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- Title
- Dynamics of human sensorimotor coordination: From behavior to brain activity.
- Creator
- Chen, Yanqing, Florida Atlantic University, Ding, Mingzhou, Kelso, J. A. Scott
- Abstract/Description
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The dynamics of human sensorimotor coordination are studied at behavioral and neural levels through temporal synchronization and syncopation tasks. In experiment 1, subjects synchronized their finger movements (in-phase) with a metronome at 2.0Hz and 1.25Hz for 1200 cycles. Fluctuations of timing errors were analyzed through correlation, power spectrum analyses and Maximum Likelihood Estimation (MLE). Results indicated that the synchronization error time series was characterized by a 1/falpha...
Show moreThe dynamics of human sensorimotor coordination are studied at behavioral and neural levels through temporal synchronization and syncopation tasks. In experiment 1, subjects synchronized their finger movements (in-phase) with a metronome at 2.0Hz and 1.25Hz for 1200 cycles. Fluctuations of timing errors were analyzed through correlation, power spectrum analyses and Maximum Likelihood Estimation (MLE). Results indicated that the synchronization error time series was characterized by a 1/falpha type of long memory process with alpha = 0.5. Previous timing models based upon motor program or simple "central clock" ideas were reviewed to show that they could not explain such long range correlations in the synchronization task. To explore the possible cognitive origins of long range correlation, experiment 2 required subjects to synchronize (on the beat) or syncopate (off the beat) to a metronome at 1Hz using different cognitive strategies. Timing fluctuations were again found to be 1/f alpha type, with alpha = 0.5 in synchronization and alpha = 0.8 in syncopation. When subjects employed a synchronization strategy to successfully syncopate, timing fluctuations shifted toward 1/f 0.5 type. This experiment indicated that the scaling exponent in timing fluctuations was related to task requirements and specific coordination strategies. Further, they suggest that the sources of such long memory originated from higher level cognitive processing in the human brain. Experiment 3 analyzed magnetoencephalography (MEG) data associated with synchronization and syncopation tasks. Brain oscillations at alpha (8--14Hz), beta (15--20Hz) and gamma (35--40Hz) frequency ranges were shown to correlate with different aspects of the coordination behavior. Specifically, through power and coherence analyses, alpha activity was linked to sensorimotor integration and "binding", beta activity was related to task requirements (synchronization or syncopation), and gamma activity was related to movement kinematics (trajectory). These results supported the idea that the 1/f alpha type of timing fluctuations originated from collective neural activities in the brain acting on multiple time scales.
Show less - Date Issued
- 2000
- PURL
- http://purl.flvc.org/fcla/dt/12649
- Subject Headings
- Sensorimotor integration, Cognitive neuroscience
- Format
- Document (PDF)
- Title
- A DISINHIBITORY MICROCIRCUIT FOR GATED CEREBELLAR LEARNING.
- Creator
- Zhang, Ke, Christie, Jason, Dawson-Scully, Ken, Florida Atlantic University, Department of Biological Sciences, Charles E. Schmidt College of Science
- Abstract/Description
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Performance motor errors trigger animals’ adaptive learning behaviors to improve the accuracy and efficiency of the movement. The cerebellum is one of the key brain centers for encoding motor performance and motor learning. Climbing fibers relay information related to motor errors to the cerebellar cortex, evoking elevation of intracellular Ca2+ signals at Purkinje cell dendrites and inducing plasticity at coactive parallel fiber synapses, ultimately recalibrating sensorimotor associations to...
Show morePerformance motor errors trigger animals’ adaptive learning behaviors to improve the accuracy and efficiency of the movement. The cerebellum is one of the key brain centers for encoding motor performance and motor learning. Climbing fibers relay information related to motor errors to the cerebellar cortex, evoking elevation of intracellular Ca2+ signals at Purkinje cell dendrites and inducing plasticity at coactive parallel fiber synapses, ultimately recalibrating sensorimotor associations to alter behavior. Molecular layer interneurons (MLIs) inhibit Purkinje cells to modulate dendritic excitability and action potential output. How MLIs contribute to the regulation and encoding of climbing fiber-evoked adaptive movements remains poorly understood. In this dissertation, I used genetic tools to manipulate the activity of MLIs while monitoring Purkinje cell dendritic activity during a cerebellum-dependent motor learning task with different contexts to evaluate how MLIs are involved in this process. The results show that by suppressing dendritic Ca2+ signals in Purkinje cells, MLI activity coincident with climbing fiber-mediated excitation prevents the occurrence of learning when adaptation is not necessary. On the other hand, with error signals present, disinhibition onto Purkinje cells, mediated by MLI-MLI microcircuit, unlocked the ability of climbing fibers to induce plasticity and motor learning.
Show less - Date Issued
- 2020
- PURL
- http://purl.flvc.org/fau/fd/FA00013526
- Subject Headings
- Cerebellum, Interneurons, Purkinje cells, Dendrites, Sensorimotor integration, Neuroplasticity
- Format
- Document (PDF)
- Title
- Detecting the spatiotemporal dynamics of neural activity on the cortical surface: applying anatomically constrained beamforming to EEG.
- Creator
- Murzin, Vyacheslav., Charles E. Schmidt College of Science, Department of Physics
- Abstract/Description
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The neurophysiological signals that are recorded in EEG (electroencephalography) and MEG (magnetoencephalography) originate from current flow perpendicular to the cortical surface due to the columnar organization of pyramidal cells in the cortical gray matter. These locations and directions have been used as anatomical constraints for dipolar sources in estimations of neural activity from MEG recordings. Here we extend anatomically constrained beamforming to EEG, which requires a more...
Show moreThe neurophysiological signals that are recorded in EEG (electroencephalography) and MEG (magnetoencephalography) originate from current flow perpendicular to the cortical surface due to the columnar organization of pyramidal cells in the cortical gray matter. These locations and directions have been used as anatomical constraints for dipolar sources in estimations of neural activity from MEG recordings. Here we extend anatomically constrained beamforming to EEG, which requires a more sophisticated forward model than MEG due to the blurring of the electric potential at tissue boundaries, but in contrast to MEG, EEG can account for both tangential and radial sources. Using computed tomography (CT) scans we create a realistic three-layer head model consisting of tessellated surfaces representing the tissue boundaries cerebrospinal fluid-skull, skull-scalp and scalp-air. The cortical gray matter surface, the anatomical constraint for the source dipoles, is extracted from magnetic resonance imaging (MRI) scans. EEG beamforming is implemented in a set of simulated data and compared for three different head models: single sphere, multi-shell sphere and realistic geometry multi-shell model that employs a boundary element method. Beamformer performance is also analyzed and evaluated for multiple dipoles and extended sources (patches). We show that using anatomical constraints with the beamforming algorithm greatly reduces computation time while increasing the spatial accuracy of the reconstructed sources of neural activity. Using the spatial Laplacian instead of the electric potential in combination with beamforming further improves the spatial resolution and allows for the detection of highly correlated sources.
Show less - Date Issued
- 2010
- PURL
- http://purl.flvc.org/FAU/1930497
- Subject Headings
- Sensorimotor integration, Brain mapping, Perceptual-motor processes
- Format
- Document (PDF)
- Title
- ARTIFICIAL INTELLIGENCE (AI) ENABLES SENSORIMOTOR INTEGRATION FOR PROSTHETIC HAND DEXTERITY.
- Creator
- Abd, Moaed A., Engeberg, Erik D., Florida Atlantic University, Department of Ocean and Mechanical Engineering, College of Engineering and Computer Science
- Abstract/Description
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Hand amputation is a devastating feeling for amputees, and it is lifestyle changing since it is challenging to perform the basic life activities with amputation. Hand amputation means interrupting the closed loop between sensory feedback and motor control. The absence of sensory feedback requires a significant cognitive effort from the amputee to perform basic daily activities with prosthetic hand. Loss of tactile sensations is a major roadblock preventing amputees from multitasking or using...
Show moreHand amputation is a devastating feeling for amputees, and it is lifestyle changing since it is challenging to perform the basic life activities with amputation. Hand amputation means interrupting the closed loop between sensory feedback and motor control. The absence of sensory feedback requires a significant cognitive effort from the amputee to perform basic daily activities with prosthetic hand. Loss of tactile sensations is a major roadblock preventing amputees from multitasking or using the full dexterity of their prosthetic hands. One of the most significant features lacking from commercial prosthetic hands is sensory feedback, according to amputees. Many amputees abandoned their prosthetic devices due to the lack of tactile feedback. In the field of prosthetics, restoring sensory feedback is the most challenging task due to the complexity of integration between the prosthetic and the peripheral nervous system. A prosthetic hand with sensory feedback that imitates the intact hand would improve the lives of millions of amputees worldwide by inducing the prosthetic hand to be a part of the body image and significant impact the control of the prosthetic. To restore the sensory feedback and improve the dexterity for upper limb amputee, multiple components needed to be integrated together to provide the sensory feedback. Tactile sensors are the first components that needed to be integrated into the sensorimotor loop. In this research two tactile sensors were integrated in the sensory feedback loop. The first tactile sensor is BioTac which is a commercially available sensor. The first novel contribution with BioTac is the development of an ANN classifier to detect the direction a grasped object slips in a dexterous robotic hand in real time, and the second novel aspect of this study is the use of slip direction detection for adaptive robotic grasp reflexes. The second tactile sensor is the liquid metal sensor (LMS), this sensor was developed entirely in our lab (BioRobotics lab). The novel contribution for LMS is to detect and prevent slip in real time application, and to recognize different surface features and different sliding speeds.
Show less - Date Issued
- 2022
- PURL
- http://purl.flvc.org/fau/fd/FA00013875
- Subject Headings
- Artificial intelligence, Haptic devices, Tactile sensors, Sensorimotor integration, Artificial hands
- Format
- Document (PDF)
- Title
- Learning to match faces and voices.
- Creator
- Davidson, Meredith., Charles E. Schmidt College of Science, Department of Psychology
- Abstract/Description
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This study examines whether forming a single identity is crucial to learning to bind faces and voices, or if people are equally able to do so without tying this information to an identity. To test this, individuals learned paired faces and voices that were in one of three different conditions: True voice, Gender Matched, or Gender Mismatched conditions. Performance was measured in a training phase as well as a test phase, and results show that participants were able to learn more quickly and...
Show moreThis study examines whether forming a single identity is crucial to learning to bind faces and voices, or if people are equally able to do so without tying this information to an identity. To test this, individuals learned paired faces and voices that were in one of three different conditions: True voice, Gender Matched, or Gender Mismatched conditions. Performance was measured in a training phase as well as a test phase, and results show that participants were able to learn more quickly and have higher overall performance for learning in the True Voice and Gender Matched conditions. During the test phase, performance was almost at chance in the Gender Mismatched condition which may mean that learning in the training phase was simply memorization of the pairings for this condition. Results support the hypothesis that learning to bind faces and voices is a process that involves forming a supramodal identity from multisensory learning.
Show less - Date Issued
- 2010
- PURL
- http://purl.flvc.org/FAU/2683140
- Subject Headings
- Sensorimotor integration, Senses and sensation, Intersensory effects, Perceptual learning, Pattern recognition systems
- Format
- Document (PDF)
- Title
- Theoretical and experimental studies of multisensory integration as a coupled dynamical system.
- Creator
- Assisi, Collins G., Florida Atlantic University, Kelso, J. A. Scott, Jirsa, Viktor K.
- Abstract/Description
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Perception and behavior are mediated by a widely distributed network of brain areas. Our main concern is, how do the components of the network interact in order to give us a variety of complex coordinated behavior? We first define the nodes of the network, termed functional units, as a strongly coupled ensemble of non-identical neurons and demonstrate that the dynamics of such an ensemble may be approximated by a low dimensional set of equations. The dynamics is studied in two different...
Show morePerception and behavior are mediated by a widely distributed network of brain areas. Our main concern is, how do the components of the network interact in order to give us a variety of complex coordinated behavior? We first define the nodes of the network, termed functional units, as a strongly coupled ensemble of non-identical neurons and demonstrate that the dynamics of such an ensemble may be approximated by a low dimensional set of equations. The dynamics is studied in two different contexts, sensorimotor coordination and multisensory integration. First, we treat movement coupled to the environment as a driven functional unit. Our central hypothesis is that this coupling must be minimally parametric. We demonstrate the experimental validity of this hypothesis and propose a theoretical model that explains the results of our experiment. A second example of the dynamics of functional units is evident in the domain of multisensory integration. We employ a novel rhythmic multisensory paradigm designed to capture the temporal features of multisensory integration parametrically. The relevant parameters of our experiment are the inter-onset interval between pairs of rhythmically presented stimuli and the frequency of presentation. We partition the two dimensional parameter space using subjects perception of the stimulus sequence. The general features of the partitioning are modality independent suggesting that these features depend on the coupling between the unisensory subsystems. We develop a model with coupled functional units and suggest a candidate coupling scheme. In subsequent chapters we probe the neural correlates of multisensory integration using fMRI and EEG. The results of our fMRI experiment demonstrate that multisensory integration is mediated by a network consisting of primary sensory areas, inferior parietal lobule, prefrontal areas and the posterior midbrain. Different percepts lead to the recruitment of different areas and their disengagement for other percepts. In analyzing the EEG data, we first develop a mathematical framework that allows us to differentiate between sources activated for both unisensory and multisensory stimulation from those sources activated only for multisensory stimulation. Using this methodology we show that the influences of multisensory processing may be seen at an early (40--60 ms) stage of sensory processing.
Show less - Date Issued
- 2005
- PURL
- http://purl.flvc.org/fcla/dt/12167
- Subject Headings
- Intersensory effects, Perceptual-motor processes, Sensorimotor integration, Psychology, Comparative, Developmental neurobiology
- Format
- Document (PDF)
- Title
- Perceptions of the environment: an ethnographic study of sensory awareness and environmental activism among south Florida yoga practitioners.
- Creator
- Weisner, Meagan L., Cameron, Mary, Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Department of Anthropology
- Abstract/Description
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The practice of yoga is an increasingly popularized movement within the West that incorporates the desire for physical fitness, spiritual consciousness, and environmentalism. Emanating from the New Age movement, the popularity of yoga has proliferated as a subculture that seeks to encourage mind–body wellbeing while representing an ethos that assumes environmental responsibility. This thesis examines the techniques of modern yoga and the influence that asana (posture) and meditational...
Show moreThe practice of yoga is an increasingly popularized movement within the West that incorporates the desire for physical fitness, spiritual consciousness, and environmentalism. Emanating from the New Age movement, the popularity of yoga has proliferated as a subculture that seeks to encourage mind–body wellbeing while representing an ethos that assumes environmental responsibility. This thesis examines the techniques of modern yoga and the influence that asana (posture) and meditational relaxation have on the senses and subsequently on environmental awareness and activism.
Show less - Date Issued
- 2015
- PURL
- http://purl.flvc.org/fau/fd/FA00004418, http://purl.flvc.org/fau/fd/FA00004418
- Subject Headings
- Cognition and culture, Environmental psychology, Mind and body, Movement therapy, Philosophy of mind, Self consciousness (Awareness), Senses and sensation, Sensorimotor integration, Yoga
- Format
- Document (PDF)
- Title
- Afferent projections to rhomboid nucleus of thalamus.
- Creator
- Owens, Michelle Ann, Florida Atlantic University, Vertes, Robert P.
- Abstract/Description
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The midline thalamus of rats is anatomically and functionally part of the "limbic" thalamus. The midline thalamic rhomboid nucleus (RH) has not been well characterized. The rhomboid nucleus is located just dorsal to the reuniens nucleus (RE), and just ventral to the central medial nucleus (CeM) of the thalamus. Using the retrograde tracer fluorogold (FG) and anti-FG antibody, we examined afferent projections to RH in the rat. Control injections were also made in CeM and the submedial nucleus...
Show moreThe midline thalamus of rats is anatomically and functionally part of the "limbic" thalamus. The midline thalamic rhomboid nucleus (RH) has not been well characterized. The rhomboid nucleus is located just dorsal to the reuniens nucleus (RE), and just ventral to the central medial nucleus (CeM) of the thalamus. Using the retrograde tracer fluorogold (FG) and anti-FG antibody, we examined afferent projections to RH in the rat. Control injections were also made in CeM and the submedial nucleus of thalamus (SMT). The main sources of input to RH were from the anterior cingulate, agranular insular, orbital, and somatosensory cortices; the claustrum; the reticular nucleus of the thalamus; the posterior hypothalamus; and various brainstem structures. Based on patterns of the afferent projections, the role of RH in arousal, attention, and mnemonic functions is discussed.
Show less - Date Issued
- 2005
- PURL
- http://purl.flvc.org/fcla/dt/13220
- Subject Headings
- Rats as laboratory animals, Rats--Nervous system, Thalamus--Research, Rats--Embryology, Afferent pathways, Perceptual-motor processes, Sensorimotor integration
- Format
- Document (PDF)
