Sunday, July 21st, 2024

Time	Event
10:51a	Self-avoidance dominates the selection of hippocampal replay Spontaneous neural activity sequences are generated by the brain in the absence of external input, yet how they are produced remains unknown. During immobility, hippocampal replay sequences depict spatial paths related to the animal's past experience or predicted future. By recording from large ensembles of hippocampal place cells in combination with optogenetic manipulation of cortical input in freely behaving rats, we show here that the selection of hippocampal replay is governed by a novel self-avoidance principle. Following movement cessation, replay of the animal's past path is strongly avoided, while replay of the future path predominates. Moreover, when the past and future paths overlap, early replays avoid both and depict entirely different trajectories. Further, replays avoid self-repetition, on a shorter timescale compared to the avoidance of previous behavioral trajectories. Eventually, several seconds into the stopping period, replay of the past trajectory dominates. This temporal organization contrasts with established and recent predictions but is well-recapitulated by a symmetry-breaking attractor model of sequence generation in which individual neurons adapt their firing rates over time. However, while the model is sufficient to produce avoidance of recently traversed or reactivated paths, it requires an additional excitatory input into recently activated cells to produce the later window of past-dominance. We performed optogenetic perturbations to demonstrate that this input is provided by medial entorhinal cortex, revealing its role in maintaining a memory of past experience that biases hippocampal replay. Together, these data provide specific evidence for how hippocampal replays are generated. (Comment on this)
10:51a	Hierarchical Bayesian modeling of multi-region brain cell count data We can now collect cell-count data across whole animal brains quantifying recent neuronal activity, gene expression, or anatomical connectivity. This is a powerful approach since it is a multi-region measurement, but because the imaging is done post-mortem, each animal only provides one set of counts. Experiments are expensive and since cells are counted by imaging and aligning a large number of brain sections, they are time-intensive. The resulting datasets tend to be under-sampled with fewer animals than brain regions. As a consequence, these data are a challenge for traditional statistical approaches. We demonstrate that hierarchical Bayesian methods are well suited to these data by presenting a 'standard' partially-pooled Bayesian model for multi-region cell-count data and applying it to two example datasets. For both datasets the Bayesian model outperformed standard parallel t-tests. Overall, the Bayesian approach's ability to capture nested data and its rigorous handling of uncertainty in under-sampled data can substantially improve inference for cell-count data. (Comment on this)
10:51a	Spatial constraints and cell surface molecule depletion structure a randomly connected learning circuit The brain can represent almost limitless objects to "categorize an unlabeled world" (Edelman, 1989). This feat is supported by expansion layer circuit architectures, in which neurons carrying information about discrete sensory channels make combinatorial connections onto much larger postsynaptic populations. Combinatorial connections in expansion layers are modeled as randomized sets. The extent to which randomized wiring exists in vivo is debated, and how combinatorial connectivity patterns are generated during development is not understood. Non-deterministic wiring algorithms could program such connectivity using minimal genomic information. Here, we investigate anatomic and transcriptional patterns and perturb partner availability to ask how Kenyon cells, the expansion layer neurons of the insect mushroom body, obtain combinatorial input from olfactory projection neurons. Olfactory projection neurons form their presynaptic outputs in an orderly, predictable, and biased fashion. We find that Kenyon cells accept spatially co-located but molecularly heterogeneous inputs from this orderly map, and ask how Kenyon cell surface molecule expression impacts partner choice. Cell surface immunoglobulins are broadly depleted in Kenyon cells, and we propose that this allows them to form connections with molecularly heterogeneous partners. This model can explain how developmentally identical neurons acquire diverse wiring identities. (Comment on this)
10:51a	Reward history guides attentional selection in whisker somatosensory (S1) cortex The history of stimuli and rewards in the recent past drives an automatic form of attention in animals and humans in which attentional priority is given to previously rewarded stimuli. The neurobiological basis for this form of attention is unknown. In a novel whisker touch detection task, we show that mice flexibly shift attention between specific whiskers, based on this recent history of stimulus-reward association. 2-photon calcium imaging and spike recordings revealed a robust neurobiological correlate in somatosensory cortex (S1), involving topographically precise, whisker-specific boosting of L2/3 pyramidal (PYR) cell sensory responses to attend whiskers, and receptive fields shifts towards attended whiskers. L2/3 VIP interneurons were activated by whisker stimuli and arousal but did not carry a whisker-specific attentional signal, so do not mediate this form of attention. Thus, reward history drives attentional capture that is associated with dynamic, topographically precise modulation of sensory evoked activity in S1. (Comment on this)
12:47p	Pyramidal neurons proportionately alter the identity and survival of specific cortical interneuron subtypes The mammalian cerebral cortex comprises a complex neuronal network that maintains a delicate balance between excitatory neurons and inhibitory interneurons. Previous studies, including our own research, have shown that specific interneuron subtypes are closely associated with particular pyramidal neuron types, forming stereotyped local inhibitory microcircuits. However, the developmental processes that establish these precise networks are not well understood. Here we show that pyramidal neuron types are instrumental in driving the terminal differentiation and maintaining the survival of specific associated interneuron subtypes. In a wild-type cortex, the relative abundance of different interneuron subtypes aligns precisely with the pyramidal neuron types to which they synaptically target. In Fezf2 mutant cortex, characterized by the absence of layer 5 pyramidal tract neurons and an expansion of layer 6 intratelencephalic neurons, we observed a corresponding decrease in associated layer 5b interneurons and an increase in layer 6 subtypes. Interestingly, these shifts in composition are achieved through mechanisms specific to different interneuron types. While SST interneurons adjust their abundance to the change in pyramidal neuron prevalence through the regulation of programmed cell death, parvalbumin interneurons alter their identity. These findings illustrate two key strategies by which the dynamic interplay between pyramidal neurons and interneurons allows local microcircuits to be sculpted precisely. These insights underscore the precise roles of extrinsic signals from pyramidal cells in the establishment of interneuron diversity and their subsequent integration into local cortical microcircuits. (Comment on this)

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