Browsing by Subject "Basal ganglia"

Now showing 1 - 9 of 9
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    Advanced Modeling of Longitudinal Spectroscopy Data
    (2014) Kundu, Madan Gopal; Harezlak, Jaroslaw; Randolph, Timothy W.; Sarkar, Jyotirmoy; Steele, Gregory K.; Yiannoutsos, Constantin T.
    Magnetic resonance (MR) spectroscopy is a neuroimaging technique. It is widely used to quantify the concentration of important metabolites in a brain tissue. Imbalance in concentration of brain metabolites has been found to be associated with development of neurological impairment. There has been increasing trend of using MR spectroscopy as a diagnosis tool for neurological disorders. We established statistical methodology to analyze data obtained from the MR spectroscopy in the context of the HIV associated neurological disorder. First, we have developed novel methodology to study the association of marker of neurological disorder with MR spectrum from brain and how this association evolves with time. The entire problem fits into the framework of scalar-on-function regression model with individual spectrum being the functional predictor. We have extended one of the existing cross-sectional scalar-on-function regression techniques to longitudinal set-up. Advantage of proposed method includes: 1) ability to model flexible time-varying association between response and functional predictor and (2) ability to incorporate prior information. Second part of research attempts to study the influence of the clinical and demographic factors on the progression of brain metabolites over time. In order to understand the influence of these factors in fully non-parametric way, we proposed LongCART algorithm to construct regression tree with longitudinal data. Such a regression tree helps to identify smaller subpopulations (characterized by baseline factors) with differential longitudinal profile and hence helps us to identify influence of baseline factors. Advantage of LongCART algorithm includes: (1) it maintains of type-I error in determining best split, (2) substantially reduces computation time and (2) applicable even observations are taken at subject-specific time-points. Finally, we carried out an in-depth analysis of longitudinal changes in the brain metabolite concentrations in three brain regions, namely, white matter, gray matter and basal ganglia in chronically infected HIV patients enrolled in HIV Neuroimaging Consortium study. We studied the influence of important baseline factors (clinical and demographic) on these longitudinal profiles of brain metabolites using LongCART algorithm in order to identify subgroup of patients at higher risk of neurological impairment.
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    Basal ganglia role in learning rewarded actions and executing previously learned choices: Healthy and diseased states
    (Public Library of Science, 2020-02-10) Mulcahy, Garrett; Atwood, Brady; Kuznetsov, Alexey; Psychiatry, School of Medicine
    The basal ganglia (BG) is a collection of nuclei located deep beneath the cerebral cortex that is involved in learning and selection of rewarded actions. Here, we analyzed BG mechanisms that enable these functions. We implemented a rate model of a BG-thalamo-cortical loop and simulated its performance in a standard action selection task. We have shown that potentiation of corticostriatal synapses enables learning of a rewarded option. However, these synapses became redundant later as direct connections between prefrontal and premotor cortices (PFC-PMC) were potentiated by Hebbian learning. After we switched the reward to the previously unrewarded option (reversal), the BG was again responsible for switching to the new option. Due to the potentiated direct cortical connections, the system was biased to the previously rewarded choice, and establishing the new choice required a greater number of trials. Guided by physiological research, we then modified our model to reproduce pathological states of mild Parkinson's and Huntington's diseases. We found that in the Parkinsonian state PMC activity levels become extremely variable, which is caused by oscillations arising in the BG-thalamo-cortical loop. The model reproduced severe impairment of learning and predicted that this is caused by these oscillations as well as a reduced reward prediction signal. In the Huntington state, the potentiation of the PFC-PMC connections produced better learning, but altered BG output disrupted expression of the rewarded choices. This resulted in random switching between rewarded and unrewarded choices resembling an exploratory phase that never ended. Along with other computational studies, our results further reconcile the apparent contradiction between the critical involvement of the BG in execution of previously learned actions and yet no impairment of these actions after BG output is ablated by lesions or deep brain stimulation. We predict that the cortico-BG-thalamo-cortical loop conforms to previously learned choice in healthy conditions, but impedes those choices in disease states.
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    Distinct cortico-striatal compartments drive competition between adaptive and automatized behavior
    (Public Library of Science, 2023-03-21) Barnett, William H.; Kuznetsov, Alexey; Lapish, Christopher C.; Psychology, School of Science
    Cortical and basal ganglia circuits play a crucial role in the formation of goal-directed and habitual behaviors. In this study, we investigate the cortico-striatal circuitry involved in learning and the role of this circuitry in the emergence of inflexible behaviors such as those observed in addiction. Specifically, we develop a computational model of cortico-striatal interactions that performs concurrent goal-directed and habit learning. The model accomplishes this by distinguishing learning processes in the dorsomedial striatum (DMS) that rely on reward prediction error signals as distinct from the dorsolateral striatum (DLS) where learning is supported by salience signals. These striatal subregions each operate on unique cortical input: the DMS receives input from the prefrontal cortex (PFC) which represents outcomes, and the DLS receives input from the premotor cortex which determines action selection. Following an initial learning of a two-alternative forced choice task, we subjected the model to reversal learning, reward devaluation, and learning a punished outcome. Behavior driven by stimulus-response associations in the DLS resisted goal-directed learning of new reward feedback rules despite devaluation or punishment, indicating the expression of habit. We repeated these simulations after the impairment of executive control, which was implemented as poor outcome representation in the PFC. The degraded executive control reduced the efficacy of goal-directed learning, and stimulus-response associations in the DLS were even more resistant to the learning of new reward feedback rules. In summary, this model describes how circuits of the dorsal striatum are dynamically engaged to control behavior and how the impairment of executive control by the PFC enhances inflexible behavior.
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    Gut and brain profiles that resemble pre-motor and early-stage Parkinson’s disease in methamphetamine self-administering rats
    (Elsevier, 2021) Persons, Amanda L.; Bradaric, Brinda D.; Kelly, Leo P.; Kousik, Sharanya M.; Graves, Steven M.; Yamamoto, Bryan K.; Napier, T. Celeste; Pharmacology and Toxicology, School of Medicine
    Introduction: Methamphetamine is a potent psychomotor stimulant, and methamphetamine abusers are up to three times more likely to develop Parkinson's disease (PD) later in life. Prodromal PD may involve gut inflammation and the accumulation of toxic proteins that are transported from the enteric nervous system to the central nervous system to mediate, in part, the degeneration of dopaminergic projections. We hypothesized that self-administration of methamphetamine in rats produces a gut and brain profile that mirrors pre-motor and early-stage PD. Methods: Rats self-administered methamphetamine in daily 3 h sessions for two weeks. Motor function was assessed before self-administration, during self-administration and throughout the 56 days of forced abstinence. Assays for pathogenic markers (tyrosine hydroxylase, glial fibrillary acidic protein (GFAP), α-synuclein) were conducted on brain and gut tissue collected at one or 56 days after cessation of methamphetamine self-administration. Results: Motor deficits emerged by day 14 of forced abstinence and progressively worsened up to 56 days of forced abstinence. In the pre-motor stage, we observed increased immunoreactivity for GFAP and α-synuclein within the ganglia of the myenteric plexus in the distal colon. Increased α-synuclein was also observed in the substantia nigra pars compacta. At 56 days, GFAP and α-synuclein normalized in the gut, but the accumulation of nigral α-synuclein persisted, and the dorsolateral striatum exhibited a significant loss of tyrosine hydroxylase. Conclusion: The pre-motor profile is consistent with gut inflammation and gut/brain α-synuclein accumulation associated with prodromal PD and the eventual development of the neurological disease.
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    The Impact of Pediatric Basal Ganglia Stroke on Mental Health in Children: Report of 2 Cases
    (Sage, 2020-12-15) Badar, Sidrah A.; Radhakrishnan, Rupa; Golomb, Meredith R.; Neurology, School of Medicine
    Background: The impact of basal ganglia stroke on mental health is better described in adults than in children. We report 2 children with significant mental health issues after basal ganglia stroke. Case reports: Patient 1, an 8-year-old boy, had mild anxiety before his left basal ganglia stroke. Post-stroke, he developed severe anxiety, obsessions, depression, and attention deficit hyperactivity disorder, in addition to a right hemiplegia and some mild chorea. He gradually improved over 3 years with psychiatric care and medication but continued to have residual symptoms. Patient 2, a 10-year-old boy, had no history of mental health issues before his right basal ganglia stroke. Post-stroke, he developed significant anxiety and mild depression, along with a left hemiplegia. He improved over 9 months and returned to his mental health baseline. Conclusions: Mental health issues after basal ganglia stroke in children can be significant, and recovery can take months to years.
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    Impaired Effective Connectivity During a Cerebellar-Mediated Sensorimotor Synchronization Task in Schizophrenia
    (Oxford University Press, 2019-04) Moussa-Tooks, Alexandra B.; Kim, Dae-Jin; Bartolomeo, Lisa A.; Purcell, John R.; Bolbecker, Amanda R.; Newman, Sharlene D.; O’Donnell, Brian F.; Hetrick, William P.; Psychiatry, School of Medicine
    Prominent conceptual models characterize schizophrenia as a dysconnectivity syndrome, with recent research focusing on the contributions of the cerebellum in this framework. The present study examined the role of the cerebellum and its effective connectivity to the cerebrum during sensorimotor synchronization in schizophrenia. Specifically, the role of the cerebellum in temporally coordinating cerebral motor activity was examined through path analysis. Thirty-one individuals diagnosed with schizophrenia and 40 healthy controls completed a finger-tapping fMRI task including tone-paced synchronization and self-paced continuation tapping at a 500 ms intertap interval (ITI). Behavioral data revealed shorter and more variable ITIs during self-paced continuation, greater clock (vs motor) variance, and greater force of tapping in the schizophrenia group. In a whole-brain analysis, groups showed robust activation of the cerebellum during self-paced continuation but not during tone-paced synchronization. However, effective connectivity analysis revealed decreased connectivity in individuals with schizophrenia between the cerebellum and primary motor cortex but increased connectivity between cerebellum and thalamus during self-paced continuation compared with healthy controls. These findings in schizophrenia indicate diminished temporal coordination of cerebral motor activity by cerebellum during the continuation tapping portion of sensorimotor synchronization. Taken together with the behavioral finding of greater temporal variability in schizophrenia, these effective connectivity results are consistent with structural and temporal models of dysconnectivity in the disorder.
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    Involvement of I(h) in dopamine modulation of tonic firing in striatal cholinergic interneurons
    (Society for Neuroscience, 2007-03-21) Deng, Ping; Zhang, Yuchun; Xu, Zao C.; Anatomy and Cell Biology, School of Medicine
    Striatal cholinergic interneurons are tonically active neurons and respond to sensory stimuli by transiently suppressing firing that is associated with sensorimotor learning. The pause in tonic firing is dependent on dopaminergic activity; however, its cellular mechanisms remain unclear. Here, we report evidence that dopaminergic inhibition of hyperpolarization-activated cation current (I(h)) is involved in this process. In neurons exhibiting regular firing in vitro, exogenous application of dopamine caused a prolongation of the depolarization-induced pause and an increase in the duration of slow afterhyperpolarization (sAHP) after depolarization. Partially blocking I(h) with specific blocker ZD7288 (4-ethylphenylamino-1,2-dimethyl-6-methylaminopyrimidinium chloride) reduced firing and mimicked the effects of dopamine on sAHP. The I(h), being active at membrane potentials negative than -50 mV, was inhibited by dopamine via activation of the D2-like receptor, but not D1-like receptor. The inhibitory effects of the D2 receptor activation on I(h) were mediated through a protein kinase A-independent cyclic AMP pathway. Consistently, D2-like receptor agonist quinpirole showed comparable effects on sAHP and firing rate as those induced by I(h) channel blocker. Moreover, dopamine was unable to further affect the sAHP duration in neurons when I(h) was blocked. These findings indicate that D2 receptor-dependent inhibition of I(h) may be a novel mechanism for modulating the pause response in tonic firing in cholinergic interneurons.
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    Mathematical Models of Basal Ganglia Dynamics
    (2013-07-12) Dovzhenok, Andrey A.; Rubchinsky, Leonid; Kuznetsov, Alexey; Its, Alexander R.; Worth, Robert; Mukhin, Evgeny
    Physical and biological phenomena that involve oscillations on multiple time scales attract attention of mathematicians because resulting equations include a small parameter that allows for decomposing a three- or higher-dimensional dynamical system into fast/slow subsystems of lower dimensionality and analyzing them independently using geometric singular perturbation theory and other techniques. However, in most life sciences applications observed dynamics is extremely complex, no small parameter exists and this approach fails. Nevertheless, it is still desirable to gain insight into behavior of these mathematical models using the only viable alternative – ad hoc computational analysis. Current dissertation is devoted to this latter approach. Neural networks in the region of the brain called basal ganglia (BG) are capable of producing rich activity patterns. For example, burst firing, i.e. a train of action potentials followed by a period of quiescence in neurons of the subthalamic nucleus (STN) in BG was shown to be related to involuntary shaking of limbs in Parkinson’s disease called tremor. The origin of tremor remains unknown; however, a few hypotheses of tremor-generation were proposed recently. The first project of this dissertation examines the BG-thalamo-cortical loop hypothesis for tremor generation by building physiologically-relevant mathematical model of tremor-related circuits with negative delayed feedback. The dynamics of the model is explored under variation of connection strength and delay parameters in the feedback loop using computational methods and data analysis techniques. The model is shown to qualitatively reproduce the transition from irregular physiological activity to pathological synchronous dynamics with varying parameters that are affected in Parkinson’s disease. Thus, the proposed model provides an explanation for the basal ganglia-thalamo-cortical loop mechanism of tremor generation. Besides tremor-related bursting activity BG structures in Parkinson’s disease also show increased synchronized activity in the beta-band (10-30Hz) that ultimately causes other parkinsonian symptoms like slowness of movement, rigidity etc. Suppression of excessively synchronous beta-band oscillatory activity is believed to suppress hypokinetic motor symptoms in Parkinson’s disease. Recently, a lot of interest has been devoted to desynchronizing delayed feedback deep brain stimulation (DBS). This type of synchrony control was shown to destabilize synchronized state in networks of simple model oscillators as well as in networks of coupled model neurons. However, the dynamics of the neural activity in Parkinson’s disease exhibits complex intermittent synchronous patterns, far from the idealized synchronized dynamics used to study the delayed feedback stimulation. The second project of this dissertation explores the action of delayed feedback stimulation on partially synchronous oscillatory dynamics, similar to what one observes experimentally in parkinsonian patients. We employ a computational model of the basal ganglia networks which reproduces the fine temporal structure of the synchronous dynamics observed experimentally. Modeling results suggest that delayed feedback DBS in Parkinson’s disease may boost rather than suppresses synchronization and is therefore unlikely to be clinically successful. Single neuron dynamics may also have important physiological meaning. For instance, bistability – coexistence of two stable solutions observed experimentally in many neurons is thought to be involved in some short-term memory tasks. Bistability that occurs at the depolarization block, i.e. a silent depolarized state a neuron enters with excessive excitatory input was proposed to play a role in improving robustness of oscillations in pacemaker-type neurons. The third project of this dissertation studies what parameters control bistability at the depolarization block in the three-dimensional conductance-based neuronal model by comparing the reduced dopaminergic neuron model to the Hodgkin-Huxley model of the squid giant axon. Bifurcation analysis and parameter variations revealed that bistability is mainly characterized by the inactivation of the Na+ current, while the activation characteristics of the Na+ and the delayed rectifier K+ currents do not account for the difference in bistability in the two models.
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    Synchronized Beta-Band Oscillations in a Model of the Globus Pallidus-Subthalamic Nucleus Network under External Input
    (Frontiers, 2016-12-20) Ahn, Sungwoo; Zauber, S. Elizabeth; Worth, Robert M.; Rubchinsky, Lenold L.; Department of Mathematical Sciences, School of Science
    Hypokinetic symptoms of Parkinson's disease are usually associated with excessively strong oscillations and synchrony in the beta frequency band. The origin of this synchronized oscillatory dynamics is being debated. Cortical circuits may be a critical source of excessive beta in Parkinson's disease. However, subthalamo-pallidal circuits were also suggested to be a substantial component in generation and/or maintenance of Parkinsonian beta activity. Here we study how the subthalamo-pallidal circuits interact with input signals in the beta frequency band, representing cortical input. We use conductance-based models of the subthalamo-pallidal network and two types of input signals: artificially-generated inputs and input signals obtained from recordings in Parkinsonian patients. The resulting model network dynamics is compared with the dynamics of the experimental recordings from patient's basal ganglia. Our results indicate that the subthalamo-pallidal model network exhibits multiple resonances in response to inputs in the beta band. For a relatively broad range of network parameters, there is always a certain input strength, which will induce patterns of synchrony similar to the experimentally observed ones. This ability of the subthalamo-pallidal network to exhibit realistic patterns of synchronous oscillatory activity under broad conditions may indicate that these basal ganglia circuits are directly involved in the expression of Parkinsonian synchronized beta oscillations. Thus, Parkinsonian synchronized beta oscillations may be promoted by the simultaneous action of both cortical (or some other) and subthalamo-pallidal network mechanisms. Hence, these mechanisms are not necessarily mutually exclusive.