Sympathetic Humans
Reorganization of the human central nervous system.
Schalow G, Zäch GA.
Schalow G, Zäch GA.
The key strategies on which the discovery of the functional organization of the central nervous system (CNS) under physiologic and pathophysiologic conditions have been based included (1) our measurements of phase and frequency coordination between the firings of alpha- and gamma-motoneurons and secondary muscle spindle afferents in the human spinal cord, (2) knowledge on CNS reorganization derived upon the improvement of the functions of the lesioned CNS in our patients in the short-term memory and the long-term memory (reorganization), and (3) the dynamic pattern approach for re-learning rhythmic coordinated behavior. The theory of self-organization and pattern formation in nonequilibrium systems is explicitly related to our measurements of the natural firing patterns of sets of identified single neurons in the human spinal premotor network and re-learned coordinated movements following spinal cord and brain lesions. Therapy induced cell proliferation, and maybe, neurogenesis seem to contribute to the host of structural changes during the process of re-learning of the lesioned CNS. So far, coordinated functions like movements could substantially be improved in every of the more than 100 patients with a CNS lesion by applying coordination dynamic therapy. As suggested by the data of our patients on re-learning, the human CNS seems to have a second integrative strategy for learning, re-learning, storing and recalling, which makes an essential contribution of the functional plasticity following a CNS lesion. A method has been developed by us for the simultaneous recording with wire electrodes of extracellular action potentials from single human afferent and efferent nerve fibres of undamaged sacral nerve roots. A classification scheme of the nerve fibres in the human peripheral nervous system (PNS) could be set up in which the individual classes of nerve fibres are characterized by group conduction velocities and group nerve fibre diameters. Natural impulse patterns of several identified single afferent and efferent nerve fibres (motoneuron axons) were extracted from multi-unit impulse patterns, and human CNS functions could be analyzed under physiologic and pathophysiologic conditions. With our discovery of premotor spinal oscillators it became possible to judge upon CNS neuronal network organization based on the firing patterns of these spinal oscillators and their driving afferents. Since motoneurons fire occasionally for low activation and oscillatory for high activation, the coherent organization of subnetworks to generate macroscopic function is very complex and for the time being, may be best described by the theory of coordination dynamics. Since oscillatory firing has also been observed by us in single motor unit firing patterns measured electromyographically, it seems possible to follow up therapeutic intervention in patients with spinal cord and brain lesions not only based on the activity levels and phases of motor programs during locomotion but also based on the physiologic and pathophysiologic firing patterns and recruitment of spinal oscillators. The improvement of the coordination dynamics of the CNS can be partly measured directly by rhythmicity upon the patient performing rhythmic movements coordinated up to milliseconds. Since rhythmic dynamic, coordinated, stereotyped movements are mainly located in the spinal cord and only little supraspinal drive is necessary to initiate, maintain, and terminate them, rhythmic, dynamic, coordinated movements were used in therapy to enforce reorganization of the lesioned CNS by improving the self-organization and relative coordination of spinal oscillators (and their interactions with occasionally firing motoneurons) which became pathologic in their firing following CNS lesion. Paraparetic, tetraparetic spinal cord and brain-lesioned patients re-learned running and other movements by an oscillator formation and coordination dynamic therapy. Our development in neurorehabilitation is in accordance with those of theoretical and computational neurosciences which deal with the self-organization of neuronal networks. In particular, jumping on a springboard 'in-phase' and in 'anti-phase' to re-learn phase relations of oscillator coupling can be understood in the framework of the Haken-Kelso-Bunz coordination dynamic model. By introducing broken symmetry, intention, learning and spasticity in the landscape of the potential function of the integrated CNS activity, the change in self-organization becomes understandable. Movement patterns re-learned by oscillator formation and coordination dynamic therapy evolve from reorganization and regeneration of the lesioned CNS by cooperative and competitive interplay between intrinsic coordination dynamics, extrinsic therapy related inputs with physiologic re-afferent input, including intention, motivation, supervised learning, interpersonal coordination, and genetic constraints including neurogenesis.
Sympathetic Humans
Acute stress impairs inhibitory control based on individual differences in parasympathetic nervous system activity.
Identifying environmental influences on inhibitory control (IC) may help promote positive behavioral and social adjustment. Although chronic stress is known to predict lower IC, the immediate effects of acute stress are unknown. The parasympathetic nervous system (PNS) may be a mechanism of the stress-IC link, given its psychophysiological regulatory role and connections to prefrontal brain regions critical to IC. We used a focused assessment of IC (the stop-signal task) to test whether an acute social stressor (the Trier Social Stress Test) affected participants' pre- to post-IC performance (n=58), compared to a control manipulation (n=31). High frequency heart-rate variability was used as an index of PNS activity in response to the manipulation. Results indicated that stress impaired IC performance, blocking the practice effects observed in control participants. We also investigated the associations between PNS activity and IC; higher resting PNS activity predicted better pre-manipulation IC, and greater PNS stressor reactivity protected against the negative effects of stress on IC. Together, these results are the first to document the immediate effects of acute stress on IC and a phenotypic marker (PNS reactivity to stressors) of susceptibility to stress-induced IC impairment. This study suggests a new way to identify situations in which individuals are likely to exhibit IC vulnerability and related consequences such as impulsivity and risk taking behavior. Targeting PNS regulation may represent a novel target for IC-focused interventions.
IBM Research Report -Sympathetic Humans -2007 Four Paths to A.I.
Inexact Reasoning – The premise here is that formal symbol manipulation, like first- order logic, is too brittle for the real world. Things are not black-and-white but rather shades of gray, and AI systems need to be able to reason in this manner. Some interesting progress has been made using Fuzzy Logic for mobile robots [3].
Deep Language – An AI cannot be expected to be fully competent straight “out of the box”, instead it needs to learn from sympathetic humans and/or from reading written material. To do this it must have a deep understanding of human language. To do this often involves a tight intermingling of syntactic and semantic [4].
Embodiment – Proponents of the embodiment solution to finding AI argue that you cannot achieve human-like intelligence unless the system has a body and can interact with the real physical world. Being embodied makes you care about objects, space, uncertainty, and actions to get tasks accomplished. In an important sense the body is just a special purpose computational engine, one that has evolved to solve very specific problems that are computationally expensive or even intractable any other way [5].
Quantum Physics – This line of argument suggests that consciousness is essential for true general intelligence, and that consciousness itself is based in quantum-level events. To achieve AI, therefore, will require finding ways to make quantum computing a reality. Although versions of the theory have been worked out in some detail as they might apply to the human case [6], the hypothesis has not been subjected to direct empirical test.
Deep Language – An AI cannot be expected to be fully competent straight “out of the box”, instead it needs to learn from sympathetic humans and/or from reading written material. To do this it must have a deep understanding of human language. To do this often involves a tight intermingling of syntactic and semantic [4].
Embodiment – Proponents of the embodiment solution to finding AI argue that you cannot achieve human-like intelligence unless the system has a body and can interact with the real physical world. Being embodied makes you care about objects, space, uncertainty, and actions to get tasks accomplished. In an important sense the body is just a special purpose computational engine, one that has evolved to solve very specific problems that are computationally expensive or even intractable any other way [5].
Quantum Physics – This line of argument suggests that consciousness is essential for true general intelligence, and that consciousness itself is based in quantum-level events. To achieve AI, therefore, will require finding ways to make quantum computing a reality. Although versions of the theory have been worked out in some detail as they might apply to the human case [6], the hypothesis has not been subjected to direct empirical test.
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