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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
DENTAL NEUROIMAGING Provides the latest neuroimaging-based evidence on the brain mechanisms of oral functions Dental Neuroimaging: The Role of the Brain in Oral Functions provides an up-to-date overview of neuroimaging research on the neural mechanisms underlying mastication, swallowing, sensory processing, and other oral topics. Divided into three parts, the book first introduces the theoretical framework of the brain-stomatognathic axis, clinical assessments for oral function, and neuroimaging methods. The second part presents recent neuroimaging findings of oral sensory and motor functions such as somatosensation, gustation, and orofacial pain and anxiety. The book concludes with a review of recent translational research and discussion of the application of neuroimaging in clinical management. Throughout the text, boxed sections highlight key information about cognitive neuroscience, imaging techniques, interpreting neuroimaging results, and relating research findings to clinical practice. * Covers specific clinical applications of dental neuroimaging in geriatric dentistry and in brain plasticity and adaptation * Summarizes classic research works in neuroscience and oral science * Discusses potential clinical applications of neuroimaging in dental practice * Features chapter summaries, further reading links, guided clinical scenarios, and numerous figures and tables Offering a systematic introduction to brain science and how it relates to dental medicine, Dental Neuroimaging: The Role of the Brain in Oral Functions is essential reading for students and researchers in disciplines such as neuroscience, neuroanatomy, oral physiology, dentistry and oral healthcare, speech therapy, and oral rehabilitation.
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Veröffentlichungsjahr: 2021
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Table of Contents
Cover
Title Page
Copyright Page
Dedication Page
List of Figures
List of Tables
List of Boxes
List of Abbreviations
Preface
Introduction to Students and Instructors
Acknowledgements
About the Companion Website
Part I: Methods of Neuroimaging and Assessment of Oral Functions
1 Introduction to Neuroimaging and the Brain–Stomatognathic Axis
1.1 Why Do Dentists Need to Understand the Brain?
1.2 What Is Neuroimaging?
1.3 How Does Neuroimaging Contribute to Clinical Practice?
1.4 The Brain–Stomatognathic Axis
References
2 Assessment of Human Brain Using MRI
2.1 Advantages and Limitations of Magnetic Resonance Imaging of the Brain
2.2 Research of Task‐based Functional Activation
2.3 Research of Structural Features of the Brain
2.4 Research of Brain Connectivity
References
3 Assessment of Oral Functions
3.1 Assessment of Masticatory and Swallowing Performance
3.2 Assessment of Orofacial Pain and Somatosensory Experience
3.3 Assessment of Cognitive Functions and Emotional Experience
References
Part II: Neuroimaging Research of Brain Mechanisms of Oral Functions
4 Brain Mechanisms of Oral Motor Functions
4.1 Introduction of Brain Mechanisms of Motor Control
4.2 Brain Mechanisms of Human Mastication
4.3 Brain Mechanisms of Human Swallowing
4.4 Cognitive Processing and Motor Learning of Oromotor Movement
References
5 Brain Mechanisms of Oral Sensory Functions
5.1 Brain Mechanisms of Oral Somatosensory Processing
5.2 Brain Mechanisms of Gustation
5.3 Cognitive–Affective Issues of Oral Sensory Functions
5.4 Brain Mechanisms of Multisensory Integration
References
6 Brain Mechanisms of Pain and Anxiety of Dental Patients
6.1 Brain Mechanisms Related to Pain
6.2 Chronic Pain, Neural Plasticity and Central Sensitization
6.3 Brain Mechanisms of Chronic Orofacial Pain
6.4 Brain Mechanisms of Dental Fear and Anxiety
References
Part III: Translational Research of Dental Neuroimaging
7 Age‐related Differences in the Brain–Stomatognathic Axis
7.1 Age‐related Differences in Brain Mechanisms
7.2 Age‐related Changes in Oral Sensorimotor Functions
7.3 Association Between the Brain and Oral Functions in Older People
7.4 Association Between Oral Conditions and Neurodegenerative Disorders
References
8 Brain Mechanisms of Adaptation of Oral Sensorimotor Functions
8.1 Brain Plasticity and Adaptation
8.2 Adaptation of Pain and Oral Sensory Functions
8.3 Functional Adaptation of Mastication and Swallowing
8.4 Brain Plasticity Associated with Oral Functional Training
References
9 A Synthesis Between Neuroimaging and Oral Healthcare
9.1 Assessment of Individual Differences in Brain–Stomatognathic Axis
9.2 Future Direction of Neuroimaging in Oral Neuroscience
References
Index
End User License Agreement
List of Tables
Chapter 1
Table 1.1 Trends of the academic publication
a
in dental research related to ...
Table 1.2 Selected findings (since 2010)
a
of neuroimaging research, which ar...
Table 1.3 Selected findings (since 2010) of brain imaging research related ...
Chapter 4
Table 4.1 Meta‐analyses of neuroimaging findings of the motor area (since 20...
Table 4.2 Neuroimaging research on the brain mechanisms of mastication (sinc...
Table 4.3 Neuroimaging research on brain mechanisms of swallowing (since 201...
Chapter 5
Table 5.1 Neuroimaging research on brain mechanisms of oral somatosensory pr...
Table 5.2 Neuroimaging research on brain mechanisms of taste or food stimuli...
Table 5.3 Neuroimaging research on brain mechanisms of oral multisensory pro...
Chapter 6
Table 6.1 Recent meta‐analytical findings on neuroimaging research on pain (...
Table 6.2 Neuroimaging research on brain mechanisms of central sensitization...
Table 6.3 Neuroimaging research on brain mechanisms of pain related to tempo...
Table 6.4 Neuroimaging research on brain mechanisms of pain related to trige...
Table 6.5 Neuroimaging research on brain mechanisms of burning mouth syndrom...
Table 6.6 Definition of fear, anxiety and phobia.
Table 6.7 Neuroimaging research on brain mechanisms of dental fear/anxiety.
Chapter 7
Table 7.1 Recent findings on age‐related changes in oral sensorimotor functi...
Table 7.2 Neuroimaging research on brain mechanisms of aging and oral functi...
Table 7.3 Neuroimaging research on brain mechanisms of oral functions and ne...
Chapter 8
Table 8.1 Neuroimaging research on brain mechanisms of brain plasticity and ...
Table 8.2 Neuroimaging research on brain mechanisms of training/intervention...
Chapter 9
Table 9.1 Proposed components of the brain–stomatognathic integrative assess...
Table 9.2 Recent findings on neuroimaging research on oral functions based o...
List of Illustrations
Chapter 1
Figure 1.1 The association between the brain and the stomatognathic system. ...
Figure 1.2 A general view of the neural circuitries of the brain mechanisms ...
Figure 1.3 Theoretical frameworks of the association between the brain, oral...
Chapter 2
Figure 2.1 The general concept of the blood‐oxygen‐level‐dependent (BOLD) me...
Figure 2.2 Examples of functional magnetic resonance imaging (fMRI) investig...
Figure 2.3 Methodological considerations of a functional magnetic resonance ...
Figure 2.4 Statistical analysis at the individual level and the group level....
Figure 2.5 Experimental design of functional neuroimaging research. (a) Unde...
Figure 2.6 Conceptual differences between functional specialization, functio...
Figure 2.7 Analysis of resting‐state functional connectivity. (a) The sponta...
Figure 2.8 Analysis of structural connectivity. (a) In deterministic tractog...
Figure 2.9 Graph‐based analysis of brain connectivity. (a) The pattern of fu...
Chapter 3
Figure 3.1 Methods of the assessment of oral cutting ability. (a) The sievin...
Figure 3.2 Methods of the assessment of oral mixing ability. (a) In the two‐...
Figure 3.3 Experimental design of pain/somatosensory experience. (a) Blood‐o...
Chapter 4
Figure 4.1 An overview of brain regions associated with motor control. The f...
Figure 4.2 Sensorimotor control of the basal ganglia and the cerebellum. (a)...
Figure 4.3 Experimental design for neuroimaging of the brain mechanisms of c...
Figure 4.4 Brain activation associated with chewing and clenching.
Figure 4.5 Experimental design for neuroimaging of the brain mechanisms of s...
Figure 4.6 Brain activation associated with water (the upper panel) and sali...
Chapter 5
Figure 5.1 Processing of oral somatosensory information. Information from in...
Figure 5.2 Experimental methods of investigating oral mechanoreceptors. (a) ...
Figure 5.3 Brain activation associated with gustation at the insula. A consi...
Figure 5.4 Basic concepts of perceptual processing. (a) Top‐down processing ...
Figure 5.5 Experimental design of manipulating threat value associated with ...
Chapter 6
Figure 6.1 Brain activation associated with pain processing. (a) The brain r...
Figure 6.2 Functional networks associated with chronic pain.
Figure 6.3 Mechanisms of peripheral and central sensitization. (a) In the no...
Figure 6.4 Brain features associated with chronic orofacial pain. (a) Brain ...
Chapter 7
Figure 7.1 Conceptual links between oral health and cognitive functions. (a)...
Chapter 8
Figure 8.1 The concept of neuroplasticity and functional adaptation. (a) Wit...
Figure 8.2 Experimental design of neuroimaging research on brain plasticity....
Chapter 9
Figure 9.1 Major aims of brain–stomatognathic integrative assessment (BSIA)....
Figure 9.2 Key elements for implementing the brain–stomatognathic integrativ...
Figure 9.3 An example of neuroimaging investigation combined with animal res...
Guide
Cover Page
Title Page
Copyright Page
Dedication Page
List of Figures
List of Tables
List of Boxes
List of Abbreviations
Preface
Introduction to Students and Instructors
Acknowledgements
About the Companion Website
Table of Contents
Begin Reading
Index
Wiley End User License Agreement
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Dental Neuroimaging
The Role of the Brain in Oral Functions
Chia‐Shu Lin
Department of Dentistry
National Yang Ming Chiao Tung University
Taipei, Taiwan, Republic of China
This edition first published in 2022© 2022 John Wiley & Sons Ltd
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Library of Congress Cataloging‐in‐Publication Data
Names: Lin, Chia‐Shu, 1976– author.Title: Dental neuroimaging : the role of the brain in oral functions / Chia‐Shu Lin.Description: Hoboken, NJ : Wiley‐Blackwell, 2022. | Includes bibliographical references and index.Identifiers: LCCN 2021047940 (print) | LCCN 2021047941 (ebook) | ISBN 9781119724209 (paperback) | ISBN 9781119724254 (Adobe PDF) | ISBN 9781119724230 (epub)Subjects: MESH: Stomatognathic System–diagnostic imaging | Neuroimaging–methods | Brain Mapping–methodsClassification: LCC RK308 (print) | LCC RK308 (ebook) | NLM WU 102 | DDC 617.5/22–dc23LC record available at https://lccn.loc.gov/2021047940LC ebook record available at https://lccn.loc.gov/2021047941
Cover Design: WileyCover Images: Courtesy of Chia‐Shu Lin; © KJ_Photography/Shutterstock
This book is dedicated to my parents, for their love and caring, my wife, I‐ting, and our children, Yuan‐han and Yi‐hsien, who are my inspiration.
List of Figures
1.1
The association between the brain and the stomatognathic system. The traditional perspective highlights the brain as a ‘systemic factor’ associated with oral health, just like the factors related to other body systems. The functional perspective highlights that the brain and mental functions guided by the brain play an essential role in stomatognathic functions.
1.2
A general view of the neural circuitries of the brain mechanisms of orofacial functions. The circuitries between the central and peripheral sites (i.e. pathways labelled in blue and red) are investigated primarily via animal models. Notably, the circuitries within the brain (i.e. the intracortical pathways labelled in black) have not been fully elucidated.
Source:
Avivi-Arber and Sessle (2018).Reproduced with permission of John Wiley and Sons.
1.3
Theoretical frameworks of the association between the brain, oral functions and behaviour. (a) The oral-to-behaviour (OB) framework, (b) the oral-brain-behaviour (OBB) framework and (c) the brain–stomatognathic axis (BSA).
2.1
The general concept of the blood-oxygen-level-dependent (BOLD) mechanism. (a) Transportation of oxygenated haemoglobin during a resting condition, when neural activity is low. (b) Transportation of oxygenated haemoglobin when neural activity increases. The neurons demand more energy by consuming oxygen provided by oxygenated haemoglobin. Via a complex haemodynamic process (e.g. an increasing rate and volume of cerebral flow), the amount of oxygenated haemoglobin increases (relatively to the amount of deoxygenated haemoglobin), leading to an over-supply or compensation of the oxygen demand from neurons.
2.2
Examples of functional magnetic resonance imaging (fMRI) investigation of chewing movement. (a) The first-level analysis. In a chewing experiment, the task conditions (i.e. when subjects are chewing) are contrasted to the baseline conditions (i.e. when subjects are resting). Brain activation reflects the difference in blood-oxygen-level-dependent (BOLD) signals in the task vs. the baseline condition. The first-level analysis focuses on the pattern of brain activation at the individual subject. (b) The second-level analysis. The second-level analysis focuses on the association between brain activation and individual variability. The association can be explored by investigating the correlation between brain activation and individual performance or comparing brain activation between different clinical groups.
2.3
Methodological considerations of a functional magnetic resonance imaging study. (a) Subjects may show great inter-individual variability in their general conditions, such as sex, age and general physical/psychological conditions. (b) Subjects may show great inter-individual variability in their personal trait and performance (e.g. pain ratings) related to an experimental task. (c) Subjects differ in brain morphology. When individual brains are compared, the individual images are normalized to a template image, using linear transformation (i.e. translation, rotation, resizing and shearing) and nonlinear transformation approaches.
2.4
Statistical analysis at the individual level and the group level. (a) The analysis at the individual level focuses on the association between task progression and the blood-oxygen-level-dependent (BOLD) time series, as shown in the left panel. For each voxel, a strong association indicates that the BOLD signals of the voxel can be predicted by the task condition, in contrast to the baseline condition (e.g. Voxel A), as shown in the right panel. (b) The analysis at the group level focuses on the association between brain features (e.g. brain activation of grey matter volume) and group factors. The association may reflect the difference in brain features between patient and control groups (the left panel) or the correlation between brain features and clinical factors (the right panel). (c) A typical image result consists of the statistical values (e.g. the t-score) from multiple voxels (represented as the grid), which are visualized by a colour scale, as shown in the left panel. The result can be thresholded according to intensity (i.e. the t-score). For example, only the voxels with a t-score >6 are preserved after thresholding, as shown in the middle panel. The result can be thresholded according to the size of a cluster of voxels. For example, only the clusters with a size larger than 100 voxels will be preserved after thresholding, as shown in the right panel.
2.5
Experimental design of functional neuroimaging research. (a) Under the assumption of pure insertion, the difference of brain activation between two experimental conditions only reflects the mental function contrasted by the conditions (e.g. perception of pain intensity). However, the contrast may be associated with more than one mental function (e.g. perception of pain intensity and attention to noxious stimuli). (b) A factorial design helps to delineate the association between two mental functions. For example, the light grey area denotes the effect of increased pain on brain activation, and the dark grey area denotes the effect of increased attention. (c) A conjunction design focuses on the pattern of brain activation common to two experimental conditions (e.g. a clenching task and a chewing task). The activation may reflect the brain mechanisms of a mental function common to both task conditions.
2.6
Conceptual differences between functional specialization, functional segregation and functional integration. (a) Functional specialization highlights the association between a brain region and a specific mental function. For example, activation at the occipital lobe is considered mainly for the processing of visual perception. (b) Functional segregation highlights that a mental function is associated with multiple brain regions that are functionally connected within a module. For example, visual cognition is associated with the module consisting of the yellow regions, and motor control is associated with the module consisting of the blue regions. (c) Functional integration highlights the pattern of global communication between multiple brain regions. For example, individual variability in mental functions may be associated with the efficiency of how information is distributed in a network.
2.7
Analysis of resting-state functional connectivity. (a) The spontaneous blood-oxygen-level-dependent (BOLD) activity is acquired using resting-state functional magnetic resonance imaging. Subjects fix their eyesight on a crosshair without additional external stimuli. (b) Brain images are segmented into multiple regions according to a brain atlas. (c) To each brain region, the mean BOLD time series is extracted by averaging the time series from all the voxels within a region. (d) Association between the regional time series is quantified with correlation coefficients. (e) The correlation coefficient represents the strength of the connection between each pair of brain regions. (f) In the seed-based approach, a brain region of interest (i.e. the ‘seed’ region) is pre-selected. Functional connectivity is calculated between the seed region and all the other voxels to explore the brain regions that have a strong connection with the seed region.
2.8
Analysis of structural connectivity. (a) In deterministic tractography, each voxel is assigned with a single direction, which reflects the principal direction of diffusivity. A continuous streamline is formed by tracking the direction of voxels. (b) Probabilistic tractography assumes that there exists an uncertainty of the direction within each voxel. In the right panel, the probabilistic distribution of the directions is estimated for each voxel. A higher probability of a ‘leftward’ direction can be identified. In the right panel, the intensity of a voxel represents the frequency that a streamline passes that voxel. For example, more streamlines pass the yellow voxel (here four out of seven streamlines) compared to the red voxel (here one out of seven streamlines). (c) Structural covariance quantifies the strength of association of a brain feature between different brain regions across subjects. For example, the cortical thickness of six brain regions is assessed for eight subjects. The right panel reveals the association between regions 2 and 6, as quantified by the correlation coefficient of the cortical thickness between the regions.
2.9
Graph-based analysis of brain connectivity. (a) The pattern of functional and structural connections between brain regions can be translated from the ‘brain space’ to the ‘network space’ with applications of graph theory. In a graph, the nodes represent brain regions and the links represent the functional and structural connectivity between regions, which can be quantified by the correlation coefficient between blood-oxygen-level-dependent (BOLD) time series and the streamlines identified by tractography, respectively. (b) In the network analysis, the global metrics quantify the degree of integration of a network. For example, characteristic path length can be calculated by finding the shortest path length between a pair of nodes, such as the path A–B–D (but not A–B–E–D) between the nodes A and D. (c) The local metrics quantify the degree of segregation of a network. For example, the clustering coefficient is used to quantify the fraction of the triangular architecture in the whole network (e.g. A–B–C and E–G–H), which represents a pattern of clustered nodes. Notably, a small-world network offers a balance between the efficiency of global and local communication. A highly regular network (i.e. the middle-right panel) and a highly random network (i.e. the middle-left panel) may suffer from a lower global and local efficiency, respectively.
3.1
Methods of the assessment of oral cutting ability. (a) The sieving method quantifies the proportion of the chewed food (e.g. peanuts) with different particle sizes, using multiple sieves with different pore sizes (e.g. from the diameter of 355–3500 µm). The total weight of food particles that pass through a sieve is plotted against the pore size of the sieve. A smaller median particle size (e.g. the grey curve) represents better performance in cutting.
Source:
Chia-Shu Lin. (b) A test gummy jelly is customized with a standardized size and shape. The chewed fragments are collected and photographed. Colour and morphological features (e.g. the area and perimeter) of each fragment, which reflect individual cutting ability, are assessed by analyzing the image.
Source:
Salazar et al. (2020). Reproduced with permission of Elsevier.
3.2
Methods of the assessment of oral mixing ability. (a) In the two-colour chewing gum test, the degree of mixing food can be assessed by the colour hue of chewing gum with different colours. For example, if a piece of red and a piece of yellow gums are well mixed, the resulting bolus would in orange homogenously. The hue of the bolus can be quantified by imaging analysis. A smaller standard deviation of hue represents a greater homogeneity of colour mixing, i.e. a better mixing ability. (b) The degree of mixing is assessed according to the pattern of spatial clusters. A piece of juice chew with red and white portions was chewed by a subject for 20 strokes and collected, as shown in the left panel. The degree of clustering is assessed based on the analysis of variogram, which reflects how fine the clusters of different colours are. A pattern with finer clusters (e.g. the case in the lower-right panel) reflects better mixing ability.
Source:
Lo et al. (2020). Reproduced with permission of John Wiley and Sons.
3.3
Experimental design of pain/somatosensory experience. (a) Blood-oxygen-level-dependent (BOLD) signals are recorded concurrently with discrete ratings of stimulation. In this design, noxious stimuli with high and low intensities are followed by a rating phase (‘?’), which requires subjects to rate the pain intensity they perceive for the stimuli. Brain activation associated with pain can be contrasted by the phases that subjects feel strong vs. mild pain, according to their ratings (i.e. the black bars). (b) BOLD signals are recorded concurrently with continuous ratings of spontaneous pain. Patients with chronic pain continuously rate their pain, which may increase spontaneously. (c) Brain features and ratings are recorded separately. In this design, the rating of pain or somatosensory experience is conducted outside a scanner. Association between the individual ratings (e.g. pain) and their brain features (e.g. grey matter volume of the insula), which are collected separately, can be investigated by correlational analysis.
4.1
An overview of brain regions associated with motor control. The figure only displays the relative position and size of the brain regions, not depicting the anatomical details.
4.2
Sensorimotor control of the basal ganglia and the cerebellum. (a) The basal ganglia consist of a direct and an indirect pathway of motor control. In both pathways, the striatum is activated by the cortex, which forms a loop of control with the thalamus (the grey arrow). In the direct pathway (the solid black arrow), the activation of the striatum inhibits the activity of the internal segment of the globus pallidus (GPi) and the substantia nigra (SNr), which further inhibits thalamic functions. Therefore, cortical activation is associated with an increased thalamic activity via the direct pathway. In the indirect pathway (the black dashed line), the activation of the striatum inhibits the activity of the external segment of the globus pallidus (GPe), which further inhibits the activity of the subthalamic nucleus (STN). Notably, the activity of the STN further activates GPi/SNr, which decreases thalamic activity. Therefore, cortical activation is associated with a decrease in thalamic activity via the indirect pathway. (b) The cerebellum plays a key role as an internal model of motor learning. A forward model predicts the sensory outcomes when motor commands are executed. It adjusts sensorimotor processing via feedback of the predicted sensory outcomes. An inverse model calculates the motor commands that would produce the sensory outcomes from desired actions. According to Wolpert et al. (2001), both models are crucial to motor control.
4.3
Experimental design for neuroimaging of the brain mechanisms of chewing. (a) The basic concept of study design. The study consists of multiple blocks of a chewing task and a baseline (no-chewing) block. (b) Variations of the study design. Different studies may differ in the number of blocks of tasks and the definition of the baseline block (e.g. resting or clenching the teeth). The variations lead to a different interpretation of imaging results.
4.4
Brain activation associated with chewing and clenching.
Source:
Lin (2018). Reproduced with permission of John Wiley and Sons.
4.5
Experimental design for neuroimaging of the brain mechanisms of swallowing. (a) Study design of the swallowing tasks, including the water swallowing task and the saliva swallowing task. (b) Examples of the study design for investigating brain mechanisms of swallowing. An overt swallowing task (with either water or saliva swallowing) is associated with the execution of swallowing movement. A covert swallowing task is associated with the motor planning of swallowing.
4.6
Brain activation associated with water (the upper panel) and saliva (the lower panel) swallowing.
Source:
Sörös et al. (2009). Reproduced with permission of John Wiley & Sons, Inc.
5.1
Processing of oral somatosensory information. Information from individual sensory modalities is transduced via peripheral receptors at the level of somatosensation and integrated to form a holistic perceptual experience (e.g. oral stereognosis) at the level of somatoperception. Information is further integrated, with knowledge and affective–motivational experience, to form a feeling of intraoral condition at the level of somatorepresentation.
5.2
Experimental methods of investigating oral mechanoreceptors. (a) Recording signals from periodontal mechanoreceptors.
Source:
Trulsson (2006). Reproduced with permission of John Wiley and Sons. (b) The food splitting task.
Source:
Grigoriadis et al. (2017) with permission of Springer Nature under the terms of the Creative Commons CC BY 4.0 License.
5.3
Brain activation associated with gustation at the insula. A consistent pattern of brain activation is identified in the insular cortex for studies focusing on the quality, intensity and affective value of taste stimuli, respectively.
Source:
Yeung et al. (2018). Reproduced with permission of Elsevier.
5.4
Basic concepts of perceptual processing. (a) Top-down processing highlights the neural processing of intrinsic (personal) factors, such as one’s goal planning, on the formation of perceptual experience. The bottom-up processing highlights the neural processing of extrinsic (environmental) factors, such as the physical features of stimuli, on the formation of perceptual experience. (b) In predictive coding, the sensory inputs that we receive from the real world are compared with our prediction of the sensory outcomes. A mismatch (i.e. ‘prediction error‘) occurs when our prediction does not fit the outcome we perceive. The prediction error is associated with attentional bias and learning. For example, we may pay more attention to an unexpected event compared to an expected one.
5.5
Experimental design of manipulating threat value associated with pain. (a) The presence of noxious stimuli is associated with visual cues, which predict low-intensity stimuli (i.e. the square) constantly or predict high-or low-intensity stimuli (i.e. the circle). The latter evokes higher anxiety related to pain due to the increased uncertainty (i.e. the stimulus intensity is less predictable). Moreover, the same low-intensity stimuli would be perceived as more painful in the high-uncertainty condition (i.e. the condition predicted by a circle). (b) The threat value of pain is associated with the severity of noxious stimuli. Subjects receive different instructions regarding the severity (e.g. may cause tissue damage or not) of noxious stimuli, which are delivered at different sites (grey and black). The detection threshold of pain, i.e. the intensity that subjects feel painful and non-painful for equal times, is determined. When subjects feel a stronger severity of the stimuli (i.e. feeling more threatened), they would report higher anxiety towards the stimuli. Moreover, the same stimuli (tuned at the detection threshold) would be perceived as painful more likely in the more threatening condition (i.e. the condition with more severity) compared to the condition they regard as less threatening.
6.1
Brain activation associated with pain processing. (a) The brain regions commonly reported in functional magnetic resonance imaging (fMRI) studies of noxious stimuli. The figure only displays the relative position and size of the brain regions, not depicting the anatomical details. Note that the insular cortex (bounded by a dashed line) is covered by the frontal, parietal and temporal operculum. (b) Metaanalytical findings of the brain activation of experimental orofacial pain in healthy subjects. Increased activation is consistently found in the posterior mid-cingulate cortex (pMCC), the PPC, the insula, the thalamus, the S1 and the S2. Decreased activation is consistently found in the primary motor cortex (M1) and the S1.
Source:
Ayoub et al. (2018). Reproduced with permission of Elsevier.
6.2
Functional networks associated with chronic pain.
Source:
Davis et al. (2017) with permission of Springer Nature under the terms of the Creative Commons CC BY 4.0 License.
6.3
Mechanisms of peripheral and central sensitization. (a) In the normal status, signals induced by noxious stimuli and non-noxious (e.g. tactile) stimuli are transduced via the pathway of nociceptive and tactile processing, respectively. (b) In peripheral sensitization, neurons would show increased responsiveness to noxious stimuli. For example, the inflammation at the peripheral site (i.e. the light red area) may reduce the threshold to evoke a response. The signals for subsequent nociceptive processing are amplified. Therefore, peripheral sensitization may be associated with hyperalgesia. (c) In secondary hyperalgesia (in contrast to primary hyperalgesia (b)), noxious stimulation to the area surrounding the site of injury or inflammation (i.e. the black arrow) elicits an amplified pain. The amplification is mediated by the central neurons (i.e. the red circle), which have been sensitized by constantly receiving nociceptive inputs from the primary lesion (i.e. the circled light grey area). (d) In allodynia, non-noxious tactile stimuli are conveyed by the Aβ fibre elicit pain. Note that at the central level, both the nociceptive and tactile pathways converge on central nociceptive neurons. The central neurons (the red square) have been sensitized by constantly receiving nociceptive inputs from the primary lesion.
6.4
Brain features associated with chronic orofacial pain. (a) Brain activation associated with chronic orofacial pain. Meta-analytical findings reveal a consistent pattern of higher brain activation in the left medial and posterior thalamus and lower brain activation in the left posterior insula in patients with chronic orofacial pain (COFP) compared to healthy controls.
Source:
Ayoub et al. (2018). Reproduced with permission of Elsevier. (b) Functional connectivity of patients with temporomandibular disorder (TMD)-related pain. The left panel reveals that TMD patients showed enhanced functional connectivity (FC) between the medial prefrontal cortex (mPFC) and the posterior cingulate cortex (PCC)/precuneus (PCu)/retrosplenial cortex (RSC) compared to healthy controls. The right panel reveals that functional connectivity between the mPFC and medial thalamus/PAG was positively correlated with pain rumination in TMD patients. Source (insets): Kucyi et al. (2014), p.3969–3975 with permission of the Society for Neuroscience under the terms of the Creative Commons Attribution 4.0 International License.
7.1
Conceptual links between oral health and cognitive functions. (a) The framework of the brain–stomatognathic axis (BSA). The framework highlights that the brain plays a key role in behavioural adaptation in feeding and oral care behaviour, which further relates to oral health. (b) The potential role of the brain in behavioural adaptation. Poor oral health may be attributed to increasing difficulty in conducting health-related behaviour (e.g. being unable to brush teeth), which is derived from neurodegenerative disorders. (c) The potential role of oral factors in brain pathologies. The ‘oral-on-brain effect’ may be associated with multiple factors, such as reduced sensory feedback from the loss of occlusal contact or increased periodontal inflammation/infection. Notably, when the brain is affected by poor oral health, it may be followed by worse adaptation of feeding and oral care behaviour, which furthers exacerbates one’s oral health. (d) The potential role of a common factor that affects both cognitive and oral functions. For example, aging is associated with structural and functional alterations of the cerebellum, which relates to not only oral sensorimotor functions but also cognition. The arrow filled with a slash pattern denotes the potential causal links of the framework.
8.1
The concept of neuroplasticity and functional adaptation. (a) With a ‘preprogrammed’ nervous system, our behaviours responding to environmental stimuli are determined by a fixed set of stimulus–response links. For example, a great danger will elicit a stronger emotional response compared to a mild danger (the upper panel). However, our nervous system is modifiable and can be tuned according to environmental changes. Long-term experience may sculpt the brain at the structural and functional levels, leading to different behaviours responding to environmental stimuli. For example, past experience may predispose the brain to be more sensitive to danger and make a stronger emotional response (the lower panel). (b) Functional adaptation is associated with the improvement of one’s functional performance under environmental challenges. For example, individuals learn to run faster (i.e. increased performance) when they are threatened by a greater danger (the upper panel). Compensation, in contrast, highlights the restoration of performance from a worse status back to a normal status. For example, individuals with a disability can run as quickly as normal individuals when facing danger by compensating their mobility with the help from tools and rehabilitative therapy (the lower panel).
8.2
Experimental design of neuroimaging research on brain plasticity. (a) A cross-sectional study reveals a significant difference in structural brain features between subjects with and without a professional skill (e.g. driving). Individual variations in brain features further relate to the duration of skill training (the left panel). Results from the cross-sectional design only suggest, but not confirm, the causal direction of a plastic effect. The difference in brain features (as observed by neuroimaging) may be attributed to prior experience of training (the middle panel). However, it is also possible that the individual differences in the brain features predispose their performance of a skill (the right panel). (b) To better elucidate the plastic effect of training, a longitudinal design is used to assess the performance and brain features at different stages of training. Importantly, one can assess whether the plastic effect, i.e. changes in brain features during the training session, can last for a period or vanish right after the termination of training. (c) The same longitudinal design also helps to elucidate individual differences in their performance. For example, the variation in brain features may account for the difference in learning speed.
9.1
Major aims of brain–stomatognathic integrative assessment (BSIA). (a) Prediction of long-term changes in oral functions. Individual differences in brain reserve and cognitive reserve may play a key role in their susceptibility to diseases. The BSIA, which includes the assessment of cognitive functions of older people, would help to predict the future condition of individual oral health. (b) Classification of patients with different risks of oral diseases. The BSIA helps to classify the patients for their risk of oral diseases and the prognosis of treatment, based on a full-scale assessment of general physical and mental status.
9.2
Key elements for implementing the brain–stomatognathic integrative assessment. (a) The multidisciplinary investigation can be undertaken in a hospital, where different departments are in charge of different assessments. Critically, the results of an assessment from one discipline (e.g. the score of cognitive tests from neurologists) are distributed for the use of other disciplines (e.g. dentistry). For example, the cognitive performance of older patients, as assessed by neurologists, is available for prosthodontists to evaluate if patients can adapt well to their new dentures. (b) In contrast to the hospital setting, a home-based assessment can be facilitated by the use of teledentistry approaches and digital technology. For example, in long-term care institutes or at home, patients can record their own oral status by photographing (via a smartphone). The image record may include a photo about their intraoral conditions (e.g. bleeding gum) or performance of oral functions (e.g. the food bolus after chewing). The images are sent to the cloud storage service for further analysis. A preliminary assessment is performed automatically by machine-learning-based algorithms, and critical problems (e.g. a poor oral mixing ability) are screened and forwarded to dental professionals for further evaluation.
9.3
An example of neuroimaging investigation combined with animal research. Using structural MRI, Avivi-Arber et al. (2017) compared the post-mortem brain volume between the mice that received molar extraction and those who received sham operation. Tooth extraction was associated with a widespread reduction in volumes of brain regions of sensorimotor and cognitive–affective processing.
Source:
Avivi-Arber et al. (2017) with permission of Frontiers Media S.A. under the terms of the Creative Commons Attribution 4.0 License.
List of Tables
1.1
Trends of the academic publication in dental research related to brain and neuroimaging.
1.2
Selected findings (since 2010) of neuroimaging research, which are related to the issues of the ‘landmark discoveries or concepts’ of oral neuroscience (Iwata and Sessle 2019), as quoted in field (A) to (G).
1.3
Selected findings (since 2010) of brain imaging research related to the clinical disciplines of dentistry.
4.1
Meta-analyses of neuroimaging findings of the motor area (since 2015).
4.2
Neuroimaging research on the brain mechanisms of mastication (since 2015).
4.3
Neuroimaging research on brain mechanisms of swallowing (since 2015).
5.1
Neuroimaging research on brain mechanisms of oral somatosensory processing (since 2015).
5.2
Neuroimaging research on brain mechanisms of taste or food stimuli (since 2015).
5.3
Neuroimaging research on brain mechanisms of oral multisensory processing.
6.1
Recent meta-analytical findings on neuroimaging research on pain (since 2015).
6.2
Neuroimaging research on brain mechanisms of central sensitization and pain (since 2015).
6.3
Neuroimaging research on brain mechanisms of pain related to temporomandibular disorders (since 2015).
6.4
Neuroimaging research on brain mechanisms of pain related to trigeminal neuralgia and painful neuropathy (since 2015).
6.5
Neuroimaging research on brain mechanisms of burning mouth syndrome (since 2015).
6.6
Definition of fear, anxiety and phobia.
6.7
Neuroimaging research on brain mechanisms of dental fear/anxiety.
7.1
Recent findings on age-related changes in oral sensorimotor functions (since 2015).
7.2
Neuroimaging research on brain mechanisms of aging and oral functions (since 2015).
7.3
Neuroimaging research on brain mechanisms of oral functions and neurodegenerative disorders (since 2010), see also Table 7.2.
8.1
Neuroimaging research on brain mechanisms of brain plasticity and oral functions (since 2010).
8.2
Neuroimaging research on brain mechanisms of training/intervention to improve swallowing (since 2015).
9.1
Proposed components of the brain–stomatognathic integrative assessment (BSIA).
9.2
Recent findings on neuroimaging research on oral functions based on animal models (since 2015).
List of Boxes
2.1
From the Brain to Behaviour – It Is All about the Energy!
2.2
From Tools to Discovery – Basic Skills about Reading Neuroimaging Data
2.3
From Tools to Discovery – Key Concepts in the Processing of Imaging Data
2.4
From Tools to Discovery – Brain Mapping and the Use of the Brain Atlas
2.5
From Research to Practice – There Is Something More Important Than an ‘Image’ for Neuroimaging
3.1
From the Brain to Behaviour – Brain Mechanisms of Rating One’s Feeling
4.1
From Tools to Discovery – Meta-analysis of Neuroimaging Findings
4.2
From Research to Practice – Better Brain, Better Chewing?
4.3
From Tools to Discovery – How to Draw a Conclusion From a Neuroimaging Study
5.1
From Research to Practice – Why Is Orofacial Apparatus So Sensitive?
6.1
From Research to Practice – Revision of the Definition of Chronic Pain by Neuroimaging Evidence
7.1
From the Brain to Behaviour – Sensorimotor Adaptation
7.2
From the Brain to Behaviour – Executive Function of the Brain
List of Abbreviations
ACC
anterior cingulate cortex
AD
axial diffusivity
ALE
activation likelihood estimation
ASL
arterial spin labelling
AzD
Alzheimer’s disease
BG
basal ganglia
BMS
burning mouth syndrome
BOLD
blood‐oxygen‐level‐dependent
CD
complete denture
CMA
cortical masticatory area
CNS
central nervous system
CPGs
central pattern generators
CSF
cerebrospinal fluid
CT
computed tomography
DMN
default mode network
dMRI
diffusion magnetic resonance imaging
DTI
diffusion tensor imaging
EEG
electroencephalography
EMG
electromyography
ERP
event‐related potential
FA
fractional anisotropy
fMRI
functional magnetic resonance imaging
fNIRS
functional near‐infrared spectroscopy
IOD
implant‐supported denture
M1
primary motor cortex
MBF
maximal biting force
MCI
mild cognitive impairment
MD
mean diffusivity
MEG
magnetoencephalography
MP
masticatory performance
mPFC
medial prefrontal cortex
MRI
magnetic resonance imaging
MRS
magnetic resonance spectroscopy
MTP
maximal tongue pressure
MVPA
multivariate pattern analysis
NAc
nucleus accumbens
NRS
numerical rating scale
OFC
orbitofrontal cortex
PAG
periaqueductal grey
PD
Parkinson's disease
PET
positron emission tomography
PFC
prefrontal cortex
PMC
premotor cortex
QST
quantitative sensory testing
RD
radial diffusivity
rs‐fMRI
resting‐state functional magnetic resonance imaging
rTMS
repetitive transcranial magnetic stimulation
S1
primary somatosensory cortex
S2
secondary somatosensory cortex
SFR
salivary flow rate
SMA
supplementary motor area
sMRI
structural magnetic resonance imaging
SPECT
single photon emission computed tomography
TDCS
transcranial direct current stimulation
TMD
temporomandibular disorders
TMS
transcranial magnetic stimulation
TN
trigeminal neuralgia
TNP
trigeminal neuropathic pain
VAS
visual analogue scale
VBM
voxel‐based morphometry
VDS
verbal descriptor scale
Preface
About 20 years ago when I just finished my DDS programme, new frontiers were rapidly expanding in dentistry and brain science. Dentistry was markedly revolutionized by innovations in biological, material and digital technology. Brain science, with the use of non‐invasive neuroimaging approaches, has risen as a mainstream field in clinical science. At the beginning of the twenty‐first century, we have witnessed the advancement of neuroimaging in various health‐related fields, such as neurodegenerative disorders and psychiatric diseases. In contrast, our knowledge of the stomatognathic system is largely based on animal and clinical research, and the brain's role in oral functions has not been fully elucidated. During my college days, the topic of the human brain and mental functions has been rarely discussed in dental textbooks.
This book responds to the evolution of using neuroimaging approaches to investigate the human brain and oral functions, which has been lasting for decades and become gradually popular in recent years. As a relatively uncharted field, ‘dental neuroimaging’ is not merely an adoption of a new method in dental research. It also focuses on the cross‐disciplinary investigation about the connection between the brain, the stomatognathic system and oral health‐related behaviour. As shown in the book, neuroimaging studies have provided many insights on the mechanisms of oral diseases, such as chronic orofacial pain and swallowing and masticatory dysfunctions. Moreover, as I have emphasized in this book, the knowledge from neuroimaging research also contributes to translational application in clinical management, such as the management of geriatric and special needs patients.
Undeniably, a single book will not cover all the progress of neuroimaging research related to oral health. The book focuses on the future directions and challenges of dental neuroimaging research rather than merely a conclusion of past knowledge about the brain and oral functions. In this book, while the key results from classic research works are summarized, more emphasis is put on recent findings and the current trend in neuroimaging research of oral topics.
As an investigator who is lucky enough to witness the rise of this cross‐disciplinary field, I hope you enjoy this book and that you would appreciate how neuroimaging helps to unravel the mysterious connection between the brain and oral functions.
Introduction to Students and Instructors
This book consists of nine inter‐related chapters, which are organized into three parts. Part I Methods of Neuroimaging and Assessment of Oral Functions focuses on the methodological issues of the research of the association between the human brain and the stomatognathic functions, which covers an introduction to theoretical frameworks of the brain–stomatognathic connection (Chapter 1), an introduction to neuroimaging methods, with a focus on magnetic resonance imaging (Chapter 2), and an introduction to clinical assessments of oral functions (Chapter 3).
Part II Neuroimaging Research of Brain Mechanisms of Oral Functions focuses on recent neuroimaging findings of oral sensory and motor functions, including the brain mechanisms of oral motor functions (e.g. mastication and swallowing) (Chapter 4), oral sensory functions (e.g. somatosensation and gustation) (Chapter 5) and orofacial pain and anxiety (Chapter 6).
Finally, in Part III Translational Research of Dental Neuroimaging, the issues related to clinical applications of dental neuroimaging are reviewed, including the association between ageing and oral function (Chapter 7), the brain mechanisms of the plasticity and adaptation of oral functions (Chapter 8) and future directions about the translation application of neuroimaging in clinical management (Chapter 9).
To readers who explore the field of brain imaging for the first time, key information regarding imaging and brain science can be found in the following supplementary materials.
From the Brain to Behaviour
: These text boxes provide further information regarding the basic information in cognitive neuroscience.
From Research to Practice
: These text boxes provide suggestions about how to properly interpret a neuroimaging finding and how the findings are related to clinical questions.
From Tools to Discovery
: These online materials include video courses that demonstrate how to use basic research tools in neuroimaging.
Further correspondence from students, faculty and clinicians is welcome.
Please send the message toChia‐Shu Lin; e‐mail: [email protected].
Acknowledgements
Writing this book echoes my career as a neuroscientist and a dentist. I am grateful to Dr Shin‐Fang Yang and Dr. Mei‐Yu Chen, who showed me the road of being a scientist, Dr Irene Tracey and Dr Katja Wiech, who introduced functional neuroimaging to me during my DPhil study at the University of Oxford, and Dr Jen‐Chuen Hsieh, who inspired me with many insights on brain science during my postdoctoral research at Taipei Veterans General Hospital.
My exploration in dental neuroimaging, a new frontier in dentistry, is greatly benefited from the discussion with my colleagues from dental research: Dr Ming‐Lun Hsu, Dr Shyh‐Yuan Lee, Dr Kuo‐Wei Chang and Dr Ching‐Yi Wu, and colleagues in from brain research: Dr David Niddam and Dr Li‐Fen Chen, at National Yang Ming Chiao Tung University. The exploration cannot go further without the professional support from the 3T MRI Core Facility at National Yang Ming Chiao Tung University.
I am grateful to the managers and editors from Wiley Publishing: Associate Commissioning Editor Loan Nguyen, Managing Editor Tanya McMullin, Content Refinement Specialist Samras Johnson Vanathaiya, Copyeditors Aravind Kannankara and Rathi Aravind, and Editorial Publication Coordinator Susan Engelken. I have been much benefited from their professional assistance in preparing this book.
Finally, I am lucky to see things just because I stand on the shoulders of many giants – the researchers and clinicians who devote themselves in oral medicine and neuroscience. This book will just be empty without their pioneering works. They are the true explorers in this new frontier.
About the Companion Website
This book is accompanied by a companion website.
www.wiley.com/go/lin/dental‐neuroimaging
The companion website includes:
Video courses
From Tools to Discovery
Lists of suggested readings for each chapter
Tables of updated information of neuroimaging literature associated with dentistry
Part IMethods of Neuroimaging and Assessment of Oral Functions
1 Introduction to Neuroimaging and the Brain–Stomatognathic Axis
1.1 Why Do Dentists Need to Understand the Brain?
1.1.1 Introduction
If we look into any textbook of clinical dentistry – be it oral pathology, prosthodontics, periodontics or orthodontics – we may not feel surprised that the word ‘brain’ would appear just very few times in the whole book. Traditionally, dentists are trained as an expert in treating oral diseases and the topics related to the brain, and its relevant disorders are usually categorized as systemic issues. The dichotomy of ‘dental vs. systemic’ suggests that the brain and behaviour issues are beyond the spotlight of dentists. Such alienation is even pronounced if we hold a ‘pathological perspective’ on the association between the brain and dentistry: oral diseases are usually not the primary aetiology of neurological/mental disorders, cardiovascular, gastrointestinal or endocrinal diseases (Figure 1.1). Therefore, there is no urgent need for dentists to learn the knowledge of the human brain.
However, the association between the brain and dentistry may show a different story if we adopt a ‘functional perspective’. Here, the brain, behaviour and oral health are directly linked if we consider that the brain plays a crucial role in maintaining oral functions, and the integrity of mental functions is critical to maintaining oral health. If we adopt the view that the brain and mental functions guided by the brain are essential to all human behaviours (e.g. from eating to toothbrushing), we may find that the brain has an essential and more dominant role in oral health (Figure 1.1).
In the following sections, we elaborate on this functional perspective by revisiting three lines of evidence. Historically, we see that dentistry and brain science are the ‘old alliance’ for more than 100 years. Educationally, we discuss the role of neuroscience in the curriculum of dental education. Finally, the new engagement between dentistry and the brain via neuroimaging methods is highlighted.
1.1.2 The ‘Old Alliance’ Between Dentistry and Brain Science
The first evidence of the alliance between dentistry and brain science exists in an article published 130 years ago entitled Reflex Neurosis in Relation to Dental Pathology. The author mentioned that ‘… pain in a tooth is not indicative of the source of trouble, … The cause may be remote or in another tooth’ (Hayes 1889), a phenomenon now we may consider as heterotopic pain. Subsequently, the author put forward some insightful speculation on orofacial pain:
Figure 1.1 The association between the brain and the stomatognathic system. The traditional perspective highlights the brain as a ‘systemic factor’ associated with oral health, just like the factors related to other body systems. The functional perspective highlights that the brain and mental functions guided by the brain play an essential role in stomatognathic functions.
Cerebral diseases, for example, insanity, softening of the brain, tumors and inflammation may produce odontalgia, but clinical reports reveal comparatively few, inasmuch owing to their obscurity positive diagnosis is often rendered difficult.
(Hayes 1889)
Though not scientifically accurate from the modern view, the statement points out the complex association between the brain and orofacial pain, which has confused dentists for more than one century. The alliance becomes cemented due to the challenge of treating orofacial pain, and new technologies, including neuroimaging, have provided new insights into this field (see Chapter 6). Our second evidence comes from the issues of infection control, especially the brain abscess secondary to dental infection. At present, dentists have been highly aware of infection control within the oral cavity. However, new challenges have emerged, such as the recent debates on the neuroinflammatory mechanisms that may underlie the link between neurodegenerative disorders and periodontal diseases (see Chapter 7). Finally, the third evidence of the old alliance has an even longer history. Back in 1790, when the terms ‘brain science’ and ‘dentistry’ have not yet popularized, in an article entitled ‘Pathological Observations on the Brain’, the author reported a potential association between epileptic signs and symptoms and irregular behaviour in eating and drinking (Anderson 1790). The finding echoes the link between the brain and oral sensorimotor functions, extensively studied in animal research (Lund 1991). New issues have emerged in modern days. For example, can older individuals be benefited from oral functional training to improve mastication and swallowing (Sessle 2019)? Can patients with neurodegenerative disorders, who have deficits in mental functions, also improve their oral functions? There are more challenges to meet for the old alliance between dentistry and brain science.
1.1.3 Dental Education: The Role of Neuroscience and the Brain
In the previous section, we have briefly discussed how the research of the brain has been linked to issues of oral health. However, the discussion may not be complete without looking into dental education for the following questions: has the role of brain science been recognized in dental education?
1.1.3.1 The Tradition of ‘Dentists as Surgeons’
A discussion of early dental education will not be complete without mentioning the contribution from Pierre Fauchard, widely recognized as the Father of Modern Dentistry, with the first textbook of dentistry Le Chirurgien Dentiste (‘The Surgeon Dentist’) published in 1728. As the name suggests, dentistry is the discipline of managing dental diseases with a surgeon's training. Notably, in this book, Fauchard has extended the professional domain of dentists from ‘teeth’ to the oral cavity (including the soft tissue). The new profession, a ‘surgeon dentist’, is different from a ‘toothpuller’ in the seventeenth to eighteenth centuries (Lynch et al. 2006). Though he also emphasized the relationship between oral and systemic diseases (Lynch et al. 2006), the primary task for dentists is to fix the structural deficits of the oral cavity, such as restoring a decayed tooth or replacing the missing teeth with a denture. All the jobs require dentists to be capable of performing complicated surgical skills.
An over‐focus on the surgical skills of dental treatment, however, had gradually received criticism since the early days when dental education became an independent discipline. As pointed by Eugene Talbot early in 1900:
The result is that study of the general diseases which affect the mouth, jaws and teeth have been neglected. Limitations of a dental education have prevented the dentist from associating local diseases with systemic causes.
(Talbot 1900)
The statement corresponds to the degree delivered for this new profession, namely Doctor of Dental Surgery (DDS), at Talbot's time. He further showed the concern that ‘… the graduate of dental surgery is not competent to associate systemic diseases with their effects on the teeth, nor is he capable of appreciating systemic lesions due to overtreatment of pathologic conditions of the teeth’ (Talbot 1900). The gap between a dentist and medical knowledge would make dentists ignore the systemic condition of patients – moreover, the ignorance may further exacerbate systemic health when dentists ‘overtreat’ patients (Talbot 1900).
1.1.3.2 Brain and Neuroscience: Is It Neglected in Dental School?
According to the Basic Science Survey Series of the American Dental Education Association (ADEA), neuroscience is widely taught in most dental schools in North American. In 2014, among 66 dental schools, 31 (47%) offered neuroscience as a standalone course, with the others integrated the neuroscience topics into other courses (Gould et al. 2014). It is also noteworthy that in most dental schools, the course was delivered by teachers from medical schools, who may not tailor‐make the course for dental students (Gould et al. 2014). The average year of teaching of the teachers is relatively high (23.1 years), suggesting fewer younger teachers are involved in the field (Gould et al. 2014). Critically, the topics to be delivered significantly varied between courses. Some topics, such as the knowledge of cranial nerves, were taught averagely for three hours. In contrast, issues of the neuropathic mechanisms of pain, including nerve regeneration, neuralgia, allodynia and hyperalgesia, were taught less than half an hour (Gould et al. 2014). Topics related to the human brain were taught in most of the courses. Nevertheless, among the 31 independent neuroscience courses, almost half of them focused on neuroanatomy, which emphasizes the knowledge of brain structure rather than the link between the brain and oral functions. This alienation reflects that many courses were taught by personnel outside the dental schools and may not provide what dentists need to know for their clinical careers.
