Publications

Top10 Articles

Top10 Articles

Dynamic Coupling of Whole-Brain Systems

Dynamic Coupling of Whole-Brain Systems
2020
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Kringelbach M.L., Cruzat J., Cabral, J., Knudsen G.M., Carhart-Harris R.L., Whybrow P.C., Logothetis N.K. and Deco G. (2020) Dynamic Coupling of Whole-Brain Neuronal and Neurotransmitter Systems, PNAS, in press.

Abstract:Remarkable progress has come from whole-brain models linking anatomy and function. Paradoxically, it is not clear how a neuronal dynamical system running in the fixed human anatomical connectome can give rise to the rich changes in the functional repertoire associated with human brain function, which is impossible to explain through long-term plasticity. Neuromodulation evolved to allow for such flexibility by dynamically updating the effectivity of the fixed anatomical connectivity. Here, we introduce a theoretical framework modeling the dynamical mutual coupling between the neuronal and neurotransmitter systems. We demonstrate that this framework is crucial to advance our understanding of whole-brain dynamics by bidirectional coupling of the two systems through combining multimodal neuroimaging data (diffusion magnetic resonance imaging [dMRI], functional magnetic resonance imaging [fMRI], and positron electron tomography [PET]) to explain the functional effects of specific serotoninergic receptor (5-HT2AR) stimulation with psilocybin in healthy humans. This advance provides an understanding of why psilocybin is showing considerable promise as a therapeutic intervention for neuropsychiatric disorders including depression, anxiety, and addiction. Overall, these insights demonstrate that the whole-brain mutual coupling between the neuronal and the neurotransmission systems is essential for understanding the remarkable flexibility of human brain function despite having to rely on fixed anatomical connectivity.

Awakening

2019
pdf_icon Deco G., Cruzat J., Cabral J., Laufs H., Tagliazucchi E., Logothetis N.K. & Kringelbach ML (2019) Awakening: predicting external stimulation to force transitions between different brain states. PNAS, 116 (36): 18088-97.

Abstract: 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.

Discovery of key whole-brain transitions and dynamics

Discovery of key whole-brain transitions and dynamics
2019
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Stevner A.B.A., Vidaurre D., Cabral J., Rapuano K., Nielsen S.F.V., Tagliazucchi E., Laufs H., Vuust P., Deco G. Woolrich M.W., Van Someren E. & Kringelbach ML (2019) Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep. Nature Communications 10:1035 .

Abstract: The modern understanding of sleep is based on the classification of sleep into stages defined by their electroencephalography (EEG) signatures, but the underlying brain dynamics remain unclear. Here we aimed to move significantly beyond the current state-of-the-art description of sleep, and in particular to characterise the spatiotemporal complexity of whole-brain networks and state transitions during sleep. In order to obtain the most unbiased estimate of how whole-brain network states evolve through the human sleep cycle, we used a Markovian data-driven analysis of continuous neuroimaging data from 57 healthy participants falling asleep during simultaneous functional magnetic resonance imaging (fMRI) and EEG. This Hidden Markov Model (HMM) facilitated discovery of the dynamic choreography between different whole-brain networks across the wake-non-REM sleep cycle. Notably, our results reveal key trajectories to switch within and between EEG-based sleep stages, while highlighting the heterogeneities of stage N1 sleep and wakefulness before and after sleep.

A Kuramoto model of self-other integration

A Kuramoto model of self-other integration
2019
pdf_icon Heggli O.A., Cabral J., Konvalinka I., Vuust P. & Kringelbach ML (2019) A Kuramoto model of self-other integration across interpersonal synchronization strategies. PLoS Computational Biology, 15(10): e1007422.

Abstract: Human social behaviour is complex, and the biological and neural mechanisms underpinning it remain debated. A particularly interesting social phenomenon is our ability and tendency to fall into synchronization with other humans. Our ability to coordinate actions and goals relies on the ability to distinguish between and integrate self and other, which when impaired can lead to devastating consequences. Interpersonal synchronization has been a widely used framework for studying action coordination and self-other integration, showing that even in simple interactions, such as joint finger tapping, complex interpersonal dynamics emerge. Here we propose a computational model of self-other integration via within- and between-person action-perception links, implemented as a simple Kuramoto model with four oscillators. The model abstracts each member of a dyad as a unit consisting of two connected oscillators, representing intrinsic processes of perception and action. By fitting this model to data from two separate experiments we show that interpersonal synchronization strategies rely on the relationship between within- and between-unit coupling. Specifically, mutual adaptation exhibits a higher between-unit coupling than within-unit coupling; leading-following requires that the follower unit has a low within-unit coupling; and leading-leading occurs when two units jointly exhibit a low between-unit coupling. These findings are consistent with the theory of interpersonal synchronization emerging through self-other integration mediated by processes of action-perception coupling. Hence, our results show that chaotic human behaviour occurring on a millisecond scale may be modelled using coupled oscillators.

Brain songs

2019
pdf_icon Deco G., Cruzat J. & Kringelbach ML (2019) Brain songs framework for discovering the relevant timescale of the human brain. Nature Communications, 10: 583.

Abstract: A key unresolved problem in neuroscience is to determine the relevant timescale for understanding spatiotemporal dynamics across the whole brain. While resting state fMRI reveals networks at an ultraslow timescale (below 0.1 Hz), other neuroimaging modalities such as MEG and EEG suggest that much faster timescales may be equally or more relevant for discovering spatiotemporal structure. Here, we introduce a novel way to generate whole-brain neural dynamical activity at the millisecond scale from fMRI signals. This method allows us to study the different timescales through binning the output of the model. These timescales can then be investigated using a method (poetically named brain songs) to extract the spacetime motifs at a given timescale. Using independent measures of entropy and hierarchy to characterize the richness of the dynamical repertoire, we show that both methods find a similar optimum at a timescale of around 200 ms in resting state and in task data.

Whole-brain multimodal neuroimaging model

Whole-brain multimodal neuroimaging model
2018
pdf_icon Deco G., Cruzat J., Cabral J., Knudsen G.M., Carhart-Harris R.L., Whybrow P.C., Logothetis N.K. & Kringelbach ML (2018) Whole-brain multimodal neuroimaging model using serotonin receptor maps explains non-linear functional effects of LSD. Current Biology, 28(19): 3065-74.

Abstract: Understanding the underlying mechanisms of the human brain in health and disease will require models with necessary and sufficient details to explain how function emerges from the underlying anatomy and is shaped by neuromodulation. Here, we provide such a detailed causal explanation using a whole-brain model integrating multimodal imaging in healthy human participants undergoing manipulation of the serotonin system. Specifically, we combined anatomical data from diffusion magnetic resonance imaging (dMRI) and functional magnetic resonance imaging (fMRI) with neurotransmitter data obtained with positron emission tomography (PET) of the detailed serotonin 2A receptor (5-HT2AR) density map. This allowed us to model the resting state (with and without concurrent music listening) and mechanistically explain the functional effects of 5-HT2AR stimulation with lysergic acid diethylamide (LSD) on healthy participants. The whole-brain model used a dynamical mean-field quantitative description of populations of excitatory and inhibitory neurons as well as the associated synaptic dynamics, where the neuronal gain function of the model is modulated by the 5-HT2AR density. The model identified the causative mechanisms for the non-linear interactions between the neuronal and neurotransmitter system, which are uniquely linked to (1) the underlying anatomical connectivity, (2) the modulation by the specific brainwide distribution of neurotransmitter receptor density, and (3) the non-linear interactions between the two. Taking neuromodulatory activity into account when modeling global brain dynamics will lead to novel insights into human brain function in health and disease and opens exciting possibilities for drug discovery and design in neuropsychiatric disorders.

Post-traumatic stress

Post-traumatic stress
2015
pdf_icon Stark E.A., Parsons C.E, Ehlers A., Van Hartevelt T.J., Charquero-Ballester M., McManners H., Stein A. & Kringelbach ML (2015) Post-traumatic stress influences the brain even in the absence of symptoms: A systematic, quantitative meta-analysis of neuroimaging studies. Neuroscience and Biobehavioural Reviews, 56: 207-21.

Abstract: 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-naive. 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-naive 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.

Syncopation, body-movement and pleasure in Groove Music

Syncopation, body-movement and pleasure in Groove Music
2014
pdf_icon Witek M. A. G., Clarke E., Wallentin M., Kringelbach ML & Vuust P. (2014) Syncopation, body-movement and pleasure in Groove Music. PLoS ONE, 9(4): e94446.

Abstract: Moving to music is an essential human pleasure particularly related to musical groove. Structurally, music associated with groove is often characterised by rhythmic complexity in the form of syncopation, frequently observed in musical styles such as funk, hip-hop and electronic dance music. Structural complexity has been related to positive affect in music more broadly, but the function of syncopation in eliciting pleasure and body-movement in groove is unknown. Here we report results from a web-based survey which investigated the relationship between syncopation and ratings of wanting to move and experienced pleasure. Participants heard funk drum-breaks with varying degrees of syncopation and audio entropy, and rated the extent to which the drum-breaks made them want to move and how much pleasure they experienced. While entropy was found to be a poor predictor of wanting to move and pleasure, the results showed that medium degrees of syncopation elicited the most desire to move and the most pleasure, particularly for participants who enjoy dancing to music. Hence, there is an inverted U-shaped relationship between syncopation, body-movement and pleasure, and syncopation seems to be an important structural factor in embodied and affective responses to groove.

A specific and rapid signature for parental instinct

A specific and rapid signature for parental instinct
2008
pdf_icon Kringelbach ML, Lehtonen A., Squire, S., Harvey A.G., Craske M.G., Holliday I.E., Green A.L., Aziz T.Z., Hansen P.C., Cornelissen P.L. & Stein A. (2008) A specific and rapid neural signature for parental instinct. PLoS ONE 3(2), e1664.

Abstract: Darwin originally pointed out that there is something about infants which prompts adults to respond to and care for them, in order to increase individual fitness, i.e. reproductive success, via increased survivorship of one’s own offspring. Lorenz proposed that it is the specific structure of the infant face that serves to elicit these parental responses, but the biological basis for this remains elusive. Here, we investigated whether adults show specific brain responses to unfamiliar infant faces compared to adult faces, where the infant and adult faces had been carefully matched across the two groups for emotional valence and arousal, as well as size and luminosity. The faces also matched closely in terms of attractiveness. Using magnetoencephalography (MEG) in adults, we found that highly specific brain activity occurred within a seventh of a second in response to unfamiliar infant faces but not to adult faces. This activity occurred in the medial orbitofrontal cortex (mOFC), an area implicated in reward behaviour, suggesting for the first time a neural basis for this vital evolutionary process. We found a peak in activity first in mOFC and then in the right fusiform face area (FFA). In mOFC the first significant peak (p,0.001) in differences in power between infant and adult faces was found at around 130 ms in the 10–15 Hz band. These early differences were not found in the FFA. In contrast, differences in power were found later, at around 165 ms, in a different band (20–25 Hz) in the right FFA, suggesting a feedback effect from mOFC. These findings provide evidence in humans of a potential brain basis for the “innate releasing mechanisms” described by Lorenz for affection and nurturing of young infants. This has potentially important clinical applications in relation to postnatal depression, and could provide opportunities for early identification of families at risk.

Subjective pleasantness

2003
pdf_icon Kringelbach ML, O’Doherty J., Rolls E.T. & Andrews C. (2003) Activation of the human orbitofrontal cortex to a liquid food stimulus is correlated with its subjective pleasantness, Cerebral Cortex, 13(10): 1064-1071.

Abstract: Single-neuron recording studies in non-human primates indicate that orbitofrontal cortex neurons represent the reward value of the sight, smell and taste of food, and even changes in the relative reward value, but provide no direct evidence on brain activity that is correlated with subjective reports of the pleasantness of food. In this fMRI investigation we report a significant correlation between the activation of a region of the human orbitofrontal cortex and the decrease in subjective pleasantness when a liquid food is eaten to satiety. Moreover, a cluster of voxels in the orbitofrontal cortex showed a decrease in its activation that was specific to the particular liquid food consumed in a meal, providing a neural correlate of sensory-specific satiety to a liquid whole food in humans. This sensory-specific reduction in activation of the orbitofrontal cortex correlating with subjective pleasantness is consistent with an important role for the orbitofrontal cortex in human emotion and motivation, and associated subjective states.

Top10 Reviews

Top10 Reviews

Hierarchy of information processing

Hierarchy of information processing
2017
pdf_icon Deco G. & Kringelbach ML (2017) Hierarchy of information processing in the brain: a novel ‘intrinsic ignition’ framework. Neuron, 94: 961-8.

Abstract: A general theory of brain function has to be able to explain local and non-local network computations over space and time. We propose a new framework to capture the key principles of how local activity influences global computation, i.e., describing the propagation of information and thus the broadness of communication driven by local activity. More specifically, we consider the diversity in space (nodes or brain regions) over time using the concept of intrinsic ignition, which are naturally occurring intrinsic perturbations reflecting the capability of a given brain area to propagate neuronal activity to other regions in a given brain state. Characterizing the profile of intrinsic ignition for a given brain state provides insight into the precise nature of hierarchical information processing. Combining this data-driven method with a causal whole-brain computational model can provide novel insights into the imbalance of brain states found in neuropsychiatric disorders.

Metastability and coherence

2016
pdf_icon Deco G. & Kringelbach ML (2016) Metastability and coherence: Extending the communication-through-coherence hypothesis from a whole-brain computational perspective. Trends in Neuroscience 39(3):125-35.

Abstract: Understanding the mechanisms for communication in the brain remains one of the most challenging scientific questions. The communication through coherence (CTC) hypothesis was originally proposed 10 years ago, stating that two groups of neurons communicate most effectively when their excitability fluctuations are coordinated in time (i.e., coherent), and this control by cortical coherence is a fundamental brain mechanism for large-scale, distant communication. In light of new evidence from whole-brain computational modelling of multimodal neuroimaging data, we link CTC to the concept of metastability, which refers to a rich exploration of the functional repertoire made possible by the underlying structural whole-brain connectivity.

Cuteness

2016
pdf_icon Kringelbach ML, Stark E.A., Alexander C., Bornstein M.H. & Stein A. (2016) On cuteness: Unlocking the parental brain and beyond. Trends in Cognitive Sciences, 20(7): 545-58.

Abstract: Cuteness in offspring is a potent protective mechanism that ensures survival for otherwise completely dependent infants. Previous research has linked cuteness to early ethological ideas of a ‘Kindchenschema’ (infant schema) where infant facial features serve as ‘innate releasing mechanisms’ for instinctual caregiving behaviours. We propose extending the concept of cuteness beyond visual features to include positive infant sounds and smells. Evidence from behavioural and neuroimaging studies links this extended concept of cuteness to simple ‘instinctual’ behaviours and to caregiving, protection, and complex emotions. We review how cuteness supports key parental capacities by igniting fast privileged neural activity followed by slower processing in large brain networks also involved in play, empathy, and perhaps even higher-order moral emotions.

Reconceptualising anhedonia

Reconceptualising anhedonia
2015
pdf_icon Rømer Thomsen K., Whybrow P. & Kringelbach ML (2015) Reconceptualising anhedonia: novel perspectives on balancing the pleasure networks in the human brain. Frontiers in Behavioural neuroscience 9:49.

Abstract: Anhedonia, the lack of pleasure, has been shown to be a critical feature of a range of psychiatric disorders. Yet, it is currently measured primarily through subjective self-reports and as such has been difficult to submit to rigorous scientific analysis. New insights from affective neuroscience hold considerable promise in improving our understanding of anhedonia and for providing useful objective behavioral measures to complement traditional self-report measures, potentially leading to better diagnoses and novel treatments. Here, we review the state-of-the-art of hedonia research and specifically the established mechanisms of wanting, liking, and learning. Based on this framework we propose to conceptualize anhedonia as impairments in some or all of these processes, thereby departing from the longstanding view of anhedonia as solely reduced subjective experience of pleasure. We discuss how deficits in each of the reward components can lead to different expressions, or subtypes, of anhedonia affording novel ways of measurement. Specifically, we review evidence suggesting that patients suffering from depression and schizophrenia show impairments in wanting and learning, while some aspects of conscious liking seem surprisingly intact. Furthermore, the evidence suggests that anhedonia is heterogeneous across psychiatric disorders, depending on which parts of the pleasure networks are most affected. This in turn has implications for diagnosis and treatment of anhedonia.

The rediscovery of slowness

The rediscovery of slowness
2015
pdf_icon Kringelbach ML, McIntosh A.R., Ritter P., Jirsa V. & Deco G. (2015) The rediscovery of slowness: exploring the timing of cognition. Trends in Cognitive Sciences 19(10):616-28.

Abstract: Slowness of thought is not necessarily a handicap but could be a signature of optimal brain function. Emerging evidence shows that neuroanatomical and dynamical constraints of the human brain shape its functionality in optimal ways, characterized by slowness during task-based cognition in the context of spontaneous resting-state activity. This activity can be described mechanistically by whole-brain computational modeling that relates directly to optimality in the context of theories arguing for metastability in the brain. We discuss the role for optimal processing of information in the context of cognitive, task-related activity, and propose that combining multi-modal neuroimaging and explicit whole-brain models focused on the timing of functional dynamics can help to uncover fundamental rules of brain function in health and disease.

Pleasure systems in the brain

2015
pdf_icon Berridge K.C. & Kringelbach ML (2015) Pleasure systems in the brain. Neuron 86:646-664.

Abstract: Pleasure is mediated by well-developed mesocorticolimbic circuitry and serves adaptive functions. In affective disorders, anhedonia (lack of pleasure) or dysphoria (negative affect) can result from breakdowns of that hedonic system. Human neuroimaging studies indicate that surprisingly similar circuitry is activated by quite diverse pleasures, suggesting a common neural currency shared by all. Wanting for reward is generated by a large and distributed brain system. Liking, or pleasure itself, is generated by a smaller set of hedonic hot spots within limbic circuitry. Those hot spots also can be embedded in broader anatomical patterns of valence organization, such as in a keyboard pattern of nucleus accumbens generators for desire versus dread. In contrast, some of the best known textbook candidates for pleasure generators, including classic pleasure electrodes and the mesolimbic dopamine system, may not generate pleasure after all. These emerging insights into brain pleasure mechanisms may eventually facilitate better treatments for affective disorders.

Great expectations

Great expectations
2014
pdf_icon Deco G. & Kringelbach ML (2014) Great expectations: using whole-brain computational connectomics for understanding neuropsychiatric disorders. Neuron, 84(3): 892-905.

Abstract: The study of human brain networks with in vivo neuroimaging has given rise to the field of connectomics, furthered by advances in network science and graph theory informing our understanding of the topology and function of the healthy brain. Here our focus is on the disruption in neuropsychiatric disorders (pathoconnectomics) and how whole-brain computational models can help generate and predict the dynamical interactions and consequences of brain networks over many timescales. We review methods and emerging results that exhibit remarkable accuracy in mapping and predicting both spontaneous and task-based healthy network dynamics. This raises great expectations that whole-brain modeling and computational connectomics may provide an entry point for understanding brain disorders at a causal mechanistic level, and that computational neuropsychiatry can ultimately be leveraged to provide novel, more effective therapeutic interventions, e.g., through drug discovery and new targets for deep brain stimulation.

The human sexual response cycle

The human sexual response cycle
2012
pdf_icon Georgiadis J. & Kringelbach ML (2012) The human sexual response cycle: brain imaging evidence linking sex to other pleasures. Progress in Neurobiology, 98(1): 49-81.

Abstract: Sexual behavior is critical to species survival, yet comparatively little is known about the neural mechanisms in the human brain. Here we systematically review the existing human brain imaging literature on sexual behavior and show that the functional neuroanatomy of sexual behavior is comparable to that involved in processing other rewarding stimuli. Sexual behavior clearly follows the established principles and phases for wanting, liking and satiety involved in the pleasure cycle of other rewards. The studies have uncovered the brain networks involved in sexual wanting or motivation/anticipation, as well as sexual liking or arousal/consummation, while there is very little data on sexual satiety or post-orgasmic refractory period. Human sexual behavior also interacts with other pleasures, most notably social interaction and high arousal states. We discuss the changes in the underlying brain networks supporting sexual behavior in the context of the pleasure cycle, the changes to this cycle over the individual’s life-time and the interactions between them. Overall, it is clear from the data that the functional neuroanatomy of sex is very similar to that of other pleasures and that it is unlikely that there is anything special about the brain mechanisms and networks underlying sex.

Translational principles of deep brain stimulation

2007
pdf_icon Kringelbach ML, Jenkinson N., Owen S.L.F. & Aziz T.Z. (2007) Translational principles of deep brain stimulation. Nature Reviews Neuroscience, 8:623-635.

Abstract: Deep brain stimulation (DBS) has shown remarkable therapeutic benefits for patients with otherwise treatment-resistant movement and affective disorders. This technique is not only clinically useful, but it can also provide new insights into fundamental brain functions through direct manipulation of both local and distributed brain networks in many different species. In particular, DBS can be used in conjunction with non-invasive neuroimaging methods such as magnetoencephalography to map the fundamental mechanisms of normal and abnormal oscillatory synchronization that underlie human brain function. The precise mechanisms of action for DBS remain uncertain, but here we give an up-to-date overview of the principles of DBS, its neural mechanisms and its potential future applications.

The human orbitofrontal cortex

The human orbitofrontal cortex
2005
pdf_icon Kringelbach ML (2005) The human orbitofrontal cortex: linking reward to hedonic experience. Nature Reviews Neuroscience, 6:691-702.

Abstract: Hedonic experience is arguably at the heart of what makes us human. In recent neuroimaging studies of the cortical networks that mediate hedonic experience in the human brain, the orbitofrontal cortex has emerged as the strongest candidate for linking food and other types of reward to hedonic experience. The orbitofrontal cortex is among the least understood regions of the human brain, but has been proposed to be involved in sensory integration, in representing the affective value of reinforcers, and in decision making and expectation. Here, the functional neuroanatomy of the human orbitofrontal cortex is described and a new integrated model of its functions proposed, including a possible role in the mediation of hedonic experience.

Books


 
2016aabook_neuropsychiatryChan RCK & Kringelbach M.L., eds. (2016) At Risk for Neuropsychiatric Disorders: An Affective Neuroscience Approach to Understanding the Spectrum. Lausanne: Frontiers Media.
2014aabook_emotionKringelbach M.L. & Phillips, H. (2014) Emotion. Pleasure and pain in the brain. Oxford University Press.
aabook_consumptionPreston S., Kringelbach M.L. & Knutson B., eds. (2014) The Interdisciplinary Science of Consumption. MIT Press.
aabook_hjernenØstergaard L., Bjarkam C., Kringelbach M.L. et al. (2014) Hjernen. Systime.
2010aabook_pleasuresKringelbach M.L. & Berridge, K.C., eds. (2010) Pleasures of the brain. Oxford University Press.
aabook_MEGHansen P.C., Kringelbach M.L & Salmelin R., eds. (2010) MEG: an introduction to methods. Oxford University Press.
aabook_NBRCornelissen P.L., Hansen P.C., Kringelbach M.L & Pugh K, eds. (2010) The neural basis of reading. Oxford University Press.
2009aabook_pleasurecenterKringelbach M.L (2009) The pleasure center. Trust your animal instincts. Oxford University Press.
2008aabog_gyldendalKringelbach M.L. (2008) Den nydelsesfulde hjerne. Nydelsens og begærets mange ansigter. Gyldendal.
abog_pauliKringelbach M.L. (2008) Njótingarsami Heilin (transl P.Nielsen) Thorshavn: Ítriv.
2004aabook_hjernerumKringelbach M.L. (2004) Hjernerum. Den følelsesfulde hjerne. People'sPress.
2002aabook_dgKringelbach M.L. (2002) DG: Centres of Excellence i 10 år. Vol I. Danish National Research Foundation.
aabook_dgKringelbach M.L. (2002) DG: Centres of Excellence i 10 år. Vol II. Danish National Research Foundation.
2001aabook_centreKringelbach M.L. (2001) 9 nye centre. Danish National Research Foundation.
aabook_thesisKringelbach M.L. (2001) The Functional Neuroanatomy of Emotion. Oxford University.
   

All publications

2020pdf_iconKringelbach M.L., Cruzat J., Cabral, J., Knudsen G.M., Carhart-Harris R.L., Whybrow P.C., Logothetis N.K. and Deco G. (2020) Dynamic Coupling of Whole-Brain Neuronal and Neurotransmitter Systems, PNAS, 117(17): 9566-76.
requestMartinez S.A., Marsman JBC, Renken R.J., Kringelbach M.L., Deco G., & ter Horst G.J. (2020) Reduced spatiotemporal brain dynamics are associated with increased depressive symptoms after a relationship breakup. Neuroimage: Clinical, in press.
pdf_iconVohryzek J., Deco G., Cessac B., Kringelbach M.L. & Cabral J. (2020) Ghost attractors in spontaneous brain activity: recurrent excursions into functionally relevant BOLD phase-locking states. Frontiers in Neuroscience, 14:20.
pdf_iconHeggli O.A., Konvalinka I., Cabral J., Brattico E., Kringelbach M.L. & Vuust P. (2020) Transient brain networks underlying interpersonal strategies during synchronized action. SCAN, in press.
requestHallett M., de Haan W., Deco G., Dengler R. Di Iiorio R., Gallea C., Gerloff C., Grefkes C., Helmich R.C., Kringelbach M.L., Miraglia F., Rektor I., Strycek O., Vecchio F., Volz L.J., Wu T. & Rossini P.M. (2020) Human Brain Connectivity: Clinical Applications for Clinical Neurophysiology. Clinical Neurophysiology, 131(7):1621-51.
pdf_iconIpiña I.P., Kehoe P.D., Kringelbach M.L., Laufs H., Ibañez A., Deco G., Perl Y.S. & Tagliazucchi E. (2020) Modeling regional changes in dynamic stability during sleep and wakefulness. Neuroimage, 215: 116833.
2019pdf_iconDeco G., Cruzat J., Cabral J., Laufs H., Tagliazucchi E., Logothetis N.K. & Kringelbach M.L. (2019) Awakening: predicting external stimulation to force transitions between different brain states. PNAS, 116 (36): 18088-97.
pdf_iconStevner A.B.A., Vidaurre D., Cabral J., Rapuano K., Nielsen S.F.V., Tagliazucchi E., Laufs H., Vuust P., Deco G. Woolrich M.W., Van Someren E. & Kringelbach M.L. (2019) Discovery of key whole-brain transitions and dynamics during human wakefulness and non-REM sleep. Nature Communications 10:1035 .
pdf_iconDeco G., Cruzat J. & Kringelbach M.L. (2019) Brain songs framework for discovering the relevant timescale of the human brain. Nature Communications, 10: 583.
request Atasoy S., Deco G. & Kringelbach M.L. (2019) Harmonic waves as the fundamental principle underlying temporo-spatial dynamics of brain and mind. Physics of Life Review, in press.
request Vila-Vidal M., Capouskova K., Atasoy S., Kringelbach M.L. & Deco G. (2019) Uncovering the spatio-temporal scales of common neuro-mental constructs. Physics of Life Review, in press.
request Ahrends C., Vuust P. & Kringelbach M.L. (2019) Predictive Intelligence for Learning and Optimisation: Multidisciplinary Perspectives from Social, Cognitive and Affective Neuroscience. In The Cambridge Handbook of Intelligence and Cognitive Neuroscience (eds Barbey A.K., Karama S. & Haier R.J.), in press.
request Jespersen K.V., Stevner A., Fernandes H.M., Sørensen S.D., Van Someren E. Kringelbach M.L. & Vuust P. (2019) Reduced structural connectivity in Insomnia Disorder. Journal of Sleep Research, e12901.
pdf_iconHeggli O.A., Cabral J., Konvalinka I., Vuust P. & Kringelbach M.L. (2019) A Kuramoto model of self-other integration across interpersonal synchronization strategies. PLoS Computational Biology, 15(10): e1007422.
pdf_iconFernandes H.M., Cabral J., Lord LD., Gleesborg C., Møller A., Deco G., Whybrow P.C., Petrovic P., James A.C. & Kringelbach M.L. (2019) Disrupted brain structural connectivity in Pediatric Bipolar Disorder. Scientific Reports, 9: 13638.
request Stark E.A., Cabral J., Riem M.M.E., IJzendoorn M.H., Stein A. & Kringelbach M.L. (2019) The power of smiling: the adult brain networks underlying learned infant emotionality. Cerebral Cortex, in press.
pdf_iconAhrends C., Bravo F., Kringelbach M.L., Vuust P. & Rohrmeier M.A. (2019) Expectation of worst possible outcomes does not explain aversion to ambiguity: Evidence from decision-making under uncertainty. Scientific Reports, 9: 12177.
pdf_iconHeggli O.A., Konvalinka I., Kringelbach M.L. & Vuust P. (2019) Musical interaction is influenced by underlying predictive models and musical expertise. Scientific Reports, 9: 11048.
request Expert P., Lord LD., Kringelbach M.L. & Petri G. eds. (2019) Editorial: Topological Neuroscience. Network Neuroscience, 3(3): 653-655.
request Padilla N., Saenger V.M., van Hartevelt T.J., Fernandes H.M., Lennartson F., Anderson J.L.R., Kringelbach M.L., Deco G. & Åden U. (2019) Breakdown of whole-brain dynamics in preterm born children. Cerebral Cortex, in press.
pdf_iconParsons C.E., LeBeau R.T., Kringelbach M.L. & Young K.S. (2019) Pawsitively sad: Pet-owners are more sensitive to negative emotion in animal distress vocalisations. Royal Society Open Science, 6(8): 181555.
pdf_iconLord L.D., Expert P., Atasoy S., Roseman, L., Rapuano K., Lambiotte R., Nutt D.J., Deco G., Carhart-Harris R., Kringelbach M.L. & Cabral J. (2019) Dynamical exploration of the repertoire of brain networks at rest is modulated by psilocybin. Neuroimage, 199: 127-42.
pdf_iconFasano M.C., Semeraro C., Cassibba R., Kringelbach M.L., Monacis L., de Palo V., Vuust P. & Brattico E. (2019) Short-term orchestral music training reduces hyperactivity and inhibitory control in school-age children: A longitudinal behavioral study. Frontiers in Psychology, 10:750.
request Donnelly-Kehoe P.D., Saenger V.M., Lisofsky N., Kühn S., Kringelbach M.L., Schwarzbach J. & Deco G. (2019) Reliable local dynamics in the brain across sessions are revealed by whole-brain modelling of resting state activity. bioRxiv, 104232. HBM, 40(10):2967-2980.
request Figueroa C.A., Cabral J., Mocking R.J.T., Rapuano K., van Hartevelt T., Deco G., Schene A.H., Kringelbach M.L. & Ruhe H.G. (2019) Altered ability to access a clinically relevant control network in pa-tients remitted from Major Depressive Disorder. HBM, 10(9):2771-27860.
request Jespersen K.V., Otto M., Kringelbach M.L., Van Someren E. & Vuust P. (2019) A randomized controlled trial of bedtime music for insomnia disorder. Journal of Sleep Research, e12817.
request Young K.S., Parsons C.E., Stein A., Vuust P., Craske M.G. & Kringelbach M.L. (2019) Neural responses to infant vocalisations in adult listeners. In: The Oxford Handbook of Voice Perception (eds. S. Frühholz and P. Belin), Oxford: OUP, pp. 251-275.
request Vuust P. & Kringelbach M.L. (2019) Music Improvisation, a challenge for empirical research. In: The Routledge Companion to Music Cognition (eds. R. Ashley & R.Timmers). London: Routledge, in press.
request Stark E., Berridge K.C. & Kringelbach M.L. (2019) Are we designed to be happy? The neuroscience of making sense of pleasure In: Cambridge Handbook of Evolutionary Perspectives on Human Behavior (eds. Lance Workman, Will Reader, Jerome H Barkow) Cambridge University Press, in press.
request Kringelbach M.L. & Deco G. (2019) Whole-brain modelling of neuroimaging data: moving beyond correlation to causation. In: Casting light on the Dark Side of Brain Imaging (eds. A. Raz & R.T. Thibault) Elsevier: New York, pp. 139-143.
request Atasoy S., Deco G. & Kringelbach M.L. (2019) Playing at the edge of criticality: Expanded whole-brain repertoire of connectome-harmonics. In: The Functional Role of Critical Dynamics in Neural Systems (eds. Herrmann M., Tümen N & Ernst U.). Springer, pp. 27-45.
request Stark E., Stein A., Young K.S., Parsons C. & Kringelbach M.L. (2019) Neurobiology of parenting. In: Handbook of Parenting (Third Edition). Volume 2: The Biology and Ecology of Parenting. (Ed. M.Bornstein). London: Routledge, pp. 250-84.
request Heggli O.A., Kringelbach M.L. & Vuust P. (2019) Please Please Me! The pleasure of music in the brain. In: Routledge Companion To Music, Mind and Well-being (eds. J. Kennaway, P. Gouk, W. Thormaehlen & J. Prins). London: Routledge, pp. 205-218.
2018request Deco G., Cruzat J., Cabral J., Knudsen G.M., Carhart-Harris R.L., Whybrow P.C., Logothetis N.K. & Kringelbach M.L. (2018) Whole-brain multimodal neuroimaging model using serotonin receptor maps explains non-linear functional effects of LSD. Current Biology, 28(19): 3065-74.
request Atasoy S., Vohryzek J., Deco G., Carhart-Harris R & Kringelbach M.L. (2018) Common neural signatures of psychedelics: Frequency-specific energy changes and repertoire expansion revealed using connectome-harmonic decomposition. Progress in Brain Research, 97-120.
request Itzhacki J., Te Lindert B.H.W., Van Der Meijden W.P., Figueiro M., Rea M., Kringelbach M.L., Mendoza J. & Van Someren E.J.W. (2018) Environmental light and time of day modulate subjective liking and wanting: an experience sampling study. Emotion, 9(1):10-20.
pdf_iconStark E., Vuust P. & Kringelbach M.L. (2018) Music, dance and other art forms: New insights into the links between hedonia (pleasure) and eudaimonia (well-being). Progress in Brain Research, 237: 129-152.
pdf_iconDaffertshofer A., Ton R., Pietras B., Kringelbach M.L. & Deco G. (2018) Scale-freeness or partial synchronization in neural mass phase oscillator networks: pick one of two? Neuroimage, 180:428-41.
pdf_iconDaffertshofer A., Ton R., Kringelbach M.L., Woolrich M.W. & Deco G. (2018) Distinct criticality of phase and amplitude dynamics in the resting brain. Neuroimage, 180:442-7.
request Zou L., Zhou H., Zhuang Y., van Hartevelt T.J., Liu S.S.Y, Cheung E.F.C., Moeller A., Kringelbach M.L. & Chan R.C.K. (2018) Neural responses during the anticipation and receipt of olfactory reward and punishment in human. Neuropsychologia, 111:172-179.
pdf_iconCruzat J., Deco G., Tauste Campo A., Principe A., Costa A., Kringelbach M.L. & Rocamora R. (2018) The dynamics of human cognition: increasing global integration coupled with decreasing segregation found using intracortical EEG. Neuroimage, 172:492-505.
request Vuust P., Witek M., Dietz M. & Kringelbach M.L. (2018) Now You Hear It: A novel predictive coding model for understanding rhythmic incongruity. Annals of NY Academy for Sciences, 1423(1): 19-29.
pdf_iconDeco G., Cabral J., Saenger V.M., Boly M., Laufs H., Tagliazucchi E., Van Someren E., Jobst B., Stevner A.B.A. & Kringelbach M.L. (2018) Perturbation of whole-brain dynamics in silico reveals mechanistic differences between brain states. Neuroimage, 169: 46-56.
2017request Deco G. & Kringelbach M.L. (2017) Hierarchy of information processing in the brain: a novel 'intrinsic ignition' framework. Neuron, 94: 961-8.
pdf_iconAtasoy S., Roseman L., Kaelen M., Kringelbach M.L., Deco G. & Carhart-Harris R. (2017) Critical brain dynamics under LSD revealed by connectome-specific harmonic decomposition. Scientific Reports, 7: 17661.
request Te Lindert B.H.W., Itzhacki J., Van Der Meijden W.P., Figueiro M., Rea M., Kringelbach M.L., Mendoza J. & Van Someren E.J.W. (2017) Bright environmental light ameliorates deficient subjective wanting and liking in insomnia: an experience sampling study. Sleep, 41(4).
pdf_iconDeco G., Tagliazucchi E., Laufs H., Sanjuan A. & Kringelbach M.L. (2017) Novel intrinsic ignition method measuring local-global integration characterises wakefulness and deep sleep. eNeuro, 4(5) e0106-17.2017
pdf_iconSaenger V.M., Kahan J., Foltynie T., Friston K., Aziz T.Z., Green A.L., Van Hartevelt T., Stevner A., Fernandes H., Mancini L., Thornton J., Yousry T., Limousin P., Zrinzo L., Hariz M., Kringelbach M.L. & Deco G. (2017) Uncovering the underlying mechanisms and whole-brain dynamics of therapeutic deep brain stimulation for Parkinson’s disease. bioRxiv, 083162. Scientific Reports, 7: 9882.
request Atasoy S., Deco G., Kringelbach M.L. & Pearson J. (2017) Harmonic brain modes: a unifying framework for linking space and time in brain dynamics. The Neuroscientist, 11(2):211-215.
pdf_iconCrisp R. & Kringelbach M.L. (2017) Higher and lower pleasures revisited: evidence from neuroscience. Neuroethics, 11(2):211-215.
request Cabral J., Kringelbach M.L. & Deco G. (2017) Functional connectivity dynamically evolves over static structural connectivity: models and mechanisms. Neuroimage, 160:84-96.
request Deco G., Cabral J., Woolrich M., Stevner A.B.A., Van Hartevelt T. & Kringelbach M.L. (2017) Single or Multi-Frequency Generators in On-going MEG Data: a Mechanistic Whole-Brain Model of empirical MEG data. bioRxiv, 084103. Neuroimage, 152: 538-550.
pdf_iconDeco G., Kringelbach M.L., Jirsa V. & Ritter P. (2017) The dynamics of resting fluctuations in the brain: metastability and its dynamical core. bioRxiv, 065284. Scientific Reports, 7(1):3095.
pdf_iconCabral J., Marques P., Magalhães R., Moreira P., Soares J.M., Deco G., Sousa N. & Kringelbach M.L. (2017) Cognitive performance in healthy ageing relates with the switching dynamics of functional connectivity during rest. Scientific Reports, 7: 5135.
pdf_iconJobst B., Hindriks H., Laufs H., Tagliazucchi E., Hahn G., Ponce-Alvarez A., Stevner A.B.A, Kringelbach M.L. & Deco G. (2017) Increased stability and breakdown of brain effective connectivity during slow-wave sleep: mechanistic insights from whole-brain computational modelling. Scientific Reports, 7:4634.
requestRiem M.M.E., IJzendoorn M.H., Parsons C.E., Young K.S., De Carli P., Kringelbach M.L. & Bakermans-Kranenburg M.J. (2017) Experimental manipulation of infant temperament affects amygdala functional connectivity. Cognitive, Affective, and Behavioral Neuroscience, 17(4): 858–68.
pdf_iconBettinardi R.G., Deco G., Karlaftis V.M., Van Hartevelt T.J., Fernandes H.M., Kourtzi Z., Kringelbach M.L. & Zamora-López G. (2017) How structure sculpts function: unveiling the contribution of anatomical connectivity to the brain's spontaneous correlation structure. arXiv:1612.02243. Chaos 27: 047409
pdf_iconParsons C.E., Young K.S., Petersen M.V., Elmholdt E-M.J., Vuust P., Stein A. & Kringelbach M.L. (2017) Duration of motherhood has incremental effects on mothers’ neural processing of infant vocal cues: a neuroimaging study of women. Scientific Reports, 7:1727.
pdf_iconDeco G., Van Hartevelt T., Fernandes H.M., Stevner A.B.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.
pdf_iconFjaeldstad A., Fernandes H.M., van Hartevelt T.J., Gleesborg C., Moeller 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.
request Lord L.D., Stevner A., Deco G. & Kringelbach M.L. (2017) Understanding principles of integration and segregation using whole-brain computational connectomics: implications for neuropsychiatric disorders. Philosophical Transactions of the Royal Society A, 375: 20160283.
request Parsons C., Young K., Stein A. & Kringelbach M.L. (2017) Intuitive parenting: understanding the neural mechanisms of parents’ adaptive responses to infants. Current Opinion in Psychology, 15:40–4.
request 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: Rewiring the Brain: A Computational Approach to Structural Plasticity in the Adult Brain (eds. A. van Ooyen & M. Butz-Ostendorf), New York: Academic Press, 527-46.
request Kringelbach M.L. and Berridge K.C. (2017) The affective core of emotion: linking pleasure, subjective well-being and optimal metastability in the brain. Emotion Review, 9(3):191-9.
2016request Kringelbach M.L., Stark E.A., Alexander C., Bornstein M.H. & Stein A. (2016) On cuteness: Unlocking the parental brain and beyond. Trends in Cognitive Sciences, 20(7): 545-58
requestDeco G. & Kringelbach M.L. (2016) Metastability and coherence: Extending the communication-through-coherence hypothesis from a whole-brain computational perspective. Trends in Neuroscience, 39(3):125-35.
requestWitek M. A. G., Popescu T., Clarke E., Hansen M., Konvalinka I., Kringelbach M.L. & Vuust P. (2016) ‘Move On Up!’ Effects of syncopation on free body-movement in groove music. Experimental Brain Research, 235(4):995-1005.
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Zamora-López G., Chen Y., Deco G., Kringelbach M.L. & Zhou C. (2016) Functional complexity emerging from anatomical constraints in the brain: the significance of network modularity and rich-clubs. Scientific Reports 6:38424.
requestKringelbach M.L. & Rapuano K. (2016) Time in the orbitofrontal cortex. Brain 139(4): 1010-3.
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Lord L.D., Expert P., Fernandes H.M., Petri G., Van Hartevelt T.J., Turkheimer F.E. & Kringelbach M.L. (2016) Insights into brain architectures from the homological scaffolds of functional connecivity networks. Frontiers in Systems Neuroscience, 10:85.
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Chan RCK & Kringelbach M.L. (2016) Editorial: At Risk for Neuropsychiatric Disorders: An Affective Neuroscience Approach to Understanding the Spectrum. Frontiers in Behavioural Neuroscience 10:165.
requestGeorgiadis J. & Kringelbach M.L. (2016) Intimacy and the brain: lessons from genital and sexual touch. In Affective Touch and the Neurophysiology of CT Afferents (H. Olausson, J. Wessberg, I. Morrison, and F. McGlone, eds), Springer, 301-21.
requestYoung K.S., Parsons C.E., Vuust P., Craske M.G., Stein A. & Kringelbach M.L. (2016) The neural basis of responsive caregiving behaviour: Investigating temporal dynamics within the parental brain. Behavioural Brain Research, 325:105-16.
requestYoung K.S., Parsons C.E., LeBeau R., Tabak B.A., Stewart A., Stein A., Kringelbach M.L., Craske M.G. (2016) Sensing emotion in voices: negativity bias and gender differences in a validation study of the Oxford Vocal ('OxVoc') Sounds Database. Psychological Assessment, 29(8): 967–77.
requestZou L., van Hartevelt T.J., Kringelbach M.L., Cheung E.F.C., Chan R.C.K. (2016) The neural mechanism of olfactory hedonic processing and judgement: An ALE meta-analysis. Neuropsychology, 30(8):970-979
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Parsons C.E., Young K.S., Jegindø E.-M., Stein A., Kringelbach M.L. (2016) Interpreting infant emotion expressions: parenthood has differential effects on men and women. Quarterly Journal of Experimental Psychology, 10:1-11.
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Young K.S., Parsons C.E., Stevner A., Woolrich M.W., Jegindø E.-M., Hartevelt T.J., Stein A., Kringelbach M.L. (2016) Evidence for a caregiving instinct: rapid differentiation of infant from adult vocalisations using magnetoencephalography. Cerebral Cortex, 26(3):1309-21.
requestRayson H., Parsons C.E., Young K.S., Goodacre T.E., Kringelbach M.L., Bonaiuto J.J., McSorley E. & Murray L. (2016) Effects of Infant Cleft Lip on Adult Gaze and Perceptions of ‘Cuteness’. Cleft Palate-Craniofacial Journal, 54 (5): 562-570.
requestBoccard SGJ, Fernandes H., Jbabdi S., Van Hartevelt T.J, Kringelbach M.L., Qyaghebeur G., Moir L., Piqueras Mancebo V., Pereira EAC, Fitzgerald JJ, Green AL, Stein J., Aziz TZ (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.
requestKringelbach M.L. & Berridge K.C. (2016) Drive and motivation in the brain. In SAGE Encyclopedia of Theory in Psychology (ed. Miller H.), New York: SAGE, 240-44.
2015pdf_icon
Kringelbach M.L., McIntosh A.R., Ritter P., Jirsa V. & Deco G. (2015) The rediscovery of slowness: exploring the timing of cognition. Trends in Cognitive Sciences 19(10):616-28.
requestKringelbach M.L. & Cattrell A. (2015) An architecture of pleasure and pain. LA Plus, 2:10-17.
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Stark E.A., Parsons C.E, Ehlers A., Van Hartevelt T.J., Charquero-Ballester M., McManners H., 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 Biobehavioural Reviews, 56: 207-21.
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Deco G., Tononi G, Boly M. & Kringelbach M.L. (2015) Rethinking segregation and integration: contributions of whole-brain modelling. Nature Reviews Neuroscience 16:430-439.
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Berridge K.C. & Kringelbach M.L. (2015) Pleasure systems in the brain. Neuron 86:646-664.
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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 Behavioural neuroscience, 9:167.
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Gebauer L., Kringelbach M.L. & Vuust P. (2015) Predictive coding links perception, action and learning to emotions in music. Physics of Life Review 13:50-52
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Witek M.A.G., Kringelbach M.L. & Vuust P. (2015) Musical rhythm and affect. Physics of Life Review 13:92-94.
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Kringelbach M.L. (2015) The pleasure of food: underlying brain mechanisms of eating and other pleasures. Flavour 4:20.
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Rømer Thomsen K., Whybrow P. & Kringelbach M.L. (2015) Reconceptualising anhedonia: novel perspectives on balancing the pleasure networks in the human brain. Frontiers in Behavioural neuroscience 9:49.
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Young K.S., Parsons C.E., Stein A., Kringelbach M.L. (2015) Motion and emotion: depression reduces psychomotor performance and alters affective movements in caregiving interactions. Frontiers in Behavioural neuroscience 9:26.
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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): 545-50.
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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. (2014) Novel fingerprinting method characterizes the necessary and sufficient structural connectivity from deep brain stimulation electrodes for a successful outcome. New Journal of Physics 17: 015001.
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Hindriks R., Woolrich M.W., Luckhoo H., Joensson M., Mohseni H., Kringelbach M.L. & Deco G. (2015) Role of white-matter pathways in coordinating alpha oscillations in resting visual cortex. Neuroimage, 106:328-39. doi: 10.1016/j.neuroimage.2014.10.057.
request
Kringelbach M.L. (2015) A balanced mind: a network perspective on mood and motivation brain pathways. In Brain stimulation: methodologies and interventions (ed. Reti I.M.). Wiley, 15-28.
2014pdf_icon
Deco G. & Kringelbach M.L. (2014) Great expectations: using whole-brain computational connectomics for understanding neuropsychiatric disorders. Neuron, 84(3): 892-905.
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Parsons C.E., Young K.S., Jegindø E.-M., Vuust P., Stein A., Kringelbach M.L. (2014) Musical training and empathy positively impact adults' sensitivity to infant distress. Frontiers in Psychology, 5:1440. doi: 10.3389/fpsyg.2014.01440
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Kringelbach M.L. & DiPerna L. (2014) Pleasures of art. Trends in Cognitive Sciences, 18(9):449-50.
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Parsons C.E, Young K.S., Craske M.G., Stein A. & Kringelbach M.L. (2014) Introducing the Oxford Vocal (OxVoc) Sounds Database: A validated set of non-acted affective sounds from human infants, adults and domestic animals. Frontiers in Psychology, 5:562. doi: 10.3389/fpsyg.2014.00562.
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Stevner A. & Kringelbach M.L. (2014) Nydelsens neurobiologi. Kognition & Pædagogik, 24(93): 18-31.
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Bhandari R, van der Veen R, Parsons CE, Young KS, Voorthuis A, Bakermans-Kranenburg MJ, Stein A, Kringelbach ML, van IJzendoorn MH (2014) Effects of intranasal oxytocin administration on memory for infant cues: Moderation by childhood emotional maltreatment. Social neuroscience 9(5):536-547.
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Bhandari R., Bakermans-Kranenburg M.J., Veen R., Parsons C.E., Young K.S., Grewen K.M., Stein A., Kringelbach M.L. & IJzendoorn M.H. (2014) Salivary oxytocin mediates the association between emotional maltreatment and responses to emotional infant faces, Physiology and Behaviour, 131: 123-128.
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Witek M.A.G., Clarke E., Kringelbach M.L. & Vuust P. (2014) Effects of polyphonic context, instrumentation and metrical location on syncopation in music. Music Perception 32:(2), 201-217.
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Witek M. A. G., Clarke E., Wallentin M., Kringelbach M.L. & Vuust P. (2014) Syncopation, body-movement and pleasure in Groove Music. PLoS ONE, 9(4): e94446.
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Boccard SGJ, FitzGerald JJ, Pereira EAC, Moir L, Van Hartevelt T.J, Kringelbach M.L., Green AL, Aziz TZ (2014) Targeting the Affective Component of Chronic Pain: A Case Series of Deep Brain Stimulation of the Anterior Cingulate Cortex. Neurosurgery, 74(6):628-635.
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Nakagawa T.T., Luckhoo H., Woolrich M.W., Joensson M., Mohseni H., Kringelbach M.L., Jirsa V., Deco G. (2014) How delays matter in an oscillatory whole-brain spiking-neuron model for MEG rhythms at rest. Neuroimage, 87:383-94.
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Mohseni H.R., Kringelbach M.L., Woolrich M.W., Baker A., Aziz T.Z. & Probert-Smith P. (2014) Non-Gaussian probabilistic MEG source localisation based on kernel density estimation. Neuroimage, 87:444-64.
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Kringelbach M.L. (2014) Balancing consumption: brain insights from the cyclical nature of pleasure. In The Interdisciplinary Science of Consumption (eds. Preston S, Kringelbach M.L. & Knutson B.), MIT Press.
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Preston S, Kringelbach M.L. & Knutson, B. (2014) Towards an interdisciplinary science of consumption. In The Interdisciplinary Science of Consumption (eds. Preston S, Kringelbach M.L. & Knutson B.), MIT Press.
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Kringelbach M.L. and Berridge K.C. (2014) Brain mechanisms of pleasure: the core affect component of emotion. In The Psychological Construction of Emotion (eds. Barrett LF & Russell J), New York: Guildford, 133-145.
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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. PLoSONE, 9(1): e86496.
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Van Hartevelt, T.J. & Kringelbach M.L. (2014) The olfactory cortex. In Brain Mapping: An Encyclopedic Reference (Arthur W. Toga ed.), Elsevier, 347-55.
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Cabral J., Kringelbach M.L. & Deco G. (2014) Exploring network dynamics underlying brain activity during rest. Progress in Neurobiology, 90:423-35.
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Cabral J., Luckhoo H., Woolrich M.W., Joensson M., Mohseni H.R., Baker A., Kringelbach M.L., Deco G. (2014) Exploring mechanisms of spontaneous MEG functional connectivity: How delayed network interactions lead to structured amplitude envelopes of band-pass filtered oscillations. Neuroimage, 90:423-35.
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Parsons C.E., Young K.S., Bhandari R., IJzendoorn M., Bakermans-Kranenburg M.J. Stein A., Kringelbach M.L. (2014) The Bonnie baby: experimentally manipulated temperament affects perceived cuteness and motivation to view infant faces. Developmental Science, 17(2): 257-69.
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Boccard SGJ, Pereira EAC, Moir L, Van Hartevelt T.J, Kringelbach M.L., FitzGerald JJ, Baker IW, Green AL, Aziz TZ (2014) Deep brain stimulation of the anterior cingulate cortex: targeting the affective component in the management of chronic pain. Neuroreport, 25(2):83-8.
2013pdf_icon
Cabral J., Fernandes H.M., Van Hartevelt, T.J., James A.C., Kringelbach M.L., Deco G. (2013) Altered structural connectivity in schizophrenia and its impact on spontaneous functional networks. Chaos, 23: 046111.
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Parsons C.E, Stark E.A., Young K.S., Stein A. & Kringelbach M.L. (2013) Understanding the human parental brain: a critical role of the orbitofrontal cortex. Social Neuroscience, 8(6): 525-43.
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Mohseni H.R., Kringelbach M.L., Woolrich M.W., Aziz T.Z. & Probert-Smith P. (2013) A new approach to the fusion of EEG and MEG signals using the LCMV beamformer. ICASSP, 1202-6.
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Mohseni H.R., Kringelbach M.L., Woolrich M.W., Aziz T.Z. & Probert-Smith P. (2013) A Non-Gaussian LCMV beamformer for MEG Source Reconstruction. ICASSP, 1247-51.
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Parsons C.E., Young K.S., Joensson M., Brattico E., Hyam J.A., Stein A., Green A.L., Aziz, T.Z., Kringelbach M.L. (2013) Ready for action: A role for the brainstem in responding to infant vocalizations. Social Cognitive and Affective Neuroscience, doi: 10.1093/scan/nst076.
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Callesen M.B., Scheel-Krüger J., Kringelbach M.L. & Møller A. (2013) A systematic review of impulse control disorders in Parkinson's Disease. Journal of Parkinson's Disease, 3:105-138.
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Parsons C.E., Young K.S., Mohseni H., Woolrich M.W., Rømer Thomsen K., Joensson M., Murray L., Goodacre T., Stein A., Kringelbach M.L. (2013) Minor structural abnormalities in the infant face disrupt neural processing: a unique window into early caregiving responses. Social Neuroscience, 8(4):268-74.
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Rømer Thomsen K., Joensson M., Lou H. C. Møller A., Gross J., Kringelbach M.L. & Changeux J.P. (2013) Altered paralimbic interaction in behavioral addiction. PNAS, 110(12):4744-9.
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Berridge K.C. & Kringelbach M.L. (2013) Neuroscience of affect: Brain mechanisms of pleasure and displeasure. Current Opinion in Neurobiology, 23(3):294-303. doi:S0959-4388(13)00033-0.
request
Parsons C.E., Young K.S. & Kringelbach M.L. (2013) Neuroanatomy of pleasure and emotion. In The Neuropsychology of Psychopathology. (Noggle C.A. & Dean R.S., eds.) Springer Press, pp. 29-56.
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Berridge K.C. & Kringelbach M.L. (2013) Towards a neuroscience of well-being - implications of insights from pleasure research. In Human Happiness and the Pursuit of Maximization (Delhey J. & Brockmann H. eds.) Springer Press, pp. 81-100.
2012request
Gebauer L., Kringelbach M.L. & Vuust P. (2012) Ever-changing cycles of musical pleasure: The role of dopamine and anticipation. Psychomusicology, Music, Mind & Brain, 22(2), 152-167.
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Georgiadis J., Kringelbach M.L. & Pfaus J.G. (2012) Sex for fun: a synthesis of human and animal neurobiology. Nature Reviews Urology, 9(9): 486-498. doi:10.1038/nrurol.2012.151.
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Kringelbach M.L. & Berridge K.C. (2012) The joyful mind. Scientific American, 307(2):40-45.
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Georgiadis J. & Kringelbach M.L. (2012) The human sexual response cycle: brain imaging evidence linking sex to other pleasures. Progress in Neurobiology, 98(1): 49-81.
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Cabral J., Hugues E., Kringelbach M.L. & Deco G. (2012) Modeling the outcome of structural disconnection on resting-state functional connectivity. Neuroimage, 62(3):1342-1353.
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Hyam J.A., Kringelbach M.L., Silburn P., Aziz T.Z. & Green A.L. (2012) The autonomic effects of deep brain stimulation - a therapeutic opportunity. Nature Reviews Neurology, 8(7):391-400.
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Mohseni H.R., Probert Smith P., Parsons C.E., Young K.S., Hyam J.A., Stein A., Stein J.F., Green A.L., Aziz T.Z. & Kringelbach M.L. (2012) MEG can map short and long-term changes in brain activity following deep brain stimulation for chronic pain. PLoS ONE, 7(6):e37993.
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Young K.S., Parsons C.E., Stein A, Kringelbach M.L. (2012) Interpreting infant vocal distress: the ameliorative effect of musical training in depression. Emotion, 12(6):1200-5. doi: 10.1037/a0028705.
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Kringelbach M.L., Stein A. & Van Hartevelt T.J. (2012) The functional human neuroanatomy of food pleasure cycles. Physiology and Behaviour 106:307-316.
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Mohseni H.R., Woolrich M.W., Kringelbach M.L., Luckhoo H., Probert Smith P. & Aziz T.Z. (2012) Fusion of magnetometer and gradiometer sensors of MEG in the presence of multiplicative error. IEEE Trans. Biomed. Eng., 59(7): 1951-1961.
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Kringelbach M.L. (2012) The functional neuroanatomy of emotion and hedonic processing. In Neuroscience in the 21st Century. (Pfaff D, ed.) Springer Press, pp. 1335-63.
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Parsons C.E., Young K.S., Parsons E., Stein A., Kringelbach M.L. (2012) Listening to infant distress vocalisations enhances effortful motor performance. Acta Paediatrica, 101(4):e189-91.
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Cabral J., Kringelbach M.L. & Deco G. (2012) Functional graph alterations in schizophrenia: a result from a global anatomical decoupling? Phamacopsychiatry, 45:S1-9.
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Parsons C.E., Young K.S., Rochat T, Kringelbach M.L, Stein A. (2012) Postnatal depression and its effects on child development: a review of evidence from low and middle income countries, British Medical Bulletin, 101(4):e189-91.
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Hyam J.A., Owen S.L.F., Kringelbach M.L., Jenkinson N., Stein J.F., Green A.L. & Aziz T.Z. (2012) Contrasting connectivity of the VIM and VOP nuclei of the motor thalamus demonstrated by probabilistic tractography. Neurosurgery, 70(1):162-169.
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Van Hartevelt, T.J. & Kringelbach M.L. (2012) The olfactory system. In The Human Nervous System. 3rd Ed. (Mai, J. & Paxinos, G., eds), Elsevier, pp. 1219-1238.
2011pdf_icon
Kringelbach M.L. & Aziz, T.Z. (2011) Neuroethical principles of deep brain stimulation. World of Neurosurgery, 76(6): 518-9.
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Lou H.C., Joensson M., Kringelbach M.L. (2011) Yoga lessons for consciousness research: a paralimbic network balancing brain resource allocation. Frontiers in Psychology, 2:366.
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Mohseni H.R., Kringelbach M.L., Woolrich M.W., Smith P.P. & Aziz T.Z. (2011) A fast solution to robust minimum variance beamformer and application to simultaneous MEG and local field potential. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings , 545-548.
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Parsons C.E., Young K.S., Parsons E, Dean A, Murray L, Goodacre T, Dalton L, Stein A, Kringelbach M.L. (2011) The impact of cleft lip on adults' responses to faces: cross-species findings, PLoS ONE 6(10): e25897.
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Berridge K.C. & Kringelbach M.L. (2011) Building a neuroscience of pleasure and well-being. Psychology of Well-Being: Theory, Research and Practice, 1:3.
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Parsons C.E., Young K.S., Kumari N., Stein A. & Kringelbach M.L. (2011) The motivational salience of infant faces is similar for men and women. PLoS ONE, 6(5): e20632.
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Kringelbach M.L., Green, A.L. & Aziz, T.Z. (2011) Balancing the brain: resting state networks and deep brain stimulation. Frontiers in Integrative Neuroscience, 5:8.
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Rømer Thomsen K., Lou H.C., Jønsson M., Hyam J.A., Holland, P., Parsons C.E., Young K.S., Møller A., Stein A., Green A.L., Kringelbach M.L. & Aziz T.Z. (2011) Impact of emotion on consciousness: Positive stimuli enhance conscious reportability. PLoS ONE 6(1): e18686.
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Kringelbach M.L. & Berridge K.C. (2011) The neurobiology of pleasure and happiness. In Oxford Handbook of Neuroethics (Illes J. & Sahakian B.J., eds), Oxford University Press, pp. 15-32.
2010pdf_icon
Kringelbach M.L., Green A.L., Owen S.L.F., Schweder P.M. & Aziz T.Z. (2010) Sing the mind electric: principles of deep brain stimulation. European Journal of Neuroscience, 32(7):1070-9.
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Kringelbach M.L. (2010) Finding pleasure in childhood. Nature, 467:918-9.
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Parsons C.E., Young K.S., Murray L., Stein A. & Kringelbach M.L. (2010) The functional neuroanatomy of the evolving parent-infant relationship. Progress in Neurobiology, 91: 220-241.
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Kringelbach M.L. & Stein A. (2010) Cortical mechanisms of human eating. Forum Nutr. 63: 164-175.
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Kringelbach M.L. & Berridge K.C. (2010) The neuroscience of happiness and pleasure. Social Research, 77:659-678.
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Vuust P. & Kringelbach M.L. (2010) The pleasure of making sense of music. Interdisciplinary Science Reviews, 35(2):168-85.
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Kringelbach M.L. & Berridge K.C. (2010) The functional neuroanatomy of pleasure and happiness. Discovery Medicine, 9(49): 579-87.
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Hansen P.C., Kringelbach M.L. & Salmelin R. (2010) Introduction to MEG. In MEG. An introduction to methods (Hansen P.C., Kringelbach M.L & Salmelin R, eds.), Oxford University Press, pp. vii-x.
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Kringelbach M.L., Hansen P.C., Green A.L. & Aziz T.Z. (2010) Using magnetoencephalography to elucidate the principles of deep brain stimulation. In MEG. An introduction to methods (Hansen P.C., Kringelbach M.L & Salmelin R, eds.), Oxford University Press, pp. 403-423.
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Cornelissen P.L., Hansen P.C., Kringelbach M.L. & Pugh K. (2010) Introduction. In The neural basis of reading (Cornelissen P.L., Hansen P.C., Kringelbach M.L & Pugh K, eds.), Oxford University Press, pp ix-xii.
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Cornelissen P.L., Kringelbach M.L. & Hansen P.C. (2010) Visual word recognition, the first 500 millliseconds. Recent insights from MEG. In The neural basis of reading (Cornelissen P.L., Hansen P.C., Kringelbach M.L & Pugh K, eds.), Oxford University Press, pp. 192-222.
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Kringelbach M.L. & Rømer Thomsen K. (2010) Colourful pleasures of the brain. In Colour in Art (Crenzien H. ed.), Louisiana/Dumont, pp. 106-113.
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Kringelbach M.L. and Berridge K.C. (2010) Introduction: the many faces of pleasure. In Pleasures of the brain (Kringelbach M.L & Berridge K.C., eds.), Oxford University Press, pp. 3-6.
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Kringelbach M.L. (2010) The hedonic brain: a functional neuroanatomy of human pleasure. In Pleasures of the brain (Kringelbach M.L & Berridge K.C., eds.), Oxford University Press, pp. 202-221.
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Kringelbach, M. L.(2010) Short Answers to Fundamental Questions about Pleasure. In Pleasures of the Brain (Kringelbach M.L & Berridge K.C., eds.), Oxford University Press, pp. 7-23.
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Vuust P. & Kringelbach M.L. (2010) The pleasure of music. In Pleasures of the brain (Kringelbach M.L & Berridge K.C., eds.), Oxford University Press, pp. 255-269.
2009pdf_icon
Kringelbach M.L. & Berridge K.C. (2009) Towards a functional neuroanatomy of pleasure and happiness. Trends in Cognitive Sciences, 13(11): 479-487.
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Kringelbach M.L. & Aziz T.Z. (2009) Deep brain stimulation: Avoiding the errors of psychosurgery. JAMA, 301(16): 1705-1707.
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Rømer Thomsen K., Callesen M.B, Linnet J., Kringelbach M.L. & Møller A. (2009) Severity of gambling is associated with severity of depressive symptoms in pathological gamblers. Behavioral Pharmacology, 20:527-536.
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Kringelbach M.L., Pereira E.A.C., Green A.L., Owen S.L.F. & Aziz T.Z. (2009) Deep brain stimulation for chronic pain. Journal of Pain Management, 3: 301-314.
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Kringelbach M.L., Green A.L., Pereira E.A.C., Owen S.L.F. & Aziz T.Z. (2009) Deep brain stimulation. The Biologist, 56:144-148.
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Kringelbach M.L. & Fejerskov O. (2009) Indsigt og udsyn: et internationalt perspektiv på fremtidens danske universitet. In Fremtidens Universitet (Sander H., ed.). Gyldendal.
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Cornelissen P.L., Kringelbach M.L., Ellis A.W., Whitney C. Holliday I.E. & Hansen P.C. (2009) Activation of the left inferior frontal gyrus (pars opercularis) in the first 200 msec of reading: evidence from magnetoencephalography (MEG). PLoS ONE, 4(4): e5359. doi:10.1371/journal.pone.0005359.
requestKringelbach M.L. (2009) Neural basis of mental representations of motivation, emotion and pleasure. In Handbook of Neuroscience for the Behavioral Sciences (Berntson G. G. & Cacioppo J.T., eds), New York: John Wiley and sons, pp. 807-28.
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Grover P.J., Pereira E.A.C., Green A.L., Brittain J.-S., Owen S.L.F., Schweder P., Kringelbach M.L., Davies P.T. & Aziz T.Z. (2009) Deep brain stimulation for cluster headache. JOCN, 16:861-866.
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Green A.L., Wang S., Stein J.F., Pereira E.A.C., Kringelbach M.L., Liu X, Brittain J.-S., Aziz T.Z. (2009) Neural signatures in patients with neuropathic pain. Neurology, 72:569-71.
requestRay N.J., Jenkinson N., Kringelbach M.L., Hansen P.C., Pereira E., Brittain J.-S., Holland P., Holliday I.E., Owen S.L.F., Stein J. F. & Aziz T.Z. (2009) Abnormal thalamocortical dynamics may be altered by deep brain stimulation (DBS): using magnetoencephalography to study DBS for phantom limb pain. Journal of Clinical Neuroscience , 16:32-36.
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Kalbitzer J., Frokjaer V.G., Erritzoe D., Svarer C., Cumming P, Nielsen F.A., Hashemi S.H., Sayed H., Baaré W.F.C., Madsen J., Hasselbalch S.G., Kringelbach M.L., Mortensen E.L. & Knudsen G.M. (2009) The personality trait openness is related to cerebral 5-HTT levels. Neuroimage, 45:280-5. doi:10.1016/j.neuroimage.2008.12.001.
2008pdf_icon
Kringelbach M.L. & Aziz T.Z. (2008) Sparking recovery with brain “pacemakers”. Scientific American Mind, 6:36-43.
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Kringelbach M.L., Vuust P. & Geake J. (2008) The pleasure of reading. Interdisciplinary Science Reviews 33.4, 321-335.
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Kringelbach M.L., Lehtonen A., Squire, S., Harvey A.G., Craske M.G., Holliday I.E., Green A.L., Aziz T.Z., Hansen P.C., Cornelissen P.L. & Stein A. (2008) A specific and rapid neural signature for parental instinct. PLoS ONE 3(2), e1664.
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Berridge K.C. & Kringelbach M.L. (2008) Affective neuroscience of pleasure: Reward in humans and other animals. Psychopharmacology 199, 457-80.
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Owen S.L.F., Heath J, Kringelbach M.L., Green A.L., Periera E.A.C., Jenkinson N., Jegan T., Stein J.F. & Aziz T.Z. (2008) Pre-operative DTI and probabilistic tractography in four patients with deep brain stimulation for chronic pain. Journal of Clinical Neuroscience 15:801-5.
2007pdf_icon
Kringelbach M.L., Jenkinson N., Owen S.L.F. & Aziz T.Z. (2007) Translational principles of deep brain stimulation. Nature Reviews Neuroscience, 8:623-635.
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Kringelbach M.L., Owen S.L.F. & Aziz T.Z. (2007) Deep brain stimulation. Future Neurology, 2:633-46.
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Owen S.L.F., Heath J., Kringelbach M.L., Stein J.F., Aziz T.Z. (2007) Pre-operative DTI and probabilistic tractography in an amputee with deep brain stimulation for lower stump pain: current status. British Journal of Neurosurgery, 21:485-490.
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Kringelbach M.L. (2007) Emotion, feelings and hedonics in the human brain. In The Emotions: a cultural reader (H. Wulff, ed.) Oxford: Berg Publishers, pp. 37-60.
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Kringelbach M.L. (2007) Orbitofrontal cortex: Emotioner og følelser i menneskehjernen. In Følelser og kognition (M. Skov & T. Wiben, eds.) Copenhagen: Museum Tusculanum Press, pp. 77-104.
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Geake J. & Kringelbach M.L. (2007) Imaging imagination: brain scanning of the imagined future. In Proceedings of the British Academy, 147: 307-326.
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Muthusamy K.A., Aravamuthan B.R., Kringelbach M.L., Jenkinson, N., Voets N.L., Johansen-Berg H., Stein J. F., Aziz T.Z. (2007) Connectivity of the human Pedunculopontine nucleus region (PPN) and diffusion tensor imaging in surgical targeting. Journal of Neurosurgery, 107:814-820.
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De Pennington N., Cattrell A., Ray N., Jenkinson N.W., Aziz T.Z., Kringelbach M.L. (2007) Neuroimaging of sensory and affective experience in the human brain. CoDesign, 3:45-55.
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Ray N.J, Kringelbach M.L, Jenkinson N., Owen S.L.F., Davies P., Wang S., De Pennington N., Hansen P.C., Stein J, Aziz T.Z. (2007) Using magnetoencephalography to investigate high frequency deep brain stimulation in a cluster headache patient. Biij, 3(1):e25.
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Kringelbach M.L., Jenkinson N., Green A.L., Owen S.L.F., Hansen P.C., Cornelissen P.L., Holliday I.E., Stein J., Aziz T.Z. (2007) Deep brain stimulation for chronic pain investigated with magnetoencephalography. NeuroReport, 8(3):223-228.
2006pdf_icon
Kringelbach M.L. (2006) Cortical systems involved in appetite and food consumption. In Appetite and body weight: integrative systems and the development of anti-obesity drugs (Cooper S.J. & Kirkham T. C., eds) London: Elsevier, pp. 5-26.
 Kringelbach M.L. (2006) Hjernerum – læring, motivation og emotion. In Innovation og aflæring (Pauli Nielsen, ed.), pp 18-48.
2005pdf_icon
Kringelbach M.L. (2005) The human orbitofrontal cortex: linking reward to hedonic experience. Nature Reviews Neuroscience, 6:691-702.
 Kringelbach M.L. (2005) Fra sans til samling: Følelsernes rationalitet. Kritik, 174:11-21.
2004pdf_icon
Pammer K., Hansen P.C., Kringelbach M.L., Holliday I.E., Barnes G., Hillebrand A., Singh K.D. & Cornelissen P.L. (2004) Visual word recognition: the first half second, Neuroimage 22(4):1819-1825.
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Kringelbach M.L. (2004) Food for thought: hedonic experience beyond homeostasis in the human brain, Neuroscience, 126:807-819.
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Kringelbach M.L. (2004) Emotion. In The Oxford Companion to the Mind 2nd edition (R.L. Gregory, ed.) Oxford: Oxford University Press, pp. 287-290.
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Kringelbach M.L. & Rolls E.T. (2004) The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology, Progress in Neurobiology, 72:341-72.
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Kringelbach M.L. (2004) Learning to change, PLoS Biology, 2(5): 577-579.
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Kringelbach M.L., de Araujo I.E.T. & Rolls E.T. (2004) Taste-related activity in the human dorsolateral prefrontal cortex, Neuroimage, 21(2):781-788.
 O’Doherty J., Rolls E.T. & Kringelbach M.L. (2004) Neuroimaging studies of crossmodal integration for emotion. In Handbook of Multisensory Processing (G. Calvert, C. Spence & B. Stein eds.) Cambridge, Mass.: MIT Press, pp. 563-579.
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Völlm B., de Araujo I.E.T., Cowen P., Rolls E.T., Kringelbach M.L., Smith K.A., Jezzard P., Heal R.J. & Matthews P. (2004) Methamphetamine activates reward circuitry in drug naïve human subjects, Neuropsychopharmacology, 29:1715-1722.
2003pdf_icon
Kringelbach M.L. & Rolls E.T. (2003) Neural correlates of rapid context-dependent reversal learning in a simple model of human social interaction, Neuroimage, 20(2):1371-1383.
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Kringelbach M.L., O’Doherty J., Rolls E.T. & Andrews C. (2003) Activation of the human orbitofrontal cortex to a liquid food stimulus is correlated with its subjective pleasantness, Cerebral Cortex, 13(10): 1064-1071.
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De Araujo I.E.T., Rolls E.T., Kringelbach M.L., McGlone F. & Phillips N. (2003) Taste-olfactory convergence, and the representation of the pleasantness of flavour, in the human brain, European Journal of Neuroscience, 18:2059-2068.
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De Araujo I.E.T., Kringelbach M.L., Rolls E.T. & McGlone, F. (2003) Human cortical responses to water in the mouth, and the effects of thirst, Journal of Neurophysiology, 90: 1865-1876.
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De Araujo I.E.T., Kringelbach M.L., Rolls E.T. & Hobden, P. (2003) The representation of umami taste in the human brain, Journal of Neurophysiology, 90:313-319.
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Rolls E.T., Kringelbach M.L. & de Araujo I.E.T. (2003) Different representations of pleasant and unpleasant odours in the human brain, European Journal of Neuroscience, 18:695-703.
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Rolls E.T., O’Doherty J., Kringelbach M.L., Francis S., Bowtell S. & McGlone F. (2003) Pleasant and painful touch are represented in the human orbitofrontal and cingulate cortices, Cerebral Cortex, 13: 308-317
2002pdf_icon
Wilson J., Jenkinson M., Araujo I., Kringelbach M.L., Rolls E.T. & Jezzard P. (2002) Fast, fully automated global and local magnetic field optimisation for fMRI of the human brain, Neuroimage, 17: 967-976.
2001pdf_icon
O’Doherty J., Kringelbach M.L., Rolls E.T., Hornak J. & Andrews C. (2001) Abstract Reward and Punishment Representations in the Human Orbitofrontal Cortex, Nature Neuroscience, 4(1):95-102.