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- All Subjects: Neurosciences
Description
Cell morphology and the distribution of voltage gated ion channels play a major role in determining a neuron's firing behavior, resulting in the specific processing of spatiotemporal synaptic input patterns. Although many studies have provided insight into the computational properties arising from neuronal structure as well as from channel kinetics, no comprehensive theory exists which explains how the interaction of these features shapes neuronal excitability. In this study computational models based on the identified Drosophila motoneuron (MN) 5 are developed to investigate the role of voltage gated ion channels, the impact of their densities and the effects of structural features.
First, a spatially collapsed model is used to develop voltage gated ion channels to study the excitability of the model neuron. Changing the channel densities reproduces different in situ observed firing patterns and induces a switch from resonator to integrator properties. Second, morphologically realistic multicompartment models are studied to investigate the passive properties of MN5. The passive electrical parameters fall in a range that is commonly observed in neurons, MN5 is spatially not compact, but for the single subtrees synaptic efficacy is location independent. Further, different subtrees are electrically independent from each other. Third, a continuum approach is used to formulate a new cable theoretic model to study the output in a dendritic cable with many subtrees, both analytically and computationally. The model is validated, by comparing it to a corresponding model with discrete branches. Further, the approach is demonstrated using MN5 and used to investigate spatially distributions of voltage gated ion channels.
First, a spatially collapsed model is used to develop voltage gated ion channels to study the excitability of the model neuron. Changing the channel densities reproduces different in situ observed firing patterns and induces a switch from resonator to integrator properties. Second, morphologically realistic multicompartment models are studied to investigate the passive properties of MN5. The passive electrical parameters fall in a range that is commonly observed in neurons, MN5 is spatially not compact, but for the single subtrees synaptic efficacy is location independent. Further, different subtrees are electrically independent from each other. Third, a continuum approach is used to formulate a new cable theoretic model to study the output in a dendritic cable with many subtrees, both analytically and computationally. The model is validated, by comparing it to a corresponding model with discrete branches. Further, the approach is demonstrated using MN5 and used to investigate spatially distributions of voltage gated ion channels.
ContributorsBerger, Sandra (Author) / Crook, Sharon (Thesis advisor) / Baer, Steven (Committee member) / Hamm, Thomas (Committee member) / Smith, Brian (Committee member) / Arizona State University (Publisher)
Created2014
Description
Dendrites are the structures of a neuron specialized to receive input signals and to provide the substrate for the formation of synaptic contacts with other cells. The goal of this work is to study the activity-dependent mechanisms underlying dendritic growth in a single-cell model. For this, the individually identifiable adult motoneuron, MN5, in Drosophila melanogaster was used. This dissertation presents the following results. First, the natural variability of morphological parameters of the MN5 dendritic tree in control flies is not larger than 15%, making MN5 a suitable model for quantitative morphological analysis. Second, three-dimensional topological analyses reveals that different parts of the MN5 dendritic tree innervate spatially separated areas (termed "isoneuronal tiling"). Third, genetic manipulation of the MN5 excitability reveals that both increased and decreased activity lead to dendritic overgrowth; whereas decreased excitability promoted branch elongation, increased excitability enhanced dendritic branching. Next, testing the activity-regulated transcription factor AP-1 for its role in MN5 dendritic development reveals that neural activity enhanced AP-1 transcriptional activity, and that AP-1 expression lead to opposite dendrite fates depending on its expression timing during development. Whereas overexpression of AP-1 at early stages results in loss of dendrites, AP-1 overexpression after the expression of acetylcholine receptors and the formation of all primary dendrites in MN5 causes overgrowth. Fourth, MN5 has been used to examine dendritic development resulting from the expression of the human gene MeCP2, a transcriptional regulator involved in the neurodevelopmental disease Rett syndrome. Targeted expression of full-length human MeCP2 in MN5 causes impaired dendritic growth, showing for the first time the cellular consequences of MeCP2 expression in Drosophila neurons. This dendritic phenotype requires the methyl-binding domain of MeCP2 and the chromatin remodeling protein Osa. In summary, this work has fully established MN5 as a single-neuron model to study mechanisms underlying dendrite development, maintenance and degeneration, and to test the behavioral consequences resulting from dendritic growth misregulation. Furthermore, this thesis provides quantitative description of isoneuronal tiling of a central neuron, offers novel insight into activity- and AP-1 dependent developmental plasticity, and finally, it establishes Drosophila MN5 as a model to study some specific aspects of human diseases.
ContributorsVonhoff, Fernando Jaime (Author) / Duch, Carsten J (Thesis advisor) / Smith, Brian H. (Committee member) / Vu, Eric (Committee member) / Crook, Sharon (Committee member) / Arizona State University (Publisher)
Created2012
Description
Recent new experiments showed that wide-field imaging at millimeter scale is capable of recording hundreds of neurons in behaving mice brain. Monitoring hundreds of individual neurons at a high frame rate provides a promising tool for discovering spatiotemporal features of large neural networks. However, processing the massive data sets is impossible without automated procedures. Thus, this thesis aims at developing a new tool to automatically segment and track individual neuron cells. The new method used in this study employs two major ideas including feature extraction based on power spectral density of single neuron temporal activity and clustering tree to separate overlapping cells. To address issues associated with high-resolution imaging of a large recording area, focused areas and out-of-focus areas were analyzed separately. A static segmentation with a fixed PSD thresholding method is applied to within focus visual field. A dynamic segmentation by comparing maximum PSD with surrounding pixels is applied to out-of-focus area. Both approaches helped remove irrelevant pixels in the background. After detection of potential single cells, some of which appeared in groups due to overlapping cells in the image, a hierarchical clustering algorithm is applied to separate them. The hierarchical clustering uses correlation coefficient as a distance measurement to group similar pixels into single cells. As such, overlapping cells can be separated. We tested the entire algorithm using two real recordings with the respective truth carefully determined by manual inspections. The results show high accuracy on tested datasets while false positive error is controlled within an acceptable range. Furthermore, results indicate robustness of the algorithm when applied to different image sequences.
ContributorsWu, Ruofan (Author) / Si, Jennie (Thesis advisor) / Sadleir, Rosalind (Committee member) / Crook, Sharon (Committee member) / Arizona State University (Publisher)
Created2016
Description
In the last 15 years, there has been a significant increase in the number of motor neural prostheses used for restoring limb function lost due to neurological disorders or accidents. The aim of this technology is to enable patients to control a motor prosthesis using their residual neural pathways (central or peripheral). Recent studies in non-human primates and humans have shown the possibility of controlling a prosthesis for accomplishing varied tasks such as self-feeding, typing, reaching, grasping, and performing fine dexterous movements. A neural decoding system comprises mainly of three components: (i) sensors to record neural signals, (ii) an algorithm to map neural recordings to upper limb kinematics and (iii) a prosthetic arm actuated by control signals generated by the algorithm. Machine learning algorithms that map input neural activity to the output kinematics (like finger trajectory) form the core of the neural decoding system. The choice of the algorithm is thus, mainly imposed by the neural signal of interest and the output parameter being decoded. The various parts of a neural decoding system are neural data, feature extraction, feature selection, and machine learning algorithm. There have been significant advances in the field of neural prosthetic applications. But there are challenges for translating a neural prosthesis from a laboratory setting to a clinical environment. To achieve a fully functional prosthetic device with maximum user compliance and acceptance, these factors need to be addressed and taken into consideration. Three challenges in developing robust neural decoding systems were addressed by exploring neural variability in the peripheral nervous system for dexterous finger movements, feature selection methods based on clinically relevant metrics and a novel method for decoding dexterous finger movements based on ensemble methods.
ContributorsPadmanaban, Subash (Author) / Greger, Bradley (Thesis advisor) / Santello, Marco (Committee member) / Helms Tillery, Stephen (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Crook, Sharon (Committee member) / Arizona State University (Publisher)
Created2017
Description
A general continuum model for simulating the flow of ions in the salt baths that surround and fill excitable neurons is developed and presented. The ion densities and electric potential are computed using the drift-diffusion equations. In addition, a detailed model is given for handling the electrical dynamics on interior membrane boundaries, including a model for ion channels in the membranes that facilitate the transfer of ions in and out of cells. The model is applied to the triad synapse found in the outer plexiform layer of the retina in most species. Experimental evidence suggests the existence of a negative feedback pathway between horizontal cells and cone photoreceptors that modulates the flow of calcium ions into the synaptic terminals of cones. However, the underlying mechanism for this feedback is controversial and there are currently three competing hypotheses: the ephaptic hypothesis, the pH hypothesis and the GABA hypothesis. The goal of this work is to test some features of the ephaptic hypothesis using detailed simulations that employ rigorous numerical methods. The model is first applied in a simple rectangular geometry to demonstrate the effects of feedback for different extracellular gap widths. The model is then applied to a more complex and realistic geometry to demonstrate the existence of strictly electrical feedback, as predicted by the ephaptic hypothesis. Lastly, the effects of electrical feedback in regards to the behavior of the bipolar cell membrane potential is explored. Figures for the ion densities and electric potential are presented to verify key features of the model. The computed steady state IV curves for several cases are presented, which can be compared to experimental data. The results provide convincing evidence in favor of the ephaptic hypothesis since the existence of feedback that is strictly electrical in nature is shown, without any dependence on pH effects or chemical transmitters.
ContributorsJones, Jeremiah (Author) / Gardner, Carl (Committee member) / Baer, Steven (Committee member) / Crook, Sharon (Committee member) / Kostelich, Eric (Committee member) / Ringhofer, Christian (Committee member) / Arizona State University (Publisher)
Created2013
Description
Non-invasive visualization of the trigeminal nerve through advanced MR sequences and methods like tractography is important for studying anatomical and microstructural changes due to pathology like trigeminal neuralgia (TN), facial dystonia, multiple sclerosis, and for surgical pre-planning. The use of specific anatomical markers from CT, MPRAGE and cranial nerve imaging (CRANI) sequences, enabled successful tractography of patient-specific trajectory of the frontal, nasociliary, infraorbital, and mandibular nerve branches extending beyond the cisternal brain stem region and leading to the face. Performance of MPRAGE sequence together with the advanced T2-weighted CRANI sequence with and without a gadolinium contrast agent, was studied to characterize identification efficiency in smaller nerve structures in the extremities. A large FOV nerve visualization exam inclusive of the anatomy of all trigeminal nerve distal branches can be obtained within an acquisition time of 20 minutes using pre-contrast CRANI and MPRAGE. Post-processing with MPR and MIP images improved nerve visualization.Transcranial electrical stimulation techniques (TES) have been used for the treatment of multiple neurodegenerative diseases. These techniques involve placing electrodes on the scalp with multiple peripheral branches of the trigeminal nerve crossing directly under that may be stimulated. This was studied through hybrid computational realistic axon models. These models also facilitated studying the effects of electrode drift during experiments on the recruitment of peripheral nerves. An optimal point of lowest threshold was found while displacing the nerve horizontally i.e., the activation thresholds of both myelinated and unmyelinated axons increased when the electrodes were displaced medially and decreased to a certain extend when the electrodes were displaced laterally, after which further lateral displacement led to increase of thresholds. Inclusion of unmyelinated axons in the modeling provided the capability of finding maximum stimulation amplitude below which side effects like pain sensation may be avoided. In the case of F3 – F4 electrode montage the maximum amplitude was 2.39 mA and in case of RS – LS montage the maximum amplitude was 2.44 mA. Such modeling studies may be useful for personalization of TES devices for finding optimal positioning of electrodes with respect to target and stimulation amplitude range that minimizes side effects.
ContributorsSahu, Sulagna (Author) / Sadleir, Rosalind (Thesis advisor) / Tillery, Stephen H (Committee member) / Crook, Sharon (Committee member) / Beeman, Scott (Committee member) / Abbas, James (Committee member) / Arizona State University (Publisher)
Created2023