Cognitive processes in the human brain are mediated by complex interactions among distributed brain regions. The interaction between the hippocampus and neocortical regions is crucial for physiologic and pathologic long-term episodic memory processing in the brain. However, the network mechanisms of this hippocampal-cortical communication remain unclear. To address this issue, we first designed organic materials and conformable electronics to create integrated neural interface devices that increase the spatiotemporal resolution of electrophysiologic monitoring.
These devices enabled acquisition of local field potentials and action potentials of individual cortical neurons from the surface of the human brain, enhancing the ability to investigate neural network mechanisms without breaching the tissue interface. Next, we employed these devices in tandem with hippocampal probes to analyze hippocampal-cortical interactions in the context of memory tasks in freely moving rodents. We determined that in the physiologic state, the spatial properties of cortical spindle oscillations predict the likelihood of coupling with hippocampal ripples and are modulated by memory demand. In the pathologic state, we showed that interictal epileptiform discharges (IEDs), ubiquitous markers of epileptic networks, disrupt hippocampal-cortical coupling required for memory consolidation.
These IEDs induce spindle oscillations in the synaptically connected cortex, producing prolonged, hypersynchronous neuronal spiking and expanding the brain territory capable of generating IEDs. Spatiotemporally targeted closed-loop electrical stimulation triggered on hippocampal IED occurrence eliminated the abnormal cortical activity patterns, preventing spread of the epileptic network and ameliorating long-term spatial memory deficits in rodents. Our findings provide new insights into mechanisms of physiologic and pathologic memory processing and offer novel approaches to therapies aimed at addressing distributed network dysfunction in neuropsychiatric disorders.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/4psn-y614 |
| Date | January 2024 |
| Creators | Hassan, Ahnaf Rashik |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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