PROJECT SUMMARY
The ultimate goal of this research program is to determine the neural mechanisms of sequence monitoring. This
knowledge can directly contribute to understanding new treatments for disorders where sequential behaviors are
disrupted, such as Obsessive-Compulsive Disorder (OCD). Daily, we monitor sequences of visual information
such as the series of bus or train stops when looking for the correct exit. Sequence monitoring is the active
process of tracking the order of subsequent “states” or steps. Monitoring is distinct from other well-studied
sequence processes, such as explicit memorization, or potentially more automatic behaviors such as a series of
motor outputs (e.g., playing the piano) or statistical sequence learning. However, the monitoring aspects of
sequence processing remain largely unknown.
Knowledge of higher-order similarities across sequences (e.g., AAAB, &&&@), abstractions, can aid sequence
monitoring. For example, understanding the steps required in each turn in a game, or the repetitive pattern in a
poem or song, can improve our awareness and processing. Abstract sequence monitoring includes viewing the
sequences that possess abstract structure, active monitoring of this structure, and response. Here, we will
determine the neural representation of abstract sequential structure using passive structured sequence viewing.
We hypothesize that a key element of sequence structure, position, is encoded in the lateral prefrontal cortex
(LPFC) with phasic bursts that in aggregate create population ramping. These neural dynamics can uniquely
“tag” each serial position in the sequence, supporting monitoring. This prediction is based on prior literature, and
on our discovery that increasing (ramping) blood oxygen level-dependent (BOLD) activity in the rostral LPFC of
humans is necessary for sequence execution and underlies sequence monitoring (Desrochers et al., 2015a,
2019). During awake fMRI, we observed parallel BOLD ramping in the LPFC of monkeys performing a structured
sequence viewing task. We will use these data to specifically target electrophysiological recordings (Desrochers
et al., 2015b; Feingold*, Desrochers* et al. 2012). This viewing task also provides robust BOLD responses to
viewed sequence deviants and avoids motor and decision-making confounds while providing experimental
flexibility. By using these activity patterns to guide neural recordings, we remove the need for anatomy-based
assumptions about cross-species homology and can localize data acquisition with sub-region specificity.
We will systematically test the hypotheses that sequence position is characterized by successive phasic
increases in neural spiking in LPFC (Aim 1), and that neural activity related to sequence position is modulated
by the passage of time and reward expectation (Aim 2). Sequence monitoring is fundamental to many natural
behaviors. These data are unique in being guided by, and directly relatable-to, fMRI mapping. While hypothesis-
driven, any outcome of these recordings from fMRI-identified brain areas will advance our understanding of this
crucial process.
