Abstract
The purpose of this chapter is to describe support for the prominent involvement of cerebellar internal models in the formation of the adaptive selection of motor planning and preparation, leading to the evolution of working memory. Within this framework, it has been suggested that (1) motor traces were created to prolong the duration in which information could be held in mind and (2) this process led to the formation of working memory and (3) cerebellar-guided internal models of the motor traces were iteratively improved and, when communicated to the cerebral cortex, updated working memory content. It is concluded that, through this process, working memory facilitated the formation of language and culture in Homo sapiens.
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Keywords
- Cerebellar internal models
- Cerebellar sequence detection
- Cerebellum
- Inner speech
- Language evolution
- Phonological loop
- Stone-tool making
- Working memory
In this chapter you are asked to understand how the manipulation of ideas in working memory arose from motor activity of early humans. The gist of what you should learn from this chapter is outlined in the following paragraphs.
Working memory is vital for basic functions in everyday life. Evidence from the field of cognitive neuroscience has shown that working memory is supported by the motor system and, in particular, by regions that are involved in motor planning and preparation, in the absence of overt movement [as in when one imagines how to accomplish a task]. These “secondary motor” regions are called upon to support working memory by generating internal motor traces that reinforce the representation of information held in mind. The primary aim of this chapter is to elucidate motor-cognitive interactions through the lens of working memory and to suggest that cerebellar-driven internal models helped to form the origins of human language and culture.
Look carefully for evidence that such secondary motor activity underlies both the everyday use of language and the evolution of language in the first place. Return to Chap. 1 of this book, and consider how Albert Einstein’s description of “thinking” fits into the idea that motor planning and preparation lead to language forms of that same motor activity.
The term inner speech has been defined variably in the literature. One common feature is that inner speech is inaudible. In this report, inner speech is broadly defined as internalized, inaudible verbal thought that may or may not reach conscious awareness and may or may not be accompanied by subliminal vocal activity. To a certain extent, our views concur with those of Vygotsky, who posited that inner speech would not resemble spoken language as we know it but would be compressed. Thus, inner speech may represent a variant of external speech but is not necessarily a direct emulation of it (i.e., speech without sound). Conceivably, though, inner speech engages a verbal code, drawing upon motor planning and preparatory brain regions that precede overt speech. [The foregoing paragraph is from Marvel & Desmond (2012, p. 43, left col.).]
Note: Students should imagine their own inner speech, i.e., their own silent speech that occurs in the privacy of their own thoughts.
Introduction
More than three decades ago, Leiner et al. (1986) proposed that the evolutionarily newest parts of the cerebellum might accelerate information processing in the cerebral cortex and thus contribute to the skillful manipulation of ideas:
It has often been remarked that an explanation is required for the threefold to fourfold increase in the size of the cerebellum that occurred in the last million years of evolution. If the selection pressure has been strong for more cerebellum in the human brain as well as for more cerebral cortex, the interaction between the cerebellum and the cerebral cortex should provide some important advantages to humans. Because the cerebellum is traditionally regarded as a motor mechanism, these cerebrocerebellar interactions are usually thought to confer [only] a motor benefit on humans, such as increased dexterity of the hand. But … a detailed examination of cerebellar circuitry suggests that its phylogenetically newest parts may serve as a fast information-processing adjunct of the association cortex and could assist this cortex in the performance of a variety of manipulative skills, including the skill that is characteristic of anthropoid apes and [in] humans: the skillful manipulation of ideas. (p. 444)
Since the time of Leiner, Leiner, and Dow’s classic proposal, this “skillful manipulation of ideas” has been extensively study by psychologists and neurologists as working memory (Baddeley, 1992; Marvel & Desmond, 2010, 2012, 2016; Marvel et al., 2019; Hayter et al., 2007).
Working Memory and the Motor System
Working memory involves the ability to hold information in mind, without reliance on external cues, in order to rehearse or manipulate that information. Working memory can be sustained as long as necessary, through updated rehearsal, as long as attention is continuous. With distraction, access to that information is disrupted. Cognitive neuroscience has revealed that the brain’s motor system actively supports working memory functions (Marvel et al., 2019). It has been suggested that working memory substrates evolved from the existing, phylogenetically older motor system to create a redundant process to enhance cognition.
Visual and auditory memory is brief, on the order of 1–2 s. However, if such memories could be held in mind for longer durations, one could elaborate upon that knowledge, for example, by imagining it in novel ways. During evolution, this ability would have improved problem-solving skills and conferred an advantage to those who could best attain it. The motor system likely provided a way for early humans to prolong the duration of information held in mind, which led to the formation of working memory.
Motor planning and preparation regions of the brain, such as the premotor cortex, supplementary motor area, and cerebellar hemispheres, have been shown to activate just prior to activation within the primary motor cortex, which co-occurs with movement execution (Hulsmann et al., 2003). Motor planning and preparation neural activations, it is believed, represent the motor sequence for pending actions, and importantly, these “secondary” motor activations can be repeated until an action occurs. Thus, motor sequences for actions may be created without subsequent implementation. For example, motor planning brain regions might create a motor sequence, or motor trace, to represent imagined vocalizations, in the absence of overt speech. Similarly, motor planning regions might create a motor trace that represents a sequence of imagined movements (e.g., hand movements required to wave hello).
When vocalizations are held in mind, without outward expression, this can be thought of inner speech. It is inaudible and may or may not reach awareness. Inner speech likely represents a variant of external speech but is not necessarily a direct emulation of it (i.e., speech without sound). Conceivably, though, inner speech engages a verbal code, drawing upon motor planning and preparatory brain regions that precede overt speech.
Inner speech is evident when one tries to hold a long list of items in mind (e.g., recipe ingredients). One may become aware of “hearing” those items repeated in their head. This is a sign of the motor system’s support of cognition. As working memory demands increase, the motor system’s activity also increases (Marvel & Desmond, 2010, 2012; Marvel et al., 2012, 2019). If the list of items becomes very long, one may feel the need to repeat those items aloud. This is the motor system ramping up its efforts further to support cognition, and “regressing” to the primitive ways in which the motor system supported early forms of working memory, as overt speech. As working memory demands decrease, motor activity also decreases, and rehearsal again goes silent, as inner speech. [A similar support of cognition by the motor system would apply to the rehearsal of nonverbal content (e.g., visual image of writing a Chinese character by someone who does not know the language). For purposes of simplicity, however, this chapter emphasizes verbal working memory.]
Working Memory at the Operational Level
Baddeley (1992) developed a model which describes the details of the operational features of working memory. These operationally defined features of “components” of working memory allowed psychologists and neurologists to design controlled, measurable studies of working memory. Baddeley proposed that working memory is a multicomponent “brain system that provides temporary storage and manipulation for complex cognitive tasks such as language comprehension, learning, and reasoning” (1992, abstract). Baddeley divided working memory into the following three subcomponents: (1) an attention-controlling system, which serves as a “central executive”; (2) a visual-spatial sketch pad, which manipulates visual images within an ongoing flow of visual-spatial experience; and (3) a phonological loop, which both stores and rehearses speech-based information. These operational features of working memory provide a framework for understanding the capacity to manipulate ideas in working memory. For example, holding verbal information in mind over brief delays may have enabled the ability to combine brief vocalizations and attach them to symbolic meaning, supporting language development (Aboitiz et al., 2006). This framework, therefore, is important to understanding the evolution of language, thinking, problem-solving, planning, and creativity.
An overall description of the evolutionary emergence of the phonological loop was described by Baddeley et al. (1998). In brief, they proposed that “the primary purpose for which the phonological loop evolved was to store unfamiliar sound patterns while more permanent memory records are being constructed” (1998, abstract). Following the findings of Ashida et al. (2019), Castellazzi et al. (2018), and Saeki et al. (2013), it is reasonable to suggest that new, repetitious words would be error corrected and modeled in the cerebellum in relation to existing phonological working memory.
A Synergistic Relationship Between Working Memory and Stone-Tool Making
Vocalizations that co-occurred with external cues would eventually become associated, leading to the formation of symbolic meanings. This foundation of language could be communicated to others who could, in turn, build upon those symbolic meanings and apply them to novel situations. This process would have been useful for communicating important information, such as environmental dangers and new skills. Similarly, covert vocalizations could also hold symbolic material, in the form of inner speech, to guide one’s thoughts and actions.
During the evolution of stone-tool making, vocalizable or imitable symbols would have supported the transfer of knowledge of procedural memory (e.g., striking a stone with specified force), concept (e.g., creating a stone with a sharp point along the edge), and social cognition (e.g., making stone weapons pleases the group elders). Through repetition, these vocalizations and actions would have adaptively selected the phonological loop and visuospatial sketch pad within working memory.
Marvel et al. stated:
Motor traces may be utilized in the maintenance of content that would be inefficient to represent by visual or acoustic means alone. For example, creating an internal trace of the motor sequences that would be necessary to read aloud visually presented letters—without actually saying them aloud—may strengthen memory retention of those letters more than simple visual representation of the orthographic images or acoustic representation of letter sounds would alone. Similarly, creating an internal trace of the motor sequences involved in drawing non-verbalizable symbols, without overtly drawing them, may prolong memory of that symbol far longer than would visual representation. (2019)
The latter example would have been especially important for goals such as stone-tool making, that is, to have a goal in mind and then attempt to create it (i.e., through stone-tool knapping).
Cerebellar Internal Models Advanced Primitive Speech Toward Sophisticated Language
Neural coding of internal models in the cerebellum would have played a major role in this evolutionary process. Recall that neural coding in cerebellar internal models is accomplished via cerebellar microcomplexes, which detect and correct movement (and cognitive) errors in order to optimize the repetitive skill learning at hand (Ito, 1997, 2008, 2011). Neural coding of cerebellar internal models related to stone-tool making could have included: (1) the role of inner speech in the phonological loop of working memory in such action (Alderson-Day & Fernyhough, 2015; Mariën et al., 2014; Marvel & Desmond, 2012; Marvel et al., 2019), (2) ramping up of repetitive inner speech in difficult tasks (Saeki et al., 2013; Marvel & Desmond, 2010, 2012; Marvel et al., 2012, 2019), and (3) cognitive and socially mediated skill development (Ito, 1997, 2008, 2011; Van Overwalle et al. 2019; Vandervert, 2018). Socially mediated skill development would have included the learned pairing between vocalizations (or actions) and outcomes that were created first by the teacher and then by the learner. The learner would have attempted to recreate those vocalizations (or actions) to generate the same outcome. In this way, stone-tool making, for example, would have induced evolutionarily pressure to augment the phonological loop (and visuospatial sketch pad) rehearsal mechanisms, which are based on secondary motor activations of planning and preparation processes.
Within this context, it can be argued that the detailed cause-and-effect relationships required in the cerebellar modeling of stone-tool making led to the iterative fine-tuning of existing internal models (Imamizu et al., 2007) and relied upon planning and preparation-related motor activity, coupled with both overt and inner vocalizations in working memory. This state of working memory likely existed in early humans approximately 1.7 million year ago with early intentional stone modification where it is estimated that technology levels became related to brain evolution (Stout & Hecht, 2017). Such primitive inner vocalization likely played all of the many different roles in working memory as appeared in the modern inner speech of Homo sapiens (see Alderson-Day and Fernyhough (2015) for excellent discussions of these roles of inner speech). Marvel et al. (2019) argued that these modern roles of inner speech in working memory were adaptively selected from such primitive roles.
In this regard, Vandervert (2018, 2019, 2020) suggested that this early stone era was the basis of the adaptive selection among cerebellar internal models from vocalization toward primitive speech and primitive inner speech. Cerebellar internal models for primitive inner speech would have adaptively increased the detailed quality of prediction of the effects of the stonework. In addition, primitive inner speech rehearsal during stonework would have helped retain constantly new, simple cause-and-effect relationships in memory (Vandervert, 2020) to improve knapping outcomes. Such an adaptive selection of “verbal” material from vocalization in early working memory is supported by Mariën et al. (2014).
This overall evolutionary scenario is strongly in sync with Baddeley et al.’s (1998) proposal that “the primary purpose for which the phonological loop evolved is to store unfamiliar sound patterns while more permanent memory records are being constructed” (abstract). Following more recent support from the findings of Castellazzi et al. (2018) and Mariën et al. (2014), it is reasonable to suggest that new, repetitious words would be error corrected and modeled in inner speech and neutrally coded with novel motor traces, guided by the cerebellum. That is, this newer evidence provides a direct neurological parallel to Baddeley, Gathercole, and Papagno’s description of the purpose and operation of the phonological loop for acquisition of new word forms.
Conclusions
Working memory emerged from evolutionary pressures that selected toward holding information in mind for more than just a few seconds. This process likely drew upon the existing motor system, which involved motor planning and preparation mechanisms, that could be activated and reactivated indefinitely. Such motor traces represented the sequence of neural activity that would be needed to execute intended actions, even if those actions were never implemented. This process provided the neural underpinnings of sustained rehearsal for verbal and nonverbal content within working memory.
Cerebellar internal models enabled fine-tuning of these motor traces to make new working memory content (primitive or modern) faster, more consistent, and optimized toward the task at hand (Ito, 1997). Evolving verbal working memory, in particular, provided the critical adaptive advantage toward the emergence of language. It is suggested that without this internal modeling by the evolving cerebellum, the manipulation of ideas via working memory that is inherent in language-driven thought [as theorized by Leiner et al., 1986 at the beginning of this chapter] would not have evolved in the cerebral cortex to distinguish Homo sapiens.
Student Essay Questions
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1.
What is inner speech?
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2.
How does inner speech sustain or support working memory?
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3.
Give two examples of everyday motor planning and preparation in visual-spatial imagination.
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4.
Why would brief, often brilliant products of working memory be sustained by intricate motor activity? Hint: Consult Einstein’s description of “thinking” in Chap. 1 of this book. Then, recognize that Einstein used his working memory to make mathematical models of his own imagined movement in space and time. Here’s Einstein’s imagination of movement at age 16:
How…could…a universal principle [underlying true physical laws] be found? After ten years of reflection such a principle resulted from a paradox upon which I had already hit at age of sixteen: If I pursue a beam of light with the velocity of c (velocity of light in a vacuum), I should observe such a beam of light as a spatially oscillatory electromagnetic field at rest. However, there seems to be no such thing, whether on the basis of experience or according to Maxwell’s equations. From the very beginning it appeared to me intuitively clear that, judged from the standpoint of such an observer, everything would have to happen according to the same laws as for an observer who, relative to the earth, was at rest. For how, otherwise, should the first observer know, i.e., be able to determine, that he is in a state of fast uniform motion? (1949, p. 53)
Einstein himself said of his intuitively derived paradox, “One sees in this paradox the germ of the special relativity theory is already contained” (Einstein, 1949, p. 53).
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5.
Why would ancient stone-tool makers have engaged in inner speech (or inner vocalization) while knapping stones, especially while first learning stone-tool making?
References
Aboitiz, F., Aboitiz, R., Garcia, R., Bosman, C., & Brunetti, E. (2006). Cortical memory mechanisms and language origins. Brain and Language, 98(1), 40–56.
Alderson-Day, B., & Fernyhough, C. (2015). Inner speech: Development, cognitive functions, phenomenology, and neurobiology. Psychological Bulletin, 141(5), 931–965.
Ashida, R., Cerminara, N. L., Edwards, R. J., Apps, R., & Brooks, J. C. W. (2019). Sensorimotor, language, and working memory representation within the human cerebellum. Human Brain Mapping, 40, 4732–4747. https://doi.org/10.1002/hbm.24733
Baddeley, A. (1992). Working memory. Science, 255, 556–559.
Baddeley, A., Gathercole, S., & Papagno, C. (1998). The phonological loop as a language learning device. The Psychological Review, 105, 158–173.
Castellazzi, G., Bruno, S. D., Toosy, A. T., Casiraghi, L., Palesi, F., Savini, G., et al. (2018). Prominent changes in cerebro-cerebellar functional connectivity during continuous cognitive processing. Frontiers in Cellular Neuroscience, 12, 331. https://doi.org/10.3389/fncel.2018.00331
Einstein, A. (1949). Autobiographical notes. In A. Schillp (Ed.), Albert Einstein: Philosopher-scientist (Vol. 1, pp. 1–95). Open Court.
Hayter, A. L., Langdon, D. W., & Ramnani, N. (2007). Cerebellar contributions to working memory. NeuroImage, 36(3), 943–954.
Hulsmann, E., Erb, M., & Grodd, W. (2003). From will to action: Sequential cerebellar contributions to voluntary movement. NeuroImage, 20(3), 1485–1492.
Imamizu, H., Higuchi, S., Toda, A., & Kawato, M. (2007). Reorganization of brain activity for multiple internal models after short but intensive training. Cortex, 43, 338–349.
Ito, M. (1997). Cerebellar microcomplexes. In J. D. Schmahmann (Ed.), The cerebellum and cognition (pp. 475–487). Academic.
Ito, M. (2008). Control of mental activities by internal models in the cerebellum. Nature Reviews Neuroscience, 9, 304–313. https://doi.org/10.1038/nrn2332
Ito, M. (2011). The cerebellum: Brain for an implicit self. FT Press.
Leiner, H., Leiner, A., & Dow, R. (1986). Does the cerebellum contribute to mental skills? Behavioral Neuroscience, 1986(100), 443–454.
Mariën, P., Ackermann, H., Adamaszek, M., Barwood, C. H., Beaton, A., Desmond, J., De Witte, E., Fawcett, A. J., Hertrich, I., Küper, M., Leggio, M., Marvel, C., Molinari, M., Murdoch, B. E., Nicolson, R. I., Schmahmann, J. D., Stoodley, C. J., Thürling, M., Timmann, D., … Ziegler, W. (2014). Consensus paper: Language and the cerebellum: an ongoing enigma. Cerebellum (London, England), 13(3), 386–410. https://doi.org/10.1007/s12311-013-0540-5
Marvel, C. L., & Desmond, J. E. (2010). Functional topography of the cerebellum in verbal working memory. Neuropsychology Review, 20, 271–279.
Marvel, C., & Desmond, J. (2012). From storage to manipulation: How the neural correlates of verbal working memory reflect varying demands on inner speech. Brain and Language, 120, 42–51.
Marvel, C. L., & Desmond, J. E. (2016). Chap 3: The cerebellum and verbal working memory. In P. Marien & M. Manto (Eds.), The linguistic cerebellum. Elsevier.
Marvel, C. L., Faulkner, M. L., Strain, E. C., Mintzer, M. Z., & Desmond, J. E. (2012). An fMRI investigation of cerebellar function during verbal working memory in methadone maintenance patients. The Cerebellum, 11, 300–310.
Marvel, C., Morgan, O., & Kronemer, S. (2019). How the motor system integrates with working memory. Neuroscience and Biobehavioral Reviews, 102. https://doi.org/10.1016/j.neubiorev.2019.04.017
Saeki, E., Baddeley, A. D., Hitch, G. J., & Saito, S. (2013). Breaking a habit: The role of the phonological loop in action control. Memory & Cognition, 41(7), 1065–1078. https://doi.org/10.3758/s13421-013-0320-y
Stout, D., & Hecht, E. (2017). The evolutionary neuroscience of cumulative culture. PNAS, 114(30), 7861–7868.
Van Overwalle, F., Manto, M., Leggio, M., & Delgado-García, J. (2019). The sequencing process generated by the cerebellum crucially contributes to social interactions. Medical Hypotheses, 128, 10.1016/j.mehy.2019.05.014.
Vandervert, L. (2018). How prediction based on sequence detection in the cerebellum led to the origins of stone tools, language, and culture and, thereby, to the rise of Homo sapiens. Frontiers in Cellular Neuroscience, 12, 408. https://doi.org/10.3389/fncel.2018.00408
Vandervert, L. (2019). The evolution of theory of mind (ToM) within the evolution of cerebellar sequence detection in stone-tool making and language: Implications for studies of higher-level cognitive functions in degenerative cerebellar atrophy. Cerebellum & Ataxias, 6(1), 1–7. https://doi.org/10.1186/s40673-019-0101-x
Vandervert, L. (2020). The cerebellum-driven social learning of inner speech in the evolution of stone-tool making and language: Innate hand-tool connections in the cerebro-cerebellar system. In F. Van Overwalle, M. Manto, Z. Cattaneo, et al. (Eds.), Consensus paper: Cerebellum and social cognition. Cerebellum. https://doi.org/10.1007/s12311-020-01155-1
Further Reading
Adamaszek, M., D'Agata, F., Ferrucci, R., Habas, C., Keulen, S., Kirkby, K. C., Leggio, M., Mariën, P., Molinari, M., Moulton, E., Orsi, L., Van Overwalle, F., Papadelis, C., Priori, A., Sacchetti, B., Schutter, D. J., Styliadis, C., & Verhoeven, J. (2017). Consensus paper: Cerebellum and emotion. The Cerebellum, 16(2), 552–576.
Bareš, M., Apps, R., Avanzino, L., Breska, A., D’Angelo, E., Filip, P., Gerwig, M., Ivry, R. B., Lawrenson, C. L., Louis, E. D., Lusk, N. A., Manto, M., Meck, W. H., Mitoma, H., & Petter, E. A. (2019). Consensus paper: Decoding the contributions of the cerebellum as a time machine. From Neurons to Clinical Applications. Cerebellum, 18(2), 266–286. https://doi.org/10.1007/s12311-018-0979-5
Baumann, O., Borra, R. J., Bower, J. M., Cullen, K. E., Habas, C., Ivry, R. B., Leggio, M., Mattingley, J. B., Molinari, M., Moulton, E. A., Paulin, M. G., Pavlova, M. A., Schmahmann, J. D., & Sokolov, A. A. (2015). Consensus paper: The role of the cerebellum in perceptual processes. Cerebellum (London, England), 14(2), 197–220. https://doi.org/10.1007/s12311-014-0627-7
Buckner, R. L. (2013). The cerebellum and cognitive function: 25 years of insight from anatomy and neuroimaging. Neuron, 80(3), 807–815. https://doi.org/10.1016/j.neuron.2013.10.044
Cook, R., Bird, G., Catmur, C., Press, C., & Heyes, C. (2014). Mirror neurons: From origin to function. The Behavioral and Brain Sciences, 37, 177–192.
Doya, K. (1999). What are the computations of the cerebellum, the basal ganglia and the cerebral cortex? Neural Networks, 12, 961–974.
Faisal, A., Stout, D., Apel, J., & Bradley, B. (2010). The manipulative complexity of Lower Paleolithic stone toolmaking. PLoS One, 5, e13718.
Geva, S., & Fernyhough, C. (2019). A penny for your thoughts: Children’s inner speech and its neuro-development. Frontiers in Psychology Cognitive Science, 10, 1708.
Imamizu, H., & Kawato, M. (2009). Brain mechanisms for predictive control by switching internal models: Implications for higher-order cognitive functions. Psychological Research, 73(4), 527–544.
Imamizu, H., & Kawato, M. (2012). Cerebellar internal models: Implications for dexterous use of tools. Cerebellum, 11, 325–335.
Ito, M. (1993). Movement and thought: Identical control mechanisms by the cerebellum. Trends in Neurosciences, 16, 448–450.
Koziol, L. F., Budding, D., Andreasen, N., D'Arrigo, S., Bulgheroni, S., Imamizu, H., Ito, M., Manto, M., Marvel, C., Parker, K., Pezzulo, G., Ramnani, N., Riva, D., Schmahmann, J., Vandervert, L., & Yamazaki, T. (2014). Consensus paper: The cerebellum’s role in movement and cognition. Cerebellum, 13(1), 151–177. https://doi.org/10.1007/s12311-013-0511-x. PMID: 23996631; PMCID: PMC4089997.
Laland, K. N., & Bateson, P. (2001). The mechanisms of imitation. Cybernetics and Systems, 32, 195–224.
Leggio, M., & Molinari, M. (2015). Cerebellar sequencing: A trick for predicting the future. Cerebellum, 14, 35–38. https://doi.org/10.1007/s12311-014-0616-x
Leiner, H., Leiner, A., & Dow, R. (1989). Reappraising the cerebellum: What does the hindbrain contribute to the forebrain? Behavioral Neuroscience, 103, 998–1008.
Leto, K., Arancillo, M., Becker, E. B., Buffo, A., Chiang, C., Ding, B., Dobyns, W. B., Dusart, I., Haldipur, P., Hatten, M. E., Hoshino, M., Joyner, A. L., Kano, M., Kilpatrick, D. L., Koibuchi, N., Marino, S., Martinez, S., Millen, K. J., Millner, T. O., … Hawkes, R. (2016). Consensus paper: Cerebellar development. Cerebellum (London, England), 15(6), 789–828. https://doi.org/10.1007/s12311-015-0724-2
Liao, D. A., Kronemer, S. I., Yau, J. M., Desmond, J. E., & Marvel, C. L. (2014). Motor system contributions to verbal and non-verbal working memory. Frontiers in Human Neuroscience, 8, 753. https://doi.org/10.3389/fnhum.2014.00753
Luria, A. R. (1980). Higher cortical functions in man (2nd ed.). Basic Books.
Macher, K., Böhringer, A., Villringer, A., & Pleger, B. (2014). Cerebellar-parietal connections underpin phonological storage. The Journal of Neuroscience, 34(14), 5029–5037.
Magnani, M., Rezek, Z., Lin, S. C., Chan, A., & Dibble, H. L. (2014). Flake variation in relation to the application of force. Journal of Archaeological Science, 46, 37–49.
Moberget, T., Gullesen, E. H., Andersson, S., Ivry, R. B., & Endestad, T. (2014). Generalized role for the cerebellum in encoding internal models: Evidence from semantic processing. The Journal of Neuroscience, 34(8), 2871–2878. https://doi.org/10.1523/JNEUROSCI.2264-13.2014
Morgan, T. J., et al. (2015). Experimental evidence for the co-evolution of hominin toolmaking teaching and language. Nature Communications, 6, 6029.
Nonaka, T., Bril, B., & Rein, R. (2010). How do stone knappers predict and control the outcome of flaking? Implications for understanding early stone tool technology. Journal of Human Evolution, 59, 155–167.
Perrone-Bertolotti, M., Rapin, L., Lachaux, J. P., Baciu, M., & Loevenbruck, H. (2014). What is that little voice inside my head? Inner speech phenomenology, its role in cognitive performance, and its relation to self-monitoring. Behavioural Brain Research, 261, 220–239.
Putt, S. S., Woods, A. D., & Franciscus, R. G. (2014). The role of verbal interaction during experimental bifacial stone tool manufacture. Lithic Technology, 39, 96–112.
Roux, V., Bril, B., & Dietrich, G. (1995). Skills and learning difficulties involved in stone knapping. World Archaeology, 27, 63–87.
Schmahmann, J. D., Guell, X., Stoodley, C. J., & Halko, M. A. (2019). The theory and neuroscience of cerebellar cognition. Annual Review of Neuroscience, 42, 337–364. https://doi.org/10.1146/annurev-neuro-070918-050258
Stout, D. (2013). Neuroscience of technology. In P. J. Richerson & M. Christiansen (Eds.), Cultural evolution: Society, technology, language, and religion (Strungmann forum reports) (pp. 157–173). MIT Press.
Stout, D., Apel, J., Commander, J., & Roberts, M. (2014). Late Acheulean technology and cognition at Boxgrove, UK. Journal of Archaeological Science, 41, 576–590.
Unsworth, N., Spillers, G., & Brewer, G. (2012). The role of working memory capacity in autobiographical retrieval: Individual differences in strategic search. Memory, 20(2), 167–176.
Wolpert, D., Doya, K., & Kawato, M. (2003). A unifying computational framework for motor control and social interaction. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 358(1431), 593–602.
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Marvel, C. (2022). From Motor Systems to Working Memory: The Origins of Stone Tools, Language, Culture, and Rise of Homo sapiens. In: The New Revolution in Psychology and the Neurosciences. Springer, Cham. https://doi.org/10.1007/978-3-031-06093-9_5
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