Layer-specific manipulation to test feedforward/feedback cortical circuitry

NIH RePORTER · NIH · R01 · $293,487 · view on reporter.nih.gov ↗

Abstract

The cortex must filter out the bulk of sensory inputs. Not enough or too much filtering may underlie a variety of disorders like autism and schizophrenia. Mounting evidence suggests that this depends on alpha/beta (~8-30 Hz) oscillations vs gamma (>35 Hz) with associated spiking. They are ubiquitous in cortex and anti-correlated. Gamma/spiking is high during sensory inputs while alpha/beta is high (and spiking is low) during conditions requiring top-down control. The central idea is alpha/beta (~8-30 Hz) rhythms in deep cortical layers inhibit the superficial layer activity (spiking and gamma, >35 Hz) that feed forward sensory inputs. Our testbed will be a model of Predictive Coding in which alpha/beta carries the top-down predictions from higher cortex that inhibit the feeding forward of bottom-up sensory inputs of predicted stimuli. We will test this hypothesis via direct cause-and-effect experiments, by manipulating the alpha/beta prediction rhythms in monkeys. We made this possible by developing a new ultra-fast latency (<10 ms) closed-loop system that can read the brain’s endogenous rhythms and phase-match electrical stimulation to them. We will also employ high-density “laminar” electrodes to record from all cortical layers and target stimulation to superficial vs deep layers. Laminar electrodes with injection ports will also allow selective pharmacological manipulation of deep vs superficial cortical layers. Monkeys will perform a local and global (patterned) oddball detection task. Our model makes specific predictions on how attenuating vs amplifying alpha/beta prediction signals will affect local physiological as well as feedforward vs feedback signaling of predictions and oddballs to higher vs lower cortex. Understanding neurophysiological properties, functions and interactions between cortical layers and their different dynamics can provide key insight into the control of cortical processing and the disorders that come from its dysfunction.

Key facts

NIH application ID
10769832
Project number
5R01MH131715-02
Recipient
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
Principal Investigator
EARL K MILLER
Activity code
R01
Funding institute
NIH
Fiscal year
2024
Award amount
$293,487
Award type
5
Project period
2023-02-01 → 2027-11-30