until you want to learn something but has lots of ongoing internal activity. This shows that this internal activity is actually incorporated into representations.