Resonant hierarchies: a multiscale framework for oscillatory dynamics in the brain

Area of Science:

• Neuroscience
• Computational Neuroscience

Background:

• Neural oscillations are fundamental to brain function but their origins and roles are not fully understood.
• Previous research has cautioned against viewing brain rhythms, such as alpha-band activity, as uniform phenomena, emphasizing the need for anatomical and functional context.
• Existing multiscale models often focus on microcircuits or network eigenmodes, lacking a unified cross-scale perspective.

Purpose of the Study:

• To provide a comprehensive review of progress in understanding neural oscillations.
• To introduce the 'resonant hierarchy' framework, integrating cellular and network-level mechanisms.
• To reposition brain rhythms as fundamental scaffolds for neural computation.

Main Methods:

• Review of existing literature on neural oscillations and brain rhythms.
• Development of the 'resonant hierarchy' framework.
• Integration of dendritic resonance, laminar organization, and conduction delays into a unified model.

Main Results:

• Dendritic branches function as frequency-selective filters at the cellular level.
• Conduction delays and anatomical structure constrain communication frequencies at larger scales.
• Canonical brain rhythms (alpha, beta, gamma) are proposed as emergent descriptors of coordination regimes within the resonant hierarchy.

Conclusions:

• The resonant hierarchy framework links cellular properties (dendritic resonance) with network dynamics (conduction delays, anatomical layout).
• This perspective generates testable predictions regarding the effects of manipulating dendritic resonance and conduction pathways.
• The framework offers a principled basis for future research in modeling, measuring, and intervening in neural oscillations.