Imaging the femoral cortex: thickness, density and mass from clinical CT.

There is growing evidence that focal thinning of cortical bone in the proximal femur may predispose a hip to fracture. Detecting such defects in clinical CT is challenging, since cortices may be significantly thinner than the imaging system's point spread function. We recently proposed a model-fitting technique to measure sub-millimetre cortices, an ill-posed problem which was regularized by assuming a specific, fixed value for the cortical density. In this paper, we develop the work further by proposing and evaluating a more rigorous method for estimating the constant cortical density, and extend the paradigm to encompass the mapping of cortical mass (mineral mg/cm(2)) in addition to thickness. Density, thickness and mass estimates are evaluated on sixteen cadaveric femurs, with high resolution measurements from a micro-CT scanner providing the gold standard. The results demonstrate robust, accurate measurement of peak cortical density and cortical mass. Cortical thickness errors are confined to regions of thin cortex and are bounded by the extent to which the local density deviates from the peak, averaging 20% for 0.5mm cortex.

Imaging the femoral cortex: Thickness, density and mass from clinical CT

There is growing evidence that focal thinning of cortical bone in the proximal femur may predispose a hip to fracture. Detecting such defects in clinical CT is challenging, since cortices may be significantly thinner than the imaging system's point spread function. We recently proposed a model-fitting technique to measure sub-millimetre cortices, an ill-posed problem which was regularized by assuming a specific, fixed value for the cortical density. In this paper, we develop the work further by proposing and evaluating a more rigorous method for estimating the constant cortical density, and extend the paradigm to encompass the mapping of cortical mass (mineral mg/cm 2) in addition to thickness. Density, thickness and mass estimates are evaluated on sixteen cadaveric femurs, with high resolution measurements from a micro-CT scanner providing the gold standard. The results demonstrate robust, accurate measurement of peak cortical density and cortical mass. Cortical thickness errors are confined to regions of thin cortex and are bounded by the extent to which the local density deviates from the peak, averaging 20% for 0.5mm cortex. © 2012 Elsevier B.V.

The role of human orbitofrontal cortex in value comparison for incommensurable objects.

The human orbitofrontal cortex is strongly implicated in appetitive valuation. Whether its role extends to support comparative valuation necessary to explain probabilistic choice patterns for incommensurable goods is unknown. Using a binary choice paradigm, we derived the subjective values of different bundles of goods, under conditions of both gain and loss. We demonstrate that orbitofrontal activation reflects the difference in subjective value between available options, an effect evident across valuation for both gains and losses. In contrast, activation in dorsal striatum and supplementary motor areas reflects subjects' choice probabilities. These findings indicate that orbitofrontal cortex plays a pivotal role in valuation for incommensurable goods, a critical component process in human decision making.

How neurons migrate: a dynamic in-silico model of neuronal migration in the developing cortex.

BACKGROUND: Neuronal migration, the process by which neurons migrate from their place of origin to their final position in the brain, is a central process for normal brain development and function. Advances in experimental techniques have revealed much about many of the molecular components involved in this process. Notwithstanding these advances, how the molecular machinery works together to govern the migration process has yet to be fully understood. Here we present a computational model of neuronal migration, in which four key molecular entities, Lis1, DCX, Reelin and GABA, form a molecular program that mediates the migration process. RESULTS: The model simulated the dynamic migration process, consistent with in-vivo observations of morphological, cellular and population-level phenomena. Specifically, the model reproduced migration phases, cellular dynamics and population distributions that concur with experimental observations in normal neuronal development. We tested the model under reduced activity of Lis1 and DCX and found an aberrant development similar to observations in Lis1 and DCX silencing expression experiments. Analysis of the model gave rise to unforeseen insights that could guide future experimental study. Specifically: (1) the model revealed the possibility that under conditions of Lis1 reduced expression, neurons experience an oscillatory neuron-glial association prior to the multipolar stage; and (2) we hypothesized that observed morphology variations in rats and mice may be explained by a single difference in the way that Lis1 and DCX stimulate bipolar motility. From this we make the following predictions: (1) under reduced Lis1 and enhanced DCX expression, we predict a reduced bipolar migration in rats, and (2) under enhanced DCX expression in mice we predict a normal or a higher bipolar migration. CONCLUSIONS: We present here a system-wide computational model of neuronal migration that integrates theory and data within a precise, testable framework. Our model accounts for a range of observable behaviors and affords a computational framework to study aspects of neuronal migration as a complex process that is driven by a relatively simple molecular program. Analysis of the model generated new hypotheses and yet unobserved phenomena that may guide future experimental studies. This paper thus reports a first step toward a comprehensive in-silico model of neuronal migration.

Transcriptome of embryonic and neonatal mouse cortex by high-throughput RNA sequencing

Brain structure and function experience dramatic changes from embryonic to postnatal development. Microarray analyses have detected differential gene expression at different stages and in disease models, but gene expression information during early brain development is limited. We have generated >27 million reads to identify mRNAs from the mouse cortex for>16,000 genes at either embryonic day 18 (E18) or postnatal day 7 (P7), a period of significant synapto-genesis for neural circuit formation. In addition, we devised strategies to detect alternative splice forms and uncovered more splice variants. We observed differential expression of 3,758 genes between the 2 stages, many with known functions or predicted to be important for neural development. Neurogenesis-related genes, such as those encoding Sox4, Sox11, and zinc-finger proteins, were more highly expressed at E18 than at P7. In contrast, the genes encoding synaptic proteins such as synaptotagmin, complexin 2, and syntaxin were up-regulated from E18 to P7. We also found that several neurological disorder-related genes were highly expressed at E18. Our transcriptome analysis may serve as a blueprint for gene expression pattern and provide functional clues of previously unknown genes and disease-related genes during early brain development.

空间及言语工作记忆任务的情绪效应：来自ERP/ fMRI的证据

In the present study, based on processing efficiency theory, we used the event-related potentials (ERP) and functional magnetic resonance image (fMRI) techniques to explore the underlying neutral mechanism of influences of negative emotion on three subsystems of working memory, phonological loop、 visuospatial sketh pad and the central executive. The modified DSMT (delayed matching-to-sample task) and n-back tasks were adopted and IAPS (International Affective Picture System) pictures were employed to induce the expected emotional state of subjects. The main results and conclusions obtained in the series of experiments are as the following: 1. In DSM tasks, we found P200 and P300 were reduced by negative emotion in both spatial and verbal tasks, however the increased negative slow wave were only observed in spatial tasks, not in verbal tasks. 2. In n-back tasks, the updating function of WM associated P300 was affected by negative emotion only in spatial tasks, not in verbal tasks. Current density analysis revealed strong current density in the fronto-parietal cortex only in the spatial tasks as well. 3. We adopted fMRI-block design and ROIs analysis, and found significant emotion and task effects in spatial WM-associated right superior parietal cortex; only emotion effect in verbal WM-associated Broca’s area; the interaction effect in attention-associated medial prefrontal area and bilateral inferior parietal cortex. These results implied the negative emotion mainly disturbed the spatial WM-related areas, and the attention control system play a key role in the interaction of spatial WM and negative emotion. 4. to further examine the effects of positive、negative and neutral emotion on tasks with different cognitive loads, the selective effect of emotion on the ERP components of spatial WM was only found in 2-back tasks, not in visual searching tasks. So, firstly the positive emotion as well as negative emotion selectively disturbed on spatial WM in light of the attention resource competition mechanism. Secondly, the selective influences based on the different WM systems, not the properties of spatial and verbal information. At last, the manner of the interaction of emotion and cognition is correlated with the cognitive load.

基底神经节的认知和记忆功能研究

The cognition and memory functions of the Basal Ganglia have been the focus of contemporary cognitive neuroscience researches. This study, from neuroanatomical and neurophysiological point of view, thoroughly surveyed the recent relevant research progress, carefully examined the evidences of the neurological basis for the Basal Ganglia possessing or participating cognition or memory functions. Moreover, it reviewed recent achievements on the cognitive functions of the basal ganglia based on researches on rodent animals, primate animals and human beings. Then it presented a series of experiments conducted, by neuropsychological and cognitive psychological methods, on neurological patients with focal lesions to the basal ganglia or combining with bilateral hippocampus or thalamus impaired to explore what the role of the basal ganglia play in human explicit and implicit memory. It was found that the lesions to the basal ganglia partially handicapped explicit verbal memory and completely impaired perceptual priming. It was also found that right cerebral cortex dysplasia but basal ganglia spared had no effects on priming tasks performances. The results suggested that the basal ganglia contain or accommodate higher cognitive functions and further suggested that priming be irrelevant to right cerebral cortex. It was posited that the basal ganglia, on the basis of interaction with prefrontal or temporal cortices, mediate movement function as well as cognition and memory functions.

Sequence-Seeking and Counter Streams: A Model for Information Processing in the Cortex

This paper presents a model for the general flow in the neocortex. The basic process, called "sequence-seeking," is a search for a sequence of mappings or transformations, linking source and target representations. The search is bi-directional, "bottom-up" as well as "top-down," and it explores in parallel a large numbe rof alternative sequences. This operation is implemented in a structure termed "counter streams," in which multiple sequences are explored along two separate, complementary pathways which seeking to meet. The first part of the paper discusses the general sequence-seeking scheme and a number of related processes, such as the learning of successful sequences, context effects, and the use of "express lines" and partial matches. The second part discusses biological implications of the model in terms of connections within and between cortical areas. The model is compared with existing data, and a number of new predictions are proposed.

GABAA receptor chloride channels are involved in the neuroprotective role of GABA following oxygen and glucose deprivation in the rat cerebral cortex but not in the hippocampus.

Assays on "ex vivo" sections of rat hippocampus and rat cerebral cortex, subjected to oxygen and glucose deprivation (OGD) and a three-hour reperfusion-like (RL) recovery, were performed in the presence of either GABA or the GABA(A) receptor binding site antagonist, bicuculline. Lactate dehydrogenase (LDH) and propidium iodide were used to quantify cell mortality. We also measured, using real-time quantitative polymerase chain reaction (qPCR), the early transcriptional response of a number of genes of the glutamatergic and GABAergic systems. Specifically, glial pre- and post-synaptic glutamatergic transporters (namely GLAST1a, EAAC-1, GLT-1 and VGLUT1), three GABAA receptor subunits (α1, β2 and γ2), and the GABAergic presynaptic marker, glutamic acid decarboxylase (GAD65), were studied. Mortality assays revealed that GABAA receptor chloride channels play an important role in the neuroprotective effect of GABA in the cerebral cortex, but have a much smaller effect in the hippocampus. We also found that GABA reverses the OGD-dependent decrease in GABA(A) receptor transcript levels, as well as mRNA levels of the membrane and vesicular glutamate transporter genes. Based on the markers used, we conclude that OGD results in differential responses in the GABAergic presynaptic and postsynaptic systems.

How Does the Cerebral Cortex Work? Developement, Learning, Attention, and 3D Vision by Laminar Circuits of Visual Cortex

A key goal of behavioral and cognitive neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how the visual cortex sees. Visual cortex, like many parts of perceptual and cognitive neocortex, is organized into six main layers of cells, as well as characteristic sub-lamina. Here it is proposed how these layered circuits help to realize the processes of developement, learning, perceptual grouping, attention, and 3D vision through a combination of bottom-up, horizontal, and top-down interactions. A key theme is that the mechanisms which enable developement and learning to occur in a stable way imply properties of adult behavior. These results thus begin to unify three fields: infant cortical developement, adult cortical neurophysiology and anatomy, and adult visual perception. The identified cortical mechanisms promise to generalize to explain how other perceptual and cognitive processes work.

Linking Visual Cortex to Visual Perception: An Alternative to the Gestalt Bubble

Lehar's lively discussion builds on a critique of neural models of vision that is incorrect in its general and specific claims. He espouses a Gestalt perceptual approach, rather than one consistent with the "objective neurophysiological state of the visual system" (p. 1). Contemporary vision models realize his perceptual goals and also quantitatively explain neurophysiological and anatomical data.

Temporal Dynamics of Decision-Making during Motion Perception in the Visual Cortex

How does the brain make decisions? Speed and accuracy of perceptual decisions covary with certainty in the input, and correlate with the rate of evidence accumulation in parietal and frontal cortical "decision neurons." A biophysically realistic model of interactions within and between Retina/LGN and cortical areas V1, MT, MST, and LIP, gated by basal ganglia, simulates dynamic properties of decision-making in response to ambiguous visual motion stimuli used by Newsome, Shadlen, and colleagues in their neurophysiological experiments. The model clarifies how brain circuits that solve the aperture problem interact with a recurrent competitive network with self-normalizing choice properties to carry out probablistic decisions in real time. Some scientists claim that perception and decision-making can be described using Bayesian inference or related general statistical ideas, that estimate the optimal interpretation of the stimulus given priors and likelihoods. However, such concepts do not propose the neocortical mechanisms that enable perception, and make decisions. The present model explains behavioral and neurophysiological decision-making data without an appeal to Bayesian concepts and, unlike other existing models of these data, generates perceptual representations and choice dynamics in response to the experimental visual stimuli. Quantitative model simulations include the time course of LIP neuronal dynamics, as well as behavioral accuracy and reaction time properties, during both correct and error trials at different levels of input ambiguity in both fixed duration and reaction time tasks. Model MT/MST interactions compute the global direction of random dot motion stimuli, while model LIP computes the stochastic perceptual decision that leads to a saccadic eye movement.

Target Selection by Frontal Cortex During Coordinated Saccadic and Smooth Pursuit Eye Movement

Oculomotor tracking of moving objects is an important component of visually based cognition and planning. Such tracking is achieved by a combination of saccades and smooth pursuit eye movements. In particular, the saccadic and smooth pursuit systems interact to often choose the same target, and to maximize its visibility through time. How do multiple brain regions interact, including frontal cortical areas, to decide the choice of a target among several competing moving stimuli? How is target selection information that is created by a bias (e.g., electrical stimulation) transferred from one movement system to another? These saccade-pursuit interactions are clarified by a new computational neural model, which describes interactions among motion processing areas MT, MST, FPA, DLPN; saccade specification, selection, and planning areas LIP, FEF, SNr, SC; the saccadic generator in the brain stem; and the cerebellum. Model simulations explain a broad range of neuroanatomical and neurophysiological data. These results are in contrast with the simplest parallel model with no interactions between saccades and pursuit than common-target selection and recruitment of shared motoneurons. Actual tracking episodes in primates reveal multiple systematic deviations from predictions of the simplest parallel model, which are explained by the current model.