When two sufficiently different stimuli are presented to each eye, perception alternates between them. This binocular rivalry is conceived as a competition for representation in the single stream of visual consciousness. The magnocellular (M) and parvocellular (P) pathways, originating in the retina, encode disparate information, but their potentially different contributions to binocular rivalry have not been determined. Here, we used functional magnetic resonance imaging to measure the human lateral geniculate nucleus (LGN), where the M and P neurons are segregated into layers receiving input from a single eye. We had three participants (one male, two females) and used achromatic stimuli to avoid contributions from color opponent neurons that may have confounded previous studies. We observed activity in the eye-specific regions of LGN correlated with perception, with similar magnitudes during rivalry or physical stimuli alternations, also similar in the M and P regions. These results suggest that LGN acti...

A central question in neuroscience is how sensory inputs are transformed into percepts. At this point, it is clear that this process is strongly influenced by prior knowledge of the sensory environment. Bayesian ideal observer models provide a useful link between data and theory that can help researchers evaluate how prior knowledge is represented and integrated with incoming sensory information. However, the statistical prior employed by a Bayesian observer cannot be measured directly, and must instead be inferred from behavioral measurements. Here, we review the general problem of inferring priors from psychophysical data, and the simple solution that follows from assuming a prior that is a Gaussian probability distribution. As our understanding of sensory processing advances, however, there is an increasing need for methods to flexibly recover the shape of Bayesian priors that are not well approximated by elementary functions. To address this issue, we describe a novel approach that applies to arbitrary...

Long-term memory formation requires anterograde transport of proteins from the soma of a neuron to its distal synaptic terminals. This allows new synaptic connections to be grown and existing ones remodeled. However, we do not yet know which proteins are transported to synapses in response to activity and temporal regulation. Here, using quantitative mass spectrometry, we have profiled anterograde protein cargos of a learning-regulated molecular motor protein kinesin [ Aplysia kinesin heavy chain 1 (ApKHC1)] following short-term sensitization (STS) and long-term sensitization (LTS) in Aplysia californica . Our results reveal enrichment of specific proteins associated with ApKHC1 following both STS and LTS, as well as temporal changes within 1 and 3 h of LTS training. A significant number of proteins enriched in the ApKHC1 complex participate in synaptic function, and, while some are ubiquitously enriched across training conditions, a few are enriched in response to specific training. For instance, factors ...

The tuning properties of neurons in the visual system can be contextually modulated by the statistics of the area surrounding their receptive field (RF), particularly when the surround contains natural features. However, stimuli presented in specific egocentric locations may have greater behavioral relevance, raising the possibility that the extent of contextual modulation may vary with position in visual space. To explore this possibility, we utilized the small size and optical transparency of the larval zebrafish to describe the form and spatial arrangement of contextually modulated cells throughout an entire tectal hemisphere. We found that the spatial tuning of tectal neurons to a prey-like stimulus sharpens when the stimulus is presented against a background with the statistics of complex natural scenes, relative to a featureless background. These neurons are confined to a spatially restricted region of the tectum and have receptive fields centered within a region of visual space in which the presence...

Wnt signaling is crucial for synapse and cognitive function. Indeed, deficient Wnt signaling is causally related to increased expression of DKK1, an endogenous negative Wnt regulator, and synapse loss, both of which likely contribute to cognitive decline in Alzheimer’s disease (AD). Increasingly, AD research efforts have probed the neuroinflammatory role of microglia, the resident immune cells of the CNS, which have furthermore been shown to be modulated by Wnt signaling. The DKK1 homolog DKK2 has been previously identified as an activated response and/or disease-associated microglia (DAM/ARM) gene in a mouse model of AD. Here, we performed a detailed analysis of DKK2 in mouse models of neurodegeneration, and in human AD brain. In APP/PS1 and APPNL-G-F AD mouse model brains as well as in SOD1G93A ALS mouse model spinal cords, but not in control littermates, we demonstrated significant microgliosis and microglial Dkk2 mRNA upregulation in a disease-stage-dependent manner. In the AD models, these DAM/ARM Dkk...

The ability to interrogate specific representations in the brain, determining how, and where, difference sources of information are instantiated can provide invaluable insight into neural functioning. Pattern component modeling (PCM) is a recent analytic technique for human neuroimaging that allows the decomposition of representational patterns in brain into contributing subcomponents. In the current study, we present a novel PCM variant that tracks the contribution of prespecified representational patterns to brain representation across areas, thus allowing hypothesis-guided employment of the technique. We apply this technique to investigate the contributions of hedonic and nonhedonic information to the neural representation of tactile experience. We applied aversive pressure (AP) and appetitive brush (AB) to stimulate distinct peripheral nerve pathways for tactile information (C-/CT-fibers, respectively) while patients underwent functional magnetic resonance imaging (fMRI) scanning. We performed represen...

The direct and indirect pathways of the basal ganglia (BG) have been suggested to learn mainly from positive and negative feedbacks, respectively. Since these pathways unevenly receive inputs from different cortical neuron types and/or regions, they may preferentially use different state/action representations. We explored whether such a combined use of different representations, coupled with different learning rates from positive and negative reward prediction errors (RPEs), has computational benefits. We modeled animal as an agent equipped with two learning systems, each of which adopted individual representation (IR) or successor representation (SR) of states. With varying the combination of IR or SR and also the learning rates from positive and negative RPEs in each system, we examined how the agent performed in a dynamic reward navigation task. We found that combination of SR-based system learning mainly from positive RPEs and IR-based system learning mainly from negative RPEs could achieve a good per...

Avoiding potentially harmful, and consuming safe food is crucial for the survival of living organisms. However, the perceived valence of sensory information can change following conflicting experiences. Pleasurability and aversiveness are two crucial parameters defining the perceived valence of a taste and can be impacted by novelty. Importantly, the ability of a given taste to serve as the conditioned stimulus (CS) in conditioned taste aversion (CTA) is dependent on its valence. Activity in anterior insula (aIC) Layer IV–VI pyramidal neurons projecting to the basolateral amygdala (BLA) is correlated with and necessary for CTA learning and retrieval, as well as the expression of neophobia toward novel tastants, but not learning taste familiarity. Yet, the cellular mechanisms underlying the updating of taste valence representation in this specific pathway are poorly understood. Here, using retrograde viral tracing and whole-cell patch-clamp electrophysiology in trained mice, we demonstrate that the intrinsi...

The ventral lateral geniculate nucleus (vLGN) is a retinorecipient region of thalamus that contributes to a number of complex visual behaviors. Retinal axons that target vLGN terminate exclusively in the external subdivision (vLGNe), which is also transcriptionally and cytoarchitectonically distinct from the internal subdivision (vLGNi). While recent studies shed light on the cell types and efferent projections of vLGNe and vLGNi, we have a crude understanding of the source and nature of the excitatory inputs driving postsynaptic activity in these regions. Here, we address this by conducting in vitro whole-cell recordings in acutely prepared thalamic slices and using electrical and optical stimulation techniques to examine the postsynaptic excitatory activity evoked by the activation of retinal or cortical layer V input onto neurons in vLGNe and vLGNi. Activation of retinal afferents by electrical stimulation of optic tract or optical stimulation of retinal terminals resulted in robust driver-like excitato...

The study used machine learning to predict The American Spinal Injury Association Impairment Scale (AIS) scores for newly injured spinal cord injury patients at hospital discharge time from hospital admission data. Additionally, machine learning was used to analyze the best model for feature importance to validate the criticality of the AIS score and highlight relevant demographic details. The data used for training machine learning models was from the National Spinal Cord Injury Statistical Center (NSCISC) database of U.S. spinal cord injury patient details. Eighteen real features were used from 417 provided features, which mapped to 53 machine learning features after processing. Eight models were tuned on the dataset to predict AIS scores, and Shapely analysis was performed to extract the most important of the 53 features. Patients within the NSCISC database who sustained injuries were between 1972 and 2016 after data cleaning ( n  = 20,790). Outcomes were test set multiclass accuracy and aggregated Shap...