Cortical Integration: Possible Solutions to the Binding and Linking Problems in Perception, Reasoning and Long Term Memory
Nick Bostrom
Page 4
Source: http://www.nickbostrom.com/old/cortical.html
An even higher degree of biologic plausibility is possessed by the simulations by Sporns et al. (1994) and Ritz et al. (1994) and others which do not contain any procedural modules, and wherein all parameters are given values that have been determined by neurophysiological experiments.
One of Sporn's system is big (10,000 neurons; one million connections) and has an architecture that is supposed to mirror that of the visual cortex in the human brain. It has successfully reproduced the linking of representations of segments of moving objects that has also been observed in cat and monkey. Neurons which are part of representations of contour segments of the same object tends to have their activity synchronised, in ways that suggests application of the basic gestalt laws.
Sporn's et al. argue that local synchronization is a prerequisite for intra-areal synchronization because the activity of single cells is not statistically significant in a realistic system; but if local synchronization is established, then it is often possible to propagate this coherence into distant regions since the brain is ordered in such a manner that axonal projections from units in a neighborhood typically have their end terminals clustered, with local branching. When this is the case, then local coherent activity in one cortical area can easily induce local coherence in another area, thus effecting a binding between the two activity patterns. One finding was that the dynamical properties of the network as regards its properties of synchronization were rather sensible to alterations in its micro-scale structural design. This would indicate that it might be necessary to include a considerable extent of the micro-structure of the cortex in order to get models that can reliably simulate the synchronised spiking that goes on in real brains. The richness in the fauna of different types of nerve cells and synaptic connection modes could conceivably have evolved to allow for such tuning and optimization of the reverberating properties of cortical areas.
In the Spike Resonance Model by Ritz et al., the neurons have an absolute refractory period; axonal delay times are assigned according to a biologically plausible distribution; and excitatory and inhibitory synaptic potentials are given a realistic shape. In spite of these complications, several quantities can be calculated analytically, and the whole system is sufficiently agile to have allowed the Ritz et al. to perform a simulation involving 32,000 rather heavily connected neurons!
The task set to the system is a rather simple matter of pattern completion. Learning is achieved according to a variant of the Hebbian learning rule. One especially interesting result was that binding by synchrony can occur between two modules, whose connectivity was set up so as to mirror the connectivity through the corpus callosum between columns in opposite hemispheres, if and only if the transmission delays are less than 5 ms on average. This is a prediction of an upper bound on interhemispheric axonal transmission delays and should lend itself to direct empirical verification. (If this prediction were falsified, that would indicate that the model is oversimplified or that the parameters have been given improper values; it would not say much about synchronization in the brain. But 5 ms does not appears to be too tight.)
Another finding was that the number of pattern that can be simultaneously active in a given region without fusing together is restricted to four. The number depends on the parameter values, especially the strength and duration of local inhibition; but four was the number obtained when the parameters were set to realistic values. If this result reflects a property of the nervous system, then that poses some limits on how synchronization can work as a mechanism for cortical integration. We shall consider this further in section 6.
4.4 The neurophysiological evidence for synchronization as a mechanism integration
That brain activity exhibits synchronization has been established. Local synchronization has been observed in pigeons, cats, and awake behaving monkeys. Interareal synchronization has been observed between area V1 and V2 in macaque monkey and between several areas in the cat, even between neurons in different hemispheres. It is still a matter of debate, however, what role, if any, synchrony has in the establishment of linking and binding structured neural representations.
The observed synchrony is quite accurate; the half-width at half-height in the correlogram are typically about 2-3 ms. However, with present technology, it is not an easy task to measure synchronization. Improved multi-electrode recordings is what we hope for. Data from individual neurons do not imply anything about whether their activity is synchronised with that of other nerve cells. When a single electrode is used to register the activity from multiple units, we can sometimes observe oscillations; and that is evidence of synchronization, for only coherent firing from the recorded units could cause such large fluctuations. But often such single-electrode experiments fail to discover existent oscillations and synchronization. The reason is sampling problems: often one or two co-ordinated bursts are all there is. The event can still be salient and well-defined on a macro-scale, but when we record from only a few cells, noise makes the regularities disappear. One way around this would be to search for synchronizations that can be expected to endure for some time; for example under conditions where an ambiguous stimulus is presented which challenges the systems' problem solving capacity and demands sustained attention. This is not unproblematic either, however, for while the neurons may oscillate in synchronization, their oscillations are not normally rhythmic! The period keeps changing, so we are faced with a nonstationary time series, which requires long sampling times in order to yield significant results.
Anyhow, both oscillation (on the scale of individual neurons up to the level of the whole brain, as in EEG patterns) and synchronization have been observed, and we may ask in what sort of relationship they stand to one another. It has been pointed out that some degree of predictability, and hence oscillation, is necessary for the maintenance of a zero-phase lag synchronization, especially between cells separated by long conduction delays, as is the case when they are located in different hemispheres. Thus a tendency to oscillation in the activity of individual cells seems to be instrumental to their collective synchronization. At the same time, it appears natural for groups of synchronised cells to begin to oscillate as they influence one another; they discharge at the same time and then presumably reload at the same rate until they are ready to make a new simultaneous discharge. Simulation studies confirm this intuition.
While the phenomenon of synchrony in cerebral activity is established beyond doubt, this does not settle the question what functional role, in any, such synchrony plays in sensory and cognitive processing. But there are findings which have an indirect or a direct bearing on this issue.
To begin with the indirect evidence, it is known that the synchronised activity in cortex is at least partly due to cortico-cortical connections; for cutting off the corpus callosum causes the synchronization between cells in different hemispheres to disappear. The fact that the synchronizing is dependent upon cortical connections is indirect evidence in that it dispels the suspicion that the synchrony is due solely to the influence of a common input from thalamic region. If that were the case, then synchrony could hardly be a dynamic binding and linking mechanism for features in perceptual processing, because thalamic cells posses but very limited feature selectivity. So by discovering that cortico-cortical connection play a major part in the synchronization process, one stumbling block is cleared away from the path to the synchrony solution of the integration problem.
Another piece of negative evidence comes from the refutation of the objection that synchronization would take too long to establish, so that it could not comply with the severe time constraints in visual processing. Gray et al.(1987) demonstrated that synchronization can be established within 50-100 ms in the visual cortex of the cat, which is consistent with behaviorally measured response times in visual discrimination tasks. It has also been shown that the patterns of synchronization possess a high degree of flexibility and can be dissolved as quickly as they can be formed.
Important direct evidence for correlation between synchronization patterns and certain perceptual features has been found in studies that measured separately the activity of several cells in the visual cortex while moving bars or contours were projected onto the retina. For instance, in one experiment, two electrodes were separated by 7 mm in the primary visual cortex of cat. It was determined that these two cells responded selectively to vertically oriented light bars on two different locations in the visual field. Then three stimulus configurations were tried in turn. In the first configuration, one light bar moved left at one location, while a second light bar moved to the right at the other location. In this case, there was no synchronization between the cells. In the second configuration, both bars moved in the same direction. Here the cross-correlogram revealed a significant degree of synchronization. In the third configuration, one long light bar moved across both locations in the visual field (as well as over the area swept by the line connecting these locations). A highly synchronised firing resulted. This suggests that synchronization can serve to link of features into an object representation. Two bars moving in opposite directions do not belong to the same object; the nodes responding to those movements are not harmonized. Two lines fragments moving in the same direction, especially if they are part of a common continuous contour, tend to have a shared origin; they get linked together through their representations being synchronised. It is intriguing that one should find the basic gestalt laws (grouping by: vicinity, similarity, continuity, common motion) reflected at such an early stage of sensory processing.
Another result gives some direct evidence, not only that synchrony occurs and is related to perceptual features, but also that it has a functional significance. In a condition known as strabismic amblyopia, the perceptual powers of one eye have deteriorated as a result of the subjects suppressing its signals in an attempt to deal with strabismic double vision. The typical symptoms are loss of stereopsis, and, for the deteriorated eye, decreased resolution and the occurrence of "crowding", a drastic impairment of the ability to recognize shapes that are surrounded with other contours. When this deficit was induced in cat, multielectrode recordings from the striate cortex revealed that neurons driven by the amblyopic eye were much less synchronised with each other than were similar neurons driven by the normal eye, when light bars or gratings were projected onto the animals' retina. Taken together with the findings mentioned in the previous section, this suggests that the synchronization of neuronal responses helps solve the task of feature integration, and that the crowding phenomenon is caused by a failure to establish proper synchronization.
4.5 Summary of evidence
So, to sum up: It is known that synchronization occurs in cortex and that cortico-cortical connections make a very significant contribution to this phenomenon. The synchronization can be achieved and abolished on a time scale that is consistent with what we know from visual discrimination experiments. Thresholds for LTP and LTD are set so high that some synchronization seems necessary if activity should overcome them and learning take place. There are several apparent advantages with having coherent cortical activity (as reviewed in the preceding section). This speaks weakly againstthe assumption that synchronization is used to solve the linking and binding problems. For if synchronization would have not have been associated with definite advantages, or would even be counterproductive to many purposes, then this would strongly suggest that the synchronization we observe would be a way to bind and link neuronal representations; for why else would it be there in such a case? However, since there are independent motivations for its existence, and since in any case neuronal networks seem to have a natural tendency to engage in coherent firing and oscillations, we cannot from the fact that synchrony is there draw the conclusion that it probably is the mechanism whereby the integration problem is solved. To prove that, we need to look for evidence that establishes a direct causal connection between synchronization and performance on tasks that require compositional neural representations. The multielectrode recordings from cat presented with moving contours and from cat with strabismic amblyopia strongly suggest, but do not prove, such a causal connection between synchronization and linking in early visual processing. No comparable results have yet been obtained for later stages in visual processing or for the problem of interareal binding.
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