Periodic Reporting for period 3 - CELPRED (Circuit elements of the cortical circuit for predictive processing)
Reporting period: 2023-02-01 to 2024-07-31
One promising theoretical framework to explain the function of neocortex is predictive processing. It postulates that cortex functions by maintaining an internal model, or internal representation, of the world through a comparison of predictions based on this internal model with incoming sensory information. Implementing predictive processing in a cortical circuit would require a set of distinct functional cell types. These would include neurons that compute a difference between top-down predictions and bottom-up input, referred to as prediction error neurons, and a separate population of neurons that integrate the output of prediction error neurons to maintain an internal representation of the world.
With our research we hope to identify the mechanisms that underly a correct balance between expectation and sensory input in normal perception. Characterizing the circuit elements underlying predictive processing in cortex may reveal a strategy to bias perception either towards top-down or bottom-up drive when the balance between the two is perturbed, as may be the case in neuropsychiatric disorders. We speculate that a hallucination is the consequence of an abnormal imbalance in top-down and bottom-up input streams.
With our research we hope to identify the mechanisms that underly a correct balance between expectation and sensory input in normal perception. Characterizing the circuit elements underlying predictive processing in cortex may reveal a strategy to bias perception either towards top-down or bottom-up drive when the balance between the two is perturbed, as may be the case in neuropsychiatric disorders. We speculate that a hallucination is the consequence of an abnormal imbalance in top-down and bottom-up input streams.
Our research is testing the framework of predictive processing and will identify different putative circuit elements and cell types that are thought to form the circuit in mouse visual cortex. We are using a combination of physiological recordings, optogenetic manipulations of neural activity, and gene expression measurements to determine the cell types that have functional responses consistent with different prediction errors, as well as those coding for the internal representation. In particular, we have identified a mechanism of lateral interactions between cortical areas that underlies the computation of audiovisual prediction errors. With experience, auditory input can begin to influence visual perception. These findings not only advance our understanding of how the brain processes information from different senses but may also have implications for understanding disorders that result in hallucinatory percepts. In addition, we have identified molecular markers for positive and negative prediction error neurons in cortex. This will allow us to perform targeted manipulations of cortical circuits to test various theoretical predictions of cortical function. Finally, we have provided a set of findings consistent with the interpretation that layer 5 neurons function to maintain an internal representation in the cortex. We are particularly excited by this, as it is likely that these neurons are essential for the neuronal correlate of conscious perception.
Refining our understanding of cortical circuitry will require methods to target proteins used for recording or manipulating neuronal activity to functionally identified subsets of neurons. To do this we have created a library of artificial minimal promoters that are small enough to fit in adeno associated viral vector and that express selectively in a subset of cortical neurons. We have then screened this library for functionally specificity and identified candidate promoters for our neuron types of interested. In the following year, we expect to finish up the publication of our research results and perform final control experiments.