Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2010. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 201-211). / An infant reaches out for her new toy, struggling day after day to simply grasp her fingers around it. A few years later, she hits a tennis serve, perfect in the timing of its intricately choreographed movements. How does a young brain learn to use the muscles it controls, to properly coordinate motor gestures into complex behavioral sequences? To a surprising extent, for many advanced vertebrate behaviors this knowledge is neither innately programmed nor acquired via deterministic developmental rules, but must be learned through trial-and-error exploration. This thesis is an investigation of the neural mechanisms that underlie the production and maturation of one exploratory behavior - the babbling, or subsong, of a juvenile zebra finch. Using lesions and inactivations of brain areas in the song system, I identified neural circuits involved in the production of subsong. Remarkably, subsong did not require the high vocal center (HVC) - a premotor structure long known as the key region for controlling singing in adult birds - but did require the lateral magnocellular nucleus of the nidopallium (LMAN) - the output region of basal ganglia-forebrain circuitry previously considered a modulatory area. Recordings in LMAN during subsong revealed premotor activity related to the vocal output on a fast timescale. These results show, for the first time, the existence of a specialized circuit for driving exploratory motor control, distinct from the one that produces the adult behavior. The existence of two neural pathways for singing has raised the question of how motor control is transferred from one pathway to another and, in particular, how the control of song timing develops in these pathways. I found that early singing can be decomposed into mechanistically distinct "modes" of syllable and silent gap timing - randomly-timed modes that are LMAN-dependent and developmentally-acquired, consistently-timed modes that are HVCdependent. Combining acoustic analysis with respiratory measurements, I found that the consistently-timed mode in gap durations is formed by brief inspiratory pressure pulses, indicating an early involvement of HVC in coordinating singing with respiration. Using mild localized cooling - a manipulation that slows down biophysical processes in a targeted brain area - I found that the circuit dynamics intrinsic to HVC and LMAN are actively involved in controlling the timescales of distinct behavioral modes. In summary, this work demonstrates the existence of two motor circuits in the song system. These circuits are specialized for the generation of distinct types of neural dynamics - random exploratory dynamics, which are dominant early in life, and stereotyped sequential dynamics, which become dominant during development. Characterization of behaviorally-relevant dynamics produced by neural circuits may be a general framework for understanding motor control and learning. / by Dmitriy Aronov. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1991. / Includes bibliographical references. / by Jong-On Hahm. / Ph.D.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1992. / Includes bibliographical references. / by Robert Paul Dolan. / Ph.D.

Thesis: Ph. D. in Neuroscience, Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references. / The amygdala is a structure well known for its role in fear and reward learning, but how these mechanisms are used for decision-making is not well understood. Decision-making involves the rapid updating of cue associations as well as the encoding of a value currency, both processes in which the amygdala has been implicated. In this thesis I develop a strategy to study value-guided decision making in rodents using an olfactory binary choice task. Using a logistic regression model, I show that the value of expected rewards is a strong influence on choice, and can bias perceptual decisions. In addition, I show that decisions are influenced by events in the near past, and a specific bias towards correct choices in the near past can be detected using this analysis. Using genetic targeting of a sub-population of amygdala neurons, I show that this population is required for the rapid learning of an olfactory decision making task. Using in-vivo calcium imaging of this population I show that these neurons are active during the inter-trial interval and modulated by choice history, suggesting a mechanism by which choice history can influence current decisions. / by Kean Jaime-Bustamante. / Ph. D. in Neuroscience

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2009. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 100-105). / In this thesis I present new contributions to the fields of neuroscience and computer science. The neuroscientific contribution is a new technique for automatically reconstructing complete neural networks from densely stained 3d electron micrographs of brain tissue. The computer science contribution is a new machine learning method for image segmentation and the development of a new theory for supervised hierarchy learning based on ultrametric distance functions. It is well-known that the connectivity of neural networks in the brain can have a dramatic influence on their computational function . However, our understanding of the complete connectivity of neural circuits has been quite impoverished due to our inability to image all the connections between all the neurons in biological network. Connectomics is an emerging field in neuroscience that aims to revolutionize our understanding of the function of neural circuits by imaging and reconstructing entire neural circuits. In this thesis, I present an automated method for reconstructing neural circuitry from 3d electron micrographs of brain tissue. The cortical column, a basic unit of cortical microcircuitry, will produce a single 3d electron micrograph measuring many 100s terabytes once imaged and contain neurites from well over 100,000 different neurons. It is estimated that tracing the neurites in such a volume by hand would take several thousand human years. Automated circuit tracing methods are thus crucial to the success of connectomics. In computer vision, the circuit reconstruction problem of tracing neurites is known as image segmentation. Segmentation is a grouping problem where image pixels belonging to the same neurite are clustered together. While many algorithms for image segmentation exist, few have parameters that can be optimized using groundtruth data to extract maximum performance on a specialized dataset. In this thesis, I present the first machine learning method to directly minimize an image segmentation error. It is based the theory of ultrametric distances and hierarchical clustering. Image segmentation is posed as the problem of learning and classifying ultrametric distances between image pixels. Ultrametric distances on point set have the special property that / (cont.) they correspond exactly to hierarchical clustering of the set. This special property implies hierarchical clustering can be learned by directly learning ultrametric distances. In this thesis, I develop convolutional networks as a machine learning architecture for image processing. I use this powerful pattern recognition architecture with many tens of thousands of free parameters for predicting affinity graphs and detecting object boundaries in images. When trained using ultrametric learning, the convolutional network based algorithm yields an extremely efficient linear-time segmentation algorithm. In this thesis, I develop methods for assessing the quality of image segmentations produced by manual human efforts or by automated computer algorithms. These methods are crucial for comparing the performance of different segmentation methods and is used through out the thesis to demonstrate the quality of the reconstructions generated by the methods in this thesis. / by Srinivas C. Turaga. / Ph.D.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2002. / Includes bibliographical references. / While it is well established that the rodent hippocampus plays a crucial role in the formation and retrieval of spatial memories, the neural mechanisms underlying this process have not been completely characterized. In this thesis I have combined large-scale recordings from multiple single cells within the hippocampus of behaving rodents with pharmacological and genetic manipulations of hippocampal function in order to investigate how the cellular and network properties of the hippocampus contribute to memory storage and retrieval. In Part I of this thesis, extracellular recordings are used to monitor systematic changes in the cellular properties of hippocampal pyramidal cells in vivo. These studies demonstrate that the biophysical characteristics of CA1 pyramidal cells undergo both short term (activity-dependent) and long-term (experience-dependent) modulations during behavior. Short tem changes in the biophysical state of hippocampal pyramidal cells interact with changes in synaptic input to determine the probability with which CA1 pyramidal cells generate single spikes or bursts of action potentials and may play an important role in influencing where and when mechanisms of plasticity are engaged during behavior (Chapters: 3-4). Longer term changes include: 1) input specific reductions in amplitude attenuation - consistent with an increase in dendritic excitability (Chapter 4), 2) increases in the rate of spike repolarization (Chapter 5), 3) reductions in spike count variability within bursts (Chapter 5), and modulations in burst length both during behavior and sleep (Chapter5). / (cont.) Together, these results provide novel insights into how changes in the intrinsic properties of hippocampal pyramidal cells are related to the process of memory formation. In Part II of this thesis, hippocampal recordings are used to characterize a novel genetically engineered mouse line in which NMDA receptors are specifically deleted from pyramidal cells within the CA3 region of the adult hippocampus (CA3-NR1 KO; Nakazawa et.al., 2001). Results indicate that while spatial information is relatively preserved within the hippocampus of CA3-NR1 mice, CA1 place cell activity within mutant animals is more sensitive to perturbations of the sensory environment relative to place cell activity in control animals. Together with behavioral data, these results provide the first direct evidence for CA3 NMDA receptor involvement in associative memory recall. / by Michael C. Quirk. / Ph.D.

Thesis: Ph. D. in Neuroscience, Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references. / As we observe and listen to other people, we interpret their actions in terms of a rich causal structure, driven by underlying mental states and dispositional traits. The ability to rapidly extract abstract social information from perceptual input, termed social perception, is critical to human social behavior. This thesis investigates the cognitive architecture of social perception by studying the functional organization and development of brain regions implicated in this process. In the first Chapters 2-4, I focus on a region that has been strongly implicated in social perception: the superior temporal sulcus (STS). In Chapter 2, I assess the overall functional organization of STS responses to different types of social stimuli, using fMRI. I find that the STS comprises a number of functionally specific subregions that process certain types of social information, such as body movement, vocal sounds, linguistic input, and abstract mental states, suggesting a functional division of labor in social perception. I also identify a multimodal region that responds both to face movement and to vocal sounds. Chapters 3-4 further explore the properties of this region, termed the fSTS. Analyzing spatial patterns of response in this region to different types of face movement, I find evidence that fSTS contains a parts-based representation of perceived face movement type, suggesting a representation more tied to face movement kinematics than implied mental state, but which generalizes across low-level visual properties (Chapter 3). Next, assessing responses to a range of naturalistic face movements and vocal sounds, I find that the fSTS responds strongly to virtually any face movement or vocal sound, irrespective of social relevance or speech content (Chapter 4). However, patterns of response in this region distinguish more and less socially relevant inputs, in a manner that generalizes across facial and vocal stimuli. Taken together, these results point to the fSTS as a mid-level region in social perceptual inference, with representations that are still tied to perceptual features, but begin to integrate visual and auditory inputs and make explicit high-level social distinctions. Lastly, in Chapter 5 I address a broader, related question: how do functionally specific brain regions such as the fSTS develop? To address this question, I develop methods for fMRI in awake infants viewing visual stimuli. I find that regions preferring specific visual categories (faces and scenes) exist by 4-6 months of age, but that responses in these regions are less selective than in adults. This suggests that functionally specific brain regions exist in some form at an early age, but that they become increasingly specialized throughout development. / by Ben Deen. / Ph. D. in Neuroscience

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2006. / Includes bibliographical references (p. 88-101). / Regulation of gene transcription by neuronal activity is thought to be key to the translation of sensory experience into long-term changes in synaptic structure and function. Here we show that cgp15, a gene encoding an extracellular signaling molecule that promotes dendritic and axonal growth and synaptic maturation, is regulated in the somatosensory cortex by sensory experience capable of inducing cortical plasticity. Using in situ hybridization, we monitored cgp15 expression in 4-week-old mouse barrel cortex after trimming all whiskers except D1. We found that cpgl5 expression is depressed in the deprived barrels and enhanced in the barrel column corresponding to the spared D1 whisker. Induction of cpgl5 expression is significantly diminished in adolescent as well as adult CREB knockout mice. cgp15 spatio-temporal expression pattern and its regulation by CREB are consistent with a role in experience-dependent plasticity of cortical circuits. Our results suggest that local structural and/or synaptic changes may be a mechanism by which the adult cortex can adapt to peripheral manipulations. The balance between proliferation and apoptosis is critical for proper development of the nervous system. / (cont.) Yet, little is known about molecules that regulate apoptosis of proliferative neurons. Here we identify a soluble, secreted form of CPG15 expressed in embryonic rat brain regions undergoing rapid proliferation and apoptosis, and show that it protects cultured cortical neurons from apoptosis by preventing activation of caspase 3. Using a lentivirus-delivered small hairpin RNA, we demonstrate that endogenous CPG15 is essential for the survival of undifferentiated cortical progenitors in vitro and in vivo. We further show that CPG15 overexpression in vivo expands the progenitor pool by preventing apoptosis, resulting in an enlarged, indented cortical plate and cellular heterotopias within the ventricular zone, similar to the phenotypes of mutant mice with supernumerary forebrain progenitors. CPG15 expressed during mammalian forebrain morphogenesis may help balance neuronal number by countering apoptosis in specific neuroblasts subpopulations, thus influencing final brain size and shape. / by Corey Harwell. / Ph.D.

Thesis: Ph. D. in Neuroscience, Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2016. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 126-170). / The ability to engage in appropriate social interaction is a critical component of daily life that requires integration of multiple neural processes and can be perturbed in numerous psychiatric diseases (Adolphs et al. 2003; Frith et al. 2008). One approach to begin understanding how the brain supports a complex array of social behaviors is to study innate, evolutionarily conserved social behaviors. Observational fear learning is one such social behavior that offers a distinct advantage for survival and is thus highly conserved across various species including rodents (Heyes et al. 1990; Kavaliers et al. 2001), monkeys (Mineka et al. 1984), and humans (Olsson et al. 2007). The data presented in this thesis combines in vivo electrophysiology, optogenetics, and rodent behavior in order to answer a number of questions about the role of the anterior cingulate cortex (ACC) and the basolateral amygdala (BLA) in observational fear learning. We show that both the ACC and the BLA contain neurons that show conditioned responses to the cue and are therefore neural correlates of observational fear learning. We photo-identify neurons within the ACC-BLA network and show that the ACC-BLA network has an enhanced representation of cue information when compared to out of network neurons. In addition, we show that ACC neurons that project to the BLA encode cue information. Next, we inhibit ACC input to the BLA during the cue and show that this impairs observational learning but not classical fear conditioning. Further, inhibition of ACC input to the BLA changes the cue response of a subset of BLA neurons. Lastly, we show that ACC input to the BLA is necessary for normal social interaction. Together, this data provides the first circuit level analysis of observational fear learning. It establishes that the transfer of cue information from the ACC to the BLA plays a causal role in enabling observational learning and that this same input is needed for general social behavior. / by Stephen Azariah Alisop. / Ph. D. in Neuroscience

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 1990. / Includes bibliographical references (p. 217-233). / by Paul Bloom. / Ph.D.