Medial temporal lobe functional connectivity predicts stimulation-induced theta power.

Focal electrical stimulation of the brain incites a cascade of neural activity that propagates from the stimulated region to both nearby and remote areas, offering the potential to control the activity of brain networks. Understanding how exogenous electrical signals perturb such networks in humans is key to its clinical translation. To investigate this, we applied electrical stimulation to subregions of the medial temporal lobe in 26 neurosurgical patients fitted with indwelling electrodes. Networks of low-frequency (5-13 Hz) spectral coherence predicted stimulation-evoked increases in theta (5-8 Hz) power, particularly when stimulation was applied in or adjacent to white matter. Stimulation tended to decrease power in the high-frequency broadband (HFB; 50-200 Hz) range, and these modulations were correlated with HFB-based networks in a subset of subjects. Our results demonstrate that functional connectivity is predictive of causal changes in the brain, capturing evoked activity across brain regions and frequency bands.

Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition.

The idea that synchronous neural activity underlies cognition has driven an extensive body of research in human and animal neuroscience. Yet, insufficient data on intracranial electrical connectivity has precluded a direct test of this hypothesis in a whole-brain setting. Through the lens of memory encoding and retrieval processes, we construct whole-brain connectivity maps of fast gamma (30-100 Hz) and slow theta (3-8 Hz) spectral neural activity, based on data from 294 neurosurgical patients fitted with indwelling electrodes. Here we report that gamma networks desynchronize and theta networks synchronize during encoding and retrieval. Furthermore, for nearly all brain regions we studied, gamma power rises as that region desynchronizes with gamma activity elsewhere in the brain, establishing gamma as a largely asynchronous phenomenon. The abundant phenomenon of theta synchrony is positively correlated with a brain region's gamma power, suggesting a predominant low-frequency mechanism for inter-regional communication.

Reset of human neocortical oscillations during a working memory task.

Both amplitude and phase of rhythmic slow-wave electroencephalographic activity are physiological correlates of learning and memory in rodents. In humans, oscillatory amplitude has been shown to correlate with memory; however, the role of oscillatory phase in human memory is unknown. We recorded intracranial electroencephalogram from human cortical and hippocampal areas while subjects performed a short-term recognition memory task. On each trial, a series of four list items was presented followed by a memory probe. We found agreement across trials of the phase of oscillations in the 7- to 16-Hz range after randomly timed stimulus events, evidence that these events either caused a phase shift in the underlying oscillation or initiated a new oscillation. Phase locking in this frequency range was not generally associated with increased poststimulus power, suggesting that stimulus events reset the phase of ongoing oscillations. Different stimulus classes selectively modulated this phase reset effect, with topographically distinct sets of recording sites exhibiting preferential reset to either probe items or to list items. These findings implicate the reset of brain oscillations in human working memory.

An autoassociative neural network model of paired-associate learning.

Hebbian heteroassociative learning is inherently asymmetric. Storing a forward association, from item A to item B, enables recall of B (given A), but does not permit recall of A (given B). Recurrent networks can solve this problem by associating A to B and B back to A. In these recurrent networks, the forward and backward associations can be differentially weighted to account for asymmetries in recall performance. In the special case of equal strength forward and backward weights, these recurrent networks can be modeled as a single autoassociative network where A and B are two parts of a single, stored pattern. We analyze a general, recurrent neural network model of associative memory and examine its ability to fit a rich set of experimental data on human associative learning. The model fits the data significantly better when the forward and backward storage strengths are highly correlated than when they are less correlated. This network-based analysis of associative learning supports the view that associations between symbolic elements are better conceptualized as a blending of two ideas into a single unit than as separately modifiable forward and backward associations linking representations in memory.

Gating of human theta oscillations by a working memory task.

Electrode grids on the cortical surface of epileptic patients provide a unique opportunity to observe brain activity with high temporal-spatial resolution and high signal-to-noise ratio during a cognitive task. Previous work showed that large-amplitude theta frequency oscillations occurred intermittently during a maze navigation task, but it was unclear whether theta related to the spatial or working memory components of the task. To determine whether theta occurs during a nonspatial task, we made recordings while subjects performed the Sternberg working memory task. Our results show event-related theta and reveal a new phenomenon, the cognitive "gating" of a brain oscillation: at many cortical sites, the amplitude of theta oscillations increased dramatically at the start of the trial, continued through all phases of the trial, including the delay period, and decreased sharply at the end. Gating could be seen in individual trials and varying the duration of the trial systematically varied the period of gating. These results suggest that theta oscillations could have an important role in organizing multi-item working memory.