According to the Nyquist Frequency, what is the sampling rate required for an analysis?

The Nyquist Frequency principle states that in order to accurately sample and reconstruct a signal without losing any information, the sampling rate must be at least twice the highest frequency present in that signal. This concept, known as the Nyquist rate, ensures that all frequencies within the signal are captured effectively. By sampling at this rate, one can prevent aliasing, which occurs when higher frequency components are misinterpreted as lower frequency components due to insufficient sampling.

Therefore, the correct answer highlights that the sampling rate must be at least 2x greater than the highest frequency in the signal. This ensures that the original signal can be reconstructed completely from the samples without any loss of information, which is crucial in neurophysiologic monitoring where accurate signal representation is essential for proper interpretation and clinical decisions.

The other options, although they incorporate relevant ideas about frequency and sampling, do not align with the fundamental requirement set forth by the Nyquist theorem. The requirement to sample at least equal to, or half the highest frequency, does not adequately protect against aliasing, whereas suggesting an even larger factor, like ten times the highest frequency, might be overly conservative and unnecessary for effective sampling in many practical scenarios.