bioRxiv preprint doi: https://doi.org/10.1101/732735; this version posted August 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
1 TITLE: Theta power and theta-gamma coupling support spatial memory retrieval
2 Authors: Umesh Vivekananda1, Daniel Bush1,2, James A Bisby1,2, Sallie Baxendale1, Roman
3 Rodionov1, Beate Diehl1, Fahmida A Chowdhury1, Andrew W McEvoy1, Anna Miserocchi1,
4 Matthew C Walker 1, Neil Burgess1,2,
5 1 Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of
6 Neurology, London WC1N 3BG
7 2 UCL Institute of Cognitive Neuroscience, Queen Square, London WC1N 3AZ
8
9 Corresponding author: Dr. Umesh Vivekananda, Department of Clinical and Experimental
10 Epilepsy, Institute of Neurology, UCL. Email: [email protected]
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1 bioRxiv preprint doi: https://doi.org/10.1101/732735; this version posted August 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
23 Abstract
24 Hippocampal theta oscillations have been implicated in spatial memory function in both
25 rodents and humans. What is less clear is how hippocampal theta interacts with higher
26 frequency oscillations during spatial memory function, and how this relates to subsequent
27 behaviour. Here we asked ten human epilepsy patients undergoing intracranial EEG
28 recording to perform a desk-top virtual reality spatial memory task, and found that increased
29 theta power in two discrete bands (‘low’ 2-5Hz and ‘high’ 6-9Hz) during cued retrieval was
30 associated with improved task performance. Similarly, increased coupling between ‘low’
31 theta phase and gamma amplitude during the same period was associated with improved
32 task performance. These results support a role of theta oscillations and theta-gamma phase-
33 amplitude coupling in human spatial memory function.
34
35 Introduction
36 Oscillations in the local field potential (LFP) reflect synchronous neural activity and are a
37 likely candidate to integrate functional brain regions across multiple spatiotemporal scales
38 (Buzsáki & Schomburg, 2015; Fries, Nikolić, & Singer, 2007). In particular, oscillations within
39 the hippocampal-entorhinal system have long been hypothesized to play a role in cognitive
40 function. The theta rhythm has been well documented in the rodent and human hippocampal
41 network during translational movement and memory function (Buzsáki & Moser, 2013;
42 Düzel, Penny, & Burgess, 2010; O’Keefe & Nadel, 1978; Vanderwolf, 1969). Theta
43 frequency in rodents is typically 6-12Hz, but in the human hippocampus, theta frequency
44 appears to be lower and occupy discrete ‘low’ (2-5Hz) and ‘high’ (6-9Hz) bands (Bush et al.,
45 2017; Lega, Jacobs, & Kahana, 2012; Watrous, Tandon, Conner, Pieters, & Ekstrom, 2013).
46 The modulation of high-frequency activity by the phase of low-frequency oscillations such as
47 theta, manifesting as phase amplitude coupling (PAC), may provide a mechanism for inter-
48 areal communication and phase coding (Canolty et al., 2006). PAC has been well
2 bioRxiv preprint doi: https://doi.org/10.1101/732735; this version posted August 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
49 documented in both human and animal studies during spatial (Bieri, Bobbitt, & Colgin, 2014;
50 Lisman & Jensen, 2013; Newman, Gillet, Climer, & Hasselmo, 2013; Tamura, Spellman,
51 Rosen, Gogos, & Gordon, 2017; Tort et al., 2008), declarative (Axmacher et al., 2010; Fell et
52 al., 2003; Lega, Burke, Jacobs, & Kahana, 2016; Tort, Komorowski, Manns, Kopell, &
53 Eichenbaum, 2009), and sequence memory tasks (Heusser, Poeppel, Ezzyat, & Davachi,
54 2016). In particular, the modulation of low (30-50Hz) and high gamma (60-100Hz) power by
55 theta phase has been described in both the rodent (Colgin, 2015; Colgin et al., 2009) and
56 human brain (Alekseichuk, Turi, Amador de Lara, Antal, & Paulus, 2016; Lega et al., 2012).
57 Here, we characterised the role of low and high theta oscillations, and their relationship with
58 concurrent gamma power, in human intracranial EEG recordings during a self-paced spatial
59 memory task. We found that low and high theta power and low and high gamma power were
60 significantly increased during spatial memory retrieval, and that both increased theta power
61 and increased PAC between low theta and gamma oscillations in the hippocampus during
62 spatial memory retrieval correlated with task performance. These results support the
63 hypothesis that theta-gamma PAC within the hippocampal formation contributes to
64 successful spatial memory retrieval in humans.
65
66 Methods
67 iEEG Recordings. Thirteen patients with drug refractory epilepsy undergoing intracranial
68 EEG monitoring for clinical purposes were asked to perform a spatial memory task. Single
69 group comparison analysis based on the effect size observed in a previous translational
70 movement study (see Bush et al., 2017) indicates that 10 patients would be required to
71 identify differences in theta power at p < 0.05 with a power of 90%. Prior approval was
72 granted by the NHS Research Ethics Committee, and informed consent was obtained from
73 each subject. Post-implantation CT and/or MRI scans were used to visually inspect and
74 identify electrode locations, confirming that 10 patients had hippocampal contacts. Patient
75 demographics are listed in Supplemental Table 1. Depth EEG was recorded continuously at
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76 a sample rate of 1,024 Hz (patients 4 and 10) or 512 Hz (all other patients) using either a
77 NicoletOne long-term monitoring system (Natus Medical, Inc.) (Patients 1–6) or Micromed
78 SD long-term monitoring system (Micromed) (patients 7–10). Recordings made at a higher
79 sampling rate were down-sampled to 512 Hz, to match those from the majority of patients,
80 before any analyses were performed. All data analysis was performed using the FieldTrip
81 toolbox (Donders Institute for Brain, Cognition and Behaviour, Radboud University, the
82 Netherlands. See http://fieldtriptoolbox.org) (Oostenveld, Fries, Maris, & Schoffelen, 2011)
83 and custom MATLAB scripts.
84
85 Task: Spatial memory was assessed using an “object location task” within a desktop virtual
86 reality environment (Figure. 1A). Patients first navigated toward and memorized the location
87 of four objects that sequentially appeared in the environment (‘encoding’). Patients were
88 then cued with an image of one object (‘cue’), placed back in the environment and asked to
89 navigate toward the remembered location of that object and make a button-press response
90 (‘response’). The object then appeared in its correct location and the trial ended when they
91 moved to the visible object (‘feedback’). Performance contrasts were computed by taking the
92 median distance error across all trials for each participant and then comparing data between
93 trials with error lower than the median (good trials) to those with error greater than the
94 median (bad trials).
95
96 Time–Frequency Analysis. Estimates of dynamic oscillatory power during periods of interest
97 were obtained by convolving the EEG signal with a five-cycle Morlet wavelet. Time–
98 frequency data were extracted from 2 s before the start of each cue period of interest to 2 s
99 after the end of that period, and data from time windows before and after the period of
100 interest were discarded after convolution to avoid edge effects. All trials that included inter-
101 ictal spikes or other artefacts, either within the period of interest or during the padding
4 bioRxiv preprint doi: https://doi.org/10.1101/732735; this version posted August 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
102 windows, were excluded from all analyses presented here. Each patient performed either
103 one or two blocks, each consisting of 20 trials, providing a mean ± SD of 19.6 ± 11.9 trials
104 for analysis, after artefact rejection. Power values were obtained for 30 logarithmically
105 spaced frequency bands in the 2–100 Hz range. All power values from each contact were
106 log transformed, and then z-scored using the mean and SD of log-transformed power values
107 in each frequency band from artefact-free periods throughout the task.
108
109 To examine changes in oscillatory power within specific frequency bands and assess
110 correlations between oscillatory power and task performance, dynamic estimates of log-
111 transformed oscillatory power were averaged over the time and frequency windows of
112 interest for each electrode contact. Mean power values were then averaged across all
113 electrode contacts in the hippocampus to provide a single value for each patient. Changes in
114 oscillatory power according to task demands were analysed using one sample t-tests,
115 repeated-measures ANOVAs and post hoc one-sample t-tests with Bonferroni correction for
116 multiple comparisons where appropriate.
117
118 Phase amplitude coupling: PAC was tested for theta phase modulation of the amplitude of
119 two specific gamma bands (30-50Hz and 60-100Hz; following Colgin et al., 2009). Phase-
120 amplitude coupling was estimated using the phase-locking value, which is equal to the
121 resultant vector length of the phase difference between low theta oscillations and the
122 envelope (i.e. amplitude) of simultaneous gamma oscillations (Mormann et al., 2005). The
123 resultant cross frequency coupling values were then z-scored across artefact-free periods
124 from throughout the task, and comparisons made between good and bad trials. To establish
125 whether changes in PAC across trials resulted purely from changes in the signal to noise
126 ratio of low frequency power, we performed linear regression between low frequency power
127 and PAC values across trials separately for each electrode contact. Beta coefficients were
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128 then averaged across all electrode contacts for each patient, allowing one-sample t-tests to
129 be performed at the second level.
130
131 Results
132 1. Object location task performance correlates with formal assessment of spatial
133 memory
134 Prior to this study, all patients underwent formal neuropsychometry testing as pre-clinical
135 evaluation for epilepsy surgery. As part of that testing, all patients (apart from one) were
136 asked to perform a complex figure recall task from the BIRT Memory and Information
137 Processing Battery (Coughlan, Oddy, & Crawford, 2007), as a measure of visuospatial
138 memory, and a percentage accuracy score was given for performance. To establish the
139 sensitivity of our object location task, we began by correlating patient performance during
140 neuropsychometry with their mean distance error during that task. We found that there was a
141 significant negative correlation between immediate recall of the complex figure and distance
142 error in our task (Pearson’s r = -0.71, p=0.032; Figure 1B). This suggests that our object
143 location task was sensitive in discerning the spatial memory abilities of our subjects.
144
145 2. Increased theta and gamma power in hippocampus during retrieval
146 Next, we examined low frequency oscillatory power on hippocampal contacts during the 3s
147 cue period, when participants were asked to retrieve the location of an object prior to being
148 replaced in the virtual environment. We found that average z-scored theta power in both the
149 low (2-5Hz; t(9)=4.36, p=0.0024) and high (6-9Hz; t(9)=3.04, p=0.016) frequency bands
150 were significantly higher during the cue period. This suggests that low and high theta
151 oscillations in the hippocampus are engaged as a result of spatial memory retrieval. Next,
152 we focussed on high frequency oscillatory power in the 30-50Hz and 60-100Hz gamma
6 bioRxiv preprint doi: https://doi.org/10.1101/732735; this version posted August 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
153 bands. We found that average z-scored gamma power in both the low (30-50Hz; t(9)=2.34,
154 p=0.047) and high (60-100Hz, t(9)=2.55, p=0.034) frequency bands were significantly higher
155 during the cue period (Figure 1C). This suggests that hippocampal gamma oscillations are
156 also engaged by spatial memory retrieval.
157
158 3. Increased theta power in hippocampus during retrieval predicts performance
159 Next, in order to establish whether increased theta and / or gamma power in the
160 hippocampus were associated with task performance, we conducted a repeated measures
161 ANOVA with factors of performance (good v bad trials) and theta frequency band (low v
162 high). We found a significant effect of performance (F(1,35)=6.4, p=0.035), but no interaction
163 (p=0.68), driven by increased low and high theta power during good trials (Figure 2A, B).
164 Repeating this analysis with factors of performance (good v bad) and gamma frequency
165 band (low v high) revealed no significant effect of performance or interaction (all p>0.094).
166 This suggests that increased theta power within the hippocampus is associated with
167 accurate performance of the object location task, while gamma power does not vary
168 between good and bad trials.
169
170 4. Increased theta-gamma phase amplitude coupling in hippocampus during retrieval
171 predicts performance
172 To further dissect the role of low and high theta oscillations in spatial memory retrieval, we
173 next examined changes in phase-amplitude coupling (PAC) between low or high frequency
174 theta phase and low or high frequency gamma amplitude. First, we conducted a repeated
175 measures ANOVA for all trials with factors of theta band (2-5Hz v 6-9Hz) and gamma band
176 (30-50Hz v 60-100Hz), but found no significant differences in z-scored PAC between any
177 pair of frequency bands (all p>0.36). In addition, z-scored PAC values between any pair of
178 theta and gamma frequency bands were not significantly different from zero (all p>0.15),
7 bioRxiv preprint doi: https://doi.org/10.1101/732735; this version posted August 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
179 suggesting that there was no overall change in theta-gamma PAC during spatial memory
180 retrieval.
181
182 Next, to examine if PAC in the hippocampus was relevant for task performance we
183 performed a three way ANOVA with factors of performance (good v bad), theta band (2-5Hz
184 v 6-9Hz) and gamma band (30-50Hz v 60-100Hz). We found that PAC differed significantly
185 between good and bad trials (F(1,63)=9.21, p=0.005), with a significant interaction between
186 good/bad trials and low/high theta (F(1,63)=4.88, p=0.031), but no other interactions
187 (p>0.17). Subsequent analysis indicated that these results were driven by the increased
188 modulation of both low and high gamma amplitude by the phase of low theta band
189 oscillations during good trials (t(9)=2.2 p=0.02; Figure 3A-D). In order to ascertain whether
190 this increase in PAC was solely a reflection of increased low theta power, and therefore
191 signal-to-noise ratio, we examined whether low theta power and PAC values correlated
192 across trials on each electrode contact, but found no evidence for a significant linear
193 relationship (p=0.23). This suggests that increased low theta phase modulation of both low
194 and high gamma amplitude in the hippocampus is associated with improved task
195 performance, independent of concurrent changes in low theta power.
196
197 Discussion
198 Although separate low (2-5Hz) and high (6-9Hz) theta bands have been observed during
199 mnemonic function in humans, their specific function has remained unclear. Here, we have
200 demonstrated distinct roles for low and high theta within the hippocampus during
201 performance of a spatial memory task. It appears that during spatial memory retrieval (i.e.
202 during cue periods), both low and high theta power and low and high gamma power are
203 increased in the hippocampus. We had previously shown that hippocampal theta power was
204 indicative of movement onset in this task (Bush et al., 2017). Theta power is also associated
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205 with task performance, as previously reported in MEG (Kaplan et al., 2012) and intracranial
206 EEG (Miller et al., 2018) studies. Moreover, we found that increased modulation of low (30-
207 50Hz) and high gamma (60-100Hz) amplitude by low theta phase in the hippocampus is
208 associated with improved task performance. Indeed, rodent models suggest that these
209 gamma frequency bands mediate the routing and temporal segregation of inputs to the
210 hippocampal CA1 region from different sources (Colgin et al., 2009). In addition, human
211 studies have demonstrated a relationship between hippocampal subfield gamma power and
212 spatial memory precision in a different object-location task (Stevenson et al., 2018).
213 214 In summary theta band oscillations are functionally relevant to spatial memory retrieval,
215 while low theta-gamma phase amplitude coupling has a role in accurate spatial memory
216 performance.
217
218 Acknowledgements
219 This work was supported by the Department of Health's National Institute for Health
220 Research, UCL/UCL Biomedical Research Centre, Wellcome Trust, UK Medical Research
221 Council, European Research Council, Epilepsy Research UK, and Academy of Medical
222 Sciences.
223 We thank all patients who participated in this study.
224
225
226
227
228
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229 Figure legends
230 Table 1. Demographics and Epilepsy History of Patients for Spatial Memory Task. F=female,
231 M=male, R=right, L=left, B=bilateral
232
233 Figure 1. Increased theta and gamma power in the hippocampus during spatial
234 memory retrieval A. Schematic of the spatial memory task B. Median distance error in the
235 spatial memory task versus assessment of complex figure recall. Line of best fit shown in
236 blue C. Average z-scored power in the hippocampus during cue periods. Low (2–5 Hz) and
237 high (6–9 Hz) theta bands and low (30-50Hz) and high (60-100Hz) gamma bands are
238 marked in grey.
239
240 Figure 2. Low and high theta power in the hippocampus are associated with improved
241 performance A. Average z-scored power in the hippocampus during cue periods of good
242 trials, with low (2–5 Hz) and high (6–9 Hz) theta bands and low (30-50Hz) and high (60-
243 100Hz) gamma bands marked in grey. B. Average z-scored power in the hippocampus
244 during cue periods of bad trials.
245
246 Figure 3. Increased low theta phase modulation of gamma amplitude is associated
247 with improved performance. A. Cross frequency spectrogram for good trials; boxed
248 regions highlight significant coupling between 2-5Hz low theta phase and 30-50Hz low and
249 60-100Hz high gamma amplitude B. Cross frequency spectrogram for bad trials C. Average
250 z-scored PAC between 2-5Hz low theta phase and 30-50Hz low gamma amplitude within the
251 hippocampus in good (grey) and bad (black) trials. D. Average z-scored PAC between 2-5Hz
252 low theta phase and 60-100Hz high gamma amplitude within the hippocampus in good
253 (grey) and bad (black) trials
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14 bioRxiv preprint doi: https://doi.org/10.1101/732735; this version posted August 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/732735; this version posted August 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/732735; this version posted August 12, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.