The subject of my Ph.D. project is the study of the neural coding of sensory-motor responses in the leech Hirudo Medicinalis. I have used a combination of multielectrode recordings, videomicroscopy and computer vision methods to quantify the leech behavior and simultaneously measure its underlying neuronal activity. Based on this experimental approach, I was able to characterize the motor pattern underlying reflexive behavior in the leech, addressing fundamental issues of systems neuroscience such as population coding and distributed organization of motor responses. In this context, the specific aims of my Ph.D. project can be summarized in three main goals: 1) to develop a new method to quantify the two-dimensional pattern of defmmation induced by muscle contraction on the leech body wall; 2) to investigate the distributed organization of leech reflexive behavior at the level of recruitment and activation of specific classes of motoneurons and muscle fibers; 3) to understand the neural basis of the reliability of leech motor responses, by quantifying their reproducibility at different levels of neural processing. In this scheme, the accomplishment of a specific aim was the starting point to address the next one. Quantitative analysis of defommtion occurring on leech body-wall was the necessary backdrop for characterizing leech sensory-motor responses at the behavioral level. This quantitative analysis of behavior, in tum, was fundamental for comparing reproducibility of leech motor responses with that of neural firing sustaining them. In the following paragraphs, I will summarize the major achievements of my Ph.D. project in relation to established main goals. The first aim of my research was to develop a reliable and innovative method to quantify the pattern of deformation that muscle contraction induces on the leech body-wall. Muscle contraction is usually measured and characterized with force and displacement transducers. The contraction of muscle fibers, however, evokes in the tissue a two and even three-dimensional displacement field, which is not properly quantified by these transducers because they provide just a single scalar quantity. I circumvented this problem by using videomicroscopy and standard tools of computer vision developed for the analysis of time varying image sequences. By computing the so called optical flow, i.e. the apparent motion of points in a time varying image sequence, it is possible to recover a two dimensional motion field, describing rather precisely the displacement caused by muscle contraction in a flattened piece of skin. The obtained two dimensional optical flow can be further analyzed by computing its migin (i.e. the singular point) and four elementary components that combine linearly: expansion, rotation, longitudinal shear and oblique shear. These elementary deformations provide a compact and accurate characterization of the contraction induced by different motoneurons. I demonstrated this technique by analyzing the displacement caused by muscle contraction on the leech body-wall. However, this method can be applied to monitor and characterize all contractions in almost flat tissues with enough visual texture. The second aim of my Ph.D. project was to apply the method described above in order to characterize the pattern of activation of different classes of motoneurons and muscles during leech reflexive behavior. Activation of motoneurons innervating leech muscles causes the appearance of a two dimensional vector field of deformations on the skin surface that can be fully characterized by computing the optical flow. I found that all motoneurons can be classified and recognized according to the elementary deformations of the contractions they elicit: longitudinal motoneurons give rise almost exclusively to longitudinal negative shear, whereas circular motoneurons give rise to both positive longitudinal shear and significant negative expansion. Oblique motoneurons induce strong oblique shear, in addition to longihidinal shear and negative expansion. These results clearly showed that contractions induced by different classes of motoneurons and muscle fibers form a set of basic behavioral units. I also investigated the way in which such behavioral units can combine to sustain motor responses and I found that optical flows induced by the contraction of longitudinal, circular and oblique fibers superimpose linearly. Complex patterns of skin deformation induced by mechanosensory stimulation can therefore be attributed rather reliably to the contraction of distinct longitudinal, circular and oblique muscle fibers. Based on this conclusion, I found that local bending, a motor response caused by local mechanical stimulation of the leech skin, is sustained by coactivation of two distinct classes of motoneurons: circular and longitudinal. I also compared the pattern of deformation produced by local bending with that produced by intracellular stimulation of mechanosensory pressure (P), touch (T) and nociceptive (N) cells: optical flows resulting from the activation of P cells were almost identical to those produced by mechanical stimulation. This confirmed that local bending is almost entirely mediated by excitation of P cells, with minor contributions from T and N cells. In conclusion, these results revealed the distributed nature of leech reflexive behavior at the level of muscle activation and motoneuron recruitment, showing that complex motor responses result from the linear sum of a small number of basic patterns of deformation. The final step in investigating distributed motor behavior in the leech was to characterize the reproducibility of local bending and that of neural firing sustaining it. I analyzed variability at different levels of processing: mechanosensory neurons, motoneurons, muscle activation and behavior. I found that spike trains in mechanosensory neurons were very reproducible, unlike those in motoneurons. However, the motor response was much more reproducible than the firing of individual motoneurons sustaining it. I showed that this reliability of the behavior is obtained by two distinct biophysical mechanisms: temporal and ensemble averaging. The former is guaranteed by the low pass filtering properties of the leech muscles that contract very slowly and therefore are poorly sensitive to the jitter of motoneuron spikes. The latter is provided by the coactivation of a population of motoneurons, firing in a statistically independent way. This statistical independence reduces the vm~ability of the population firing. These results have a general significance, because they show that reproducible spike trains are not required to sustain reproducible behaviors and illustrate how the nervous system can cope with umeliable components to produce reliable action.

A Multidisciplinary Study of Neural Coding Underlying Sensory-Motor Responses in the Leech / Zoccolan, Davide Franco. - (2002 Oct 25).

A Multidisciplinary Study of Neural Coding Underlying Sensory-Motor Responses in the Leech

Zoccolan, Davide Franco
2002

Abstract

The subject of my Ph.D. project is the study of the neural coding of sensory-motor responses in the leech Hirudo Medicinalis. I have used a combination of multielectrode recordings, videomicroscopy and computer vision methods to quantify the leech behavior and simultaneously measure its underlying neuronal activity. Based on this experimental approach, I was able to characterize the motor pattern underlying reflexive behavior in the leech, addressing fundamental issues of systems neuroscience such as population coding and distributed organization of motor responses. In this context, the specific aims of my Ph.D. project can be summarized in three main goals: 1) to develop a new method to quantify the two-dimensional pattern of defmmation induced by muscle contraction on the leech body wall; 2) to investigate the distributed organization of leech reflexive behavior at the level of recruitment and activation of specific classes of motoneurons and muscle fibers; 3) to understand the neural basis of the reliability of leech motor responses, by quantifying their reproducibility at different levels of neural processing. In this scheme, the accomplishment of a specific aim was the starting point to address the next one. Quantitative analysis of defommtion occurring on leech body-wall was the necessary backdrop for characterizing leech sensory-motor responses at the behavioral level. This quantitative analysis of behavior, in tum, was fundamental for comparing reproducibility of leech motor responses with that of neural firing sustaining them. In the following paragraphs, I will summarize the major achievements of my Ph.D. project in relation to established main goals. The first aim of my research was to develop a reliable and innovative method to quantify the pattern of deformation that muscle contraction induces on the leech body-wall. Muscle contraction is usually measured and characterized with force and displacement transducers. The contraction of muscle fibers, however, evokes in the tissue a two and even three-dimensional displacement field, which is not properly quantified by these transducers because they provide just a single scalar quantity. I circumvented this problem by using videomicroscopy and standard tools of computer vision developed for the analysis of time varying image sequences. By computing the so called optical flow, i.e. the apparent motion of points in a time varying image sequence, it is possible to recover a two dimensional motion field, describing rather precisely the displacement caused by muscle contraction in a flattened piece of skin. The obtained two dimensional optical flow can be further analyzed by computing its migin (i.e. the singular point) and four elementary components that combine linearly: expansion, rotation, longitudinal shear and oblique shear. These elementary deformations provide a compact and accurate characterization of the contraction induced by different motoneurons. I demonstrated this technique by analyzing the displacement caused by muscle contraction on the leech body-wall. However, this method can be applied to monitor and characterize all contractions in almost flat tissues with enough visual texture. The second aim of my Ph.D. project was to apply the method described above in order to characterize the pattern of activation of different classes of motoneurons and muscles during leech reflexive behavior. Activation of motoneurons innervating leech muscles causes the appearance of a two dimensional vector field of deformations on the skin surface that can be fully characterized by computing the optical flow. I found that all motoneurons can be classified and recognized according to the elementary deformations of the contractions they elicit: longitudinal motoneurons give rise almost exclusively to longitudinal negative shear, whereas circular motoneurons give rise to both positive longitudinal shear and significant negative expansion. Oblique motoneurons induce strong oblique shear, in addition to longihidinal shear and negative expansion. These results clearly showed that contractions induced by different classes of motoneurons and muscle fibers form a set of basic behavioral units. I also investigated the way in which such behavioral units can combine to sustain motor responses and I found that optical flows induced by the contraction of longitudinal, circular and oblique fibers superimpose linearly. Complex patterns of skin deformation induced by mechanosensory stimulation can therefore be attributed rather reliably to the contraction of distinct longitudinal, circular and oblique muscle fibers. Based on this conclusion, I found that local bending, a motor response caused by local mechanical stimulation of the leech skin, is sustained by coactivation of two distinct classes of motoneurons: circular and longitudinal. I also compared the pattern of deformation produced by local bending with that produced by intracellular stimulation of mechanosensory pressure (P), touch (T) and nociceptive (N) cells: optical flows resulting from the activation of P cells were almost identical to those produced by mechanical stimulation. This confirmed that local bending is almost entirely mediated by excitation of P cells, with minor contributions from T and N cells. In conclusion, these results revealed the distributed nature of leech reflexive behavior at the level of muscle activation and motoneuron recruitment, showing that complex motor responses result from the linear sum of a small number of basic patterns of deformation. The final step in investigating distributed motor behavior in the leech was to characterize the reproducibility of local bending and that of neural firing sustaining it. I analyzed variability at different levels of processing: mechanosensory neurons, motoneurons, muscle activation and behavior. I found that spike trains in mechanosensory neurons were very reproducible, unlike those in motoneurons. However, the motor response was much more reproducible than the firing of individual motoneurons sustaining it. I showed that this reliability of the behavior is obtained by two distinct biophysical mechanisms: temporal and ensemble averaging. The former is guaranteed by the low pass filtering properties of the leech muscles that contract very slowly and therefore are poorly sensitive to the jitter of motoneuron spikes. The latter is provided by the coactivation of a population of motoneurons, firing in a statistically independent way. This statistical independence reduces the vm~ability of the population firing. These results have a general significance, because they show that reproducible spike trains are not required to sustain reproducible behaviors and illustrate how the nervous system can cope with umeliable components to produce reliable action.
Torre, Vincent
Zoccolan, Davide Franco
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/57439
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