Research Byte: Dynamic switching between #brainnetworks (#executivecontrol #defaultmode) predicts #creative ability - attention #cognition #schoolpsychology #creativity

Dynamic switching between brain networks predicts creative ability.  

Qunlin et al.,(2025).   Click here read article and download PDF (Communications Biology) if you so desire.

Abstract

Creativity is hypothesized to arise from a mental state which balances spontaneous thought and cognitive control, corresponding to functional connectivity between the brain’s Default Mode (DMN) and Executive Control (ECN) Networks. Here, we conduct a large-scale, multi-center examination of this hypothesis. Employing a meta-analytic network neuroscience approach, we analyze resting-state fMRI and creative task performance across 10 independent samples from Austria, Canada, China, Japan, and the United States (N= 2433)—constituting the largest and most ethnically diverse creativity neuroscience study to date. Using time-resolved network analysis, we investigate the relationship between creativity (i.e., divergent thinking ability) and dynamic switching between DMN and ECN. We find that creativity, but not general intelligence, can be reliably predicted by the number of DMN-ECN switches. Importantly, we identify an inverted-U relationship between creativity and the
degree of balance between DMN-ECN switching, suggesting that optimal creative performance requires balanced brain network dynamics. Furthermore, an independent task-fMRI validation study (N= 31) demonstrates higher DMN-ECN switching during creative idea generation (compared to a control condition) and replicates the inverted-U relationship. Therefore, we provide robust evidence across multi-center datasets that creativity is tied to the capacity to dynamically switch between brain networks supporting spontaneous and controlled cognition.

CHC cognitive theory update: Glr is now separate Gl and Gr broad abilities & upcoming change in WJ V Tests of Cognitive Ability—minimizing the jingle-jangle fallacy.

In the latest “unofficial” CHC theory of intellectual abilities description and definition of broad and narrow CHC abilities, Schneider and McGrew [me] (2018), declared the broad Glr ability divorce (which had a trial separation in our prior 2012 CHC chapter) official with the cleaving of Glr into the separate broad abilities of learning efficiency (Gl) and retrieval fluency (Gr). Gl is now “the ability to learn, store, and consolidate new information over periods of time measured in minutes, hours, days, and years” (Schneider & McGrew, 2018, p. 100).  Gr is “the rate and fluency at which individuals can access information (Schneider & McGrew, 2018, p. 102).

Schneider and McGrew (2018) recognized the risk involved in using the term learning efficiency for Gl.  They stated we:

               recognize the risk in using the word efficiency, given the conceptual confusion surrounding the term—stemming from its use in a variety of disciplines and even its multiple meanings within educational psychology (Hoffman, 2012; Hoffman & Schraw, 2009, 2010). We do not mean efficiency as conveyed by the Gs + Gwm mental efficiency notion present in certain intelligence composite scores (the WJ III/WJ IV Cognitive Efficiency cluster; the Wechsler batteries' Cognitive Proficiency Index). Our definition is consistent with Hoffman's (2012) conception as related to the efficiency of learning and storing new information: ‘Learning efficiency is primarily based upon individual performance during learning when accounting for the incremental costs associated with the learning process. Individual performance means measurable changes in the amount, rate, frequency, or qualitative complexity of knowledge structures. Incremental costs mean factors such as time taken, effort invested, or error rates incurred’ (p.  134; original emphasis). For example, to learn and retain a certain amount of information (e.g., a 16-word list), some individuals need to exert more effort than others. To achieve the same outcome, they need more learning inputs (e.g., more learning trials or more time to study) (p. 100).

Although Schneider and McGrew (2018) recommended calling the new CHC Gl domain learning efficiency, they noted that the term learning efficiency has multiple meanings and can suffer from the jingle-jangle fallacy (Kelly, 1927)— “when erroneous assumptions are made that two different things are the same because the same name (the jingle fallacy), or that identical to almost identical things are different because they are labeled differently (the jangle fallacy) (p. 143). As a result, I (Kevin McGrew) have recommended that in the forthcoming WJ V, Gl be called long-term storage instead of learning efficiency. The prior WJ IV had the previous Glr ability domain cluster.

Joel Schneider and I, at some future point, will revisit our official CHC Gl term and definition in future publications.

Schneider, W. J., & McGrew, K. S. (2018). The Cattell-Horn-Carroll Theory of Cognitive Abilities. In D. P. Flanagan & Erin M. McDonough (Eds.), Contemporary intellectual assessment: Theories, tests and issues (4th ed., pp. 73-163).  New York: Guilford Press.

 

"Intelligent" intelligence testing with the WJ IV COG #7: Why do some individuals obtain markedly different scores on the various WJ IV Ga tests?

This is # 7 in the "Intelligent" intelligence testing with the WJ IV COG series at IQs Corner.  Copies of the PPT module can be downloaded by clicking on the LinkedIn icon in the right-hand corner of the slide show below  A PDF copy of all slides can be found here.

This module was developed in response to a thread on the IAPCHC listserv where an individual asked for help in understanding why the WJ IV Phonological Processing test score could be so much different (lower) that the WJ IV Sound Blending and Segmentation test scores.

Enjoy.

"Intelligent" intelligence testing with the WJ IV COG: Why do some individuals obtain markedly different scores on the various WJ IV Ga tests? from Kevin McGrew

The CHC model of human cognitive abilities--a proposed revision (v2.3): Has Glr been incorrectly conceptualized since 1997?

This presentation contains a historical overview of the derivation of the Glr ability domain in contemporary CHC theory. It then presents new data, as well as historical conclusions of the CHC masters, that makes a strong case for replacing the stratum II broad ability domain of Glr with two separate broad ability domains of Gl (learning efficiency) and Gr (retrieval fluency). How to obtain WJ IV scores for these two broad abilities is presented, as well as other possible Gl and Gr tests indicators from the CHC cross-battery literature.

A pdf copy of this set of slides, one per page, can be downloaded here.

CHC model of inteligence revised (v2.4). Has Glr been incorrectly conceptualized since 1997? from Kevin McGrew

Research Byte: A new measure of imagination abiltiy

 

 

Original Research ARTICLE

Front. Psychol., 18 April 2016 | http://dx.doi.org/10.3389/fpsyg.2016.00496

A New Measure of Imagination Ability: Anatomical Brain Imaging Correlates

Rex E. Jung^1,2*, Ranee A. Flores² and Dan Hunter³

• ¹Department of Psychology, University of New Mexico, Albuquerque, NM, USA
• ²Department of Neurosurgery, University of New Mexico, Albuquerque, NM, USA
• ³Hunter Higgs, LLC, Boston, MA, USA

Imagination involves episodic memory retrieval, visualization, mental simulation, spatial navigation, and future thinking, making it a complex cognitive construct. Prior studies of imagination have attempted to study various elements of imagination (e.g., visualization), but none have attempted to capture the entirety of imagination ability in a single instrument. Here we describe the Hunter Imagination Questionnaire (HIQ), an instrument designed to assess imagination over an extended period of time, in a naturalistic manner. We hypothesized that the HIQ would be related to measures of creative achievement and to a network of brain regions previously identified to be important to imagination/creative abilities. Eighty subjects were administered the HIQ in an online format; all subjects were administered a broad battery of tests including measures of intelligence, personality, and aptitude, as well as structural Magnetic Resonance Imaging (sMRI). Responses of the HIQ were found to be normally distributed, and exploratory factor analysis yielded four factors. Internal consistency of the HIQ ranged from 0.76 to 0.79, and two factors (“Implementation” and “Learning”) were significantly related to measures of Creative Achievement (Scientific—r = 0.26 and Writing—r = 0.31, respectively), suggesting concurrent validity. We found that the HIQ and its factors were related to a broad network of brain volumes including increased bilateral hippocampi, lingual gyrus, and caudal/rostral middle frontal lobe, and decreased volumes within the nucleus accumbens and regions within the default mode network (e.g., precuneus, posterior cingulate, transverse temporal lobe). The HIQ was found to be a reliable and valid measure of imagination in a cohort of normal human subjects, and was related to brain volumes previously identified as central to imagination including episodic memory retrieval (e.g., hippocampus). We also identified compelling evidence suggesting imagination ability linked to decreased volumes involving the nucleus accumbens and regions within the default mode network. Future research will be important to assess the stability of this instrument in different populations, as well as the complex interaction between imagination and creativity in the human brain.

Research byte: Simple addition problem solving may be autmoatic counting procedures and not quick retrieval from long-term memory

File under Gq, Glr, and Gr as per CHC model

 Fast automated counting procedures in addition problem solving: When are they used and why are they mistaken for retrieval? ^☆

• Kim Uittenhove,
• Catherine Thevenot,
• Pierre Barrouillet^,

 Show more

doi:10.1016/j.cognition.2015.10.008

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Highlights

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It is universally assumed that the answer of small additions is retrieved from memory.

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Contrariwise, we replicate that they are solved by automated compacted procedures.

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Moreover, we show here that these procedures are limited to operands up to 4.

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Counterintuitively, RTs suggest that retrieval could be used for larger additions.

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Compacted procedures are faster than retrieval and consequently mistaken for it.

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Abstract

Contrary to a widespread assumption, a recent study suggested that adults do not solve very small additions by directly retrieving their answer from memory, but rely instead on highly automated and fast counting procedures (Barrouillet & Thevenot, 2013). The aim of the present study was to test the hypothesis that these automated compiled procedures are restricted to small quantities that do not exceed the size of the focus of attention (i.e., 4 elements). For this purpose, we analyzed the response times of ninety adult participants when solving the 81 additions with operands from 1 to 9. Even when focusing on small problems (i.e. with sums ⩽10) reported by participants as being solved by direct retrieval, chronometric analyses revealed a strong size effect. Response times increased linearly with the magnitude of the operands testifying for the involvement of a sequential multistep procedure. However, this size effect was restricted to the problems involving operands from 1 to 4, whereas the pattern of response times for other small problems was compatible with a retrieval hypothesis. These findings suggest that very fast responses routinely interpreted as reflecting direct retrieval of the answer from memory actually subsume compiled automated procedures that are faster than retrieval and deliver their answer while the subject remains unaware of their process, mistaking them for direct retrieval from long-term memory.

High working memory related to more idea generation (creativity), especially when writing (vs speaking)

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Higher working memory results in more idea generation (creativity), especially when writing (vs speaking) ideas

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Creativity and IQ tests: Review and thoughts of James Kaufman

 

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Verbal creative behavior related to the precuneus (and default brain network)

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Sunday, July 26, 2015

2:21 PM

Research byte: Good brief article linking contemporary creativity (Glr) and CHC model research

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Tuesday, February 24, 2015

7:45 PM

Cognitive abilities and oral and silent reading: Same or different?

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Word retrieval/access--let kids use their hands to gesture

Interesting study that suggests, as per the Lexical Retrieval Hypothesis, that the use of motoric gestures during speech facilitates word access/retrieval in kids.

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More support for the developmental cascade model (Gs, Gwm, Glr and Gf)

As readers of this blog know, I am partial to research that continues to support Fry and Hale's developmental cascade model, which indicates that processing speed (Gs) has a direct effect on working memory (Gwm/Gsm), which in turn has direct effect on fluid reasoning (Gf) or general intelligence (g). Gs influence is indirect--mediated by Gwm. Another study continues to support this model but adds the wrinkle of secondary memory (some Glr abilities), which also only has an indirect effect on Gf as mediated by Gwm.

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Gs->working memory->Gf developmental-differential psych developmental cascade model

Very interesting research that suggests a developmental (neo-Piagetian) wrinkle to the developmental cascade model, a model that has shown that Gs influences working memory (Gwm), and working memory in turn influences Gf (but Gs has no direct influencee on Gf).

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"However, the exact role of speed and working memory is still debated. Some researchers emphasize speed as a purer index of the quality of information processing in the brain (e.g., Jensen, 1998). This interpretation is based on studies which estimate the relation between speed and intelligence without involving working memory. Others emphasize working memory because it is the workspace of thinking (Kyllonen & Christal, 1990). Studies emphasizing working memory usually measure all three constructs in young adults, when working memory is the dominant predictor of Gf, according to the patterns to be described below. Finally, others assume a causal linear relation between them such that changes in speed cause changes (or differences) in working memory which, in turn, cause changes (or differences) in Gf (Case, 1985; Coyle, Pillow, Snyder, & Kochunov, 2011; Kail, 1991; Kail & Ferrer, 2007). However, this chain of relations may only reflect the fact that working memory tasks are both timed, like speed tasks, and require information management, like Gf tasks, rather than a causal sequence. In fact, there is evidence that control of attention is common to all, speed, WM, and Gf, explaining their relations (Cowan, Morey, Chen, & Bunting, 2007; Engle et al., 1999; Stankov & Roberts, 1997)"

Note. Attentional control (AC) is now proposed to represent a narrow ability under the broad CHC domain of Gwm (short-term working memory) by the authors of the forthcoming WJ IV [Conflict of interest disclosure--I am one of the coauthors of the WJ III and WJ IV). This is consistent with Schneider and McGrew's (2012) recent book chapter CHC model update.

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"Demetriou et al. (2013) showed recently that the relations between these constructs are more complicated than originally assumed, because they vary with growth. Specifically, speed increases and WM expands. Gf evolves along a reconceptuali-zation sequence (ReConceP) where changes in the nature of representations alternate with changes in the command and interlinking of representations constructed earlier."

"These patterns provide support for an integrated developmental–differential theory of intelligence that would explicate why Gf changes coalesce with speed at the beginning of developmental cycles and with WM changes at the end. Gf undergoes three types of change: representational, inferential, and complexity."

I previously presented (McGrew, 2005) support for the developmental cascade model in 5 age-differentiated WJ III norm samples (see one of the sample models below). Instead of causal models with Gf as the criterion, I specified a criterion g-factor defined by Gv, Ga, Glr, Gf, and Gc. The results strongly supported the Gwm->g link, and significant causal links from Gs to working memory. Gs did not dispaly a direct link to g in the childhood samples, but did demonstrate small significant direct paths to g in the adolescent and adult samples.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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Decreasing default brain network activity (mind wandering) helps with episodic memory

A other article demonstrating the importance of controlled attention (focus) on cognitive performance.

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Memory Interventionist Certification Program; Psychological Processing Analyzer 2.0; Review of CPPS

On behalf of my friend and colleague, Dr. Milton Dehn, I am sharing some announcements from Schoolhouse Educational Services..

First is a Memory Interventionist Certification Program for psychologists and school psychologists.  This is a 36-hour, competency-based program to train psychologists on evidence-based methods to improve memory, learning, and daily functioning for individuals with memory programs.

Second, version 2.0 of the Psychological Processing Analyzer will be released in a few weeks.  This software is designed to identify the pattern of strengths and weaknesses among psychological processes.

I have no financial interests in either of these two activities/products.  However, I was the measurement consultant for Dr. Dehn's Children's Psychological Processing Scale (CPPS) and do have a small financial royalty interest in the sales of that instrument.  The CPPS was just independently review in the Journal of Psychological Assessment (click here).

CHC Theory: Long-term storage and retrieval (Glr) definition

Long-Term Storage & Retrieval (Glr):   The ability to store, consolidate, and retrieve information over periods of time measured in minutes, hours, days, and years. Short-term memory has to do with information that has been encoded seconds ago and must be retrieved while it is being actively maintained in primary memory. Short-term memory tests often involve information that is stored in long-term memory. What distinguishes Gsm from Glr tests is that there is a continuous attempt to maintain awareness of that information. A Glr test involves information that has been put out of immediate awareness long enough for the contents of primary memory to be displaced completely. In Glr tests, continuous maintenance of information in primary memory is difficult, if not impossible.

 Glr-Learning Efficiency:  All tasks of learning efficiency must present more information than can be retained in Gsm

• Associative Memory (MA). The ability to remember previously unrelated information as having been paired.
• Meaningful Memory (MM). The ability to remember narratives and other forms of semantically related information. 
• Free Recall Memory (M6). The ability to recall lists in any order.

Glr-Retrieval Fluency:  The rate and fluency at which individuals they can access information stored in long-term memory.

       (Fluency factors they involve the production of ideas)

• Ideational Fluency (FI). Ability to rapidly produce a series of ideas, words, or phrases related to a specific condition or object. Quantity, not quality or response originality, is emphasized.
• Associational Fluency (FA). Ability to rapidly produce a series of original or useful ideas related to a particular concept. In contrast to Ideational Fluency (FI), quality rather quantity of production is emphasized. 
• Expressional Fluency (FE). Ability to rapidly think of different ways of expressing an idea.
• Sensitivity to Problems/Alterative Solution Fluency (SP). Ability to rapidly think of a number of alternative solutions to a particular practical problem
• Originality/Creativity (FO). Ability to rapidly produce original, clever, and insightful responses (expressions, interpretations) to a given topic, situation, or task.

       (Fluency abilities that involve the recall of words)

• Naming Facility (NA). Ability to rapidly call objects by their names. In contemporary reading research, this ability is called rapid automatic naming (RAN) or speed of lexical access
• Word Fluency (FW). Ability to rapidly produce words that share a non-semantic feature.

       (Fluency abilities related to figures)

• Figural Fluency (FF). Ability to rapidly draw or sketch as many things (or elaborations) as possible when presented with a nonmeaningful visual stimulus (e.g., set of unique visual elements). Quantity is emphasized over quality.
• Figural Flexibility (FX). Ability to rapidly draw different solutions to figural problems.

The above definitions were abstracted from Schneider and McGrew's (2012) contemporary CHC theory chapter in the form of a special CHC v2.0 publication. See the chapter for more in depth information regarding this ability domain and contemporary CHC theory.

Prior definitions in this series can be found here.

Thanks to Dr. Scott Barry Kaufman for permission to to use the above graphic depiction of this CHC ability. These CHC icons are part of Dr. Kaufman's book, Ungifted: Intelligence Redefined, and are the creative work of George Doutsiopoulos.

Research byte: Importance of executive control (updating, inhibiting) in lexical access (rapid naming speed)

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Research Byte: Gf, Gc and and creativity (metaphors)

.Articles suggests that creative metaphors related to Gf and Glr abilities while conventional metaphors related to Gc

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