|Slight Stimuli and Reorganized Information Flow in the Brain|
|SciMed - Neuroscience|
|TS-Si News Service|
|Sunday, 25 March 2012 14:00|
Göttingen, Germany. The direction of information flow in the brain can change, depending on the time pattern of communication between different areas. This reorganization can be triggered even by a slight stimulus, such as a scent or sound, at the right time.
The finding explains a famous optical illusion which can be seen in a split second either as a cup or two faces.
Even slight stimuli can change the information flow in the brain because of the way different regions of the brain are connected with each other. The resulting information processing can be changed by the assembling and disassembling of nerve fibres joining distant brain circuits. But such events are much too slow to explain rapid changes in perception. From experimental studies it was known that the responsible actions must be at least two orders of magnitude faster. Scientists now show for the first time that it is possible to change the information flow in a tightly interconnected network in a simple manner.
Click Pic for Details
Brain Network. Is there one cup or two faces? What we believe we see in one of the most famous optical illusions changes in a split second; and so does the path that the information takes in the brain.
This is an example of how figure–ground organization can influence the perceptions of an observer. Edge-assignment can affect the perception of shape, since it depends on the direction of the border between the black and white regions.Scientists of the Max Planck Institute for Dynamics and Self-Organization, the Bernstein Center for Computational Neuroscience (BCCN) Göttingen and the German Primate Center (DPZ) now show how this is possible without changing the cellular links of the network. Their theoretical study appears in the journal PLos Computational Biology.
Many areas of the brain display a rhythmic nerve cell activity. "The interacting brain areas are like metronomes that tick at the same speed and in a distinct temporal pattern," says the physicist and principal investigator Demian Battaglia. The researchers were now able to demonstrate that this temporal pattern determines the information flow. "If one of the metronomes is affected, (e.g., through an external stimulus), then it changes beat, ticking in an altered temporal pattern compared to the others.
The other areas adapt to this new situation through self-organisation and start playing a different drum beat as well. It is therefore sufficient to impact one of the areas in the network to completely reorganize its functioning, as we have shown in our model," explains Battaglia.
The applied perturbation does not have to be particularly strong. "It is more important that the 'kick' occurs at exactly the right time of the rhythm," says Battaglia. This might play a significant role for perception processes: "When viewing a picture, we are trained to recognize faces as quickly as possible even if there aren't any. But if we smell a fragrance reminiscent of wine, we immediately see the cup in the picture. This allows us to quickly adjust to things that we did not expect, changing the focus of our attention."
Next, the scientists want to test the model on networks with a more realistic anatomy. They also hope that the findings inspire future experimental studies, as Battaglia says: "It would be fantastic if, in some years, certain brain areas could be stimulated so finely and precisely that the theoretically predicted effects can be measured through imaging methods."
FundingFinancial support was provided by the German Federal Ministry of Education and Research (BMBF) via the Bernstein Center for Computational Neuroscience (BCCN) Göttingen.
CitationDynamic effective connectivity of inter-areal brain circuits. Demian Battaglia, Annette Witt, Fred Wolf, Theo Geisel.PLos Computational Biology 2012; 8(3): e1002438. doi:10.1371/journal.pcbi.1002438
Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we advance here that dynamic interactions between brain rhythms provide as well the basis for the self-organized control of this “communication-through-coherence”, making thus possible a fast “on-demand” reconfiguration of global information routing modalities.
The circuits of the brain must perform a daunting amount of functions. But how can “brain states” be flexibly controlled, given that anatomic inter-areal connections can be considered as fixed, on timescales relevant for behavior? We hypothesize that, thanks to the nonlinear interaction between brain rhythms, even a simple circuit involving few brain areas can originate a multitude of effective circuits, associated with alternative functions selectable “on demand”. A distinction is usually made between structural connectivity, which describes actual synaptic connections, and effective connectivity, quantifying, beyond correlation, directed inter-areal causal influences. In our study, we measure effective connectivity based on time-series of neural activity generated by model inter-areal circuits. We find that “causality follows dynamics”. We show indeed that different effective networks correspond to different dynamical states associated to a same structural network (in particular, different phase-locking patterns between local neuronal oscillations). We then find that “information follows causality” (and thus, again, dynamics). We demonstrate that different effective networks give rise to alternative modalities of information routing between brain areas wired together in a fixed structural network. In particular, we show that the self-organization of interacting “analog” rate oscillations control the flow of “digital-like” information encoded in complex spiking patterns.
|Last Updated on Sunday, 25 March 2012 14:04|