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Connecting networks to neurons
Connecting networks to neurons
25
Michael I. Posner
Pictures of the human brain have been enormously helpful. Just as the image of earth from space helped give rise to earth day, colorful images of the living human brain influenced the congressional declaration of “The Decade of the Brain,” made in the United States in the 1990s. Brain images, such as those depicted in Fig. 25.1, result from the activity of many thousands of nerve cells working together. A dream of neuroscience is to bridge the gap from these large-scale activation maps to the work of groups of cells and even to single neurons and axons such as those depicted in Fig. 25.2. This chapter discusses research on attention networks that might help connect neuroimaging to cellular and molecular events. Since the early days of neuroimaging, I have been most involved in studying attentional networks. Experiments from Figure 25.1 Neuroimages in bright colors of brain areas active various fields, includ- during various language tasks. Contributed by Michael Posner. ing behavioral, developmental, and imaging research, have converged to establish three brain networks involved in attention. These networks achieve an alert state (alerting), orient to sensory events (orienting), and control conflict between competing response tendencies (executive) [1]. Each of these networks involves mostly separate brain areas although the networks frequently work in concert when individuals perform a task. Perhaps most remarkable in these efforts is that merely asking someone to exercise control over their thoughts or feelings activates attentional networks. By now, many studies have established this by asking individuals to attend to visual stimuli rather than simultaneous auditory events [2], to create a visual image [3], to avoid
Casting Light on the Dark Side of Brain Imaging. DOI: https://doi.org/10.1016/B978-0-12-816179-1.00025-6 © 2019 Elsevier Inc. All rights reserved.
146
Casting Light on the Dark Side of Brain Imaging
negative [4] or positive reactions [5] to a stimulus, or even to control the order of mental operations when performing a task [6]. In these studies a complex attentional network is activated (including the anterior cingulate, anterior insula, and striatum), in addition to the specific sensory or motor areas of the brain which are directly involved in the specific task. Since these areas Figure 25.2 A picture of an individual connective fiber (axon) are activated in experiwith the surrounding myelin rings as insulation. Electron ments involving instrucmicrograph 16K magnification. Contributed by Dr. Denise tions to control, it Piscopo. seems reasonable to conclude that they are also used in the implementation of our natural wishes and desires in addition to responding to the instructions of the researcher. Not only do attentional brain networks correlate with specific tasks, they are also important for our success in life. Tasks which activate these brain areas are related to ratings, both by oneself and others, on how well someone can control their thoughts and feelings in daily life [7]. From such ratings in young children, studies have successfully predicted their later success in income, health, and social relations as adults [8]. The skills and brain networks involved in self-control, moreover, are far from fixed; they can be taught, for example, through computerized tasks and mindfulness meditation. In studies on humans, using diffusion tensor imaging, mindfulness meditation as well as other purely cognitive tasks has altered the connectivity of attention networks by improving the ability of axons to connect neurons. How could the purely mental activity of meditation, which involves keeping your attention fixed in the present and not allowing it to wander, result in a physical change in the white matter that surrounds axons? Several studies recording from scalp electrodes (EEG) have shown that meditation training increases rhythmic oscillations (4 8 Hz, theta range) over mid line frontal brain areas involved in attentional control. This finding led to the hypothesis [9] that theta stimulation activated dormant nonneuronal brain cells (oligodendrocytes) that lead to increases in myelin that surrounds axons. To test this hypothesis, we can use a technique called optogenetics. This method uses lasers to activate or suppress cells that have been rendered sensitive to light [10]. Currently, optogenetics can only be done in animal models, but it is possible that less invasive versions may be available in the future.
Connecting networks to neurons
147
Optogenetics and animal models may not be overly useful for studying language tasks like those shown in Fig. 25.1, but we can use them to study many interesting human tasks like those involving attention networks of alerting, orienting, and conflict resolution. For example, we can directly stimulate or inhibit neurons in the anterior cingulate of mice and observe how this procedure alters the kind of attentional control found in studies of human self-regulation (for an example, see [11]). After controlling the output and frequency of firing from the anterior cingulate with optogenetics, we have used electromicrographs to observe the change in white matter, as shown in Fig. 25.2. By relating the human and mouse studies, we can move beyond the idea of self-regulation as a purely psychological level of explanation and toward a detailed account of how neurons influence the brain networks that lead to self-control. Control networks in the brain seem to be active even when participants are at rest and not carrying out any task [12] (see chapter 23). Researchers have imaged these large-scale brain networks of attention to trace their development from infancy to old age. To get a more detailed understanding of these networks, scientists have imaged individual brain cells in rodents and shown the role of slow oscillatory brain rhythms in supporting the activity of large-scale networks [13]. These advancements give promise of a molecular understanding of how seemingly spontaneous activity of brain networks at rest can organize during brain development. Being able to see images of brain networks provides a strong visual experience which is perhaps often more persuasive than it should be. To increase the insights we can gain from these images, researchers can use brain stimulation, animal models, and computational models (see chapter 24)—to investigate different levels of analyses. Linking large-scale human networks to the underlying cellular structure will not answer all the interesting questions of the human brain; it is, however, a critical next step in our effort to further such understanding.
Additional readings Raichle ME. A paradigm shift in functional brain imaging. J Neurosci 2009;29/41:12729 34. Rothbart MK. Becoming who we are. New York: Guilford; 2011. Posner MI. Attention in a social world. New York: Oxford Univ. Press; 2012.
25
Michael I. Posner
Pictures of the human brain have been enormously helpful. Just as the image of earth from space helped give rise to earth day, colorful images of the living human brain influenced the congressional declaration of “The Decade of the Brain,” made in the United States in the 1990s. Brain images, such as those depicted in Fig. 25.1, result from the activity of many thousands of nerve cells working together. A dream of neuroscience is to bridge the gap from these large-scale activation maps to the work of groups of cells and even to single neurons and axons such as those depicted in Fig. 25.2. This chapter discusses research on attention networks that might help connect neuroimaging to cellular and molecular events. Since the early days of neuroimaging, I have been most involved in studying attentional networks. Experiments from Figure 25.1 Neuroimages in bright colors of brain areas active various fields, includ- during various language tasks. Contributed by Michael Posner. ing behavioral, developmental, and imaging research, have converged to establish three brain networks involved in attention. These networks achieve an alert state (alerting), orient to sensory events (orienting), and control conflict between competing response tendencies (executive) [1]. Each of these networks involves mostly separate brain areas although the networks frequently work in concert when individuals perform a task. Perhaps most remarkable in these efforts is that merely asking someone to exercise control over their thoughts or feelings activates attentional networks. By now, many studies have established this by asking individuals to attend to visual stimuli rather than simultaneous auditory events [2], to create a visual image [3], to avoid
Casting Light on the Dark Side of Brain Imaging. DOI: https://doi.org/10.1016/B978-0-12-816179-1.00025-6 © 2019 Elsevier Inc. All rights reserved.
146
Casting Light on the Dark Side of Brain Imaging
negative [4] or positive reactions [5] to a stimulus, or even to control the order of mental operations when performing a task [6]. In these studies a complex attentional network is activated (including the anterior cingulate, anterior insula, and striatum), in addition to the specific sensory or motor areas of the brain which are directly involved in the specific task. Since these areas Figure 25.2 A picture of an individual connective fiber (axon) are activated in experiwith the surrounding myelin rings as insulation. Electron ments involving instrucmicrograph 16K magnification. Contributed by Dr. Denise tions to control, it Piscopo. seems reasonable to conclude that they are also used in the implementation of our natural wishes and desires in addition to responding to the instructions of the researcher. Not only do attentional brain networks correlate with specific tasks, they are also important for our success in life. Tasks which activate these brain areas are related to ratings, both by oneself and others, on how well someone can control their thoughts and feelings in daily life [7]. From such ratings in young children, studies have successfully predicted their later success in income, health, and social relations as adults [8]. The skills and brain networks involved in self-control, moreover, are far from fixed; they can be taught, for example, through computerized tasks and mindfulness meditation. In studies on humans, using diffusion tensor imaging, mindfulness meditation as well as other purely cognitive tasks has altered the connectivity of attention networks by improving the ability of axons to connect neurons. How could the purely mental activity of meditation, which involves keeping your attention fixed in the present and not allowing it to wander, result in a physical change in the white matter that surrounds axons? Several studies recording from scalp electrodes (EEG) have shown that meditation training increases rhythmic oscillations (4 8 Hz, theta range) over mid line frontal brain areas involved in attentional control. This finding led to the hypothesis [9] that theta stimulation activated dormant nonneuronal brain cells (oligodendrocytes) that lead to increases in myelin that surrounds axons. To test this hypothesis, we can use a technique called optogenetics. This method uses lasers to activate or suppress cells that have been rendered sensitive to light [10]. Currently, optogenetics can only be done in animal models, but it is possible that less invasive versions may be available in the future.
Connecting networks to neurons
147
Optogenetics and animal models may not be overly useful for studying language tasks like those shown in Fig. 25.1, but we can use them to study many interesting human tasks like those involving attention networks of alerting, orienting, and conflict resolution. For example, we can directly stimulate or inhibit neurons in the anterior cingulate of mice and observe how this procedure alters the kind of attentional control found in studies of human self-regulation (for an example, see [11]). After controlling the output and frequency of firing from the anterior cingulate with optogenetics, we have used electromicrographs to observe the change in white matter, as shown in Fig. 25.2. By relating the human and mouse studies, we can move beyond the idea of self-regulation as a purely psychological level of explanation and toward a detailed account of how neurons influence the brain networks that lead to self-control. Control networks in the brain seem to be active even when participants are at rest and not carrying out any task [12] (see chapter 23). Researchers have imaged these large-scale brain networks of attention to trace their development from infancy to old age. To get a more detailed understanding of these networks, scientists have imaged individual brain cells in rodents and shown the role of slow oscillatory brain rhythms in supporting the activity of large-scale networks [13]. These advancements give promise of a molecular understanding of how seemingly spontaneous activity of brain networks at rest can organize during brain development. Being able to see images of brain networks provides a strong visual experience which is perhaps often more persuasive than it should be. To increase the insights we can gain from these images, researchers can use brain stimulation, animal models, and computational models (see chapter 24)—to investigate different levels of analyses. Linking large-scale human networks to the underlying cellular structure will not answer all the interesting questions of the human brain; it is, however, a critical next step in our effort to further such understanding.
Additional readings Raichle ME. A paradigm shift in functional brain imaging. J Neurosci 2009;29/41:12729 34. Rothbart MK. Becoming who we are. New York: Guilford; 2011. Posner MI. Attention in a social world. New York: Oxford Univ. Press; 2012.