scholarly journals Investment in higher order central processing regions is not constrained by brain size in social insects

2014 ◽  
Vol 281 (1784) ◽  
pp. 20140217 ◽  
Author(s):  
Mario L. Muscedere ◽  
Wulfila Gronenberg ◽  
Corrie S. Moreau ◽  
James F. A. Traniello

The extent to which size constrains the evolution of brain organization and the genesis of complex behaviour is a central, unanswered question in evolutionary neuroscience. Advanced cognition has long been linked to the expansion of specific brain compartments, such as the neocortex in vertebrates and the mushroom bodies in insects. Scaling constraints that limit the size of these brain regions in small animals may therefore be particularly significant to behavioural evolution. Recent findings from studies of paper wasps suggest miniaturization constrains the size of central sensory processing brain centres (mushroom body calyces) in favour of peripheral, sensory input centres (antennal and optic lobes). We tested the generality of this hypothesis in diverse eusocial hymenopteran species (ants, bees and wasps) exhibiting striking variation in body size and thus brain size. Combining multiple neuroanatomical datasets from these three taxa, we found no universal size constraint on brain organization within or among species. In fact, small-bodied ants with miniscule brains had mushroom body calyces proportionally as large as or larger than those of wasps and bees with brains orders of magnitude larger. Our comparative analyses suggest that brain organization in ants is shaped more by natural selection imposed by visual demands than intrinsic design limitations.

Science ◽  
2018 ◽  
Vol 360 (6394) ◽  
pp. 1222-1227 ◽  
Author(s):  
P. K. Reardon ◽  
Jakob Seidlitz ◽  
Simon Vandekar ◽  
Siyuan Liu ◽  
Raihaan Patel ◽  
...  

Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology.


2013 ◽  
Vol 82 (3) ◽  
pp. 177-184 ◽  
Author(s):  
Sean O'Donnell ◽  
Marie R. Clifford ◽  
Sara DeLeon ◽  
Christopher Papa ◽  
Nazaneen Zahedi ◽  
...  

2021 ◽  
Author(s):  
Shannon L.M. Heald ◽  
Stephen C. Van Hedger ◽  
John Veillette ◽  
Katherine Reis ◽  
Joel S. Snyder ◽  
...  

AbstractThe ability to generalize rapidly across specific experiences is vital for robust recognition of new patterns, especially in speech perception considering acoustic-phonetic pattern variability. Behavioral research has demonstrated that listeners are rapidly able to generalize their experience with a talker’s speech and quickly improve understanding of a difficult-to-understand talker without prolonged practice, e.g., even after a single training session. Here, we examine the differences in neural responses to generalized versus rote learning in auditory cortical processing by training listeners to understand a novel synthetic talker using a Pretest-Posttest design with electroencephalography (EEG). Participants were trained using either (1) a large inventory of words where no words repeated across the experiment (generalized learning) or (2) a small inventory of words where words repeated (rote learning). Analysis of long-latency auditory evoked potentials at Pretest and Posttest revealed that while rote and generalized learning both produce rapid changes in auditory processing, the nature of these changes differed. In the context of adapting to a talker, generalized learning is marked by an amplitude reduction in the N1-P2 complex and by the presence of a late-negative (LN) wave in the auditory evoked potential following training. Rote learning, however, is marked only by temporally later source configuration changes. The early N1-P2 change, found only for generalized learning, suggests that generalized learning relies on the attentional system to reorganize the way acoustic features are selectively processed. This change in relatively early sensory processing (i.e. during the first 250ms) is consistent with an active processing account of speech perception, which proposes that the ability to rapidly adjust to the specific vocal characteristics of a new talker (for which rote learning is rare) relies on attentional mechanisms to adaptively tune early auditory processing sensitivity.Statement of SignificancePrevious research on perceptual learning has typically examined neural responses during rote learning: training and testing is carried out with the same stimuli. As a result, it is not clear that findings from these studies can explain learning that generalizes to novel patterns, which is critical in speech perception. Are neural responses to generalized learning in auditory processing different from neural responses to rote learning? Results indicate rote learning of a particular talker’s speech involves brain regions focused on the memory encoding and retrieving of specific learned patterns, whereas generalized learning involves brain regions involved in reorganizing attention during early sensory processing. In learning speech from a novel talker, only generalized learning is marked by changes in the N1-P2 complex (reflective of secondary auditory cortical processing). The results are consistent with the view that robust speech perception relies on the fast adjustment of attention mechanisms to adaptively tune auditory sensitivity to cope with acoustic variability.


2021 ◽  
Author(s):  
Erika L. Schumacher ◽  
Bruce A. Carlson

AbstractBrain region size generally scales allometrically with total brain size, but mosaic shifts in brain region size independent of brain size have been found in several lineages and may be related to the evolution of behavioral novelty. African weakly electric fishes (Mormyroidea) evolved a mosaically enlarged cerebellum and hindbrain, yet the relationship to their behaviorally novel electrosensory system remains unclear. We addressed this by studying South American weakly electric fishes (Gymnotiformes) and weakly electric catfishes (Synodontis spp.), which evolved varying aspects of electrosensory systems, independent of mormyroids. If the mormyroid mosaic increases are related to evolving an electrosensory system, we should find similar mosaic shifts in gymnotiforms and Synodontis. Using micro-computed tomography scans, we quantified brain region scaling for multiple electrogenic, electroreceptive, and non-electrosensing species. We found mosaic increases in cerebellum in all three electrogenic lineages relative to non-electric lineages and mosaic increases in torus semicircularis and hindbrain associated with the evolution of electrogenesis and electroreceptor type. These results show that evolving novel electrosensory systems is repeatedly and independently associated with changes in the sizes of individual brain regions independent of brain size, which suggests that selection can impact structural brain composition to favor specific regions involved in novel behaviors.


2015 ◽  
Vol 282 (1810) ◽  
pp. 20151008 ◽  
Author(s):  
Kristina Noreikiene ◽  
Gábor Herczeg ◽  
Abigél Gonda ◽  
Gergely Balázs ◽  
Arild Husby ◽  
...  

The mosaic model of brain evolution postulates that different brain regions are relatively free to evolve independently from each other. Such independent evolution is possible only if genetic correlations among the different brain regions are less than unity. We estimated heritabilities, evolvabilities and genetic correlations of relative size of the brain, and its different regions in the three-spined stickleback ( Gasterosteus aculeatus ). We found that heritabilities were low (average h 2 = 0.24), suggesting a large plastic component to brain architecture. However, evolvabilities of different brain parts were moderate, suggesting the presence of additive genetic variance to sustain a response to selection in the long term. Genetic correlations among different brain regions were low (average r G = 0.40) and significantly less than unity. These results, along with those from analyses of phenotypic and genetic integration, indicate a high degree of independence between different brain regions, suggesting that responses to selection are unlikely to be severely constrained by genetic and phenotypic correlations. Hence, the results give strong support for the mosaic model of brain evolution. However, the genetic correlation between brain and body size was high ( r G = 0.89), suggesting a constraint for independent evolution of brain and body size in sticklebacks.


2015 ◽  
Vol 11 (11) ◽  
pp. 20150678 ◽  
Author(s):  
Orsolya Vincze ◽  
Csongor I. Vágási ◽  
Péter L. Pap ◽  
Gergely Osváth ◽  
Anders Pape Møller

Long-distance migratory birds have relatively smaller brains than short-distance migrants or residents. Here, we test whether reduction in brain size with migration distance can be generalized across the different brain regions suggested to play key roles in orientation during migration. Based on 152 bird species, belonging to 61 avian families from six continents, we show that the sizes of both the telencephalon and the whole brain decrease, and the relative size of the optic lobe increases, while cerebellum size does not change with increasing migration distance. Body mass, whole brain size, optic lobe size and wing aspect ratio together account for a remarkable 46% of interspecific variation in average migration distance across bird species. These results indicate that visual acuity might be a primary neural adaptation to the ecological challenge of migration.


2019 ◽  
pp. 423-472
Author(s):  
Georg F. Striedter ◽  
R. Glenn Northcutt

After summarizing the earlier chapters, which focused on the evolution of specific lineages, this chapter examines general patterns in the evolution of vertebrate nervous systems. Most conspicuous is that relative brain size and complexity increased independently in many lineages. The proportional size of individual brain regions tends to change predictably with absolute brain size (and neurogenesis timing), but the scaling rules vary across lineages. Attempts to link variation in the size of individual brain areas (or entire brains) to behavior are complicated in part because the connections, internal organization, and functions of individual brain regions also vary across phylogeny. In addition, major changes in the functional organization of vertebrate brains were caused by the emergence of novel brain regions (e.g., neocortex in mammals and area dorsalis centralis in teleosts) and novel circuits. These innovations significantly modified the “vertebrate brain Bauplan,” but their mechanistic origins and implications require further investigation.


2019 ◽  
Vol 2019 ◽  
pp. 1-21 ◽  
Author(s):  
Laura Bell ◽  
Lisa Wagels ◽  
Christiane Neuschaefer-Rube ◽  
Janina Fels ◽  
Raquel E. Gur ◽  
...  

One of the most significant effects of neural plasticity manifests in the case of sensory deprivation when cortical areas that were originally specialized for the functions of the deprived sense take over the processing of another modality. Vision and audition represent two important senses needed to navigate through space and time. Therefore, the current systematic review discusses the cross-modal behavioral and neural consequences of deafness and blindness by focusing on spatial and temporal processing abilities, respectively. In addition, movement processing is evaluated as compiling both spatial and temporal information. We examine whether the sense that is not primarily affected changes in its own properties or in the properties of the deprived modality (i.e., temporal processing as the main specialization of audition and spatial processing as the main specialization of vision). References to the metamodal organization, supramodal functioning, and the revised neural recycling theory are made to address global brain organization and plasticity principles. Generally, according to the reviewed studies, behavioral performance is enhanced in those aspects for which both the deprived and the overtaking senses provide adequate processing resources. Furthermore, the behavioral enhancements observed in the overtaking sense (i.e., vision in the case of deafness and audition in the case of blindness) are clearly limited by the processing resources of the overtaking modality. Thus, the brain regions that were previously recruited during the behavioral performance of the deprived sense now support a similar behavioral performance for the overtaking sense. This finding suggests a more input-unspecific and processing principle-based organization of the brain. Finally, we highlight the importance of controlling for and stating factors that might impact neural plasticity and the need for further research into visual temporal processing in deaf subjects.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Yuxiang Yan ◽  
Louisa Dahmani ◽  
Jianxun Ren ◽  
Lunhao Shen ◽  
Xiaolong Peng ◽  
...  

Abstract Signal loss in blood oxygen level-dependent (BOLD) functional neuroimaging is common and can lead to misinterpretation of findings. Here, we reconstructed compromised fMRI signal using deep machine learning. We trained a model to learn principles governing BOLD activity in one dataset and reconstruct artificially compromised regions in an independent dataset, frame by frame. Intriguingly, BOLD time series extracted from reconstructed frames are correlated with the original time series, even though the frames do not independently carry any temporal information. Moreover, reconstructed functional connectivity maps exhibit good correspondence with the original connectivity maps, indicating that the model recovers functional relationships among brain regions. We replicated this result in two healthy datasets and in patients whose scans suffered signal loss due to intracortical electrodes. Critically, the reconstructions capture individual-specific information. Deep machine learning thus presents a unique opportunity to reconstruct compromised BOLD signal while capturing features of an individual’s own functional brain organization.


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