Components of aging

Age-related cognitive decline has been linked to a reduction in attentional resources that are assumed to result from alterations in the aging brain. A core ability that is subject to age-related decline is visual attention, which enables individuals to select the most important information for conscious processing and action. However, visual attention is considered a conglomerate of various functions and the specific components underlying age differences in performance remain little understood. The present PhD project aimed at dissociating age effects on several (sub-) components that concur in visual attention tasks within a neurocognitive approach. Established and theoretically grounded psychological paradigms that allow separating various attentional components were combined with event-related potentials (ERPs), which provide a temporally fine-graded dissociation of cognitive processes involved in a task. 1st Project The first project was designed to determine the origin(s) of age-related decline in visual search, a key paradigm of attention research. To pursue this goal on a micro-level, response time measures in a compound-search task, in which the target-defining feature of a pop-out target (color/shape) was dissociated from the response-defining feature (orientation), were coupled with lateralized ERPs. Several ERP components tracked the timing of processing stages involved in this task, these being (1) allocation of attention to the target, marked by the posterior-contralateral negativity (PCN), (2) target analyses in vSTM, marked by the sustained posterior-contralateral negativity (SPCN), (3) response selection, marked by the stimulus-locked lateralized readiness potential (LRP) and (4) response execution, marked by the response-locked LRP. Slowed response times (RT) in older participants were associated with age differences in all analyzed ERPs, indicating that behavioural slowing accrues across multiple stages within the information processing stream. Furthermore, v behavioral data and ERPs were analyzed with respect to age and carry-over effects from one trial to the next. The intertrial analyses revealed relatively automatic processes – such as dimension weighting facilitating the early stage of visual selection, and response weighting facilitating the late stage of response execution – to be preserved in older age. By contrast, more controlled processes – such as the flexible stimulus-response (S-R) (re-) mapping across trials on the intermediate stages of response selection - were particularly affected by aging. This indicates that besides general slowing, specific age decrements in executively controlled processes contribute to age-related decline in visual search. 2nd Project The second project explored neural markers of individual and age differences in attention parameters formally integrated in Bundesen’s computational Theory of Visual Attention (TVA). According to the model, two parameters of general visual attention capacity, perceptual processing speed C and visual short-term memory (vSTM) storage capacity K are defined and can be modeled mathematically independently for a particular individual. More recently, the neural interpretation of the model (NTVA) suggested that the two functions (at least partly) rely on distinct brain mechanisms. To test this assumption in an empirical approach, individual TVA-based estimates were derived in a standard TVA whole report task, and ERPs of the same participants were recorded in an adapted EEG-compatible version of the task. In the first study of the second project, we explored neurophysiological markers of interindividual differences in the two functions in younger participants. The results revealed distinct ERP correlates to be related to the parameters: Individuals with higher compared to lower processing speed C had significantly smaller posterior N1 amplitudes, suggesting that the rate of object categorization is associated with the efficiency of early visual processing. Individuals with higher compared to lower storage capacity showed stronger contralateral delay activity (CDA) over visual areas, indicating that the limit of vi vSTM relies on topographically-organized sustained activation within the visual system. These results can be regarded as direct neuroscientific evidence for central assumptions of the theoretical framework. In the second study of the second project, the same approach was pursued to investigate whether and how TVA attentional capacity parameters and their neural markers change with aging. First, the same ERP correlates of processing speed and storage capacity indexing individual differences in younger participants (i.e., the posterior N1 marked differences in processing speed C and the CDA marked differences in storage capacity K, respectively) were found to be valid also in the older group. In addition to this, two further components marked performance differences in the parameters exclusively within the older group: Older participants with lower processing speed showed smaller anterior N1 amplitudes relative to faster older and all younger participants, suggesting a selective loss of resources supporting early control of attentional guidance. Older participants with higher storage capacity exhibited a stronger right-central positivity than older participants with lower storage capacity and all younger participants. This pattern is indicative of compensatory recruitment of additional neural resources in high-functioning older individuals, presumably related to enhanced executive control fostering sustained activation of vSTM representations. Again, these findings strongly support the NTVA framework, proposing distinct neural mechanisms underlying processing speed and storage capacity. Furthermore, they show that distinct mechanisms of attentional control determine the two functions in older age

A feedback model of perceptual learning and categorisation

Top-down, feedback, influences are known to have significant effects on visual information processing. Such influences are also likely to affect perceptual learning. This article employs a computational model of the cortical region interactions underlying visual perception to investigate possible influences of top-down information on learning. The results suggest that feedback could bias the way in which perceptual stimuli are categorised and could also facilitate the learning of sub-ordinate level representations suitable for object identification and perceptual expertise

Task switching in the prefrontal cortex

The overall goal of this dissertation is to elucidate the cellular and circuit mechanisms underlying flexible behavior in the prefrontal cortex. We are often faced with situations in which the appropriate behavior in one context is inappropriate in others. If these situations are familiar, we can perform the appropriate behavior without relearning how the context relates to the behavior — an important hallmark of intelligence. Neuroimaging and lesion studies have shown that this dynamic, flexible process of remapping context to behavior (task switching) is dependent on prefrontal cortex, but the precise contributions and interactions of prefrontal subdivisions are still unknown. This dissertation investigates two prefrontal areas that are thought to be involved in distinct, but complementary executive roles in task switching — the dorsolateral prefrontal cortex (dlPFC) and the anterior cingulate cortex (ACC). Using electrophysiological recordings from macaque monkeys, I show that synchronous network oscillations in the dlPFC provide a mechanism to flexibly coordinate context representations (rules) between groups of neurons during task switching. Then, I show that, wheras the ACC neurons can represent rules at the cellular level, they do not play a significant role in switching between contexts — rather they seem to be more related to errors and motivational drive. Finally, I develop a set of web-enabled interactive visualization tools designed to provide a multi-dimensional integrated view of electrophysiological datasets. Taken together, these results contribute to our understanding of task switching by investigating new mechanisms for coordination of neurons in prefrontal cortex, clarifying the roles of prefrontal subdivisions during task switching, and providing visualization tools that enhance exploration and understanding of large, complex and multi-scale electrophysiological data

Effects of non-pharmacological or pharmacological interventions on cognition and brain plasticity of aging individuals.

Brain aging and aging-related neurodegenerative disorders are major health challenges faced by modern societies. Brain aging is associated with cognitive and functional decline and represents the favourable background for the onset and development of dementia. Brain aging is associated with early and subtle anatomo-functional physiological changes that often precede the appearance of clinical signs of cognitive decline. Neuroimaging approaches unveiled the functional correlates of these alterations and helped in the identification of therapeutic targets that can be potentially useful in counteracting age-dependent cognitive decline. A growing body of evidence supports the notion that cognitive stimulation and aerobic training can preserve and enhance operational skills in elderly individuals as well as reduce the incidence of dementia. This review aims at providing an extensive and critical overview of the most recent data that support the efficacy of non-pharmacological and pharmacological interventions aimed at enhancing cognition and brain plasticity in healthy elderly individuals as well as delaying the cognitive decline associated with dementia

Stochastic accumulation of feature information in perception and memory

It is now well established that the time course of perceptual processing influences the first second or so of performance in a wide variety of cognitive tasks. Over the last20 years, there has been a shift from modeling the speed at which a display is processed, to modeling the speed at which different features of the display are perceived and formalizing how this perceptual information is used in decision making. The first of these models(Lamberts, 1995) was implemented to fit the time course of performance in a speeded perceptual categorization task and assumed a simple stochastic accumulation of feature information. Subsequently, similar approaches have been used to model performance in a range of cognitive tasks including identification, absolute identification, perceptual matching, recognition, visual search, and word processing, again assuming a simple stochastic accumulation of feature information from both the stimulus and representations held in memory. These models are typically fit to data from signal-to-respond experiments whereby the effects of stimulus exposure duration on performance are examined, but response times (RTs) and RT distributions have also been modeled. In this article, we review this approach and explore the insights it has provided about the interplay between perceptual processing, memory retrieval, and decision making in a variety of tasks. In so doing, we highlight how such approaches can continue to usefully contribute to our understanding of cognition

Toward a second-person neuroscience

LS & BT : equal contributions (shared first-authorship)Peer reviewedPreprin