Penelope A. Lewis

Brain activation patterns during measurement of sub- and supra-second intervals

The possibility that different neural systems are used to measure temporal durations at the sub-second and several second ranges has been supported by pharmacological manipulation, psychophysics, and neural network modelling. Here, we add to this literature by using fMRI to isolate differences between the brain networks which measure 0.6 and 3s in a temporal discrimination task with visual discrimination for control. We observe activity in bilateral insula and dorsolateral prefrontal cortex, and in right hemispheric pre-supplementary motor area, frontal pole, and inferior parietal cortex during measurement of both intervals, suggesting that these regions constitute a system used in temporal discrimination at both ranges. The frontal operculum, left cerebellar hemisphere and middle and superior temporal gyri, all show significantly greater activity during measurement of the shorter interval, supporting the hypotheses that the motor system is preferentially involved in the measurement of sub-second intervals, and that auditory imagery is preferentially used during measurement of the same. Only a few voxels, falling in the left posterior cingulate and inferior parietal lobe, are more active in the 3s condition. Overall, this study shows that although many brain regions are used for the measurement of both sub- and supra-second temporal durations, there are also differences in activation patterns, suggesting that distinct components are used for the two durations.

Remembering the time: a continuous clock

The neural mechanisms for time measurement are currently a subject of much debate. This article argues that our brains can measure time using the same dorsolateral prefrontal cells that are known to be involved in working memory. Evidence for this is: (1) the dorsolateral prefrontal cortex is integral to both cognitive timing and working memory; (2) both behavioural processes are modulated by dopamine and disrupted by manipulation of dopaminergic projections to the dorsolateral prefrontal cortex; (3) the neurons in question ramp their activity in a temporally predictable way during both types of processing; and (4) this ramping activity is modulated by dopamine. The dual involvement of these prefrontal neurons in working memory and cognitive timing supports a view of the prefrontal cortex as a multipurpose processor recruited by a wide variety of tasks.

Overlapping memory replay during sleep builds cognitive schemata.

Sleep enhances integration across multiple stimuli, abstraction of general rules, insight into hidden solutions and false memory formation. Newly learned information is better assimilated if compatible with an existing cognitive framework or schema. This article proposes a mechanism by which the reactivation of newly learned memories during sleep could actively underpin both schema formation and the addition of new knowledge to existing schemata. Under this model, the overlapping replay of related memories selectively strengthens shared elements. Repeated reactivation of memories in different combinations progressively builds schematic representations of the relationships between stimuli. We argue that this selective strengthening forms the basis of cognitive abstraction, and explain how it facilitates insight and false memory formation.

Brain activity correlates differentially with increasing temporal complexity of rhythms during initialisation, synchronisation, and continuation phases of paced finger tapping.

Activity in parts of the human motor system has been shown to correlate with the complexity of performed motor sequences in terms of the number of limbs moved, number of movements, and number of trajectories. Here, we searched for activity correlating with temporal complexity, in terms of the number of different intervals produced in the sequence, using an overlearned tapping task. Our task was divided into three phases: movement selection and initiation (initiate), synchronisation of finger tapping with an external auditory cue (synchronise), and continued tapping in absence of the auditory pacer (continue). Comparisons between synchronisation and continuation showed a pattern in keeping with prior neuroimaging studies of paced finger tapping. Thus, activation of bilateral SMA and basal ganglia was greater in continuation tapping than in synchronisation tapping. Parametric analysis revealed activity correlating with temporal complexity during initiate in bilateral supplementary and pre-supplementary motor cortex (SMA and preSMA), rostral dorsal premotor cortex (PMC), basal ganglia, and dorsolateral prefrontal cortex (DLPFC), among other areas. During synchronise, correlated activity was observed in bilateral SMA, more caudal dorsal and ventral PMC, right DLPFC and right primary motor cortex. No correlated activity was observed during continue at P<0.01 (corrected, cluster level), though left angular gyrus was active at P<0.05. We suggest that the preSMA and rostral dorsal PMC activities during initiate may be associated with selection of timing parameters, while activation in centromedial prefrontal cortex during both initiate and synchronise may be associated with temporal error monitoring or correction. The absence of activity significantly correlated with temporal complexity during continue suggests that, once an overlearned timed movement sequence has been selected and initiated, there is no further adjustment of the timing control processes related to its continued production in absence of external cues.

A right hemispheric prefrontal system for cognitive time measurement

Despite a growing body of neuroimaging data, little consensus has been reached regarding the neural correlates of temporal processing in humans. This paper presents a reanalysis of two previously published neuroimaging experiments, which used two different cognitive timing tasks and examined both sub- and supra-second intervals. By processing these data in an identical manner, this reanalysis allows valid comparison and contrasting across studies. Conjunction of these studies using inclusive masking reveals shared activity in right hemispheric dorsolateral and ventrolateral prefrontal cortex and anterior insula, supporting a general-purpose system for cognitive time measurement in the right hemispheric prefrontal cortex. Consideration of the patterns of activity in each dataset with respect to the others, and taking task characteristics into account, provides insight into the possible role of dorsolateral prefrontal cortex in working memory and of posterior parietal cortex and anterior cingulate in attentional processing during cognitive time measurement tasks.

The precision of temporal judgement: Milliseconds, many minutes, and beyond

The principle that the standard deviation of estimates scales with the mean estimate, commonly known as the scalar property, is one of the most broadly accepted fundamentals of interval timing. This property is measured using the coefficient of variation (CV) calculated as the ratio between the standard deviation and the mean. In 1997, John Gibbon suggested that different time measurement mechanisms may have different levels of absolute precision, and would therefore be associated with different CVs. Here, we test this proposal by examining the CVs produced by human subjects timing a broad range of intervals (68 ms to 16.7 min). Our data reveal no evidence for multiple mechanisms, but instead show a continuous logarithmic decrease in CV as timed intervals increase. This finding joins other recent reports in demonstrating a systematic violation of the scalar property in timing data. Interestingly, the estimated CV of circadian judgements fits onto the regression of decreasing CV, suggesting a link between short interval and circadian timing mechanisms.

Sleep-dependent consolidation of statistical learning.

The importance of sleep for memory consolidation has been firmly established over the past decade. Recent work has extended this by suggesting that sleep is also critical for the integration of disparate fragments of information into a unified schema, and for the abstraction of underlying rules. The question of which aspects of sleep play a significant role in integration and abstraction is, however, currently unresolved. Here, we examined the role of sleep in abstraction of the implicit probabilistic structure in sequential stimuli using a statistical learning paradigm, and tested for its role in such abstraction by searching for a predictive relationship between the type of sleep obtained and subsequent performance improvements using polysomnography. In our experiments, participants were exposed to a series of tones in a probabilistically determined sequential structure, and subsequently tested for recognition of novel short sequences adhering to this same statistical pattern in both immediate- and delayed-recall sessions. Participants who consolidated over a night of sleep improved significantly more than those who consolidated over an equivalent period of daytime wakefulness. Similarly, participants who consolidated across a 4-h afternoon delay containing a nap improved significantly more than those who consolidated across an equivalent period without a nap. Importantly, polysomnography revealed a significant correlation between the level of improvement and the amount of slow-wave sleep obtained. We also found evidence of a time-based consolidation process which operates alongside sleep-specific consolidation. These results demonstrate that abstraction of statistical patterns benefits from sleep, and provide the first clear support for the role of slow-wave sleep in this consolidation.

Orbital prefrontal cortex volume correlates with social cognitive competence

Intentionality, or Theory of Mind, is the ability to explain and predict the behaviour of others by attributing to them intentions and mental states and is hypothesised to be one of several social cognitive mechanisms which have impacted upon brain size evolution. Though the brain activity associated with processing this type of information has been studied extensively, the neuroanatomical correlates of these abilities, e.g. whether subjects who perform better have greater volume of associated brain regions, remain to be investigated. Because social abilities of this type appear to have evolved relatively recently, and because the prefrontal cortex (PFC) was the last brain region to develop both phylogenetically and ontogenetically, we hypothesised a relationship between PFC volume and intentional competence. To test this, we estimated the volume of four regional prefrontal subfields in each cerebral hemisphere, in 40 healthy adult humans by applying stereological methods on T(1)-weighted magnetic resonance images. Our results reveal a significant linear relationship between intentionality score and volume of orbital PFC (p=0.01). Since this region is known to be involved in the processing of social information our findings support the hypothesis that brain size evolution is, at least in part, the result of social cognitive mechanisms supporting social cohesion.

The role of sleep spindles and slow-wave activity in integrating new information in semantic memory.

Assimilating new information into existing knowledge is a fundamental part of consolidating new memories and allowing them to guide behavior optimally and is vital for conceptual knowledge (semantic memory), which is accrued over many years. Sleep is important for memory consolidation, but its impact upon assimilation of new information into existing semantic knowledge has received minimal examination. Here, we examined the integration process by training human participants on novel words with meanings that fell into densely or sparsely populated areas of semantic memory in two separate sessions. Overnight sleep was polysomnographically monitored after each training session and recall was tested immediately after training, after a night of sleep, and 1 week later. Results showed that participants learned equal numbers of both word types, thus equating amount and difficulty of learning across the conditions. Measures of word recognition speed showed a disadvantage for novel words in dense semantic neighborhoods, presumably due to interference from many semantically related concepts, suggesting that the novel words had been successfully integrated into semantic memory. Most critically, semantic neighborhood density influenced sleep architecture, with participants exhibiting more sleep spindles and slow-wave activity after learning the sparse compared with the dense neighborhood words. These findings provide the first evidence that spindles and slow-wave activity mediate integration of new information into existing semantic networks.

Mood-dependent memory

Have you ever noticed that when you are in a bad mood the whole world seems to be against you? More negative things seem to happen, and you even remember past episodes of your life in a more negative way than usual. Most of us have experienced this phenomenon, but few will have thought about how this mood might interact with our ability to remember. In a recent paper, Susanne Erk et al. shed light on a possible neural basis for this phenomena.