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Koolschijn, R. S.

Publications and source records attributed to Koolschijn, R. S..

6 recordsLinked to original sources

Dissecting the contribution of recent reward versus recent performance history on cognitive effort allocation

An extensive body of literature has shown that humans tend to avoid expending cognitive effort, just like for physical effort or financial resources. How then, do we decide whether to put this effort in? Decision-making not only involves choosing our actions, but also the meta-decision of how much cognitive effort to invest in making this choice, weighing the costs of cognitive effort against potential rewards. Popular recent theories, grounded in the field of reinforcement learning, suggest that this cost-benefit trade-off can be informed by the opportunity costs of effort investment, which the brain may approximate by the estimated average reward rate per unit time. It follows from intuition that in a low reward environment, investing cognitive resources in the task at hand will less likely lead to missed opportunities. Recent studies provided support for this idea, showing that people exert more cognitive effort when reward rate is low. Here, we replicate one of the key previous findings but provide an important nuance to this result. Cognitive effort allocation was better explained by participants recent performance history (i.e. accuracy rate) than average reward rate. In combination with the observation that participants were insensitive to the reward currently at stake, this invites a reinterpretation of these previous findings and suggests the need for further studies to assess whether environmental richness may indeed serve as a heuristic to modulate cognitive effort allocation.

neuroscience↗

Rapid modulation of choice behavior by ultrasound on the human frontal eye fields

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. HighlightsO_LIFocused ultrasound modulates saccades with high spatial and temporal precision C_LIO_LIInhibitory circuits in the frontal eye fields shape choice computations C_LIO_LIGABA levels predict individual variability in ultrasound-induced behavioral changes C_LIO_LIUltrasound can be used to probe fast neural dynamics and individual differences C_LI

neuroscience↗

Noradrenaline causes a spread of association in the hippocampal cognitive map

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. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=137 HEIGHT=200 SRC="FIGDIR/small/610602v3_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@85d4ceorg.highwire.dtl.DTLVardef@564073org.highwire.dtl.DTLVardef@a16111org.highwire.dtl.DTLVardef@ebe1fc_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

A mechanism for hippocampal memory recall based on excitatory-inhibitory fluctuations in neocortex

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.

neuroscience↗

Prior expectations evoke stimulus templates in the deep layers of V1

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.

neuroscience↗

The hippocampus and neocortical inhibitory engrams protect against memory interference

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.

neuroscience↗