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Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems.

The elucidation of organism-scale metabolic networks necessitates the development of integrative methods to analyze and interpret the systemic properties of cellular metabolism. A shift in emphasis from single metabolic reactions to systemically defined pathways is one consequence of such an integrative analysis of metabolic systems. The constraints of systemic stoichiometry, and limited thermodynamics have led to the definition of the flux space within the context of convex analysis. The flux space of the metabolic system, containing all allowable flux distributions, is constrained to a convex polyhedral cone in a high-dimensional space. From metabolic pathway analysis, the edges of the high-dimensional flux cone are vectors that correspond to systemically defined "extreme pathways" spanning the capabilities of the system. The addition of maximum flux capacities of individual metabolic reactions serves to further constrain the flux space and has led to the development of flux balance analysis using linear optimization to calculate optimal flux distributions. Here we provide the precise theoretical connections between pathway analysis and flux balance analysis allowing for their combined application to study integrated metabolic function. Shifts in metabolic behavior are calculated using linear optimization and are then interpreted using the extreme pathways to demonstrate the concept of pathway utilization. Changes to the reaction network, such as the removal of a reaction, can lead to the generation of suboptimal phenotypes that can be directly attributed to the loss of pathway function and capabilities. Optimal growth phenotypes are calculated as a function of environmental variables, such as the availability of substrate and oxygen, leading to the definition of phenotypic phase planes. It is illustrated how optimality properties of the computed flux distributions can be interpreted in terms of the extreme pathways. Together these developments are applied to an example network and to core metabolism of Escherichia coli demonstrating the connections between the extreme pathways, optimal flux distributions, and phenotypic phase planes. The consequences of changing environmental and internal conditions of the network are examined for growth on glucose and succinate in the face of a variety of gene deletions. The convergence of the calculation of optimal phenotypes through linear programming and the definition of extreme pathways establishes a different perspective for the understanding of how a defined metabolic network is best used under different environmental and internal conditions or, in other words, a pathway basis for the interpretation of the metabolic reaction norm.

Glucose↗

PubMed2003

Topology and computational performance of attractor neural networks.

To explore the relation between network structure and function, we studied the computational performance of Hopfield-type attractor neural nets with regular lattice, random, small-world, and scale-free topologies. The random configuration is the most efficient for storage and retrieval of patterns by the network as a whole. However, in the scale-free case retrieval errors are not distributed uniformly among the nodes. The portion of a pattern encoded by the subset of highly connected nodes is more robust and efficiently recognized than the rest of the pattern. The scale-free network thus achieves a very strong partial recognition. The implications of these findings for brain function and social dynamics are suggestive.

Journal Article↗

PubMed1979

Innervation of hippocampal explants by central catecholaminergic neurons in co-cultured fetal mouse brain stem explants.

The ability of central catecholaminergic neurons to grow into and establish functional connections with the hippocampus in vitro was studied using organotypic tissue culture. Brain stem explanted from the region of the locus coeruleus and hippocampal explants, from 18-day fetal mice, were maintained as co-cultures and were also grown separately. After 1-4 weeks these tissues were analyzed by glyoxylic acid-induced histofluorescence, by light and electron microscopic radioautography after incubation with [3H]norepinephrine, and by electrophysiology. Brain stem explants exhibited specifically fluorescent catecholaminergic cell bodies and varicose fibers after 2-4 weeks in culture. In contrast, no fluorescent cells or neurites could be seen in isolated hippocampal cultures grown for 2-3 weeks in vitro. When hippocampal explants were grown near brain stem explants, catecholaminergic fibers grew out of the brain stem and entered the hippocampus. In additional experiments, co-cultures of brain stem and hippocampus were incubated with [3H]norepinephrine (0.5 micron) and the monoamine oxidase inhibitor nialamide (100 micron). Radioautographic analyses revealed that brain stem neurites which entered the hippocampus took up norepinephrine, whereas neurites in the isolated hippocampal explants did not. Electron microscopic studies of the hippocampus showed varicose axon terminals within the hippocampus to be preferentially labeled. Although close relationships could be seen between labeled axons and dendrites, junctions exhibiting the membranous modifications associated with synapses were never seen. Electrophysiological studies suggested that the catecholaminergic neurites within the hippocampus were functional. Complex synaptically mediated slow wave discharges could be evoked by electrical stimuli in isolated hippocampal explants. Introduction of the beta adrenergic antagonist propranolol (0.4-4.3 micron) did not alter, or slightly depressed, these hippocampal discharges. On the other hand, in hippocampus-brain stem co-cultures, these concentrations of propranolol enhanced the complex hippocampal responses to brain stem or hippocampal stimuli. Similar enhancement of hippocampal responses by propranolol also occurred in these cocultures after acute surgical extirpation of the brain stem explant. The data suggest, therefore, that the action of propranol was probably to block adrenergic inhibitory connections with hippocampal synaptic networks. These experiments provide morphological and electrophysiological evidence that catecholaminergic neurons from fetal mouse brain stem maintained in organotypic tissue culture can grow into and functionally innervate the hippocampus.

Animals↗

PubMed1994

Refined structure of transketolase from Saccharomyces cerevisiae at 2.0 A resolution.

The crystal structure of transketolase from Saccharomyces cerevisiae has been refined to a crystallographic residual of 15.7% at 2.0 A resolution using the program package X-PLOR. The refined model of the transketolase homodimer, corresponding to 1356 amino acid residues in the asymmetric unit, consists of 10,396 protein atoms, 1040 solvent molecules, 52 thiamine diphosphate atoms and two calcium ions. All amino acid residues except for the two N-terminal residues of the two subunits are defined in the electron density maps and refined. The estimated root-mean-square (r.m.s.) error of the model is less than 0.2 A as deduced from Luzzati plots. The r.m.s. deviation from ideality is 0.017 A for bond distances and 3.1 degrees for bond angles. The main-chain torsion angles of non-glycine residues lie within the allowed regions of the Ramachandran plots. The model shows a very good fit to the electron density maps. The average B-factor for all protein atoms in the first subunit is 19 A2, and 15A2 in the second. The average B-factor for solvent atoms is 32A2. The two subunits of transketolase were refined independently and have nearly identical structures with an r.m.s. deviation of 0.24 A for C alpha atoms 3 to 680, and slightly less when aligning the individual domains. A few exceptions from the 2-fold symmetry are found, mostly in the surface residues. The thiamine diphosphate cofactors have identical conformations. The cofactor is shielded from solvent except for the C-2 atom of the thiazolium ring. A calcium ion is bound to the diphosphate group of thiamine and protein ligands. The metal binding site and the interactions of thiamine diphosphate with protein residues are described. A network of hydrogen bonds consisting of glutamic acid residues and internal water molecules connects the two thiamine diphosphate molecules. Its structure and possible functional implications are discussed.

Amino Acid Sequence↗

PubMed1987

Detection and estimation of neural connectivity based on crosscorrelation analysis.

Crosscorrelation analysis of simultaneously recorded activity of pairs of neurons is a common tool to infer functional neural connectivity. The adequacy of crosscorrelation procedures to detect and estimate neural connectivity has been investigated by means of computer simulations of small networks composed of fairly realistic modelneurons. If the mean interval of neural firings is much larger than the duration of postsynaptic potentials, which will be the case in many central brain areas excitatory connections are easier to detect than inhibitory ones. On the other hand, inhibitory connections are revealed better if the mean firing interval is much smaller than post-synaptic potential duration. In general the effects of external stimuli and the effects of neural connectivity do not add linearly. Furthermore, neurons may exhibit a certain degree of timelock to the stimulus. For these reasons the commonly applied "shift predictor" procedure to separate stimulus and neural effects appears to be of limited value. In case of parallel direct and indirect neural pathways between two neurons crosscorrelation analysis does not estimate the direct connection but instead an effective connectivity, which reflects the combined influences of the parallel pathways.

Animals↗

PubMed2006

Generalized cortex activation by the auditory midbrain: Mediation by acetylcholine and subcortical relays.

The inferior colliculus (IC) is a critical component of the ascending projection system carrying auditory information from the brainstem to the forebrain. Recent evidence indicates that, in addition to its role in auditory processing, the IC can exert a generalized, modulatory effect on the forebrain by activating the neocortical electrocorticogram (ECoG). Given the sparse direct projections from the IC to the cortex, it appears that the effect of the IC to produce ECoG activation is indirect, mediated by one or several neuromodulatory systems that have diffuse access to the entire cortical mantle. However, the anatomical relays that permit the IC to influence cortical activity have not been elucidated. In the present experiments, electrical stimulation of the IC suppressed slow, large amplitude oscillations in the ECoG of urethane anesthetized rats, replacing them with higher-frequency cortical activation. This effect was blocked by the muscarinic receptor antagonist scopolamine (0.5-1.0 mg/kg, i.p.), suggestive of a critical role of acetylcholine (ACh) release. Consistent with this hypothesis, localized lidocaine infusions (2%, 1 microl) into the cholinergic basal forebrain complex strongly reduced ECoG activation elicited by IC stimulation. To identify additional relays between the IC and basal forebrain, the effects of lidocaine infusions into the superior colliculus, medial prefrontal cortex, midline thalamus, and dorsal raphe were also studied. Inactivation of the superior colliculus and dorsal raphe reduced IC-induced activation, while prefrontal cortex and thalamic infusions were ineffective. Concurrent basal forebrain and raphe inactivation produced effects similar to that of inactivation of the basal forebrain alone, suggesting that these two areas are arranged in series, rather than acting as independent, parallel pathways. These results suggest that the ability of the IC to induce ECoG activation is mediated, in large parts, by the basal forebrain cholinergic system. Consistent with anatomical evidence, the superior colliculus and dorsal raphe appear to provide important links to functionally connect the IC to the basal forebrain, allowing the IC to indirectly access the entire cortical mantle and enhance processing in neocortical networks.

Acetylcholine↗

PubMed2003

Combined functional MRI and tractography to demonstrate the connectivity of the human primary motor cortex in vivo.

In this study, we combined advanced MR techniques to explore primary motor cortex (M1) connectivity in the human brain. We matched functional and anatomical information using motor functional MRI (fMRI) and white matter tractography inferred from diffusion tensor imaging (DTI). We performed coregistered DTI and motor task fMRI in 8 right-handed healthy subjects and in 1 right-handed patient presenting with a left precentral tumour. We used the fast-marching tractography (FMT) algorithm to define 3D connectivity maps within the whole brain, from seed points selected in the white matter adjacent to the location of the maximum of fMRI activation. Connectivity maps were then anatomically normalised and analysed using statistical parametric mapping software (SPM99) allowing group comparisons (left versus right hemisphere in control subjects and patient versus control subjects). The results demonstrated, in all control subjects, strong connections from M1 to the pyramidal tracts, premotor areas, parietal cortices, thalamus, and cerebellum. M1 connectivity was asymmetric, being more extensive in the dominant hemisphere. The patient had differences in M1 connectivity from the control group. Thus, fMRI-correlated DTI-FMT is a promising tool to study the structural basis of functional networks in the human brain in vivo.

Adult↗

PubMed1983

A multifunction network of computers in a large pathology department. Integration of word processing, data base management, and general purpose computing using network principles.

We report the strategies for design and implementation of a system of compatible mini- and microcomputers intended to improve efficiency of data handling and research in several clinical and academic divisions of a large university hospital department of Pathology. A dedicated, preprogrammed, multiuser, word processing computer and small standalone word processing stations connected to a general purpose minicomputer, using standard network protocols for communication, permit virtually error-free movement of data between computers doing functionally distinct tasks of word processing, data base management, and general scientific computing. User programming is minimized and is done in a simple, well-known, high-level language. We show that cost, thruput, speed, document volume, document size, revision cycle frequency, data base size, and frequency of use are important design criteria and that existing staff can be trained easily to operate the systems.

Computers↗

PubMed2005

Rate equation approach for correlations in growing network models.

We propose a rate equation approach to compute two vertex correlations in scale-free growing network models based on the preferential attachment mechanism. The formalism, based on previous work of Szabo [Phys. Rev. E. 67, 056102 (2002)] for the clustering spectrum, measuring three vertex correlations, is based on a rate equation in the continuous degree and time approximation for the average degree of the nearest neighbors of vertices of degree k , with an appropriate boundary condition. We study the properties of both two and three vertex correlations for linear preferential attachment models, and also for a model yielding a large clustering coefficient. The expressions obtained are checked by means of extensive numerical simulations. The rate equation proposed can be generalized to more sophisticated growing network models, and also extended to deal with related correlation measures. As an example, we consider the case of a recently proposed model of weighted networks, for which we are able to compute a weighted two vertex correlation function, taking into account the strength of the interactions between connected vertices.

Journal Article↗

PubMed1994

Supervised training of dynamical neural networks for associative memory design and identification of nonlinear maps.

Complexity of implementation has been a major difficulty in the development of gradient descent learning algorithms for dynamical neural networks with feedback and recurrent connections. Some insights from the stability properties of the equilibrium points of the network, which suggest an appropriate tailoring of the sigmoidal nonlinear functions, can however be utilized in obtaining simplified learning rules, as demonstrated in this paper. An analytical proof of convergence of the learning scheme under specific conditions is given and some upper bounds on the adaptation parameters for an efficient implementation of the training procedure are developed. The performance features of the learning algorithm are illustrated by applying it to two problems of importance, viz., design of associative memories and nonlinear input-output mapping. For the first application, a systematic procedure is given for training a network to store multiple memory vectors as its stable equilibrium points, whereas for the second application, specific training rules are developed for a three-layer network architecture comprising a dynamical hidden layer for the identification of nonlinear input-output maps. A comparison with the performance of a standard backpropagation network provides an illustration of the capabilities of the present network architecture and the learning algorithm.

Algorithms↗

PubMed1992

Parallel distributed network characteristics of the DSCT.

1. We examined the functional organization of the dorsal spinocerebellar tract (DSCT) and found that it is similar to that of a parallel distributed network having widespread connectivity among parallel elements. The prevailing view is that the DSCT provides receptor-specific information to the cerebellum regarding muscle and cutaneous inputs from the hindlimbs, but that view does not consider the convergent inputs to DSCT neurons from multimodal polysynaptic pathways. 2. Spontaneously active DSCT neurons respond to peripheral stimulation with changes in their firing probability. We characterized the temporal patterns of poststimulus excitability changes for a large number of neurons using principal component analysis. The response of each neuron was represented by a response vector in three-dimensional principal component space, in which similar vectors represent responses having a similar waveform for their poststimulus activity patterns. 3. We compared the responses of large populations of DSCT units to two types of stimuli: small (3-8 deg) passive rotations of the foot at the ankle of an intact limb (234 cells) and stretch or contraction of an isolated muscle group (gastrocnemius-soleus, 168 cells). Most of the cells tested had significant responses (P < 0.05) to both types of stimuli (40-78% responded to muscle stimulation and 88% to foot rotation), and they exhibited similar patterns of poststimulus activity. Long-lasting inhibitory responses and excitatory responses with a range of peak times (< 10- > 60 ms) were prevalent in all cases. The population response to each stimulus was characterized by the relative incidence of response types among the units in a representative sample of the population. 4. The time course of excitability changes induced in DSCT cells by the stimuli could have been determined primarily by the presynaptic circuitry or by postsynaptic factors intrinsic to the DSCT cells. The evidence presented suggests that the selection of response waveforms and their distribution among the DSCT cells was determined presynaptically. We found that individual cells were capable of diverse responses to different stimuli. 5. Sample groups of 7-30 cells were selected at random and also on the basis of the similarity of their responses to one type of stimulus. The distributions of response types among the cells of the sample groups were compared to the distributions for the entire population recorded for each stimulus.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

PubMed1998

RST: a connectionist architecture to deal with spatiotemporal relationships.

In the past decade, connectionism has proved its efficiency in the field of static pattern recognition. The next challenge is to deal with spatiotemporal problems. This article presents a new connectionist architecture, RST (réseau spatio temporel [spatio temporal network]), with such spatiotemporal capacities. It aims at taking into account at the architecture level both spatial relationships (e.g., as between neighboring pixels in an image) and temporal relationships (e.g., as between consecutive images in a video sequence). Concerning the spatial aspect, the network is embedded in actual space (two) or three-dimensional-, the metrics of which directly influence its structure through a connection distribution function. For the temporal aspect, we looked toward biology and used a leaky-integrator neuron model with a refractory period and postsynaptic potentials. The propagation of activity by spatiotemporal synchronized waves enables RST to perform motion detection and localization in sequences of video images.

Image Processing, Computer-Assisted↗

PubMed2005

The human hippocampus: cognitive maps or relational memory?

The hippocampus is widely accepted to play a pivotal role in memory. Two influential theories offer competing accounts of its fundamental operating mechanism. The cognitive map theory posits a special role in mapping large-scale space, whereas the relational theory argues it supports amodal relational processing. Here, we pit the two theories against each other using a novel paradigm in which the relational processing involved in navigating in a city was matched with similar navigational and relational processing demands in a nonspatial (social) domain. During functional magnetic resonance imaging, participants determined the optimal route either between friends' homes or between the friends themselves using social connections. Separate brain networks were engaged preferentially during the two tasks, with hippocampal activation driven only by spatial relational processing. We conclude that the human hippocampus appears to have a bias toward the processing of spatial relationships, in accordance with the cognitive map theory. Our results both advance our understanding of the nature of the hippocampal contribution to memory and provide insights into how social networks are instantiated at the neural level.

Adult↗

PubMed2006

Network theory to understand microarray studies of complex diseases.

Complex diseases, such as allergy, diabetes and obesity depend on altered interactions between multiple genes, rather than changes in a single causal gene. DNA microarray studies of a complex disease often implicate hundreds of genes in the pathogenesis. This indicates that many different mechanisms and pathways are involved. How can we understand such complexity? How can hypotheses be formulated and tested? One approach is to organize the data in network models and to analyze these in a top-down manner. Globally, networks in nature are often characterized by a small number of highly connected nodes, while the majority of nodes have few connections. The highly connected nodes serve as hubs that affect many other nodes. Such hubs have key roles in the network. In yeast cells, for example, deletion of highly connected proteins is associated with increased lethality, compared to deletion of less connected proteins. This suggests the biological relevance of networks. Moving down in the network structure, there may be sub-networks or modules with specific functions. These modules may be further dissected to analyze individual nodes. In the context of DNA microarray studies of complex diseases, gene-interaction networks may contain modules of co-regulated or interacting genes that have distinct biological functions. Such modules may be linked to specific gene polymorphisms, transcription factors, cellular functions and disease mechanisms. Genes that are reliably active only in the context of their modules can be considered markers for the activity of the modules and may thus be promising candidates for biomarkers or therapeutic targets. This review aims to give an introduction to network theory and how it can be applied to microarray studies of complex diseases.

Humans↗

PubMed2005

Functional connectivity in elderly controls and AD patients using resting state fMRI: a pilot study.

Conventionally, Alzheimer's disease (AD) and other dementias are diagnosed using clinical assessment, neuropsychology and also structural neuroimaging, showing neuronal degeneration starting in the hippocampal regions. However, there is an increasing need for a new method that is more sensitive to early AD identification than currently possible. A new promising technique that may be used for this is to measure local brain activation using functional magnetic resonance imaging (fMRI), since functional loss predates structural loss of brain tissue. A new method to apply fMRI is to study connectivity between brain regions during a resting state without application of a task. Recent data suggest that connectivity within memory systems during such a resting state is associated with the level of memory function. Here we explain how we will study healthy elderly controls, patients with a mild cognitive impairment (MCI, considered to be a transitional stage between normal condition and AD), and AD patients using resting state connectivity fMRI. If resting state connectivity is sensitive to cognitive decline, this will be of great importance for noninvasive dementia research, offering a tool to easily study functional networks in the brain without the requirement of a memory task, and perhaps offering a tool sensitive for early diagnostics.

Aged↗

PubMed1997

[Intervention of GABAergic neurotransmission in partial epilepsies].

The gamma-aminobutyric acid (GABA) is one of the most important inhibitory transmitter in the CNS. When GABA is released in the synaptic cleft, it can act on two types of receptors, type A (GABAA-R) and type B. The GABAA-R is an ionotropic receptor whose subunits form a chloride channel. It contains specific binding sites at least for GABA, benzodiazepines, picrotoxin, barbiturates, anesthetic steroids, divalent cations such as Zn2+ and other compounds. Neurotransmitters and neuropeptides that regulate intracellular second messengers may modulate the responses of GABAA-R in the post-synaptic membrane and thus affect the synaptic plasticity. While consensus sites for several kinases are present on many subunit-subtypes, the functional consequences of these phosphorylations are unclear. However, the maintenance of normal GABA currents required the activity of a unique kinase specific for the GABAA-R. This intracellular regulation site might be involved in synaptic plasticity and considered as a site of vulnerability for epileptogenesis. The generation of epileptic discharge, synchronized burst firing and interictal spikes, can be subsequent to the alteration of GABAA-R function. A consequence of GABAergic disinhibition is the formation of new polysynaptic pathways leading to a network of neurons that were previously not connected. Cell loss and plasticity are currently observed in most patients with temporal lobe epilepsy. CA1 pyramidal cells are missing and mossy fibers of dentate granule cells project back through the granule cell layer to form recurrent terminals on granule cell dendrites. This mossy fiber sprouting leads to the destruction of most dentate hilar somatostatine interneurons. Nevertheless, local circuit neurons containing glutamic acid decarboxylase survive in this layer and in all regions of the sclerotic hippocampus. A decrease of the GABA release has been proposed as a basis for disinhibition temporal-lobe epilepsy is partially characterized by a loss of glutamate-stimulated GABA release that is secondary to a reduction in the number of GABA transporters. A molecular reorganization of GABAA-R subunits has been suggested in the kindling model of temporal lobe epilepsy because the zinc released from abberantly sprouted mossy fiber terminals is responsible for a collapse of augmented inhibition by GABA. These results support the concept of a loss of inhibition in chronic epilepsy models and probably in human epilepsies.

Animals↗

PubMed2004

Basic organization principles of the VOR: lessons from frogs.

Locomotion is associated with a number of optical consequences that degrade visual information processing in the absence of appropriate compensatory movements. The resulting retinal image flow is counteracted by coordinated eye-head reflexes that are initiated by optokinetic and vestibular inputs. The contribution of the vestibulo-ocular reflex (VOR) for stabilizing retinal images is relatively small in amplitude in frogs but important in function by compensating for the non-linearities of the neck motor system. The spatial tuning of the VOR networks underlying the angular (AVOR) and linear (LVOR) with respect to canal and extraocular motor coordinates is organized in a common, canal-related reference frame. Thereby, the axes of head and eye rotation are aligned, principle and auxiliary VOR connections transform vestibular into motor signals and parallel AVOR and LVOR circuits mediate vergence and version signals separately. Comparison of these results with data from other vertebrates demonstrates a number of fundamental organization principles common to most vertebrates. However, the fewer degrees of behavioral freedom of frogs are reflected by the absence of, e.g. a functioning velocity storage network or of a fixation suppression of the VOR. In vitro experiments with the isolated brainstem and branches of N.VIII attached were used to study the putative transmitters of vestibular nerve afferent inputs, the postsynaptic receptor subtypes of second-order vestibular neurons and their dynamic response properties. Evidence is presented that suggests that afferent vestibular nerve fibers with different dynamic response properties activate different subtypes of glutamate receptors. The convergence pattern of monosynaptic afferent nerve inputs from different labyrinthine organs onto second-order vestibular neurons is remarkably specific. As a rule, second-order vestibular neurons receive converging afferent nerve inputs from one semicircular canal and from a specific sector of hair cells on one otolith organ. This convergence pattern remains malleable even in adulthood and reorganization is initiated by activity-related changes in vestibular nerve afferent fibers. The output of second-order vestibular neurons is modified by at least three inhibitory control loops. Uncrossed inhibitory vestibular side loops appear to control specifically the dynamic response tuning, whereas coplanar commissural inhibitory inputs improve mainly the spatial tuning and the cerebellar feedback loop controls the response gain. Among the targets of second-order vestibular projection neurons are extraocular motoneurons and internuclear neurons. Extraocular motoneurons differ among each other by the presence of very different response dynamics. These differences may represent a co-adaptation to the response dynamics of twitch and non-twitch extraocular muscle fibers. Different dynamical properties are required for a rapid acceleration of the globe at the one end and for the maintenance of a stable eccentric eye position over long periods of time at the other end of a continuum of variations in dynamic response properties. The maintenance of a given eccentric eye position over long periods of time is especially well developed in frogs and assists visual surveillance during lurking in the absence of saccades.

Animals↗

PubMed2007

Functional imaging reveals respiratory network activity during hypoxic and opioid challenge in the neonate rat tilted sagittal slab preparation.

In mammals, respiration-modulated networks are distributed rostrocaudally in the ventrolateral quadrant of the medulla. Recent studies have established that in neonate rodents, two spatially separate networks along this column-the parafacial respiratory group (pFRG) and the pre-Bötzinger complex (preBötC)-are hypothesized to be sufficient for respiratory rhythm generation, but little is known about the connectivity within or between these networks. To be able to observe how these networks interact, we have developed a neonate rat medullary tilted sagittal slab, which exposes one column of respiration-modulated neurons on its surface, permitting functional imaging with cellular resolution. Here we examined how respiratory networks responded to hypoxic challenge and opioid-induced depression. At the systems level, the sagittal slab was congruent with more intact preparations: hypoxic challenge led to a significant increase in respiratory period and inspiratory burst amplitude, consistent with gasping. At opioid concentrations sufficient to slow respiration, we observed periods at integer multiples of control, matching quantal slowing. Consistent with single-unit recordings in more intact preparations, respiratory networks were distributed bimodally along the rostrocaudal axis, with respiratory neurons concentrated at the caudal pole of the facial nucleus, and 350 microns caudally, at the level of the pFRG and the preBötC, respectively. Within these regions neurons active during hypoxia- and/or opioid-induced depression were ubiquitous and interdigitated. In particular, contrary to earlier reports, opiate-insensitive neurons were found at the level of the preBötC.

Analgesics, Opioid↗