[FieldTrip] Call for Papers :: NIPS 2011 Workshop on Interpretable Decoding of Higher Cognitive States from Neural Data

Irina Simanova irina.simanova at mpi.nl
Tue Aug 30 14:22:31 CEST 2011


Interpretable Decoding of Higher Cognitive States from Neural Data

NIPS 2011 Workshop, Dec 16 or 17, 2011, Granada, Spain

(Please feel free to distribute the CFP to all the interested persons  
and groups.)

Overview

Over recent years, machine learning methods have become a crucial  
analytical tool in cognitive neuroscience (see reviews by Formisano et  
al., 2008; Pereira et al., 2009). Decoding techniques have  
dramatically increased the sensitivity of experiments, and so also the  
subtlety of cognitive questions that can be asked. At the same time  
the mental phenomena being studied are moving beyond lower-level  
perceptual and motor processes which are directly grounded in external  
measurable realities.

Decoding higher cognition and interpreting the learned behaviour of  
the classifiers used pose unique challenges, as these psychological  
states are complex, fast-changing and often ill-defined. Contemporary  
machine learning methods deal well with the small numbers of cases,  
and high numbers of co-linear dimensions typical of neural data, and  
are generally optimized to maximize classification performance, rather  
than to enable meaningful interpretation of the features they learn  
from. And indeed recent work has succeeded to decode psychological  
phenomena including visual object recognition (e.g. Kriegeskorte et  
al., 2008; Connolly et al., 2011), perceptual interpretation of sounds  
(Staeren et al., 2009),  lexical semantics (Mitchell et al., 2008;  
Siminova et al., 2010; Devereux et al., 2010; Murphy et al., 2011),  
decision making during game playing (Xiang et al., 2009) and the  
process of mental arithmetic (Anderson et al., 2008). But for the  
cognitive scientists who use these methods, the primary question is  
often not "how much" but rather "how" and "why" the patterns of neural  
activity identified by a machine learning algorithm encode particular  
cognitive processes.

The aim of this workshop is therefore to 1) discuss the achievements  
and problems of the decoding of high-level cognitive states, and 2)  
explore the use of machine learning methodologies and other  
computational models that enable such cognitive interpretation of  
neural recordings of different modalities. Advances in this field  
require close collaboration between machine learning experts,  
neuroscientists and cognitive scientists. Thus, this workshop is  
highly interdisciplinary and will aim to attract submissions also from  
outside the existing NIPS community. By stimulating discussions among  
experts in the different fields, the workshop seeks to generate novel  
insights and new directions for research.

Topics of interest

The field requires techniques that are capable of taking advantage of  
spatially distributed patterns in the brain, that are separated in  
space but coordinated in their activity. Methods should also be  
sensitive to the fine-grained temporal patterns of multiple processes  
- which may proceed in a serial fashion, overlapping or in parallel  
with each-other, or in multiple passes with bidirectional information  
flows. Different recording modalities have distinctive advantages:  
fMRI provides very fine millimetre-level localisation in the brain but  
poor temporal resolution, while EEG and MEG have millisecond temporal  
resolution at the cost of spatial resolution. Ideally machine learning  
methods would be able to meaningfully combine complementary  
information from these different neuroimaging techniques (see e.g. De  
Martino et al., 2010). Moreover, as the processes underlying higher  
cognition are so complex, methods should be able to disentangle even  
tightly linked and confounded subprocesses. Finally, general use  
algorithms that could induce latent dimensions from neural data, and  
so reveal the "hidden" psychological states, would be a dramatic  
advance on current hypothesis-driven analytical paradigms. Originality  
of approach is encouraged and submissions on any related  
methodological approach are welcomed, such as:

- Interpreting spatial and temporal location of selected features and  
their weights
- Discovering "hidden" or "latent" cognitive representations
- Disentangling confounded processes and representations
- Comparing or combining data from recording modalities (e.g. fMRI,  
EEG, structural MRI, DTI, MEG, NIRS, EcOG, single cell recordings)
- Fuzzy and partial classifications
- Unaligned or incommensurate feature spaces and data representation

As noted above, the complexity of higher cognition poses challenges.  
To take language comprehension as an example, speech is received at  
3-4 words; acoustic, semantic and syntactic processing can occur in  
parallel; and the form of underlying representations (sentence  
structures, conceptual descriptions) remains controversial. We welcome  
submissions dealing with any high-level cognitive functions that  
exhibit similar complexity, for instance:

- Knowledge representation and concepts
- Language and communication
- Understanding visual and auditory experience
- Memory and learning
- Reasoning and problem solving
- Decision making and executive control

Submissions

Authors are invited to submit full papers on original, unpublished  
work in the topic area of this workshop via the NIPS 2011 submission  
site at https://cmt.research.microsoft.com/NIPS2011/Default.aspx.  
Submissions should be formatted using the NIPS 2011 stylefiles, with  
blind review and not exceeding 8 pages plus an extra page for  
references. Author and submission information can be found at http://nips.cc/PaperInformation/AuthorSubmissionInstructions 
. The stylefiles are available at http://nips.cc/PaperInformation/StyleFiles 
. Each submission will be reviewed at least by two members of the  
programme committee. Accepted papers will be published in the workshop  
proceedings. Dual submissions to the main NIPS 2011 conference and  
this workshop are allowed; if you submit to the main session, indicate  
this when you submit to the workshop. If your paper is accepted for  
the main session, you should withdraw your paper from the workshop  
upon notification by the main session.

Important Dates

- Aug 30, 2011: Call for papers
- Sep 23, 2011: Deadline for submission of workshop papers
- Oct 15, 2011: Notification of acceptance
- Oct 31, 2011: Camera-ready papers due
- Dec 16 or 17, 2011: Workshop date

Links

- NIPS 2011 website: http://nips.cc/Conferences/2011/
- Workshop website: https://sites.google.com/site/decodehighcogstate
- Call for Papers: https://sites.google.com/site/decodehighcogstate/cfp/

Kind regards,
The Workshop Organizers,
Kai-min Kevin Chang, Anna Korhonen, Irina Simanova, Brian Murphy

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