Title: Linking Cognitive Function and Brain Through Neural Context
1Linking Cognitive Function and Brain Through
Neural Context
Department of Psychology University of Toronto
2Overview
- Localized vs. Distributed Function
- Neural plasticity
- Dynamic processes
- Neural Context
- Theory examples
3Kleist, 1934
4Why localize function?
- Enables more precision in clinical evaluation
- Clues as to functional organization
- What are the critical sites?
- Constraints for cognitive/behavioural theory
5Localization of Cortical Function
- Primarily confirmed through focal lesion and/or
stimulation - Additional confirmation through physiological
measures - Not always a nice match!
- A region can participate in a function, but not
be critical for its expression.
6Localization of Cortical Function
- Problems
- Plasticity The brain changes in response to any
perturbation (short- or long-term) - Deficits after damage may be related to tissue
loss per se, or the response of intact tissue - Cannot inform as to mechanisms (not explanatory)
-
7Cortical plasticity
- Best examples of cortical plasticity come from
the study of the damaged brain. - Degeneration tracing in neuroanatomy
- Diaschisis (Von Monakov)
- Spreading cortical depression, distal effects
- Peripheral limb damage
- Merzenich, Ramachandran
- Central damage
- Nudo, Schallert, Whishaw
- Experience-dependent
- Recanzone, Weinberger, Gonzalez-Lima
8Response to damagePeripheral dennervation
Hickmott Merzenich, J Neurophys, 2002
9Response to damagePatient M.L.s Frontal Lobe
Lesion
Levine, et al, Brain, 1998
10Altered Hippocampal Activity During Retrieval in
ML
rCBF response
ENC
ENC
ENC
RET
RET
RET
TBI
M.L.
Ctls
11Problems
- Brain response to perturbation is rapid and
changes with time - Persistant deficits may come about through
abnormal operations of intact tissue - Damage may alter the systems supporting intact
function
12Historical positionsDynamic function
- We suggest the material basis of the higher
nervous processes is the brain as a whole, but
that the brain is a highly differentiated system
whose parts are responsible for different aspects
of the unifed whole.Luria (1962) - Higher
cortical functions in man - Bethe, Lashley, Hebb, Lorente de No, Mountcastle,
Edelman, Mesulam, Bressler
13Localization of Cortical Function
- Primarily confirmed through focal lesion and/or
stimulation - Additional confirmation through physiological
measures - Not always a nice match!
- A region can participate in a function, but not
be critical for its expression.
14Mapping of the brain to cognition
15Cabeza Nyberg Imaging Cognition II 275 PET
and fMRI Studies (J Cognit Neuro, 2000)
16Neural Context
- The behavioural relevance of activity changes in
one brain area depends on the activity in other
areas. - The important factor is not that a particular
event occurred at a particular site, but rather
under what neural context did that event occur --
in other words what was the rest of the brain
doing? (McIntosh, 1999, Memory)
17Neural Context
- Results from anatomy
- Anatomical determinism
- Depends on dominant afferent and efferent
influence - Allows information from specialized areas to be
combined in different ways depending on the
present demands - Differentiate and integrate (Tononi Edelman,
Science, 1998) - Aggregate functions
18Anatomical determinism
19Aggregate Functions
- Brain areas are sparsely connected
- Enables flexibility in system response
- All parts of the brain possess the rudimentary
characteristics necessary for cognitive function
(e.g., response plasticity) - Brain areas combine through their interactions
such that their aggregate property is the
cognitive process - Population coding
McIntosh, 2000, Neural Networks
20Neural Context
21Examples of Neural Context
- Visual cortex several examples (see review
Worgotter Eysel, 2000, TINS) - Responses dependent on adjacent cells, background
noise, stimulus context, salience, feedback - Invertebrates (see review by Kristan Shaw,
1997, Current Biol) - Dissimilar behaviors can be mediated by the same
networks through spatiotemporal variations in
population activity
22Examples of Neural ContextMultifunctional
Networks
J Neuroscience, 2002
23Examples of Neural ContextEquivalence of
function in frontal and parietal cortices
Chafee Goldman-Rakic, 1998, 2000, J Neurophys
24Methodological Note
- Functional connectivity (Gerstein, et al., 1978)
- temporal correlation or covariance among
measured neural elements - requires no assumptions about mediation of
influences - interregional correlations, multivariate analyses
(Partial Least Squares) - Effective connectivity (Aertsen, et al., 1989)
- influence (effect) that one neural element has on
another - requires some assumptions about mediate of
influences - path analysis, multiple regression
25Partial Least Squares
- Project voxel value within task onto every other
voxel in the image within a task yielding matrix
X - ZjTYj, where Zj is a vector of voxel values from
condition j and Y is a matrix of m voxels for the
rest of the image, matrix X is thus a jm
rectangular matrix of within-task covariances - Perform a singular value decomposition (SVD) on X
to define the latent variables (LV) - SVD(X) U,S,V where
- X USVT
- U is the j by m orthonormal matrix containing
voxel weights (singular or eigen image) - i.e. what is the pattern of functional
connectivity? - S is a diagonal matrix of j singular (eigen)
values. - VT is the transpose of matrix V, a j by j
orthonormal matrix of scan weights. - i.e., does the pattern differ across tasks?
26Structural Equation Modeling (McIntosh
Gonzalez-Lima, 1991, McIntosh et al, 1994, Buchel
Friston, 1997)
27Dorsal vs. Ventral Cortical Processing Streams
28Differential Sensory ConditioningLeft Prefrontal
Interactions Awareness
McIntosh, Rajah Lobaugh, Science, 1999
29Neural Context Same area engaged in different
functional networks
- Differential Sensory Learning with Reversal
- Visual target
- Two tones, T1 low, T2 high frequency
- Phase 1, T1 CS, T2 CS-
- Phase 2, T1 CS-, T2 CS
30Differential Conditioning with Reversal
31Brain-behavior Relations
- One pattern differentiated conditioned
facilitation between groups - Second pattern related to CS/CS- differentiaion
in Aware group
32Hippocampal Functional Connectivity
33Hippocampal Functional ConnectivityAware group
network
34Hippocampal Functional Connectivity
35Hippocampal Functional ConnectivityUnaware group
network
36Reversal Study Implications
- Same region may be part of different functional
networks that support different behaviours - Neural Context
37Reversal Study Implications
- Same region may be part of different functional
networks that support different behaviours - Neural Context
- Awareness not synonymous with involvement of
hippocampus, or any particular region, but with
the configuration of a given functional network - Aggregate function
38Conclusions
- Regions may be critical for a particular
operation, but the operation itself arises from
combined actions of many regions - Greater effort needed to merge distributed
assessment of brain function with study of the
damaged brain (e.g., E.A. Maguire et al, Brain,
2001)
39Effects of bilateral hippocampal damage
Maguire, et al, 2001, Brain
40Conclusions
- Regions may be critical for a particular
operation, but the operation itself arises from
combined actions of many regions - Greater effort needed to merge distributed
assessment of brain function with study of the
damaged brain (e.g., E.A. Maguire et al, Brain,
2001) - Brain regions can participate in more than one
function - Contributions of a region is determined through
neural context what is the rest of the brain
doing?
41Take home message
- Classic approaches to studying brain organization
are no longer adequate - Do not take into account functional plasticity
- Neural Context Partly resulting from plasticity,
brain regions can participate in more than one
cognitive operation - Detailed studies of reorganization in damaged and
diseased brains will lead to a new appreciation
of - Neural dynamics (why does damage in X produce a
deficit?) - Neurocognitive mapping