Biology subjects

Bullock, D.

Publications and source records attributed to Bullock, D..

5 recordsLinked to original sources

bioRxiv2022

Emotional intensity can enrich or degrade memories: impact of the amygdalar pathway on hippocampus through inhibitory neurons

The brains emotional system powerfully modulates processing of context and episodic memory. A key pathway that mediates these effects is the projection from the amygdala to the hippocampus. Wang and Barbas (1) uncovered a distinctive pattern in the pathways from amygdala to hippocampus in primates. In hippocampal CA3, a pathway from the amygdala innervated excitatory pyramidal neurons as well as parvalbumin (PV) and calretinin (CR) inhibitory neurons. In hippocampal CA1, amygdalar projections also innervated pyramidal neurons and CR interneurons, but not PV interneurons. The effects of these complex circuits can best be probed using computational simulations. We developed a model of spiking neurons to investigate the implications and significance of these amygdala-hippocampal circuits for affective influence on processing mnemonic context, and to test their effects as input from the amygdala gradually increased. Our simulations revealed that moderate input from the amygdala can enhance detail in CA3 representations that can correctly sort out contexts and episodes from memory. However, high amygdalar input suppressed CA3 responses to non-amygdalar inputs through powerful inhibitory neurons, leading to memory representations that lack detail. Moreover, high amygdalar input prematurely hastened the timing of responses in CA1 occurring when the current situation broadly and non-specifically matched a remembered context. Amygdalar pathways to hippocampus enable a mechanism whereby affective signaling appropriately enhances hippocampal representations of remembered context. However, when amygdalar input is excessive in high emotional arousal, there is loss of memory detail and overgeneralization, as seen in post-traumatic stress disorder or pathologic phobias.

neuroscience↗

bioRxiv2020

Collegiate athlete brain data for white matter mapping and network neuroscience

We describe a dataset of processed data with associated reproducible preprocessing pipeline collected from two collegiate athlete groups and one non-athlete group. The dataset shares minimally processed diffusion-weighted magnetic resonance imaging (dMRI) data, three models of the diffusion signal in the voxel, full-brain tractograms, segmentation of the major white matter tracts as well as structural connectivity matrices. There is currently a paucity of similar datasets openly shared. Furthermore, major challenges are associated with collecting this type of data. The data and derivatives shared here can be used as a reference to study the effects of long-term exposure to collegiate athletics, such as the effects of repetitive head impacts. We use advanced anatomical and dMRI data processing methods publicly available as reproducible web services at brainlife.io.

neuroscience↗

bioRxiv2020

Visual information routes in the posterior dorsal and ventral face network studied with intracranial neurophysiology, and white matter tract endpoints

Occipito-temporal regions within the face network process perceptual and socio-emotional information, but the dynamics and information flow between different nodes of this network is still debated. Here, we analyzed intracerebral EEG from 11 epileptic patients viewing a stimulus sequence beginning with a neutral face with direct gaze. The gaze could avert or remain direct, while the emotion changed to fearful or happy. N200 field potential peak latencies indicated that face processing begins in inferior occipital cortex and proceeds anteroventrally to fusiform and inferior temporal cortices, in parallel. The superior temporal sulcus responded preferentially to gaze changes with augmented field potential amplitudes for averted versus direct gaze, and large effect sizes relative to other network regions. An overlap analysis of posterior white matter tractography endpoints (from 1066 healthy brains) relative to active intracerebral electrodes in the 11 patients showed likely involvement of both dorsal and ventral posterior white matter pathways. Overall, our data provide new insight on the timing of face and social cue processing in the occipito-temporal brain and anchor the superior temporal cortex in dynamic gaze processing.

animal behavior and cognition↗

bioRxiv2020

Classifyber, a robust streamline-based linear classifier for white matter bundle segmentation

Virtual delineation of white matter bundles in the human brain is of paramount importance for multiple applications, such as pre-surgical planning and connectomics. A substantial body of literature is related to methods that automatically segment bundles from diffusion Magnetic Resonance Imaging (dMRI) data indirectly, by exploiting either the idea of connectivity between regions or the geometry of fiber paths obtained with tractography techniques, or, directly, through the information in volumetric data. Despite the remarkable improvement in automatic segmentation methods over the years, their segmentation quality is not yet satisfactory, especially when dealing with datasets with very diverse characteristics, such as different tracking methods, bundle sizes or data quality. In this work, we propose a novel, supervised streamline-based segmentation method, called Classifyber, which combines information from atlases, connectivity patterns, and the geometry of fiber paths into a simple linear model. With a wide range of experiments on multiple datasets that span from research to clinical domains, we show that Classifyber substantially improves the quality of segmentation as compared to other state-of-the-art methods and, more importantly, that it is robust across very diverse settings. We provide an implementation of the proposed method as open source code, as well as web service.

neuroscience↗

bioRxiv2019

Graded striatal learning factors enable switches between goal-directed and habitual modes, by reassigning behavior control to the fastest-computed representation that predicts reward

Different compartments of striatum mediate distinctive behavior-control modes, notably goal-directed versus habitual behavior. Normally, animals move back and forth between these modes as they adapt to changing contingencies of reward. However, this ability is compromised when dopaminergic drugs are used as reinforcers. These facts suggest that a set of biological variables, which make striatal decision making both highly plastic and uniquely sensitive to dopamine, contribute both to normal switches among modes and to the susceptibility for excessive habit formation when dopaminergic drugs serve as rewards. Indeed, data have revealed an impressive number of plasticity- and dopamine-related neural factors that vary systematically (with either increasing or decreasing gradients) across the rostral-ventral-medial to caudal-dorsal-lateral axis within striatum, the same axis implicated in switches among behavioral modes. Computer simulations reported here show how a dopamine-dependent parallel learning algorithm, if applied within modeled cortico-striatal circuits with parameters that reflect these striatal gradients, can explain normal mode switching, both into the habitual mode and returns to goal-directed mode, while also exhibiting a susceptibility to excessive habit formation when a dopaminergic drug serves as reward. With the same parameters, the model also directly illuminates: why interval and probabilistic reinforcement schedules are more habit forming than fixed-ratio schedules; why extinction learning is not (and should not be) a mirror image of acquisition learning; and why striatal decisions guided by reward-guided learning typically exhibit a highly sensitive tradeoff between speed and accuracy.

neuroscience↗