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Neuroscience Brown Bag Series
September 29, 2016

Samantha Hauser

Department of Hearing and Speech

Vanderbilt University

12:10pm

Wilson Hall Room 316

“Behavioral Consequences of Cochlear Histopathology Following Noise Overexposure in Nonhuman Primates”

Noise exposure is one of the most common etiologies of hearing loss. Though it has been studied in other animal models, the nonhuman primate model of noise induced hearing loss allows for studies of anatomy, physiology, and behavior within the same subjects under controlled exposure conditions. We found that macaque monkeys needed to be exposed to a more intense sound to cause overt hearing loss compared to rodents. These permanent changes in physiological measures and cochlear histopathology are correlated with impairment on variety of behavioral detection tasks. Detection of tones and masked tones and the bandwidth of auditory perceptual filters are affected in a frequency specific manner. These changes are correlated with the frequency specific destruction of inner and outer hair cells. Detection of tones in modulated maskers post-exposure showed no difference from steady state noise maskers, whereas pre-exposure results show a threshold benefit in maskers with low frequency modulations. Such temporal processing impairments were likely related to inner hair cell ribbon synaptopathy. These results reveal that behavioral effects of noise exposure are similar to those seen in humans and provide preliminary information on the correlations between noise exposure, cochlear histopathology, and perceptual changes in hearing.


Quantitative Methods Colloquium Series
October 3, 2016

Simpler isn't better, it's just simpler: OLS regression weights make better predictions than simple alternative weights in realistic simulations

Michael Nelson, Quantitative Methods, Vanderbilt Dept. of Psychology & Human Development

Several respected statisticians (e.g., Wainer, 1976; Dana, 1979; Dana and Dawes, 2004; Waller and Jones, 2010) have argued that researchers should consider using simpler alternatives to ordinary least squares (OLS) regression weights, such as equal weights or correlation weights, which are less sensitive to sample variation and are therefore less prone to problems of overfitting. I present the results of a series of Monte Carlo simulations comparing OLS, equal, and correlation regression weights, updating simulations by Dana and Dawes (2004) to examine specific scenarios. Simulation results show that alternative weights consistently improve model predictions only when a set of parameters can be matched with the optimal weight type for its particular population characteristics, an impossible requirement given realistic limitations on a researcher's a priori knowledge. As such, OLS weights are generally the best choice, though researchers must be careful not to attribute more precision to predictions than the data allow.


Clinical Science Brown Bag Series
October 4, 2016

Maureen MCHugo PhD

Department of Psychiatry & Behavioral Sciences

Vanderbilt University School of Medicine

https://medschool.vanderbilt.edu/psychiatry/faculty/primary/mchugomk

12:10pm

Wilson Hall Room 316

“Increased Amplitude Of Low Frequency Fluctuations But Normal Functional Connectivity Of The Hippocampus In Schizophrenia”

Clinical and preclinical studies have established that the hippocampus is hyperactive in schizophrenia, making it a possible biomarker for drug development. Increased hippocampal connectivity, which can be studied conveniently with resting state imaging, has been proposed as a readily accessible corollary of hippocampal hyperactivity. In recent work, we tested the hypothesis that hippocampal activity and connectivity are increased in patients with schizophrenia using several common methods. Our results indicate that although intrinsic hippocampal activity may be increased in schizophrenia, this finding may not extend to aggregate functional connectivity. Neuroimaging methods that assess hippocampal activity may be more promising for the identification of a biomarker for schizophrenia.


CCN Brown Bag Series
October 5, 2016

Jennifer Trueblood

Department of Psychology

Vanderbilt University

Wednesday, 10/5/2016

12:10pm

WH 113

“A quantum probability framework for human probabilistic inference”

There is considerable variety in human inference (e.g., a doctor inferring the presence of a disease, a juror inferring the guilt of a defendant, or someone inferring their future weight loss based on current diet and exercise). As such, people display a wide range of behaviors when making inference judgments. Sometimes, people’s judgments appear Bayesian (i.e., normative), but in other cases, judgments deviate from the normative prescription of classical probability theory. How can we combine both Bayesian and non-Bayesian influences in a principled way? In this talk, I will propose a unified explanation of human inference using quantum probability (QP) theory. I will discuss how changing assumptions about compatibility (i.e., how joint events are represented) leads to the construction of a hierarchy of models, from ‘fully’ quantum to ‘fully’ classical, that could be adopted by different individuals in different situations. I will illustrate the approach with new laboratory experiments and model comparisons as well as discuss two factors that determine the form of the representation, individual differences in cognitive thinking style and familiarity with the reasoning domain. I will conclude by showing how the framework can used to understand real world causal judgments using a large (N=1200) experiment conducted during the US Presidential primaries involving judgments about the outcomes of primaries and the eventual nominations.


ACCRE Special Presentation
October 5, 2016

Using GPUs on ACCRE

4pm, Wednesday October 5, 2016

Wilson Hall 316

Members of Vanderbilt's ACCRE (Advanced Computing Center for Research and Education) will be giving a presentation and holding a Q&A session on using GPUs on ACCRE’s high performance computing cluster. Labs potentially interested in using their GPU capabilities should try to have someone attend.

 

GPUs for computing are basically the same technology (and often the exact same physical hardware) used for graphics/video cards in PCs. Your video display is a large matrix of (pixel) data (i.e., millions of them for a high resolution monitor). GPUs are a computing architecture that can perform operations on these matrices in parallel very quickly (responsible for the amazing things you see in advanced video games). GPUs for computing basically use the engine within the graphic card to perform operations on large arrays and matrices of data (e.g., image and signal processing) without having them displayed on the computer monitor. Hence any computation (analysis, simulation) that can be written to take advantage of the parallel architecture on GPUs can, at least in principle, perform those computations orders of magnitude more quickly than on a CPU (yes, 100x faster for the right problem programmed the right way). Unfortunately, it is not always trivial to port programs that run on a CPU to a GPU and get those speed gains. Some labs may be able to take advantage of software others have written and simply want to know whether and how they can run this software on ACCRE; other labs may be interested in exploring whether and how their current analysis/simulation programs can be rewritten to take advantage of a GPU architecture.


Neuroscience Brown Bag Series
October 6, 2016

Pamela Beck Drury

Private Clinical Practice

Nashville, TN.

12:10pm

Wilson Hall Room 316

“Neurofeedback: Combining Principles of Biofeedback, Operant Conditioning, and Neuroplasticity to Improve Clinical Outcomes”

For decades biofeedback has used principles of operant conditioning to help people learn to self-regulate physiology. Neurofeedback is a type of biofeedback in which these principles are applied to brain activity. Advances in technology, such as quantitative EEG, allow us to assess for and train any dysregulation in brain activity identified through comparison with a normative database. By combining principles of neuroplasticity and operant conditioning, individuals can learn to self-regulate activity associated with a number of clinical conditions, including ADHD, anxiety, depression, migraine headaches, postconcussive syndrome, stroke, seizure disorder, and traumatic brain injury. Outcome research is promising for a number of clinical presentations, though more scientifically rigorous research is needed.

 


Clinical Science Brown Bag Series
October 11, 2016

Suzanne Avery

Department of Psychiatry

Vanderbilt University School of Medicine

12:10pm

Wilson Hall Room 316

Title & Abstract TBA


CCN Brown Bag Series
October 12, 2016

Patryk Laurent, Ph.D.

Senior Scientist, Director of R&D

Brain Corporation

San Diego, CA

12:10pm

Wilson Hall Rm. 113

Title & Abstract TBA


Neuroscience Brown Bag Series
October 13, 2016

Suzana Herculano

Department of Psychology

Vanderbilt University

12:10pm

Wilson Hall Room 316

Evolutionary generation of brain diversity: How to build a bigger cortex by tweaking just three parameters” The cerebral cortex of mammals varies enormously in volume, surface area, thickness, number of neurons, gray/white matter ratio, and degree of folding. The relationships across these variables are also multiple and clade-specific. Surprisingly, however, we find that all these variables and the relationships among them can be predicted by a model based on just three parameters related to cortical development, with clade-specific values. This talk will present our model of generation of cortical diversity, explain what those three parameters are, and address the implications for understanding brain evolution and for future studies on the developmental origins of evolutionary diversity.


Clinical Science Brown Bag Series
October 18, 2016

Jennifer Blackford PhD

Department of Psychiatry & behavioral Sciences

Vanderbilt University School of Medicine

https://medschool.vanderbilt.edu/psychiatry/faculty/primary/urbanojc

12:10pm

Wilson Hall Room 316

Title & Abstract TBA


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