Maternal Hypothyroxinemia During Pregnancy and Growth of the Fetal and Infant Head

Severe maternal thyroid dysfunction during pregnancy affects fetal brain growth and corticogenesis. This study focused on the effect of maternal hypothyroxinemia during early pregnancy on growth of the fetal and infant head. In a population-based birth cohort, we assessed thyroid status in early pregnancy (median 13.4, 90% range 10.8-17.2), in 4894 women, and measured the prenatal and postnatal head size of their children at 5 time points. Hypothyroxinemia was defined as normal thyroid-stimulating hormone levels and free thyroxine-4 concentrations below the 10th percentile. Statistical analysis was performed using linear generalized estimating equation. Maternal hypothyroxinemia was associated with larger fetal and infant head size (overall estimate beta: 1.38, 95% confidence interval 0.56; 2.19, P = .001). In conclusion, in the general population, even small variations in maternal thyroid function during pregnancy may affect the developing head of the young child

Maternal Hypothyroxinemia During Pregnancy and Growth of the Fetal and Infant Head

Severe maternal thyroid dysfunction during pregnancy affects fetal brain growth and corticogenesis. This study focused on the effect of maternal hypothyroxinemia during early pregnancy on growth of the fetal and infant head. In a population-based birth cohort, we assessed thyroid status in early pregnancy (median 13.4, 90% range 10.8-17.2), in 4894 women, and measured the prenatal and postnatal head size of their children at 5 time points. Hypothyroxinemia was defined as normal thyroid-stimulating hormone levels and free thyroxine-4 concentrations below the 10th percentile. Statistical analysis was performed using linear generalized estimating equation. Maternal hypothyroxinemia was associated with larger fetal and infant head size (overall estimate beta: 1.38, 95% confidence interval 0.56; 2.19, P = .001). In conclusion, in the general population, even small variations in maternal thyroid function during pregnancy may affect the developing head of the young child

Adaptive Filtering Enhances Information Transmission in Visual Cortex

Sensory neuroscience seeks to understand how the brain encodes natural environments. However, neural coding has largely been studied using simplified stimuli. In order to assess whether the brain's coding strategy depend on the stimulus ensemble, we apply a new information-theoretic method that allows unbiased calculation of neural filters (receptive fields) from responses to natural scenes or other complex signals with strong multipoint correlations. In the cat primary visual cortex we compare responses to natural inputs with those to noise inputs matched for luminance and contrast. We find that neural filters adaptively change with the input ensemble so as to increase the information carried by the neural response about the filtered stimulus. Adaptation affects the spatial frequency composition of the filter, enhancing sensitivity to under-represented frequencies in agreement with optimal encoding arguments. Adaptation occurs over 40 s to many minutes, longer than most previously reported forms of adaptation.Comment: 20 pages, 11 figures, includes supplementary informatio

Functional MRI of Auditory Responses in the Zebra Finch Forebrain Reveals a Hierarchical Organisation Based on Signal Strength but Not Selectivity

BACKGROUND: Male songbirds learn their songs from an adult tutor when they are young. A network of brain nuclei known as the 'song system' is the likely neural substrate for sensorimotor learning and production of song, but the neural networks involved in processing the auditory feedback signals necessary for song learning and maintenance remain unknown. Determining which regions show preferential responsiveness to the bird's own song (BOS) is of great importance because neurons sensitive to self-generated vocalisations could mediate this auditory feedback process. Neurons in the song nuclei and in a secondary auditory area, the caudal medial mesopallium (CMM), show selective responses to the BOS. The aim of the present study is to investigate the emergence of BOS selectivity within the network of primary auditory sub-regions in the avian pallium. METHODS AND FINDINGS: Using blood oxygen level-dependent (BOLD) fMRI, we investigated neural responsiveness to natural and manipulated self-generated vocalisations and compared the selectivity for BOS and conspecific song in different sub-regions of the thalamo-recipient area Field L. Zebra finch males were exposed to conspecific song, BOS and to synthetic variations on BOS that differed in spectro-temporal and/or modulation phase structure. We found significant differences in the strength of BOLD responses between regions L2a, L2b and CMM, but no inter-stimuli differences within regions. In particular, we have shown that the overall signal strength to song and synthetic variations thereof was different within two sub-regions of Field L2: zone L2a was significantly more activated compared to the adjacent sub-region L2b. CONCLUSIONS: Based on our results we suggest that unlike nuclei in the song system, sub-regions in the primary auditory pallium do not show selectivity for the BOS, but appear to show different levels of activity with exposure to any sound according to their place in the auditory processing stream

Representation of Time-Varying Stimuli by a Network Exhibiting Oscillations on a Faster Time Scale

Sensory processing is associated with gamma frequency oscillations (30–80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input; the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp. Author Summary Sensory processing of time-varying stimuli, such as speech, is associated with high-frequency oscillatory cortical activity, the functional significance of which is still unknown. One possibility is that the oscillations are part of a stimulus-encoding mechanism. Here, we investigate a computational model of such a mechanism, a spiking neuronal network whose intrinsic oscillations interact with external input (waveforms simulating short speech segments in a single acoustic frequency band) to encode stimuli that extend over a time interval longer than the oscillation's period. The network implements a temporally sparse encoding, whose robustness to time warping and neuronal noise we quantify. To our knowledge, this study is the first to demonstrate that a biophysically plausible model of oscillations occurring in the processing of auditory input may generate a representation of signals that span multiple oscillation cycles.National Science Foundation (DMS-0211505); Burroughs Wellcome Fund; U.S. Air Force Office of Scientific Researc

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

Evaluation of dog owners' perceptions concerning radiation therapy

<p>Abstract</p> <p>Background</p> <p>External radiation therapy (RT) has been available for small animals in Sweden since 2006. This study was designed to obtain information on owner experiences and perceptions related to RT of cancer in their dogs. Another survey was used to determine the attitudes about use of RT in a group of Swedish veterinarians. Their responses were analyzed and compared to their level of knowledge of oncology and RT.</p> <p>Methods</p> <p>Owners of all dogs (n = 23) who had undergone RT for malignancy at Jönköping Small Animal Hospital between March 2006 to September 2007 were interviewed. A questionnaire was given to a selected group of veterinarians.</p> <p>Results</p> <p>All 23 owners responded. All owners thought that their dog did well during RT and most that their dog was also fine during the following phase when acute RT-related skin reactions occur and heal. Three owners stated that their dog had pain that negatively impacted quality of life because of radiation dermatitis. Five owners reported that RT positively impacted quality of life of the dog during the first weeks after RT because palliation was achieved. The owners were not disturbed by the efforts required of them. All but one owner (22 of 23) stated that they would make the same decision about RT again if a similar situation occurred. The most important factor for this decision was the chance to delay occurrence of tumour-related discomfort. The chance for cure was of less importance but still essential, followed by expected side effects. Time commitments, travel, number of treatments required and financial cost; all had low impact. The veterinarian survey showed that less background knowledge of small animal oncology/RT was associated with more negative expectations of RT for small animals.</p> <p>Conclusion</p> <p>The results show that for these owners, RT was a worthwhile treatment modality and that the discomfort for the dog was manageable and acceptable relative to the benefits. Improved continuing education about small animal RT in Sweden will likely result in increased evidence-based and positive treatment recommendations concerning RT by veterinarians.</p

Estimating Receptive Fields from Responses to Natural Stimuli with Asymmetric Intensity Distributions

The reasons for using natural stimuli to study sensory function are quickly mounting, as recent studies have revealed important differences in neural responses to natural and artificial stimuli. However, natural stimuli typically contain strong correlations and are spherically asymmetric (i.e. stimulus intensities are not symmetrically distributed around the mean), and these statistical complexities can bias receptive field (RF) estimates when standard techniques such as spike-triggered averaging or reverse correlation are used. While a number of approaches have been developed to explicitly correct the bias due to stimulus correlations, there is no complementary technique to correct the bias due to stimulus asymmetries. Here, we develop a method for RF estimation that corrects reverse correlation RF estimates for the spherical asymmetries present in natural stimuli. Using simulated neural responses, we demonstrate how stimulus asymmetries can bias reverse-correlation RF estimates (even for uncorrelated stimuli) and illustrate how this bias can be removed by explicit correction. We demonstrate the utility of the asymmetry correction method under experimental conditions by estimating RFs from the responses of retinal ganglion cells to natural stimuli and using these RFs to predict responses to novel stimuli