CNBC Annual Retreat 7 Springs Resort and Conference Center 10/7-9/16

Transcription

1 CNBC Annual Retreat 7 Springs Resort and Conference Center 10/7-9/16 FRIDAY, October 7, :00 PM Check-in for guests with Friday arrival 7:00-9:30 PM Pizza party and student grant-building with group data blitz Carol Colby & Dave Touretzky, CNBC Education Committee Co-Directors Season s 1-5 9:30 PM midnight Student games and party SATURDAY, October 8, 2016 SESSION I TRAINEE TALKS McClelland Awards (Student) 10:00 AM Matthew Golub, Ph.D. Electrical and Computer Engineering, Carnegie Mellon University Internal models for interpreting neural population activity during sensorimotor control 10:30 AM Kyle Dunovan Competing basal-ganglia pathways determine the difference between stopping and deciding not to go Strick Awards (Postdoc) 11:00 AM Elizabeth Hirshorn, Ph.D. Decoding and disrupting left mid fusiform gyrus activity during word reading 11:30 AM Darcy Griffin, Ph.D. Systems Neuroscience Institute, University of Pittsburgh Motor output through the corticomotoneuronal system 12:00 PM 3:00 PM Break / Lunch (Free Time) Please pick up a box lunch in the Wintergreen Room, next to registration table 12:00 PM 1:00 PM Postdoc Data Brunch (open to everyone) 2:45 PM Break / Snack Wintergreen Room

2 SESSION II FROM EYES TO EYE FIELDS 3:00-3:40 PM Kevin Chan, Ph.D., Assistant Professor Departments of Ophthalmology & Bioengineering, University of Pittsburgh The neural basis of sensory substitution in the blind 3:40-4:20 PM Neeraj (Raj) Gandhi, Ph.D., Associate Professor Department of Bioengineering, University of Pittsburgh Temporal dynamics of sensory-to-motor transformation in control of eye movements 4:20-5:00 PM Louis-Philippe Morency, Ph.D., Assistant Professor Language Technology Institute, School of Computer Science, Carnegie Mellon University Modeling human communication dynamics 5:00-5:15 PM Break 5:15 PM 6:15 PM Keynote: Sabine Kastner, Ph.D. Professor of Neuroscience & Psychology, Princeton Neuroscience Institute Neural dynamics of the primate attention network 6:15-9:15 PM Poster Session / Dinner Grand Ballroom 9:30-11:00 PM Junior Faculty and Postdoc Happy Hour Matterhorn Lounge SUNDAY, October 9, 2016 SESSION III NEW(ISH) FACULTY TALKS 10:00-10:20 AM Poster Award Winner s Data Blitz Session 10:20-11:00 AM Marc Coutanche, Ph.D., Assistant Professor The employment of neural systems in human learning: Determinants and implications for memory 11:00-11:40 AM Maysam Chamanzar, Ph.D., Assistant Professor Electrical and Computer Engineering, Carnegie Mellon University Next generation neural interfaces: From physical implants to virtual implants 11:40-11:45 AM Closing remarks

3 ABSTRACTS Maysam Chamanzar, Ph.D., Electrical and Computer Engineering, Carnegie Mellon University Next Generation neural interfaces: from physical implants to virtual implants The development of new neural technologies will revolutionize our understanding of the brain function enabling us to mitigate nervous system disorders and also advance brain-machine interfaces (BMIs). In this talk, I will introduce the needs and opportunities to make next generation neural interfaces. I will discuss ongoing research in my lab on developing hybrid implantable optrodes (optical-electrical probes) for neural recording and stimulation. Benefiting from the best of both silicon and polymer material properties, these probes have greater than ten times the density and are two orders of magnitude more compliant than the state of the art, exerting minimal tissue damage and tethering forces while still providing full-volume cortical sampling. I will also introduce a novel parylene-inparylene (PiP) photonics platform that can be monolithically integrated with our probes for high-resolution optogenetic stimulation in ECoGs. I will also discuss a radical complementary approach to guide and steer light in the brain for targeted optogenetic stimulation. In this approach, non-invasive ultrasound will define and guide the trajectory of light without physically implanting either a waveguide or a light source. The trajectory of light deep in the tissue can be steered fast by reconfiguring ultrasound interference patterns in the brain tissue. Kevin Chan, Ph.D., Departments of Ophthalmology & Bioengineering, University of Pittsburgh The neural basis of sensory substitution in the blind Vision loss is a major health problem worldwide. Although sensory substitution devices such as the BrainPort tactilevision device and the voice sound-vision device can provide indirect visual perception to the blind subjects using alternative senses, little is known about the mechanisms through which the multisensory processes interact with the neural connections to influence perception and behavior in the blind. This talk will discuss the plastic changes in the visually impaired brains, and the structural and functional brain involvements in the context of sensory substitution use in blind subjects using advanced magnetic resonance imaging. Marc Coutanche, Ph.D., The employment of neural systems in human learning: Determinants and implications for memory Learning from our environment draws on a multitude of brain systems, including networks underlying perception, meaning, and language, among others. The particular set of brain regions engaged at any moment, and their respective roles, can differ based on subtle (but systematic) variations in the learning context, and the learner s brain. In this talk, I will discuss recent work from my lab investigating factors that affect how brain systems are employed to acquire declarative information, and the impact on the nature of the eventual memories. I will first describe evidence that learning with the simultaneous processing of known concepts leads to rapid cortical encoding, which in turn impacts future retrieval. Next, I will discuss how anatomical differences relate to the types of information that an individual extracts from learning episodes. Finally, I will connect this with insights into the role of the ventral stream in perception and memory. Kyle Dunovan, Psychology, University of Pittsburgh Competing basal-ganglia pathways determine the difference between stopping and deciding not to go The architecture of corticobasal ganglia pathways allows for many routes to inhibit a planned action: the hyperdirect pathway performs fast action cancellation and the indirect pathway competitively constrains execution signals from the direct pathway. We present a novel model, principled off of basal ganglia circuitry, that differentiates control dynamics of reactive stopping from intrinsic no-go decisions. Using a nested diffusion model, we show how reactive braking depends on the state of an execution process. In contrast, no-go decisions are best captured by a failure of the

4 execution process to reach the decision threshold due to increasing constraints on the drift rate. This model accounts for both behavioral and functional MRI (fmri) responses during inhibitory control tasks better than alternative models. The advantage of this framework is that it allows for incorporating the effects of context in reactive and proactive control into a single unifying parameter, while distinguishing action cancellation from no-go decisions. Neeraj (Raj) Gandhi, Ph.D., Department of Bioengineering, University of Pittsburgh Temporal dynamics of sensory-to-motor transformation in control of eye movements Sensory-to-motor transformations are fundamental for facilitating interactions with the environment. When shifting the visual axis to an object of interest, neurons in many structures along the oculomotor neuraxis (e.g., frontal eye fields, superior colliculus) discharge an initial sensory burst of spikes to register the stimulus and then a motor burst to trigger the saccadic eye movement. Given that such neurons project to the eye movement generating circuitry in the brainstem, a long standing enigma has been why the initial sensory burst is unable to trigger a movement while the subsequent motor burst is sufficient. One leading theory states that the movement is triggered when premotor activity reaches a threshold that is able to overcome potent inhibition of the saccadic system. This view is unsatisfactory because the threshold level could be crossed by the visual burst also but without triggering a saccade. I will present an alternate hypothesis that the saccade initiation signal requires not only a high firing rate but also temporal consistency in the population activity. I will provide evidence that the sensory burst has unstable temporal dynamics and therefore cannot trigger a saccade, while the premotor burst is stable and hence suited to initiate the movement. Matthew Golub, Ph.D., Electrical and Computer Engineering, Carnegie Mellon University Internal models for interpreting neural population activity during sensorimotor control To successfully guide limb movements, the brain takes in sensory information about the limb, internally tracks the state of the limb, and produces appropriate motor commands. It is widely believed that this process uses an internal model, which describes our prior beliefs about how the limb responds to motor commands. Here, we leveraged a brainmachine interface (BMI) paradigm in rhesus monkeys and novel statistical analyses of neural population activity to gain insight into moment-by-moment internal model computations. We discovered that a mismatch between subjects internal models and the actual BMI explains roughly 65% of movement errors, as well as long-standing deficiencies in BMI speed control. More broadly, this work provides an approach for interpreting neural population activity in the context of how prior beliefs guide the transformation of sensory input to motor output. Darcy Griffin, Ph.D., Systems Neuroscience Institute, University of Pittsburgh Motor output through the corticomotoneuronal system Muscles are multi-functional. They serve as agonists for some directions of movement and as synergists, fixators and antagonist for others. Movement dexterity depends on the central control over the precise timing and amplitude not only of agonist muscle activity, but also of muscles performing other functions. We examined the contribution of the corticomotoneuronal (CM) cell population to the generation of different muscle functions. CM cells are a specialized subset of primary motor cortex (M1) output neurons that make monosynaptic connections with spinal motoneurons. We used spike-triggered averaging of electromyographic activity to identify CM cells and their target muscles. We analyzed the activity of CM cells and their target muscles while a monkey performed a wrist task which required movement in eight directions across three different wrist postures. We found that different CM cells connected to the same muscle activated the muscle for different functions (i.e. agonist, synergist, fixator or antagonist). Thus, separate populations of CM cells are used to generate different muscle functions. Elizabeth Hirshorn, Ph.D., Psychology, University of Pittsburgh Decoding and disrupting left mid fusiform gyrus activity during word reading The nature of the visual representation for words in the brain has been debated for over 150 years, with a resurgence in the last 15 years. We used direct brain stimulation and intracranial electroencephalography to provide support for, and elaborate upon, the visual word form hypothesis. This hypothesis states that activity in the left midfusiform gyrus (lmfg) reflects visually organized information about words and word parts. In patients with electrodes placed directly in their

5 lmfg, we found that disrupting lmfg activity through stimulation led to impaired perception of whole words and letters. Furthermore, using machine-learning methods to analyze the electrophysiological data from these electrodes, we found that information in the lmfg contributed to at least two distinguishable stages of word processing: an early stage that reflects gist-level visual representation sensitive to orthographic statistics and consistent with an orthographic similarity space, and a later stage that reflects more precise representation sufficient for the individuation of orthographic word forms. These results provide strong support for the visual word form hypothesis and demonstrate that across time the lmfg is involved in multiple stages of orthographic representation. Sabine Kastner, Ph.D., Princeton Neuroscience Institute, Princeton University Neural dynamics of the primate attention network The selection of information from our cluttered sensory environments is one of the most fundamental cognitive operations performed by the primate brain. In the visual domain, the selection process is thought to be mediated by a static spatial mechanism a spotlight that can be flexibly shifted around the visual scene. This spatial search mechanism has been associated with a large-scale network that consists of multiple nodes distributed across all major cortical lobes and includes also subcortical regions. To identify the specific functions of each network node and their functional interactions is a major goal for the field of cognitive neuroscience. In my lecture, I will challenge two common notions of attention research. First, I will show behavioral and neural evidence that the attentional spotlight is neither stationary nor unitary. In the appropriate behavioral context, even when spatial attention is sustained at a given location, additional spatial mechanisms operate flexibly in parallel to monitor the visual environment. Second, spatial attention is assumed to be under top-down control of higher order cortex. In contrast, I will provide neural evidence indicating that attentional control is exerted through thalamo-cortical interactions. Together, this evidence indicates the need for major revisions of traditional attention accounts. Louis-Philippe Morency, Ph.D., Language Technology Institute, School of Computer Science, Carnegie Mellon University Modeling human communication dynamics Human face-to-face communication is a little like a dance, in that participants continuously adjust their behaviors based on verbal and nonverbal cues from the social context. Today s computers and interactive devices are still lacking many of these human-like abilities to hold fluid and natural interactions. Leveraging recent advances in machine learning, audio-visual signal processing and computational linguistic, my research focuses on creating computational technologies able to analyze, recognize and predict human subtle communicative behaviors in social context. I formalize this new research endeavor with a Human Communication Dynamics framework, addressing four key computational challenges: behavioral dynamic, multimodal dynamic, interpersonal dynamic and societal dynamic. Central to this research effort is the introduction of new probabilistic models able to learn the temporal and fine-grained latent dependencies across behaviors, modalities and interlocutors. In this talk, I will present some of our recent achievements modeling multiple aspects of human communication dynamics, motivated by applications in healthcare (depression, PTSD, suicide, autism), education (learning analytics), business (negotiation, interpersonal skills) and social multimedia (opinion mining, social influence).