Distinct phase-amplitude couplings distinguish cognitive processes in human attention

Abstract Spatial attention is the cognitive function that coordinates the selection of visual stimuli with appropriate behavioral responses. Recent studies have reported that phase-amplitude coupling (PAC) of low and high frequencies covaries with spatial attention, but differ on the direction of covariation and the frequency ranges involved. We hypothesized that distinct phase-amplitude frequency pairs have differentiable contributions during tasks that manipulate spatial attention. We investigated this hypothesis with electrocorticography (ECoG) recordings from participants who engaged in a cued spatial attention task. To understand the contribution of PAC to spatial attention we classified cortical sites by their relationship to spatial variables or behavioral performance. Local neural activity in spatial sites was sensitive to spatial variables in the task, while local neural activity in behavioral sites correlated with reaction time. We found two PAC frequency clusters that covaried with different aspects of the task. During a period of cued attention, delta-phase/high-gamma (DH) PAC was sensitive to cue direction in spatial sites. In contrast, theta-alpha-phase/beta-low-gamma-amplitude (TABL) PAC robustly correlated with future reaction times in behavioral sites. Finally, we investigated the origins of TABL PAC and found it corresponded to behaviorally relevant, sharp waveforms, which were also coupled to a low frequency rhythm. We conclude that TABL and DH PAC correspond to distinct mechanisms during spatial attention tasks and that sharp waveforms are elements of a coupled dynamical process

Coupled Correlates of Attention and Consciousness

Introduction: Brain Computer Interfaces (BCIs) have been shown to restore lost motor function that occurs in stroke using electrophysiological signals. However, little evidence exists for the use of BCIs to restore non-motor stroke deficits, such as the attention deficits seen in hemineglect. Attention is a cognitive function that selects objects or ideas for further neural processing, presumably to facilitate optimal behavior. Developing BCIs for attention is different from developing motor BCIs because attention networks in the brain are more distributed and associative than motor networks. For example, hemineglect patients have reduced levels of arousal, which exacerbates their attentional deficits. More generally, attention is a state of high arousal and salient conscious experience. Current models of consciousness suggest that both slow wave sleep and Propofol-induced unconsciousness lie at one end of the consciousness spectrum, while attentive states lie at the other end. Accordingly, investigating the electrophysiology underlying attention and the extremes of consciousness will further the development of attentional BCIs. Phase amplitude coupling (PAC) of neural oscillations has been suggested as a mechanism for organizing local and global brain activity across regions. While evidence suggests that delta-high-gamma PAC, which includes very low frequencies (i.e. delta, 1-3 Hz) coupled with very high frequencies (i.e. gamma 70-150 Hz), is implicated in attention, less evidence exists for the involvement of coupled mid-range frequencies (i.e. theta, 4-7Hz, alpha: 8-15 Hz, beta: 15-30 Hz and low-gamma: 30-50 Hz, aka TABL PAC). We found that TABL PAC correlates with reaction time in an attention task. These mid-range frequencies are important because they can be used in non-invasive electroencephalography (EEG) BCI’s. Therefore, we investigated the origins of these mid-frequency interactions in both attention and consciousness. In this work, we evaluate the relationship between PAC to attention and arousal, with emphasis on developing control signals for an attentional BCI. Objective: To understand how PAC facilitates attention and arousal for building BCI’s that restore lost attentional function. More generally, our objective was to discover and understand potential control features for BCIs that enhance attention and conscious experience. Methods: We used four electrophysiological datasets in human subjects. The first dataset included six subjects with invasive ECoG recordings while subjects engaged in a Posner cued spatial attention task. The second dataset included five subjects with ECoG recordings during sleep and awake states. The third dataset included 6 subjects with invasively monitored ECoG during induction and emergence from Propofol anesthesia. We validated findings from the second dataset with an EEG dataset that included 39 subjects with EEG and sleep scoring. We developed custom, wavelet-based, signal processing algorithms designed to optimally calculate differences in mid-frequency-range (i.e. TABL) PAC and compare them to DH PAC across different attentional and conscious states. We developed non-parametric cluster-based permutation tests to infer statistical significance while minimizing the false-positive rate. In the attention experiment, we used the location of cued spatial stimuli and reaction time (RT) as markers of attention. We defined stimulus-related and behaviorally-related cortical sites and compared their relative PAC magnitudes. In the sleep dataset, we compared PAC across sleep states (e.g. Wake vs Slow Wave Sleep). In the anesthesia dataset, we compared the beginning and ending of induction and emergence (e.g. Wake vs Propofol Induced Loss of Consciousness) Results: We found different patterns of activity represented by TABL PAC and DH PAC in both attention and sleep datasets. First, during a spatial attention task TABL PAC robustly predicted whether a subject would respond quickly or slowly. TABL PAC maintained a consistent phase-preference across all cortical sites and was strongest in behaviorally-relevant cortical sites. In contrast, DH PAC represented the location of attention in spatially-relevant cortical sites. Furthermore, we discovered that sharp waves caused TABL PAC. These sharp waves appeared to be transient beta (50ms) waves that occurred at ~140 ms intervals, corresponding to a theta oscillation. In the arousal dataset DH PAC increased in both slow wave sleep (SWS) and Propofol-induced loss of consciousness (PILOC) states. However, TABL PAC increased only during PILOC and decreased during SWS, when compared to waking states. We provide evidence that TABL PAC represents “gating by inhibition” in the human brain. Conclusions: Our goal was to develop electrophysiological signals representing attention and to understand how these features explain the relationship between attention and low-arousal states. We found a novel biomarker, TABL PAC, that predicted non-spatial aspects of attention and discriminated between two states of unconsciousness. The evidence suggested that TABL PAC represents inhibitory activity that filters out irrelevant information in attention tasks. This inhibitory mechanism of was confirmed by significant increases in TABL PAC during Propofol anesthesia, when compared to SWS or waking brain activity. We conclude that TABL PAC informs the development of electrophysiological control signals for attention and the discrimination of unconscious states

Distinct phase-amplitude couplings distinguish cognitive processes in human attention.

Spatial attention is the cognitive function that coordinates the selection of visual stimuli with appropriate behavioral responses. Recent studies have reported that phase-amplitude coupling (PAC) of low and high frequencies covaries with spatial attention, but differ on the direction of covariation and the frequency ranges involved. We hypothesized that distinct phase-amplitude frequency pairs have differentiable contributions during tasks that manipulate spatial attention. We investigated this hypothesis with electrocorticography (ECoG) recordings from participants who engaged in a cued spatial attention task. To understand the contribution of PAC to spatial attention we classified cortical sites by their relationship to spatial variables or behavioral performance. Local neural activity in spatial sites was sensitive to spatial variables in the task, while local neural activity in behavioral sites correlated with reaction time. We found two PAC frequency clusters that covaried with different aspects of the task. During a period of cued attention, delta-phase/high-gamma (DH) PAC was sensitive to cue direction in spatial sites. In contrast, theta-alpha-phase/beta-low-gamma-amplitude (TABL) PAC robustly correlated with future reaction times in behavioral sites. Finally, we investigated the origins of TABL PAC and found it corresponded to behaviorally relevant, sharp waveforms, which were also coupled to a low frequency rhythm. We conclude that TABL and DH PAC correspond to distinct mechanisms during spatial attention tasks and that sharp waveforms are elements of a coupled dynamical process

ELECTROPHYSIOLOGICAL MECHANISMS FOR PREPARING CONTROL IN TIME

Cognitive control is critical in guiding goal-directed behavior, preparing neural resources and adapting processing to promote optimal action in a given environment. According to the Dual Mechanisms of Control theory (Braver, 2012), control can be dichotomized into proactive and reactive modes of control, utilized reciprocally in ahead-of-time preparation versus last-minute, stimulus-evoked reaction. Although a substantial body of work has tested differences between proactive control and reactive control, the underlying assumption of proactive control as a unitary process has not been systematically investigated. Very little is known as to how or when proactive control is initiated, sustained, or implemented. As time is an integral building block of perception, cognition, and action (Buhusi & Meck, 2005), one should expect temporal information to be integrated into proactive control. Cognitive control is costly (Shenhav, Botvinick, & Cohen, 2013), and a temporally-guided modulation of control may offer substantial cost savings. By measuring proactive control on a sub-second time-scale, we can begin to gauge whether dissociable sub-types of proactive control are utilized demanding on temporal demands. Moreover, by comparing proactive control processes across different temporal demands, we can parse out when different aspects of control are computed and implemented. Through a meta-analytic review and three empirical experiments, this dissertation provides insight into how timing dynamics may influence the computation, maintenance, and instantiation of proactive cognitive control. First, a meta-analysis on the cued control literature reveals that seemingly trivial experimental parameters shape the use of proactive versus reactive control. Two EEG studies then demonstrate how modulating timing dynamics influences prefrontal mechanisms for preparatory cognitive control. In a final EEG study, we compare the mechanisms utilized to retain control goals versus visuo-spatial working memory items. Overall, this dissertation elucidates several novel electrophysiological mechanisms by which timing information is implemented in the computation and retention of cognitive control rules. Further, we provide evidence that individual differences in impulsivity and working memory shape distinct aspects of preparation. The findings reported here make clear that timing information is critical in guiding proactive control processes, and support a fundamental reconsideration of proactive control based on temporal dynamics

Atypical Cortical Connectivity in Autism Spectrum Disorder (ASD) as Measured by Magnetoencephalography (MEG)

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition, characterised by impairments in social interaction and communication, the presence of repetitive behaviours, and multisensory hyper- and hypo-sensitives. This thesis utilised magnetoencephalography, in combination with robust analysis techniques, to investigate the neural basis of ASD. Based on previous research, it was hypothesised that cortical activity in ASD would be associated with disruptions to oscillatory synchronisation during sensory processing, as well as during high-level perspective-taking. More specifically, a novel framework was introduced, based on local gamma-band dysregulation, global hypoconnectivity and deficient predictive-coding. To test this framework, data were collected from adolescents diagnosed with ASD and age-matched controls. Using a visual grating stimulus, it was found that in primary visual cortex, ASD participants had reduced coupling between the phase of alpha oscillations and the amplitude of gamma oscillations (i.e. phase amplitude coupling), suggesting dysregulated visual gamma in ASD. These findings were based on a robust analysis pipeline outlined in Chapter 2. Next, directed connectivity in the visual system was quantified using Granger causality. Compared with controls, ASD participants showed reductions in feedback connectivity, mediated by alpha oscillations, but no differences in inter-regional feedforward connectivity, mediated by gamma oscillations. In the auditory domain, it was found that ASD participants had reduced steady-state responses at 40Hz, in terms of oscillatory power and inter-trial coherence, again suggesting dysregulated gamma. Investigating predictive-coding theories of ASD using an auditory oddball paradigm, it was found that evoked responses to the omission of an expected tone were reduced for ASD participants. Finally, we found reductions in theta-band oscillatory power and connectivity for ASD participants, during embodied perspective-taking. Overall, these findings fit the proposed framework, and demonstrate that cortical activity in ASD is characterised by disruptions to oscillatory synchronisation, at the local and global scales, during both sensory processing and higher-level perspective-taking