Christiane Debono

Dr. Christiane Debono


Research Focus & Metrics

Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2004 in Nature Reviews Neuroscience
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Journal Article
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CDChristiane Debono
Christiane Debono
MTMaria Toledo-Rodriguez
Maria Toledo-Rodriguez
YWYun Wang
Yun Wang
AGAnirudh Gupta
Anirudh Gupta
GSGilad Silberberg
Gilad Silberberg
CWCaizhi Wu
Caizhi Wu

1 October 2015 in Cell
Verified
Journal Article
Closed access
CDChristiane Debono
Christiane Debono
EMEilif Muller
Eilif Muller
SRSrikanth Ramaswamy
Srikanth Ramaswamy
MRMichael W. Reimann
Michael W. Reimann
MAMarwan Abdellah
Marwan Abdellah
FSFelix Schürmann
Felix Schürmann

1 February 2006 in Nature Reviews Neuroscience
Verified
Journal Article
Closed access
CDChristiane Debono
Christiane Debono

7 March 2011 in Proceedings of the National Academy of Sciences
Verified
Journal Article
Closed access
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RPRodrigo Perin
Rodrigo Perin
TBThomas K. Berger
Thomas K. Berger
CDChristiane Debono
Christiane Debono
Neuronal circuitry is often considered a clean slate that can be dynamically and arbitrarily molded by experience. However, when we investigated synaptic connectivity in groups of pyramidal neurons in the neocortex, we found that both connectivity and synaptic weights were surprisingly predictable. Synaptic weights follow very closely the number of connections in a group of neurons, saturating after only 20% of possible connections are formed between neurons in a group. When we examined the network topology of connectivity between neurons, we found that the neurons cluster into small world networks that are not scale-free, with less than 2 degrees of separation. We found a simple clustering rule where connectivity is directly proportional to the number of common neighbors, which accounts for these small world networks and accurately predicts the connection probability between any two neurons. This pyramidal neuron network clusters into multiple groups of a few dozen neurons each. The neurons composing each group are surprisingly distributed, typically more than 100 μm apart, allowing for multiple groups to be interlaced in the same space. In summary, we discovered a synaptic organizing principle that groups neurons in a manner that is common across animals and hence, independent of individual experiences. We speculate that these elementary neuronal groups are prescribed Lego-like building blocks of perception and that acquired memory relies more on combining these elementary assemblies into higher-order constructs.

12 June 2017 in Frontiers in Computational Neuroscience
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Journal Article
Open access
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MRMichael W. Reimann
Michael W. Reimann
MNMax Nolte
Max Nolte
MSMartina Scolamiero
Martina Scolamiero
KTKatharine Turner
Katharine Turner
RPRodrigo Perin
Rodrigo Perin
CDChristiane Debono
Christiane Debono
The lack of a formal link between neural network structure and its emergent function has hampered our understanding of how the brain processes information. We have now come closer to describing such a link by taking the direction of synaptic transmission into account, constructing graphs of a network that reflect the direction of information flow, and analyzing these directed graphs using algebraic topology. Applying this approach to a local network of neurons in the neocortex revealed a remarkably intricate and previously unseen topology of synaptic connectivity. The synaptic network contains an abundance of cliques of neurons bound into cavities that guide the emergence of correlated activity. In response to stimuli, correlated activity binds synaptically connected neurons into functional cliques and cavities that evolve in a stereotypical sequence toward peak complexity. We propose that the brain processes stimuli by forming increasingly complex functional cliques and cavities.

23 November 2004 in The Journal of Physiology
Verified
Journal Article
Open access
PDF file
YWYun Wang
Yun Wang
MTMaria Toledo‐Rodriguez
Maria Toledo‐Rodriguez
AGAnirudh Gupta
Anirudh Gupta
CWCaizhi Wu
Caizhi Wu
GSGilad Silberberg
Gilad Silberberg
CDChristiane Debono
Christiane Debono
Whole‐cell patch‐clamp recordings followed by histochemical staining and single‐cell RT‐PCR were obtained from 180 Martinotti interneurones located in layers II to VI of the somatosensory cortex of Wistar rats (P13–P16) in order to examine their anatomical, electrophysiological and molecular properties. Martinotti cells (MCs) mostly displayed ovoid‐shaped somata, bitufted dendritic morphologies, and axons with characteristic spiny boutons projecting to layer I and spreading horizontally across neighbouring columns more than 1 mm. Electron microscopic examination of MC boutons revealed that all synapses were symmetrical and most synapses (71%) were formed onto dendritic shafts. MCs were found to contact tuft, apical and basal dendrites in multiple neocortical layers: layer II/III MCs targeted mostly layer I and to a lesser degree layer II/III; layer IV MCs targeted mostly layer IV and to a lesser degree layer I; layer V and VI MCs targeted mostly layer IV and layer I and to a lesser degree the layer in which their somata was located. MCs typically displayed spike train accommodation (90%; n= 127) in response to depolarizing somatic current injections, but some displayed non‐accommodating (8%) and a few displayed irregular spiking responses (2%). Some accommodating and irregular spiking MCs also responded initially with bursts (17%). Accommodating responses were found in all layers, non‐accommodating mostly in upper layers and bursting mostly in layer V. Single‐cell multiplex RT‐PCR performed on 63 MCs located throughout layers II–VI, revealed that all MCs were somatostatin (SOM) positive, and negative for parvalbumin (PV) as well as vasoactive intestinal peptide (VIP). Calbindin (CB), calretinin (CR), neuropeptide Y (NPY) and cholecystokinin (CCK) were co‐ expressed with SOM in some MCs. Some layer‐specific trends seem to exist. Finally, 24 accommodating MCs were examined for the expression of 26 ion channel genes. The ion channels with the highest expression in these MCs were (from highest to lowest); Caβ1, Kv3.3, HCN4, Caβ4, Kv3.2, Kv3.1, Kv2.1, HCN3, Caα1G, Kv3.4, Kv4.2, Kv1.1 and HCN2. In summary, this study provides the first detailed analysis of the anatomical, electrophysiological and molecular properties of Martinotti cells located in different neocortical layers. It is proposed that MCs are crucial interneurones for feedback inhibition in and between neocortical layers and columns.