Lifeboat Foundation

Eliminativism is a radical philosophical theory that holds that certain folk psychological concepts, such as beliefs, desires, and emotions, do not exist. Eliminativists argue that these concepts are either false or useless, and that we should eliminate them from our scientific and philosophical vocabulary.

This video will explore the philosophy of eliminativism in detail. We will discuss the arguments for and against eliminativism, as well as the implications of eliminativism for our understanding of the mind.

When an object hits a body of water vertically, it is accompanied by a strong hydrodynamic force fueled by the flow of water around it, which propels it forward. The magnitude of this force is known to vary depending on the mass of the object hitting the water.

In a study published in Device has reported a new self-powered electrostatic tweezer that offers superior accumulation and tunability of triboelectric charges, enabling unprecedented flexibility and adaptability for manipulating objects in various working scenarios. The research team was led by Dr. Du Xuemin from the Shenzhen Institute of Advanced Technology (SIAT) of the Chinese Academy of Sciences.

A team of scientists has developed a novel hybrid scheme for both steady and unsteady single-phase compressible flow simulations. Their scheme has potential applications in real-world scenarios, offering a promising avenue for future research.

The mechanisms of recognition and response to emotional stimuli are not fully understood. Here, the authors reveal tuning to semantic and emotional image features within occipital temporal cortex that efficiently encodes information suited to guiding behavior.

Imagine discovering a creature that could be as old as 500 years, swimming in the depths of the ocean. This is exactly what you find with the Greenland shark, a species now recognized as the longest-lived vertebrate in the world.

Julius Nielsen, a marine biologist at the University of Copenhagen, led a research team that made this groundbreaking discovery. They found a Greenland shark that was at least 272 years old, possibly even reaching 500 years in age, surpassing the previous record held by a 211-year-old bowhead whale.

Determining the age of many fish is done by counting the growth layers in calcium carbonate “stones” found in their ears, similar to counting tree rings. However, sharks don’t have these earstones. Additionally, the Greenland shark lacks other calcium-rich tissues suitable for this method. Instead, scientists used a different technique: examining the lenses in their eyes.

Intracortical microstimulation (ICMS) in human primary somatosensory cortex (S1) has been used to successfully evoke naturalistic sensations. However, the neurophysiological mechanisms underlying the evoked sensations remain unknown. To understand how specific stimulation parameters elicit certain sensations we must first understand the representation of those sensations in the brain. In this study we record from intracortical microelectrode arrays implanted in S1, premotor cortex, and posterior parietal cortex of a male human participant performing a somatosensory imagery task. The sensations imagined were those previously elicited by ICMS of S1, in the same array of the same participant. In both spike and local field potential recordings, features of the neural signal can be used to classify different imagined sensations. These features are shown to be stable over time. The sensorimotor cortices only encode the imagined sensation during the imagery task, while posterior parietal cortex encodes the sensations starting with cue presentation. These findings demonstrate that different aspects of the sensory experience can be individually decoded from intracortically recorded human neural signals across the cortical sensory network. Activity underlying these unique sensory representations may inform the stimulation parameters for precisely eliciting specific sensations via ICMS in future work.

SIGNIFICANCE STATEMENT
Electrical stimulation of human cortex is increasingly more common for providing feedback in neural devices. Understanding the relationship between naturally evoked and artificially evoked neurophysiology for the same sensations will be important in advancing such devices. Here, we investigate the neural activity in human primary somatosensory, premotor, and parietal cortices during somatosensory imagery. The sensations imagined were those previously elicited during intracortical microstimulation (ICMS) of the same somatosensory electrode array. We elucidate the neural features during somatosensory imagery that significantly encode different aspects of individual sensations and demonstrate feature stability over almost a year. The correspondence between neurophysiology elicited with or without stimulation for the same sensations will inform methods to deliver more precise feedback through stimulation in the future.

Keywords: brain-machine interface; human; intracortical microstimulation; sensation; somatosensation.

Consciousness is a heavy quest that has puzzled philosophers for over two thousand years. Because of its subjectivity and elusiveness, it was not a subject for scientific study until recent decades. With the unprecedented advances of artificial intelligence (AI), in particular, the remarkable performance of large language models (LLM), understanding consciousness becomes pragmatic and pressing beyond the philosophical and academic debates — how can we tell if ChatGPT has consciousness, and how can humankind be prepared if “artificial” consciousness arises in the foreseeable future?

For the last three decades, neuroscientists have made initial strides in theorizing the inner workings of consciousness in human brains based on vast experimental data, as triggered primarily by two factors.

First, the advances in scientific methods have empowered scientists to study the activities of neural cell assemblies in awake-behaving primates and humans. These techniques include brain imaging technologies, neurophysiological recording of hundreds of neurons simultaneously, and neural network modeling propelled by AI.

The ancient creature’s guts bring ancient history to life.