Mapping working memory retrieval in space and in time:A combined electroencephalography and electrocorticography approach

In this study, we investigated the time course and neural correlates of the retrieval process underlying visual working memory. We made use of a rare dataset in which the same task was recorded using both scalp electroencephalography (EEG) and Electrocorticography (ECoG), respectively. This allowed us to examine with great spatial and temporal detail how the retrieval process works, and in particular how the medial temporal lobe (MTL) is involved. In each trial, participants judged whether a probe face had been among a set of recently studied faces. With a method that combines hidden semi-Markov models and multivariate pattern analysis, the neural signal was decomposed into a sequence of latent cognitive stages with information about their durations on a trial-by-trial basis. Analyzed separately, EEG and ECoG data yielded converging results on discovered stages and their interpretation, which reflected 1) a brief pre-attention stage, 2) encoding the stimulus, 3) retrieving the studied set, and 4) making a decision. Combining these stages with the high spatial resolution of ECoG suggested that activity in the temporal cortex reflected item familiarity in the retrieval stage; and that once retrieval is complete, there is active maintenance of the studied face set in the decision stage in the MTL. During this same period, the frontal cortex guides the decision by means of theta coupling with the MTL. These observations generalize previous findings on the role of MTL theta from long-term memory tasks to short-term memory tasks

Information flows from hippocampus to auditory cortex during replay of verbal working memory items

The maintenance of items in working memory (WM) relies on a widespread network of cortical areas and hippocampus where synchronization between electrophysiological recordings reflects functional coupling. We investigated the direction of information flow between auditory cortex and hippocampus while participants heard and then mentally replayed strings of letters in WM by activating their phonological loop. We recorded local field potentials from the hippocampus, reconstructed beamforming sources of scalp EEG, and - additionally in four participants - recorded from subdural cortical electrodes. When analyzing Granger causality, the information flow was from auditory cortex to hippocampus with a peak in the [4 8] Hz range while participants heard the letters. This flow was subsequently reversed during maintenance while participants maintained the letters in memory. The functional interaction between hippocampus and the cortex and the reversal of information flow provide a physiological basis for the encoding of memory items and their active replay during maintenance

Shifts in Gamma Phase–Amplitude Coupling Frequency from Theta to Alpha Over Posterior Cortex During Visual Tasks

The phase of ongoing theta (4–8 Hz) and alpha (8–12 Hz) electrophysiological oscillations is coupled to high gamma (80–150 Hz) amplitude, which suggests that low-frequency oscillations modulate local cortical activity. While this phase–amplitude coupling (PAC) has been demonstrated in a variety of tasks and cortical regions, it has not been shown whether task demands differentially affect the regional distribution of the preferred low-frequency coupling to high gamma. To address this issue we investigated multiple-rhythm theta/alpha to high gamma PAC in two subjects with implanted subdural electrocorticographic grids. We show that high gamma amplitude couples to the theta and alpha troughs and demonstrate that, during visual tasks, alpha/high gamma coupling preferentially increases in visual cortical regions. These results suggest that low-frequency phase to high-frequency amplitude coupling is modulated by behavioral task and may reflect a mechanism for selection between communicating neuronal networks

Formation of visual memories controlled by gamma power phase-locked to alpha oscillations

Neuronal oscillations provide a window for understanding the brain dynamics that organize the flow of information from sensory to memory areas. While it has been suggested that gamma power reflects feedforward processing and alpha oscillations feedback control, it remains unknown how these oscillations dynamically interact. Magnetoencephalography (MEG) data was acquired from healthy subjects who were cued to either remember or not remember presented pictures. Our analysis revealed that in anticipation of a picture to be remembered, alpha power decreased while the cross-frequency coupling between gamma power and alpha phase increased. A measure of directionality between alpha phase and gamma power predicted individual ability to encode memory: stronger control of alpha phase over gamma power was associated with better memory. These findings demonstrate that encoding of visual information is reflected by a state determined by the interaction between alpha and gamma activity

Frontal Functional Connectivity of Electrocorticographic Delta and Theta Rhythms during Action Execution Versus Action Observation in Humans

We have previously shown that in seven drug-resistant epilepsy patients, both reaching-grasping of objects and the mere observation of those actions did desynchronize subdural electrocorticographic (ECoG) alpha (8–13 Hz) and beta (14–30) rhythms as a sign of cortical activation in primary somatosensory-motor, lateral premotor and ventral prefrontal areas (Babiloni et al., 2016a). Furthermore, that desynchronization was greater during action execution than during its observation. In the present exploratory study, we reanalyzed those ECoG data to evaluate the proof-of-concept that lagged linear connectivity (LLC) between primary somatosensory-motor, lateral premotor and ventral prefrontal areas would be enhanced during the action execution compared to the mere observation due to a greater flow of visual and somatomotor information. Results showed that the delta-theta (<8 Hz) LLC between lateral premotor and ventral prefrontal areas was higher during action execution than during action observation. Furthermore, the phase of these delta-theta rhythms entrained the local event-related connectivity of alpha and beta rhythms. It was speculated the existence of a multi-oscillatory functional network between high-order frontal motor areas which should be more involved during the actual reaching-grasping of objects compared to its mere observation. Future studies in a larger population should cross-validate these preliminary results

A Quest for Meaning in Spontaneous Brain Activity - From fMRI to Electrophysiology to Complexity Science

The brain is not a silent, complex input/output system waiting to be driven by external stimuli; instead, it is a closed, self-referential system operating on its own with sensory information modulating rather than determining its activity. Ongoing spontaneous brain activity costs the majority of the brain\u27s energy budget, maintains the brain\u27s functional architecture, and makes predictions about the environment and the future. I have completed three separate studies on the functional significance and the organization of spontaneous brain activity. The first study showed that strokes disrupt large-scale network coherence in the spontaneous functional magnetic resonance imaging: fMRI) signals, and that the degree of such disruption predicts the behavioral impairment of the patient. This study established the functional significance of coherent patterns in the spontaneous fMRI signals. In the second study, by combining fMRI and electrophysiology in neurosurgical patients, I identified the neurophysiological signal underlying the coherent patterns in the spontaneous fMRI signal, the slow cortical potential: SCP). The SCP is a novel neural correlate of the fMRI signal, most likely underlying both spontaneous fMRI signal fluctuations and task-evoked fMRI responses. Some theoretical considerations have led me to propose a hypothesis on the involvement of the neural activity indexed by the SCP in the emergence of consciousness. In the last study I investigated the temporal organization across a wide range of frequencies in the spontaneous electrical field potentials recorded from the human brain. This study demonstrated that the arrhythmic, scale-free brain activity often discarded in human and animal electrophysiology studies in fact contains rich, complex structures, and further provided evidence supporting the functional significance of such activity

Waveform detection by deep learning reveals multi-area spindles that are selectively modulated by memory load

Sleep is generally considered to be a state of large-scale synchrony across thalamus and neocortex; however, recent work has challenged this idea by reporting isolated sleep rhythms such as slow oscillations and spindles. What is the spatial scale of sleep rhythms? To answer this question, we adapted deep learning algorithms initially developed for detecting earthquakes and gravitational waves in high-noise settings for analysis of neural recordings in sleep. We then studied sleep spindles in non-human primate electrocorticography (ECoG), human electroencephalogram (EEG), and clinical intracranial electroencephalogram (iEEG) recordings in the human. Within each recording type, we find widespread spindles occur much more frequently than previously reported. We then analyzed the spatiotemporal patterns of these large-scale, multi-area spindles and, in the EEG recordings, how spindle patterns change following a visual memory task. Our results reveal a potential role for widespread, multi-area spindles in consolidation of memories in networks widely distributed across primate cortex

Nonuniform Power Changes and Spatial, Temporal and Spectral Diversity in High Gamma Band (\u3e60 Hz) Signals in Human Electrocorticography

High-gamma band: \u3e60Hz) power changes in cortical electrophysiology are a reliable indicator of focal, event-related cortical activity. In spite of discoveries of oscillatory subthreshold and synchronous suprathreshold activity at the cellular level, there is an increasingly popular view that high-gamma band amplitude changes recorded from cellular ensembles are the result of asynchronous firing activity that yields wideband and uniform power increases. Others have demonstrated independence of power changes in the low- and high-gamma bands, but to date, no studies have shown evidence of any such independence above 60Hz. Based on non-uniformities in time-frequency analyses of electrocorticographic: ECoG) signals, we hypothesized that induced high-gamma band: 60-500Hz) power changes are more heterogeneous than currently understood. We quantified this spectral non-uniformity with two different approaches using single-word repetition tasks in human subjects. First, we showed that the functional responsiveness of different ECoG high-gamma sub-bands can discriminate cognitive tasks: e.g., hearing, reading, speaking) and cortical locations. Power changes in these sub-bands of the high-gamma range are consistently present within single trials and have statistically different time courses within the trial structure. Moreover, when consolidated across all subjects within three task-relevant anatomic regions: sensorimotor, Broca\u27s area, and superior temporal gyrus), these behavior- and location- dependent power changes evidenced nonuniform trends across the population of subjects. Second, we studied the dynamics of multiple frequency bands in order to quantify the diversity present in the ECoG signals. Using a matched filter construct and receiver operating characteristic: ROC) analysis we show that power modulations correlated with phonemic content in spoken and heard words are represented diffusely in space, time and frequency. Correlating power modulation in multiple frequency bands above 60 Hz over broad cortical areas, with time varying envelopes significantly improved performed area under the ROC curve scores in phoneme prediction experiments. Finally we show preliminary evidence supporting our hypothesis in microarray ECoG data. Taken together, the nonuniformity of high frequency power changes and the information content captured in the spatio-temporal dynamics of those frequencies suggests that a new approach to evaluating high-gamma band cortical activity is necessary. These findings show that in addition to time and location, frequency is another fundamental dimension of high-gamma dynamics