Phase–amplitude coupling (PAC) has been proposed as a neural mechanism for coordinating information processing across brain regions. Here we sought to characterize PAC in the human hippocampus, and in temporal and frontal cortices, during the formation of new episodic memories. Intracranial recordings taken as 56 neurosurgical patients studied and recalled lists of words revealed significant hippocampal PAC, with slow-theta activity (2.5–5 Hz) modulating gamma band activity (34–130 Hz). Furthermore, a significant number of hippocampal electrodes exhibited greater PAC during successful than unsuccessful encoding, with the gamma activity at these sites coupled to the trough of the slow-theta oscillation. These same conditions facilitate LTP in animal models, providing a possible mechanism of action for this effect in human memory. Uniquely in the hippocampus, phase preference during item encoding exhibited a biphasic pattern. Overall, our findings help translate between the patterns identified during basic memory tasks in animals and those present during complex human memory encoding. We discuss the unique properties of human hippocampal PAC and how our findings relate to influential theories of information processing based on theta–gamma interactions.
Development of oscillatory synchronization (MEG) predicts language abilities in children→
/Synchronization of oscillations among brain areas is understood to mediate network communication supporting cognition, perception, and language. How task-dependent synchronization during word production develops throughout childhood and adolescence, as well as how such network coherence is related to the development of language abilities, remains poorly understood. To address this, we recorded magnetoencephalography while 73 participants aged 4–18 years performed a verb generation task. Atlas-guided source reconstruction was performed, and phase synchronization among regions was calculated. Task-dependent increases in synchronization were observed in the theta, alpha, and beta frequency ranges, and network synchronization differences were observed between age groups. Task-dependent synchronization was strongest in the theta band, as were differences between age groups. Network topologies were calculated for brain regions associated with verb generation and were significantly associated with both age and language abilities. These findings establish the maturational trajectory of network synchronization underlying expressive language abilities throughout childhood and adolescence and provide the first evidence for an association between large-scale neurophysiological network synchronization and individual differences in the development of language abilities.
Neural cross-frequency coupling: Connecting architectures, mechanisms, and functions→
/Looks good.
Neural oscillations are ubiquitously observed in the mammalian brain, but it has proven difficult to tie oscillatory patterns to specific cognitive operations. Notably, the coupling between neural oscillations at different timescales has recently received much attention, both from experimentalists and theoreticians. We review the mechanisms underlying various forms of this cross-frequency coupling. We show that different types of neural oscillators and cross-frequency interactions yield distinct signatures in neural dynamics. Finally, we associate these mechanisms with several putative functions of cross-frequency coupling, including neural representations of multiple environmental items, communication over distant areas, internal clocking of neural processes, and modulation of neural processing based on temporal predictions.
Measuring directionality between neuronal oscillations of different frequencies→
/This measure is based on the phase-slope index (PSI) between the phase of slower oscillations and the power envelope of faster oscillations. Further, we propose a randomization framework for statistically evaluating the coupling measures when controlling for multiple comparisons over the investigated frequency ranges. The method was firstly validated on simulated data and next applied to resting state electrocorticography (ECoG) data. These results demonstrate that the method works reliably. In particular, we found that the power envelope of gamma oscillations drives the phase of slower oscillations in the alpha band.
