@article {68786,
	title = {Distributing task-related neural activity across a cortical network through task-independent connections.},
	journal = {Nature Communications},
	volume = {14},
	year = {2023},
	month = {2023 May 18},
	pages = {2851},
	abstract = {<p>Task-related neural activity is widespread across populations of neurons during goal-directed behaviors. However, little is known about the synaptic reorganization and circuit mechanisms that lead to broad activity changes. Here we trained a subset of neurons in a spiking network with strong synaptic interactions to reproduce the activity of neurons in the motor cortex during a decision-making task. Task-related activity, resembling the neural data, emerged across the network, even in the untrained neurons. Analysis of trained networks showed that strong untrained synapses, which were independent of the task and determined the dynamical state of the network, mediated the spread of task-related activity. Optogenetic perturbations suggest that the motor cortex is strongly-coupled, supporting the applicability of the mechanism to cortical networks. Our results reveal a cortical mechanism that facilitates distributed representations of task-variables by spreading the activity from a subset of plastic neurons to the entire network through task-independent strong synapses.</p>
},
	keywords = {Action Potentials, Models, Neurological, Neurons, Synapses},
	issn = {2041-1723},
	doi = {10.1038/s41467-023-38529-y},
	author = {Kim, Christopher M and Finkelstein, Arseny and Chow, Carson C and Svoboda, Karel and Darshan, Ran}
}
@article {46709,
	title = {Eukaryotic transcriptional dynamics: from single molecules to cell populations.},
	journal = {Nature Reviews Genetics},
	volume = {14},
	year = {2013},
	month = {2013 Aug},
	pages = {572-84},
	abstract = {<p>Transcriptional regulation is achieved through combinatorial interactions between regulatory elements in the human genome and a vast range of factors that modulate the recruitment and activity of RNA polymerase. Experimental approaches for studying transcription in vivo now extend from single-molecule techniques to genome-wide measurements. Parallel to these developments is the need for testable quantitative and predictive models for understanding gene regulation. These conceptual models must also provide insight into the dynamics of transcription and the variability that is observed at the single-cell level. In this Review, we discuss recent results on transcriptional regulation and also the models those results engender. We show how a non-equilibrium description informs our view of transcription by explicitly considering time- and energy-dependence at the molecular level.</p>
},
	keywords = {DNA-Directed RNA Polymerases, Gene Expression Regulation, Genome, Human, Humans, Transcription Factors, Transcription, Genetic},
	issn = {1471-0064},
	doi = {10.1038/nrg3484},
	author = {Coulon, Antoine and Chow, Carson C and Singer, Robert H and Larson, Daniel R}
}
