Population dynamics

…and cellular mechanisms to physiology, population dynamics, communities and ecosystems. Comparisons between tractable models and natural systems integrate mechanistic, ecological and evolutionary approaches, with implications for conservation, agriculture and human health. Talks, poster sessions and discussion focus on emerging and unpublished research. Applicants need a science or engineering bachelor’s degree or equivalent; underg

…may address neural circuits and population dynamics, development, perception, cognition, learning, behaviour or machine-learning analysis of neural data. The appointee establishes an independent funded programme and collaborates with experimental researchers across Duke. Priority consideration applies to submissions received by 1 December 2026.

…to neural response patterns in a population state space, where each axis represents activity of one neuron, dimensionality reduction methods often reveal low-dimensional manifolds encoding behaviorally relevant variables. Alternatively, when the same responses are viewed in a selectivity space, where each axis represents a response feature (e.g., task condition or time), dimensionality reduction methods can

…motifs have been identified in PFC population activity that could support certain aspects of this process (e.g., context-dependent line attractors for sensory input integration). PFC is also known to encode a plethora of decision-relevant variables, including task progression, action, and value. It remains an open question whether there are dynamical motifs that track all these variables to inform decisions. Further, it is unclear how outcome feedback alters neural representations of these variables and impacts

…Yet, how various populations of neurons separated by millimeters reliably communicate is still unclear. Here, we investigate how moment-to-moment and trial-to-trial fluctuations of population dynamics in the secondary (M2) motor cortex relate to stable population

How does the brain process and integrate information from different sensory modalities? This intriguing question has been explored in this study by recording the activity of the Ventral Premotor Cortex (VPC) in two trained macaques (Macaca mulatta) while performing a Bimodal Detection Task (BDT) previously used by Parra et al., 2022. In BDT, subjects were required to identify and report the modality, or the absence thereof, of a near-threshold stimulus that could be either tactile or acoustic. An initial approach on single cells revealed the presence of neurons that were responsive to tactile

Chronic pain is a serious clinical and scientific problem, affecting 1 in 5 people worldwide, yet its mechanisms and ways to treat it remain poorly understood. Pain is modulated by endogenous pain modulatory pathways that connect the brain to the spinal cord, up- and down-regulating the transmission of nociceptive information. The most important region when such modulation occurs is the Rostral Ventromedial Medulla (Fields et al., 1983; Chen and Heinricher, 2022). Despite extensive work characterising the responses of RVM cells during pharmacological interventions, little is currently known ab

…To address this, we performed population recordings of the barrel and perirhinal cortices of head-fixed mice while an object deflected their whiskers. Both ipsi- and contralateral stimulations we

Schizophrenia is a major debilitating psychiatric disorder with a lifetime prevalence of ~1%, and its clinical presentation encompasses positive, negative, and cognitive symptoms. Despite decades of research, the underlying neurophysiology has remained elusive.Here, we examine the large-scale neurophysiology underlying schizophrenia by employing multiple, simultaneous Neuropixel recordings in rodents carrying a rare genetic variant implicated in the disease. Three or four Neuropixel probes were simultaneously targeted to prefrontal cortices, motor cortices, striatum, hippocampus, auditory cort

…However, the broader population dynamics and mechanisms orchest

Theoretical neuroscience aims to understand the relationship between neuron dynamics and connectivity in recurrent circuits. This has been intensively studied at the local level, where dynamics is described by pairwise correlations. Recent advances in simultaneous recordings of many neurons have allowed researchers to address the question at the global level, such as for the dimensionality of population dynamics. Our work contributes to this effort by analyzing the impact of connectivity statistics, including certain motifs, on the bulk and outlier covariance eigenvalues. By considering linear

…framework for simultaneously inferring population dynamics on single trials and tuning functions of individual neurons to the latent population state. When applied to recordin

We recorded and analyzed the population activity of hundreds of neurons in the medial premotor areas (MPC) of rhesus monkeys performing an isochronous tapping task guided by brief flashing stimuli or auditory tones. The animals showed a strong bias towards visual metronomes, with rhythmic tapping that was more precise and accurate than for auditory metronomes. The population dynamics in state space as well as the corresponding neural sequences shared the following properties across modalities: the circular dynamics of the neural trajectories and the neural sequences formed a regenerating loop

…between rate 'units' whose dynamics are governed by smooth, continuous differential equations. However, the response of biological single neurons is better described by all-or-none events - spikes - that are triggered in response to the processing of their synaptic input by the complex dynamics of their membrane. One line of research has attempted to resolve this discrepancy by

Rajanlab designs neural network models constrained by experimental data, and reverse engineers them to figure out how brain circuits function in health and disease. Recently, we have been developing a powerful new theory-based framework for “in-vivo tract tracing” from multi-regional neural activity collected experimentally. We call this framework CURrent-Based Decomposition (CURBD). CURBD employs recurrent neural networks (RNNs) directly constrained, from the outset, by time series measurements acquired experimentally, such as Ca2+ imaging or electrophysiological data. Once trained, these da

…reflected in the evolution of neural population dynamics, has thus far been overlooked. In this talk, I will present evidence for a novel mechanism for predictive proce