Trends in Cognitive Sciences
ReviewSpecial Issue: The ConnectomeCortical dynamics revisited
Section snippets
Extending classical views of information processing in the brain
The research strategy for analysing the connectivity of brains and the transformation of response properties of individual neurons along processing streams extending from sensory organs to executive structures has been extremely successful and has provided support for the notion of serial processing across hierarchically organised cortical areas [1]. However, advances in the analysis of the cortical connectome, the introduction of multisite recording techniques, and the development of imaging
Evidence requiring extension of concepts
Anatomical evidence
- (i)
Within processing streams, including thalamic relays, feedback projections are in general more numerous than feedforward projections, emphasising the importance of top-down control.
- (ii)
Intracortical tangential connections cross the boundaries between areas [2]. Thus, at least the supragranular and to some extent the infragranular layers of the cerebral cortex appear as continuously coupled sheets, the different cortical areas being distinguished mainly by their input and output
Dynamic coordination of distributed activity
The dense connectome allows for virtually unconstrained interactions among any pair of neurons in the cortical mantel, either through direct connections or via a few switching nodes. This necessitates dynamic coordination of interactions at all scales, global to configure functional networks on the fixed backbone of anatomical connections and local to flexibly associate object attributes in distributed representations (assemblies in the Hebbian sense). In both cases mechanisms are required to
The nature and role of resting-state activity
The evidence that the resting-state activity of the brain is highly structured raises the question of whether this activity contains information and, if so, what this information represents and how it is encoded. The dynamics of resting-state activity must somehow reflect the functional architecture of cortical networks. Because this architecture is determined by genetic factors and modified by experience, spontaneous activity patterns should contain information about evolutionary and
The fingerprints of network dynamics
The dynamics of complex systems can vary between two extremes. All elements of the system could be active independently and exhibit stochastic activity (high dimensionality) or all elements could be synchronised (low dimensionality). Both extreme states have low computational potential. However, under normal conditions the cerebral cortex operates in an intermediate regime where the emergent dynamics are complex and computational power is high (see below). Interestingly, this is also true for
Epiphenomenal or computationally relevant signatures
The observations on dimensionality reduction bear on the question of whether system properties disclosed with simple stimuli are computationally relevant or only epiphenomena. The canonical RFs resulting from selective recombination of input connections and oscillations are an emergent property of recurrent networks. The functional roles of input recombination and recurrency are undisputed but oscillations are often considered maladaptive epiphenomena because they create instabilities and, by
Concluding remarks
The novel data on the structural and functional organisation of the cerebral cortex support concepts that emphasise distributed coding and information processing in self-organised complex systems with nonlinear dynamics. As outlined above, there is now sufficient empirical evidence to warrant targeted experimental testing of a set of hypotheses derived from these concepts (Box 2).
To test the hypotheses listed in Box 2 will require in-depth analysis of dynamic states across scales and the
Acknowledgements
The author is indebted to his colleagues in the department for discussions and constructive critiques. Thanks go to Andreea Lazar, Viola Priesemann, and Ingo Fischer for providing direct and substantial input to earlier versions of the manuscript, to Michaela Wicke for editorial assistance, to Driss Benzaid for the preparation of figures, and to three anonymous reviewers who contributed constructive comments. This work was supported by the Max Planck Society, the ESI, the FIAS, the Hertie
Glossary
- Assembly
- introduced by Donald Hebb in the context of his seminal proposal that neuronal representations of composite cognitive objects should comprise coherent assemblies (ensembles) of neurons whereby the responses of the individual neurons represent only subcomponents (one of many features) of the object. By introducing this notion of a combinatorial code, Hebb intended to overcome the ‘combinatorial explosion’ that would be the consequence of representing complex contents by individual,
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