The breadth of research in the Murray Lab reflects the diverse scientific interests of lab members. Research topics include:
- Large-Scale Brain Organization and Dynamics
- Neural Representational Geometry
- Working Memory & Attention
- Reinforcement Learning
- Decision Making
- Statistical & Modeling Methods
Large-Scale Brain Organization and Dynamics
Example publications:
- Murray JD, et al. (2014) A hierarchy of intrinsic timescales across primate cortex. Nature Neuroscience 17:1661
- Burt JB, et al. (2018) Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography. Nature Neuroscience 21:1251 [DOI]
- Demirtas M, et al. (2019) Hierarchical heterogeneity across human cortex shapes large-scale neural dynamics. Neuron 101:1181 [DOI]
- Burt JB, et al. (2021) Transcriptomics-informed large-scale cortical model captures topography of pharmacological neuroimaging effects of LSD. eLife 10:e69320 [DOI]
- Shinn M, et al. (2023) Functional brain networks reflect spatial and temporal autocorrelation. Nature Neuroscience 26:867 [DOI]
Neural Representational Geometry
Example publications:
- Ehrlich DB & Murray JD (2022) Geometry of neural computation unifies working memory and planning. Proceedings of the National Academy of Sciences 119:e2115610119 [DOI]
- Ito T & Murray JD (2023) Multitask representations in the human cortex transform along a sensory-to-motor hierarchy. Nature Neuroscience 26:306 [DOI]
Working Memory & Attention
Example publications:
- Murray JD, et al. (2014) Linking microcircuit dysfunction to cognitive impairment: effects of disinhibition associated with schizophrenia in a cortical working memory model. Cerebral Cortex 24:859
- Murray JD, et al. (2017) Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex. Proceedings of the National Academy of Sciences 114:394 [DOI]
- Murray JD, et al. (2017) Working memory and decision-making in a frontoparietal circuit model. Journal of Neuroscience 37:12167
- Li D, et al. (2021) Trial-to-trial variability of spiking delay activity in prefrontal cortex constrains burst-coding models of working memory. Journal of Neuroscience 41:8928 [DOI]
- Gu QL, et al. (2021) Computational circuit mechanisms underlying thalamic control of attention. bioRxiv 10.1101/2020.09.16.300749 [DOI]
Reinforcement Learning
Example publications:
- Pettine WW, et al. (2023) Human latent-state generalization through prototype learning with discriminative attention. Nature Human Behavior 7:442 [DOI]
Decision Making
Example publications:
- Cavanagh SE*, Lam NH*, et al. (2020) A circuit mechanism for decision making biases and NMDA receptor hypofunction. eLife 9:e53664 [DOI]
- Shinn M, et al. (2020) Confluence of timing and reward biases in perceptual decision-making dynamics. Journal of Neuroscience 40:7326 [DOI]
- Shinn M, et al. (2022) Transient neuronal suppression for exploitation of new sensory evidence. Nature Communications 13:23 [DOI]
- Lam NH, et al. (2022) Effects of altered excitation-inhibition balance on decision making in a cortical circuit model. Journal of Neuroscience 42:1035 [DOI]
Statistical & Modeling Methods
Example publications:
- Shinn M*, Lam NH* & Murray JD (2020) A flexible framework for simulating and fitting generalized drift-diffusion models. eLife 9:e56938.[DOI]
- Burt JB, et al. (2020) Generative modeling of brain maps with spatial autocorrelation. NeuroImage 220:117038 [DOI]
- Ehrlich DB*, Stone JT*, et al. (2021) PsychRNN: an accessible and flexible Python package for training recurrent neural network models on cognitive tasks. eNeuro 0427-20.2020 [DOI]
- Helmer H, et al. (2020) On stability of Canonical Correlation Analysis and Partial Least Squares with application to brain-behavior associations. bioRxiv 10.1101/2020.08.25.265546 [DOI]