Biology subjects

Laamerad, P.

Publications and source records attributed to Laamerad, P..

6 recordsLinked to original sources

bioRxiv2026

Reassessing Choice Probability: What 59 Macaque Studies Tell Us About Decision-Related Activity in Visual Cortex

Choice probability (CP) quantifies the trial-by-trial covariation between a sensory neurons response and perceptual reports. Despite extensive interest in CP as a window into how perception is linked to the activity of sensory neurons, the usefulness of CP remains debated. On one hand, reported CP magnitudes vary widely across seemingly equivalent studies, questioning its utility as a metric. On the other hand, the absence of clear patterns in CP variability has made it difficult to use it to adjudicate between competing models of visual perception. Here, we performed a meta-analysis of 150 CP estimates from 59 macaque neurophysiology studies to identify factors that systematically influence CP. We confirmed the positive relationship between CP and neuronal sensitivity both across and within individual studies. When controlled for sensitivity, we found remarkable consistency in CP across varying tasks and brain regions with two notable exceptions. First, CPs were higher in tasks involving bistable percepts, reinforcing the link between CP magnitude and subjective perception. Second, CPs were smaller in area V1, supporting prior suggestions about V1s special role in visual processing. We further found a significant effect of stimulus duration on CP, providing evidence against strictly feedforward models and favoring models with substantial feedback and recurrent processing. Finally, we offer recommendations for future studies to enhance the cross-study comparability and theoretical utility of choice signals as the field transitions to large-scale population recordings. More broadly, our findings demonstrate the benefits of meta-studies that expose patterns across many different tasks and animals - yielding insights that complement large-scale population recordings.

neuroscience↗

bioRxiv2026

Mid-superior temporal sulcus encodes spatial context and behavioral state in freely moving macaques

Primate neuroscience has traditionally studied the brain under highly constrained conditions, limiting our understanding of neural function during real-world behavior. The mid-superior temporal sulcus (mSTS) is implicated in social perception, but its role during unconstrained behavior has not been tested. Here we performed wireless depth-electrode recordings from both banks of mSTS in macaques freely exploring a large three-dimensional arena, combined with 3D pose tracking and behavioral segmentation. Neural encoding models revealed mSTS firing rates were jointly modulated by spatial position, body kinematics, and geometric visual proxies, preferentially encoded in allocentric coordinates but with a shift toward body-centric encoding during vertical exploration. Neural populations carried decodable information about discrete behavioral syllables, with broad temporal generalization and neural similarity that tracked the sequential structure of behavior. Population manifold analysis revealed that the same behavior occupied different regions of population space at different spatial locations, and population dynamics showed structured organization around behavioral transitions. Together, these results suggest that mSTS populations carry joint information about spatial context and behavioral state during natural behavior.

neuroscience↗

bioRxiv2025

The flexible contribution of cortical area V4 to visual perception

Humans and other primates are capable of learning to recognize new visual stimuli throughout their lifetimes. Most theoretical models assume that such learning occurs through the adjustment of the large number of synaptic weights connecting the visual cortex to downstream decision-making areas. While this approach to learning can optimize performance on behavioral tasks, it can also be costly in terms of time and energy. An alternative hypothesis is that the brain favors simpler learning rules that do not necessarily optimize the readout of information from visual cortical neurons. Here we have examined these hypotheses by reversibly inactivating visual area V4 in non-human primates at different stages of training on shape discrimination tasks. We find that V4 inactivation generally has a behavioral effect for only a subset of the stimuli that are encoded in the V4 population activity, specifically those that can be represented efficiently in the population firing rate. As a result, there is little relationship between neural measures of discriminability and the causal contribution of V4 neurons to a particular task. This pattern of results can be explained by incorporating a strong inductive bias for simpler perceptual readouts into existing theoretical frameworks. Such a simplicity bias is suboptimal in the sense that it ignores information that could theoretically be extracted from the neural population, but it has the likely advantage of facilitating efficient learning on ecologically-relevant timescales.

neuroscience↗

bioRxiv2025

Brain stimulation preferentially influences long-range projections in primates

Advances in brain stimulation have made it possible to target smaller and smaller regions for electromagnetic stimulation, in the hopes of producing increasingly focal neural effects. However, the brain is extensively interconnected, and the neurons comprising those connections may themselves be particularly susceptible to neurostimulation. Here, we test this hypothesis by identifying long-range projections in single-unit recordings from non-human primates receiving transcranial alternating current stimulation (tACS). We find that putative long-range projections are more strongly affected by stimulation than other cells. Specifically, they are both more entrained on average and account for occurrences of extremely strong entrainment. Since stimulation appears to target the edges, rather than nodes, of neural networks, it may be necessary to rethink how neurostimulation strategies are designed.

neuroscience↗

bioRxiv2023

Decision-related activity and movement selection in primate visual cortex

Fluctuations in the activity of sensory neurons often predict perceptual decisions. This connection can be quantified with a metric called choice probability (CP), and there has been a longstanding debate about whether CP reflects a causal influence on decisions, or an echo of decision-making activity elsewhere in the brain. Here we show that CP can actually reflect a third variable, namely the movement used to indicate the decision. In a standard visual motion discrimination task, neurons in the middle temporal (MT) area of the primate visual cortex responded more strongly during trials in which the animals executed a saccade toward their receptive fields, and less strongly for saccades directed away from the receptive fields. The resulting trial-to-trial variability accounted for much of the CP observed across the neuronal population, and it arose through training. Surprisingly, the learned association between MT activity and oculomotor selection was causal, as pharmacological inactivation of MT neurons biased behavioral responses away from the corresponding receptive field locations. These results demonstrate that training on a task with fixed sensorimotor contingencies introduces movement-related activity in sensory brain regions, and that this plasticity can shape the neural circuitry of perceptual decision-making.

animal behavior and cognition↗

bioRxiv2023

Asymmetric stimulus representations bias visual perceptual learning

The primate visual cortex contains various regions that exhibit specialization for different stimulus properties, such as motion, shape, and color. Within each region there is often further specialization, such that particular stimulus features, such as horizontal and vertical orientations, are overrepresented. These asymmetries are associated with well-known perceptual biases, but little is known about how they influence visual learning. Most theories would predict that learning is optimal, in the sense that it is unaffected by these asymmetries. But other approaches to learning would result in specific patterns of perceptual biases. To distinguish between these possibilities, we trained human observers to discriminate between expanding and contracting motion patterns, which have a highly asymmetrical representation in visual cortex. Observers exhibited biased percepts of these stimuli, and these biases were affected by training in ways that were often suboptimal. We simulated different neural network models and found that a learning rule that involved only adjustments to decision criteria, rather than connection weights, could account for our data. These results suggest that cortical asymmetries influence visual perception and that human observers often rely on suboptimal strategies for learning.

neuroscience↗