1999 — 2001 |
Jenison, Rick Lynn |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Models of Cortical Neural Coding of Auditory Space @ University of Wisconsin Madison
DESCRIPTION (Adapted From The Applicant's Abstract): The long-term objective of this research is to understand the cortical mechanisms that underlie spatial hearing. Although there is now a wealth of neurophysiological and psychophysical data related to sound localization mechanisms, the is a paucity of formal stistical and mathematical models that provide a theoretical framwork for this research, that might integrate these large knowledge bases, that give insight into the underlying mechanisms, or that drive new laboratory experimentation. The models will be based on, and provide a bridge between, the directional selectivity of primary auditory cortical neurons as measured in single-neuron electrophysiological experiments and human spatial acuity as determine in complementary psychophysical studies. The cortical data are in the form of spatial receptive fields measured with the aid of a virtual space paradigm. We propose to pursue four related specific aims: 1) We will functionally approximate the directional sensitivity of the auditory cortical neurons as measured by their response patterns using the von Mises basis function. This set of basis functions is unique in that it is spherical rather than Cartesian. This approach is similar to the framework developed to describve simple-cell receptive fields in visual cortex using Gabor functions or Difference-of-gaussians, 2) We will develop ideal observer models of spatial direction based on a theory of maximum-likelihood estimates, and test these models psychophysically. 3) We will develop models of maximum-likelihood estimators of latency reference to test the feasibility of latency based coding of sound direction. 4) We will develop ideal observer models based on correlated response patterns. This approach of integrating theoretical modeling with electrophysiological and psychophysical analyses will provide new insights into cortiucal mechanisms underlying spatial hearing and drive new physiological and behavioral studies.
|
1 |
2008 — 2013 |
Jenison, Rick |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
The Role of the Human Amygdala in Coding Economic Risk and Ambiguity @ University of Wisconsin-Madison
The objective of this research is to identify the neural circuitry involved in value-based decision-making. The experiments to be conducted involve a unique subject group -- participant-patients with intractable epilepsy who have undergone implantation of intracranial electrodes for periods of up to two weeks in attempts to identify the locus of seizures using EEG-like recordings. These implants enable direct recording of neural activity of regions of the brain region - in the present study in the region known as the amygdala. Subjects will respond to decision making tasks designed to test specific hypotheses of decision-making. The project is organized into three major aims: 1) to record the neural coding of primitive economic variables such as reward probability and magnitude, 2) to record the neural coding of risk and ambiguity, and 3) to ascertain the impact of microstimulation of specific locations in the brain on observed preferences. Because of its relatively precise temporal and spatial characteristics, microstimulation is a particularly powerful tool for establishing causal relationships between physiologically characterized neurons and behavioral performance. This project has the potential to fundamentally impact our understanding of how economic decisions are made.
|
0.915 |
2009 — 2011 |
Jenison, Rick Lynn |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Crcns: Decoding Goal-Directed Valuation in the Human Amygdala @ University of Wisconsin-Madison
DESCRIPTION (provided by applicant): Many daily decisions are instances of value-based decision-making. Examples include what to buy at a store, or what to eat for lunch. An essential computation that the brain needs to perform to make these kinds of decisions is to assign value to each of the options under consideration. An important open question in the field is whether the human amygdala encodes signals that affect value-based choices, perhaps by influencing activity in the medial orbitofrontal cortex. This proposal describes an extremely cross-disciplinary collaboration between a computational neuroscientist (Rick Jenison), a neurosurgeon and human electrophysiologist (Matthew Howard), and a neuroeconomist (Antonio Rangel) that seeks to combine tools from all of these fields to address this question. The proposal has four key aims: Specific Aim 1. To apply computational and statistical modeling tools from point process theory and Bayesian particle filters to analyze the encoding of subjective value signals in single-unit recordings from awake behaving human patients with pharmacologically intractable epilepsy and in fMRI experiments. Specific Aim 2. To investigate the extent to which the human amygdala is involved in value-based appetitive decision-making using single-unit recordings, microstimulation, fMRI, and the computational tools from Specific Aim 1. Specific Aim 3. To investigate the extent to which the human amygdala is involved in value-based aversive decision-making using single-unit recordings, microstimulation, fMRI, and the computational tools from Specific Aim 1. Specific Aim 4. To implement an intensive and unique cross-disciplinary education and training program for three post-docs in order to prepare them for further work at the intersection of the three disciplines represented in this proposal. Intellectual merit: First, the combination of point process and Bayesian particle filters tools from computational neuroscience, with human electrophysiology techniques from neurobiology, and with experimental paradigms from model-based fMRi taken from neuroeconomics has the potential to generate a quantum-leap in our understanding of the role of the human amygdala in value-based choice. Second, the methods that we propose will be able to look not only for correIations between brain activity and value computations, but also for the causality of such signals. Third, the computational approaches that we propose entail an extension of tools to domains in which the variables encoded by the brain are subjective (e.g., valuations) instead of objective (e.g., a location in space), which could have a myriad of applications in various areas of decision, social, and cognitive neuroscience, as well as psychiatry. Fourth, the combination of human single-unit data with related fMRI analyses will provide as a sidebenefit insights about the relationship between the BOLD signal and the underlying action potentials. Broader Impacts: The proposal also has a strong educational and training component. Future advances in neuroeconomics and decision neuroscience are likely to come at the crossdisciplinary intersection of computational neuroscience, neurobiology, and neuroeconomics. Unfortunately, it is difficult for young neuroscientists to get the necessary expertise in more than one of these areas. In order to address this shortcoming we will implement an intensive and quite unique crossdisciplinary education and training program for three post-docs to prepare them for further work at the intersection of the three disciplines represented in this proposal. Not only that, in order to increase diversity in science, applications for the post-doctoral position from women and members of disadvantaged minorities will be strongly encouraged, and such applicants will be favored. Many psychiatric disorders can be characterized as diseases of decision making. Consider, as extreme examples, the cases of addiction and OCD. The role of the amygdala in these diseases it is not well-understood. This research will contribute to the nascent field of computational psychiatry by advancing our understanding of the interaction between the amygdala computations and the value-based decision-making systems.
|
1 |