bioRxiv Subject Collection: Neuroscience's Journal
[Most Recent Entries]
[Calendar View]
Friday, May 3rd, 2024
| Time |
Event |
| 2:46a |
Human hippocampal CA3 uses specific functional connectivity rules for efficient associative memory
The human brain has remarkable computational power. It generates sophisticated behavioral sequences, stores engrams over an individual's lifetime, and produces higher cognitive functions up to the level of consciousness. However, so little of our neuroscience knowledge covers the human brain, and it remains unknown whether this organ is truly unique, or is a scaled version of the extensively studied rodent brain. To address this fundamental question, we determined the cellular, synaptic, and connectivity rules of the hippocampal CA3 recurrent circuit using multicellular patch clamp-recording. This circuit is the largest autoassociative network in the brain, and plays a key role in memory and higher-order computations such as pattern separation and pattern completion. We demonstrate that human hippocampal CA3 employs sparse connectivity, in stark contrast to neocortical recurrent networks. Connectivity sparsifies from rodents to humans, providing a circuit architecture that maximizes associational power. Unitary synaptic events at human CA3-CA3 synapses showed both distinct species-specific and circuit-dependent properties, with high reliability, unique amplitude precision, and long integration times. We also identify differential scaling rules between hippocampal pathways from rodents to humans, with a moderate increase in the convergence of CA3 inputs per cell, but a marked increase in human mossy fiber innervation. Anatomically guided full-scale modeling suggests that the human brain's sparse connectivity, expanded neuronal number, and reliable synaptic signaling combine to enhance the associative memory storage capacity of CA3. Together, our results reveal unique rules of connectivity and synaptic signaling in the human hippocampus, demonstrating the absolute necessity of human brain research and beginning to unravel the remarkable performance of our autoassociative memory circuits. | | 2:46a |
Disentangling neural correlates of tinnitus and hyperacusis following noise exposure in auditory cortex of rats
Both tinnitus and hyperacusis, likely triggered by hearing loss, can be attributed to maladaptive plasticity in auditory perception. However, owing to their co-occurrence, disentangling their neural mechanisms proves difficult. We hypothesized that the neural correlates of tinnitus are associated with neural activities triggered by low-intensity tones, while hyperacusis is linked to responses to moderate- and high-intensity tones. To test these hypotheses, we conducted behavioral and electrophysiological experiments in rats 2 to 8 days after traumatic tone exposure. In the behavioral experiments, prepulse and gap inhibition tended to exhibit different frequency characteristics (although not reaching sufficient statistical levels), suggesting that exposure to traumatic tones resulted in hyperacusis and tinnitus symptoms at different frequency ranges. When examining the auditory cortex at the thalamocortical recipient layer, we observed that tinnitus symptoms correlated with a disorganized tonotopic map, typically characterized by responses to low-intensity tones. Neural correlates of hyperacusis were found in the cortical recruitment function at the multi-unit activity (MUA) level, but not at the local field potential (LFP) level, in response to moderate- and high-intensity tones. This shift from LFP to MUA was associated with a loss of monotonicity, suggesting a crucial role for inhibitory synapses. Thus, in acute symptoms of traumatic tone exposure, our experiments successfully disentangled the neural correlates of tinnitus and hyperacusis at the thalamocortical recipient layer of the auditory cortex. They also suggested that tinnitus is linked to central noise, whereas hyperacusis is associated with aberrant gain control. Further interactions between animal experiments and clinical studies will offer insights into neural mechanisms, diagnosis and treatments of tinnitus and hyperacusis, specifically in terms of long-term plasticity of chronic symptoms. | | 2:46a |
Clinical Response to Neurofeedback in Major Depression Relates to Subtypes of Whole-Brain Activation Patterns During Training
Major Depressive Disorder (MDD) presents a significant public health challenge. Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) shows promise as a treatment for this disorder, although its mechanisms of action remain unclear. This study investigated whole-brain response patterns during rtfMRI-NF training to explain interindividual variability in clinical efficacy in MDD. We analyzed data from 95 participants (67 active, 28 control) with MDD from previous rtfMRI-NF studies designed to increase left amygdala activation through positive autobiographical memory recall. We focused on whole-brain activation patterns during two critical epochs of the neurofeedback procedure: activation during the self-regulation period and transient responses to feedback signal presentation. Through a systematic process involving feature selection, manifold extraction, and clustering with cross-validation, we identified subtypes within these patterns. Significant symptom reduction was observed in the active group (t=-4.404, d=-0.704, p<0.001) but not in the control group (t=-1.609, d=-0.430, p=0.111); however, left amygdala activation did not account for the variability in clinical efficacy. Subtyping analysis revealed two subtypes in regulation activation and three subtypes in brain responses to feedback signals (regulation: F=8.735, p=0.005; feedback response: F=5.326, p=0.008; interaction: F=3.471, p=0.039). Subtypes associated with significant symptom reduction were characterized by selective increases in control regions, including lateral prefrontal areas, and decreases in regions associated with self-referential thinking, such as default mode areas. These findings suggest that large-scale brain activity is more critical for clinical efficacy than the level of activation in the neurofeedback target region during training. Tailoring neurofeedback training to incorporate these patterns could significantly enhance its therapeutic efficacy. | | 2:46a |
Behavioural evidence of spectral opponent processing in the visual system of stomatopod crustaceans
Stomatopods, commonly known as mantis shrimps, possess an intricate colour vision with up to 12 photoreceptor classes organised in four specialised ommatidia rows (rows 1-4 in the midband region of the eye) for colour perception. While 2-4 spectral sensitivities suffice for most visual systems, the mechanism behind stomatopods' 12-channel colour vision remains unclear. Based on neuroarchitecture, it was initially suggested that rows 1-4 may function as four parallel dichromatic channels allowing fine spectral discrimination and strong colour constancy in narrow spectral zones. Subsequently, unexpectedly low resolution in behavioural experiments indicated that a binning processing system may operate instead of or in addition to the 'normal' opponent processing system, categorising information into separate channels to create an activation pattern for rapid colour recognition. Previous anatomical and behavioural studies have speculated on the potential coexistence of these two systems in stomatopods' colour vision. However, no behavioural study has specifically investigated the potential for colour opponency in their colour vision. Our findings provide the first direct behavioural evidence for spectral opponency in stomatopods' visual system, showing that rows 1-4 operate, at least some of the time, as multiple dichromatic channels. | | 2:46a |
Digital twins for understanding mechanisms of learning disabilities: Personalized deep neural networks reveal impact of neuronal hyperexcitability
Learning disabilities affect a significant proportion of children worldwide, with far-reaching consequences for their academic, professional, and personal lives. Here we develop digital twins - biologically plausible personalized Deep Neural Networks (pDNNs) - to investigate the neurophysiological mechanisms underlying learning disabilities in children. Our pDNN reproduces behavioral and neural activity patterns observed in affected children, including lower performance accuracy, slower learning rates, neural hyper-excitability, and reduced neural differentiation of numerical problems. Crucially, pDNN models reveal aberrancies in the geometry of manifold structure, providing a comprehensive view of how neural excitability influences both learning performance and the internal structure of neural representations. Our findings not only advance knowledge of the neurophysiological underpinnings of learning differences but also open avenues for targeted, personalized strategies designed to bridge cognitive gaps in affected children. This work reveals the power of digital twins integrating AI and neuroscience to uncover mechanisms underlying neurodevelopmental disorders. | | 3:23a |
Non-invasive evidence for rhythmic interactions between the human brain, spinal cord, and muscle
Voluntary human movement relies on interactions between the spinal cord, brain, and sensory afferents. The integrative function of the spinal cord has proven particularly difficult to study directly and non-invasively in humans due to challenges in measuring spinal cord activity. Investigations of sensorimotor integration often rely on cortico-muscular coupling, which can capture interactions between the brain and muscle, but cannot reveal how the spinal cord mediates this communication. Here, we introduce a system for direct, non-invasive imaging of concurrent brain and cervical spinal cord activity in humans using optically-pumped magnetometers (OPMs). We used this system to study endogenous interactions between the brain, spinal cord, and muscle involved in sensorimotor control during simple maintained contraction. Participants (n=3) performed a hand contraction with real-time visual feedback while we recorded brain and spinal cord activity using OPMs and muscle activity using EMG. We first identify the part of the spinal cord exhibiting a peak in estimated current flow in the cervical region during contraction. We then demonstrate that rhythmic activity in the spinal cord exhibits significant coupling with both brain and muscle activity in the 5-35 Hz frequency range. These findings evidence the possibility of concurrent spatio-temporal imaging along the entire neuro-axis. | | 2:32p |
Prefrontal dopamine circuits are required for active avoidance learning but not fear learning
The medial prefrontal cortex (mPFC) resolves approach-avoidance conflicts and mediates associative processes required for learning to avoid threats. Dopamine (DA) projections from the ventral tegmental area (VTA) to the mPFC carry information about aversive outcomes that may inform prefrontal computations. However, the role of prefrontal DA in learning based on aversive outcomes remains poorly understood. Here, we used platform mediated avoidance (PMA) to study the role of mPFC DA in threat avoidance learning in mice. We show that activity within dopaminergic VTA terminals in the mPFC is required for signaled avoidance learning, but not for escape, conditioned fear, or to recall a previously learned avoidance strategy. Using a Rescorla-Wagner model fit to the behavior of individual mice, we discovered that VTA-mPFC activity drives experience-dependent transitions in the mode of learning. As mice learn PMA, changes in avoidance behavior were initially driven by experiences of shock and later by successful shock avoidance. Inhibition of VTA-mPFC terminals prevented this transition. Taken together, these data indicate that mPFC DA is necessary to rapidly form associations between predictive cues and actions that preempt aversive outcomes. |
|