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The Believing Brain - Michael Shermer [72]

By Root 451 0
monkey’s F5 neurons spiked whenever the monkey reached for a peanut placed in front of it. The serendipity came when one of the experimenters reached in and grabbed one of the peanuts, causing the same neurons in the monkey’s brain to fire. Monkey do, monkey see, monkey motor neurons fire. The motor neurons were mirroring the motor activity of others, and thus they became known as mirror neurons. As Rizzolatti recalled, “We were lucky, because there was no way to know such neurons existed. But we were in the right area to find them.”33

Throughout the 1990s neuroscientists scrambled to learn more about mirror neurons, finding them in other parts of the brain, such as the inferior frontal and inferior parietal regions of the brain, and not only in monkeys but in humans as well through fMRI brain scans.34 UCLA neuroscientist Marco Iacoboni and his colleagues, for example, imaged the brains of subjects as they watched people make finger movements and then imitated those same finger movements, discovering that the same areas of the frontal cortex and parietal lobe in both conditions were active.35

Rizzolatti suggested that mirror neurons are just motor neurons responding to seeing as well as doing. When you see an action it is recorded on your visual cortex, but to more deeply understand what the act means in terms of its consequences the observation must be linked to the motor system of the brain so that there is an internal check with the external world. With this basic neural network in place, higher-order functions can be layered onto it, such as imitation. In order to imitate someone’s actions, you need both a visual memory of how the action looked as well as a motor memory of how the action felt when implemented. There is now considerable research linking the mirror neural network to imitation learning.

In a 1998 fMRI experiment, for example, people were shown two different hand actions, one without a context and one with a context that revealed the intention of the action. The latter scene activated the subject’s mirror neuron network, revealing just where in the brain the perception of another intentional agent is located.36 A very clever 2005 experiment was conducted in which monkeys watched a person either grasp an object and place it in a cup or grasp an apple and bring it to his mouth—similar action, different intention. Recording forty-one individual mirror neurons in the inferior parietal lobe of the monkeys’ brains, it was discovered that the “grasp-to-eat” motion triggered fifteen mirror neurons to fire, but these were silent when observing the “grasp-to-place” motion. Interestingly, the neuroscientists concluded, the mirror neurons in this part of the brain “code the same act (grasping) in a different way according to the final goal of the action in which the act is embedded.”37 In other words, there are neurons specialized for discriminating between different intentions: grasping in order to place versus grasping in order to eat. More generally, this implicates mirror neurons in both predicting others’ actions and inferring their intentions, which is the very foundation of agenticity.

Belief in the Brain

How is it that people come to believe something that seemingly defies reason? The answer is in the thesis of this book: beliefs come first; reasons for belief follow in confirmation of the realism dependent on the belief. Most belief claims fall somewhere in the fuzzy borderlands between unquestionably true and unmistakably false. How do our brains process such a broad swath of beliefs? To find out, in 2007 neuroscientists Sam Harris, Sameer A. Sheth, and Mark S. Cohen employed fMRI to scan the brains of fourteen adults at the UCLA Brain Mapping Center. They presented their subjects with a series of statements designed to be plainly true, clearly false, or undecidable at the moment. In response, the volunteers were to press a button indicating belief, disbelief, or uncertainty. For example:

MATHEMATICAL

True: (2 + 6) + 8 = 16.

False: 62 can be evenly divided by 9.

Uncertain: 1.257 = 32608.5153.

FACTUAL

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