Header Image
People with ADHD affected brain regions

Sitemap

People with ADHD affected brain regions

1. People with ADHD affected brain regions

ADHD is associated with changes in various regions of the brain:

  • PFC
    • DlPFC
    • MPFC
    • OlPFC
  • Basal ganglia1
    • Striatum
      • Nucleus caudates
      • Thalamus
  • Cerebellum1
  • Corpus callosum1
  • Largest reductions in gray matter in:2
    • Frontal-parietal brain regions
    • Corpus callosum
    • Limbic system
      This includes:3
      • Corpus mamillare
        • Memory formation, in the context of the Papez neuron circle
        • Sexual functions
      • Cingulate gyrus
        • Vegetative functions
        • Psychomotor and locomotor drive
      • Parahippocampal gyrus
        • Primarily transmits information from the limbic system to the hippocampus
        • Memory formation
      • Hippocampus
        • Memory formation
        • Vegetative and emotional functions
      • Amygdala
        • Storage of emotionally moving memory content
        • Vegetative and sexual functions
  • Significant hypoactivation in2
    • Several frontal-temporal brain regions
    • Right postcentral gyrus
    • Left insula
    • Corpus callosum

An analysis of car crashes in unaffected individuals found a correlation between percuneus volume and car crashes consistent with changes in ADHD.4

One study found no structural change in the substantia nigra in adults with ADHD.5

2. Volume changes in brain regions with ADHD

In ADHD, the volume of various brain regions is altered, and usually reduced.
It is possible that signaling pathways mediating apoptosis, autophagy and oxidative stress could play a role in the variability of volumetric differences between people with and without ADHD.6

In children with ADHD, studies found that compared to non-affected children

  • Total brain volume reduced
    • (by 4 %)7
  • Caudates reduced (meta-analysis of k = 23 studies with n = 3,200 children and adults aged 4 - 63 years)879
  • Cortex (compared to non-affected persons)10
    • ASS:
      • Greater cortical thickness
      • Larger cortex volume in the upper temporal cortex
      • Gender-specific
      • No interaction Age / diagnosis
    • ADHD:
      • More global increase in cortical thickness
      • Had a smaller cortical volume and a smaller surface area in a large part of the cortex
      • Independent of gender
      • Age / diagnosis interaction
      • Higher ADHD PRS correlated with reduced cortical thickness in the bilateral transverse temporal regions in adults11
    • AuDHS:
      unique pattern from
      * Widespread increase in cortical thickness
      * Certain decrease in surface area
  • PFC12
    • Anterior PFC reduced7
    • Orbital PFC reduced, predominantly on the right13
  • Inferior dorsolateral frontal region13
  • Basal ganglia
    • Right12
    • Striatum
      • Downsized13
      • Enlarged14
    • Pallidum (globus pallidus)
      • Reduced7 13
      • Unchanged (meta-analysis of k = 23 studies with n = 3,200 children and adults aged 4 - 63 years)6
    • Nucleus accumbens
      • Reduced (meta-analysis of k = 23 studies with n = 3,200 children and adults aged 4 - 63 years)8
    • Putamen
      • Reduced (meta-analysis of k = 23 studies with n = 3,200 children and adults aged 4 - 63 years)8
      • Changed9
  • Cerebellum
  • Vermis (Central vermis area)
    • Predominantly reduced on the right713
  • ACC
    • Reduced, mostly underactivated13
  • Corpus callosum12
    • Splenium (beam bulge) reduced1315
  • Thalamus
    • Changed9
    • Hypoactive16
    • Unchanged (meta-analysis of k = 23 studies with n = 3,200 children and adults aged 4 - 63 years)8
  • Amygdala
    • Reduced (meta-analysis of k = 23 studies with n = 3,200 children and adults aged 4 - 63 years)8, bilateral17
    • Smaller bilateral amygdala volume correlated with inattention and hyperactivity/impulsivity17
  • Hippocampus
    • Reduced (meta-analysis of k = 23 studies with n = 3,200 children and adults aged 4 - 63 years)8

Conclusions: Individual differences in amygdala volume contribute meaningfully to the assessment of ADHD risk and severity. From a conceptual perspective, amygdala involvement is consistent with behavioral and functional imaging data on atypical reinforcement sensitivity as a marker of ADHD risk. Methodologically, the results show that the reference standards for brain imaging can be applied to answer clinically informative, targeted and specific questions.

The effects are stronger in boys than in girls, which correlates with the Polygenic Risk Score.9

One study investigated structural and functional changes in the glymphatic system in treatment-free children with ADHD. The cerebral volume of the Virchow-Robin spaces was increased by 32 % (15.514 mL vs. 11.702 mL).18

Interestingly, the reductions in the size of certain brain regions that are usually observed from the age of 60 appear to be less pronounced in ADHD. This is discussed as a neuroprotective factor of ADHD. It remains to be seen whether this is a consequence of ADHD itself or of stimulant treatment.
This is particularly significant in brain regions in which a strong loss of volume correlates with cognitive impairment and Alzheimer’s, such as the hippocampus and amygdala.19

3. White substance

The white matter consists mainly of neurons and their extensions (axons). Myelinated axons look white.

A meta-analysis of 129 studies with n = 6739 people with ADHD and n = 6476 controls found conspicuous changes in the posterior interhemispheric connections responsible for the cognitive and motor functions affected by ADHD:20

  • reduced fractional anisotropy (FA) in the projection, commissural and association pathways, which correlated with symptom severity and cognitive deficits
  • consistently reduced FA in the splenium and corpus callosum, extending to the cingulum
  • lower FA was only found in old age, not in children
    • possibly due to the late development of the callosal fibers

ADHD was found to have significantly increased axial diffusivity in the right cingulum bundle.21

Children with ADHD showed microstructural changes and alterations in long-range white matter connections. Learning problems and hyperactivity/impulsivity correlated negatively with the mean FA value in the right forceps major (the occipital part of the fibers of the corpus callosum), the left IFOF and the left genu capsulae internae.22

Gray matter-white matter-tissue contrast (GWC) was elevated in 8 to 15 year old boys with ADHD, within the23

  • lingual regions bilaterally
  • insular regions bilaterally
  • transverse temporal regions on the left
    • this increase correlated with reduced inattention
  • parahippocampal regions on the right
  • pericalcarine regions right

The cortical thickness was unchanged.23

4. Myelination

One study found no differences in ADHD in terms of myelin content throughout the brain.24
ADHD correlated with

  • a higher mean myelin volume fraction in
    • bilateral inner capsule
    • outer capsule
    • Corona radiata
    • Corpus callosum
    • left tapetum
    • left superior fronto-occipital fascia
    • right cingulum

5. Cerebral blood flow (CBF)

A meta-analysis of k = 20 studies with n = 2232 subjects found that in people with ADHD25

  • in idle state
    • reduced CBF (hypoperfusion)
      • in the right orbitofrontal gyrus
      • in the temporal cortex
      • in the basal ganglia
      • in the putamen
    • increased CBF (hyperperfusion)
      • in the frontal lobe
      • in the left postcentral gyrus
      • in the occipital lobe
  • for cognitive tasks
    • increased CBF (hyperperfusion)
      • in frontal areas
      • in temporal regions
      • in the cingulate cortex
      • in the Precuneus
  • after administration of methylphenidate
    • Increase in CBF
      • in striatal and posterior periventricular regions
      • in the right thalamus
      • in the precentral gyrus

Individual studies found changes in cerebral blood flow in ADHD:

  • significantly reduced (hypoperfusion)
    • in the large quiescent state networks26
      e.g. ventral attention network, somatomotor network, limbic network
    • in subcortical regions26
    • in the orbitofrontal cortex27
    • in the middle temporal gyrus in the right hemisphere27

Increased cerebral blood flow (hyperperfusion) was found in contrast27

  • dorsomedial prefrontal PFC
  • in the somatosensory area on both sides

Treatment with methylphenidate27

  • reduced hyperperfusion in the somatosensory area
  • caused reduced blood flow in the right striatum
  • increased CBF in the superior prefrontal area
  • reduced CBF in the ventral higher visual areas on both sides

Hypoperfusion correlated with inattention or full ADHD symptoms:26

  • in the left putamen/global pallidum
  • in the left amygdala
  • in the left hippocampus

Adults with ADHD were found to have weaker negative functional connectivity between the left amygdala and the bilateral supplementary motor area, the bilateral superior frontal gyrus and the left medial frontal gyrus.26


  1. Biederman, Faraone (2005): Attention-deficit hyperactivity disorder. Lancet. 2005 Jul 16-22;366(9481):237-48. doi: 10.1016/S0140-6736(05)66915-2. Erratum in: Lancet. 2006 Jan 21;367(9506):210. PMID: 16023516. REVIEW

  2. Yu M, Gao X, Niu X, Zhang M, Yang Z, Han S, Cheng J, Zhang Y (2023): Meta-analysis of structural and functional alterations of brain in patients with attention-deficit/hyperactivity disorder. Front Psychiatry. 2023 Jan 6;13:1070142. doi: 10.3389/fpsyt.2022.1070142. PMID: 36683981; PMCID: PMC9853532. METASTUDIE

  3. DocCheck Flexikon: Limbisches System

  4. Putra HA, Park K, Oba H, Yamashita F (2023): Adult attention-deficit/hyperactivity disorder traits in healthy adults associated with brain volumetric data identify precuneus involvement in traffic crashes. Sci Rep. 2023 Dec 18;13(1):22466. doi: 10.1038/s41598-023-49907-3. PMID: 38105321; PMCID: PMC10725881.

  5. Friedrich I, von Kuenheim D, Wozniak D, Meyer P, Mauche N, Huang J, Classen J, Strauss M, Rumpf JJ (2024): No evidence of structural abnormality of the substantia nigra in adult attention-deficit/hyperactivity disorder: a pilot cross-sectional cohort study. Front Psychiatry. 2024 May 30;15:1395836. doi: 10.3389/fpsyt.2024.1395836. PMID: 38873538; PMCID: PMC11169831.

  6. Hess JL, Akutagava-Martins GC, Patak JD, Glatt SJ, Faraone SV (2018): Why is there selective subcortical vulnerability in ADHD? Clues from postmortem brain gene expression data. Mol Psychiatry. 2018 Aug;23(8):1787-1793. doi: 10.1038/mp.2017.242. PMID: 29180674; PMCID: PMC6985986.

  7. Castellanos (2001): Neuroimaging studies of ADHD. In Solanto, Arnsten, Castellanos (Herausgeber): Stimulant drugs and ADHD: Basic and clinical neuroscience (p. 243–258). zitiert nach Solanto (2002): Dopamine dysfunction in AD/HD: integrating clinical and basic neuroscience research. Behav Brain Res. 2002 Mar 10;130(1-2):65-71.

  8. Hoogman M, Bralten J, Hibar DP, Mennes M, Zwiers MP, Schweren LSJ, van Hulzen KJE, Medland SE, Shumskaya E, Jahanshad N, Zeeuw P, Szekely E, Sudre G, Wolfers T, Onnink AMH, Dammers JT, Mostert JC, Vives-Gilabert Y, Kohls G, Oberwelland E, Seitz J, Schulte-Rüther M, Ambrosino S, Doyle AE, Høvik MF, Dramsdahl M, Tamm L, van Erp TGM, Dale A, Schork A, Conzelmann A, Zierhut K, Baur R, McCarthy H, Yoncheva YN, Cubillo A, Chantiluke K, Mehta MA, Paloyelis Y, Hohmann S, Baumeister S, Bramati I, Mattos P, Tovar-Moll F, Douglas P, Banaschewski T, Brandeis D, Kuntsi J, Asherson P, Rubia K, Kelly C, Martino AD, Milham MP, Castellanos FX, Frodl T, Zentis M, Lesch KP, Reif A, Pauli P, Jernigan TL, Haavik J, Plessen KJ, Lundervold AJ, Hugdahl K, Seidman LJ, Biederman J, Rommelse N, Heslenfeld DJ, Hartman CA, Hoekstra PJ, Oosterlaan J, Polier GV, Konrad K, Vilarroya O, Ramos-Quiroga JA, Soliva JC, Durston S, Buitelaar JK, Faraone SV, Shaw P, Thompson PM, Franke B (2017): Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults: a cross-sectional mega-analysis. Lancet Psychiatry. 2017 Apr;4(4):310-319. doi: 10.1016/S2215-0366(17)30049-4. PMID: 28219628; PMCID: PMC5933934. METASTUDY

  9. Mooney, Bhatt, Hermosillo, Ryabinin, Nikolas, Faraone, Fair, Wilmot, Nigg (2020): Smaller total brain volume but not subcortical structure volume related to common genetic risk for ADHD. Psychol Med. 2020 Jan 24;1-10. doi: 10.1017/S0033291719004148. PMID: 31973781.

  10. Bedford SA, Lai MC, Lombardo MV, Chakrabarti B, Ruigrok A, Suckling J, Anagnostou E, Lerch JP, Taylor M, Nicolson R, Stelios G, Crosbie J, Schachar R, Kelley E, Jones J, Arnold PD, Courchesne E, Pierce K, Eyler LT, Campbell K, Barnes CC, Seidlitz J, Alexander-Bloch AF, Bullmore ET, Baron-Cohen S, Bethlehem RAI; MRC AIMS Consortium; Lifespan Brain Chart Consortium (2024): Brain-Charting Autism and Attention-Deficit/Hyperactivity Disorder Reveals Distinct and Overlapping Neurobiology. Biol Psychiatry. 2024 Aug 14:S0006-3223(24)01513-0. doi: 10.1016/j.biopsych.2024.07.024. PMID: 39128574.

  11. Kuramitsu A, Ohi K, Shioiri T (2024): Associations of polygenic risk scores differentiating attention-deficit hyperactivity disorder from autism spectrum disorder with cognitive and cortical alterations in Schizophrenia patients. Eur Child Adolesc Psychiatry. 2024 Aug 7. doi: 10.1007/s00787-024-02549-w. PMID: 39110189.

  12. Regan SL, Williams MT, Vorhees CV (2022): Review of rodent models of attention deficit hyperactivity disorder. Neurosci Biobehav Rev. 2022 Jan;132:621-637. doi: 10.1016/j.neubiorev.2021.11.041. PMID: 34848247; PMCID: PMC8816876.)

  13. Barkley (2014): The Importance of Emotion in ADHD; https://drive.google.com/file/d/0B885LHMHOu5BWmR1YlNoOElCLTg/view?resourcekey=0-lBjUELS_pba99fW5nP5vng unter Verweis auf Cortese, Kelly, Chabernaud, Proal, Di Martino, Milham, Castellanos (2012): Toward systems neuroscience of ADHD: a meta-analysis of 55 fMRI studies. Am J Psychiatry. 2012 Oct;169(10):1038-55. doi: 10.1176/appi.ajp.2012.11101521. PMID: 22983386; PMCID: PMC3879048.

  14. Chang JC, Lin HY, Gau SS (2023): Distinct developmental changes in regional gray matter volume and covariance in individuals with attention-deficit hyperactivity disorder: A longitudinal voxel-based morphometry study. Asian J Psychiatr. 2023 Dec 12;91:103860. doi: 10.1016/j.ajp.2023.103860. PMID: 38103476.

  15. Valera EM, Faraone SV, Murray KE, Seidman LJ (2007): Meta-analysis of structural imaging findings in attention-deficit/hyperactivity disorder. Biol Psychiatry. 2007 Jun 15;61(12):1361-9. doi: 10.1016/j.biopsych.2006.06.011. PMID: 16950217. METASTUDY

  16. Källstrand J, Niklasson K, Lindvall M, Claesdotter-Knutsson E (2022): Reduced thalamic activity in ADHD under ABR forward masking conditions. Appl Neuropsychol Child. 2022 Dec 16:1-7. doi: 10.1080/21622965.2022.2155520. PMID: 36524942.

  17. Nárai Á, Hermann P, Rádosi A, Vakli P, Weiss B, Réthelyi JM, Bunford N, Vidnyánszky Z (2024): Amygdala Volume is Associated with ADHD Risk and Severity Beyond Comorbidities in Adolescents: Clinical Testing of Brain Chart Reference Standards. Res Child Adolesc Psychopathol. 2024 Mar 14. doi: 10.1007/s10802-024-01190-0. PMID: 38483760.

  18. Chen Y, Wang M, Su S, Dai Y, Zou M, Lin L, Qian L, Li X, Zhang H, Liu M, Chu J, Yang J, Yang Z (2023): Assessment of the glymphatic function in children with attention-deficit/hyperactivity disorder. Eur Radiol. 2023 Sep 6. doi: 10.1007/s00330-023-10220-2. PMID: 37673963.

  19. Dutta CN, Christov-Moore L, Ombao H, Douglas PK (2022): Neuroprotection in late life attention-deficit/hyperactivity disorder: A review of pharmacotherapy and phenotype across the lifespan. Front Hum Neurosci. 2022 Sep 26;16:938501. doi: 10.3389/fnhum.2022.938501. PMID: 36226261; PMCID: PMC9548548.

  20. Parlatini V, Itahashi T, Lee Y, Liu S, Nguyen TT, Aoki YY, Forkel SJ, Catani M, Rubia K, Zhou JH, Murphy DG, Cortese S (2023): White matter alterations in Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review of 129 diffusion imaging studies with meta-analysis. Mol Psychiatry. 2023 Jul 21. doi: 10.1038/s41380-023-02173-1. PMID: 37479785.

  21. Hu R, Tan F, Chen W, Wu Y, Jiang Y, Du W, Zuo Y, Gao B, Song Q, Miao Y (2023): Microstructure abnormalities of the diffusion quantities in children with attention-deficit/hyperactivity disorder: an AFQ and TBSS study. Front Psychiatry. 2023 Aug 22;14:1237113. doi: 10.3389/fpsyt.2023.1237113. PMID: 37674550; PMCID: PMC10477457.

  22. Zhou R, Dong P, Chen S, Qian A, Tao J, Zheng X, Cheng J, Yang C, Huang X, Wang M (2022): The long-range white matter microstructural alterations in drug-naive children with ADHD: A tract-based spatial statistics study. Psychiatry Res Neuroimaging. 2022 Oct 7;327:111548. doi: 10.1016/j.pscychresns.2022.111548. PMID: 36279811. n = 98

  23. Wang C, Shen Y, Cheng M, Zhu Z, Lv Y, Zhang X, Feng Z, Yang Z, Zhao X (2023): Cortical gray-white matter contrast abnormalities in male children with attention deficit hyperactivity disorder. Front Hum Neurosci. 2023 Dec 21;17:1303230. doi: 10.3389/fnhum.2023.1303230. PMID: 38188507; PMCID: PMC10768013.

  24. Lin L, Chen Y, Dai Y, Yan Z, Zou M, Zhou Q, Qian L, Cui W, Liu M, Zhang H, Yang Z, Su S (2023): Quantification of myelination in children with attention-deficit/hyperactivity disorder: a comparative assessment with synthetic MRI and DTI. Eur Child Adolesc Psychiatry. 2023 Sep 15. doi: 10.1007/s00787-023-02297-3. PMID: 37712949.

  25. Berthier J, Endomba FT, Lecendreux M, Mauries S, Geoffroy PA (2024): Cerebral blood flow in attention deficit hyperactivity disorder: A systematic review. Neuroscience. 2024 Dec 2:S0306-4522(24)00693-6. doi: 10.1016/j.neuroscience.2024.11.075. PMID: 39631658. REVIEW

  26. Tan YW, Liu L, Wang YF, Li HM, Pan MR, Zhao MJ, Huang F, Wang YF, He Y, Liao XH, Qian QJ (2020): Alterations of cerebral perfusion and functional brain connectivity in medication-naïve male adults with attention-deficit/hyperactivity disorder. CNS Neurosci Ther. 2020 Feb;26(2):197-206. doi: 10.1111/cns.13185. PMID: 31231983; PMCID: PMC6978256.

  27. Lee JS, Kim BN, Kang E, Lee DS, Kim YK, Chung JK, Lee MC, Cho SC (2005): Regional cerebral blood flow in children with attention deficit hyperactivity disorder: comparison before and after methylphenidate treatment. Hum Brain Mapp. 2005 Mar;24(3):157-64. doi: 10.1002/hbm.20067. PMID: 15486990; PMCID: PMC6871721.

Diese Seite wurde am 07.02.2025 zuletzt aktualisiert.