Synchronous, rhythmic changes in the membrane polarization of neurons form oscillations in local field potentials. It is hypothesized that high-frequency brain oscillations reflect local cortical information processing, and low-frequency brain oscillations project information flow across larger cortical networks. This provides complex forms of information transmission due to interactions between oscillations at different frequency bands, which can be rendered with cross-frequency coupling (CFC) metrics. Phase-amplitude coupling (PAC) is one of the most common representations of the CFC. PAC reflects the coupling of the phase of oscillations in a specific frequency band to the amplitude of oscillations in another frequency band. In a normal brain, PAC accompanies multi-item working memory in the hippocampus, and changes in PAC have been associated with diseases such as schizophrenia, obsessive-compulsive disorder (OCD), Alzheimer disease (AD), epilepsy, and Parkinson’s disease (PD). The purpose of this article is to explore CFC across the central nervous system and demonstrate its correlation to neurological disorders. Results from previously published studies are reviewed to explore the significant role of CFC in large neuronal network communication and its abnormal behavior in neurological disease. Specifically, the association of effective treatment in PD such as dopaminergic medication and deep brain stimulation with PAC changes is described. Lastly, CFC analysis of the electrocorticographic (ECoG) signals recorded from the motor cortex of a Parkinson’s disease patient and the parahippocampal gyrus of an epilepsy patient are demonstrated. This information taken together illuminates possible roles of CFC in the nervous system and its potential as a therapeutic target in disease states. This will require new neural interface technologies such as phase-dependent stimulation triggered by PAC changes, for the accurate recording, monitoring, and modulation of the CFC signal.
Dopamine transporter (DAT) SPECT imaging is increasingly utilized for diagnostic purposes in suspected Parkinsonian syndromes. We performed a cross-sectional study to investigate whether assessment of texture in DAT SPECT radiotracer uptake enables enhanced correlations with severity of motor and cognitive symptoms in Parkinson's disease (PD), with the long-term goal of enabling clinical utility of DAT SPECT imaging, beyond standard diagnostic tasks, to tracking of progression in PD. Quantitative analysis in routine DAT SPECT imaging, if performed at all, has been restricted to assessment of mean regional uptake. We applied a framework wherein textural features were extracted from the images. Notably, the framework did not require registration to a common template, and worked in the subject-native space. Image analysis included registration of SPECT images onto corresponding MRI images, automatic region-of-interest (ROI) extraction on the MRI images, followed by computation of Haralick texture features. We analyzed 141 subjects from the Parkinson's Progressive Marker Initiative (PPMI) database, including 85 PD and 56 healthy controls (HC) (baseline scans with accompanying 3 T MRI images). We performed univariate and multivariate regression analyses between the quantitative metrics and different clinical measures, namely (i) the UPDRS (part III - motor) score, disease duration as measured from (ii) time of diagnosis (DD-diag.) and (iii) time of appearance of symptoms (DD-sympt.), as well as (iv) the Montreal Cognitive Assessment (MoCA) score. For conventional mean uptake analysis in the putamen, we showed significant correlations with clinical measures only when both HC and PD were included (Pearson correlation r = − 0.74, p-value < 0.001). However, this was not significant when applied to PD subjects only (r = − 0.19, p-value = 0.084), and no such correlations were observed in the caudate. By contrast, for the PD subjects, significant correlations were observed in the caudate when including texture metrics, with (i) UPDRS (p-values < 0.01), (ii) DD-diag. (p-values < 0.001), (iii) DD-sympt (p-values < 0.05), and (iv) MoCA (p-values < 0.01), while no correlations were observed for conventional analysis (p-values = 0.94, 0.34, 0.88 and 0.96, respectively). Our results demonstrated the ability to capture valuable information using advanced texture metrics from striatal DAT SPECT, enabling significant correlations of striatal DAT binding with clinical, motor and cognitive outcomes, and suggesting that textural features hold potential as biomarkers of PD severity and progression.
We have two arms, many muscles in each arm, and numerous neurons that contribute to their control. How does the brain assign responsibility to each of these potential actors? We considered a bimanual task in which people chose how much force to produce with each arm so that the sum would equal a target. We found that the dominant arm made a greater contribution, but only for specific directions. This was not because the dominant arm was stronger. Rather, it was less noisy. A cost that included unimanual noise and strength accounted for both direction-and handedness-dependent choices that young people made. To test whether there was a causal relationship between unimanual noise and bimanual control, we considered elderly people, whose unimanual noise is comparable in the two arms. We found that, in bimanual control, the elderly showed no preference for their dominant arm. We noninvasively stimulated the motor cortex to produce a change in unimanual strength and noise, and found a corresponding change in bimanual control. Using the noise measurements, we built a neuronal model. The model explained the anisotropic distribution of preferred directions of neurons in the monkey motor cortex and predicted that, in humans, there are changes in the number of these cortical neurons with handedness and aging. Therefore, we found that coordination can be explained by the noise and strength of each effector, where noise may be a reflection of the number of task-related neurons available for control of that effector in the motor cortex.
In Parkinson's disease (PD), the human brain is capable of producing motor commands, but appears to require greater than normal subjective effort, particularly for the more-affected side. What is the nature of this subjective effort and can it be altered? We used an isometric task in which patients produced a goal force by engaging both arms, but were free to assign any fraction of that force to each arm. The patients preferred their less-affected arm, but only in some directions. This preference was correlated with lateralization of signaldependent noise: the direction of force for which the brain was less willing to assign effort to an arm was generally the direction for which that arm exhibited greater noise. Therefore, the direction-dependent noise in each arm acted as an implicit cost that discouraged use of that arm. To check for a causal relationship between noise and motor cost, we used bilateral transcranial direct current stimulation of the motor cortex, placing the cathode on the more-affected side and the anode on the less-affected side. This stimulation not only reduced the noise on the more-affected arm, it also increased the willingness of the patients to assign force to that arm. In a 3 d double-blind study and in a 10 d repeated stimulation study, bilateral stimulation of the two motor cortices with cathode on the more-affected side reduced noise and increased the willingness of the patients to exert effort. This stimulation also improved the clinical motor symptoms of the disease.
Background: Phase-amplitude coupling (PAC) in which the amplitude of a faster field potential oscillation is coupled to the phase of a slower rhythm, is one of the most well-studied interactions between oscillations at different frequency bands. In a healthy brain, PAC accompanies cognitive functions such as learning and memory, and changes in PAC have been associated with neurological diseases including Parkinson's disease (PD), schizophrenia, obsessive-compulsive disorder, Alzheimer's disease, and epilepsy. Objective: /Hypothesis: In PD, normalization of PAC in the motor cortex has been reported in the context of effective treatments such as dopamine replacement therapy and deep brain stimulation (DBS), but the possibility of normalizing PAC through intervention at the cortex has not been shown in humans. Phasetargeted stimulation (PDS) has a strong potential to modulate PAC levels and potentially normalize it. Methods: We applied stimulation pulses triggered by specific phases of the beta oscillations, the low frequency oscillations that define phase of gamma amplitude in beta-gamma PAC, to the motor cortex of seven PD patients at rest during DBS lead placement surgery We measured the effect on PAC modulation in the motor cortex relative to stimulation-free periods. Results: We describe a system for phase-targeted stimulation locked to specific phases of a continuously updated slow local field potential oscillation (in this case, beta band oscillations) prediction. Stimulation locked to the phase of the peak of beta oscillations increased beta-gamma coupling both during and after stimulation in the motor cortex, and the opposite phase (trough) stimulation reduced the magnitude of coupling after stimulation. Conclusion: These results demonstrate the capacity of cortical phase-targeted stimulation to modulate PAC without evoking motor activation, which could allow applications in the treatment of neurological disorders associated with abnormal PAC, such as PD.
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