Investigating the neural mechanisms of human cognitive function through intracranial recordings

National Institute Of Neurological Disorders And Stroke

Investigators

Linked publications, trials & patents

Abstract

FY2022 has seen significant progress towards realizing our goals and objectives. We have continued our efforts capturing and analyzing intracranial recordings while participants engage in cognitive tasks designed to probe memory encoding and retrieval. Patients with drug resistant epilepsy receiving intracranial electrodes and surgical treatment at the Clinical Center have been recruited for these studies. Our work takes advantage of the opportunities to record both intracranial EEG and single unit spiking activity from these implanted electrodes as participants perform a variety of cognitive tasks during the monitoring period. Our efforts are focused on understanding changes in human brain activity across these different spatial scales. In order to probe how memories are formed and retrieved in the brain, we have focused our efforts on understanding how information is represented in the neural signals that we record. To this end, we have uncovered a number of important phenomena. We have recently shown that synchronized bursts of spiking activity together contribute to the emergence of ripple oscillations at the local field potential level, and that coordinated ripples across multiple micro-electrodes together contribute to the ripples observed at the largest spatial scale in the iEEG recordings (Tong AP, Vaz A, Wittig JH, Inati SK, Zaghloul KA (2021) eLife). We have also shown that traveling waves of oscillatory activity coordinate underlying spiking activity and may be relevant for the ability to move information across the brain (Sreekumar V, Wittig JH, Inati SK, Zaghloul KA (2022) Traveling waves at the macro and micro scale in the human brain, In Revision). Given these underlying neurophysiological phenomena, we have focused much of our efforts examining these neural signals at the smaller micro scale. We have now shown in a number of different experimental paradigms that the bursts of spiking activity that contribute to the observed ripples are organized into a specific temporal sequence. Our hypothesis has been that this sequential order of spiking activity may be a fundamental building block for representing information in the brain. By examining these sequences of spiking activity as participants view images drawn from different semantic categories, we have now found preliminary evidence that the specific order of neuronal firing in the anterior temporal lobe can distinguish different semantic categories, and therefore temporal order of neural activity seems to play a role in representing different semantic information. This aligns with our previous work showing that the order of spiking activity that is present as individuals encode items into their memory is replayed when they retrieve those same items, suggesting that the order of spiking activity carries specific information about the items we are representing in our brains. We have also explored how connectivity at the smallest spatial scales may provide insights into the functional organization and structure of the human cortex, and how such organization may be relevant for encoding information. We have found that small local patches of cortex, which we refer to as modules, are highly connected and that activity within these modules is differentially modulated by different stimuli, suggesting that these modules encode different functional information. These modules exhibit the same spatial dimensions and functional characteristics of cortical columns that are hypothesized to exist throughout the human cortex. We have recently published a manuscript describing this work (Chapeton JI, Wittig JH, Inati SK, Zaghloul KA (2022) Nature Communications, In Press). We have spent much of our effort over the past year now building upon this foundation in a number of different ways. For example, we have identified that the specific sequences of spiking activity that we observe in our data are both specific to individual items being represented in the brain but also are relatively constrained in their overall order. The spiking sequences observed in an individual patch of cortex during different times are, in general, somewhat similar to one another. Our data therefore suggest that the spiking activity of any patch of cortex can be characterized by a relatively stable backbone of sequential firing, around which individual variations in spiking order may enable the representations of item-specific information. We have now completed a manuscript describing this work (Vaz AP, Wittig JH, Inati SK, Zaghloul KA (2022) In Review). We have also spent our efforts over the past year focusing on how long-term episodic memory may interact with other cognitive processes. For example, we have been examining the intersection between long term and short term memory. As one of the cornerstones of human cognition, short-term (or working) memory (STM) plays a fundamental role in various perceptual and cognitive functions. Notably, there are significant parallels between the computations required for the precision of STM and those required to minimize mnemonic interference for long-term memory, a process referred to as pattern separation that has traditionally been ascribed to the medial temporal lobe (MTL). We have recently uncovered direct evidence supporting the hypothesis that the circuitry of the MTL, long viewed as a dedicated module for distinguishing similar neural representations of information in long-term memory, also supports STM precision. We have completed this work and a manuscript describing this work has been recently submitted for publication (Xie W, Wittig JH, Bhasin S, Zawora C, Inati SK, Zhang W, Zaghloul KA (2022) In Review). Finally, we have also taken advantage of our recordings that we capture in patients with drug resistant epilepsy, and our experience investigating neural signals in the context of cognition, to begin studies investigating what how these signals may inform us about seizures, about how they emerge, and in how they propagate. In one of our first studies in this domain, we examined the oscillatory nature of the signals we record during seizures. This phenomenon, known as the recruitment rhythm, appears on multiple electrodes and we hypothesized that these rhythms represent the receipt of traveling waves from a pathological source of seizure activity. We developed an algorithm to localize this source of activity based on these phase differences in these rhythms across electrodes, and found that localization in this manner appears relatively accurate in identifying the source of seizures in individual patients. We published a manuscript describing this work (Diamond JM, Diamond BE, Trotta MS, Dembny K, Inati SK, Zaghloul KA (2021) Brain). Over the past year, we have now extended this work to examine interictal epileptiform discharges, which we also hypothesized reflected the receipt of a traveling wave activity from a pathological seizure source. Indeed, we found that the time differences we observe between electrodes when there is an interictal discharges matches the time differences we see between electrodes during seizures. Again, using a similar localization algorithm, we found that we can use these time differences to localize the hypothesized source of pathologic activity. We have recently completed a manuscript describing this work (Diamond JM, Withers CP, Chapeton JI, Rahman S, Inati SK, Zaghloul KA (2022) In Review).