Use the following passage to answer questions: A doctor is examining a CT scan, looking for evidence of a tumor. Either there is a tumor (signal present) or there is not (signal absent). Either the doctor sees a tumor (she responds 'yes') or does not (she responds 'no'). There are four possible outcomes: hit (tumor present and doctor says 'yes'), miss (tumor present and doctor says 'no'), false alarm (tumor absent and doctor says 'yes'), or correct rejection (tumor absent and doctor says 'no'). Hits and correct rejections are good. False alarms and misses are bad. Detecting a tumor is... Show more Use the following passage to answer questions: A doctor is examining a CT scan, looking for evidence of a tumor. Either there is a tumor (signal present) or there is not (signal absent). Either the doctor sees a tumor (she responds 'yes') or does not (she responds 'no'). There are four possible outcomes: hit (tumor present and doctor says 'yes'), miss (tumor present and doctor says 'no'), false alarm (tumor absent and doctor says 'yes'), or correct rejection (tumor absent and doctor says 'no'). Hits and correct rejections are good. False alarms and misses are bad. Detecting a tumor is difficult, and there will always be some amount of uncertainty. There are two kinds of noise factors that contribute to the uncertainty: internal noise and external noise. External noise: There are many possible sources of external noise. There can be noise factors that are part of the photographic process, a smudge, or a bad spot on the film. Or there can be something in the person's lung that is fine but looks a bit like a tumor. All of these are examples of external noise. Internal noise: Internal noise refers to the fact that neural responses are noisy. For example, a doctor may see many tumors a day and as such develop a set of neurons used when making decisions on whether a scan shows a tumor. These hypothetical tumor detectors will give noisy and variable responses. After one glance at a scan of a healthy lung, the hypothetical tumor detectors might fire 10 spikes per second. After a different glance at the same scan and under the same conditions, these neurons might fire 40 spikes per second. Internal response: It is actually not likely that there are tumor detector neurons in a radiologist's brain. But there is some internal state, reflected by neural activity somewhere in the brain, that determines the doctor's impression about whether a tumor is present. This is a fundamental issue; the state of the doctor's mind is reflected by neural activity somewhere in her brain. This neural activity might be concentrated in just a few neurons, or it might be distributed across a large number of neurons. Since we do not know much about where/when this neural activity is, let's simply refer to it as the doctor's internal response. This internal response is inherently noisy. Even when there is no tumor present (no-signal trials), there will be some internal response (sometimes more, sometimes less) in the doctor's sensory system. Show less
Use the following passage to answer questions:
A doctor is examining a CT scan, looking for evidence of a tumor. Either there is a tumor (signal present) or there is not (signal absent). Either the doctor sees a tumor (she responds 'yes') or does not (she responds 'no'). There are four possible outcomes: hit (tumor present and doctor says 'yes'), miss (tumor present and doctor says 'no'), false alarm (tumor absent and doctor says 'yes'), or correct rejection (tumor absent and doctor says 'no'). Hits and correct rejections are good. False alarms and misses are bad. Detecting a tumor is difficult, and there will always be some amount of uncertainty. There are two kinds of noise factors that contribute to the uncertainty: internal noise and external noise. External noise: There are many possible sources of external noise. There can be noise factors that are part of the photographic process, a smudge, or a bad spot on the film. Or there can be something in the person's lung that is fine but looks a bit like a tumor. All of these are examples of external noise. Internal noise: Internal noise refers to the fact that neural responses are noisy. For example, a doctor may see many tumors a day and as such develop a set of neurons used when making decisions on whether a scan shows a tumor. These hypothetical tumor detectors will give noisy and variable responses. After one glance at a scan of a healthy lung, the hypothetical tumor detectors might fire 10 spikes per second. After a different glance at the same scan and under the same conditions, these neurons might fire 40 spikes per second. Internal response: It is actually not likely that there are tumor detector neurons in a radiologist's brain. But there is some internal state, reflected by neural activity somewhere in the brain, that determines the doctor's impression about whether a tumor is present. This is a fundamental issue; the state of the doctor's mind is reflected by neural activity somewhere in her brain. This neural activity might be concentrated in just a few neurons, or it might be distributed across a large number of neurons. Since we do not know much about where/when this neural activity is, let's simply refer to it as the doctor's internal response. This internal response is inherently noisy. Even when there is no tumor present (no-signal trials), there will be some internal response (sometimes more, sometimes less) in the doctor's sensory system.
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