Deep brain stimulation increases motor cortical 1/f noise and decouples high gamma amplitude from beta phase Scott R. Cole, Erik J. Peterson, Coralie de Hemptinne, Philip A. Starr, Bradley Voytek Deep brain stimulation (DBS) of the subthalamic nucleus is a common and effective treatment for Parkinsonian motor signs, including bradykinesia and rigidity. Recently, it was discovered that Parkinson’s Disease patients show pathological overcoupling between the beta phase and high gamma amplitude in the primary motor cortex (M1). DBS-induced decoupling may underlie improvement of Parkinsonian motor signs. In frontal and temporal regions, phase-amplitude coupling decreases with age. Empirical findings and computational simulations support the hypothesis that this reduction in coupling is caused by decreased synchrony in population spike timing. This desynchronization is also associated with increased 1/f noise, manifested as a flattening of the slope of the power spectral density. We test the hypothesis that the neurophysiological mechanism of high-frequency DBS of the STN is the desynchronization of M1 spiking. This hypothesis predicts that the decrease in M1 coupling is the result of population spike desynchronization, and thus the DBS-induced reduction in coupling should be predicted by the DBS-induced increase in 1/f noise. Electrocorticography recordings were obtained over M1 in Parkinson’s Disease patients before and during DBS. We observed that DBS caused: 1) significant decreases in coupling; 2) significant flattening of the power spectrum, and most importantly; 3) a correlation between the magnitude of the changes in (1) and (2) such that increased 1/f noise predicts the drop in coupling. DBS-induced spiking desynchronization seems to decrease pathological overcoupling allowing M1 to respond more dynamically to signals from frontal executive areas.

Exploring the Neural Basis of the Electrophysiological Power Spectrum Richard Gao & Bradley Voytek The power spectrum of meso- and macro-scale brain electrical recordings in the forms of the local field potential (LFP), electrocorticogram (ECoG), and electroencephalogram (EEG) are often described to be following an inverse power law relationship, given by 𝑃 = 𝐴𝐹!!, where F is frequency, P is power, and A and 𝜒 are free parameters characterizing the power law. In the log-log domain, this relationship is represented by a linear trend with a negative slope of – 𝜒 and a y-intercept of 𝑙𝑜𝑔𝐴. This phenomenon has been well documented in empirical data, noting changes in A and 𝜒 during various perceptual and motor tasks. In addition, recent computational models using population-spiking neurons have attributed these parameters to different biological mechanisms. While the power law formulation of the spectrum has proven fruitful, two key observations are unsatisfactorily accounted for. First, there have been reports of an increase in strictly high gamma power (>60Hz), resulting in a curling of the spectrum, without changes in the slope or intercept. Second, rotations of the spectrum resulting from a change in slope are observed to be about a frequency of ~25Hz, instead of 1Hz, which would be the case if only a change in 𝜒 were to occur. Here, we argue that a strict inverse power law model is an incomplete description of the underlying processes giving rise to the power spectrum, and propose the addition of an additive term, i.e. 𝑃 = 𝐴𝐹!! + 𝐵. Furthermore, we postulate that B, a broadband signal akin to white noise, arises from de-correlated (Poissonic) population firing engaged in local computation. Using a Poisson population model, we demonstrate that an increased firing rate leads to both an increase in gamma power (high frequency curling) and a rotation of the spectrum about ~25Hz. In addition, we validate our model by demonstrating an improved fit of the power spectrum derived from human ECoG and rat LFP data. In summary, the new formulation has both explanatory powers over the data and a sound neurophysiological basis, improving our understanding of the power spectrum of electrophysiological data.

Influencing visual target detection with oscillatory phase-specific stimulus presentation Robert J. Gougelet, Thomas Donoghue, Matthew Piper, Alric Althoff, Thomas P. Urbach, Bradley Voytek We investigated the extent to which ongoing electroencephalography (EEG) neural oscillations emanating from fronto- parietal and occipital scalp regions in the theta (3-7 Hz) and alpha (8-12 Hz) frequency ranges contribute to the detection of visual stimuli in humans. We first observed how subject-specific alpha phase affects the detection of a cued, near-threshold visual target such that the visual cortical alpha phase at the time of visual stimulus onset biased target detection, replicating previous reports. We extended these observations by presenting visual targets at specific phases of the ongoing oscillatory alpha using a real-time oscillatory phase tracking system. We implemented online phase tracking in two ways, and compare the efficacy of them both. In the first, we sampled the ongoing EEG datastream and peak filtered it using a phase- and group-delay compensated Parks-McLelland FIR digital bandpass filter, centered at the pre-determined maximum amplitude and center frequency of the subject-specific occipital alpha oscillation. Only periods when the ratio of alpha/broadband power spectra reached a predetermined threshold were isolated for phase detection. Peaks and troughs of the filtered datastream were then extracted to determine the periodic timing of the ongoing alpha phase. We extrapolated the timing characteristics of the detected peaks to predict peak and trough phase intervals beyond the causal window of the datastream, and presented stimuli during such intervals in real- time. In the second, we recorded a few minutes of resting EEG to identify individual visual cortical alpha center frequency. These data also allow us to identify alpha peaks and troughs using a simple thresholding procedure wherein the top and bottom 0.1% of the sorted amplitude values of the raw, ongoing EEG reflect, with very high accuracy (> 95%), individual alpha peaks and troughs. Given the stability of the alpha occipital rhythm over short (< 1 cycle) time frames, we attempted to present stimuli during specific phases of the dominant oscillatory alpha as well.

Neural network properties can be inferred from electrophysiological power spectral geometry Torben Noto, Richard Gao, Erik Peterson, Bradley Voytek The study of the biophysical and cognitive role of neural oscillations has become a cornerstone of modern neuroscience. These oscillations are inferred from the power spectral density (PSD) of the neurophysiological signal of interest. The PSD of electrophysiological neural activity assumes a general 1/f form. Although changes of power in narrow frequency bands (alpha, beta, etc.) have been related to a variety of cognitive and behavioral states, and the broadband power (the offset) of this process has been shown to reflect aggregate population spiking activity, there is scant evidence for how other global properties of power spectral geometry relate to the underlying neural network activity. Treating the neural power spectra as a holistic entity affords the application of different analyses that may provide novel insights that would not be evident in narrow bands. Presumably, neural networks produce characteristic changes in the full spectrum (aside from narrowband oscillations) under different operational modes, so it may be possible to estimate certain features of the network from its geometry. Concurrent single cell and local field recordings from rat hippocampus and recordings directly from human cortex allow us to probe these relationships. The slope of the broadband spectrum (10-100 Hz) had a positive correlation with spike count (r=0.35) and a negative correlation with the fano factor of the inter-spike interval (r= -.35). Additionally, the slope of high gamma (80-125 Hz) negatively correlated with phase/amplitude coupling (r = -0.1). These results draw a link between spectral geometry, network properties, and neurobiology, and support the idea that the power spectrum should be considered as a holistic entity that contains a wealth of information about the network that produces it.

Spike-field coupling does not imply spike-spike coupling Erik Peterson & Bradley Voytek The origin and function of oscillatory activity remains a major outstanding question in neuroscience. One prominent hypothesis for the functional role of gamma oscillations is 'communication through coherence'. This theory posits that regional coherence enhances communication by increasing the precision of spike timing, i.e. spike-spike coupling. The focus on coherence has lead to computational investigations of already oscillating populations. While important in establishing coherence as useful for communications, and in showing how information flow is maximized when coherence between oscillating pairs is maximized, these studies skip over a basic question: is spike-time precision enhanced by the onset and amplitude of gamma oscillations? By definition, oscillating neural populations have repeating periods of decreased firing. If all else is held equal, these periods of relative silence would mean a decrease in information flow. As firing declines so does information. If oscillations increase information flow, they must alter spiking to overcome these 'silent costs'. Keeping with the idea that oscillations alter spike timing, and using Hodgkin-Huxley neurons in classic excitatory- inhibitory configurations, we simulated the effect of gamma onset and amplitude on spike precision and on information flow. Our simulations suggest a much larger range of parameters can generate gamma oscillations, compared to only a narrow range of parameters that can actually increase precision and information transmission in excitatory neurons. From a theoretical perspective, our results suggest the 'communication through coherence' hypothesis may require fairly stringent biophysical constraints to function as proposed. When aggregating over all models, gamma power does not statistically predict spike precision, nor does a change to spike-field coupling imply a change in spike-spike coupling. In sum these results suggest gamma oscillations, when driven solely by excitatory-inhibitory interactions, reflect mostly silent periods rather than the spike-time shifting necessary for enhanced precision.

Oscillatory visual cortical alpha disruptions in age-related working memory impairments Tammy Tran, Nicole Hoffner, Bradley Voytek Neural oscillations in the visual cortex play an important role in attention and memory. Oscillations, in particular 8-12 Hz alpha activity, support interregional communication, and ongoing fluctuations in alpha power and phase bias perception and cognition. While these phenomena are fairly well characterized individually, here we examine the overlap between visual attention and working memory and how these oscillatory processes are affected by healthy aging. We used electroencephalographic (EEG) recordings to compare behavioral performance and alpha activity of younger and older adults (20-30 and 60-70 years old) during a lateralized, visual working memory task. In this task, subjects were first presented with a non-informative, foveally-presented alerting cue indicating the beginning of a trial. This cue was followed by brief presentation of a visual working memory array and a delay period. Subjects then reported if a second, test array was the same as or different from the memory array. In this task, older adults showed increased reaction times overall and decreased accuracy in high memory load trials. Both groups showed decreased contralateral delay activity with increasing memory load. Analysis of extrastriate alpha power revealed decreased contralateral power during the delay period in both groups. While older adults also showed decreased ipsilateral alpha power, younger adults showed increased ipsilateral power instead, revealing significant lateralized alpha power differences as a function of age. Analysis of alpha phase revealed that, while memory array presentation equally increased extrastriate phase-resetting (or intertrial coherence, ITC) in both groups, younger adults showed strong alerting-cue-induced ITC that was nearly absent in older adults. These results suggest that in performing this task, older adults make less use of the alerting cue than do younger adults, and older adults may rely more heavily on bilateral visual cortical attention systems than do younger adults.

Auditory attention modulates frontal and temporal oscillatory dynamics in humans: Evidence from electrocorticography Roemer van der Meij, Aurélie Bidet-Caulet, Josef Parvizi, Nathan Crone, Edward Chang, Robert T. Knight, Bradley Voytek The brain needs to flexibly route information in distributed neuronal networks to meet the needs of rapid environmental changes. This selective communication between neuronal populations could be achieved via oscillatory dynamics. One such oscillatory phenomenon is phase-amplitude coupling (PAC), which reflects the hierarchical modulation of oscillations at different frequencies, but also the phase-coupled modulation of local neuronal spiking activity. The latter, manifested as high gamma activity (HG; 70-250 Hz) is modulated by oscillations at multiple frequencies dependent on task demands. HG can be observed as broadband increased power in the power spectrum of micro- to mesoscale measurements in human electrocorticographic data obtained from subdural recordings (ECoG). Recent evidence suggests that the power spectrum, which reflects both oscillatory and non-oscillatory processes, can provide insight into the dynamics supporting goal-directed behavior. Notably, an upward rotation (flattening) of the power spectrum could reflect a shift in neuronal resources from a regime of tight oscillatory inhibition towards one of increased sensitivity to incoming signals. Local HG activity has been shown to be modulated by low frequency rhythms that are coherent over broader regions suggesting that power spectral changes could be coordinated in a similar manner. To investigate this, we obtained ECoG recordings from 8 epilepsy patients undergoing resective surgery while they performed a dichotic attention task. They had to detect deviant sounds within a relevant stream while ignoring an irrelevant acoustic stream. A third condition (control condition) was added in which all sounds received the same amount of attention. We found that fronto-temporal HG activity increased, frontal theta increased, and temporal alpha decreased as a function of attention. Additionally, we also observed upward rotations (a flattening) of the power spectrum at temporal electrodes, which captures both the decrease of temporal alpha, and the increase of temporal HG activity. Moreover, this spectral flattening was found to be phase-locked to distributed frontal theta rhythms, suggesting temporally coordinated changes in neuronal recruitment. Taken together, these results show the modulation of local neuronal activity by distributed oscillatory rhythms as a function of task demands. Importantly, this modulation occurred (1) on timescales as short as several 100ms, and (2) between distinct regions including auditory cortex and frontal areas. The results provide evidence that oscillatory dynamics provide a key mechanism for routing of information in the brain.