Degeneracy and cognitive anatomy

doi:10.1016/S1364-6613(02)01976-9

Trends in Cognitive Sciences

Volume 6, Issue 10, 1 October 2002, Pages 416-421

https://doi.org/10.1016/S1364-6613(02)01976-9 Get rights and content

Abstract

Cognitive models indicate that there are multiple ways of completing the same task. This implicit degeneracy cannot be revealed by functional imaging studies of normal subjects if more than one of the sufficient neural systems is activated. Nor can it be detected by neuropsychological studies of patients because their performance might not be impaired when only one degenerate system is damaged. We propose that degenerate sets of sufficient neural systems can only be identified by an iterative approach that integrates the lesion-deficit model and functional imaging studies of normal and neurologically damaged subjects.

Section snippets

The lesion-deficit model

Until the first PET studies of language processing were reported [10], the primary method for establishing cognitive anatomy was the lesion-deficit model. The principle behind this approach is that if a physiological lesion results in a cognitive deficit, then part of the lesioned area must be necessary for the lost cognitive process. Throughout the last century several methodological developments enabled the lesion-deficit approach in humans. Delineation of permanent (pathophysiological and

Functional imaging studies of normal subjects

It is generally assumed that functional imaging techniques will overcome many of the limitations associated with the lesion-deficit model. The main advantages that functional imaging offers are that it can identify the set of regions that are engaged for one task relative to another and it is not limited to ‘lesioned’ cortex. For example, when normal subjects are instructed to match written words on the basis of their meaning, they activate a distributed set of areas (the semantic-retrieval

Combining the lesion-deficit approach with functional imaging studies of normal subjects

Functional imaging can, in principle, identify the set of regions that are sufficient for a cognitive operation and the lesion-deficit model identifies which of these areas are necessary. We have previously argued 24., 25. that a combination of functional imaging and the lesion-deficit model should enable us to identify ‘necessary and sufficient’ brain systems. We were wrong – there might be no single necessary and sufficient system because the existence of two or more degenerate systems that

Motivation for functional imaging studies of neurologically damaged patients

We have argued that functional imaging results can be used to guide neuropsychological investigations and that neuropsychological investigations can be used to test predictions generated from functional imaging data. It is possible, however, that the ability to complete the task might not be impaired following any combination of lesions to areas activated in functional imaging studies of normal subjects. This could occur if there are latent systems that are either untrained or ‘inhibited’ in

Conclusion

In this article we have discussed the concept of degeneracy at the level of cognitive anatomy. The key point is that a full understanding of the degenerate sets of neural systems that underlie any given cognitive task can only be revealed by systematically combining data from neuropsychological and neuroimaging studies of normal subjects and neurological patents (see Fig. 6). We believe that an understanding of degeneracy will provide insights into intersubject variability and the mechanisms

Acknowledgements

This work was funded by the Wellcome Trust. The data reported in Fig. 3, Fig. 4 and Fig. 5 were collected by C.J.P. and co-workers, and originally reported in a different format in Rik Vandenberghe et al. [22] and Cath Mummery et al. [23].

References (30)

A. Pascual-Leone
Transcranial magnetic stimulation in cognitive neuroscience–virtual lesion, chronometry, and functional connectivity
Curr. Opin. Neurobiol.
(2000)
K.J. Friston
Multi-subject fMRI studies and conjunction analysis
NeuroImage
(1999)
C.J. Price et al.
Cognitive conjunctions: a new approach to brain activation experiments
Neuroimage
(1997)
J. Ashburner et al.
Voxel-based morphometry – the methods
NeuroImage
(2000)
G.M. Edelman
G.M. Edelman
The Remembered Present. A Biological Theory of Consciousness
(1989)
G. Tononi
Measures of degeneracy and redundancy in biological networks
Proc. Natl. Acad. Sci. U. S. A.
(1999)
G.M. Edelman et al.
Deneracy and complexity in biological systems
Proc. Natl. Acad. Sci. U. S. A.
(2001)
J.C. Marshall et al.
Patterns of paralexia: a psycholinguistic approach
J. Psycholinguist. Res.
(1973)
M.S. Seidenberg et al.
A distributed developmental model of word recognition and naming
Psychol. Rev.
(1989)

G.W. Humphreys et al.

Routes to object constancy: implications from neurological impairments of object constancy

Q. J. Exp. Psychol.

(1984)

G. Hinton et al.

Learning and relearning in Boltzman machines

J. McClelland

Why there are complementary learning systems in the hippocampus and neocortex–Insights from the successes and failures of connectionist models of learning and memory

Psychol. Rev.

(1995)

S.E. Petersen

Positron emission tomographic studies of the cortical anatomy of single word processing

Nature

(1988)

W. Penfield et al.

Speech and Brain Mechanism

(1959)

Cited by (356)

Disentangling neuroplasticity mechanisms in post-stroke language recovery
2024, Brain and Language
A major objective in post-stroke aphasia research is to gain a deeper understanding of neuroplastic mechanisms that drive language recovery, with the ultimate goal of enhancing treatment outcomes. Subsequent to recent advances in neuroimaging techniques, we now have the ability to examine more closely how neural activity patterns change after a stroke. However, the way these neural activity changes relate to language impairments and language recovery is still debated. The aim of this review is to provide a theoretical framework to better investigate and interpret neuroplasticity mechanisms underlying language recovery in post-stroke aphasia. We detail two sets of neuroplasticity mechanisms observed at the synaptic level that may explain functional neuroimaging findings in post-stroke aphasia recovery at the network level: feedback-based homeostatic plasticity and associative Hebbian plasticity. In conjunction with these plasticity mechanisms, higher-order cognitive control processes dynamically modulate neural activity in other regions to meet communication demands, despite reduced neural resources. This work provides a network-level neurobiological framework for understanding neural changes observed in post-stroke aphasia and can be used to define guidelines for personalized treatment development.
Pragmatic language comprehension: Role of theory of mind, executive functions, and the prefrontal cortex
2024, Neuropsychologia
The specific contribution of focal damage of the prefrontal cortex and the cognitive mechanisms accounting for communicative-pragmatic disorders remains unclear. The objective of the current study was to investigate the impact of focal prefrontal cortex damage on the ability to understand indirect speech or hints and to identify the prefrontal neural mechanisms involved. We also examined the underlying cognitive mechanisms of disorders of indirect speech understanding particularly theory of mind and executive functions. Thirty patients with focal prefrontal cortex damage and 30 control subjects were compared on their performances on the Hinting task assessing pragmatic language skills, the "Faux-Pas" task and the Reading the Mind in the Eyes task assessing Theory of Mind and a battery of executive tasks. Patients were significantly impaired compared with control subjects on all these abilities. Both deficits of executive functions and theory of mind were able to predict impaired ability of patients in understanding non-literal meanings on the Hinting task. Finally, using voxel-based lesion analysis we identified a partially shared neural prefrontal network involved in all these abilities centered on the dorsomedial and ventral regions of the prefrontal cortex.
Improving the study of brain-behavior relationships by revisiting basic assumptions
2023, Trends in Cognitive Sciences
Neuroimaging research has been at the forefront of concerns regarding the failure of experimental findings to replicate. In the study of brain-behavior relationships, past failures to find replicable and robust effects have been attributed to methodological shortcomings. Methodological rigor is important, but there are other overlooked possibilities: most published studies share three foundational assumptions, often implicitly, that may be faulty. In this paper, we consider the empirical evidence from human brain imaging and the study of non-human animals that calls each foundational assumption into question. We then consider the opportunities for a robust science of brain-behavior relationships that await if scientists ground their research efforts in revised assumptions supported by current empirical evidence.
fMRI functional connectivity is a better predictor of general intelligence than cortical morphometric features and ICA parcellation order affects predictive performance
2023, Intelligence
Intelligence, as a general cognitive ability, shows a substantial inter-subject variation. Because of its impact on our lives, there is great interest in explaining the neural substrates of these differences. We used a large set of neuroimaging and behavioral data from 805 subjects, provided by the Human Connectome Project, and applied predictive models based on elastic-net regression using functional connectivity and brain morphometric data to predict general intelligence values. Additionally, we explored the impact of brain spatial distribution of the input connectivity data in the regression model using two strategies: brain parcellation and individual components. Features derived from functional connectivity were considerably more correlated with general intelligence than cortical thickness and surface area. Considering the regularization terms in this particular prediction problem, the best performances were obtained when the impact of all the independent variables was considered in the regresion, i.e. null LASSO sparsity term. Using different parcellation schemes affected predictive performances, which indicates spatial heterogeneity in the regression. We were able to explain 17,5% of the general intelligence variance, in the best performance reached, with a brain parcellation of 25 independent components; by other hand, using only cortical morphometric features the performance reduced to 1,6% for both cortical thickness and surface area. While no component, in particular, was responsible for predicting a large portion of the variance, the spatial components with the best results comprehend parietal, frontal and occipital regions, in agreement with the Parieto-Frontal Integration Theory (P-FIT).
Functionally and structurally distinct fusiform face area(s) in over 1000 participants
2023, NeuroImage
The fusiform face area (FFA) is a widely studied region causally involved in face perception. Even though cognitive neuroscientists have been studying the FFA for over two decades, answers to foundational questions regarding the function, architecture, and connectivity of the FFA from a large (N>1000) group of participants are still lacking. To fill this gap in knowledge, we quantified these multimodal features of fusiform face-selective regions in 1053 participants in the Human Connectome Project. After manually defining over 4,000 fusiform face-selective regions, we report five main findings. First, 68.76% of hemispheres have two cortically separate regions (pFus-faces/FFA-1 and mFus-faces/FFA-2). Second, in 26.69% of hemispheres, pFus-faces/FFA-1 and mFus-faces/FFA-2 are spatially contiguous, yet are distinct based on functional, architectural, and connectivity metrics. Third, pFus-faces/FFA-1 is more face-selective than mFus-faces/FFA-2, and the two regions have distinct functional connectivity fingerprints. Fourth, pFus-faces/FFA-1 is cortically thinner and more heavily myelinated than mFus-faces/FFA-2. Fifth, face-selective patterns and functional connectivity fingerprints of each region are more similar in monozygotic than dizygotic twins and more so than architectural gradients. As we share our areal definitions with the field, future studies can explore how structural and functional features of these regions will inform theories regarding how visual categories are represented in the brain.
Meta-analytic evidence for a novel hierarchical model of conceptual processing
2023, Neuroscience and Biobehavioral Reviews
Conceptual knowledge plays a pivotal role in human cognition. Grounded cognition theories propose that concepts consist of perceptual-motor features represented in modality-specific perceptual-motor cortices. However, it is unclear whether conceptual processing consistently engages modality-specific areas. Here, we performed an activation likelihood estimation (ALE) meta-analysis across 212 neuroimaging experiments on conceptual processing related to 7 perceptual-motor modalities (action, sound, visual shape, motion, color, olfaction-gustation, and emotion). We found that conceptual processing consistently engages brain regions also activated during real perceptual-motor experience of the same modalities. In addition, we identified multimodal convergence zones that are recruited for multiple modalities. In particular, the left inferior parietal lobe (IPL) and posterior middle temporal gyrus (pMTG) are engaged for three modalities: action, motion, and sound. These “trimodal” regions are surrounded by “bimodal” regions engaged for two modalities. Our findings support a novel model of the conceptual system, according to which conceptual processing relies on a hierarchical neural architecture from modality-specific to multimodal areas up to an amodal hub.

View all citing articles on Scopus

View full text

Trends in Cognitive Sciences

OpinionDegeneracy and cognitive anatomy

Abstract

Section snippets

The lesion-deficit model

Functional imaging studies of normal subjects

Combining the lesion-deficit approach with functional imaging studies of normal subjects

Motivation for functional imaging studies of neurologically damaged patients

Conclusion

Acknowledgements

Curr. Opin. Neurobiol.

NeuroImage

Neuroimage

NeuroImage

The Remembered Present. A Biological Theory of Consciousness

Measures of degeneracy and redundancy in biological networks

Proc. Natl. Acad. Sci. U. S. A.

Deneracy and complexity in biological systems

Proc. Natl. Acad. Sci. U. S. A.

Patterns of paralexia: a psycholinguistic approach

J. Psycholinguist. Res.

A distributed developmental model of word recognition and naming

Psychol. Rev.

Routes to object constancy: implications from neurological impairments of object constancy

Q. J. Exp. Psychol.

Learning and relearning in Boltzman machines

Why there are complementary learning systems in the hippocampus and neocortex–Insights from the successes and failures of connectionist models of learning and memory

Psychol. Rev.

Positron emission tomographic studies of the cortical anatomy of single word processing

Nature

Speech and Brain Mechanism

Opinion
Degeneracy and cognitive anatomy