Van subsidie naar outputfinanciering en businessplan

In 1999 werd de bibliotheek van het KIT geconfronteerd met veranderend subsidiebeleid: de overeenkomst voor ‘onbepaalde duur’ werd opgezegd. Subsidie voor capaciteit (input) werd omgezet in financiering van producten (output). Een veranderingsproces, begeleid door adviesbureaus, werd ingezet om gesubsidieerde activiteiten te definiëren als producten. Ieder product werd volgens een format omschreven, gekwantificeerd, en voorzien van kwaliteitscriteria, meetmethode en prijs. Per vierkante meter, werkplek en medewerker zijn overheadkosten berekend om integrale kostprijzen vast te stellen per product ter vergelijking met prijzen elders (benchmarking). Outputfinanciering heeft geleid tot transparantie voor de opdrachtgever. Ook bij de opdrachtnemer is sprake van positieve effecten: bij de leiding t.a.v. management en kwaliteitsbeheer van producten, bij medewerkers vanwege een helder productplan en de eigen verantwoordelijkheden daarin voor planning en uitvoering. Nadat het proces succesvol is doorlopen, wordt een volgende stap noodzakelijk omdat de opdrachtgever prijsstijgingen niet (volledig) compenseert. Additionele inkomsten zullen inkrimping en (deeltijd)ontslag moeten voorkomen

Awakening: Predicting external stimulation to force transitions between different brain states

A fundamental problem in systems neuroscience is how to force a transition from one brain state to another by external driven stimulation in, for example, wakefulness, sleep, coma, or neuropsychiatric diseases. This requires a quantitative and robust definition of a brain state, which has so far proven elusive. Here, we provide such a definition, which, together with whole-brain modeling, permits the systematic study in silico of how simulated brain stimulation can force transitions between different brain states in humans. Specifically, we use a unique neuroimaging dataset of human sleep to systematically investigate where to stimulate the brain to force an awakening of the human sleeping brain and vice versa. We show where this is possible using a definition of a brain state as an ensemble of "metastable substates," each with a probabilistic stability and occurrence frequency fitted by a generative whole-brain model, fine-tuned on the basis of the effective connectivity. Given the biophysical limitations of direct electrical stimulation (DES) of microcircuits, this opens exciting possibilities for discovering stimulation targets and selecting connectivity patterns that can ensure propagation of DES-induced neural excitation, potentially making it possible to create awakenings from complex cases of brain injury.Spanish Research Project PSI2016-75688-P (Agencia Estatal de Investigación/Fondo Europeo de Desarrollo Regional, European Union); by the European Union’s Horizon 2020 Re-search and Innovation Programme under Grant Agreements 720270 (Hu-man Brain Project [HBP] SGA1) and 785907 (HBP SGA2); and by the CatalanAgency for Management of University and Research Grants Programme 2017 SGR 1545. J. Cabral is supported by Portuguese Foundation for Sci-ence and Technology CEECIND/03325/2017, Portugal. M.L.K. is supportedby the European Research Council Consolidator Grant: CAREGIVING (615539) and Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117)

Novel fingerprinting method characterises the necessary and sufficient structural connectivity from deep brain stimulation electrodes for a successful outcome

Deep brain stimulation (DBS) is a remarkably effective clinical tool, used primarily for movement disorders. DBS relies on precise targeting of specific brain regions to rebalance the oscillatory behaviour of whole-brain neural networks. Traditionally, DBS targeting has been based upon animal models (such as MPTP for Parkinson's disease) but has also been the result of serendipity during human lesional neurosurgery. There are, however, no good animal models of psychiatric disorders such as depression and schizophrenia, and progress in this area has been slow. In this paper, we use advanced tractography combined with whole-brain anatomical parcellation to provide a rational foundation for identifying the connectivity 'fingerprint' of existing, successful DBS targets. This knowledge can then be used pre-surgically and even potentially for the discovery of novel targets. First, using data from our recent case series of cingulate DBS for patients with treatment-resistant chronic pain, we demonstrate how to identify the structural 'fingerprints' of existing successful and unsuccessful DBS targets in terms of their connectivity to other brain regions, as defined by the whole-brain anatomical parcellation. Second, we use a number of different strategies to identify the successful fingerprints of structural connectivity across four patients with successful outcomes compared with two patients with unsuccessful outcomes. This fingerprinting method can potentially be used pre-surgically to account for a patient's individual connectivity and identify the best DBS target. Ultimately, our novel fingerprinting method could be combined with advanced whole-brain computational modelling of the spontaneous dynamics arising from the structural changes in disease, to provide new insights and potentially new targets for hitherto impenetrable neuropsychiatric disorders

Uncovering the underlying mechanisms and whole-brain dynamics of deep brain stimulation for Parkinson's disease

Deep brain stimulation (DBS) for Parkinson's disease is a highly effective treatment in controlling otherwise debilitating symptoms. Yet the underlying brain mechanisms are currently not well understood. Whole-brain computational modeling was used to disclose the effects of DBS during resting-state functional Magnetic Resonance Imaging in ten patients with Parkinson's disease. Specifically, we explored the local and global impact that DBS has in creating asynchronous, stable or critical oscillatory conditions using a supercritical bifurcation model. We found that DBS shifts global brain dynamics of patients towards a Healthy regime. This effect was more pronounced in very specific brain areas such as the thalamus, globus pallidus and orbitofrontal regions of the right hemisphere (with the left hemisphere not analyzed given artifacts arising from the electrode lead). Global aspects of integration and synchronization were also rebalanced. Empirically, we found higher communicability and coherence brain measures during DBS-ON compared to DBS-OFF. Finally, using our model as a framework, artificial in silico DBS was applied to find potential alternative target areas for stimulation and whole-brain rebalancing. These results offer important insights into the underlying large-scale effects of DBS as well as in finding novel stimulation targets, which may offer a route to more efficacious treatmentsIn this work, Gustavo Deco is supported by the ERC Advanced Grant: DYSTRUCTURE (n. 295129), by the Spanish Research Project PSI2016-75688-P and by the the European Union's Horizon 2020 research and innovation programme under grant agreement n. 720270 (HBP SGA1). Morten Kringelbach is supported by the ERC Consolidator Grant CAREGIVING (n. 615539) and the Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117). Victor M Saenger is supported by the Research Personnel Training program PSI2013-42091-P funded by the Spanish Ministry of Economy and Competitiveness.info:eu-repo/semantics/publishedVersio

How structure sculpts function: Unveiling the contribution of anatomical connectivity to the brain's spontaneous correlation structure

Intrinsic brain activity is characterized by highly organized co-activations between different regions, forming clustered spatial patterns referred to as resting-state networks. The observed co-activation patterns are sustained by the intricate fabric of millions of interconnected neurons constituting the brain's wiring diagram. However, as for other real networks, the relationship between the connectional structure and the emergent collective dynamics still evades complete understanding. Here, we show that it is possible to estimate the expected pair-wise correlations that a network tends to generate thanks to the underlying path structure. We start from the assumption that in order for two nodes to exhibit correlated activity, they must be exposed to similar input patterns from the entire network. We then acknowledge that information rarely spreads only along a unique route but rather travels along all possible paths. In real networks, the strength of local perturbations tends to decay as they propagate away from the sources, leading to a progressive attenuation of the original information content and, thus, of their influence. Accordingly, we define a novel graph measure, topological similarity, which quantifies the propensity of two nodes to dynamically correlate as a function of the resemblance of the overall influences they are expected to receive due to the underlying structure of the network. Applied to the human brain, we find that the similarity of whole-network inputs, estimated from the topology of the anatomical connectome, plays an important role in sculpting the backbone pattern of time-average correlations observed at rest.This work was supported by (R.G.B.) the FI-DGR scholarship of the Catalan Government through the Age`ncia de Gestio d’Ajuts Universitari i de Recerca, under Agreement No. 2013FI-B1-00099, (G.Z.L.) the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 720270 (HBP SGA1), (G.D.) the European Research Council Advanced Grant: DYSTRUCTURE (295129) and the Spanish Research Project No. PSI2013- 42091-P, (Z.K.) European Community’s Seventh Framework Programme [FP7/2007-2013] under agreement PITN-GA- 2011-290011, (V.M.K.) European Community’s Seventh Framework Programme [FP7/2007-2013] under Agreement No. PITN-GA-2012-316746 and (M.L.K.) by the European Research Council Consolidator Grant No. CAREGIVING (615539)