Topic: computational model

Explicit similarity judgments tend to emphasize relational information more than do difference judgments. In this talk, I propose and test the hypothesis that this asymmetry arises because human reasoners represent the relation different as the negation of the relation same (i.e., as not-same). This proposal implies that processing difference is more cognitively demanding than processing similarity. Both for verbal comparisons between word pairs, and for visual comparisons between sets of geometric shapes, participants completed a triad task in which they selected which of two options was eith

The capacities to learn and to store memories are two of the most important functions of the brain, but these abilities are inherently at odds with each other. On one hand, a neuronal network must be flexible enough to quickly store new information, but on the other it must be stable enough to prevent old memories from being constantly overwritten. Metaplasticity in which the timescale of synaptic modifications made by an individual neuron changes could resolve this flexibility-stability tradeoff. We propose that this strategy may be implemented in the olfactory bulb (OB). A striking, characte

Our perception of time isn’t like a clock; it varies depending on other aspects of experience, such as what we see and hear in that moment. However, in everyday life, the properties of these simple features can change frequently, presenting a challenge to understanding real-world time perception based on simple lab experiments. We developed a computational model of human time perception based on tracking changes in neural activity across brain regions involved in sensory processing, using fMRI. By measuring changes in brain activity patterns across these regions, our approach accommodates the

Human behavior is known to be idiosyncratic, yet research in neuroscience typically assumes a universal brain-behavior relationship. Here we test this assumption by estimating the level of idiosyncrasy by compare two different aspects of brain function: task- and behavior-based activation. Human subjects (N=50) perform a perceptual task with confidence inside an MRI scanner. For each subject, task-based activation strength is estimated from blocks of 8 trials. We first show that task-based activation maps are both stable within an individual (r = 0.99) and similar across people (r = 0.59). Beh

How do children learn to read in different countries? How do deficits in various components of the reading network affect learning outcomes? What are the consequences of such deficits in different languages? In this talk, I will present a full-blown developmentally plausible computational model of reading acquisition that has been implemented in English, French, Italian and German. The model can simulate individual learning trajectories and intervention outcomes on the basis of three component skills: orthography, phonology, and vocabulary. I will use the model to show how cross-language diffe

In order for animals to thrive in their complex environments, their sensory systems must form representations of objects that are invariant to changes in some dimensions of their physical cues. For example, we can recognize a friend’s speech in a forest, a small office, and a cathedral, even though the sound reaching our ears will be very different in these three environments. I will discuss our recent experiments into how neurons in auditory cortex can form stable representations of sounds in this acoustically varied world. We began by using a normative computational model of hearing to exami

Selection is the hallmark of attention: processing improves for attended items but is relatively impaired for unattended items. It is well known that visual spatial attention changes sensory signals and perception in this selective fashion. In the work I will present, we asked whether and how attentional selection happens across time. First, our experiments revealed that voluntary temporal attention (attention to specific points in time) is selective, resulting in perceptual tradeoffs across time. Second, we measured small eye movements called microsaccades and found that directing voluntary t

Current computational models of visual salience accurately predict the distribution of fixations on isolated visual stimuli. It is not known, however, whether the global salience of a stimulus, that is its effectiveness in the competition for attention with other stimuli, is a function of the local salience or an independent measure. Further, do task and familiarity with the competing images influence eye movements? In this talk, I will present the analysis of a computational model of the global salience of natural images. We trained a machine learning algorithm to learn the direction of the f

Astrocytes play a crucial role in regulating synaptic strength and orchestrating synaptic plasticity, which is fundamental for learning and memory. However, the specific mechanisms by which astrocytes and their neuroactive transmitters, like D-serine, control these processes remain largely unexplored. D-serine, a co-agonist for the NMDA receptor, has garnered increasing interest as a potential regulatory molecule in synaptic plasticity. Given its activity-dependent release mediated by astrocytes, D-serine is a key player in balancing long-term synaptic depression (LTD) and potentiation (LTP) d