Intelligent Insights on Intelligence Theories and Tests
Showing posts with label music. Show all posts
Showing posts with label music. Show all posts
Saturday, September 21, 2019
All you need is g? Predicting piano skill acquisition in beginners: The role of general intelligence, music aptitude, and mindset
Thursday, October 26, 2017
Musicians have better memory than nonmusicians: A meta-analysis
More research, this time a meta-analysis, documenting the cognitive benefits of musical training. I better not show this to my mother who never liked the fact that I only took one year of piano:)
Musicians have better memory than nonmusicians: A meta-analysis
Francesca Talamini, Gianmarco Altoè, Barbara Carretti, Massimo Grassi
Abstract
The three meta-analyses revealed a small effect size for long-term memory, and a medium effect size for short-term and working memory, suggesting that musicians perform better than nonmusicians in memory tasks. Moreover, the effect of the moderator suggested that, the type of stimuli influences this advantage.
Click on image to enlarge. Article link.
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Musicians have better memory than nonmusicians: A meta-analysis
Francesca Talamini, Gianmarco Altoè, Barbara Carretti, Massimo Grassi
Abstract
The three meta-analyses revealed a small effect size for long-term memory, and a medium effect size for short-term and working memory, suggesting that musicians perform better than nonmusicians in memory tasks. Moreover, the effect of the moderator suggested that, the type of stimuli influences this advantage.
Click on image to enlarge. Article link.
- Posted using BlogPress from my iPad
Saturday, November 21, 2015
Thursday, December 25, 2014
Sunday, August 31, 2014
The sound of music: Two new music and cognitive functioning articles
Click on images to enlarge
- Posted using BlogPress from my iPad
- Posted using BlogPress from my iPad
Friday, December 09, 2011
Wednesday, September 14, 2011
Research Byte: Musicians experience less central auditory processing cognitive decline with age
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Monday, February 07, 2011
Ga (auditory processing)--the adolescent social butterfly at the CHC intelligence theory ball
In the CHC theory of intelligence, Gc is historically known as crystallized intelligence. Although featured prominently in CHC theory, Hunt (2000) has lamented the fact that researchers and intelligence scholars have largely ignored Gc recently in favor of studying more exciting or “sexy” CHC constructs (e.g., Gf). He called it the “wallflower” ability.
If Gc is the wallflower (Hunt, 2000) at the CHC ball, then Ga (auditory processing) is an adolescent social butterfly flitting from factor to factor, not readily defined or understood by others, and still in an awkward formative stage of adolescent theoretical and psychometric identity formation (with notable identity role confusion). Ga was the least studied factor in Carroll’s (1993) treatise, largely because reliable and valid technology for measuring Ga abilities did not exist during most of the days of prolific psychometric factor analytic research. This situation has been recently remedied by an explosion of wide ranging (but not necessarily internally coherent or organized research) on a wide array of Ga characteristics (see Conway, Pisoni & Kronenberger, 2009; Gathercole, 2006; Hubbard, 2010; Rammsayer & Brandler, 2007)
Conway, Pisoni and Kronenberger (2009) have gone as far as elevating auditory abilities to the status as a critical ability for higher level cognition and language development. Given the temporal/sequential nature of sound, these researchers suggest auditory abilities provide critical exposure to serially ordered events, “bootstrapping the development of sequential processing and behavior. Sound thus provides a ‘scaffolding”—a supporting framework—that organisms use to learn how to interpret and process sequential information” (p. 275). Thus, auditory abilities are believed to play a foundational causal role in the development of “perception, sensory-motor control, language, and higher level functions” (p. 278). Pretty heady stuff for the Ga social butterfly!
The possibility of components of Ga being crucial to cognitive development is reinforced by Rammsayer and colleagues (Helmbold, Troche, & Rammsayer, 2007; Rammsayer & Brandler, 2007) who have presented an intriguing program of systematic research that have suggested that auditory based temporal processing tasks form a temporal psychometric g-factor that is more strongly associated with psychometric g than a reaction time g-factor, the long considered holy grail essence of g.
Further reflecting the adolescent nature of our understanding of the Ga domain is the fact that auditory imagery, which according Hubbard (2010, p. 302) was defined by Intons-Peterson (1992, p. 46) as “the introspective persistence of an auditory experience, including one constructed from components drawn from long-term memory, in the absence of direct sensory instigation of that experience,” has a massive body of research literature—yet auditory imagery is nowhere to be found in the current CHC taxonomy. Hubbard's (2010) comprehensive review covers such wide ranging research as “(a) imagery for auditory features (pitch, timbre, loudness), (b) imagery for complex nonverbal auditory stimuli (musical contour, melody, harmony, tempo, notational audiation, environmental sounds), (c) imagery for verbal stimuli (speech, text, in dreams, interior monologue), (d) auditory imagery's relationship to perception and memory (detection, encoding, recall, mnemonic properties, phonological loop), and (e) individual differences in auditory imagery (in vividness, musical ability and experience, synesthesia, musical hallucinosis, schizophrenia, amusia).”
Additional examples of the emerging importance of Ga abilities, many not yet included in the CHC taxonomy, exist in other arenas. First, central auditory processing disorders (CAPD), which refer to “difficulties in the perceptual processing of auditory information in the auditory nervous system as demonstrated by poor performance in one or more of the following skill areas: auditory discrimination, auditory pattern recognition, temporal aspects of audition, auditory performance in competing acoustic signals, and auditory performance with de-graded acoustic signals” (DeBonis & Moncrieff, 2008, p. 4-5), are now recognized by professional associations serving speech-language pathologists and audiologists and have been linked to specific language disorders. Second, numerous studies have been studying performance on non- or pseudo-word repetition tasks, tasks that appear to measure a Ga conglomerate involving acoustic signal processing, phonological awareness and sensitivity, an apparent Glr-type phonological storage and recoding ability, and speech-motor planning (see review of Gathercole, 2006 for research findings and Archibald and Gathercole, 2006 for review of measures). Although the non-word repetition tests are most likely factorially messy, the resultant research begs for scrutiny given a meta-analysis of 34 studies that reported a significant difference (d = 0.65, N = 2865) between individuals with specific reading disabilities and matched control groups without a reading disability (Herrmann, Matyas & Pratt, 2006).
Third—and beyond. Research in Ga domains proliferates like mosquitoes on a humid summer evening in Minnesota, with research investigating rapid auditory gap detection (Stefanatos, Braitman, & Madigan, 2007) , speech perception and auditory temporal processing (Boets, Wouters, Van Wieringen, & Ghesquiere, 2007), rhythm perception and production (van Noorden & Moelansts, 2006), rhythm sensitivity (Holliman, Wood & Sheely, 2010), to name but a few. Clearly the domain of Ga is not well understood. Ga-related research is scattered across research labs, disciplines, and journals. It would be a huge task to integrate all the research. A clear understanding of the dimensional structural of the very broad Ga domain requires extensive factor analytic research.
If in doubt, I recently searched the IAP Reference Data Base and found over 1,600+ references that includes some form of "auditory" term in a journal title or keywords. Click here to view.
- iPost using BlogPress from my Kevin McGrew's iPad
intelligence IQ tests IQ testing IQ scores CHC intelligence theory CHC theory Cattell-Horn-Carroll human cognitive abilities psychology school psychology individual differences cognitive psychology neuropsychology psychology special education educational psychology psychometrics psychological assessment psychological measurement IQs Corner neuroscience neurocognitive cognitive abilities cognition Gc Ga crystallized intelligence auditory processing
If Gc is the wallflower (Hunt, 2000) at the CHC ball, then Ga (auditory processing) is an adolescent social butterfly flitting from factor to factor, not readily defined or understood by others, and still in an awkward formative stage of adolescent theoretical and psychometric identity formation (with notable identity role confusion). Ga was the least studied factor in Carroll’s (1993) treatise, largely because reliable and valid technology for measuring Ga abilities did not exist during most of the days of prolific psychometric factor analytic research. This situation has been recently remedied by an explosion of wide ranging (but not necessarily internally coherent or organized research) on a wide array of Ga characteristics (see Conway, Pisoni & Kronenberger, 2009; Gathercole, 2006; Hubbard, 2010; Rammsayer & Brandler, 2007)
Conway, Pisoni and Kronenberger (2009) have gone as far as elevating auditory abilities to the status as a critical ability for higher level cognition and language development. Given the temporal/sequential nature of sound, these researchers suggest auditory abilities provide critical exposure to serially ordered events, “bootstrapping the development of sequential processing and behavior. Sound thus provides a ‘scaffolding”—a supporting framework—that organisms use to learn how to interpret and process sequential information” (p. 275). Thus, auditory abilities are believed to play a foundational causal role in the development of “perception, sensory-motor control, language, and higher level functions” (p. 278). Pretty heady stuff for the Ga social butterfly!
The possibility of components of Ga being crucial to cognitive development is reinforced by Rammsayer and colleagues (Helmbold, Troche, & Rammsayer, 2007; Rammsayer & Brandler, 2007) who have presented an intriguing program of systematic research that have suggested that auditory based temporal processing tasks form a temporal psychometric g-factor that is more strongly associated with psychometric g than a reaction time g-factor, the long considered holy grail essence of g.
Further reflecting the adolescent nature of our understanding of the Ga domain is the fact that auditory imagery, which according Hubbard (2010, p. 302) was defined by Intons-Peterson (1992, p. 46) as “the introspective persistence of an auditory experience, including one constructed from components drawn from long-term memory, in the absence of direct sensory instigation of that experience,” has a massive body of research literature—yet auditory imagery is nowhere to be found in the current CHC taxonomy. Hubbard's (2010) comprehensive review covers such wide ranging research as “(a) imagery for auditory features (pitch, timbre, loudness), (b) imagery for complex nonverbal auditory stimuli (musical contour, melody, harmony, tempo, notational audiation, environmental sounds), (c) imagery for verbal stimuli (speech, text, in dreams, interior monologue), (d) auditory imagery's relationship to perception and memory (detection, encoding, recall, mnemonic properties, phonological loop), and (e) individual differences in auditory imagery (in vividness, musical ability and experience, synesthesia, musical hallucinosis, schizophrenia, amusia).”
Additional examples of the emerging importance of Ga abilities, many not yet included in the CHC taxonomy, exist in other arenas. First, central auditory processing disorders (CAPD), which refer to “difficulties in the perceptual processing of auditory information in the auditory nervous system as demonstrated by poor performance in one or more of the following skill areas: auditory discrimination, auditory pattern recognition, temporal aspects of audition, auditory performance in competing acoustic signals, and auditory performance with de-graded acoustic signals” (DeBonis & Moncrieff, 2008, p. 4-5), are now recognized by professional associations serving speech-language pathologists and audiologists and have been linked to specific language disorders. Second, numerous studies have been studying performance on non- or pseudo-word repetition tasks, tasks that appear to measure a Ga conglomerate involving acoustic signal processing, phonological awareness and sensitivity, an apparent Glr-type phonological storage and recoding ability, and speech-motor planning (see review of Gathercole, 2006 for research findings and Archibald and Gathercole, 2006 for review of measures). Although the non-word repetition tests are most likely factorially messy, the resultant research begs for scrutiny given a meta-analysis of 34 studies that reported a significant difference (d = 0.65, N = 2865) between individuals with specific reading disabilities and matched control groups without a reading disability (Herrmann, Matyas & Pratt, 2006).
Third—and beyond. Research in Ga domains proliferates like mosquitoes on a humid summer evening in Minnesota, with research investigating rapid auditory gap detection (Stefanatos, Braitman, & Madigan, 2007) , speech perception and auditory temporal processing (Boets, Wouters, Van Wieringen, & Ghesquiere, 2007), rhythm perception and production (van Noorden & Moelansts, 2006), rhythm sensitivity (Holliman, Wood & Sheely, 2010), to name but a few. Clearly the domain of Ga is not well understood. Ga-related research is scattered across research labs, disciplines, and journals. It would be a huge task to integrate all the research. A clear understanding of the dimensional structural of the very broad Ga domain requires extensive factor analytic research.
If in doubt, I recently searched the IAP Reference Data Base and found over 1,600+ references that includes some form of "auditory" term in a journal title or keywords. Click here to view.
- iPost using BlogPress from my Kevin McGrew's iPad
intelligence IQ tests IQ testing IQ scores CHC intelligence theory CHC theory Cattell-Horn-Carroll human cognitive abilities psychology school psychology individual differences cognitive psychology neuropsychology psychology special education educational psychology psychometrics psychological assessment psychological measurement IQs Corner neuroscience neurocognitive cognitive abilities cognition Gc Ga crystallized intelligence auditory processing
Wednesday, December 29, 2010
Neuropsychology of music and math disabilities: Guest blog post by Dr. Brad Hale
Dr. Brad Hale provided the following research information in a recent post on the PEDS listserv. With Brad's permission, I'm reproducing the information "as is." Thanks Brad.
There's lots of data now to support different types of math disability; we found 5 subtypes consistent with the NP and educational literature (visual-spatial, math reasoning, executive/computation, math facts/knowledge, Gerstmann Syndrome subtypes), we suggest are related to right posterior, right frontal, frontal-subcortical, left temporal/parietal, and left parietal dysfunction respectively. There were also two subtypes with math disability also showing the visual-spatial and math reasoning pattern in our SLD-psychopathology study. But clearly there are multiple neuropsychological processes involved in math and math disability, just like reading and reading disability. See the following articles/chapters (and our School Neuropsychology book):
Hale, J. B., Wycoff, K. L., & Fiorello, C. A. (2010). RTI and cognitive hypothesis testing for specific learning disabilities identification and intervention: The best of both worlds. In D. P. Flanagan & V. C. Alfonso (Eds.), Essentials of Specific Learning Disability Identification. Hoboken, NJ: John Wiley & Sons.
Hain, L. A., & Hale, J. B. (2010). “Nonverbal” learning disabilities or Asperger Syndrome? Clarification through cognitive hypothesis testing. In N. Mather & L. E. Jaffe (Eds.), Expert Psychological Report Writing. New York, NY: John Wiley & Sons.
Hale, J. B. (2010). Cognitive hypothesis testing for a child with math disability. In C. A. Riccio, J. R. Sullivan, & M. J. Cohen (Eds.), Neuropsychological assessment and intervention for childhood and adolescent disorders (pp. 54-62). New York, NY: John Wiley & Sons.
Hain, L. A., Hale, J. B., & Glass-Kendorski, J. (2009). Comorbidity of psychopathology in cognitive and academic SLD subtypes. In S. G. Pfeifer & G. Rattan (Eds.), Emotional disorders: A neuropsychological, psychopharmacological, and educational perspective (pp. 199-226). Middletown, MD: School Neuropsychology Press.
Hale, J. B., Fiorello, C. A., Dumont, R., Willis, J. O., Rackley, C., & Elliott, C. (2008). Differential Ability Scales–Second Edition (neuro)psychological Predictors of Math Performance for Typical Children and Children with Math Disabilities. Psychology in the Schools, 45, 838-858.
Hale, J. B., Fiorello, C. A., Miller, J. A., Wenrich, K., Teodori, A. M., & Henzel, J. (2008). WISC-IV assessment and intervention strategies for children with specific learning disabilities. In A. Prifitera, D. H. Saklofske, & L. G. Weiss (Eds.), WISC-IV clinical assessment and intervention (2nd ed.) (pp. 109-171). New York, NY: Elsevier Science.
Hale, J. B., Fiorello, C. A., Kavanagh, J. A., Holdnack, J. A., & Aloe, A. M. (2007). Is the demise of IQ interpretation justified? A response to special issue authors. Applied Neuropsychology, 14, 37-51.
Hale, J. B., & Fiorello, C. A. (2004). School neuropsychology: A practitioner’s handbook. New York, NY: Guilford Press.
Hale, J. B., Fiorello, C. A., Bertin, M., & Sherman, R. (2003). Predicting math competency through neuropsychological interpretation of WISC-III variance components. Journal of Psychoeducational Assessment, 21, 358-380.
As for music, the old assumption that the right hemisphere is specialized for music doesn't seem to fit well with the data. With the right superior temporal lobe more sensitive to spectral information, and the left sensitive to temporal information, different aspects of music are processed in the right and left hemispheres. There are differences in which hemisphere processes drums, violin, and saxophone if I remember correctly... This also fits well with our knowledge of a right preference for prosody and a left preference for phonological processing. However, subcortical structures have also been implicated, so as Drs. Koziol and Budding like to remind us, we shouldn't go "corticocentric" in our explanation of musical processing and skill. Then there is the literature that fits with the left-automatized/right-novel aspect of music, where novices use more right hemisphere functions to listen/play music, whereas expert musicians use more the left. Finally, there is the emotional valence associated with music, and whether we like it or not! See below:
Auditory perception of temporal and spectral events in patients with focal left and right cerebral lesions*1
Donald A. Robin, Daniel Tranel and Hanna Damasio
Available online 30 August 2004.
Abstract
The auditory perception of temporal and spectral information was studied in subjects with lesions in the temporoparietal region of the left (LH group), or right (RH group) hemisphere (n = 5 in each group) and in five normal controls. The temporal tasks included gap detection and two complex pattern perception tasks in which subjects had to identify the placement of the two closest tones (separated by the shortest interval) within a sequence of six tones. The spectral tasks involved pitch matching and frequency discrimination. The results showed a “double dissociation”: (1) the LH group was impaired in their ability to perceive temporal information, but the perception of spectral information was normal, and (2) the RH group was impaired in their ability to perceive spectral information, but the perception of temporal information was normal. The findings are consistent with the notion that temporal processing is a function of left-hemisphere structures and that spectral processing is a function of right-hemisphere structures.
Brain Organization for Music Processing
Annual Review of Psychology
Vol. 56: 89-114 (Volume publication date February 2005)
First published online as a Review in Advance on June 21, 2004
Isabelle Peretz and Robert J. Zatorre
ABSTRACT
Research on how the brain processes music is emerging as a rich and stimulating area of investigation of perception, memory, emotion, and performance. Results emanating from both lesion studies and neuroimaging techniques are reviewed and integrated for each of these musical functions. We focus our attention on the common core of musical abilities shared by musicians and nonmusicians alike. Hence, the effect of musical training on brain plasticity is examined in a separate section, after a review of the available data regarding music playing and reading skills that are typically cultivated by musicians. Finally, we address a currently debated issue regarding the putative existence of music-specific neural networks. Unfortunately, due to scarcity of research on the macrostructure of music organization and on cultural differences, the musical material under focus is at the level of the musical phrase, as typically used in Western popular music.
How Many Music Centers Are in the Brain?
ECKART O. ALTENMÜLLER
Annals of the New York Academy of Sciences
Volume 930, THE BIOLOGICAL FOUNDATIONS OF MUSIC pages 273–280, June 2001
Abstract: When reviewing the literature on brain substrates of music processing, a puzzling variety of findings can be stated. The traditional view of a left-right dichotomy of brain organization—assuming that in contrast to language, music is primarily processed in the right hemisphere—was challenged 20 years ago, when the influence of music education on brain lateralization was demonstrated. Modern concepts emphasize the modular organization of music cognition. According to this viewpoint, different aspects of music are processed in different, although partly overlapping neuronal networks of both hemispheres. However, even when isolating a single “module,” such as, for example, the perception of contours, the interindividual variance of brain substrates is enormous. To clarify the factors contributing to this variability, we conducted a longitudinal experiment comparing the effects of procedural versus explicit music teaching on brain networks. We demonstrated that cortical activation during music processing reflects the auditory “learning biography,” the personal experiences accumulated over time. Listening to music, learning to play an instrument, formal instruction, and professional training result in multiple, in many instances multisensory, representations of music, which seem to be partly interchangeable and rapidly adaptive. In summary, as soon as we consider “real music” apart from laboratory experiments, we have to expect individually formed and quickly adaptive brain substrates, including widely distributed neuronal networks in both hemispheres
Functional Anatomy of Musical Perception in Musicians
Takashi Ohnishi,
Hiroshi Matsuda,
Takashi Asada,
Makoto Aruga1,
Makiko Hirakata1,
Masami Nishikawa,
Asako Katoh and
Etsuko Imabayashi
Abstract
The present study used functional magnetic resonance to examine the cerebral activity pattern associated with musical perception in musicians and non-musicians. Musicians showed left dominant secondary auditory areas in the temporal cortex and the left posterior dorsolateral prefrontal cortex during a passive music listening task, whereas non-musicians demonstrated right dominant secondary auditory areas during the same task. A significant difference in the degree of activation between musicians and non-musicians was noted in the bilateral planum temporale and the left posterior dorsolateral prefrontal cortex. The degree of activation of the left planum temporale correlated well with the age at which the person had begun musical training. Furthermore, the degree of activation in the left posterior dorsolateral prefrontal cortex and the left planum temporale correlated significantly with absolute pitch ability. The results indicated distinct neural activity in the auditory association areas and the prefrontal cortex of trained musicians. We suggest that such activity is associated with absolute pitch ability and the use-dependent functional reorganization produced by the early commencement of long-term training.
Hits to the left, flops to the right: different emotions during listening to music are reflected in cortical lateralisation patterns
Eckart Altenmüller, , Kristian Schürmann, Vanessa K. Lim and Dietrich Parlitz
Abstract
In order to investigate the neurobiological mechanisms accompanying emotional valence judgements during listening to complex auditory stimuli, cortical direct current (dc)-electroencephalography (EEG) activation patterns were recorded from 16 right-handed students. Students listened to 160 short sequences taken from the repertoires of jazz, rock-pop, classical music and environmental sounds (each n=40). Emotional valence of the perceived stimuli were rated on a 5-step scale after each sequence. Brain activation patterns during listening revealed widespread bilateral fronto-temporal activation, but a highly significant lateralisation effect: positive emotional attributions were accompanied by an increase in left temporal activation, negative by a more bilateral pattern with preponderance of the right fronto-temporal cortex. Female participants demonstrated greater valence-related differences than males. No differences related to the four stimulus categories could be detected, suggesting that the actual auditory brain activation patterns were more determined by their affective emotional valence than by differences in acoustical “fine” structure. The results are consistent with a model of hemispheric specialisation concerning perceived positive or negative emotions proposed by Heilman [Journal of Neuropsychiatry and Clinical Neuroscience 9 (1997) 439].
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intelligence IQ tests IQ scores CHC theory Cattell-Horn-Carroll human cognitive abilities psychology school psychology individual differences cognitive psychology neuropsychology special education educational psychology psychometrics psychological assessment psychological measurement IQs Corner neuroscience neurocognitive cognitive abilities cognition Gq quantitative abilities quantitative knowledge quantitative reasoning music perception math disabilities dyscalculia
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