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<p>Centrally active peptides have increasingly been implicated in diverse neuro-psychiatric disorders in humans. Although several clinical studies have attested to the therapeutic potential of L-Prolyl-L-Leucyl-Glycinamide (PLG) in Parkinson's disease, no unifying hypothesis concerning its mode of action can be formulated. The present critical analysis of the pharmacological property of PLG was predicated on the hypothesis that there exist putative receptor sites of PLG manifesting differential modulatory effects on dopaminergic neurotransmission.</p> <p>The action of PLG was examined in behavioral paradihms reflecting dopamine dependent extrapyramidal motor dysfunction: haloperidol-and morphine-induced catalepsy in rats. Chronic, but not acute, treatment of PLG significantly antagonized hoth morphine and haloperidol catalepsy.</p> <p>The influence of PLG on in vitro dopamine receptor function was evaluated, and the resutls showed that PLG selectively enhanced the affinity of the specific binding of the agonist H-apomorphine to doapmine receptors in rat striatum. PLG, however, failed to alter ³H-spiroperidol binding in vitro.</p> <p>A radioligand binding assay was developed to identify specific putative binding sites of PLG in normal rat and human brain. ³H-PLG bound to membrane homogenates from both human and rat striatum with high affinity and in a saturable manner. The regional distribution profile of the specific ³H-PLG binding demonstrated that human substantia nigra exhibited thehighest level of ³H-PLG binding sites, followed by the striatum and hypothalamus. In the rat brain, the striatum was highly enriched with PLG binding sites. Pharmacologically active analogues of PLG completed for specific ³H-PLG binding with relative potencies paralleling their in vitro biological activities.</p> <p>The potential anti-dyskinetic activity of PLG was evaluated in the pharmacological animal model of tardive dyskinesia. In rats, PLG, when administered concurrently with haloperidol of chlorpromazine, antagonized the enhancements in specific ³H-spiroperidol binding in the striatum as associated with chronic neuroleptic treatment.</p> <p>The results of the present study support the hypothesis that putative PLG binding sites are functionally coupled to dopamine/neuroleptic adenylate cyclase complex and raise the issue as to the feasibility of specific peptidergic dysfunction and peptide replacement therapy in neuro-psychiatric disorders.</p> / Doctor of Philosophy (PhD)

A growing body of research indicates that much of the brain’s computation is invisible from the activity of individual neurons, but instead instantiated via population-level dynamics. According to this ‘dynamical systems hypothesis’, population-level neural activity evolves according to underlying dynamics that are shaped by network connectivity. While these dynamics are not directly observable in empirical data, they can be inferred by studying the structure of population trajectories. Quantification of this structure, the ‘trajectory geometry’, can then guide thinking on the underlying computation. Alternatively, modeling neural populations as dynamical systems can predict trajectory geometries appropriate for particular tasks. This approach of characterizing and interpreting trajectory geometry is providing new insights in many cortical areas, including regions involved in motor control and areas that mediate cognitive processes such as decision-making. In this thesis, I advance the characterization of population structure by introducing hypothesis-guided metrics for the quantification of trajectory geometry. These metrics, trajectory tangling in primary motor cortex and trajectory divergence in the Supplementary Motor Area, abstract away from task-specific solutions and toward underlying computations and network constraints that drive trajectory geometry. Primate motor cortex (M1) projects to spinal interneurons and motoneurons, suggesting that motor cortex activity may be dominated by muscle-like commands. Observations during reaching lend support to this view, but evidence remains ambiguous and much debated. To provide a different perspective, we employed a novel behavioral paradigm that facilitates comparison between time-evolving neural and muscle activity. We found that single motor cortex neurons displayed many muscle-like properties, but the structure of population activity was not muscle-like. Unlike muscle activity, neural activity was structured to avoid ‘trajectory tangling’: moments where similar activity patterns led to dissimilar future patterns. Avoidance of trajectory tangling was present across tasks and species. Network models revealed a potential reason for this consistent feature: low trajectory tangling confers noise robustness. We were able to predict motor cortex activity from muscle activity by leveraging the hypothesis that muscle-like commands are embedded in additional structure that yields low trajectory tangling. The Supplementary Motor Area (SMA) has been implicated in many higher-order aspects of motor control. Previous studies have demonstrated that SMA might track motor context. We propose that this computation necessitates that neural activity avoids ‘trajectory divergence’: moments where two similar neural states become dissimilar in the future. Indeed, we found that population activity in SMA, but not in M1, reliably avoided trajectory divergence, resulting in fundamentally different geometries: cyclical in M1 and helix-like in SMA. Analogous structure emerged in artificial networks trained without versus with context-related inputs. These findings reveal that the geometries of population activity in SMA and M1 are fundamentally different, with direct implications regarding what computations can be performed by each area. The characterization and statistical analysis of trajectory geometry promises to advance our understanding of neural network function by providing interpretable, cohesive explanations for observed population structure. Commonality between individuals and networks can be uncovered and more generic, task-invariant, fundamental aspects of neural response can be explored.

Thesis (Ph.D.)--Georgetown University, 2009. / Includes bibliographical references.

Thesis (Ph.D.)--Georgetown University, 2009. / Includes bibliographical references.

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