Topic: population dynamics

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

Higher cortical areas carry a wide range of sensory, cognitive, and motor signals supporting complex goal-directed behavior. These signals mix in heterogeneous responses of single neurons, making it difficult to untangle underlying mechanisms. I will present two approaches for revealing interpretable circuit mechanisms from heterogeneous neural responses during cognitive tasks. First, I will show a flexible nonparametric 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

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

According to the theory of predictive processing, expectations modulate neural activity so as to optimize the processing of sensory inputs expected in the current environment. While there is accumulating evidence that the brain indeed operates under this principle, most of the attention has been placed on mechanisms that rely on static coding properties of neurons. The potential contribution of dynamical features, such as those 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

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