The concept of intelligence has been debated since introduction of IQ tests in the early 1900s. Numerous alternatives to unitary intelligence have achieved limited acceptance and IQ remains the predominant theoretical basis for schooling. Multiple intelligences theory, despite criticism it lacks experimental validity, has had sustained interest by educators worldwide as a means of personalizing instruction and curriculum. The neuroscientific evidence for the intelligences has not been updated since 1983. This investigation reviewed 417 neuroscientific studies examining neural correlates for skill units within seven intelligences. Neural activation patterns demonstrate each skill unit has its own unique neural underpinnings as well as neural features shared with other skill units within its designated intelligence. These patterns of commonality and uniqueness provide richly detailed neural architectures in support of MI theory as a scientific model of human intelligence. This brief article provides an excerpt from the full dataset describing the neural features for cognitive-skill units for the linguistic intelligence. Full details for six other intelligences are available in the original full article and supporting Supplemental Materials.

Keywords: Frames of mind, Multiple intelligences, Occipitotemporal

CHRONIC PAIN AND ACUTE PAIN

This investigation examines the neuroscientific bases for the theory of multiple intelligences (MI) as described by Gardner [1] in his influential book Frames of Mind. Gardner [1] redefined intelligence as the ability to solve problems or create products of value in a culture or community. Using this broad, common-sense definition and criteria that cover a range of evidence (e.g. neuroscience, psychometric and evolutionary evidence and atypical populations); Gardner [1] described eight distinct forms of intelligence that are possessed by all people, but in varying degrees. The eight intelligences identified to date are linguistic, logical-mathematical, spatial, kinesthetic, musical, interpersonal, intrapersonal and naturalist (Table 1). Each intelligence represents a composite of related cognitive-skills that includes convergent problem-solving as well as divergent thinking and creativity.

Educators around the world responded to MI theory with enthusiasm by revising instruction, redesigning curriculum and re-envisioning entire schools in order to personalize the educational experience and maximize success for all students regardless of their cognitive profiles [2]. However, doubts about the scientific validity and efficacy of MI theory limit its acceptance and adoption by traditional educational institutions [3].

MI theory was one of the first contemporary models of intelligence based on neuroscience evidence gathered by Gardner in the early 1980s. This evidence has not been comprehensively reevaluated since 1983, until recently when over 500 neuroscience reports were systematically reviewed. Five investigations used a “wisdom of the field” approach to gather insights from a wealth of neuroscience evidence to determine if the eight intelligences possess neural coherence aligned with contemporary cognitive models of skill and ability [4,5]. These data models indicate that each of the intelligences have neural architectures that are equivalent with the most widely accepted neural descriptions of general intelligence (IQ).

The idea of multiple intelligences is still evolving from a framework presented in 1983 towards a fully realized scientific theory. Shearer and Karanian [4] demonstrated that each intelligence has general neural coherence but for a theory to have scientific validity more detailed neural modeling is required. The following review of 417 neuroscience reports organizes 30 years of neural data according to the core skill units within each of seven intelligences. Naturalist is not included due to a limited number of studies available for its skill units. The goal was to determine if the evidence describes meaningful neural differences and commonalities among three or four skill units within each intelligence as predicted by MI theory.

The minimum number of studies included in this analysis was 32 for logical-mathematical and a maximum of 101 for intrapersonal (mean=60) (Table 1, column 1). A complex data set was obtained where neural activation patterns from three levels (primary, sub-regions, multi-regions) were matched to the intelligences’ skill units. The eight primary neural regions were defined as frontal, temporal, parietal, occipital, cerebellum, subcortical, cingulate and insular. Numerous sub-regions within each primary region were systematically organized (i.e., prefrontal gyrus, anterior cingulate, etc.) in addition to multi-region activation patterns (i.e., limbic system, occipitotemporal cortex, etc.).

SUMMARY AND CONCLUSION

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A detailed description of the entire neural data is beyond the scope of this discussion so the linguistic intelligence data will be presented to illustrate how the neural architectures for cognitive-skill units are related to each other and to their designated intelligence. Linguistic intelligence includes three cognitive-skill units: Reading, Writing and Speech.

LINGUISTIC

Linguistic intelligence is associated most strongly with the temporal (51 cites, 33%), frontal (44 cites, 28%) and parietal (24 cites, 15%) primary regions. Temporal sub-regions identified include inferior temporal, fusiform gyrus and visual word form area. Frontal sub-regions include inferior frontal gyrus, posterior inferior frontal gyrus and Brocas Area. Parietal sub-regions include inferior parietal lobule, angular gyrus and precuneus.

The reading skill unit has its highest primary regions nearly identical to those of the whole intelligence described above. Many of the same sub-regions are also included. Writing skill unit is dominated by the frontal (13 cites, 31%) and occipital (8 cites, 19%) regions. Sub-regions within the frontal cortex include prefrontal, motor cortex, dorsolateral PFC, Brocas Area and the orbitofrontal gyrus. Speech has the temporal cortex as its dominant (12 cites, 52%) with related sub-regions: superior temporal sulcus, Wernickes area and the visual word form area.

Overall, two skill units have temporal, frontal and parietal as their highest while it is in fourth place for the Writing unit. Writing is also different with occipital in second place and it is of much less importance to the other skill units. Each skill unit has its own unique sub-region pattern while having two sub-regions in common. Reading has four sub-regions unique to it while both writing and speech have five sub-regions that are not shared with either of the other two skill units (Table 2 and Figure 1).

DISCUSSION AND CONCLUSION

This investigation uncovered neural evidence indicating that within each of the multiple intelligences is cognitive-skill units that have their own neural uniqueness and commonalities. These shared and unique neural activations are evident in large (primary) regions as well as smaller sub-regions and large-scale multi-region activation patterns.

There are three potential implications emanating from this investigation. First, the development of any new scientific theory rarely emerges fully realized in a single effort. Frames of Mind are a comprehensive description of MI theory with brief descriptions of several neural regions associated with each of the seven intelligences. Extensive accounts of many other kinds of data are provided in support of Gardner’s contention that intelligence is best characterized as multiple rather than singular. The present analysis adds multiple layers of neural description to the frameworks underpinning each of the intelligences and their constituent skill units.

Neuroscientists study specific behaviors and then extrapolate from the data to infer broader abstract categories of behavior. The theory of multiple intelligences has been difficult to investigate directly due to the abstract nature of the designated intelligences as composites of skills and cognitive performances. The neural architectures presented here offer a detailed roadmap of specific behaviors amenable to experimental research not previously available. Thus, making further investigation of human intelligence in its many forms more amenable to scientific study.

Lastly, this work describes the neural features underlying specific cognitive-skills that are the target of instruction in schools and classrooms, e.g. reading, mathematical reasoning, musical performance and whole-body movement, etc. MI theory has inspired many educators to alter instruction, curriculum, and school design without this knowledge. However, due to scientific doubt and criticism by administrators, these efforts have been difficult to deploy widely and to sustain their integration into existing educational systems. The dichotomy between the science of brain research and the art of instruction has been described as a “bridge too far” by Bruer [6].

The emerging field of educational cognitive neuroscience strives to bridge these differences and apply its findings from the lab to the classroom in ways that can be systematic and replicable without over-simplification [7]. The detailed neural architectures described here represent a practical interface between instructional efforts and insights about how the brain functions during a variety of intellectual activities. This multiple intelligences-inspired interface provides a detailed neural foundation for the creation of educational systems that can personalize instruction and curriculum to maximize engagement, motivation and achievement of all students.

1.       Gardner H (1983) Frames of mind: The theory of multiple intelligences. New York: Basic Books.

2.       Chen J, Moran S, Gardner H (2009) Multiple intelligences around the world. San Francisco, CA: Jossey-Bass.

3.       Plucker J, Callahan C (2014) Research on giftedness and gifted education: Status of the field and considerations for the future. Exceptional Children 80: 390-406.

4.       Shearer CB, Karanian JM (2017) The neuroscience of intelligence: Empirical support for the theory of multiple intelligences? Trends Neurosci Educ 6: 211-223.

5.       Shearer B (2018) Multiple intelligences in teaching and education: Lessons learned from neuroscience. J Intelligence 6: 38.

6.       Bruer JT (1997) Education and the brain: A bridge too far. Educ Res 26: 4-16.

7.       Goswami U, Szucs D (2011) Educational neuroscience: Developmental mechanisms: Towards a conceptual framework. NeuroImage 57: 651-658.