Theory & Data Analysis Tools

CRCNS: Regulation of assembly and disassembly of the postsynaptic density during synaptic plasticity and its effect on AMPAR trapping

Fast glutamatergic synaptic transmission is based on a precise and complex molecular organization which requires the control of the number of AMPA-type glutamate receptors (AMPARs) at the postsynaptic sites of glutamatergic synapses on dendritic spines. The number of AMPARs varies as a function of pre- and postsynaptic activation history of the synapse. It is now well described that synapses can change their number of AMPARs and therefore, their response properties through biochemical mechanisms of synaptic plasticity. In this way, information is stored in the brain.

CRCNS: Crossbeam Transcranial Ultrasound Technology to Stimulate the Deep Brain

Numerous neuroscience and clinical applications exist for a noninvasive neuromodulation technology that can reach deep in the brain with high resolution. One compelling clinical application is the treatment of drug addiction, a major public health challenge in the US. In humans, the neural targets for treatment are 1-4 mm3, and thus a critical goal is to stimulate deep in the brain with higher resolutions than currently available with any noninvasive stimulation modality.

CRCNS: Computational Modeling of Microvascular Effects in Cortical Laminar fMRI

Today, the most widespread tool for measuring whole-brain activity noninvasively is functional magnetic resonance imaging (fMRI). Although fMRI tracks neural activity indirectly through measuring the associated changes in blood flow, volume and oxygenation, recent evidence has suggested that these active hemodynamic changes in the brain are far more precisely coordinated than previously believed, perhaps at the fine spatial scale of the basic modules of functional architecture: cerebral cortical columns and layers.

CRCNS: Circuit mechanisms of priors and learning during decision making

When learning a new task, both rats and humans exhibit suboptimal behaviors plagued with superstitious ticks and idiosyncratic biases. One prominent example of such suboptimality are sequential effects: animals tend to bias their choices based on previous decisions and outcomes, hindering performance in common laboratory tasks using independent trials. Recurrent neural networks (RNN) have become a common tool to study potential neural mechanisms of cognition. Yet, RNNs typically behave much closer to optimality in laboratory tasks than real subjects.

CRCNS: Deconstructing dynamics of motor cortex in freely moving behavior

What operations are performed by the mammalian central nervous systems to coordinate and conduct voluntary movement? Motor systems neuroscience seeks to understand these neural mechanisms. The last two decades have witnessed a transformation in this field with the use of multielectrode recordings and statistical estimation and modeling techniques. These technological advances have yielded rich, low-dimensional neural dynamics that are suggestive of the mechanisms underlying behavior.

CRCNS: Multifocal causal mapping of brain networks supporting human cognition

Neuroimaging methods such as functional MRI and magneto- / electroencephalography (MEG/EEG) cannot directly reveal causal relationships between regional brain activity and behavior. To allow causal inference, transcranial magnetic stimulation (TMS) has been used to perturb local cortical activity to create temporary "virtual lesions”.

CRCNS: Understanding Single-Neuron Computation Using Nonlinear Model Optimization

Motivation and Objectives Why are ion channels localized in subcellular dendritic compartments and is there a tight coupling of the observed localization with neuron function? We argue that this fundamental question [55, 44] can be addressed by studying the biophysical mechanisms of single neuron computation in two model systems where a large amount of electrophysiological and anatomical data is available and has been tied to the functional roles of key neurons.

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