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Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons
Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons
Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons
<table class="infobox infobox-cell">
<tr>
<th class="infobox-header" colspan="2">Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons</th>
</tr>
<tr>
<td class="label">Taxonomy</td>
<td>ID</td>
</tr>
<tr>
<td class="label">Cell Ontology (CL)</td>
<td>[CL:0000598](https://www.ebi.ac.uk/ols4/ontologies/cl/classes/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FCL_0000598)</td>
</tr>
<tr>
<td class="label">Database</td>
<td>ID</td>
</tr>
<tr>
<td class="label">Cell Ontology</td>
<td>[CL:0000598](https://www.ebi.ac.uk/ols4/ontologies/cl/classes/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FCL_0000598)</td>
</tr>
<tr>
<td class="label">Full Name</td>
<td>Dorsolateral Prefrontal Cortex Pyramidal Neurons</td>
</tr>
<tr>
<td class="label">Abbreviation</td>
<td>DLPFC</td>
</tr>
<tr>
<td class="label">Location</td>
<td>Lateral prefrontal cortex, middle frontal gyrus, Brodmann areas 46 and 9</td>
</tr>
<tr>
<td class="label">Cell Type</td>
<td>Glutamatergic pyramidal neurons</td>
</tr>
<tr>
<td class="label">Layer</td>
<td>Layer 2/3 (cortical-cortical) and Layer 5 (subcortical projection)</td>
</tr>
<tr>
<td class="label">Allen Atlas ID</td>
<td>Mouse: 33</td>
</tr>
<tr>
<td class="label">Gene</td>
<td>Expression Level</td>
</tr>
<tr>
<td class="label">CaMKIIα (Camk2a)</td>
<td>Ver...
Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons
Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons
<table class="infobox infobox-cell">
<tr>
<th class="infobox-header" colspan="2">Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons</th>
</tr>
<tr>
<td class="label">Taxonomy</td>
<td>ID</td>
</tr>
<tr>
<td class="label">Cell Ontology (CL)</td>
<td>[CL:0000598](https://www.ebi.ac.uk/ols4/ontologies/cl/classes/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FCL_0000598)</td>
</tr>
<tr>
<td class="label">Database</td>
<td>ID</td>
</tr>
<tr>
<td class="label">Cell Ontology</td>
<td>[CL:0000598](https://www.ebi.ac.uk/ols4/ontologies/cl/classes/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FCL_0000598)</td>
</tr>
<tr>
<td class="label">Full Name</td>
<td>Dorsolateral Prefrontal Cortex Pyramidal Neurons</td>
</tr>
<tr>
<td class="label">Abbreviation</td>
<td>DLPFC</td>
</tr>
<tr>
<td class="label">Location</td>
<td>Lateral prefrontal cortex, middle frontal gyrus, Brodmann areas 46 and 9</td>
</tr>
<tr>
<td class="label">Cell Type</td>
<td>Glutamatergic pyramidal neurons</td>
</tr>
<tr>
<td class="label">Layer</td>
<td>Layer 2/3 (cortical-cortical) and Layer 5 (subcortical projection)</td>
</tr>
<tr>
<td class="label">Allen Atlas ID</td>
<td>Mouse: 33</td>
</tr>
<tr>
<td class="label">Gene</td>
<td>Expression Level</td>
</tr>
<tr>
<td class="label">CaMKIIα (Camk2a)</td>
<td>Very High</td>
</tr>
<tr>
<td class="label">Vglut1 (Slc17a7)</td>
<td>Very High</td>
</tr>
<tr>
<td class="label">FOXP2</td>
<td>High</td>
</tr>
<tr>
<td class="label">RORB</td>
<td>High</td>
</tr>
<tr>
<td class="label">GAD1</td>
<td>Moderate</td>
</tr>
<tr>
<td class="label">NR4A1</td>
<td>Moderate</td>
</tr>
<tr>
<td class="label">FOS</td>
<td>Moderate</td>
</tr>
</table>
Introduction
Dorsolateral Prefrontal Cortex (Dlpfc) Pyramidal Neurons is an important component in the neurobiology of neurodegenerative diseases. This page provides detailed information about its structure, function, and role in disease processes.
Overview
Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons is a specialized neuronal population involved in emotion regulation and executive function. These neurons play critical roles in fear extinction, decision-making, and working memory and are vulnerable in various neurodegenerative diseases. [@miller2001]
Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons
The Dorsolateral Prefrontal Cortex (DLPFC), corresponding to Brodmann areas 46 and 9, is the canonical executive function region of the cerebral cortex. DLPFC pyramidal neurons form the backbone of working memory, cognitive control, and goal-directed behavior. These neurons are exquisitely vulnerable in aging and neurodegenerative diseases. [@arnsten2009]
<!-- taxonomy-enrichment --> [@robbins2009]
<!-- multi-taxonomy-enrichment -->
Multi-Taxonomy Classification
Taxonomy Database Cross-References
Morphology & Electrophysiology
- Morphology: pyramidal neuron (source: Cell Ontology)
- Morphology can be inferred from Cell Ontology classification
PanglaoDB Marker Cross-References
- Unknown (PanglaoDB):
External Database Links
- [Cell Ontology (CL:0000598)](https://www.ebi.ac.uk/ols4/ontologies/cl/classes/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FCL_0000598)
- [OBO Foundry (CL:0000598)](http://purl.obolibrary.org/obo/CL_0000598)
- [Allen Brain Cell Atlas](https://portal.brain-map.org/atlases-and-data/bkp/abc-atlas)
- [CellxGene Census](https://cellxgene.cziscience.com/)
- [Human Cell Atlas](https://www.humancellatlas.org/)
- [PanglaoDB](https://panglaodb.se/)
Taxonomy & Classification
PanglaoDB Marker Cross-References
- Unknown (PanglaoDB):
External Database Links
- [Cell Ontology (CL:0000598)](https://www.ebi.ac.uk/ols4/ontologies/cl/classes/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FCL_0000598)
- [OBO Foundry (CL:0000598)](http://purl.obolibrary.org/obo/CL_0000598)
- [Allen Brain Cell Atlas](https://portal.brain-map.org/atlases-and-data/bkp/abc-atlas)
- [CellxGene Census](https://cellxgene.cziscience.com/)
- [PanglaoDB](https://panglaodb.se/)
Quick Facts
Morphology and Markers
Cellular Morphology
DLPFC pyramidal neurons are among the most studied neurons in the primate brain:
- Large pyramidal somata (20-35 μm diameter in Layer 5)
- Prominent apical dendrite extending to Layer 1 with extensive tuft
- Extensive basilar dendritic arborization in Layers 3-5
- High spine density on dendrites (10-15 spines/μm)
- Long axonal collaterals forming horizontal connections
Molecular Markers
Key molecular markers for DLPFC pyramidal neurons:
- CaMKIIα (Camk2a) - excitatory neuron marker
- Vglut1 (Slc17a7) - vesicular glutamate transporter
- FOXP2 - transcription factor enriched in DLPFC
- RORβ - nuclear receptor for circadian regulation
- SATB2 - chromatin remodeling factor
- ER81 (Etv1) - transcription factor for projection neurons
Normal Function
Working Memory
The DLPFC is the neural substrate for working memory:
- Maintains information "online" for seconds to minutes
- Layer 3 neurons encode stimulus identity and quantity
- Layer 5 neurons generate output to guide behavior
- Delay period activity maintains representations
- NMDA receptor-dependent synaptic plasticity underlies learning
Cognitive Control
DLPFC implements top-down cognitive control:
- Suppresses inappropriate responses
- Resolves conflict between competing stimuli
- Shifts between task sets
- Coordinates between multiple brain regions
- Maintains task rules in memory
Executive Function
DLPFC supports higher-order executive processes:
- Planning and sequencing complex behaviors
- Decision-making under uncertainty
- Inhibiting prepotent responses
- Cognitive flexibility and set-shifting
- Temporal discounting and reward evaluation
Vulnerability in Neurodegenerative Diseases
Alzheimer's Disease
- Early metabolic decline: DLPFC shows early hypometabolism in AD (posterior cingulate and precuneus precede, but DLPFC follows)
- Tau pathology: Neurofibrillary tangles reach DLPFC in Braak Stage IV-V
- Working memory deficits: Early impairment of DLPFC-dependent working memory
- Executive dysfunction: Planning, organization, and cognitive control decline
- Synaptic loss: Dendritic spine reduction precedes neuron loss
Parkinson's Disease
- Dopaminergic deafferentation: DLPFC receives dopaminergic input from VTA; loss impairs function
- Working memory deficits: Particularly for spatial and complex information
- Executive dysfunction: Planning, set-shifting, and inhibition deficits
- Cognitive fluctuations: DLPFC function fluctuates with medication state
Frontotemporal Dementia
- Primary target: bvFTD shows early and severe DLPFC involvement
- Executive impairment: Severe deficits in planning, reasoning, flexibility
- Behavioral disinhibition: Loss of top-down control over behavior
- Working memory deficits: May be less prominent than in AD
Huntington's Disease
- Early prefrontal dysfunction: DLPFC metabolic changes precede motor symptoms
- Working memory deficits: Characteristic impairment of spatial working memory
- Executive dysfunction: Planning, cognitive flexibility, inhibition deficits
- Circuit disruption: Striatal loops with DLPFC are disrupted
Progressive Supranuclear Palsy
- Frontal involvement: PSP prominently affects prefrontal cortex
- Executive dysfunction: Severe deficits in planning and cognitive control
- Freezing of thought: Reduced verbal fluency and processing speed
Transcriptomic Profile
Key differentially expressed genes in DLPFC pyramidal neurons (from Allen Brain Atlas):
Therapeutic Implications
Transcranial Magnetic Stimulation
- High-frequency rTMS to DLPFC improves working memory in healthy elderly
- Theta-burst stimulation shows promise for cognitive enhancement
- FDA-approved for treatment-resistant depression
Cognitive Training
- Working memory training can improve DLPFC function
- Transfer effects to untrained cognitive domains
- Combined with physical exercise may enhance benefits
Pharmacological Approaches
- Dopaminergic agents: May enhance DLPFC function in PD
- Acetylcholinesterase inhibitors: May improve attention and working memory
- NMDA receptor modulators: Under investigation for cognitive enhancement
Lifestyle Interventions
- Aerobic exercise: Increases DLPFC volume and function
- Meditation: Increases DLPFC activity and gray matter density
- Cognitive reserve: Education and intellectual enrichment buffer DLPFC decline
Connections
Afferent Inputs
- Posterior parietal cortex (spatial attention)
- Superior temporal cortex (object information)
- Hippocampus (episodic memory)
- Thalamic mediodorsal nucleus (arousal, motivation)
- Amygdala (emotional salience)
Efferent Projections
- Posterior parietal cortex (feedback)
- Premotor and supplementary motor areas
- Basal ganglia (caudate head; cognitive loop)
- Superior temporal cortex
- Thalamic mediodorsal nucleus
- Infralimbic Cortex Pyramidal Neurons
- Anterior Cingulate Cortex Pyramidal Neurons
- [Prefrontal Cortex](/brain-regions/prefrontal-cortex)
- [Alzheimer's Disease](/diseases/alzheimers-disease)
- [Parkinson's Disease](/diseases/parkinsons-disease)
- [Frontotemporal Dementia](/diseases/frontotemporal-dementia)
- [Working Memory](/mechanisms/working-memory)
Background
The study of Dorsolateral Prefrontal Cortex (Dlpfc) Pyramidal Neurons has evolved significantly over the past decades. Research in this area has revealed important insights into the underlying mechanisms of neurodegeneration and continues to drive therapeutic development.
Historical context and key discoveries in this field have shaped our current understanding and will continue to guide future research directions.
Research Evidence
Dynamic functional connectivity measures are more reliable than stationary connectivity measures in attention networks
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Dorsal attention network (DAN) Factor 3 (anterior DAN) obtained at rest significantly predicts alerting effect on Attention Network Test in both sessions (p=0.001 and p=0.037)
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Fronto-parietal task control network (FPTC) Factor 3 predicts orienting effect at Session 1 (p=0.010)
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
The relationship between DAN Factor 3 and alerting effect was present during both rest and task conditions
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Changes in dynamic connectivity factor scores between sessions correlated with changes in accuracy in Incongruent Flanker trials
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Higher dynamic connectivity (factor scores) was associated with larger alerting and orienting effects, possibly reflecting more effortful processing or rigidity in resource reallocation
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
No significant group differences in ICA-defined resting networks between PD and controls, suggesting subtle differences in early-stage PD
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Dynamic connectivity factor structures are stable across rest and task states (Procrustes congruence 0.89-0.93 for DAN)
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Individual differences in dynamic connectivity are reliable across scanner sessions but not invariant, and changes reflect behavioral changes
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Attention Network Test (ANT) behavioral performance measurement
PD participants showed slowed response latencies across all conditions. PD participants had significantly larger alerting effect (No Cue - Center Cue) compared to controls (PD: 47ms vs Controls: 28ms, p=0.025). No significant differences in orienting or executive effects between groups.
Model System: Human participants: 25 Parkinson disease (PD) patients and 21 healthy controls (ages 41-86)
Statistical Significance: p = 0.025 for alerting effect difference between groups
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
ICA analysis of resting-state networks
Identified dorsal attention network (DAN), salience network, and default mode network (DMN). No significant group differences found between PD and controls in these networks.
Model System: Human participants: 25 PD patients and 21 controls undergoing resting-state fMRI
Statistical Significance: No significant group differences (p > 0.05 after correction)
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Dynamic connectivity factor analysis
Extracted 4 factors for each network (DAN, FPTC, DMN). Factor structures were qualitatively similar to previous aging sample but explained less variance in this sample. Reliability of factor scores was higher than reliability of individual pairwise correlations.
Model System: Human participants: 25 PD and 21 controls during resting-state fMRI scans
Statistical Significance: DAN factor reliability 0.56-0.64, FPTC 0.35-0.69, DMN 0.57-0.78 (all p < 0.01 except FPTC Factor 4 p=0.01)
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Reliability comparison: dynamic vs stationary connectivity
Dynamic connectivity measures are more reliable than stationary connectivity measures. Median reliability of factor scores higher than median reliability of pairwise correlations for DAN (p=0.020) and DMN (p=0.036). FPTC showed marginally significant difference (p=0.082).
Model System: Same 46 participants in resting-state fMRI
Statistical Significance: DAN: p=0.020, DMN: p=0.036, FPTC: p=0.082
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Prediction of alerting effect from resting-state dynamic connectivity
DAN Factor 3 (anterior DAN) significantly predicted alerting effect magnitude at both sessions (Session 1: p=0.001, R2=0.21; Session 2: p=0.037, R2=0.09). Effect remained significant after controlling for age. Group-by-factor interaction significant at Session 1 (p=0.002) but not Session 2.
Model System: 46 participants (25 PD, 21 controls) from resting-state scans to ANT performance
Statistical Significance: Session 1: t(44)=3.46, p=0.001; Session 2: t(44)=2.15, p=0.037; Group x Factor interaction Session 1: p=0.002
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Prediction of orienting effect from resting-state dynamic connectivity
FPTC Factor 3 predicted orienting effect at Session 1 (p=0.010) but not Session 2 (p=0.116). No significant group or group-by-factor interaction.
Model System: 46 participants from resting-state scans to ANT orienting effect
Statistical Significance: Session 1: t(44)=2.70, p=0.010; Session 2: t(44)=1.6, p=0.116
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Task-based dynamic connectivity analysis
DAN factor structure during task highly congruent with rest (Procrustes correlation 0.93 Session 1, 0.89 Session 2, p=0.001). DAN Factor 3 during tasks predicted alerting effect (Session 1: p=0.023, R2=0.11; Session 2: p=0.107). During tasks, DAN Factor 3 also negatively predicted orienting effect at Session 2 (p=0.013).
Model System: 46 participants during ANT task fMRI runs
Statistical Significance: DAN Factor 3: Session 1 p=0.023, Session 2 p=0.107; Orienting: Session 2 p=0.013
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Change in dynamic connectivity predicting behavioral change
Increase in DAN Factor 3 between sessions correlated with improvement in accuracy in Incongruent Flanker condition (r=0.37, p=0.011). Increase in FPTC Factor 3 correlated with improvement in Incongruent (r=0.39, p=0.007) and Center Cue conditions (r=0.32, p=0.027).
Model System: Longitudinal: Session 1 to Session 2 change in same 46 participants
Statistical Significance: DAN Factor 3: r(44)=0.37, p=0.011; FPTC Factor 3 Incongruent: r(44)=0.39, p=0.007; FPTC Factor 3 Center Cue: r(44)=0.32, p=0.027
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Disease Vulnerability
- [Parkinson's Disease](/diseases/parkinsons-disease)
- [Alzheimer's Disease](/diseases/alzheimers-disease)
- [Frontotemporal Dementia](/diseases/frontotemporal-dementia)
Research Evidence
Dynamic functional connectivity measures are more reliable than stationary connectivity measures in attention networks
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Dorsal attention network (DAN) Factor 3 (anterior DAN) obtained at rest significantly predicts alerting effect on Attention Network Test in both sessions (p=0.001 and p=0.037)
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Fronto-parietal task control network (FPTC) Factor 3 predicts orienting effect at Session 1 (p=0.010)
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
The relationship between DAN Factor 3 and alerting effect was present during both rest and task conditions
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Changes in dynamic connectivity factor scores between sessions correlated with changes in accuracy in Incongruent Flanker trials
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Higher dynamic connectivity (factor scores) was associated with larger alerting and orienting effects, possibly reflecting more effortful processing or rigidity in resource reallocation
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
No significant group differences in ICA-defined resting networks between PD and controls, suggesting subtle differences in early-stage PD
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Dynamic connectivity factor structures are stable across rest and task states (Procrustes congruence 0.89-0.93 for DAN)
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Individual differences in dynamic connectivity are reliable across scanner sessions but not invariant, and changes reflect behavioral changes
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Attention Network Test (ANT) behavioral performance measurement
PD participants showed slowed response latencies across all conditions. PD participants had significantly larger alerting effect (No Cue - Center Cue) compared to controls (PD: 47ms vs Controls: 28ms, p=0.025). No significant differences in orienting or executive effects between groups.
Model System: Human participants: 25 Parkinson disease (PD) patients and 21 healthy controls (ages 41-86)
Statistical Significance: p = 0.025 for alerting effect difference between groups
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
ICA analysis of resting-state networks
Identified dorsal attention network (DAN), salience network, and default mode network (DMN). No significant group differences found between PD and controls in these networks.
Model System: Human participants: 25 PD patients and 21 controls undergoing resting-state fMRI
Statistical Significance: No significant group differences (p > 0.05 after correction)
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Dynamic connectivity factor analysis
Extracted 4 factors for each network (DAN, FPTC, DMN). Factor structures were qualitatively similar to previous aging sample but explained less variance in this sample. Reliability of factor scores was higher than reliability of individual pairwise correlations.
Model System: Human participants: 25 PD and 21 controls during resting-state fMRI scans
Statistical Significance: DAN factor reliability 0.56-0.64, FPTC 0.35-0.69, DMN 0.57-0.78 (all p < 0.01 except FPTC Factor 4 p=0.01)
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Reliability comparison: dynamic vs stationary connectivity
Dynamic connectivity measures are more reliable than stationary connectivity measures. Median reliability of factor scores higher than median reliability of pairwise correlations for DAN (p=0.020) and DMN (p=0.036). FPTC showed marginally significant difference (p=0.082).
Model System: Same 46 participants in resting-state fMRI
Statistical Significance: DAN: p=0.020, DMN: p=0.036, FPTC: p=0.082
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Prediction of alerting effect from resting-state dynamic connectivity
DAN Factor 3 (anterior DAN) significantly predicted alerting effect magnitude at both sessions (Session 1: p=0.001, R2=0.21; Session 2: p=0.037, R2=0.09). Effect remained significant after controlling for age. Group-by-factor interaction significant at Session 1 (p=0.002) but not Session 2.
Model System: 46 participants (25 PD, 21 controls) from resting-state scans to ANT performance
Statistical Significance: Session 1: t(44)=3.46, p=0.001; Session 2: t(44)=2.15, p=0.037; Group x Factor interaction Session 1: p=0.002
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Prediction of orienting effect from resting-state dynamic connectivity
FPTC Factor 3 predicted orienting effect at Session 1 (p=0.010) but not Session 2 (p=0.116). No significant group or group-by-factor interaction.
Model System: 46 participants from resting-state scans to ANT orienting effect
Statistical Significance: Session 1: t(44)=2.70, p=0.010; Session 2: t(44)=1.6, p=0.116
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Task-based dynamic connectivity analysis
DAN factor structure during task highly congruent with rest (Procrustes correlation 0.93 Session 1, 0.89 Session 2, p=0.001). DAN Factor 3 during tasks predicted alerting effect (Session 1: p=0.023, R2=0.11; Session 2: p=0.107). During tasks, DAN Factor 3 also negatively predicted orienting effect at Session 2 (p=0.013).
Model System: 46 participants during ANT task fMRI runs
Statistical Significance: DAN Factor 3: Session 1 p=0.023, Session 2 p=0.107; Orienting: Session 2 p=0.013
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
Change in dynamic connectivity predicting behavioral change
Increase in DAN Factor 3 between sessions correlated with improvement in accuracy in Incongruent Flanker condition (r=0.37, p=0.011). Increase in FPTC Factor 3 correlated with improvement in Incongruent (r=0.39, p=0.007) and Center Cue conditions (r=0.32, p=0.027).
Model System: Longitudinal: Session 1 to Session 2 change in same 46 participants
Statistical Significance: DAN Factor 3: r(44)=0.37, p=0.011; FPTC Factor 3 Incongruent: r(44)=0.39, p=0.007; FPTC Factor 3 Center Cue: r(44)=0.32, p=0.027
[Madhyastha et al., (2015)](https://doi.org/10.1089/brain.2014.0248)
References
- [Prefrontal Cortex](/brain-regions/prefrontal-cortex)
- Brainstem
- Parkinson'- Executive Function Pathway
External Links
- [BrainMaps Project- [Neuroscience Literature](https://pubmed.ncbi.nlm.nih.gov/)
- [Allen Brain Atlas](https://brain-map.org/)
Pathway Diagram
The following diagram shows the key molecular relationships involving Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons discovered through SciDEX knowledge graph analysis:
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| kg_node_id | None |
| entity_type | cell |
| origin_type | v1_polymorphic_backfill |
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| __merged_from | {'merged_at': '2026-05-13', 'unprefixed_id': 'cell-types-dorsolateral-prefrontal-cortex-pyramidal-neurons'} |
| _schema_version | 1 |
No provenance edges found
Use ?embed=1 to load the artifact without SciDEX chrome — suitable for iframing into wiki pages or external sites.
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[Dorsolateral Prefrontal Cortex (DLPFC) Pyramidal Neurons](http://scidex.ai/artifact/wiki-cell-types-dorsolateral-prefrontal-cortex-pyramidal-neurons)
http://scidex.ai/artifact/wiki-cell-types-dorsolateral-prefrontal-cortex-pyramidal-neurons