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Department of Cognitive Science, Krieger School of Arts and Sciences at Johns Hopkins
June 7, 2016
Institute of Neuroscience and Psychology, University of Glasgow
February 1, 2016
Professor of Psychological and Brain Sciences, Dartmouth College
January 25, 2016
Faces convey emotion. This makes them useful for understanding the internal state of others as well as what the internal state of others might mean for us. In this talk, I will make a case for faces - that is, the use of images of the facial expressions of others as experimental stimuli to better understand how our brains navigate the social world. We will see that facial expressions can be used to predict individual differences in healthy participants and participants suffering from emotional disorders. I will argue that one particular facial expression can be used to tap into a prefrontal-amygdala circuitry that appears crucial for at least a portion of the regulatory processes that make navigating our social world manageable.
Thayer School of Engineering at Dartmouth
December 12, 2014
Functional near-infrared spectroscopy (fNIRS) provides high temporal resolution measurements of concentration changes in cerebral oxyhemoglobin and deoxyhemoglobin. This information is complementary to other neuroimaging methods such as function magnetic resonance imaging (fMRI) and electroencephalography (EEG) and can be acquired simultaneously with these other methods. This talk will provide an introduction to the fundamentals of fNIRS and its capabilities and limitations for studying human brain function. Methods for multimodal neuroimaging using fNIRS with EEG and fMRI will be explained. Examples will be drawn from an ongoing study of neuromuscular coupling in patients with multiple sclerosis.
Professor of Neurobiology, Stanford University
Investigator, Howard Hughes Medical Institute
In April 2013, President Obama announced a grand challenge - the BRAIN Initiative - for US scientists to unlock the mysteries of the human brain. Dr. William Newsome, co-chair of the BRAIN planning committee appointed by NIH Director Francis Collins, will describe the project: what it is, why is is important, and how it can be achieved. The committee's report is now available on-line at the NIH BRAIN website: http://nih.gov/science/brain/2025.index.htm
Department of Biology and Centre for Theoretical Neuroscience, University of Waterloo
November 20, 2013
The hippocampus is a brain structure most famously associated with episodic memory -- the ability to recall what happened on our 18th birthday, or where we parked our car this morning. By recording from ensembles of neurons in the rat hippocampus, we can ask how neural activity during experience relates to subsequent memory recall and behavioral choice, at fine timescales. Decoding these neural ensembles reveals that the hippocampus compresses ongoing experience into repeating theta sequences, which can dynamically "look ahead" or "look behind" the animal. Furthermore, subsequent recall is not limited to literal "replay" of experience but includes, for instance, sequences not previously experienced. Finally, neurons in the ventral striatum, a reward-related brain structure that receives inputs from the hippocampus, participate in these hippocampal timing phenomena. Taken together, these observations elucidate how hippocampal memories may contribute to a predictive world model useful for, say, taking a shortcut directly to your car in the parking lot.
National Institute of Mental Health, Bethesda, MD
January 17, 2014
When an individual interacts with its environment, visual events reach the brain in a manner that is both inherently dynamic and highly parallel. In the primate ventral visual cortex, experiments have revealed clustered populations of neurons that respond selectively to flashed images of faces and other object categories. Under natural conditions, does activity in such populations primarily reflect the presence of certain object categories, or is it shaped by other aspects of a scene's temporal dynamics? To investigate this issue, we measured fMRI and single unit activity in macaques as they viewed naturalistic videos depicting a variety of social and nonsocial behaviors. In comparing fMRI time courses to a family of time-varying feature models derived from the videos, we found that one feature, image motion, dominated fMRI responses throughout the ventral visual pathway. Additionally, single unit recordings from the fundus of the anterior STS revealed a diversity of responses across neurons, in which response features were not easily identifiable. This was true even within a face selective region, suggesting that the driving features of these regions may be more complex than seen under traditional experimental designs.
Department of Music and Department of Computer Science, Dartmouth College, Hanover, NH
January 24, 2014
Michael Casey and Jessica Thompson
Our previous work (Casey, Thompson, Kang, Raizada, and Wheatley 2012) investigated decoding hemodynamic brain activity in the feed-forward pathways involved in music listening with rich stimuli. Our current work investigates top-down music processing via auditory imagery with an imagined music task. Most previous work on auditory imagery (e.g. Zatorre 2000; Zatorre, Halpern, and Bouffard 2010) used familiar tunes, such as nursery rhymes, that have associated lyrics which elicit activation of language areas in the brain. We required stimuli that were clearly pitched and musical, but without words, that would be easy to imagine. This led us to choose musical scales, which are accurately imagined by most trained musicians.
Our pilot experiment compared hemodynamic brain activity to heard and imagined musical tones at two different levels of pitch hierarchy; absolute pitch and relative scale degree. We used a continuous scanner acquisition paradigm with a two-second TR. Twenty four major scales were heard and imagined in ascending and descending order. Notes were two seconds long to align with the scanner TR. A total of thirty-six distinct pitches were used in the experiment. The data was labeled in two ways, according to absolute pitch and relative scale degree, without one variable confounding the other. We applied masks for primary auditory cortex, which contains a tonotopic organization of spectro-temporal receptive fields, and secondary auditory cortex (STS/STG), which is implicated in the cognition of hierarchical pitch structures.
Using the MVPA paradigm we tested both spectral clustering (unsupervised) and support vector machine (supervised) classification of high-low and pitch category discrimination for both the heard and imagined BOLD responses with absolute and relative pitch conditions. Preliminary supervised learning results for the absolute-pitch heard experiment yielded Acc=0.57 SE=0.023 (NULL Acc=0.50 SE=0.006) and absolute-pitch imagined results were ACC=0.60 SE=0.04. We will present further results of our preliminary experiments and give an overview of future directions for this work.
The Johns Hopkins University School of Medicine, Department of Neuroscience
May 28, 2014
The hippocampus, long recognized as important for episodic memory function, is increasingly also seen as part of a network that is important for the imagination of future episodes. By recording from many hundreds of neurons simultaneously in freely moving animals, we show that hippocampal neurons are activated in sequences corresponding to temporally-compressed spatial episodes, in a phenomenon often termed "replay". These sequences occur frequently during the awake state, and I will present several features of this activity in novel environments that suggest that learning is required, and that extra-hippocampal circuits process this information. I will also show that, in a spatial memory task, the sequences can proceed from the animal's current location to a remembered goal location, and depict the route that the animal is about to take, even when the specific combination of start and end locations has not been experienced before, i.e. when the trajectory is novel and must be inferred from the animal's prior experience. I will further present evidence from animal models of psychiatric disease showing that these sequence events are specifically impacted. Together, these results suggest a neuronal model system for understanding high-level cognitive function in both normal and disease states.
Last Updated: 9/29/16