Peter Rudebeck - US grants

Project summary Dysfunction within the circuits connecting the prefrontal cortex (PFC) and limbic system is the cause of nearly every psychiatric condition, including anxiety disorders. Determining how individual pathways within these circuits function to drive specific aspects of cognition and affect would revolutionize our understanding of the biological bases of psychiatric disorders and provide the critical foundation for pathway-specific treatments in humans. In order to establish the function of these circuits, we must be able to characterize and manipulate the activity of distinct neural pathways that connect the prefrontal and limbic system. The ability to do this in monkeys would be a major advance in basic neuroscience research and would also have significant translational impact. This is because the macaque PFC is more similar, in both its cytoarchitecture and its connections, to the human PFC than that of any other available animal model. What we discover in macaques can be directly translated to humans and have the greatest possible bearing on the understanding and treatment of psychiatric disorders. Our goal here is to develop the use of pathway specific manipulations of neural activity in monkeys and to combine them with recordings of single neurons to answer a fundamental question relating to the pathophysiology of anxiety disorders. Neuroimaging studies of people with anxiety disorders have observed dysfunction between the ventrolateral PFC and amygdala, but little is know about the specific contribution of this circuit to behavior and the role of specific pathways within this circuit. We hypothesize that the ventrolateral PFC-amygdala circuit is vital for encoding the probability that an event will occur. Furthermore, we theorize that dysfunction within the specific pathway from amygdala to ventrolateral PFC heightens anxiety related to the likelihood that a negative outcome will occur. To test our hypothesis we will use an innovative combination of single-neuron recordings, field potential recordings, and pathway specific chemogenetic silencing, analyzing the timing of reward-related neural responses (Aim1) and the LFP synchrony (Aim 2) within this circuit under normal physiological conditions and when neurons in the amygdala that specifically project to the ventrolateral prefrontal cortex are transiently inhibited (Aim 3). Completing the aims of this project will fundamentally advance our understanding of the neural pathways and mechanisms involved in representing uncertainty as well as providing a pathway specific understanding of how amygdala influences outcome probability representations. In addition, achieving the aims of this project will not only provide unique insights into the pathophysiology of anxiety disorders, but it will also lay the foundation for pathway specific manipulations of neural activity in the monkey brain. Given the close correspondence between the human and monkey brains, these experiments in monkeys are a necessary first step to refining and evaluating the potential use of these techniques to treat humans with anxiety disorders.

Project Summary Pertrubed affective processing is a defining symptom of a host of psychiatric disorders, such as depression where it is a primary symptom, and disorders where affective disturbances are secondary symptoms, for example, schizophrenia. Studies of healthy individuals and those with depressed mood implicate a network of areas centering on ventral anterior cingulate cortex (ACC) and amygdala in the control of long-term changes in affect. Despite this understanding, the neural mechanisms that generate and regulate affective experiences are unclear. One reason for this lack of clarity stems from the fact that studies of affect in animals typically only assess instantaneous and short-lived behavioral and neural responses to discrete aversive or positive stimuli. These stimuli typically last less than a second and generally belonging to a small class (e.g., juice) that are not particularly ecologically relevant. To date, no studies in non-human primates have probed the neural basis of affective states that extend over minutes or hours, durations typical of mood states in humans. Such studies would form the foundation for understanding how mood is controlled at the level of brain circuits and single neurons. The objective of this proposal is to determine how the circuit connecting ventral ACC and amygdala functions before, during, and after the induction of either negative or positive affective states in non-human primates. We hypothesize that negative and positive temporally extended affective states will be associated with unique patterns of local and circuit-level neural activity within ventral ACC and amygdala during affect induction and the selection (or regulation) of affective state. We will test our hypothesis by first determining how local and circuit level activity within ventral ACC and amygdala encodes the valence of dynamic, ecologically relevant stimuli that generate unique affective states (Aim 1). We will record both single neurons and local field potentials in both ventral ACC and amygdala and analyze the timing of the neural responses and LFP coherence among these areas to gain circuit-level understanding. Then, using a translationally- relevant affect induction technique that mirrors affect induction paradigms used in humans, we will establish how affect-related neural activity within the ventral ACC-amygdala circuit is altered when temporally extended changes in affective state, both positive and negative, are induced (Aim 2). The induction of affective state will be confirmed using both behavioral (i.e., response selection) and cardiac correlates of parasympathetic and sympathetic activity, measures of affective state that are well validated in humans. Once the neural mechanisms, the specific patterns of neural activity within the ventral ACC-amygdala circuit that control affective states are known, we anticipate being able to either increase or decrease activity in this circuit to influence affective states. This project marks a significant departure from standard approaches to studying affective non-human primates and has the potential to provide vital knowledge for treating mood disorders.

Our understanding of the human brain has rapidly progressed with recent technological advances in both experimental neuroscience and artificial intelligence. Despite this, neither approach in isolation is able to explain how distinct cognitive functions such as learning, remembering, reasoning, and intuition emerge from processes inside the brain. In particular, we lack an understanding of how a relatively small and finite number of brain areas are used to accomplish this large and varied repertoire of cognitive functions. Bridging the fields of neuroscience and artificial intelligence, we seek to discover how the brain tracks the cognitive function that is currently engaged and switches between functions during ongoing behavior. We will apply new computational models, called "multi-purpose recurrent neural networks," to neural activity captured from the brains of different animal models to identify common mechanisms that allow animals to track and switch among cognitive functions. By bridging across experimental species, our findings will reveal fundamental features of brain processing. Further, our integrated approach, which uses a multi-disciplinary team of investigators and industry-academia partnerships, will promote cross-fertilization of knowledge and methods between artificial intelligence and neuroscience. We will also achieve broader societal benefits through collaboration with a graphic artist to develop graphic novel abstracts for widely comprehensible, visually appealing representations of the science for publication.

A relatively small number of neural circuits in the brain are used to accomplish a large and varied repertoire of cognitive functions. Achieving this multi-purpose functionality requires neural circuits to both track the engaged function(s) and switch between them. How such tracking and switching is accomplished remains unclear. Computational models based on neural and behavioral data offer an opportunity to identify these key components of the brain's multipurpose functionality. However, existing models that simulate one task at a time lack the flexibility that underlies the brain's capacity to support many tasks. On the other hand, models that simulate multiple cognitive functions lack biologically realistic tracking and switching mechanisms. Here, we propose a new approach to this problem. We will develop a new class of data-inspired multi-purpose recurrent neural network (RNN) models that incorporate biologically plausible mechanisms to track the task being performed and the transitions between tasks. We will also analyze three distinct experimental datasets using machine learning to identify principles underlying multi-purpose functionality, particularly those that are conserved across species. Specifically, we will characterize multi-purpose functionality at the level of dynamic states. We define dynamic states as time-varying patterns of population activity that allow neural circuits to perform multiple tasks, engage them sequentially, and switch between them as task conditions or contexts change. We hypothesize that multi-purpose RNNs can incorporate dynamic states and simulate the brain's ability to track and switch between tasks, in a manner consistent with experimental data. First, we will develop and characterize data-inspired multi-purpose RNNs with internal state representations that track the engaged cognitive function/task performed. Second, we will incorporate functional and structural modularity into RNNs and analyze them in parallel with multi-region neural recordings. The resulting computational framework will enable us to identify key features of state representations and mechanisms underlying multi-purpose functionality in experimental data. What we discover will lay the foundation for understanding and testing core principles of how neural networks throughout the brain support diverse cognitive functions, enabling key advances in the study of cognition. Further, these robust, scalable multi-purpose RNN models containing internally represented states will better leverage existing large-scale neural data and galvanize new experiments designed to test model predictions. For instance, we expect to identify spatio-temporal markers from ongoing neural dynamics that predict upcoming behavioral transitions. In summary, we will build on recent advances in computer science, specifically, deep learning and other AI/ML-based techniques for neural networks, and bring them to bear on a key problem in neuroscience. Our integrative strategy maximally leverages the rapid pace of advances in computer science toward serving neuroscience and neuroengineering to catalyze new investigations beyond the confines of a lab.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project summary Anhedonia is a defining symptom of mood disorders and anxiety disorders and is characterized by a loss of positive affect from rewarding experiences. Current theories of anhedonia emphasize that it consists of two distinct components: one is related to the expectation of reward, the other to the pleasure from receiving rewards. Understanding how the brain processes expected and received rewards at the level of single neurons is therefore a key challenge for basic neuroscience. Imaging studies indicate that one part of the prefrontal cortex, the subcallosal anterior cingulate cortex (ACC) is active when rewards are expected and is altered in individuals with anhedonia. Corroborating this finding, data from studies of monkeys with lesions of the subcallosal ACC indicate that this area is important for behavior related to the expectation, but not the receipt of rewards. However, no approach to date has been able to provide a circuit-level understanding of how the subcallosal ACC influences reward expectation. This level of understanding is important as deep brain stimulation of subcallosal ACC and nearby white matter pathways alleviates anhedonia in some patients. This intervention is hypothesized to work by altering functional interaction between subcallosal ACC and either amygdala or ventral striatum. Which pathway is more important for controlling behavior related to reward expectation or the requisite activity patterns is unknown. Our goal here is to determine the neural mechanisms engaged in the subcallosal ACC-amygdala-VS circuit when rewards are expected and then received. We hypothesize that the role of the subcallosal ACC is to modulate reward encoding within ventral striatum and amygdala during reward expectation, but not receipt. To test our hypothesis we will use an innovative combination of single-neuron recordings, field potential recordings, electrical stimulation, diffusion imaging methods, and chemogenetics analyzing the timing of reward-related neural responses and LFP coherence among the three sites under normal physiological conditions, when neurons in subcallosal ACC are chronically activated using chemogenetic methods, and when acute electrical stimulation is applied both under normal conditions and when the area is chronically activated. Completing these aims will fundamentally advance our understanding of the neural circuits and activity patterns that control reward-related behavioral and neural activity in primates as well as providing a circuit level understanding of how subcallosal ACC influences expected reward processing. This level of understanding has the potential to inform and help refine pathway- specific interventions for all disorders characterized by a loss pleasure from reward, such as depression as well as schizophrenia.

Project summary Although single neurons occasionally project to a single downstream target, it is more often the case that their axons collateralize and project to multiple distinct anatomical areas. This feature of neuroanatomy has been appreciated for over 100 years and is theorized to be critical to coordinating brain-wide states. Despite this, collateral projections have largely been overlooked in contemporary neuroscience. This is because mapping collateral projections has practically been beyond the reach of empirical investigation, especially in non-human primates where single neurons can project over wide areas. To surmount these issues, our goal here is the comprehensive development of a sequencing-based approach that will allow us to reveal the patterns of connections of single neurons in non-human primates using Multiplexed Analysis of Projections by Sequencing (MAPseq). This approach allows the full collateral projections of potentially thousands of individual neurons to be mapped in a single animal. The first step towards our goal is to validate a sequencing-based connectomic approach in macaque monkeys that has previously been developed and validated in mice (Aim1). Then, once validated we will determine the local and long-range connections of individual neurons in one part of the limbic system in macaques, the amygdala. Our primary focus here is to determine the patterns of collateral projections from amygdala to the frontal cortex (FC) as these have been implicated in the pathophysiology of many psychiatric disorders. With the method for discerning the multiple projection targets of single neurons in the macaque brain in hand we will then compare the patterns that we see in amygdala to those in mice (Aim 2). We hypothesize that through the expansion and differentiation of FC in non-human primates, single amygdala neurons in non-human primates will be many more collateral projections compared to mice. In summary, when successful, our approach has the potential to fully discern the projection profiles of single neurons in non-human primates. This will enable novel insights into the neuroanatomical networks present in non-human primates, provide a powerful new tool for investigating comparative anatomy and aid interpretation of functional studies that target the amygdala in both non-human primates and mice.