More Like this

1. Comparative analysis reveals distinctive epigenetic features of the human cerebellum

   https://doi.org/10.1371/journal.pgen.1009506  

   Guevara, Elaine E. ; Hopkins, William D. ; Hof, Patrick R. ; Ely, John J. ; Bradley, Brenda J. ; Sherwood, Chet C. ( May 2021 , PLOS Genetics)

   Gojobori, Takashi (Ed.)

   Identifying the molecular underpinnings of the neural specializations that underlie human cognitive and behavioral traits has long been of considerable interest. Much research on human-specific changes in gene expression and epigenetic marks has focused on the prefrontal cortex, a brain structure distinguished by its role in executive functions. The cerebellum shows expansion in great apes and is gaining increasing attention for its role in motor skills and cognitive processing, including language. However, relatively few molecular studies of the cerebellum in a comparative evolutionary context have been conducted. Here, we identify human-specific methylation in the lateral cerebellum relative to the dorsolateral prefrontal cortex, in a comparative study with chimpanzees ( Pan troglodytes ) and rhesus macaques ( Macaca mulatta ). Specifically, we profiled genome-wide methylation levels in the three species for each of the two brain structures and identified human-specific differentially methylated genomic regions unique to each structure. We further identified which differentially methylated regions (DMRs) overlap likely regulatory elements and determined whether associated genes show corresponding species differences in gene expression. We found greater human-specific methylation in the cerebellum than the dorsolateral prefrontal cortex, with differentially methylated regions overlapping genes involved in several conditions or processes relevant to human neurobiology,more »including synaptic plasticity, lipid metabolism, neuroinflammation and neurodegeneration, and neurodevelopment, including developmental disorders. Moreover, our results show some overlap with those of previous studies focused on the neocortex, indicating that such results may be common to multiple brain structures. These findings further our understanding of the cerebellum in human brain evolution.« less
2. Co-operation of long-term and working memory representations in simultaneous chaining by rhesus monkeys ( Macaca mulatta )

   https://doi.org/10.1177/1747021819838432  

   Templer, Victoria L. ; Gazes, Regina Paxton ; Hampton, Robert R. ( April 2019 , Quarterly Journal of Experimental Psychology)

   We studied the memory representations that control execution of action sequences by training rhesus monkeys ( Macaca mulatta) to touch sets of five images in a predetermined arbitrary order (simultaneous chaining). In Experiment 1, we found that this training resulted in mental representations of ordinal position rather than learning associative chains, replicating the work of others. We conducted novel analyses of performance on probe tests consisting of two images “derived” from the full five-image lists (i.e., test B, D from list A→B→C→D→E). We found a “first item effect” such that monkeys responded most quickly to images that occurred early in the list in which they had been learned, indicating that monkeys covertly execute known lists mentally until an image on the screen matches the one stored in memory. Monkeys also made an ordinal comparison of the two images presented at test based on long-term memory of positional information, resulting in a “symbolic distance effect.” Experiment 2 indicated that ordinal representations were based on absolute, rather than on relative, positional information because subjects did not link two lists into one large list after linking training, unlike what occurs in transitive inference. We further examined the contents of working memory during listmore »execution in Experiments 3 and 4 and found evidence for a prospective, rather than a retrospective, coding of position in the lists. These results indicate that serial expertise in simultaneous chaining results in robust absolute ordinal coding in long-term memory, with rapidly updating prospective coding of position in working memory during list execution.

   « less
3. Ketamine disrupts naturalistic coding of working memory in primate lateral prefrontal cortex networks

   https://doi.org/10.1038/s41380-021-01082-5  

   Roussy, Megan ; Luna, Rogelio ; Duong, Lyndon ; Corrigan, Benjamin ; Gulli, Roberto A. ; Nogueira, Ramon ; Moreno-Bote, Rubén ; Sachs, Adam J. ; Palaniyappan, Lena ; Martinez-Trujillo, Julio C. ( May 2021 , Molecular Psychiatry)

   null (Ed.)

   Abstract Ketamine is a dissociative anesthetic drug, which has more recently emerged as a rapid-acting antidepressant. When acutely administered at subanesthetic doses, ketamine causes cognitive deficits like those observed in patients with schizophrenia, including impaired working memory. Although these effects have been linked to ketamine’s action as an N-methyl-D-aspartate receptor antagonist, it is unclear how synaptic alterations translate into changes in brain microcircuit function that ultimately influence cognition. Here, we administered ketamine to rhesus monkeys during a spatial working memory task set in a naturalistic virtual environment. Ketamine induced transient working memory deficits while sparing perceptual and motor skills. Working memory deficits were accompanied by decreased responses of fast spiking inhibitory interneurons and increased responses of broad spiking excitatory neurons in the lateral prefrontal cortex. This translated into a decrease in neuronal tuning and information encoded by neuronal populations about remembered locations. Our results demonstrate that ketamine differentially affects neuronal types in the neocortex; thus, it perturbs the excitation inhibition balance within prefrontal microcircuits and ultimately leads to selective working memory deficits.
4. A neural network for online spike classification that improves decoding accuracy

   https://doi.org/10.1152/jn.00641.2019  

   Issar, Deepa ; Williamson, Ryan C. ; Khanna, Sanjeev B. ; Smith, Matthew A. ( April 2020 , Journal of Neurophysiology)

   Separating neural signals from noise can improve brain-computer interface performance and stability. However, most algorithms for separating neural action potentials from noise are not suitable for use in real time and have shown mixed effects on decoding performance. With the goal of removing noise that impedes online decoding, we sought to automate the intuition of human spike-sorters to operate in real time with an easily tunable parameter governing the stringency with which spike waveforms are classified. We trained an artificial neural network with one hidden layer on neural waveforms that were hand-labeled as either spikes or noise. The network output was a likelihood metric for each waveform it classified, and we tuned the network’s stringency by varying the minimum likelihood value for a waveform to be considered a spike. Using the network’s labels to exclude noise waveforms, we decoded remembered target location during a memory-guided saccade task from electrode arrays implanted in prefrontal cortex of rhesus macaque monkeys. The network classified waveforms in real time, and its classifications were qualitatively similar to those of a human spike-sorter. Compared with decoding with threshold crossings, in most sessions we improved decoding performance by removing waveforms with low spike likelihood values. Furthermore, decodingmore »with our network’s classifications became more beneficial as time since array implantation increased. Our classifier serves as a feasible preprocessing step, with little risk of harm, that could be applied to both off-line neural data analyses and online decoding. NEW & NOTEWORTHY Although there are many spike-sorting methods that isolate well-defined single units, these methods typically involve human intervention and have inconsistent effects on decoding. We used human classified neural waveforms as training data to create an artificial neural network that could be tuned to separate spikes from noise that impaired decoding. We found that this network operated in real time and was suitable for both off-line data processing and online decoding.« less
5. Pinpointing the neural signatures of single-exposure visual recognition memory

   https://doi.org/10.1073/pnas.2021660118  

   Mehrpour, Vahid ; Meyer, Travis ; Simoncelli, Eero P. ; Rust, Nicole C. ( April 2021 , Proceedings of the National Academy of Sciences)

   Memories of the images that we have seen are thought to be reflected in the reduction of neural responses in high-level visual areas such as inferotemporal (IT) cortex, a phenomenon known as repetition suppression (RS). We challenged this hypothesis with a task that required rhesus monkeys to report whether images were novel or repeated while ignoring variations in contrast, a stimulus attribute that is also known to modulate the overall IT response. The monkeys’ behavior was largely contrast invariant, contrary to the predictions of an RS-inspired decoder, which could not distinguish responses to images that are repeated from those that are of lower contrast. However, the monkeys’ behavioral patterns were well predicted by a linearly decodable variant in which the total spike count was corrected for contrast modulation. These results suggest that the IT neural activity pattern that best aligns with single-exposure visual recognition memory behavior is not RS but rather sensory referenced suppression: reductions in IT population response magnitude, corrected for sensory modulation.