Clinically indicated electrical stimulation strategies to treat patients with medically refractory epilepsy.

Focal epilepsies represent approximately half of all diagnoses, and more than one-third of these patients are refractory to pharmacologic treatment. Although resection can result in seizure freedom, many patients do not meet surgical criteria, as seizures may be multifocal in origin or have a focus in an eloquent region of the brain. For these individuals, several U.S. Food and Drug Administration (FDA)-approved electrical stimulation paradigms serve as alternative options, including vagus nerve stimulation, responsive neurostimulation, and stimulation of the anterior nucleus of the thalamus. All of these are safe, flexible, and lead to progressive seizure control over time when used as an adjunctive therapy to antiepileptic drugs. Focal epilepsies frequently involve significant comorbidities such as cognitive decline. Similar to antiepilepsy medications and surgical resection, current stimulation targets and parameters have yet to address cognitive impairments directly, with patients reporting persistent comorbidities associated with focal epilepsy despite a significant reduction in the number of their seizures. Although low-frequency theta oscillations of the septohippocampal network are critical for modulating cellular activity and, in turn, cognitive processing, the coordination of neural excitability is also imperative for preventing seizures. In this review, we summarize current FDA-approved electrical stimulation paradigms and propose that theta oscillations of the medial septal nucleus represent a novel neuromodulation target for concurrent seizure reduction and cognitive improvement in epilepsy. Ultimately, further advancements in clinical neurostimulation strategies will allow for the efficient treatment of both seizures and comorbidities, thereby improving overall quality of life for patients with epilepsy

Large-scale Network Representations during Episodic Mnemonic Processing in Humans

Spatial and temporal details constitute critical components of our memories for recently experienced events, termed episodic memories. Both knowledge about where we were and approximately when things happened during our day are important cues for remembering what happened to us at an earlier event. A region called the hippocampus has been strongly implicated in the forming and retrieving of these episodic memories. However, the relative importance of cortical areas in conjunction with the hippocampus to episodic memory remains under debate. Specifically, a vast majority of the studies have focused only on characterizing the individual contributions of the hippocampus or specific cortical modules to episodic memory rather than determining the interactions among them. With the studies conducted here, I have represented episodic mnemonic processes as large-scale networks derived from functional connectivity analyses applied to human neuroimaging and electrophysiology data. By applying quantitative measures from the field of graph theory, I aim to provide insight into the global and local organization of coordinated interactions between regions throughout the brain. I hypothesize that network analyses will demonstrate that different aspects of episodic memory, including encoding and retrieval, will produce specific network representations. Furthermore, the large-scale functional network organization will vary based upon the type of information being processed and during directed cognition as compared to rest. First, I provide an overview of past research dedicated to understanding the neural basis of memory processes through networks. Next, I present a neuroimaging study evaluating the unique networks present during successful and unsuccessful retrieval and during spatiotemporal processing. Increases in overall network connectivity exemplified successful retrieval with density correlating with retrieval accuracy. Furthermore, I identified distinct but overlapping subnetworks for spatial and temporal retrieval with the hippocampus and additional neocortical regions as hubs of connectivity within the networks. In a second neuroimaging experiment, I again established separate spatiotemporal networks and applied a data-driven approach to characterize connectivity patterns involved in the encoding and retrieval of contextual information. A comparison of task-based with resting-state partitions showed that data-driven models capture variance in memory performance and supply a parsimonious view of network topology. Finally, in an electrophysiology study, we disrupted network connectivity (and possibly communication) by directly stimulating specific areas in order to provide evidence for the utility and accuracy of network representations. Specifically, we targeted the spatial retrieval network and produced a deficit in spatial but not temporal retrieval performance. Thus, network models are a new avenue of research into the brain-wide interactions thought to represent relevant mnemonic processes and can be leveraged to gain insight into brain-behavior relationships

Flexible network community organization during the encoding and retrieval of spatiotemporal episodic memories

Memory encoding and retrieval involve distinct interactions between multiple brain areas, yet the flexible structure of corresponding large-scale networks during such memory processing remains unclear. Using functional magnetic resonance imaging, we employed a spatiotemporal encoding and retrieval task, detecting functional community structure across the multiple components of our task. Consistent with past work, we identified a set of stable subnetworks, mostly belonging to primary motor and sensory cortices but also identified a subset of flexible hubs, mostly belonging to higher association areas. These “mover” hubs changed connectivity patterns across spatial and temporal memory encoding and retrieval, engaging in an integrative role within the network. Global encoding network and subnetwork dissimilarity predicted retrieval performance. Together, our findings emphasize the importance of flexible network allegiance among some hubs and the importance of network reconfiguration to human episodic memory.National Institutes of HealthUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [NS087527, NS076856]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Multiple interacting brain areas underlie successful spatiotemporal memory retrieval in humans.

Emerging evidence suggests that our memories for recent events depend on a dynamic interplay between multiple cortical brain regions, although previous research has also emphasized a primary role for the hippocampus in episodic memory. One challenge in determining the relative importance of interactions between multiple brain regions versus a specific brain region is a lack of analytic approaches to address this issue. Participants underwent neuroimaging while retrieving the spatial and temporal details of a recently experienced virtual reality environment; we then employed graph theory to analyze functional connectivity patterns across multiple lobes. Dense, large-scale increases in connectivity during successful memory retrieval typified network topology, with individual participant performance correlating positively with overall network density. Within this dense network, the hippocampus, prefrontal cortex, precuneus, and visual cortex served as "hubs" of high connectivity. Spatial and temporal retrieval were characterized by distinct but overlapping "subnetworks" with higher connectivity within posterior and anterior brain areas, respectively. Together, these findings provide new insight into the neural basis of episodic memory, suggesting that the interactions of multiple hubs characterize successful memory retrieval. Furthermore, distinct subnetworks represent components of spatial versus temporal retrieval, with the hippocampus acting as a hub integrating information between these two subnetworks