一般流体智力的脑成像研究述评

对一般流体智力的脑成像研究有助于探明智力的脑机制。从结构成像与功能成像两个方面阐述了相关的研究。已有研究表明,一般流体智力与总的脑体积、额叶或其他多个脑区的灰质体积中等正相关。一般智力（g）因素负荷高的任务比负荷低的任务引发特定脑区更大的激活。较早的研究发现一般智力水平个体差异与脑区的激活呈负相关,但此后的一些研究却得到相反的结论。未来的研究应加强对个体差异的研究,将脑成像技术与EEG或ERP技术结合起来,整合多水平（心理测量、遗传学等）的研究结果,进一步阐明一般流体智力的脑机制     

反应时、信息加工速度与g

反应时、信息加工速度与ｇ阎巩固（北京师范大学心理系）１９０４年，英国心理学家斯皮尔曼发表了题为《一般智力：它的客观决定因素与测量》的论文，提出了一般智力的概念。斯皮尔曼发现，所有复杂的心理测验之间都存在着正相关。由于各个测验互不相同，测验间存在正相关...     

智力与信息加工速度研究中的检测时范式

检测时是信息加工速度的重要指标,也是智力与信息加工速度关系的研究领域内一种重要的实验范式。文章在简要介绍反应时范式的基础上,着重介绍了检测时范式的实验任务、基本原理以及检测时与智商之间的关系。同时,通过与反应时范式的比较,讨论了检测时范式在智力与信息加工速度研究中的优点和局限性,以及其在解决相关研究领域问题上的方法学意义。     

品牌消费旅程中消费者的认知心理过程——神经营销学视角

品牌消费旅程通常指的是对于品牌消费服务的多维度(包括认知, 情绪, 感觉, 行为和品牌关系)响应。揭示品牌消费旅程的认知心理过程是目前营销学领域之中研究的重点与热点。在梳理当前神经营销领域内有关功能性核磁共振(fMRI)、事件相关电位(ERP)、事件相关震荡(ERO)的相关研究成果后, 将消费者在品牌消费旅程之中的认知心理进程划分为注意吸引、决策形成、消费体验和品牌忠诚四个阶段, 并系统阐述了每个阶段之中消费者心理进程的神经机制与脑区活动, 进而全面立体地揭示消费心理的全貌。未来研究可以进一步探索不同神经指标在具体营销情境下的表征意义, 并结合超扫描技术进一步解析多个被试间的神经耦合情况。     

工作记忆、加工速度与流体智力的发展

近几年有关认知发展心理机制的研究成为一个认知发展领域一个颇引人注目的内容．这些研究探讨了年龄、工作记忆、加工速度与流体智力之间的关系。研究发现．在流体智力的发展过程中,工作记忆可能比加工速度发挥着更直接、更一般的作用,而加工速度则对工作记忆的发展起直接调节作用。     

弱智儿童心理旋转的研究

该研究探讨了一组9~12岁弱智儿童的“心理旋转”能力,该组儿童平均年龄10.1岁,平均智商（IQ）53.8（中度智力残疾）。研究结果与正常儿童（均龄8岁）作了比较。结果显示,弱智儿童的心理旋转能力明显较之正常儿童为差,智力缺陷对视觉图形空间定向能力（心理旋转）有着明显的影响。但无论弱智儿童或是正常儿童的结果均未发现性别差异。     

青少年与成年人情绪冲突控制的年龄差异：一项行为和ERP研究（英文）

青春期被喻为“狂风骤雨期”,青少年可能比年幼的儿童和年长的成年人有更大的情绪抑制和控制的需求。情绪抑制控制能力与冒险行为、异常的心理和行为发展有关。本研究采用事件相关电位（ERP）方法探讨青少年与成人之间的情绪冲突控制的差异。31名早期青少年（男生19名;M年龄=12.66岁）和33名成年人（男生16名;M年龄=20.15岁）完成了面孔-词Stroop任务。在该任务中,情绪词叠加在情绪面孔上构成一致和不一致条件,被试被要求判断面孔的效价（面孔任务）或词语的效价（词语任务）。分析两组被试在行为表现和与情绪信息加工相关的ERP成分上的年龄差异。结果表明：（1）青少年在面孔判断任务中存在Stroop效应（一致性条件下的反应时间比不一致条件下的反应时间短）,而对于成年人而言,在面孔和词语判断任务中均发现了Stroop效应;（2）在青少年中,不一致条件诱发的N450波幅显著大于一致条件;（3）N450成分的Stroop效应仅在词语判断任务中出现,而SP成分的Stroop效应仅在面孔判断任务中出现。研究结果提供了神经证据表明,与成人相比,青少年处理情绪冲突的能力较差,这可能与其情绪控制相关的前额叶...     

情绪智力对初中生心理适应的影响：一项追踪研究

为考察情绪智力对初中生心理适应的影响及人际素质与逆境信念的中介作用,对466名初中生进行为期半年的追踪调查。结果显示：（1）情绪智力、人际素质、逆境信念和心理适应间存在同时性和继时性正相关;（2）情绪智力正向预测初中生心理适应;（3）人际素质、逆境信念在情绪智力与初中生心理适应间起链式中介作用。追踪研究结果表明,在延时条件下,情绪智力能够依次通过人际素质、逆境信念来进一步影响初中生心理适应。     

注意促进效应的ERP研究

近期发现，采用目标探测任务作为二级任务时，目标探测条件不仅不会削弱，甚至会提高记忆成绩，产生注意促进效应（ABE）。为进一步探究目标探测的作用机制，研究采用事件相关电位（ERP）技术，对比目标与分心条件在编码和提取过程中所诱发的ERP差异。结果表明，两类条件在再认过程中所诱发的ERP差异不仅表现在早期与知觉加工相关的ERP成份上，并且一直持续到了后期与细节提取相关的ERP成分上。由此推测，ABE不仅体现在编码早期的知觉加工阶段，更会延续到后期的复述与精加工。     

检测时与智力关系的研究述评

检测时是信息加工速度的重要指标,它与一般智力测验分数之间存在着稳定的相关,两者之间的相关常被解释为智力个体差异的认知或生理学的基础。文章介绍了检测时与智商之间的相关研究。讨论了研究者对检测时和智力之间相关本质的几种理论解释。同时,总结了从生物学和发展的角度对检测时与智力之间相关的本质理解的研究。在此基础上,文章分了检测时与智力之间关系研究中存在的问题和未来的研究方向     

Reversing the speed–IQ correlation: Intra-individual variability and attentional control in the inspection time paradigm

Elementary cognitive tasks (ECTs) are simple tasks involving basic cognitive processes for which speed of performance typically correlates with IQ. Inspection time (IT) has the strongest IQ correlations and is considered critical evidence for neural speed underlying individual differences in intelligence. However, results from Bors et al. [Bors, D.A., Stokes, T.L., Forrin, B. & Hodder, S.L., (1999). Inspection Time and Intelligence: Practice, strategies, and attention. Intelligence, 27, 111–129.] suggest task consistency may underlie this shared variance. One possibility is that performance consistency reflects attentional mechanisms, as previous research has shown relationships between attentional control and cognitive performance. In study 1, participants were administered the Raven's Advanced Progressive Matrices and performed an alternative version of the IT task to measure individual trial-by-trial consistency expressed as the standard deviation of IT (ITSD). The alternative procedure yielded IT–IQ correlations similar to those obtained in previous studies and ITSD accounted for the IT–IQ variance. A second experiment tested whether ITSD measures attentional control, as participants simultaneously performed the IT task and an attention-demanding verbalization task. Under these conditions, high IQ participants performed worse on IT. These results suggest IT performance may reflect individual differences in attentional control and that this variable may account for the variance shared between IT and IQ.     

Intelligence, reaction times, and peripheral nerve conduction velocity

Two studies (with sample sizes of 85 and 88) are reported that investigated relationships among measures of intelligence, speed of information processing, and peripheral nerve conduction velocity (NCV). In both studies, NCV was significantly correlated with IQ scores (rs = .42 and .48) and with reaction times (RTs; rs = −.28 and −.18): Thus, faster NCV was associated with higher IQ scores and faster speed of processing. In both studies, NCV and RTs contributed significantly, in combination, to the prediction of fullscale IQ (shrunken multiple Rs = .53 and .57), but the expected pattern of causal relationships between the variables was not borne out. The results are interpreted in terms of a “neural efficiency” model of intelligence, which has recieved support from other studies of physiological correlates of human intelligence.     

Early electro-cortical correlates of inspection time task performance

The concept of general intelligence (g) summarizes the well established finding that scores on separate cognitive tasks are positively correlated, indicating a trait common to many aspects of information processing. Inspection time is a well-established correlate of IQ, where those of a higher IQ can correctly identify a briefly presented stimulus with a greater level of accuracy than those of a lower IQ. This study used two age-matched samples, selected on the basis of their scores on Raven's Advanced Progressive Matrices from the undergraduate population of Bangor University. In order to address the confound of inspection time and IQ of previous ITT-ERP research, each participant of the presented study performed an IT task with the same five levels of stimulus duration while undergoing 64-channel EEG recording. The high IQ group made significantly fewer errors at each level of stimulus duration and exhibited a significantly larger N1 response. N1 latency and other ERP components did not distinguish the two IQ groups. Given the specificity of ERP group differences to the N1, the results of the present study suggest that the link between IT performance and g is attributable to individual differences in directing attention to a spatial region.     

Processing speed, intelligence, creativity, and school performance: Testing of causal hypotheses using structural equation models

According to mental speed theory of intelligence, the speed of information processing constitutes an important basis for cognitive abilities. However, the question, how mental speed relates to real world criteria, like school, academic, or job performance, is still unanswered. The aim of the study is to test an indirect speed-factor model in comparison to rivaling models explaining the relationships between different mental abilities and performance. In this speed-factor model, basic cognitive processing is assumed to influence higher mental abilities (IQ and creativity). Intelligence and creativity themselves should be valid predictors of school performance. We computed bivariate correlations and structural equation models to test this hypothesis, using indicators of processing speed [Zahlen-Verbindungs-Test (ZVT) and Coding Test], psychometric intelligence [Kognitiver Fähigkeits-Test (KFT) and Raven's Advanced Progressive Matrices (APM)], creativity [Verbaler Kreativitäts-Test (VKT) and Verwendungs-Test (VWT)] and school performance (grades). In a sample of 271 students from German gymnasiums (Class Levels 9 to 11) the speed-factor model can reproduce at best the empirical relationships between processing speed, intelligence, creativity, and school performance: It assumes that processing speed influences higher mental abilities (intelligence and creativity), which, in the sequel, influence school performance. Therefore, processing speed seems to have no direct effect on school performance; the effect is indirect as it operates via mediation through higher cognitive abilities.     

The relationship between speed of information processing and cognitive ability

Speed of information processing as measured by various reaction time and inspection tasks has been shown to correlate with psychometric intelligence, and it has been suggested that general intelligence (g) is determined to some degree by the speed that information is processed. If this is so, then various measures of speed of information processing should correlate substantially with each other, and each should also correlate with a wide range of psychometric tests that load on g. Alternatively, intelligence may be considered to be a multi-faceted complex of partially related abilities with specific abilities being dependent upon specific cognitive processes. If this is the case, it should be possible to discover independent cognitive processes, some of which correlate with one facet or broad ability and some with another. This paper presents three experiments in which the relationship between intellectual ability and four speed of information processing measures was examined. These were rate of memory scanning, rate of retrieval of information from long term memory, speed of stimulus-response mapping and inspection time (IT). Results showed that correlations between IT and most reaction time measures of speed of information processing were low, and that correlations between different versions of IT were negligible. In addition, some cognitive tasks with verbal material (memory scanning rate for digits and Posner letter matching IT) correlated most substantially with Verbal Reasoning whereas non-verbal (two-line) IT consistently correlated with tests loading on g. It was thus suggested that while non-verbal IT may be a measure of a perceptual speed attribute that contributes to mental functioning, other “speed of information processing” parameters may be more specific to a subset of abilities.     

Inspection time and intelligence in 7-yr-old children: A follow-up

Remeasures of inspection time (IT) were obtained from 30 of the 47 children reported in Nettelbeck and Young (Personality and Individual Differences, 10, 605–614, 1989). Ages ranged from 7 yr–0 months to 7–11 and Full Scale IQ (WISC-R) ranged from 93 to 142 (mean = 116.5 SD = 12.2). Correlations between IT and the WISC-R subtests, scales and factors used in the earlier study were generally statistically significant: and similar to those found earlier. The correlation between IT and Full Scale IQ was — 0.49, with those children whose IQs were below the median score of 116 again contributing more to this outcome. Similarly, the IT-IQ correlation was higher among children showing less well-directed attention in the IT task. Once again IT correlated better with Verbal IQ, supporting the hypothesis that IT is better associated with more general intellectual functioning than with specific cognitive abilities. Cross-lagged panel correlations between IT and IQ were —0.40, whether predicting IQ from IT or the reverse. Thus, there was no evidence for a causal relationship between these variables, although both may reflect a common cognitive ability factor.     

A somatosensory latency between the thalamus and cortex also correlates with level of intelligence

As part of a study on speed of information processing and intelligence, 205 young adult postsecondary students were tested for somatosensory evoked potential (SEP) latencies and intelligence. Following stimulation at the wrist, latencies of three SEPs were determined: N13, generated in the cervical spinal cord/medulla region; N19, generated in the thalamus; P22, generated in the arm region of the somatosensory (parietal) cortex. These latencies and two latency differences, N19 - N13 and P22 - N19, were tested for correlation with a nonverbal measure of intelligence; only P22 - N19 significantly correlated (r = −.217; P = .013, two-tailed). Comparing this latency difference in students in the first IQ quartile (mean IQ = 103.4) with that of students in the fourth quartile (M = 131.2) showed mean differences of 4.13 ms versus 3.21 ms, respectively (p = .0034, two-tailed).P22 - N19 measures time for signal transmission from the thalamus to the sensory cortex. These results agree with considerably more extensive data on visually evoked potentials showing a negative correlation between IQ and the latency for a visual stimulus of the retina to produce a signal at the visual cortex (most of this latency is between the thalamus and the cortex; Reed & Jensen, 1992). The findings here agree with the visual results and strongly suggest that the IQ-latency correlation occurs because the latency indexes cortical nerve conduction velocity, an important component of information processing speed.     

Group differences in intelligence and speed of information-processing

Three samples of different levels of mental ability, but each of average or above- average intelligence, were administered a battery of reaction time test which measure the speed with which persons can execute various elementary cognitive processes. Discriminant analyses revealed significant differences between the groups in reaction times and intraindividual standard deviations, and univariate analyses indicated that higher ability groups tended to obtain significantly faster mean reaction times and to show significantly less intraindividual variability than lower ability groups. Groups which differed the most in mental ability differed to the greatest extent on the more complex reaction time tests but this pattern was reversed for groups which were relatively close in mean IQ. Generally, the results support the hypothesis that speed- of-processing is an important factor unferlying intelligence, but a number of puzzling findings indicate the need for continued research in this area.     

Measures of timed performance and intelligence

The question of an association between IQ and measures of timed performance derived from inspection time and reaction time was examined in a sample of 182 adults and by reanalyzing data involving 48 adults from a previously published study. Multiple regression analysis found that measures of timed performance accounted for as much as 25% of IQ variance in the normal population, but that the inclusion of borderline and mildly retarded subjects resulted in much higher correlation coefficients because of the markedly less efficient performance of these persons in tasks of this kind. This outcome raised doubts about the validity of combining data from retarded and nonretarded subjects. Results ran counter to claims that tasks of the kind used are largely uninfluenced by cognitive variables, so that findings are not necessarily explained satisfactorily in terms of a mental speed factor. It was concluded that these measures of timed performance do not, at this time, provide a basis from which a reliable culture-fair measure of intelligence might be devised.