Biology subjects

Halpern, D. J.

Publications and source records attributed to Halpern, D. J..

4 recordsLinked to original sources

bioRxiv2022

Human hippocampal ripples signal encoding of episodic memories

Recent human electrophysiology work has uncovered the presence of high frequency oscillatory events, termed ripples, during awake behavior. This prior work focuses on ripples in the medial temporal lobe (MTL) during memory retrieval. Few studies, however, investigate ripples during item encoding. Many studies have found neural activity during encoding that predicts later recall, termed subsequent memory effects (SMEs), but it is unclear if ripples during encoding also predict subsequent recall. Detecting ripples in 116 neurosurgical participants (n = 61 male) performing an episodic memory task, we find insignificant ripple SMEs in any MTL region, even as these regions exhibit robust high frequency activity (HFA) SMEs. Instead, hippocampal ripples increase during encoding of items leading to recall of temporally or semantically associated items, a phenomenon known as clustering. This subsequent clustering effect (SCE) arises specifically when hippocampal ripples occur during both encoding and retrieval, suggesting that ripples mediate the encoding and future reinstatement of episodic memories.

neuroscience↗

bioRxiv2021

Identifying Causal Subsequent Memory Effects

Over 40 years of accumulated research has detailed associations between neuroimaging signals measured during a memory encoding task and later memory performance, across a variety of brain regions, measurement tools, statistical approaches and behavioral tasks. But the interpretation of these Subsequent Memory Effects (SMEs) remains unclear: if the identified signals reflect cognitive and neural mechanisms of memory encoding then the underlying neural activity must be causally related to future memory. However, almost all previous SME analyses do not control for potential confounders of this causal interpretation, such as serial position and item effects. We collect a large fMRI dataset and use a novel experimental design and analysis approach that allows us to statistically adjust for all exogenous confounding variables. We find that, using standard approaches without adjustment, we replicate several univariate and multivariate subsequent memory effects and are able to predict memory performance across people. However, we are unable to identify any signal that reliably predicts subsequent memory after adjusting for confounding variables, bringing into doubt the causal status of these effects. We apply the same approach to subjects judgments of learning collected during an encoding period, and show that these behavioral measures of encoding quality do predict memory after adjustments, suggesting that it is possible to measure signals at the time of encoding that reflect causal mechanisms but that existing neuroimaging measures may not have the precision and specificity to do so.

neuroscience↗

bioRxiv2021

Getting Blood from a Stone: Improving Neural Inferences without Additional Neural Data

In recent years, the cognitive neuroscience literature has come under criticism for containing many low-powered studies, limiting the ability to make reliable statistical inferences. Typically, the suggestion for increasing power is to collect more data with neural signals. However, many studies in cognitive neuroscience use parameters estimated from behavioral data in order to make inferences about neural signals (such as fMRI BOLD signal). In this paper, we explore how cognitive neuroscientists can learn more about their neuroimaging signal by collecting data on behavior alone and using alternative estimators designed to leverage this information. We demonstrate through simulation and mathematical derivations that knowing more about the marginal distribution of behavior can improve inferences about the mapping between cognitive processes and neural data. We analyze the magnitude of this benefit, finding that it depends on the desired estimand and several underlying study parameters. While in many cases the absolute gains in precision can be modest, our results demonstrate that, in realistic settings, additional behavioral data can lead to the same improvement in the precision of inferences more cheaply and easily than collecting additional data from subjects in a neuroimaging study. This means that when conducting a neuroimaging study, researchers now have another knob to turn in a design analysis: the number of subjects collected in the scanner and the number of behavioral subjects collected outside the scanner (in the lab or online).

neuroscience↗

bioRxiv2020

Intolerance to uncertainty modulates neural synchrony between political partisans

Political partisans see the world through an ideologically biased lens. What drives political polarization? It has been posited that polarization arises because holding extreme political views satisfies a need for certain and stable beliefs about the world. We examined the relationship between uncertainty tolerance and political polarization using brain-to-brain synchrony analysis, which measured committed liberals and conservatives subjective interpretation of a continuous political narrative. Participants (N=44) watched a political debate while undergoing fMRI. Shared ideology between participants increased neural synchrony in many brain areas including key regions of the valuation and theory-of-mind networks (e.g. temporoparietal junction). The degree of neural synchrony was modulated by uncertainty aversion: Uncertainty-intolerant individuals experienced greater brain-to-brain synchrony with politically like-minded peers and lower synchrony with political opponents. This effect was observed for liberals and conservatives alike. Moreover, increasing neural synchrony between committed partisans predicted subsequent polarized attitude formation about the debate after the scanning session. These results suggest that uncertainty attitudes gate the shared neural processing of political narratives, thereby fueling polarized attitude formation about hot-button issues.

neuroscience↗