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Weidemann, C. T.

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

4 recordsLinked to original sources

Direct Brain Recordings Identify a Causal Subsequent-Memory Effect

Endogenous variation in brain state and stimulus-specific evoked activity can both contribute to successful encoding. Previous studies, however, have not clearly distinguished among these components. We address this question by analyzing intracranial EEG recorded from epilepsy patients as they studied and subsequently recalled lists of words. We first trained classifiers to predict recall of either single items or entire lists and found that both classifiers exhibited similar performance. We found that list-level classifier output--a biomarker of successful encoding--tracked item presentation and recall events, despite having no information about the trial structure. Across widespread brain regions, decreased low- and increased high-frequency activity (HFA) marked successful encoding of both items and lists. We found regional differences in the hippocampus and prefrontal cortex, where in the hippocampus HFA correlated more strongly with item recall, whereas in the prefrontal cortex HFA correlated more strongly with list performance. Despite subtle differences in item- and list-level features, the similarity in overall classification performance, spectral signatures of successful recall, and fluctuations of spectral activity across the encoding period argue for a shared endogenous process that causally impacts the brains ability to learn new information.

neuroscience↗

A neural code of egocentric spatial information in human medial temporal lobe

Spatial navigation relies on neural systems that encode information about places, distances, and directions in relation to the external world or relative to the navigating organism. Since the proposal of cognitive maps, the neuroscience of navigation has focused on allocentric (world-referenced) neural representations including place, grid, and head-direction cells. Here, using single-neuron recordings during virtual navigation, we identify "anchor cells" in the human brain as a neural code for egocentric (self-centered) spatial maps: Anchor cells represent egocentric directions towards "anchor points" located in the environmental center or periphery. Anchor cells were abundant in parahippocampal cortex, supported full vectorial representations of egocentric space, and were integrated into a neural memory network. Neurons encoding allocentric direction complemented anchor-cell activity, potentially assisting anchor cells in transforming percepts into allocentric representations. Anchor cells may facilitate egocentric navigation strategies, may support route planning from egocentric viewpoints, and may underlie the first-person perspective in episodic memories.

neuroscience↗

Neural measures of subsequent memory reflect endogenous variability in cognitive function

Human cognition exhibits a striking degree of variability: Sometimes we rapidly forge new associations whereas at other times new information simply does not stick. Correlations between neural activity during encoding and subsequent retrieval performance have implicated such "subsequent memory effects" (SMEs) as important for understanding the neural basis of memory formation. Uncontrolled variability in external factors that also predict memory performance, however, confounds the interpretation of these effects. By controlling for a comprehensive set of external variables, we investigated the extent to which neural correlates of successful memory encoding reflect variability in endogenous brain states. We show that external variables that reliably predict memory performance have relatively small effects on electroencephalographic (EEG) correlates of successful memory encoding. Instead, the brain activity that is diagnostic of successful encoding primarily reflects fluctuations in endogenous neural activity. These findings link neural activity during learning to endogenous states that drive variability in human cognition.

neuroscience↗

Dynamics of brain activity reveal a unitary recognition memory signal

Dual-process models of recognition memory typically assume that independent familiarity and recollection signals with distinct temporal profiles can each lead to recognition (enabling two routes to recognition), whereas single-process models posit a unitary \"memory strength\" signal. Using multivariate classifiers trained on spectral EEG features, we quantified neural evidence for recognition decisions as a function of time. Classifiers trained on a small portion of the decision period performed similarly to those also incorporating information from previous time points indicating that neural activity reflects an integrated evidence signal. We propose a single-route account of recognition memory that is compatible with contributions from familiarity and recollection signals, but relies on a unitary evidence signal that integrates all available evidence.

neuroscience↗