CNBC logo


2015 CNBC Retreat Schedule | Print |

Events held in Sunburst Room unless otherwise noted.

Friday, October 9

5:00 pm Check-in for guests with Friday arrivals

7:00 pm

Pizza/Salad/Soft Drinks

Training Program Overview
Nathan Urban & Rob Kass, CNBC Co-Directors
Carol Colby & Dave Touretzky, CNBC Education Committee Co-Chairs

Speed Data-ing and Collaborative Group Activity
Seasons Room 1-5


Saturday, October 10

8:30 am

Continental Breakfast, Seasons 3-5
Meeting, Sunburst Room

8:55 am


Matthew Smith, Ph.D.
Ophthalmology, University of Pittsburgh

Timothy Verstynen, Ph.D.
Psychology, Carnegie Mellon University

9:00-10:30 am

Session 1: Neuroscience of Addiction
Moderator: Matt Smith, Ph.D.

Erika Forbes, Ph.D.
Psychiatry, University of Pittsburgh
Reward circuitry: A role in the development of depression (abstract)

Yan Dong, Ph.D.
Neuroscience, University of Pittsburgh
Synaptic remodeling underlying cocaine craving (abstract)

Susanne Ahmari, M.D., Ph.D.
Psychiatry, University of Pittsburgh
Visualizing cortico-striatal activity during emergence of compulsive behaviors (abstract)

10:30-11:00 am



11:00-12:30 pm


Session 2: Trainee Award Talks
Moderator: Matt Smith, Ph.D.

Adam Snyder, Ph.D.
Electrical & Computer Engineering, Carnegie Mellon University
Global network influences on local functional connectivity (abstract)

Joanna Urban-Ciecko, Ph.D.
Biological Sciences, Carnegie Mellon University
Neocortical somatostatin neurons reversibly silence excitatory transmission via GABAb receptors (abstract)

Moderator: Tim Verstynen, Ph.D.

Chelsea Eddington
Psychology, University of Pittsburgh
How meaning similarity influences ambiguous word processing: The current state of the literature (abstract)

Kevin Jarbo
Psychology, Carnegie Mellon University
Converging structural and functional connectivity of orbitofrontal, dorsolateral prefrontal, and posterior parietal cortex in the human striatum (abstract)

12:30-1:30 pm

Box Lunch & Faculty/Post Doc/Student meetings

Faculty Lunch/Meeting in Wintergreen

Post Doc Lunch/Meeting in Hemlock

Student Lunch/Meeting in Sunburst
(Students please pick up lunch in Seasons 3)


1:30-3:00 pm


Free Time
(Student Reps organizing events)

3:00-4:00 pm

Session 3: Big Data Neuroscience
Moderator: Tim Verstynen, Ph.D.

Andreas Pfenning, Ph.D.
Computational Biology, Carnegie Mellon University
Data-driven approach to identifying the mechanisms underlying neural disorders (abstract)

Jana Kainerstorfer, Ph.D.
Biomedical Engineering, Carnegie Mellon University
Non-invasive near-infrared imaging of cerebral function in humans (abstract)

4:00-5:10 pm

Keynote Address:

Chris Eliasmith, Ph.D.
Director, Center for Theoretical Neuroscience
University of Waterloo
Building brains from bottom to top (abstract)

Sunburst Room


5:10-5:30 pm


Seasons 3-5


5:30-6:50 pm


Panel Discussion: Big Brain Data - Is there a battle between data-driven and model-driven approaches?
Moderators: Matt Smith, Ph.D. & Tim Verstynen, Ph.D.

Susanne Ahmari, M.D., Ph.D.
Psychiatry, University of Pittsburgh

Steve Chase, Ph.D.
CNBC / Biomedical Engineering, Carnegie Mellon University

Chris Eliasmith, Ph.D.
Center for Theoretical Neuroscience, University of Waterloo

Andreas Pfenning, Ph.D.
Computational Biology, Carnegie Mellon University

7:00-9:30 pm

Dinner & Poster Session
Grand Ballroom




Susanne Ahmari, M.D., Ph.D.

Visualizing cortico-striatal activity during emergence of compulsive behaviors

Compulsive behaviors are a central component of Obsessive Compulsive Disorder (OCD), as well as prominent, disabling and notoriously-treatment resistant symptoms of many severe psychiatric disorders, including autism, schizophrenia, and addiction. Although OCD symptoms have been broadly linked to abnormal activity in cortical-basal ganglia circuits via human imaging studies, we still have a quite limited understanding of how maladaptive repetitive behaviors are encoded in the brain. Our lab is using novel technologic approaches and statistical strategies that finally allow us to address this topic by determining: 1) which neural circuits underlie maladaptive repetitive behaviors, 2) how these behaviors are encoded in the brain, and 3) when the neural code changes as these behaviors develop and resolve.

Our previous work has demonstrated that a) brief but repeated optogenetic hyperstimulation of projections from orbitofrontal cortex (OFC) to ventromedial striatum (VMS) leads to long-lasting perseverative grooming, a mouse behavior linked to OCD (Ahmari et al, Science, 2013); and b) compulsive grooming behavior is associated with increased neural activity in the striatum (measured in awake-behaving mice using both in vivo microscopy and in vivo electrophysiology). Using transgenic OCD mouse-models and healthy control mice combined with in vivo optogenetics, electrophysiology, and microscopy, we are now identifying the specific activity patterns, cell-types, and circuits responsible for the development of abnormal repetitive behaviors. Preliminary findings suggest that perseverative grooming induced via both pharmacologic or transgenic methods is associated with pauses in ventral striatal neural activity, despite overall increased firing rates. This suggests potential novel neural mechanisms underlying the generation of abnormal repetitive behaviors.

Yan Dong, Ph.D.

Synaptic remodeling underlying cocaine craving

A transient but prominent increase in the level of “silent synapses” – a signature of immature glutamatergic synapses that contain only NMDA receptors without stably expressed AMPA receptors – has been identified in the nucleus accumbens (NAc) following exposure to cocaine. As the NAc is a critical forebrain region implicated in forming addiction-associated behaviors, the initial discoveries have raised speculations about whether and how these drug-induced synapses mature and potentially contribute to addiction-related behaviors. Here, we summarize recent progress in recognizing the pathway-specific regulations of silent synapse maturation, and its diverse impacts on behavior. We provide an update of the guiding hypothesis – the Neural Rejuvenation Hypothesis – with recently emerged evidence of silent synapses in cocaine craving and relapse.

Chelsea Eddington

How meaning similarity influences ambiguous word processing: The current state of the literature

The majority of words in the English language do not correspond to a single meaning, but rather correspond to two or more unrelated meanings (i.e., are homonyms) or multiple related senses (i.e., are polysemes). It has been proposed that the different types of "semantically-ambiguous words" (i.e., words with more than one meaning) are processed and represented differently in the human mind. Several review papers and books have been written on the subject of semantic ambiguity (e.g., Adriaens, Small, Cottrell, & Tanenhaus, 1988; Burgess & Simpson, 1988; Degani & Tokowicz, 2010; Gorfein, 1989, 2001; Simpson, 1984). However, several more recent studies (e.g., Klein & Murphy, 2001; Klepousniotou, 2002; Klepousniotou & Baum, 2007; Rodd, Gaskell, & Marslen-Wilson, 2002) have investigated the role of the semantic similarity between the multiple meanings of ambiguous words on processing and representation, whereas this was not the emphasis of previous reviews of the literature. In this review, we focus on the current state of the semantic ambiguity literature that examines how different types of ambiguous words influence processing and representation. We analyze the consistent and inconsistent findings reported in the literature and how factors such as semantic similarity, meaning/sense frequency, task, timing, and modality affect ambiguous word processing. We discuss the findings with respect to recent parallel distributed processing (PDP) models of ambiguity processing (Armstrong & Plaut, 2008, 2011; Rodd, Gaskell, & Marslen-Wilson, 2004). Finally, we discuss how experience/instance-based models (e.g., Hintzman, 1986; Reichle & Perfetti, 2003) can inform a comprehensive understanding of semantic ambiguity resolution.

Chris Eliasmith, Ph.D.

Building brains from bottom to top

There has recently been an international surge of interest in building large brain models. The European Union's Human Brain Project (HBP) has received 1 billion euros worth of funding, and President Obama announced the Brain Initiative along with a similar level of funding. However the large scale models affiliated with both projects do not demonstrate how their generated complex neural activity relates to observable behaviour -- arguably the central challenge for neuroscience. I will present our recent work on large-scale brain modeling that is focussed on both biological realism and reproducing human behaviour. I will demonstrate how the model relates to both low-level neural data and high-level behavioural data. Finally, I will discuss applications of this research to understanding both the biological basis of cognition and building more advanced robots.

Erika Forbes, Ph.D.

Reward circuitry: A role in the development of depression

Adolescence is notable for changes in both reward-driven behavior and function in neural reward circuitry, and it is also the most vulnerable time for the emergence of depression. Seemingly paradoxically, the same behavioral, social, and neural changes that make adolescence a time of fun-seeking are postulated to contribute to the development of depression. This presentation will focus on neural reward systems as a factor in the etiology, pathophysiology, and treatment of depression. Consistent with longstanding conceptual models of reduced positive affect in depression, our findings implicate disruptions in reward systems, including regions such as the striatum and medial prefrontal cortex, in adolescent depression. In addition, we have found that function in adolescents’ reward circuitry is associated with early social context, predicts increase in depression over time, and predicts response to treatment. More recently, we have focused on social reward and personally relevant reward as contexts that are especially sensitive to depression. This work points toward future investigation of topics such as the development of co-occurring depression and substance use. With greater integration of affective neuroscience and developmental psychopathology, efforts to understand and prevent depression can be increasingly fruitful.

Kevin Jarbo

Converging structural and functional connectivity of orbitofrontal, dorsolateral prefrontal, and posterior parietal cortex in the human striatum

Modification of spatial attention via reinforcement learning (Lee and Shomstein, 2013) requires the integration of reward, attention, and executive processes. Corticostriatal pathways are an ideal neural substrate for this integration because these projections exhibit a globally parallel (Alexander et al., 1986 ), but locally overlapping (Haber, 2003), topographical organization. Here we explore whether there are unique striatal regions that exhibit convergent anatomical connections from orbitofrontal cortex, dorsolateral prefrontal cortex, and posterior parietal cortex. Deterministic fiber tractography on diffusion spectrum imaging data from neurologically healthy adults (N = 60) was used to map frontostriatal and parietostriatal projections. In general, projections from cortex were organized according to both a medial–lateral and a rostral–caudal gradient along the striatal nuclei. Within rostral aspects of the striatum, we identified two bilateral convergence zones (one in the caudate nucleus and another in the putamen) that consisted of voxels with unique projections from orbitofrontal cortex, dorsolateral prefrontal cortex, and parietal regions. The distributed cortical connectivity of these striatal convergence zones was confirmed with follow-up functional connectivity analysis from resting state fMRI data, in which a high percentage of structurally connected voxels also showed significant functional connectivity. The specificity of this convergent architecture to these regions of the rostral striatum was validated against control analysis of connectivity within the motor putamen. These results delineate a neurologically plausible network of converging corticostriatal projections that may support the integration of reward, executive control, and spatial attention that occurs during spatial reinforcement learning.

Jana Kainerstorfer, Ph.D.

Non-invasive near-infrared imaging of cerebral function in humans

Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical technique that measures the cerebral concentrations of oxy-hemoglobin and deoxy-hemoglobin with a time resolution of tens of milliseconds. Similar to fMRI, task related functional activation can be measured. While fMRI has superior spatial resolution, fNIRS benefits from high temporal resolutions as well as from measuring both oxy-hemoglobin and deoxy-hemoglobin concentration changes. In this talk I will describe advantages and limitations of fNIRS and how we use fNIRS data sets to obtain information about changes in cerebral blood volume (CBV), cerebral blood flow (CBF), as well as cerebral metabolic rate of oxygen (CMRO2). I will further describe how we use fNIRS to (a) model cerebral hemodynamic changes in the brain and their microvascular alterations due to disease and (b) for clinical translation and measurements on a variety of patient populations. I will also introduce a novel hemodynamic model, which in conjunction with fNIRS allows for quantification of local cerebral autoregulation as well as for measurements of microvascular venous oxygen saturation, both important physiological parameters in a variety of diseases.

Andreas Pfenning, Ph.D.

Data-driven approach to identifying the mechanisms underlying neural disorders

Advances in genomics have allowed research teams to create large genome-wide associations study cohorts, with up to hundreds of thousands of subjects, which combine genetic information on millions of locations in the genome with disease diagnostics. Translating those large datasets into knowledge of the brain has been enormously challenging, as vast majority of sequence mutations associated with complex neurological and psychiatric disorders lie in poorly understood non-coding regions of the genome.  In this talk, I will describe my research to understand the consequence of those non-coding sequence mutations on brain function, which integrates information from several sources. First, high-throughput epigenetic experiments show which brain regions are most relevant to neural disorders. Then, an analysis of expression quantitative train loci (eQTLs) relates those mutations to genes and pathways. Using these methods, I provide evidence that Alzheimer’s disease predisposition is primarily mediated by the immune system and that Schizophrenia is influenced by how a neuron responds to activity.

Adam Snyder, Ph.D.

Global network influences on local functional connectivity

A central neuroscientific pursuit is understanding neuronal interactions that support computations underlying cognition and behavior. Although neurons interact across disparate scales – from cortical columns to whole-brain networks – research has been restricted to one scale at a time. We measured local interactions through multi-neuronal recordings while accessing global networks using scalp EEG in Rhesus macaques. We measured spike count correlation, an index of functional connectivity with computational relevance, and EEG oscillations, which have been linked to various cognitive functions. We found a surprising non-monotonic relationship between EEG oscillation amplitude and spike count correlation, contrary to the intuitive expectation of a direct relationship. With a widely-used network model we were able to replicate these findings by incorporating a private signal targeting inhibitory neurons, a common mechanism proposed for gain modulation. Finally, we report that spike count correlation explains nonlinearities in the relationship between EEG oscillations and response time in a spatial selective attention task.

Joanna Urban-Ciecko, Ph.D.

Neocortical somatostatin neurons reversibly silence excitatory transmission via GABAb receptors

Understanding the dynamic range for excitatory transmission is a critical component of building a functional circuit diagram for the mammalian brain. Here we show that, in the context of network activity, excitatory synaptic transmission between neocortical neurons in rodent somatosensory cortex is markedly lower than expected, measured both by lower EPSP amplitude and high failure rates. This phenomenon is mediated by tonic activation of presynaptic GABAb receptors that is gated through the spontaneous activity of somatostatin-expressing interneurons. Optogenetic suppression of somatostatin neuron firing was sufficient to enhance EPSP amplitude and reduce failure rates, effects that were fully reversible and occluded by GABAb antagonists. These data indicate that somatostatin-expressing interneurons can rapidly and reversibly rewire neocortical networks through controlling presynaptic release properties, and provide a specific synaptic mechanism by which these cells could gate plasticity and learning.

Building brains from bottom to top