Theta–gamma cross-frequency coupling relates to the level of human intelligence

Dynamic network interactions among distinct brain rhythms as a hallmark of physiologic state and function

“…A number of studies on brain dynamics at the microscopic level have focused on local field potentials [36][37][38][39][40] and related interactions between neuronal oscillations 41 often with emphasis on modeling approaches. At the macroscopic integrated system level, studies have traditionally considered coherence of the same cortical rhythm across brain areas 42 with limited investigations on synchronous occurrence of specific pairs of cortical rhythms 26,[43][44][45][46][47] , mainly in the context of memory and cognition [48][49][50] . We present a systematic empirical study of network interactions among all physiologically relevant cortical rhythms, and discover distinct classes of coupling forms that coexist during a given physiologic state and reorganize with transitions across physiologic states.…”

From neural oscillations to reasoning ability: Simulating the effect of the theta-to-gamma cycle length ratio on individual scores in a figural analogy test

“…They suggested that WM capacity is dependent on the number of asynchronous gamma cycles (evoked by a global inhibitory signal) that can be fitted into one theta cycle. This prediction was recently confirmed by Kamiń ski, Brzezicka, and Wróbel (2011), who demonstrated that the number of items stored within the well-known Sternberg task that requires matching the target to n items preceding it, positively correlated with the theta-to-gamma cycle length ratio (for a less direct evidence see also Axmacher, Henseler, Jensen, Weinreich, Elger, & Fell, 2010;Pahor & Jaušovec, 2014). However, Lisman and Idiart's model does not explain why a particular capacity limit arises, because the particular theta-to-gamma ratio has been arbitrarily set in the model in order to fit a limit of 7 ± 2 items, and it does not result from any intrinsic properties of the model (i.e., given different parameters, the model could yield a much larger capacity limit).…”

“…There is still not enough empirical data on the relationships between the theta-to-gamma ratio and WM capacity, and it will be even more difficult to confirm predictions that more effective reasoning results from more gamma peaks in one theta cycle (for the first attempt in that direction, though barely conclusive, see Pahor & Jaušovec, 2014), as it was to validate the respective predictions of WM models (Kamiń ski et al, 2011). Reasoning processes occur in larger time scales (minutes) than WM processes (seconds or even milliseconds), so recordings of gamma and theta cycles throughout the reasoning task will likely confound situations when an increased theta-to-gamma ratio is really needed (e.g., in mapping, in which many objects have to be mutually related simultaneously), with cases in which a decreased ratio may facilitate performance (e.g., when one goal must be focused on, or some distraction needs to be prevented).…”

Linking flexibility of brain networks to cognitive development in preschool children

“…Further, here we focused on the neuronal oscillations belonging to classical frequency bands and assumed that the functional network associated with each band to be separated. However, these oscillations are not necessarily independent, instead fast and slow oscillations do interact with each other, enabling a flexible communication and an efficient information transfer between distant brain regions Bonnefond et al (2017); recent empirical evidence do provide correlated evidence of cross-frequency coupling as a neural measure of intelligence in adults Gągol et al (2018); Pahor and Jaušovec (2014), and future research should look at the inter-network coupling between interacting neuronal oscillations in children. Further, our MEG data were recorded when the children were watching cartoon of their own choice.…”