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You searched for +publisher:"Georgia Tech" +contributor:("Stanley, Garrett B."). Showing records 1 – 23 of 23 total matches.

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1. Thourson, Scott. Conductive polymer microwires for single cell bioelectrical stimulation.

Degree: PhD, Mechanical Engineering, 2018, Georgia Tech

 There are currently no bioelectrical probes that are able to provide long-term electrical connections to a large population of single cells in the body. The… (more)

Subjects/Keywords: Conductive polymers; PEDOT:PSS; Microelectrodes; Microstimulation; Nanowires

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APA (6th Edition):

Thourson, S. (2018). Conductive polymer microwires for single cell bioelectrical stimulation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61621

Chicago Manual of Style (16th Edition):

Thourson, Scott. “Conductive polymer microwires for single cell bioelectrical stimulation.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/61621.

MLA Handbook (7th Edition):

Thourson, Scott. “Conductive polymer microwires for single cell bioelectrical stimulation.” 2018. Web. 24 Oct 2020.

Vancouver:

Thourson S. Conductive polymer microwires for single cell bioelectrical stimulation. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/61621.

Council of Science Editors:

Thourson S. Conductive polymer microwires for single cell bioelectrical stimulation. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/61621


Georgia Tech

2. Chong, Kelly K. Experience dependent coding of intonations by offsets in mouse auditory cortex.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2019, Georgia Tech

 Acoustic communication is an important aspect of many social interactions across mammalian species. The encoding of intra-species vocalizations and plasticity mechanisms engaged during the process… (more)

Subjects/Keywords: Neuroscience; Neural coding; Sensory; Auditory; Plasticity; Offset; Intonation; Frequency modulation; Encoding; Mouse; Cortex; Vocalization processing; Electrophysiology; Maternal; Sinusoidal frequency modulation

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APA (6th Edition):

Chong, K. K. (2019). Experience dependent coding of intonations by offsets in mouse auditory cortex. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62628

Chicago Manual of Style (16th Edition):

Chong, Kelly K. “Experience dependent coding of intonations by offsets in mouse auditory cortex.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/62628.

MLA Handbook (7th Edition):

Chong, Kelly K. “Experience dependent coding of intonations by offsets in mouse auditory cortex.” 2019. Web. 24 Oct 2020.

Vancouver:

Chong KK. Experience dependent coding of intonations by offsets in mouse auditory cortex. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/62628.

Council of Science Editors:

Chong KK. Experience dependent coding of intonations by offsets in mouse auditory cortex. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62628


Georgia Tech

3. Stoy, William Andrew. Automated single-cell electroporation and subcortical whole-cell recording in vivo.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2019, Georgia Tech

 Whole-cell patch clamping is uniquely suited to investigations of cell type and function in the living brain because of its stable intracellular access; however, the… (more)

Subjects/Keywords: Neuroscience; Patch clamp; Whole cell; Automation

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APA (6th Edition):

Stoy, W. A. (2019). Automated single-cell electroporation and subcortical whole-cell recording in vivo. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62632

Chicago Manual of Style (16th Edition):

Stoy, William Andrew. “Automated single-cell electroporation and subcortical whole-cell recording in vivo.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/62632.

MLA Handbook (7th Edition):

Stoy, William Andrew. “Automated single-cell electroporation and subcortical whole-cell recording in vivo.” 2019. Web. 24 Oct 2020.

Vancouver:

Stoy WA. Automated single-cell electroporation and subcortical whole-cell recording in vivo. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/62632.

Council of Science Editors:

Stoy WA. Automated single-cell electroporation and subcortical whole-cell recording in vivo. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62632


Georgia Tech

4. Borden, Peter Young. The impact of thalamic state on thalamocortical sensory processing.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2019, Georgia Tech

 The sensory thalamus controls the transmission of information from the periphery to the cortex and shapes our sensory percepts. While the thalamus receives prominent afferent… (more)

Subjects/Keywords: Neuroscience; Cortex; Thalamus; Cortical imaging; GEVI; ArcLight; Hyperpolarization; Thalamocortical

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APA (6th Edition):

Borden, P. Y. (2019). The impact of thalamic state on thalamocortical sensory processing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62679

Chicago Manual of Style (16th Edition):

Borden, Peter Young. “The impact of thalamic state on thalamocortical sensory processing.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/62679.

MLA Handbook (7th Edition):

Borden, Peter Young. “The impact of thalamic state on thalamocortical sensory processing.” 2019. Web. 24 Oct 2020.

Vancouver:

Borden PY. The impact of thalamic state on thalamocortical sensory processing. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/62679.

Council of Science Editors:

Borden PY. The impact of thalamic state on thalamocortical sensory processing. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62679


Georgia Tech

5. Zeller-Townson, Riley. Measurement of activity-dependent response to electrical stimulation in small unmyelinated axons.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2018, Georgia Tech

 One of the most fundamental aspects of neurophysiology is that neurons are electrically excitable- that is, provided the appropriate electrical or sensory stimulus, they will… (more)

Subjects/Keywords: Axon; Microelectrode array; Electrophysiology; Clinical neural stimulation

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APA (6th Edition):

Zeller-Townson, R. (2018). Measurement of activity-dependent response to electrical stimulation in small unmyelinated axons. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62202

Chicago Manual of Style (16th Edition):

Zeller-Townson, Riley. “Measurement of activity-dependent response to electrical stimulation in small unmyelinated axons.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/62202.

MLA Handbook (7th Edition):

Zeller-Townson, Riley. “Measurement of activity-dependent response to electrical stimulation in small unmyelinated axons.” 2018. Web. 24 Oct 2020.

Vancouver:

Zeller-Townson R. Measurement of activity-dependent response to electrical stimulation in small unmyelinated axons. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/62202.

Council of Science Editors:

Zeller-Townson R. Measurement of activity-dependent response to electrical stimulation in small unmyelinated axons. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/62202


Georgia Tech

6. Ollerenshaw, Douglas R. Adaptive information processing during detection and discrimination of tactile sensory stimuli.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2013, Georgia Tech

 Our sensory systems provide us with our ability to perceive and ultimately act upon the world around us. One of the challenges constantly placed on… (more)

Subjects/Keywords: Neuroscience; Sensory neurophysiology; Biomedical engineering

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APA (6th Edition):

Ollerenshaw, D. R. (2013). Adaptive information processing during detection and discrimination of tactile sensory stimuli. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52933

Chicago Manual of Style (16th Edition):

Ollerenshaw, Douglas R. “Adaptive information processing during detection and discrimination of tactile sensory stimuli.” 2013. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/52933.

MLA Handbook (7th Edition):

Ollerenshaw, Douglas R. “Adaptive information processing during detection and discrimination of tactile sensory stimuli.” 2013. Web. 24 Oct 2020.

Vancouver:

Ollerenshaw DR. Adaptive information processing during detection and discrimination of tactile sensory stimuli. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/52933.

Council of Science Editors:

Ollerenshaw DR. Adaptive information processing during detection and discrimination of tactile sensory stimuli. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/52933


Georgia Tech

7. Kodandaramaiah, Suhasa Bangalore. Robotics for in vivo whole cell patch clamping.

Degree: PhD, Mechanical Engineering, 2012, Georgia Tech

 Whole-cell patch clamp electrophysiology of neurons in vivo enables the recording of electrical events in cells with great precision, and supports a wide diversity of… (more)

Subjects/Keywords: Robotics; Neuroscience; Patch clamping; Patch-clamp techniques (Electrophysiology); Electrophysiology; Robotics in medicine

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APA (6th Edition):

Kodandaramaiah, S. B. (2012). Robotics for in vivo whole cell patch clamping. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/51932

Chicago Manual of Style (16th Edition):

Kodandaramaiah, Suhasa Bangalore. “Robotics for in vivo whole cell patch clamping.” 2012. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/51932.

MLA Handbook (7th Edition):

Kodandaramaiah, Suhasa Bangalore. “Robotics for in vivo whole cell patch clamping.” 2012. Web. 24 Oct 2020.

Vancouver:

Kodandaramaiah SB. Robotics for in vivo whole cell patch clamping. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/51932.

Council of Science Editors:

Kodandaramaiah SB. Robotics for in vivo whole cell patch clamping. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/51932


Georgia Tech

8. Whitmire, Clarissa. The role of thalamic state in dynamic tactile encoding.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2017, Georgia Tech

 Sensory pathways extract information about the local environment to guide our actions and behaviors. The internal representation of the outside world is built on patterns… (more)

Subjects/Keywords: Neural engineering; Somatosensation; Neural coding; Thalamocortical

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APA (6th Edition):

Whitmire, C. (2017). The role of thalamic state in dynamic tactile encoding. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59235

Chicago Manual of Style (16th Edition):

Whitmire, Clarissa. “The role of thalamic state in dynamic tactile encoding.” 2017. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/59235.

MLA Handbook (7th Edition):

Whitmire, Clarissa. “The role of thalamic state in dynamic tactile encoding.” 2017. Web. 24 Oct 2020.

Vancouver:

Whitmire C. The role of thalamic state in dynamic tactile encoding. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/59235.

Council of Science Editors:

Whitmire C. The role of thalamic state in dynamic tactile encoding. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59235


Georgia Tech

9. Zhu, Mengchen. Sparse coding models of neural response in the primary visual cortex.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2015, Georgia Tech

 Sparse coding is an influential unsupervised learning approach proposed as a theoretical model of the encoding process in the primary visual cortex (V1). While sparse… (more)

Subjects/Keywords: Computational neuroscience

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APA (6th Edition):

Zhu, M. (2015). Sparse coding models of neural response in the primary visual cortex. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53868

Chicago Manual of Style (16th Edition):

Zhu, Mengchen. “Sparse coding models of neural response in the primary visual cortex.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/53868.

MLA Handbook (7th Edition):

Zhu, Mengchen. “Sparse coding models of neural response in the primary visual cortex.” 2015. Web. 24 Oct 2020.

Vancouver:

Zhu M. Sparse coding models of neural response in the primary visual cortex. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/53868.

Council of Science Editors:

Zhu M. Sparse coding models of neural response in the primary visual cortex. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/53868


Georgia Tech

10. Norman, Sharon Elizabeth. Quantifying dynamics and variability in neural systems.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 Synchronized neural activity, in which the firing of neurons is coordinated in time, is an observed phenomenon in many neural functions. The conditions that promote… (more)

Subjects/Keywords: Phase resetting curve; Neurons; Variability; Computational neuroscience; Electrophysiology

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APA (6th Edition):

Norman, S. E. (2014). Quantifying dynamics and variability in neural systems. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54269

Chicago Manual of Style (16th Edition):

Norman, Sharon Elizabeth. “Quantifying dynamics and variability in neural systems.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/54269.

MLA Handbook (7th Edition):

Norman, Sharon Elizabeth. “Quantifying dynamics and variability in neural systems.” 2014. Web. 24 Oct 2020.

Vancouver:

Norman SE. Quantifying dynamics and variability in neural systems. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/54269.

Council of Science Editors:

Norman SE. Quantifying dynamics and variability in neural systems. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54269


Georgia Tech

11. Laxpati, Nealen G. Optogenetic dissection of septohippocampal neural circuitry for the treatment of epilepsy.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2015, Georgia Tech

 Over 50 million people worldwide suffer from epilepsy. Of these, nearly a third will be refractory to medical therapy, and many will be poor candidates… (more)

Subjects/Keywords: Optogenetics; Medial septum

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APA (6th Edition):

Laxpati, N. G. (2015). Optogenetic dissection of septohippocampal neural circuitry for the treatment of epilepsy. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54895

Chicago Manual of Style (16th Edition):

Laxpati, Nealen G. “Optogenetic dissection of septohippocampal neural circuitry for the treatment of epilepsy.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/54895.

MLA Handbook (7th Edition):

Laxpati, Nealen G. “Optogenetic dissection of septohippocampal neural circuitry for the treatment of epilepsy.” 2015. Web. 24 Oct 2020.

Vancouver:

Laxpati NG. Optogenetic dissection of septohippocampal neural circuitry for the treatment of epilepsy. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/54895.

Council of Science Editors:

Laxpati NG. Optogenetic dissection of septohippocampal neural circuitry for the treatment of epilepsy. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54895


Georgia Tech

12. Zheng, He. STATE-DEPENDENT INFORMATION PROCESSING IN THE RAT VIBRISSA PATHWAY.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2015, Georgia Tech

 To navigate the world, we must efficiently extract relevant information from complex sensory inputs to form perceptions and make decisions on a moment-to-moment basis. The… (more)

Subjects/Keywords: Somatosensory stimulus coding; sensory adaptation; brain state.

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APA (6th Edition):

Zheng, H. (2015). STATE-DEPENDENT INFORMATION PROCESSING IN THE RAT VIBRISSA PATHWAY. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56205

Chicago Manual of Style (16th Edition):

Zheng, He. “STATE-DEPENDENT INFORMATION PROCESSING IN THE RAT VIBRISSA PATHWAY.” 2015. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/56205.

MLA Handbook (7th Edition):

Zheng, He. “STATE-DEPENDENT INFORMATION PROCESSING IN THE RAT VIBRISSA PATHWAY.” 2015. Web. 24 Oct 2020.

Vancouver:

Zheng H. STATE-DEPENDENT INFORMATION PROCESSING IN THE RAT VIBRISSA PATHWAY. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/56205.

Council of Science Editors:

Zheng H. STATE-DEPENDENT INFORMATION PROCESSING IN THE RAT VIBRISSA PATHWAY. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/56205

13. Lu, Linlin. Soft carbon nanotube fiber electrodes for multimodal neural interfacing.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2019, Georgia Tech

 Electrodes made of stainless steel, noble metals and crystalline silicon have been widely used for neural recording and neural stimulation in neuroscience study and clinical… (more)

Subjects/Keywords: Chronic neural electrodes; Implantable neural electrodes; Brain computer interface; MRI compatible; Flexible neural electrodes; Multimodal neural electrodes

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APA (6th Edition):

Lu, L. (2019). Soft carbon nanotube fiber electrodes for multimodal neural interfacing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/61769

Chicago Manual of Style (16th Edition):

Lu, Linlin. “Soft carbon nanotube fiber electrodes for multimodal neural interfacing.” 2019. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/61769.

MLA Handbook (7th Edition):

Lu, Linlin. “Soft carbon nanotube fiber electrodes for multimodal neural interfacing.” 2019. Web. 24 Oct 2020.

Vancouver:

Lu L. Soft carbon nanotube fiber electrodes for multimodal neural interfacing. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/61769.

Council of Science Editors:

Lu L. Soft carbon nanotube fiber electrodes for multimodal neural interfacing. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/61769


Georgia Tech

14. Millard, Daniel C. Identification and control of neural circuit dynamics for natural and surrogate inputs in-vivo.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2014, Georgia Tech

 A principal goal of neural engineering is to control the activation of neural circuits across space and time. The ability to control neural circuits with… (more)

Subjects/Keywords: Electrical stimulation; Optogenetics; Voltage sensitive dye imaging; Sensory; Vibrissa; Nonlinear dynamics

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APA (6th Edition):

Millard, D. C. (2014). Identification and control of neural circuit dynamics for natural and surrogate inputs in-vivo. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53405

Chicago Manual of Style (16th Edition):

Millard, Daniel C. “Identification and control of neural circuit dynamics for natural and surrogate inputs in-vivo.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/53405.

MLA Handbook (7th Edition):

Millard, Daniel C. “Identification and control of neural circuit dynamics for natural and surrogate inputs in-vivo.” 2014. Web. 24 Oct 2020.

Vancouver:

Millard DC. Identification and control of neural circuit dynamics for natural and surrogate inputs in-vivo. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/53405.

Council of Science Editors:

Millard DC. Identification and control of neural circuit dynamics for natural and surrogate inputs in-vivo. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/53405


Georgia Tech

15. Bolus, Michael. Closed loop optogenetic control and thalamic state.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2020, Georgia Tech

 Dating as far back as the eighteenth century with Luigi Galvani's seminal studies in bioelectricity, interfacing with the nervous system at fast timescales has proven… (more)

Subjects/Keywords: Closed-loop; Feedback; Optogenetic; Neuroscience; Thalamus

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APA (6th Edition):

Bolus, M. (2020). Closed loop optogenetic control and thalamic state. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63661

Chicago Manual of Style (16th Edition):

Bolus, Michael. “Closed loop optogenetic control and thalamic state.” 2020. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/63661.

MLA Handbook (7th Edition):

Bolus, Michael. “Closed loop optogenetic control and thalamic state.” 2020. Web. 24 Oct 2020.

Vancouver:

Bolus M. Closed loop optogenetic control and thalamic state. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/63661.

Council of Science Editors:

Bolus M. Closed loop optogenetic control and thalamic state. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63661

16. Kornuta, Jeffrey Alan. Characterization of lymphatic pump function in response to mechanical loading.

Degree: PhD, Mechanical Engineering, 2014, Georgia Tech

 The lymphatic system is crucial for normal physiologic function, performing such basic functions as maintaining tissue fluid balance, trafficking immune cells, draining interstitial proteins, as… (more)

Subjects/Keywords: Lymphatic biomechanics; Vascular perfusion system; Model predictive control; Dynamic shear stress

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APA (6th Edition):

Kornuta, J. A. (2014). Characterization of lymphatic pump function in response to mechanical loading. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52208

Chicago Manual of Style (16th Edition):

Kornuta, Jeffrey Alan. “Characterization of lymphatic pump function in response to mechanical loading.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/52208.

MLA Handbook (7th Edition):

Kornuta, Jeffrey Alan. “Characterization of lymphatic pump function in response to mechanical loading.” 2014. Web. 24 Oct 2020.

Vancouver:

Kornuta JA. Characterization of lymphatic pump function in response to mechanical loading. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/52208.

Council of Science Editors:

Kornuta JA. Characterization of lymphatic pump function in response to mechanical loading. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52208

17. Kuykendal, Michelle Lea. Closed-loop optimization of extracellular electrical stimulation for targeted neuronal activation.

Degree: PhD, Electrical and Computer Engineering, 2014, Georgia Tech

 We have developed a high-throughput system of closed-loop electrical stimulation and optical recording that facilitates the rapid characterization of extracellular stimulus-evoked neural activity. The ability… (more)

Subjects/Keywords: Selective stimulation; Extracellular electrical stimulation; MEA; Microelectrode array; Optical recording; Stochastic response; Probabilistic activation

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APA (6th Edition):

Kuykendal, M. L. (2014). Closed-loop optimization of extracellular electrical stimulation for targeted neuronal activation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52303

Chicago Manual of Style (16th Edition):

Kuykendal, Michelle Lea. “Closed-loop optimization of extracellular electrical stimulation for targeted neuronal activation.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/52303.

MLA Handbook (7th Edition):

Kuykendal, Michelle Lea. “Closed-loop optimization of extracellular electrical stimulation for targeted neuronal activation.” 2014. Web. 24 Oct 2020.

Vancouver:

Kuykendal ML. Closed-loop optimization of extracellular electrical stimulation for targeted neuronal activation. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/52303.

Council of Science Editors:

Kuykendal ML. Closed-loop optimization of extracellular electrical stimulation for targeted neuronal activation. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/52303

18. Killian, Nathaniel J. Bioelectrical dynamics of the entorhinal cortex.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2013, Georgia Tech

 The entorhinal cortex (EC) in the medial temporal lobe plays a critical role in memory formation and is implicated in several neurological diseases including temporal… (more)

Subjects/Keywords: Spatial representation; Primate; Medial temporal lob; Entorhinal cortex; Hippocampus; Grid cell; Border cell; Memory; Saccade; Fixation; Visual; Stimulus; Saccade-direction cell; Encoding; Recognition; Macaque; Monkey; MTL; Perfusion; Perforated microelectrode array; Neurons; Brain slice; Three-dimensional culture; MEA

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APA (6th Edition):

Killian, N. J. (2013). Bioelectrical dynamics of the entorhinal cortex. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52148

Chicago Manual of Style (16th Edition):

Killian, Nathaniel J. “Bioelectrical dynamics of the entorhinal cortex.” 2013. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/52148.

MLA Handbook (7th Edition):

Killian, Nathaniel J. “Bioelectrical dynamics of the entorhinal cortex.” 2013. Web. 24 Oct 2020.

Vancouver:

Killian NJ. Bioelectrical dynamics of the entorhinal cortex. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/52148.

Council of Science Editors:

Killian NJ. Bioelectrical dynamics of the entorhinal cortex. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/52148

19. Gollnick, Clare Ann. Probabilistic encoding and feature selectivity in the somatosensory pathway.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2014, Georgia Tech

 Our sensory experiences are encoded in the patterns of activity of the neurons in our brain. While we know we are capable of sensing and… (more)

Subjects/Keywords: Neural code; Somatosensation; Barrel cortex

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APA (6th Edition):

Gollnick, C. A. (2014). Probabilistic encoding and feature selectivity in the somatosensory pathway. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54025

Chicago Manual of Style (16th Edition):

Gollnick, Clare Ann. “Probabilistic encoding and feature selectivity in the somatosensory pathway.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/54025.

MLA Handbook (7th Edition):

Gollnick, Clare Ann. “Probabilistic encoding and feature selectivity in the somatosensory pathway.” 2014. Web. 24 Oct 2020.

Vancouver:

Gollnick CA. Probabilistic encoding and feature selectivity in the somatosensory pathway. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/54025.

Council of Science Editors:

Gollnick CA. Probabilistic encoding and feature selectivity in the somatosensory pathway. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54025

20. Kelly, Sean T. Neural population coding of visual motion.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2014, Georgia Tech

 Motion in the outside world forms one of the primary uses of visual information for many animals. The ability to interpret motion quickly and accurately… (more)

Subjects/Keywords: Primary visual cortex; Neural coding; LGN; Orientation tuning; Natural scenes; Motion; Neural models; Computation neuroscience

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kelly, S. T. (2014). Neural population coding of visual motion. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54840

Chicago Manual of Style (16th Edition):

Kelly, Sean T. “Neural population coding of visual motion.” 2014. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/54840.

MLA Handbook (7th Edition):

Kelly, Sean T. “Neural population coding of visual motion.” 2014. Web. 24 Oct 2020.

Vancouver:

Kelly ST. Neural population coding of visual motion. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/54840.

Council of Science Editors:

Kelly ST. Neural population coding of visual motion. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54840

21. Thompson, Garth John. Neural basis and behavioral effects of dynamic resting state functional magnetic resonance imaging as defined by sliding window correlation and quasi-periodic patterns.

Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2013, Georgia Tech

 While task-based functional magnetic resonance imaging (fMRI) has helped us understand the functional role of many regions in the human brain, many diseases and complex… (more)

Subjects/Keywords: fMRI; Dynamic analysis; Sliding window; Sliding windows; Resting state; Default mode; Functional connectivity; Functional network; Correlation; Coherence; Functional magnetic resonance imaging; Local field potentials; LFP; Band-limited power; BLP; Inter-individual; Intra-individual; Spontaneous activity; Brain; Primary somatosensory cortex; Rodent; Rat; Human; Simultaneous experiments; Neural basis; Glial basis; Neurons; Astrocytes; Vasomotion; Hemodynamic response; Dynamic; Spatiotemporal dynamics; Quasi-periodic patterns; Brain networks; Resting state networks; Anesthesia; Dexmedetomidine; Isoflurane; Awake; Global signal; Magnetic resonance imaging; Brain Pathophysiology; Brain mapping

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Thompson, G. J. (2013). Neural basis and behavioral effects of dynamic resting state functional magnetic resonance imaging as defined by sliding window correlation and quasi-periodic patterns. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/49083

Chicago Manual of Style (16th Edition):

Thompson, Garth John. “Neural basis and behavioral effects of dynamic resting state functional magnetic resonance imaging as defined by sliding window correlation and quasi-periodic patterns.” 2013. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/49083.

MLA Handbook (7th Edition):

Thompson, Garth John. “Neural basis and behavioral effects of dynamic resting state functional magnetic resonance imaging as defined by sliding window correlation and quasi-periodic patterns.” 2013. Web. 24 Oct 2020.

Vancouver:

Thompson GJ. Neural basis and behavioral effects of dynamic resting state functional magnetic resonance imaging as defined by sliding window correlation and quasi-periodic patterns. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/49083.

Council of Science Editors:

Thompson GJ. Neural basis and behavioral effects of dynamic resting state functional magnetic resonance imaging as defined by sliding window correlation and quasi-periodic patterns. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/49083

22. Lin, Frank. Experience dependent changes in the auditory cortical representation of natural sounds.

Degree: PhD, Biomedical Engineering, 2012, Georgia Tech

 Vocal communication sounds are an important class of signals due to their role in social interaction, reproduction, and survival. The higher-order mechanisms by which our… (more)

Subjects/Keywords: Electrophysiology; Neural coding; Plasticity; Neuroscience; Auditory cortex; Auditory cortex; Auditory perception; Speech perception; Hearing

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APA (6th Edition):

Lin, F. (2012). Experience dependent changes in the auditory cortical representation of natural sounds. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/49015

Chicago Manual of Style (16th Edition):

Lin, Frank. “Experience dependent changes in the auditory cortical representation of natural sounds.” 2012. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/49015.

MLA Handbook (7th Edition):

Lin, Frank. “Experience dependent changes in the auditory cortical representation of natural sounds.” 2012. Web. 24 Oct 2020.

Vancouver:

Lin F. Experience dependent changes in the auditory cortical representation of natural sounds. [Internet] [Doctoral dissertation]. Georgia Tech; 2012. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/49015.

Council of Science Editors:

Lin F. Experience dependent changes in the auditory cortical representation of natural sounds. [Doctoral Dissertation]. Georgia Tech; 2012. Available from: http://hdl.handle.net/1853/49015

23. Holst, Gregory Leonard. In vivo serial patch clamp robotics for cell-type identification in the mouse visual cortex.

Degree: PhD, Mechanical Engineering, 2016, Georgia Tech

 Our ability to probe the immense complexity of the brain, with its approximately 80 billion neurons, is currently limited by the available tools to record… (more)

Subjects/Keywords: Electrophysiology; Patch-clamp; Neuroscience; Visual cortex; Layer 5; Robotics; Cell-type; Neuron

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Holst, G. L. (2016). In vivo serial patch clamp robotics for cell-type identification in the mouse visual cortex. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56270

Chicago Manual of Style (16th Edition):

Holst, Gregory Leonard. “In vivo serial patch clamp robotics for cell-type identification in the mouse visual cortex.” 2016. Doctoral Dissertation, Georgia Tech. Accessed October 24, 2020. http://hdl.handle.net/1853/56270.

MLA Handbook (7th Edition):

Holst, Gregory Leonard. “In vivo serial patch clamp robotics for cell-type identification in the mouse visual cortex.” 2016. Web. 24 Oct 2020.

Vancouver:

Holst GL. In vivo serial patch clamp robotics for cell-type identification in the mouse visual cortex. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2020 Oct 24]. Available from: http://hdl.handle.net/1853/56270.

Council of Science Editors:

Holst GL. In vivo serial patch clamp robotics for cell-type identification in the mouse visual cortex. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56270

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