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. 2010 Jul 21;30(29):9793-800.
doi: 10.1523/JNEUROSCI.0915-10.2010.

Voluntary control over prestimulus activity related to encoding

Affiliations

Voluntary control over prestimulus activity related to encoding

Matthias J Gruber et al. J Neurosci. .

Abstract

A new development in our understanding of human long-term memory is that effective memory formation relies on neural activity just before an event. It is unknown whether such prestimulus activity is under voluntary control or a reflection of random fluctuations over time. In the present study, we addressed two issues: (1) whether prestimulus activity is influenced by an individual's motivation to encode, and (2) at what point in time encoding-related activity emerges. Electrical brain activity was recorded while healthy male and female adults memorized series of words. Each word was preceded by a cue, which indicated the monetary reward that would be received if the following word was later remembered. Memory was tested after a short delay with a five-way recognition task to separate different sources of recognition. Electrical activity elicited by the reward cue predicted later memory of a word. Crucially, however, this was only observed when the incentive to memorize a word was high. Encoding-related activity preceded high-reward words that were later recollected. This activity started shortly after cue onset and persisted until word onset. Prestimulus activity thus not only signals cue-related processing but also an ensuing preparatory state. In contrast, reward-related activity was limited to the time period immediately after the reward cue. These findings indicate that engaging neural activity that benefits the encoding of an upcoming event is under voluntary control, reflecting a strategic preparatory state in anticipation of processing an event.

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Figures

Figure 1.
Figure 1.
Example sequence of events during the study phase. Participants memorized series of words (e.g., “CAT” and “LIP”), each of which was preceded by the string “20p” written in black or the string “£2” written in green. The string served as a prestimulus cue, indicating the amount of money that would be earned if the following word was correctly identified in a recognition memory test performed at ∼15 min after the study phase. The comparisons of interest involved electrical brain activity elicited in the 2000 ms cue-word interval.
Figure 2.
Figure 2.
Reward-related neural activity. A, Group-averaged ERP waveforms elicited by low- and high-reward cues, regardless of memory performance to the following words. Waveforms are shown for three representative midline electrode sites (equivalent to Fz, Cz, and Pz of the international 10/10 system). Positive values are plotted upward. For graphical purposes, the waveforms displayed in this and all following figures are low-pass filtered at 15.5 Hz. B, Two-dimensional voltage spline maps showing the scalp distribution of reward-related activity (difference between high- and low-reward cues) in the 200–300, 300–600, and 600–1100 ms latency regions after cue onset. Maps are range scaled.
Figure 3.
Figure 3.
Encoding-related neural activity before word onset predicting later confident recognition. Group-averaged ERP waveforms elicited by low- and high-reward cues at three midline electrode sites (equivalent to Fz, Cz, and Pz of the international 10/10 system), separated as a function of later memory performance to the following words. Positive values are plotted upward. On the left are waveforms elicited by low-reward cues, overlaid according to whether the following word was later confidently recognized (given a remember or confident old judgment) or forgotten (judged as new). No differences are apparent. On the right are waveforms elicited by high-reward cues, again contrasting later confidently recognized and forgotten words. A positive-going subsequent memory effect emerges from ∼300 ms after cue onset.
Figure 4.
Figure 4.
Results of a bootstrap analysis on encoding-related neural activity before word onset in the low- and high-reward conditions. In each condition, equal numbers of confidently recognized and forgotten words were selected at random with replacement for each subject. The group average was then computed, and the mean amplitude in the 600–1100 ms interval was measured across all 32 electrode sites. This process was repeated 10,000 times. The resulting sampling distributions are shown here. Each gray dot represents a sample value for forgotten words, and each black dot represents a sample value for recognized words. Bootstrap iterations are displayed along the horizontal axes. Distributions for the low-reward condition are shown on the left, and those for the high-reward condition are shown on the right. There is a clear separation between the distributions of recognized and forgotten words in the high-reward condition. No such separation is apparent in the low-reward condition. For statistical comparisons, see Results.
Figure 5.
Figure 5.
Encoding-related neural activity before word onset predicting later recollection in the high-reward condition. A, Group-averaged ERP waveforms elicited by high-reward cues at the three midline electrode sites (equivalent to Fz, Cz, and Pz of the international 10/10 system). Waveforms are overlaid according to whether the following word was recollected (given a remember judgment), confidently judged as familiar (given a confident old judgment), or forgotten (given a new judgment) in the subsequent recognition test. The waveforms are based on the subset of participants with at least 13 trials in each category. Positive values are plotted upward. Activity preceding later recollected words differs from activity preceding confidently familiar and forgotten words. B, Range-scaled two-dimensional voltage spline maps illustrating the positive-going, widespread scalp distribution of the recollection-related subsequent memory effect before word onset. Shown are the amplitude differences between ERPs for later recollected and forgotten words in the 300–600, 600–1100, and 1100–2000 ms periods in the cue-word interval. Note that these maps were computed across all participants with sufficient numbers of recollected and forgotten trials to maximize the signal-to-noise ratio, not just the subset shown in A.

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