In this paper we provide a quantitative electroencephalogram (EEG) analysis to study the effect of hypothermia on the neurological recovery of brain after cardiac arrest. We hypothesize that the brain injury results in a reduction in information of the brain rhythm. To measure the information content of the EEG a new measure called information quantity (IQ), which is the Shannon entropy of decorrelated EEG signals, is developed. For decorrelating EEG signals, we use the discrete wavelet transform (DWT) which is known to have good decorrelating properties and to show a good match to the standard clinical bands in EEG. In simulation for measuring the amount of information, the IQ shows better tracking capability for dynamic amplitude change and frequency component change than conventional entropy-based measures. Experiments are carried out in rodents to monitor the neurological recovery after cardiac arrest. In addition, EEG signal recovery under normothermic (37 degrees C) and hypothermic (33 degrees C) resuscitation following 5, 7 and 9 minutes of cardiac arrest is recorded and analyzed. Experimental results show that the IQ is higher for hypothermic than normothermic rats. The results quantitatively support the hypothesis that hypothermia accelerates the recovery of brain injury after cardiac arrest.