Network Neuroscience: Sorted Tags (Keywords): Systems_Neurology , Network_Neuroscience: Human_brain, Neurology, Complexity, Complexity_Theory, Complexity_Profiling_Chart, CPC, neurons, neuronal_population, higher_functions, systems, complexity, emergence, evolve, clustering, connectivity, networks, lattice_networks, community_networks, smallworld_networks, hierarchy_networks, hub_networks, VSCS_networks, Integrative_networks, space_networks.

1. Very-Important Very-Draft SLIDES
!!
Systems Neurology Ver 1.0 August 17th 2023 HABIB’s Complexity 3D Perspective Eng. Emad Farag HABIB
Eng. Emad Farag HABIB
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2. Systems Neurology Ver 1.0 August 17th 2023 HABIB’s Complexity 3D Perspective Eng. Emad Farag HABIB
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3. Systems Neurology Ver 1.0 August 17th 2023 HABIB’s Complexity 3D Perspective Eng. Emad Farag HABIB
Network-Neuroscience LargeScale-Networks Terminology :
Very-Important Very-Draft ! TERMS : Concerns Mainly : [ Neurolists/ ICT, AI, Network Engineers ] : 20230800 Eng. Emad Farag HABIB (NTX.n) / Rivals: Will EDIT Such
ITEM SET NOTABLE NOTIONS LISTS NOTES
n what? (Definitional) sets: Nodes
(Common) sets: Structures
Resulting Set Name[Nd./ Str.]
Notion(s) Related Notions Lists & Dualities Fn [Y/N/Sub/NA] = [ Same Fn/Different Fn/ Sub Fn/ Not Applicable] , Fn=Meso not Macro : the "Set"
Math. Notes Akas Details Notes Ref: & Notes
Basics:
n Edges Path, Route - Path, Route 2: Graph=[Node/ Edge] ~ Series (or Loop) of n Edges/ Graph "Transverse" or browse Preliminary RESEARCH Conce
n Neurons Node Nd Node Connectivity-based Ensemble
n: Node=[Neuron1/ Neuron2/ Neuron3/ ..]
(2 Nodes + 1 Edge)
Tuple (Simple) - Tuple= Conn. 3: Tuple=[Node1-Edge-Node2] (2 Nodes ONLY + 1 Edge ONLY)
(N. ENSEMBLES Layers)
Many Different Possible Ensembles (6)
- Ensembles (Gen.) 2 Notions: [[[ Ensemble= Grouping, Subsystem / Layers: =[Nestedness/ Hierarchical/ Inclusion-Embedding] ]]]
6: [Neurons --> Nodes --> Communities --> Hubs (and Akas) --> Large-scale Networks --> Spatial Integration (Whole Brain)]
Ensemble & Grouping: on NOD
Standard Ensembles:
n Edges/ m Nodes Random Str. (theoretical) Randomity of conn. - (NA) n Edges/ m Nodes w/o any REGULARITY
n Nodes Cluster Str. Dense Conn. Amid sparseIntra/Inter Conn. 2: [Denesly Conn. Internally/ Sparsley Conn. Externaly]
~Y local Conn. > Regional Conn. aka: ~Set, ~Population, “ Neural unit” aka: M odule! (VIM P, NOT M o
n Nodes Community Str. Fn! Conn. 2 Notions: [[[ Similar Conn. Pattern/ Dissimilar Fn ]]]
2: [Conn./ Fn ] ~N p=Node.Community.Assignment : Stochastic: stochastic block model
aka: ~Set, ~Population, “ Neural unit”
VIM P: Same Connectivity-pattern, Different Fn
n Tiers(Fns.) Hierarchical Str. No Transverse Conn. (between "non same-parent children" nodes)
Notion of Tiers 3: [Sup, Sib, Sub] (Sub Fn) No (Intra Links) / Tiers= Layers, Plies aka: Tree, M aster-details
Siblings are conn. only via (Parent Node) /
n Nodes/ Path Lattice Str. Lattice Str & Fn 2: [Neighbouring N./ Remote N.]
(Sub Fn) No (Intra Links)/ just to Neighbouring Nodes
aka: Ring, Loop, Crystal = n Community with ZERO Degree (Intra) !
n Paths/ Nodes Small-world Str. (Extra!) Parallel Conn. Relates to Intelligence "Individual Differences"/ Economoy of Connectivity
2: [uni-conn/ n-conn] to same Nodes!
(Sub Fn) (Intra Links) / n Paths for Same Nodes aka: SW, Shortcut ! Very Common in many Brain Fn
n Community Hub(Gen) Nd. Highly Connected Node Conn. Degree 3: [Hub(Gen.)/ Rich Club Hub/ Core Hub]
High Degree per node (Generally)
n Community Hub[Provincial/ Connector] Nd. Ditto, Location Provincial/ Universal
2: [Provincial H./ Connector H.] (ditto) (Generally) Ref: DOC8 "M odular Brain Ne
n Community Core(Gap) Nd. D3+ - (Intra Links) : Degree>2 Core aka: Gap ! VIM P: Same Connectivity-pattern, Different Fn
n Community Rich Club Nd. D4+ - (Intra Links) : Degree>3
n Community Core–periphery Str. n Communities forming a Str.
Forming (Attatchment) Mechanism: preferential !! (for high degree nodes)
5: * (Nodes)/ Communities/ Cores(Gaps)/ Peripheries/ Core–periphery +, simpler to Complexer!
Fairly Y Stats: heavy-tailed degree distribution aka: Hub-str !! ( though there is NOTING called Hub-str )
VIM P: very suggestive of a scale-free networks
Ref: DOC7
n Hubs/Communities Large-scale Network Str. Large-scale Ensemble - Fairly N (Generally) aka: LSN: Usually: dedicated to SAM E Fn
n (overall Fn) ! / 1 Str. VSCS Str. Variable System-str - N Same (Whole Structure) performs n Overall Fns !
Variable-Structure Control-System
n Large-scale Networks Spatial Integration Str. Full-scale Ensemble Max Balance [FEP-AI]
- Sure N (remote, distant, Spatial) conn. Of n Large-scale Ns.
aka: Global Integration PATHOLOGY: most VULNERA
(Higher ??} ?? Str. ?? - cf "Theory of Human Intelligence { 201
8 }" : "ou
Advanced Ensembles:
n times Dynamic N. Str. Dynamics and Time-change n points in Time Y
n Layers(Anat.) Multi-layers, Spatial Str. non 2D 3: [X,Y,Z] 3D not "n Tiers(Fns.)"
n (info) ! Inference - Information InstantiationConsciousness!, Subjectivity
3: [a-priori/ likelihood/ a-posteriori]
Y Bayesian Inf.: Instance, Mirror, Copy, Representation
aka: shortcut! (as a copy, not an "economic route")
Misc. & Research Frontiers Ensembles:
n Nodes: Combinatorial
Combinatorial PATTERN Codeing - ~Distributed Info Storage!Pattern Storage - Y? Info is coded ! : represents some PATTERN APP.: usually for Sensory Inform
Reciprocal Action (2 Nodes)
[Agonist/Antagonist], Excitatory/Inhibitory, Reciprocal
- Reciprocity: Excite/InhibitRhythmic, Periodic, Oscillation, via Agonism/Antagonism
2: [Agonist/Antagonist] Y (Abstract): Coupled, Duality, Reciprocal,
aka: [Agonist/Antagonist], Excitatory/Inhibitory: reverb, ..
[basis for: rhythmic, periodic functions and beh
Re: DOC2
n (nodes/Tuple) Simplical Complex - meta (2-nodes , 1-edge) 9: *** DAG.Edges // Parecellation (~ROI , ~Sub CNS.BA ,) // Clique Complex (coactivity patterns ) // Adjancy Matrix // “Concurre
n>2 : ( "Polyadic" VS Dyads ) Tuples aka: clique topology, Clique Complex, M eta-Dyads // aka: “ Concurrenc
Violate Standard definition of "Tuple" // many s
n (Nodes/Edge) HyperGraph - meta (node^edge^node) - n>2 : ( multi-noded edge VS bi-noded edge ) Violate Standard definition of "Edge"
n Edges Community!
eFC framework - Edges Ensemble !! opposite to all of the above
- (~ Parallel n Edges) : EDGE "Functional Connectivety" VS Node "Functional Connectivet
Brain regions NOT assign to only one commun
But not ONLY Edges (cf "Preli
Abbrev.: n=many / Nt. Network & Ensemble, Nd.Node (not neuron!) / Str. Structure, Fn: Function/ Anatomical, Structural/ aka: also-known-as/ Gen. General (not Generative)/ Conn Connectivity, Connections/ VS Versus
ICT: Info Comm Tech/
FEP-AI: Free-Energy Principle - Active Inference // DAG: Directed Acyclic Graph//

4. Systems Neurology Ver 1.0 August 17th 2023 HABIB’s Complexity 3D Perspective Eng. Emad Farag HABIB
ADDENDUM ! , Non-expected! : (Meta Frontiers) : 0902 / / 0904: cf "POSTPONE it ALL"
TIMESCALES: Ensemble's Formation: TIMESCALES: millisecoonds to decades !
Balances, Compromises: [[[ [robustness VS performance] // NTX.Taxonomy: 2D: [permeability index / control centrality] { cf: NTX.Taxo
LEARNING, Reorg: TYPES = MATURITY PHASES 3: [trial and-error/ association/ systematic learning (int + ext) ]
~ Common-sense, Co-Existances:
[[[ Modularity & Modulity // Synchrony & Similarity !! // .. ]]]
Multi-Factorial, n Dep: [[[ network controllability centrality = [ controllability degree X interconnection strength ] // Energy Scaling law
~Counter-intuitives? : [[[ CMX.MDLT.Hi = simple tasks VS CMX.MDLT.Low = complex tasks /// NTX.CMX.Control: sparse, inhomogene
CONTROL!: ( aka: "Science.Goals3" )
SUMMARY: issues // DETAILS: issues
Analytical & Math : [[[ ODE, PDE / State Space, System Matrix, .. / Linear Programming/
VIMP: VIMP: ~Pan-NTX.Types VIMP: VIMP: ~Pan-NTX.Types !!!: [[[ Food Webs/ Metabolic networks/ Social n/ Citation n/ Protein str n/ Electr
OTHER, Theoretical : [[[ Sciences: wrt each other! //