Publication Date: 2010 Sep PMID: 20803786
Authors: Wiedemann, C.
Journal: Nat Rev Neurosci



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Publication Date: 2010 Sep PMID: 20725096
Authors: Hackman, D. A. - Farah, M. J. - Meaney, M. J.
Journal: Nat Rev Neurosci

Human brain development occurs within a socioeconomic context and childhood socioeconomic status (SES) influences neural development--particularly of the systems that subserve language and executive function. Research in humans and in animal models has implicated prenatal factors, parent-child interactions and cognitive stimulation in the home environment in the effects of SES on neural development. These findings provide a unique opportunity for understanding how environmental factors can lead to individual differences in brain development, and for improving the programmes and policies that are designed to alleviate SES-related disparities in mental health and academic achievement.

MeSH Categories: Animals, Brain/*growth & development/*physiology/physiopathology, Cognition/physiology, Humans, Mental Disorders/physiopathology, *Social Class

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Publication Date: 2010 Sep PMID: 20725095
Authors: Kumar, A. - Rotter, S. - Aertsen, A.
Journal: Nat Rev Neurosci

The brain is a highly modular structure. To exploit modularity, it is necessary that spiking activity can propagate from one module to another while preserving the information it carries. Therefore, reliable propagation is one of the key properties of a candidate neural code. Surprisingly, the conditions under which spiking activity can be propagated have received comparatively little attention in the experimental literature. By contrast, several computational studies in the last decade have addressed this issue. Using feedforward networks (FFNs) as a generic network model, they have identified two dynamical activity modes that support the propagation of either asynchronous (rate code) or synchronous (temporal code) spiking. Here, we review the dichotomy of asynchronous and synchronous propagation in FFNs, propose their integration into a single extended conceptual framework and suggest experimental strategies to test our hypothesis.

MeSH Categories: *Action Potentials, Animals, Humans, *Neural Networks (Computer), Neural Pathways/physiology, Neurons/*physiology

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Publication Date: 2010 Sep PMID: 20717121
Authors: Vollenweider, F. X. - Kometer, M.
Journal: Nat Rev Neurosci

After a pause of nearly 40 years in research into the effects of psychedelic drugs, recent advances in our understanding of the neurobiology of psychedelics, such as lysergic acid diethylamide (LSD), psilocybin and ketamine have led to renewed interest in the clinical potential of psychedelics in the treatment of various psychiatric disorders. Recent behavioural and neuroimaging data show that psychedelics modulate neural circuits that have been implicated in mood and affective disorders, and can reduce the clinical symptoms of these disorders. These findings raise the possibility that research into psychedelics might identify novel therapeutic mechanisms and approaches that are based on glutamate-driven neuroplasticity.

MeSH Categories: Animals, Brain/*drug effects, Hallucinogens/*pharmacology/therapeutic use, Humans, Models, Neurological, Mood Disorders/drug therapy

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Publication Date: 2010 Sep PMID: 20700142
Authors: Gottfried, J. A.
Journal: Nat Rev Neurosci

The stimulus complexity of naturally occurring odours presents unique challenges for central nervous systems that are aiming to internalize the external olfactory landscape. One mechanism by which the brain encodes perceptual representations of behaviourally relevant smells is through the synthesis of different olfactory inputs into a unified perceptual experience--an odour object. Recent evidence indicates that the identification, categorization and discrimination of olfactory stimuli rely on the formation and modulation of odour objects in the piriform cortex. Convergent findings from human and rodent models suggest that distributed piriform ensemble patterns of olfactory qualities and categories are crucial for maintaining the perceptual constancy of ecologically inconstant stimuli.

MeSH Categories: Animals, Brain/anatomy & histology/*physiology, Discrimination (Psychology)/physiology, Humans, Odors, Olfactory Pathways/anatomy & histology/physiology, Olfactory Perception/*physiology, Pattern Recognition, Physiological/physiology

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Publication Date: 2010 Sep 1 PMID: 20809258
Authors: Lopour, B. A. - Tasoglu, S. - Kirsch, H. E. - Sleigh, J. W. - Szeri, A. J.
Journal: J Comput Neurosci

Here we show that a mathematical model of the human sleep cycle can be used to obtain a detailed description of electroencephalogram (EEG) sleep stages, and we discuss how this analysis may aid in the prediction and prevention of seizures during sleep. The association between EEG data and the cortical model is found via locally linear embedding (LLE), a method of dimensionality reduction. We first show that LLE can distinguish between traditional sleep stages when applied to EEG data. It reliably separates REM and non-REM sleep and maps the EEG data to a low-dimensional output space where the sleep state changes smoothly over time. We also incorporate the concept of strongly connected components and use this as a method of automatic outlier rejection for EEG data. Then, by using LLE on a hybrid data set containing both sleep EEG and signals generated from the mesoscale cortical model, we quantify the relationship between the data and the mathematical model. This enables us to take any sample of sleep EEG data and associate it with a position among the continuous range of sleep states provided by the model; we can thus infer a trajectory of states as the subject sleeps. Lastly, we show that this method gives consistent results for various subjects over a full night of sleep and can be done in real time.

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Publication Date: 2010 Aug 27 PMID: 20799059
Authors: Fey, D. - Commins, S. - Bullinger, E.
Journal: J Comput Neurosci

The Morris water maze is an experimental procedure in which animals learn to escape swimming in a pool using environmental cues. Despite its success in neuroscience and psychology for studying spatial learning and memory, the exact mnemonic and navigational demands of the task are not well understood. Here, we provide a mathematical model of rat swimming dynamics on a behavioural level. The model consists of a random walk, a heading change and a feedback control component in which learning is reflected in parameter changes of the feedback mechanism. The simplicity of the model renders it accessible and useful for analysis of experiments in which swimming paths are recorded. Here, we used the model to analyse an experiment in which rats were trained to find the platform with either three or one extramaze cue. Results indicate that the 3-cues group employs stronger feedback relying only on the actual visual input, whereas the 1-cue group employs weaker feedback relying to some extent on memory. Because the model parameters are linked to neurological processes, identifying different parameter values suggests the activation of different neuronal pathways.

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Publication Date: 2010 Aug 27 PMID: 20799058
Authors: Bradley, P. J. - Wiesenfeld, K. - Butera, R. J.
Journal: J Comput Neurosci

A significant degree of heterogeneity in synaptic conductance is present in neuron to neuron connections. We study the dynamics of weakly coupled pairs of neurons with heterogeneities in synaptic conductance using Wang-Buzsaki and Hodgkin-Huxley model neurons which have Types I and II excitability, respectively. This type of heterogeneity breaks a symmetry in the bifurcation diagrams of equilibrium phase difference versus the synaptic rate constant when compared to the identical case. For weakly coupled neurons coupled with identical values of synaptic conductance a phase locked solution exists for all values of the synaptic rate constant, alpha. In particular, in-phase and anti-phase solutions are guaranteed to exist for all alpha. Heterogeneity in synaptic conductance results in regions where no phase locked solution exists and the general loss of the ubiquitous in-phase and anti-phase solutions of the identically coupled case. We explain these results through examination of interaction functions using the weak coupling approximation and an in-depth analysis of the underlying multiple cusp bifurcation structure of the systems of coupled neurons.

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Publication Date: 2010 Aug 27 PMID: 20799057
Authors: Lizier, J. T. - Heinzle, J. - Horstmann, A. - Haynes, J. D. - Prokopenko, M.
Journal: J Comput Neurosci

The human brain undertakes highly sophisticated information processing facilitated by the interaction between its sub-regions. We present a novel method for interregional connectivity analysis, using multivariate extensions to the mutual information and transfer entropy. The method allows us to identify the underlying directed information structure between brain regions, and how that structure changes according to behavioral conditions. This method is distinguished in using asymmetric, multivariate, information-theoretical analysis, which captures not only directional and non-linear relationships, but also collective interactions. Importantly, the method is able to estimate multivariate information measures with only relatively little data. We demonstrate the method to analyze functional magnetic resonance imaging time series to establish the directed information structure between brain regions involved in a visuo-motor tracking task. Importantly, this results in a tiered structure, with known movement planning regions driving visual and motor control regions. Also, we examine the changes in this structure as the difficulty of the tracking task is increased. We find that task difficulty modulates the coupling strength between regions of a cortical network involved in movement planning and between motor cortex and the cerebellum which is involved in the fine-tuning of motor control. It is likely these methods will find utility in identifying interregional structure (and experimentally induced changes in this structure) in other cognitive tasks and data modalities.

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Publication Date: 2010 Aug 21 PMID: 20730481
Authors: Dimitrov, A. G. - Cummins, G. I. - Baker, A. - Aldworth, Z. N.
Journal: J Comput Neurosci

We present an application of the information distortion approach to neural coding. The approach allows the discovery of neural symbols and the corresponding stimulus space of a neuron or neural ensemble simultaneously and quantitatively, making few assumptions about the nature of either code or relevant features. The neural codebook is derived by quantizing sensory stimuli and neural responses into small reproduction sets, and optimizing the quantization to minimize the information distortion function. The application of this approach to the analysis of coding in sensory interneurons involved a further restriction of the space of allowed quantizers to a smaller family of parametric distributions. We show that, for some cells in this system, a significant amount of information is encoded in patterns of spikes that would not be discovered through analyses based on linear stimulus-response measures.

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Publication Date: 2010 Aug 21 PMID: 20730480
Authors: Kim, A. J. - Lazar, A. A. - Slutskiy, Y. B.
Journal: J Comput Neurosci

The lack of a deeper understanding of how olfactory sensory neurons (OSNs) encode odors has hindered the progress in understanding the olfactory signal processing in higher brain centers. Here we employ methods of system identification to investigate the encoding of time-varying odor stimuli and their representation for further processing in the spike domain by Drosophila OSNs. In order to apply system identification techniques, we built a novel low-turbulence odor delivery system that allowed us to deliver airborne stimuli in a precise and reproducible fashion. The system provides a 1% tolerance in stimulus reproducibility and an exact control of odor concentration and concentration gradient on a millisecond time scale. Using this novel setup, we recorded and analyzed the in-vivo response of OSNs to a wide range of time-varying odor waveforms. We report for the first time that across trials the response of OR59b OSNs is very precise and reproducible. Further, we empirically show that the response of an OSN depends not only on the concentration, but also on the rate of change of the odor concentration. Moreover, we demonstrate that a two-dimensional (2D) Encoding Manifold in a concentration-concentration gradient space provides a quantitative description of the neuron's response. We then use the white noise system identification methodology to construct one-dimensional (1D) and two-dimensional (2D) Linear-Nonlinear-Poisson (LNP) cascade models of the sensory neuron for a fixed mean odor concentration and fixed contrast. We show that in terms of predicting the intensity rate of the spike train, the 2D LNP model performs on par with the 1D LNP model, with a root mean-square error (RMSE) increase of about 5 to 10%. Surprisingly, we find that for a fixed contrast of the white noise odor waveforms, the nonlinear block of each of the two models changes with the mean input concentration. The shape of the nonlinearities of both the 1D and the 2D LNP model appears to be, for a fixed mean of the odor waveform, independent of the stimulus contrast. This suggests that white noise system identification of Or59b OSNs only depends on the first moment of the odor concentration. Finally, by comparing the 2D Encoding Manifold and the 2D LNP model, we demonstrate that the OSN identification results depend on the particular type of the employed test odor waveforms. This suggests an adaptive neural encoding model for Or59b OSNs that changes its nonlinearity in response to the odor concentration waveforms.

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Publication Date: 2010 Aug 20 PMID: 20725773
Authors: Chandrasekaran, L. - Achuthan, S. - Canavier, C. C.
Journal: J Comput Neurosci

Phase response curves (PRCs) have been widely used to study synchronization in neural circuits comprised of pacemaking neurons. They describe how the timing of the next spike in a given spontaneously firing neuron is affected by the phase at which an input from another neuron is received. Here we study two reciprocally coupled clusters of pulse coupled oscillatory neurons. The neurons within each cluster are presumed to be identical and identically pulse coupled, but not necessarily identical to those in the other cluster. We investigate a two cluster solution in which all oscillators are synchronized within each cluster, but in which the two clusters are phase locked at nonzero phase with each other. Intuitively, one might expect this solution to be stable only when synchrony within each isolated cluster is stable, but this is not the case. We prove rigorously the stability of the two cluster solution and show how reciprocal coupling can stabilize synchrony within clusters that cannot synchronize in isolation. These stability results for the two cluster solution suggest a mechanism by which reciprocal coupling between brain regions can induce local synchronization via the network feedback loop.

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Publication Date: 2010 Aug 19 PMID: 20721613
Authors: Martiniuc, A. V. - Knoll, A.
Journal: J Comput Neurosci

The estimation of motion direction from time varying retinal images is a fundamental task of visual systems. Neurons that selectively respond to directional visual motion are found in almost all species. In many of them already in the retina direction selective neurons signal their preferred direction of movement. Scientific evidences suggest that direction selectivity is carried from the retina to higher brain areas. Here we adopt a simple integrate-and-fire neuron model, inspired by recent work of Casti et al. (2008), to investigate how directional selectivity changes in cells postsynaptic to directional selective retinal ganglion cells (DSRGC). Our model analysis shows that directional selectivity in the postsynaptic cells increases over a wide parameter range. The degree of directional selectivity positively correlates with the probability of burst-like firing of presynaptic DSRGCs. Postsynaptic potentials summation and spike threshold act together as a temporal filter upon the input spike train. Prior to the intricacy of neural circuitry between retina and higher brain areas, we suggest that sharpening is a straightforward result of the intrinsic spiking pattern of the DSRGCs combined with the summation of excitatory postsynaptic potentials and the spike threshold in postsynaptic neurons.

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Publication Date: 2010 Aug 18 PMID: 20717840
Authors: Clewley, R.
Journal: J Comput Neurosci

This work presents a neuroinformatic method for deriving mechanistic descriptions of fine-structured neural activity. This is a new development in the computer-assisted analysis of dynamics in conductance-based models, which is illustrated using single compartment models of an action potential. A sequence of abstract, qualitative motifs is inferred from this analysis, forming a template that is independent of the specific equations from which they were abstracted. The template encodes the assumptions behind the model reduction steps used to derive the motifs, and so specifies quantitative information about their domains of validity. The template representation of a mechanism is converted to a hybrid dynamical system, which is simulated as a sequence of low-dimensional reduced models (in this example, phase plane models) with appropriate switching conditions taken from the motifs. We demonstrate the validity of the template on a detailed single neuron model of spiking taken from the literature, and show that the corresponding hybrid system simulation closely mimics the spiking dynamics of the full model.

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Publication Date: 2010 Aug 13 PMID: 20706781
Authors: Vicente, R. - Wibral, M. - Lindner, M. - Pipa, G.
Journal: J Comput Neurosci

Understanding causal relationships, or effective connectivity, between parts of the brain is of utmost importance because a large part of the brain's activity is thought to be internally generated and, hence, quantifying stimulus response relationships alone does not fully describe brain dynamics. Past efforts to determine effective connectivity mostly relied on model based approaches such as Granger causality or dynamic causal modeling. Transfer entropy (TE) is an alternative measure of effective connectivity based on information theory. TE does not require a model of the interaction and is inherently non-linear. We investigated the applicability of TE as a metric in a test for effective connectivity to electrophysiological data based on simulations and magnetoencephalography (MEG) recordings in a simple motor task. In particular, we demonstrate that TE improved the detectability of effective connectivity for non-linear interactions, and for sensor level MEG signals where linear methods are hampered by signal-cross-talk due to volume conduction.

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Publication Date: 2010 Aug 11 PMID: 20700637
Authors: Achuthan, S. - Butera, R. J. - Canavier, C. C.
Journal: J Comput Neurosci

A phase resetting curve (PRC) keeps track of the extent to which a perturbation at a given phase advances or delays the next spike, and can be used to predict phase locking in networks of oscillators. The PRC can be estimated by convolving the waveform of the perturbation with the infinitesimal PRC (iPRC) under the assumption of weak coupling. The iPRC is often defined with respect to an infinitesimal current as z(i)(varphi), where varphi is phase, but can also be defined with respect to an infinitesimal conductance change as z(g)(varphi). In this paper, we first show that the two approaches are equivalent. Coupling waveforms corresponding to synapses with different time courses sample z(g)(varphi) in predictably different ways. We show that for oscillators with Type I excitability, an anomalous region in z(g)(varphi) with opposite sign to that seen otherwise is often observed during an action potential. If the duration of the synaptic perturbation is such that it effectively samples this region, PRCs with both advances and delays can be observed despite Type I excitability. We also show that changing the duration of a perturbation so that it preferentially samples regions of stable or unstable slopes in z(g)(varphi) can stabilize or destabilize synchrony in a network with the corresponding dynamics.

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Publication Date: 2010 Aug 10 PMID: 20697790
Authors: Dehghani, N. - Bedard, C. - Cash, S. S. - Halgren, E. - Destexhe, A.
Journal: J Comput Neurosci

The resistive or non-resistive nature of the extracellular space in the brain is still debated, and is an important issue for correctly modeling extracellular potentials. Here, we first show theoretically that if the medium is resistive, the frequency scaling should be the same for electroencephalogram (EEG) and magnetoencephalogram (MEG) signals at low frequencies (<10 Hz). To test this prediction, we analyzed the spectrum of simultaneous EEG and MEG measurements in four human subjects. The frequency scaling of EEG displays coherent variations across the brain, in general between 1/f and 1/f (2), and tends to be smaller in parietal/temporal regions. In a given region, although the variability of the frequency scaling exponent was higher for MEG compared to EEG, both signals consistently scale with a different exponent. In some cases, the scaling was similar, but only when the signal-to-noise ratio of the MEG was low. Several methods of noise correction for environmental and instrumental noise were tested, and they all increased the difference between EEG and MEG scaling. In conclusion, there is a significant difference in frequency scaling between EEG and MEG, which can be explained if the extracellular medium (including other layers such as dura matter and skull) is globally non-resistive.

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This paper reviews the literature on the nature and incidence of child sexual abuse, explores the link between child sexual abuse and later sexual exploitation, and reviews the literature on prevention strategies and effective interventions in child sexual abuse services. Our understanding of the international epidemiology of child sexual abuse is considerably greater than it was just 10 years ago, and studies from around the world are examined. Childhood sexual abuse can involve a wide number of psychological sequelae, including low self-esteem, anxiety, and depression. Numerous studies have noted that child sexual abuse victims are vulnerable to later sexual revictimization, as well as the link between child sexual abuse and later engagement in high-risk sexual behaviour. Survivors of child sexual abuse are more likely to have multiple sex partners, become pregnant as teenagers, and experience sexual assault as adults. Various models which attempt to account for this inter-relationship are presented; most invoke mediating variables such as low self-esteem, drug/alcohol use, PTSD and distorted sexual development. Prevention strategies for child sexual abuse are examined including media campaigns, school-based prevention programmes, and therapy with abusers. The results of a number of meta-analyses are examined. However, researchers have identified significant methodological limitations in the extant research literature that impede the making of recommendations for implementing existing therapeutic programmes unreservedly.

Studies report that women use as much or more physical intimate partner violence (IPV) as men. Most of these studies measure IPV by counting the number of IPV acts over a specified time period, but counting acts captures only one aspect of this complex phenomenon. To inform interventions, women’s motivations for using IPV must be understood. A systematic review, therefore, was conducted to summarize evidence regarding women’s motivations for the use of physical IPV in heterosexual relationships. Four published literature databases were searched, and articles that met inclusion criteria were abstracted. This was supplemented with a bibliography search and expert consultation. Eligible studies included English-language publications that directly investigated heterosexual women’s motivations for perpetrating nonlethal, physical IPV. Of the 144 potentially eligible articles, 23 met inclusion criteria. Over two thirds of studies enrolled participants from IPV shelters, courts, or batterers’ treatment programs. Women’s motivations were primarily assessed through interviews or administration of an author-created questionnaire. Anger and not being able to get a partner’s attention were pervasive themes. Self-defense and retaliation also were commonly cited motivations, but distinguishing the two was difficult in some studies. Control was mentioned but not listed as a primary motivation. IPV prevention and treatment programs should explore ways to effectively address women’s relationship concerns and ability to manage anger and should recognize that women commonly use IPV in response to their partner’s violence.

Domestic violence (DV) against women during pregnancy affects many women and unborn infants worldwide. Pregnancy presents a window of opportunity for health care providers to identify DV and provide appropriate intervention. The aim of this systematic review was to appraise the effectiveness of DV screening and interventions for women identified for DV through screening in pregnancy. The Cochrane Library, EMBASE, MEDLINE, and PsycINFO were searched from January 1995 to November 2009 to identify potentially relevant studies. Studies using any comparative methodology from both national and international arenas were included but had to be in the English language. Nine studies (13 references) met the inclusion criteria, five for screening and four for interventions. Of the five screening studies, the identification of DV was significantly higher compared to studies that used a nonstandardized screen or no screen at all. There was also evidence that recurrent screening throughout the pregnancy further increased identification rates. There was some evidence that interventions for pregnant women who had experienced DV reduced the amount of violence experienced by these women, but the evidence is very limited by the small number of randomized studies with small participant numbers. Further research is required to establish the most effective interventions for women who are identified at risk of DV during pregnancy.