The Cerebellum: Adaptive Prediction for Movement and Cognition.
TL;DR: This work examines how two key concepts that have been suggested as general computational principles of cerebellar function- prediction and error-based learning- might be relevant in the operation of cognitive cerebro-cerebellar loops.
About: This article is published in Trends in Cognitive Sciences.The article was published on 2017-05-01 and is currently open access. It has received 394 citations till now. The article focuses on the topics: Brain stimulation & Neuropsychology.
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TL;DR: Application of diffusion map embedding to resting-state data from the Human Connectome Project dataset shows for the first time that cerebellar functional regions follow a gradual organization which progresses from primary (motor) to transmodal (DMN, task-unfocused) regions.
Abstract: A central principle for understanding the cerebral cortex is that macroscale anatomy reflects a functional hierarchy from primary to transmodal processing. In contrast, the central axis of motor and nonmotor macroscale organization in the cerebellum remains unknown. Here we applied diffusion map embedding to resting-state data from the Human Connectome Project dataset (n = 1003), and show for the first time that cerebellar functional regions follow a gradual organization which progresses from primary (motor) to transmodal (DMN, task-unfocused) regions. A secondary axis extends from task-unfocused to task-focused processing. Further, these two principal gradients revealed novel functional properties of the well-established cerebellar double motor representation (lobules I-VI and VIII), and its relationship with the recently described triple nonmotor representation (lobules VI/Crus I, Crus II/VIIB, IX/X). Functional differences exist not only between the two motor but also between the three nonmotor representations, and second motor representation might share functional similarities with third nonmotor representation.
254 citations
Cites background from "The Cerebellum: Adaptive Prediction..."
...Similarly, tasks that activate DMN regions such as daydreaming and mind wandering (Mason et al., 2007; Christoff et al., 2009; Stawarczyk et al., 2011) can be conceptualized as more distant from motor processing than goal-directed cognitive control and decision-making processes that activate…...
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TL;DR: This work analyzes endocranial casts of Homo sapiens fossils from different time periods to show that, 300,000 years ago, brain size in early H. sapiens already fell within the range of present-day humans.
Abstract: Modern humans have large and globular brains that distinguish them from their extinct Homo relatives. The characteristic globularity develops during a prenatal and early postnatal period of rapid brain growth critical for neural wiring and cognitive development. However, it remains unknown when and how brain globularity evolved and how it relates to evolutionary brain size increase. On the basis of computed tomographic scans and geometric morphometric analyses, we analyzed endocranial casts of Homo sapiens fossils (N = 20) from different time periods. Our data show that, 300,000 years ago, brain size in early H. sapiens already fell within the range of present-day humans. Brain shape, however, evolved gradually within the H. sapiens lineage, reaching present-day human variation between about 100,000 and 35,000 years ago. This process started only after other key features of craniofacial morphology appeared modern and paralleled the emergence of behavioral modernity as seen from the archeological record. Our findings are consistent with important genetic changes affecting early brain development within the H. sapiens lineage since the origin of the species and before the transition to the Later Stone Age and the Upper Paleolithic that mark full behavioral modernity.
206 citations
TL;DR: The paper substantiates the concept of CCAS with recent evidence from different scientific angles, promotes awareness of the CCAS as a clinical entity, and examines the current insight into the therapeutic options available.
Abstract: Sporadically advocated over the last two centuries, a cerebellar role in cognition and affect has been rigorously established in the past few decades. In the clinical domain, such progress is epitomized by the “cerebellar cognitive affective syndrome” (“CCAS”) or “Schmahmann syndrome.” Introduced in the late 1990s, CCAS reflects a constellation of cerebellar-induced sequelae, comprising deficits in executive function, visuospatial cognition, emotion–affect, and language, over and above speech. The CCAS thus offers excellent grounds to investigate the functional topography of the cerebellum, and, ultimately, illustrate the precise mechanisms by which the cerebellum modulates cognition and affect. The primary objective of this task force paper is thus to stimulate further research in this area. After providing an up-to-date overview of the fundamental findings on cerebellar neurocognition, the paper substantiates the concept of CCAS with recent evidence from different scientific angles, promotes awareness of the CCAS as a clinical entity, and examines our current insight into the therapeutic options available. The paper finally identifies topics of divergence and outstanding questions for further research.
192 citations
TL;DR: The principles emerging from studies of the cerebellum have striking parallels with those in other brain areas and in artificial neural networks, as well as some notable differences, which can inform future research on supervised learning and inspire next-generation machine-based algorithms.
Abstract: Supervised learning plays a key role in the operation of many biological and artificial neural networks. Analysis of the computations underlying supervised learning is facilitated by the relatively simple and uniform architecture of the cerebellum, a brain area that supports numerous motor, sensory, and cognitive functions. We highlight recent discoveries indicating that the cerebellum implements supervised learning using the following organizational principles: ( a) extensive preprocessing of input representations (i.e., feature engineering), ( b) massively recurrent circuit architecture, ( c) linear input-output computations, ( d) sophisticated instructive signals that can be regulated and are predictive, ( e) adaptive mechanisms of plasticity with multiple timescales, and ( f) task-specific hardware specializations. The principles emerging from studies of the cerebellum have striking parallels with those in other brain areas and in artificial neural networks, as well as some notable differences, which can inform future research on supervised learning and inspire next-generation machine-based algorithms.
157 citations
Cites background from "The Cerebellum: Adaptive Prediction..."
...In this review, we summarize recent discoveries about how supervised learning is implemented in the cerebellum, a neural system that is tightly interconnected with multiple brain areas and plays a key role in the adaptive control of motor, sensory, and cognitive functions (Sokolov et al. 2017)....
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...…cerebellar modules support many functions, including fine motor control and navigation (Lefort et al. 2015), learned fear and other emotions (Perciavalle et al. 2013, Strata 2015), reward (Mittleman et al. 2008), and cognitive processing (Hoche et al. 2016, Koziol et al. 2014, Sokolov et al. 2017)....
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...The highly recurrent architecture in the cerebellum may support similar functions, including language processing and the coordination of sequential movements (Hikosaka et al. 1999, Leggio & Molinari 2015, Penhune & Steele 2012, Sokolov et al. 2017)....
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...The Purkinje cells are a key part of the adaptive processor that generates responses and distributes them, via the cerebellar nuclei, to numerous brain areas, including sensory, decision-making, and motor centers (Sokolov et al. 2017)....
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TL;DR: This consensus paper brings together experts from different fields to discuss recent efforts in understanding the role of the cerebellum in social cognition, and the understanding of social behaviors and mental states by others, its effect on clinical impairments such as cerebellar ataxia and autism spectrum disorder, and how the Cerebellum can become a potential target for noninvasive brain stimulation as a therapeutic intervention.
Abstract: The traditional view on the cerebellum is that it controls motor behavior. Although recent work has revealed that the cerebellum supports also nonmotor functions such as cognition and affect, only during the last 5 years it has become evident that the cerebellum also plays an important social role. This role is evident in social cognition based on interpreting goal-directed actions through the movements of individuals (social "mirroring") which is very close to its original role in motor learning, as well as in social understanding of other individuals' mental state, such as their intentions, beliefs, past behaviors, future aspirations, and personality traits (social "mentalizing"). Most of this mentalizing role is supported by the posterior cerebellum (e.g., Crus I and II). The most dominant hypothesis is that the cerebellum assists in learning and understanding social action sequences, and so facilitates social cognition by supporting optimal predictions about imminent or future social interaction and cooperation. This consensus paper brings together experts from different fields to discuss recent efforts in understanding the role of the cerebellum in social cognition, and the understanding of social behaviors and mental states by others, its effect on clinical impairments such as cerebellar ataxia and autism spectrum disorder, and how the cerebellum can become a potential target for noninvasive brain stimulation as a therapeutic intervention. We report on the most recent empirical findings and techniques for understanding and manipulating cerebellar circuits in humans. Cerebellar circuitry appears now as a key structure to elucidate social interactions.
145 citations
Additional excerpts
...…Lupo6 & Qianying Ma1 &Marco Michelutti11,12 & Giusy Olivito6,7 &Min Pu1 & Laura C. Rice13 & Jeremy D. Schmahmann10 & Libera Siciliano14 & Arseny A. Sokolov11,15,16,17 & Catherine J. Stoodley13 & Kim van Dun18 & Larry Vandervert19 &Maria Leggio6,7 Mario Manto mmanto@ulb.ac.be Zaira Cattaneo…...
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References
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TL;DR: In this paper, the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI data from 1,000 subjects and a clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex.
Abstract: Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.
6,284 citations
TL;DR: A perceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal symbol systems and implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.
Abstract: Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components - not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored.
5,259 citations
"The Cerebellum: Adaptive Prediction..." refers background in this paper
...Thus, to some extent sensorimotor internal models are thought to participate in sociocognitive processes, an idea captured by the notion of embodied cognition [126]....
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TL;DR: This Review looks at some key brain theories in the biological and physical sciences from the free-energy perspective, suggesting that several global brain theories might be unified within a free- energy framework.
Abstract: A free-energy principle has been proposed recently that accounts for action, perception and learning. This Review looks at some key brain theories in the biological (for example, neural Darwinism) and physical (for example, information theory and optimal control theory) sciences from the free-energy perspective. Crucially, one key theme runs through each of these theories — optimization. Furthermore, if we look closely at what is optimized, the same quantity keeps emerging, namely value (expected reward, expected utility) or its complement, surprise (prediction error, expected cost). This is the quantity that is optimized under the free-energy principle, which suggests that several global brain theories might be unified within a free-energy framework.
4,866 citations
"The Cerebellum: Adaptive Prediction..." refers background in this paper
...Of course, prediction is not unique to the cerebellum; indeed, all brain processing may entail some form of prediction [159]....
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TL;DR: For example, Frith as discussed by the authors showed that children with autism have a specific problem with theory-of-mind tasks, such as looking for the hidden chocolate in the cupboard.
3,256 citations
TL;DR: A detailed theory of cerebellar cortex is proposed whose consequence is that the cerebellum learns to perform motor skills and two forms of input—output relation are described, both consistent with the cortical theory.
Abstract: 1.
A detailed theory of cerebellar cortex is proposed whose consequence is that the cerebellum learns to perform motor skills. Two forms of input-output relation are described, both consistent with the cortical theory. One is suitable for learning movements (actions), and the other for learning to maintain posture and balance (maintenance reflexes).
2.
It is known that the cells of the inferior olive and the cerebellar Purkinje cells have a special one-to-one relationship induced by the climbing fibre input. For learning actions, it is assumed that:
(a)
each olivary cell responds to a cerebral instruction for an elemental movement. Any action has a defining representation in terms of elemental movements, and this representation has a neural expression as a sequence of firing patterns in the inferior olive; and
(b)
in the correct state of the nervous system, a Purkinje cell can initiate the elemental movement to which its corresponding olivary cell responds.
3.
Whenever an olivary cell fires, it sends an impulse (via the climbing fibre input) to its corresponding Purkinje cell. This Purkinje cell is also exposed (via the mossy fibre input) to information about the context in which its olivary cell fired; and it is shown how, during rehearsal of an action, each Purkinje cell can learn to recognize such contexts. Later, when the action has been learnt, occurrence of the context alone is enough to fire the Purkinje cell, which then causes the next elemental movement. The action thus progresses as it did during rehearsal.
4.
It is shown that an interpretation of cerebellar cortex as a structure which allows each Purkinje cell to learn a number of contexts is consistent both with the distributions of the various types of cell, and with their known excitatory or inhibitory natures. It is demonstrated that the mossy fibre-granule cell arrangement provides the required pattern discrimination capability.
5.
The following predictions are made.
(a)
The synapses from parallel fibres to Purkinje cells are facilitated by the conjunction of presynaptic and climbing fibre (or post-synaptic) activity. Reprinted with permission of The Physiological Society, Oxford, England.
(b)
No other cerebellar synapses are modifiable.
(c)
Golgi cells are driven by the greater of the inputs from their upper and lower dendritic fields.
6.
For learning maintenance reflexes, 2(a) and 2 (b) are replaced by 2’. Each olivary cell is stimulated by one or more receptors, all of whose activities are usually reduced by the results of stimulating the corresponding Purkinje cell.
7.
It is shown that if (2’) is satisfied, the circuit receptor → olivary cell → Purkinje cell → effector may be regarded as a stabilizing reflex circuit which is activated by learned mossy fibre inputs. This type of reflex has been called a learned conditional reflex, and it is shown how such reflexes can solve problems of maintaining posture and balance.
8.
5(a), and either (2) or (2’) are essential to the theory: 5(b) and 5(c) are not absolutely essential, and parts of the theory could survive the disproof of either.
3,151 citations
"The Cerebellum: Adaptive Prediction..." refers background in this paper
...Dating from influential theories by Marr and Albus [61, 62], experimental evidence has demonstrated that climbing fiber inputs from the inferior olive to the cerebellar cortex can result in long-term depression (LTD) of the parallel fiber synapses onto Purkinje cells [44]....
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...Dating from influential theories by Marr and Albus [61,62], experimental evidence has demonstrated that climbing fiber inputs from the inferior olive to the cerebellar cortex can result in long-term depression (LTD) of the parallel fiber synapses onto Purkinje cells [44]....
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