This Machine learning theory matches your claim that neural representations are common across groups of people. The scientist had people look at words. He compared the brain activity of a person looking at a word and the brain activity of the person looking at the picture matching the word. The brain activity of both was similar. Then he looked at the results of groups looking at the word and found that they group had similar results. People think the same, in general neural linguistic terms. Sensory activity of the brain was connected to verbs associated with that part of the brain. Sensory: see, hear, listen, taste, touch, smell, fear. Motor: rub, lift, manipulate, run, push, move, say, eat. Abstract: fill, open, ride, approach, near, enter, drive, wear, break, clean. For each verb has 20,000 voxels/coefficients to be analyzed in a regression model. The model solves the coefficients. The model trains of the brain activity associated with the verb. In a pool of 9 people the model was 79% accurate in recognizing the verb. Eat activates voxels in the pars opercularus (gustatory cortex). Gustatory cortex is activated during eating. Push activities voxels in the postcentral gyrus (planning motor actions). Run activities voxels in the Superior temporal sulcus (body motion) The model used 10,000 words most frequent English words and predict the most activate each brain region. The scientist looked at 72 regions of the brain. Right Opercularis: wheat, beans, fruit, meat, paxil, pie, mills, break, homework, eve, potatoes, drink. (wheat) Right Superior Posterior Temporal lobe: sticks, fingers, chicken, foot, tongue, rope, sauce, nose, breasts, neck, hand, rail. Left Anterior Cingulate: poison, lovers, galaxy, harvest, sin, hindu, rays, thai, tragedy, danger, chaos, mortality. What is Machine Learning 1. Andrew Ng says machine learning is a top topic for information technology. 2. Machine learning is being applied to a wide range of problems. Machine learning groups and classifies hypothesis from medical records highlighting probable diagnosis. Machine learning is a part of the check identification process. Machine learning looks for fraudulent electronic transactions. Machine learning has been applied to Netflix to learn from movies watched and make predictions about movies you may be interested in. Machine learning optimizes the engine performance of your vehicle. 3. Machine learning is the field of study that gives machines the ability to learn without being explicitly programmed says Author Samuels. 4. Learning theory is supervised learning and begins by telling the algorithm the right answer and the algorithm learns the relationships from the inputs leading to the right answer and is expected to produce more of the right answers. 5. Unsupervised learning is used for solving many problems and grouping information into clusters. Unsupervised learning algorithms have been used to create line detection and 3D models from the angular displacements. Unsupervised learning algorithms discover structure in data. 6. Reinforced learning is based on reward function or conditional reflexive learning. If the algorithm is right then a positive feedback is provided and if the algorithm is wrong then an inhibitory feedback is inputting into the system.[Learn More ...]

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