Language outside the focus of attention: the mismatch negativity as a tool for studying higher cognitive processes

Which aspects of language and cognitive processing take place irrespective of whether subjects focus their attention on incoming stimuli and are, in this sense, automatic? The Mismatch Negativity (MMN), a neurophysiological brain response recorded in the EEG and MEG, is elicited by attended and unattended stimuli alike. Recent studies investigating the cognitive processes underlying spoken language processing found that even under attentional withdrawal, MMN size and topography reflect the activation of memory traces for language elements in the human brain. Familiar sounds of one's native language elicit a larger MMN than unfamiliar sounds, and at the level of meaningful language units, words elicit a larger MMN than meaningless pseudowords. This suggests that the MMN reflects the activation of memory networks for language sounds and spoken words. Unattended word stimuli elicit an activation sequence starting in superior-temporal cortex and rapidly progressing to left-inferior-frontal lobe. The spatio-temporal patterns of cortical activation depend on lexical and semantic properties of word stems and affixes, thus indicating that the MMN can give clues about lexico-semantic information processing stored in long term memory. At the syntactic level, MMN size was found to reflect whether a word string conforms to abstract grammatical rules. This growing body of results suggests that lexical, semantic and syntactic information can be processed by the central nervous system outside the focus of attention in a largely automatic manner. Analysis of spatio-temporal patterns of generator activations underlying the MMN to speech may be an important tool for investigating the brain dynamics of spoken language processing and the activated distributed cortical circuits acting at long-term memory traces.     

mGlu5 negative allosteric modulators: a patent review (2010 – 2012)

Introduction: The design and development of small molecule negative allosteric modulators (NAMs) of the metabotropic glutamate receptor subtype 5 (mGlu₅) has been an area of intense interest for over a decade. Potential roles have been established for mGlu₅ NAMs in the treatment of diseases such as pain, anxiety, gastroesophageal reflux disease (GERD), Parkinson's disease levodopa-induced dyskinesia (PD-LID), fragile X syndrome (FXS), autism, addiction, and depression.

Areas covered: This review begins with an update of the clinical trial efforts with mGlu₅ NAMs. Following that update, the review summarizes small molecule mGlu₅ NAM patent applications published between 2010 and 2012. These summaries are subdivided into three separate groups: inventions related to improvements in drug properties and/or developability, new chemical entities that contain a disubstituted alkyne, and new chemical entities that do not contain a disubstituted alkyne.

Expert opinion: Given the abundant promise found within the mGlu₅ NAM field, optimism remains that a drug will emerge from this therapeutic class. Still, the launch of a new drug is far from a certainty. It is encouraging to observe the ever-increasing chemical diversity among mGlu₅ NAMs. Finally, in spite of the mature nature of this field, room remains for new advancements.     

Strategies to assess blood–brain barrier penetration

Background: The principles and screening strategies for brain penetration in drug discovery are important in identifying drug candidates with desirable CNS properties. Objective: Define key variables and assays that are essential for determining brain penetration. Methods: This review covers issues, methods, and strategies for assessing brain penetration of small molecules in drug discovery. Results/conclusion: Brain penetration is assessed using both initial rate and extent at steady-state. Unbound drug is the active species that exerts pharmacological effects. Low brain penetration can be due to low blood–brain barrier (BBB) permeability, P-glycoprotein (Pgp) efflux, or high plasma protein binding. Successful methods include: parallel artificial membrane permeability assay (PAMPA)-BBB permeability, MDR1-MDCKII for Pgp efflux, B-P dialysis for fraction unbound, and in vivo B/P ratio to extrapolate unbound brain drug concentration.     

早产儿神经行为检测及早期干预在儿科保健门诊中应用的效果评价

目的 探讨神经行为检测对早产儿早期神经行为异常发现率的影响,评价医院家庭干预模式对早产儿生长发育的影响,以期为早产儿早期神经行为异常的检测和干预提供依据,进一步探讨在儿科保健门诊普遍开展神经行为检测的可行性.方法 对干预组152例早产儿纠正月龄后进行新生儿神经行为测定,对评分＜37分者建议定期在医院进行干预治疗(包括运动疗法和物理治疗,配合神经电刺激治疗仪等);评分≥37分者给家长发放个性化训练计划,指导家长在家中进行干预训练,在随访中根据神经测评情况调整干预内容.纠正月龄3个月后应用《0～6岁小儿神经心理行为检查》量表进行发育评估,应用52项神经行为检查评估神经系统发育情况.对照组138例在纠正月龄3个月后直接进行发育评估和神经筛查.结果 对照组神经系统异常检出率高于干预组,在发育评估各功能区检测中,对照组大运动和适应能力与干预组比较差异有统计学意义.结论 NBNA检查操作简单、安全性强,能早期发现神经发育偏离的早产儿,有助于对早产儿进行早期干预.采用家庭与门诊相结合的干预模式,可减少神经系统异常的发生,促进早产儿的智能和运动发育水平.     

Imaging biomarkers for treatment development for impaired cognition: report of the sixth CNTRICS meeting: Biomarkers recommended for further development

The Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia initiative, funded by an R13 conference grant from the National Institute of Mental Health, has sought to facilitate the translation of measures from the basic science of cognition into practical brain-based tools to measure treatment effects on cognition in schizophrenia. In this overview article, we summarize the process and products of the sixth meeting in this series, which focused on the identification of promising imaging paradigms, based on the measurement of cognitive evoked potentials (event-related potential) of cognition-related time-frequency analyses of the electroencephalography as well as functional magnetic resonance imaging. A total of 23 well-specified paradigms from cognitive neuroscience that measure cognitive functions previously identified as targets for treatment development were identified at the meeting as being recommended for the further developmental work needed in order to validate and optimize them as biomarker measures. Individual paradigms are discussed in detail in 6 domain-based articles in this volume. Ongoing issues related to the development of these and other measures as valid, sensitive and reliable measurement, and assessment tools, as well as the steps necessary for the development of specific measures for use as biomarkers for treatment development and personalized medicine, are discussed.     

Optimization and validation of a visual integration test for schizophrenia research

The Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia initiative highlighted a contour integration test as a promising index of visual integration impairment because of its well-established psychometric properties; its prior validation in healthy adults, patients, and nonhuman primates; and its potential sensitivity to treatment effects. In this multisite study, our goals were to validate the task on the largest subject sample to date, clarify the task conditions and number of trials that best discriminate patients from controls, and determine whether this discrimination can occur in standard clinical trial settings. For our task, subjects briefly observed a field of disconnected, oriented elements and attempted to decide whether a subset of those elements formed a leftward- or rightward-pointing shape. Difficulty depended on the amount of orientational jitter that was added to the shape's elements. Two versions of this Jittered Orientation Visual Integration task (JOVI) were examined. Study 1 did not reveal between-group differences in threshold (ie, the jitter magnitude needed to reach a performance level of ～80%), but this likely owed to the wide sampling distribution of jitter levels and resulting floor/ceiling effects in many conditions. Study 2 incorporated a narrower range of difficulty levels and revealed lower thresholds (worse performance) among patients (p < .001). This group difference remained even when only the first half of the trials was analyzed (p = .001). Thus, the JOVI-2 provides a brief, sensitive measure of visual integration deficits in schizophrenia. Neural implications and potential future applications of the JOVI are discussed.     

社会神经科学视角下青少年冒险行为的变化

青春期是个＂疾风骤雨＂的时期,相对于其它时期,容易出现冒险行为。社会神经科学是一个新兴的领域,其研究目标是了解社会过程和社会行为的生物学机制并且利用生物学的概念和方法来启发和完善社会过程和行为。在社会神经科学领域,学者们开始使用功能性磁共振成像和行为实验等方法研究青少年早期至成年早期之间的大脑结构变化,寻找童年期至青春期冒险行为上升以及青春期至成年期冒险行为下降的变化机制。文章对社会神经科学解释青少年冒险行为的变化机制进行了文献梳理,并在此基础上提出了小结和展望。     

Foraging optimally in social neuroscience: computations and methodological considerations

Research in social neuroscience has increasingly begun to use the tools of computational neuroscience to better understand behaviour. Such approaches have proven fruitful for probing underlying neural mechanisms. However, little attention has been paid to how the structure of experimental tasks relates to real-world decisions, and the problems that brains have evolved to solve. To go significantly beyond current understanding, we must begin to use paradigms and mathematical models from behavioural ecology, which offer insights into the decisions animals must make successfully in order to survive. One highly influential theory—marginal value theorem (MVT)—precisely characterises and provides an optimal solution to a vital foraging decision that most species must make: the patch-leaving problem. Animals must decide when to leave collecting rewards in a current patch (location) and travel somewhere else. We propose that many questions posed in social neuroscience can be approached as patch-leaving problems. A richer understanding of the neural mechanisms underlying social behaviour will be obtained by using MVT. In this ‘tools of the trade’ article, we outline the patch-leaving problem, the computations of MVT and discuss the application to social neuroscience. Furthermore, we consider the practical challenges and offer solutions for designing paradigms probing patch leaving, both behaviourally and when using neuroimaging techniques.     

Computational approaches to the neuroscience of social perception

Across multiple domains of social perception—including social categorization, emotion perception, impression formation and mentalizing—multivariate pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data has permitted a more detailed understanding of how social information is processed and represented in the brain. As in other neuroimaging fields, the neuroscientific study of social perception initially relied on broad structure–function associations derived from univariate fMRI analysis to map neural regions involved in these processes. In this review, we trace the ways that social neuroscience studies using MVPA have built on these neuroanatomical associations to better characterize the computational relevance of different brain regions, and discuss how MVPA allows explicit tests of the correspondence between psychological models and the neural representation of social information. We also describe current and future advances in methodological approaches to multivariate fMRI data and their theoretical value for the neuroscience of social perception.     

Comparing different pre-processing routines for infant fNIRS data

Functional Near Infrared Spectroscopy (fNIRS) is an important neuroimaging technique in cognitive developmental neuroscience. Nevertheless, there is no general consensus yet about best pre-processing practices. This issue is highly relevant, especially since the development and variability of the infant hemodynamic response (HRF) is not fully known. Systematic comparisons between analysis methods are thus necessary. We investigated the performance of five different pipelines, selected on the basis of a systematic search of the infant NIRS literature, in two experiments. In Experiment 1, we used synthetic data to compare the recovered HRFs with the true HRF and to assess the robustness of each method against increasing levels of noise. In Experiment 2, we analyzed experimental data from a published study, which assessed the neural correlates of artificial grammar processing in newborns. We found that with motion artifact correction (as opposed to rejection) a larger number of trials were retained, but HRF amplitude was often strongly reduced. By contrast, artifact rejection resulted in a high exclusion rate but preserved adequately the characteristics of the HRF. We also found that the performance of all pipelines declined as the noise increased, but significantly less so than if no pre-processing was applied. Finally, we found no difference between running the pre-processing on optical density or concentration change data. These results suggest that pre-processing should thus be optimized as a function of the specific quality issues a give dataset exhibits.