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Overlap among spatial memories triggers divergence of hippocampal representations

Across the domains of spatial navigation and episodic memory, the hippocampus is thought to play a critical role in disambiguating (pattern separating) representations of overlapping events. However, the mechanisms underlying hippocampal pattern separation are not fully understood. Here, using a naturalistic route-learning paradigm and spatiotemporal pattern analysis of human fMRI data, we found that hippocampal representations of overlapping routes gradually diverged with learning to the point that they became less similar than representations of non-overlapping events. This representational reversal of the objective route similarity (a) was selective to the hippocampus, (b) only occurred for the specific route segments that were shared across routes, and (c) was predicted by the degree to which individual hippocampal voxels were initially shared across route representations. These findings indicate that event overlap triggers a repulsion of hippocampal representations--a finding that provides critical mechanistic insight into how and why hippocampal representations become separated.

neuroscience

NAPR: a cloud-based framework for neuroanatomical age prediction

This paper describes NAPR, a cloud-based framework for accessing age prediction models created using machine learning-based analysis of neuroimaging data. The NAPR service is provided at https://www.cloudneuro.org. The NAPR system allows external users to predict the age of individual subjects using their own MRI data. As a demonstration of the NAPR approach, age prediction models were trained using healthy control data from the ABIDE, CoRR, DLBS and NKI Rockland neuroimaging datasets (total N = 2367). MRI scans were processed using Freesurfer v5.3. Age prediction models were trained using relevance vector machines and Gaussian processes machine learning techniques. NAPR will allow for rigorous and transparent out-of-sample assessment of age prediction model performance, and may therefore assist in the translation of neuroimaging-based modelling techniques to the clinic.

neuroscience

Glutamate release is inhibitory and unnecessary for the long-term potentiation of presynaptic function

Long-term potentiation (LTP) and long-term depression (LTD) of transmitter release probability (Pr) are thought to be triggered by the activation of glutamate receptors. Here, we demonstrate that glutamate release at CA3-CA1 synapses is in fact inhibitory and unnecessary for increases in Pr. Instead, at active presynaptic terminals, postsynaptic depolarization alone can increase Pr by promoting the release of nitric oxide from neuronal dendrites in a manner dependent on L-type voltage-gated Ca2+ channels. The release of glutamate, in contrast, decreases Pr by activating presynaptic NMDA receptors (NMDAR). Thus, net changes in Pr are determined by the combined effect of both LTP-promoting and LTD-promoting processes, that is, by the amount of glutamate release and postsynaptic depolarization that accompany presynaptic activity, respectively. Neither of these processes directly depends on the activation of postsynaptic NMDARs. We further show that presynaptic changes can be captured by a simple learning rule, in which the role of presynaptic plasticity is to ensure that the ability for a presynaptic terminal to release glutamate is matched with its ability to predict postsynaptic spiking.

neuroscience

Glucocorticoids change neural decoding in the middle cingulate cortex accompanied by a reduction of subjective fear in patients with spider phobia

Glucocorticoids--stress hormones released from the adrenal cortex--reduce phobic fear in anxiety disorders and enhance psychotherapy, possibly by reducing the retrieval of fear memories and enhancing the consolidation of new corrective memories. Glucocorticoid signaling in the basolateral amygdala can influence connected fear and memory-related cortical regions, but this is not fully understood. Previous studies investigated specific pathways moderated by glucocorticoids, for example, visual-temporal pathways; however, these analyses were limited to a-priori selected regions. Here, we performed whole-brain pattern analysis to localize phobic stimulus decoding related to the fear-reducing effect of glucocorticoids. We reanalyzed functional magnetic resonance imaging (fMRI) data from a previously published study with spider-phobic patients and healthy controls. The patients received either glucocorticoids or a placebo treatment before the exposure to spider images. There was moderate evidence that patients with phobia had higher decoding of phobic content in the anterior cingulate cortex (ACC) and the left and right anterior insula compared to controls. Decoding in the ACC and the right insula showed strong evidence for correlation with experienced fear. Patients with cortisol reported a reduction of fear by 10-13%; however, there was only weak evidence for changes in neural decoding compared to placebo which was found in the precuneus, the opercular cortex, and the left cerebellum.

neuroscience

Locomotor activity modulates associative learning in mouse cerebellum

Changes in behavioral state are associated with modulation of sensory responses across visual, auditory and somatosensory cortices. Here we show that locomotor activity independently modulates performance in delay eyeblink conditioning, a cerebellum-dependent form of associative learning. Increased locomotor speed in head-fixed mice was associated with earlier onset of learning and trial-by-trial enhancement of learned responses. The influence of locomotion on conditioned responses was dissociable from changes in arousal and was independent of the sensory modality of the conditioned stimulus. Eyelid responses evoked by optogenetic stimulation of mossy fiber terminals within the cerebellar cortex, but not at sites downstream, were also positively modulated by ongoing locomotion. We conclude that locomotor activity modulates delay eyeblink conditioning through mechanisms acting on the mossy fiber pathway within the cerebellar cortex. Taken together, these results suggest a novel role for behavioral state modulation in associative learning and provide a potential mechanism through which engaging in movement can improve an individuals ability to learn.

neuroscience

Identification of Mechanisms of Functional Signaling Between Human Hippocampus Regions

BackgroundStandard BOLD connectivity analyses depend on aggregating the signals of individual voxels within regions of interest (ROIs). In certain cases, this spatial aggregation implies a loss of valuable functional and anatomical information about subsets of voxels that drive the ROI level connectivity.\n\nNew MethodWe use the FGES algorithm, a data-driven score-based graphical search method, to identify subsets of voxels that are chiefly responsible for exchanging signals between ROIs. We apply the method to high-resolution resting state functional magnetic resonance imaging (rs-fMRI) data from medial temporal lobe regions of interest of a single healthy individual measured repeated times over a year and a half.\n\nResultsThe FGES algorithm recovered subsets of voxels within larger medial temporal lobe ROIs of entorhinal cortex and hippocampus subfields that show spatially consistency across different scanning sessions, and are statistically significant under tests that validate the role of these subsets as main drivers of effective connectivity between hippocampal regions of interest.\n\nComparison with Existing MethodsIn contrast to standard functional connectivity methods, the FGES algorithm is robust against false positive connections produced by transitive closures of adjacencies (correlation methods) and common effect conditioning (Markov random field methods).\n\nConclusionsThe FGES algorithm allows for identification of communication subsets of voxels driving the connectivity between regions of interest, recovering valuable anatomical and functional information that is lost when ROIs are aggregated. The FGES algorithm is specially suited for voxelwise connectivity research, given its short running time and scalability to big data problems.

neuroscience

Toddlers later diagnosed with autism exhibit multiple structural abnormalities in temporal corpus callosum fibers

Interhemispheric functional connectivity abnormalities are often reported in autism and it is thus not surprising that structural defects of the corpus callosum (CC) are consistently found using both traditional MRI and DTI techniques. Past DTI studies however, have subdivided the CC into 2 or 3 segments without regard for where fibers may project to within the cortex, thus placing limitations on our ability to understand the nature, timing and neurobehavioral impact of early CC abnormalities in autism. Leveraging a unique cohort of 97 toddlers (68 autism; 29 typical) we utilized a novel technique that identified seven CC tracts according to their cortical projections. Results revealed that younger (<2.5 years old), but not older toddlers with autism exhibited abnormally low mean, radial, and axial diffusivity values in the CC tracts connecting the occipital lobes and the temporal lobes. Fractional anisotropy and the cross sectional area of the temporal CC tract were significantly larger in young toddlers with autism. These findings indicate that water diffusion is more restricted and unidirectional in the temporal CC tract of young toddlers who develop autism. Such results may be explained by a potential overabundance of small caliber axons generated by excessive prenatal neural proliferation as proposed by previous genetic, animal model, and postmortem studies of autism. Furthermore, early diffusion measures in the temporal CC tract of the young toddlers were correlated with outcome measures of autism severity at later ages. These findings regarding the potential nature, timing, and location of early CC abnormalities in autism add to accumulating evidence, which suggests that altered inter-hemispheric connectivity, particularly across the temporal lobes, is a hallmark of the disorder.

neuroscience

SynEM: Automated synapse detection for connectomics

Nerve tissue contains a high density of chemical synapses, about 1 per {micro}m3 in the mammalian cerebral cortex. Thus, even for small blocks of nerve tissue, dense connectomic mapping requires the identification of millions to billions of synapses, of which about 80-90% are excitatory synapses. While the focus of connectomic data analysis has been on neurite reconstruction, synapse detection becomes limiting when datasets grow in size and dense mapping is required. Here, we report SynEM, a method for automated detection of excitatory synapses from conventionally en-bloc stained 3D electron microscopy image stacks. The approach is based on a segmentation of the image data and focuses on classifying borders between neuronal processes as synaptic or non-synaptic. SynEM yields 98% precision and recall in binary excitatory cortical connectomes with no user interaction. It scales to large volumes of cortical neuropil, plausibly even whole-brain datasets. SynEM removes the burden of manual synapse annotation for large densely mapped connectomes.

neuroscience

The impact of visual gaze direction on auditory object tracking

Subjective experience suggests that we are able to direct our auditory attention independent of our visual gaze, e.g when shadowing a nearby conversation at a cocktail party. But what are the consequences at the behavioural and neural level? While numerous studies have investigated both auditory attention and visual gaze independently, little is known about their interaction during selective listening. In the present EEG study, we manipulated visual gaze independently of auditory attention while participants detected targets presented from one of three loudspeakers. We observed increased response times when gaze was directed away from the locus of auditory attention. Further, we found an increase in occipital alpha-band power contralateral to the direction of gaze, indicative of a suppression of distracting input. Finally, this condition also led to stronger central theta-band power, which correlated with the observed effect in response times, indicative of differences in top-down processing. Our data suggest that a misalignment between gaze and auditory attention both reduce behavioural performance and modulate underlying neural processes. The involvement of central theta-band and occipital alpha-band effects are in line with compensatory neural mechanisms such as increased cognitive control and the suppression of task irrelevant inputs.

neuroscience

Network component analysis reveals developmental trajectories of structural connectivity and specific alterations in autism spectrum disorder

The structural organisation of the brain can be characterised as a hierarchical ensemble of segregated modules linked by densely interconnected hub regions that facilitate distributed functional interactions. Disturbances to this network may be an important marker of abnormal development. Recently, several neurodevelopmental disorders, including autism spectrum disorder (ASD), have been framed as disorders of connectivity but the full nature and timing of these disturbances remain unclear.\n\nIn this study, we use non-negative matrix factorisation, a data-driven, multivariate approach, to model the structural network architecture of the brain as a set of superposed subnetworks, or network components.\n\nIn an openly available dataset of 196 subjects scanned between 5 to 85 years we identify a set of robust and reliable subnetworks that develop in tandem with age and reflect both anatomically local and long-range, network hub connections. In a second experiment, we compare network components in a cohort of 51 high-functioning ASD adolescents to a group of age-matched controls. We identify a specific subnetwork representing an increase in local connection strength in the cingulate cortex in ASD (t=3.44, p<0.001).\n\nThis work highlights possible long-term implications of alterations to the developmental trajectories of specific cortical subnetworks.

neuroscience

Molecular pathway underlying bouton stabilization by Semaphorin4D during inhibitory synapse formation

Changes in inhibitory connections are essential for experience-dependent circuit adaptations. Defects in inhibitory synapses are linked to neurodevelopmental disorders, but the molecular processes underlying inhibitory synapse formation are not well understood. Here we use high resolution two-photon microscopy in organotypic hippocampal slices to examine the signaling pathways induced by the postsynaptic signaling molecule Semaphorin4D (Sema4D) during inhibitory synapse formation. By monitoring changes in individual GFP-labeled presynaptic boutons we found that the primary action of Sema4D is to induce stabilization of presynaptic boutons within tens of minutes. Stabilizing boutons rapidly recruited synaptic vesicles, which was followed by accumulation of postsynaptic gephyrin. Newly formed inhibitory synapses were complete and functional after 24 hours, as determined by electrophysiology and immunohistochemistry. We further showed that Sema4D signaling is regulated by network activity and can induce a local increase in bouton density, suggesting a possible role in circuit adaptation. We further examined the intracellular signaling cascade triggered by Sema4D and found that bouton stabilization occurred through rapid remodeling of actin, and this could be mimicked by the actin-depolymerizing drug Latrunculin B or by reducing ROCK activity. The intracellular signaling cascade required activation of the receptor tyrosine kinase MET, which is a well-known autism risk factor. Our immunohistochemistry data suggests that MET may be localized to presynaptic inhibitory axons. Together, our data yield important insights in the molecular pathway underlying activity-dependent Sema4D-induced synapse formation and reveal a novel role for MET in inhibitory synapses.\n\nSignificance StatementGABAergic synapses provide the main inhibitory control of neuronal activity in the brain. We make important steps in unraveling the molecular processes that take place when formation of inhibitory synapses is triggered by a specific signaling molecule, Sema4D. We find that this process depends on network activity and involves specific remodeling of the intracellular actin cytoskeleton. We also reveal a previously unknown role for MET in inhibitory synapses. As defects in GABAergic synapses have been implied in many brain disorders, and mutations in MET are strong risk factors for autism, our findings urge for a further investigation of the role of MET at inhibitory synapses.

neuroscience

Computations underlying peoples risk-preferences in social interactions

Interacting with others to decide how finite resources should be allocated between parties which may have competing interests is an important part of social life. Considering that not all of our proposals to others are always accepted, the outcomes of such social interactions are, by their nature, probabilistic and risky. Here, we highlight cognitive processes related to value computations in human social interactions, based on mathematical modelling of the proposer behavior in the Ultimatum Game. Our results suggest that the perception of risk is an overarching process across non-social and social decision-making, whereas nonlinear weighting of others acceptance probabilities is unique to social interactions in which others valuation processes needs to be inferred. Despite the complexity of social decision-making, human participants make near-optimal decisions by dynamically adjusting their decision parameters to the changing social value orientation of their opponents through influence by multidimensional inferences they make about those opponents (e.g. how prosocial they think their opponent is relative to themselves).

neuroscience

Effects of altered excitation-inhibition balance on decision making in a cortical circuit model

BackgroundDisruption of the synaptic balance between excitation and inhibition (E/I balance) in cortical circuits is a leading hypothesis for pathophysiologies of neuropsychiatric disorders, such as schizophrenia. However, it is poorly understood how synaptic E/I disruptions propagate upward to induce cognitive deficits, including impaired decision making (DM).\n\nMethodsWe investigated how E/I perturbations may impair temporal integration of evidence during perceptual DM in a biophysically-based model of association cortical microcircuits. Using multiple psychophysical task paradigms, we characterized effects of NMDA receptor hypofunction at two key synaptic sites: inhibitory interneurons (elevating E/I ratio, via disinhibition), versus excitatory pyramidal neurons (lowering E/I ratio).\n\nResultsDisruption of E/I balance in either direction can similarly impair DM as assessed by psychometric performance, following inverted-U dependence. Nonetheless, these regimes make dissociable predictions for task paradigms that characterize the time course of evidence accumulation. Under elevated E/I ratio, DM is impulsive: evidence early in time is weighted much more than late evidence. In contrast, under lowered E/I ratio, DM is indecisive: evidence integration and winner-take-all competition between options are weakened. These effects are well captured by an extended drift-diffusion model with self-coupling.\n\nConclusionsOur findings characterize critical roles of cortical E/I balance in cognitive functions, the utility of timing-sensitive psychophysical paradigms, and relationships between circuit and psychological models. The model makes specific predictions for behavior and neural activity that are testable in humans or animals under causal manipulations of E/I balance and in disease states.

neuroscience

A lineage-related reciprocal inhibition circuitry for sensory-motor action selection

The insect central complex and vertebrate basal ganglia are forebrain centres involved in selection and maintenance of behavioural actions. However, little is known about the formation of the underlying circuits, or how they integrate sensory information for motor actions. Here, we show that paired embryonic neuroblasts generate central complex ring neurons that mediate sensory-motor transformation and action selection in Drosophila. Lineage analysis resolves four ring neuron subtypes, R1-R4, that form GABAergic inhibition circuitry among inhibitory sister cells. Genetic manipulations, together with functional imaging, demonstrate subtype-specific R neurons mediate the selection and maintenance of behavioural activity. A computational model substantiates genetic and behavioural observations suggesting that R neuron circuitry functions as salience detector using competitive inhibition to amplify, maintain or switch between activity states. The resultant gating mechanism translates facilitation, inhibition and disinhibition of behavioural activity as R neuron functions into selection of motor actions and their organisation into action sequences.

neuroscience

Altered topology of neural circuits in congenital prosopagnosia

Using a novel fMRI-based inter-subject functional correlation (ISFC) approach, which isolates stimulus-locked inter-regional correlation patterns, we compared the cortical topology of the neural circuit for face processing in participants with congenital prosopagnosia (CP) and matched controls. Whereas the anterior temporal lobe served as the major network hub for face processing in controls, this was not the case for the CPs. Instead, this group evinced hyper-connectivity in posterior regions of the visual cortex, mostly associated with the lateral occipital and the inferior temporal cortices. Moreover, the extent to which the network organization was atypical differed as a function of the severity of the face recognition deficit. These results offer new insights into the perturbed cortical topology in CP, which may serve as the underlying neural basis of the behavioral deficits typical of this disorder. The approach adopted here has the potential to uncover altered topologies in other neurodevelopmental disorders, as well.\n\nSignificance StatementCongenital prosopagnosia (CP; face blindness), a developmental deficit in face recognition, is thought to affect up to 3% of the population. Understanding its neural basis is challenging as there is no obvious deficit on conventional structural or functional MRI scans. Using an innovative, fMRI-based inter-subject correlation approach geared towards tracking inter-regional stimulus-locked brain activation, the present study uncovers marked topological differences in a distributed brain network of higher-order visual regions in CP relative to controls. Alteration in topology also differs as a function of the severity of the deficit. These findings shed new light on the neural perturbations underlying CP, and the analytic approach we have adopted may have utility in elucidating the neural basis of other neurodevelopmental disorders such as dyslexia or amusia.

neuroscience

A Change-point Analysis Method for Single-trial Study of Simultaneous EEG-fMRI of Auditory/Visual Oddball Task

Simultaneous EEG-fMRI has been vastly used to investigate functional networks of brain combining high spatial resolution (millimeter) of fMRI with high temporal resolution (millisecond) of EEG. However, to extract the most relevant information from the acquired data, it is necessary to develop analysis methods with less ad hoc assumptions. To this end, brain rhythms are often used which are the specific frequency-bands of EEG signal and assumed to represent diverse sub-second cognitive processes at different parts of the cortex. Furthermore, single-trial analysis of EEG is believed to show more realistic picture of ongoing and event-related activities of brain. Here, we present a nonparametric multiple change-point detection and estimation method for the single-trial analysis of simultaneous EEG-fMRI experiment recorded during auditory and visual oddball tasks. In a simple attention task like oddball, the frontal cortex of brain is responsible to distinguish and respond appropriately to target versus standard events. By using EEG signal at the frontal cortex, we show that the -band activity changes according to \"inhibition timing\" hypothesis and the {beta}-band activity is in line with \"maintaining the status quo\" hypothesis. Furthermore, using these activities to build regressors in the GLM analysis of fMRI, we localize active brain regions with high spatial and temporal resolutions and elaborate further on the coordination of attentional networks across brain.

neuroscience

Spatially periodic activation patterns of retrosplenial cortex encode route sub-spaces and distance travelled

Traversal of a complicated route is often facilitated by considering it as a set of related sub-spaces. Such compartmentalization processes could occur within retrosplenial cortex, a structure whose neurons simultaneously encode position within routes and other spatial coordinate systems. Here, retrosplenial cortex neurons were recorded as rats traversed a track having recurrent structure at multiple scales. Consistent with a major role in compartmentalization of complex routes, individual RSC neurons exhibited periodic activation patterns that repeated across route segments having the same shape. Concurrently, a larger population of RSC neurons exhibited single-cycle periodicity over the full route, effectively defining a framework for encoding of sub-route positions relative to the whole. The same population simultaneously provides a novel metric for distance from each route position to all others. Together, the findings implicate retrosplenial cortex in the extraction of path sub-spaces, the encoding of their spatial relationships to each other, and path integration.

neuroscience

On the relationship between psychopathy and general intelligence: A meta-analytic review

Substantial research has investigated the association between intelligence and psychopathic traits. The findings to date have been inconsistent and have not always considered the multi-dimensional nature of psychopathic traits. Moreover, there has been a tendency to confuse psychopathy with other closely related, clinically significant disorders. The current study represents a meta-analysis conducted to evaluate the direction and magnitude of the association of intelligence with global psychopathy, as well as its factors and facets, and related disorders (Antisocial Personality Disorder, Conduct Disorder, and Oppositional Defiant Disorder). Our analyses revealed a small, significant, negative relationship between intelligence and total psychopathy (r = -.07, p = .001). Analysis of factors and facets found differential associations, including both significant positive (e.g., interpersonal facet) and negative (e.g., affective facet) associations, further affirming that psychopathy is a multi-dimensional construct. Additionally, intelligence was negatively associated with Antisocial Personality Disorder (r = -.13, p = .001) and Conduct Disorder (r = -.11, p = .001), but positively with Oppositional Defiant Disorder (r = .06, p = .001). There was significant heterogeneity across studies for most effects, but the results of moderator analyses were inconsistent. Finally, bias analyses did not find significant evidence for publication bias or outsized effects of outliers.

neuroscience