[HTML][HTML] Integrative benchmarking to advance neurally mechanistic models of human intelligence
A potentially organizing goal of the brain and cognitive sciences is to accurately explain
domains of human intelligence as executable, neurally mechanistic models. Years of …
domains of human intelligence as executable, neurally mechanistic models. Years of …
Scanning the horizon: towards transparent and reproducible neuroimaging research
Functional neuroimaging techniques have transformed our ability to probe the
neurobiological basis of behaviour and are increasingly being applied by the wider …
neurobiological basis of behaviour and are increasingly being applied by the wider …
Similarity of neural network representations revisited
Recent work has sought to understand the behavior of neural networks by comparing
representations between layers and between different trained models. We examine methods …
representations between layers and between different trained models. We examine methods …
Deep problems with neural network models of human vision
Deep neural networks (DNNs) have had extraordinary successes in classifying
photographic images of objects and are often described as the best models of biological …
photographic images of objects and are often described as the best models of biological …
Getting aligned on representational alignment
Biological and artificial information processing systems form representations that they can
use to categorize, reason, plan, navigate, and make decisions. How can we measure the …
use to categorize, reason, plan, navigate, and make decisions. How can we measure the …
Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns
Contextual embeddings, derived from deep language models (DLMs), provide a continuous
vectorial representation of language. This embedding space differs fundamentally from the …
vectorial representation of language. This embedding space differs fundamentally from the …
Neural tuning and representational geometry
A central goal of neuroscience is to understand the representations formed by brain activity
patterns and their connection to behaviour. The classic approach is to investigate how …
patterns and their connection to behaviour. The classic approach is to investigate how …
Contrastive learning explains the emergence and function of visual category-selective regions
Modular and distributed coding theories of category selectivity along the human ventral
visual stream have long existed in tension. Here, we present a reconciling framework …
visual stream have long existed in tension. Here, we present a reconciling framework …
THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior
Understanding object representations requires a broad, comprehensive sampling of the
objects in our visual world with dense measurements of brain activity and behavior. Here …
objects in our visual world with dense measurements of brain activity and behavior. Here …
Promises and limitations of human intracranial electroencephalography
Intracranial electroencephalography (iEEG), also known as electrocorticography when using
subdural grid electrodes or stereotactic EEG when using depth electrodes, is blossoming in …
subdural grid electrodes or stereotactic EEG when using depth electrodes, is blossoming in …