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![The number of neurons in the cerebellum versus the number in the cerebral cortex. Neuron count data from: Lent et.al. [35]](publication/301598067/figure/fig1/AS:362309278027784@1463392671575/The-number-of-neurons-in-the-cerebellum-versus-the-number-in-the-cerebral-cortex-Neuron.png)
The number of neurons in the cerebellum versus the number in the cerebral cortex. Neuron count data from: Lent et.al. [35]
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Vandervert described how, in collaboration with the cerebral cortex, unconscious learning of cerebellar internal models leads to enhanced executive control in working memory in expert music performance and in scientific discovery. Following Vandervert’s arguments, it is proposed that since music performance and scientific discovery, two...
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Context 1
... such studies particularly relevant to the present article are the following: Akshoomoff et al. [3]; Balsters, Whalen, Robertson et al. [28]; Ito [7,8]; Leggio and Molinari [4]; Liao, Kronemer, Yau et al. [29]; Marvel and Desmond [30,31]: Schmahmann [32]; Stoodley, Valera and Schmahmann [33]; Strick, Dum and Fiez [34]; Vandervert [1]. Figure 1 illustrates the enormous, 69 billion-neuron computational capacity of the cerebellum compared to 16 billion neurons in the cerebral cortex [35] that is proposed have been and continues to be behind the evo- lution of uniquely human culture. As Leiner, Leiner and Dow [9] argued three decades ago, critically important in this relationship has been the evolutionary expansion of the cerebellum's dentate nucleus: ...
Citations
... However, despite the performance gains, the existing networks have been shown to be brittle and have several limitations and shortcomings. They require huge amounts of data to train, struggle with noisy and imbalanced datasets, do not generalize well to out-of-distribution data, and are vulnerable to shortcut learning and adversarial attacks [32]. While there have been studies on addressing these challenges individually, the majority of these specialized techniques and regularization approaches for overcoming a specific challenge lead to a trade-off in performance and do not provide a general solution [31]. ...
... The cerebellum is an important learning site in the brain [25,32] and, therefore, several studies in neuroscience have scrutinized how efficient learning is enabled in the cerebellum [11,12,18,19]. It has a relatively simple circuit architecture that resembles a three-layer feedforward network of neurons in which the "hidden layer" consists of Purkinje cells (P-cells), and the output layer consists of deep cerebellar nucleus (DCN) neurons. ...
As our understanding of the mechanisms of brain function is enhanced, the value of insights gained from neuroscience to the development of AI algorithms deserves further consideration. Here, we draw parallels with an existing tree-based ANN architecture and a recent neuroscience study[27] arguing that the error-based organization of neurons in the cerebellum that share a preference for a personalized view of the entire error space, may account for several desirable features of behavior and learning. We then analyze the learning behavior and characteristics of the model under varying scenarios to gauge the potential benefits of a similar mechanism in ANN. Our empirical results suggest that having separate populations of neurons with personalized error views can enable efficient learning under class imbalance and limited data, and reduce the susceptibility to unintended shortcut strategies, leading to improved generalization. This work highlights the potential of translating the learning machinery of the brain into the design of a new generation of ANNs and provides further credence to the argument that biologically inspired AI may hold the key to overcoming the shortcomings of ANNs.
... This specific performance of individual cerebellar structures, still to be clarified in detail, is learned through the repeated improvement of predictions, but also the control by internal models in the cerebellum and made available to the cerebral networks responsible for this . According to Vandervert (2016), the following new explanations for music learning can be discussed: ...
This chapter addresses how the embodiment approach may represent a unifying perspective for examining the cerebellar role in emotional behavior and psychological traits. It is not intended to be exhaustive, but rather it can be a good starting point for advancing the cerebellar neural mechanism underlying embodiment. Our goal is to provide illustrative examples of embodied emotions and psychological traits in the emerging field of emotional and cognitive cerebellum. We illustrate how the cerebellum could be an important hub in the embodiment processes, associated with empathic abilities, impaired emotional identification and expression (as occurring for example in the presence of alexithymia), and specific psychological constructs (i.e., hypnotizability).
... -Learning and memory processes. The cerebellum was also found to be involved in learning and memory processes (i.e., procedural, associative, and declarative) (Vandervert, 2016). Procedural memory has certainly received the most attention in literature, with cellular long-term depression and potentiation being the proven mechanisms through which the cerebellum mediates skill acquisition (Hirano, 1990). ...
The role of the cerebellum in neurodegenerative disorders that target cognitive functions has been a subject of increasing interest over the past years. However, a review focused on making clinicians more aware of the role of the cerebellum in dementia is still missing. This narrative review explores the possible factors explaining the involvement of the cerebellum in different kinds of dementia by providing more insights on how this structure can be relevant in clinical practice. It emerged that, despite overlapping in specific areas, structural cerebellar alterations in dementia show a certain degree of disease-specificity. Furthermore, the relevance of cerebellar changes in dementia is corroborated by correlations observed between their topography and cognitive symptomatology, as well as by its previously ignored involvement of the cerebellum in early stages of dementia. Despite needing further investigations, these findings could become a useful diagnostic aid for clinicians that should not be overlooked, in particular for those individuals who do not show distinct and manifest brain or neuropsychological alterations, but that still make clinicians suspect the presence of a neurocognitive disease.
... Vandervert (2015) and Vandervert and Vandervert-Moe[36] argued that such compositions and blends are often sent to working memory areas of the cerebral cortex in a spontaneous fashion and thus give rise to the intuitive insight behind creativity. With the evolution of the cerebellum of Homo sapiens(Leiner, Leiner & Dow, 1986, 1989, Vandervert[31,37] argued that this process was prominent (perhaps predominant) in driving the evolution of culture. ...
The purpose of this article is to argue that the patterns of sequence control over kinematics (movements) and dynamics (forces) which evolved in phonological processing in inner speech during the evolution of the social-cognitive capacities behind stone-tool making that led to the emergence of Homo sapiens are homologous to the social cerebellum’s capacity to learn patterns of sequence within language that we refer to as mathematics. It is argued that this evolution (1) selected toward a social cognitive cerebellum which arose from the arduous, repetitive precision patterns of knapping (stone shaping) and (2) that over a period of a million-plus years was selected from mentalizing toward the kinematics and dynamics as observed and modeled in Theory of Mind (ToM) of more experienced stone knappers. It is concluded that components of this socially-induced autobiographical knowledge, namely, (1) segmenting events, (2) sequencing events, and (3) sequencing event clusters, all at various levels of abstraction, can inform optimum approaches to one-on-one tutoring of children with mathematical learning disabilities.
... However, Nieder does not mention the fact that this intense training was found to engage bilateral areas of the cerebellum. Since the one-on-one tutorial training involved a high level of intense prolonged practice and, at the same time, employed intense social modeling learned in cerebellar internal models [23,[29][30][31], it was highly probable that the cerebellum was key to the corrective alignment of activity of the brain's overengagement in the MLDs. This idea is strongly supported by two lines of cerebellum research. ...
... Second, in social learning, the cerebellum learns internal models of the behavior and imagined thoughts of others-these are referred to as theory of mind (TOM) models [17]. The cerebellum thus learns the optimization and automaticity of skills and social behavior of others [23,[28][29][30][31]. ...
... Following directly in the vein of the above more recent and broader cerebellum research, Vandervert [21][22][23][24][25] provided arguments on the contributions of the cognitive and social cerebellum in the following areas: the origin of mathematics [21], the leaning of culture [22], and the beginnings of language in the phonological loop of working memory during stone-tool evolution [23][24][25]. The purpose of this article is to provide newer evidence and argument that language evolved principally through inner speech (in the phonological loop of working memory) modeled in the cerebellum as it evolved reciprocally with the evolution of stone-tool making. ...
... Following directly in the vein of the above more recent and broader cerebellum research, Vandervert [21][22][23][24][25] provided arguments on the contributions of the cognitive and social cerebellum in the following areas: the origin of mathematics [21], the leaning of culture [22], and the beginnings of language in the phonological loop of working memory during stone-tool evolution [23][24][25]. The purpose of this article is to provide newer evidence and argument that language evolved principally through inner speech (in the phonological loop of working memory) modeled in the cerebellum as it evolved reciprocally with the evolution of stone-tool making. ...
... 7862-7863) Vandervert [23,24] pointed out that, in their overall description of the evolution of stone-tool knapping and the brain, Stout and Hecht [30] concentrated on functions of the cerebral cortex and did not mention the possible roles of cerebellar internal modeling. To round out the discussion of learning stone-tool knapping, these roles could have included the following: (1) the role of neural coding in internal models in the cerebellum for cognitive and socially mediated skill development as described by Ito [7][8][9]; Van Overwalle, Manto, Leggio & Delgado-Garcia [11]; Vandervert [22], (2) the role of inner or silent speech in the phonological loop of working memory in such action as described by Alderson-Day and Fernyhough [28], Crespi, Read and Hurd [34], Mariën, Ackermann, Adamaszek, Barwood, Beaton, Desmond, et al. [18], Marvel and Desmond [26] and Marvel, Morgan and Kronemer [6], and (3) the role of the cerebellum in the internal modeling of repetitive silent speech in difficult tasks [18,33,39,40]. Recall, neural coding in cerebellar internal models, see (1) above, is accomplished by cerebellar microcomplexes which during repetitive skill learning correct movement and cognitive errors toward optimization of the skill at hand [7][8][9]. ...
Based on advances in cerebellum research as to its cognitive, social, and language contributions to working memory, the purpose of this article is to describe new support for the prominent involvement of cerebellar internal models in the adaptive selection of language. Within this context it has been proposed that (1) cerebellar internal models of inner speech during stone-tool making accelerated the adaptive evolution of new cause-and-effect sequences of precision stone-tool knapping requirements, and (2) that these evolving cerebellar internal models coded (i.e., learned in corticonuclear microcomplexes) such cause-and-effect sequences as phonological counterparts and, these, when sent to the cerebral cortex, became new phonological working memory. This article describes newer supportive research findings on (1) the cerebellum's role in silent speech in working memory, and (2) recent findings on genetic aspects (FOXP2) of the role of silent speech in language evolution. It is concluded that within overall cerebro-cerebellar evolution, without the evolution of cerebellar coding of stone-tool making sequences of primitive working memory (beginning approximately 1.7 million years ago) language would not have evolved in the subsequent evolution of Homo sapiens.
... It is well established that the cerebellar tissue plays a crucial role controlling locomotor activity [33] Lesions in the cerebellum lead to locomotor impairment, deficits in visual spatial processing, and linguistic skills [29]. The cerebellum and the cerebral cortex also influence the anxious behavior and the cognitive domain [33,54]. Although, we did not find any significative alterations in anxiety parameters or locomotor activity. ...
... Cerebellar cortical circuitry is eminently invariant being concerned with higher order behavior [29,54]. Impairment in working memory tasks can be part of the cerebellar cognitive affective syndrome which also leads to deficits in planning and set-shifting [29,33]. ...
... It has also been proposed as an analog to both the cerebellum and the cortex due to a similar architecture and gene expression, respectively (Farris, 2011;Tomer et al., 2010). Interestingly, although the cerebellum has classically been associated with motor function, there is increasing evidence for its role in cognition (Leiner et al., 1993;Vandervert, 2016) and as a key region in ASD susceptibility (Chen et al., 2017;Peter et al., 2016;Wang et al., 2014). This association has, however, been attributed to dysfunction of Purkinje cells (Box 1) (Clifford et al., 2019;Tsai et al., 2012), for which no correlate has been identified in Drosophila, thus limiting studies into this interesting topic. ...
Intellectual disability (ID) and autism spectrum disorders (ASD) are frequently co-occurring neurodevelopmental disorders and affect 2-3% of the population. Rapid advances in exome and genome sequencing have increased the number of known implicated genes by threefold, to more than a thousand. The main challenges in the field are now to understand the various pathomechanisms associated with this bewildering number of genetic disorders, to identify new genes and to establish causality of variants in still-undiagnosed cases, and to work towards causal treatment options that so far are available only for a few metabolic conditions. To meet these challenges, the research community needs highly efficient model systems. With an increasing number of relevant assays and rapidly developing novel methodologies, the fruit fly Drosophila melanogaster is ideally positioned to change gear in ID and ASD research. The aim of this Review is to summarize some of the exciting work that already has drawn attention to Drosophila as a model for these disorders. We highlight well-established ID- and ASD-relevant fly phenotypes at the (sub)cellular, brain and behavioral levels, and discuss strategies of how this extraordinarily efficient and versatile model can contribute to 'next generation' medical genomics and to a better understanding of these disorders.
... Accordingly, their watershed proposal spurred a huge amount of brain imaging research on the cerebellum's contributions to the motor, cognitive, and affective functions, and, specifically, the cerebellum's contributions to what they referred to as the "skillful manipulation of ideas" (1986, p. 444). Over the last three decades, Leiner et al.'s above-quoted proposal has been broadly confirmed and further extended (Ito, 1993(Ito, , 1997Akshoomoff et al., 1997;Desmond and Fiez, 1998;Dum and Strick, 2003;Strick et al., 2009;Balsters et al., 2010Balsters et al., , 2013Imamizu and Kawato, 2012;Marvel and Desmond, 2012;Stoodley et al., 2012;Bostan et al., 2013;Schmahmann, 2013;Leggio and Molinari, 2015;Moberget and Ivry, 2016;Vandervert, 2016Vandervert, , 2017aAdamaszek et al., 2017). Balsters et al. (2010Balsters et al. ( , 2013 and Bostan et al. (2013) are of particularly strong support of Leiner et al. (1986Leiner et al. ( , 1989Leiner et al. ( , 1991 in finding that (1) cerebro-cerebellar connections between the prefrontal cortex and the lateral cerebellum have grown more in volume in recent evolution than the rest of the cerebro-cerebellar connections, and (2) that, in these two-way connections, the cerebellum contributes skill routines and strategies for both first-and second-order rule-governed information processing, the highest levels of idea manipulation. ...
... First, the cerebellum-driven development of attentional control of cause-and-effect relationships and thus prediction in the working memory of the infant will be described. Second, it will be argued that increases in this same cerebellum-driven development of attentional control in working memory increased early human capacities for the mental and dexterous manipulation of these cause-and-effect relationships which undergirded the evolution of the advanced stone-tool technology and language of Homo sapiens (Vandervert, 2011(Vandervert, , 2015(Vandervert, , 2016(Vandervert, , 2017b). ...
... Vandervert further argued that this adaptive selection of the phonological loop parallels Mandler's (1992bMandler's ( , 2008 position that the infant's conceptual primitives (Figure 1) provide the bases for both simple inferential and analogical thought and the conceptual basis for the acquisition of the relational aspects of language. Via the acquisition of the adaptive phonological loop in working memory, then, more detailed cause-and-effect relationships could be mentally held and manipulated in working memory toward more refined predictions of future states, future states that became the framework for the adaptive origins of culture and, then, the relentless advance of culture (Vandervert, 2011(Vandervert, , 2016). We will return to Vandervert (2011) pre-human stone-tool scenario below. ...
This article extends Leiner et al.'s watershed position that cerebellar mechanisms played prominent roles in the evolution of the manipulation and refinement of ideas and language. First it is shown how cerebellar mechanism of sequence-detection may lead to the foundational learning of a predictive working memory in the infant. Second, it is argued how this same cerebellar mechanism may have led to the adaptive selection toward the progressively predictive phonological loop in the evolution of working memory of pre-humans. Within these contexts, cerebellar sequence detection is then applied to an analysis of leading anthropologists Stout and Hecht's cerebral cortex-based explanation of the evolution of culture and language through the repetitious rigors of stone-tool knapping. It is argued that Stout and Hecht's focus on the roles of areas of the brain's cerebral cortex is seriously lacking, because it can be readily shown that cerebellar sequence detection importantly (perhaps predominantly) provides more fundamental explanations for the origins of culture and language. It is shown that the cerebellum does this in the following ways: (1) through prediction-enhancing silent speech in working memory, (2) through prediction in observational learning, and (3) through prediction leading to accuracy in stone-tool knapping. It is concluded, in agreement with Leiner et al. that the more recently proposed mechanism of cerebellar sequence-detection has played a prominent role in the evolution of culture, language, and stone-tool technology, the earmarks of Homo sapiens. It is further concluded that through these same mechanisms the cerebellum continues to play a prominent role in the relentless advancement of culture.
... The phenomenon of rhythmic qualities in children's physical enactment of repetitive movement has recently been considered by a range of scholars with interest in both typical and atypical cognitive development and learning (Trninic & Saxe, 2017). The phylogenetically evolved tendency of the human cognitive architecture to enact physical movement in coordinated rhythmic structure bears developmental advantages (Kelso & Engstrom, 2006;Richmond & Zacks, 2017;Vandervert, 2016). For example, motor-action researchers Spencer, Semjen, Yang, and Ivry (2006) demonstrated the utility of rhythm in constructing and enacting a temporal event structure consisting of bimanual actions. ...
This article concerns the purpose, function, and mechanisms of students’ rhythmic behaviors as they solve embodied-interaction problems, specifically problems that require assimilating quantitative information structures embedded into the environment. Analyzing multimodal data of one student tackling a bimanual interaction design for proportion, we observed the (1) evolution of coordinated movements with stable temporal–spatial qualities; (2) breakdown of this proto-rhythmic form when it failed to generalize across the problem space; (3) utilization of available resources to obtain greater specificity by way of measuring spatial spans of movements; (4) determination of an arithmetic pattern governing the sequence of spatial spans; and (5) creation of a meta-rhythmic form that reconciles continuous movement with the arithmetic pattern. The latter reconciliation selectively retired, modified, and recombined features of her previous form. Rhythmic enactment, even where it is not functionally imperative, appears to constitute a tacit adaptation goal. Its breakdown reveals latent phenomenal properties of the environment, creating opportunities for quantitative reasoning, ultimately supporting the learning of curricular content.
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