An hypothesis about redundancy and reliability in the brains of higher species: analogies with genes, internal organs, and engineering systems

Age-related differences in network controllability are mitigated by redundancy in large-scale brain networks

The aging brain undergoes major changes in its topology. The mechanisms by which the brain mitigates age-associated changes in topology to maintain robust control of brain networks are unknown. Here we use diffusion MRI data from cognitively intact participants (n = 480, ages 40-90) to study age-associated differences in the average controllability of structural brain networks, topological features that could mitigate these differences, and the overall effect on cognitive function. We find age-associated declines in average controllability in control hubs and large-scale networks, particularly within the frontoparietal control and default mode networks. Further, we find that redundancy, a hypothesized mechanism of reserve, quantified via the assessment of multi-step paths within networks, mitigates the effects of topological differences on average network controllability. Lastly, we discover that average network controllability, redundancy, and grey matter volume, each uniquely contribute to predictive models of cognitive function. In sum, our results highlight the importance of redundancy for robust control of brain networks and in cognitive function in healthy-aging.

Information decomposition and the informational architecture of the brain

To explain how the brain orchestrates information-processing for cognition, we must understand information itself. Importantly, information is not a monolithic entity. Information decomposition techniques provide a way to split information into its constituent elements: unique, redundant, and synergistic information. We review how disentangling synergistic and redundant interactions is redefining our understanding of integrative brain function and its neural organisation. To explain how the brain navigates the trade-offs between redundancy and synergy, we review converging evidence integrating the structural, molecular, and functional underpinnings of synergy and redundancy; their roles in cognition and computation; and how they might arise over evolution and development. Overall, disentangling synergistic and redundant information provides a guiding principle for understanding the informational architecture of the brain and cognition.

Small vessel disease and cognitive reserve oppositely modulate global network redundancy and cognitive function: A study in middle-to-old aged community participants

Cerebral small vessel disease (SVD) can disrupt the global brain network and lead to cognitive impairment. Conversely, cognitive reserve (CR) can improve one's cognitive ability to handle damaging effects like SVD, partly by optimizing the brain network's organization. Understanding how SVD and CR collectively influence brain networks could be instrumental in preventing cognitive impairment. Recently, brain redundancy has emerged as a critical network protective metric, providing a nuanced perspective of changes in network organization. However, it remains unclear how SVD and CR affect global redundancy and subsequently cognitive function. Here, we included 121 community-dwelling participants who underwent neuropsychological assessments and a multimodal MRI examination. We visually examined common SVD imaging markers and assessed lifespan CR using the Cognitive Reserve Index Questionnaire. We quantified the global redundancy index (RI) based on the dynamic functional connectome. We then conducted multiple linear regressions to explore the specific cognitive domains related to RI and the associations of RI with SVD and CR. We also conducted mediation analyses to explore whether RI mediated the relationships between SVD, CR, and cognition. We found negative correlations of RI with the presence of microbleeds (MBs) and the SVD total score, and a positive correlation of RI with leisure activity-related CR (CRI-leisure). RI was positively correlated with memory and fully mediated the relationships between the MBs, CRI-leisure, and memory. Our study highlights the potential benefits of promoting leisure activities and keeping brain redundancy for memory preservation in older adults, especially those with SVD.

Accumulation of network redundancy marks the early stage of Alzheimer's disease

Brain wiring redundancy counteracts aging-related cognitive decline by reserving additional communication channels as a neuroprotective mechanism. Such a mechanism plays a potentially important role in maintaining cognitive function during the early stages of neurodegenerative disorders such as Alzheimer's disease (AD). AD is characterized by severe cognitive decline and involves a long prodromal stage of mild cognitive impairment (MCI). Since MCI subjects are at high risk of converting to AD, identifying MCI individuals is essential for early intervention. To delineate the redundancy profile during AD progression and enable better MCI diagnosis, we define a metric that reflects redundant disjoint connections between brain regions and extract redundancy features in three high-order brain networks-medial frontal, frontoparietal, and default mode networks-based on dynamic functional connectivity (dFC) captured by resting-state functional magnetic resonance imaging (rs-fMRI). We show that redundancy increases significantly from normal control (NC) to MCI individuals and decreases slightly from MCI to AD individuals. We further demonstrate that statistical features of redundancy are highly discriminative and yield state-of-the-art accuracy of up to 96.8 ± 1.0% in support vector machine (SVM) classification between NC and MCI individuals. This study provides evidence supporting the notion that redundancy serves as a crucial neuroprotective mechanism in MCI.

Age-related changes in network controllability are mitigated by redundancy in large-scale brain networks

The aging brain undergoes major changes in its topology. The mechanisms by which the brain mitigates age-associated changes in topology to maintain robust control of brain networks are unknown. Here we used diffusion MRI data from cognitively intact participants (n=480, ages 40-90) to study age-associated changes in the controllability of structural brain networks, features that could mitigate these changes, and the overall effect on cognitive function. We found age-associated declines in controllability in control hubs and large-scale networks, particularly within the and frontoparietal control and default mode networks. Redundancy, quantified via the assessment of multi-step paths within networks, mitigated the effects of changes in topology on network controllability. Lastly, network controllability, redundancy, and grey matter volume each played important complementary roles in cognitive function. In sum, our results highlight the importance of redundancy for robust control of brain networks and in cognitive function in healthy-aging.

The association between hippocampal volume and memory in pathological aging is mediated by functional redundancy

Hippocampal neurodegeneration, a primary component of Alzheimer's disease pathology, relates to poor cognition; however, the mechanisms underlying this relationship are not well understood. Using a sample of cognitively normal older adults and individuals with mild cognitive impairment, this study aims to determine the topological properties of functional networks accompanying hippocampal atrophy in aging, along with their association to cognition and clinical progression. We considered two conceptually differing topological properties: redundancy (the existence of alternative channels of functional commutation) and local efficiency (the efficiency of local information exchange). Hippocampal redundancy, but not local efficiency, mediated the association between low hippocampal volume and low memory in both the whole sample and in ß-amyloid positive participants. Additionally, participants with high hippocampal volume, redundancy, and memory clustered separately from those with low values on all three measures, with the latter group showing higher conversion rates to dementia within three years. Together, these results demonstrate that reduced hippocampal redundancy is one mechanism through which hippocampal atrophy associates with memory impairment in healthy and pathological aging.

A Computational Framework for Controlling the Self-Restorative Brain Based on the Free Energy and Degeneracy Principles

The brain is a non-linear dynamical system with a self-restoration process, which protects itself from external damage but is often a bottleneck for clinical treatment. To treat the brain to induce the desired functionality, formulation of a self-restoration process is necessary for optimal brain control. This study proposes a computational model for the brain's self-restoration process following the free-energy and degeneracy principles. Based on this model, a computational framework for brain control is established. We posited that the pre-treatment brain circuit has long been configured in response to the environmental (the other neural populations') demands on the circuit. Since the demands persist even after treatment, the treated circuit's response to the demand may gradually approximate the pre-treatment functionality. In this framework, an energy landscape of regional activities, estimated from resting-state endogenous activities by a pairwise maximum entropy model, is used to represent the pre-treatment functionality. The approximation of the pre-treatment functionality occurs via reconfiguration of interactions among neural populations within the treated circuit. To establish the current framework's construct validity, we conducted various simulations. The simulations suggested that brain control should include the self-restoration process, without which the treatment was not optimal. We also presented simulations for optimizing repetitive treatments and optimal timing of the treatment. These results suggest a plausibility of the current framework in controlling the non-linear dynamical brain with a self-restoration process.

A Case for 3D Integrated System Design for Neuromorphic Computing and AI Applications

Over the last decade, artificial intelligence (AI) has found many applications areas in the society. As AI solutions have become more sophistication and the use cases grew, they highlighted the need to address performance and energy efficiency challenges faced during the implementation process. To address these challenges, there has been growing interest in neuromorphic chips. Neuromorphic computing relies on non von Neumann architectures as well as novel devices, circuits and manufacturing technologies to mimic the human brain. Among such technologies, three-dimensional (3D) integration is an important enabler for AI hardware and the continuation of the scaling laws. In this paper, we overview the unique opportunities 3D integration provides in neuromorphic chip design, discuss the emerging opportunities in next generation neuromorphic architectures and review the obstacles. Neuromorphic architectures, which relied on the brain for inspiration and emulation purposes, face grand challenges due to the limited understanding of the functionality and the architecture of the human brain. Yet, high-levels of investments are dedicated to develop neuromorphic chips. We argue that 3D integration not only provides strategic advantages to the cost-effective and flexible design of neuromorphic chips, it may provide design flexibility in incorporating advanced capabilities to further benefit the designs in the future.

Accrual of functional redundancy along the lifespan and its effects on cognition

Despite the necessity to understand how the brain endures the initial stages of age-associated cognitive decline, no brain mechanism has been quantitatively specified to date. The brain may withstand the effects of cognitive aging through redundancy, a design feature in engineered and biological systems, which entails the presence of substitute elements to protect it against failure. Here, we investigated the relationship between functional network redundancy and age over the human lifespan and their interaction with cognition, analyzing resting-state functional MRI images and cognitive measures from 579 subjects. Network-wide redundancy was significantly associated with age, showing a stronger link with age than other major topological measures, presenting a pattern of accumulation followed by old-age decline. Critically, redundancy significantly mediated the association between age and executive function, with lower anti-correlation between age and cognition in subjects with high redundancy. The results suggest that functional redundancy accrues throughout the lifespan, mitigating the effects of age on cognition.

Lower functional hippocampal redundancy in mild cognitive impairment

With an increasing prevalence of mild cognitive impairment (MCI) and Alzheimer's disease (AD) in response to an aging population, it is critical to identify and understand neuroprotective mechanisms against cognitive decline. One potential mechanism is redundancy: the existence of duplicate elements within a system that provide alternative functionality in case of failure. As the hippocampus is one of the earliest sites affected by AD pathology, we hypothesized that functional hippocampal redundancy is protective against cognitive decline. We compared hippocampal functional redundancy derived from resting-state functional MRI networks in cognitively normal older adults, with individuals with early and late MCI, as well as the relationship between redundancy and cognition. Posterior hippocampal redundancy was reduced between cognitively normal and MCI groups, plateauing across early and late MCI. Higher hippocampal redundancy was related to better memory performance only for cognitively normal individuals. Critically, functional hippocampal redundancy did not come at the expense of network efficiency. Our results provide support that hippocampal redundancy protects against cognitive decline in aging.

Novel sensory paradigms for neuromodulation in disorders of consciousness in traumatic brain injury

PURPOSE OF REVIEW

Traumatic brain injury (TBI) represents a major cause of mortality and disability worldwide. In cases of severe TBI, disorders of consciousness (DoC) can occur and therapeutic options for these conditions are few and of limited efficacy. Sensory stimulation, an instrument to improve arousal and awareness, is frequently applied in the neurorehabilitation of DoC, but scientific evidence supporting its efficacy is limited. Our aim is to review the recent literature concerning novel sensory paradigms used in sensory stimulation protocols in DoC following TBI.

RECENT FINDINGS

Recent studies on sensory stimulation have investigated different types of stimulation protocols, focusing on the issue of how to demonstrate that improvements are related to the treatment applied and not to spontaneous recovery. Moreover, these studies have also shown that paraclinical tests should be useful not only to discover signs of awareness when behavioural assessment fails to do so, but also to measure the effects of sensory stimulation.

SUMMARY

Future studies about novel types of sensory stimulation, whose effects should be possibly measured through paraclinical approaches, are recommended in order to increase the probability that the proper individualized stimulation is administered for each patient.

Advancing System Performance with Redundancy: From Biological to Artificial Designs

Redundancy is a fundamental characteristic of many biological processes such as those in the genetic, visual, muscular, and nervous systems, yet its driven mechanism has not been fully comprehended. Until recently, the only understanding of redundancy is as a mean to attain fault tolerance, which is reflected in the design of many man-made systems. On the contrary, our previous work on redundant sensing (RS) has demonstrated an example where redundancy can be engineered solely for enhancing accuracy and precision. The design was inspired by the binocular structure of human vision, which we believe may share a similar operation. In this letter, we present a unified theory describing how such utilization of redundancy is feasible through two complementary mechanisms: representational redundancy (RPR) and entangled redundancy (ETR). We also point out two additional examples where our new understanding of redundancy can be applied to justify a system's superior performance. One is the human musculoskeletal system (HMS), a biological instance, and the other is the deep residual neural network (ResNet), an artificial counterpart. We envision that our theory would provide a framework for the future development of bio-inspired redundant artificial systems, as well as assist studies of the fundamental mechanisms governing various biological processes.

The promise and perils of causal circuit manipulations

The development of increasingly sophisticated methods for recording and manipulating neural activity is revolutionizing neuroscience. By probing how activity patterns in different types of neurons and circuits contribute to behavior, these tools can help inform mechanistic models of brain function and explain the roles of distinct circuit elements. However, in systems where functions are distributed over large networks, interpreting causality experiments can be challenging. Here we review common assumptions underlying circuit manipulations in behaving animals and discuss the strengths and limitations of different approaches.

Intracranial volume and dementia: some evidence in support of the cerebral reserve hypothesis

The brain reserve hypothesis has been posited as being one important mediating factor for developing dementia, especially Alzheimer's disease (AD). Evidence for this hypothesis is mixed though different methodologies have made these findings difficult to interpret. We examined imaging data from a large cohort (N=194) of mixed dementia patients and controls, 65years old and older from the Cache County, Utah Study of Memory and Aging for evidence of the brain reserve hypothesis using total intracranial volume (TICV) as a quantitative measure of pre-morbid brain size and a vicarious indicator of reserve. A broader spectrum of non-demented elderly control subjects from previous studies was also included for comparison (N=423). In addition, non-parametric Classification and Regression Tree (CART) analyses were performed to model group heterogeneity and identify any subgroups of patients where TICV might be an important predictor of dementia. Parametrically, no main effect was found for TICV when predicting a dementia diagnosis; however, the CART analysis did reveal important TICV subgroups, including a sex differential wherein ε4 APOE allele presence in males and low TICV predicted AD classification. TICV, APOE, and other potential mediator/moderator variables are discussed in the context of the brain reserve hypothesis.

Topology and graph theory applied to cortical anatomy may help explain working memory capacity for three or four simultaneous items

Cognitive experimentation suggests that at any single instant only three or four items ("chunks") are simultaneously prominent as a working memory (WM) trace, if we disregard the rehearsal component of WM. The reason for small WM capacity may concern combinatorial manageability. How might the neural representations of these few coactive chunks occupy a spatially distributed set of areas of the sheet-like cortex, while providing both order and flexibility to associate items in WM? Each attribute of each simultaneously active WM item must have broad access to the representational facilities of the cortical sheet, comprising tens of thousands of modular "cortical columns." The two hypothesized neural levels of WM during any moment of cognition comprise (a) "binding" together of many distributed attribute representations within each respective WM chunk, and (b) combinatorial play among three or four WM chunk-representations. Anatomical and functional evidence of cortical unity through its depth suggests that cortex may be viewed as essentially planar in its distribution of activations. Thus, a moment's WM is hypothesized here to reside in myriad activated cortical planar "patches," each subdivided into up to four amoeboid "subpatches." Two different lines of topological reasoning suggest orderly associations of such representations. (1) The four-color principle of map topology, and the related K(4) is planar theorem of graph theory, imply that if a small cortical area is dynamically subdivided into no more than four, discretely bounded planar subareas, then each such segment has ample free access to each of the others. (2) A hypothetical alternative to such associative adjacency of simultaneously active cortical representations of chunk-attributes is associative overlap, whereby, in dense cortical neuropil, activated subpatches behave like Venn diagrams of intersecting sets. As the number of Venn-like coactive subpatches within a patch increases, maintaining ad hoc associativity among all combinations requires exponentially proliferating intersections. Beyond four, serpentine subpatch shapes are required, which could easily lead to pathologies of omission or commission. As hypothesized by many researchers, the binding of the widely distributed cortical modules that represent a given chunk may involve synchrony or coherence of a single EEG frequency. Elsewhere, I have conjectured that such a binding frequency for a single chunk may bear a harmonic relationship with the additional EEG frequencies that are simultaneously binding the other WM chunks. Other possible mechanisms of binding have also been hypothesized. Whatever the mechanism, the many attributes of a moment's complement of three or four WM chunks must generally have an accidental relationship with the spatial distribution of the cortical feature analyzers that must be activated to represent those attributes. Therefore, the cortex may need, and have, comprehensive anatomical connections of each of its modules for representing an attribute (or of small redundant module groupings) with every other. If such whole-part cortico-cortical connections are somehow exploited not only to fully represent each cognitive chunk in its bound-together attributes, but also to bring the major business of intensive WM information processing down to the level of local circuits, in the sorts of topological patterning hypothesized here, there may be two adaptive results: (1) Time and other economies would be achieved in the reduction of activity in distant cortico-cortical connections to lower-energy global orchestration, or binding processes. (2) The piecemeal local topological limit to four subpatches would be writ large, across the entire cortex, preventing an unconstrained combinatorial explosion of associations among all attributes of all three or four simultaneously active chunks. Such hypothetical convergence to foci in local subpatch interactions might take place primarily in association cortex, and/or it might involve temporary shifts in response properties in some cortical subpat might involve temporary shifts in response properties in some cortical subpatches. Quantitative studies of the densely packed cortical fine structure, by Braitenberg and Schüz, and others, seem potentially consistent with this vision of cortical function in cognition.

Traumatic brain injury as a risk factor for Alzheimer's disease: a review

Accumulating epidemiological evidence implicates traumatic brain injury as a pathogenic agent in the development of Alzheimer's disease (AD). Considering the increase in the prevalence of both traumatic brain injury and AD in recent times, the possibility that brain trauma may provoke the early development of AD has important implications for health service planning, preventative efforts, and medico-legal compensation settlements. This paper evaluates the plausibility of the proposed link between traumatic brain injury and AD, largely by way of exploring a theoretical perspective advanced by Satz (1993) and considering recent contributions from the epidemiological, neuropathological, and biochemical literature that are pertinent to this issue. The literature reviewed provides sufficient support and empirical vindication to give credence to the proposed association between these two neuropsychological entities at the statistical, theoretical, and biological level.

Hypothesized neural dynamics of working memory: several chunks might be marked simultaneously by harmonic frequencies within an octave band of brain waves

The capacity of working memory (WM) for up to about seven simple items holds true both for humans and other species, and may depend upon a common characteristic of mammalian brains. This paper develops the conjecture that each WM item is represented by a different brain wave frequency. The binding-by-synchrony hypothesis, now being widely investigated, holds that the attributes of a single cognitive element cohere because electroencephalogram (EEG) synchrony temporarily unifies their substrates, which are distributed among different brain regions. However, thought requires keeping active more than one cognitive element, or WM "chunk," at a time. If there is indeed a brain wave frequency code for cognitive item-representations that are copresent within the same volume of neural tissue, the simple mathematical relationships of harmonies could provide a basis for maintaining distinctness and for orderly changes. Thus, a basic aspect of music may provide a model for an essential characteristic of WM. Music is a communicative phenomenon of "intermediate complexity," more highly organized than the firing patterns of individual neurons but simpler than language. If there is a distinct level of neural processing within which the microscopic physiological activity of neurons self-organizes into the macroscopic psychology of the organism, it might require such moderate complexity. Some of the obvious properties of music--orderly mixing and transitions among limited numbers of signal lines-are suggestive of properties that a dynamic neural process might need in order to organize and reorganize WM markers, but there are a number of additional, nonobvious advantageous properties of summating sinusoids in music-like relationships. In particular, harmonies register a stable periodic signal in the briefest possible time. Thus, the regularity of summating sinusoids whose frequencies bear harmony ratios suggests a particular kind of tradeoff between parallel and serial processing. When there are few copresent waves, at EEG frequencies, this sort of parallel coding retains behaviorally meaningful brief periods. A necessary companion hypothesis is that the brain wave frequencies underlying WM are confined to a single octave; that is, the upper and lower bounds of the band are in the ratio of 2:1. This hypothesized restriction, suggested by an empirical property of EEG bands that has been widely reported but rarely commented upon, has the important property of precluding spurious difference rhythms. A restriction to an octave, of "harmonious" frequency-markers for WM items, also seems consistent with a great deal of behavioral data suggesting that WM comprises a rapidly fading trace process in which only up to three or four item-representations are strongly activated simultaneously. There is also an additional, sequential renewal-or-revision process, within which up to another three or four items are being actively refreshed by rehearsal or replaced. Such serial processing may involve a less stringent octave band crowding problem.

Training redundant artificial neural networks: imposing biology on technology

One biological principle that is often overlooked in the design of artificial neural networks (ANNs) is redundancy. Redundancy is the replication of processes within the brain. This paper examines the effects of redundancy on learning in ANNs when given either a function-approximation task or a pattern-classification task. The function-approximation task simulated a robotic arm reaching toward an object in two-dimensional space, and the pattern-classification task was detecting parity. Results indicated that redundant ANNs learned the pattern-classification problem much faster, and converge on a solution 100% of the time, whereas standard ANNs sometimes failed to learn the problem. Furthermore, when overall network error is considered, redundant ANNs were significantly more accurate than standard ANNs in performing the function-approximation task. These results are discussed in terms of the relevance of redundancy to the performance of ANNs in general, and the relevance of redundancy in biological systems in particular.

Oxidative and other DNA damages as the basis of aging: a review

DNA damages occur continuously in cells of living organisms. While most of these damages are repaired, some accumulate. In particular, there is evidence for DNA damage accumulation in non-dividing cells of mammals. These accumulated DNA damages probably interfere with RNA transcription. We consider that the decline in the ability of DNA to serve as a template for gene expression is the primary cause of aging. Oxidative DNA damages are among the best documented and prevalent DNA damages and are likely to be a prominent cause of aging.