Theta activity in the hippocampus is related to specific cognitive and behavioral stages. Here, we describe an analytical method to detect highly-organized theta oscillations within the hippocampus using a time-frequency (i.e., wavelet analysis)-based approach.
Theta activity is generated in the septohippocampal system and can be recorded using deep intrahippocampal electrodes and implantable electroencephalography (EEG) radiotelemetry or tether system approaches. Pharmacologically, hippocampal theta is heterogeneous (see dualistic theory) and can be differentiated into type I and type II theta. These individual EEG subtypes are related to specific cognitive and behavioral states, such as arousal, exploration, learning and memory, higher integrative functions, etc. In neurodegenerative diseases such as Alzheimer's, structural and functional alterations of the septohippocampal system can result in impaired theta activity/oscillations. A standard quantitative analysis of the hippocampal EEG includes a Fast-Fourier-Transformation (FFT)-based frequency analysis. However, this procedure does not provide details about theta activity in general and highly-organized theta oscillations in particular. In order to obtain detailed information on highly-organized theta oscillations in the hippocampus, we have developed a new analytical approach. This approach allows for time- and cost-effective quantification of the duration of highly-organized theta oscillations and their frequency characteristics.
Theta activity in the brain is related to different cognitive and functional states, including arousal, attention, voluntary movement, exploratory behavior, attention behavior, learning and memory, somatosensory integration, and rapid eye movement (REM) sleep1,2. Principally, theta activity as a rhythmic entity can be generated in various cerebral regions and is highly organized and synchronized as theta oscillations. Below, we will focus on the analysis and quantification of theta activity/oscillations that are generated within the septohippocampal system3,4. Within the septum, GABAergic, glutamatergic, and cholinergic neurons project to the hippocampus and contribute to the initiation and maintenance of theta oscillatory behavior. There is an ongoing discussion on whether hippocampal theta oscillations are initiated in the septum, i.e., the septal pacemaker-hippocampal follower model, (extrahippocampal theory) or intrinsically within the hippocampus (intrahippocampal theory)5,6,7.
Regardless of their origin, hippocampal theta oscillations have been in the focus of interest for years, particularly in transgenic mouse models. These models allow for the implantation of deep EEG electrodes and for the recording of hippocampal theta oscillations under specific cognitive and behavioral tasks8. Hippocampal theta oscillations are heterogenous in nature. Based on the so-called dualistic theory of theta oscillations, one can differentiate between atropine-sensitive type II theta and atropine-insensitive type I theta9,10,11. The latter can typically be induced by muscarinic M1/M3 receptor agonists, e.g., arecoline, pilocarpine, and urethane. However, urethane is a multi-target drug that, besides muscarinic activation, also exerts complex effects on other ion channel entities. For type II theta, the muscarinic pathway includes the activation of M1/M3 and a subsequent Gq/11 (Gα)-mediated activation of phospholipase C β1/4 (PLCβ1/4), inositol trisphosphate (InsP3), diacylglycerole (DAG), Ca2+, and protein kinase C (PKC). The role of PLCβ1 and PLCβ4 in thetagenesis has been validated in knock-out studies using PLCβ1-/- and PLCβ4-/- mice exhibiting a complete loss or significant attenuation of theta oscillation12,13,14. Additional M1, M3, and M5 downstream targets (channels/currents) of the muscarinic signaling cascade include various conductances, such as M-type K+ channel (KM) via voltage-dependent K+ channel (Kv7); slow after hyperpolarization K+ channel (KsAHP); leak K+ channel (Kleak), probably via TWIK-related acid-sensitive K+ channel (TASK1/3); cation current (ICAT), probably via Na+ leak channel (NALCN); and Ih via hyperpolarization and cyclic nucleotide gated channels (HCN). In addition, M2/M4 acetylcholine receptors (AChRs) were reported to interfere with inward rectifier K+ channel 3.1 (Kir3.1) and inward rectifier K+ channel 3.2 (Kir3.2)15.
Currently, commercially-available analytical software allows for fast FFT-based frequency analysis, e.g., analysis of power (P, mV2) or power spectrum density (PSD, mV2/Hz). Power or power spectrum density (PSD) analysis of the theta frequency range only gives a global overview of its activity. However, in order to get a detailed insight into cognitive and behavior-related theta activity, the analysis of highly-organized theta oscillations is mandatory. The assessment of highly-organized theta oscillations is of central importance in the field of neurodegenerative and neuropsychiatric diseases. Most experimental disease studies are carried out in transgenic mouse models using highly-sophisticated neurosurgical approaches to record epidural surface and deep intracerebral EEGs. These techniques include both tether systems16 and radiotelemetric setups17,18. Theta oscillations can be recorded as spontaneous and behavior-related theta oscillations under long-term recording conditions. Additionally, theta oscillations can be recorded following pharmacological induction but also following the exposure of animals to behavioral or cognitive tasks or to sensory stimuli, such as tail pinching.
Early approaches to characterize theta oscillations were described by Csicsvari et al.19. The authors designed a semi-automated tool for short-term theta analysis (15 – 50 min) that is not suitable for long-time EEG recordings. Our method, described here, allows for the analysis of long-term EEG recording > 48 h20. Csicsvari et al.10 also referred to the theta-delta ratio, but no threshold for the determination of highly-organized theta oscillations is provided. The delta and theta range definitions match our frequency range definitions. As it is not explicitly mentioned, we presume that an FFT-based method is used by Csicsvari et al. to calculate the power of the theta-delta frequency bands. This again clearly differs from our method, since we calculate wavelet-based amplitudes on a large number of frequency scales (frequency steps Δ(f) = 0.05 Hz), resulting in much higher precision. The duration of the individually-analyzed EEG epoch is similar to our definition.
Klausberger et al.21 also make use of theta-delta ratios for the analysis of long-term EEG recordings. However, there are three major differences compared to our approach: i) the EEG epoch duration is much longer, i.e., at least 6 s; ii) the theta-delta ratio is set to 4, which is much higher than our threshold, and is related to different frequency range definitions; and iii) the power definition is likely to be based on an FFT approach, which lacks high precision, particularly for very short time windows (2 s, i.e., 5 cycles for oscillations with a frequency of 2.5 Hz). In such cases, a wavelet-based procedure is more recommendable. A study by Caplan et al.22 solely calculated theta power while ignoring the theta-delta power ratio. Thus, the Caplan approach22 cannot differentiate between cognitive theta-rich processes accompanied by a high or low delta.
In the following protocol, we will present our analytical wavelet-based approach to reliably analyze highly-organized theta oscillations in hippocampal EEG recordings from mice. Since this procedure works automatically, it can be applied to large data sets and long-term EEG measurements.
All animal experimentation was performed according to the guidelines of the local and institutional Council on Animal Care (University of Bonn, BfArM, LANUV, Germany). In addition, all animal experimentation was carried out in accordance with superior legislation, e.g., the European Communities Council Directive of 24 November 1986 (86/609/EEC), or individual regional or national legislation. Specific effort was made to minimize the number of animals used, as well as their suffering.
1. Animal Housing and EEG Recording Conditions
2. Radiotelemetric EEG Electrode Implantation and EEG Recordings
3. Spontaneous Recordings of Theta Oscillations and Pharmacological Induction
4. Validation of EEG Electrode Placement
5. Data Acquisition
6. EEG Data Analysis
Theta activity can be recorded in a wide range of central nervous system (CNS) regions. Here, we present an analysis of theta oscillations from the murine hippocampus. Such oscillations can occur during different behavioral and cognitive states. It is highly recommended to analyze theta oscillations under both spontaneous long-term, task-related short-term, and pharmacologically-induced conditions.
Figure 1 illustrates a representative intrahippocampal CA1 recording under control conditions. If the animal is not in a spontaneous "theta state," the intrahippocampal EEG is often characterized by large-irregular-amplitude (LIA) activity. Administration of muscarinic receptor agonists (e.g., arecoline, pilocarpine, or urethane) results in highly-organized theta oscillations that can be blocked by atropine (50 mg/kg, i.p., Figure 1).
In order to quantify highly-organized theta oscillations with the appropriate time resolution, the theta detection tool was used to classify 2.5 s EEG epochs as either theta-negative or theta-positive (Figure 2). Based on this classification, it is possible to quantify the total duration of theta oscillations under spontaneous conditions or specific behavioral and cognitive tasks.
In order to analyze a 30-min EEG segment (as for pharmacological urethane/atropine theta dissection), we first perform a time-frequency analysis for a frequency range of 0.2-12 Hz, which displays the amplitude (mV) in a color-coded fashion (Figure 3 A). As becomes obvious in Figure 3 A, high-amplitude theta activity, which is confirmed by a visual inspection of the EEG (white arrows), is accompanied by a low amplitude in the delta frequency range. Then, the maximum amplitudes of the theta (3.5-8.5 Hz) and delta (2-3.4 Hz) frequency ranges are plotted (Figure 3 B). Systematic correlation studies revealed that the ratio of maximum theta amplitude to maximum delta amplitude exceeding 1.5, indicating highly-organized theta oscillations (Figure 3 C).
Figure 4 demonstrates how urethane can induce hippocampal theta oscillations (white circles in Figure 4 II). Urethane is a multi-target drug that can trigger type II theta due its agonistic action on muscarinic receptors. Following an atropine injection (Figure 4 III), these type II theta oscillations (atropine-sensitive theta oscillations) are abolished. It is important to consider that the muscarinic receptor agonists, in addition to atropine, have individual pharmacokinetic properties that affect the time characteristics of theta occurrence and theta blockade. It should be noted that atropine-insensitive type I theta remains unaffected by muscarinic receptor antagonists.
A summary of the whole theta detection and quantification tool is depicted in Figure 5. It results in the calculation of the amplitude, frequency, and sum/mean theta duration. In contrast to previously-described techniques, it makes use of a wavelet-based approach with high precision. The analytical tool described here has several fields of application. Theta oscillations are generated in the septohippocampal system and are often impaired by neurodegenerative processes, e.g., in Alzheimer's disease. Numerous mouse models of Alzheimer's disease have been described that vary in homology, isomorphism, and predictability. Some of these models were reported to exhibit a reduction in theta activity, whereas others were shown to display an increase in theta activity, the reason for which remains to be determined. We successfully applied the theta detection tool described here to characterize altered theta oscillatory architecture in the 5XFAD model of Alzheimer's disease8. However, it might also be applied in epilepsy research and neuropsychiatric diseases.
Figure 1: Theta Oscillations in C57Bl/6 Mice. Radiotelemetric intrahippocampal CA1 recording under spontaneous conditions (I) and following urethane injection (800 mg/kg, i.p., II). Following urethane injection, highly-organized theta oscillations become visible, which can be blocked by atropine (50 mg/kg, i.p.). This figure has been modified from reference20, with permission. Please click here to view a larger version of this figure.
Figure 2: A Wavelet-based Analysis of a Deep CA1 EEG Recording from a C57Bl/6 Mouse. (A and B) Two 2.5-s EEG epochs are depicted, visually classified as non-theta and theta segments, respectively. (C and D) Time-frequency analysis of the CA1 EEG segments displayed in A and B in the range of 0.2-12 Hz, with the amplitude being color-coded. The time-frequency analysis in C exhibits irregular, fluctuating theta architecture regarding frequencies and time, whereas a segment with highly synchronized theta oscillations is characterized by a regular, non-fluctuating high amplitude theta of a nearly constant frequency of 6 Hz. The ratio of maximum theta to maximum delta amplitude is 1.25 in C and 4.67 in D, clearly classifying B as a theta oscillation EEG segment. This figure was reprinted from Reference 20, with permission. Please click here to view a larger version of this figure.
Figure 3: A Wavelet-based Theta Detection Tool. (A) Time-frequency analysis of a 30 min EEG segment (not shown) that has been recorded following urethane administration. The complex Morlet wavelet-based analysis was performed in the range of 0.2-12 Hz, with the amplitude (mV) being color-coded. (B) This image displays the maximum amplitude of the theta frequency band (3.5-8.5 Hz, green) and the upper delta band (2-3.4 Hz, red) for the 30-min EEG segment. (C) This figure illustrates the ratio of the maximum theta amplitude (green in B) and the maximum delta amplitude (red in B). Note that highly-synchronized theta oscillations correlate with suprathreshold ratios in C. This figure was reprinted from Reference 20, with permission. Please click here to view a larger version of this figure.
Figure 4: Wavelet-based Analysis of Pharmacologically-induced, Highly-organized Theta Oscillations. Representative 30-min EEG segments (not shown) are analyzed in the frequency range of 0-12 Hz with the amplitude (mV) being color-coded. A urethane injection at 800 mg/kg, i.p., resulted in the fragmented occurrence of highly-organized theta oscillations, with a predominant frequency of about 6 Hz (white circles). Following an atropine injection at 50 mg/kg, i.p., these theta oscillations are abolished. This figure was reprinted from Reference 20, with permission. Please click here to view a larger version of this figure.
Figure 5: Flow Diagram Illustrating the Quantification of Highly-organized Theta Oscillations Recorded from the Murine CA1. Type II theta oscillations can be analyzed using a control recording (phase), a post-injection (e.g., urethane, arecoline, or pilocarpine) phase, and a post-atropine phase (A1). 30 min EEG segments (A2) from each phase are time-frequency analyzed in the range from 0.2-12 Hz using a wavelet-based approach (B1 and B2). Next, theta segment detection is initiated (C1), giving a closer look at the time-frequency characteristics of theta range (3.5-8.5 Hz, C2) and the upper delta range (2-3.4 Hz, C3) for EEG epochs that are 2.5 s each (C4 and C5). Subsequently, the amplitude is analyzed over the theta and delta frequency range depicting the maximum values (C6 and C7). If the maximum amplitude of theta/delta exceeds 1.5, the 2.5 s EEG segment is classified as an epoch of highly-organized theta oscillation (C8), with a defined amplitude and frequency (D1-D3). This theta detection tool allows for the quantification of theta oscillation architecture (E1). Please click here to view a larger version of this figure.
Theta activity is of central relevance in systemic neurophysiology. It can be observed in various brain regions, particularly in the hippocampus, where it is related to specific behavioral and cognitive states. In addition, hippocampal theta can be pharmacologically differentiated into atropine-sensitive type II and atropine-insensitive type I theta. Type I is thought to be related to locomotion, such as walking or running27,28,29,30,31, whereas type II can be observed during the alert-immobility state27,28,29,30. Alert-immobility states can be induced by infrequent and random tone or tactile stimuli, for example32. Type II theta is also related to passive whole-body rotation14. During paradoxical sleep, both atropine-sensitive and atropine-resistant theta rhythms are present33. The resting-immobility state is characterized by large irregular activity (LIA)27.
In general, theta oscillations can be recorded under spontaneous conditions, but also following pharmacological induction (e.g., via the application of muscarinic receptor agonists, such as urethane, pilocarpine, arecoline, oxotremorine, etc.). Note that, pharmacodynamically, urethane is a multi-target drug that can enhance type II theta but also inhibit type I theta. In contrast, pilocarpine, arecoline, and oxotremorine selectively induce type II theta. Depending on the pharmacokinetics of the muscarinic agonists used, it takes a variable amount of time until theta oscillations occur. Type II can be blocked effectively by atropine. Critically, the dosages of muscarinic agonists and antagonists to induce and block type II theta oscillations are species- and strain-dependent. Thus, it is absolutely essential to perform dose-effect studies to unravel the optimal dose for the induction of theta oscillations and for their blockage for a specific scientific question. Short-lasting theta oscillations can also be induced by sensory stimuli, such as tail- or paw-pinching.
There are different approaches to characterize theta activity in general. FFT-based approaches, resulting in continuous or discontinuous (frequency band-related) power spectrum density (PSD) analysis/plots or in a power analysis for individual frequency bands, are standard approaches that provide valuable information on frequency characteristics.
However, to achieve a more complex insight into theta architecture, additional approaches seem to be necessary. In particular, one might be interested in the different organizational states of theta and their frequencies, which cannot be assessed directly and accurately by the aforementioned procedures. In contrast, the novel analytical technique presented here is wavelet-based and capable of evaluating highly-organized, short-term theta oscillations. They do not correspond to standard theta power, which also considers paroxysmal, discontinuous theta activity. The focus is to elicit specific time-frequency characteristics in the EEG data that are typical for theta epochs. Thus, the new method prevents false-positive classifications of theta epochs. The automated procedure guarantees the evaluation of long-lasting EEG data sets and therefore includes reliable statistical comparisons of physiological cycles (light/dark cycle or circadian rhythmicity) during long-term studies.
This protocol is of special importance in the analysis of EEG data obtained from animal models of neurodegenerative diseases, particularly in the characterization of highly-organized theta architecture in the septohippocampal and other neural systems. Complex and high-precision theta analysis might help to determine EEG fingerprints that can serve as EEG biomarkers in the future.
The authors have nothing to disclose.
The authors would like to thank Dr. Christina Ginkel (German Center for Neurodegenerative Diseases, DZNE) and Dr. Robert Stark (DZNE) for their assistance with animal breeding and animal healthcare. This work was financially supported by the Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, BfArM), Bonn, Germany.
Carprofen (Rimadyl VET – Injektionslösung) | Pfizer | PZN 0110208208 | 20ml |
binocular surgical magnification microscope | Zeiss Stemi 2000 | 0000001003877, 4355400000000, 0000001063306, 4170530000000, 4170959255000, 4551820000000, 4170959040000, 4170959050000 | |
Dexpanthenole (Bepanthen Wund- und Heilsalbe) | Bayer | PZN: 1578818 | |
drapes (sterile) | Hartmann | PZN 0366787 | |
70% ethanol | Carl Roth | 9065.5 | |
0.3% / 3% hydrogene peroxide solution | Sigma | 95321 | 30% stock solution |
gloves (sterile) | Unigloves | 1570 | |
dental glas ionomer cement | KentDental /NORDENTA | 957 321 | |
heat-based surgical instrument sterilizer | F.S.T. | 18000-50 | |
high-speed dental drill | Adeor | SI-1708 | |
Inhalation narcotic system (isoflurane) | Harvard Apparatus GmbH | 34-1352, 10-1340, 34-0422, 34-1041, 34-0401, 34-1067, 72-3044, 34-0426, 34-0387, 34-0415, 69-0230 | |
Isoflurane | Baxter 250 ml | PZN 6497131 | |
Ketamine | Pfizer | PZN 07506004 | |
Lactated Ringer's solution (sterile) | Braun | L7502 | |
Nissl staining solution | Armin Baack | BAA31712159 | |
pads (sterile) | ReWa Krankenhausbedarf | 2003/01 | |
Steel and tungsten electrodes parylene coated | FHC Inc., USA | UEWLGESEANND | |
stereotaxic frame | Neurostar | 51730M | ordered at Stoelting |
(Stereo Drive-New Motorized Stereotaxic) | |||
tapes (sterile) | BSN medical GmbH & Co. KG | 626225 | |
TA10ETA-F20 | DSI | 270-0042-001X | Radiofrequency transmitter 3.9 g, 1.9 cc, input voltage range ± 2.5 mV, channel bandwidth (B) 1-200 Hz, nominal sampling rate (f) 1000 Hz (f = 5B) temperature operating range 34-41 °C warranted battery life 4 months |
TL11M2-F20EET | DSI | 270-0124-001X | Radiofrequency transmitter 3.9 g, 1.9 cc, input voltage range ± 1.25 mV, channel bandwidth (B) 1-50 Hz, nominal sampling rate (f) 250 Hz (f = 5B) temperature operating range 34-41 °C warranted battery life 1.5 months |
Vibroslicer 5000 MZ | Electron Microscopy Sciences | 5000-005 | |
Xylazine (Rompun) | Bayer | PZN: 1320422 | |
Matlab | Mathworks Inc. | programming, computing and visualization software | |
SPSS | IBM | statistical analysis software |