The influence of non-neural factors on BOLD signal magnitude

To what extent is the size of the blood-oxygen-level-dependent (BOLD) response influenced by factors other than neural activity? In a re-analysis of three neuroimaging datasets, we find large systematic inhomogeneities in the BOLD response magnitude in primary visual cortex (V1): stimulus-evoked BOLD responses, expressed in units of percent signal change, are up to 50% larger along the representation of the horizontal meridian than the vertical meridian. To assess whether this surprising effect can be interpreted as differences in local neural activity, we quantified several factors that potentially contribute to the size of the BOLD response. We find strong relationships between BOLD response magnitude and cortical thickness, cortical curvature, and the presence of large veins. These relationships are consistently found across subjects and suggest that variation in BOLD response magnitudes across cortical locations reflects, in part, differences in anatomy and vascularization. To compensate for these factors, we implement a regression-based correction method and show that after correction, BOLD responses become more homogeneous across V1. The correction reduces the horizontal/vertical difference by about half, indicating that some of the difference is likely not due to neural activity differences. Additionally, we find that while the cerebral sinuses overlap with the vertical meridian representation in V1, they do not explain the observed horizontal/vertical difference. We conclude that interpretation of variation in BOLD response magnitude across cortical locations should consider the influence of the potential confounding factors of cortical thickness, curvature, and vascularization.

Low statistical power and overestimated anthropogenic impacts, exacerbated by publication bias, dominate field studies in global change biology

Field studies are essential to reliably quantify ecological responses to global change because they are exposed to realistic climate manipulations. Yet such studies are limited in replicates, resulting in less power and, therefore, unreliable effect estimates. Further, while manipulative field experiments are assumed to be more powerful than non-manipulative observations, it has rarely been scrutinized using extensive data. Here, using 3,847 field experiments that were designed to estimate the effect of environmental stressors on ecosystems, we systematically quantified their statistical power and magnitude (Type M) and sign (Type S) errors. Our investigations focused upon the reliability of field experiments to assess the effect of stressors on both ecosystem’s response magnitude and variability. When controlling for publication bias, single experiments were underpowered to detect response magnitude (median power: 18% – 38% depending on mean difference metrics). Single experiments also had much lower power to detect response variability (6% – 12% depending on variance difference metrics) than response magnitude. Such underpowered studies could exaggerate estimates of response magnitude by 2 – 3 times (Type M errors) and variability by 4 – 10 times. Type S errors were comparatively rare. These observations indicate that low power, coupled with publication bias, inflates the estimates of anthropogenic impacts. Importantly, we found that meta-analyses largely mitigated the issues of low power and exaggerated effect size estimates. Rather surprisingly, manipulative experiments and non-manipulative observations had very similar results in terms of their power, Type M and S errors. Therefore, the previous assumption about the superiority of manipulative experiments in terms of power is overstated. These results call for highly powered field studies to reliably inform theory building and policymaking, via more collaboration and team science, and large-scale ecosystem facilities. Future studies also require transparent reporting and open science practices to approach reproducible and reliable empirical work and evidence synthesis.

Stimulus-dependent representational drift in primary visual cortex

ABSTRACTTo produce consistent sensory perception, neurons must maintain stable representations of sensory input. However, neurons in many regions exhibit progressive drift across days. Longitudinal studies have found stable responses to artificial stimuli across sessions in primary sensory areas, but it is unclear whether this stability extends to naturalistic stimuli. We performed chronic 2-photon imaging of mouse V1 populations to directly compare the representational stability of artificial versus naturalistic visual stimuli over weeks. Responses to gratings were highly stable across sessions. However, neural responses to naturalistic movies exhibited progressive representational drift across sessions. Differential drift was present across cortical layers, in inhibitory interneurons, and could not be explained by differential response magnitude or higher order stimulus statistics. However, representational drift was accompanied by similar differential changes in local population correlation structure. These results suggest representational stability in V1 is stimulus-dependent and related to differences in preexisting circuit architecture of co-tuned neurons.

Selective effects of arousal on population coding of natural sounds in auditory cortex

The ability to discriminate between complex natural sounds is critical for survival. Changes in arousal and other aspects of behavioral state can impact the accuracy of sensory coding, affecting both the reliability of single neuron responses and the degree of correlated noise between neurons. However, it is unclear how these effects interact to influence coding of diverse natural stimuli. We recorded the spiking activity of neural populations in primary auditory cortex (A1) evoked by a large library of natural sounds while monitoring changes in pupil size as an index of arousal. Heightened arousal increased response magnitude and reduced noise correlations between neurons, improving coding accuracy on average. Rather than suppressing shared noise along all dimensions of neural activity, the change in noise correlations occurred via coherent, low-dimensional modulation of response variability in A1. The modulation targeted a different group of neurons from those undergoing changes in response magnitude. Thus, changes in response magnitude and correlation are mediated by distinct mechanisms. The degree to which these low-dimensional changes were aligned with the high-dimensional natural sound-evoked activity was variable, resulting in stimulus-dependent improvements in coding accuracy.

ANALYSIS OF TEMPORAL AND FREQUENCY CHARACTERISTICS OF SIMULTANEOUS GEODEFORMATION SIGNALS REGISTERED AT “KARYMSHINA” SITE

На Камчатке в измерительном пункте Карымшина в период с 2016 г. по настоящее время проводятся одновременные геодеформационные наблюдения. Для их проведения установлены лазерный деформограф-интерферометр и трехкомпонентный сейсмоакустический приёмник. Ранее выявлено, что в период деформационных возмущений в породах регистрируется большое количество сигналов. В настоящей работе представлены результаты анализа регистрируемых сигналов, исследованы их амплитудно-частотные характеристики и выявлены постоянные спектральные составляющие. Simultaneous geodeformational observations have been carried out from 2016 to the present time at Karymshina site on Kamchatka. A laser deformograph-interferometer and a three-component seismoacoustic receiver were installed to conduct these observations. Earlier it was revealed that a large number of signals were registered in rocks during deformation disturbances. In this work, we present the analysis results of the registered signals. Signal frequency response (magnitude and phase) was studied, and constant spectral components were identified.

Population response magnitude variation in inferotemporal cortex predicts image memorability

Most accounts of image and object encoding in inferotemporal cortex (IT) focus on the distinct patterns of spikes that different images evoke across the IT population. By analyzing data collected from IT as monkeys performed a visual memory task, we demonstrate that variation in a complementary coding scheme, the magnitude of the population response, can largely account for how well images will be remembered. To investigate the origin of IT image memorability modulation, we probed convolutional neural network models trained to categorize objects. We found that, like the brain, different natural images evoked different magnitude responses from these networks, and in higher layers, larger magnitude responses were correlated with the images that humans and monkeys find most memorable. Together, these results suggest that variation in IT population response magnitude is a natural consequence of the optimizations required for visual processing, and that this variation has consequences for visual memory.