The frontal lobe is located in the anterior part of the cerebral hemispheres:
• Anterior to the parietal lobe.
(The frontal lobe is separated from the parietal lobe by the central sulcus (of Rolando)).
• Superior to the .
(The frontal lobe is separated from the by the lateral fissure of Sylvius).

Magnetic resonance imaging (MRI) for manual volumetric measurement of the brain’s frontal lobe and its subregions is an established method for researching neural correlations of clinical disorders or cognitive functions⁽¹⁾.

However, there is no consensus on MRIs regarding the methods radiologists use to identify appropriate boundaries of a given region of interest (ROI). 

The methods that they use may still bear little relation to each other or the underlying structural, functional, and connective architecture⁽²⁾.

The lack of consensus for imaging methods poses challenges for analyzing and synthesizing exam results.

The brain’s frontal lobes are both cyto-architectonically and functionally diverse. A significant amount of research examines their contributions to various cognitive processes and clinical conditions⁽³⁾.

Laminar organization (arranged in layers) differentiates the frontal lobes’ regions. This organization depends on neuronal density, granule cells, glial content, and afferent and efferent connectivity⁽⁴⁾.

Professionals have reported frontal lobe structural abnormalities in psychiatric, behavioral, and neurological disorders. Other studies note the lack of such abnormalities in normal development and aging^(5-7).

However, different publications used varied methods in defining and measuring the frontal regions. This variability has critical implications for analyzing, reporting, and synthesizing neuroanatomical abnormalities in clinical populations.

Additionally, the variability could explain inconsistent areas amongst findings of a population’s reported neuroanatomical characteristics⁽⁸⁾.

Tools for Brain Measurement

There are two categories for measuring brain structure, namely manual and automated⁽⁹⁾.

Manual ROI delineation affords precise control over boundary placement on a slice-by-slice basis for a participant’s MR image⁽¹⁰⁾.

This method offers a high degree of reliability and allows adherence to individual differences in brain morphology. However, it requires skill in neuroanatomy and involves significant time investment.

Automated methods require less user input, thus reducing personnel time costs. Such methods are potentially more feasible for studying large cohorts⁽¹¹⁾. 

Furthermore, automated methods avoid the potential for bias and reproducibility issues that manual rater drifts introduce.

However, choices throughout the processing chain may introduce other forms of systematic and non-systematic bias. Even automated parcellation methods require user-driven input in the first instance.

In other words, radiologists must base the software for automated segmentation of a target sample on a specific structural schema or atlas.

There is no standardized protocol to identify the ROIs manually. The parcellations derived from automated atlas-based methods nearly match the manually delineated approach on which they are based⁽¹²⁾.

Posterior Frontal Boundary

At its posterior-lateral edge, the frontal lobe is anterior to the central sulcus.

The central sulcus (or the central fissure of Rolando) is a deep brain groove separating the frontal lobe from the parietal tissue.

This deep sulcus runs from the medial wall, over the lateral convexity until its ventrolateral termination at the Sylvian fissure⁽¹³⁾.

Frontal Pole

The frontal pole (FP) is a distinct subregion. Like the posterior frontal lobe (FL) boundary, volumes of some or all FL regions depend on the FP boundary⁽¹⁴⁾.

Ignoring this region may result in excess image noise from distributing the frontal lobes’ anterior portion between multiple regions.

A further complication of ignoring this region then arises. The anterior-most portions of the frontal gyri in the coronal plane become more challenging to differentiate in 2D.

This condition makes continuing subregional parcellation challenging and potentially unreliable.

Anterior Cingulate Cortex (ACC)

The ACC is the rostral (towards the nose) portion of the cingulate gyrus. It runs immediately dorsal to the corpus callosum, wrapping around its most anterior extent (genu) on the frontal lobes’ medial wall⁽¹⁵⁾.

The dorsal region involves goal-based action selection through its strong connections to the lateral frontal and premotor regions.

Meanwhile, the ventral region contributes to emotional processing and links to the ventral and medial frontal areas⁽¹⁶⁾.

These connections make the ventral ACC a particular ROI for research into various affective disorders.

Dorsolateral Frontal Cortex

Radiologists commonly refer to this subsection as the dorsolateral prefrontal cortex (DLPFC). Based on detailed post-mortem brain exams, Brodmann areas 9 and 46 (BA9 and BA46; cerebral cortex regions) display some cortical positioning variation between individuals⁽¹⁷⁾.

Still, BA46 lies predominantly on the middle frontal gyrus (MFG), while BA9 lies mainly on the SFG.

Evidence from functional imaging and lesion studies link this area with working memory⁽¹⁸⁾, attentional control, switching^(19-20), planning⁽²¹⁾, and fluid intelligence^(22-23).

Inferior-Lateral Frontal Cortex

The inferior-frontal gyrus (IFG) extends ventrally from the inferior frontal sulcus. This area contains the pars opercularis and triangularis (BA44 and BA45, or Broca’s area, the motor speech area) and the pars orbitalis (BA47, which plays a central role in the language production system)^(24-25).

Professionals believe that the IFG is a core substrate of the mirror neuron system.

This area may also be related to social reciprocity in autism spectrum disorders. Disturbed action imitation pathophysiology is another potential relation⁽²⁶⁾.

Additionally, some studies have implicated the IFG in thought disorder⁽²⁷⁾, making this an ROI in schizophrenia research^(28-30).

Orbitofrontal Cortex (OFC)

The OFC is on the frontal lobes’ ventral aspect, immediately superior to the frontal bones’ orbital part. It is anterior to the insula cortex and extends dorsomedial to the subgenual cingulate sulcus^(31-32).

Animal models, human imaging, and lesion studies suggest that this region combines the taste and smell processes with representations of emotional valence and expected stimuli reward value⁽³³⁾.

Reference:

• Harnsberger HR, Osborn AG, Ross JS, Moore KR, Salzman KL, Carrasco CR, Halmiton BE, Davidson HC, Wiggins RH. Diagnostic and Surgical Imaging Anatomy: Brain, Head and Neck, Spine. 3rd ed. Salt Lake City, Utah. Amirsys. 2007.
• Bourjat P, Veillon F. Imagerie radiologique tête et cou. Paris, Vigot. 1995.
• Gouazé A, Baumann JA, Dhem A. Sobota. Atlas d’Anatomie humaine. Tome 3. Système nerveux central, système nerveux autonome, organe des sens et peau, vaisseaux et nerfs périphériques. 1er éd. Paris, Maloine. 1977.
• Kahle W, Cabrol C. Anatomie. Tome 3: Système nnerveux et organe des sens. 1er éd. Paris, Flammarion. 1979.

---

1. Cox, S. R., Ferguson, K. J., Royle, N. A., Shenkin, S. D., MacPherson, S. E., MacLullich, A. M., Deary, I. J., & Wardlaw, J. M. (2014). A systematic review of brain frontal lobe parcellation techniques in magnetic resonance imaging. Brain structure & function, 219(1), 1–22. https://doi.org/10.1007/s00429-013-0527-5
2. Cox, S. R., Ferguson, K. J., Royle, N. A., Shenkin, S. D., MacPherson, S. E., MacLullich, A. M., Deary, I. J., & Wardlaw, J. M. (2014). A systematic review of brain frontal lobe parcellation techniques in magnetic resonance imaging. Brain structure & function, 219(1), 1–22. https://doi.org/10.1007/s00429-013-0527-5
3. Cox, S. R., Ferguson, K. J., Royle, N. A., Shenkin, S. D., MacPherson, S. E., MacLullich, A. M., Deary, I. J., & Wardlaw, J. M. (2014). A systematic review of brain frontal lobe parcellation techniques in magnetic resonance imaging. Brain structure & function, 219(1), 1–22. https://doi.org/10.1007/s00429-013-0527-5
4. Zald DH (2007) Orbital versus dorsolateral prefrontal cortex: anatomical insights into content versus process differentiation models of the prefrontal cortex. Ann N Y Acad Sci 1121:395–406
5. Convit A, Wolf OT, de Leon MJ, Patalinjug M, Kandil E, Caraos C, Scherer A, Saint Louis LA, Cancro R (2001) Volumetric analysis of the pre-frontal regions: findings in aging and schizophrenia. Psychiatry Res Neuroimaging 107(2):61–73
6. Salat DH, Kaye JA, Janowsky JS (2001) Selective preservation and degeneration within the prefrontal cortex in aging and Alzheimer disease. Arch Neurol 58(9):1403–1408
7. Yücel M, McKinnon MC, Chahal R, Taylor VH, Macdonald K, Joffe R, MacQuenn GM (2008) Anterior cingulate volumes in nevertreated patients with major depressive disorder. Neuropsychopharmacology 33:3157–3163
8. Zhou S-Y, Suzuki M, Hagino H, Takahashi T, Kawasaki Y, Matsui M, Seto H, Kurachi M (2005) Volumetric analysis of sulci/gyri defined in vivo frontal lobe regions in schizophrenia: precentral gyrus, cingulate gyrus, and prefrontal region. Psychiatry Res Neuroimaging 139:127–139
9. Cox, S. R., Ferguson, K. J., Royle, N. A., Shenkin, S. D., MacPherson, S. E., MacLullich, A. M., Deary, I. J., & Wardlaw, J. M. (2014). A systematic review of brain frontal lobe parcellation techniques in magnetic resonance imaging. Brain structure & function, 219(1), 1–22. https://doi.org/10.1007/s00429-013-0527-5
10. Cox, S. R., Ferguson, K. J., Royle, N. A., Shenkin, S. D., MacPherson, S. E., MacLullich, A. M., Deary, I. J., & Wardlaw, J. M. (2014). A systematic review of brain frontal lobe parcellation techniques in magnetic resonance imaging. Brain structure & function, 219(1), 1–22. https://doi.org/10.1007/s00429-013-0527-5
11. Cox, S. R., Ferguson, K. J., Royle, N. A., Shenkin, S. D., MacPherson, S. E., MacLullich, A. M., Deary, I. J., & Wardlaw, J. M. (2014). A systematic review of brain frontal lobe parcellation techniques in magnetic resonance imaging. Brain structure & function, 219(1), 1–22. https://doi.org/10.1007/s00429-013-0527-5
12. Cox, S. R., Ferguson, K. J., Royle, N. A., Shenkin, S. D., MacPherson, S. E., MacLullich, A. M., Deary, I. J., & Wardlaw, J. M. (2014). A systematic review of brain frontal lobe parcellation techniques in magnetic resonance imaging. Brain structure & function, 219(1), 1–22. https://doi.org/10.1007/s00429-013-0527-5
13. Cox, S. R., Ferguson, K. J., Royle, N. A., Shenkin, S. D., MacPherson, S. E., MacLullich, A. M., Deary, I. J., & Wardlaw, J. M. (2014). A systematic review of brain frontal lobe parcellation techniques in magnetic resonance imaging. Brain structure & function, 219(1), 1–22. https://doi.org/10.1007/s00429-013-0527-5
14. Cox, S. R., Ferguson, K. J., Royle, N. A., Shenkin, S. D., MacPherson, S. E., MacLullich, A. M., Deary, I. J., & Wardlaw, J. M. (2014). A systematic review of brain frontal lobe parcellation techniques in magnetic resonance imaging. Brain structure & function, 219(1), 1–22. https://doi.org/10.1007/s00429-013-0527-5
15. Cox, S. R., Ferguson, K. J., Royle, N. A., Shenkin, S. D., MacPherson, S. E., MacLullich, A. M., Deary, I. J., & Wardlaw, J. M. (2014). A systematic review of brain frontal lobe parcellation techniques in magnetic resonance imaging. Brain structure & function, 219(1), 1–22. https://doi.org/10.1007/s00429-013-0527-5
16. Mansouri FA, Tanaka K, Buckley MJ (2009) Conflict induced behavioural adjustment: a clue to the executive functions of the prefrontal cortex. Nat Rev Neurosci 10:141–152
17. Rajkowska G, Goldman-Rakic PS (1995) Cytoarchitectonic definition of prefrontal areas in the normal human cortex: II. Variability in locations of areas 9 and 46 and relationship to the Talairach Coordinate System. Cereb Cortex 5(4):323–337
18. Petrides M (2000) The role of the mid-dorsolateral prefrontal cortex in working memory. Exp Brain Res 133(1):44–54
19. Cabeza R, Nyberg L (2000) Imaging cognition II: an empirical review of 275 PET and fMRI studies. J Cogn Neurosci 12(1):1–47
20. Shallice T, Stuss DT, Picton TW, Alexander MP, Gillingham S (2008) Mapping task switching in frontal cortex through neuropsychological group studies. Front Neurosci 2(1):79–85
21. Unterrainer JM, Owen AM (2006) Planning and problem solving: from neuropsychology to functional neuroimaging. J Physiol 99(4–6):308–317
22. Deary IJ, Penke L, Johnson W (2010) The neuroscience of human intelligence differences. Nat Rev Neurosci 11(3):201–211
23. Jung RE, Haier RJ (2007) The parieto-frontal integration theory (P-FIT) of intelligence: converging neuroimaging evidence. Behav Brain Sci 30(2):135–154
24. Keller SS, Crow T, Foundas A, Amunts K, Roberts N (2009) Broca’s area: nomenclature, anatomy, typology and asymmetry. Brain Lang 109:29–48
25. Petrides M, Tomiauolo F, Yeterian EH, Pandya DN (2012) The prefrontal cortex: comparative architectonic organization in the human and the macaque monkey brains. Cortex 48(1):46–57
26. Yamasaki S, Yamasue H, Abe O, Suga M, Yamada H, Inoue H, Kuwabara H, Kawakubo Y, Yahata N, Aoki S, Kano Y, Kato N, Kasai K (2010) Reduced gray matter volume of pars opercularis is associated with impaired social communication in highfunctioning autism spectrum disorders. Biol Psychiatry 68(12):1141–1147
27. Nishitani N, Schurman M, Amunts K, Hari R (2005) Broca’s region: from action to language. Physiol 20:60–69
28. Suga M, Yamasue H, Abe O, Yamasaki S, Yamada H, Inoue H, Takei K, Aoki S, Kasai K (2010) Reduced gray matter volume of Brodmann’s area 45 is associated with severe psychotic symptoms in patients with schizophrenia. Eur Arch Psychiatry Clin Neurosci 260:465–473
29. Suzuki M, Zhou S-Y, Takahashi T, Hagino H, Kawasaki Y, Niu L, Matsui M, Seto H, Kurachi M (2005) Differential contributions of prefrontal and temporolimbic pathology to mechanisms of psychosis. Brain 128(9):2109–2122
30. Yamasue H, Iwanami A, Hirayasu Y, Yamada H, Abe O, Kuroki N, Fukuda R, Tsujii K, Aoki S, Ohtomo K, Kato N, Kasai K (2004) Localized volume reduction in prefrontal, temporolimbic, and paralimbic regions in schizophrenia: an MRI parcellation study. Psychiatry Res 131(3):195–207
31. Petrides M, Pandya DN (1994) Comparative architectonic analysis of the human and the macaque frontal cortex. In: Boller F, Grafman J (eds) Handbook of neuropsychology, vol 9th. Elsevier, Amsterdam, pp 17–58
32. Chiavaras MM, LeGoualher G, Evans A, Petrides M (2001) Threedimensional probabilistic atlas of the human orbitofrontal sulci in standardized stereotaxic space. NeuroImage 13(3):479–496
33. Hof PR, Mufson EJ, Morrison JH (1995) Human orbitofrontal cortex: cytoarchitecture and quantitative immunohistochemical parcellation. J Comp Neurol 359(1):48–68