Eleventh Annual Summer Interdisciplinary Conference

Authors, Titles, Abstracts


Listing by speaker

SpeakerBiederman, Irving
Author 1Biederman, Irving
University of Southern California
bieder@usc.edu
Author 2Lescroart, Mark D.
University of Southern California
mark.lescroart@berkeley.edu
Author 3Kim, Jiye G.
University of Southern California
jiyekim@princeton.edu
Author 4Hayworth, Kenneth J.
University of Southern California
hayworth@fas.harvard.edu
TitleThe Neural Basis of Visual Relations
AbstractThe identity of an object is not only specified by the shape of its parts but also by the relations among the parts. Rearranging parts can produce a completely different object, in the same manner as rearranging the phonemes in “fur” can yield “rough.” How does the visual system represent the relative positions of parts? Formally, between-part relations can be characterized by specifying the relations between the medial axes (imaginary lines through the centers) of an object’s parts. An fMRI multi-voxel classification study tested whether the medial axis structure is represented in the human visual system independent of part identity and overall object orientation. In visual regions of interest, a support vector machine classifier was trained to distinguish objects that shared either the same medial axis structures or the same orientations. Whereas in V1, orientation dominated, by the level of V3, different medial axis structures were more accurately classified than different orientations, indicating a change in the representation of shape compared to earlier visual areas even when the subjects were not performing a discrimination based on axis structure. The sensitivity to relative vs. absolute position holds not only for the relations between parts but the relations between objects that define real-world scenes. The picture that emerges is one in which part and scene-like relations are not inferred at some stage following object identification but are likely achieved simultaneously with the specification of object shape.


SpeakerEliasmith, Chris
Author 1Eliasmith, Chris
University of Waterloo
celiasmith@uwaterloo.ca
Author 2Choo, Xuan
University of Waterloo
xchoo.mainframe@gmail.com
Author 3Stewart, Terry
University of Waterloo
terry.stewart@gmail.com
TitleLarge-scale cognitive modelling with single neurons
AbstractOur lab has developed a method for constructing biologically realistic spiking neuron models called the Neural Engineering Framework (NEF). Most of these models have been for small-scale neural systems (e.g. rodent path integration, working memory, zebrafish motor control, etc.). In this talk I describe how these same principles can be used to provide a useful approach to cognitive modelling, which we call the Semantic Pointer Architecture (SPA). I demonstrate the approach by describing a cognitive model called SPAUN with 2.8 million neurons that works on natural image input and produces arm movements as output. It is able to perform any of 8 different perceptual, motor, and cognitive tasks without any changes to the model. These tasks include copying viewed input, serial working memory, reinforcement learning, and inducing patterns in structured, language-like input as found in the Raven's matrix intelligence test. I argue that the SPA provides a principled way of bridging the gap between biological constraints and psychological constraints on cognition. In the course of presenting these models, I will demonstrate Nengo (www.nengo.ca), a neural modelling environment which can be used to simplify the construction and simulation of such models.


SpeakerHolden, John
Author 1Holden, John
University of Cincinnati
john.holden@uc.edu
Author 2Rajaraman, Srinivasan
University of Cincinnati
N/A
TitleThe Self-Organizing Dynamics of Cognitive Performance
AbstractEmpirical patterns of response time variability derived from elementary cognitive performances are examined using the concepts and statistical tools of fractal geometry, nonlinear dynamics, and the physics of self-organizing systems. The outcomes suggest new ways of understanding how the human body, nervous system, and mind coordinate the myriad processes that support and constrain human thought and action.


Speakerjones, Matt
Author 1jones, Matt
University of Colorado
mcj@colorado.edu
Author 2Corral, Daniel
University of Colorado
daniel.corral@colorado.edu
Author 3Foster, James
University of Colorado
james.m.foster@colorado.edu
TitleLearning Higher-Order Relations
AbstractTheories of analogical reasoning hold that analogy is the recognition of a common (i.e., isomorphic) system of relations among the objects in two different scenarios. Such systems of relations can be thought of as higher-order relations--relations among relations. We propose that, once learned, higher-order relations can act as elements in future analogies, leading to an iterative process that produces compositional hierarchies of relational concepts. This mechanism may play an important role in development of abstract concepts. We will present current experimental and modeling work that attempts to support and flesh out these ideas.


SpeakerLee, Soo-Young
Author 1Lee, Soo-Young
KAIST
sylee@kaist.ac.kr
TitleUnderstanding un-represented human intention
AbstractBased on physiological and behavioral measurements we present recognition experiments of human intention, which is not presented by users. Although current human-machine interfaces are utilizing explicitly-represented human intention such as keystrokes, gesture, and speech, the actual hidden human intention may be different from the explicit one. Therefore, it is necessary to understand the un-represented intention for the next-generation intelligent human-oriented user interface. We had measured EEG, fMRI, eye gaze, GSR, and video signals, while the subjects are asked both obvious and non-obvious sensitive personal questions. Also, the subjects made ‘Yes’ or “No’ answer for each question by speech. We had separately trained SVM classifiers for each measured modality from the obvious questions, and tested the SVMs for the non-obvious questions. The agreement (or disagreement) among different modality, and the explicitly-represented intention are analyzed. It demonstrated the possibility of understanding human implicit intention from EEG, video, and/or speech signals, which may be utilized as a next-generation human-machine interface.


SpeakerMiller, Cynthia
Author 1Miller, Cynthia
Emerson College
cymiller@tiac.net
TitleProcessing Communal Sentiment: Rasa Theory, Cognition, and the Experience of Community
AbstractCommunal sentiments, such as nationalism, reflect the unique and dynamic interactions of individual and group, cognition and culture. In so doing, these sentiments reproduce and redefine the identities and local knowledge of the communities in which they are constructed. This paper examines how the experiences of these complex, multi-layered sentiments are processed and communicated within the cultural group, using Rasa Theory - a paradigm drawn from early Sanskrit Criticism - as its primary descriptive tool. Rasa was originally conceived as a framework of thematic structure which enabled the individual to participate in collective sentiment. In the present application, it serves to highlight symbolic cognitive and emotional cues to the experience of community.


SpeakerMusca, Serban C.
Author 1Musca, Serban C.
CRPCC (EA 1285), European University of Brittany, Rennes, France
serban-claudiu.musca@uhb.fr
Author 2Collange , Julie
University Paris Descartes, Boulogne Billancourt, France
julie.collange@parisdescartes.fr
Author 3Sanitioso, Rasyid B.
University Paris Descartes, Boulogne Billancourt, France
rasyid.sanitioso@parisdescartes.fr
Author 4Augustinova , Maria
LAPSCO UMR 6024 CNRS, CNRS and University of Clermont-Ferrand, Clermont-Ferrand, France
maria.augustinova@univ-bpclermont.fr
TitlePower of the desired self: The working self-concept influences the processing of self-unrelated information
AbstractThe transient changes in self-perception that makes it possible for somebody to come across as the right person in the right place was termed working self-concept (WSC). Within this framework past research showed that WSC affects the processing of self-relevant information. We go one step further and propose that a person’s WSC entails an embodiment that concurs with the desired self-perception (i.e., the person “becomes” precisely that desired self that is motivated by the situation), which has profound consequences. In particular WSC would affect the processing of information in the broadest sense: people embody their current WSC and reason within the frame of their currently embodied WSC. To test this hypothesis we used a task that requires processing information that is not self-relevant, namely Kahneman & Tversky’s (1973) lawyer-engineer (L-E) task. In the L-E task people are presented with base rate information concerning the composition of a group of people (e.g., there are 70% of lawyers and 30% of engineers), and are given an individuating description of a person from that group (e.g., “Dan shows no interest in political and social issues and spends most of his free time on his many hobbies, which include home carpentry and mathematical puzzles”); when asked to estimate the chances out of one hundred that Dan is an engineer, people often disregard base rate information and rely instead on the individuating information. In favor of our claim, we present results that show how this classic finding is dramatically affected by participants’ desire to possess a desired characteristic.


SpeakerMyung, Jay
Author 1Myung, Jay
Ohio State University
ijmyung@gmail.com
Author 2Cavagnaro, Daniel
California State University, Fullerton
dcavagnaro@fullerton.edu
Author 3Gonzalez, Richard
University of Michigan
gonzo@umich.edu
Author 4Pitt, Mark
Ohio State University
pitt.2@osu.edu
TitleActive Learning Approach to Risky Choice Experiments
AbstractCollecting data to discriminate between models of risky choice requires careful selection of decision stimuli. Models of decision making aim to predict decisions across a wide range of possible stimuli, but practical limitations force experimenters to select only a handful of them for actual testing. Some stimuli are more diagnostic between models than others, so the choice of stimuli is critical. This paper provides the theoretical background and a methodological framework for adaptive selection of optimal stimuli for discriminating among models of risky choice. The approach, called Adaptive Design Optimization (ADO), adapts the stimulus in each experimental trial based on the results of the preceding trials. We demonstrate the validity of the approach with simulation studies aiming to discriminate Expected Utility, Weighted Expected Utility, Original Prospect Theory, and Cumulative Prospect Theory models.


SpeakerOberauer, Klaus
Author 1Oberauer, Klaus
University of Zurich
k.oberauer@psychologie.uzh.ch
TitleUpdating working memory: A computational model
AbstractWorking memory maintains the information needed for ongoing cognitive processes. To serve this purpose it must be rapidly updated. I will a model for updating working memory. The model builds on existing connectionist models of short-term memory (e.g., Farrell & Lewandowsky, 2002, PB&R), and adds a mechanism for rapidly swapping information between working memory and long-term memory. The current contents of working memory are chunked, and the chunk is associated to a retrieval cue in long-term memory. When retrieved, the chunk is unpacked in working memory, recreating the original set of items. I will apply the model to data from experiments on list switching and on task switching.


SpeakerPalmeri, Thomas
Author 1Palmeri, Thomas
Vanderbilt University
thomas.j.palmeri@vanderbilt.edu
Author 2Purcell, Braden
Vanderbilt University
braden.a.purcell@Vanderbilt.edu
Author 3Schall, Jeffrey
Vanderbilt University
jeffrey.d.schall.2@vanderbilt.edu
Author 4Logan, Gordon
Vanderbilt University
gordon.logan@vanderbilt.edu
TitleFrom salience to saccades: Multiple-alternative gated stochastic accumulator model of visual search
AbstractI will describe a stochastic accumulator model demonstrating that visual search performance can be understood as a gated feed-forward cascade from a salience map to multiple competing stochastic accumulators. The model quantitatively accounts for behavior and predicts neural dynamics of macaque monkeys performing visual search for a target stimulus among different numbers of distractors. The evidence accumulated in the model is equated with the spike trains recorded from visually responsive neurons in the frontal eye field that encode stimulus salience. Accumulated variability in the firing rates of these neurons explains choice probabilities and the distributions of correct and error response times with search arrays of different set sizes if the accumulators are mutually inhibitory. The dynamics of the stochastic accumulators quantitatively predict the activity of presaccadic movement neurons that initiate eye movements if gating inhibition prevents accumulation before sufficient evidence about stimulus salience has emerged. Adjustments in the level of gating inhibition can control tradeoffs in speed and accuracy that optimize visual search performance.


SpeakerTrcek, Denis
Author 1Trcek, Denis
Faculty of computer and information science, University of Ljubljana
denis.trcek@fri.uni-lj.si
TitleTrust and its computational modelling with Qualitative Assessment Dynamics
AbstractTrust is a manifestation of (frequently non-rational) reasoning and assessment processes. Therefore it has to be treated in line with this fact and adequately supported in computing environments. One such methodology is Qualitative Assessment Dynamics, QAD, which is aligned with cognitive ergonomics requirements. QAD not only complements existing trust management methodologies in computerized environments, but gives new grounds for advanced multidisciplinary research like computational economics.