Short CV/Education and training

  • Roshan Cools studies the chemistry of the adaptive mind: the motivational and cognitive control of human behaviour and its modulation by the major ascending neuromodulators (in particular dopamine and serotonin). She is an elected member of the Royal Netherlands Academy of Arts and Sciences and the Academia Europaea.

  • She completed her undergraduate degree in Experimental Psychology at the University of Groningen, The Netherlands, in 1998. She then moved to Trevor Robbins’ lab at the University of Cambridge, UK, for an M Phil degree (1999), a PhD degree (2002), a St John’s College Junior Research Fellowship (2002-2006) and a Royal Society Dorothy Hodgkin Research Fellowship (2002 – 2006).

  • She spent two post-doc years at UC Berkeley working with Mark D’Esposito from 2003, before moving back to Cambridge in 2005, where she obtained a Royal Society University Research Fellowship (2006 -2007).

  • In November 2007 she returned to The Netherlands, where she is now Principal Investigator at the Donders Institute for Brain, Cognition and Behaviour and Professor of Cognitive Neuropsychiatry at the Radboud university medical center in Nijmegen, holding several prestigious awards, e.g. from the Dutch Organisation for Scientific Research (a Vici), the James McDonnell foundation (a scholar award) and the Royal Netherlands Academy of Arts and Sciences (a KNAW Ammodo award).

  • She serves as active editor for the Journal of cognitive Neuroscience and the Journal of Neuroscience and is a member of the Advisory Council for Science, Technology and Innovation (to the Dutch government) and the Board of the Rathenau Institute.

Selected publications

  • Froböse M I, Swart JC, Cook JL, Geurts DEM, den Ouden HEM, Cools R (in press). Catecholaminergic modulation of the avoidance of cognitive control. Journal of Experimental Psychology: General.

  • van Holst R, Sescousse R, Janssen LK, Janssen M, Berry AS, Jagust WJ, Cools R (2018). Increased striatal dopamine synthesis capacity in gambling addiction. Biological Psychiatry 83(12):1036-1043

  • Swart J, Froböse M, Cook J, Geurts D, Frank MJ, Cools R* and den Ouden H* (2017). Catecholaminergic challenge uncovers distinct Pavlovian and instrumental mechanisms of motivated (in)action. Elife; 6:e22169

  • Piray P, den Ouden HEM, Van der Schaaf ME, Toni E, Cools R (2017). Dopaminergic modulation of the functional ventrodorsal architecture of the human striatum. Cerebral Cortex 27(1):485-495

  • Fallon SJ, Van der Schaaf ME, ter Huurne N, Cools R (2017). The neurocognitive cost of enhancing cognition with methylphenidate: improved distractor resistance but impaired updating. J Cogn Neurosci 29(4):652-663

  • Den Ouden H, Fernandez G, Elshout J, Rijpkema M, Hoogman M, Franke B, Daw ND, Cools R (2013). Dissociable effects of dopamine and serotonin on reversal learning. Neuron 80(4):1090-100

  • Geurts D, Huys Q, den Ouden H, Cools R (2013). Serotonin and aversive Pavlovian control of instrumental behavior in humans. J Neurosci 33(48):18932-9

  • Van Schouwenburg M, O'Shea J, Mars R, Rushworth R, and Cools R (2012). Controlling human striatal cognitive function via the frontal cortex. J Neurosci 32(16):5631-7

  • Cools R and D’Esposito M (2011). Inverted-U-Shaped dopamine actions on human working memory and cognitive control. Biol Psychiatry 69(12):e113-25

  • Cools R, Nakamura K, Daw ND (2011): Serotonin and Dopamine: Unifying Affective, Activational, and Decision Functions. Neuropsychopharmacology Reviews 36(1):98-113


Selected projects

Chemical neuromodulation of higher cognitive function

  • The goal of the Motivational and Cognitive Control lab is to understand the mental processes, computations, and neural mechanisms that enable and motivate us to act in accordance with our goals.

    We approach this question by studying effects of challenging the major ascending chemical neuromodulators, such as dopamine, noradrenaline and serotonin. These different systems have diffuse ramifications throughout cortical and subcortical regions that enable them to exert a global influence on brain function. However, they are now also well established to modulate dissociable functions, in part reflecting their innervation of distinct target regions.

    To study these effects, we combine psychopharmacology, functional MRI, neurochemical PET and computational cognitive modelling in human volunteers with and without neuropsychiatric disorders.

  • Cognitive Control and Working Memory

  • Cognitive flexibility versus stability: Role of dopamine (and noradrenaline)

  • The brain catecholamines dopamine (and noradrenaline) play important roles in complex cognitive functions such as working memory. This somewhat ill-defined term generally refers to the ‘on-line’ stabilization of task-relevant representations, but often also implies flexible updating of those representations in response to novel information. A dynamic task-dependent balance between these opponent functions is critically important for a wide range of cognitive abilities such as reasoning, language comprehension, planning, and spatial processing and has been associated most commonly with circuits connecting the prefrontal cortex with the striatum. One major goal of our group is to unravel the roles of the catecholamines in cognitive flexibility and in its tradeoff with cognitive stability.

  • Read more >

    Flexible updating and stabilization can be conceptualized as representing functionally opponent processes. If we update too readily, then we are likely to get distracted, rendering our behavior unstable. Conversely, if our representations are overly persistent or stable, then there is a danger of inflexibility and unresponsiveness to new information. In the lab, we use psychopharmacology, cognitive science, functional magnetic resonance imaging and dopamine PET imaging to study the catecholaminergic modulation of working memory. We test the hypothesis that the balance between cognitive flexibility and stability is adjusted depending on task demands, and sensitive to challenges of the catecholamine system, for example, with methylphenidate, or tyrosine supplementation. Evidence so far indicates that the same dopaminergic drug (or disorder) can have opposite effects on task performance depending on demands for cognitive stability and flexibility (Fallon et al., 2016; Cools et al., 2010). Moreover, effects of dopaminergic drugs on cognitive stability and flexibility are accompanied by modulation of distinct prefrontal and striatal brain regions respectively (Cools et al., 2011; 2007). We are currently working on further psychopharmacological studies, for example with patients with Parkinson’s disease, to study the role of noradrenaline in the tradeoff between cognitive flexibility and stability in working memory.

  • Fallon SJ, Van der Schaaf ME, ter Huurne N, Cools R (2017). The neurocognitive cost of enhancing cognition with methylphenidate: improved distractor resistance but impaired updating. J Cogn Neurosci 29(4):652-663

  • Boot N, Baas M, van Gaal S, Cools R, De Dreu CKW (2017). Creative Cognition and Dopaminergic Modulation of Fronto-striatal Networks: Integrative Review and Research Agenda. Neuroscience & Biobehavioral Reviews 78:13-23

  • Goldfarb EV, Frobose MI, Cools R, Phelps RA (2017). Stress and cognitive flexibility: Cortisol increases are associated with enhanced updating but impaired switching. J Cogn Neurosci 29(1):14-24

  • Van Schouwenburg MR, den Ouden H, Cools R (2015). Selective attentional enhancement and inhibition of fronto-posterior connectivity by the basal ganglia during attention switching. Cerebral Cortex 25(6):1527-34

    Bloemendaal M; van Schouwenburg M; Miyakawa A; Aarts E; D'Esposito M; Cools R (2015). Dopaminergic modulation of distracter-resistance and prefrontal delay period signal. Psychopharm 232(6):1061-70

    Fallon SJ, Smulders K, Esselink R, van de Warrenburg BP, Bloem BR, Cools R (2015). Differential optimal dopamine levels for set-shifting and working memory in Parkinson’s disease. Neuropsychologia 77:42-51.

    Van Schouwenburg MR, Onnink AMH; ter Huurne N; Kan CC, Zwiers MP, Hoogman M, Franke B, Buitelaar JK, Cools R (2014). Cognitive flexibility depends on white matter microstructure of the basal ganglia. Neuropsychologia 53:171-7

  • Beeler JA, Cools R, Luciana M, Ostlund S, Petzinger G (2014). A kinder, gentler dopamine…Highlighting dopamine’s role in behavioural flexibility. Front Neurosci 8:4

  • Stelzel C, Fiebach CJ, Cools R, Tafazoli S, D’Esposito M (2013). Dissociable fronto-striatal effects of dopamine D2 receptor stimulation on cognitive vs. motor flexibility. Cortex 49(10):2799-811

  • Van Schouwenburg MR, Zwiers MP, van der Schaaf ME, Geurts DE, Schellekens AF, Buitelaar JK, Verkes RJ, Cools R (2013) Anatomical connection strength predicts dopaminergic drug effects on fronto-striatal function. Psychopharm 227(3):521-31

  • Van Schouwenburg M, O'Shea J, Mars R, Rushworth R, and Cools R (2012). Controlling human striatal cognitive function via the frontal cortex. J Neurosci 32(16):5631-7

  • Cools R (2011). Dopaminergic control of the striatum for high-level cognition. Curr Opin Neurobiol 21:402-407

  • Cools R and D’Esposito M (2011). Inverted-U-Shaped dopamine actions on human working memory and cognitive control. Biol Psychiatry 69(12):e113-25.

  • Van Schouwenburg M, Den Ouden H, Cools R (2010). The human basal ganglia modulate fronto-posterior connectivity during attention shifting. J Neurosci 30:9910-9918.

  • Van Holstein M, Aarts E, van der Schaaf ME, Geurts DE, Verkes RJ, Franke B, van Schouwenburg MR, Cools R (2011). Human cognitive flexibility depends on dopamine D2 receptor signaling. Psychopharm 218(3):567-78.

  • Van Schouwenburg M, Aarts E, Cools R (2010). Dopaminergic Modulation of Cognitive Control: Distinct Roles for the Prefrontal Cortex and the Basal Ganglia. Curr Pharm Des 16(18):2026-32 [3.6]

  • Cools R, Miyakawa A, Sheridan M, D'Esposito M (2010). Enhanced frontal function in Parkinson's disease. Brain 133:225-33

  • Van Schouwenburg M, Den Ouden H, Cools R (2010). The human basal ganglia modulate fronto-posterior connectivity during attention shifting. J Neurosci 30:9910- 9918

  • Cools R, Gibbs SE, Miyakawa A, Jagust W, D'Esposito M (2008). Working memory capacity predicts dopamine synthesis capacity in the human striatum. J Neurosci 28(5):1208-12

  • Cools R, Sheridan M, Jacobs EJ, D’Esposito MD (2007). Impulsive personality predicts dopamine-dependent changes in fronto-striatal activity during component processes of working memory. J Neurosci 27(20): 5506-5514

  • Cools R, Barker R A, Sahakian B J, Robbins T W (2003). L-Dopa medication remediates cognitive inflexibility, but increases impulsivity in patients with Parkinson’s disease. Neuropsychologia 41:1431-1441

  • Lewis SJ, Cools R, Robbins TW, Dove A, Barker RA, Owen AM (2003). Using executive heterogeneity to explore the nature of working memory deficits in Parkinson's disease. Neuropsychologia 41(6):645-54

  • Cools R, Stefanova E, Barker RA, Robbins TW, Owen AM (2002) Dopaminergic modulation of high-level cognition in Parkinson’s disease: The role of prefrontal cortex revealed by PET. Brain 125: 584-594

  • Cools R, Barker RA, Sahakian BJ, and Robbins TW (2001). Mechanisms of cognitive set flexibility in Parkinson’s disease. Brain 124:2503-2512

  • Reinforcement Learning and Decision Making

  • Reversal learning and Compulsivity: Role of Dopamine

  • Brain dopamine is probably best known for its implication in reinforcement learning. We study the contribution of dopamine to not only reward, but also punishment learning, in the context of reversal learning paradigms, as models of compulsivity. Indeed dopamine-related compulsivity, as seen in addiction or in medicated Parkinson’s disease, has often been attributed to dopamine-induced increases in the weight on the benefits versus the costs of actions. In the lab, we combine psychopharmacology with computational reinforcement learning modeling, genetics, electrophysiology and/or neuroimaging (EEG, PET and fMRI) to increase our understanding of the paradoxical relationship between dopamine and compulsivity.

  • Recent relevant papers:

    Van der Schaaf ME, Van Schouwenburg MR, Geurts D, Schellekens AFA, Buitelaar J, Verkes RJ, Cools R (2014). Establishing the dopamine-dependency of human striatal signals during reward and punishment reversal learning. Cereb Cortex 24(3):633-42

  • Den Ouden H, Fernandez G, Elshout J, Rijpkema M, Hoogman M, Franke B, Daw ND, Cools R (2013). Dissociable effects of dopamine and serotonin on reversal learning. Neuron 80(4):1090-100

  • Read more>

    For example, we have shown, using computational genetics, that effects of the dopamine transporter polymorphism on perseveration after a reversal are better accounted for by increased reliance on previous reinforcement, corresponding computationally to a reduction in the learning rate, than by reduced sensitivity to punishment (den Ouden et al., 2013). Furthermore, in a different line of work, we have demonstrated that the same dopaminergic drug can have diametrically opposite effects on reversal learning, in subjects with high and low baseline dopamine synthesis capacity in the striatum (Cools et al. 2009). Moreover, the use of a pretreatment design enabled us to conclude that such effects are mediated by the dopamine D2 receptor. That study also showed that it was accompanied by modulation of BOLD signal in the striatum and can be predicted from individual variation in baseline working memory capacity (Van der Schaaf et al., 2014). In ongoing work, we acquire PET and psychopharmacological (fMRI) data from large samples of volunteers (n±100 ) to account for the large individual variability in drug effects on reward learning, thus incidentally also contributing to precision psychiatry.

    Van der Schaaf ME, Van Schouwenburg MR, Geurts D, Schellekens AFA, Buitelaar J, Verkes RJ, Cools R (2014). Establishing the dopamine-dependency of human striatal signals during reward and punishment reversal learning. Cereb Cortex 24(3):633-42

  • Van der Schaaf ME, Fallon SJ, ter Huurne N, Buitelaar J, Cools R (2013). Working memory capacity predicts effects of methylphenidate on reversal learning. Neuropsychopharmacology 38(10):2011-8

  • Van der Schaaf ME, Zwiers MP, van Schouwenburg MR, Geurts DEM, Schellekens AFA, Buitelaar JK, Verkes RJ, Cools R (2013). Dopaminergic drug effects during reversal learning depend on anatomical connections between the orbitofrontal cortex and the amygdala. Front Neurosci. Aug 14;7:142

  • Von Borries K, Verkes RJ, Bulten BH, Cools R, de Bruijn ERA (2013). Feedback-related negativity codes outcome valence, but not outcome expectancy during reversal learning. Cogn Affect Behav Neurosci 13(4):737-46

  • Smittenaar P, Chase HW, Aarts E, Nusselein B, Bloem BR, Cools R (2012). Decomposing effects of dopaminergic medication in Parkinson’s disease on probabilistic action selection: learning or performance? Eur J Neurosci 35(7):1144-51

  • Van der Schaaf M, Warmerdam E, Crone E, Cools R (2012). Distinct linear and non-linear trajectories of reward and punishment reversal learning during development: Relevance for dopamine's role in adolescent decision making. Developmental Cognitive Neuroscience 1(4):578-90

  • Chase HW, Swainson R, Durham L, Benham L, Cools R (2011). Feedback-related negativity codes prediction error, but not behavioural adjustment during probabilistic reversal learning. J Cogn Neurosci. 23(4):936-946 [5.7]

  • Robinson OJ, Frank MJ, Sahakian BJ, Cools R (2010). Dissociable responses to punishment in distinct striatal regions during reversal learning. Neuroimage 51:1459-1467

  • Robinson OJ, Standing HR, DeVito EE, Cools R, Sahakian BJ (2010). Dopamine precursor depletion improves punishment prediction during reversal learning in healthy females but not males. Psychopharm 211(2):187-95

  • Cools R, Frank MF, Gibbs SE, Miyakawa A, Jagust W, D'Esposito M (2009). Striatal dopamine predicts outcome-specific reversal learning and its sensitivity to dopaminergic drug administration. J Neurosci 29: 1538-1543

  • Clatworthy PL, Lewis SJ, Brichard L, Hong YT, Izquierdo D, Clark L, Cools R, Aigbirhio FI, Baron JC, Fryer TD, Robbins TW (2009). Dopamine release in dissociable striatal subregions predicts the different effects of oral methylphenidate on reversal learning and spatial working memory. J Neurosci 29(15):4690-6

  • Dodds CM, Müller U, Clark L, van Loon A, Cools R, Robbins TW (2008). Methylphenidate has differential effects on blood oxygenation level-dependent signal related to cognitive subprocesses of reversal learning. J Neurosci 28(23):5976-82

  • Cools R, Lewis SGJ, Clark L, Barker RA, Robbins TW (2007). L-DOPA disrupts activity in the nucleus accumbens during reversal learning in Parkinson’s disease. Neuropsychopharmacology 32 (1): 180-189

  • Cools R, Altamirano L, D’Esposito M (2006). Reversal learning in Parkinson’s disease depends on medication status and outcome valence. Neuropsychologia 44 (10):1663-1673

  • Cools R, Clark L, Owen AM, Robbins TW (2002). Defining the neural mechanisms of probabilistic reversal learning using event-related functional MRI. J Neurosci 22: 4563-4567

  • Cools R, Barker RA, Sahakian BJ, Robbins TW (2001). Enhanced or impaired cognitive function in Parkinson's disease as a function of dopaminergic medication and task demands. Cereb Cortex 11:1136-1143

  • Motivational Control

  • Motivation of Cognitive Control: Role of Dopamine

  • Our third line of research represents an integration of our first and second lines of work: Dopamine’s dual roles in cognitive control and in value computation lead to the obvious next question whether value-based decisions about whether or not to exert cognitive control also depend on dopamine transmission.

  • An answer to this question would begin to address why people so often fail to exert cognitive control. Resource allocation accounts have shifted attention from capacity limitation to motivation. According to these accounts, cognitive control comes not only with benefits, but also with a cost based on which people (learn to) decide to avoid exerting control. However, the nature of this cost of cognitive control is unclear. In ongoing work, we are studying the origins of both the cost and benefits of cognitive control: What makes some people cognition avoidant, but others cognition seeking?

  • Relevant recent papers

  • Froböse M, Swart JC, Cook JL, Geurts DEM, den Ouden HEM, Cools R (2018). Catecholaminergic modulation of the avoidance of cognitive control. J Exp Psychol: Gen 147(12):1763-1781

    Timmer MHM, Esselink RAJ, Cools R (2018). Enhanced motivation of cognitive control in Parkinson’s disease. Eur J Neurosci 48(6):2374-2384.

    Froböse M, Cools R. (2018). Chemical neuromodulation of cognitive control avoidance. Curr Opinion Behav Sci 22, 121-127

    Cools R (2016). The costs and benefits of brain dopamine for cognitive control. Wiley Interdiscip Rev Cogn Sci 7(5):317-329

    Read more>

  • Resource allocation accounts are supported by experiments that show that performance decrements caused by effort can be overcome by increases in incentive motivation, for example as a function of monetary rewards. We have demonstrated that effects of incentive motivation on cognitive control depend on striatal dopamine, in healthy volunteers and in patients with Parkinson’s disease (Aarts et al., 2010; 2012;2014; Timmer et al. 2017).

  • According to some such resource allocation accounts, the subjective cost of cognitive effort represents a motivational signal to switch to alternative tasks, thus promoting flexibility and preventing fixation on a current ongoing task. We are currently assessing whether failures of cognitive control can reflect a choice to pursue alternative tasks that may be more rewarding.

    Such a motivational mechanism would be adaptive, given that our constantly changing environment requires a dynamic balance between the cognitive states of focus and flexibility.

  • The key question is how we decide when to be focused and when to relax the constraints and destabilize in order to be flexible. We have argued that we arbitrate between a focused (closed) state versus a flexible (open) one, based on a cost-benefit analysis in which the value of cognitive effort corresponds to increased focus and is weighted against its (e.g. opportunity) cost, corresponding to reduced flexibility.

  • Relevant papers:

    Westbrook A, Cools R, Braver TS (2019). Editorial. Special Issue on Cognitive Effort. Neuropsychologia 123:1-4.

    Cools R (2015). The cost of dopamine for dynamic cognitive control. Current Opinion in Behavioral Sciences 4: 152-159

    Aarts E, van Holstein M, Hoogman M, Onnink M, Kan C, Franke B, Buitelaar J, Cools R (2015). Reward modulation of cognitive function in adult ADHD: a pilot study on the role of striatal dopamine. Behav Pharmacol 26(1-2):227-40

    Piray P, den Ouden HEM, Van der Schaaf ME, Toni E, Cools R (2017). Dopaminergic modulation of the functional ventrodorsal architecture of the human striatum. Cerebral Cortex 27(1):485-495

  • Aarts E, Wallace DL, Dang LC, Jagust W, Cools R, D'Esposito M (2014). Dopamine and the cognitive downside of a promised bonus. Psych Sci 25(4):1003-9

  • Braver T, Krug M, Chiew K, Kool W, Westbrook J, Clement N, Adcock A, Barch D, Botvinick M, Carver C, Cools R, Custers R, Dickinson A, Dweck C, Fishbach A, Gollwitzer P, Hess T, Isaacowitz D, Mather M, Murayama K, Pessoa L, Samanez-Larkin G, Somerville L (2014). Mechanisms of Motivation-Cognition Interaction: Challenges and Opportunities. Cogn Affect Behav Neurosci 14(2):443-72

  • Fallon SJ, Cools R (2014). Reward Acts on the pFC to Enhance Distractor Resistance of Working Memory Representations. J Cogn Neurosci 26(12):2812-26

  • Aarts E, Helmich RC, Janssen MJ, Oyen WJ, Bloem BR, Cools R (2012). Aberrant reward processing in Parkinson's disease is associated with dopamine cell loss. Neuroimage 59(4):3339-46

  • Aarts E, van Holstein M, Cools R (2011) Striatal dopamine and the interface between motivation and cognition. Front Cognition 2; 163.

  • Aarts E, Roelofs A, Franke B, Rijpkema M, Fernández G, Helmich RC, Cools R (2010). Striatal dopamine mediates the interface between motivational and cognitive control in humans: Evidence from genetic imaging. Neuropsychopharmacology 35:1943-1951

  • Motivational Biases of Behaviour: Role of Serotonin versus Dopamine

  • When we see a threat, we tend to hold back. When we see a reward, we have a strong urge to approach. Reward or punishment cues bias action, eliciting appetitive activation and/or aversive inhibition, respectively. Such motivational biases of behavior are often considered to reflect cue-based, ‘Pavlovian’ effects, which arise as hardwired responses to learned stimulus-associated outcome predictions. We study the role of catecholamine as well as serotonin transmission in these motivational action biases, which we have shown can in fact arise also from biases in instrumental learning (Swart et al., 2019). Specifically we have tested the motivational opponency hypothesis, according to which serotonin and dopamine play key roles in linking so-called Pavlovian aversive and appetitive predictions with behavioral inhibition and activation, respectively. Moreover, we study the degree to which such motivational biases can transfer to more cognitive learning systems (Piray et al. 2019).

  • Recent relevant publications

    Piray P, Ly V, Roelofs K, Cools R*, Toni I* (2019). Emotionally aversive cues suppress neural systems underlying optimal learning in socially anxious individuals. J Neurosci 39 (8):1445-1456

    Swart J, Froböse M, Cook J, Geurts D, Frank MJ, Cools R* and den Ouden H* (2017). Catecholaminergic challenge uncovers distinct Pavlovian and instrumental mechanisms of motivated (in)action. Elife May 15, 6

  • Geurts D, Huys Q, den Ouden H, Cools R (2013). Serotonin and aversive Pavlovian control of instrumental behavior in humans. J Neurosci 33(48):18932-9

  • Cools R, Nakamura K, Daw ND (2011): Serotonin and Dopamine: Unifying Affective, Activational, and Decision Functions. Neuropsychopharmacology Reviews 36(1):98-113

    Read more>

    Crockett M and Cools R (2015). Serotonin and aversive processing in affective and social decision-making. Current Opinion in Behavioral Sciences 5:64-70

  • den Ouden HEM, Swart JC, Schmidt K, Fekkes D, Geurts DEM, Cools R (2015).

    Acute serotonin depletion releases motivated inhibition of response vigour. Psychopharm 232(7):1303-12

  • Chiu Y-C, Cools R, Aron A (2014). Opposing Effects of Appetitive and Aversive Cues on Go/ Nogo Behavior and Motor Excitability. J Cogn Neurosci 26(8):1851-60

  • Ly V, Bergman TO, Gladwin T, Volman I, Usberti N, Cools R*, and Roelofs K* (2016). Reduced affective biasing of instrumental action with tDCS over the prefrontal cortex. Brain Stimulation 9(3):380-7

  • Ly V, Huys Q, Stins J, Roelofs K, Cools R (2014). Individual differences in bodily freezing predict emotional biases in decision making. Front Behav Neurosci 8:237

  • Geurts DEM, Huys QJM, den Ouden HEM, Cools R (2013). Aversive Pavlovian control of instrumental behaviour in humans. J Cogn Neurosci 25(9):1428-41 [5.7]

  • Crockett MJ, Clark L, Roiser JP, Robinson OJ, Cools R, Chase HW, Ouden Hd, Apergis-Schoute A, Campbell-Meiklejohn D, Seymour B, Sahakian BJ, Rogers RD, Robbins TW (2012). Converging evidence for central 5-HT effects in acute tryptophan depletion. Mol Psychiatry 17(2):121-3

  • Robinson OJ, Cools R, Sahakian BJ (2012). Tryptophan depletion disinhibits punishment but not reward prediction: implications for resilience. Psychopharm 219(2):599-605

  • Cools R, Nakamura K, Daw ND (2011): Serotonin and Dopamine: Unifying Affective, Activational, and Decision Functions. Neuropsychopharmacology Reviews 36(1):98-113

  • Huys QJ, Cools R, Gölzer M, Friedel E, Heinz A, Dolan RJ, Dayan P (2011). Disentangling the roles of approach, activation and valence in instrumental and pavlovian responding. PLoS Comput Biol 7(4):e1002028

  • Robinson OJ, Cools R, Crockett MJ, Sahakian BJ (2010). Mood state moderates the role of serotonin in cognitive biases. J Psychopharm 24(4):573-83

  • Cools R, Robinson OJ, Sahakian BJ (2008). Acute tryptophan depletion in healthy volunteers enhances punishment prediction but does not affect reward prediction. Neuropsychopharmacology 33(9):2291-9

  • Cools R, Roberts AC, Robbins TW (2008). Serotoninergic regulation of emotional and behavioural control processes. Trends Cogn Sci 12(1):31-40

  • Cools R, Calder AJ, Lawrence AD, Clark L, Bullmore E, Robbins TW (2005). Individual differences in threat sensitivity predict serotonergic modulation of amygdala response to fearful faces. Psychopharmacology 180: 670-679

  • Cools R, Blackwell A, Clark L, Menzies L, Cox S, Robbins TW (2005). Tryptophan depletion disrupts the motivational guidance of goal-directed behavior as a function of trait impulsivity. Neuropsychopharmacology 30 (7): 1362-1373

  • Clark L, Roiser JP, Cools R, Rubinsztein DC, Sahakian BJ, Robbins TW (2005). Stop signal response inhibition is not modulated by tryptophan depletion or the serotonin transporter polymorphism in healthy volunteers: implications for the 5-HT theory of impulsivity. Psychopharm 182(4):570-8

  • Evers EA, Cools R, Clark L, van der Veen FM, Jolles J, Sahakian BJ, Robbins TW (2005). Serotonergic modulation of prefrontal cortex during negative feedback in probabilistic reversal learning. Neuropsychopharm 30(6):1138-47

    Curiosity

    A fundamental cognitive motivation is the drive to seek information: curiosity. What makes us curious? To what degree is information seeking behavior independent from our basic drive to maximize reward and minimize punishment? Together with Floris de Lange, we study non-instrumental curiosity, a form of curiosity that, when relieved, is not associated with primary reward. We use both self-report and willingness-to-wait measures to assess participants’ curiosity. So far we have shown that curiosity is a function of both the uncertainty and the expected value of an outcome.

    Relevant recent papers:

    Van Lieshout L, de Lange F, Cools R (in press). Motives underlying human curiosity. Nature Hum Behav

    van Lieshout LLF, Vandenbroucke ARE, Müller NCJ, Cools R, de Lange FP (2018). Induction and relief of curiosity elicit parietal and frontal activity. J Neurosci: 38(10) 2579-2588

    Inference

  • The efficiency and flexibility with which we infer (or generate) meaning during language comprehension (or production) is remarkable. How does our brain do it? In a new line of research, embedded within the Language in Interaction consortium, we will treat linguistic inference as an advanced solution to the multi-step, sequential choice problems that we have long faced in other cognitive domains (e.g. chess, foraging and spatial navigation). Specifically, we anticipate to make unique progress in unraveling the mechanisms of fast, flexible linguistic inference by leveraging recent major advances in our understanding of the representations and computations necessary for sequential model-based action planning. This approach will also lead us to revise current dual-system dogma’s in non-linguistic domains, that have commonly over-focused on the contrast between a cognitive (flexible, but slow) and a habitual (fast, but inflexible) system: The current quest will encourage the integration of so-called ‘cognitive habits’ and their associated cognitive map-related neural mechanisms into theoretical models of both linguistic and nonlinguistic inference.

  • Computational Psychiatry and Neurology

  • Knowledge of the cognitive functions of the major neurotransmitters significantly advances the field of computational psychiatry and neurology, which aim to bridge the gap between neuroscience, neurology and psychiatry by elucidating the cognitive computations underlying (mal)adaptive behaviors. Indeed, many of the major neuropsychiatric and neurological disorders are cognitive in nature. Definition of neuropsychiatric abnormality in terms of its cognitive mechanism is increasingly recognized to be important for diagnosis, prognosis and optimizing treatment development. We contribute to this, either within the group, or in collaborative efforts, by studying motivational and cognitive control in Parkinson’s disease, gambling addiction, eating disorder, ADHD, depression, anxiety, psychopathy, gambling addiction and schizophrenia.

  • Recent relevant papers:

  • Timmer MHM, Sescousse G, Esselink RAJ, Piray P, Cools R (2018). Mechanisms underlying dopamine-induced risky choice in Parkinson’s disease with and without depression (history). Computational Psychiatry 2, 11-27

  • van Holst R, Sescousse R, Janssen LK, Janssen M, Berry AS, Jagust WJ, Cools R (2018). Increased striatal dopamine synthesis capacity in gambling addiction. Biological Psychiatry 83: 1036-1043

  • Read more >

  • Parkinson’s disease

  • In my early work, I put forward the ‘dopamine overdose hypothesis’ to account for the contrasting effects of dopaminergic medication on distinct cognitive functions in Parkinson’s disease. This hypothesis states that dopaminergic medication doses that are necessary to remediate the motor and cognitive deficits that are associated with severely depleted dopamine levels in the dorsal frontostriatal circuitry actually impair other cognitive functions by detrimentally ‘overdosing’ dopamine levels in relatively intact brain regions, such as the ventral striatum and prefrontal cortex (Cools et al., 2001; 2003; 2007; Cools, 2006). In recent work, we have demonstrated that such dopamine-induced cognitive and decision anomalies depend on the presence of a history of depression (Timmer et al., 2018).

    In ongoing longitudinal cohort work (e.g. the Personalized Parkinson’s disease Project, in collaboration with Rick Helmich and Bas Bloem), we focus on identifying computational biomarkers for predicting disease progression and development of neuropsychiatric anomalies, including impulse control disorder and apathy.

  • Relevant papers:

    Timmer MHM, Esselink RAJ, Cools R (2018). Enhanced motivation of cognitive control in Parkinson’s disease. Eur J Neurosci 48(6):2374-2384

  • Timmer MHM, Sescousse G, Van der Schaaf ME, Esselink RAJ, Cools R (2017). Reward learning deficits in Parkinson’s disease depend on depression. Psychol Med 47:2302-2311

    Fallon SJ, Smulders K, Esselink R, van de Warrenburg BP, Bloem BR, Cools R (2015). Differential optimal dopamine levels for set-shifting and working memory in Parkinson’s disease. Neuropsychologia 77:42-51.

    Robbins TW, Cools R (2014). Cognitive Deficits in Parkinson’s Disease: A Cognitive Neuroscience Perspective. Movement Dis 29:597:607

  • Smittenaar P, Chase HW, Aarts E, Nusselein B, Bloem BR, Cools R (2012). Decomposing effects of dopaminergic medication in Parkinson’s disease on probabilistic action selection: learning or performance? Eur J Neurosci 35(7):1144-51

  • De Wit S, Barker RA, Dickinson A, Cools R (2011). Habitual versus goal-directed action control in Parkinson disease. J Cogn Neurosci. 23(5):1218-1229

  • Cools R, Rogers R, Barker RA, Robbins TW (2010). Top-down attentional control in Parkinson’s disease: salient considerations. J Cogn Neurosci 22(5):848-59

  • Cools R, Miyakawa A, Sheridan M, D'Esposito M (2010). Enhanced frontal function in Parkinson's disease. Brain 133:225-33

  • Cools R, Lewis SGJ, Clark L, Barker RA, Robbins TW (2007). L-DOPA disrupts activity in the nucleus accumbens during reversal learning in Parkinson’s disease. Neuropsychopharmacology 32 (1): 180-189

  • Cools R, Altamirano L, D’Esposito M (2006). Reversal learning in Parkinson’s disease depends on medication status and outcome valence. Neuropsychologia 44 (10):1663-1673

  • Cools R, Barker R A, Sahakian B J, Robbins T W (2003). L-Dopa medication remediates cognitive inflexibility, but increases impulsivity in patients with Parkinson’s disease. Neuropsychologia 41:1431-1441

  • Cools R, Barker RA, Sahakian BJ, Robbins TW (2001). Enhanced or impaired cognitive function in Parkinson's disease as a function of dopaminergic medication and task demands. Cereb Cortex 11:1136-1143

  • Gambling Addiction

  • Ojala K, Janssen L, Hashemi M, Timmer M, Geurts D, ter Huurne N, Cools R, and Sescousse G (2018). Dopaminergic drug effects on probability weighting during risky decision-making. eNeuro. Apr 6;5(2).

  • Sescousse G, Janssen L, Hashemi M, Timmer M, Geurts D, ter Huurne N, Clark L, Cools R (2016). Amplified striatal responses to near-miss outcomes in pathological gamblers. Neuropsychopharmacology 41(10):2614-23

    Janssen L, Sescousse G; Hashemi M; Timmer M, ter Huurne N, Geurts D, Cools R (2015). Abnormal modulation of reward versus punishment learning by a dopamine D2-receptor antagonist in pathological gamblers. Psychopharmacology 232(18):3345-53.

    Depression

  • Timmer MHM, Sescousse G, Esselink RAJ, Piray P, Cools R (2018). Mechanisms underlying dopamine-induced risky choice in Parkinson’s disease with and without depression (history). Computational Psychiatry 2, 11-27

  • Timmer MHM, Sescousse G, Van der Schaaf ME, Esselink RAJ, Cools R (2017). Reward learning deficits in Parkinson’s disease depend on depression. Psychol Med 47:2302-2311

  • Huys QJM, Gölzer M, Friedel E, Heinz A, Cools R, Dayan P, Dolan RJ (2016). The specificity of Pavlovian regulation is associated with recovery from depression. Psychological Medicine 46(5):1027-35

  • Robinson OJ, Cools R, Carlisi CO, Sahakian BJ, Drevets WC (2012). Ventral striatum response during reward and punishment reversal learning in unmedicated major depressive disorder. Am J Psychiatry 169(2):152-9 [15.1]

  • ADHD

    von Rhein D, Oldehinkel M, Beckmann CF, Oosterlaan J, Heslenfeld D, Hartman CA, Hoekstra PJ, Franke B, Cools R, Buitelaar JK, Mennes M (2016). Aberrant local striatal functional connectivity in attention-deficit/hyperactivity disorder. J Child Psychol Psychiatry. 57(6):697-705.

    Von Rhein D, Cools R, Zwiers MP, van der Schaaf M, Franke B, Luman M, Oosterlaan J, Heslenfeld DJ, Hoekstra PJ, Hartman CA, Faraone SV, van Rooij D, van Dongen EV, Lojowska M, Mennes M, Buitelaar J. (2015). Increased neural responses to reward in adolescents and young adults with Attention-deficit/Hyperactiviy Disorder and their unaffected siblings. J Am Acad Child Adolesc Psychiatry 54(5):394-402

    Aarts E, van Holstein M, Hoogman M, Onnink M, Kan C, Franke B, Buitelaar J, Cools R (2015). Reward modulation of cognitive function in adult ADHD: a pilot study on the role of striatal dopamine. Behav Pharmacol 26(1-2):227-40

    von Rhein D, Oldehinkel M, Beckmann CF, Oosterlaan J, Heslenfeld D, Hartman CA, Hoekstra PJ, Franke B, Cools R, Buitelaar JK, Mennes M (2016). Aberrant local striatal functional connectivity in attention-deficit/hyperactivity disorder. J Child Psychol Psychiatry. 57(6):697-705.

    Anxiety

  • Ly V, Cools R, Roelofs K (2014). Aversive disinhibition of behavior and striatal signaling in social avoidance. Social Cogn Aff Neurosci 9(10):1530-6

  • Psychopathy

  • Geurts D, von Borries K, Volman I, Bulten B, Cools R*, Verkes R*. (2016). Neural connectivity during reward expectation dissociates psychopathic criminals from noncriminal individuals with high impulsive/antisocial psychopathic traits. Social Cognitive and Affective Neuroscience 11(8):1326-34

  • Ly V, Von Borries AKL, Brazil IA, Bulten BH, Cools R*, Roelofs K* (2016). Reduced transfer of affective value to instrumental behavior in violent offenders. Journal of Abnormal Psychology 125(5):657-63

  • Schizophenia

    Culbreth AJ, Gold JM, Cools R & Barch DM (2016). Impaired Activation in Cognitive Control Regions Predicts Reversal Learning in Schizophrenia. Schizophrenia Bulletin 42(2):484-93

    Ragland JD, Cohen NJ, Cools R, Frank MJ, Hannula DE, Ranganath C (2012). CNTRICS imaging biomarkers final task selection: Long-term memory and reinforcement learning. Schizophr Bull 38(1):62-72

  • Ragland JD, Cools R, Frank M, Pizzagalli DA, Preston A, Ranganath C, Wagner AD (2009). CNTRICS final task selection: long-term memory. Schizophr Bull 35(1):197-212

  • Cools R, Brouwer WH, de Jong R, Slooff C (2000). Flexibility, inhibition, and planning: frontal dysfunctioning in schizophrenia. Brain Cogn 43:108-12

  • Eating disorder

  • Janssen LK, Duif I, van Loon I, Wegman J, de Vries J, Cools R, Aarts E (2017). Loss of lateral prefrontal cortex control in food-directed attention and goal-directed food choice in obesity. Neuroimage 146:148-156

Membership in scientific bodies/juries

  • since 2019: F1000

    since 2018: Elected Member, Royal Netherlands Academy of Arts and Sciences (KNAW)

    since 2018: Elected Member, International Neuropsychological Symposium (INS)

    since 2016: Elected Member, Academia Europaea (Section Behavioural Sciences)

    since 2014: Member, (Government) Advisory Council for Science and Technology Policy, NL

    since 2012: Member, Board of the Rathenau Institute (research, debate on Science and Technology)

    since 2013: Fellow, Association for Psychological Science, UK

    since 2011: Member, Advisory Council Attention and Performance, US

    since 2003: Member, Society for Neuroscience, US

    since 2003: Member, Cognitive Neuroscience Society, US

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