Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-22T20:45:30.411Z Has data issue: false hasContentIssue false

The devil is in the detail: exploring the intrinsic neural mechanisms that link attention-deficit/hyperactivity disorder symptomatology to ongoing cognition

Published online by Cambridge University Press:  05 December 2018

Deniz Vatansever*
Affiliation:
Department of Psychology, University of York, Heslington, York, UK York Neuroimaging Centre, University of York, Heslington, York, UK Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
Natali S. Bozhilova
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, Psychology and Neuroscience, Institute of Psychiatry, King's College London, London, UK
Philip Asherson
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, Psychology and Neuroscience, Institute of Psychiatry, King's College London, London, UK
Jonathan Smallwood
Affiliation:
Department of Psychology, University of York, Heslington, York, UK York Neuroimaging Centre, University of York, Heslington, York, UK
*
Author for correspondence: Deniz Vatansever, E-mail: [email protected]

Abstract

Background

Attention-deficit/hyperactivity disorder (ADHD) is a developmental condition that profoundly affects quality of life. Although mounting evidence now suggests uncontrolled mind-wandering as a core aspect of the attentional problems associated with ADHD, the neural mechanisms underpinning this deficit remains unclear. To that extent, competing views argue for (i) excessive generation of task-unrelated mental content, or (ii) deficiency in the control of task-relevant cognition.

Methods

In a cross-sectional investigation of a large neurotypical cohort (n = 184), we examined alterations in the intrinsic brain functional connectivity architecture of the default mode (DMN) and frontoparietal (FPN) networks during resting state functional magnetic resonance imaging in relation to ADHD symptomatology, which could potentially underlie changes in ongoing thought within variable environmental contexts.

Results

The results illustrated that ADHD symptoms were linked to lower levels of detail in ongoing thought while the participants made more difficult, memory based decisions. Moreover, greater ADHD scores were associated with lower levels of connectivity between the DMN and right sensorimotor cortex, and between the FPN and right ventral visual cortex. Finally, a combination of high levels of ADHD symptomology with reduced FPN connectivity to the visual cortex was associated with reduced levels of detail in thought.

Conclusions

The results of our study suggest that the frequent mind-wandering observed in ADHD may be an indirect consequence of the deficient control of ongoing cognition in response to increasing environmental demands, and that this may partly arise from dysfunctions in the intrinsic organisation of the FPN at rest.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Andrews-Hanna, JR, Smallwood, J and Spreng, RN (2014) The default network and self-generated thought: component processes, dynamic control, and clinical relevance. Annals of the New York Academy of Sciences 1316, 2952.Google Scholar
Ashburner, J and Friston, KJ (2005) Unified segmentation. Neuroimage 26, 839851.Google Scholar
Baird, B, Smallwood, J, Mrazek, MD, Kam, JW, Franklin, MS and Schooler, JW (2012) Inspired by distraction: mind wandering facilitates creative incubation. Psychological Science 23, 11171122.Google Scholar
Baird, B, Smallwood, J, Lutz, A and Schooler, JW (2014) The decoupled mind: mind-wandering disrupts cortical phase-locking to perceptual events. Journal of Cognitive Neuroscience 26, 25962607.Google Scholar
Banaschewski, T, Jennen-Steinmetz, C, Brandeis, D, Buitelaar, JK, Kuntsi, J, Poustka, L, Sergeant, JA, Sonuga-Barke, EJ, Frazier-Wood, AC and Albrecht, B (2012) Neuropsychological correlates of emotional lability in children with ADHD. Journal of Child Psychology and Psychiatry and Allied Disciplines 53, 11391148.Google Scholar
Barkley, RA (1997) Behavioral inhibition, sustained attention, and executive functions: constructing a unifying theory of ADHD. Psychological Bulletin 121, 65.Google Scholar
Barkley, RA and Fischer, M (2010) The unique contribution of emotional impulsiveness to impairment in major life activities in hyperactive children as adults. Journal of the American Academy of Child and Adolescent Psychiatry 49, 503513.Google Scholar
Behzadi, Y, Restom, K, Liau, J and Liu, TT (2007) A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage 37, 90101.Google Scholar
Bernhardt, BC, Smallwood, J, Tusche, A, Ruby, FJ, Engen, HG, Steinbeis, N and Singer, T (2014) Medial prefrontal and anterior cingulate cortical thickness predicts shared individual differences in self-generated thought and temporal discounting. Neuroimage 90, 290297.Google Scholar
Castellanos, FX, Margulies, DS, Kelly, C, Uddin, LQ, Ghaffari, M, Kirsch, A, Shaw, D, Shehzad, Z, Di Martino, A, Biswal, B, Sonuga-Barke, EJ, Rotrosen, J, Adler, LA and Milham, MP (2008) Cingulate-precuneus interactions: a new locus of dysfunction in adult attention-deficit/hyperactivity disorder. Biological Psychiatry 63, 332337.Google Scholar
Christoff, K, Irving, ZC, Fox, KC, Spreng, RN and Andrews-Hanna, JR (2016) Mind-wandering as spontaneous thought: a dynamic framework. Nature Reviews: Neuroscience 17, 718731.Google Scholar
Ciric, R, Wolf, DH, Power, JD, Roalf, DR, Baum, GL, Ruparel, K, Shinohara, RT, Elliott, MA, Eickhoff, SB, Davatzikos, C, Gur, RC, Gur, RE, Bassett, DS and Satterthwaite, TD (2017) Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity. Neuroimage 154, 174187.Google Scholar
Cole, MW, Reynolds, JR, Power, JD, Repovs, G, Anticevic, A and Braver, TS (2013) Multi-task connectivity reveals flexible hubs for adaptive task control. Nature Neuroscience 16, 13481355.Google Scholar
Cortese, S, Kelly, C, Chabernaud, C, Proal, E, Di Martino, A, Milham, MP and Castellanos, FX (2012) Toward systems neuroscience of ADHD: a meta-analysis of 55 fMRI studies. American Journal of Psychiatry 169, 10381055.Google Scholar
Duncan, J (2010) The multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour. Trends in Cognitive Sciences 14, 172179.Google Scholar
Eichele, T, Debener, S, Calhoun, VD, Specht, K, Engel, AK, Hugdahl, K, von Cramon, DY and Ullsperger, M (2008) Prediction of human errors by maladaptive changes in event-related brain networks. Proceedings of the National Academy of Sciences of the United States of America 105, 61736178.Google Scholar
Faraone, SV (2007) ADHD in adults – a familiar disease with unfamiliar challenges. CNS Spectrums 12, 1417.Google Scholar
Fayyad, J, De Graaf, R, Kessler, R, Alonso, J, Angermeyer, M, Demyttenaere, K, De Girolamo, G, Haro, JM, Karam, EG and Lara, C (2007) Cross-national prevalence and correlates of adult attention–deficit hyperactivity disorder. The British Journal of Psychiatry 190, 402409.Google Scholar
Fox, MD, Snyder, AZ, Vincent, JL, Corbetta, M, Van Essen, DC and Raichle, ME (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America 102, 96739678.Google Scholar
Fox, KCR, Foster, BL, Kucyi, A, Daitch, AL and Parvizi, J (2018) Intracranial electrophysiology of the human default network. Trends in Cognitive Sciences 22, 307324.Google Scholar
Franklin, MS, Mrazek, MD, Anderson, CL, Johnston, C, Smallwood, J, Kingstone, A and Schooler, JW (2014) Tracking distraction: the relationship between mind-wandering, meta-awareness, and ADHD symptomatology. Journal of Attention Disorders 21, 475486.Google Scholar
Friston, KJ, Williams, S, Howard, R, Frackowiak, RS and Turner, R (1996) Movement-related effects in fMRI time-series. Magnetic Resonance in Medicine 35, 346355.Google Scholar
Germano, E, Gagliano, A and Curatolo, P (2010) Comorbidity of ADHD and dyslexia. Developmental Neuropsychology 35, 475493.Google Scholar
Ghanizadeh, A (2011) Sensory processing problems in children with ADHD, a systematic review. Psychiatry Investigation 8, 8994.Google Scholar
Gray, S, Woltering, S, Mawjee, K and Tannock, R (2014) The Adult ADHD Self-Report Scale (ASRS): utility in college students with attention-deficit/hyperactivity disorder. PeerJ 2, e324.Google Scholar
Kam, JW, Dao, E, Farley, J, Fitzpatrick, K, Smallwood, J, Schooler, JW and Handy, TC (2011) Slow fluctuations in attentional control of sensory cortex. Journal of Cognitive Neuroscience 23, 460470.Google Scholar
Kane, MJ, Brown, LH, McVay, JC, Silvia, PJ, Myin-Germeys, I and Kwapil, TR (2007) For whom the mind wanders, and when: an experience-sampling study of working memory and executive control in daily life. Psychological Science 18, 614621.Google Scholar
Kessler, RC, Adler, LA, Barkley, R, Biederman, J, Conners, CK, Faraone, SV, Greenhill, LL, Jaeger, S, Secnik, K, Spencer, T, Ustun, TB and Zaslavsky, AM (2005) Patterns and predictors of attention-deficit/hyperactivity disorder persistence into adulthood: results from the national comorbidity survey replication. Biological Psychiatry 57, 14421451.Google Scholar
Kessler, RC, Adler, LA, Gruber, MJ, Sarawate, CA, Spencer, T and Van Brunt, DL (2007) Validity of the World Health Organization Adult ADHD Self-Report Scale (ASRS) Screener in a representative sample of health plan members. International Journal of Methods in Psychiatric Research 16, 5265.Google Scholar
Kieling, C, Kieling, RR, Rohde, LA, Frick, PJ, Moffitt, T, Nigg, JT, Tannock, R and Castellanos, FX (2010) The age at onset of attention deficit hyperactivity disorder. American Journal of Psychiatry 167, 1416.Google Scholar
Kofler, MJ, Rapport, MD, Sarver, DE, Raiker, JS, Orban, SA, Friedman, LM and Kolomeyer, EG (2013) Reaction time variability in ADHD: a meta-analytic review of 319 studies. Clinical Psychology Review 33, 795811.Google Scholar
Konishi, M, McLaren, DG, Engen, H and Smallwood, J (2015) Shaped by the past: the default mode network supports cognition that is independent of immediate perceptual input. PLoS ONE 10, e0132209.Google Scholar
Konishi, M, Brown, K, Battaglini, L and Smallwood, J (2017) When attention wanders: pupillometric signatures of fluctuations in external attention. Cognition 168, 1626.Google Scholar
Liddle, EB, Hollis, C, Batty, MJ, Groom, MJ, Totman, JJ, Liotti, M, Scerif, G and Liddle, PF (2011) Task-related default mode network modulation and inhibitory control in ADHD: effects of motivation and methylphenidate. Journal of Child Psychology and Psychiatry and Allied Disciplines 52, 761771.Google Scholar
Mazoyer, B, Zago, L, Mellet, E, Bricogne, S, Etard, O, Houdé, O, Crivello, F, Joliot, M, Petit, L and Tzourio-Mazoyer, N (2001) Cortical networks for working memory and executive functions sustain the conscious resting state in man. Brain Research Bulletin 54, 287298.Google Scholar
McLean, A, Dowson, J, Toone, B, Young, S, Bazanis, E, Robbins, TW and Sahakian, BJ (2004) Characteristic neurocognitive profile associated with adult attention-deficit/hyperactivity disorder. Psychological Medicine 34, 681692.Google Scholar
McVay, JC and Kane, MJ (2009) Conducting the train of thought: working memory capacity, goal neglect, and mind wandering in an executive-control task. Journal of Experimental Psychology: Learning, Memory, and Cognition 35, 196204.Google Scholar
Medea, B, Karapanagiotidis, T, Konishi, M, Ottaviani, C, Margulies, D, Bernasconi, A, Bernasconi, N, Bernhardt, BC, Jefferies, E and Smallwood, J (2016) How do we decide what to do? Resting-state connectivity patterns and components of self-generated thought linked to the development of more concrete personal goals. Experimental Brain Research 236, 24692481.Google Scholar
Mick, E and Faraone, SV (2008) Genetics of attention deficit hyperactivity disorder. Child and Adolescent Psychiatric Clinics of North America 17, 261284, vii–viii.Google Scholar
Mitchell, JT, Zylowska, L and Kollins, SH (2015) Mindfulness meditation training for attention-deficit/hyperactivity disorder in adulthood: current empirical support, treatment overview, and future directions. Cognitive and Behavioral Practice 22, 172191.Google Scholar
Mowlem, FD, Skirrow, C, Reid, P, Maltezos, S, Nijjar, SK, Merwood, A, Barker, E, Cooper, R, Kuntsi, J and Asherson, P (2016) Validation of the mind excessively wandering scale and the relationship of mind wandering to impairment in adult ADHD. Journal of Attention Disorders doi: 10.1177/1087054716651927.Google Scholar
Mrazek, MD, Smallwood, J, Franklin, MS, Chin, JM, Baird, B and Schooler, JW (2012) The role of mind-wandering in measurements of general aptitude. Journal of Experimental Psychology: General 141, 788798.Google Scholar
Murphy, C, Rueschemeyer, SA, Watson, D, Karapanagiotidis, T, Smallwood, J and Jefferies, E (2017) Fractionating the anterior temporal lobe: MVPA reveals differential responses to input and conceptual modality. Neuroimage 147, 1931.Google Scholar
Owen, AM, McMillan, KM, Laird, AR and Bullmore, E (2005) N-back working memory paradigm: a meta-analysis of normative functional neuroimaging studies. Human Brain Mapping 25, 4659.Google Scholar
Pironti, VA, Lai, MC, Muller, U, Dodds, CM, Suckling, J, Bullmore, ET and Sahakian, BJ (2014) Neuroanatomical abnormalities and cognitive impairments are shared by adults with attention-deficit/hyperactivity disorder and their unaffected first-degree relatives. Biological Psychiatry 76, 639647.Google Scholar
Poerio, GL, Sormaz, M, Wang, HT, Margulies, D, Jefferies, E and Smallwood, J (2017) The role of the default mode network in component processes underlying the wandering mind. Social Cognitive and Affective Neuroscience 12, 10471062.Google Scholar
Power, JD, Mitra, A, Laumann, TO, Snyder, AZ, Schlaggar, BL and Petersen, SE (2014) Methods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage 84, 320341.Google Scholar
Radloff, LS (1977) The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement 1, 385401.Google Scholar
Regev, M, Simony, E, Lee, K, Tan, KM, Chen, J and Hasson, U (2018) Propagation of information along the cortical hierarchy as a function of attention while reading and listening to stories. doi: 10.1093/cercor/bhy282.Google Scholar
Ruby, FJ, Smallwood, J, Engen, H and Singer, T (2013 a) How self-generated thought shapes mood--the relation between mind-wandering and mood depends on the socio-temporal content of thoughts. PLoS ONE 8, e77554.Google Scholar
Ruby, FJ, Smallwood, J, Sackur, J and Singer, T (2013 b) Is self-generated thought a means of social problem solving? Frontiers in Psychology 4, 972.Google Scholar
Saad, ZS, Gotts, SJ, Murphy, K, Chen, G, Jo, HJ, Martin, A and Cox, RW (2012) Trouble at rest: how correlation patterns and group differences become distorted after global signal regression. Brain Connectivity 2, 2532.Google Scholar
Seli, P (2016) The attention-lapse and motor decoupling accounts of SART performance are not mutually exclusive. Consciousness and Cognition 41, 189198.Google Scholar
Seli, P, Smallwood, J, Cheyne, JA and Smilek, D (2015) On the relation of mind wandering and ADHD symptomatology. Psychonomic Bulletin & Review 22, 629636.Google Scholar
Seli, P, Carriere, JS, Wammes, JD, Risko, EF, Schacter, DL and Smilek, D (2018) On the clock: evidence for the rapid and strategic modulation of mind wandering. Psychological Science 29, 12471256.Google Scholar
Shulman, GL, Fiez, JA, Corbetta, M, Buckner, RL, Miezin, FM, Raichle, ME and Petersen, SE (1997) Common blood flow changes across visual tasks: II. Decreases in cerebral Cortex. Journal of Cognitive Neuroscience 9, 648663.Google Scholar
Skirrow, C, McLoughlin, G, Kuntsi, J and Asherson, P (2009) Behavioral, neurocognitive and treatment overlap between attention-deficit/hyperactivity disorder and mood instability. Expert Review of Neurotherapeutics 9, 489503.Google Scholar
Smallwood, J (2013) Distinguishing how from why the mind wanders: a process-occurrence framework for self-generated mental activity. Psychological Bulletin 139, 519535.Google Scholar
Smallwood, J and Andrews-Hanna, J (2013) Not all minds that wander are lost: the importance of a balanced perspective on the mind-wandering state. Frontiers in Psychology 4, 441.Google Scholar
Smallwood, J and Schooler, JW (2015) The science of mind wandering: empirically navigating the stream of consciousness. Annual Review of Psychology 66, 487518.Google Scholar
Smallwood, J, Beach, E, Schooler, JW and Handy, TC (2008) Going AWOL in the brain: mind wandering reduces cortical analysis of external events. Journal of Cognitive Neuroscience 20, 458469.Google Scholar
Smallwood, J, Nind, L and O'Connor, RC (2009) When is your head at? An exploration of the factors associated with the temporal focus of the wandering mind. Consciousness and Cognition 18, 118125.Google Scholar
Smallwood, J, Schooler, JW, Turk, DJ, Cunningham, SJ, Burns, P and Macrae, CN (2011) Self-reflection and the temporal focus of the wandering mind. Consciousness and Cognition 20, 11201126.Google Scholar
Smallwood, J, Gorgolewski, KJ, Golchert, J, Ruby, FJ, Engen, H, Baird, B, Vinski, MT, Schooler, JW and Margulies, DS (2013 a) The default modes of reading: modulation of posterior cingulate and medial prefrontal cortex connectivity associated with comprehension and task focus while reading. Frontiers in Human Neuroscience 7, 734.Google Scholar
Smallwood, J, Ruby, FJ and Singer, T (2013 b) Letting go of the present: mind-wandering is associated with reduced delay discounting. Consciousness and Cognition 22, 17.Google Scholar
Smallwood, J, Karapanagiotidis, T, Ruby, F, Medea, B, de Caso, I, Konishi, M, Wang, HT, Hallam, G, Margulies, DS and Jefferies, E (2016) Representing representation: integration between the temporal lobe and the posterior cingulate influences the content and form of spontaneous thought. PLoS ONE 11, e0152272.Google Scholar
Smythe, I and Everatt, J (2001) A new dyslexia checklist for adults. In The Dyslexia Handbook (Smythe, Ian, ed). Bracknell, UK: British Dyslexia Association.Google Scholar
Sormaz, M, Murphy, C, Wang, HT, Hymers, M, Karapanagiotidis, T, Poerio, G, Margulies, DS, Jefferies, E and Smallwood, J (2018) Default mode network can support the level of detail in experience during active task states. Proceedings of the National Academy of Sciences of the United States of America 115, 93189323.Google Scholar
Teasdale, JD, Proctor, L, Lloyd, CA and Baddeley, AD (1993) Working memory and stimulus-independent thought: effects of memory load and presentation rate. European Journal of Cognitive Psychology 5, 417433.Google Scholar
Turnbull, A, Wang, HT, Schooler, JW, Jefferies, E, Margulies, DS and Smallwood, J (2018) The ebb and flow of attention: between-subject variation in intrinsic connectivity and cognition associated with the dynamics of ongoing experience. Neuroimage 185, 286299.Google Scholar
Turner, DC, Blackwell, AD, Dowson, JH, McLean, A and Sahakian, BJ (2005) Neurocognitive effects of methylphenidate in adult attention-deficit/hyperactivity disorder. Psychopharmacology 178, 286295.Google Scholar
van Dongen, EV, von Rhein, D, O'Dwyer, L, Franke, B, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Oosterlaan, J, Rommelse, N and Buitelaar, J (2015) Distinct effects of ASD and ADHD symptoms on reward anticipation in participants with ADHD, their unaffected siblings and healthy controls: a cross-sectional study. Molecular Autism 6, 48.Google Scholar
Vatansever, D, Menon, DK, Manktelow, AE, Sahakian, BJ and Stamatakis, EA (2015) Default mode dynamics for global functional integration. Journal of Neuroscience 35, 1525415262.Google Scholar
Vatansever, D, Manktelow, AE, Sahakian, BJ, Menon, DK and Stamatakis, EA (2016 a) Angular default mode network connectivity across working memory load. Human Brain Mapping 38, 4152.Google Scholar
Vatansever, D, Manktelow, AE, Sahakian, BJ, Menon, DK and Stamatakis, EA (2016 b) Cognitive flexibility: a default network and basal ganglia connectivity perspective. Brain Connectivity 6, 201207.Google Scholar
Vatansever, D, Menon, DK and Stamatakis, EA (2017) Default mode contributions to automated information processing. Proceedings of the National Academy of Sciences of the United States of America 114, 1282112826.Google Scholar
Vatansever, D, Manktelow, AE, Sahakian, BJ, Menon, DK and Stamatakis, EA (2018) Default mode network engagement beyond self-referential internal mentation. Brain Connectivity 8, 245253.Google Scholar
Vidaurre, D, Quinn, AJ, Baker, AP, Dupret, D, Tejero-Cantero, A and Woolrich, MW (2016) Spectrally resolved fast transient brain states in electrophysiological data. Neuroimage 126, 8195.Google Scholar
Whitfield-Gabrieli, S and Nieto-Castanon, A (2012) Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connectivity 2, 125141.Google Scholar
Yeo, BT, Krienen, FM, Sepulcre, J, Sabuncu, MR, Lashkari, D, Hollinshead, M, Roffman, JL, Smoller, JW, Zollei, L, Polimeni, JR, Fischl, B, Liu, H and Buckner, RL (2011) The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology 106, 11251165.Google Scholar
Supplementary material: File

Vatansever et al. supplementary material

Vatansever et al. supplementary material 1

Download Vatansever et al. supplementary material(File)
File 13 MB