Musical Training Induces Functional Plasticity in Human Hippocampus

Training can change the functional and structural organization of the brain, and animal models demonstrate that the hippocampus formation is particularly susceptible to training-related neuroplasticity. In humans, however, direct evidence for functional plasticity of the adult hippocampus induced by training is still missing. Here, we used musicians' brains as a model to test for plastic capabilities of the adult human hippocampus. By using functional magnetic resonance imaging optimized for the investigation of auditory processing, we examined brain responses induced by temporal novelty in otherwise isochronous sound patterns in musicians and musical laypersons, since the hippocampus has been suggested previously to be crucially involved in various forms of novelty detection. In the first cross-sectional experiment, we identified enhanced neural responses to temporal novelty in the anterior left hippocampus of professional musicians, pointing to expertise-related differences in hippocampal processing. In the second experiment, we evaluated neural responses to acoustic temporal novelty in a longitudinal approach to disentangle training-related changes from predispositional factors. For this purpose, we examined an independent sample of music academy students before and after two semesters of intensive aural skills training. After this training period, hippocampal responses to temporal novelty in sounds were enhanced in musical students, and statistical interaction analysis of brain activity changes over time suggests training rather than predisposition effects. Thus, our results provide direct evidence for functional changes of the adult hippocampus in humans related to musical training.

Preclinical Evaluation of Radiolabeled DOTA-Derivatized Cyclic Minigastrin Analogs for Targeting Cholecystokinin Receptor Expressing Malignancies

Targeting of cholecystokinin receptor expressing malignancies such as medullary thyroid carcinoma is currently limited by low in vivo stability of radioligands. To increase the stability, we have developed and preclinically evaluated two cyclic 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA)-minigastrin analogs radiolabeled with (111)In and (68)Ga.

Chemical Research with Undergraduate Collaborators: Building Cyclic Polymers

Undergraduate research in chemistry provides not only a meaningful experience for the students, but is essential in getting research done. This talk will focus on an ongoing project in my lab: designing large molecules of specific shapes by studying the fundamental reactions. While results will be discussed, the talk will be tailored towards a general audience. I will attempt to highlight the outstanding contributions made by Bucknell students that have worked in my lab.

Quantum Mechnical Investion of Cyclic 3',5'- Adenosine Monophosphate, the Second Hormonal Messenger

Full geometry optimizations using the PM3, AM1, 3-21G∗/HF and 6-31G∗/HF levels of theory were conducted on the syn and anti conformations of cyclic3′,5′-adenosine monophosphate (cAMP). Comparison of the anti crystal structures with the semiempirical and ab initio results revealed that the ab initio results agree well with the experimental results. The results of semiempirical calculations are in qualitative agreement with experimental and ab initio values, with the exception of the glycosyl torsion angle for the anti conformer. Sugar puckering, which is not handled properly by semiempirical methods for unconstrained sugars, nucleosides, nucleotides and nucleotide base pairs, is modeled reasonably well by the semiempirical methods for cAMP. This improvement results from the constraints introduced by the cyclization of AMP to form the phosphodiester.

Use of the Supermolecule Approach To Model the Syn and Anti Conformations of Solvated Cyclic 3‘,5‘-Adenosine Monophosphate

The supermolecule approach has been used to model the hydration of cyclic 3‘,5‘-adenosine monophosphate, cAMP. Model building combined with PM3 optimizations predict that the anti conformer of cAMP is capable of hydrogen bonding to an additional solvent water molecule compared to the syn conformer. The addition of one water to the syn superstructure with concurrent rotation of the base about the glycosyl bond to form the anti superstructure leads to an additional enthalpy of stabilization of approximately −6 kcal/mol at the PM3 level. This specific solute−solvent interaction is an example of a large solvent effect, as the method predicts that cAMP has a conformational preference for the anti isomer in solution. This conformational preference results from a change in the number of specific solute−solvent interactions in this system. This prediction could be tested by NMR techniques. The number of waters predicted to be in the first hydration sphere around cAMP is in agreement with the results of hydration studies of nucleotides in DNA. In addition, the detailed picture of solvation about this cyclic nucleotide is in agreement with infrared experimental results.

Molecular mechanisms of muscle plasticity with exercise

The skeletal muscle phenotype is subject to considerable malleability depending on use. Low-intensity endurance type exercise leads to qualitative changes of muscle tissue characterized mainly by an increase in structures supporting oxygen delivery and consumption. High-load strength-type exercise leads to growth of muscle fibers dominated by an increase in contractile proteins. In low-intensity exercise, stress-induced signaling leads to transcriptional upregulation of a multitude of genes with Ca2+ signaling and the energy status of the muscle cells sensed through AMPK being major input determinants. Several parallel signaling pathways converge on the transcriptional co-activator PGC-1α, perceived as being the coordinator of much of the transcriptional and posttranscriptional processes. High-load training is dominated by a translational upregulation controlled by mTOR mainly influenced by an insulin/growth factor-dependent signaling cascade as well as mechanical and nutritional cues. Exercise-induced muscle growth is further supported by DNA recruitment through activation and incorporation of satellite cells. Crucial nodes of strength and endurance exercise signaling networks are shared making these training modes interdependent. Robustness of exercise-related signaling is the consequence of signaling being multiple parallel with feed-back and feed-forward control over single and multiple signaling levels. We currently have a good descriptive understanding of the molecular mechanisms controlling muscle phenotypic plasticity. We lack understanding of the precise interactions among partners of signaling networks and accordingly models to predict signaling outcome of entire networks. A major current challenge is to verify and apply available knowledge gained in model systems to predict human phenotypic plasticity.

A triplet spike-timing–dependent plasticity model generalizes the Bienenstock–Cooper–Munro rule to higher-order spatiotemporal correlations

Synaptic strength depresses for low and potentiates for high activation of the postsynaptic neuron. This feature is a key property of the Bienenstock–Cooper–Munro (BCM) synaptic learning rule, which has been shown to maximize the selectivity of the postsynaptic neuron, and thereby offers a possible explanation for experience-dependent cortical plasticity such as orientation selectivity. However, the BCM framework is rate-based and a significant amount of recent work has shown that synaptic plasticity also depends on the precise timing of presynaptic and postsynaptic spikes. Here we consider a triplet model of spike-timing–dependent plasticity (STDP) that depends on the interactions of three precisely timed spikes. Triplet STDP has been shown to describe plasticity experiments that the classical STDP rule, based on pairs of spikes, has failed to capture. In the case of rate-based patterns, we show a tight correspondence between the triplet STDP rule and the BCM rule. We analytically demonstrate the selectivity property of the triplet STDP rule for orthogonal inputs and perform numerical simulations for nonorthogonal inputs. Moreover, in contrast to BCM, we show that triplet STDP can also induce selectivity for input patterns consisting of higher-order spatiotemporal correlations, which exist in natural stimuli and have been measured in the brain. We show that this sensitivity to higher-order correlations can be used to develop direction and speed selectivity.

Interactions between short-term and long-term plasticity: shooting for a moving target

Far from being static transmission units, synapses are highly dynamical elements that change over multiple time scales depending on the history of the neural activity of both the pre- and postsynaptic neuron. Moreover, synaptic changes on different time scales interact: long-term plasticity (LTP) can modify the properties of short-term plasticity (STP) in the same synapse. Most existing theories of synaptic plasticity focus on only one of these time scales (either STP or LTP or late-LTP) and the theoretical principles underlying their interactions are thus largely unknown. Here we develop a normative model of synaptic plasticity that combines both STP and LTP and predicts specific patterns for their interactions. Recently, it has been proposed that STP arranges for the local postsynaptic membrane potential at a synapse to behave as an optimal estimator of the presynaptic membrane potential based on the incoming spikes. Here we generalize this approach by considering an optimal estimator of a non-linear function of the membrane potential and the long-term synaptic efficacy—which itself may be subject to change on a slower time scale. We find that an increase in the long-term synaptic efficacy necessitates changes in the dynamics of STP. More precisely, for a realistic non-linear function to be estimated, our model predicts that after the induction of LTP, causing long-term synaptic efficacy to increase, a depressing synapse should become even more depressing. That is, in a protocol using trains of presynaptic stimuli, as the initial EPSP becomes stronger due to LTP, subsequent EPSPs should become weakened and this weakening should be more pronounced with LTP. This form of redistribution of synaptic efficacies agrees well with electrophysiological data on synapses connecting layer 5 pyramidal neurons.

Extremes of Lineage Plasticity in the Drosophila Brain

An often-overlooked aspect of neural plasticity is the plasticity of neuronal composition, in which the numbers of neurons of particular classes are altered in response to environment and experience. The Drosophila brain features several well-characterized lineages in which a single neuroblast gives rise to multiple neuronal classes in a stereotyped sequence during development. We find that in the intrinsic mushroom body neuron lineage, the numbers for each class are highly plastic, depending on the timing of temporal fate transitions and the rate of neuroblast proliferation. For example, mushroom body neuroblast cycling can continue under starvation conditions, uncoupled from temporal fate transitions that depend on extrinsic cues reflecting organismal growth and development. In contrast, the proliferation rates of antennal lobe lineages are closely associated with organismal development, and their temporal fate changes appear to be cell-cycle dependent, such that the same numbers and types of uniglomerular projection neurons innervate the antennal lobe following various perturbations. We propose that this surprising difference in plasticity for these brain lineages is adaptive, given their respective roles as parallel processors versus discrete carriers of olfactory information.