Chapter 3: The nerve cell
Multiple Choice Questions (1-20)
1. If the synapse between neurons is inhibitory, the probability of the next neuron firing
is
a. increased
b. decreased
c. unchanged
d. dependent upon the type of neuron
2. If the synapse between neurons is excitatory, the probability of the next neuron firing
is
a. increased
b. decreased
c. unchanged
d. dependent upon the type of neuron
3. What is an artificial neural net (ANN)?
a. the intricate connections between neurons that exist in the brain
b. a model of a brain function that utilizes idealized neurons
c. the circuitry that is found in artificial intelligence devices
d. a tangle of neuronal axons that no longer function properly
4. The reentrant, or ” two-way”, connections between neuronal arrays are
a. by far the most common connection type
b. limited to connections within the cerebral cortex
c. only about 10% of the connections in the cortex
d. limited to vision cortex
5. Hebbian learning refers to notion that “neurons that fire together, wire together.” Its
defining feature is that
a. the threshold for firing an action potential is dependent upon the type of neuron
b. the formation of a particular type of neuron occurs at the same stage of
development
c. learning involves increased efficiency in synaptic transmission
d. neural arrays are formed between similar types of neurons
6. Neural Darwinism can be summarized as
a. “survival of the organisms with the most complex nervous system”
b. “survival of the biggest neurons”
c. “survival of the organisms with the most adaptive nervous system”
d. “survival of the fittest cells and synapses”
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7. Making predictions about which interpretation of an ambiguous stimulus is likely to
be correct involves a kind of
processing.
a. lateral
b. input-driven
c. top-down
d. bottom-up
8. Which of the following is the best metaphor for neuronal choice points?
a. sliding on a slide
b. swinging on a swing set
c. driving with traffic down a one-way street
d. choosing a direction at a fork in the road
9. Hierarchies of neuronal arrays exist for
a. sensory systems
b. motor systems
c. both sensory and motor systems
d. neither sensory nor motor systems
10. Learned but non-voluntary processes are called
a. reflexes
b. circuits
c. automatic processes
d. subconscious processes
11. Two ways that the brain encodes information are (1) in spatial arrays and maps, and
(2) in changing the firing rate of neurons. Which of the following describes these
types of coding?
a. They are both examples of types of spatial coding
b. The first is an example of temporal spatial coding, and the second is an example
of spatial coding
c. The first is an example of spatial coding, and the second is an example of
temporal coding
d. They are both examples of differing types of temporal coding
12. How does an “integrate-and-fire” neuron work?
a. Neurons will fire when they receive any type of information from the neuron
before it
b. The strength of the action potential fired is dependent upon the strength of the
signal the neuron receives
c. Graded voltage inputs are summed, and if a threshold point is crossed, the
neuron will fire an all-or-none action potential
d. The neuron will only fire if it receives information from all of the neurons it
receives information from, or not at all
13. Sensory systems (such as vision, touch, hearing) are
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a.
b.
c.
d.
organized in strictly feedforward hierarchies
comprised of roughly 50% one-way and 50% two-way connections
comprised of mostly two-way connections that aid in resolving ambiguous inputs
comprised of mostly one-way connections in order to produce temporal encoding
of sensory features
14. Neuronal arrays that represent spatial patterns are frequently referred to as
a. spiking codes
b. semantic networks
c. maps
d. hierarchies
19. Some working assumptions in the study of neurons and their connections include
a. a simplified neuron to build cognitive models from artificial neural nets
b. connections are either inhibitory or excitatory
c. most neural connections are two-way
d. all of the above
20.Finding one’s way home in the dark is an example of
a. sensori-motor feedforward processing
b. lateral inhibition
c. top-down or expectation-driven processing
d. temporal coding
Short Answer Questions (1-3)
1. Briefly explain how sensory and motor regions can be viewed as hierarchies.
2. In your own words, describe the idea behind Hebbian learning. What neural changes
are occurring during Hebbian learning?
3. What role does re-entrant (two-way) connections play in brain function?
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