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Limbic System: Amygdala, Hippocampus, Hypothalamus, Septal Nuclei, Cingulate
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Head Injuries, Concussions & Brain Damage: Cerebral and Cranial Trauma, Skull Fractures….
Basal Ganglia, Brainstem, Cerebellum, Striatum, Thalamus: Caudate, Putamen, Globus Pallidus...
Frontal Lobes: Neuroscience, Personality, Emotion, Language, Alien Hand, Free Will….
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Neuroscience
Neuroscience Neuropsychology, Neuropsychiatry, Behavioral Neurology - E-Books
Neuroscience: Neuropsychology, Neuropsychiatry. Introduction...
The Frontal Lobes: Neuroscience, Neuropschiatry, Neuropsychology, Neurology...
Parietal Lobe: Body Image, Visual Spatial Perception, Language
Stroke: Thrombi, Emboli, Hemorrhage, Aneurysms, Athersclerosis, TIA, CVA...
Basal Ganglia, Striatum, Thalamus, Caudate, Putamen, Globus Pallidus, Brainstem...
Limbic System: Hypothalamus, Amygdala, Hippocampus, Cingulate...
Temporal Lobe: Language, Memory, Emotion
Head Injuries, Skull Fractures, Concussions, Contusions, Hemorrhage, Coma...
Memory, Amnesia, Amygdala, Hippocampus, Neural Networks…
Free Will and the Frontal Lobes: Loss of Will, Against the Will…
Brainstem and Cerebellum: Medulla, Pons, Midbrain....
Right Hemisphere, Left Hemisphere, Consciousness, Unconscious Mind....

Developmental Neuroscience E-Books
Fetal Cognitive & Brain Development: Normal & Abnormal
Child & Infant Emotional & Cognitive Brain Development
Neuroscience.
Brain & Mind
Introduction, Primer
Development of Consciousness, Language, Emotion & Thought

Consciousness
Development, Quantum Physics, Neuroscience E-Books
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Infinity - The Big Bang
Extinctions
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Infinite Universe: Quantum Physics of Infinity
Extinctions: History, Origins & Future of Mass Extinctions
The Big Bang: A Critical Analysis...


BrainMind.com News


Source:

Face It! The Brain is Wired To Recognize Faces, April 7, 2006

It has been well established that specific areas of the human brain contain face-recognition neurons, whereas others are responsive to specific facial features.

These face-neurons have been found in the temporal lobe, the amygdala, and hippocampus.

Some scientists believed that the "faces aren’t special in the way many scientists once thought,” says Maximilian Riesenhuber, PhD, assistant professor of neuroscience and senior author of a study to be published in Neuron. “Rather, they are particular group of objects which the brain has learned to distinguish very well, much as it would for any other similar objects that are critical to human survival and communication.”

“We think that this is because we are face ‘experts,’ having learned over many years to spot fine differences in upright faces, but not in inverted faces. That experience makes faces unique, but there’s nothing scientifically special about faces,” Riesenhuber says.

The Georgetown scientists hypothesized that facial recognition does not rely on face-specific mechanisms but instead uses the same neural mechanisms for faces that are used to discriminate other objects. Over the years, because of the importance of facial identity and expression for social communication, humans have simply developed a strong talent for recognizing and distinguishing faces. This experience with faces then leads to the learning of a population of neurons finely tuned to different faces, Riesenhuber says.

The researchers then tested these predictions against experimental data measured in a functional Magnetic Resonance Imaging (fMRI) machine, a high-powered imaging technology that can measure the brain activity of test subjects, and by other behavioral techniques. Subjects were shown pairs of images of similar human faces that had been morphed using computer graphics software, while the researchers observed how brain activation changed for more or less similar pairs of faces.

However, what they found was that a small group of neurons in the “fusiform face area,” an area of the brain generally thought to be responsible for face recognition, was highly selective for different faces, just as most scientist have believed for years.

“We knew that the fusiform face area is highly involved and necessary for us to understand faces, but we did not know what kind of processing was going on inside that ‘black box’,” he said. “By using a computational model to quantitatively link neuronal processing, brain imaging and behavior, we now have a mechanistic model describing which neurons are involved and how they are behaving when we look at faces.”






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