Biology subjects

Sreenivasan, K. K.

Publications and source records attributed to Sreenivasan, K. K..

3 recordsLinked to original sources

bioRxiv2021

Working Memory Representations in Visual Cortex Mediate the Effects of Distraction

Although the contents of working memory (WM) can be decoded from activity in visual cortex, these representations may play a limited role if they are not robust to distraction. Here, we used model-based fMRI to estimate the impact that a distracting visual task had on WM representations in several visual field maps in visual and frontoparietal association cortex. Distraction caused the fidelity of WM representations in all maps to briefly dip when both the memorandum and distractor were jointly encoded by the population activities. Moreover, distraction induced small biases in memory errors which were predicted by biases in neural decoding in early visual cortex, but not other regions. Although distraction briefly disrupts WM representations, the widespread redundancy with which WM information is encoded may protect against catastrophic loss. In early visual cortex, nonetheless, the neural representation of information in WM and behavioral performance were intertwined, solidifying its importance in memory.

neuroscience↗

bioRxiv2020

Using a betting game to reveal the rich nature of visual working memories

When we ask people to hold a color in working memory, what do they store? Do they remember colors as point estimates (e.g. a particular shade of red) or are memory representations richer, such as uncertainty distributions over feature space? We developed a novel paradigm (a betting game) to measure the nature of working memory representations. Participants were shown a set of colored circles and, after a brief memory delay, asked about one of the objects. Rather than reporting a single color, participants placed multiple bets to create distributions in color space. The dispersion of bets was correlated with performance, indicating that participants internal uncertainty guided bet placement. Furthermore, relative to the first response, memory performance improved when averaging across multiple bets, showing that memories contain more information than can be conveyed in a single response. Finally, information about the item in memory was present in subsequent responses even when the first response would generally be classified as a guess or report of an incorrect item, suggesting that such failures are not all-or-none. Thus, memory representations are more than noisy point estimates; they are surprisingly rich and probabilistic.

neuroscience↗

bioRxiv2020

Spatially-specific working memory activity in the human superior colliculus

Theoretically, working memory (WM) representations are encoded by population activity of neurons with distributed tuning across the stored feature. Here, we leverage computational neuroimaging approaches to map the topographic organization of human superior colliculus (SC) and model how population activity in SC encodes WM representations. We first modeled receptive field properties of voxels in SC, deriving a detailed topographic organization resembling that of the primate SC. Neural activity within male and female human SC persisted throughout a retention interval of several types of modified memory-guided saccade tasks. Assuming an underlying neural architecture of the SC based on its retinotopic organization, we used an encoding model to show that the pattern of activity in human SC represents locations stored in WM. Our tasks and models allowed us to dissociate the locations of visual targets and the motor metrics of memory-guided saccades from the spatial locations stored in WM, thus confirming that human SC represents true WM information. These data have several important implications. They add the SC to a growing number of cortical and subcortical brain areas that form distributed networks supporting WM functions. Moreover, they specify a clear neural mechanism by which topographically organized SC encodes WM representations. Significance StatementUsing computational neuroimaging approaches, we mapped the topographic organization of human superior colliculus (SC) and modeled how population activity in SC encodes working memory (WM) representations, rather than simpler visual or motor properties that have been traditionally associated with the laminar maps in the primate SC. Together, these data both position the human SC into a distributed network of brain areas supporting WM and elucidate the neural mechanisms by which the SC supports WM.

neuroscience↗