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- 09/10 Jesse Prinz, University of North Carolina, Chapel Hill - Abstract
- 09/17 Evan Thompson, University of Toronto - Abstract
- 10/08 Jay McClelland, Stanford University - Abstract
- 10/22 Sue Becker, McMaster University - Abstract
- 10/29 Daniel Schwartz, Stanford University - Abstract
Abstract 9/10: Jesse Prinz, University of North Carolina, Chapel Hill
Title: The Emotional Basis of Moral Values
Abstract: There is a long-standing philosophical view according to which moral
values have an emotional basis. Some philosophers reject this view,
however, and it has been the subject of considerable debate. Recent
results from cognitive neuroscience, psychology, and psychopatholoy
offer strong support for the emotional view. Recent research is also
moving beyond old theories by revealing the specific nature of the
emotions that undergird morality. In this talk, I review recent work
in moral psychology and propose a theory that systematizes the
findings. One implication of this theory is that there can be
considerable variation in morality, because cultures can condition
emotional responses in different ways. Some moral debates may
result from incommensurable culturally conditioned emotional
dispositions.9/17: Evan Thompson, University of Toronto
Title: Meditation and the Neuroscience of Consciousness
Abstract: The main idea to be explored in this lecture is that neuroscience can advance
the investigation of consciousness by employing introspective reports based on
contemplative mental training of attention and awareness. The following topics
will be discussed: (i) issues regarding introspection in cognitive science; (ii) the
nature of contemplative mental training; (iii) contemplative introspection and the
neurodynamics of consciousness; (iv) experience-dependent brain development.10/8: Jay McClelland, Stanford University
Title: Graded Constraints in English Word Forms
Abstract: I will a describe graded constraint theory of English word forms that
addresses the distribution of forms in the lexicon, the goodness
judgments given by native speakers of nonwords as candidate wordforms,
and the pattern of errors seen in language impaired individuals
including dysfluent aphasics and individuals with specific language
impairment. The theory is applied to the rhymes of English monosyllabic
monomorphemes (items like 'cat', 'hold' and 'clamp'). Within a template
specifying possible rhymes, a number of graded constraints are
identified. For example, in rhymes containing at least one stop
consonant, there is a graded constraint favoring short vowels, a graded
constraint favoring unvoiced vs voiced obstruents, a constraint favoring
coronal articulation, and a constraint against added embellishments such
as a nasal, fricative, liquid, or second stop consonant (as in 'apt').
Each constraint affects the goodness of a rhyme type in a graded,
cumulative fashion. Occurrence rates of different types of rhymes in
the language conform closely to the predictions of both non-parametric
and parametric versions of the theory. By adding a cut-off threshold,
the theory can explain with good accuracy which types of rhymes occur at
all and which do not occur, although both linear and interaction terms
are necessary to give a complete account. The theory also accounts well
for native speaker's judgments of the relative goodness of different
rhyme types, although there are subtle differences between the patterns
of occurrence and the patterns of judgments.10/22: Sue Becker, McMaster University
Title: Hippocampal encoding of space and time
Abstract: The involvement of the hippocampus in space is widely acknowledged but
remains poorly understood. In the first part of this talk, I will present
a computational theory of the neural mechanisms in the parietal and
temporal lobes that support spatial navigation, imagery, and episodic
recall (Byrne, Becker and Burgess, Psych Review, in press). Predictions of
the model are currently being tested in an fMRI study of spatial memory
and imagery in virtual reality (with Neil Burgess and John King), and in a
VR study of implicit learning of spatial layouts using the "yellowcab"
game (with Mike Kahana). In the second part of the talk, I will consider
how the hippocampus encodes spatio-temporal information. In
recent work with Geoff Hinton, we show how a Restricted Boltzmann Machine
model of the hippocampus can account for the encoding of episodic
sequences. The model also postulates a role for theta oscillations and
forward and reverse sequence replay in learning the spatio-temporal
structure of events.10/29: Daniel Schwartz, Stanford University
Title: TBA
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