Matthew Chafee - US grants

DESCRIPTION (provided by applicant): The human brain processes sensory input flexibly to extract the most useful information and generate the most advantageous response given current behavioral strategies and goals. Computational flexibility of this type is often referred to as executive control, particularly when it involves the brain selecting to implement one cognitive process over another in order to determine the best course of action within a given context. We have a limited understanding of how executive control, as such, is mediated by physiological events in cortical neurons. To increase our knowledge of the cellular basis of executive control, I propose to simultaneously record the electrical activity of ensembles of 20-30 individually isolated neurons in prefrontal cortex (area 46) and in posterior parietal cortex (area 7a) of monkeys as they perform a task requiring them to exert executive control over spatial cognition. Specifically, monkeys will assign visual stimuli to alternative spatial categories according to a variable grouping criterion (rule) that we instruct and change on a trial-by-trial basis. In this task, we present a line that serves as a category boundary, and define spatial categories as groups of spatial positions that bear the same spatial relationship to the line - such that, for example, all points to the left of the line comprise one category, and all points to the right another. By shifting and rotating the boundary, we require the brain to flexibly reassign a fixed set of spatial positions to alternative spatial categories in a rule- dependent manner, and this requires the brain to exert executive control over spatial categorization as a cognitive and physiological process. Our objective is to discover how executive control over spatial categorization is implemented at a cellular level, by measuring rule-dependent changes in distributed neural representations of the spatial category to which the brain has assigned a stimulus under a given rule. We will test the hypothesis that rule-dependent changes in category representation will emerge first and be strongest in prefrontal cortex. This will support our hypothesis that prefrontal cortex sits above parietal cortex in a hierarchy of areas mediating executive control over cognitive processing in distributed cortical systems, and provide some of the first detail about the neural mechanisms by which this control is implemented at a cellular level. PUBLIC HEALTH RELEVANCE: The research described in this proposal investigates the neural mechanisms of executive control in prefrontal cortical networks of the nonhuman primate brain. Executive control refers to the capacity of the brain to selectively implement alternative cognitive processes on the basis of behavioral rules, goals or strategies. To understand how executive control is implemented by cortical neurons, we will record the electrical activity of groups of neurons in the prefrontal and posterior parietal cortex of monkeys as they perform a task in which rules govern spatial cognitive processing. Prefrontal and parietal cortexes are anatomically connected and jointly support spatial cognitive function. By discovering how rules modulate patterns of electrical activity associated with cognitive processing in this cortical network, we will be able to discover how executive control is implemented at a cellular level, and further determine whether prefrontal cortex plays a predominant role in mediating executive control. This in turn will help us understand the neural processes that may be disrupted to produce deficits in executive function in human diseases, such as prefrontal stroke, or schizophrenia.

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Abstract
Proposal #1451007
This award is being made jointly by the Neural Systems Cluster in the Division of Integrative and Organismal Systems and the Instrument Development for Biological Research program (IDBR) in the Division of Biological Infrastructure.

How an animal renders a correct decision to select an appropriate behavior to express over another is not well understood at the level of individual brain neurons. Such decision making, however, is not always easy to study or understand because a number of factors can bias behavioral choice in dynamic ways (for example, fluctuating neurohormones or environmental conditions). Even in simpler invertebrate animals, with a reduced number of brain neurons, the operational state of their neural networks is neither easy to follow nor predictable. Thus to solve some of the most pressing questions in the field of neuroscience, technological advances must be made so that the functioning of brains can be studied under more naturalistic conditions. To this end, a team of scientists in engineering, nanoscience, chemistry, computer science, and biology will work together to design, fabricate and test a novel brain recording and stimulation device that, in parallel, will detect fluctuations in neuroactive substances. The team will begin by making prototypes of the device and testing it on leech and insect brains that have fewer neurons, but have well defined correlations between nerve cell activity and behaviors. The team is committed to the interdisciplinary cross-training of graduate and undergraduate students, especially females and underrepresented minorities. The goal of team mentoring is such that students will be well versed in both the biological and engineering aspects of the device. School visits are also planned to engage K-12 students in neuroscience, chemistry and engineering-related demonstrations, encouraging them to participate in STEM fields.

The cross-disciplinary team will fabricate and test a novel multi-electrode integrated ElectroCorticoGraphy (ECoG) device and chemical sensing system having high temporal resolution. Patterned brain activity will be collected in parallel with neuromodulatory substances such as dopamine (DA), serotonin (5-HT) and octopamine (OA). The team's aim is to fabricate a device that will be 2 x 2 mm square, micron-level thin, flexible and biocompatible for extended use, with a minimum of output wires; our future goal will be to develop a completely remote sensing/monitoring capability. Such post-fabrication modification will be conducted at the University of Minnesota's Nano Center. Furthermore, the team aims to identify conserved neural algorithms or rules for context-dependent decision making that span the invertebrates (leech and honey bee) to non-human primates. Fabricated devices will be placed: 1) around dorsal and ventral aspects of the brain of the leech while it makes a decision to crawl or swim (DA and 5-HT-dependent switching); 2) over the Kenyon cells of the honey bee brain during a modified PER (proboscis-extension) learning-and-memory task (potential DA, 5-HT, and OA involvement); and 3) over the Prefrontal Cortex of monkeys during a spatial-cognitive task that will mimic one used for the honey bee (measuring DA changes).

? DESCRIPTION (provided by applicant): The objective of this proposal is to characterize the circuit basis of cognitive control in monkey prefrontal cortex, and to learn how a specific failure of circuit dynamics can lead to errors in cognitive control that are very much like those seen in several human neuropsychiatric diseases, including schizophrenia. To evaluate functional interactions between neurons in circuits, we will combine large scale, single neuron recording in prefrontal and parietal cortex simultaneously while monkeys perform the same cognitive control task used to measure cognitive impairment in neuropsychiatric patients. This will provide many sets of simultaneously recorded neurons (each containing ~40-60 neurons). Prefrontal and parietal cortex are anatomically connected and both contribute to cognitive control. We will then analyze temporal relationships in the spike trains of simultaneously recorded neurons to detect patterns of functional coupling between them. We will infer that neurons are functionally coupled in cases that the timing of their action potentials, or fluctuations in the behavioral information they encode, covary between neurons over time on a rapid time scale. To measure these interactions, we develop and apply two novel analytical approaches that quantify functional coupling between neurons both in terms of spike times and coded information. We then relate patterns of functional coupling between neurons to specific information processing operations required by the task. This provides a basis to relate synaptic function to computation in prefrontal circuits. Next we will block NMDA receptors (NMDAR) in monkeys using a systemically administered drug. This will induce a transient period of cognitive impairment in monkeys, during which time they will make a specific pattern of errors in task performance that is nearly identical to the error pattern of patients with schizophrenia performing the same task. Neural recording during the cognitive impairment will allow us to relate changes in functional coupling to errors in performance. We will test the hypotheses that: (a) computations for cognitive control are mediated by information transfer between neurons in prefrontal circuits, (b) this transmission is mediated by precise control of the timing of action potentials in communicating neurons, (c) action potential timing in communicating neurons is strongly influenced by NMDA receptors, (d) loss of NMDAR synaptic function distorts activity timing relationships between neurons, (e) this causes loss of information transfer between neurons, (f) leading to cognitive control failure. By establishing this chain of events, from synapses through circuits to cognition, we will relate a very specific pattern of cognitive failure seen in neuropsychiatric disease to a causal cortical circuit failure.

PROJECT SUMMARY: PROJECT 1 The purpose of PROJECT 1 is to use nonhuman primates to examine prefrontal local circuit and distributed network impairments associated with state representation dysfunctions of relevance to individuals with psychosis. PROJECT 1 will relate synaptically mediated functional interactions between neurons in prefrontal networks to computations that support state representation processes. In Aim 1, we will quantify functional neural interactions by measuring temporal correlations in the timing of action potentials (?spikes?) imposed by synaptic interactions between the neurons. In Aim 2, we will disrupt those interactions by pharmacologically blocking NMDA receptors (NMDAR), which induces a period of transient cognitive impairment during which monkeys commit similar patterns of behavioral errors during the DPX decision-making task as do people with schizophrenia. We will record neural activity in prefrontal cortex and anatomically connected brain areas (posterior parietal cortex and the dorsal striatum) concurrently during the period of cognitive impairment, while monkeys perform the DPX and Bandit tasks, which allow us to index state estimation, state learning, and state stability processes. We will discover how reducing NMDAR synaptic transmission alters functional interactions between neurons in prefrontal networks, leading to computational failures in state representation processes. To provide a bridge to neural signals that we can record in humans, we will record neural signals that reflect brain activity at the microscale (single neuron action potentials), mesoscale (local field potentials within a cortical area) and macroscale (local field potentials and EEG across cortical areas) from prefrontal cortex and connected structures simultaneously. We will use causal discovery analysis to identify the parameters that can be found with more limited neurophysiological techniques available in humans (for PROJECTS 3 and 4). As PROJECT 4 identifies specific cognitive training regimens that improve state estimation and state stability in individuals with early psychosis, PROJECT 1 will back-translate these paradigms to monkeys to identify training-induced changes in attractor network parameters at the neurophysiological (micro-, meso- and macro- circuit) levels.