Can Brain Parts and Functions of the Cerebrum Be Mapped?
Yes, brain parts and functions of the cerebrum can be mapped using various neuroimaging and anatomical techniques. Modern technology allows researchers to identify which regions control specific functions like movement, sensation, language, and cognition. This mapping relies on methods ranging from structural analysis of tissue organization to functional imaging that tracks brain activity in real-time.
The Cerebrum’s Structural Organization
The cerebrum occupies roughly 87% of total brain volume, making it the brain’s largest component. This massive structure divides into two hemispheres connected by the corpus callosum, a bundle of white matter fibers that enables communication between both sides.
Each hemisphere contains an outer layer of gray matter called the cerebral cortex, approximately 2-4 millimeters thick. Below this cortex sits white matter composed of myelinated axons that transmit signals between different brain regions. Deep within the white matter lie subcortical structures including the basal ganglia, which regulate motor control and cognitive functions.
The cortex’s surface features a distinctive folded pattern. Raised ridges called gyri increase surface area, while grooves called sulci create boundaries between regions. Deeper grooves are termed fissures. This folding pattern isn’t arbitrary—it allows roughly 80,000 square millimeters of cortical surface to fit within the skull while maintaining the compact size necessary for human birth.
Four Primary Lobes
The cerebrum divides into four main lobes, each with distinct functional responsibilities:
The frontal lobe occupies the anterior portion of each hemisphere, extending from the forehead to the central sulcus. This lobe handles executive functions including planning, decision-making, and personality expression. It contains the primary motor cortex in the precentral gyrus, which initiates voluntary movements. The inferior frontal gyrus houses Broca’s area in the dominant hemisphere—typically the left—responsible for speech production.
The parietal lobe sits behind the central sulcus and above the lateral fissure. Its primary function involves processing sensory information. The postcentral gyrus contains the primary somatosensory cortex, which receives input about touch, pain, temperature, and body position. The superior and inferior parietal lobules integrate sensory information with spatial awareness and attention.
The temporal lobe occupies the lateral surface below the lateral fissure. This region processes auditory information through the primary auditory cortex in the superior temporal gyrus. The temporal lobe also contains structures crucial for memory, including the hippocampus and amygdala. Wernicke’s area, located in the posterior superior temporal gyrus of the dominant hemisphere, enables language comprehension.
The occipital lobe forms the posterior portion of each hemisphere. This lobe specializes in visual processing, with the primary visual cortex (V1) located in the calcarine sulcus. Surrounding areas (V2-V5) process increasingly complex visual features like object recognition, motion, and color.
Historical Foundation: The Brodmann Map
German neuroanatomist Korbinian Brodmann created one of neuroscience’s most enduring contributions between 1909 and 1910. By examining the cellular architecture of the cerebral cortex under a microscope, he identified 52 distinct areas based on cell shape, size, and arrangement patterns.
Brodmann’s numbering system wasn’t random—he started at the top of the brain with Area 1 and worked systematically through different regions. Some areas have become synonymous with specific functions. Area 4 corresponds to the primary motor cortex, Areas 1-3 comprise the primary somatosensory cortex, and Area 17 represents the primary visual cortex.
Modern neuroimaging has validated many of Brodmann’s original distinctions. A 2016 study by Glasser and van Essen identified approximately 180 distinct cortical areas using multimodal MRI techniques, showing remarkable correspondence with Brodmann’s century-old map. The durability of this classification system reflects how cellular organization correlates with functional specialization.
Different Brodmann areas perform specialized roles. Area 44 and 45, forming Broca’s area, control speech production and language processing. Areas 41 and 42 in the superior temporal gyrus process auditory information. Areas 39 and 40 in the inferior parietal lobule contribute to reading comprehension and language understanding as part of Wernicke’s area.
Modern Brain Mapping Techniques
Advances in technology have transformed how researchers map brain structure and function. Multiple complementary methods now exist, each with distinct advantages and limitations.
Structural Mapping Methods
Magnetic resonance imaging (MRI) provides detailed anatomical images without radiation exposure. High-resolution structural MRI can distinguish between gray and white matter, measure cortical thickness, and identify individual gyri and sulci with millimeter precision. T1-weighted imaging reveals anatomical detail, while T2-weighted sequences highlight different tissue properties.
Diffusion tensor imaging (DTI) tracks water molecule movement along white matter tracts. This technique reconstructs the brain’s wiring diagram by showing how fiber bundles connect different regions. DTI has revealed major pathways like the arcuate fasciculus connecting language areas, though current methods face limitations in resolving crossing fibers and accurately estimating connection strength.
Polarized light imaging and the Klingler dissection technique offer alternative structural approaches. The Klingler method, developed in the 1930s, uses freezing and careful dissection to reveal white matter tracts in three dimensions. These methods remain valuable for surgical planning and anatomical education.
Functional Mapping Methods
Functional MRI (fMRI) has become the dominant tool for studying brain activity since its introduction in the early 1990s. This technique detects blood oxygen level-dependent (BOLD) signals, which reflect increased blood flow to active brain regions. When neurons fire, they consume oxygen, triggering increased blood flow that exceeds metabolic demand. This creates a detectable change in the ratio of oxygenated to deoxygenated hemoglobin.
fMRI offers several advantages over earlier techniques. It’s non-invasive, requires no radiation or contrast agents, and can map the entire brain during task performance. Typical fMRI studies achieve spatial resolution of 2-3 millimeters, with temporal resolution of 1-2 seconds. Recent advances using high-field magnets (7 Tesla and above) push spatial resolution below 1 millimeter for specific brain regions.
The Individual Brain Charting project, published in 2018 and updated through 2025, demonstrates fMRI’s potential. Researchers scanned 12 participants performing dozens of cognitive tasks, creating high-resolution functional maps at 1.5mm resolution. This approach minimizes inter-subject variability by collecting extensive data from the same individuals, enabling precise functional localization.
Magnetoencephalography (MEG) measures magnetic fields generated by neuronal activity. Unlike fMRI, which tracks blood flow changes occurring over seconds, MEG captures electromagnetic signals with millisecond precision. This temporal resolution reveals the timing of neural processes, showing how information flows between brain regions. A 2024 MIT study combined MEG with fMRI to map visual memory processing, showing that memorable images trigger sustained responses in early visual cortex around 300 milliseconds after presentation.
Positron emission tomography (PET) tracks radioactive tracers to measure metabolism, blood flow, or neurotransmitter activity. While less common than fMRI due to radiation exposure, PET provides unique information about neurochemical processes and receptor distribution.
Advanced Mapping Approaches
Recent developments have pushed brain mapping toward higher resolution and more sophisticated analysis. A December 2024 study from the University of Birmingham introduced methods for modeling interactions among multiple brain regions simultaneously, rather than just pairwise connections. Using data from the Human Connectome Project, researchers demonstrated that higher-order connectivity patterns can identify individual subjects with high accuracy and predict behavioral traits more effectively than traditional approaches.
Deep learning has accelerated parcellation—the process of dividing the brain into functional units. Traditional atlas-based methods required hours of computation to warp reference brains to match individual anatomy. Neural networks trained on thousands of brain scans can now perform whole-brain parcellation in minutes while maintaining or exceeding accuracy of conventional approaches. A 2024 study introduced OpenMAP-T1, achieving rapid parcellation of 280 anatomical regions using deep learning on standard T1-weighted MRI.
The BRAIN Initiative, launched by the NIH, pushed toward unprecedented resolution in 2024. Researchers published maps of a cubic millimeter of human brain tissue at nanometer resolution using electron microscopy combined with AI analysis. This tiny volume contained approximately 150 million synaptic connections. While mapping the entire brain at this scale remains computationally infeasible, these detailed maps reveal circuit-level organization underlying larger-scale function.
Functional Localization Principles
The concept that specific brain regions perform specialized functions has evolved considerably since the 19th century. Early phrenologists incorrectly believed skull bumps revealed underlying brain structure and personality. Modern neuroscience recognizes a more nuanced picture: while regions show functional preferences, complex behaviors recruit distributed networks.
Primary Sensory and Motor Areas
Certain cortical regions serve as primary processing centers for specific modalities. The primary motor cortex in the precentral gyrus (Brodmann Area 4) contains neurons that project directly to spinal motor neurons, initiating voluntary movement. This region exhibits somatotopic organization—a systematic mapping of body parts onto cortical surface. Wilder Penfield’s famous “motor homunculus” diagram illustrates this organization, showing that body parts requiring fine motor control (hands, face, tongue) occupy disproportionately large cortical territory.
The primary somatosensory cortex in the postcentral gyrus (Brodmann Areas 1, 2, 3) mirrors this organization. Different strips of cortex process distinct sensory features: Area 3a handles muscle spindle information, Area 3b processes cutaneous touch, Area 1 processes texture, and Area 2 integrates shape and size information.
Primary visual cortex (V1, Brodmann Area 17) occupies the banks of the calcarine sulcus in the occipital lobe. This region processes basic visual features like edges, orientation, and motion direction through specialized populations of neurons. Surrounding areas progressively extract more complex features: V2 processes depth and surface properties, V4 specializes in color and shape, and V5 (also called MT) analyzes motion.
Primary auditory cortex (A1, Brodmann Areas 41, 42) sits within the superior temporal gyrus in a region called Heschl’s gyrus. This area exhibits tonotopic organization, with different cortical locations responding preferentially to specific sound frequencies, creating a map of the audible spectrum.
Language Networks
Language processing involves multiple interconnected regions rather than isolated centers. Broca’s area in the inferior frontal gyrus (Areas 44, 45) contributes to speech production, grammatical processing, and verbal working memory. Damage to this region produces “expressive” or “non-fluent” aphasia, where patients understand language but struggle to produce grammatically correct speech.
Wernicke’s area in the posterior superior temporal gyrus (Area 22, plus portions of Areas 39 and 40) enables language comprehension. Lesions here cause “receptive” or “fluent” aphasia—patients produce grammatically structured speech that lacks meaningful content and cannot understand spoken or written language.
The arcuate fasciculus, a white matter tract, connects these language regions. Modern understanding recognizes that language processing extends beyond these classical areas to include portions of the temporal lobe for semantic memory, prefrontal regions for linguistic working memory, and motor cortex for articulatory control.
Association Areas and Higher Cognition
Beyond primary sensory and motor regions lie vast association areas that integrate information across modalities and support complex cognition. The prefrontal cortex, occupying the anterior portion of the frontal lobe, manages executive functions including planning, decision-making, working memory, and impulse control. Different prefrontal subregions show functional specialization: dorsolateral areas support working memory and cognitive control, orbitofrontal regions process reward and emotion, and ventromedial areas integrate visceral states with decision-making.
The posterior parietal cortex integrates sensory information to construct representations of space and body position. The superior parietal lobule supports sensorimotor integration and spatial attention, while the inferior parietal lobule contributes to tool use, mathematical cognition, and components of language processing.
The temporal lobes beyond primary auditory cortex support object recognition, semantic memory, and social perception. The fusiform gyrus shows preferential responses to faces, while adjacent regions respond more strongly to places, bodies, or written words. These preferences aren’t absolute—they reflect gradient-like tuning properties rather than strict category boundaries.
Cross-Hemispheric Organization
The cerebrum exhibits both contralateral control and hemispheric specialization. Each hemisphere primarily controls the opposite side of the body: the right hemisphere governs left-side motor function and receives left-side sensory input, and vice versa. This organization begins during embryonic development through an axial twist in the growing nervous system.
Hemispheric lateralization means the left and right hemispheres show functional asymmetries despite similar anatomical structures. In approximately 95% of right-handed individuals and 70% of left-handed individuals, the left hemisphere dominates language processing. This doesn’t mean the right hemisphere plays no role in communication—it processes prosody (emotional tone), metaphor, and contextual aspects of language.
The right hemisphere typically shows advantages for spatial processing, face recognition, and musical perception. However, these lateralization patterns reflect statistical tendencies rather than absolute divisions. The popular notion of people being “left-brained” or “right-brained” oversimplifies actual brain organization—virtually all complex tasks recruit both hemispheres working in coordination.
The corpus callosum enables hemispheric communication through approximately 200 million axons. Studies of “split-brain” patients, whose corpus callosum was severed to treat severe epilepsy, revealed how hemispheres process information independently when disconnected. These studies contributed to understanding hemispheric specialization, though they also spawned misconceptions about complete functional separation.
Mapping in Clinical Practice
Brain mapping serves critical clinical purposes beyond basic research. Neurosurgeons use preoperative fMRI to identify eloquent cortex—regions essential for language, motor control, or other vital functions—near tumors or vascular malformations. This information guides surgical approaches to maximize lesion removal while minimizing functional deficits.
Intraoperative electrocortical stimulation remains the gold standard for identifying critical functional regions during surgery. Surgeons apply electrical current directly to exposed cortex while patients perform tasks, mapping motor responses or disrupting language to delineate safe resection boundaries. While more invasive than fMRI, this technique provides real-time, patient-specific functional information.
Functional mapping assists epilepsy surgery planning by localizing seizure foci and determining which tissue can be safely removed. The Wada test, involving temporary anesthesia of one hemisphere through carotid injection, determines language dominance before surgery. However, fMRI increasingly supplements or replaces this invasive procedure.
Brain mapping also guides deep brain stimulation (DBS) for movement disorders and psychiatric conditions. Precise targeting of subcortical structures like the subthalamic nucleus for Parkinson’s disease or the subgenual cingulate for depression requires detailed anatomical knowledge combined with individualized planning. The anterior commissure and posterior commissure serve as key landmarks for stereotactic coordinate systems used in surgical planning.
Current Limitations and Challenges
Despite remarkable progress, brain mapping faces significant constraints. Spatial resolution remains limited—even high-field fMRI achieves only millimeter-scale resolution, while individual neurons measure micrometers. A single fMRI voxel contains hundreds of thousands of neurons, meaning measured signals reflect averaged activity across diverse cell populations.
Temporal resolution presents challenges for fMRI. The BOLD response peaks 5-6 seconds after neural activity and reflects vascular changes rather than direct neuronal firing. This limits ability to resolve rapid cognitive processes or determine causal sequences. MEG and EEG offer better temporal resolution but sacrifice spatial precision.
Individual variability complicates mapping efforts. While gross anatomical landmarks show consistency, detailed patterns of gyri and sulci vary substantially between individuals. Functional organization also varies—language regions can shift due to early brain injury, and even healthy individuals show different locations for specific functions. Standard atlas-based approaches may mislocate functional regions in specific individuals by centimeters.
Diffusion MRI tractography faces well-documented limitations. The technique struggles with crossing fibers, can produce spurious connections, and cannot currently quantify connection strength accurately. Validation studies comparing tractography to invasive tract-tracing in animal models reveal that reconstructed pathways often miss true connections or suggest implausible routes.
Computational demands scale dramatically with resolution and cohort size. Mapping a single cubic millimeter of brain tissue at synaptic resolution generates petabytes of data. The Human Connectome Project dataset, containing high-quality MRI data from over 1,000 subjects, requires sophisticated infrastructure for storage, analysis, and sharing. Processing time for advanced techniques can range from hours to weeks per subject.
Recent Advances and Future Directions
The field continues rapid evolution driven by technological innovation and large-scale data sharing initiatives. The Human Connectome Project established standardized protocols and openly shared data, enabling researchers worldwide to probe the same high-quality datasets. This approach accelerates discovery by allowing different groups to test diverse hypotheses on common data rather than each collecting separate small samples.
Machine learning has transformed data analysis capabilities. Neural networks trained on large datasets can identify subtle patterns invisible to traditional statistics, predict individual traits from brain structure, and even reconstruct visual experiences from fMRI data. Self-supervised learning approaches, inspired by natural language processing, treat brain activity as a sequence to be modeled, enabling better representation of temporal dynamics.
Ultra-high-field MRI scanners (7 Tesla and above) push spatial resolution boundaries. These systems reveal fine-scale anatomical details like cortical layers and small subcortical nuclei previously invisible in clinical imaging. Combined with advanced pulse sequences, they enable functional mapping at unprecedented resolution, though physiological noise and safety considerations present ongoing challenges.
Optogenetics—using light to control genetically modified neurons—combined with fMRI in animal models (“optofMRI”) has clarified relationships between neural activity and BOLD signals. These studies confirm that the BOLD response tracks neural firing with reasonable fidelity, validating interpretations of human fMRI data.
Brain-computer interfaces represent both an application of mapping knowledge and a new source of mapping data. Implanted electrode arrays, like those developed by Neuralink and Precision Neuroscience, provide direct neural recordings at high temporal resolution. In 2025, Precision Neuroscience achieved a record 4,096 electrodes in a single human brain, enabling detailed mapping of speech and motor regions during clinical procedures. As these technologies advance, they generate increasingly detailed functional maps while offering therapeutic potential for paralysis and communication disorders.
Integration Across Scales
Understanding brain function requires integrating information across organizational levels—from molecular mechanisms through cellular properties, local circuits, regional systems, and whole-brain networks. Recent initiatives emphasize this multiscale approach.
Gene expression atlases map which genes are active in different brain regions, revealing molecular signatures underlying functional specialization. The Allen Brain Atlas provides detailed maps of human brain gene expression, showing how molecular organization relates to anatomical structure. Researchers have begun combining these molecular maps with functional imaging to understand how genetic variation influences brain organization and behavior.
Single-cell transcriptomics characterizes molecular profiles of individual neurons, revealing unexpected diversity. Traditional classifications divided neurons into a few broad categories, but modern techniques identify dozens of distinct cell types based on gene expression patterns. Understanding how these cellular populations distribute across the cortex and contribute to functional specialization remains an active area of investigation.
Computational modeling bridges scales by simulating how cellular properties give rise to circuit behavior and how circuit dynamics produce system-level phenomena observable in imaging. These models help interpret empirical data and generate testable predictions. For example, models of neural oscillations link cellular properties of excitatory and inhibitory neurons to rhythmic patterns seen in EEG and MEG, which in turn relate to cognitive states.
Mapping Applications Beyond Neuroscience
Brain mapping techniques influence multiple fields beyond basic neuroscience research. Cognitive psychology uses fMRI to test theories about mental processes, examining which brain regions activate during attention, memory, emotion, or reasoning tasks. Educational neuroscience applies these methods to understand learning and development, potentially informing teaching strategies.
Neuromarketing employs brain imaging to study consumer behavior and advertising effectiveness. While controversial, these applications demonstrate growing interest in understanding decision-making and preference formation at a neural level. Similar approaches appear in neuroeconomics, which examines the brain basis of economic decision-making, risk assessment, and social exchange.
Psychiatry increasingly adopts brain mapping for diagnosis and treatment planning. While no imaging biomarkers currently achieve clinical diagnostic standards for psychiatric conditions, research maps differences in brain connectivity associated with depression, schizophrenia, autism, and other disorders. Some studies show promise for using brain features to predict treatment response, suggesting potential for personalized medicine approaches.
Forensic applications have emerged, though with significant controversy. Some researchers propose using brain imaging to detect deception, assess criminal responsibility, or predict violence risk. These applications raise serious ethical concerns about accuracy, interpretation, and individual rights. Courts have generally treated such evidence skeptically, recognizing current limitations.
The mapping of brain structure and function will continue advancing as technology evolves and interdisciplinary collaboration deepens. While complete circuit-level mapping of the human brain remains beyond current capabilities, the combination of improved imaging, computational power, and biological understanding steadily fills gaps in our knowledge. These maps serve both as scientific tools for understanding how brains work and as practical guides for treating brain disorders.
Frequently Asked Questions
What is the most accurate brain mapping technique available today?
No single technique provides complete information—different methods excel at different aspects. For structural detail at the microscopic level, electron microscopy combined with AI analysis achieves nanometer resolution, as demonstrated in 2024 BRAIN Initiative work. For non-invasive functional mapping, high-field fMRI (7 Tesla) offers the best combination of spatial resolution (submillimeter) and whole-brain coverage. MEG provides superior temporal resolution (milliseconds) for tracking neural dynamics. Clinical applications typically combine multiple techniques, using structural MRI for anatomy, fMRI for functional localization, and sometimes intraoperative stimulation for final verification.
How do scientists know which brain region controls which function?
Multiple converging evidence sources establish structure-function relationships. Lesion studies examine deficits following stroke, injury, or surgical removal—if damage to area X consistently impairs function Y, this suggests X contributes to Y. Stimulation studies apply electrical current to specific regions during neurosurgery, temporarily disrupting activity to map critical areas. Functional neuroimaging reveals which regions activate during specific tasks. Connectivity analysis traces anatomical pathways linking regions. Modern research emphasizes that complex functions typically involve networks rather than single regions, so mapping identifies nodes and connections within distributed systems.
Can brain maps predict individual cognitive abilities or personality?
Current brain imaging shows modest predictive ability for certain traits when analyzing large datasets. Machine learning models can predict fluid intelligence, working memory capacity, and some personality dimensions from brain structure and connectivity patterns, typically achieving correlations of 0.2-0.4. These predictions work at the group level but remain too imprecise for individual assessment. Factors including genetics, environment, life experiences, and measurement noise all contribute to individual differences. While research maps general principles of brain organization, substantial individual variation limits personalized prediction accuracy.
Do all brains have the same functional organization?
Brains show both striking similarities and meaningful differences in organization. Primary sensory and motor areas occupy consistent locations across individuals, with relatively preserved somatotopic and retinotopic maps. Higher-order association areas show more variability in precise functional boundaries. Major white matter tracts follow consistent courses, though details vary. Individual differences stem from genetic factors, developmental experiences, learning, and in some cases, reorganization following injury. While atlases provide useful templates, clinical applications require patient-specific mapping to account for individual anatomical and functional variations.
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