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Ideal observer analysis can be augmented similarly to incorporate research involving more complex stimulus content.
A larger advantage of the EM algorithm can be expected under more complex stimulus mixtures.
By utilizing more complex stimulus statistics that approximate those found in language [11], [12], this experimental paradigm could provide a real-time window into subcortical function during the learning process itself [62], [63].
The maximum in our study seems to peak somewhat later, which is probably caused by a more complex stimulus presentation in our study.
One advantage of these alternative spike-triggered methods is that they can be readily applied to more complex stimulus conditions, such as natural stimuli.
Therefore, skull tapping is a more complex stimulus type, likely to result in activation of multiple sensors on both sides of the head bilaterally activating the superior and inferior vestibular nerves [ 23, 24].
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Rapidly changing urban surroundings and exposure to more complex stimuli may also enhance intelligence.
Some of the other examples of learning considered earlier have already suggested that animals can actually respond to additional, more complex stimuli.
Aftereffects also occur for more complex stimuli, such as faces.
Firstly, pictures are evidently more complex stimuli than letters and digits.
More recently, the range of stimuli used to probe sensory function has been expanded to include more complex stimuli such as Gaussian white noise.
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