scholarly journals Hippocampal volumes and neuron numbers increase along a gradient of environmental harshness: a large-scale comparison

2008 ◽  
Vol 276 (1656) ◽  
pp. 401-405 ◽  
Author(s):  
Timothy C Roth ◽  
Vladimir V Pravosudov
Keyword(s):  
Spatial Memory ◽  
Large Scale ◽  
Memory Function ◽  
Brain Regions ◽  
Climatic Conditions ◽  
Day Length ◽  
Harsh Environments ◽  
Environmental Pressures ◽  
Food Caching ◽  
Climatic Severity

Environmental conditions may provide specific demands for memory, which in turn may affect specific brain regions responsible for memory function. For food-caching animals, in particular, spatial memory appears to be important because it may have a direct effect on fitness via the accuracy of cache retrieval. Animals living in more harsh environments should rely more on cached food, and thus theoretically should have better memory to support cache retrieval, which may be crucial for survival. Consequently, animals in harsh environments may benefit from more neurons within a larger hippocampus (Hp), a part of the brain involved in spatial memory. Here, we present the first large-scale test of the hypothesis that Hp structure is related to the severity of the environment within a single food-caching species (the black-capped chickadee, Poecile atricapillus ) with a large range encompassing a great diversity of climatic conditions. Hp size in birds collected at five locations along a gradient of environmental harshness from Alaska to Kansas ranked perfectly with climatic severity. Birds from more harsh northern climates (defined by lower ambient temperature, shorter day length and more snow cover) had significantly larger Hp volumes and more Hp neurons (both relative to telencephalon volume) than those from more mild southern latitudes. Environmental pressures therefore seem capable of influencing specific brain regions independently, which may result in enhanced memory, and hence survival, in harsh climates.

scholarly journals Variation in hippocampal morphology along an environmental gradient: controlling for the effects of day length

2011 ◽  
Vol 278 (1718) ◽  
pp. 2662-2667 ◽  
Author(s):  
Timothy C. Roth ◽  
Lara D. LaDage ◽  
Vladimir V. Pravosudov
Keyword(s):  
Spatial Memory ◽  
Snow Cover ◽  
Cognitive Abilities ◽  
Memory Function ◽  
Geographical Area ◽  
Brain Regions ◽  
Day Length ◽  
Relative Role ◽  
Food Caching ◽  
Significant Difference

Environmental conditions may create increased demands for memory, which in turn may affect specific brain regions responsible for memory function. This may occur either via phenotypic plasticity or selection for individuals with enhanced cognitive abilities. For food-caching animals, in particular, spatial memory appears to be important because it may have a direct effect on fitness via their ability to accurately retrieve food caches. Our previous studies have shown that caching animals living in more harsh environments (characterized by low temperatures, high snow cover and short day lengths) possess more neurons within a larger hippocampus (Hp), a part of the brain involved in spatial memory. However, the relative role of each of these environmental features in the relationship is unknown. Here, we dissociate the effects of one theoretically important factor (day length) within the environmental severity/Hp relationship by examining food-caching birds (black-capped chickadee, Poecile atricapillus ) selected at locations along the same latitude, but with very different climatic regimes. There was a significant difference in Hp attributes among populations along the same latitude with very different climatic features. Birds from the climatically mild location had significantly smaller Hp volumes and fewer Hp neurons than birds from the more harsh populations, even though all populations experienced similar day lengths. These results suggest that variables such as temperature and snow cover seem to be important even without the compounding effect of reduced day length at higher latitudes and suggest that low temperature and snow cover alone may be sufficient to generate high demands for memory and the hippocampus. Our data further confirmed that the association between harsh environment and the hippocampus in food-caching animals is robust across a large geographical area and across years.

scholarly journals Breathing coordinates limbic network dynamics underlying memory consolidation

2018 ◽  
Author(s):  
Nikolaos Karalis ◽  
Anton Sirota
Keyword(s):  
Memory Consolidation ◽  
Information Transfer ◽  
Large Scale ◽  
Memory Function ◽  
Network Dynamics ◽  
Brain Regions ◽  
Neuronal Dynamics ◽  
Dual Mechanism ◽  
Relationship Of ◽  
The Relationship

The coordinated activity between remote brain regions underlies cognition and memory function. Although neuronal oscillations have been proposed as a mechanistic substrate for the coordination of information transfer and memory consolidation during sleep, little is known about the mechanisms that support the widespread synchronization of brain regions and the relationship of neuronal dynamics with other bodily rhythms, such as breathing. Here we address this question using large-scale recordings from a number of structures, including the medial prefrontal cortex, hippocampus, thalamus, amygdala and nucleus accumbens in mice. We identify a dual mechanism of respiratory entrainment, in the form of an intracerebral corollary discharge that acts jointly with an olfactory reafference to coordinate limbic network dynamics, such as hippocampal ripples and cortical UP and DOWN states, involved in memory consolidation. These results highlight breathing, a perennial rhythmic input to the brain, as an oscillatory scaffold for the functional coordination of the limbic circuit, enabling the segregation and integration of information flow across neuronal networks.

scholarly journals Neural representations of space in the hippocampus of a food-caching bird

Science ◽  
2021 ◽  
Vol 373 (6552) ◽  
pp. 343-348
Author(s):  
H. L. Payne ◽  
G. F. Lynch ◽  
D. Aronov
Keyword(s):  
Spatial Memory ◽  
Neural Activity ◽  
Strong Dependence ◽  
Bird Species ◽  
Brain Regions ◽  
Food Caching ◽  
Neural Representations ◽  
Hippocampal Activity ◽  
Species Specific ◽  
Representations Of Space

Spatial memory in vertebrates requires brain regions homologous to the mammalian hippocampus. Between vertebrate clades, however, these regions are anatomically distinct and appear to produce different spatial patterns of neural activity. We asked whether hippocampal activity is fundamentally different even between distant vertebrates that share a strong dependence on spatial memory. We studied tufted titmice, food-caching birds capable of remembering many concealed food locations. We found mammalian-like neural activity in the titmouse hippocampus, including sharp-wave ripples and anatomically organized place cells. In a non–food-caching bird species, spatial firing was less informative and was exhibited by fewer neurons. These findings suggest that hippocampal circuit mechanisms are similar between birds and mammals, but that the resulting patterns of activity may vary quantitatively with species-specific ethological needs.

scholarly journals Research on capacity optimization of micro-grid hybrid energy storage system based on simulated annealing artificial fish swarm algorith with memory function

2020 ◽  
Vol 185 ◽  
pp. 01023
Author(s):  
Yuan An ◽  
Jianing Li ◽  
Cenyue Chen
Keyword(s):  
Simulated Annealing ◽  
Energy Storage ◽  
Large Scale ◽  
Memory Function ◽  
Storage System ◽  
Energy Storage System ◽  
Hybrid Energy ◽  
Hybrid Energy Storage ◽  
Hybrid Energy Storage System ◽  
With Memory

The intermittence and uncertainty of wind power and photovoltaic power have hindered the large-scale development of both. Therefore, it is very necessary to properly configure energy storage devices in the wind-solar complementary power grid. For the hybrid energy storage system composed of storage battery and supercapacitor, the optimization model of hybrid energy storage capacity is established with the minimum comprehensive cost as the objective function and the energy saving and charging state as the constraints. A simulated annealing artificial fish school algorithm with memory function is proposed to solve the model. The results show that the hybrid energy storage system can greatly save costs and improve system economy.

scholarly journals Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Arian Ashourvan ◽  
Preya Shah ◽  
Adam Pines ◽  
Shi Gu ◽  
Christopher W. Lynn ◽  
...  
Keyword(s):  
White Matter ◽  
Maximum Entropy ◽  
Large Scale ◽  
Structural Connectivity ◽  
Quantitative Relationship ◽  
Brain Regions ◽  
Maximum Entropy Model ◽  
Entropy Model ◽  
Activation Patterns ◽  
Co Activation

AbstractA major challenge in neuroscience is determining a quantitative relationship between the brain’s white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes’ activation patterns’ probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM’s interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions’ distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain’s structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.

scholarly journals Pharmacological Blockade of PPARα Exacerbates Inflammatory Pain-Related Impairment of Spatial Memory in Rats

Biomedicines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 610
Author(s):  
Jessica C. Gaspar ◽  
Catherine Healy ◽  
Mehnaz I. Ferdousi ◽  
Michelle Roche ◽  
David P. Finn
Keyword(s):  
Spatial Memory ◽  
Cognitive Processing ◽  
Inflammatory Pain ◽  
Dorsal Hippocampus ◽  
Memory Function ◽  
Intraperitoneal Administration ◽  
Compensatory Mechanism ◽  
Chronic Inflammatory Pain ◽  
Pharmacological Blockade ◽  
Innate Anxiety

Peroxisome proliferator-activated receptors (PPARs) are ligand-dependent transcription factors that exist in three isoforms: PPARα, PPARβ/δ and PPARγ. Studies suggest that the PPAR signalling system may modulate pain, anxiety and cognition. The aim of the present study was to investigate whether endogenous signalling via PPARs differentially modulates innate anxiety responses and mnemonic function in the presence and absence of inflammatory pain. We examined the effects of intraperitoneal administration of GW6471 (PPARα antagonist), GSK0660 (PPARβ/δ antagonist), GW9662 (PPARγ antagonist), and N-palmitoylethanolamide (PEA) on rat behaviour in the elevated plus maze (EPM), open field (OF), light-dark box (LDB), and novel object recognition (NOR) tests in the presence or absence of chronic inflammatory pain. Complete Freund’s Adjuvant (CFA)-injected rats exhibited impaired recognition and spatial mnemonic performance in the NOR test and pharmacological blockade of PPARα further impaired spatial memory in CFA-treated rats. N-oleoylethanolamide (OEA) levels were higher in the dorsal hippocampus in CFA-injected animals compared to their counterparts. The results suggest a modulatory effect of CFA-induced chronic inflammatory pain on cognitive processing, but not on innate anxiety-related responses. Increased OEA-PPARα signalling may act as a compensatory mechanism to preserve spatial memory function following CFA injection.

scholarly journals Cell migration guided by long-lived spatial memory

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Joseph d’Alessandro ◽  
Alex Barbier--Chebbah ◽  
Victor Cellerin ◽  
Olivier Benichou ◽  
René Marc Mège ◽  
...  
Keyword(s):  
Cell Migration ◽  
Spatial Memory ◽  
Large Scale ◽  
Single Cells ◽  
Environmental Perturbations ◽  
Motile Cells ◽  
Unicellular Organisms ◽  
Biochemical Signals ◽  
The Impact ◽  
Cell Trajectories

AbstractLiving cells actively migrate in their environment to perform key biological functions—from unicellular organisms looking for food to single cells such as fibroblasts, leukocytes or cancer cells that can shape, patrol or invade tissues. Cell migration results from complex intracellular processes that enable cell self-propulsion, and has been shown to also integrate various chemical or physical extracellular signals. While it is established that cells can modify their environment by depositing biochemical signals or mechanically remodelling the extracellular matrix, the impact of such self-induced environmental perturbations on cell trajectories at various scales remains unexplored. Here, we show that cells can retrieve their path: by confining motile cells on 1D and 2D micropatterned surfaces, we demonstrate that they leave long-lived physicochemical footprints along their way, which determine their future path. On this basis, we argue that cell trajectories belong to the general class of self-interacting random walks, and show that self-interactions can rule large scale exploration by inducing long-lived ageing, subdiffusion and anomalous first-passage statistics. Altogether, our joint experimental and theoretical approach points to a generic coupling between motile cells and their environment, which endows cells with a spatial memory of their path and can dramatically change their space exploration.

scholarly journals Spatial and Temporal Characteristics of Environmental Air Quality and Its Relationship with Seasonal Climatic Conditions in Eastern China during 2015–2018

2021 ◽  
Vol 18 (9) ◽  
pp. 4524
Author(s):  
Zhiyuan Wang ◽  
Xiaoyi Shi ◽  
Chunhua Pan ◽  
Sisi Wang
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Air Pollutants ◽  
Large Scale ◽  
Asian Summer Monsoon ◽  
Eastern China ◽  
Climatic Conditions ◽  
Uniform Structure ◽  
Concentration Limit ◽  
Environmental Air

Exploring the relationship between environmental air quality (EAQ) and climatic conditions on a large scale can help better understand the main distribution characteristics and the mechanisms of EAQ in China, which is significant for the implementation of policies of joint prevention and control of regional air pollution. In this study, we used the concentrations of six conventional air pollutants, i.e., carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), fine particulate matter (PM2.5), coarse particulate matter (PM10), and ozone (O3), derived from about 1300 monitoring sites in eastern China (EC) from January 2015 to December 2018. Exploiting the grading concentration limit (GB3095-2012) of various pollutants in China, we also calculated the monthly average air quality index (AQI) in EC. The results show that, generally, the EAQ has improved in all seasons in EC from 2015 to 2018. In particular, the concentrations of conventional air pollutants, such as CO, SO2, and NO2, have been decreasing year by year. However, the concentrations of particulate matter, such as PM2.5 and PM10, have changed little, and the O3 concentration increased from 2015 to 2018. Empirical mode decomposition (EOF) was used to analyze the major patterns of AQI in EC. The first mode (EOF1) was characterized by a uniform structure in AQI over EC. These phenomena are due to the precipitation variability associated with the East Asian summer monsoon (EASM), referred to as the “summer–winter” pattern. The second EOF mode (EOF2) showed that the AQI over EC is a north–south dipole pattern, which is bound by the Qinling Mountains and Huaihe River (about 35° N). The EOF2 is mainly caused by seasonal variations of the mixed concentration of PM2.5 and O3. Associated with EOF2, the Mongolia–Siberian High influences the AQI variation over northern EC by dominating the low-level winds (10 m and 850 hPa) in autumn and winter, and precipitation affects the AQI variation over southern EC in spring and summer.

scholarly journals On the structural connectivity of large-scale models of brain networks at cellular level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Giuseppe Giacopelli ◽  
Domenico Tegolo ◽  
Emiliano Spera ◽  
Michele Migliore
Keyword(s):  
Large Scale ◽  
Brain Networks ◽  
Structural Connectivity ◽  
Network Models ◽  
Brain Regions ◽  
Cellular Level ◽  
Scale Model ◽  
Mathematical Framework ◽  
Underlying Mechanisms ◽  
Experimental Findings

AbstractThe brain’s structural connectivity plays a fundamental role in determining how neuron networks generate, process, and transfer information within and between brain regions. The underlying mechanisms are extremely difficult to study experimentally and, in many cases, large-scale model networks are of great help. However, the implementation of these models relies on experimental findings that are often sparse and limited. Their predicting power ultimately depends on how closely a model’s connectivity represents the real system. Here we argue that the data-driven probabilistic rules, widely used to build neuronal network models, may not be appropriate to represent the dynamics of the corresponding biological system. To solve this problem, we propose to use a new mathematical framework able to use sparse and limited experimental data to quantitatively reproduce the structural connectivity of biological brain networks at cellular level.

scholarly journals Reconfiguration of human evolving large-scale epileptic brain networks prior to seizures: an evaluation with node centralities

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rieke Fruengel ◽  
Timo Bröhl ◽  
Thorsten Rings ◽  
Klaus Lehnertz
Keyword(s):  
Large Scale ◽  
Brain Networks ◽  
Brain Regions ◽  
Brain Network ◽  
Theoretical Concept ◽  
Global Network ◽  
Time Resolved ◽  
Functional Connections ◽  
Node Centrality ◽  
Network Mechanism

AbstractPrevious research has indicated that temporal changes of centrality of specific nodes in human evolving large-scale epileptic brain networks carry information predictive of impending seizures. Centrality is a fundamental network-theoretical concept that allows one to assess the role a node plays in a network. This concept allows for various interpretations, which is reflected in a number of centrality indices. Here we aim to achieve a more general understanding of local and global network reconfigurations during the pre-seizure period as indicated by changes of different node centrality indices. To this end, we investigate—in a time-resolved manner—evolving large-scale epileptic brain networks that we derived from multi-day, multi-electrode intracranial electroencephalograpic recordings from a large but inhomogeneous group of subjects with pharmacoresistant epilepsies with different anatomical origins. We estimate multiple centrality indices to assess the various roles the nodes play while the networks transit from the seizure-free to the pre-seizure period. Our findings allow us to formulate several major scenarios for the reconfiguration of an evolving epileptic brain network prior to seizures, which indicate that there is likely not a single network mechanism underlying seizure generation. Rather, local and global aspects of the pre-seizure network reconfiguration affect virtually all network constituents, from the various brain regions to the functional connections between them.

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