Biology subjects

Maniscalco, B.

Publications and source records attributed to Maniscalco, B..

5 recordsLinked to original sources

bioRxiv2025

Attention robustly dissociates objective performance and subjective visibility reports

Visual experience can sometimes depart from visual performance, providing a powerful lens into the mechanisms generating conscious perception. In one proposed dissociation--subjective inflation--unattended locations in the periphery appear stronger than attended ones despite equated performance. Subjective inflation has played a central role in motivating theories of consciousness that reject the sufficiency of sensory signals for conscious perception. Yet the empirical basis for subjective inflation is limited. Here, in a large-scale adversarial collaboration, we conducted four simultaneously-replicated experiments testing the strength, character, and extent of subjective inflation under inattention. We used a new analytic approach to quantify inattentional inflation over full psychometric functions, beyond single matched-performance levels. We found robust inattentional inflation for contrast-dependent and texture-based perception, at and above the visual threshold. However at suprathreshold, we found inattentional inflation for the overall stimulus but not the specific feature relevant for performance. Finally, we establish the unifying principle that inattentional inflation occurs if and only if attention reduces performance thresholds more than visibility thresholds. Thus what we think we see may regularly exceed what we can visually discriminate, placing constraints on theories of conscious perception.

neuroscience↗

bioRxiv2019

Atypical spatial frequency dependence of visual metacognition among schizophrenia patients

Although altered early stages of visual processing have been reported among schizophrenia patients, how such atypical visual processing may affect higher-level cognition remains largely unknown. Here we tested the hypothesis that metacognitive performance may be atypically modulated by spatial frequency (SF) of visual stimuli among individuals with schizophrenia, given their altered magnocellular function. To study the effect of SF on metacognitive performance, we asked patients and controls to perform a visual detection task on gratings with different SFs and report confidence, and analyzed the data using the signal detection theoretic measure meta-d. Control subjects showed better metacognitive performance after yes- (stimulus-presence) than after no- (stimulus-absence) responses ( yes-response advantage) for high SF (HSF) stimuli but not for low SF (LSF) stimuli. The patients, to the contrary, showed a yes-response advantage not only for HSF but also for LSF stimuli, indicating atypical SF dependency of metacognition. An fMRI experiment using the same task revealed that the dorsolateral prefrontal cortex (DLPFC), known to be crucial for metacognition, shows activity mirroring the behavioral results: decoding accuracy of perceptual confidence in DLPFC was significantly higher for HSF than for LSF stimuli in controls, whereas this decoding accuracy was independent of SF in patients. While individuals without schizophrenia may flexibly adapt metacognitive computations across SF ranges, patients may employ a different mechanism that is independent of SF. Because visual stimuli of low SF have been linked to top-down processing in predictive coding, this may reflect atypical functioning in these processes in schizophrenia. HighlightsO_LIVisual metacognition of controls was dependent on spatial frequency. C_LIO_LIVisual metacognition of schizophrenia patients was independent of spatial frequency. C_LIO_LIPatients and controls differently rely on the dorsolateral prefrontal cortex. C_LIO_LISensory inputs may reach metacognitive circuits in an atypical manner among patients. C_LI

neuroscience↗

bioRxiv2019

Tuned normalization in perceptual decision-making circuits can explain seemingly suboptimal confidence behavior

Current dominant views hold that perceptual confidence reflects the probability that a decision is correct. Although these views have enjoyed some empirical support, recent behavioral results indicate that confidence and the probability of being correct can be dissociated. An alternative hypothesis suggests that confidence instead reflects the magnitude of evidence in favor of a decision while being relatively insensitive to the evidence opposing the decision. We considered how this alternative hypothesis might be biologically instantiated by developing a simple leaky competing accumulator neural network model incorporating a known property of sensory neurons: tuned normalization. The key idea of the model is that each accumulator neurons normalization tuning dictates its contribution to perceptual decisions versus confidence judgments. We demonstrate that this biologically plausible model can account for several counterintuitive findings reported in the literature, where confidence and decision accuracy were shown to dissociate -- and that the differential contribution a neuron makes to decisions versus confidence judgments based on its normalization tuning is vital to capturing some of these effects. One critical prediction of the model is that systematic variability in normalization tuning exists not only in sensory cortices but also in the decision-making circuitry. We tested and validated this prediction in macaque superior colliculus (SC; a region implicated in decision-making). The confirmation of this novel prediction provides direct support for our model. These findings suggest that the brain has developed and implements this alternative, heuristic theory of perceptual confidence computation by capitalizing on the diversity of neural resources available. SignificanceThe dominant view of perceptual confidence proposes that confidence optimally reflects the probability that a decision is correct. But recent empirical evidence suggests that perceptual confidence exhibits a suboptimal confirmation bias, just as in human decision-making in general. We tested how this bias might be neurally implemented by building a biologically plausible neural network model, and showed that the bias emerges when each neurons degree of divisive normalization dictates how it drives decisions versus confidence judgments. We confirmed the models biological substrate using electrophysiological recordings in monkeys. These results challenge the dominant model, suggesting that the brain instead capitalizes on the diversity of available machinery (i.e., neuronal resources) to implement heuristic -- not optimal -- strategies to compute subjective confidence.

neuroscience↗

bioRxiv2017

On a ‘failed’ attempt to manipulate conscious perception with transcranial magnetic stimulation to prefrontal cortex

It has been reported that continuous theta burst transcranial magnetic stimulation (TMS) to the dorsolateral prefrontal cortex (DLPFC) impairs metacognitive awareness in visual perception (Rounis et al., 2010). Bor et al. (2017) recently attempted to replicate this result. However, the authors modified the experimental design of the original study considerably, meaning that this was not strictly a replication. In some cases, the changes are a priori expected to lower the chance of obtaining positive findings. Despite these changes, the researchers in fact still found an effect similar to Rounis et al.s, but they claimed that it was necessary to adopt certain criteria to discard {bsim}30% of their subjects, after which a null result was reported. Using computer simulations, we evaluated whether the subject exclusion criteria Bor et al. adopted was appropriate or beneficial. We found that, contrary to their intended purpose, excluding subjects by their criteria does not actually reduce false positive rates. Taking into account both their positive result (without subject exclusion) and negative result (after exclusion) in a Bayesian framework, we further found that their results suggest a 75% or greater likelihood that TMS to DLPFC does in fact impair metacognition, directly contradicting their claim of replication failure. That lesion and chemical inactivation studies are known to demonstrate positive effects in similar paradigms further suggests that Bor et al.s alleged negative finding cannot be taken as evidence against the role of the prefrontal cortex in conscious perception in general.

neuroscience↗

bioRxiv2017

Initial-State-Dependent, Robust, Transient Neural Dynamics Encode Conscious Visual Perception

Recent research has identified late-latency, long-lasting neural activity as a robust correlate of conscious perception. Yet, the dynamical nature of this activity is poorly understood, and the mechanisms governing its presence or absence and the associated conscious perception remain elusive. We applied dynamic-pattern analysis to whole-brain slow cortical dynamics recorded by magnetoencephalography (MEG) in human subjects performing a threshold-level visual perception task. Up to 1 second before stimulus onset, brain activity pattern across widespread cortices significantly predicted whether a threshold-level visual stimulus was later consciously perceived. This initial state of brain activity interacts nonlinearly with stimulus input to shape the evolving cortical activity trajectory, with seen and unseen trials following well separated trajectories. Furthermore, cortical activity trajectories during conscious perception are fast evolving and robust to small variations in the initial state. These results suggest that brain dynamics underlying conscious visual perception belongs to the class of initial-state-dependent, robust, transient neural dynamics.\n\nAUTHOR SUMMARYWhat brain mechanisms underlie conscious perception? A commonly adopted paradigm for studying this question is to present human subjects with threshold-level stimuli. When shown repeatedly, the same stimulus is sometimes consciously perceived, sometimes not. Using magnetoencephalography, we shed light on the neural mechanisms governing whether the stimulus is consciously perceived in a given trial. We observed that depending on the initial brain state defined by widespread activity pattern in the slow cortical potential (<5 Hz) range, a physically identical, brief (30 - 60 ms) stimulus input triggers distinct sequences of activity pattern evolution over time that correspond to either consciously perceiving the stimulus or not. Such activity pattern evolution forms a \"trajectory\" in the state space and affords significant single-trial decoding of perceptual outcome from 1 sec before to 3 sec after stimulus onset. While previous theories on conscious perception have emphasized sustained, high-level activity, we found that brain dynamics underlying conscious perception exhibit fast-changing activity patterns. These results significantly further our understanding on the neural mechanisms governing conscious access of a stimulus and the dynamical nature of neural activity underlying conscious perception.

neuroscience↗