Efficient Coding in the Economics of Human Brain Connectomics

AbstractIn systems neuroscience, most models posit that brain regions communicate information under constraints of efficiency. Yet, metabolic and information transfer efficiency across structural networks are not understood. In a large cohort of youth, we find metabolic costs associated with structural path strengths supporting information diffusion. Metabolism is balanced with the coupling of structures supporting diffusion and network modularity. To understand efficient network communication, we develop a theory specifying minimum rates of message diffusion that brain regions should transmit for an expected fidelity, and we test five predictions from the theory. We introduce compression efficiency, which quantifies differing trade-offs between lossy compression and communication fidelity in structural networks. Compression efficiency evolves with development, heightens when metabolic gradients guide diffusion, constrains network complexity, explains how rich-club hubs integrate information, and correlates with cortical areal scaling, myelination, and speed-accuracy trade-offs. Our findings elucidate how network structures and metabolic resources support efficient neural communication.

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Efficient Coding in the Economics of Human Brain Connectomics

Network Neuroscience ◽

10.1162/netn_a_00223 ◽

2021 ◽

pp. 1-65

Author(s):

Dale Zhou ◽

Christopher W. Lynn ◽

Zaixu Cui ◽

Rastko Ciric ◽

Graham L. Baum ◽

...

Keyword(s):

Random Walk ◽

Structural Connectivity ◽

Brain Regions ◽

Lossy Compression ◽

Hierarchical Organization ◽

Network Efficiency ◽

Compression Efficiency ◽

Efficient Coding ◽

Trade Offs ◽

Structural Networks

Abstract In systems neuroscience, most models posit that brain regions communicate information under constraints of efficiency. Yet, evidence for efficient communication in structural brain networks remains sparse. The principle of efficient coding proposes that the brain transmits maximal information in a metabolically economical or compressed form to improve future behavior. To determine how structural connectivity supports efficient coding, we develop a theory specifying minimum rates of message transmission between brain regions to achieve an expected fidelity, and we test five predictions from the theory based on random walk communication dynamics. In doing so, we introduce the metric of compression efficiency, which quantifies the trade-off between lossy compression and transmission fidelity in structural networks. In a large sample of youth (n = 1,042; age 8–23 years), we analyze structural networks derived from diffusion weighted imaging and metabolic expenditure operationalized using cerebral blood flow. We show that structural networks strike compression efficiency trade-offs consistent with theoretical predictions. We find that compression efficiency prioritizes fidelity with development, heightens when metabolic resources and myelination guide communication, explains advantages of hierarchical organization, links higher input fidelity to disproportionate areal expansion, and shows that hubs integrate information by lossy compression. Lastly, compression efficiency is predictive of behavior—beyond the conventional network efficiency metric—for cognitive domains including executive function, memory, complex reasoning, and social cognition. Our findings elucidate how macroscale connectivity supports efficient coding, and serve to foreground communication processes that utilize random walk dynamics constrained by network connectivity.

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The Influence of Intrinsic Motivation on Decisions Between Actions

10.21203/rs.3.rs-1111413/v1 ◽

2021 ◽

Author(s):

Ignasi Cos ◽

Gustavo Deco ◽

Matthieu Gilson

Keyword(s):

Pupil Diameter ◽

Motor Adaptation ◽

Brain Regions ◽

Social Pressure ◽

Brain Dynamics ◽

Motor Behaviour ◽

Cortical Areas ◽

Trade Offs ◽

Speed Accuracy

Abstract Extensive research explains how pre-frontal cortical areas process explicit rewards, and how pre-motor and motor cortices are recipients of that processing to energize motor behaviour. However, the specifics of motor behaviour, decisions between actions and brain dynamics when driven by no explicit reward, remain poorly understood. Are patterns of decision and motor control altered wen performing under social pressure? Are the same brain regions that typically process explicit rewards also involved in this expression of motivation? To answer these questions, we designed a novel task of decision-making between precision reaches and manipulated motivation by means of social pressure, defined by the presence or absence of virtual partner of a higher/lower aiming skill than our participants. We assessed the overall influence of this manipulation by analysing movements, decisions, pupil dilation and electro-encephalography. We show that the presence of a partner consistently increased aiming accuracy along with pupil diameter, furthermore the more skilled the partner. Remarkably, increased accuracy is attained by faster movements, consistently with a vigour effect that breaches speed-accuracy trade-offs typical of motor adaptation. This implicated an ensemble of cortical sources including pre-frontal areas, concerned with the processing of reward, but also pre-motor and occipital sources, consistent with the nature of the task. Overall, these results strongly suggest the role of social pressure as a motivational drive, enabling an increase of both vigour and accuracy in a non-trivial fashion.

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Dual Goals for Speed and Accuracy on the Same Performance Task

Journal of Personnel Psychology ◽

10.1027/1866-5888/a000063 ◽

2012 ◽

Vol 11 (3) ◽

pp. 118-126 ◽

Cited By ~ 3

Author(s):

Olive Emil Wetter ◽

Jürgen Wegge ◽

Klaus Jonas ◽

Klaus-Helmut Schmidt

Keyword(s):

Memory Scanning ◽

Performance Task ◽

Performance Tasks ◽

Trade Off ◽

Test Experiment ◽

Trade Offs ◽

New Finding ◽

Sternberg Paradigm ◽

Speed Accuracy ◽

Speed And Accuracy

In most work contexts, several performance goals coexist, and conflicts between them and trade-offs can occur. Our paper is the first to contrast a dual goal for speed and accuracy with a single goal for speed on the same task. The Sternberg paradigm (Experiment 1, n = 57) and the d2 test (Experiment 2, n = 19) were used as performance tasks. Speed measures and errors revealed in both experiments that dual as well as single goals increase performance by enhancing memory scanning. However, the single speed goal triggered a speed-accuracy trade-off, favoring speed over accuracy, whereas this was not the case with the dual goal. In difficult trials, dual goals slowed down scanning processes again so that errors could be prevented. This new finding is particularly relevant for security domains, where both aspects have to be managed simultaneously.

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Effect of Multishell Diffusion MRI Acquisition Strategy and Parcellation Scale on Rich-Club Organization of Human Brain Structural Networks

Diagnostics ◽

10.3390/diagnostics11060970 ◽

2021 ◽

Vol 11 (6) ◽

pp. 970

Author(s):

Maedeh Khalilian ◽

Kamran Kazemi ◽

Mahshid Fouladivanda ◽

Malek Makki ◽

Mohammad Sadegh Helfroush ◽

...

Keyword(s):

Human Brain ◽

Clustering Coefficient ◽

Quality Data ◽

B Values ◽

Rich Club ◽

Global Efficiency ◽

Acquisition Strategy ◽

The Rich ◽

Structural Networks ◽

Single Shell

The majority of network studies of human brain structural connectivity are based on single-shell diffusion-weighted imaging (DWI) data. Recent advances in imaging hardware and software capabilities have made it possible to acquire multishell (b-values) high-quality data required for better characterization of white-matter crossing-fiber microstructures. The purpose of this study was to investigate the extent to which brain structural organization and network topology are affected by the choice of diffusion magnetic resonance imaging (MRI) acquisition strategy and parcellation scale. We performed graph-theoretical network analysis using DWI data from 35 Human Connectome Project subjects. Our study compared four single-shell (b = 1000, 3000, 5000, 10,000 s/mm2) and multishell sampling schemes and six parcellation scales (68, 200, 400, 600, 800, 1000 nodes) using five graph metrics, including small-worldness, clustering coefficient, characteristic path length, modularity and global efficiency. Rich-club analysis was also performed to explore the rich-club organization of brain structural networks. Our results showed that the parcellation scale and imaging protocol have significant effects on the network attributes, with the parcellation scale having a substantially larger effect. Regardless of the parcellation scale, the brain structural networks exhibited a rich-club organization with similar cortical distributions across the parcellation scales involving at least 400 nodes. Compared to single b-value diffusion acquisitions, the deterministic tractography using multishell diffusion imaging data consisting of shells with b-values higher than 5000 s/mm2 resulted in significantly improved fiber-tracking results at the locations where fiber bundles cross each other. Brain structural networks constructed using the multishell acquisition scheme including high b-values also exhibited significantly shorter characteristic path lengths, higher global efficiency and lower modularity. Our results showed that both parcellation scale and sampling protocol can significantly impact the rich-club organization of brain structural networks. Therefore, caution should be taken concerning the reproducibility of connectivity results with regard to the parcellation scale and sampling scheme.

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Disrupted rich-club organization of brain structural networks in Parkinson’s disease

Brain Structure and Function ◽

10.1007/s00429-021-02319-3 ◽

2021 ◽

Author(s):

Tiantian Liu ◽

Yan Yan ◽

Jing Ai ◽

Duanduan Chen ◽

Jinglong Wu ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Rich Club ◽

Structural Networks

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Evidence from cluster analysis for differentiation of antisaccade performance groups based on speed/accuracy trade-offs

International Journal of Psychophysiology ◽

10.1016/j.ijpsycho.2012.03.008 ◽

2012 ◽

Vol 85 (2) ◽

pp. 274-277 ◽

Cited By ~ 4

Author(s):

Qingyang Li ◽

Michael T. Amlung ◽

Manouela Valtcheva ◽

Jazmin Camchong ◽

Benjamin P. Austin ◽

...

Keyword(s):

Cluster Analysis ◽

Trade Offs ◽

Speed Accuracy

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Playing With BEARS: Balancing Effort, Accuracy, and Response Speed in a Semantic Feature Verification Anomia Treatment Game

Journal of Speech Language and Hearing Research ◽

10.1044/2021_jslhr-20-00543 ◽

2021 ◽

pp. 1-27

Author(s):

William S. Evans ◽

Robert Cavanaugh ◽

Yina Quique ◽

Emily Boss ◽

Jeffrey J. Starns ◽

...

Keyword(s):

Treatment Outcomes ◽

Retrieval Practice ◽

Single Case ◽

Case Series ◽

Response Speed ◽

Semantic Feature ◽

System Calibration ◽

Trade Offs ◽

Practice Efficiency ◽

Speed Accuracy

Purpose The purpose of this study was to develop and pilot a novel treatment framework called BEARS (Balancing Effort, Accuracy, and Response Speed). People with aphasia (PWA) have been shown to maladaptively balance speed and accuracy during language tasks. BEARS is designed to train PWA to balance speed–accuracy trade-offs and improve system calibration (i.e., to adaptively match system use with its current capability), which was hypothesized to improve treatment outcomes by maximizing retrieval practice and minimizing error learning. In this study, BEARS was applied in the context of a semantically oriented anomia treatment based on semantic feature verification (SFV). Method Nine PWA received 25 hr of treatment in a multiple-baseline single-case series design. BEARS + SFV combined computer-based SFV with clinician-provided BEARS metacognitive training. Naming probe accuracy, efficiency, and proportion of “pass” responses on inaccurate trials were analyzed using Bayesian generalized linear mixed-effects models. Generalization to discourse and correlations between practice efficiency and treatment outcomes were also assessed. Results Participants improved on naming probe accuracy and efficiency of treated and untreated items, although untreated item gains could not be distinguished from the effects of repeated exposure. There were no improvements on discourse performance, but participants demonstrated improved system calibration based on their performance on inaccurate treatment trials, with an increasing proportion of “pass” responses compared to paraphasia or timeout nonresponses. In addition, levels of practice efficiency during treatment were positively correlated with treatment outcomes, suggesting that improved practice efficiency promoted greater treatment generalization and improved naming efficiency. Conclusions BEARS is a promising, theoretically motivated treatment framework for addressing the interplay between effort, accuracy, and processing speed in aphasia. This study establishes the feasibility of BEARS + SFV and provides preliminary evidence for its efficacy. This study highlights the importance of considering processing efficiency in anomia treatment, in addition to performance accuracy. Supplemental Material https://doi.org/10.23641/asha.14935812

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