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People with ADHD affected brain regions


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

2. Volume changes in brain regions with ADHD

In ADHD, the volume of various brain regions is altered.

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

  • Total brain volume reduced
    • (by 4 %)5
  • Caudates downsized56
  • PFC7
    • Anterior PFC reduced5
    • Orbital PFC reduced, predominantly on the right8
  • Inferior dorsolateral frontal region8
  • Basal ganglia
    • Right7
    • Striatum reduced in size8
    • Striatum enlarged9
    • Globus pallidus reduced in size5 8
  • Cerebellum
    • Reduced 67
    • Enlarged9
  • Central vermis area, mainly reduced on the right58
  • ACC
    • Reduced, mostly underactivated8
  • Corpus callosum7
    • Splenium (beam bulge) reduced8
  • Putamen changed6
  • Thalamus changes6 or hypoactive10
  • Amygdala
    • Bilaterally reduced11
    • Smaller bilateral amygdala volume correlated with inattention and hyperactivity/impulsivity11

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.6

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).12

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.13

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:14

  • 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

A significantly increased axial diffusivity in the right cingulum bundle was found in ADHD.15

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.16

Gray matter-white matter-tissue contrast (GWC) was elevated in 8 to 15 year old boys with ADHD, within the17

  • 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.17

4. Myelination

One study found no differences in ADHD in terms of myelin content throughout the brain.18
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

  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. 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.

  6. 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.

  7. 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.)

  8. Barkley (2014): The Importance of Emotion in ADHD; 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

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