Lifeboat Foundation

Background: To evaluate the electroretinogram waveform in autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) using a discrete wavelet transform (DWT) approach.

Methods: A total of 55 ASD, 15 ADHD and 156 control individuals took part in this study. Full field light-adapted electroretinograms (ERGs) were recorded using a Troland protocol, accounting for pupil size, with five flash strengths ranging from −0.12 to 1.20 log photopic cd.s.m^–2. A DWT analysis was performed using the Haar wavelet on the waveforms to examine the energy within the time windows of the a-and b-waves and the oscillatory potentials (OPs) which yielded six DWT coefficients related to these parameters. The central frequency bands were from 20–160 Hz relating to the a-wave, b-wave and OPs represented by the coefficients: a20, a40, b20, b40, op80, and op160, respectively. In addition, the b-wave amplitude and percentage energy contribution of the OPs (%OPs) in the total ERG broadband energy was evaluated.

Results: There were significant group differences (p < 0.001) in the coefficients corresponding to energies in the b-wave (b20, b40) and OPs (op80 and op160) as well as the b-wave amplitude. Notable differences between the ADHD and control groups were found in the b20 and b40 coefficients. In contrast, the greatest differences between the ASD and control group were found in the op80 and op160 coefficients. The b-wave amplitude showed both ASD and ADHD significant group differences from the control participants, for flash strengths greater than 0.4 log photopic cd.s.m^–2 (p < 0.001).

Despite constituting less than 2% of the body’s mass, the human brain consumes approximately 20% of total caloric intake, with 50% of the energy being used by cortex (Herculano-Houzel, 2011). The majority of this energy is spent by neurons to reverse the ion fluxes associated with electrical signaling via Na⁺/K⁺ ATPase (Attwell and Laughlin, 2001; Harris et al., 2012). Excitatory synaptic currents and action potentials are particularly costly in this regard, accounting for approximately 57% and 23% of the energy budget for electrical signaling in gray matter, respectively (Harris et al., 2012; Sengupta et al., 2010). Given this cost, and the scarcity of resources, the brain is thought to have evolved an energy-efficient coding strategy that maximizes information transmission per unit energy (i.e., ATP) (Barlow, 2012; Levy and Baxter, 1996). This strategy accounts for a number of cellular features, including the low mean firing rate of neurons and the high failure rate of synaptic transmission, as well as higher order features, such as the structure of neuronal receptive fields (Albert et al., 2008; Attwell and Laughlin, 2001; Harris et al., 2015; Levy and Baxter, 1996; Olshausen and Field, 1997; Sterling and Laughlin, 2015). Scarcity of food, therefore, appears to have strongly sculpted information coding in the brain throughout evolution.

Energy intake is not fixed but can vary substantially across individuals, environments, and time (Hladik, 1988; Knott, 1998). Given that the brain is energy limited, one hypothesis is that in times of food scarcity, neuronal networks should save energy by reducing information processing. There is some evidence to suggest that this is the case in invertebrates (Kauffman et al., 2010; Longden et al., 2014; Plaçais et al., 2017; Placais and Preat, 2013). In Drosophila 0, food deprivation inactivates neural pathways required for long-term memory to preserve energy (Plaçais et al., 2017; Placais and Preat, 2013). Experimental re-activation of these pathways restores memory formation but significantly reduces survival rates (Placais and Preat, 2013). Similar memory impairments are seen with reduced food intake in C. elegans (Kauffman et al., 2010). Moreover, in blowfly, food deprivation reduces visual interneuron responses during locomotion, consistent with energy savings (Longden et al., 2014). However, it remains unclear whether and how the mammalian brain, and cortical networks in particular, regulate information processing and energy use in times of food scarcity.

Here we used the mouse primary visual cortex (V1) as a model system to examine how food restriction affects information coding and energy consumption in cortical networks. We assessed neuronal activity and ATP consumption using whole-cell patch-clamp recordings and two-photon imaging of V1 layer 2/3 excitatory neurons in awake, male mice. We found that food restriction, resulting in a 15% reduction of body weight, led to a 29% reduction in ATP expenditure associated with excitatory postsynaptic currents, which was mediated by a decrease in single-channel AMPA receptor (AMPAR) conductance. Reductions in AMPAR current were compensated by an increase in input resistance and a depolarization of the resting membrane potential, which preserved neuronal excitability; neurons were therefore able to generate a comparable rate of spiking as controls, while spending less ATP on the underlying excitatory currents. This energy-saving strategy, however, had a cost to coding precision. Indeed, we found that an increase in input resistance and depolarization of the resting membrane potential also increased the subthreshold variability of visual responses, which increased the probability for small depolarizations to cross spike threshold, leading to a broadening of orientation tuning by 32%. Broadened tuning was associated with reduced coding precision of natural scenes and behavioral impairment in fine visual discrimination. We found that these deficits in visual coding under food restriction correlated with reduced circulating levels of leptin, a hormone secreted by adipocytes in proportion to fat mass (Baile et al., 2000), and were restored by exogenous leptin supplementation. Our findings reveal key metabolic state-dependent mechanisms by which the mammalian cortex regulates coding precision to preserve energy in times of food scarcity.

Neuro-Protection & Neuro-Regeneration R&D For Optic Pathologies — Dr. Thomas V. Johnson, MD, PhD, Johns Hopkins Medicine

Dr. Thomas V. Johnson III, M.D., Ph.D. (https://www.hopkinsmedicine.org/profiles/details/thomas-johnson) is a glaucoma specialist and the Allan and Shelley Holt Rising Professor in Ophthalmology at Wilmer Eye Institute, at Johns Hopkins University. He is also a member of the Retinal ganglion cell (RGC) Repopulation, Stem cell Transplantation, and Optic nerve Regeneration (RReSTORe) consortium (https://www.hopkinsmedicine.org/wilmer/research/storm/rrestore/index.html), an initiative focused on advancing translational development of vision restoration therapies for glaucoma and other primary optic neuropathies by assembling an international group of more than 100 leading and emerging investigators from related fields.

Continue reading “Dr Thomas V Johnson III, MD, PhD — Neuro-Protection & Neuro-Regeneration R&D For Optic Pathologies” »

Humans are unrivaled in the area of cognition. After all, no other species has sent probes to other planets, produced lifesaving vaccines, or created poetry. How information is processed in the human brain to make this possible is a question that has drawn endless fascination, yet no definitive answers.

Our understanding of brain function has changed over the years. But current theoretical models describe the brain as a “distributed information-processing system.” This means it has distinct components that are tightly networked through the brain’s wiring. To interact with each other, regions exchange information though a system of input and output signals.

However, this is only a small part of a more complex picture. In a study published last week in Nature Neuroscience, using evidence from different species and multiple neuroscientific disciplines, we show that there isn’t just one type of information processing in the brain. How information is processed also differs between humans and other primates, which may explain why our species’ cognitive abilities are so superior.

Scientists at the Institute of Cancer Research in London have developed a new light-activated “photoimmunotherapy” that could help treat brain cancer. The key is a compound that glows under light to guide surgeons to the tumor, while near-infrared light activates a cancer-killing mechanism.

The new study builds on a common technique called Fluorescence Guided Surgery (FGS), which involves introducing a fluorescent agent to the body which glows under exposure to light. This is paired with a synthetic molecule that binds to a specific protein, such as those expressed by cancer cells. The end result is tumors that glow under certain lighting conditions or imaging, guiding surgeons to remove the affected cells more precisely.

For the new study, the researchers gave the technique an extra ability – killing the cancer as well. They added a new molecule that binds to a protein called EGFR, which is often mutated in cases of the brain cancer glioblastoma. After the fluorescence has helped surgeons remove the bulk of the tumor, they can shine near-infrared light on the site, which switches the compound into a tumor-killing mode by releasing reactive oxygen species. The idea is to kill off any remaining cells that could – and often do – stage an aggressive comeback after surgery.

Scientists achieve brain to brain communication between humans.

We need to know whether a gathering individual could work together utilizing just their cerebrums.

Based on a novel intertwined theoretical and experimental approach, we examined one of the pillars of the Orch OR model, namely the gravity-related collapse model. In this context, we examined the Orch OR calculations using the gravity-related (called Diosi-Penrose, DP, for reasons we explain in the article) theory along with recent experimental constraints on the DP cutoff parameter (R0). We showed that, in this context, the Orch OR based on the DP theory is definitively ruled out for the case of atomic nuclei level of separation, without needing to consider the impact of environmental decoherence; we also showed that the case of partial separation requires the brain to maintain coherent superpositions of tubulin of such mass, duration, and size that vastly exceed any of the coherent superposition states that have been achieved with state-of-the-art optomechanics and macromolecular interference experiments. We conclude that none of the scenarios we discuss (with possible exception to the case of partial separation of tubulins) are plausible.

When our phones and computers run out of power, their glowing screens go dark and they die a sort of digital death. But switch them to low-power mode to conserve energy, and they cut expendable operations to keep basic processes humming along until their batteries can be recharged.

Our energy-intensive brain needs to keep its lights on too. Brain cells depend primarily on steady deliveries of the sugar glucose, which they convert to adenosine triphosphate (ATP) to fuel their information processing. When we’re a little hungry, our brain usually doesn’t change its energy consumption much. But given that humans and other animals have historically faced the threat of long periods of starvation, sometimes seasonally, scientists have wondered whether brains might have their own kind of low-power mode for emergencies.

Now, in a paper published in Neuron in January, neuroscientists in Nathalie Rochefort’s lab at the University of Edinburgh have revealed an energy-saving strategy in the visual systems of mice. They found that when mice were deprived of sufficient food for weeks at a time — long enough for them to lose 15%-20% of their typical healthy weight — neurons in the visual cortex reduced the amount of ATP used at their synapses by a sizable 29%.

[Epistemic Status: written off the top of my head, thought about it for over a decade]

What do we desire for a theory of consciousness?

Continue reading “Digital Computers Will Remain Unconscious Until They Recruit Physical Fields for Holistic Computing Using Well-Defined Topological Boundaries” »