Abstract
High Frequency Oscillations Are Associated with Cognitive Processing in Human Recognition Memory
Kucewicz MT, Cimbalnik J, Matsumoto JY, Brinkmann BH, Bower MR, Vasoli V, Sulc V, Meyer F, Marsh WR, Stead SM, Worrell GA. Brain 2014;137:2231–2244.
High frequency oscillations are associated with normal brain function, but also increasingly recognized as potential biomarkers of the epileptogenic brain. Their role in human cognition has been predominantly studied in classical gamma frequencies (30–100 Hz), which reflect neuronal network coordination involved in attention, learning and memory. Invasive brain recordings in animals and humans demonstrate that physiological oscillations extend beyond the gamma frequency range, but their function in human cognitive processing has not been fully elucidated. Here we investigate high frequency oscillations spanning the high gamma (50–125 Hz), ripple (125–250 Hz) and fast ripple (250–500 Hz) frequency bands using intracranial recordings from 12 patients (five males and seven females, age 21–63 years) during memory encoding and recall of a series of affectively charged images. Presentation of the images induced high frequency oscillations in all three studied bands within the primary visual, limbic and higher order cortical regions in a sequence consistent with the visual processing stream. These induced oscillations were detected on individual electrodes localized in the amygdala, hippocampus and specific neocortical areas, revealing discrete oscillations of characteristic frequency, duration and latency from image presentation. Memory encoding and recall significantly modulated the number of induced high gamma, ripple and fast ripple detections in the studied structures, which was greater in the primary sensory areas during the encoding (Wilcoxon rank sum test, P = 0.002) and in the higher-order cortical association areas during the recall (Wilcoxon rank sum test, P = 0.001) of memorized images. Furthermore, the induced high gamma, ripple and fast ripple responses discriminated the encoded and the affectively charged images. In summary, our results show that high frequency oscillations, spanning a wide range of frequencies, are associated with memory processing and generated along distributed cortical and limbic brain regions. These findings support an important role for fast network synchronization in human cognition and extend our understanding of normal physiological brain activity during memory processing.
Commentary
High frequency oscillations (HFOs) have garnered considerable attention in epilepsy research over the past 15 years. Originally discovered within normal brain tissue (1), HFOs are brief (<100 ms), low amplitude discharges composed of frequencies above the gamma range (>60 Hz). The role of HFOs in normal cognitive processing is still an active area of research, as they represent higher order cortical processing and are seen throughout the brain. Later work has demonstrated that HFOs are increased in epileptic tissue (2), and over the ensuing years considerable evidence has shown that HFOs are a potential biomarker of epilepsy (3). Thus, HFOs paradoxically appear to be markers of both normal and epileptic brain processes, which has been one of the primary barriers to using them in epilepsy care. Most prior research has been unable to distinguish normal from epileptic HFOs, which confounds the analysis considerably: there is no known reliable method to ascertain which HFOs are uniquely associated with epilepsy. In this work, Kucewicz et al. took the opposite approach and instead developed a method to identify HFOs that are associated with cortical visual processing—in other words, they found a way to isolate the normal HFOs. While their results provide important insights into the role of HFOs in normal cognition, the method itself is a major breakthrough, as it is capable of accurately identifying normal HFOs within a patient that has both normal and epileptic EEG waveforms.
After decades of recordings limited to gamma and theta rhythms, HFOs are a relatively new entity, and there is hope that they may provide novel insights into brain physiology. Part of their intriguing novelty is that they exist on a smaller spatiotemporal scale than traditional EEG recordings, demonstrating the brief activity of cortical columns and possibly of individual cells. For instance, in the hippocampus during memory consolidation, individual neuron firing during HFOs can follow a highly organized order related to the original memory (4). The physiological implications of this activity are still under investigation. Such experiments are very difficult to undertake in humans, as they require invasive high-resolution recordings. This typically requires recording from patients undergoing intracranial EEG monitoring for epilepsy, but by definition such patients are likely to have both normal and epileptic HFOs and the results can be confusing. For this reason, past research into normal HFOs in humans has been quite limited.
In humans, there are two main options to isolate normal HFOs: 1) perform experiments in patients without epilepsy, or 2) control that the recorded events are normal. The first option is rare but not impossible, as past work at the Mayo Clinic has included patients being monitored for intractable facial pain (5). The second option has been elusive for many years. While early studies suggested that HFOs over 250 Hz (“fast ripples”) were specific to epilepsy, many later articles have shown that fast ripples are seen in normal brain regions as well. Recently, the Mayo Clinic group pioneered a protocol in which normal HFOs can be identified by their temporal relationship to a sensory stimulus (6). They marked the time of the stimulus, observed for gamma activity that followed, and assumed that HFOs during that period were normal. They compared those induced events with HFOs arising spontaneously on epileptic spikes and found noticeable differences in the spectral power, peak frequency, and duration. These three features are, to date, the most accurate way to distinguish normal and epileptic HFOs.
In the current work, the same group (Kucewicz et al.) used that protocol to focus on the role of physiological HFOs in human cortical processing. Twelve patients undergoing intracranial epilepsy monitoring were presented visual images for both encoding and recall. In the encoding phase, they viewed a series of 80 pleasant and unpleasant pictures; then in the recall phase, they viewed 140 images and had to identify those that were repeats. As in the earlier article, the authors identified normal HFOs based upon the stereotyped latency from the stimulus. In this case, the study focused solely on normal cortical processing, so there was no comparison with any epileptic HFOs. They found that during cortical processing, the low frequency activity (gamma and below) decreases while the HFOs increase in specific brain regions. The HFOs behave as expected with cortical processing: they arise primarily in sensory regions (occipital and parietal) during coding stimuli; while during recall, they are more prominent in the association regions (frontal, temporal). HFOs arise in sequence from occipital to frontal regions, following the rational order of the visual stream. In addition, tasks requiring memory access produced increased HFOs in the hippocampus and amygdala, and specific patterns of HFOs were associated with similar types of images. This logical neuroanatomic and biophysical behavior provides strong evidence that the HFOs are indeed produced by normal cortical activity and are biomarkers of higher order cortical processing.
While the primary goal of this study was to explore the role of HFOs in normal processing, a secondary outcome has greater importance to epilepsy research. Because the visual processing stream is well understood, it is straightforward to compare the HFO results with expected physiology. Thus, by demonstrating that their detected events behave in the expected manner, the authors proved that they had correctly identified normal HFOs—effectively providing a physiological validation of their method. Although it is unclear how to compare these induced, “event-related” HFOs with spontaneous HFOs, they are clearly associated with normal activity and can form a new reference for HFO research. This dataset can now be used as a validated gold standard of normal HFOs in patients with epilepsy. Future work can make use of this dataset and methods to find more accurate approaches for distinguishing normal from abnormal HFOs.