Oscillations and Episodic Memory: Addressing the Synchronization/Desynchronization Conundrum
Authors: Simon Hanslmayr, Bernhard P. Staresina, Howard Bowman
Journal: Trends in Neurosciences (2016)

Data from rodent as well as human studies suggest that theta/gamma synchronization in the hippocampus (i.e., theta phase to gamma power cross-frequency coupling) mediates the binding of different elements in episodic memory. In vivo and in vitro animal studies suggest that theta provides selective time windows for fast-acting synaptic modifications and recent computational models have implemented these mechanisms to explain human memory formation and retrieval. Recent data from human experiments suggest that low-frequency power decreases in the neocortex, most evident in the alpha/beta frequency range, mediate encoding and reinstatement of episodic memories. The content of reinstated memories can be decoded from cortical low-frequency patterns. Brain oscillations are one of the core mechanisms underlying episodic memory. However, while some studies highlight the role of synchronized oscillatory activity, others highlight the role of desynchronized activity. We here describe a framework to resolve this conundrum and integrate these two opposing oscillatory behaviors. Specifically, we argue that the synchronization and desynchronization reflect a division of labor between a hippocampal and a neocortical system, respectively. We describe a novel oscillatory framework that integrates synchronization and desynchronization mechanisms to explain how the two systems interact in the service of episodic memory. Brain oscillations are one of the core mechanisms underlying episodic memory. However, while some studies highlight the role of synchronized oscillatory activity, others highlight the role of desynchronized activity. We here describe a framework to resolve this conundrum and integrate these two opposing oscillatory behaviors. Specifically, we argue that the synchronization and desynchronization reflect a division of labor between a hippocampal and a neocortical system, respectively. We describe a novel oscillatory framework that integrates synchronization and desynchronization mechanisms to explain how the two systems interact in the service of episodic memory. Brain oscillations (see Glossary) provide temporal windows for neural firing and shape synaptic plasticity by synchronizing and desynchronizing neural assemblies. Oscillations therefore have a particularly high potential to shed light on the mechanisms underlying episodic memory [1Fell J. Axmacher N. The role of phase synchronization in memory processes.Nat. Rev. Neurosci. 2011; 12: 105-118Crossref PubMed Scopus (1004) Google Scholar, 2Buzsaki G. Neural syntax: cell assemblies, synapsembles, and readers.Neuron. 2010; 68: 362-385Abstract Full Text Full Text PDF PubMed Scopus (747) Google Scholar]. However, over the past few years a conundrum has emerged regarding how brain oscillations relate to memory [3Hanslmayr S. Staudigl T. How brain oscillations form memories – a processing based perspective on oscillatory subsequent memory effects.Neuroimage. 2014; 85: 648-655Crossref PubMed Scopus (145) Google Scholar]. Whereas some studies highlight the role of synchronized activity, mainly in the theta (∼3–8 Hz) and gamma (∼40–80 Hz) frequencies [1Fell J. Axmacher N. The role of phase synchronization in memory processes.Nat. Rev. Neurosci. 2011; 12: 105-118Crossref PubMed Scopus (1004) Google Scholar], others highlight the role of desynchronized activity, mainly in the lower-frequency ranges (<20 Hz [4Hanslmayr S. et al.Oscillatory power decreases and long-term memory: the information via desynchronization hypothesis.Front. Hum. Neurosci. 2012; 6: 74Crossref PubMed Scopus (108) Google Scholar]). This conundrum exists at both an empirical and a theoretical level. Based on Hebb's seminal idea – neurons that fire together, wire together – a strong case can be made that synchrony is required for memory formation [1Fell J. Axmacher N. The role of phase synchronization in memory processes.Nat. Rev. Neurosci. 2011; 12: 105-118Crossref PubMed Scopus (1004) Google Scholar, 2Buzsaki G. Neural syntax: cell assemblies, synapsembles, and readers.Neuron. 2010; 68: 362-385Abstract Full Text Full Text PDF PubMed Scopus (747) Google Scholar]. However, mathematical information theory, alongside physiological studies in animals, postulates that high synchrony, especially in the lower-frequency ranges (<20 Hz), reduces information coding [4Hanslmayr S. et al.Oscillatory power decreases and long-term memory: the information via desynchronization hypothesis.Front. Hum. Neurosci. 2012; 6: 74Crossref PubMed Scopus (108) Google Scholar, 5Schneidman E. et al.Synergy from silence in a combinatorial neural code.J. Neurosci. 2011; 31: 15732-15741Crossref PubMed Scopus (46) Google Scholar, 6Mitchell J.F. et al.Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4.Neuron. 2009; 63: 879-888Abstract Full Text Full Text PDF PubMed Scopus (484) Google Scholar]. We here aim to integrate these two seemingly incompatible concepts and present a mechanistic framework to resolve this conundrum. Building on complementary learning systems [7O'Reilly R.C. et al.Complementary learning systems.Cogn. Sci. 2014; 38: 1229-1248Crossref PubMed Scopus (125) Google Scholar], we assume a division of labor between a hippocampal system, which mainly binds information, and a neocortical system, which mainly represents the content of this information. Based on recent findings, we argue that this division of labor is visible in the two opposing oscillatory behaviors, with the hippocampal system showing synchronization in the theta/gamma range [8Rutishauser U. et al.Human memory strength is predicted by theta-frequency phase-locking of single neurons.Nature. 2010; 464: 903-907Crossref PubMed Scopus (427) Google Scholar, 9Lisman J.E. Jensen O. The theta–gamma neural code.Neuron. 2013; 77: 1002-1016Abstract Full Text Full Text PDF PubMed Scopus (855) Google Scholar, 10Rey H.G. et al.Timing of single-neuron and local field potential responses in the human medial temporal lobe.Curr. Biol. 2014; 24: 299-304Abstract Full Text Full Text PDF PubMed Scopus (42) Google Scholar], mediating binding [11Staudigl T. Hanslmayr S. Theta oscillations at encoding mediate the context-dependent nature of human episodic memory.Curr. Biol. 2013; 23: 1101-1106Abstract Full Text Full Text PDF PubMed Scopus (148) Google Scholar], and the neocortex showing low-frequency desynchronization [4Hanslmayr S. et al.Oscillatory power decreases and long-term memory: the information via desynchronization hypothesis.Front. Hum. Neurosci. 2012; 6: 74Crossref PubMed Scopus (108) Google Scholar], mediating the representation of information [12Staudigl T. et al.Temporal-pattern similarity analysis reveals the beneficial and detrimental effects of context reinstatement on human memory.J. Neurosci. 2015; 35: 5373-5384Crossref PubMed Scopus (39) Google Scholar, 13Waldhauser G.T. et al.Alpha/beta oscillations indicate inhibition of interfering visual memories.J. Neurosci. 2012; 32: 1953-1961Crossref PubMed Scopus (101) Google Scholar]. The critical role of the hippocampus for intact episodic memory has been firmly established by neuropsychological studies , animal models, computational models , as well as human neuroimaging [14Eichenbaum H. et al.The medial temporal lobe and recognition memory.Annu. Rev. Neurosci. 2007; 30: 123-152Crossref PubMed Scopus (1846) Google Scholar]. Notably, hippocampal engagement seems particularly important for the key characteristic of episodic memories; that is, binding discontiguous (i.e., separate) event details into rich associative memory traces [15Staresina B.P. Davachi L. Mind the gap: binding experiences across space and time in the human hippocampus.Neuron. 2009; 63: 267-276Abstract Full Text Full Text PDF PubMed Scopus (199) Google Scholar]. How is this feat accomplished mechanistically? Gamma oscillations, operating at timescales below 30 ms, have recently been proposed as the prime candidate to facilitate learning-related synaptic changes such as spike-timing-dependent plasticity (STDP)/long-term potentiation (LTP) [1Fell J. Axmacher N. The role of phase synchronization in memory processes.Nat. Rev. Neurosci. 2011; 12: 105-118Crossref PubMed Scopus (1004) Google Scholar]. Does the hippocampus recruit such gamma oscillations in the service of episodic memory formation and retrieval? Direct hippocampal recordings from human epilepsy patients have found that gamma power increases correlate with both successful memory encoding [16Long N.M. et al.Subsequent memory effect in intracranial and scalp EEG.Neuroimage. 2014; 84: 488-494Crossref PubMed Scopus (91) Google Scholar] and retrieval [17Burke J.F. et al.Theta and high-frequency activity mark spontaneous recall of episodic memories.J. Neurosci. 2014; 34: 11355-11365Crossref PubMed Scopus (68) Google Scholar]. One caveat related to these results is that, on closer examination, the gamma effects were found to be part of more broadband power increases, ranging from 30 Hz to 100 Hz [18Burke J.F. et al.Human intracranial high-frequency activity during memory processing: neural oscillations or stochastic volatility?.Curr. Opin. Neurobiol. 2015; 31: 104-110Crossref PubMed Scopus (55) Google Scholar, 19Lega B.C. et al.Human hippocampal theta oscillations and the formation of episodic memories.Hippocampus. 2012; 22: 748-761Crossref PubMed Scopus (293) Google Scholar]. The functional significance of such broadband power increases remains under debate, but consensus has emerged that they reflect multi-unit spiking activity rather than true oscillatory activity ([20Ray S. Maunsell J.H. Do gamma oscillations play a role in cerebral cortex?.Trends Cogn. 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Perhaps even more compelling evidence for hippocampal gamma oscillations supporting episodic memory processes comes from studies examining short-range inter-regional synchronization, particularly between the hippocampus and the adjacent entorhinal cortex (EC). In human epilepsy patients, gamma-band coherence has been found to increase between these regions as a function of successful episodic encoding [24Fell J. et al.Human memory formation is accompanied by rhinal–hippocampal coupling and decoupling.Nat. Neurosci. 2001; 4: 1259-1264Crossref PubMed Scopus (571) Google Scholar] as well as retrieval [25Staresina B.P. et al.Memory signals are temporally dissociated in and across human hippocampus and perirhinal cortex.Nat. Neurosci. 2012; 15: 1167-1173Crossref PubMed Scopus (96) Google Scholar] (Figure 1B). Recordings from rodent models have gone further to identify a frequency-specific 'routing function' of gamma oscillations, such that the CA1 subregion is functionally coupled with CA3 versus the EC in different gamma sub-bands [26Colgin L.L. et al.Frequency of gamma oscillations routes flow of information in the hippocampus.Nature. 2009; 462: 353-357Crossref PubMed Scopus (893) Google Scholar]. Establishing the relevance of this coupling for learning processes, a recent study has linked the gamma-band coherence between CA1 and the EC to the encoding and retrieval of odor/space associations [27Igarashi K.M. et al.Coordination of entorhinal–hippocampal ensemble activity during associative learning.Nature. 2014; 510: 143-147Crossref PubMed Scopus (242) Google Scholar]. In summary, converging evidence has accumulated across different species and across different experimental paradigms for a critical role of synchronized hippocampal gamma oscillations in the service of episodic memory. The pressing question is then how these oscillations are themselves regulated. Ignited by the hallmark observation of theta phase precession of hippocampal place cells [28O'Keefe J. Recce M. L. Phase relationship between hippocampal place units and the EEG theta rhythm.Hippocampus. 1993; 3: 317-330Crossref PubMed Scopus (1780) Google Scholar], much research has been dedicated to understanding the role of the theta rhythm in orchestrating memory-related neural signals [29Hasselmo M.E. What is the function of hippocampal theta rhythm? Linking behavioral data to phasic properties of field potential and unit recording data.Hippocampus. 2005; 15: 936-949Crossref PubMed Scopus (333) Google Scholar]. A striking example is the finding – observed via direct recordings from the human hippocampus – that successful episodic encoding may not necessarily rely on the net increase in hippocampal firing rates but on the temporal precision of single-unit firing with respect to the concurrent theta phase [8Rutishauser U. et al.Human memory strength is predicted by theta-frequency phase-locking of single neurons.Nature. 2010; 464: 903-907Crossref PubMed Scopus (427) Google Scholar]. Importantly, recent research has begun to investigate not only how the theta rhythm may clock single-unit firing but also how oscillatory patterns in the gamma range may be related to the ongoing theta phase [9Lisman J.E. Jensen O. The theta–gamma neural code.Neuron. 2013; 77: 1002-1016Abstract Full Text Full Text PDF PubMed Scopus (855) Google Scholar]. For instance, the abovementioned coupling between CA1 and CA3 versus the EC was not only expressed in different gamma sub-bands but also occurred at different phases of the theta cycle [26Colgin L.L. et al.Frequency of gamma oscillations routes flow of information in the hippocampus.Nature. 2009; 462: 353-357Crossref PubMed Scopus (893) Google Scholar]. Moreover (and notwithstanding the abovementioned question of whether gamma power increases reflect true oscillatory changes versus multi-unit spiking), evidence has accumulated in both rodent models and human intracranial recordings that hippocampal theta–gamma coupling is linked to successful episodic memory processes [30Lega B. et al.Slow-theta-to-gamma phase–amplitude coupling in human hippocampus supports the formation of new episodic memories.Cereb. Cortex. 2014; (Published online October 14, 2014)https://doi.org/10.1093/cercor/bhu232Crossref Scopus (111) Google Scholar]. Of particular importance is a recent magnetoencephalography (MEG) study that showed that item–context binding, a hallmark of episodic memory, critically depends on theta–gamma coupling in the medial temporal lobe (MTL), and specifically on whether gamma oscillations are coupled to the peak or the trough of a theta cycle (Figure 1A) [11Staudigl T. Hanslmayr S. Theta oscillations at encoding mediate the context-dependent nature of human episodic memory.Curr. Biol. 2013; 23: 1101-1106Abstract Full Text Full Text PDF PubMed Scopus (148) Google Scholar, 30Lega B. et al.Slow-theta-to-gamma phase–amplitude coupling in human hippocampus supports the formation of new episodic memories.Cereb. Cortex. 2014; (Published online October 14, 2014)https://doi.org/10.1093/cercor/bhu232Crossref Scopus (111) Google Scholar, 31Tort A.B. et al.Theta–gamma coupling increases during the learning of item–context associations.Proc. Natl. Acad. Sci. 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Taking these findings together, the mnemonic functions of the hippocampus appear to be intimately linked to neuronal synchronization in the gamma frequency band, with a regulatory influence of the phase of ongoing theta oscillations (Figure 1A,B). Oscillatory power decreases during the formation of memories (i.e., encoding) are typically observed in the lower-frequency ranges (<20 Hz), especially during encoding of items that are later remembered compared with later not remembered [34Noh E. et al.Using single-trial EEG to predict and analyze subsequent memory.Neuroimage. 2014; 84: 712-723Crossref PubMed Scopus (56) Google Scholar, 16Long N.M. et al.Subsequent memory effect in intracranial and scalp EEG.Neuroimage. 2014; 84: 488-494Crossref PubMed Scopus (91) Google Scholar, 35Burke J.F. et al.Human intracranial high-frequency activity maps episodic memory formation in space and time.Neuroimage. 2014; 85: 834-843Crossref PubMed Scopus (81) Google Scholar, 36Fellner M.C. et al.Brain oscillatory subsequent memory effects differ in power and long-range synchronization between semantic and survival processing.Neuroimage. 2013; 79: 361-370Crossref PubMed Scopus (55) Google Scholar, 37Hanslmayr S. et al.The relationship between brain oscillations and BOLD signal during memory formation: a combined EEG–fMRI Study.J. Neurosci. 2011; 31: 15674-15680Crossref PubMed Scopus (121) Google Scholar]. For instance, during encoding of verbal material, alpha/beta power decreases (∼12–18 Hz) are most evident in the left inferior prefrontal cortex [16Long N.M. et al.Subsequent memory effect in intracranial and scalp EEG.Neuroimage. 2014; 84: 488-494Crossref PubMed Scopus (91) Google Scholar, 37Hanslmayr S. et al.The relationship between brain oscillations and BOLD signal during memory formation: a combined EEG–fMRI Study.J. Neurosci. 2011; 31: 15674-15680Crossref PubMed Scopus (121) Google Scholar, 38Meeuwissen E.B. et al.Evidence for human fronto-central gamma activity during long-term memory encoding of word sequences.PLoS ONE. 2011; 6: e21356Crossref PubMed Scopus (28) Google Scholar]. Importantly, such left frontal beta power decreases are not a simple (incidental) byproduct of memory formation but are causally relevant, as demonstrated in a recent combined electroencephalography (EEG)–rhythmic transcranial magnetic stimulation (rTMS) study [39Hanslmayr S. et al.Entrainment of prefrontal beta oscillations induces an endogenous echo and impairs memory formation.Curr. Biol. 2014; 24: 904-909Abstract Full Text Full Text PDF PubMed Scopus (121) Google Scholar] (Figure 1C). Given that the left inferior prefrontal cortex is strongly involved in semantic processing in general, these results fit with several findings in the language domain showing that left prefrontal beta power decreases during semantic processing [40Kielar A. et al.Localization of electrophysiological responses to semantic and syntactic anomalies in language comprehension with MEG.Neuroimage. 2015; 105: 507-524Crossref PubMed Scopus (38) Google Scholar, 41Singh K.D. Which "neural activity" do you mean? fMRI MEG, oscillations and neurotransmitters.Neuroimage. 2012; 62: 1121-1130Crossref PubMed Scopus (91) Google Scholar]. Memory formation for nonverbal material (i.e., images) is also accompanied by power decreases; however, these decreases apparently occur more in the alpha range at parieto-occipital regions [34Noh E. et al.Using single-trial EEG to predict and analyze subsequent memory.Neuroimage. 2014; 84: 712-723Crossref PubMed Scopus (56) Google Scholar]. Clearly, more studies are needed to investigate alpha/beta power decreases during memory formation of different materials (including words, images, and sounds), but the pattern of results so far suggests that alpha/beta desynchronization indexes information processing in specialized cortical modules during the perception of an event [42Jensen O. Mazaheri A. Shaping functional architecture by oscillatory alpha activity: gating by inhibition.Front. Hum. Neurosci. 2010; 4: 186Crossref PubMed Scopus (1669) Google Scholar, 43Klimesch W. Alpha-band oscillations, attention, and controlled access to stored information.Trends Cogn. Sci. 2012; 16: 606-617Abstract Full Text Full Text PDF PubMed Scopus (1588) Google Scholar] and therefore predict its likelihood of being later remembered. Of note, this negative relationship between power decreases and memory formation might also extend to the theta frequency range, as indexed by several recent studies showing that theta power decreases correlate with memory formation [16Long N.M. et al.Subsequent memory effect in intracranial and scalp EEG.Neuroimage. 2014; 84: 488-494Crossref PubMed Scopus (91) Google Scholar, 44Greenberg J.A. et al.Decreases in theta and increases in high frequency activity underlie associative memory encoding.Neuroimage. 2015; 114: 257-263Crossref PubMed Scopus (66) Google Scholar]. A similar picture arises for power decreases during memory retrieval. For instance, the topography of alpha/beta power decreases varies with the type of retrieved material (i.e., words versus faces [45Burgess A.P. Gruzelier J.H. Short duration power changes in the EEG during recognition memory for words and faces.Psychophysiology. 2000; 37: 596-606Crossref PubMed Google Scholar] or locations versus objects [46Khader P.H. Rosler F. EEG power changes reflect distinct mechanisms during long-term memory retrieval.Psychophysiology. 2011; 48: 362-369Crossref PubMed Scopus (59) Google Scholar]), suggesting that power decreases indicate material-specific memory reactivation. Direct support for this comes from studies that presented objects during encoding to either the left or right visual hemifield and showed that memory retrieval of centrally presented objects is indeed reflected by alpha/beta power decreases contralateral to the site at which the item was encoded [13Waldhauser G.T. et al.Alpha/beta oscillations indicate inhibition of interfering visual memories.J. Neurosci. 2012; 32: 1953-1961Crossref PubMed Scopus (101) Google Scholar, 47Waldhauser G.T. et al.Episodic memory retrieval functionally relies on very rapid reactivation of sensory information.J. Neurosci. 2016; (Published online November 23, 2015)https://doi.org/10.1523/JNEUROSCI.2101-15.2016Crossref PubMed Scopus (69) Google Scholar] (Figure 1D). Using multivariate pattern analysis of time–frequency data, two MEG/intracranial EEG (iEEG) studies went one step further and demonstrated that the content of reactivated material can be reliably decoded from alpha/beta frequencies [12Staudigl T. et al.Temporal-pattern similarity analysis reveals the beneficial and detrimental effects of context reinstatement on human memory.J. Neurosci. 2015; 35: 5373-5384Crossref PubMed Scopus (39) Google Scholar, 48Jafarpour A. et al.Replay of very early encoding representations during recollection.J. Neurosci. 2014; 34: 242-248Crossref PubMed Scopus (62) Google Scholar]. For instance, applying a temporal-pattern-analysis approach, Staudigl et al. [12Staudigl T. et al.Temporal-pattern similarity analysis reveals the beneficial and detrimental effects of context reinstatement on human memory.J. Neurosci. 2015; 35: 5373-5384Crossref PubMed Scopus (39) Google Scholar] demonstrated that the reactivation of individual dynamic contexts (i.e., movie clips) can be decoded from the temporal pattern of beta phase in material-specific cortical areas (i.e., parahippocampal area, visual cortex; [12Staudigl T. et al.Temporal-pattern similarity analysis reveals the beneficial and detrimental effects of context reinstatement on human memory.J. Neurosci. 2015; 35: 5373-5384Crossref PubMed Scopus (39) Google Scholar]). Together, these results offer an interesting possibility for the mechanistic role of low-frequency power decreases: decreases in oscillatory activity enable a neural assembly to express a stimulus-specific code by allowing a more complex (i.e., information-rich) temporal phase trajectory. Arguably, such a coding mechanism would not work very efficiently in situations of high synchrony (i.e., a stationary signal), where large populations of neurons are entrained to the same rhythm [4Hanslmayr S. et al.Oscillatory power decreases and long-term memory: the information via desynchronization hypothesis.Front. Hum. Neurosci. 2012; 6: 74Crossref PubMed Scopus (108) Google Scholar]. Taking these findings together, we postulate that low-frequency power decreases reflect the active engagement of cortical modules during encoding and retrieval of memories. An open question is what a low-frequency power decrease means mechanistically (i.e., at the neural level) and how it relates to the theta/gamma dynamics in the hippocampal system. Although more research is needed to answer this complex question, a convergent picture can be derived from three different recent frameworks. (i) Following the alpha inhibition framework, low-frequency power decreases could act as a gating mechanism whereby decreasing alpha power increases firing rates [42Jensen O. Mazaheri A. Shaping functional architecture by oscillatory alpha activity: gating by inhibition.Front. Hum. Neurosci. 2010; 4: 186Crossref PubMed Scopus (1669) Google Scholar, 43Klimesch W. Alpha-band oscillations, attention, and controlled access to stored information.Trends Cogn. Sci. 2012; 16: 606-617Abstract Full Text Full Text PDF PubMed Scopus (1588) Google Scholar]. Notably, this negative relationship between oscillatory activity and neural firing might also extend to higher (beta) and lower (theta) frequencies [9Lisman J.E. Jensen O. The theta–gamma neural code.Neuron. 2013; 77: 1002-1016Abstract Full Text Full Text PDF PubMed Scopus (855) Google Scholar]. (ii) A second line of research suggests that synchronized firing in low frequencies is a main contributor to the trial-by-trial variance in neural firing (termed 'noise correlations'), thereby reducing the reliability with which a neural code is expressed in a population of neurons [6Mitchell J.F. et al.Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4.Neuron. 2009; 63: 879-888Abstract Full Text Full Text PDF PubMed Scopus (484) Google Scholar, 49Cohen M.R. Kohn A. Measuring and interpreting neuronal correlations.Nat. Neurosci. 2011; 14: 811-819Crossref PubMed Scopus (618) Google Scholar]. Decreasing the amplitude of these low-frequency oscillations would reduce such neural noise correlations and thus increase the reliability of a neural code that is conveyed to downstream neurons (i.e., in the hippocampus). (iii) Finally, power decreases themselves could be a mechanism to de-correlate neural activity to enhance the neural coding capacity per se. Power decreases might thereby allow flexible phase adjustments in a neural population to form a temporal code representing the identity of a specific stimulus [4Hanslmayr S. et al.Oscillatory power decreases and long-term memory: the information via desynchronization hypothesis.Front. Hum. Neurosci. 2012; 6: 74Crossref PubMed Scopus (108) Google Scholar, 12Staudigl T. et al.Temporal-pattern similarity analysis reveals the beneficial and detrimental effects of context reinstatement on human memory.J. Neurosci. 2015; 35: 5373-5384Crossref PubMed Scopus (39) Google Scholar, 50Ng B.S. et al.EEG phase patterns reflect the selectivity of neural firing.Cereb. Cortex. 2013; 23: 389-398Crossref PubMed Scopus (105) Google Scholar]. The common notion between all of these different frameworks, however, is that power decreases enable a neural assembly to express a neural code in some form; that is, via an increase in firing rate, a reduction in noise, or phase encoding. Any such code would be meaningless if it were not interpreted by a 'reader' [2Buzsaki G. Neural syntax: cell assemblies, synapsembles, and readers.Neuron. 2010; 68: 362-385Abstract Full Text Full Text PDF PubMed Scopus (747) Google Scholar]. Here we assume that this reader is the hippocampus (Figure 2). The Complementary Learning Systems (CLS) theory has championed the position that the neocortex and hippocampus provide different but complementary representational formats, with the neocortex supporting a rich integrated representation learned over many experiences and the hippocampus providing a sparse representation learned in 'one shot' (or at least few shots). The theory also proposes that the hippocampus, sitting at the end of the processing pathway, provides online learning of conjunctive representations, which bind the constituent elements of an episodic memory. This is implemented by strengthening the synapses between contributing neurons through LTP. We argue that the CLS theory provides a framework within which the disparity in synchrony of oscillations between cortex and hippocampus can be reconciled. Stated explicitly, we propose that the complementarity of component subsystems is reflected in the disparity of oscillatory dynamics that these subsystems exhibit. Our proposal is most clearly understood by considering the sequence of steps that we envisage realize encoding of episodic memories (illustrated in Figure 2). (i) Sensory stimulation (e.g., seeing a person in a particular place) induces a reduction in alpha/beta oscillations to allow neocortical units to encode the content of that stimulation [42Jensen O. Mazaheri A. Shaping functional architecture by oscill