Intrinsic gain modulation and adaptive neural coding

In many cases, the computation of a neural system can be reduced to a receptive field, or a set of linear filters, and a thresholding function, or gain curve, which determines the firing probability; this is known as a linear/nonlinear model. In some forms of sensory adaptation, these linear filters and gain curve adjust very rapidly to changes in the variance of a randomly varying driving input. An apparently similar but previously unrelated issue is the observation of gain control by background noise in cortical neurons: the slope of the firing rate vs current (f-I) curve changes with the variance of background random input. Here, we show a direct correspondence between these two observations by relating variance-dependent changes in the gain of f-I curves to characteristics of the changing empirical linear/nonlinear model obtained by sampling. In the case that the underlying system is fixed, we derive relationships relating the change of the gain with respect to both mean and variance with the receptive fields derived from reverse correlation on a white noise stimulus. Using two conductance-based model neurons that display distinct gain modulation properties through a simple change in parameters, we show that coding properties of both these models quantitatively satisfy the predicted relationships. Our results describe how both variance-dependent gain modulation and adaptive neural computation result from intrinsic nonlinearity.Comment: 24 pages, 4 figures, 1 supporting informatio

Stimulus-dependent maximum entropy models of neural population codes

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. To be able to infer a model for this distribution from large-scale neural recordings, we introduce a stimulus-dependent maximum entropy (SDME) model---a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. The model is able to capture the single-cell response properties as well as the correlations in neural spiking due to shared stimulus and due to effective neuron-to-neuron connections. Here we show that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. As a result, the SDME model gives a more accurate account of single cell responses and in particular outperforms uncoupled models in reproducing the distributions of codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like surprise and information transmission in a neural population.Comment: 11 pages, 7 figure

Decorrelation and efficient coding by retinal ganglion cells

An influential theory of visual processing asserts that retinal center-surround receptive fields remove spatial correlations in the visual world, producing ganglion cell spike trains that are less redundant than the corresponding image pixels. For bright, high-contrast images, this decorrelation would enhance coding efficiency in optic nerve fibers of limited capacity. We tested the central prediction of the theory and found that the spike trains of retinal ganglion cells were indeed decorrelated compared with the visual input. However, most of the decorrelation was accomplished not by the receptive fields, but by nonlinear processing in the retina. We found that a steep response threshold enhanced efficient coding by noisy spike trains and that the effect of this nonlinearity was near optimal in both salamander and macaque retina. These results offer an explanation for the sparseness of retinal spike trains and highlight the importance of treating the full nonlinear character of neural codes

Receptive Field Inference with Localized Priors

The linear receptive field describes a mapping from sensory stimuli to a one-dimensional variable governing a neuron's spike response. However, traditional receptive field estimators such as the spike-triggered average converge slowly and often require large amounts of data. Bayesian methods seek to overcome this problem by biasing estimates towards solutions that are more likely a priori, typically those with small, smooth, or sparse coefficients. Here we introduce a novel Bayesian receptive field estimator designed to incorporate locality, a powerful form of prior information about receptive field structure. The key to our approach is a hierarchical receptive field model that flexibly adapts to localized structure in both spacetime and spatiotemporal frequency, using an inference method known as empirical Bayes. We refer to our method as automatic locality determination (ALD), and show that it can accurately recover various types of smooth, sparse, and localized receptive fields. We apply ALD to neural data from retinal ganglion cells and V1 simple cells, and find it achieves error rates several times lower than standard estimators. Thus, estimates of comparable accuracy can be achieved with substantially less data. Finally, we introduce a computationally efficient Markov Chain Monte Carlo (MCMC) algorithm for fully Bayesian inference under the ALD prior, yielding accurate Bayesian confidence intervals for small or noisy datasets

Antenatal and postnatal corticosteroid and resuscitation induced lung injury in preterm sheep

<p>Abstract</p> <p>Background</p> <p>Initiation of ventilation using high tidal volumes in preterm lambs causes lung injury and inflammation. Antenatal corticosteroids mature the lungs of preterm infants and postnatal corticosteroids are used to treat bronchopulmonary dysplasia.</p> <p>Objective</p> <p>To test if antenatal or postnatal corticosteroids would decrease resuscitation induced lung injury.</p> <p>Methods</p> <p>129 d gestational age lambs (n = 5-8/gp; term = 150 d) were operatively delivered and ventilated after exposure to either 1) no medication, 2) antenatal maternal IM Betamethasone 0.5 mg/kg 24 h prior to delivery, 3) 0.5 mg/kg Dexamethasone IV at delivery or 4) Cortisol 2 mg/kg IV at delivery. Lambs then were ventilated with no PEEP and escalating tidal volumes (<it>V</it>_T) to 15 mL/kg for 15 min and then given surfactant. The lambs were ventilated with <it>V</it>_T8 mL/kg and PEEP 5 cmH₂0 for 2 h 45 min.</p> <p>Results</p> <p>High V_Tventilation caused a deterioration of lung physiology, lung inflammation and injury. Antenatal betamethasone improved ventilation, decreased inflammatory cytokine mRNA expression and alveolar protein leak, but did not prevent neutrophil influx. Postnatal dexamethasone decreased pro-inflammatory cytokine expression, but had no beneficial effect on ventilation, and postnatal cortisol had no effect. Ventilation increased liver serum amyloid mRNA expression, which was unaffected by corticosteroids.</p> <p>Conclusions</p> <p>Antenatal betamethasone decreased lung injury without decreasing lung inflammatory cells or systemic acute phase responses. Postnatal dexamethasone or cortisol, at the doses tested, did not have important effects on lung function or injury, suggesting that corticosteroids given at birth will not decrease resuscitation mediated injury.</p

Air Trapping on Chest CT Is Associated with Worse Ventilation Distribution in Infants with Cystic Fibrosis Diagnosed following Newborn Screening

BACKGROUND: In school-aged children with cystic fibrosis (CF) structural lung damage assessed using chest CT is associated with abnormal ventilation distribution. The primary objective of this analysis was to determine the relationships between ventilation distribution outcomes and the presence and extent of structural damage as assessed by chest CT in infants and young children with CF. METHODS: Data of infants and young children with CF diagnosed following newborn screening consecutively reviewed between August 2005 and December 2009 were analysed. Ventilation distribution (lung clearance index and the first and second moment ratios [LCI, M(1)/M(0) and M(2)/M(0), respectively]), chest CT and airway pathology from bronchoalveolar lavage were determined at diagnosis and then annually. The chest CT scans were evaluated for the presence or absence of bronchiectasis and air trapping. RESULTS: Matched lung function, chest CT and pathology outcomes were available in 49 infants (31 male) with bronchiectasis and air trapping present in 13 (27%) and 24 (49%) infants, respectively. The presence of bronchiectasis or air trapping was associated with increased M(2)/M(0) but not LCI or M(1)/M(0). There was a weak, but statistically significant association between the extent of air trapping and all ventilation distribution outcomes. CONCLUSION: These findings suggest that in early CF lung disease there are weak associations between ventilation distribution and lung damage from chest CT. These finding are in contrast to those reported in older children. These findings suggest that assessments of LCI could not be used to replace a chest CT scan for the assessment of structural lung disease in the first two years of life. Further research in which both MBW and chest CT outcomes are obtained is required to assess the role of ventilation distribution in tracking the progression of lung damage in infants with CF

A Realistic Validation Study of a New Nitrogen Multiple-Breath Washout System

Background For reliable assessment of ventilation inhomogeneity, multiple-breath washout (MBW) systems should be realistically validated. We describe a new lung model for in vitro validation under physiological conditions and the assessment of a new nitrogen (N2)MBW system. Methods The N2MBW setup indirectly measures the N2 fraction (FN2) from main-stream carbon dioxide (CO2) and side-stream oxygen (O2) signals: FN2 = 1−FO2−FCO2−FArgon. For in vitro N2MBW, a double chamber plastic lung model was filled with water, heated to 37°C, and ventilated at various lung volumes, respiratory rates, and FCO2. In vivo N2MBW was undertaken in triplets on two occasions in 30 healthy adults. Primary N2MBW outcome was functional residual capacity (FRC). We assessed in vitro error (√[difference]2) between measured and model FRC (100–4174 mL), and error between tests of in vivo FRC, lung clearance index (LCI), and normalized phase III slope indices (Sacin and Scond). Results The model generated 145 FRCs under BTPS conditions and various breathing patterns. Mean (SD) error was 2.3 (1.7)%. In 500 to 4174 mL FRCs, 121 (98%) of FRCs were within 5%. In 100 to 400 mL FRCs, the error was better than 7%. In vivo FRC error between tests was 10.1 (8.2)%. LCI was the most reproducible ventilation inhomogeneity index. Conclusion The lung model generates lung volumes under the conditions encountered during clinical MBW testing and enables realistic validation of MBW systems. The new N2MBW system reliably measures lung volumes and delivers reproducible LCI values

Mechanisms of Maximum Information Preservation in the Drosophila Antennal Lobe

We examined the presence of maximum information preservation, which may be a fundamental principle of information transmission in all sensory modalities, in the Drosophila antennal lobe using an experimentally grounded network model and physiological data. Recent studies have shown a nonlinear firing rate transformation between olfactory receptor neurons (ORNs) and second-order projection neurons (PNs). As a result, PNs can use their dynamic range more uniformly than ORNs in response to a diverse set of odors. Although this firing rate transformation is thought to assist the decoder in discriminating between odors, there are no comprehensive, quantitatively supported studies examining this notion. Therefore, we quantitatively investigated the efficiency of this firing rate transformation from the viewpoint of information preservation by computing the mutual information between odor stimuli and PN responses in our network model. In the Drosophila olfactory system, all ORNs and PNs are divided into unique functional processing units called glomeruli. The nonlinear transformation between ORNs and PNs is formed by intraglomerular transformation and interglomerular interaction through local neurons (LNs). By exploring possible nonlinear transformations produced by these two factors in our network model, we found that mutual information is maximized when a weak ORN input is preferentially amplified within a glomerulus and the net LN input to each glomerulus is inhibitory. It is noteworthy that this is the very combination observed experimentally. Furthermore, the shape of the resultant nonlinear transformation is similar to that observed experimentally. These results imply that information related to odor stimuli is almost maximally preserved in the Drosophila olfactory circuit. We also discuss how intraglomerular transformation and interglomerular inhibition combine to maximize mutual information

Hyperresponsiveness to inhaled but not intravenous methacholine during acute respiratory syncytial virus infection in mice

BACKGROUND: To characterise the acute physiological and inflammatory changes induced by low-dose RSV infection in mice. METHODS: BALB/c mice were infected as adults (8 wk) or weanlings (3 wk) with 1 × 10(5 )pfu of RSV A2 or vehicle (intranasal, 30 μl). Inflammation, cytokines and inflammatory markers in bronchoalveolar lavage fluid (BALF) and airway and tissue responses to inhaled methacholine (MCh; 0.001 – 30 mg/ml) were measured 5, 7, 10 and 21 days post infection. Responsiveness to iv MCh (6 – 96 μg/min/kg) in vivo and to electrical field stimulation (EFS) and MCh in vitro were measured at 7 d. Epithelial permeability was measured by Evans Blue dye leakage into BALF at 7 d. Respiratory mechanics were measured using low frequency forced oscillation in tracheostomised and ventilated (450 bpm, flexiVent) mice. Low frequency impedance spectra were calculated (0.5 – 20 Hz) and a model, consisting of an airway compartment [airway resistance (Raw) and inertance (Iaw)] and a constant-phase tissue compartment [coefficients of tissue damping (G) and elastance (H)] was fitted to the data. RESULTS: Inflammation in adult mouse BALF peaked at 7 d (RSV 15.6 (4.7 SE) vs. control 3.7 (0.7) × 10(4 )cells/ml; p < 0.001), resolving by 21 d, with no increase in weanlings at any timepoint. RSV-infected mice were hyperresponsive to aerosolised MCh at 5 and 7 d (PC(200 )Raw adults: RSV 0.02 (0.005) vs. control 1.1 (0.41) mg/ml; p = 0.003) (PC(200 )Raw weanlings: RSV 0.19 (0.12) vs. control 10.2 (6.0) mg/ml MCh; p = 0.001). Increased responsiveness to aerosolised MCh was matched by elevated levels of cysLT at 5 d and elevated VEGF and PGE(2 )at 7 d in BALF from both adult and weanling mice. Responsiveness was not increased in response to iv MCh in vivo or EFS or MCh challenge in vitro. Increased epithelial permeability was not detected at 7 d. CONCLUSION: Infection with 1 × 10(5 )pfu RSV induced extreme hyperresponsiveness to aerosolised MCh during the acute phase of infection in adult and weanling mice. The route-specificity of hyperresponsiveness suggests that epithelial mechanisms were important in determining the physiological effects. Inflammatory changes were dissociated from physiological changes, particularly in weanling mice

Tidal Volume Single Breath Washout of Two Tracer Gases - A Practical and Promising Lung Function Test

Small airway disease frequently occurs in chronic lung diseases and may cause ventilation inhomogeneity (VI), which can be assessed by washout tests of inert tracer gas. Using two tracer gases with unequal molar mass (MM) and diffusivity increases specificity for VI in different lung zones. Currently washout tests are underutilised due to the time and effort required for measurements. The aim of this study was to develop and validate a simple technique for a new tidal single breath washout test (SBW) of sulfur hexafluoride (SF(6)) and helium (He) using an ultrasonic flowmeter (USFM)