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Sherman, B. E.

Publications and source records attributed to Sherman, B. E..

8 recordsLinked to original sources

Statistical learning in epilepsy: Behavioral, anatomical, and causal mechanisms in the human brain

Statistical learning, the fundamental cognitive ability of humans to extract regularities across experiences over time, engages the medial temporal lobe in the healthy brain. This leads to the hypothesis that statistical learning may be impaired in epilepsy patients, and that this impairment could contribute to their varied memory deficits. In turn, epilepsy patients provide a platform to advance basic understanding of statistical learning by helping to evaluate the necessity of medial temporal lobe circuitry through disease and causal perturbations. We implemented behavioral testing, volumetric analysis of the medial temporal lobe substructures, and direct electrical brain stimulation to examine statistical learning across a cohort of 61 epilepsy patients and 28 healthy controls. Behavioral performance in a statistical learning task was negatively associated with seizure frequency, irrespective of where seizures originated in the brain. The volume of hippocampal subfields CA1 and CA2/3 correlated with statistical learning performance, suggesting a more specific role of the hippocampus. Indeed, transient direct electrical stimulation of the hippocampus disrupted statistical learning. Furthermore, the relationship between statistical learning and seizure frequency was selective: behavioral performance in an episodic memory task was impacted by structural lesions in the medial temporal lobe and by antiseizure medications, but not by seizure frequency. Overall, these results suggest that statistical learning may be hippocampally dependent and that this task could serve as a clinically useful behavioral assay of seizure frequency distinct from existing neuropsychological tests. Simple and short statistical learning tasks may thus provide patient-centered endpoints for evaluating the efficacy of novel treatments in epilepsy.

neuroscience↗

Hippocampal mechanisms support cortisol-induced memory enhancements

Stress can powerfully influence episodic memory, often enhancing memory encoding for emotionally salient information. These stress-induced memory enhancements stand at odds with demonstrations that stress and the stress-related hormone cortisol can negatively affect the hippocampus, a brain region important for episodic memory encoding. To resolve this apparent conflict and determine whether and how the hippocampus supports memory encoding under cortisol, we combined behavioral assays of associative memory, high-resolution functional magnetic resonance imaging (fMRI), and pharmacological manipulation of cortisol in a within-participant, double-blinded procedure. Hydrocortisone led to enhanced functional connectivity between hippocampal subregions, which predicted subsequent memory enhancements for emotional information. Cortisol also modified the relationship between hippocampal representations and memory: whereas hippocampal signatures of distinctiveness predicted memory under placebo, relative integration predicted memory under cortisol. Together, these data provide novel evidence that the human hippocampus contains the necessary machinery to support emotional memory enhancements under stress.

neuroscience↗

Online abstraction during statistical learning revealed by neural entrainment from intracranial recordings

We encounter the same people, places, and objects in predictable sequences and configurations. These regularities are learned efficiently by humans via statistical learning. Importantly, statistical learning creates knowledge not only of specific regularities, but also of more abstract, generalizable regularities. However, prior evidence of such abstract learning comes from post-learning behavioral tests, leaving open the question of whether abstraction occurs online during initial exposure. We address this question by measuring neural entrainment during statistical learning with intracranial recordings. Neurosurgical patients viewed a stream of scene photographs with regularities at one of two levels: In the Exemplar-level Structured condition, the same photographs appeared repeatedly in pairs. In the Category-level Structured condition, the photographs were trial-unique but their categories were paired across repetitions. In a baseline Random condition, the same photographs repeated but in a scrambled order. We measured entrainment at the frequency of individual photographs, which was expected in all conditions, but critically also at half of that frequency -- the rate at which to-be-learned pairs appeared in the two structured conditions (but not the random condition). Neural entrainment to both exemplar and category pairs emerged within minutes throughout visual cortex and in frontal and temporal brain regions. Many electrode contacts were sensitive to only one level of structure, but a significant number encoded both exemplar and category regularities. These findings suggest that abstraction occurs spontaneously during statistical learning, providing insight into the brains unsupervised mechanisms for building flexible and robust knowledge that generalizes across input variation and conceptual hierarchies.

neuroscience↗

Resilient anatomy and local microplasticity of na&iumlve and stress hematopoiesis

The bone marrow has an extraordinary capacity to adjust blood cell production to meet physiological demands in response to insults. The spatial organization of normal and stress responses is largely unknown due to the lack of methods to visualize most steps of blood production. Here we develop strategies to image multipotent hematopoiesis, megakaryopoiesis, erythropoiesis, and lymphopoiesis in mice. We combine these with imaging of myelopoiesis1 to define the anatomy of hematopoiesis in homeostasis, after acute insults, and during geriatric age. Blood production takes place via long-range migration of multipotent progenitors away from stem cells. Lineage-committed progenitors are then serially recruited to blood vessels where they contribute to lineage-specific microanatomical structures, composed of progenitors and immature cells, which function as production lines for mature blood cells. This anatomy is durable and resilient to insults as it was maintained after hemorrhage, acute bacterial infection, and with aging. Production lines enable hematopoietic plasticity as they differentially -and selectively-modulate their numbers and output in response to acute insults and then return to homeostasis. In geriatric mice the number of production lines is maintained, but their microanatomy becomes permanently remodeled in a cell- and lineage-specific manner indicating chronic anatomical adaptations to hematopoietic aging. Our studies uncover the sophisticated and durable anatomy of blood production -defined by distinct migratory behaviors depending on the maturation stage- and identify discrete microanatomical production lines that confer plasticity to hematopoiesis.

physiology↗

Temporal dynamics of competition between statistical learning and episodic memory in intracranial recordings of human visual cortex

The function of long-term memory is not just to reminisce about the past, but also to make predictions that help us behave appropriately and efficiently in the future. This predictive function of memory provides a new perspective on the classic question from memory research of why we remember some things but not others. If prediction is a key outcome of memory, then the extent to which an item generates a prediction signifies that this information already exists in memory and need not be encoded. We tested this principle using human intracranial EEG as a time-resolved method to quantify prediction in visual cortex during a statistical learning task and link the strength of these predictions to subsequent episodic memory behavior. Epilepsy patients of both sexes viewed rapid streams of scenes, some of which contained regularities that allowed the category of the next scene to be predicted. We verified that statistical learning occurred using neural frequency tagging and measured category prediction with multivariate pattern analysis. Although neural prediction was robust overall, this was driven entirely by items that were subsequently forgotten. Such interference provides a mechanism by which prediction can regulate memory formation to prioritize encoding of information that could help learn new predictive relationships. Significance StatementWhen faced with a new experience, we are rarely at a loss for what to do. Rather, because many aspects of the world are stable over time, we rely upon past experiences to generate expectations that guide behavior. Here we show that these expectations during a new experience come at the expense of memory for that experience. From intracranial recordings of visual cortex, we decoded what humans expected to see next in a series of photographs based on patterns of neural activity. Photographs that generated strong neural expectations were more likely to be forgotten in a later behavioral memory test. Prioritizing the storage of experiences that currently lead to weak expectations could help improve these expectations in future encounters.

neuroscience↗

Remembering the pattern: A longitudinal case study on statistical learning in spatial navigation and memory consolidation

Distinct brain systems are thought to support statistical learning over different timescales. Regularities encountered during online perceptual experience can be acquired rapidly by the hippocampus. Further processing during offline consolidation can establish these regularities gradually in cortical regions, including the medial prefrontal cortex (mPFC). These mechanisms of statistical learning may be critical during spatial navigation, for which knowledge of the structure of an environment can facilitate future behavior. Rapid acquisition and prolonged retention of regularities have been investigated in isolation, but how they interact in the context of spatial navigation is unknown. We had the rare opportunity to study the brain systems underlying both rapid and gradual timescales of statistical learning using intracranial electroencephalography (iEEG) longitudinally in the same patient over a period of three weeks. As hypothesized, spatial patterns were represented in the hippocampus but not mPFC for up to one week after statistical learning and then represented in the mPFC but not hippocampus two and three weeks after statistical learning. Taken together, these findings clarify that the hippocampus may do the initial work of extracting regularities and transfer these integrated memories to cortex, rather than only storing individual experiences and leaving it up to cortex to extract regularities. HighlightsO_LICase study of an epilepsy patient tested longitudinally over three weeks. C_LIO_LIWe tracked time-dependent changes in neural representations of spatial patterns. C_LIO_LIRepresentations reconstructed from hippocampal activity reflected patterns learned within a week. C_LIO_LIRepresentations reconstructed from activity in the mPFC reflected patterns learned 2-3 weeks ago. C_LI

neuroscience↗

Mnemonic content and hippocampal patterns shape judgments of time

Our experience of time can feel dilated or compressed, rather than reflecting true "clock time." Although many contextual factors influence the subjective perception of time, it is unclear how memory accessibility plays a role in constructing our experience of and memory for time. Here, we used a combination of behavioral and fMRI measures to ask the question of how memory is incorporated into temporal duration judgments. Behaviorally, we found that event boundaries, which have been shown to disrupt ongoing memory integration processes, result in the temporal compression of duration judgments. Additionally, using a multivoxel pattern similarity analysis of fMRI data, we found that greater temporal pattern change in the left hippocampus within individual trials was associated with longer duration judgments. Together, these data suggest that mnemonic processes play a role in constructing representations of time. Statement of RelevanceOur everyday experiences convey a powerful truth: That our perception of time often diverges from the reality of time. When enjoying an active vacation with family, time moves quickly: hours go by in minutes. When sitting through an unnecessary meeting, time moves slowly: minutes go by in hours. What is the origin of these phenomenologically compelling illusions of time perception? Past research has examined how a range of specific factors, from emotions to blinking, contribute to the distortion of time. Here, in contrast, we evaluate how the content and accessibility of our memories shapes time perception. We show that context shifts, known to disrupt memory processing, also lead to robust contractions of perceived time. We discuss how both effects -- memory disruptions and time distortions -- may be linked via the hippocampus. "An hour, once it lodges in the queer element of the human spirit, may be stretched to fifty or a hundred times its clock length; on the other hand, an hour may be accurately represented on the timepiece of the mind by one second." -- Virginia Woolf

neuroscience↗

Learning not to remember: How predicting the future impairs encoding of the present

Memory is typically thought of as enabling reminiscence about past experiences. However, memory also informs and guides processing of future experiences. These two functions of memory are often at odds: remembering specific experiences from the past requires storing idiosyncratic properties that define particular moments in space and time, but by definition such properties will not be shared with similar situations in the future and thus may not be applicable to future situations. We discovered that, when faced with this conflict, the brain prioritizes prediction over encoding. Behavioral tests of recognition and source recall showed that items allowing for prediction of what will appear next based on learned regularities were less likely to be encoded into memory. Brain imaging revealed that the hippocampus was responsible for this interference between statistical learning and episodic memory. The more that the hippocampus predicted the category of an upcoming item, the worse the current item was encoded. This competition may serve an adaptive purpose, focusing encoding on experiences for which we do not yet have a predictive model.

neuroscience↗