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Description
Intracortical microstimulation (ICMS) within somatosensory cortex can produce artificial sensations including touch, pressure, and vibration. There is significant interest in using ICMS to provide sensory feedback for a prosthetic limb. In such a system, information recorded from sensors on the prosthetic would be translated into electrical stimulation and delivered directly

Intracortical microstimulation (ICMS) within somatosensory cortex can produce artificial sensations including touch, pressure, and vibration. There is significant interest in using ICMS to provide sensory feedback for a prosthetic limb. In such a system, information recorded from sensors on the prosthetic would be translated into electrical stimulation and delivered directly to the brain, providing feedback about features of objects in contact with the prosthetic. To achieve this goal, multiple simultaneous streams of information will need to be encoded by ICMS in a manner that produces robust, reliable, and discriminable sensations. The first segment of this work focuses on the discriminability of sensations elicited by ICMS within somatosensory cortex. Stimulation on multiple single electrodes and near-simultaneous stimulation across multiple electrodes, driven by a multimodal tactile sensor, were both used in these experiments. A SynTouch BioTac sensor was moved across a flat surface in several directions, and a subset of the sensor's electrode impedance channels were used to drive multichannel ICMS in the somatosensory cortex of a non-human primate. The animal performed a behavioral task during this stimulation to indicate the discriminability of sensations evoked by the electrical stimulation. The animal's responses to ICMS were somewhat inconsistent across experimental sessions but indicated that discriminable sensations were evoked by both single and multichannel ICMS. The factors that affect the discriminability of stimulation-induced sensations are not well understood, in part because the relationship between ICMS and the neural activity it induces is poorly defined. The second component of this work was to develop computational models that describe the populations of neurons likely to be activated by ICMS. Models of several neurons were constructed, and their responses to ICMS were calculated. A three-dimensional cortical model was constructed using these cell models and used to identify the populations of neurons likely to be recruited by ICMS. Stimulation activated neurons in a sparse and discontinuous fashion; additionally, the type, number, and location of neurons likely to be activated by stimulation varied with electrode depth.
ContributorsOverstreet, Cynthia K (Author) / Helms Tillery, Stephen I (Thesis advisor) / Santos, Veronica (Committee member) / Buneo, Christopher (Committee member) / Otto, Kevin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Learning by trial-and-error requires retrospective information that whether a past action resulted in a rewarded outcome. Previous outcome in turn may provide information to guide future behavioral adjustment. But the specific contribution of this information to learning a task and the neural representations during the trial-and-error learning process is not

Learning by trial-and-error requires retrospective information that whether a past action resulted in a rewarded outcome. Previous outcome in turn may provide information to guide future behavioral adjustment. But the specific contribution of this information to learning a task and the neural representations during the trial-and-error learning process is not well understood. In this dissertation, such learning is analyzed by means of single unit neural recordings in the rats' motor agranular medial (AGm) and agranular lateral (AGl) while the rats learned to perform a directional choice task. Multichannel chronic recordings using implanted microelectrodes in the rat's brain were essential to this study. Also for fundamental scientific investigations in general and for some applications such as brain machine interface, the recorded neural waveforms need to be analyzed first to identify neural action potentials as basic computing units. Prior to analyzing and modeling the recorded neural signals, this dissertation proposes an advanced spike sorting system, the M-Sorter, to extract the action potentials from raw neural waveforms. The M-Sorter shows better or comparable performance compared with two other popular spike sorters under automatic mode. With the sorted action potentials in place, neuronal activity in the AGm and AGl areas in rats during learning of a directional choice task is examined. Systematic analyses suggest that rat's neural activity in AGm and AGl was modulated by previous trial outcomes during learning. Single unit based neural dynamics during task learning are described in detail in the dissertation. Furthermore, the differences in neural modulation between fast and slow learning rats were compared. The results show that the level of neural modulation of previous trial outcome is different in fast and slow learning rats which may in turn suggest an important role of previous trial outcome encoding in learning.
ContributorsYuan, Yu'an (Author) / Si, Jennie (Thesis advisor) / Buneo, Christopher (Committee member) / Santello, Marco (Committee member) / Chae, Junseok (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Animals learn to choose a proper action among alternatives according to the circumstance. Through trial-and-error, animals improve their odds by making correct association between their behavioral choices and external stimuli. While there has been an extensive literature on the theory of learning, it is still unclear how individual neurons and

Animals learn to choose a proper action among alternatives according to the circumstance. Through trial-and-error, animals improve their odds by making correct association between their behavioral choices and external stimuli. While there has been an extensive literature on the theory of learning, it is still unclear how individual neurons and a neural network adapt as learning progresses. In this dissertation, single units in the medial and lateral agranular (AGm and AGl) cortices were recorded as rats learned a directional choice task. The task required the rat to make a left/right side lever press if a light cue appeared on the left/right side of the interface panel. Behavior analysis showed that rat's movement parameters during performance of directional choices became stereotyped very quickly (2-3 days) while learning to solve the directional choice problem took weeks to occur. The entire learning process was further broken down to 3 stages, each having similar number of recording sessions (days). Single unit based firing rate analysis revealed that 1) directional rate modulation was observed in both cortices; 2) the averaged mean rate between left and right trials in the neural ensemble each day did not change significantly among the three learning stages; 3) the rate difference between left and right trials of the ensemble did not change significantly either. Besides, for either left or right trials, the trial-to-trial firing variability of single neurons did not change significantly over the three stages. To explore the spatiotemporal neural pattern of the recorded ensemble, support vector machines (SVMs) were constructed each day to decode the direction of choice in single trials. Improved classification accuracy indicated enhanced discriminability between neural patterns of left and right choices as learning progressed. When using a restricted Boltzmann machine (RBM) model to extract features from neural activity patterns, results further supported the idea that neural firing patterns adapted during the three learning stages to facilitate the neural codes of directional choices. Put together, these findings suggest a spatiotemporal neural coding scheme in a rat AGl and AGm neural ensemble that may be responsible for and contributing to learning the directional choice task.
ContributorsMao, Hongwei (Author) / Si, Jennie (Thesis advisor) / Buneo, Christopher (Committee member) / Cao, Yu (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Approximately 1.7 million people in the United States are living with limb loss and are in need of more sophisticated devices that better mimic human function. In the Human Machine Integration Laboratory, a powered, transtibial prosthetic ankle was designed and build that allows a person to regain ankle function with

Approximately 1.7 million people in the United States are living with limb loss and are in need of more sophisticated devices that better mimic human function. In the Human Machine Integration Laboratory, a powered, transtibial prosthetic ankle was designed and build that allows a person to regain ankle function with improved ankle kinematics and kinetics. The ankle allows a person to walk normally and up and down stairs, but volitional control is still an issue. This research tackled the problem of giving the user more control over the prosthetic ankle using a force/torque circuit. When the user presses against a force/torque sensor located inside the socket the prosthetic foot plantar flexes or moves downward. This will help the user add additional push-off force when walking up slopes or stairs. It also gives the user a sense of control over the device.
ContributorsFronczyk, Adam (Author) / Sugar, Thomas G. (Thesis advisor) / Helms-Tillery, Stephen (Thesis advisor) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Locomotion is of prime importance in enabling human beings to effectively respond

in space and time to meet different needs. Approximately 2 million Americans live

with an amputation with most of those amputations being of the lower limbs. To

advance current state-of-the-art lower limb prosthetic devices, it is necessary to adapt

performance at a

Locomotion is of prime importance in enabling human beings to effectively respond

in space and time to meet different needs. Approximately 2 million Americans live

with an amputation with most of those amputations being of the lower limbs. To

advance current state-of-the-art lower limb prosthetic devices, it is necessary to adapt

performance at a level of intelligence seen in human walking. As such, this thesis

focuses on the mechanisms involved during human walking, while transitioning from

rigid to compliant surfaces such as from pavement to sand, grass or granular media.

Utilizing a unique tool, the Variable Stiffness Treadmill (VST), as the platform for

human walking, rigid to compliant surface transitions are simulated. The analysis of

muscular activation during the transition from rigid to different compliant surfaces

reveals specific anticipatory muscle activation that precedes stepping on a compliant

surface. There is also an indication of varying responses for different surface stiffness

levels. This response is observed across subjects. Results obtained are novel and

useful in establishing a framework for implementing control algorithm parameters to

improve powered ankle prosthesis. With this, it is possible for the prosthesis to adapt

to a new surface and therefore resulting in a more robust smart powered lower limb

prosthesis.
ContributorsObeng, Ruby Afriyie (Author) / Artemiadis, Panagiotis (Thesis advisor) / Santello, Marco (Thesis advisor) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2019
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Description
A previous study demonstrated that learning to lift an object is context-based and that in the presence of both the memory and visual cues, the acquired sensorimotor memory to manipulate an object in one context interferes with the performance of the same task in presence of visual information about a

A previous study demonstrated that learning to lift an object is context-based and that in the presence of both the memory and visual cues, the acquired sensorimotor memory to manipulate an object in one context interferes with the performance of the same task in presence of visual information about a different context (Fu et al, 2012).
The purpose of this study is to know whether the primary motor cortex (M1) plays a role in the sensorimotor memory. It was hypothesized that temporary disruption of the M1 following the learning to minimize a tilt using a ‘L’ shaped object would negatively affect the retention of sensorimotor memory and thus reduce interference between the memory acquired in one context and the visual cues to perform the same task in a different context.
Significant findings were shown in blocks 1, 2, and 4. In block 3, subjects displayed insignificant amount of learning. However, it cannot be concluded that there is full interference in block 3. Therefore, looked into 3 effects in statistical analysis: the main effects of the blocks, the main effects of the trials, and the effects of the blocks and trials combined. From the block effects, there is a p-value of 0.001, and from the trial effects, the p-value is less than 0.001. Both of these effects indicate that there is learning occurring. However, when looking at the blocks * trials effects, we see a p-value of 0.002 < 0.05 indicating significant interaction between sensorimotor memories. Based on the results that were found, there is a presence of interference in all the blocks but not enough to justify the use of TMS in order to reduce interference because there is a partial reduction of interference from the control experiment. It is evident that the time delay might be the issue between context switches. By reducing the time delay between block 2 and 3 from 10 minutes to 5 minutes, I will hope to see significant learning to occur from the first trial to the second trial.
ContributorsHasan, Salman Bashir (Author) / Santello, Marco (Thesis director) / Kleim, Jeffrey (Committee member) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / W. P. Carey School of Business (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
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Description
Brain-computer interface technology establishes communication between the brain and a computer, allowing users to control devices, machines, or virtual objects using their thoughts. This study investigates optimal conditions to facilitate learning to operate this interface. It compares two biofeedback methods, which dictate the relationship between brain activity and the movement

Brain-computer interface technology establishes communication between the brain and a computer, allowing users to control devices, machines, or virtual objects using their thoughts. This study investigates optimal conditions to facilitate learning to operate this interface. It compares two biofeedback methods, which dictate the relationship between brain activity and the movement of a virtual ball in a target-hitting task. Preliminary results indicate that a method in which the position of the virtual object directly relates to the amplitude of brain signals is most conducive to success. In addition, this research explores learning in the context of neural signals during training with a BCI task. Specifically, it investigates whether subjects can adapt to parameters of the interface without guidance. This experiment prompts subjects to modulate brain signals spectrally, spatially, and temporally, as well differentially to discriminate between two different targets. However, subjects are not given knowledge regarding these desired changes, nor are they given instruction on how to move the virtual ball. Preliminary analysis of signal trends suggests that some successful participants are able to adapt brain wave activity in certain pre-specified locations and frequency bands over time in order to achieve control. Future studies will further explore these phenomena, and future BCI projects will be advised by these methods, which will give insight into the creation of more intuitive and reliable BCI technology.
ContributorsLancaster, Jenessa Mae (Co-author) / Appavu, Brian (Co-author) / Wahnoun, Remy (Co-author, Committee member) / Helms Tillery, Stephen (Thesis director) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / Department of Psychology (Contributor)
Created2014-05
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Description
Menopause is associated with a wide array of negative symptoms. As average lifespan increases due to advances in healthcare and technology, more women are spending a larger portion of their lives in a menopausal state low in estrogen and progesterone. Hormone therapies such as Conjugated Equine Estrogens (CEE) and the

Menopause is associated with a wide array of negative symptoms. As average lifespan increases due to advances in healthcare and technology, more women are spending a larger portion of their lives in a menopausal state low in estrogen and progesterone. Hormone therapies such as Conjugated Equine Estrogens (CEE) and the bioidentical estrogen, 17-estradiol (E2), are commonly prescribed to treat the negative symptoms of menopause. Our laboratory has previously shown that CEE has differential effects on cognitive ability depending on whether menopause is transitional (VCD) or surgical (ovariectomy, OVX). Further, the negative impact of CEE on cognitive function in a transitional ovary-intact model of menopause was associated with high levels of serum androstenedione; the primary hormone circulating in a follicle-deplete menopausal state. Here, we investigate the cognitive effects of these two common hormone therapies separately, and in conjunction with the hormone androstenedione, in a "blank-slate" OVX mouse model. We assessed cognitive ability using two behavioral tasks such at the Water Radial Arm Maze (WRAM, measuring spatial working and reference memory) and the Morris water maze (MM, measuring spatial reference memory). In the WRAM, every treatment group saw impaired performance compared to Vehicle but the combination group of E2 plus Androstenedione. In the MM, the combination group of E2 plus Androstenedione actually enhanced performance in the maze compared to every other comparable group. Translationally, these results suggest that CEE given in the presence of an androstenedione-dominant hormone milieu is impairing to cognition, E2 in this same manner is not. These results yield valuable insight into optimal hormone therapies for menopausal women.
ContributorsGranger, Steven Jay (Author) / Bimonte-Nelson, Heather (Thesis director) / Presson, Clark (Committee member) / Hiroi, Sheri (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Drospirenone (DRSP) is a novel, pharmacologically unique synthetic progestin with properties more similar to the endogenous progestogen, progesterone, than any other progestin currently on the market. While a significant amount of research has been conducted on the risks associated with DRSP, the impact of DRSP on cognition, especially in reference

Drospirenone (DRSP) is a novel, pharmacologically unique synthetic progestin with properties more similar to the endogenous progestogen, progesterone, than any other progestin currently on the market. While a significant amount of research has been conducted on the risks associated with DRSP, the impact of DRSP on cognition, especially in reference to learning and memory, is not well understood. However, it is imperative to fully understand the cognitive effects of DRSP, both alone and in combination with EE (as taken in a combined oral contraceptive [COC]), so that women and their physicians can make a fully-informed decision when deciding to take a DRSP-containing COC. Study 1 examined the effects of three doses of DRSP in order to determine the optimal dose for combining with EE, and found that the medium dose of DRSP (30 µg/day) enhanced spatial working memory performance. In Study 2, the medium dose of DRSP from Study 1 was combined with low (0.125 µg/day) and high (0.3 µg/day) doses of EE to examine the effects of DRSP as taken with EE in a COC. The results from Study 2 indicated that when DRSP was combined with a low, but not high, dose of EE, spatial working memory impairments were seen at the highest working memory load. Anxiety-like behavior was evaluated using the OFT, and DRSP was shown to decrease measures of anxiety-like behavior. Additionally, while treatment with a high dose of EE decreased several measures of anxiety-like behavior, a low dose of EE did not, suggestive of a dose response. Taken together, the findings presented from both studies suggest that some of the cognitive effects of the combination of DRSP with EE are different than those of either hormone administered on its own. Further exploration in a preclinical, ovary-intact animal model is a next step to fully understand these effects in the translational context of a contraceptive, given that women taking an EE-DRSP combination are typically ovary-intact.
ContributorsPoisson, Mallori Louise (Author) / Bimonte-Nelson, Heather (Thesis director) / Doane, Leah (Committee member) / School of Nutrition and Health Promotion (Contributor) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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Description
Estradiol (E2) and Levonorgestrel (Levo) are two hormones commonly used in hormone therapy (HT) to decrease symptoms associated with menopause. Both of these hormones have been shown to have beneficial effects on cognition when given alone in a rodent model of menopause. However, it is unknown whether these hormones, when

Estradiol (E2) and Levonorgestrel (Levo) are two hormones commonly used in hormone therapy (HT) to decrease symptoms associated with menopause. Both of these hormones have been shown to have beneficial effects on cognition when given alone in a rodent model of menopause. However, it is unknown whether these hormones, when taken in combination, are beneficial or harmful to cognition. This is a critically important question given that these hormones are most often given in combination versus separately. This thesis is composed of two studies examining the cognitive effects of E2 and Levo using a rat model of surgical menopause. Study 1 assessed how the dose of E2 treatment in rats impacted cognitive performance, and found that low dose E2 enhanced working memory performance. Next, based on the results from Study 1, Study 2 used low dose E2 in combination with different doses of Levo to examine the cognitive effects of several E2 to Levo ratio combinations. The results from Study 2 demonstrated that the combination of low dose E2 with a high dose of Levo at a 1:2 ratio impaired cognition, and that the ratio currently used in HT, 3:1, may also negatively impact cognition. Indeed, there was a dose response effect indicating that working and reference memory performance was incrementally impaired as Levo dose increased. The findings in this thesis suggest that the E2 plus Levo combination is likely not neutral for cognitive function, and prompts further evaluation in menopausal women, as well as drug discovery research to optimize HT using highly controlled preclinical models.
ContributorsBerns-Leone, Claire Elizabeth (Co-author) / Prakapenka, Alesia (Co-author) / Pena, Veronica (Co-author) / Northup-Smith, Steven (Co-author) / Melikian, Ryan (Co-author) / Ladwig, Ducileia (Co-author) / Patel, Shruti (Co-author) / Croft, Corissa (Co-author) / Bimonte-Nelson, Heather (Thesis director) / Glenberg, Arthur (Committee member) / Conrad, Cheryl (Committee member) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12