Howard Bowman

Place cells and concept neurons are defined by a rise in firing rate at a particular location or for a particular person or object. Neurons without such a rise remain unlabeled, although they keep firing during the task. Such neurons could still carry information in the timing of their spikes. Hippocampal theta provides a reference for this timing. We therefore asked whether the theta phase of a neuron’s spikes depends on location or on the viewed image, even when its firing rate does not. We analysed hippocampal neurons in humans navigating a virtual city, rats running on a linear track, and humans viewing images of animals, faces, and places. In both navigation datasets, more neurons than expected by chance fired at a consistent theta phase at particular locations. This phase tuning remained after we excluded neurons whose firing rate depended on location. In human navigation, the spike phases of these remaining neurons improved location decoding beyond the firing rates of all neurons. More phase-tuned neurons than expected by chance also fired at progressively earlier theta phases as participants passed each neuron’s preferred location. This pattern resembles phase precession, which classically occurs as an animal crosses the firing-rate field of a place cell. The neurons that showed it had no firing-rate field, so their phase shift was anchored to the location defined by phase tuning alone. During image viewing, more neurons than expected by chance changed the theta phase of their spikes after a particular image appeared. This effect remained after we removed, for each neuron, the images that changed its firing rate. Spike phases alone also predicted the image category above chance. Theta-relative spike timing therefore carries information about location and images that firing rate alone misses. We propose that weak input changes when a neuron fires within the theta cycle, whereas strong input also raises its firing rate.

Resolving the binding problem, i.e., how we integrate perceptual features in space and time to perceive objects, people and events as coherent wholes instead of masses of free-floating features, has been a central goal of cognitive scientists for decades. Conjunction errors occur whenever features are mis-bound leading to illusory percepts that were not actually presented. A specific kind of Rapid Serial Visual Presentation experiment induces temporal illusory conjunctions, called distractor intrusion errors. Despite these errors being well-established, current theories and models provide limited explanations. We present the 2-feature Simultaneous Type/Serial Token (2f-ST2) Model, the latest addition to the family of ST2-models, which simulates the most important behavioural and electrophysiological distractor intrusion findings. These include response distributions, reaction time patterns, and evoked electrophysiology responses. Importantly, we simulate these results across diverse empirical paradigms, implementing a range of stimulus sets, temporal dynamics, and involving multiple responses after each trial, without needing to modify our model's architecture or core parameters. Our findings are discussed in relation to theories of selective attention and working-memory binding. We argue that the 2f-ST2 model is more parsimonious than the leading theory of distractor-intrusions (the focussed-attention/sophisticated-guessing model), since it uses only a single binding mechanism, implying that correct bindings are simply fortunate conjunctions. The 2f-ST2 model further makes predictions for stimulus-competition, subjective-visibility and human electrophysiology. In summary, the ST2-model is a general framework for understanding how perception, temporal attention and working-memory interact, and the 2f-ST2 model extends the framework to distractor intrusions, thus explaining temporal feature binding.

In Rapid Serial Visual Presentation (RSVP), the vast majority of stimuli are not consciously perceived, but the salient ones breakthrough into awareness and can be reported. In addition, these breakthrough events are observable with EEG, since they generate a P3 or other distinguishing components. The Fringe-P3 method is based upon these characteristics. Concealed knowledge studies have successfully employed this Fringe-P3 method using own-name and own email-address, with the method being shown to be less vulnerable to counter-measures than other approaches. It has also been shown that famous faces presented in RSVP differentially break into awareness and generate a distinct evoked response component. In this paper, we further enhance the applicability of the Fringe-P3 method by demonstrating the effectiveness of the method on personally-familiar faces. While salient, such stimuli do not have the exquisite salience of famous faces, being a better match to the level of salience that might be found in forensic applications. Our findings suggest that the Fringe-P3 method could be used to detect intrinsic salience of familiar faces, even when there was no task associated with these faces. We investigated the sensitivity of the ERP-based RSVP paradigm to infer recognition of familiar faces, and performed statistical inference in the Time and Frequency domains, to differentiate between known and unknown faces, at group and participant levels.

Active inference is a process theory of perception, learning, and decision making that is applied to a range of research fields, including neuroscience, robotics, psychology, and machine learning. Active inference rests on an objective function called the expected free energy, which can be justified by the intuitive plausibility of its formulations—for example, the risk plus ambiguity and information gain/pragmatic value formulations. This letter seeks to formalize the problem of deriving these formulations from a single root expected free energy definition—the unification problem. Then we analyze two approaches to defining expected free energy. More precisely, the expected free energy is either defined as (1) the risk over observations plus ambiguity or (2) the risk over states plus ambiguity. In the first setting, no rigorous mathematical justification for the expected free energy has been proposed to date, but all the formulations can be recovered from it by assuming that the likelihood of target distribution T(o|s) is the likelihood of the generative model P(o|s). Importantly, under this likelihood constraint, if the likelihood is lossless,1 then prior preferences over observations can be defined arbitrarily. However, in the more general case of partially observable Markov decision processes (POMDPs), we demonstrate that the likelihood constraint effectively restricts the set of valid prior preferences over observations. Indeed, only a limited class of prior preferences over observations is compatible with the likelihood mapping of the generative model. In the second setting, a justification of the root expected free energy definition exists, but this setting only accounts for two formulations: the risk over states plus ambiguity and entropy plus expected energy formulations. We conclude with a discussion of the conditions under which a unification of expected free energy formulations has been proposed in the literature by appeal to the free energy principle in the specific context of systems without random fluctuations.

Half of all road accidents result from either lack of driver attention or from maintaining insufficient separation between vehicles. Collision from the rear, in particular, has been identified as the most common class of accident in the UK, and its influencing factors have been widely studied for many years. Rear-mounted stop lamps, illuminated when braking, are the primary mechanism to alert following drivers to the need to reduce speed or brake. This paper develops a novel brain response approach to measuring subject reaction to different brake light designs. A variety of off-the-shelf brake light assemblies are tested in a physical simulated driving environment to assess the cognitive reaction times of 22 subjects. Eight pairs of LED-based and two pairs of incandescent bulb-based brake light assemblies are used and electroencephalogram (EEG) data recorded. Channel Pz is utilised to extract the P3 component evoked during the decision making process that occurs in the brain when a participant decides to lift their foot from the accelerator and depress the brake. EEG analysis shows that both incandescent bulb-based lights are statistically slower to evoke cognitive responses than all tested LED-based lights. Between the LED designs, differences are evident, but not statistically significant, attributed to the significant amount of movement artifact in the EEG signal.

We provide evidence that the brain searches for salient stimuli below the level of conscious awareness. We show that, while targets are found very efficiently in Rapid Serial Visual Presentation (RSVP), distractors do not leave a strong memory trace, especially if the memory probe is unexpected. This fits with traditional theories of late attentional selection, whereby “correct rejections” of non-targets are performed with very little processing cost. Our findings are also consistent with the tokenized percept theory of conscious perception, one element of which is that conscious awareness is required to provide sustained representations.

In Rapid Serial Visual Presentation (RSVP), the vast majority of stimuli are not consciously perceived, but the salient ones breakthrough into awareness and can be reported. In addition, these breakthrough events are observable with EEG, since they generate a P3 or other distinguishing components. The Fringe-P3 method is based upon these characteristics. Concealed knowledge studies have successfully employed this Fringe-P3 method using own-name and own email-address, with the method being shown to be less vulnerable to counter-measures than other approaches. It has also been shown that famous faces presented in RSVP differentially break into awareness and generate a distinct evoked response component. In this paper, we further enhance the applicability of the Fringe-P3 concealed knowledge test by demonstrating the effectiveness of the method on personally-familiar faces. While salient, such stimuli do not have the exquisite salience of famous faces, being a better match to the level of salience that might be found in forensic applications. Our findings suggest that the Fringe-P3 method could be used to detect intrinsic salience of familiar faces, even when there was no task associated with these faces. We investigated the sensitivity of the ERP-based RSVP paradigm to infer recognition of familiar faces, and performed statistical inference in the Time and Frequency domains, to differentiate between known and unknown faces, at group and participant levels.

A key question in consciousness studies is what is distinct about a conscious as opposed to a sub-conscious percept. The experiments presented here provide evidence for the hypothesis that only conscious percepts enable the formation of episodic memories. We do this by assessing proactive interference (PI) in rapid serial visual presentation (RSVP) streams. Specifically, in a post-stream recognition memory test, we quantify memory for items presented in the RSVP stream close in time to the memory test. PI is demonstrated if performance on long RSVP streams is worse than on short streams, where long streams have many more items presented before the item probed in the recognition memory test. We demonstrate PI on reaction times for slow streams [stimulus onset asynchrony (SOA) 350 ms], but not for fast streams (SOA 83 or 100 ms). We investigate the implications of this reaction time difference by fitting drift diffusion models. The failure to see PI in fast streams raises the possibility that stimuli presented below the threshold of awareness are not episodically encoded.