Incorporating Biologically Realistic Neuron Models into the NEF

Theoretical neuroscience is fundamentally concerned with the relationship between biological mechanisms, information processing, and cognitive abilities, yet current models often lack either biophysical realism or cognitive functionality. This thesis aims to partially fill this gap by incorporating geometrically and electrophisologically accurate models of individual neurons into the Neural Engineering Framework (NEF). After discussing the relationship between biologically complex neurons and the core principles/assumptions of the NEF, a neural model of working memory is introduced to demonstrate the NEF's existing capacity to capture biological and cognitive features. This model successfully performs the delayed response task and provides a medium for simulating mental disorders (ADHD) and its pharmacological treatments. Two methods of integrating more biologically sophisticated NEURON models into the NEF are subsequently explored and their ability to implement networks of varying complexity are assessed: the trained synaptic weights do realize the core NEF principles, though several errors remain unresolved. Returning to the working memory model, it is shown that bioneurons can perform the requisite computations in context, and that simulating the biophysical effects of pharmacological compounds produces results consistent with electrophysiological and behavioral data from monkeys

Dynamical Systems in Spiking Neuromorphic Hardware

Dynamical systems are universal computers. They can perceive stimuli, remember, learn from feedback, plan sequences of actions, and coordinate complex behavioural responses. The Neural Engineering Framework (NEF) provides a general recipe to formulate models of such systems as coupled sets of nonlinear differential equations and compile them onto recurrently connected spiking neural networks – akin to a programming language for spiking models of computation. The Nengo software ecosystem supports the NEF and compiles such models onto neuromorphic hardware. In this thesis, we analyze the theory driving the success of the NEF, and expose several core principles underpinning its correctness, scalability, completeness, robustness, and extensibility. We also derive novel theoretical extensions to the framework that enable it to far more effectively leverage a wide variety of dynamics in digital hardware, and to exploit the device-level physics in analog hardware. At the same time, we propose a novel set of spiking algorithms that recruit an optimal nonlinear encoding of time, which we call the Delay Network (DN). Backpropagation across stacked layers of DNs dramatically outperforms stacked Long Short-Term Memory (LSTM) networks—a state-of-the-art deep recurrent architecture—in accuracy and training time, on a continuous-time memory task, and a chaotic time-series prediction benchmark. The basic component of this network is shown to function on state-of-the-art spiking neuromorphic hardware including Braindrop and Loihi. This implementation approaches the energy-efficiency of the human brain in the former case, and the precision of conventional computation in the latter case

The role of the medial prefrontal cortex in delay discounting

Indiana University-Purdue University Indianapolis (IUPUI)Increased delay discounting (DD) has been associated with and is theorized to contribute to alcoholism and substance abuse. It is also been associated with numerous other mental disorders and is believed to be a trans-disease process (i.e., a process that occurs in and contributes to multiple different pathologies). Consequently insights gained from studying DD are likely to apply to many different diseases. Studies on the neurobiological underpinnings of DD have two main interpretations. The first interpretation is that two different neurobehavioral systems exist, one favoring delayed rewards (executive system) and one favoring immediate rewards (impulsive system), and the system with the greater relative activation determines choice made by an individual. Alternatively, a single valuation system may exist. This system integrates different information about outcomes and generates a value signal that then guides decision making. Preclinical investigations have steered clear of these two different interpretations and rather focused on the role of individual structures in DD. One such structure, the rat mPFC, may generate an outcome representation of delayed rewards that is critically involved in attributing value to delayed rewards. Moreover, there is evidence indicating the rat mPFC may correspond to the primate dlPFC, an executive system structure. The current body of work set about testing the hypotheses that the mPFC is necessary for attributing value to delayed rewards and that decreasing the activity in an executive system area, and thus the executive system, shifts inter-temporal preference towards immediate rewards. To this end the rat mPFC was inactivated using an hM4Di inhibitory designer receptor exclusively activated by designer drugs (DREADD; experiment 1) or microinjections of tetrodotoxin (TTX; experiment 2) while animals completed an adjusting amount DD task. Activation of the hM4Di inhibitory DREADD receptor caused a decrease in DD, opposite of what was predicted. Electrophysiological recordings revealed a subpopulation of neurons actually increased their firing in response to hM4Di receptor activation, potentially explaining the unpredicted results. Microinjections of TTX to completely silence neural activity in the mPFC failed to produce a change in DD. Together both results indicate that mPFC activity is capable of manipulating but is not necessary for DD and the attribution of value to the delayed reward. Consequently, a secondary role for the rat mPFC in DD is proposed in line with single valuation system accounts of DD. Further investigations determining the primary structures responsible for sustaining delayed reward valuation and how manipulating the mPFC may be a means to decrease DD are warranted, and continued investigation that delineates the neurobiological processes of delayed reward valuation may provide valuable insight to both addiction and psychopathology

Trifling matters: differential regulation of feedforward and feedback interneurons of the dentate gyrus by release of endogenous norepinephrine

Norepinephrine is known to play an important role in hippocampal function. Norepinephrine is required for long-term potentiation in dentate gyrus, and norepinephrine blockade or depletion can interfere with acquisition and retrieval in hippocampal dependent tasks. While gross measures of hippocampal function such as evoked potentials demonstrate plastic changes under the influence of norepinephrine, single unit studies to date report suppression of principle cell firing and increased firing rates for inhibitory interneurons. Such changes should reflect an increase in inhibition and would predict a decrease in plasticity. -- In this thesis I examine the effect of "natural" synaptic release of norepinephrine on spontaneous firing rates of cells in dentate gyrus, with concomitant electroencephalographic recording. Physiologically identified interneurons are classified as either feedforward or feedback depending on whether they were activated prior to, or after, the perforant path evoked population spike. Principle cells are identified by their characteristic firing properties and a firing latency within the window of the performant path evoked population spike. -- In this study feedforward interneurons virtually cease firing in response to synaptic release of norepinephrine, producing a period of disinhibition which lasts several minutes. Simultaneously, cells identified as principle cells increase their firing rates. Feedback interneurons demonstrated a mixed profile with some cells increasing their firing rates and others decreasing their firing rates. -- Fast Fourier analysis of the electroencephalographic recordings revealed a increase in relative power in the theta band as reported previously, together with a decrease in overall power and a decrease in relative power of the gamma band. These data are compared to previous studies of noradrenergic effects on single unit, evoked potential, and electroencephalography measures in the literature. The results are also compared to existing models of plasticity such as long-term potentiation and gamma power regulated acquisition and recall of hippocampal representations. Finally a new framework is proposed as to how norepinephrine may play a role in plasticity by allowing new information to be bound to mature hippocampal representations

Neurochemical substrates linked to impulsive and compulsive phenotypes in addiction: A preclinical perspective.

Funder: Institute for Neuroscience at Cambridge UniversityFunder: GlaxoSmithKline; Id: http://dx.doi.org/10.13039/100004330Funder: Boehringer Ingelheim Pharma GmbHDrug compulsion manifests in some but not all individuals and implicates multifaceted processes including failures in top-down cognitive control as drivers for the hazardous pursuit of drug use in some individuals. As a closely related construct, impulsivity encompasses rash or risky behaviour without foresight and underlies most forms of drug taking behaviour, including drug use during adverse emotional states (i.e., negative urgency). While impulsive behavioural dimensions emerge from drug-induced brain plasticity, burgeoning evidence suggests that impulsivity also predates the emergence of compulsive drug use. Although the neural substrates underlying the apparently causal relationship between trait impulsivity and drug compulsion are poorly understood, significant advances have come from the interrogation of defined limbic cortico-striatal circuits involved in motivated behaviour and response inhibition, together with chemical neuromodulatory influences from the ascending neurotransmitter systems. We review what is presently known about the neurochemical mediation of impulsivity, in its various forms, and ask whether commonalities exist in the neurochemistry of compulsive drug-motivated behaviours that might explain individual risk for addiction