[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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