Biology subjects

Sprague, T. C.

Publications and source records attributed to Sprague, T. C..

14 recordsLinked to original sources

bioRxiv2026

Neural priority maps encode behavioral relevance independently across multiple attended locations

Retinotopic cortical regions encode both the physical salience and behavioral relevance of visual stimuli, suggesting that these areas support neural "priority maps" of the visual field. These maps, which are instantiated as distributed neural codes across visual, parietal, and frontal areas, guide covert attention and overt motor plans. Previous work has characterized how these maps encode the task relevance of a single covertly-attended visual stimulus among multiple stimuli. However, it remains unknown how relevance-related modulations scale with the number of task-relevant locations. If modulations reflect limitations in attention-related enhancements of relevant neural populations, attending to more stimuli should reduce the magnitude of modulations. Instead, if relevance-related modulations reflect the selection of task-relevant populations by long-range inputs to optimize coding for further processing, each relevant stimulus location would be modulated by an equivalent amount, independent of other stimuli. We collected functional magnetic resonance imaging (fMRI) data while participants performed a demanding covert attention task requiring they monitor zero, one, or two peripheral task-relevant stimuli. Using a spatial inverted encoding model, we reconstructed neural priority maps from activation patterns across retinotopic cortex. Strikingly, relevance-related enhancement at each attended location was equivalent whether one or two locations were cued, with no evidence for attenuation when multiple stimuli were relevant. Moreover, task-related modulations were spatially focal and disjoint, localized to each cued stimulus location. These results suggest a model whereby behavioral relevance is encoded categorically in neural priority maps: BOLD signal from neural populations at each task-relevant location are equivalently and independent enhanced regardless of how many other locations are concurrently relevant. This modulatory profile reveals a relevance map that signals which populations require selective augmentation to guide decision-making through the plethora of local neural computations associated with covert attention, with performance limitations arising at later processing stages rather than within early sensory representations.

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bioRxiv2025

Attention Modulates Stimulus Representations in Neural Feature Dimension Maps

Computational theories posit that attention is guided by a combination of spatial maps for individual features that can be dynamically weighted according to task goals. Consistent with this framework, when a stimulus contains several features, attending to one or another feature results in stronger fMRI responses in regions preferring the attended feature. We hypothesized that multivariate activation patterns across feature-responsive cortical regions form spatial feature dimension maps, which combine to guide attentional priority. We tested this prediction by reconstructing spatial maps from fMRI activation patterns across retinotopic regions of visual cortex while participants performed a feature-selective attention task. Participants viewed a peripheral visual stimulus at a random location which always contained moving colored dots. On each trial, participants were precued to report the predominant direction of motion or color of the stimulus, or to attend fixation. Stimulus representations in reconstructed maps based on a spatial inverted encoding model were selectively enhanced in color-selective regions when color was attended, and in motion-selective regions when motion was attended. While enhancement was localized to the stimulus position in color-selective regions, modulations in motion-selective regions was consistent with a more global enhancement when motion was task relevant. These results suggest feature-selective cortical regions support neural feature dimension maps: spatial maps of different visual features that are dynamically reweighted based on task demands to guide visual behavior to the most relevant locations based on important features

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bioRxiv2024

Neural mechanisms of resource allocation in working memory

To mitigate capacity limits of working memory, people allocate resources according to an items relevance. However, the neural mechanisms supporting such a critical operation remain unknown. Here, we developed computational neuroimaging methods to decode and demix neural responses associated with multiple items in working memory with different priorities. In striate and extrastriate cortex, the gain of neural responses tracked the priority of memoranda. Higher-priority memoranda were decoded with smaller error and lower uncertainty. Moreover, these neural differences predicted behavioral differences in memory prioritization. Remarkably, trialwise variability in the magnitude of delay activity in frontal cortex predicted differences in decoded precision between low and high-priority items in visual cortex. These results suggest a model in which feedback signals broadcast from frontal cortex sculpt the gain of memory representations in visual cortex according to behavioral relevance, thus, identifying a neural mechanism for resource allocation.

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bioRxiv2024

Prioritizing of working memory resources depends onprefrontal cortex

How the prefrontal cortex contributes to working memory remains controversial, as theories differ in their emphasis on its role in storing memories versus controlling their content. To adjudicate between these competing ideas, we tested how perturbations to the human (both sexes) lateral prefrontal cortex impact the storage and control aspects of working memory during a task that requires human subjects to allocate resources to memory items based on their behavioral priority. Our computational model made a strong prediction that disruption of this control process would counterintuitively improve memory for low-priority items. Remarkably, transcranial magnetic stimulation of retinotopically-defined superior precentral sulcus, but not intraparietal sulcus, unbalanced the prioritization of resources, improving memory for low-priority items as predicted by the model. Therefore, these results provide direct causal support for models in which the prefrontal cortex controls the allocation of resources that support working memory, rather than simply storing the features of memoranda. SIGNIFICANCE STATEMENTAlthough higher-order cognition depends on working memory, the resources that support our memory are severely limited in capacity. To mitigate this limitation, we allocate memory resources according to the behavioral relevance of items. Nonetheless, the neural basis of these abilities remain unclear. Here, we tested the hypothesis that a region in lateral prefrontal cortex controls prioritization in working memory. Indeed, perturbing this region with transcranial magnetic stimulation disrupted the prioritization of working memory resources. Our results provide causal evidence for the hypothesis that prefrontal cortex primarily controls the allocation of memory resources, rather than storing the contents of working memory.

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bioRxiv2023

Feature-specific salience maps in human cortex

Priority maps are representations of visual space that determine the relative importance of scene locations. Computational theories suggest that priority maps identify salient locations based on individual feature dimensions (e.g., color, motion), which are integrated into an aggregate priority map. While widely accepted, a core assumption of this framework--the existence of independent feature dimension maps in visual cortex--remains untested. Here, we tested the hypothesis that feature-selective retinotopic regions in human cortex act as neural feature dimension maps, indexing salience based on their preferred feature. We used fMRI activation patterns to reconstruct spatial maps while participants viewed stimuli with salient regions defined by color or motion direction. Reconstructed spatial maps selectively represented salient locations defined by each regions preferred feature. These findings identify spatially organized feature dimension maps that characterize the salience of scene locations based on a specific visual feature, confirming a key prediction of priority map theory.

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bioRxiv2021

Behavioral prioritization enhances working memory precision and neural population gain

Humans allocate visual working memory (WM) resource according to behavioral relevance, resulting in more precise memories for more important items. Theoretically, items may be maintained by feature-tuned neural populations, where the relative gain of the populations encoding each item determines precision. To test this hypothesis, we compared the amplitudes of delay-period activity in the different parts of retinotopic maps representing each of several WM items, predicting amplitude would track with behavioral priority. Using fMRI, we scanned participants while they remembered the location of multiple items over a WM delay, then reported the location of one probed item using a memory-guided saccade. Importantly, items were not equally probable to be probed (0.6, 0.3, 0.1, 0.0), which was indicated with a pre-cue. We analyzed fMRI activity in ten visual field maps in occipital, parietal, and frontal cortex known to be important for visual WM. In early visual cortex, but not association cortex, the amplitude of BOLD activation within voxels corresponding to the retinotopic location of visual WM items increased with the priority of the item. Interestingly, these results were contrasted with a common finding that higher-level brain regions had greater delay-period activity, demonstrating a dissociation between the absolute amount of activity in a brain area, and the activity of different spatially-selective populations within it. These results suggest that the distribution of WM resources according to priority sculpts the relative gains of neural populations that encode items, offering a neural mechanism for how prioritization impacts memory precision.

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bioRxiv2021

Spatial working memory representations in human cortex are robust to a task-irrelevant interrupting stimulus

Visual working memory (WM) enables the maintenance and manipulation of information no longer accessible in the visual world. Previous research has identified spatial WM representations in activation patterns in visual, parietal, and frontal cortex. In natural vision, the period between the encoding of information into WM and the time when it is used to guide behavior (the delay period) is rarely "empty", as is the case in most of the above laboratory experiments. In naturalistic conditions, eye movements, movement of the individual, and events in the environment result in visual signals which may overwrite or impair the fidelity of WM representations, especially in early sensory cortices. Here, we evaluated the extent to which a brief, irrelevant interrupting visual stimulus presented during a spatial WM delay period impaired behavioral performance and WM representation fidelity assayed using an image reconstruction technique (inverted encoding model). On each trial, participants (both sexes) viewed two target dots and were immediately post-cued to remember the precise spatial position of one dot. On 50% of trials, a brief interrupter stimulus appeared. While we observed strong transient univariate visual responses to the distracter stimulus, we saw no change in reconstructed neural WM representations under distraction, nor a change in behavioral performance on a continuous recall task. This suggests that spatial WM representations may be particularly robust to interference from incoming task-irrelevant visual information, perhaps related to their role in guiding movements.

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bioRxiv2021

Persistent Activity during Working Memory from Front to Back

Working memory (WM) extends the duration over which information is available for processing. Given its importance in supporting a wide-array of high level cognitive abilities, uncovering the neural mechanisms that underlie WM has been a primary goal of neuroscience research over the past century. Here, we critically review what we consider the two major arcs of inquiry, with a specific focus on findings that were theoretically transformative. For the first arc, we briefly review classic studies that led to the canonical WM theory that cast the prefrontal cortex (PFC) as a central player utilizing persistent activity of neurons as a mechanism for memory storage. We then consider recent challenges to the theory regarding the role of persistent neural activity. The second arc, which evolved over the last decade, stemmed from sophisticated computational neuroimaging approaches enabling researchers to decode the contents of WM from the patterns of neural activity in many parts of the brain including early visual cortex. We summarize key findings from these studies, their implications for WM theory, and finally the challenges these findings pose. A comprehensive theory of WM will require a unification of these two arcs of research.

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bioRxiv2021

Joint representation of working memory and uncertainty in human cortex

Neural representations of visual working memory (VWM) are noisy, and thus, decisions based on VWM are inevitably subject to uncertainty. However, the mechanisms by which the brain simultaneously represents the content and uncertainty of memory remain largely unknown. Here, inspired by the theory of probabilistic population codes, we test the hypothesis that the human brain represents an item maintained in VWM as a probability distribution over stimulus feature space, thereby capturing both its content and uncertainty. We used a neural generative model to decode probability distributions over memorized locations from fMRI activation patterns. We found that the mean of the probability distribution decoded from retinotopic cortical areas predicted memory reports on a trial-by-trial basis. Moreover, in several of the same mid-dorsal stream areas the spread of the distribution predicted subjective trial-by-trial uncertainty judgments. These results provide evidence that VWM content and uncertainty are jointly represented by probabilistic neural codes.

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bioRxiv2021

Shared long-term and short-term memory representational formats in occipital and parietal cortex

Current theories propose that the short-term retention of information in working memory (WM) and the recall of information from long-term memory (LTM) are supported by overlapping neural mechanisms in occipital and parietal cortex. Both are thought to rely on reinstating patterns of sensory activity evoked by the perception of the remembered item. However, the extent of the shared representations between WM and LTM are unclear, and it is unknown how WM and LTM representations may differ across cortical regions. We designed a spatial memory task that allowed us to directly compare the representations of remembered spatial information in WM and LTM. Critically, we carefully matched the precision of behavioral responses in these tasks. We used fMRI and multivariate pattern analyses to examine representations in (1) retinotopic cortex and (2) lateral parietal cortex (LPC) regions previously implicated in LTM. We show that visual memories were represented in a sensory-like code in both tasks across retinotopic regions in occipital and parietal cortex. LPC regions also encoded remembered locations in both WM and LTM, but in a format that differed from the sensory-evoked activity. These results suggest a striking correspondence in the format of WM and LTM representations across occipital and parietal cortex. On the other hand, we show that activity patterns in nearly all parietal regions, but not occipital regions, contained information that could discriminate between WM trials and LTM trials. Our data provide new evidence for theories of memory systems and the representation of mnemonic content.

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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.

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bioRxiv2019

Inverted encoding models estimate sensible channel responses for sensible models

In a commentary published in eNeuro, Gardner & Liu (2019) discuss the role of model specification in interpreting the output of complex models of neural data. As a case study, they suggest that one variant of such analyses, the inverted encoding model (IEM) analysis framework, should not be used to assay properties of \"stimulus representations\" because the ability to apply linear transformations at various stages of the analysis procedure renders results arbitrary. As we discuss, the specification of all models is arbitrary to the extent that an experimenter makes choices based on current knowledge of the model system. However, the results derived from any given model, such as the reconstructed channel response profiles obtained from an IEM analysis, are uniquely defined and are arbitrary only in the sense that changes in the model can predictably change results. Moreover, with knowledge of the model used for IEM analyses, the results remain informative as comparisons between reconstructed channel response profiles across task conditions using a fixed encoding model - the most common use of the IEM technique - can generally capture changes in population-level representation magnitude across linear transformations. Thus, changes in the magnitude of the response profiles across conditions are preserved, even across unprincipled linear transforms. IEM-based channel response profiles should therefore not be considered arbitrary when the model is clearly specified and guided by our best understanding of neural population representations in the brain regions being analyzed. Intuitions derived from this case study are important to consider when interpreting results from all model-based analyses, which are similarly contingent upon the specification of the models used.

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bioRxiv2019

Value-driven attentional capture enhances distractor representations in early visual cortex

When a behaviorally relevant stimulus has been previously associated with reward, behavioral responses are faster and more accurate compared to equally relevant but less valuable stimuli. Conversely, task irrelevant stimuli that were previously associated with a high reward can capture attention and distract processing away from relevant stimuli (e.g. the chocolate bar in the pantry when you are looking for a nice healthy apple). While increasing the value of task-relevant stimuli systematically up-regulates neural responses in early visual cortex to facilitate information processing, it is not clear if the value of task-irrelevant distractors influences behavior via competition in early visual cortex or via competition at later stages of decision-making and response selection. Here, we measured fMRI in human visual cortex while subjects performed a value-based learning task, and applied a multivariate inverted encoding model to assess the fidelity of distractor representations in early visual cortex. We found that the fidelity of neural representations related to task-irrelevant distractors increased when the distractors were previously associated with a high reward. Moreover, this value-based modulation of distractor representations only occurred when the distractors were previously selected as targets on preceding trials. Together, these findings suggest that value-driven attentional capture begins with sensory modulations of distractor representations in early areas of visual cortex.

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bioRxiv2017

Category learning biases sensory representations in visual cortex.

Categorization allows organisms to generalize existing knowledge to novel stimuli and to discriminate between physically similar yet conceptually different stimuli. Humans, nonhuman primates, and rodents can readily learn arbitrary categories defined by low-level visual features, and learning distorts perceptual sensitivity for category-defining features such that differences between physically similar yet categorically distinct exemplars are enhanced while differences between equally similar but categorically identical stimuli are reduced. We report a basis for these distortions in human occipitoparietal cortex. In three experiments, we used an inverted encoding model to recover population-level representations of stimuli from multivoxel and multi-electrode patterns of human brain activity while human participants (both sexes) classified continuous stimulus sets into discrete groups. In each experiment, reconstructed representations of to-be-categorized stimuli were systematically biased towards the center of the appropriate category. These biases were largest for exemplars near a category boundary, predicted participants overt category judgments, emerged shortly after stimulus onset, and could not be explained by mechanisms of response selection or motor preparation. Collectively, our findings suggest that category learning can influence processing at the earliest stages of cortical visual processing. Significance StatementCategory learning enhances perceptual sensitivity for physically similar yet categorically different stimuli. We report a possible mechanism for these distortions in human occipitoparietal cortex.. In three experiments, we used an inverted encoding model to recover population-level representations of stimuli from multivariate patterns in occipitoparietal cortex while participants categorized sets of continuous stimuli into discrete groups. The recovered representations were systematically biased by category membership, with larger biases for exemplars adjacent to a category boundary. These results suggest that mechanisms of categorization shape information processing at the earliest stages of the visual system.

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