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Theodoni, P.

Publications and source records attributed to Theodoni, P..

4 recordsLinked to original sources

From comparative connectomics to large-scale working memory modeling in macaque and marmoset

Although macaques and marmosets are both primates of choice for studying the brain mechanisms of cognition, they differ in key aspects of anatomy and behavior. Interestingly, recent connectomic analysis revealed that strong top-down projections from the prefrontal cortex to the posterior parietal cortex, present in macaques and important for executive function, are absent in marmosets. Here, we propose a consensus mapping that bridges the two species cortical atlases and allows for direct area-to-area comparison of their connectomes, which are then used to build comparative computational large-scale modeling of the frontoparietal circuit for working memory. We found that the macaque model exhibits resilience against distractors, a prerequisite for normal working memory function. By contrast, the marmoset model predicts a sensitivity to distractibility commonly observed behaviorally in this species. Surprisingly, this contrasting trend can be swapped by scaling intrafrontal and frontoparietal, and offer a credible prediction to the marmosets behavior in this specific task.

neuroscience↗

A connectome-based model of conscious access in monkey cortex

A growing body of evidence suggests that conscious perception of a sensory stimulus coincides with all-or-none activity across multiple cortical areas, a phenomenon called ignition. In contrast, the same stimulus, when undetected, induces only transient activity. In this work, we report a large-scale model of the macaque cortex based on recently quantified structural mesoscopic connectome data. We use this model to simulate a detection task, and demonstrate how a dynamical bifurcation mechanism produces ignition-like events in the model network. The model predicts that feedforward excitatory transmission is primarily mediated by the fast AMPA receptors to ensure rapid signal propagation from sensory to associative areas. In contrast, a greater proportion of the inter-areal feedback projections and local recurrent excitation depend on the slow NMDA receptors, to ensure ignition of distributed frontoparietal activity. Our model predicts, counterintuitively, that fast-responding sensory areas contain a higher ratio of NMDA to AMPA receptors compared to association cortical areas that show slow, sustained activity. We validate this prediction using cortex-wide in-vitro receptor autoradiography data. Finally, we show how this model can account for various behavioral and physiological effects linked to consciousness. Together, these findings clarify the neurophysiological mechanisms of conscious access in the primate cortex and support the concept that gradients of receptor densities along the cortical hierarchy contribute to distributed cognitive functions.

neuroscience↗

Structural attributes and principles of the neocortical connectome in the marmoset monkey

The marmoset monkey has become an important primate model in Neuroscience. Here we characterize salient statistical properties of inter-areal connections of the marmoset cerebral cortex, using data from retrograde tracer injections. We found that the connectivity weights are highly heterogeneous, spanning five orders of magnitude, and are log-normally distributed. The cortico-cortical network is dense, heterogeneous and has high specificity. The reciprocal connections are the most prominent and the probability of connection between two areas decays with their functional dissimilarity. The laminar dependence of connections defines a hierarchical network correlated with microstructural properties of each area. The marmoset connectome reveals parallel streams associated with different sensory systems. Finally, the connectome is spatially embedded with a characteristic length that obeys a power law as a function of brain volume across species. These findings provide a connectomic basis for investigations of multiple interacting areas in a complex large-scale cortical system underlying cognitive processes.

neuroscience↗

A Model Of Plasticity-Dependent Network Activity In Rodent Hippocampus During Exploration Of Novel Environments

Place cells of the rodent hippocampus fire action potentials when the animal traverses a particular spatial location in a given environment. Therefore, for any given trajectory one will observe a repeatable sequence of place cell activations as the animal explores. Interestingly, when the animal is quiescent or sleeping, one can observe similar sequences of activation, although at a highly compressed rate, known as \"replays\". It is hypothesized that this replay underlies the process of memory consolidation whereby memories are \"transferred\" from hippocampus to cortex. However, it remains unclear how the memory of a particular environment is actually encoded in the place cell activity and what the mechanism for replay is. Here we study how plasticity during spatial exploration shapes the patterns of synaptic connectivity in model networks of place cells. Specifically, we show how plasticity leads to the emergence of patterns of activity which represent the spatial environment learned. These states become spontaneously active when the animal is quiescent, reproducing the phenomenology of replays. Interestingly, replay emerges most rapidly when place cell activity is modulated by an ongoing oscillation. The optimal oscillation frequency can be calculated analytically, is directly related to the plasticity rule, and for experimentally determined values of the plasticity window in rodent slices gives values in the theta range. A major prediction of this model is that the pairwise correlation of place cells which encode for neighboring locations should increase during initial exploration, leading up to the critical transition. We find such an increase in a population of simultaneously recorded CA1 pyramidal cells from a rat exploring a novel track. Furthermore, in a rat in which hippocampal theta is reduced through inactivation of the medial septum we find no such increase. Our model is the first to show how theta-modulation can speed up learning by facilitating the emergence of environment-specific network-wide patterns of synaptic connectivity in hippocampal circuits.

neuroscience↗