Key facts

Time frame: 2018 to 2020

Origin: Spontanous Application

Collaboration with HBP:  

Funding: Sapienza University of Rome (IT)

Modulation of slow OScillAtions In Cognitive tasks

MOSAIC is a project funded by Sapienza University of Rome. The overall goal is to describe how cortical networks dynamics is modulated across brain and behavioral states.

 

Project Description and Objectives

Within MOSAIC we will study the brain dynamics by combining a high-resolution approach to small portions of the cortex with full-scalp recording (ECoG/EEG). Behaviourally, we will focus on dynamic decision-making and hierarchical learning by having monkeys trained in tasks where the motor decision is taken by weighting both recent experiences and the relative value of premises. Neural activity will be finally obtained and analysed at different temporal and spatial scales.

MOSAIC, at the microscopic level, by measuring intracortical multi-unit activity (MUA) and local field potential (LFP) with multielectrode arrays chronically implanted in the cortex of monkeys, will describe the repertoire of spatiotemporal patterns spontaneously emerging during the execution of complex tasks.

 

Slow oscillations are the electrical representation of deep sleep in humans and other animals. They have been linked to synaptic plasticity, to learning, and memory consolidation.

MOSAIC will explore with unprecedented details the neuronal mechanisms underlying the evolution of slow oscillations dynamics in monkeys, in their relationship with learning and task solving. As a pilot study for future investigations we will explore the role of sleep-induced slow oscillations on learning-related neuronal dynamics. 

 

During the last decades, a large body of basic research, on the synaptic, single cell, network and computational level has built a translational bridge to relate different features in the EEG to the underlying neuronal activity patterns. MOSAIC will provide further tools and insights for improving current methods of EEG and invasive signals analysis and will shed new light on the neural mechanisms of neuronal interaction within both local and distributed networks. This will perfectly fit into the current efforts of the European neuroscience community to connect the microscopic and macroscopic dynamics of the brain within and beyond the Human Brain Project. The focus on sleep will foster the understanding of the biological origins of sleep-related behavioural disorders in order to provide insights toward new cures with strong scientific background.

 

 

Collaboration with HBP 

MOSAIC members have collaborated and are currently cooperating with HBP members participating to WP3.2 (Sleep/wake transitions and slow-wave activity) in particular with ISS and INFN.

The collaboration could be easily extended to other groups within HBP interested to the analysis (WP3.3, WP3.4, SP2) and modelling (SP4) of the role of oscillations in different brain states and areas.

MOSAIC aims to obtain access to HBP facilities, such as those developed in WP5.7 (Tools and curation for integrated parallelized analysis of activity data) for approaching complementary methods of analysis of large dataset of recording. Finally, the increasing dimension of datasets from multiscale recording of neural activity from chronically implanted microelectrodes, and the need for high-resolution multi-scale simulations will benefit of the access to the facilities and tools provided within SP7 (High Performance Analytics & Computing Platform). 

MOSAIC could provide to HBP partners, within the framework of collaborative projects, neurophysiological and behavioral data from different type of task conditions including those obtained in the current project (animals recorded both during task solving and interleaved sleep periods). Typically monkeys are surgically implanted with chronic multielectrode arrays. Sometime we add a mesoscopic full-region approach with epidural ECoG grids targeting the frontal lobe, and. EEG full-scalp recording.

 

Partnering Organisation

 

Publications

Pani P, Giarrocco F, Giamundo M, Montanari R, Brunamonti E, Ferraina S. Visual salience of the stop signal affects the neuronal dynamics of controlled inhibition. Scientific Reports, 2018, 8 (1), 14265.

 

Brunamonti E, Mione V, Di Bello F, Pani P, Genovesio A, Ferraina S. Neuronal modulation in the prefrontal cortex in a transitive inference task: evidence of neuronal correlates of mental schema management. Journal of Neuroscience, 2016, 36 (4), 1223-1236.

 

Papazachariadis O, Dante V, Verschure PFMJ, Del Giudice P, Ferraina S. iTBS-induced LTP-like plasticity parallels oscillatory activity changes in the primary sensory and motor areas of macaque monkeys. PloS one, 2014, 9 (11), e112504.

 

Pani P, Di Bello F, Brunamonti E, D’Andrea V, Papazachariadis O, Ferraina S. Alpha-and beta-band oscillations subserve different processes in reactive control of limb movements

Frontiers in behavioral neuroscience, 2014, 8, 383.

 

Mattia M, Pani P, Mirabella G, Costa S, Del Giudice P, Ferraina S. Heterogeneous attractor cell assemblies for motor planning in premotor cortex. Journal of Neuroscience, 2013, 33 (27), 11155-11168.

 

Marcos E, Pani P, Brunamonti E, Deco G, Ferraina S, Verschure PFMJ. Neural variability in premotor cortex is modulated by trial history and predicts behavioral performance. Neuron, 2013, 78 (2), 249-255.