show me your prefrontal cortex


Together with collegues from London and Tokyo neuroscientist John-Dylan Haynes did an experiment (however up to now only with 21 test persons as it seems), where a person had to choose wether he/she wanted either to add or to substract two numbers. And even before the test persons saw the numbers and before they started to compute it was possible – by using a MRI brain scan – to tell with a 70% chance, what kind of desicion the person was going to make, or in other words: using the MRI the scientists could “read the mind” of the test persons (with a 70% chance). Freely chosen decisions are usually happening in the prefrontal cortex.

The trick by which the invisible is made visible lies in a new method called “multivariate pattern recognition”. A computer
is programmed to recognize characteristic activation patterns in the brain that typically occur in association
with specific thoughts. Once this computer has been “trained” it can be used to predict the decisions of
subjects from their brain activity alone. An important technical innovation also lies in combining information
across extended regions of the brain to strongly increase sensitivity.

The study also reveals fundamental principles about the way the brain stores intentions. “The experiments
show that intentions are not encoded in single neurons but in a whole spatial pattern of brain activity”, says
Haynes. They furthermore reveal that different regions of the prefrontal cortex perform different operations.
Regions towards the front of the brain store the intention until it is executed, whereas regions further back
take over when subjects become active and start doing the calculation. “Intentions for future actions that are
encoded in one part of the brain need to be copied to a different region to be executed”, says Haynes.

quote from the Press release of Max Planck Society.
->german press release of the bernstein zentrum
-> article on wired

2 Responses to “show me your prefrontal cortex”

  1. Yılmaz Değirmenci Says:

    Using SQUID devices to read human brain activities may help increase our understanding of human brain.

  2. Run D.M.V. Says:

    In contrast to patterns of more or less well understood constant firing rates, signal propagation is still less well understood.There is now however some progress, at least with regard to the mathematical understanding of dendrite computation. In the paper:
    Tuft dendrites of pyramidal neurons operate as feedback-modulated functional subunits one finds:

    Basal and proximal apical dendrites have been shown to function as independent computational subunits within a two-layer feedforward processing scheme. The outputs of the subunits are linearly summed and passed through a final non-linearity. It is an open question whether this mathematical abstraction can be applied to apical tuft dendrites as well. Using a detailed compartmental model of CA1 pyramidal neurons and a novel theoretical framework based on iso-response methods, we first show that somatic sub-threshold responses to brief synaptic inputs cannot be described by a two-layer feedforward model. Then, we relax the core assumption of subunit independence and introduce non-linear feedback from the output layer to the subunit inputs. We find that additive feedback alone explains the somatic responses to synaptic inputs to most of the branches in the apical tuft.

    The figures in the article could have been more clearly though.

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