Paola Arlotta is interested in understanding the molecular laws that govern the birth, differentiation, and assembly into working circuitry of clinically relevant neuron types in the cerebral cortex. The complexity of the nervous system fascinates her, and she is driven to integrate developmental and evolutionary knowledge to inform novel strategies for circuit repair in the cortex. Arlotta received her Master’s in Biochemistry from the University of Trieste, Italy, and her Ph.D. in Molecular Biology from the University of Portsmouth, UK. She came to Boston as a postdoctoral fellow in Neuroscience at Harvard Medical School and, in 2008, she joined the Harvard faculty. In 2014 she was promoted to Professor in the department of Stem Cell and Regenerative Biology and in 2018 she was appointed the inaugural professor to the Golub Family Chair. She has been a Principal Faculty Member at the Harvard Stem Cell Institute since 2007 and is also affiliated with the Center for Brain Science. Arlotta is the recipient of many awards, including the 2017 George Ledlie Prize from Harvard and a 2018 von Humboldt Foundation research award. Her work has been published in Science, Nature, Nature Neuroscience, Nature Cell Biology, and Neuron.
Thesis Defense Seminar
In humans, high visual acuity is restricted to a small (~1o) region of the retina: the foveola. Even if the foveola covers less than 1% of the visual field, the stimulus within this region can be complex, particularly when examining natural scenes. What are the contributions of attention and eye movements in foveal vision? Studying attention at this scale is challenging because small eye movements continuously shift the image on the retina, covering an area as large as the foveola itself. Furthermore, localizing the line of sight within a 1 degree region is challenging and beyond the capabilities of most eye-trackers. Thanks to a combination of techniques allowing for high-resolution recordings of eye position, retinal stabilization, and accurate gaze localization, we circumvented these challenges and examined how attention and visual exploration are controlled at the scale of the foveola. Here we show that fine spatial vision in the foveola is enhanced by means of three different mechanisms: (a) Covert shifts of attention. High-resolution attentional reallocations independent of eye movements improve vision at selected foveal locations. (b) Microsaccade preparation. Planning of microsaccades, saccades smaller than half a degree, enhances fine spatial vision at the microsaccade target location at the expenses of other nearby locations within the foveola. (c) Visual exploration. The visual system possesses not only a coarser priority map of the extrafoveal space to guide saccades, but also a finer grain priority map that is used to guide microsaccades once the region of interest is foveated. The precise repositioning of the preferred retinal locus by means of microsaccades enables visual exploration of foveal stimuli. Our findings show that, contrary to common intuition, simply placing a stimulus within the foveola is not sufficient for fine spatial vision; vision is the outcome of an orchestrated synergy of motor, cognitive and attentional factors at all levels, from the examination of visual scenes to the examination of detail.
Individuals vary substantially in their attitudes towards uncertainty: some embrace it, while others avoid it at all costs; some learn quickly to reduce uncertainty, while others do not. I will describe a series of behavioral and neuroimaging studies, in which we examined decision-making, learning, and passive valuation in uncertain environments. Our behavioral results show age-related changes in specific features of behavior under uncertainty, as well as links between some of these features and pathological behavior. Our neural results reveal potential mechanisms for these individual and age-related differences.
Abstract: Brain-wide fluctuations in local field potential oscillations reflect emergent network-level signals that mediate behavior. Cracking the code whereby these oscillations coordinate in time and space (spatiotemporal dynamics) to represent complex behaviors would provide fundamental insights into how the brain signals emotional pathology. Using machine learning, we discover a spatiotemporal dynamic network that predicts the emergence of depression-related behavioral dysfunction in mice subjected to chronic social defeat stress. Activity patterns in this network originate in prefrontal cortex and ventral striatum, relay through amygdala and ventral tegmental area, and converge in ventral hippocampus. This network is increased by acute threat, and it is also enhanced in three independent models of depression vulnerability. Finally, we demonstrate that this vulnerability network is biologically distinct from the networks that encode dysfunction after stress. Thus, we reveal a convergent mechanism through which depression vulnerability is mediated in the brain. We also demonstrate a novel strategy for linking mesoscale brain states to emotional behavior.
Cortical circuits in the early visual stream, including primary visual cortex (V1), are necessary for extraction of information from external sensory inputs. These circuits comprise a variety of projection neurons that transmit signals to downstream areas, including cortical and subcortical structures involved in the generation of behavior. A key unanswered question is whether different neuronal populations in V1 encode distinct sensory representations that are "customized" for specific behavioral functions. Here, we combine 2-photon calcium imaging and optogenetic manipulation to demonstrate that a subset of layer 5 neurons that project to the brainstem selectively encode behaviorally-relevant information in a visually-guided classical conditioning task. Activity in corticopontine cells, but not closely intermingled corticostriatal cells, reliably predicts trial-to-trial behavior, and their suppression impairs performance. Our findings reveal functional heterogeneity in microcircuits of the early visual system and indicate the existence of segregated pathways in V1 for the coordination of behavior.
Cortical circuit function is highly flexible, adapting rapidly to changes in environmental context and behavioral demand. Indeed, although the physical components of local circuits remain relatively constant, the precise population of neurons participating in ongoing patterns of activity can vary tremendously from moment to moment. GABAergic interneurons are key mediators of this flexible cortical circuit function. We find that different populations of interneurons are differentially regulated by behavioral states such as arousal and quiescence, contributing to state-dependent changes in visual processing and perceptual performance. We find that inhibitory regulation of GABAergic populations is a critical element of circuit function. In turn, loss or dysregulation of key inhibitory interneurons disrupts the flexible function of cortical circuits and impairs both cortical development and sensory processing in the mature brain. Our recent findings highlight unanticipated roles for sparse but powerful inhibitory populations, such as the VIP cells, and uncover the impact of inhibitory-to-inhibitory interactions in the cortex.