Individual differences in theta-band oscillations in a spatial memory network revealed by electroencephalography predict rapid place learning

Abstract

Spatial memory has been closely related to the medial temporal lobe and theta oscillations are thought to play a key role. However, it remains difficult to investigate medial temporal lobe activation related to spatial memory with non-invasive electrophysiological methods in humans. Here, we combined the virtual delayed-matching-to-place task, reverse-translated from the watermaze delayed-matching-to-place task in rats, with high-density electroencephalography recordings. Healthy young volunteers performed this computerised task in a virtual circular arena, which contained a hidden target whose location moved to a new place every four trials, allowing the assessment of rapid memory formation. Using behavioural measures as predictor variables for source reconstructed frequency-specific electroencephalography power, we found that inter-individual differences in 'search preference' during 'probe trials', a measure of one-trial place learning known from rodent studies to be particularly hippocampus-dependent, correlated predominantly with distinct theta-band oscillations (approximately 7 Hz), particularly in the right temporal lobe, the right striatum and inferior occipital cortex or cerebellum. This pattern was found during both encoding and retrieval/expression, but not in control analyses and could not be explained by motor confounds. Alpha-activity in sensorimotor and parietal cortex contralateral to the hand used for navigation also correlated (inversely) with search preference. This latter finding likely reflects movement-related factors associated with task performance, as well as a frequency difference in (ongoing) alpha-rhythm for high-performers versus low-performers that may contribute to these results indirectly. Relating inter-individual differences in ongoing brain activity to behaviour in a continuous rapid place-learning task that is suitable for a variety of populations, we could demonstrate that memory-related theta-band activity in temporal lobe can be measured with electroencephalography recordings. This approach holds great potential for further studies investigating the interactions within this network during encoding and retrieval, as well as neuromodulatory impacts and age-related changes.

Keywords: Memory; electroencephalography; medial temporal lobe; theta oscillations; water maze.

Figure 1.

The virtual DMP task and the structure of the experimental sessions. (a) and (b) Participants were placed within a circular environment, with landmarks presented at varying distances from the circular wall, and were instructed to find a hidden target (see Figure 2 for an illustration of search paths). (c) In order to repeatedly test rapid place learning, the hidden goal (filled circles in panel (c)) moved after every four trials, and was placed at eight different locations during an experimental session (filled squares in panel (a)). (d) Each participant completed one experimental session split into four blocks. Each block started with a 2-min resting state period, followed by two sets of four navigation trials. During each set of four trials, the goal was placed in the same location, and participants began one trial from each of the notional cardinal points of the environment. Participants were then instructed that the goal had moved, and completed another set of four trials navigating to the new location. In trial 1, participants could not know the location of the target and had to search for it. In trials 2–4, the participants could use the memory of the location acquired during trial 1 in order to navigate to the target efficiently. At locations 4, 6 and 8, the second of the four navigation trials was ran as a probe trial (marked by an *), during which no feedback was given when participants crossed the target location. Probe trials continued for 60 s, during which participants’ ‘search preference’ for correct location could be measured. EEG was recorded continuously throughout the entire session.

Figure 2.

Behavioural performance on the virtual DMP test. (a) Illustration of one participant’s search paths during the four trials to one location. (b) Path-length measures as a function of trial, averaged across all locations and participants. Left: total path length is the entire translational distance (without rotations) travelled by the participant; numbers represent (arbitrary) ‘maze units’ as distance measure. Right: path efficiency is path length normalised to the distance of starting position to target location. Averages of each participant across trials have been subtracted; error bars thus represent standard error of mean condition differences across participants, that is, confidence intervals. (c) Left: average heat map of participant locations during probe trials, with the target location at 0,0. Colour code represents the average normalised frequency as a function of spatial location. Right: histogram of locations for the three different probe trials in sequence of occurrence. Numbers on x-axis represent the spatial distance from target in ‘maze-units’; y-axis represents the normalised frequencies.

Figure 3.

Negative correlations between oscillatory EEG activity and distance to target. (a)–(d) Negative correlations of EEG activity during probe trials (retrieval/expression) and trial 1 (encoding) with average distance to target during probe trial. Crosshairs in brain topographies show the location of cross-section planes (chosen to provide good overview). (a) Frequency spectrum of the omnibus significant cluster for the probe trial, correcting for multiple comparisons across frequencies and three spatial dimensions; higher theta-band activity during the probe trial is correlated with smaller distance to target. (b) Axial, coronal and sagittal views of the thresholded cluster (brain activations are sign-inverted to frequency spectra): activation is centred in (predominantly right) temporal cortex, inferior occipital cortex or cerebellum and striatum, forming one large cluster. (c) and (d) Same as (a) and (b), but now for the oscillatory activity during trial 1 (encoding); note the spectral and spatial similarity of the effects. (e) and (f) As a control analysis, the average distance during all non-probe trials was correlated to the EEG activity in the corresponding trials (to test for potential confounds, for example, related to sensorimotor factors). The largest cluster of this analysis was a peak in occipital alpha/beta activity (also sign-inverted) that did, however, not reach omnibus significance. All colour scales here show t-values averaged across the whole frequency domain (including frequencies where no significant correlation was found), with dark red corresponding to the lowest and white to the highest t-values, hence associated numeric values are arbitrary.

Figure 4.

Positive correlations between oscillatory EEG activity and distance to target. (a)–(d) Positive correlations of EEG activity during probe trials (retrieval/expression) and trial 1 (encoding) with average distance to target during probe trials. Crosshairs in brain topographies show the location of cross-section planes (chosen to provide good overview). (a) The spectrum of this effect for the probe trial, while (b) its topography with a clear maximum over left primary sensorimotor cortex. This cluster, however, failed to reach omnibus significance. (c) The spectral distribution of the highly significant (p < 0.01) cluster for the encoding trial 1, while (d) its brain topography over left parietal areas. Since these effects, located over motor and sensorimotor regions, likely reflect motor-related patterns, a control analysis was conducted: the rate of button presses (see main text) was correlated with EEG activity across all trials. (e) The spectrum of this effect. Note that a higher rate of button presses (i.e. less stationary movement patterns) correlates with reduced alpha-activity (whereas in (a)–(d) the average distance from target, a value likely to be inversely related to button press rate was used). (f) The topography of this highly significant effect (p < 0.001), which is similar though more widespread than the effect in (b) and (d). All colour scales here show t-values averaged across the whole frequency domain (including frequencies where no significant correlation was found), with dark red corresponding to the lowest and white to the highest t-values, hence associated numeric values are arbitrary.

Figure 5.

Principal component control analysis. (a) Averaged power spectra, not baseline corrected, in high-performing probe trials (red line) compared to low-performing probe trials (blue line). (b) The same for the resting state period immediately preceding the respective probe trials. (c) The results of the t-test for independent samples of baseline-corrected power during the probe trial.