PMC:2940414 / 1659-3833 JSONTXT

{"project":"2_test","denotations":[{"id":"20859448-9416664-38126384","span":{"begin":493,"end":497},"obj":"9416664"},{"id":"20859448-18075116-38126385","span":{"begin":701,"end":705},"obj":"18075116"},{"id":"20859448-6104038-38126386","span":{"begin":1209,"end":1213},"obj":"6104038"},{"id":"20859448-11348584-38126387","span":{"begin":1906,"end":1910},"obj":"11348584"},{"id":"20859448-18584059-38126388","span":{"begin":1928,"end":1932},"obj":"18584059"},{"id":"20859448-16135888-38126389","span":{"begin":1964,"end":1968},"obj":"16135888"},{"id":"20859448-18958276-38126390","span":{"begin":1985,"end":1989},"obj":"18958276"}],"text":"In their natural context, neural circuits are part of a sensory-motor loop. They are embodied along with sensory organs to perceive the environment in which the animal is situated. Neurons in turn control the animal's movements, which results in new sensory input. This tight, continuous sensory-motor loop (from brain, to body, to environment, back to brain) is important for learning to predict the consequences of actions and is essential for optimizing adaptive behaviors (Chiel and Beer, 1997; Clark, 1997; Pfeifer and Bongard, 2007). Neuroscience researchers and biomedical engineers are beginning to appreciate how closing the loop around a neural circuit (Potter et al., 2006; Arsiero et al., 2007) can provide more natural information about nervous system dynamics, and lead to more effective treatment of nervous system disorders. Consider a typical open-loop experiment, where sensory input is presented to an anesthetized, reduced, or even disembodied nervous system, and its response is measured. In contrast, with closed-loop experiments, some aspects of how the nervous system responds will determine what is presented next, in real time, without experimenter intervention (Brice and McLellan, 1980). In this way, input and output sides of the nervous system can be studied together, in a more natural context. On the clinical side, consider the deep-brain stimulation currently used to treat Parkinsonism: stimulation parameters remain constant at levels set by the clinician, operating open-loop, regardless of the present brain state of the patient. In contrast, future closed-loop therapies will continuously tailor brain stimulation to optimize therapeutic effect and respond to changing brain states. By closing the loop with technology, researchers can probe or alter nervous system function not only in intact animals, but also in reduced preparations such as hybrots (Reger et al., 2000; DeMarse et al., 2001; Potter, 2002; Karniel et al., 2005; Bakkum et al., 2007). Considering that nervous systems are dynamic, complex, and responsive, it is logical that the tools we use to probe and modulate them should also be dynamic, complex, and responsive."}

{"project":"TEST0","denotations":[{"id":"20859448-228-236-173674","span":{"begin":493,"end":497},"obj":"[\"9416664\"]"},{"id":"20859448-161-169-173675","span":{"begin":701,"end":705},"obj":"[\"18075116\"]"},{"id":"20859448-199-207-173676","span":{"begin":1209,"end":1213},"obj":"[\"6104038\"]"},{"id":"20859448-184-192-173677","span":{"begin":1906,"end":1910},"obj":"[\"11348584\"]"},{"id":"20859448-206-214-173678","span":{"begin":1928,"end":1932},"obj":"[\"18584059\"]"},{"id":"20859448-231-239-173679","span":{"begin":1964,"end":1968},"obj":"[\"16135888\"]"},{"id":"20859448-226-234-173680","span":{"begin":1985,"end":1989},"obj":"[\"18958276\"]"}],"text":"In their natural context, neural circuits are part of a sensory-motor loop. They are embodied along with sensory organs to perceive the environment in which the animal is situated. Neurons in turn control the animal's movements, which results in new sensory input. This tight, continuous sensory-motor loop (from brain, to body, to environment, back to brain) is important for learning to predict the consequences of actions and is essential for optimizing adaptive behaviors (Chiel and Beer, 1997; Clark, 1997; Pfeifer and Bongard, 2007). Neuroscience researchers and biomedical engineers are beginning to appreciate how closing the loop around a neural circuit (Potter et al., 2006; Arsiero et al., 2007) can provide more natural information about nervous system dynamics, and lead to more effective treatment of nervous system disorders. Consider a typical open-loop experiment, where sensory input is presented to an anesthetized, reduced, or even disembodied nervous system, and its response is measured. In contrast, with closed-loop experiments, some aspects of how the nervous system responds will determine what is presented next, in real time, without experimenter intervention (Brice and McLellan, 1980). In this way, input and output sides of the nervous system can be studied together, in a more natural context. On the clinical side, consider the deep-brain stimulation currently used to treat Parkinsonism: stimulation parameters remain constant at levels set by the clinician, operating open-loop, regardless of the present brain state of the patient. In contrast, future closed-loop therapies will continuously tailor brain stimulation to optimize therapeutic effect and respond to changing brain states. By closing the loop with technology, researchers can probe or alter nervous system function not only in intact animals, but also in reduced preparations such as hybrots (Reger et al., 2000; DeMarse et al., 2001; Potter, 2002; Karniel et al., 2005; Bakkum et al., 2007). Considering that nervous systems are dynamic, complex, and responsive, it is logical that the tools we use to probe and modulate them should also be dynamic, complex, and responsive."}

{"project":"0_colil","denotations":[{"id":"20859448-9416664-173674","span":{"begin":493,"end":497},"obj":"9416664"},{"id":"20859448-18075116-173675","span":{"begin":701,"end":705},"obj":"18075116"},{"id":"20859448-6104038-173676","span":{"begin":1209,"end":1213},"obj":"6104038"},{"id":"20859448-11348584-173677","span":{"begin":1906,"end":1910},"obj":"11348584"},{"id":"20859448-18584059-173678","span":{"begin":1928,"end":1932},"obj":"18584059"},{"id":"20859448-16135888-173679","span":{"begin":1964,"end":1968},"obj":"16135888"},{"id":"20859448-18958276-173680","span":{"begin":1985,"end":1989},"obj":"18958276"}],"text":"In their natural context, neural circuits are part of a sensory-motor loop. They are embodied along with sensory organs to perceive the environment in which the animal is situated. Neurons in turn control the animal's movements, which results in new sensory input. This tight, continuous sensory-motor loop (from brain, to body, to environment, back to brain) is important for learning to predict the consequences of actions and is essential for optimizing adaptive behaviors (Chiel and Beer, 1997; Clark, 1997; Pfeifer and Bongard, 2007). Neuroscience researchers and biomedical engineers are beginning to appreciate how closing the loop around a neural circuit (Potter et al., 2006; Arsiero et al., 2007) can provide more natural information about nervous system dynamics, and lead to more effective treatment of nervous system disorders. Consider a typical open-loop experiment, where sensory input is presented to an anesthetized, reduced, or even disembodied nervous system, and its response is measured. In contrast, with closed-loop experiments, some aspects of how the nervous system responds will determine what is presented next, in real time, without experimenter intervention (Brice and McLellan, 1980). In this way, input and output sides of the nervous system can be studied together, in a more natural context. On the clinical side, consider the deep-brain stimulation currently used to treat Parkinsonism: stimulation parameters remain constant at levels set by the clinician, operating open-loop, regardless of the present brain state of the patient. In contrast, future closed-loop therapies will continuously tailor brain stimulation to optimize therapeutic effect and respond to changing brain states. By closing the loop with technology, researchers can probe or alter nervous system function not only in intact animals, but also in reduced preparations such as hybrots (Reger et al., 2000; DeMarse et al., 2001; Potter, 2002; Karniel et al., 2005; Bakkum et al., 2007). Considering that nervous systems are dynamic, complex, and responsive, it is logical that the tools we use to probe and modulate them should also be dynamic, complex, and responsive."}