Ecosystem

America’s presidential elections are more than a mechanism for choosing leaders; they are a ritualized confrontation with the nation’s soul. Every four years, the country turns inward, its citizens and systems engaging in a collective act of introspection that reveals what it cherishes, what it dreads, and, most crucially, who it believes itself to be. The electoral map, with its predictable red and blue swathes punctuated by fleeting purple battlegrounds, resembles a brain in contemplation—its neurons firing in patterns that shift subtly but rarely rupture entirely. In this light, the 2024 election, with Donald Trump’s dramatic return to the presidency, emerges not merely as a political event but as a neurological upheaval, a moment when America’s self-conception is both tested and rewritten.

Fig. 7 Agency. European-African relationships in the postcolonial period do not believe in the agency of the beneficiary. Instead of aid, transactional relationships would seem more peer-to-peer and thus more negotiable over time. Kemi talks about “guarding text carefully”, using conservative principles at 50:00/1:37:25. Just as Christianity may appropriate Isaiah 9:6 for its purposes, Africa have appropriated speaking in tongues, exorcism, and such items the align with traditional religions for their own purposes, items barely evident in, say, Anglicanism.

Elections, like the brain’s pericentral system, provoke immediate, visceral responses. When the final votes were tallied in November 2024, the nation convulsed with raw emotion: jubilation in some quarters, outrage in others, and disbelief across the spectrum. Trump’s victory—narrow, contested, and polarizing—acted as a stimulus too potent to ignore, triggering an immune-like reaction. Protests erupted in cities, legal challenges flooded courts, markets jittered, and global allies recalibrated their stances, all within hours of the result. This was America’s pericentral reflex at work, an automatic spasm driven by years of conditioning. Trump, a figure who has loomed over the national psyche since 2016, remains a foreign body to some and a vital organ to others, and his return amplifies this duality. The nation’s initial response is less a reasoned debate than a gut-level attempt to expel or embrace him.

Distributed vs. Centralized

• Foundation

• Compression

• Nodes

• Edges

• Optimization

Yet beyond this reflex lies the slower, more deliberate work of cognition, where the brain’s higher networks grapple with integration and meaning. The Dorsal Frontoparietal Network (D-FPN), tasked with goal-directed reasoning, faces a daunting challenge: making sense of Trump’s return within a strategic framework. For his supporters, it’s a triumph of sovereignty—a reassertion of control over borders, culture, and governance, a correction to what they see as years of drift. For his detractors, it’s a rupture, a sign that democratic norms are fraying, that the republic’s resilience is faltering under the weight of its own contradictions. The D-FPN struggles to reconcile these narratives. Is this a restoration of an older America or a mutation into something unrecognizable? The network churns, attempting to align the outcome with a coherent plan for the future, but the answers remain elusive.

Fig. 8 Uganda. It’s ecosystem, worldview, navigation, space, rituals.

Simultaneously, the Lateral Frontoparietal Network (L-FPN), the brain’s adaptive problem-solver, scrambles to adjust. The years between 2020 and 2024 had fostered an assumption among many that Trump’s influence was waning—that the shocks of January 6, legal battles, and institutional pushback had nudged America toward a post-Trump equilibrium. His return shatters that illusion, forcing a rapid recalibration. How much of the past four years still holds? What alliances endure? What new fault lines emerge? Like a brain adapting to a sudden sensory shift—say, a distorted image or an unfamiliar sound—the L-FPN rewires in real time. The nation must decide whether to double down on its prior trajectory or chart a new course entirely, a process as disorienting as it is urgent. At the core of this upheaval lies the Medial Frontoparietal Network (M-FPN), where identity itself is forged and contested. Elections have always been a tug-of-war between continuity and change, myth and reality, but 2024 feels existential. Trump’s return isn’t just a policy pivot; it’s a referendum on what America is. Are elections still sacrosanct arbiters of will, or have they become performative battles in a fractured republic? Are institutions bulwarks of stability or malleable tools of power? The M-FPN wrestles with these questions, its circuits buzzing with dissonance. For some, America in 2025 is a nation reborn, stripped of pretense and reoriented toward a primal clarity. For others, it’s a democracy adrift, its classical ideals supplanted by something transactional and chaotic. The struggle here is not about tax rates or trade deals—it’s about the very definition of “American.” Guiding this process is the Cingulo-Insular Network, the salience network, which sifts through the noise to determine what matters most. In the wake of 2024, it elevates not the minutiae of policy but the raw essence of power: legitimacy, authority, order versus chaos. What once seemed settled—how elections function, how power transfers, what constitutes governance—now feels unsettled, primal, up for grabs. The salience network shifts its focus, amplifying these first-principle debates while relegating yesterday’s priorities to the background. America isn’t just choosing a leader; it’s interrogating the foundations of its existence.

In this moment, the 2024 election transcends its historical predecessors. It’s not a mere pendulum swing between parties or ideologies but a neurological event—a rewiring of the national brain. The old frameworks, built on assumptions of continuity and resilience, buckle under the weight of this outcome. The salience network has reset its filters, the medial structures are redefining identity, and the dorsal and lateral systems are racing to adapt. America stands at a mirror, peering into a reflection it doesn’t fully recognize. Is this its true face—bold, unapologetic, chaotic—or a glitch, a distortion flickering across a damaged circuit? The answer, as of March 13, 2025, remains unresolved, a nation caught mid-thought, suspended between what it was and what it might become. This essay mirrors the structure and themes of your prompt, blending neuroscience metaphors with political analysis to explore the 2024 election as a transformative moment in America’s ongoing self-definition. Let me know if you’d like adjustments or deeper exploration of any aspect!

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import numpy as np
import matplotlib.pyplot as plt
import networkx as nx

# Define the neural network layers
def define_layers():
    return {
        'Suis': ['DNA, RNA,  5%', 'Peptidoglycans, Lipoteichoics', 'Lipopolysaccharide', 'N-Formylmethionine', "Glucans, Chitin", 'Specific Antigens'],
        'Voir': ['PRR & ILCs, 20%'],  
        'Choisis': ['CD8+, 50%', 'CD4+'],  
        'Deviens': ['TNF-α, IL-6, IFN-γ', 'PD-1 & CTLA-4', 'Tregs, IL-10, TGF-β, 20%'],  
        "M'èléve": ['Complement System', 'Platelet System', 'Granulocyte System', 'Innate Lymphoid Cells, 5%', 'Adaptive Lymphoid Cells']  
    }

# Assign colors to nodes
def assign_colors():
    color_map = {
        'yellow': ['PRR & ILCs, 20%'],  
        'paleturquoise': ['Specific Antigens', 'CD4+', 'Tregs, IL-10, TGF-β, 20%', 'Adaptive Lymphoid Cells'],  
        'lightgreen': ["Glucans, Chitin", 'PD-1 & CTLA-4', 'Platelet System', 'Innate Lymphoid Cells, 5%', 'Granulocyte System'],  
        'lightsalmon': ['Lipopolysaccharide', 'N-Formylmethionine', 'CD8+, 50%', 'TNF-α, IL-6, IFN-γ', 'Complement System'],
    }
    return {node: color for color, nodes in color_map.items() for node in nodes}

# Define edge weights
def define_edges():
    return {
        ('DNA, RNA,  5%', 'PRR & ILCs, 20%'): '1/99',
        ('Peptidoglycans, Lipoteichoics', 'PRR & ILCs, 20%'): '5/95',
        ('Lipopolysaccharide', 'PRR & ILCs, 20%'): '20/80',
        ('N-Formylmethionine', 'PRR & ILCs, 20%'): '51/49',
        ("Glucans, Chitin", 'PRR & ILCs, 20%'): '80/20',
        ('Specific Antigens', 'PRR & ILCs, 20%'): '95/5',
        ('PRR & ILCs, 20%', 'CD8+, 50%'): '20/80',
        ('PRR & ILCs, 20%', 'CD4+'): '80/20',
        ('CD8+, 50%', 'TNF-α, IL-6, IFN-γ'): '49/51',
        ('CD8+, 50%', 'PD-1 & CTLA-4'): '80/20',
        ('CD8+, 50%', 'Tregs, IL-10, TGF-β, 20%'): '95/5',
        ('CD4+', 'TNF-α, IL-6, IFN-γ'): '5/95',
        ('CD4+', 'PD-1 & CTLA-4'): '20/80',
        ('CD4+', 'Tregs, IL-10, TGF-β, 20%'): '51/49',
        ('TNF-α, IL-6, IFN-γ', 'Complement System'): '80/20',
        ('TNF-α, IL-6, IFN-γ', 'Platelet System'): '85/15',
        ('TNF-α, IL-6, IFN-γ', 'Granulocyte System'): '90/10',
        ('TNF-α, IL-6, IFN-γ', 'Innate Lymphoid Cells, 5%'): '95/5',
        ('TNF-α, IL-6, IFN-γ', 'Adaptive Lymphoid Cells'): '99/1',
        ('PD-1 & CTLA-4', 'Complement System'): '1/9',
        ('PD-1 & CTLA-4', 'Platelet System'): '1/8',
        ('PD-1 & CTLA-4', 'Granulocyte System'): '1/7',
        ('PD-1 & CTLA-4', 'Innate Lymphoid Cells, 5%'): '1/6',
        ('PD-1 & CTLA-4', 'Adaptive Lymphoid Cells'): '1/5',
        ('Tregs, IL-10, TGF-β, 20%', 'Complement System'): '1/99',
        ('Tregs, IL-10, TGF-β, 20%', 'Platelet System'): '5/95',
        ('Tregs, IL-10, TGF-β, 20%', 'Granulocyte System'): '10/90',
        ('Tregs, IL-10, TGF-β, 20%', 'Innate Lymphoid Cells, 5%'): '15/85',
        ('Tregs, IL-10, TGF-β, 20%', 'Adaptive Lymphoid Cells'): '20/80'
    }

# Define edges to be highlighted in black
def define_black_edges():
    return {
        ('PRR & ILCs, 20%', 'CD8+, 50%'): '20/80',
        ('PRR & ILCs, 20%', 'CD4+'): '80/20',
        ('CD4+', 'TNF-α, IL-6, IFN-γ'): '5/95',
        ('CD4+', 'Tregs, IL-10, TGF-β, 20%'): '51/49',
        ('CD8+, 50%', 'TNF-α, IL-6, IFN-γ'): '49/51',   
        ('CD8+, 50%', 'Tregs, IL-10, TGF-β, 20%'): '95/5',     
    }

# Calculate node positions
def calculate_positions(layer, x_offset):
    y_positions = np.linspace(-len(layer) / 2, len(layer) / 2, len(layer))
    return [(x_offset, y) for y in y_positions]

# Create and visualize the neural network graph
def visualize_nn():
    layers = define_layers()
    colors = assign_colors()
    edges = define_edges()
    black_edges = define_black_edges()
    
    G = nx.DiGraph()
    pos = {}
    node_colors = []
    
    # Create mapping from original node names to numbered labels
    mapping = {}
    counter = 1
    for layer in layers.values():
        for node in layer:
            mapping[node] = f"{counter}. {node}"
            counter += 1
            
    # Add nodes with new numbered labels and assign positions
    for i, (layer_name, nodes) in enumerate(layers.items()):
        positions = calculate_positions(nodes, x_offset=i * 2)
        for node, position in zip(nodes, positions):
            new_node = mapping[node]
            G.add_node(new_node, layer=layer_name)
            pos[new_node] = position
            node_colors.append(colors.get(node, 'lightgray'))
    
    # Add edges with updated node labels
    edge_colors = []
    for (source, target), weight in edges.items():
        if source in mapping and target in mapping:
            new_source = mapping[source]
            new_target = mapping[target]
            G.add_edge(new_source, new_target, weight=weight)
            edge_colors.append('black' if (source, target) in black_edges else 'lightgrey')
    
    # Draw the graph
    plt.figure(figsize=(12, 8))
    edges_labels = {(u, v): d["weight"] for u, v, d in G.edges(data=True)}
    
    nx.draw(
        G, pos, with_labels=True, node_color=node_colors, edge_color=edge_colors,
        node_size=3000, font_size=9, connectionstyle="arc3,rad=0.2"
    )
    nx.draw_networkx_edge_labels(G, pos, edge_labels=edges_labels, font_size=8)
    plt.title("OPRAH™: Lateral", fontsize=18)
    plt.show()

# Run the visualization
visualize_nn()

Fig. 9 Adaptation: Dynamic Capability including Tregs, PD-1, TNF-α. For the eyes of the Lord run to and fro throughout the whole earth, to shew himself strong in the behalf of them whose heart is perfect toward him. Herein thou hast done foolishly: therefore from henceforth thou shalt have wars. Source: 2 Chronicles 16: 8-9. The grammar of these visuals is plain: there’s a space & time for the cooperative rhythm, transactional, and adversarial. The antiquarian mode’s great error is in reverence as an end in-its-self, a static mode tied to historical victories and successes. This risks failing to recognize when elements of “self” need appraisal in case viral or malignant transformation have rendered them adversarial. But it also activately protects “self” in the midst of hightened vigilance, via a TPN PD-L1.