The impact of age and sex on the oscillatory dynamics of visuospatial processing

&NA; The ability to dynamically allocate neural resources within the visual space is supported by a number of spectrally‐specific oscillatory responses, and such visuospatial processing has been found to decline moderately with age and differ by sex. However, the direct effects of age and sex on these oscillatory dynamics remains poorly understood. Using magnetoencephalography (MEG), structural magnetic resonance imaging, and advanced source reconstruction and statistical methods, we investigated the impact of aging and sex on behavioral performance and the underlying neural dynamics during visuospatial processing. In a large sample spanning a broad age range, we find that a number of prototypical attention and perception network components, both spectrally‐ and spatially‐defined, exhibit complex and uniquely informative relationships with age and sex. Specifically, neural responses in the theta range (4–10 Hz) were found to covary with chronological age in prefrontal and motor cortices, signifying a possible relationship between age and cognitive control. Further, we found that beta (18–24 Hz) activity covaried with age across a large swath of the somato‐motor strip, supporting previous findings of motor planning and execution deficits with increasing age. Finally, gamma‐frequency (48–70 Hz) oscillations were found to exhibit robust covariance with age in superior parietal and temporo‐parietal areas, indicating that the mapping of saliency in visual space is modulated by the normal aging process. Interestingly, behavioral performance and some of these oscillatory neural responses also exhibited interactions between age and sex, indicating sex differences in the evolution of the neural coding of visual perception as age increases. In particular, men were found to have stronger correlations between age and neural oscillatory responses during task performance than women in lateral occipital and superior temporal regions in the alpha band and in dorsolateral prefrontal cortex in the gamma band, while women exhibited more robust covariance between age and neural responses than men in inferior temporal and medial prefrontal cortex in the theta range. HighlightsHealthy adults spanning a broad age range performed a visuospatial task during MEG.Participants exhibited theta, alpha, beta, and gamma neural responses to the task.Theta and gamma oscillations covaried with age in frontal and parietal cortices.Gamma activity differed by biological sex in parietal and cerebellar regions.Multi‐spectral age/sex interactions occurred in occipital and prefrontal areas.

[1]  R. Oostenveld,et al.  Nonparametric statistical testing of EEG- and MEG-data , 2007, Journal of Neuroscience Methods.

[2]  Ayelet Landau Distributed attention is implemented through theta-rhythmic gamma modulation. , 2015, Journal of vision.

[3]  Alex I. Wiesman,et al.  Polarity-dependent modulation of multi-spectral neuronal activity by transcranial direct current stimulation , 2018, Cortex.

[4]  Huiquan Wang,et al.  Edited magnetic resonance spectroscopy detects an age-related decline in brain GABA levels , 2013, NeuroImage.

[5]  S. Resnick,et al.  Age differences in spatial memory in a virtual environment navigation task , 2001, Neurobiology of Aging.

[6]  P. A. Tonali,et al.  Effects of aging on motor cortex excitability , 2006, Neuroscience Research.

[7]  Joseph T. Gwin,et al.  Motor control and aging: Links to age-related brain structural, functional, and biochemical effects , 2010, Neuroscience & Biobehavioral Reviews.

[8]  H. Asada,et al.  Frontal midline theta rhythms reflect alternative activation of prefrontal cortex and anterior cingulate cortex in humans , 1999, Neuroscience Letters.

[9]  Maha Adamo,et al.  Changing channels: An fMRI study of aging and cross-modal attention shifts , 2006, NeuroImage.

[10]  A. Villringer,et al.  Sexual dimorphism in the human brain: evidence from neuroimaging. , 2013, Magnetic resonance imaging.

[11]  Vince D. Calhoun,et al.  The lifespan trajectory of neural oscillatory activity in the motor system , 2018, Developmental Cognitive Neuroscience.

[12]  Krish D. Singh,et al.  Visual gamma oscillations: The effects of stimulus type, visual field coverage and stimulus motion on MEG and EEG recordings , 2013, NeuroImage.

[13]  Alex I. Wiesman,et al.  Oscillations during observations: Dynamic oscillatory networks serving visuospatial attention , 2017, Human brain mapping.

[14]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[15]  E. Basar,et al.  Gamma, alpha, delta, and theta oscillations govern cognitive processes. , 2001, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[16]  Stefano Baldassi,et al.  The assessment of subjective visual vertical: comparison of two psychophysical paradigms and age-related performance , 2013, Attention, Perception, & Psychophysics.

[17]  A. Dale,et al.  High consistency of regional cortical thinning in aging across multiple samples. , 2009, Cerebral cortex.

[18]  O. Bertrand,et al.  Attention modulates gamma-band oscillations differently in the human lateral occipital cortex and fusiform gyrus. , 2005, Cerebral cortex.

[19]  A. Aron,et al.  Theta burst stimulation dissociates attention and action updating in human inferior frontal cortex , 2010, Proceedings of the National Academy of Sciences.

[20]  D. Plude,et al.  Aging, selective attention, and feature integration. , 1989, Psychology and aging.

[21]  N. Logothetis,et al.  Neurophysiological investigation of the basis of the fMRI signal , 2001, Nature.

[22]  Bart Gips,et al.  Temporal coding organized by coupled alpha and gamma oscillations prioritize visual processing , 2014, Trends in Neurosciences.

[23]  W. Singer,et al.  Hemodynamic Signals Correlate Tightly with Synchronized Gamma Oscillations , 2005, Science.

[24]  A. Leventhal,et al.  GABA and Its Agonists Improved Visual Cortical Function in Senescent Monkeys , 2003, Science.

[25]  Dustin Scheinost,et al.  Sex differences in normal age trajectories of functional brain networks , 2015, Human brain mapping.

[26]  R. VanRullen,et al.  The phase of ongoing EEG oscillations predicts visual perception , 2010 .

[27]  Mi-Hyun Choi,et al.  Effects of Aging on Visuospatial Performance and Cerebral Activation and Lateralization: An FMRI Study , 2008, The International journal of neuroscience.

[28]  Mark W. Greenlee,et al.  Structural and functional neural correlates of visuospatial information processing in normal aging and amnestic mild cognitive impairment , 2012, Neurobiology of Aging.

[29]  M. D. Ernst Permutation Methods: A Basis for Exact Inference , 2004 .

[30]  R. Ilmoniemi,et al.  Signal-space projection method for separating MEG or EEG into components , 1997, Medical and Biological Engineering and Computing.

[31]  John S. Allen,et al.  Normal neuroanatomical variation due to age: The major lobes and a parcellation of the temporal region , 2005, Neurobiology of Aging.

[32]  F. Battaglia,et al.  Oscillations in the prefrontal cortex: a gateway to memory and attention , 2011, Current Opinion in Neurobiology.

[33]  Stefan Debener,et al.  Size matters: effects of stimulus size, duration and eccentricity on the visual gamma-band response , 2004, Clinical Neurophysiology.

[34]  D. Tucker,et al.  Frontal midline theta and the error-related negativity: neurophysiological mechanisms of action regulation , 2004, Clinical Neurophysiology.

[35]  Tom R. Gaunt,et al.  Prenatal and early life influences on epigenetic age in children: a study of mother–offspring pairs from two cohort studies , 2015, Human molecular genetics.

[36]  Boman R. Groff,et al.  Frontoparietal Networks Mediate the Behavioral Impact of Alpha Inhibition in Visual Cortex. , 2018, Cerebral cortex.

[37]  Alan C. Evans,et al.  Brain Connectivity , 2011, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[38]  M. Goldberg,et al.  Attention, intention, and priority in the parietal lobe. , 2010, Annual review of neuroscience.

[39]  K. Cosgrove,et al.  Evolving Knowledge of Sex Differences in Brain Structure, Function, and Chemistry , 2007, Biological Psychiatry.

[40]  Vincenzo Paolo Senese,et al.  Visuospatial memory in healthy elderly, AD and MCI: a review. , 2009, Current aging science.

[41]  J. Cerella,et al.  Aging, executive control, and attention: a review of meta-analyses , 2002, Neuroscience & Biobehavioral Reviews.

[42]  R. Knight,et al.  Prefrontal deficits in attention and inhibitory control with aging. , 1997, Cerebral cortex.

[43]  Alexa B. Roggeveen,et al.  Large-scale gamma-band phase synchronization and selective attention. , 2008, Cerebral cortex.

[44]  K. Langa,et al.  Assessment of cognition using surveys and neuropsychological assessment: the Health and Retirement Study and the Aging, Demographics, and Memory Study. , 2011, The journals of gerontology. Series B, Psychological sciences and social sciences.

[45]  S Hale,et al.  Converging evidence that visuospatial cognition is more age-sensitive than verbal cognition. , 2000, Psychology and aging.

[46]  Ole Jensen,et al.  Alpha Oscillations Correlate with the Successful Inhibition of Unattended Stimuli , 2011, Journal of Cognitive Neuroscience.

[47]  J. Schoffelen,et al.  Prestimulus Oscillatory Activity in the Alpha Band Predicts Visual Discrimination Ability , 2008, The Journal of Neuroscience.

[48]  N. Cohen,et al.  Attentional Control in the Aging Brain: Insights from an fMRI Study of the Stroop Task , 2002, Brain and Cognition.

[49]  J Gross,et al.  REPRINTS , 1962, The Lancet.

[50]  Ronald J Killiany,et al.  Edited Magnetic Resonance Spectroscopy Detects an Age-Related Decline in Nonhuman Primate Brain GABA Levels , 2016, BioMed research international.

[51]  石井 良平 Medial prefrontal cortex generates frontal midline theta rhythm , 1999 .

[52]  S. Taulu,et al.  Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements , 2006, Physics in medicine and biology.

[53]  L. Stankov Aging, attention, and intelligence. , 1988 .

[54]  M. Levine,et al.  An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease , 2016, Genome Biology.

[55]  O. Bertrand,et al.  Relationship between task‐related gamma oscillations and BOLD signal: New insights from combined fMRI and intracranial EEG , 2007, Human brain mapping.

[56]  J. Lisman,et al.  The θ-γ neural code. , 2013, Neuron.

[57]  Xiangrui Li,et al.  Decreased proportion of GABA neurons accompanies age-related degradation of neuronal function in cat striate cortex , 2008, Brain Research Bulletin.

[58]  J. Kaiser,et al.  Human gamma-frequency oscillations associated with attention and memory , 2007, Trends in Neurosciences.

[59]  Timothy P. L. Roberts,et al.  Relating MEG measured motor cortical oscillations to resting γ-Aminobutyric acid (GABA) concentration , 2011, NeuroImage.

[60]  Catherine Tallon-Baudry,et al.  Visual Grouping and the Focusing of Attention Induce Gamma-band Oscillations at Different Frequencies in Human Magnetoencephalogram Signals , 2006, Journal of Cognitive Neuroscience.

[61]  S. Resnick,et al.  Age differences in the neural systems supporting human allocentric spatial navigation , 2006, Neurobiology of Aging.

[62]  P. Fries,et al.  Attention Samples Stimuli Rhythmically , 2012, Current Biology.

[63]  Derek K. Jones,et al.  Resting GABA concentration predicts peak gamma frequency and fMRI amplitude in response to visual stimulation in humans , 2009, Proceedings of the National Academy of Sciences.

[64]  J. Lisman,et al.  The Theta-Gamma Neural Code , 2013, Neuron.

[65]  L. White,et al.  Adult age differences in the functional neuroanatomy of visual attention: A combined fMRI and DTI study , 2007, Neurobiology of Aging.

[66]  Alex I. Wiesman,et al.  Aberrant occipital dynamics differentiate HIV-infected patients with and without cognitive impairment , 2018, Brain : a journal of neurology.

[67]  L. Ferrucci,et al.  Association Between Visuospatial Ability and Vestibular Function in the Baltimore Longitudinal Study of Aging , 2015, Journal of the American Geriatrics Society.

[68]  R. Ptak,et al.  Theta-band functional connectivity in the dorsal fronto-parietal network predicts goal-directed attention , 2016, Neuropsychologia.

[69]  Nick S. Ward,et al.  Beta oscillations reflect changes in motor cortex inhibition in healthy ageing , 2014, NeuroImage.

[70]  Tony W. Wilson,et al.  Is an absolute level of cortical beta suppression required for proper movement? Magnetoencephalographic evidence from healthy aging , 2016, NeuroImage.

[71]  F. Schmitt,et al.  Critical decline in fine motor hand movements in human aging. , 1999, Neurology.

[72]  Alex R. Smith,et al.  Sex differences in the structural connectome of the human brain , 2013, Proceedings of the National Academy of Sciences.

[73]  J. Cavanagh,et al.  Frontal midline theta reflects anxiety and cognitive control: Meta-analytic evidence , 2015, Journal of Physiology-Paris.

[74]  W. Singer,et al.  Progress in Biophysics and Molecular Biology , 1965 .

[75]  Tony W Wilson,et al.  tDCS Modulates Visual Gamma Oscillations and Basal Alpha Activity in Occipital Cortices: Evidence from MEG , 2018, Cerebral cortex.

[76]  O. Jensen,et al.  Frontal theta activity in humans increases with memory load in a working memory task , 2002, The European journal of neuroscience.

[77]  Natasha M. Maurits,et al.  Brain mechanisms underlying the effects of aging on different aspects of selective attention , 2014, NeuroImage.

[78]  Jean-Marc Constans,et al.  Voxel-based mapping of brain gray matter volume and glucose metabolism profiles in normal aging , 2009, Neurobiology of Aging.

[79]  James M Provenzale,et al.  Age-related changes in neural activity during visual target detection measured by fMRI. , 2004, Cerebral cortex.

[80]  Floris P. de Lange,et al.  Local Entrainment of Alpha Oscillations by Visual Stimuli Causes Cyclic Modulation of Perception , 2014, The Journal of Neuroscience.

[81]  Krish D. Singh,et al.  Orientation Discrimination Performance Is Predicted by GABA Concentration and Gamma Oscillation Frequency in Human Primary Visual Cortex , 2009, The Journal of Neuroscience.