Biology subjects

Lerman, C.

Publications and source records attributed to Lerman, C..

7 recordsLinked to original sources

bioRxiv2024

A structural MRI marker predicts individual differences in impulsivity and classifies patients with behavioral-variant frontotemporal dementia from matched controls

Impulsive decision-making is a symptom across many neuropsychiatric and neurological disorders. Yet, it is still unknown whether impulsivity can be predicted based on individual differences in brain structure. Here, we used machine-learning to develop a structural MRI signature of impulsivity, tested its validity in several independent samples, and assessed its diagnostic value in patients with behavioral variant frontotemporal dementia (bvFTD)--a neurodegenerative disease characterized by high impulsivity. The resulting whole-brain grey matter density pattern--the Structural Impulsivity Signature (SIS)--showed a good prediction-outcome correlation of r=0.35 (out-of-sample, p=0.0028) in the training sample of healthy adults (N=117) and significantly predicted individual differences in impulsivity in four other, independent studies (total N=626), including healthy and clinical participants with neuropsychiatric and neurological conditions. Further, the SIS separated bvFTD patients from controls with high accuracy (81% correct, p=0.002) and predicted impulsivity-related symptom severity among patients. The spatial distribution of weights in the SIS brain pattern highlights the key role of brain regions associated with affective processing in impulsivity. Together, these results provide evidence for a new structural neuromarker of individual differences in impulsivity that can be easily applied to new samples. Future studies can further assess its predictive value towards better prevention, diagnosis and treatment of mental disorders associated with impulsivity symptoms.

neuroscience↗

bioRxiv2024

Multivariate analysis of multimodal brain structure predicts individual differences in risk and intertemporal preference

Large changes to brain structure (e.g., from damage or disease) can explain alterations in behavior. It is therefore plausible that smaller structural differences in healthy samples can be used to better understand and predict individual differences in behavior. Despite the brains multivariate and distributed structure-to-function mapping, most studies have used univariate analyses of individual structural brain measures. Here we used a multivariate approach in a multimodal data set composed of volumetric, surface-based, diffusion-based, and functional resting-state MRI measures to predict reliable individual differences in risk and intertemporal preferences. We show that combining twelve brain structure measures led to better predictions across tasks than using any individual measure, and by examining model coefficients, we visualize the relative contribution of different brain measures from different brain regions. Using a multivariate approach to brain structure-to-function mapping that combines across many brain structure properties, along with reliably measured behavior phenotypes, may increase out-of-sample prediction accuracies and insight into neural underpinnings. Furthermore, this methodological approach may be useful to improve predictions and neural insight across basic, translational, and clinical research fields.

neuroscience↗

bioRxiv2023

Less cortical complexity in ventromedial prefrontal cortex is associated with a greater preference for risky and immediate rewards

In our everyday lives, we are often faced with situations in which we have to make choices that involve risky or delayed rewards. However, the extent to which we are willing to accept larger risky (over smaller certain) or larger delayed (over smaller immediate) rewards vary across individuals. Here we investigated the relationship between cortical surface complexity in medial prefrontal cortex and individual differences in risky and intertemporal preferences. We found that lower cortical complexity in ventromedial prefrontal cortex (vmPFC) was associated with a greater preference for risky and immediate rewards. In addition to these common structural associations in mPFC, we also found associations between lower cortical complexity and a greater preference for immediate rewards that extended into left dorsomedial prefrontal cortex and right vmPFC. Taken together, the shared association suggests that lower cortical complexity in vmPFC may be a structural marker for individual differences in impulsive behavior.

neuroscience↗

bioRxiv2021

An fMRI-based brain marker predicts individual differences in delay discounting

Individual differences in impatience--how much we discount future compared to immediate rewards--are associated with general life outcomes and related to substance use, psychiatric diseases, and obesity. Here, we use machine-learning on fMRI activity during an intertemporal choice task to develop a brain marker of individual differences in delay discounting. Study 1 (N=110) was used as a training and cross-validation set, resulting in significant prediction accuracy (r = 0.49) and suggesting an interplay between brain regions associated with affect, value, and cognitive control. The validity of the brain marker was replicated in an independent data set (Study 2, N=145, r = 0.45). In both studies, responses of the marker significantly differed between overweight and lean individuals. This pattern is a first step towards a generalizable neuromarker of delay discounting and a potentially transdiagnostic phenotype, which can be used as a brain-based target measure in future studies.

neuroscience↗

bioRxiv2021

The Future is Less Concrete than the Present: A Neural Signature of the Concreteness of Prospective Thought Is Modulated by Temporal Proximity during Intertemporal Decision-Making

Why do people discount future rewards? Multiple theories in psychology argue that future events are imagined less concretely than immediate events, thereby diminishing their perceived value. Here we provide neuroscientific evidence for this proposal. First, we construct a neural signature of the concreteness of prospective thought, using an fMRI dataset where the concreteness of imagined future events is orthogonal to their valence by design. Then, we apply this neural signature in two additional fMRI datasets, each using a different delay discounting task, to show that neural measures of concreteness decline as rewards are delayed farther into the future. Significance StatementPeople tend to devalue, or discount, outcomes in the future relative to those that are more immediate. This tendency is evident in peoples difficulty in making healthy food choices or saving money for retirement. Several psychological theories propose that discounting occurs because delayed outcomes are perceived less concretely that more immediate ones. Here we build a brain decoder for the concreteness of future thought and use this unobtrusive measure to show that outcomes are processed less concretely as they occur farther into the future.

neuroscience↗

bioRxiv2020

Neural Correlates of Value Are Intrinsically History Dependent

The authors have withdrawn their manuscript since they no longer stand by the results reported in this preprint. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

neuroscience↗

bioRxiv2019

Subjective value, not a grid-like code, describes neural activity in ventromedial prefrontal cortex during value-based decision-making

Across many studies, ventromedial prefrontal cortex (vmPFC) activity has been found to correlate with subjective value during value-based decision-making. Recently, however, vmPFC has also been shown to reflect a hexagonal gridlike code during navigation through physical and conceptual space. This raises the possibility that the subjective value correlates previously observed in vmPFC may have actually been a misconstrued gridlike signal. Here, we first show that, in theory, a hexagonal gridlike code of two-dimensional attribute space could mimic vmPFC activity previously attributed to subjective value. However, using fMRI data from a large number of subjects performing an intertemporal choice task, we show clear and unambiguous evidence that subjective value is a better description of vmPFC activity than a hexagonal gridlike code. In fact, we find no significant evidence at all for a hexagonal gridlike code in vmPFC activity during intertemporal choice. This result limits the generality of gridlike modulation as description of vmPFC activity. We suggest that vmPFC may flexibly switch representational schemes so as to encode the most relevant information for the current task.

neuroscience↗