Biology subjects

Donner, T. H.

Publications and source records attributed to Donner, T. H..

40 records · Page 3Linked to original sources

bioRxiv2018

Surprise About Sensory Event Timing Drives Cortical Transients in the Beta Frequency Band

Understanding the statistical structure of the environment is crucial for adaptive behavior. Humans and non-human decision-makers seem to track such structure through a process of probabilistic inference, which enables predictions about behaviorally relevant events. Deviations from such predictions cause surprise, which in turn helps improve the inference. Surprise about the timing of behaviorally relevant sensory events drives phasic responses of neuromodulatory brainstem systems, which project to the cerebral cortex. Here, we developed a computational model-based magnetoencephalography (MEG) approach for mapping the resulting cortical transients across space, time, and frequency, in the human brain. We used a Bayesian updating model to estimate the predicted timing of the next stimulus change in a simple visual detection task. This model yielded quantitative trial-by-trial estimates of temporal surprise. The model-based surprise variable predicted trial-by-trial variations in reaction time more strongly than the externally observable interval timings alone. Trial-by-trial variations in surprise were negatively correlated with the power of cortical population activity measured with MEG. This surprise-related power suppression occurred transiently around the behavioral response, specifically in the beta frequency band. It peaked in left lateral prefrontal as well as in frontal midline regions, and its cortical distribution was distinct from the movement-related suppression of beta power in motor cortex. Our results indicate that surprise about sensory event timing transiently suppresses ongoing beta-band oscillations in association cortex. This transient suppression of frontal beta-band oscillations might reflect an active reset triggered by surprise, and is in line with the idea that beta-oscillations help maintain cognitive sets.\n\nSignificance statementAgents continuously track the statistical structure of the environment, in order to make predictions about behaviorally relevant sensory events. Deviations from such predictions cause surprise, which in turn drives phasic responses of neuromodulatory brainstem systems that project to the cerebral cortex. We developed a computational model-based magnetoencephalography approach, which enabled us to map out transients changes in cortical population dynamics elicited by surprise about sensory event timing, across space, time, and frequency, in the human brain. The model-based estimates of surprise predicted behavior as well as a transient suppression of beta frequency-band oscillations in frontal cortical regions. Our results are in line with conceptual accounts that have linked neural oscillations in the beta-band to the maintenance of cognitive sets.

neuroscience↗

bioRxiv2018

Choice history biases subsequent evidence accumulation

AO_SCPLOWBSTRACTC_SCPLOWPerceptual choices depend not only on the current sensory input, but also on the behavioral context. An important contextual factor is the history of ones own choices. Choice history often strongly biases perceptual decisions, and leaves traces in the activity of brain regions involved in decision processing. Yet, it remains unknown how such history signals shape the dynamics of later decision formation. Models of perceptual choice construe decision formation as the accumulation of sensory evidence towards decision bounds. In this framework, it is commonly assumed that choice history signals shift the starting point of accumulation towards the bound reflecting the previous choice. We here present results that challenge this idea. We fit bounded-accumulation decision models to behavioral data from perceptual choice tasks, and estimated bias parameters that depended on observers previous choices. Across multiple task protocols and sensory modalities, individual history biases in overt behavior were consistently explained by a history-dependent change in the evidence accumulation, rather than in its starting point. Choice history signals thus seem to bias the interpretation of current sensory input, akin to shifting endogenous attention towards (or away from) the previously selected interpretation.

neuroscience↗

bioRxiv2017

Catecholamines, not acetylcholine, alter cortical and perceptual dynamics in line with increased excitation inhibition ratio

The ratio between excitatory and inhibitory neurons (E/I ratio) is vital for cortical circuit dynamics, computation, and behavior. This ratio may be under the dynamic control of neuromodulatory systems, which are in turn implicated in several neuropsychiatric disorders. In particular, the catecholaminergic (dopaminergic and noradrenergic) and cholinergic systems have highly specific effects on excitatory and inhibitory cortical neurons, which might translate into changes in the local net E/I ratio. Here, we assessed and compared their net effects on net E/I ratio in human cortex, through an integrated application of computational modeling, placebo-controlled pharmacological intervention, magnetoencephalographic recordings of cortical activity dynamics, and perceptual psychophysics. We found that catecholamines, but not acetylcholine, altered both the temporal structure of intrinsic activity fluctuations in visual and parietal cortex, and the volatility of perceptual inference based on ambiguous visual input. Both effects indicate that catecholamines increase the net E/I ratio in visual and parietal cortex.

neuroscience↗

bioRxiv2017

Confidence-dependent accumulation of past decision variables biases perceptual choice

Perceptual decision-making is biased by previous events, including the history of preceding choices: Observers tend to repeat (or alternate) their judgments of the sensory environment more often than expected by chance. Computational models postulate that these so-called choice history biases result from the accumulation of internal decision signals across trials. Here, we provide psychophysical evidence for such a mechanism and its adaptive utility. Male and female human observers performed different variants of a challenging visual motion discrimination task near psychophysical threshold. In a first experiment, we decoupled categorical perceptual choices and motor responses on a trial-by-trial basis. Choice history bias was explained by previous perceptual choices, not motor responses, highlighting the importance of internal decision signals in action-independent formats. In a second experiment, observers performed the task in stimulus environments containing different levels of autocorrelation and providing no external feedback about choice correctness. Despite performing under overall high levels of uncertainty, observers adjusted both the strength and the sign of their choice history biases to these environments. When stimulus sequences were dominated by either repetitions or alternations, the individual degree of this adjustment of history bias was about as good a predictor of individual performance as individual perceptual sensitivity. The history bias adjustment scaled with two proxies for observers confidence about their previous choices (accuracy and reaction time). Taken together, our results are consistent with the idea that action-independent, confidence-modulated decision variables are accumulated across choices in a flexible manner that depends on decision-makers model of their environment.\n\nSignificance statementDecisions based on sensory input are often influenced by the history of ones preceding choices, manifesting as a bias to systematically repeat (or alternate) choices. We here provide support for the idea that such choice history biases arise from the context-dependent accumulation of a quantity referred to as the decision variable: the variables sign dictates the choice and its magnitude the confidence about choice correctness. We show that choices are accumulated in an actionindependent format and a context-dependent manner, weighted by the confidence about their correctness. This confidence-weighted accumulation of choices enables decision-makers to flexibly adjust their behavior to different sensory environments. The bias adjustment can be as important for optimizing performance as ones sensitivity to the momentary sensory input.

neuroscience↗