Auditory cortical regions show resting-state functional connectivity with the default mode-like network in echolocating bats.

Echolocating bats are among the most social and vocal of all mammals. These animals are ideal subjects for functional MRI (fMRI) studies of auditory social communication given their relatively hypertrophic limbic and auditory neural structures and their reduced ability to hear MRI gradient noise. Yet, no resting-state networks relevant to social cognition (e.g., default mode-like networks or DMLNs) have been identified in bats since there are few, if any, fMRI studies in the chiropteran order. Here, we acquired fMRI data at 7 Tesla from nine lightly anesthetized pale spear-nosed bats (Phyllostomus discolor). We applied independent components analysis (ICA) to reveal resting-state networks and measured neural activity elicited by noise ripples (on: 10 ms; off: 10 ms) that span this species' ultrasonic hearing range (20 to 130 kHz). Resting-state networks pervaded auditory, parietal, and occipital cortices, along with the hippocampus, cerebellum, basal ganglia, and auditory brainstem. Two midline networks formed an apparent DMLN. Additionally, we found four predominantly auditory/parietal cortical networks, of which two were left-lateralized and two right-lateralized. Regions within four auditory/parietal cortical networks are known to respond to social calls. Along with the auditory brainstem, regions within these four cortical networks responded to ultrasonic noise ripples. Iterative analyses revealed consistent, significant functional connectivity between the left, but not right, auditory/parietal cortical networks and DMLN nodes, especially the anterior-most cingulate cortex. Thus, a resting-state network implicated in social cognition displays more distributed functional connectivity across left, relative to right, hemispheric cortical substrates of audition and communication in this highly social and vocal species.

Cholinergic modulation supports dynamic switching of resting state networks through selective DMN suppression.

Brain activity during the resting state is widely used to examine brain organization, cognition and alterations in disease states. While it is known that neuromodulation and the state of alertness impact resting-state activity, neural mechanisms behind such modulation of resting-state activity are unknown. In this work, we used a computational model to demonstrate that change in excitability and recurrent connections, due to cholinergic modulation, impacts resting-state activity. The results of such modulation in the model match closely with experimental work on direct cholinergic modulation of Default Mode Network (DMN) in rodents. We further extended our study to the human connectome derived from diffusion-weighted MRI. In human resting-state simulations, an increase in cholinergic input resulted in a brain-wide reduction of functional connectivity. Furthermore, selective cholinergic modulation of DMN closely captured experimentally observed transitions between the baseline resting state and states with suppressed DMN fluctuations associated with attention to external tasks. Our study thus provides insight into potential neural mechanisms for the effects of cholinergic neuromodulation on resting-state activity and its dynamics.

Nodal degree centrality in the default mode-like network of the TgF344-AD Alzheimer's disease rat model as a measure of early network alterations.

This study investigates brain network alterations in the default mode-like network (DMLN) at early stages of disease progression in a rat model of Alzheimer's disease (AD) with application in the development of early diagnostic biomarkers of AD in translational studies. Thirteen male TgF344-AD (TG) rats, and eleven male wild-types (WT) littermates underwent longitudinal resting-state fMRI at the age of 4 and 6 months (pre and early-plaque stages of AD). Alterations in connectivity within DMLN were characterized by calculating the nodal degree (ND), a graph theoretical measure of centrality. The ND values of the left CA2 subregion of the hippocampus was found to be significantly lower in the 4-month-old TG cohort compared to the age-matched WT littermates. Moreover, a lower ND value (hypo-connectivity) was observed in the right prelimbic cortex (prL) and basal forebrain in the 6-month-old TG cohort, compared to the same age WT cohort. Indeed, the ND pattern in the DMLN in both TG and WT cohorts showed significant differences across the two time points that represent pre-plaque and early plaque stages of disease progression. Our findings indicate that lower nodal degree (hypo-connectivity) in the left CA2 in the pre-plaque stage of AD and hypo-connectivity between the basal forebrain and the DMLN regions in the early-plaque stage demonstrated differences in comparison to healthy controls. These results suggest that a graph-theoretical measure such as the nodal degree, can characterize brain networks and improve our insights into the mechanisms underlying Alzheimer's disease.

Early altered directionality of resting brain network state transitions in the TgF344-AD rat model of Alzheimer's disease.

Introduction: Alzheimer's disease (AD) is a progressive neurodegenerative disease resulting in memory loss and cognitive decline. Synaptic dysfunction is an early hallmark of the disease whose effects on whole-brain functional architecture can be identified using resting-state functional MRI (rsfMRI). Insights into mechanisms of early, whole-brain network alterations can help our understanding of the functional impact of AD's pathophysiology. Methods: Here, we obtained rsfMRI data in the TgF344-AD rat model at the pre- and early-plaque stages. This model recapitulates the major pathological and behavioral hallmarks of AD. We used co-activation pattern (CAP) analysis to investigate if and how the dynamic organization of intrinsic brain functional networks states, undetectable by earlier methods, is altered at these early stages. Results: We identified and characterized six intrinsic brain states as CAPs, their spatial and temporal features, and the transitions between the different states. At the pre-plaque stage, the TgF344-AD rats showed reduced co-activation of hub regions in the CAPs corresponding to the default mode-like and lateral cortical network. Default mode-like network activity segregated into two distinct brain states, with one state characterized by high co-activation of the basal forebrain. This basal forebrain co-activation was reduced in TgF344-AD animals mainly at the pre-plaque stage. Brain state transition probabilities were altered at the pre-plaque stage between states involving the default mode-like network, lateral cortical network, and basal forebrain regions. Additionally, while the directionality preference in the network-state transitions observed in the wild-type animals at the pre-plaque stage had diminished at the early-plaque stage, TgF344-AD animals continued to show directionality preference at both stages. Discussion: Our study enhances the understanding of intrinsic brain state dynamics and how they are impacted at the early stages of AD, providing a nuanced characterization of the early, functional impact of the disease's neurodegenerative process.

Early classification of Alzheimer's disease phenotype based on hippocampal electrophysiology in the TgF344-AD rat model.

The hippocampus plays a vital role in navigation, learning, and memory, and is affected in Alzheimer's disease (AD). This study investigated the classification of AD-transgenic rats versus wild-type littermates using electrophysiological activity recorded from the hippocampus at an early, presymptomatic stage of the disease (6 months old) in the TgF344-AD rat model. The recorded signals were filtered into low frequency (LFP) and high frequency (spiking activity) signals, and machine learning classifiers were employed to identify the rat genotype (TG vs. WT). By analyzing specific frequency bands in the low frequency signals and calculating distance metrics between spike trains in the high frequency signals, accurate classification was achieved. Gamma band power emerged as a valuable signal for classification, and combining information from both low and high frequency signals improved the accuracy further. These findings provide valuable insights into the early stage effects of AD on different regions of the hippocampus.

EEG-based functional connectivity for tactile roughness discrimination.

Tactile sensation and perception involve cooperation between different parts of the brain. Roughness discrimination is an important phase of texture recognition. In this study, we investigated how different roughness levels would influence the brain network characteristics. We recorded EEG signals from nine right-handed healthy subjects who underwent touching three surfaces with different levels of roughness. The experiment was separately repeated in 108 trials for each hand for both static and dynamic touch. For estimation of the functional connectivity between brain regions, the phase lag index method was employed. Frequency-specific connectivity patterns were observed in the ipsilateral and contralateral hemispheres to the hand of interest, for delta, theta, alpha, and beta frequency bands under the study. A number of connections were identified to be in charge of discrimination between surfaces in both alpha and beta frequency bands for the left hand in static touch and for the right hand in dynamic touch. In addition, common connections were determined in both hands for all three roughness in alpha band for static touch and in theta band for dynamic touch. The common connections were identified for the smooth surface in beta band for static touch and in delta and alpha bands for dynamic touch. As observed for static touch in alpha band and for dynamic touch in theta band, the number of common connections between the two hands was decreased by increasing the surface roughness. The results of this research would extend the current knowledge about tactile information processing in the brain. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09876-1.

Longitudinal investigation of changes in resting-state co-activation patterns and their predictive ability in the zQ175 DN mouse model of Huntington's disease.

Huntington's disease (HD) is a neurodegenerative disorder caused by expanded (≥ 40) glutamine-encoding CAG repeats in the huntingtin gene, which leads to dysfunction and death of predominantly striatal and cortical neurons. While the genetic profile and clinical signs and symptoms of the disease are better known, changes in the functional architecture of the brain, especially before the clinical expression becomes apparent, are not fully and consistently characterized. In this study, we sought to uncover functional changes in the brain in the heterozygous (HET) zQ175 delta-neo (DN) mouse model at 3, 6, and 10 months of age, using resting-state functional magnetic resonance imaging (RS-fMRI). This mouse model shows molecular, cellular and circuitry alterations that worsen through age. Motor function disturbances are manifested in this model at 6 and 10 months of age. Specifically, we investigated, longitudinally, changes in co-activation patterns (CAPs) that are the transient states of brain activity constituting the resting-state networks (RSNs). Most robust changes in the temporal properties of CAPs occurred at the 10-months time point; the durations of two anti-correlated CAPs, characterized by simultaneous co-activation of default-mode like network (DMLN) and co-deactivation of lateral-cortical network (LCN) and vice-versa, were reduced in the zQ175 DN HET animals compared to the wild-type mice. Changes in the spatial properties, measured in terms of activation levels of different brain regions, during CAPs were found at all three ages and became progressively more pronounced at 6-, and 10 months of age. We then assessed the cross-validated predictive power of CAP metrics to distinguish HET animals from controls. Spatial properties of CAPs performed significantly better than the chance level at all three ages with 80% classification accuracy at 6 and 10 months of age.

Alterations in theta-gamma coupling and sharp wave-ripple, signs of prodromal hippocampal network impairment in the TgF344-AD rat model.

Alzheimer's disease (AD) is a severe neurodegenerative disorder caused by the accumulation of toxic proteins, amyloid-beta (Aß) and tau, which eventually leads to dementia. Disease-modifying therapies are still lacking, due to incomplete insights into the neuropathological mechanisms of AD. Synaptic dysfunction is known to occur before cognitive symptoms become apparent and recent studies have demonstrated that imbalanced synaptic signaling drives the progression of AD, suggesting that early synaptic dysfunction could be an interesting therapeutic target. Synaptic dysfunction results in altered oscillatory activity, which can be detected with electroencephalography and electrophysiological recordings. However, the majority of these studies have been performed at advanced stages of AD, when extensive damage and cognitive symptoms are already present. The current study aimed to investigate if the hippocampal oscillatory activity is altered at pre-plaque stages of AD. The rats received stereotactic surgery to implant a laminar electrode in the CA1 layer of the right hippocampus. Electrophysiological recordings during two consecutive days in an open field were performed in 4-5-month-old TgF344-AD rats when increased concentrations of soluble Aß species were observed in the brain, in the absence of Aß-plaques. We observed a decreased power of high theta oscillations in TgF344-AD rats compared to wild-type littermates. Sharp wave-ripple (SWR) analysis revealed an increased SWR power and a decreased duration of SWR during quiet wake in TgF344-AD rats. The alterations in properties of SWR and the increased power of fast oscillations are suggestive of neuronal hyperexcitability, as has been demonstrated to occur during presymptomatic stages of AD. In addition, decreased strength of theta-gamma coupling, an important neuronal correlate of memory encoding, was observed in the TgF344-AD rats. Theta-gamma phase amplitude coupling has been associated with memory encoding and the execution of cognitive functions. Studies have demonstrated that mild cognitive impairment patients display decreased coupling strength, similar to what is described here. The current study demonstrates altered hippocampal network activity occurring at pre-plaque stages of AD and provides insights into prodromal network dysfunction in AD. The alterations observed could aid in the detection of AD during presymptomatic stages.

The impact of selective and non-selective medial septum stimulation on hippocampal neuronal oscillations: A study based on modeling and experiments.

Alzheimer's disease (AD) is a neurodegenerative disorder with a rising socioeconomic impact on societies. The hippocampus (HPC), which plays an important role in AD, is affected in the early stages. The medial septum (MS) in the forebrain provides major cholinergic input to the HPC and has been shown to play a significant role in generating oscillations in hippocampal neurons. Cholinergic neurons in the basal forebrain are particularly vulnerable to neurodegeneration in AD. To better understand the role of MS neurons including the cholinergic, glutamatergic, and GABAergic subpopulations in generating the well-known brain rhythms in HPC including delta, theta, slow gamma, and fast gamma oscillations, we designed a detailed computational model of the septohippocampal pathway. We validated the results of our model, using electrophysiological recordings in HPC with and without stimulation of the cholinergic neurons in MS using designer receptors exclusively activated by designer drugs (DREADDs) in healthy male ChAT-cre rats. Then, we eliminated 75% of the MS cholinergic neurons in the model to simulate degeneration in AD. A series of selective and non-selective stimulations of the remaining MS neurons were performed to understand the dynamics of oscillation regulation in the HPC during the degenerated state. In this way, appropriate stimulation strategies able to normalize the aberrant oscillations are proposed. We found that selectively stimulating the remaining healthy cholinergic neurons was sufficient for network recovery and compare this to stimulating other subpopulations and a non-selective stimulation of all MS neurons. Our data provide valuable information for the development of new therapeutic strategies in AD and a tool to test and predict the outcome of potential theranostic manipulations.

Altered dynamics of glymphatic flow in a mature-onset Tet-off APP mouse model of amyloidosis.

BACKGROUND: Alzheimer's disease (AD) is an incurable neurodegenerative disorder characterised by the progressive buildup of toxic amyloid-beta (Aß) and tau protein aggregates eventually leading to cognitive decline. Recent lines of evidence suggest that an impairment of the glymphatic system (GS), a brain waste clearance pathway, plays a key role in the pathology of AD. Moreover, a relationship between GS function and neuronal network integrity has been strongly implicated. Here, we sought to assess the efficacy of the GS in a transgenic Tet-Off APP mouse model of amyloidosis, in which the expression of mutant APP was delayed until maturity, mimicking features of late-onset AD-the most common form of dementia in humans. METHODS: To evaluate GS function, we used dynamic contrast-enhanced MRI (DCE-MRI) in 14-month-old Tet-Off APP (AD) mice and aged-matched littermate controls. Brain-wide transport of the Gd-DOTA contrast agent was monitored over time after cisterna magna injection. Region-of-interest analysis and computational modelling were used to assess GS dynamics while characterisation of brain tissue abnormalities at the microscale was performed ex vivo by immunohistochemistry. RESULTS: We observed reduced rostral glymphatic flow and higher accumulation of the contrast agent in areas proximal to the injection side in the AD group. Clustering and subsequent computational modelling of voxel time courses revealed significantly lower influx time constants in AD relative to the controls. Ex vivo evaluation showed abundant amyloid plaque burden in the AD group coinciding with extensive astrogliosis and microgliosis. The neuroinflammatory responses were also found in plaque-devoid regions, potentially impacting brain-fluid circulation. CONCLUSIONS: In a context resembling late-onset AD in humans, we demonstrate the disruption of glymphatic function and particularly a reduction in brain-fluid influx in the AD group. We conjecture that the hindered circulation of cerebrospinal fluid is potentially caused by wide-spread astrogliosis and amyloid-related obstruction of the normal routes of glymphatic flow resulting in redirection towards caudal regions. In sum, our study highlights the translational potential of alternative approaches, such as targeting brain-fluid circulation as potential therapeutic strategies for AD.

Altered basal forebrain function during whole-brain network activity at pre- and early-plaque stages of Alzheimer's disease in TgF344-AD rats.

BACKGROUND: Imbalanced synaptic transmission appears to be an early driver in Alzheimer's disease (AD) leading to brain network alterations. Early detection of altered synaptic transmission and insight into mechanisms causing early synaptic alterations would be valuable treatment strategies. This study aimed to investigate how whole-brain networks are influenced at pre- and early-plague stages of AD and if these manifestations are associated with concomitant cellular and synaptic deficits.  METHODS: To this end, we used an established AD rat model (TgF344-AD) and employed resting state functional MRI and quasi-periodic pattern (QPP) analysis, a method to detect recurrent spatiotemporal motifs of brain activity, in parallel with state-of-the-art immunohistochemistry in selected brain regions. RESULTS: At the pre-plaque stage, QPPs in TgF344-AD rats showed decreased activity of the basal forebrain (BFB) and the default mode-like network. Histological analyses revealed increased astrocyte abundance restricted to the BFB, in the absence of amyloid plaques, tauopathy, and alterations in a number of cholinergic, gaba-ergic, and glutamatergic synapses. During the early-plaque stage, when mild amyloid-beta (Aß) accumulation was observed in the cortex and hippocampus, QPPs in the TgF344-AD rats normalized suggesting the activation of compensatory mechanisms during this early disease progression period. Interestingly, astrogliosis observed in the BFB at the pre-plaque stage was absent at the early-plaque stage. Moreover, altered excitatory/inhibitory balance was observed in cortical regions belonging to the default mode-like network. In wild-type rats, at both time points, peak activity in the BFB preceded peak activity in other brain regions-indicating its modulatory role during QPPs. However, this pattern was eliminated in TgF344-AD suggesting that alterations in BFB-directed neuromodulation have a pronounced impact in network function in AD. CONCLUSIONS: This study demonstrates the value of rsfMRI and advanced network analysis methods to detect early alterations in BFB function in AD, which could aid early diagnosis and intervention in AD. Restoring the global synaptic transmission, possibly by modulating astrogliosis in the BFB, might be a promising therapeutic strategy to restore brain network function and delay the onset of symptoms in AD.

Combining magnetic resonance imaging with readout and/or perturbation of neural activity in animal models: Advantages and pitfalls.

One of the main challenges in brain research is to link all aspects of brain function: on a cellular, systemic, and functional level. Multimodal neuroimaging methodology provides a continuously evolving platform. Being able to combine calcium imaging, optogenetics, electrophysiology, chemogenetics, and functional magnetic resonance imaging (fMRI) as part of the numerous efforts on brain functional mapping, we have a unique opportunity to better understand brain function. This review will focus on the developments in application of these tools within fMRI studies and highlight the challenges and choices neurosciences face when designing multimodal experiments.

Visual Motion Coherence Responses in Human Visual Cortex.

Random dot kinematograms (RDKs) have recently been used to train subjects with cortical scotomas to perform direction of motion discrimination, partially restoring visual motion perception. To study the recovery of visual perception, it is important to understand how visual areas in normal subjects and subjects with cortical scotomas respond to RDK stimuli. Studies in normal subjects have shown that blood oxygen level-dependent (BOLD) responses in human area hV5/MT+ increase monotonically with coherence, in general agreement with electrophysiology studies in primates. However, RDK responses in prior studies were obtained while the subject was performing fixation, not a motion discrimination condition. Furthermore, BOLD responses were gauged against a baseline condition of uniform illumination or static dots, potentially decreasing the specificity of responses for the spatial integration of local motion signals (motion coherence). Here, we revisit this question starting from a baseline RDK condition of no coherence, thereby isolating the component of BOLD response due specifically to the spatial integration of local motion signals. In agreement with prior studies, we found that responses in the area hV5/MT+ of healthy subjects were monotonically increasing when subjects fixated without performing a motion discrimination task. In contrast, when subjects were performing an RDK direction of motion discrimination task, responses in the area hV5/MT+ remained flat, changing minimally, if at all, as a function of motion coherence. A similar pattern of responses was seen in the area hV5/MT+ of subjects with dense cortical scotomas performing direction of motion discrimination for RDKs presented inside the scotoma. Passive RDK presentation within the scotoma elicited no significant hV5/MT+ responses. These observations shed further light on how visual cortex responses behave as a function of motion coherence, helping to prepare the ground for future studies using these methods to study visual system recovery after injury.

Therapeutic efficacy of seizure onset zone-targeting high-definition cathodal tDCS in patients with drug-resistant focal epilepsy.

OBJECTIVE: Epilepsy is a common neurological disease with recurrent seizures. Transcranial direct-current stimulation (tDCS) is a safe, non-invasive method used for neuromodulation. The aim of this study was to explore the efficacy of cathodal high-definition tDCS (HD-tDCS) as a noninvasive method for the treatment of patients with drug-resistant focal epilepsy (DRFE). METHODS: This study was conducted as a randomized parallel and double-blind clinical trial. Twenty patients with DRFE were randomly selected through the convenience sampling method and then were divided into two groups. Ten patients received 2 mA cathodal HD-tDCS targeting the seizure-onset zone for 30 min for 2 weeks (5 consecutive days in each week and 10 days in total). Ten patients were randomized to the sham group. Seizure frequency and Interictal Epileptiform Discharges (IEDs) frequency were the primary outcome measures of this study. Quality of Life in Epilepsy Inventory (QoLIE-89) and Montreal Cognitive Assessment (MoCA) scores were used as secondary outcome measures. RESULTS: Seizure frequency decreased significantly among the patients in the treatment group 2 weeks (P-value ≤ 0.05), 1 month (P-value ≤ 0.05), and 2 months (P-value ≤ 0.05) after the stimulation in comparison to the sham group. Patients in the treatment group showed a decrease in the frequency of IED 2 weeks (P-value ≤ 0.05), 1 month (P-value ≤ 0.05), and 2 months (P-value ≤ 0.05) after stimulation. This cathodal stimulation protocol also improved the overall QoLIE-89 score after the stimulation compared to the sham group. CONCLUSIONS: The present study showed that cathodal HD-tDCS had a positive effect on seizure frequency and IED in patients with DRFE. More evidence is required to define the optimal stimulation parameters of HD-tDCS for the treatment of epilepsy. SIGNIFICANCE: Cathodal HD-tDCS targeting the seizure-onset zone is a promising treatment modality for patients with drug-resistant focal epilepsy.

Macaque Area V2/V3 Reorganization Following Homonymous Retinal Lesions.

In the adult visual system, topographic reorganization of the primary visual cortex (V1) after retinal lesions has been extensively investigated. In contrast, the plasticity of higher order extrastriate areas following retinal lesions is less well studied. Here, we used fMRI to study reorganization of visual areas V2/V3 following the induction of permanent, binocular, homonymous retinal lesions in 4 adult macaque monkeys. We found that the great majority of voxels that did not show visual modulation on the day of the lesion in the V2/V3 lesion projection zone (LPZ) demonstrated significant visual modulations 2 weeks later, and the mean modulation strength remained approximately stable thereafter for the duration of our observations (4-5 months). The distribution of eccentricities of visually modulated voxels inside the V2/V3 LPZ spanned a wider range post-lesion than pre-lesion, suggesting that neurons inside the LPZ reorganize by receiving input either from the foveal or the peripheral border of the LPZ, depending on proximity. Overall, we conclude that area V2/V3 of adult rhesus macaques displays a significant capacity for topographic reorganization following retinal lesions markedly exceeding the corresponding capacity of area V1.

Functional network antagonism and consciousness.

Spontaneous brain activity changes across states of consciousness. A particular consciousness-mediated configuration is the anticorrelations between the default mode network and other brain regions. What this antagonistic organization implies about consciousness to date remains inconclusive. In this Perspective Article, we propose that anticorrelations are the physiological expression of the concept of segregation, namely the brain's capacity to show selectivity in the way areas will be functionally connected. We postulate that this effect is mediated by the process of neural inhibition, by regulating global and local inhibitory activity. While recognizing that this effect can also result from other mechanisms, neural inhibition helps the understanding of how network metastability is affected after disrupting local and global neural balance. In combination with relevant theories of consciousness, we suggest that anticorrelations are a physiological prior that can work as a marker of preserved consciousness. We predict that if the brain is not in a state to host anticorrelations, then most likely the individual does not entertain subjective experience. We believe that this link between anticorrelations and the underlying physiology will help not only to comprehend how consciousness happens, but also conceptualize effective interventions for treating consciousness disorders in which anticorrelations seem particularly affected.

The fMRI resting paradigm can quantify brain function by surpassing communication and sophisticated setups, hence helping to infer consciousness in individuals who are unable to communicate with their environment. A particular consciousness-mediated rsfMRI configuration is that of functional anticorrelations, that is, the antagonistic relationship between a specific set of brain regions. We suggest that anticorrelations are a key physiological prior, without which consciousness cannot be supported, because the brain cannot segregate how regions get connected. We postulate that segregation is possible thanks to neural inhibition, by regulating global and local inhibitory activity. We believe that the link between anticorrelations and the underlying physiology can help not only to comprehend how consciousness happens, but also conceptualize effective interventions for treating its disorders.

Hemispheric and Sex Differences in Mustached Bat Primary Auditory Cortex Revealed by Neural Responses to Slow Frequency Modulations.

The mustached bat (Pteronotus parnellii) is a mammalian model of cortical hemispheric asymmetry. In this species, complex social vocalizations are processed preferentially in the left Doppler-shifted constant frequency (DSCF) subregion of primary auditory cortex. Like hemispheric specializations for speech and music, this bat brain asymmetry differs between sexes (i.e., males>females) and is linked to spectrotemporal processing based on selectivities to frequency modulations (FMs) with rapid rates (>0.5 kHz/ms). Analyzing responses to the long-duration (>10 ms), slow-rate (<0.5 kHz/ms) FMs to which most DSCF neurons respond may reveal additional neural substrates underlying this asymmetry. Here, we bilaterally recorded responses from 176 DSCF neurons in male and female bats that were elicited by upward and downward FMs fixed at 0.04 kHz/ms and presented at 0-90 dB SPL. In females, we found inter-hemispheric latency differences consistent with applying different temporal windows to precisely integrate spectrotemporal information. In males, we found a substrate for asymmetry less related to spectrotemporal processing than to acoustic energy (i.e., amplitude). These results suggest that in the DSCF area, (1) hemispheric differences in spectrotemporal processing manifest differently between sexes, and (2) cortical asymmetry for social communication is driven by spectrotemporal processing differences and neural selectivities for amplitude.

A neuromimetic realization of hippocampal CA1 for theta wave generation.

Recent advances in neural engineering allowed the development of neuroprostheses which facilitate functionality in people with neurological problems. In this research, a real-time neuromorphic system is proposed to artificially reproduce the theta wave and firing patterns of different neuronal populations in the CA1, a sub-region of the hippocampus. The hippocampal theta oscillations (4-12 Hz) are an important electrophysiological rhythm that contributes in various cognitive functions, including navigation, memory, and novelty detection. The proposed CA1 neuromimetic circuit includes 100 linearized Pinsky-Rinzel neurons and 668 excitatory and inhibitory synapses on a field programmable gate array (FPGA). The implemented spiking neural network of the CA1 includes the main neuronal populations for the theta rhythm generation: excitatory pyramidal cells, PV+ basket cells, and Oriens Lacunosum-Moleculare (OLM) cells which are inhibitory interneurons. Moreover, the main inputs to the CA1 region from the entorhinal cortex via the perforant pathway, the CA3 via Schaffer collaterals, and the medial septum via fimbria-fornix are also implemented on the FPGA using a bursting leaky-integrate and fire (LIF) neuron model. The results of hardware realization show that the proposed CA1 neuromimetic circuit successfully reconstructs the theta oscillations and functionally illustrates the phase relations between firing responses of the different neuronal populations. It is also evaluated the impact of medial septum elimination on the firing patterns of the CA1 neuronal population and the theta wave's characteristics. This neuromorphic system can be considered as a potential platform that opens opportunities for neuroprosthetic applications in future works.

Resting Brain Fluctuations Are Intrinsically Coupled to Visual Response Dynamics.

How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional magnetic resonance imaging to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) are the most prominent component of mouse resting brain dynamics. These QPPs captured the temporal alignment of anticorrelation between the default mode (DMN)- and task-positive (TPN)-like networks, with global brain fluctuations, and activity in neuromodulatory nuclei of the reticular formation. Specifically, the phase of QPPs prior to stimulation could significantly stratify subsequent visual response magnitude, suggesting QPPs relate to brain state fluctuations. This is the first observation in mice that dynamics of the DMN- and TPN-like networks, and particularly their anticorrelation, capture a brain state dynamic that affects sensory processing. Interestingly, QPPs also displayed transient onset response properties during visual stimulation, which covaried with deactivations in the reticular formation. We conclude that QPPs appear to capture a brain state fluctuation that may be orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.