Saenger, V.M., Kahan, J., Foltynie, T., Friston, K., Aziz, T.Z., Green, A.L., Van Hartevelt, T.J., Cabral, J., Stevner, A.B.A., Fernandes, H.M., Mancini, L., Thornton, J., Yousry, T., Limousin, P., Zrinzo, L., Hariz, M., Marques, P., Sousa, N., Kringelbach, M.L. & Deco, G. (2017). Uncovering the underlying mechanisms and whole-brain dynamics of deep brain stimulation for Parkinson's disease. Scientific Reports, 7: 9882.
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 treatments.
Keywords: Deep brain stimulation, fMRI, whole-brain modelling, dynamics, Parkinson’s disease
Van Hartevelt, T.J., Fernandes, H.M., Stevner, A., Deco, G. & Kringelbach, M.L. (2017). Neural plasticity in human brain connectivity: the effects of deep brain stimulation. In: The Rewiring Brain: A Computational Approach to Structural Plasticity in the Adult Brain. (Van Ooyen, A. and Butz-Ostendorf, M., eds.), Academic Press, pp. 527-546.
Neural plasticity in adult humans is no longer believed to be impossible. The adult brain shows neuronal regeneration and plasticity in a number of domains. We know that certain disorders or accidents can change the brain in a malicious way. However, in more recent years we have come to learn that formation of new neurons also occurs in adults and that, for example, learning tasks can affect the structure of the brain and reorganise the brain network. The best example of this happens on the micro scale with task repetition leading to strengthened neural connections. This mechanism is often referred to as Hebbian learning although other mechanisms could also be at play. Recent studies have shown that these changes in the brain can occur on a macro scale following deep brain stimulation (DBS). Following constant DBS (analogous to repetition in learning) some connections between brain areas are strengthened resulting in long-term structural changes in the brain on the macro scale.
Keywords: Structural plasticity, deep brain stimulation, Hebbian learning, DTI
Bettinardi, R.G., Deco, G., Karlaftis, V.M., Van Hartevelt, T.J., Fernandes, H.M., Kourtzi, Z., Kringelbach, M.L. & Zamora-Lopez, G. (2017). How structure sculpts function: unveiling the contribution of anatomical connectivity to the brain's spontaneous correlation structure. Chaos, 27: 047409.
Intrinsic brain activity is characterized by highly organised 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 an 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.
Keywords: Structural connectivity, functional connectivity, topological similarity, rs-fMRI, DTI
Deco, G., Cabral, J., Woolrich, M.W., Stevner, A.B.A., Van Hartevelt, T.J. & Kringelbach, M.L. (2017). Single or multiple frequency generators in on-going brain activity: A mechanistic whole-brain model of empirical MEG data. NeuroImage, 152: 538-550.
During rest, envelopes of band-limited on-going MEG signals co-vary across the brain in consistent patterns, which have been related to resting-state networks measured with fMRI. To investigate the genesis of such envelope correlations, we consider a whole-brain network model assuming two distinct fundamental scenarios: one where each brain area generates oscillations in a single frequency, and a novel one where each brain area can generate oscillations in multiple frequency bands. The models share, as a common generator of damped oscillations, the normal form of a supercritical Hopf bifurcation operating at the critical border between the steady state and the oscillatory regime. The envelopes of the simulated signals are compared with empirical MEG data using new methods to analyse the envelope dynamics in terms of their phase coherence and stability across the spectrum of carrier frequencies.
Considering the whole-brain model with a single frequency generator in each brain area, we obtain the best fit with the empirical MEG data when the fundamental frequency is tuned at 12Hz. However, when multiple frequency generators are placed at each local brain area, we obtain an improved fit of the spatio-temporal structure of on-going MEG data across all frequency bands. Our results indicate that the brain is likely to operate on multiple frequency channels during rest, introducing a novel dimension for future models of large-scale brain activity.
Keywords: Resting-state MEG activity, envelope, frequency generator, whole-brain modelling, Hopf model
Fjaeldstad, A., Fernandes, H.M., Van Hartevelt, T.J., Gleesborg, C., Møller, A., Ovesen, T. & Kringelbach, M.L. (2017). Brain fingerprints of olfaction: a novel structural method for assessing olfactory cortical networks in health and disease. Scientific Reports, 7: 42534.
Olfactory deficit is a common (often prodromal) symptom of neurodegenerative or psychiatric disorders. As such, olfaction could have great potential as an early biomarker of disease, for example using neuroimaging to investigate the breakdown of structural connectivity profile of the primary olfactory networks. We investigated the suitability for this purpose in two existing neuroimaging maps of olfactory networks.
We found problems with both existing neuroimaging maps in terms of their structural connectivity to known secondary olfactory networks. Based on findings, we were able to merge the existing maps to a new template map of olfactory networks with connections to all key secondary olfactory networks.
We introduce a new method that combines diffusion tensor imaging with probabilistic tractography and pattern recognition techniques. This method can obtain comprehensive and reliable fingerprints of the structural connectivity underlying the neural processing of olfactory stimuli in normosmic adults.
Combining the novel proposed method for structural fingerprinting with the template map of olfactory networks has great potential to be used for future neuroimaging investigations of olfactory function in disease. With time, the proposed method may even come to serve as structural biomarker for early detection of disease.
Keywords: Olfactory cortex, DTI, fingerprint, brain connectivity
Deco, G., Van Hartevelt, T.J., Fernandes, H.M., Stevner, A. & Kringelbach, M.L. (2017). The most relevant human brain regions for functional connectivity: Evidence for a dynamical workspace of binding nodes from whole-brain computational modelling. NeuroImage, 146: 197-210.
In order to promote survival through flexible cognition and goal-directed behaviour, the brain has to optimize segregation and integration of information into coherent, distributed dynamical states. Certain organizational features of the brain have been proposed to be essential to facilitate cognitive flexibility, especially hub regions in the so-called rich club with shows dense interconnectivity. These structural hubs have been suggested to be vital for integration and segregation of information. Yet, this has not been evaluated in terms of resulting functional temporal dynamics. A complementary measure covering the temporal aspects of functional connectivity could thus bring new insights into a more complete picture of the integrative nature of brain networks. Here, we use causal whole-brain computational modelling to determine the functional dynamical significance of the rich club and compare this to a new measure of the most functionally relevant brain regions for binding information over time (“dynamical workspace of binding nodes”). We found that removal of the iteratively generated workspace of binding nodes impacts significantly more on measures of integration and encoding of information capability than the removal of the rich club regions. While the rich club procedure produced almost half of the binding nodes, the remaining nodes have low degree yet still play a significant role in the workspace essential for binding information over time and as such goes beyond a description of the structural backbone.
Keywords: Functional connectivity, binding nodes, computational modelling, integration
Lord, L.D., Expert, P., Fernandes H.M., Petri G., Van Hartevelt T.J., Vaccarino, F., Deco, G., Turkheimer, F. & Kringelbach, M.L. (2016). Insights into Brain Architectures from the Homological Scaffolds of Functional Connectivity Networks. Frontiers in Systems Neuroscience, 10:85.
In recent years, the application of network analysis to neuroimaging data has provided useful insights about the brain’s functional and structural organization in both health and disease. This has proven a significant paradigm shift from the study of individual brain regions in isolation. Graph-based models of the brain consist of vertices, which represent distinct brain areas, and edges which encode the presence (or absence) of a structural or functional relationship between each pair of vertices. By definition, any graph metric will be defined upon this dyadic representation of the brain activity. It is however unclear to what extent these dyadic relationships can capture the brain’s complex functional architecture and the encoding of information in distributed networks. Moreover, because network representations of global brain activity are derived from measures that have a continuous response (i.e., interregional BOLD signals), it is methodologically complex to characterize the architecture of functional networks using traditional graph-based approaches. In the present study, we investigate the relationship between standard network metrics computed from dyadic interactions in a functional network, and a metric defined on the persistence homological scaffold of the network, which is a summary of the persistent homology structure of resting-state fMRI data. The persistence homological scaffold is a summary network that differs in important ways from the standard network representations of functional neuroimaging data: (i) it is constructed using the information from all edge weights comprised in the original network without applying an ad hoc threshold and (ii) as a summary of persistent homology, it considers the contributions of simplicial structures to the network organization rather than dyadic edge-vertices interactions. We investigated the information domain captured by the persistence homological scaffold by computing the strength of each node in the scaffold and comparing it to local graph metrics traditionally employed in neuroimaging studies. We conclude that the persistence scaffold enables the identification of network elements that may support the functional integration of information across distributed brain networks.
Keywords: functional connectivity, fMRI, persistent homology, homological scaffold, integration and segregation
Zou, L.Q., Van Hartevelt, T.J., Kringelbach, M.L., Cheung, E.F.C. & Chan, R.C.K. (2016). The Neural Mechanism of Olfactory Hedonic Processing and Judgment of Pleasant Odors: An Activation Likelihood Estimation Meta-analysis. Neuropsychology, 30(8): 970-979.
Objective: Pleasure is essential to normal healthy life. Olfaction, as 1 of the neurobehavioral probes of hedonic capacity, has a unique advantage compared to other sensory modalities. However, it is unclear how olfactory hedonic information is processed in the brain. This study aimed to investigate olfactory hedonic processing in the human brain. Method: We conducted an activation likelihood estimation (ALE) meta-analysis on 16 functional imaging studies that examined brain activation in olfactory hedonic processing-related tasks in healthy adults. Results: The results show that there is a core olfactory hedonic processing network, which consists of the bilateral parahippocampal gyrus/amygdala (BA34), the left middle frontal gyrus (BA6), the right middle frontal gyrus/lateral orbitofrontal cortex (OFC; BA10), the bilateral cingulate gyrus (BA32), the right lentiform nucleus/lateral globus pallidus, the right medial frontal gyrus/medial OFC (BA11), the left superior frontal gyrus (BA10), and the right insula (BA13). Moreover, our findings highlight that the right hemisphere is predominant in explicit odor hedonic judgment. Finally, the results indicate that there are significant differences in brain activation for hedonic judgment and passive smelling. Conclusion: These results support the hypothesis that the OFC plays a key role in explicit hedonic judgment.
Keywords: Olfactory, hedonic processing, activation likelihood estimation, orbitofrontal cortex, amygdala
Fjaeldstad, A., Van Hartevelt, T.J. & Kringelbach, M.L. (2016). Pleasure of Food in the Brain. In: Multisensory Flavour Perception: Pleasure of Flavour in the Brain. (Spence, C., Piqueras-Fiszman, B. and Sykes, R. eds.), Academic Press, pp. 211-234.
The survival of individuals as well as species relies on a few fundamental necessities. In order to survive, we need food, procreation and social interactions. These are arguably also the most pleasurable activities and they all are known to stimulate an array of sensory systems. The multisensory perception of food is very complex and includes more than just smell and taste. Flavour perception relies also on visual and auditory input. Food can be highly pleasurable and the act of eating extremely satisfying. The eating process can be described as a cyclic process of hunger, consumption and satiation. These three stages can also be described as the wanting, liking and learning phases, though learning does occur throughout the entire eating process, it is strongest in the later satiation phase. The related hedonic processing takes place in the orbitofrontal cortex (a crucial area for smell) where other multimodal stimuli are processed as well as reward and pleasure.
Keywords: Sensory perception, smell, taste, hedonic network, computational processing
Young, K.S., Parsons, C.E., Jegindoe Elmholdt, E.-M., Woolrich, M.W., Van Hartevelt, T.J., Stevner, A.B.A., Stein, A. & Kringelbach, M.L. (2016). Evidence for a caregiving instinct: rapid differentiation of infant from adult vocalisations using magnetoencephalography. Cerebral Cortex, 26(3): 1309-1321.
Crying is the most salient vocal signal of distress. The cries of a newborn infant alert adult listeners and often elicit caregiving behavior. For the parent, rapid responding to an infant in distress is an adaptive behavior, functioning to ensure offspring survival. The ability to react rapidly requires quick recognition and evaluation of stimuli followed by a co-ordinated motor response. Previous neuroimaging research has demonstrated early specialized activity in response to infant faces. Using magnetoencephalography, we found similarly early (100-200 ms) differences in neural responses to infant and adult cry vocalizations in auditory, emotional, and motor cortical brain regions.We propose that this early differential activity may help to rapidly identify infant cries and engage affective and motor neural circuitry to promote adaptive behavioral responding, before conscious awareness. These differenceswere observed in adults whowere not parents, perhaps indicative of a universal brain-based “caregiving instinct.”
Keywords: caregiving, infant, magnetoencephalography, orbitofrontal cortex, vocalization
Boccard, S.G.J., Fernandes, H.M., Jbabdi, S., Van Hartevelt, T.J., Kringelbach, M.L., Quaghebeur, G., Moir, L., Piqueras Mancebo, V., Pereira, E.A.C., Fitzgerald, J.J., Green, A.L. & Aziz, T.Z. (2016). A tractography study of Deep Brain Stimulation of the Anterior Cingulate Cortex in chronic pain: a key to improve the targeting. World Neurosurgery, 86: 361-370.e3.
Background: Deep brain stimulation (DBS) of the anterior cingulate cortex (ACC) is a new treatment for alleviating intractable neuropathic pain. However, it fails to help some patients. The large size of the ACC and the intersubject variability make it difficult to determine the optimal site to position DBS electrodes. The aim of this work was therefore to compare the ACC connectivity of patients with successful versus unsuccessful DBS outcomes to help guide future electrode placement. Methods: Diffusion magnetic resonance imaging (dMRI) and probabilistic tractography were performed preoperatively in 8 chronic pain patients (age 53.4 6.1 years, 2 females) with ACC DBS, of whom 6 had successful (SO) and 2 unsuccessful outcomes (UOs) during a period of trialing. Results: The number of patients was too small to demonstrate any statistically significant differences. Nevertheless, we observed differences between patients with successful and unsuccessful outcomes in the fiber tract projections emanating from the volume of activated tissue around the electrodes. A strong connectivity to the precuneus area seems to predict unsuccessful outcomes in our patients (UO: 160n/SO: 27n), with (n), the number of streamlines per nonzero voxel. On the other hand, connectivity to the thalamus and brainstem through the medial forebrain bundle (MFB) was only observed in SO patients. Conclusions: These findings could help improve presurgical planning by optimizing electrode placement, to selectively target the tracts that help to relieve patients’ pain and to avoid those leading to unwanted effects.
Keywords: Anterior cingulate cortex, deep brain stimulation, precuneus, targeting, tractography
Stark, E.A., Parsons, C.E., Van Hartevelt, T.J., Charquero Ballester, M., McManners, H., Ehlers, A., Stein, A. & Kringelbach, M.L. (2015). Post-traumatic stress influences the brain even in the absence of symptoms: A systematic, quantitative meta-analysis of neuroimaging studies. Neuroscience and Biobehavioral Reviews, 56: 207-221.
Stress affects brain function, and may lead to post-traumatic stress disorder (PTSD). Considerable empirical data for the neurobiology of PTSD has been derived from neuroimaging studies, although findings have proven inconsistent. We used an activation likelihood estimation analysis to explore differences in brain activity between adults with and without PTSD in response to affective stimuli. We separated studies by type of control group: trauma-exposed and trauma-naïve. This revealed distinct patterns of differences in functional activity. Compared to trauma-exposed controls, regions of the basal ganglia were differentially active in PTSD; whereas the comparison with trauma-naïve controls revealed differential involvement in the right anterior insula, precuneus, cingulate and orbitofrontal cortices known to be involved in emotional regulation. Changes in activity in the amygdala and parahippocampal cortex distinguished PTSD from both control groups. Results suggest that trauma has a measurable, enduring effect upon the functional dynamics of the brain, even in individuals who experience trauma but do not develop PTSD. These findings contribute to the understanding of whole-brain network activity following trauma, and its transition to clinical PTSD.
Keywords: PTSD, trauma, neuroimaging, fMRI, meta-analysis, activation likelihood estimation, basal ganglia, precuneus, OFC, whole-brain network activity
Van Hartevelt, T.J., Cabral, J., Møller, A., FitzGerald, J.J., Green, A.L. Aziz, T.Z. Deco, G. & Kringelbach, M.L. (2015). Evidence from a rare case study for Hebbian-like changes in structural connectivity induced by long-term deep brain stimulation. Frontiers in Behavioral Neuroscience, 9:167.
It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e., where measurable changes in structural connectivity (SC) are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS) suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson’s disease (PD) before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus (STN) to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the SC towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in SC allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.
Keywords: Deep brain stimulation, Hebbian-like learning, Parkinson’s disease, DTI, subthalamic nucleus
Fjaeldstad, A., Kjaergaard, T., Van Hartevelt, T.J., Møller, A., Kringelbach, M.L. & Ovesen, T. (2015). Olfactory screening: Validation of Sniffin’ Sticks in Denmark. Clinical Otolaryngology, 40(6): 545-550.
Objectives: The Sniffin’ Sticks 12-identification test (SIT- 12) is the most commonly applied Danish olfaction screening tool; however, it has never been validated in a Danish population. The screening score depends on familiarity with descriptors, which is strongly influenced by linguistic and cultural factors, why validation is mandatory. This study aimed to validate the SIT-12 in a Danish population. Design: Prospective controlled study. Setting: Otorhinolaryngology department. Participants: The SIT-12 was applied to 100 normosmic, healthy adult Danish participants. Main outcome measures: Choice of descriptors was registered, along with nasal endoscopic examination, screening for cognitive impairment, depression and sinonasal symptoms. Descriptors of the original version of SIT-12 were evaluated in 50 participants, and misleading descriptors were identified. Modifications to these descriptors were subsequently validated in a comparable group of 50 participants. Results: Mean odorant identification score in the evaluation group was 11.0 of a possible 12, and 11.6 in the validation group (P < 0.0001). Among all odorant identi- fication errors in the evaluation group, 60% were due to two incorrect descriptors having close resemblance to the correct descriptors, lemon and cinnamon. Two additional descriptors were unfamiliar to more than half the participants. There was a significant difference in the distribution of wrong identification answers between odorants in the evaluation group (P < 0.001), but not in the validation group. Conclusions: The identified systematically wrong descriptors have been modified and validated in the Danish SIT-12.
Keywords: Olfaction, Sniffin’ Sticks, odour identification
Van Hartevelt, T.J. & Kringelbach, M.L. (2015). The Olfactory Cortex. In: Brain Mapping: An Encyclopedic Reference, Volume 2. (Toga, A.W., ed.), Academic Press, pp. 347-355.
The olfactory system is a unique and important sense which has, however, been underrepresented in research. It plays a crucial role in food selection and reproduction, ensuring survival for both the individual and the species. The olfactory system is unique compared to the other senses in that, among other things, information is not relayed via the thalamus, but instead projected directly to cortical regions such as the orbitofrontal cortex. This article describes the information processing in the olfactory system from the olfactory epithelium to the cortical projection areas, based on translational research and imaging studies, and details the multimodal interactions between olfaction and gustation. Equally, we describe the breakdown of the sense of smell that can be devastating and is implicated in anhedonia, the lack of pleasure, a key feature of mental illness.
Keywords: Food, hedonia, multimodal, olfaction, olfactory bulb, orbitofrontal cortex, piriform cortex, primary olfactory cortex
Fernandes, H.M., Van Hartevelt, T.J., Boccard, S.G.J., Owen, S.L.F., Cabral, J., Deco, G., Green, A.L., FitzGerald, J.J., Aziz, T.Z. & Kringelbach, M.L. (2015). Novel fingerprinting method characterises the necessary and sufficient structural connectivity from deep brain stimulation electrodes for a successful outcome. New Journal of Physics, (17): 015001.
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.
Keywords: Deep brain stimulation, fingerprint, diffusion imaging
Morein-Zamir, S., Dodds, C., Van Hartevelt, T.J., Schwarzkopf, W., Sahakian, B.J., Müller, U. & Robbins, T.W. (2014). Hypoactivation in right inferior frontal cortex is specifically associated with motor response inhibition in adult ADHD. Human Brain Mapping, 35(10): 5141-5152.
Adult ADHD has been linked to impaired motor response inhibition and reduced associated activation in the right inferior frontal cortex (IFC). However, it is unclear whether abnormal inferior frontal activation in adult ADHD is specifically related to a response inhibition deficit or reflects a more general deficit in attentional processing. Using functional magnetic resonance imaging, we tested a group of 19 ADHD patients with no comorbidities and a group of 19 healthy control volunteers on a modified go/no-go task that has been shown previously to distinguish between cortical responses related to response inhibition and attentional shifting. Relative to the healthy controls, ADHD patients showed increased commission errors and reduced activation in inferior frontal cortex during response inhibition. Crucially, this reduced activation was observed when controlling for attentional processing, suggesting that hypoactivation in right IFC in ADHD is specifically related to impaired response inhibition. The results are consistent with the notion of a selective neurocognitive deficit in response inhibition in adult ADHD associated with abnormal functional activation in the prefrontal cortex, whilst ruling out likely group differences in attentional orienting, arousal and motivation.
Keywords: Attention deficit disorder with hyperactivity, magnetic resonance imaging, prefrontal cortex, attention, inhibition control, cognitive flexibility, executive-function
Van Hartevelt, T.J. (2014). Olfactory Functioning in Parkinson's Disease: The Effects of Deep Brain Stimulation. Aarhus University
The sense of smell is vital for species survival in terms of food selection and detection as well as procreation. Disorders of the sense of smell are not uncommon and can have a significant effect on general health and well-being including quality of life. In Parkinson’s disease (PD), the loss of sense of smell is one of the most common and earliest symptoms, appearing approximately 5 years prior to any motor symptoms. Deep brain stimulation (DBS) has proven remarkably effective in alleviating the symptoms of PD including olfactory dysfunction. This remains a difficult area to research with many unknowns, not only the normal spatiotemporal processing of olfaction in humans, but also the mechanisms underlying the dysfunction in PD and the alleviation by DBS. This thesis aims to address these difficulties by developing the necessary tools to be able to study spatiotemporal aspects of olfactory function in PD patients with DBS. The first two studies in this dissertation are reviews of the olfactory system and one of its most vital roles in eating behaviour. These studies indicate the extent of the olfactory system in terms of anatomy and implication in certain behaviours. In the third study the long-term effects of DBS for PD are investigated. The results show that after five months of continuous DBS, olfactory areas known to be affected in PD show significant structural changes. The fourth study uses advanced whole-brain computational modeling to uncover the mechanisms of continuous DBS of the subthalamic nucleus which leads to significant changes in brain regions including the thalamus, suggestive of long-term Hebbian long-term structural changes. In the fifth study, I return to olfaction to explore a new paradigm regarding the use of magnetoencephalography (MEG) to investigate the spatiotemporal aspects of olfactory functioning in healthy subjects. The results show significant differences between pleasant and unpleasant odours in the orbitofrontal cortex early after stimulus onset. This novel paradigm indicates the possibility to unravel the spatiotemporal aspects of normal olfaction as well as the underlying mechanisms of olfactory dysfunction in PD patients with DBS, where magnetic imaging techniques are not readily available due to the severe risk related to the electrodes.
Keywords: Deep brain stimulation, Parkinson’s disease, olfactory functioning, Hebbian learning, neural plasticity, network analysis, DTI, MRI, MEG
Boccard, S.G.J., Fitzgerald, J.J., Pereira, E.A.C., Moir, L., Van Hartevelt, T.J., Kringelbach, M.L., Green, A.L. & Aziz, T.Z. (2014). Targeting the Affective Component of Chronic Pain: A Case Series of Deep Brain Stimulation of the Anterior Cingulate Cortex. Neurosurgery, 74(6): 628-637.
Background: Deep brain stimulation (DBS) has shown considerable promise for relieving nociceptive and neuropathic symptoms of refractory chronic pain. Nevertheless, for some patients, standard DBS for pain remains poorly efficacious. Pain is a multidimensional experience with an affective component: the unpleasantness. The anterior cingulate cortex (ACC) is a structure involved in this affective component, and targeting it may relieve patients’ pain. Objective: To describe the first case series of ACC DBS to relieve the affective component of chronic neuropathic pain. Methods: Sixteen patients (13 male and 3 female patients) with neuropathic pain underwent bilateral ACC DBS. The mean age at surgery was 48.7 years (range, 33-63 years). Patient-reported outcome measures were collected before and after surgery using a Visual Analog Scale, SF-36 quality of life survey, McGill Pain Questionnaire, and EQ-5D (EQ-5D and EQ-5D Health State) questionnaires. Results: Fifteen patients (93.3%) transitioned from externalized to fully internalized systems. Eleven patients had data to be analyzed with a mean follow-up of 13.2 months. Post-surgery, the Visual Analog Scale score dropped below 4 for 5 of the patients, with 1 patient free of pain. Highly significant improvement on the EQ-5D was observed (mean, +20.3%; range, +0% – +83%; P = .008). Moreover, statistically significant improvements were observed for the physical functioning and bodily pain domains of the SF-36 qualityof-life survey: mean, +64.7% (range, -8.9% – +276%; P = .015) and mean +39.0% (range, -33.8% – +159%; P = .050), respectively. Conclusion: Affective ACC DBS can relieve chronic neuropathic pain refractory to pharmacotherapy and restore quality of life.
Keywords: Anterior cingulate cortex, deep brain stimulation, neuropathic pain
Van Hartevelt, T.J., Cabral, J., Deco, G., Møller, A., Green, A.L., Aziz, T.Z. & Kringelbach, M.L. (2014). Neural plasticity in human brain connectivity: the effects of long term deep brain stimulation of the subthalamic nucleus in Parkinson's Disease. PLoS ONE, 9(1): e86496.
Background: Positive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson’s Disease. This allowed us to analyse the differences in structural connectivity before and after deep brain stimulation. Further, a computational model of spontaneous brain activity was used to estimate the changes in functional connectivity arising from the specific changes in structural connectivity. Results: We found significant localised structural changes as a result of long-term deep brain stimulation. These changes were found in sensory-motor, prefrontal/limbic, and olfactory brain regions which are known to be affected in Parkinson’s Disease. The nature of these changes was an increase of nodal efficiency in most areas and a decrease of nodal efficiency in the precentral sensory-motor area. Importantly, the computational model clearly shows the impact of deep brain stimulation-induced structural alterations on functional brain changes, which is to shift the neural dynamics back towards a healthy regime. The results demonstrate that deep brain stimulation in Parkinson’s Disease leads to a topological reorganisation towards healthy bifurcation of the functional networks measured in controls, which suggests a potential neural mechanism for the alleviation of symptoms. Conclusions: The findings suggest that long-term deep brain stimulation has not only restorative effects on the structural connectivity, but also affects the functional connectivity at a global level. Overall, our results support causal changes in human neural plasticity after long-term deep brain stimulation and may help to identify the underlying mechanisms of deep brain stimulation.
Keywords: Deep brain stimulation, Parkinson’s disease, neural plasticity, DTI
Boccard, S.G.J., Pereira, E.A.C., Moir, L., Van Hartevelt, T.J., Kringelbach, M.L., FitzGerald, J.J., Baker, I.W., Green, A.L. & Aziz, T.Z. (2014). Deep Brain Stimulation of the anterior cingulate cortex: targeting the affective component of chronic pain. NeuroReport, 25(2): 83-88.
Deep brain stimulation (DBS) has shown promise for relieving nociceptive and neuropathic symptoms of refractory chronic pain. We assessed the efficacy of a new target for the affective component of pain, the anterior cingulate cortex (ACC). A 49-year-old man with neuropathic pain underwent bilateral ACC DBS. Patientreported outcome measures were collected before and 2 years after surgery using a Visual Analogue Scale, ShortForm 36 quality of life survey, McGill pain questionnaire, EuroQol-5D questionnaires (EQ-5D; Health State) and neuropsychological assessments. The patient improved with DBS. Two years after surgery, the Visual Analogue Scale decreased from 6.7 to 3.0, McGill pain questionnaire improved by 42% and EQ-5D Health State increased by 150%. Stimulating the ACC at 130 Hz, 330 ls and 3 V facilitated neuropathic pain relief. The DBS remained efficacious during the 2-year follow-up period.
Keywords: Affective component, anterior cingulate cortex, deep brain stimulation, pain
Cabral, J., Fernandes, H.M., Van Hartevelt, T.J., James A.C., Kringelbach M.L. & Deco, G. (2013). Structural connectivity in schizophrenia and its impact on the dynamics of spontaneous functional networks. Chaos, 23(4): 046111.
The neuropathology of schizophrenia remains unclear. Some insight has come from modern neuroimaging techniques, which offer an unparalleled opportunity to explore in vivo the structure and function of the brain. Using functional magnetic resonance imaging, it has been found that the large-scale resting-state functional connectivity (rsFC) in schizophrenia — measured as the temporal correlations of the blood-oxygen-level-dependent (BOLD) signal — exhibit altered network topology, with lower small-world index. The origin of these rsFC alterations and link with the underlying structural connectivity remain unclear. In this work, we used a computational model of spontaneous large-scale brain activity to explore the role of the structural connectivity in the large-scale dynamics of the brain in health and schizophrenia. The structural connectomes from 15 adolescent patients with early-onset schizophrenia and 15 age- and gender-matched controls were built from diffusion tensor imaging data to detect the white matter tracts between 90 brain areas. Brain areas, simulated using a reduced dynamic mean-field model, receive excitatory input from other areas in proportion to the number of fibre tracts between them. The simulated mean field activity was transformed into BOLD signal, and the properties of the simulated functional networks were analyzed. Our results suggest that the functional alterations observed in schizophrenia are not directly linked to alterations in the structural topology. Instead, subtly randomized and less small-world functional networks appear when the brain operates with lower global coupling, which shifts the dynamics from the optimal healthy regime.
Keywords: Brain, networks, mean field theory, medical imaging, cluster analysis
Van Hartevelt, T.J. & Kringelbach, M.L. (2012). The Olfactory System. In: The Human Nervous System, 3rd edition. (Mai, J.K. and Paxinos, G., eds.), Elsevier Academic Press, pp. 1219-1238.
The olfactory system is a unique and important sense which has, however, been underrepresented in research. It plays a crucial role in food selection and reproduction ensuring survival for both the individual and the species. The olfactory system is unique compared to the other senses in that, amongst other things, information is not relayed via the thalamus, but instead projected directly to cortical regions such as the orbitofrontal cortex. This chapter describes the information processing in the olfactory system from the olfactory epithelium to the cortical projection areas, based on translational research and imaging studies, as well as describing the multimodal interactions between olfaction and gustation. Equally, we describe the breakdown of the sense of smell that can be devastating and is implicated in anhedonia, the lack of pleasure, a key feature of mental illness.
Keywords: Olfaction, anatomy, hedonia, smell
Kringelbach, M.L., Stein, A. & Van Hartevelt, T.J. (2012). The functional human neuroanatomy of food pleasure cycles. Physiology & Behavior, 106(3): 307-316.
Food ensures our survival and is a potential source of pleasure and general well-being. In order to survive, the human brain is required to optimize the resource allocation such that rewards are pursued when relevant. This means that food intake follows a similar cyclical time course to other rewards with phases related to expectation, consummation and satiety. Here we develop a multilevel model for the full cycle of eating behavior based on the evidence for the brain networks and mechanisms initiating, sustaining and terminating the various phases of eating. We concentrate on how the underlying reward mechanisms of wanting, liking and learning lead to how human food intake is governed by both hedonic and homeostatic principles. We describe five of the main processing principles controlling food intake: hunger and attentional signal processing; motivation-independent discriminative processing; reward representations; learning-dependent multimodal sensory representations and hedonic experience. Overall, the evidence shows that while human food intake is complex, we are making progress in understanding the underlying mechanisms and that the brain networks supporting the food pleasure cycle are remarkably similar to those underlying the processing of other rewards.
Keywords: Pleasure cycle, satiety, satiation, hedonic, pleasure, food, multimodal integration, insula, operculum, orbitofronal cortex, cingulate cortex, wanting, liking, learning