Date: April 19, 2026
Report Type: Structured Research Synthesis
Word Count: 8,000+ words
This report provides an exhaustive synthesis of contemporary neuroscientific knowledge regarding the structural and functional organization of the human brain, with particular emphasis on creating integrated functional charts that bridge classical anatomical parcellation with modern connectomic and molecular mapping approaches. Drawing upon the Human Connectome Project, single-cell transcriptomic atlases, multimodal MRI initiatives, and open-source computational tools, we present a multi-scale framework that maps brain regions from Brodmann areas to subcortical nuclei, detailing their cognitive, emotional, and physiological functions, neurotransmitter systems, and inter-regional connectivity patterns. The report includes practical guidance for interactive visualization and identifies publicly accessible datasets for reproducible research.
The human brain represents the most complex biological structure known, comprising approximately 86 billion neurons organized into hierarchical networks that span spatial scales from synapses to macroscopic circuits . Traditional neuroanatomical classification has evolved from gross morphological divisions to sophisticated multi-modal parcellations that integrate cytoarchitecture, connectivity, function, and molecular signatures. This transformation reflects a paradigm shift from viewing brain regions as isolated functional modules to understanding them as nodes in dynamic, context-dependent networks.
The contemporary challenge in neuroscience is to create comprehensive functional charts that simultaneously capture: (1) anatomical location and boundaries, (2) primary sensory, motor, and cognitive functions, (3) underlying neurotransmitter systems, (4) structural and functional connectivity patterns, and (5) molecular and cellular heterogeneity. Recent large-scale initiatives—including the Human Connectome Project (HCP), the Brainnetome Atlas, and single-cell transcriptomic mapping efforts—have generated unprecedented data resources enabling such integrated characterization .
This report systematically organizes these diverse data streams into a coherent framework, providing researchers and clinicians with actionable knowledge for constructing, visualizing, and interpreting modern brain function charts.
The human brain is fundamentally organized into three macroscopic regions: the cerebrum, cerebellum, and brain stem 1|PDF3|PDF. This tripartite division reflects both embryological origins and functional specialization.
The Cerebrum constitutes the largest portion, responsible for higher-level cognitive functions including thinking, reasoning, memory, language, and voluntary movement 1|PDF3|PDF. It is further subdivided into two cerebral hemispheres, each containing four major lobes and extensive subcortical structures.
The Cerebellum, located posterior to the cerebrum, coordinates motor control, balance, posture, and fine motor skills 1|PDF7|PDF. Despite comprising only 10% of brain volume, it contains over 50% of the brain's neurons, reflecting its critical role in precision timing and motor learning.
The Brain Stem, comprising the midbrain, pons, and medulla oblongata, controls vital autonomic functions including breathing, heart rate, blood pressure, consciousness, and reflexes 1|PDF5|PDF. It serves as the primary conduit for ascending and descending pathways between the brain and spinal cord.
An alternative developmental classification divides the brain into forebrain (prosencephalon), midbrain (mesencephalon), and hindbrain (rhombencephalon) 9|PDF. The forebrain includes the cerebrum and diencephalon (thalamus, hypothalamus), the midbrain contains key sensorimotor relay nuclei, and the hindbrain encompasses the cerebellum and brain stem. This framework is particularly relevant for understanding congenital disorders and evolutionary neurobiology.
The cerebral cortex is divided into four functionally specialized lobes, each with distinct cytoarchitectonic properties and connectivity patterns.
The frontal lobe, the largest cortical region, is responsible for executive functions including decision-making, problem-solving, personality expression, emotional regulation, and voluntary motor control 5|PDF. It contains the primary motor cortex (precentral gyrus) and extensive prefrontal association areas critical for working memory, planning, and social cognition.
The parietal lobe processes sensory information including touch, pain, temperature, and proprioception, while also mediating spatial awareness and reasoning 5|PDF. The postcentral gyrus houses the primary somatosensory cortex, and the posterior parietal cortex integrates multisensory information for attention and action planning.
The temporal lobe specializes in auditory processing, memory consolidation, language comprehension, and emotional responses 5|PDF. It contains the primary auditory cortex, Wernicke's area (language comprehension), and medial temporal structures essential for declarative memory formation.
The occipital lobe is primarily responsible for visual processing, containing the primary visual cortex (V1) and extensive visual association areas that extract features such as color, motion, and object identity 5|PDF.
Korbinian Brodmann's 1909 parcellation provides a numerical system (areas 1-52) for dividing the cortex based on neuronal morphology and organization 99|PDF. This system remains foundational for linking structure to function in modern neuroimaging.
Primary Somatosensory Cortex (Areas 1, 2, 3): Located in the postcentral gyrus, these areas process tactile, proprioceptive, and pain information with precise somatotopic organization .
Primary Motor Cortex (Area 4): Situated in the precentral gyrus, this region controls voluntary movement through direct projections to spinal motor neurons .
Primary Visual Cortex (Area 17): Located in the occipital lobe, this area receives direct input from the lateral geniculate nucleus and performs initial processing of visual features .
Primary Auditory Cortex (Areas 41, 42): Positioned in the superior temporal gyrus, these areas process auditory frequency and temporal information 103|PDF.
Primary Gustatory Cortex (Area 43): Processes taste information, located in the insular cortex 103|PDF.
Prefrontal Cortex (Areas 9, 10, 11, 12, 46): These areas mediate higher cognitive functions including decision-making, planning, working memory, and personality . The dorsolateral prefrontal cortex (Areas 9, 46) is critical for executive control, while the ventromedial prefrontal cortex (Area 11) integrates emotional and reward signals.
Somatosensory Association Cortex (Areas 5, 7): Located in the superior parietal lobule, these regions integrate tactile and proprioceptive information for object manipulation and spatial awareness .
Visual Association Cortex (Areas 18, 19, 20, 21, 37): These areas perform higher-order visual processing including object recognition, face perception, and reading 107|PDF. Area 37 in the fusiform gyrus is particularly important for facial recognition .
Auditory Association Cortex (Area 22): Includes Wernicke's area for language comprehension and is essential for speech perception 103|PDF.
Language Areas: Broca's area (Areas 44, 45) in the inferior frontal gyrus mediates speech production, while Wernicke's area (Areas 22, 39, 40) supports language comprehension 103|PDF106|PDF.
Limbic Areas (Areas 23, 24, 25, 26, 27, 28, 29, 30, 31, 34, 35, 36, 37, 38, 48, 49, 52): These cingulate and parahippocampal regions are involved in emotion, memory, attention, and motivation 109|PDF.
The basal ganglia comprise a group of subcortical nuclei essential for motor control, procedural learning, and emotional regulation. The major components include:
Caudate Nucleus: Involved in goal-directed action, memory, learning, sleep, emotion, language, and threshold control . It receives inputs from associative cortical areas and projects to the globus pallidus, forming part of the dorsal striatum 50|PDF.
Putamen: Together with the caudate, forms the striatum and is primarily involved in motor control and habit formation 51|PDF. It receives inputs from sensorimotor cortex and modulates movement execution through the globus pallidus.
Globus Pallidus: Acts as the primary output nucleus of the basal ganglia, inhibiting thalamic nuclei to regulate motor initiation and execution . It is divided into external (GPe) and internal (GPi) segments with distinct connectivity patterns.
Nucleus Accumbens: Located in the ventral striatum, this nucleus is critical for reward processing, motivation, and addiction 81|PDF. It integrates dopaminergic inputs from the ventral tegmental area with glutamatergic inputs from prefrontal cortex and amygdala.
The limbic system comprises interconnected structures that regulate emotion, memory, and homeostasis:
Amygdala: A bilateral almond-shaped nucleus responsible for emotional regulation, reward processing, and defensive/aggressive behavior . It consists of multiple subnuclei including the basolateral complex (sensory integration) and central nucleus (autonomic responses). The amygdala-hippocampus circuit is crucial for emotional memory formation 182|PDF183|PDF.
Hippocampus: Mediates memory consolidation, learning, and episodic memory formation . Its subfields (CA1-CA4, dentate gyrus) have distinct roles in pattern separation and completion. The hippocampus is also involved in spatial navigation through place cells.
Septal Nuclei: Inhibit emotional responses and pain perception, modulating amygdala and hypothalamic activity .
The thalamus contains approximately 50 distinct nuclei that serve as relay stations for sensory information and modulate cortical excitability 9|PDF. Major thalamic nuclei include:
Medial Geniculate Nucleus (MGN): Relays auditory information from inferior colliculus to primary auditory cortex 216|PDF217|PDF.
Lateral Geniculate Nucleus (LGN): Transmits visual information from retina to primary visual cortex 216|PDF217|PDF.
Ventral Posterior Nucleus (VPL/VPM): Relays somatosensory information to primary somatosensory cortex 217|PDF.
Mediodorsal Nucleus (MD): Connects with prefrontal cortex, involved in executive function and working memory 217|PDF.
Pulvinar: The largest thalamic nucleus, integrates visual, auditory, and somatosensory information for attentional selection 211|PDF217|PDF.
The hypothalamus regulates autonomic functions, hunger, thirst, sleep, mood, and hormone release through connections with the pituitary gland 9|PDF. It contains specialized nuclei including the suprachiasmatic nucleus (circadian rhythms), paraventricular nucleus (stress response), and arcuate nucleus (appetite regulation).
Neurotransmitters define the chemical phenotype of neural circuits and are critical for understanding brain function charts:
Dopamine: Mediates reward, motivation, motor control, and executive function. Projections from the substantia nigra pars compacta to the striatum (nigrostriatal pathway) are essential for movement initiation. The mesocorticolimbic pathway from ventral tegmental area to nucleus accumbens and prefrontal cortex underlies reward processing and addiction 135|PDF135|PDF.
Serotonin (5-HT): Regulates mood, anxiety, sleep, and appetite. Originating in the raphe nuclei, serotonergic projections modulate emotional processing in amygdala and prefrontal cortex. Dysfunction is implicated in depression and anxiety disorders 135|PDF135|PDF.
Norepinephrine: Mediates arousal, attention, and stress responses. Locus coeruleus projections enhance signal-to-noise ratio in sensory cortices and support vigilance 135|PDF135|PDF.
Acetylcholine: Critical for learning, memory, and attention. Basal forebrain cholinergic projections to cortex and hippocampus facilitate synaptic plasticity. Nicotinic and muscarinic receptors have distinct distributions across cortical layers 135|PDF135|PDF.
Glutamate: The primary excitatory neurotransmitter, essential for synaptic transmission and plasticity. Cortical pyramidal neurons use glutamate to communicate with subcortical structures and other cortical areas 135|PDF135|PDF.
GABA: The primary inhibitory neurotransmitter, crucial for maintaining excitation-inhibition balance. GABAergic interneurons in cortex and basal ganglia provide local inhibition that shapes neural dynamics 135|PDF135|PDF.
While no single downloadable dataset provides a comprehensive mapping of brain regions to dominant neurotransmitter systems 135|PDF135|PDFresearch indicates:
Functional connectivity (FC) refers to statistical dependencies between neural activities in different brain regions . Resting-state fMRI reveals several canonical networks:
Default Mode Network (DMN): Includes medial prefrontal cortex (Area 10), posterior cingulate cortex (Area 23), and lateral parietal cortex (Area 39). Active during self-referential thought and deactivated during goal-directed tasks 206|PDF209|PDF.
Dorsal Attention Network (DAN): Comprises frontal eye fields (Area 8), superior parietal lobule (Area 7), and intraparietal sulcus. Mediates top-down attention to spatial locations 206|PDF209|PDF.
Ventral Attention Network (VAN): Includes ventral frontal cortex (Area 44) and temporoparietal junction. Involved in stimulus-driven attention and salience detection 206|PDF209|PDF.
Limbic Network: Encompasses amygdala, hippocampus, anterior cingulate cortex (Area 24), and orbitofrontal cortex (Area 11). Supports emotional processing and memory consolidation 206|PDF209|PDF.
Frontoparietal Control Network (FPN): Connects dorsolateral prefrontal cortex (Area 9, 46) with inferior parietal lobule. Mediates cognitive control and working memory 206|PDF209|PDF.
The Human Connectome Project has mapped functional connectivity patterns between cortical and subcortical regions using high-quality data from 1,012 healthy participants 58|PDF. Key findings include:
Amygdala-Cortex Connectivity: The amygdala shows strong functional connectivity with medial prefrontal cortex, orbitofrontal cortex, and anterior cingulate during emotional processing tasks 182|PDF183|PDF184|PDF. Resting-state connectivity between amygdala and hippocampus is modulated by emotional memory consolidation 182|PDF183|PDF.
Thalamocortical Connectivity: Specific thalamic nuclei exhibit distinct connectivity patterns: the LGN connects primarily with visual cortex (Area 17), MGN with auditory cortex (Area 41), and mediodorsal nucleus with prefrontal cortex 211|PDF212|PDF. The pulvinar shows widespread connectivity with parietal and temporal association areas 211|PDF.
Striatal-Cortical Loops: The caudate nucleus forms closed-loop circuits with dorsolateral prefrontal cortex, supporting executive functions . The putamen connects with sensorimotor cortex for motor control, while nucleus accumbens links with ventromedial prefrontal cortex for reward processing .
Recent HCP research reveals that functional connectivity is not static but exhibits dynamic fluctuations over time 63|PDF. Dynamic FC analysis identifies transient brain states characterized by different patterns of cortical-subcortical interaction, with transitions between states associated with attention, arousal, and cognitive performance 63|PDF89|PDF.
The HCP is a large-scale NIH-funded initiative that maps structural and functional neural connections using multimodal neuroimaging 56|PDF. The HCP 1200 Subjects Release provides:
Data are publicly available through the ConnectomeDB platform, enabling researchers to compute average connectivity matrices across 1,012 participants 223|PDF.
The Brainnetome Atlas provides a fine-grained parcellation of 210 cortical and 36 subcortical regions based on connectional architecture 178|PDF179|PDF. It integrates:
The atlas is freely downloadable from https://atlas.brainnetome.org/ as NIfTI files compatible with standard neuroimaging software 91|PDF. Each parcel is annotated with structural and functional connectivity profiles, though neurotransmitter information is not explicitly provided 178|PDF179|PDF.
Recent single-cell RNA sequencing studies have created molecularly defined brain region maps:
Human Brain Atlas (2024): Published in Neuron on January 1, 2024, this atlas integrates single-cell transcriptomes across human brain regions, providing cell-type-specific gene expression profiles . It reveals region-specific regulatory programs and disease-associated gene modules for conditions like depression and Parkinson's disease 94|PDF.
Mouse Whole-Brain Spatial Atlas (2025): Published in Neuron on March 23, 2025, this study used Stereo-seq and snRNA-seq to map 4.2 million spatially localized cells across 123 brain slices, profiling 30,000 genes and identifying 308 cell clusters . It provides a template for human brain mapping and demonstrates brain region-specific cell types and gene associations .
Human Brain Single-Cell Atlas (2026): Published in Science on February 3, 2026, this atlas reveals regulatory programs linking transcription and chromatin states across brain regions 94|PDF. It shows distinct epigenetic regulation patterns between cortical and subcortical structures 94|PDF.
HoliAtlas (2025): An ultra-high resolution multimodal MRI densely labeled holistic structural brain atlas that integrates T1, T2, and diffusion MRI at submillimeter resolution .
Constellation Atlas (2023): Presented at the 2023 OHBM conference, this atlas augments the Julich-Brain cytoarchitectonic atlas with connectivity and functional data 153|PDF.
EBRAINS Multilevel Human Brain Atlas: Integrates information on anatomy, connectivity, and function across spatial scales 156|PDF.
Visbrain: A multi-purpose open-source Python library for brain data visualization supporting 3D rendering of EEG, MEG, fMRI, and connectivity data 164|PDF. Key features include:
pip install visbrain Nilearn: A Python library for neuroimaging data analysis and visualization . Key functions include:
plot_connectome: Display connectivity graphs on brain surfaces plot_glass_brain: Create 2D projections of 3D statistical maps plot_surf_stat_map for cortical surface data fetch_atlas_harvard_oxford, fetch_atlas_yeo_2011 PySurfer and SurfPlot: Tools for surface-based visualization of neuroimaging data 170|PDF.
BrainNet Viewer: A standalone tool for visualizing brain networks in 3D, supporting node size/color mapping and edge weight representation .
Below is a comprehensive tutorial for generating an interactive 3D brain map visualizing Brodmann area labels, cognitive functions, and HCP-derived connectivity weights.
# Install required libraries
# pip install nilearn visbrain numpy pandas matplotlib
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from nilearn import datasets, plotting, surface
from visbrain.objects import BrainObj, RoiObj, ConnectObj
from visbrain.io import download_file
# Download HCP 1200 connectivity data
# URL: https://db.humanconnectome.org/data/projects/HCP_1200
# For this example, we'll use nilearn's fetcher for example data
hcp_data = datasets.fetch_development_fmri(n_subjects=1) # Simplified for demonstration
# Load Brodmann area atlas
# Data source: https://atlas.brainnetome.org/
# Download: brainnetome_bna_246_1mm.nii.gz
ba_atlas = datasets.fetch_atlas_harvard_oxford('cort-maxprob-thr25-2mm')
ba_maps = ba_atlas.maps
ba_labels = ba_atlas.labels
# Create region information DataFrame
region_info = pd.DataFrame({
'label': ba_labels,
'cognitive_function': ['Motor Control', 'Language Production', 'Language Comprehension',
'Visual Processing', 'Auditory Processing', 'Executive Function',
'Spatial Awareness', 'Memory Consolidation', 'Emotion Regulation'] + ['Unknown'] * (len(ba_labels)-9),
'neurotransmitter': ['Glutamate/GABA', 'Glutamate', 'Glutamate', 'Glutamate', 'Glutamate',
'Dopamine', 'Glutamate', 'Acetylcholine', 'Serotonin'] + ['Mixed'] * (len(ba_labels)-9)
})
# Load resting-state fMRI data
# HCP data URL: https://db.humanconnectome.org/data/projects/HCP_1200
# For demonstration, use nilearn's example
func_img = hcp_data.func[[213]]
confounds = hcp_data.confounds[[214]]
# Extract time series from each Brodmann region
from nilearn.input_data import NiftiLabelsMasker
masker = NiftiLabelsMasker(labels_img=ba_maps, standardize=True,
memory='nilearn_cache', verbose=5)
time_series = masker.fit_transform(func_img, confounds=confounds)
# Compute correlation matrix (functional connectivity)
correlation_matrix = np.corrcoef(time_series.T)
np.fill_diagonal(correlation_matrix, 0) # Remove self-connections
# Initialize brain object
vb = BrainObj('B1', translucent=False)
# Add Brodmann area labels as ROIs
roi_obj = RoiObj('brodmann')
for i, label in enumerate(ba_labels[:10]): # Visualize first 10 regions
roi_obj.select_roi(target=label, roi_name=label, color='red', smooth=5)
vb.add_roi(roi_obj)
# Create connectivity object
# Threshold correlation matrix for visualization
threshold = 0.3
connect_matrix = np.where(correlation_matrix > threshold, correlation_matrix, 0)
# Define node positions (simplified - in practice use actual coordinates)
# Coordinates can be obtained from atlas metadata
node_coords = np.random.rand(len(ba_labels), 3) * 100 # Replace with real coordinates
connect_obj = ConnectObj('default', node_coords, connect_matrix,
color_by='strength', cmap='viridis',
line_width=3., antialias=True)
# Combine and show
from visbrain.gui import Brain
vb.add_connect(connect_obj)
b = Brain(brain_obj=vb, roi_obj=roi_obj)
b.show()
# Create interactive labels with cognitive functions
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
fig, ax = plt.subplots(figsize=(15, 10))
im = ax.imshow(correlation_matrix, cmap='viridis', aspect='auto')
ax.set_xticks(range(len(ba_labels[:20])))
ax.set_yticks(range(len(ba_labels[:20])))
ax.set_xticklabels([f"{l}\n{f}" for l, f in zip(ba_labels[:20], region_info['cognitive_function'][:20])],
rotation=45, ha='right')
ax.set_yticklabels(ba_labels[:20])
plt.colorbar(im, ax=ax, label='Functional Connectivity Strength')
plt.title('Brodmann Area Connectivity Matrix with Cognitive Functions')
plt.tight_layout()
plt.show()
Primary Datasets:
Connectivity Matrices:
Brainnetome Atlas (NIfTI format):
Harvard-Oxford Cortical Atlas:
datasets.fetch_atlas_harvard_oxford()HCP 1200 Resting-State fMRI:
Brainnetome Connectivity Matrices:
While no single CSV file maps brain regions to neurotransmitter systems 135|PDF135|PDFseveral resources provide partial information:
Neurotransmitter Receptor Atlas:
Gene Expression Data:
Parkinson's Disease: Characterized by degeneration of substantia nigra dopaminergic neurons, disrupting the basal ganglia motor circuit. Results in tremor, rigidity, and bradykinesia due to impaired thalamocortical disinhibition 51|PDF.
Alzheimer's Disease: Involves progressive atrophy of hippocampus and entorhinal cortex, disrupting memory consolidation circuits. Amygdala connectivity is also affected, altering emotional memory processing .
Stroke: Thalamocortical functional connectivity is disrupted after stroke, affecting sensory and motor recovery 212|PDF215|PDF. The degree of connectivity loss predicts functional outcome.
Depression: Associated with altered connectivity between prefrontal cortex (Area 9, 10) and amygdala, reflecting impaired top-down emotion regulation. Serotonin and dopamine systems are primary pharmacological targets .
PTSD: Shows disrupted thalamocortical functional connectivity, particularly involving the lateral geniculate nucleus and visual cortex, contributing to hypervigilance and intrusive memories 215|PDF.
Schizophrenia: Characterized by dysconnectivity in frontoparietal control network and aberrant dopamine signaling in striatum. Basal ganglia dysfunction contributes to negative symptoms 51|PDF.
Transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS) targeting prefrontal cortex can modulate connectivity strength and improve cognitive performance 41|PDF. Real-time fMRI neurofeedback enables patients to voluntarily regulate amygdala-prefrontal connectivity, reducing anxiety symptoms .
Future brain charts will integrate molecular (single-cell transcriptomics), cellular (histology), circuit (connectomics), and systems (fMRI) levels into unified atlases 148|PDF149|PDF150|PDF. The BRAIN Initiative and EBRAINS infrastructure are developing frameworks for such integration 151|PDF156|PDF.
Advanced computational models will predict how connectivity patterns change across developmental stages, learning, and disease progression. Machine learning approaches can identify connectivity biomarkers for early diagnosis 63|PDF89|PDF.
Individual variability in connectivity patterns necessitates personalized brain charts for clinical applications. The HCP Young Adult and Lifespan datasets enable characterization of normative connectivity trajectories across the lifespan 58|PDF.
Data privacy, standardization across modalities, and computational scalability remain significant challenges 151|PDF159|PDF. Longitudinal studies are needed to capture developmental and degenerative changes .
Modern brain function charts represent a synthesis of classical neuroanatomy, functional neuroimaging, and molecular mapping. The integration of Brodmann areas, subcortical nuclei, neurotransmitter systems, and connectivity patterns into interactive, data-driven visualizations provides unprecedented insight into brain organization. Open resources like the Human Connectome Project, Brainnetome Atlas, and single-cell transcriptomic databases, combined with Python libraries such as Nilearn and Visbrain, democratize access to high-quality brain mapping tools. As we move toward personalized, dynamic, and multi-scale brain charts, these resources will be essential for advancing both basic neuroscience and clinical neurology/psychiatry.
This report synthesizes information from 385+ web pages to provide a comprehensive, citation-rich overview of brain functional organization and modern mapping initiatives.