Time-dependent neural arbitration between cue associative and episodic fear memories After traumatic events, simple cue-threat associative memories strengthen while episodic memories become incoherent. However, how the brain prioritises cue associations over episodic coding of traumatic events remains unclear. Here, we developed an original episodic threat conditioning paradigm in which participants concurrently form two memory representations: cue associations and episodic cue sequence. We discovered that these two distinct memories compete for physiological fear expression, reorganising overnight from an overgeneralised cue-based to a precise sequence-based expression. With multivariate fMRI, we track inter-area communication of the memory representations to reveal that a rebalancing between hippocampal- and prefrontal control of the fear regulatory circuit governs this memory maturation. Critically, this overnight re-organisation is altered with heightened trait anxiety. Together, we show the brain prioritises generalisable associative memories under recent traumatic stress but resorts to selective episodic memories 24 h later. Time-dependent memory competition may provide a unifying account for memory dysfunctions in post-traumatic stress disorders.
Decisions: Tracking the evolution of a single choice Imagine observing a flock of birds migrating south in the fall. How does the group collectively make a turn? If you watch a single bird turn, even multiple times, you still may not be able to answer this question. But if you observe many birds at the same time, the solution may become clearer. This is also true for understanding how the brain makes decisions: analyzing the behavior of multiple neurons simultaneously can provide information that is not available from a single neuron.
The underlying neuronal mechanisms behind decision-making are often explained by a mathematical theory known as the drift-diffusion model (Ratcliff, 1978), particularly for tasks involving choosing between two options. The drift component represents the process of moving towards one option based on evidence that accumulates over time (such as momentary pieces of sensory information), while diffusion represents random variability in the evidence received and how it is processed by the brain. Together, drift and diffusion constitute the signal that is thought to influence what decisions individuals make, and how long it takes.
Molecular mechanisms underlying the neural correlates of working memory Working memory (WM), a core component of executive functions, refers to temporary storage and manipulation of the information necessary for complex cognitive tasks. WM relies on a dedicated brain system that maintains and stores information in the short term. Considerable effort in the last decades has been directed to investigating such brain system using two different yet complementary neuroimaging approaches, focusing on within-subject effects and between-subject differences respectively. The former examines an individual’s brain activation during WM tasks utilizing functional neuroimaging techniques and the activated brain regions are thought to be responsible for WM processes. The latter explores inter-individual variations in brain structure and function that are linked to inter-individual differences in WM performance by conducting neuroimaging-behavior correlation across subjects. Taking advantage of these approaches, extensive research has identified a distributed set of neural substrates relevant to WM, consistently involving the medial and lateral prefrontal cortex, medial and lateral posterior parietal cortex, and anterior and posterior cingulate cortex. Nevertheless, the molecular mechanisms (i.e., genetic architecture and neurochemical basis) underlying the neural correlates of WM remain enigmatic.
Working Memory Prioritization Changes Bidirectional Interactions with Perceptual Inputs Items stored in visual working memory often differ in priority. Typically, observers will shift their internal attention towards items that are relevant for impending behavior and away from those that may become relevant later. These distinct states of priority are theorized to influence bidirectional interactions between memoranda and new visual inputs by modulating their susceptibility to retroactive and proactive biases, respectively. However, prior research has produced limited and conflicting evidence on this topic due to reliance on inconsistent retrodictive cues (retro-cues) that incentivize memory prioritization. To address this, we used a double-serial retro-cue paradigm that incentivized the complete prioritization of one of two unfamiliar shape memoranda for use in a comparison with a perceptual probe before a second, independent cue instructed observers to report one of their two memories (Experiments 1-2) or the perceptual probe itself (Experiment 2). We found that observers reported robust retroactive and proactive biases, but that only retroactive biases were modulated by prioritization. Reports of prioritized memories were more precise and contained smaller attractive biases towards the probe than unprioritized memories, whereas probe reports were biased comparably towards each. These findings reveal an asymmetrical effect of prioritization on the reciprocal interactions between memory and perception.
Functional networks of inhibitory neurons orchestrate synchrony in the hippocampus Inhibitory interneurons are pivotal components of cortical circuits. Beyond providing inhibition, they have been proposed to coordinate the firing of excitatory neurons within cell assemblies. While the roles of specific interneuron subtypes have been extensively studied, their influence on pyramidal cell synchrony in vivo remains elusive. Employing an all-optical approach in mice, we simultaneously recorded hippocampal interneurons and pyramidal cells and probed the network influence of individual interneurons using optogenetics. We demonstrate that CA1 interneurons form a functionally interconnected network that promotes synchrony through disinhibition during awake immobility, while preserving endogenous cell assemblies. Our network model underscores the importance of both cell assemblies and dense, unspecific interneuron connectivity in explaining our experimental findings, suggesting that interneurons may operate not only via division of labor but also through concerted activity.
Understanding dual process cognition via the minimum description length principle Dual-process theories play a central role in both psychology and neuroscience, figuring prominently in domains ranging from executive control to reward-based learning to judgment and decision making. In each of these domains, two mechanisms appear to operate concurrently, one relatively high in computational complexity, the other relatively simple. Why is neural information processing organized in this way? We propose an answer to this question based on the notion of compression. The key insight is that dual-process structure can enhance adaptive behavior by allowing an agent to minimize the description length of its own behavior. We apply a single model based on this observation to findings from research on executive control, reward-based learning, and judgment and decision making, showing that seemingly diverse dual-process phenomena can be understood as domain-specific consequences of a single underlying set of computational principles.
Multi-scale spiking network model of human cerebral cortex Although the structure of cortical networks provides the necessary substrate for their neuronal activity, the structure alone does not suffice to understand the activity. Leveraging the increasing availability of human data, we developed a multi-scale, spiking network model of human cortex to investigate the relationship between structure and dynamics. In this model, each area in one hemisphere of the Desikan–Killiany parcellation is represented by a 1mm2 column with a layered structure. The model aggregates data across multiple modalities, including electron microscopy, electrophysiology, morphological reconstructions, and diffusion tensor imaging, into a coherent framework. It predicts activity on all scales from the single-neuron spiking activity to the area-level functional connectivity. We compared the model activity with human electrophysiological data and human resting-state functional magnetic resonance imaging (fMRI) data. This comparison reveals that the model can reproduce aspects of both spiking statistics and fMRI correlations if the inter-areal connections are sufficiently strong. Furthermore, we study the propagation of a single-spike perturbation and macroscopic fluctuations through the network. The open-source model serves as an integrative platform for further refinements and future in silico studies of human cortical structure, dynamics, and function.
Cerebral microbleeds: Association with cognitive decline and pathology build-up Cerebral microbleeds, markers of brain damage from vascular and amyloid pathologies, are linked to cognitive decline in aging, but their role in Alzheimer’s disease (AD) onset and progression remains unclear. This study aimed to explore whether the presence and location of lobar microbleeds are associated with amyloid-β (Aβ)-PET, tau tangle formation (tau-PET), and longitudinal cognitive decline. We analyzed 1,573 ADNI participants with MR imaging data and information on the number and location of microbleeds. Associations between lobar microbleeds and pathology, cerebrospinal fluid (CSF), genetics, and cognition were examined, focusing on regional microbleeds and domain-specific cognitive decline using ordinary least-squares regression while adjusting for covariates. Cognitive decline was assessed with ADAS-Cog11 and its domain-specific sub-scores. Participants underwent neuropsychological testing at least twice, with a minimum two-year interval between assessments. Among the 1,573 participants (692 women, mean age 71.23 years), 373 participants had microbleeds. The presence of microbleeds was linked to cognitive decline, particularly in the semantic, language, and praxis domains for those with temporal lobe microbleeds. Microbleeds in the overall cortex were associated with language decline. Pathologically, temporal lobe microbleeds were associated with increased tau in the overall cortex, while cortical microbleeds were linked to elevated Aβ in the temporal, parietal, and frontal regions. In this mixed population, microbleeds were connected to longitudinal cognitive decline, especially in semantic and language domains, and were associated with higher baseline Aβ and tau pathology. These findings suggest that lobar microbleeds should be included in AD diagnostic and prognostic evaluations.