8.3 Persistent and transient reorganization
8.3.3 Two classes of experiments
Guided by these two cases we classified all experiments into two classes based on visual inspection of orientation maps and maps of local similarities. The first class consists of all experiments for which a widespread rearrangement was persistent over the period of 7 days. The second class contains all experiments for which the map showed a tendency to recover completely within a few days after ICMS. From the six experiments, three fitted into the first class and three into the second class.
The time course of rearrangement quantified by the similarityCwith the reference
Figure 8.4: Transient changes induced by ICMS. Illustration as in Fig. 8.3. In this experiment (k116), the final map is very similar to the initial one (cross-correlation, Pre/-3days,C = 0.89; Pre/Post,C= 0.71; Pre/+7days,C = 0.87). Immediately after ICMS the map is different even at regions far away from the ICMS site. However, apart from a pinwheel pair vanishing at the right end, the map nearly recovers after7 days. For comparison with the model, refer to Fig.
7.2.
map recorded immediately before ICMS is summarized in Fig. 8.5. Non-recovery experiments are marked in orange, recovery-experiments in blue. Grey symbols mark sham-experiments, i.e. control experiments carried out in identical fashion, but without inducing any current in the cortex. Generally the similarity was re-duced immediately after ICMS when compared to the control similarity between maps recorded before ICMS. In the recovery-class, similarities almost returned to this baseline after 7 days. In experiment k114 for which the map was recorded al-ready 3 days after ICMS, the similarity exhibited an intermediate value suggesting that the map had recovered only partially after this period. A possible interpre-tation is that the reorganization associated with recovery to the original state can last more than 3 days. In the non-recovery class, the similarity either remained constant on a relatively low level 5-7 days after ICMS or decreased progressively.
Interestingly, this decrease was observed to initiate after 5 days in experiment k109 for which the map was recorded twice after 5 and after 7 days. Consistent with
Figure 8.5: Reorganization in-duced by ICMS: Summary of ex-periments. Depicted are simi-larities C between the reference map recorded immediately be-fore ICMS (Pre) and the map at other stages of the experiment.
Different symbols denote differ-ent animals. Grey indicates sham experiments, orange cases with persistent, blue with just transient reorganization.
experiment k114, this suggests that the process of reorganization induced by ICMS can require several days.
Following Fig. 8.5, the degree of reorganization obtained in an experiment can be quantified by comparing the similarity valuesCat different stages of the exper-iment. For this purpose we defined the modification
∆C = Cpost
Clate (8.2)
as the quotient between the similarityCpost observed immediately after ICMS and the similarityClateobtained several days after ICMS for the latest map being recor-ded. The modification ∆C is large if the induced reorganization is large and it is small if the map largely recovers. It will be used in Section 8.6.
We conclude that by ICMS, orientation maps can be converted to a different map persistent at least over 7 days. Moreover, induced changes can be transient lead-ing to a largely complete recovery of the original map. Both observations support the hypothesis that the reorganization of the orientation map follows an attractor dynamics.
8.4 Spatial-temporal dynamics
In order to obtain a better understanding of the reorganization initiated by ICMS, we conducted a series of acute experiments (Fig. 8.1a). Besides the relatively high temporal resolution gained with this method (of≈2h) we also increased the frame of the recording window by a factor oft two since we were interested in the spread-ing and the spatial range of the induced changes.
We observed a progressive rearrangement in the hours following ICMS. The rear-rangement developed continously indicating that the reorganization evolves with a temporal scale on the order of 1h (Fig. 8.6). Largest changes were found within
a distance of 3mm from the ICMS site and often, the maximum change was not di-rectly at the ICMS site. For the experiment shown in Fig. 8.6a, the induced changes were initially small and remained small up to 3h before becoming much stronger after 9h. In contrast, for the experiment in Fig. 8.6b, the effect was maximal im-mediately after ICMS and decreased thereafter. In the example shown in Fig. 8.6c, changes went back and forth. The observed increase and decrease often resembled a process of relaxation further supporting the hypothesis of an underlying attractor dynamics. However, a reorganization as strong as observed for the chronic exper-iments 7 days after ICMS was generally not seen in the acute experexper-iments. One possible interpretation consistent with experiments k114 and k109 (Fig. 8.5) is that the reorganization of large regions of the map and regions away from the ICMS site takes place on the temporal scale of days rather than hours. An alternative explanation is that reorganization may require normal visual experience or sleep.
Figure 8.6: Transient changes induced by ICMS. a, b, c, SimilarityC0 as a function of the distance from the ICMS site (averaged over concentric rings around the ICMS site) evolving in acute experiments. Induced changes can increase substantially over a period of several hours after termination of ICMS (a). Already immediately after termination of ICMS (post) the induced changes can spread over3mm (b). Changes can decrease after ICMS and progressively in-crease at a later stage (c). For comparison with the model, refer to Fig. 7.3.
8.5 Induced pinwheel dynamics
A further quantity of particular interest is the pinwheel density. In Section 7.5.2 we showed that the model predicts a complex pinwheel dynamics under ICMS includ-ing movement, creation and annihilation durinclud-ing and after ICMS. In this Section we test this by applying the pinwheel analysis developed in Chapter 4 to the ICMS data. To estimate the position of pinwheels between the recordings, we linearly interpolated between subsequent maps (see Section 8.2).