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In this work we studied the neural state transitions undergone by the hippocampal neural network using a hidden Markov model (HMM) framework. We first employed a measure based on the Lempel-Ziv (LZ) estimator to characterize the changes in the hippocampal oscillation patterns in terms of their complexity. These oscillations correspond to different modes of hippocampal network synchronization induced by the cholinergic agonist carbachol in the CA1 region of mice hippocampus. HMMs are then used to model the dynamics of the LZ-derived complexity signals as first-order Markov chains. Consequently, the signals corresponding to our oscillation recordings can be segmented into a sequence of statistically discriminated hidden states. The segmentation is used for detecting transitions in neural synchronization modes in data recorded from wild-type and triple transgenic mice models (3xTG) of Alzheimer's disease (AD). Our data suggest that transition from low-frequency (delta range) continuous oscillation mode into high-frequency (theta range) oscillation, exhibiting repeated burst-type patterns, occurs always through a mode resembling a mixture of the two patterns, continuous with burst. The relatively random patterns of oscillation during this mode may reflect the fact that the neuronal network undergoes re-organization. Further insight into the time durations of these modes (retrieved via the HMM segmentation of the LZ-derived signals) reveals that the mixed mode lasts significantly longer (p < 10(-4)) in 3xTG AD mice. These findings, coupled with the documented cholinergic neurotransmission deficits in the 3xTG mice model, may be highly relevant for the case of AD.

In this paper, we examined the effect of nicotine exposure and increased body temperature on the complexity (dynamics) of the genioglossus muscle (EMGg) and the diaphragm muscle (EMGdia) to explore the effects of nicotine and hyperthermia. Nonlinear dynamical analysis of the EMGdia and EMGg signals was performed using the approximate entropy method on 15 (7 saline- and 8 nicotine-treated) juvenile rats (P25-P35) and 19 (11 saline- and 8 nicotine-treated) young adult rats (P36-P44). The mean complexity values were calculated over the ten consecutive breaths using the approximate entropy method during mild elevated body temperature (38 degrees C) and severe elevated body temperature (39-40 degrees C) in two groups. In the first (nicotine) group, rats were treated with single injections of nicotine enough to produce brain levels of nicotine similar to those achieved in human smokers (2.5 (mg kg(-1))/day) until the recording day. In the second (control) group, rats were treated with injections of saline, beginning at postnatal 5 days until the recording day. Our results show that warming the rat by 2-3 degrees C and nicotine exposure significantly decreased the complexity of the EMGdia and EMGg for the juvenile age group. This reduction in the complexity of the EMGdia and EMGg for the nicotine group was much greater than the normal during elevated body temperatures. We speculate that the generalized depressive effects of nicotine exposure and elevated body temperature on the respiratory neural firing rate and the behavior of the central respiratory network could be responsible for the drastic decrease in the complexity of the EMGdia and EMGg signals, the outputs of the respiratory neural network during early maturation.

We investigated the influence of 2-APB (2-aminoethoxy-diphenylborate) acute exposure on hippocampal oscillations using time-frequency analysis methods including continuous wavelet transform and short-time Fourier transform. We hypothesized that acute exposure to 2-APB drastically reduced the hippocampal gamma oscillations. We estimated the hippocampal oscillations' time-frequency representations from 24 hippocampal slices in five rats. Our results indicated that it took at least 100 ms to see any hippocampal activities in response to the 100 Hz stimulus. The hippocampal oscillations' spectral energies dominated in the 31-60 Hz and 61-90 Hz frequency bands in the early time (100-200 ms) segment post-stimulus and in the 31-60 Hz and 61-90 Hz frequency bands after 200 ms until 400 ms post-stimulus. They were noticeably reduced in the late time segment (above 400 ms). The hippocampal oscillations' spectral energies in the 31-60 and 61-90 Hz frequency bands still dominated the early time segment after the acute 2-APB exposure. The 2-APB exposure never changed the energy content in all three frequency bands in the early time segment (p > 0.01). The exposure significantly reduced the energy content in both the mid-time segment and in the 31-60 Hz frequency band (p < 0.001) and in both the second time segment and in the 61-90 Hz frequency band (p < 0.01). Additionally, in the late time segment, the energy content in all three frequency bands was notably reduced post-drug exposure (p < 0.001).

In this paper, we examine the effect of elevated body temperature on the complexity of the diaphragm electromyography (EMGdia), the output of the respiratory neural network--using the approximate entropy method. The diaphragm EMG, EEG, EOG as well as other physiological signals (tracheal pressure, blood pressure and respiratory volume) in chronically instrumented rats were recorded at two postnatal ages: 25-35 days age (juvenile, n = 5) and 36-44 days age (early adult, n = 6) groups during control (36-37 degrees C), mild elevated body temperature (38 degrees C) and severe elevated body temperature (39-40 degrees C). Three to five trials of the recordings were performed at normal body temperature before raising the animal's core temperature by 1-4 degrees C with an electric heating pad. At the elevated temperature, another 3-5 trials were performed. Finally, the animal was cooled to the original temperature, and trials were again repeated. Complexity values of the diaphragm EMG signal were estimated and evaluated using the approximate entropy method (ApEn) over the ten consecutive breaths. Our results suggested that the mean approximate entropy values for the juvenile age group were 1.01 +/- 0.01 (standard error) during control, 0.91 +/- 0.02 during mild elevated body temperature and 0.81 +/- 0.02 during severe elevated body temperature. For the early adult age group, these values were 0.94 +/- 0.01 during control, 0.93 +/- 0.01 during mild elevated body temperature and 0.92 +/- 0.01 during severe elevated body temperature. Our results show that the complexity values and the durations of the diaphragm EMG (EMGdia) were significantly decreased when the elevated body temperature was shifted from control or mild to severe body temperature (p < 0.05) for the juvenile age group. However, for the early adult age group, an increase in body temperature slightly reduced the complexity measures and the duration of the EMGdia. But, these changes were not statistically significant. These results furthermore suggest that during maturation, the output of the central pattern generator becomes less complex probably because the elevated body temperature reduces the neural activity and alters the behavior of the central respiratory controller, making it more susceptible to sudden infant death syndrome (SIDS).

Since sleep is known to influence respiratory activity we studied whether the sleep state would affect the complexity value of the respiratory network output. Specifically, we tested the hypothesis that the complexity values of the diaphragm EMG (EMGdia) activity would be lower during REM compared to NREM. Furthermore, since REM is primarily generated by a homogeneous population of neurons in the medulla, the possibility that REM-related respiratory output would be less complex than that of the awake state was also considered. Additionally, in order to examine the influence of neuron vulnerabilities within the rostral ventral medulla (RVM) on the complexity of the respiratory network output, we inhibited respiratory neurons in the RVM by microdialysis of GABA(A) receptor agonist muscimol. Diaphragm EMG, nuchal EMG, EEG, EOG as well as other physiological signals (tracheal pressure, blood pressure and respiratory volume) were recorded from five unanesthetized chronically instrumented intact piglets (3-10 days old). Complexity of the diaphragm EMG (EMGdia) signal during wakefulness, NREM and REM was evaluated using the approximate entropy method (ApEn). ApEn values of the EMGdia during NREM and REM sleep were found significantly (p < 0.05 and p < 0.001, respectively) lower than those of awake EMGdia after muscimol inhibition. In the absence of muscimol, only the differences between REM and wakefulness ApEn values were found to be significantly different.

In this paper, we investigate the influence of hypercapnia on the dynamics of the phrenic neurogram in the piglet in two different age groups: 3-7 days (n = 11) and 10-16 days (n = 9). The phrenic neurogram was recorded from 17 piglets (3-16 days old) during control (40% O(2) with 3-5% end-tidal CO(2)), mild hypercapnia (40% O(2) with 7% CO(2)) and severe hypercapnia (40% O(2) with 15% CO(2)) and analyzed using the approximate entropy (ApEn) method. The mean values of the approximate entropy (complexity) of phrenic neurograms during the first 7 days of the postnatal age were 1.56 +/- 0.1 (standard deviation) during normal breathing, 1.51 +/- 0.1 during mild hypercapnia and 1.37 +/- 0.08 during severe hypercapnia. These values for the 10-16 days age group were 1.51 +/- 0.1 during control, 1.49 +/- 0.11 during mild hypercapnia and 1.38 +/- 0.05 during severe hypercapnia. The mean values of phrenic neurogram durations during the first 7 days of the postnatal age were 0.82 +/- 0.03 (standard deviation) s during normal breathing, 0.85 +/- 0.007 s during mild hypercapnia and 0.65 +/- 0.05 s during severe hypercapnia. These values for the 10-16 days age group were 0.97 +/- 0.09 s during control, 1.10 +/- 0.05 during mild hypercapnia and 0.78 +/- 0.05 s during severe hypercapnia. Our results show that the complexity values of the phrenic neurogram were significantly decreased when the CO(2) concentration was shifted from control or mild to severe hypercapnia (p < 0.05) for both the 3-7 days old and the 10-16 days old groups. In addition, the duration of the phrenic neurogram decreased when the concentration was shifted from control or mild to severe hypercapnia (p < 0.05). But no significant changes in the duration of the phrenic neurogram were observed between control and mild hypercapnia concentration. These results suggest that severe hypercapnia can be characterized with a significant decrease of the complexity values and durations of the phrenic neurogram during inspiration during early maturation.

In this paper, we assess the complexity (fractal measure) of body motion during walking in patients with Parkinson's disease. The body motion of 11 patients with Parkinson's disease and 10 healthy elderly subjects was recorded using a triaxial accelerometry technique. A triaxial accelerometer was attached to the lumbar region. An assessment of the complexity of body motion was made using a maximum-likelihood-estimator-based fractal analysis method. Our data suggest that the fractal measures of the body motion of patients with Parkinson's disease are higher than those of healthy elderly subjects. These results were statistically different in the X (anteroposterior), Y (lateral) and Z (vertical) directions of body motion between patients with Parkinson's disease and the healthy elderly subjects (p < 0.01 in X and Z directions and p < 0.05 in Y direction). The complexity (fractal measure) of body motion can be useful to assess and monitor the output from the motor system during walking in clinical practice.

Progressive hypoxemia in anesthetized, peripherally chemodenervated piglets results in initial depression of the phrenic neurogram (PN) culminating in phrenic silence and, eventually, gasping. These changes reverse after the 30 min reoxygenation (recovery) period. To determine if changes in the PN patterns correspond to changes in temporal patterning, we have used the approximate entropy (ApEn) method to examine the effects of maturation on the complexity of breathing patterns in chemodenervated, vagotomized and decerebrated piglets during severe hypoxia and reoxygenation. The phrenic neurogram in piglets was recorded during eupnea (normal breathing), severe hypoxia (gasping) and recovery from severe hypoxia in 31 piglets (2-35 days). Nonlinear dynamical analysis of the phrenic neurogram was performed using the ApEn method. The mean ApEn values for a recording of five consecutive breaths during eupnea, a few phrenic neurogram signals during gasping, the beginning of the recovery period, and five consecutive breaths at every 5 min interval for the 30 min recovery period were calculated. Our data suggest that gasping resulted in reduced duration of the phrenic neurogram, and the gasp-like patterns exist at the beginning of the recovery. But, the durations of phrenic neurograms during recovery were increased after 10 min postreoxygenation, but were restored 30 min post recovery. The ApEn (complexity) values of the phrenic neurogram during eupnea were higher than those of gasping and the early (the onset of) recovery from severe hypoxia (p < 0.01), but were not statistically different than 5 min post recovery regardless of the maturation stages. These results suggest that hypoxia results in a reversible reconfiguration of the central respiratory pattern generator.