Visual Recollection for Non-Declarative Representations

Recollection is a pattern completion process that enables retrieval of arbitrarily associated information following minimal study. These attributes enable recollection to support retrieval of many kinds of mnemonic representations, from highly associative contextual information to very specific low-level representations. However, recollection is typically studied in the context of declarative memory tasks, in which participants exhibit recollection by explicitly reporting on the recollected information. Is it the case that recollection is limited to declarable representations, or is it a more general process that occurs for any representation? Two experiments and a novel analysis technique are presented to answer this question. The results suggest that recollection is not limited to declarable representations. These results argue against theories of recognition memory that restrict the representational input allowed to mnemonic processes; mnemonic processes in general may act on arbitrary representations

Uncovering the Neural and Behavioral Factors That Underlie Changes in Processing Visual Orientation

From moment to moment, the visual environment appears stable; despite prolonged scrutiny, the edge of a desk is not perceived to change. But this apparent stability emerges from perceptual and decisional systems that undergo continuous modulation. In two chapters, I focus on two different kinds of modulation to the processing of visual orientation (i.e., the tilt of an edge). In both chapters, the form of modulation is latent, obscured by standard analyses. To detect those latent changes in perceptual decisions, I develop in this dissertation new statistical tools, at both behavioral and neural levels. In the first chapter, I consider modulations to behavior in an orientation judgment task. Viewing and responding to an orientation causes systematic errors in subsequent responses (Fischer & Whitney, 2014; Gibson & Radner, 1937): the orientation reported on one trial can appear to be biased either toward (attracted to) or away (repelled) from recent orientations. I performed a meta-analysis of the literature on attractive biases, finding a wide variety of effect sizes, with no experimental variable clearly explaining this variation. I show that this variation likely arises from a mixture of attraction to the last response and repulsion from the last stimulus; both forces affect every response, and for any experiment the relative mixture can result in on-average behavior that is only repulsive, only attractive, or neither. I developed two complementary techniques for disentangling this mixture and demonstrate their effectiveness as applied to both a new experiment and previously published experiments. In the second chapter, I developed a technique for identifying how orientation “tuning” functions change with experimental manipulations (e.g., high/low contrast). These tuning functions and their modulation have been observed with single-cell electrophysiology in animals, but there are no non-invasive methods for identifying them in humans. Using functional magnetic resonance imaging, individual voxels exhibit tuning despite arising from the combined responses of hundreds of thousands of neurons. My technique models the distribution of neurons contributing to each voxel and uses model comparison to identify the most likely form of neuromodulation. I validated this technique with a new neuroimaging experiment

Stand-up Coding

Current issues people are coding throug

A Computational Model of Perceptual Deficits in Medial Temporal Lobe Amnesia

Damage to the Medial Temporal Lobe (MTL) impairs declar- ative memory and perception. The Representational-Hierar- chical (RH) Account explains such impairments by assuming that MTL stores conjunctive representations of items and events, and that individuals with MTL damage must rely upon representations of simple visual features in posterior visual cortex. A recent study revealed a surprising anti-perceptual learning effect in MTL-damaged individuals: with exposure to a set of visual stimuli, discrimination performance worsened rather than improved. We expand the RH account to explain this paradox by assuming that visual discrimination is per- formed using a familiarity heuristic. Exposure to a set of highly similar stimuli entails repeated presentation of simple visual features, eventually rendering all feature representations equally (maximally) familiar and hence inutile for solving the task. Since the unique conjunctions represented in MTL do not occur repeatedly, healthy individuals are shielded from this perceptual interference. We simulate this mechanism with a neural network previously used to simulate recognition memory, thereby providing a model that accounts for both mnemonic and perceptual deficits caused by MTL damage us- ing a unified architecture and mechanism

Workshops

Materials for coding workshop

Meetings

Happenings from each weekly meetin

A modeling framework for determining modulation of neural-level tuning from non-invasive human fMRI data

Many neuroscience theories assume that tuning modulation of individual neurons underlies changes in human cognition. However, non-invasive fMRI lacks sufficient resolution to visualize this modulation. To address this limitation, we developed an analysis framework called Inferring Neural Tuning Modulation (INTM) for “peering inside” voxels. Precise specification of neural tuning from the BOLD signal is not possible. Instead, INTM compares theoretical alternatives for the form of neural tuning modulation that might underlie changes in BOLD across experimental conditions. The most likely form is identified via formal model comparison, with assumed parametric Normal tuning functions, followed by a non-parametric check of conclusions. We validated the framework by successfully identifying a well-established form of modulation: visual contrast-induced multiplicative gain for orientation tuned neurons. INTM can be applied to any experimental paradigm testing several points along a continuous feature dimension (e.g., direction of motion, isoluminant hue) across two conditions (e.g., with/without attention, before/after learning)

Experimental Materials

MATLAB + PTB code for running experimen