scholarly journals Individual differences in cortical processing speed predict cognitive abilities: a model-based cognitive neuroscience account

2018 ◽  
Author(s):  
Anna-Lena Schubert ◽  
Michael D. Nunez ◽  
Dirk Hagemann ◽  
Joachim Vandekerckhove
Keyword(s):  
Individual Differences ◽  
Cognitive Ability ◽  
Processing Speed ◽  
Cognitive Abilities ◽  
Test Scores ◽  
Cognitive Modeling ◽  
Higher Order ◽  
Neural Processing ◽  
Ability Test ◽  
Evidence Accumulation

AbstractPrevious research has shown that individuals with greater cognitive abilities display a greater speed of higher-order cognitive processing. These results suggest that speeded neural information-processing may facilitate evidence accumulation during decision making and memory updating and thus yield advantages in general cognitive abilities. We used a hierarchical Bayesian cognitive modeling approach to test the hypothesis that individual differences in the velocity of evidence accumulation mediate the relationship between neural processing speed and cognitive abilities. We found that a higher neural speed predicted both the velocity of evidence accumulation across behavioral tasks as well as cognitive ability test scores. However, only a small part of the association between neural processing speed and cognitive abilities was mediated by individual differences in the velocity of evidence accumulation. The model demonstrated impressive forecasting abilities by predicting 36% of individual variation in cognitive ability test scores in an entirely new sample solely based on their electrophysiological and behavioral data. Our results suggest that individual differences in neural processing speed might affect a plethora of higher-order cognitive processes, that only in concert explain the large association between neural processing speed and cognitive abilities, instead of the effect being entirely explained by differences in evidence accumulation speeds.

scholarly journals Individual differences in cortical processing speed predict cognitive abilities: A model-based cognitive neuroscience account

2018 ◽  
Author(s):  
Anna-Lena Schubert ◽  
Michael D. Nunez ◽  
Dirk Hagemann ◽  
Joachim Vandekerckhove
Keyword(s):  
Individual Differences ◽  
Cognitive Ability ◽  
Processing Speed ◽  
Cognitive Abilities ◽  
Test Scores ◽  
Cognitive Modeling ◽  
Higher Order ◽  
Neural Processing ◽  
Ability Test ◽  
Evidence Accumulation

Previous research has shown that individuals with greater cognitive abilities display a greater speed of higher-order cognitive processing. These results suggest that speeded neural information processing may facilitate evidence accumulation during decision making and memory updating and thus yield advantages in general cognitive abilities. We used a hierarchical Bayesian cognitive modeling approach to test the hypothesis that individual differences in the velocity of evidence accumulation mediate the relationship between neural processing speed and cognitive abilities. We found that a higher neural speed predicted both the velocity of evidence accumulation across behavioral tasks and cognitive ability test scores. However, only a negligible part of the association between neural processing speed and cognitive abilities was mediated by individual differences in the velocity of evidence accumulation. The model demonstrated impressive forecasting abilities by predicting 36% of individual variation in cognitive ability test scores in an entirely new sample solely based on their electrophysiological and behavioral data. Our results suggest that individual differences in neural processing speed might affect a plethora of higher-order cognitive processes, that only in concert explain the large association between neural processing speed and cognitive abilities, instead of the effect being entirely explained by differences in evidence accumulation speeds.

Perceptual Grouping and High-Order Cognitive Ability

2013 ◽  
Vol 34 (3) ◽  
pp. 153-158 ◽  
Author(s):  
Gabriella Brick Larkin ◽  
Daniel D. Kurylo
Keyword(s):  
Individual Differences ◽  
Cognitive Ability ◽  
Standardized Tests ◽  
Processing Speed ◽  
Visual Processing ◽  
Cognitive Abilities ◽  
Perceptual Grouping ◽  
High Order ◽  
Integrative Function ◽  
Cognitive Components

High-order cognitive functions require the integration of information across functionally related modules. This relationship suggests that cognitive ability is related to the efficiency and processing speed of basic integrative function. In order to examine individual differences for this relationship, we compared standardized tests of intelligence to visual perceptual grouping abilities, which represents a basic process of integration. Sixty participants discriminated perceived grouping of dot patterns based upon similarity in luminance. Psychophysical measurements were made of the functional limits and processing speed of grouping. We assessed cognitive abilities with the Wechsler Abbreviated Scale of Intelligence (WASI) and found that measures of grouping efficiency as well as speed varied considerably across subjects, indicating substantial individual differences at this relatively early level of visual processing. Faster grouping speed was associated with higher scores on all WASI subtests, whereas grouping ability, when not restricted by time, was associated only with the performance IQ components. These results demonstrate an association between a basic integrative function, in which cognitive and motoric factors were minimized, with measures of high-order cognition, which include both verbal and spatial cognitive components.

Range shrinkage of cognitive ability test scores in applicant pools

2010 ◽  
Author(s):  
Jonas W. B. Lang ◽  
Martin Kersting ◽  
Ute R. Hulsheger
Keyword(s):  
Cognitive Ability ◽  
Test Scores ◽  
Ability Test

scholarly journals Longitudinal Associations Between Loneliness and Cognitive Ability in the Lothian Birth Cohort 1936

2018 ◽  
Vol 74 (8) ◽  
pp. 1376-1386 ◽  
Author(s):  
Judith A Okely ◽  
Ian J Deary
Keyword(s):  
Cognitive Ability ◽  
Birth Cohort ◽  
Processing Speed ◽  
Verbal Memory ◽  
Cognitive Abilities ◽  
Birth Cohort Study ◽  
Visuospatial Ability ◽  
Lothian Birth Cohort ◽  
Longitudinal Associations ◽  
Reciprocal Associations

Abstract Objectives Loneliness is associated with poorer cognitive function in old age; however, the direction of this association is unknown. We tested for reciprocal associations between loneliness and the cognitive ability domains of processing speed, visuospatial ability, verbal memory, and crystallized ability. Method We used three triennial waves of longitudinal data from the Lothian Birth Cohort Study 1936, and tested for cross-lagged associations between loneliness and cognitive abilities using cross-lagged panel models. Results Better processing speed, visuospatial ability, or crystallized ability at age 73, was associated with less positive changes in loneliness between ages 73 and 76; however, these associations were not replicated between ages 76 and 79. Loneliness at ages 73 and 76 did not predict subsequent changes in cognitive abilities. Discussion Our findings indicate an association between cognitive ability and loneliness, such that individuals with lower cognitive abilities at age 73 may be at a slightly higher risk of becoming lonely. However, we did not find support for the hypothesis that loneliness causes a decline in cognitive health.

scholarly journals Changing our thinking about changing their thinking in older adulthood

2017 ◽  
Vol 29 (9) ◽  
pp. 1405-1407
Author(s):  
Viviana M. Wuthrich
Keyword(s):  
Older Adults ◽  
Individual Differences ◽  
Cognitive Flexibility ◽  
Cognitive Deficits ◽  
Processing Speed ◽  
Cognitive Abilities ◽  
Anxiety And Depression ◽  
Cognitive Changes ◽  
Older Adulthood ◽  
New Learning

It is well-established that as people age, deterioration in cognitive abilities including processing speed, memory, and cognitive flexibility occurs, although vast individual differences occur in the rate and consequences of this decline (Christensen, 2001). Anxiety and depression in late life are also associated with specific cognitive deficits in memory and executive functioning that may impact on new learning (Yochim et al., 2013). Therefore, it is possible that cognitive changes make it more difficult for older adults to learn how to change their thinking particularly in the context of psychological therapy.

scholarly journals Individual learning phenotypes drive collective behavior

2020 ◽  
Vol 117 (30) ◽  
pp. 17949-17956 ◽  
Author(s):  
Chelsea N. Cook ◽  
Natalie J. Lemanski ◽  
Thiago Mosqueiro ◽  
Cahit Ozturk ◽  
Jürgen Gadau ◽  
...  
Keyword(s):  
Individual Differences ◽  
Social Interactions ◽  
Cognitive Ability ◽  
Honey Bee ◽  
Collective Behavior ◽  
Cognitive Abilities ◽  
Learning Behavior ◽  
Collective Foraging ◽  
Familiar Stimuli ◽  
Bee Colonies

Individual differences in learning can influence how animals respond to and communicate about their environment, which may nonlinearly shape how a social group accomplishes a collective task. There are few empirical examples of how differences in collective dynamics emerge from variation among individuals in cognition. Here, we use a naturally variable and heritable learning behavior called latent inhibition (LI) to show that interactions among individuals that differ in this cognitive ability drive collective foraging behavior in honey bee colonies. We artificially selected two distinct phenotypes: high-LI bees that ignore previously familiar stimuli in favor of novel ones and low-LI bees that learn familiar and novel stimuli equally well. We then provided colonies differentially composed of different ratios of these phenotypes with a choice between familiar and novel feeders. Colonies of predominantly high-LI individuals preferred to visit familiar food locations, while low-LI colonies visited novel and familiar food locations equally. Interestingly, in colonies of mixed learning phenotypes, the low-LI individuals showed a preference to visiting familiar feeders, which contrasts with their behavior when in a uniform low-LI group. We show that the shift in feeder preference of low-LI bees is driven by foragers of the high-LI phenotype dancing more intensely and attracting more followers. Our results reveal that cognitive abilities of individuals and their social interactions, which we argue relate to differences in attention, drive emergent collective outcomes.

scholarly journals Disentangling the Effects of Processing Speed on the Association between Age Differences and Fluid Intelligence

2019 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Anna-Lena Schubert ◽  
Dirk Hagemann ◽  
Christoph Löffler ◽  
Gidon T. Frischkorn
Keyword(s):  
Individual Differences ◽  
Age Differences ◽  
Processing Speed ◽  
Cognitive Aging ◽  
Fluid Intelligence ◽  
Higher Order ◽  
Mediation Effect ◽  
Model Parameters ◽  
Response Planning ◽  
Age Related

Several studies have demonstrated that individual differences in processing speed fully mediate the association between age and intelligence, whereas the association between processing speed and intelligence cannot be explained by age differences. Because measures of processing speed reflect a plethora of cognitive and motivational processes, it cannot be determined which specific processes give rise to this mediation effect. This makes it hard to decide whether these processes should be conceived of as a cause or an indicator of cognitive aging. In the present study, we addressed this question by using a neurocognitive psychometrics approach to decompose the association between age differences and fluid intelligence. Reanalyzing data from two previously published datasets containing 223 participants between 18 and 61 years, we investigated whether individual differences in diffusion model parameters and in ERP latencies associated with higher-order attentional processing explained the association between age differences and fluid intelligence. We demonstrate that individual differences in the speed of non-decisional processes such as encoding, response preparation, and response execution, and individual differences in latencies of ERP components associated with higher-order cognitive processes explained the negative association between age differences and fluid intelligence. Because both parameters jointly accounted for the association between age differences and fluid intelligence, age-related differences in both parameters may reflect age-related differences in anterior brain regions associated with response planning that are prone to be affected by age-related changes. Conversely, age differences did not account for the association between processing speed and fluid intelligence. Our results suggest that the relationship between age differences and fluid intelligence is multifactorially determined.

scholarly journals Making Cognitive Latent Variables Manifest: Distinct Neural Networks for Fluid Reasoning and Processing Speed

2015 ◽  
Vol 27 (6) ◽  
pp. 1249-1258 ◽  
Author(s):  
Christian Habeck ◽  
Jason Steffener ◽  
Daniel Barulli ◽  
Yunglin Gazes ◽  
Qolamreza Razlighi ◽  
...  
Keyword(s):  
Individual Differences ◽  
Cognitive Ability ◽  
Cognitive Abilities ◽  
Latent Variables ◽  
Latent Variable ◽  
Cognitive Tasks ◽  
Neural Activation ◽  
Strongly Correlated ◽  
Activation Patterns ◽  
Fluid Reasoning

Cognitive psychologists posit several specific cognitive abilities that are measured with sets of cognitive tasks. Tasks that purportedly tap a specific underlying cognitive ability are strongly correlated with one another, whereas performances on tasks that tap different cognitive abilities are less strongly correlated. For these reasons, latent variables are often considered optimal for describing individual differences in cognitive abilities. Although latent variables cannot be directly observed, all cognitive tasks representing a specific latent ability should have a common neural underpinning. Here, we show that cognitive tasks representing one ability (i.e., either perceptual speed or fluid reasoning) had a neural activation pattern distinct from that of tasks in the other ability. One hundred six participants between the ages of 20 and 77 years were imaged in an fMRI scanner while performing six cognitive tasks, three representing each cognitive ability. Consistent with prior research, behavioral performance on these six tasks clustered into the two abilities based on their patterns of individual differences and tasks postulated to represent one ability showed higher similarity across individuals than tasks postulated to represent a different ability. This finding was extended in the current report to the spatial resemblance of the task-related activation patterns: The topographic similarity of the mean activation maps for tasks postulated to reflect the same reference ability was higher than for tasks postulated to reflect a different reference ability. Furthermore, for any task pairing, behavioral and topographic similarities of underlying activation patterns are strongly linked. These findings suggest that differences in the strengths of correlations between various cognitive tasks may be because of the degree of overlap in the neural structures that are active when the tasks are being performed. Thus, the latent variable postulated to account for correlations at a behavioral level may reflect topographic similarities in the neural activation across different brain regions.

scholarly journals Genetics of Cognition: Outline of a Collaborative Twin Study

Twin Research ◽  
2001 ◽  
Vol 4 (1) ◽  
pp. 48-56 ◽  
Author(s):  
Margie Wright ◽  
Eco De Geus ◽  
Juko Ando ◽  
Michelle Luciano ◽  
Danielle Posthuma ◽  
...  
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
The Netherlands ◽  
Cognitive Ability ◽  
Processing Speed ◽  
Twin Study ◽  
Memory Task ◽  
Inspection Time ◽  
Phenotypic Correlation ◽  
Spatial Span

AbstractAmultidisciplinary collaborative study examining cognition in a large sample of twins is outlined. A common experimental protocol and design is used in The Netherlands, Australia and Japan to measure cognitive ability using traditional IQ measures (i.e., psychometric IQ), processing speed (e.g., reaction time [RT] and inspection time [IT]), and working memory (e.g., spatial span, delayed response [DR] performance). The main aim is to investigate the genetic covariation among these cognitive phenotypes in order to use the correlated biological markers in future linkage and association analyses to detect quantitativetrait loci (QTLs). We outline the study and methodology, and report results from our preliminary analyses that examines the heritability of processing speed and working memory indices, and their phenotypic correlation with IQ. Heritability of Full Scale IQ was 87% in the Netherlands, 83% in Australia, and 71% in Japan. Heritability estimates for processing speed and working memory indices ranged from 33–64%. Associations of IQ with RT and IT (−0.28 to −0.36) replicated previous findings with those of higher cognitive ability showing faster speed of processing. Similarly, significant correlations were indicated between IQ and the spatial span working memory task (storage [0.31], executive processing [0.37]) and the DR working memory task (0.25), with those of higher cognitive ability showing better memory performance. These analyses establish the heritability of the processing speed and working memory measures to be used in our collaborative twin study of cognition, and support the findings that individual differences in processing speed and working memory may underlie individual differences in psychometric IQ.

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