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Christelle Anaclet
Dec 12, 2012; 32:17970-17976
BehavioralSystemsCognitive

Neural responses are naturally variable from one moment to the next, even when the stimulus is held constant. What factors might underlie this variability in neural population activity? We hypothesized that spontaneous fluctuations in cortical stimulus representations are created by changes in arousal state. We tested the hypothesis using a combination of fMRI, probabilistic decoding methods, and pupillometry. Human participants (20 female, 12 male) were presented with gratings of random orientation. Shortly after viewing the grating, participants reported its orientation and gave their level of confidence in this judgment. Using a probabilistic fMRI decoding technique, we quantified the precision of the stimulus representation in the visual cortex on a trial-by-trial basis. Pupil size was recorded and analyzed to index the observer's arousal state. We found that the precision of the cortical stimulus representation, reported confidence, and variability in the behavioral orientation judgments varied from trial to trial. Interestingly, these trial-by-trial changes in cortical and behavioral precision and confidence were linked to pupil size and its temporal rate of change. Specifically, when the cortical stimulus representation was more precise, the pupil dilated more strongly prior to stimulus onset and remained larger during stimulus presentation. Similarly, stronger pupil dilation during stimulus presentation was associated with higher levels of subjective confidence, a secondary measure of sensory precision, as well as improved behavioral performance. Taken together, our findings support the hypothesis that spontaneous fluctuations in arousal state modulate the fidelity of the stimulus representation in the human visual cortex, with clear consequences for behavior.

Injuries to the central nervous system (CNS) can cause severe neurological deficits. Axonal regrowth is a fundamental process for the reconstruction of compensatory neuronal networks after injury; however, it is extremely limited in the adult mammalian CNS. In this study, we conducted a loss-of-function genetic screen in cortical neurons, combined with a Web resource-based phenotypic screen, and identified synaptotagmin 4 (Syt4) as a novel regulator of axon elongation. Silencing Syt4 in primary cultured cortical neurons inhibits neurite elongation, with changes in gene expression involved in signaling pathways related to neuronal development. In a spinal cord injury model, inhibition of Syt4 expression in cortical neurons prevented axonal sprouting of the corticospinal tract, as well as neurological recovery after injury. These results provide a novel therapeutic approach to CNS injury by modulating Syt4 function.

Sleep is known to drive the consolidation of motor memories. During nonrapid eye movement (NREM) sleep, the close temporal proximity between slow oscillations (SOs) and spindles ("nesting" of SO-spindles) is known to be essential for consolidation, likely because it is closely associated with the reactivation of awake task activity. Interestingly, recent work has found that spindles can occur in temporal clusters or "trains." However, it remains unclear how spindle trains are related to the nesting phenomenon. Here, we hypothesized that spindle trains are more likely when SOs co-occur in the prefrontal and motor cortex. We conducted simultaneous neural recordings in the medial prefrontal cortex (mPFC) and primary motor cortex (M1) of male rats training on the reach-to-grasp motor task. We found that intracortically recorded M1 spindles are organized into distinct temporal clusters. Notably, the occurrence of temporally precise SOs between mPFC and M1 was a strong predictor of spindle trains. Moreover, reactivation of awake task patterns is much more persistent during spindle trains in comparison with that during isolated spindles. Together, our work suggests that the precise coupling of SOs across mPFC and M1 may be a potential driver of spindle trains and persistent reactivation of motor memory during NREM sleep.

The superior colliculus receives a direct projection from retinal ganglion cells. In primates, it remains unknown if the same ganglion cells also supply the lateral geniculate nucleus. To address this issue, a double-label experiment was performed in two male macaques. The animals fixated a target while injection sites were scouted in the superior colliculus by recording and stimulating with a tetrode. Once suitable sites were identified, cholera toxin subunit B-Alexa Fluor 488 was injected via an adjacent micropipette. In a subsequent acute experiment, cholera toxin subunit B-Alexa Fluor 555 was injected into the lateral geniculate nucleus at matching retinotopic locations. After a brief survival period, ganglion cells were examined in retinal flatmounts. The percentage of double-labeled cells varied locally, depending on the relative efficiency of retrograde transport by each tracer and the precision of retinotopic overlap of injection sites in each target nucleus. In counting boxes with extensive overlap, 76–98% of ganglion cells projecting to the superior colliculus were double labeled. Cells projecting to the superior colliculus constituted 4.0–6.7% of the labeled ganglion cell population. In one particularly large zone, there were 5,746 cells labeled only by CTB-AF555, 561cells double labeled by CTB-AF555 and CTB-AF488, but no cell labeled only by CTB-AF488. These data indicate that retinal input to the macaque superior colliculus arises from a collateral axonal branch supplied by ~5% of the ganglion cells that project to the lateral geniculate nucleus. Surprisingly, there exist no ganglion cells that project exclusively to the SC.

In demanding listening situations, a listener's motivational state may affect their cognitive investment. Here, we aim to delineate how domain-specific sensory processing, domain-general neural alpha power, and pupil size as a proxy for cognitive investment encode influences of motivational state under demanding listening. Participants (male and female) performed an auditory gap-detection task while the pupil size and the magnetoencephalogram were simultaneously recorded. Task demand and a listener's motivational state were orthogonally manipulated through changes in gap duration and monetary-reward prospect, respectively. Whereas task difficulty impaired performance, reward prospect enhanced it. The pupil size reliably indicated the modulatory impact of an individual's motivational state. At the neural level, the motivational state did not affect auditory sensory processing directly but impacted attentional postprocessing of an auditory event as reflected in the late evoked-response field and alpha-power change. Both pregap pupil dilation and higher parietal alpha power predicted better performance at the single-trial level. The current data support a framework wherein the motivational state acts as an attentional top–down neural means of postprocessing the auditory input in challenging listening situations.

Odor information arrives first in the main olfactory bulb and is then broadcasted to the olfactory cortices and striatum. Downstream regions have unique cellular and connectivity architectures that may generate different coding patterns to the same odors. To reveal region-specific response features, tuning and decoding of single-unit populations, we recorded responses to the same odors under the same conditions across regions, namely, the main olfactory bulb (MOB), the anterior olfactory nucleus (AON), the anterior piriform cortex (aPC), and the olfactory tubercle of the ventral striatum (OT), of awake male mice. We focused on chemically closely related aldehydes that still create distinct percepts. The MOB had the highest decoding accuracy for aldehydes and was the only region encoding chemical similarity. The MOB had the highest fraction of inhibited responses and narrowly tuned odor-excited responses in terms of timing and odor selectivity. Downstream, the interconnected AON and aPC differed in their response patterns to the same stimuli. While odor-excited responses dominated the AON, the aPC had a comparably high fraction of odor-inhibited responses. Both cortices share a main output target that is the MOB. This prompted us to test if the two regions convey also different net outputs. Aldehydes activated AON terminals in the MOB as a bulk signal but inhibited those from the aPC. The differential cortical projection responses generalized to complex odors. In summary, olfactory regions reveal specialized features in their encoding with AON and aPC differing in their local computations, thereby generating inverse net centrifugal and intercortical outputs.

Systemic study of pathogenic pathways and interrelationships underlying genes associated with Alzheimer's disease (AD) facilitates the identification of new targets for effective treatments. Recently available large-scale multiomics datasets provide opportunities to use computational approaches for such studies. Here, we devised a novel disease gene identification (digID) computational framework that consists of a semi-supervised deep learning classifier to predict AD-associated genes and a protein–protein interaction (PPI) network-based analysis to prioritize the importance of these predicted genes in AD. digID predicted 1,529 AD-associated genes and revealed potentially new AD molecular mechanisms and therapeutic targets including GNAI1 and GNB1, two G-protein subunits that regulate cell signaling, and KNG1, an upstream modulator of CDC42 small G-protein signaling and mediator of inflammation and candidate coregulator of amyloid precursor protein (APP). Analysis of mRNA expression validated their dysregulation in AD brains but further revealed the significant spatial patterns in different brain regions as well as among different subregions of the frontal cortex and hippocampi. Super-resolution STochastic Optical Reconstruction Microscopy (STORM) further demonstrated their subcellular colocalization and molecular interactions with APP in a transgenic mouse model of both sexes with AD-like mutations. These studies support the predictions made by digID while highlighting the importance of concurrent biological validation of computationally identified gene clusters as potential new AD therapeutic targets.

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