Measures of neural similarity, bioRxiv, 2018-10-12
One fundamental question is what makes two brain states similar. For example, what makes the activity in visual cortex elicited from viewing a robin similar to a sparrow? One common assumption in fMRI analysis is that neural similarity is described by Pearson correlation. However, there are a host of other possibilities, including Minkowski and Mahalanobis measures, with each differing in its mathematical, theoretical, neural computational assumptions. Moreover, the operable measures may vary across brain regions and tasks. Here, we evaluated which of several competing similarity measures best captured neural similarity. Our technique uses a decoding approach to assess the information present in a brain region and the similarity measures that best correspond to the classifier's confusion matrix are preferred. Across two published fMRI datasets, we found the preferred neural similarity measures were common across brain regions, but differed across tasks. Moreover, Pearson correlation was consistently surpassed by alternatives.
biorxiv neuroscience 100-200-users 2018Computational noise in reward-guided learning drives behavioral variability in volatile environments, bioRxiv, 2018-10-11
AbstractWhen learning the value of actions in volatile environments, humans often make seemingly irrational decisions which fail to maximize expected value. We reasoned that these ‘non-greedy’ decisions, instead of reflecting information seeking during choice, may be caused by computational noise in the learning of action values. Here, using reinforcement learning (RL) models of behavior and multimodal neurophysiological data, we show that the majority of non-greedy decisions stems from this learning noise. The trial-to-trial variability of sequential learning steps and their impact on behavior could be predicted both by BOLD responses to obtained rewards in the dorsal anterior cingulate cortex (dACC) and by phasic pupillary dilation – suggestive of neuromodulatory fluctuations driven by the locus coeruleus-norepinephrine (LC-NE) system. Together, these findings indicate that most of behavioral variability, rather than reflecting human exploration, is due to the limited computational precision of reward-guided learning.
biorxiv neuroscience 100-200-users 2018Functional clustering of dendritic activity during decision-making, bioRxiv, 2018-10-11
SummaryThe active properties of dendrites support local nonlinear operations, but previous imaging and electrophysiological measurements have produced conflicting views regarding the prevalence of local nonlinearities in vivo. We imaged calcium signals in pyramidal cell dendrites in the motor cortex of mice performing a tactile decision task. A custom microscope allowed us to image the soma and up to 300 μm of contiguous dendrite at 15 Hz, while resolving individual spines. New analysis methods were used to estimate the frequency and spatial scales of activity in dendritic branches and spines. The majority of dendritic calcium transients were coincident with global events. However, task-associated calcium signals in dendrites and spines were compartmentalized by dendritic branching and clustered within branches over approximately 10 μm. Diverse behavior-related signals were intermingled and distributed throughout the dendritic arbor, potentially supporting a large computational repertoire and learning capacity in individual neurons.
biorxiv neuroscience 100-200-users 2018Genetic variability in response to Aβ deposition influences Alzheimer’s risk, bioRxiv, 2018-10-09
AbstractGenetic analysis of late-onset Alzheimer’s disease risk has previously identified a network of largely microglial genes that form a transcriptional network. In transgenic mouse models of amyloid deposition we have previously shown that the expression of many of the mouse orthologs of these genes are co-ordinately up-regulated by amyloid deposition. Here we investigate whether systematic analysis of other members of this mouse amyloid-responsive network predicts other Alzheimer’s risk loci. This statistical comparison of the mouse amyloid-response network with Alzheimer’s disease genome-wide association studies identifies 5 other genetic risk loci for the disease (OAS1, CXCL10, LAPTM5, ITGAM and LILRB4). This work suggests that genetic variability in the microglial response to amyloid deposition is a major determinant for Alzheimer’s risk.One Sentence SummaryIdentification of 5 new risk loci for Alzheimer’s by statistical comparison of mouse Aβ microglial response with gene-based SNPs from human GWAS
biorxiv neuroscience 0-100-users 2018Bright and photostable chemigenetic indicators for extended in vivo voltage imaging, bioRxiv, 2018-10-06
Imaging changes in membrane potential using genetically encoded fluorescent voltage indicators (GEVIs) has great potential for monitoring neuronal activity with high spatial and temporal resolution. Brightness and photostability of fluorescent proteins and rhodopsins have limited the utility of existing GEVIs. We engineered a novel GEVI, Voltron, that utilizes bright and photostable synthetic dyes instead of protein-based fluorophores, extending the combined duration of imaging and number of neurons imaged simultaneously by more than tenfold relative to existing GEVIs. We used Voltron for in vivo voltage imaging in mice, zebrafish, and fruit flies. In mouse cortex, Voltron allowed single-trial recording of spikes and subthreshold voltage signals from dozens of neurons simultaneously, over 15 minutes of continuous imaging. In larval zebrafish, Voltron enabled the precise correlation of spike timing with behavior.
biorxiv neuroscience 200-500-users 2018High-performance GFP-based calcium indicators for imaging activity in neuronal populations and microcompartments, bioRxiv, 2018-10-04
AbstractCalcium imaging with genetically encoded calcium indicators (GECIs) is routinely used to measure neural activity in intact nervous systems. GECIs are frequently used in one of two different modes to track activity in large populations of neuronal cell bodies, or to follow dynamics in subcellular compartments such as axons, dendrites and individual synaptic compartments. Despite major advances, calcium imaging is still limited by the biophysical properties of existing GECIs, including affinity, signal-to-noise ratio, rise and decay kinetics, and dynamic range. Using structure-guided mutagenesis and neuron-based screening, we optimized the green fluorescent protein-based GECI GCaMP6 for different modes of in vivo imaging. The jGCaMP7 sensors provide improved detection of individual spikes (jGCaMP7s,f), imaging in neurites and neuropil (jGCaMP7b), and tracking large populations of neurons using 2-photon (jGCaMP7s,f) or wide-field (jGCaMP7c) imaging.
biorxiv neuroscience 200-500-users 2018