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The way we perceive the world is strongly influenced by our expectations. In line with this, much recent research has revealed that prior expectations strongly modulate sensory processing. However, the neural circuitry through which the brain integrates external sensory inputs with internal expectation signals remains unknown. In order to understand the computational architecture of the cortex, we need to investigate the way these signals flow through the cortical layers. This is crucial because the different cortical layers have distinct intra- and interregional connectivity patterns, and therefore determining which layers are involved in a cortical computation can inform us on the sources and targets of these signals. Here, we used ultra-high field (7T) functional magnetic resonance imaging (fMRI) to reveal that prior expectations evoke stimulus-specific activity selectively in the deep layers of the primary visual cortex (V1). These findings are in line with predictive processing theories proposing that neurons in the deep cortical layers represent perceptual hypotheses and thereby shed light on the computational architecture of cortex.

•Recent advances in MRS now allow for event-related functional MRS, with temporal resolution in the order of seconds.•We provide a user guide for experimental design, data acquisition and analysis considerations for event-related fMRS.•We use simulations to determine optimal settings to detect event-related changes in GABA.•We provide a critical perspective on the appropriate interpretation of event-related fMRS. Proton-Magnetic Resonance Spectroscopy (MRS) is a non-invasive brain imaging technique used to measure the concentration of different neurochemicals. “Single-voxel” MRS data is typically acquired across several minutes, before individual transients are averaged through time to give a measurement of neurochemical concentrations. However, this approach is not sensitive to more rapid temporal dynamics of neurochemicals, including those that reflect functional changes in neural computation relevant to perception, cognition, motor control and ultimately behaviour. In this review we discuss recent advances in functional MRS (fMRS) that now allow us to obtain event-related measures of neurochemicals. Event-related fMRS involves presenting different experimental conditions as a series of trials that are intermixed. Critically, this approach allows spectra to be acquired at a time resolution in the order of seconds. Here we provide a comprehensive user guide for event-related task designs, choice of MRS sequence, analysis pipelines, and appropriate interpretation of event-related fMRS data. We raise various technical considerations by examining protocols used to quantify dynamic changes in GABA, the primary inhibitory neurotransmitter in the brain. Overall, we propose that although more data is needed, event-related fMRS can be used to measure dynamic changes in neurochemicals at a temporal resolution relevant to computations that support human cognition and behaviour.

The brain has a remarkable capacity to acquire and store memories that can later be selectively recalled. These processes are supported by the hippocampus which is thought to index memory recall by reinstating information stored across distributed neocortical circuits. However, the mechanism that supports this interaction remains unclear. Here, in humans, we show that recall of a visual cue from a paired associate is accompanied by a transient increase in the ratio between glutamate and GABA in visual cortex. Moreover, these excitatory-inhibitory fluctuations are predicted by activity in the hippocampus. These data suggest the hippocampus gates memory recall by indexing information stored across neocortical circuits using a disinhibitory mechanism. Memories are stored by distributed groups of neurons in the brain, with individual neurons contributing to multiple memories. In a part of the brain called the neocortex, memories are held in a silent state through a balance between excitatory and inhibitory activity. This is to prevent them from being disrupted by incoming information. When a memory is recalled, an area of the brain called the hippocampus is thought to instruct the neocortex to activate the appropriate neuronal network. But how the hippocampus and neocortex coordinate their activity to switch memories ‘on’ and ‘off’ is unclear. The answer may lie in the fact that neurons in the neocortex consist of two broad types: excitatory and inhibitory. Excitatory neurons increase the activity of other neurons. They do this by releasing a chemical called glutamate. Inhibitory neurons reduce the activity of other neurons, by releasing a chemical called GABA. Koolschijn, Shpektor et al. hypothesized that the hippocampus activates memories by changing the balance of excitatory and inhibitory activity in neocortex. To test this idea, Koolschijn, Shpektor et al. invited healthy volunteers to explore a virtual reality environment. The volunteers learned that specific sounds in the environment predicted the appearance of particular visual patterns. The next day, the volunteers returned to the environment and viewed these patterns again. After each pattern, they were invited to open a virtual box. Volunteers learned that some patterns led to money in the virtual box, while other patterns did not. Finally, on day three, the volunteers listened to the sounds from day one again, this time while lying in a brain scanner. The volunteers’ task was to infer whether each of the sounds would lead to money. Given that the sounds were never directly paired with the content of the virtual box, the volunteers had to solve the task by recalling the associated visual patterns. As they did so, the brain scanner measured their overall brain activity. It also assessed the relative levels of excitatory and inhibitory activity in visual areas of the neocortex, by measuring glutamate and GABA. The results revealed that as the volunteers recalled the visual cues, activity in both the hippocampus and the visual neocortex increased. Moreover, the ratio of glutamate to GABA in visual neocortex also increased which was predicted by activity in the hippocampus. This suggests that the hippocampus reactivates memories stored in neocortex by temporarily increasing excitatory activity to release memories from inhibitory control. Disturbances in the balance of excitation and inhibition occur in various neuropsychiatric disorders, including schizophrenia, autism, epilepsy and Tourette’s syndrome. Damage to the hippocampus is known to cause amnesia. The current findings suggest that memories may become inaccessible – or may be activated inappropriately – when the interaction between the hippocampus and neocortex goes awry. Future studies could test this possibility in clinical populations.

The mammalian brain stores relationships between items and events in the world as cognitive maps in the hippocampal system. However, the neural mechanisms that control cognitive map formation remain unclear. Here, using a double-blind study design with a pharmacological intervention in humans, we show that the neuromodulator noradrenaline elicits a significant 'spread of association' across the hippocampal cognitive map. This neural spread of association predicts overgeneralisation errors measured in behaviour, and is predicted by physiological markers for noradrenergic arousal, namely an increase in the pupil dilation response and reduced cortical GABAergic tone. Thus, noradrenaline sets the width of the 'smoothing kernel' for plasticity across the cognitive map. Elevated noradrenaline can allow disparate memories to become linked, introducing potential for distortions in the cognitive map that deviate from direct experience.Competing Interest StatementM.B. has received travel expenses from Lundbeck for attending conferences and has acted as a consultant for J&J, Novartis, Boehringher and CHDR. He previously owned shares in P1vital Ltd. All other authors declare no competing interests.Footnotes* Neural network model section, author list.

The way we perceive the world is strongly influenced by our expectations. In line with this, much recent research has revealed that prior expectations strongly modulate sensory processing. However, the neural circuitry through which the brain integrates external sensory inputs with internal expectation signals remains unknown. In order to understand the computational architecture of the cortex, we need to investigate the way these signals flow through the cortical layers. This is crucial because the different cortical layers have distinct intra- and interregional connectivity patterns, and therefore determining which layers are involved in a cortical computation can inform us on the sources and targets of these signals. Here, we used ultra-high field (7T) functional magnetic resonance imaging (fMRI) to reveal that prior expectations evoke stimulus templates selectively in the deep layers of the primary visual cortex. These results shed light on the neural circuit underlying perceptual inference.

ABSTRACT The brain has a remarkable capacity to acquire and store memories that can later be selectively recalled. These processes are supported by the hippocampus which is thought to index memory recall by reinstating information stored across distributed neocortical circuits. However, the mechanism that supports this interaction remains unclear. Here, in humans, we show that recall of a visual cue from a paired associate is accompanied by a transient increase in the ratio between glutamate and GABA in visual cortex. Moreover, these excitatory-inhibitory fluctuations are predicted by activity in the hippocampus. These data suggest the hippocampus gates memory recall by indexing information stored across neocortical circuits using a disinhibitory mechanism. Competing Interest Statement The authors have declared no competing interest. Footnotes * ↵† indicates equal contribution

A fundamental challenge in neuroscience is establishing causal brain-function relationships with spatial and temporal precision. Transcranial ultrasonic stimulation (TUS) offers a unique opportunity to modulate deep brain structures non-invasively with high spatial resolution, but temporally precise effects and their neurophysiological foundations have yet to be demonstrated in humans. Here, we develop a temporally precise TUS protocol targeting the frontal eye fields (FEFs) — a well-characterized circuit critical for saccadic eye movements. We demonstrate that TUS induces robust excitatory behavioral effects. Importantly, individual differences in baseline GABAergic inhibitory tone predict response magnitude. These findings establish TUS as a reliable tool for chronometric circuit interrogation and highlight the importance of neurophysiological state in neuromodulation. This work bridges human and animal research, advancing targeted TUS applications in neuroscience and clinical settings. Focused ultrasound modulates saccades with high spatial and temporal precision Inhibitory circuits in the frontal eye fields shape choice computations GABA levels predict individual variability in ultrasound-induced behavioral changes Ultrasound can be used to probe fast neural dynamics and individual differences

Our experiences often overlap with each other, sharing features, stimuli or higher-order information. But despite this overlap, we are able to selectively recall individual memories to guide our decisions and future actions. The neural mechanisms that support such precise memory recall, however, remain unclear. Here, using ultra-high field 7T MRI we reveal two distinct mechanisms that protect memories from interference. The first mechanism involves the hippocampus, where the BOLD signal predicts behavioural measures of memory interference, and contextual representations that aid separation of overlapping memories are organised using a relational code. The second mechanism involves neocortical inhibition: when we reduce the concentration of neocortical GABA using trans-cranial direct current stimulation (tDCS) neocortical memory interference increases in proportion to the reduction in GABA, which in turn predicts behavioural performance. Together these findings suggest that memory interference is mediated by both the hippocampus and neocortex, where the hippocampus aids separation of memories by coding context-dependent relational information, while neocortical inhibition prevents unwanted co-activation between overlapping memories.