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Full-Text Articles in Life Sciences
Cortical Representation Of Learning Social Interactions In Freely Moving Non-Human Primates, Melissa Franch
Cortical Representation Of Learning Social Interactions In Freely Moving Non-Human Primates, Melissa Franch
Dissertations & Theses (Open Access)
The motivation and capacity to be social is necessary for human survival. Successful learning of complex, prosocial behavior stems from the ability to perceive and respond to visual cues, such as the body language and facial expressions, from others in our environment. This dependence on visual information to guide social interaction is especially true for humans and non-human primates. Although recent studies in primate neurophysiology discovered neurons that can encode socially relevant variables, like reward and social actions, the underlying neural mechanisms of learning advanced social concepts, such as cooperation, are not well understood. Further, previous work has identified …
Ultrastructural Correlates Of Axons And Synapses Belonging To Different Circuits In Ferret Primary Visual Cortex, Anjelique Sawh
Ultrastructural Correlates Of Axons And Synapses Belonging To Different Circuits In Ferret Primary Visual Cortex, Anjelique Sawh
Dissertations and Theses
The goal of this study was to determine differences in distinctive layers of mammalian primary visual cortex through analysis of their ultrastructural characteristics. Characterizing brain circuitry using 3-dimensional reconstruction of electron microscopy images, and subsequent ultrastructural analysis of axonal populations provides us with a better understanding of the connectivity of the neural circuits. By quantifying ultrastructural differences in axonal processes such as synaptic densities, types of synapses and their post-synaptic densities (PSDs), mitochondrial volumes, synaptic vesicle aggregates, dendritic targets, and bouton volumes, we aimed to understand whether differences in anatomical specializations among different cortical layers could underlie differences in function …
Effect Of Noise On Mutually Inhibiting Pyramidal Cells In Visual Cortex: Foundation Of Stochasticity In Bi-Stable Perception, Naoki Kogo, Felix Kern, Thomas Nowotny, Raymond Van Ee, Richard Van Wezel, Takeshi Aihara
Effect Of Noise On Mutually Inhibiting Pyramidal Cells In Visual Cortex: Foundation Of Stochasticity In Bi-Stable Perception, Naoki Kogo, Felix Kern, Thomas Nowotny, Raymond Van Ee, Richard Van Wezel, Takeshi Aihara
MODVIS Workshop
Bi-stable perception has been an important tool to investigate how visual input is interpreted and how it reaches consciousness. To explain the mechanisms of this phenomenon, it has been assumed that a mutual inhibition circuit plays a key role. It is possible that this circuit functions to resolve ambiguity of input image by quickly shifting the balance of competing signals in response to conflicting features. Recently we established an in vitro neural recording system combined with computerized connections mediated by model neurons and synapses (“dynamic clamp” system). With this system, mutual inhibition circuit between two pyramidal cells from primary visual …
The Impact Of Cortical State On Neural Coding And Behavior, Charles Beaman
The Impact Of Cortical State On Neural Coding And Behavior, Charles Beaman
Dissertations & Theses (Open Access)
The brain is never truly silent – up to 80% of its energy budget is expended during ongoing activity in the absence of sensory input. Previous research has shown that sensory neurons are not exclusively influenced by external stimuli but rather reflect interactions between sensory inputs and the ongoing activity of the brain. Yet, whether fluctuations in the state of cortical networks influence sensory coding in neural circuits and the behavior of the animal are unknown. To shed light on this issue, we conducted multi-unit electrophysiology experiments in visual areas V1 and V4 of behaving monkeys. First, we studied the …
Characterizing Receptive Field Selectivity In Area V2, Corey M. Ziemba, Robbe Lt Goris, J Anthony Movshon, Eero P. Simoncelli
Characterizing Receptive Field Selectivity In Area V2, Corey M. Ziemba, Robbe Lt Goris, J Anthony Movshon, Eero P. Simoncelli
MODVIS Workshop
The computations performed by neurons in area V1 are reasonably well understood, but computation in subsequent areas such as V2 have been more difficult to characterize. When stimulated with visual stimuli traditionally used to investigate V1, such as sinusoidal gratings, V2 neurons exhibit similar selectivity (but with larger receptive fields, and weaker responses) relative to V1 neurons. However, we find that V2 responses to synthetic stimuli designed to produce naturalistic patterns of joint activity in a model V1 population are more vigorous than responses to control stimuli that lacked this naturalistic structure (Freeman, et. al. 2013). Armed with this signature …
Effects Of Resting State On Perceptual Learning, Sarah Eagleman Ph.D.
Effects Of Resting State On Perceptual Learning, Sarah Eagleman Ph.D.
Dissertations & Theses (Open Access)
Psychophysical experiments in humans have demonstrated that improvements in perceptual learning tasks occur following daytime rests. The neural correlates of how rest influences subsequent sensory processing during these tasks remain unclear. One possible neural mechanism that may underlie this behavioral improvement is reactivation. Previously evoked network activity reoccurs – reactivates - in the absence of further stimulation. Reactivation was initially discovered in the hippocampus but has now been found in several brain areas including cortex. This phenomenon has been implicated as a general mechanism by which neural networks learn and store sensory information. However, whether reactivation occurs in areas relevant …
Variance Predicts Salience In Central Sensory Processing, Ann M. Hermundstad, John J. Briguglio, Mary M. Conte, Jonathan D. Victor, Vijay Balasubramanian, Gašper Tkačik
Variance Predicts Salience In Central Sensory Processing, Ann M. Hermundstad, John J. Briguglio, Mary M. Conte, Jonathan D. Victor, Vijay Balasubramanian, Gašper Tkačik
Publications and Research
Information processing in the sensory periphery is shaped by natural stimulus statistics. In the periphery, a transmission bottleneck constrains performance; thus efficient coding implies that natural signal components with a predictably wider range should be compressed. In a different regime—when sampling limitations constrain performance—efficient coding implies that more resources should be allocated to informative features that are more variable. We propose that this regime is relevant for sensory cortex when it extracts complex features from limited numbers of sensory samples. To test this prediction, we use central visual processing as a model: we show that visual sensitivity for local multi-point …