Reconfiguration of the pontomedullary respiratory network: a computational modeling study with coordinated in vivo experiments.

A large body of data suggests that the pontine respiratory group (PRG) is involved in respiratory phase-switching and the reconfiguration of the brain stem respiratory network. However, connectivity between the PRG and ventral respiratory column (VRC) in computational models has been largely ad hoc. We developed a network model with PRG-VRC connectivity inferred from coordinated in vivo experiments. Neurons were modeled in the "integrate-and-fire" style; some neurons had pacemaker properties derived from the model of Breen et al. We recapitulated earlier modeling results, including reproduction of activity profiles of different respiratory neurons and motor outputs, and their changes under different conditions (vagotomy, pontine lesions, etc.). The model also reproduced characteristic changes in neuronal and motor patterns observed in vivo during fictive cough and during hypoxia in non-rapid eye movement sleep. Our simulations suggested possible mechanisms for respiratory pattern reorganization during these behaviors. The model predicted that network- and pacemaker-generated rhythms could be co-expressed during the transition from gasping to eupnea, producing a combined "burst-ramp" pattern of phrenic discharges. To test this prediction, phrenic activity and multiple single neuron spike trains were monitored in vagotomized, decerebrate, immobilized, thoracotomized, and artificially ventilated cats during hypoxia and recovery. In most experiments, phrenic discharge patterns during recovery from hypoxia were similar to those predicted by the model. We conclude that under certain conditions, e.g., during recovery from severe brain hypoxia, components of a distributed network activity present during eupnea can be co-expressed with gasp patterns generated by a distinct, functionally "simplified" mechanism.

Respiratory pattern generator model using Ca++-induced Ca++ release in neurons shows both pacemaker and reciprocal network properties.

There are two contradictory explanations for central respiratory rhythmogenesis. One suggests that respiratory rhythm emerges from interaction between inspiratory and expiratory neural semicenters that inhibit each other and thereby provide reciprocal rhythmic activity (Brown 1914). The other uses bursting pacemaker activity of individual neurons to produce the rhythm (Feldman and Cleland 1982). Hybrid models have been developed to reconcile these two seemingly conflicting mechanisms (Smith et al. 2000; Rybak et al. 2001). Here we report computer simulations that demonstrate a unified mechanism of the two types of oscillator. In the model, we use the interaction of Ca(++)-dependent K+ channels (Mifflin et al. 1985) with Ca(++)-induced Ca++ release from intracellular stores (McPherson and Campbell 1993), which was recently revealed in neurons (Hernandez-Cruz et al. 1997; Mitra and Slaughter 2002a,b; Scornik et al. 2001). Our computations demonstrate that uncoupled neurons with these intracellular mechanisms show conditional pacemaker properties (Butera et al. 1999) when exposed to steady excitatory inputs. Adding weak inhibitory synapses (based on increased K+ conductivity) between two model neural pools surprisingly synchronizes the activity of both neural pools. As inhibitory synaptic connections between the two pools increase from zero to higher values, the model produces first dissociated pacemaker activity of individual neurons, then periodic synchronous bursts of all neurons (inspiratory and expiratory), and finally reciprocal rhythmic activity of the neural pools.

Endogenous excitatory drive to the respiratory system in rapid eye movement sleep in cats.

A putative endogenous excitatory drive to the respiratory system in rapid eye movement (REM) sleep may explain many characteristics of breathing in that state, e.g. its irregularity and variable ventilatory responses to chemical stimuli. This drive is hypothetical, and determinations of its existence and character are complicated by control of the respiratory system by the oscillator and its feedback mechanisms. In the present study, endogenous drive was studied during apnoea caused by mechanical hyperventilation. We reasoned that if there was a REM-dependent drive to the respiratory system, then respiratory activity should emerge out of the background apnoea as a manifestation of the drive. Diaphragmatic muscle or medullary respiratory neuronal activity was studied in five intact, unanaesthetized adult cats who were either mechanically hyperventilated or breathed spontaneously in more than 100 REM sleep periods. Diaphragmatic activity emerged out of a background apnoea caused by mechanical hyperventilation an average of 34 s after the onset of REM sleep. Emergent activity occurred in 60 % of 10 s epochs in REM sleep and the amount of activity per unit time averaged approximately 40 % of eupnoeic activity. The activity occurred in episodes and was poorly related to pontogeniculo-occipital waves. At low CO2 levels, this activity was non-rhythmic. At higher CO2 levels (less than 0.5 % below eupnoeic end-tidal percentage CO2 levels in non-REM (NREM) sleep), activity became rhythmic. Medullary respiratory neurons were recorded in one of the five animals. Nineteen of twenty-seven medullary respiratory neurons were excited in REM sleep during apnoea. Excited neurons included inspiratory, expiratory and phase-spanning neurons. Excitation began about 43 s after the onset of REM sleep. Activity increased from an average of 6 impulses s-1 in NREM sleep to 15.5 impulses s-1 in REM sleep. Neuronal activity was non-rhythmic at low CO2 levels and became rhythmic when levels were less than 0.5 % below eupnoeic end-tidal levels in NREM sleep. The level of CO2 at which rhythmic neuronal activity developed corresponded to eupnoeic end-tidal CO2 levels in REM sleep. These results demonstrate an endogenous excitatory drive to the respiratory system in REM sleep and account for rapid and irregular breathing and the lower set-point to CO2 in that state.

Suppression of diaphragmatic activity during spontaneous ponto-geniculo-occipital waves in cat.

It has been reported that spontaneous ponto-geniculo-occipital (PGO) waves, which occur during REM sleep in the cat, are associated with a brief inhibition of diaphragmatic activity (Orem, 1980). This report was preliminary and not supported by a detailed analysis. We report here analysis of the relationship between PGO waves and diaphragmatic activity based on 3073 PGO waves recorded simultaneously with diaphragmatic activity. The results show that there is indeed an inhibition of diaphragmatic activity during PGO waves. This inhibition has an amplitude up to 20% of background, and a duration (approximately 80 ms) approximately coinciding with the temporal duration of the PGO wave. In addition, we analyzed the relationships among the activity of medullary respiratory neurons, PGO waves, and diaphragmatic activity. Two neurons were observed whose relationships to diaphragmatic activity and PGO waves were consistent with the idea that they mediated the PGO-associated inhibition of diaphragmatic activity. However, the number of PGO waves involved in the analysis of the interaction between medullary respiratory neuronal activity and diaphragmatic activity was small and, although suggestive, was not conclusive.

Computer simulation of a cerebellar cortex compartment. I. General principles and properties of a neural net.

Here, Marr's theory of the cerebellum is elaborated at a detailed cellular level. The experimental grounds for the theory are briefly reviewed and problems related to (mossy-fibres) - (granule cell) coding are formulated. The properties of several particular types of (mossy-fibres) - (granule cell) connection matrices are illustrated through computer simulation.

Computer simulation of a cerebellar cortex compartment. II. An information learning and its recall in the Marr's memory unit.

Computer simulation experiments are described regarding information storage and retrieval at a network consisting of one Purkinje cell and 20,000 granule cells. The information content depends on a scheme type and the properties of Purkinje cells. It is shown that a practically attainable information record efficiency is of the order 0.6 bit per binary memorising synapse. Associative information recall is demonstrated for the Marr's memory unit and expressions are derived for an information-content estimation based on parameter values obtained by simulation. The consequences of this computer simulation for physiological experiments are extensively discussed.