Neural entrainment and network resonance in support of top-down guided attention

Abstract

Which neural mechanisms provide the functional basis of top-down guided cognitive control? Here, we review recent evidence that suggest that the neural basis of attention is inherently rhythmic. In particular, we discuss two physical properties of self-sustained networks, namely entrainment and resonance, and how these shape the timescale of attentional control. Several recent findings revealed theta-band (3-8 Hz) dynamics in top-down guided behavior. These reports were paralleled by intracranial recordings, which implicated theta oscillations in the organization of functional attention networks. We discuss how the intrinsic network architecture shapes covert attentional sampling as well as overt behavior. Taken together, we posit that theta rhythmicity is an inherent feature of the attention network in support of top-down guided goal-directed behavior.

Figure 1. Oscillatory entrainment and resonance

EEG oscillator model response (black; [29]) relative to external sensory input (red) and concomitant band-pass filtered version (grey). Note that all 5 subpanels were derived from the same underlying oscillator model. (A) Evoked responses to rhythmic stimuli when no neural oscillator is present. Note that band-pass filtering renders the signal sinusoidal despite the absence of an ongoing oscillation. For an in-depth discussion of the relationship of evoked responses and phase-alignment see [25,26]. (B) No external sensory stream is present, but events are predicted based on top-down priors. Predicted events can either occur (green solid line) or not (green dashed line). However, the build-up of the ramping neural activity (such as contingent negative variation EEG potential, CNV) and subsequent return to baseline might mimic phase entrainment after band-pass filtering a linearly trending signal [29] due to filter-ringing. (C) True entrainment: An ongoing oscillator is entrained by a rhythmic input at a slightly different frequency. The entrained oscillation becomes phase-locked and the amplitude increases. After the entraining stream stops the oscillator exhibits a reverberation at the driving frequency for several cycles. (D) Resonating response to a single stimulus might mimic reverberations of a true oscillator. Note that band-pass filtering even renders the pre-stimulus period sinusoidal due to the single evoked response. Hence, phase estimates at stimulus onset might appear to be biased. However, phase estimates, after the initial evoked response, accurately track the phase of the decaying response. (E) Superposition of resonating responses to multiple stimuli mimics entrainment signatures as well as for phase-reset phenomena. Phase estimates after the initial response reflects a good approximation of the underlying signal. Note that neither this scenario nor panel A capture true, cognitively driven, phase alignment but mimic oscillatory patterns in response to a sensory stimulus.

Figure 2. Theta mediates rhythmic top-down control

(A) Behavioral data from a target detection experiment where a 2×2 design (predictive vs. non-predictive and 10 Hz flicker vs. arrhythmic stimulation) was employed. Single subject behavioral time courses for predictive and non-predictive conditions filtered in the alpha-band. Note the rhythmic theta modulation (arrows) of the alpha envelope (red) in the predictive (left) but not the non-predictive (right) condition. (B) Left: Spectral analysis of behavioral hit rate time courses reveal elevated alpha power for non-predictive contexts (dashed lines). Note that alpha power is higher when the preceding stream was flickered at 10 Hz (green dashed lines). This increase was interpreted as evidence for alpha entrainment through the 10 Hz flicker. However, top-down guided processing (solid lines) exhibited markedly reduced alpha power, which was not modulated by the entraining stream (right panel), thus, indicating that top-down control alleviates effects of bottom-up sensory entrainment. (C) Simultaneous EEG recordings revealed distinct sources reflecting perception (posterior alpha) and cognitive content (frontal low theta). The graphs in A-C are reproduced from [10].

Figure 3. Theta rhythmicity in the fronto-parietal attention network

(A) Schematic of context-dependent network reconfigurations: Different network configurations might exhibit characteristic frequency-specific response when input into the system is provided (solid lines indicate observations; dashed lines indicate suspected network motifs). Responses often decay over time or are terminated by another network reconfiguration. (B) Single trial example of a intracranial electrode placed over parietal cortex: After a cue-evoked response, high frequency band activity, a surrogate for multi-unit spiking activity, fluctuated at a theta frequency. This rhythmicity was terminated after target presentation and subsequent overt response. (C) Topographical depiction of theta rhythmic sampling. Note parietal, frontal and motor areas contribute significantly to the behavioral rhythmic sampling. Lower right: Behavior-phase relationships are coherent in the fronto-parietal attention network and can be delineated from the sensorimotor network. The graphs in B-C are reproduced with permission from [36].