Biology subjects

Levi, A. J.

Publications and source records attributed to Levi, A. J..

5 recordsLinked to original sources

bioRxiv2026

Dynamic interactions between sensory and decision-making circuits shape temporal evidence weighting

Perceptual decisions require the brain to integrate sensory evidence over time, yet the temporal weighting of evidence can be flexibly adjusted according to task demands. How such flexibility emerges from interactions between sensory and decision circuits remains unclear. Here, we combined behavioral and neural measurements with recurrent network modeling to investigate the mechanisms underlying temporal weighting of sensory evidence. Macaques performed a motion-discrimination task in which the temporal statistics of sensory evidence favored early, late or uniform integration. Behavioral psychophysical kernels revealed corresponding shifts in the influence of evidence across time, accompanied by systematic changes in motion discriminability and choice-related activity modulation in visual area MT. We developed a recurrent sensory-decision network incorporating reciprocal feedforward and feedback interactions and a temporally structured modulatory input, resembling an urgency signal. The model reproduced the observed behavioral and neural signatures across temporal weighting conditions. Mechanistically, shifting the onset and dynamics of modulatory inputs systematically reconfigured the temporal profile of evidence weighting without substantially altering sensory response dynamics. Choice-related activity in MT can be decomposed in a bottom-up component with the same time-course as the psychophysical kernel, and a top-down component reflecting the decision build-up. These findings suggest that flexible temporal integration can emerge from dynamic interactions between sensory transmission, recurrent decision circuits and temporally structured urgency modulation, providing a mechanistic framework for how neural systems adapt the computation of sensory evidence to changing task demands.

neuroscience↗

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↗

bioRxiv2021

Sensory and choice responses in MT distinct from motion encoding

Macaque area MT is well known for its visual motion selectivity and relevance to motion perception, but the possibility of it also reflecting non-sensory functions has largely been ignored. Manipulating subjects temporal evidence weighting revealed multiple components of MT responses that were, surprisingly, not interpretable as behaviorally-relevant modulations of motion encoding, nor as consequences of readout of motion direction. MTs time-varying motion-driven responses were starkly changed by our strategic manipulation, but with timecourses opposite the subjects temporal weighting strategies. Furthermore, large choice-correlated signals were represented in population activity distinctly from motion responses (even after the stimulus) with multiple phases that both lagged psychophysical readout and preceded motor responses. These results reveal multiple cognitive contributions to MT responses that are task-related but not functionally relevant to encoding or decoding of motion for psychophysical direction discrimination, calling into question its nature as a simple sensory area.

neuroscience↗

bioRxiv2020

"Supersessioning": A hardware/software system for electrophysiology spanning multiple sessions in marmosets

We introduce a straightforward, robust method for recording and analyzing spiking activity over timeframes longer than a single session, with primary application to the marmoset (Callithrix jacchus). Although in theory the marmosets smooth brain allows for broad deployment of powerful tools in primate cortex, in practice marmosets do not typically engage in long experimental sessions akin to rhesus monkeys. This potentially limits their value for detailed, quantitative neurophysiological study. Here we describe chronically-implanted arrays with a 3D arrangement of electrodes yielding stable single and multi-unit responses, and an analytic method for creating "supersessions" combining that array data across multiple experiments. We could match units across different recording sessions over several weeks, demonstrating the feasibility of pooling data over sessions. This could be a key tool for extending the viability of marmosets for dissecting neural computations in primate cortex.

neuroscience↗

bioRxiv2019

Stimulus-choice (mis)alignment in primate MT cortex

For stimuli near perceptual threshold, the trial-by-trial activity of single neurons in many sensory areas is correlated with the animals perceptual report. This phenomenon has often been attributed to feedforward readout of the neural activity by the downstream decision-making circuits. The interpretation of choice-correlated activity is quite ambiguous, but its meaning can be better understood in the light of population-wide correlations among sensory neurons. Using a statistical nonlinear dimensionality reduction technique on single-trial ensemble recordings from the middle temporal area during perceptual-decision-making, we extracted low-dimensional neural tra jectories that captured the population-wide fluctuations. We dissected the particular contributions of sensory-driven versus choice-correlated activity in the low-dimensional population code. We found that the neural trajectories strongly encoded the direction of the stimulus in single dimension with a temporal signature similar to that of single MT neurons. If the downstream circuit were optimally utilizing this information, choice-correlated signals should be aligned with this stimulus encoding dimension. Surprisingly, we found that a large component of the choice information resides in the subspace orthogonal to the stimulus representation inconsistent with the optimal readout view. This misaligned choice information allows the feedforward sensory information to coexist with the decision-making process. The time course of these signals suggest that this misaligned contribution likely is feedback from the downstream areas. We hypothesize that this non-corrupting choice-correlated feedback might be related to learning or reinforcing sensory-motor relations in the sensory population. Author summaryIn sensorimotor decision-making, internal representation of sensory stimuli is utilized for the generation of appropriate behavior for the context. Therefore, the correlation between variability in sensory neurons and perceptual decisions is sometimes explained by a causal, feedforward role of sensory noise in behavior. However, this correlation could also originate via feedback from decision-making mechanisms downstream of the sensory representation. This cannot be resolved by analyzing single unit responses, but requires a population level analysis. Area MT contains both sensory and choice information and is known to be the key sensory area for visual motion perception. Thus the decision-making process may be corrupting the sensory representation. However, we find that the sensory stimuli and choice variables are separate at the population level,contradicting the previous interpretations based on single unit recordings. This new insight postulates how neural systems can maintain a mixed representation while allows learning and adaptation.

neuroscience↗