Carnegie Mellon University Annual Progress Report: 2011 Formula

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Pennsylvania Department of Health – 2013-2014 Annual C.U.R.E. Report

Carnegie Mellon University – 2011 Formula Grant – Page 1

Carnegie Mellon University

Annual Progress Report: 2011 Formula Grant

Reporting Period

July 1, 2013 – June 30, 2014

Formula Grant Overview

The Carnegie Mellon University received $943,032 in formula funds for the grant award period

January 1, 2012 through December 31, 2014. Accomplishments for the reporting period are

described below.

Research Project 1: Project Title and Purpose

Correlated Structure in Motor Cortical Populations – Motor control is one of the most important

tasks the brain performs, and disorders of motor control affect millions of people. Although a

wealth of psychophysical studies have led to good descriptions of the phenomenological

processes underlying motor control and adaptation, the neural implementations of these

processes are not well understood. One problem is that motor control is inherently a neural

population phenomenon: movements are generated by groups of neurons that must work in a

coordinated fashion to produce precisely timed muscle activation patterns. Using brain-

computer interfaces, we will study how various features of the motor task act to shape the

correlation structure of cortical population activity.

Anticipated Duration of Project

1/1/2012 – 12/31/2014

Project Overview

Volitional motor control is inherently a neural population phenomenon: to generate movements,

neural activity from collections of neurons across multiple brain areas must be coordinated to

result in precisely timed muscle activation patterns. This coordination is expressed by statistical

dependencies in the tuning of groups of neurons, the so-called signal correlation, which arises

from network constraints such as common inputs into groups of neurons. In motor control, these

common inputs relate to the cognitive and behavioral factors underlying movement generation.

By studying how signal correlations relate to various features of the task, like feedback or

redundancy, we can probe how these parameters coordinate population activity in motor cortex

and, ultimately, shape motor planning.

This project is a coupling of experimental and computational approaches to characterize the

flexible correlation structure of motor neuronal populations. We will have monkeys implanted

with chronic multielectrode recording arrays perform a combination of motor tasks including

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arm reaching and brain-computer interface (BCI) cursor control. Data from these tasks will be

used to build a statistical model that fits the correlation structure as a function of both

volitionally controllable driving inputs and task-dependent sensory feedback. Ultimately, the

lessons we learn from the formulation of these models will improve our understanding of the

cognitive and computational principles of motor control, and unite the neural encoding of

movement with behavioral theories of motor control.

Specific Aim 1: Dissociate volitional from non-volitional dependencies in correlation patterns.

Specific Aim 2: Describe how correlation patterns change as a function of task redundancy.

Principal Investigator

Steven M. Chase, PhD

Assistant Professor

Carnegie Mellon University

115 Mellon Institute

4400 Fifth Ave

Pittsburgh, PA 15213

Other Participating Researchers

Andrew Schwartz, PhD – employed by the University of Pittsburgh

Expected Research Outcomes and Benefits

We anticipate several potential outcomes and benefits resulting from this study. (1) This

research has direct implications for improving neural prosthetic devices, which have the potential

to improve the quality of life for a substantial population of patients living with neurological

movement disorders. Results from this study will be leveraged to current, ongoing clinical trials.

(2) Robotic controllers generally lack the flexibility and robustness exhibited in physiological

motor control. By furthering our understanding of the basic mechanisms of motor control, our

findings could improve the design and performance of general autonomous control systems

across a wide variety of applications. (3) Graduate students supported by this grant will be

extensively cross-trained in both computational and experimental approaches to systems

neuroscience, placing them at the forefront of a rapidly growing field. (4) Methodologies

developed during this study will be directly incorporated into the classes taught by the Principal

Investigator.

Summary of Research Completed

Milestones for reporting period:

 Present Aim 1 preliminary results at conference.

 Finish Aim 2 experiments.

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 Implant electrode array into hemisphere 2 and start Aim 1 experiments using neurons

from second hemisphere.

Research accomplished during this reporting period

Last reporting period we acquired a non-human primate and were in the process of training him

to perform arm reaching tasks. In this project period, we completed the training and performed

surgery to implant a chronic multielectrode recording array in primary motor cortex (M1). The

surgery was a success, a sample of recordings from the array are shown in Fig. 1.

Since our theoretical work has progressed more quickly on Aim 2 than on Aim 1, we started

collecting data from the experiments outlined in Aim 2. To examine the effects of task

redundancy on neural recruitment in M1, we have been collecting data in a novel reaching task

where the subject needs to make movements constrained to varying numbers of dimensions. An

example of initial findings in this direction is given in Fig. 2.

In off-line data analysis on previously collected data, we tested the hypothesis that changes in

neural tuning observed during changes in task redundancy are coordinated across neurons. The

data do not support this hypothesis: rather, it appears the changes in each neuron are independent

of the changes in other neurons, a finding that is not predicted by current theories of how

populations of neurons work together to encode movement. These results were reported at the

Computational Systems Neuroscience (Cosyne) annual meeting in Feb. 2014:

Rasmussen, Schwartz, and Chase (2014) Dynamic range adaptation in motor cortical

neurons. Cosyne.

Also in off-line data, we have been attempting to further our understanding of neural correlations

and coordination during movement by investigating the information carried by populations of

neurons about movement parameters. Results of this analysis for arm speed and direction of

movement were published this year in an article that acknowledges CURE funding:

Golub, Yu, Schwartz and Chase (2014). Motor cortical control of movement speed with

implications for brain-machine interface control. J Neurophysiol. 112:411-29.

Although data collection has started, progress on the experimental side of this project is running

slightly behind schedule. We will be requesting a one year no-cost extension so that we may

complete the experiments.

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Figure 1: Screen shot of recordings from the multielectrode recording array chronically implanted in the primary

motor cortex of the monkey on this project. Recordings are shown roughly two months post-surgery. Most

channels show clear signs of action potentials emitted from well-isolated neurons.

Figure 2: Estimates of the information carried by the neural population about target direction, when different

numbers of targets are presented in two dimensions only (left) or three dimensions (right). Note that in the 3D

case, the information carried by the population runs much closer to the theoretical upper limit (dotted lines),

indicating that some task configurations are more efficiently encoded than others.

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Research Project 2: Project Title and Purpose

Non-invasive Optical Imaging of Perceptual Learning and Development – The reliability and

consistency of ordinary sight and hearing makes it natural to presume that perceptual systems are

hard-wired and stable. Instead, however, they are highly dynamic and adapt flexibly to allow

perceivers to discover regularities in the environment. In fact, over time perceptual expertise

develops such that the brain’s response to some classes of highly significant stimuli (faces,

written words, speech) is markedly distinct. Our ultimate objective is to understand the learning

mechanisms that serve the development of perceptual expertise to better understand

developmental disorders (autism, dyslexia) and brain injuries that affect perception and to

engineer devices to improve perception among those with impairments.

Anticipated Duration of Project

1/1/2012 – 12/31/2014

Project Overview

Our ultimate goal is to understand how perceptual systems are shaped by experience to develop

perceptual expertise for some classes of stimuli. Humans exhibit such expertise for faces and

native-language speech sounds and, later with developing literacy, for printed words. Human

perceptual expertise for recognizing and categorizing these stimuli well exceeds the capacity of

even the most sophisticated software for face and speech recognition. Understanding the learning

mechanisms involved with extracting perceptual regularity from an inherently noisy and variable

environment will provide insight about how to improve automatic machine recognition systems.

It will also inform how to remediate perceptual problems arising from brain injury and

developmental disorders and how to build effective rehabilitation programs for individuals with

perceptual impairments.

The specific long-term aim is to address the development of perceptual expertise among pre-

school aged children, a developmental window during which perceptual systems are thought to

be highly malleable and during which time developmental disorders that impact perceptual

expertise (autism, specific language impairment) tend to be discovered. The present research is

unique and innovative because it allows for simultaneous measurement of brain and behavioral

responses in young children who are unable to participate in many other forms of neuroimaging

research, thus allowing us to probe the development of perceptual expertise. In the present

project, we test the hypothesis that adaptation of an optical neuroimaging signal will serve as a

more sensitive measure of children’s phonetic representations than their behavioral responses

and 2) that acoustic context will further shape these representations. At a broad level, achieving

our aims will set the stage for Carnegie Mellon University’s faculty to focus its research

expertise toward innovative new approaches to studying the development of perceptual expertise

and its health implications.

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Principal Investigator

Lori L. Holt, PhD

Professor

Carnegie Mellon University

5000 Forbes Avenue

Pittsburgh, PA 15213

Other Participating Researchers

Kai-Min Chang, PhD; Marlene Berhmann, PhD; David Plaut, PhD; David Rakison, PhD;

Erik Thiessen, PhD; Anna Fisher, PhD; Nathan Urban, PhD; Michael Tarr, PhD – employed by

Carnegie Mellon University

Theodore Huppert, PhD – employed by the University of Pittsburgh

Expected Research Outcomes and Benefits

Perceptual learning is a robust phenomenon, measurable throughout the lifespan in humans and

other species that is thought to support a variety of basic cognitive, perceptual and language

functions. It is important because changes in the way that perceptual input is processed and

represented impact all subsequent processing at higher levels. Understanding brain function as it

relates to developing perceptual expertise for particular classes of stimuli will allow us to

generate models of how perceptual learning can be harnessed to improve perceptual processing

(such as training physicians to better detect tumors in visually-noisy scans) and remediate

everyday perception when perceptual systems go awry. Deficits in perceptual learning are

observed across a variety of brain disorders including schizophrenia for auditory processing,

autism for faces and speech, specific language impairment and dyslexia for spoken language and

words, and in response to traumatic brain injury, stroke, and seizure. Determining how to

engineer systems to remediate brain disorders affecting perceptual processing requires an

understanding of the relationship of brain function to perceptual learning and how perceptual

expertise for specific classes of stimuli develops. Neuroimaging tools that can be used effectively

to study the developing brain are necessary in this endeavor. The present project exploits

functional near-infrared spectroscopy (fNIRS) as a neuroimaging technique suitable for use with

children and therefore significant for measuring brain development. By understanding how the

brain changes with development of perceptual expertise, we believe we can better understand the

causes of perceptual symptoms for brain disorders.

Summary of Research Completed

Milestones for reporting period: Collect data to test hypotheses with child participants; analyze

data and prepare report(s) of results.

Research accomplished during this reporting period

In the present project year we achieved our objective to authorize near infrared spectroscopy

(NIRS) as “minimal risk” for use in research with children and adults, as it is on other campuses

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internationally (and as are other neuroimaging techniques like functional magnetic resonance

imaging, fMRI). This opens the opportunity to test children at the Carnegie Mellon Children’s

School in our experiments. The approval process involved a great deal of coordination, visits

from international experts to discuss ethics with our review panel, and multiple meetings with

the Carnegie Mellon University Institutional Review Board.

With approval to conduct research, we have begun training researchers ranging from graduate

students to faculty in NIRS research, experimental design, and research protocols. We have

benefited from the expertise of Dr. Theodore Huppert of University of Pittsburgh in leading

these efforts. During the past year, we met our milestone of pilot testing our new NIRS system

with adult participants. We were unable to enroll child participants during this period due to

delays in moving our protocol through the process to certify NIRS as minimal risk and thereby

suitable for testing children at the Carnegie Mellon Children’s School. Now that we have full

approval for research with adult and child participants we wish to expand the research by one

year to complete this work.

We have also achieved scientific objectives. Dr. Marlene Behrmann’s laboratory at Carnegie

Mellon University has initiated a study of the hemodynamic response in the visual cortex as

individuals (adult participants) view a series of achromatic grating patterns. The patterns have

either a drifting or vibrating motion and vary in contrast. The ultimate purpose of this research is

to investigate basic sensory-evoked responses in individuals with autism. The project has

received Institutional Review and is underway.

Drs. Anna Fisher and Erik Thiessen of Carnegie Mellon University are collaborating to pursue

NIRS as a measure of the development of selective sustained attention through the preschool and

elementary school years. They address several key issues using a novel paradigm for assessing

selective sustained attention in young children. A broad aim is to examine selective sustained

attention and specify developmental trajectories of selective sustained attention in 2- to 7-year-

old children thereby establishing a baseline contributing to the efforts of refining the cognitive

phenotype of the Attention Deficit Hyperactivity Disorder (ADHD). The use of NIRS will bear

on the often-hypothesized developmental changes in the contribution of exogenous and

endogenous factors to selective sustained attention. In this project period, Drs. Fisher and

Thiessen submitted a grant proposal entitled “Development of Selective Sustained Attention in

Preschool and Elementary School Children,” they trained their laboratories in NIRS protocols,

established software to link their behavioral experiments to the time course of NIRS data

collection, and developed a collaborative relationship with Dr. Theodore Huppert who is a local

expert in NIRS. The project has passed Institutional Review and is ready to begin pilot testing

with children.

Our scientific achievements also involved pilot testing behavioral protocols suitable for pairing

with NIRS among both adult and child participants.

Through extensive preliminary research we have verified the effectiveness of a simple incidental

training paradigm, the Systematic Multimodal Associations Reaction Time (SMART) task, in

training listeners to categorize sounds. This task mimics critical aspects of learning in natural

environments (multimodal associations, predictive relationships, indirect training, no explicit

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instruction or feedback), but its simple task demands are amenable for use among patients and

children.

In the SMART task, participants must rapidly detect the appearance of a visual stimulus among

four possible screen locations and report its position with a key press (Figure 1). A brief sound

precedes the appearance of each visual target. Unknown to participants, each sound is an

exemplar drawn from one of four distinct sound categories. In the first three blocks and the fifth

experiment block the relationship between the sound category and the visual target location is

fixed such that the sound category is consistently associated with one of the visual target

locations (Training Blocks, 100 trials/block). In the fourth block, this association is destroyed by

random assignment of sound categories to visual target locations (Test Block – Random). On

each trial of each block, the task is rapid visual detection. However, if participants incidentally

learn about the sound categories due to the consistent pairing of sound category exemplars with

the location of the visual target in the Training Blocks, we expect reaction time to detect the

visual target to be slower in the random Test Block when the relationship between sound and

visual target is arbitrary. We refer to this implicit measure of auditory category learning as the

RT cost (RT

Block4

– RT

Block3

). We also measure category learning and generalization to novel

exemplars explicitly via an explicit sound categorization task that follows the SMART task. In

this task, participants hear a sound exemplar drawn from the sound categories experienced

during the visual detection task, but not heard previously. They indicate which box an “X” would

be most likely to appear (although no visual targets appear in this task and there is no feedback

about the correctness of responses). Each sound is presented 20 times in a random order. This

presents the opportunity to collect both implicit and explicit measures of auditory category

learning as well as to examine the extent to which the measures are in agreement. Our results

(Figure 2) demonstrate the effectiveness of this indirect training task in producing robust

nonspeech auditory and non-native speech category learning among typical adults. Each measure

shows evidence of generalization of acquired category knowledge to novel category exemplars

not heard in training, a hallmark of robust category learning. In all, the entire task takes about 40

minutes for control participants to complete. It is simple and easily administered. We expect

patients and children to be slower to respond in the SMART task relative to control participants.

What is unique about the SMART task is that it capitalizes on a simple, overt visual detection

task to incidentally train participants to learn to learn auditory categories. It is extremely well-

suited for use with NIRS due to its block structure.

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