Neuroscience seminars

We study the dynamics of (inhibitory) balanced networks at varying (i) the level of symmetry in the synaptic connectivity; and (ii) the ariance of the synaptic efficacies (synaptic gain). We find three regimes of activity. For suitably low synaptic gain, regardless of the level of symmetry, there exists a unique stable fixed point. Using a cavity-like approach, we develop a quantitative theory that describes the statistics of the activity in this unique fixed point, and the conditions for its stability. Increasing the synaptic gain, the unique fixed point destabilizes, and the network exhibits chaotic activity for zero or negative levels of symmetry (i.e., random or antisymmetric). Instead, for positive levels of symmetry, there is multi-stability among a large number of marginally stable fixed points. In this regime, ergodicity is broken and the network exhibits non-exponential relaxational dynamics. We discuss the potential relevance of such a “glassy” phase to explain some features of cortical activity.

fMRI results have shown that the supplementary motor area (SMA) and the basal ganglia, most often discussed in their roles in generating action, are engaged by beat-based timing even in the absence of movement. Some have argued that the motor system is “recruited” by beat-based timing tasks due to the presence of motor-like timescales, but a deeper understanding of the roles of these motor structures is lacking. Reviewing a body of motor neurophysiology literature and drawing on the “active inference” framework, I argue that we can see the motor and timing functions of these brain areas as examples of dynamic sub-second prediction informed by sensory event timing. I hypothesize that in both cases, sub-second dynamics in SMA predict the progress of a temporal process outside the brain, and direct pathway activation in basal ganglia selects temporal and sensory predictions for the upcoming interval -- the only difference is that in motor processes, these predictions are made manifest through motor effectors. If we can unify our understanding of beat-based timing and motor control, we can draw on the substantial motor neuroscience literature to make conceptual leaps forward in the study of predictive timing and musical rhythm.

Medium-spiny neurons (MSNs) in the striatum are required for interval timing, or the estimation of the time over several seconds via a motor response. We and others have shown that striatal MSNs can encode the duration of temporal intervals via time-dependent ramping activity, progressive monotonic changes in firing rate preceding behaviorally salient points in time. Here, we investigated how timing-related activity within striatal ensembles changes with experience. We leveraged a rodent-optimized interval timing task in which mice ‘switch’ response ports after an amount of time has passed without reward. We report three main results. First, we found that the proportion of MSNs exhibiting time-dependent modulations of firing rate increased after 10 days of task overtraining. Second, temporal decoding by MSN ensembles increased with experience and was largely driven by time-related ramping activity. Finally, we found that time-related ramping activity generalized across both correct and error trials. These results enhance our understanding of striatal temporal processing by demonstrating that time-dependent activity within MSN ensembles evolves with experience and is dissociable from motor- and reward-related processes.

One of the best established recurrent inhibitory pathways is the recurrent inhibition of mammalian motoneurons through Renshaw cells. Golgi cells form an inhibitory feedback circuit in the granular layer of cerebellum. Feedback inhibitory pathways are long established “textbook” elements of neural circuitry, but in both cases their functional role has not been well established. Here I will present some new observations on the function of recurrent inhibition in the spinal-cord, supporting the idea that this connection frequency tunes transmission of inputs through motoneurons. Secondly, I will discuss evidence that the function of Golgi cells is much more complex than classical studies based on circuit connectivity suggest.

In order to re-install neurogenesis after loss of neurons upon injury or neurodegeneration, we need to understand the basic principles of neurogenesis. I will first discuss about our discovery of a novel centrosome protein (Camargo et al., 2019) and discuss unpublished work about the great diversity of interphase centrosome proteomes and their relevance for neurodevelopmental disorders. I would then present work on a master regulator of neural stem cell amplification and brain folding (Stahl et al., 2013; Esgleas et al., 2020) to proceed presenting data on utilizing some of these factors for turning astrocytes into neurons. I will present data on the critical role of mitochondria in this conversion process (Gascon et al., 2016, Russo et al., 2020) and how it regulates the speed of conversion also showing unpublished data. If time permits I may touch on recent progress in in vivo reprogramming (Mattugini et al., 2019). Taken together, these data highlight the surprising specificity and importance of organelle diversity from centrosome, nucleolus and mitochondria as key regulators in development and reprogramming.

Empirical evidence and theoretical models both increasingly emphasize the importance of interoceptive processing in mental health. Indeed, many mood and psychiatric disorders involve disturbed feelings and/or beliefs about the visceral body. However, current methods to measure interoceptive ability are limited in a number of ways, restricting the utility and interpretation of interoceptive biomarkers in psychiatry. I will present some newly developed measures and models which aim to improve our understanding of disordered brain-body interaction in psychiatric illnesses.

Major depressive disorder (MDD) is a sexually dimorphic disease. This sexual dimorphism is believed to result from sex-specific molecular alterations affecting functional pathways regulating the capacity of men and women to cope with daily life stress differently. Transcriptional changes associated with epigenetic alterations have been observed in the brain of men and women with depression and similar changes have been reported in different animal models of stress-induced depressive-like behaviors. In fact, most of our knowledge of the biological basis of MDD is derived from studies of chronic stress models in rodents. However, while these models capture certain aspects of the features of MDD, the extent to which they reproduce the molecular pathology of the human syndrome remains unknown and the functional consequences of these changes on the neuronal networks controlling stress responses are poorly understood. During this presentation, we will first address the extent by which transcriptional signatures associated with MDD compares in men and women. We will then transition to the capacity of different mouse models of chronic stress to recapitulate some of the transcriptional alterations associated with the expression of MDD in both sexes. Finally, we will briefly elaborate on the functional consequences of these changes at the neuronal level and conclude with an integrative perspective on the contribution of sex-specific transcriptional profiles on the expression of stress responses and MDD in men and women.

In this talk series, addiction neuroscientists from across the world share their personal stories/experiences on the beauty of addiction neuroscience and how/why they have decided to invest their scientific life in this field. We hope that this talk series would encourage and support a new generation of young and passionate addiction neuroscientists in different countries to revolutionize the field of addiction medicine.

How can neural networks exhibit persistent activity on time scales much larger than allowed by cellular properties? We address this question in the context of larval zebrafish, a model vertebrate that is accessible to brain-scale neuronal recording and high-throughput behavioral studies. We study in particular the dynamics of a bilaterally distributed circuit, the so-called ARTR, including hundreds neurons. ARTR exhibits slow antiphasic alternations between its left and right subpopulations, which can be modulated by the water temperature, and drive the coordinated orientation of swim bouts, thus organizing the fish spatial exploration. To elucidate the mechanism leading to the slow self-oscillation, we train a network graphical model (Ising) on neural recordings. Sampling the inferred model allows us to generate synthetic oscillatory activity, whose features correctly capture the observed dynamics. A mean-field analysis of the inferred model reveals the existence several phases; activated crossing of the barriers in between those phases controls the long time scales present in the network oscillations. We show in particular how the barrier heights and the nature of the phases vary with the water temperature.